The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Next generation big data analytics state of the artNazrul Islam
This document reviews recent research on network big data, including different data types (online network data, mobile/IoT data, geography data, spatial temporal data, streaming/real-time data, and visual data), storage models, privacy and security issues, analysis methods, and applications. It discusses the trends in network big data moving from simple online social network data to include more data sources and data that has spatial, temporal, and real-time components. The challenges of analyzing large and diverse datasets from networks are also addressed.
Design and Development of an Algorithm for Image Clustering In Textile Image ...IJCSEA Journal
All textile industries aim to produce competitive materials and the competition enhancement depends mainly on designs and quality of the dresses produced by each industry. Every day, a vast amount of textile images are being generated such as images of shirts, jeans, t-shirts and sarees. A principal driver of innovation is World Wide Web, unleashing publication at the scale of tens and millions of content creators. Images play an important role as a picture is worth thousand words in the field of textile design and marketing. A retrieving of images needs special concepts such as image annotation, context, and image content and image values. This research work aimed at studying the image mining process in detail and analyzes the methods for retrieval. The textile images analyze various methods for clustering the images and developing an algorithm for the same. The retrieval method considered is based on relevance feedback, scalable method, edge histogram and color layout. The image clustering algorithm is designed based on color descriptors and k-means clustering algorithm. A software prototype to prove the proposed algorithm has been developed using net beans integrated development environment and found successful.
Feature based similarity search in 3 d object databasesunyil96
This document discusses feature-based similarity search in 3D object databases. It surveys existing feature-based methods for 3D object retrieval and proposes a taxonomy for these methods. The document also presents experimental results that compare the effectiveness of some surveyed methods. Similarity search in 3D object databases has applications in fields like computer-aided design, medicine, molecular biology, and military applications. Defining similarity among 3D objects and designing algorithms to implement such similarity definitions is a difficult problem that researchers have worked to solve.
Novel framework for optimized digital forensic for mitigating complex image ...IJECEIAES
Digital Image Forensic is significantly becoming popular owing to the increasing usage of the images as a media of information propagation. However, owing to the presence of various image editing tools and software, there is also an increasing threat to image content security. Reviewing the existing approaches to identify the traces or artifacts states that there is a large scope of optimization to be implemented to enhance the processing further. Therefore, this paper presents a novel framework that performs cost-effective optimization of digital forensic technique with an idea of accurately localizing the area of tampering as well as offers a capability to mitigate the attacks of various forms. The study outcome shows that the proposed system offers better outcomes in contrast to the existing system to a significant scale to prove that minor novelty in design attributes could induce better improvement with respect to accuracy as well as resilience toward all potential image threats.
Machine Learning in Material Characterizationijtsrd
Machine learning has shown great potential applications in material science. It is widely used in material design, corrosion detection, material screening, new material discovery, and other fields of materials science. The majority of ML approaches in materials science is based on artificial neural networks ANNs . The use of ML and related techniques for materials design, development, and characterization has matured to a main stream field. This paper focuses on the applications of machine learning strategies for material characterization. Matthew N. O. Sadiku | Guddi K. Suman | Sarhan M. Musa "Machine Learning in Material Characterization" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-6 , October 2021, URL: https://www.ijtsrd.com/papers/ijtsrd46392.pdf Paper URL : https://www.ijtsrd.com/engineering/electrical-engineering/46392/machine-learning-in-material-characterization/matthew-n-o-sadiku
CONTENT RECOVERY AND IMAGE RETRIVAL IN IMAGE DATABASE CONTENT RETRIVING IN TE...Editor IJMTER
Digital Images are used in magazines, blogs, website, television and more. Digital image processing
techniques are used for feature selection, pattern extraction classification and retrieval requirements. Color, texture
and shape features are used in the image processing. Digital images processing also supports computer graphics
and computer vision domains. Scene text recognition is performed with two schemes. They are character
recognizer and binary character classifier models. A character recognizer is trained to predict the category of a
character in an image patch. A binary character classifier is trained for each character class to predict the existence
of this category in an image patch. Scene text recognition is performed on detected text regions. Pixel-based layout
analysis method is adopted to extract text regions and segment text characters in images. Text character
segmentation is carried out with color uniformity and horizontal alignment of text characters. Discriminative
character descriptor is designed by combining several feature detectors and descriptors. Histogram of Oriented
Gradients (HOG) is used to identify the character descriptors. Character structure is modeled at each character
class by designing stroke configuration maps. The scene text extraction scheme is also supports for smart mobile
devices. Text recognition methods are used with text understanding and text retrieval applications. The text
recognition scheme is enhanced with content based image retrieval process. The system is integrated with
additional representative and discriminative features for text structure modeling process. The system is enhanced to
perform text and word level recognition using lexicon analysis. The training process is included with word
database update task.
MITIGATION TECHNIQUES TO OVERCOME DATA HARM IN MODEL BUILDING FOR MLijaia
Given the impact of Machine Learning (ML) on individuals and the society, understanding how harm might
be occur throughout the ML life cycle becomes critical more than ever. By offering a framework to
determine distinct potential sources of downstream harm in ML pipeline, the paper demonstrates the
importance of choices throughout distinct phases of data collection, development, and deployment that
extend far beyond just model training. Relevant mitigation techniques are also suggested for being used
instead of merely relying on generic notions of what counts as fairness.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Next generation big data analytics state of the artNazrul Islam
This document reviews recent research on network big data, including different data types (online network data, mobile/IoT data, geography data, spatial temporal data, streaming/real-time data, and visual data), storage models, privacy and security issues, analysis methods, and applications. It discusses the trends in network big data moving from simple online social network data to include more data sources and data that has spatial, temporal, and real-time components. The challenges of analyzing large and diverse datasets from networks are also addressed.
Design and Development of an Algorithm for Image Clustering In Textile Image ...IJCSEA Journal
All textile industries aim to produce competitive materials and the competition enhancement depends mainly on designs and quality of the dresses produced by each industry. Every day, a vast amount of textile images are being generated such as images of shirts, jeans, t-shirts and sarees. A principal driver of innovation is World Wide Web, unleashing publication at the scale of tens and millions of content creators. Images play an important role as a picture is worth thousand words in the field of textile design and marketing. A retrieving of images needs special concepts such as image annotation, context, and image content and image values. This research work aimed at studying the image mining process in detail and analyzes the methods for retrieval. The textile images analyze various methods for clustering the images and developing an algorithm for the same. The retrieval method considered is based on relevance feedback, scalable method, edge histogram and color layout. The image clustering algorithm is designed based on color descriptors and k-means clustering algorithm. A software prototype to prove the proposed algorithm has been developed using net beans integrated development environment and found successful.
Feature based similarity search in 3 d object databasesunyil96
This document discusses feature-based similarity search in 3D object databases. It surveys existing feature-based methods for 3D object retrieval and proposes a taxonomy for these methods. The document also presents experimental results that compare the effectiveness of some surveyed methods. Similarity search in 3D object databases has applications in fields like computer-aided design, medicine, molecular biology, and military applications. Defining similarity among 3D objects and designing algorithms to implement such similarity definitions is a difficult problem that researchers have worked to solve.
Novel framework for optimized digital forensic for mitigating complex image ...IJECEIAES
Digital Image Forensic is significantly becoming popular owing to the increasing usage of the images as a media of information propagation. However, owing to the presence of various image editing tools and software, there is also an increasing threat to image content security. Reviewing the existing approaches to identify the traces or artifacts states that there is a large scope of optimization to be implemented to enhance the processing further. Therefore, this paper presents a novel framework that performs cost-effective optimization of digital forensic technique with an idea of accurately localizing the area of tampering as well as offers a capability to mitigate the attacks of various forms. The study outcome shows that the proposed system offers better outcomes in contrast to the existing system to a significant scale to prove that minor novelty in design attributes could induce better improvement with respect to accuracy as well as resilience toward all potential image threats.
Machine Learning in Material Characterizationijtsrd
Machine learning has shown great potential applications in material science. It is widely used in material design, corrosion detection, material screening, new material discovery, and other fields of materials science. The majority of ML approaches in materials science is based on artificial neural networks ANNs . The use of ML and related techniques for materials design, development, and characterization has matured to a main stream field. This paper focuses on the applications of machine learning strategies for material characterization. Matthew N. O. Sadiku | Guddi K. Suman | Sarhan M. Musa "Machine Learning in Material Characterization" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-6 , October 2021, URL: https://www.ijtsrd.com/papers/ijtsrd46392.pdf Paper URL : https://www.ijtsrd.com/engineering/electrical-engineering/46392/machine-learning-in-material-characterization/matthew-n-o-sadiku
CONTENT RECOVERY AND IMAGE RETRIVAL IN IMAGE DATABASE CONTENT RETRIVING IN TE...Editor IJMTER
Digital Images are used in magazines, blogs, website, television and more. Digital image processing
techniques are used for feature selection, pattern extraction classification and retrieval requirements. Color, texture
and shape features are used in the image processing. Digital images processing also supports computer graphics
and computer vision domains. Scene text recognition is performed with two schemes. They are character
recognizer and binary character classifier models. A character recognizer is trained to predict the category of a
character in an image patch. A binary character classifier is trained for each character class to predict the existence
of this category in an image patch. Scene text recognition is performed on detected text regions. Pixel-based layout
analysis method is adopted to extract text regions and segment text characters in images. Text character
segmentation is carried out with color uniformity and horizontal alignment of text characters. Discriminative
character descriptor is designed by combining several feature detectors and descriptors. Histogram of Oriented
Gradients (HOG) is used to identify the character descriptors. Character structure is modeled at each character
class by designing stroke configuration maps. The scene text extraction scheme is also supports for smart mobile
devices. Text recognition methods are used with text understanding and text retrieval applications. The text
recognition scheme is enhanced with content based image retrieval process. The system is integrated with
additional representative and discriminative features for text structure modeling process. The system is enhanced to
perform text and word level recognition using lexicon analysis. The training process is included with word
database update task.
MITIGATION TECHNIQUES TO OVERCOME DATA HARM IN MODEL BUILDING FOR MLijaia
Given the impact of Machine Learning (ML) on individuals and the society, understanding how harm might
be occur throughout the ML life cycle becomes critical more than ever. By offering a framework to
determine distinct potential sources of downstream harm in ML pipeline, the paper demonstrates the
importance of choices throughout distinct phases of data collection, development, and deployment that
extend far beyond just model training. Relevant mitigation techniques are also suggested for being used
instead of merely relying on generic notions of what counts as fairness.
Text region extraction from low resolution display board imaIAEME Publication
The document presents a new method for extracting text regions from low resolution display board images using wavelet features. The method divides the input image into 50x50 pixel blocks and extracts wavelet energy features from each block at two resolution levels. These features are used to classify blocks as text or non-text using discriminant functions. Detected text blocks are then merged to extract text regions. The method achieved a 97% detection rate on a variety of 100 low resolution display board images each sized 240x320 pixels.
This document summarizes a research paper that proposes a method for detecting and recognizing faces using the Viola Jones algorithm and Back Propagation Neural Network (BPNN).
The paper first discusses face detection and recognition challenges. It then provides background on Viola Jones algorithm and BPNN. The proposed methodology uses Viola Jones for face detection, converts the image to grayscale and binary, then trains segments or the whole image with BPNN. Results are analyzed using training, testing and validation curves in the MATLAB neural network tool to minimize error. In under 3 sentences, this document outlines the key techniques, proposed method, and analysis approach discussed in the source research paper.
Top 5 most viewed articles from academia in 2019 - gerogepatton
The International Journal of Artificial Intelligence & Applications (IJAIA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Artificial Intelligence & Applications (IJAIA). It is an international journal intended for professionals and researchers in all fields of AI for researchers, programmers, and software and hardware manufacturers. The journal also aims to publish new attempts in the form of special issues on emerging areas in Artificial Intelligence and applications
MobiGIS 2016 workshop report: The Fifth ACM SIGSPATIAL International Workshop...Reza Nourjou, Ph.D.
MobiGIS 2016 workshop report: The Fifth ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems: San Francisco, California, USA - October 31, 2016
Preprocessing Techniques for Image Mining on Biopsy ImagesIJERA Editor
This document discusses preprocessing techniques for image mining on biopsy images. It begins with an introduction to biomedical imaging and image mining. The key steps in image mining are described as image retrieval, preprocessing, feature extraction, data mining, and interpretation. Various preprocessing techniques are then evaluated on biopsy images, including interpolation, thresholding, and segmentation. Bicubic interpolation and Otsu thresholding produced good results for enhancing renal biopsy images. Overall, the document evaluates different preprocessing methods and their effects on biopsy images to help extract meaningful features for disease detection through image mining.
Integrating Web Services With Geospatial Data Mining Disaster Management for ...Waqas Tariq
Data Mining (DM) and Geographical Information Systems (GIS) are complementary techniques for describing, transforming, analyzing and modeling data about real world system. GIS and DM are naturally synergistic technologies that can be joined to produce powerful market insight from a sea of disparate data. Web Services would greatly simplify the development of many kinds of data integration and knowledge management applications. This research aims to develop a Spatial DM web service. It integrates state of the art GIS and DM functionality in an open, highly extensible, web-based architecture. The Interoperability of geospatial data previously focus just on data formats and standards. The recent popularity and adoption of Web Services has provided new means of interoperability for geospatial information not just for exchanging data but for analyzing these data during exchange as well. An integrated, user friendly Spatial DM System available on the internet via a web service offers exciting new possibilities for geo-spatial analysis to be ready for decision making and geographical research to a wide range of potential users.
Text and Object Recognition using Deep Learning for Visually Impaired Peopleijtsrd
This document presents a system to aid visually impaired people using object and text detection with deep learning. Object detection is performed using a convolutional neural network trained on datasets like MS-COCO and PASCAL VOC. Text detection uses a fully convolutional neural network. Detected objects and text are converted to speech using a text-to-speech synthesizer to help visually impaired users understand their surroundings. The system achieves real-time object detection and can detect multiple objects and text in an image with reasonable accuracy depending on lighting and other conditions.
AN ONTOLOGY FOR EXPLORING KNOWLEDGE IN COMPUTER NETWORKSijcsa
This document presents an ontology for exploring knowledge in computer networks that was developed using OWL format. Over 500 concepts related to various aspects of computer networks like scope, scale, topology, etc. were identified and classified. Relationships between concepts were analyzed and over 550 relationships between 33 types of relationships were identified. The ontology was implemented using the Protege tool and can help users search for concepts in the computer networks domain on semantic web applications.
Content-based Image Retrieval System for an Image Gallery Search Application IJECEIAES
Content-based image retrieval is a process framework that applies computer vision techniques for searching and managing large image collections more efficiently. With the growth of large digital image collections triggered by rapid advances in electronic storage capacity and computing power, there is a growing need for devices and computer systems to support efficient browsing, searching, and retrieval for image collections. Hence, the aim of this project is to develop a content-based image retrieval system that can be implemented in an image gallery desktop application to allow efficient browsing through three different search modes: retrieval by image query, retrieval by facial recognition, and retrieval by text or tags. In this project, the MPEG-7-like Powered Localized Color and Edge Directivity Descriptor is used to extract the feature vectors of the image database and the facial recognition system is built around the Eigenfaces concept. A graphical user interface with the basic functionality of an image gallery application is also developed to implement the three search modes. Results show that the application is able to retrieve and display images in a collection as thumbnail previews with high retrieval accuracy and medium relevance and the computational requirements for subsequent searches were significantly reduced through the incorporation of text-based image retrieval as one of the search modes. All in all, this study introduces a simple and convenient way of offline image searches on desktop computers and provides a stepping stone to future content-based image retrieval systems built for similar purposes.
Satellite and Land Cover Image Classification using Deep Learningijtsrd
Satellite imagery is very significant for many applications including disaster response, law enforcement and environmental monitoring. These applications require the manual identification of objects and facilities in the imagery. Because the geographic area to be covered are great and the analysts available to conduct the searches are few, automation is required. The traditional object detection and classification algorithms are too inaccurate, takes a lot of time and unreliable to solve the problem. Deep learning is a family of machine learning algorithms that can be used for the automation of such tasks. It has achieved success in image classification by using convolutional neural networks. The problem of object and facility classification in satellite imagery is considered. The system is developed by using various facilities like Tensor Flow, XAMPP, FLASK and other various deep learning libraries. Roshni Rajendran | Liji Samuel "Satellite and Land Cover Image Classification using Deep Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-5 , August 2020, URL: https://www.ijtsrd.com/papers/ijtsrd32912.pdf Paper Url :https://www.ijtsrd.com/computer-science/other/32912/satellite-and-land-cover-image-classification-using-deep-learning/roshni-rajendran
The document reviews various feature extraction techniques that have been used for content-based image retrieval (CBIR) systems. It discusses several approaches for extracting color, texture, shape and spatial features from images. It also examines different similarity measures and evaluation methods for CBIR systems, including precision, recall and distance metrics. Feature extraction is a key factor for CBIR, and the paper provides an overview of some of the major techniques that have been explored for this task.
Achieving Sustainable Development Goals using Computer VisionAkshat Gupta
This paper discusses how computer vision and image classification techniques can help achieve the UN's Sustainable Development Goals by promoting green economy initiatives. It reviews research on using image binarization and feature extraction for content-based image classification. The paper finds that a local thresholding technique called Niblack's method achieves the highest accuracy for classifying images in a sample dataset. Promoting technologies like this could encourage online transactions and digitization, reducing environmental impact while achieving economic and social benefits in line with sustainable development.
New Research Articles 2019 July Issue International Journal of Artificial Int...gerogepatton
The International Journal of Artificial Intelligence & Applications (IJAIA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Artificial Intelligence & Applications (IJAIA). It is an international journal intended for professionals and researchers in all fields of AI for researchers, programmers, and software and hardware manufacturers. The journal also aims to publish new attempts in the form of special issues on emerging areas
The document is a call for papers for the International Conference on Machine Learning and Data Analysis (ICMLDA 2008) to be held October 22-24, 2008 in San Francisco, USA. It provides information on submission guidelines and important dates, as well as an overview of topics that will be covered at the conference related to machine learning and data analysis techniques and applications. Accepted papers will be published in the conference proceedings and considered for publication in relevant journals.
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
This curriculum vitae summarizes the career and accomplishments of Dr. Yuan Yan Tang. Dr. Tang holds a Ph.D. in Computer Science from Concordia University and has held prestigious positions including Chair Professor at Hong Kong Baptist University and Dean of the College of Computer Science at Chongqing University. He has organized numerous international conferences and published over 300 papers. Dr. Tang is a fellow of both the IEEE and IAPR, and has received many honors and awards for his scholarly contributions and leadership in his field.
MULTI-LEVEL FEATURE FUSION BASED TRANSFER LEARNING FOR PERSON RE-IDENTIFICATIONgerogepatton
Most of the currently known methods treat person re-identification task as classification problem and used commonly neural networks. However, these methods used only high-level convolutional feature or to express the feature representation of pedestrians. Moreover, the current data sets for person reidentification is relatively small. Under the limitation of the number of training set, deep convolutional networks are difficult to train adequately. Therefore, it is very worthwhile to introduce auxiliary data sets help training. In order to solve this problem, this paper propose a novel method of deep transfer learning, and combines the comparison model with the classification model and multi-level fusion of the
convolution features on the basis of transfer learning. In a multi-layers convolutional network, the characteristics of each layer of network are the dimensionality reduction of the previous layer of results, but the information of multi-level features is not only inclusive, but also has certain complementarity. We can using the information gap of different layers of convolutional neural networks to extract a better feature expression. Finally, the algorithm proposed in this paper is fully tested on four data sets (VIPeR, CUHK01, GRID and PRID450S). The obtained re-identification results prove the effectiveness of the algorithm.
Anatomical Survey Based Feature Vector for Text Pattern DetectionIJEACS
The vital objective of artificial intelligence is to discover and understand the human competences, one of which is the capability to distinguish several text objects within one or more images exhibited on any canvas including prints, videos or electronic displays. Multimedia data has increased rapidly in past years. Textual information present in multimedia contains important information about the image/video content. However it needs to technologically verify the commonly used human intelligence of detecting and differentiating the text within an image, for computers. Hence in this paper feature set based on anatomical study of human text detection system is proposed.
This document presents a critical review report on a course about algorithm design and analysis. It summarizes a paper that studied forecasting techniques based on directed weighted social graphs. The paper generated a social graph from user actions and predicted future activities. It captured user data to create the graph and used rule-based mining for forecasting. Results found the method was more efficient than Apriori and predictions were over 80% accurate. The review critiqued strengths like clear methodology but noted weaknesses such as the title being too broad and lack of recommendations.
Semi-supervised auto-encoder for facial attributes recognitionTELKOMNIKA JOURNAL
The particularity of our faces encourages many researchers to exploit their features in different domains such as user identification, behaviour analysis, computer technology, security, and psychology. In this paper, we present a method for facial attributes analysis. The work addressed to analyse facial images and extract features in the purpose to recognize demographic attributes: age, gender, and ethnicity (AGE). In this work, we exploited the robustness of deep learning (DL) using an updating version of autoencoders called the deep sparse autoencoder (DSAE). In this work we used a new architecture of DSAE by adding the supervision to the classic model and we control the overfitting problem by regularizing the model. The pass from DSAE to the semi-supervised autoencoder (DSSAE) facilitates the supervision process and achieves an excellent performance to extract features. In this work we focused to estimate AGE jointly. The experiment results show that DSSAE is created to recognize facial features with high precision. The whole system achieves good performance and important rates in AGE using the MORPH II database
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original
contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication. IJCSIT publishes original research papers and review papers, as well as auxiliary material such as: research papers, case studies, technical reports etc.
Text region extraction from low resolution display board imaIAEME Publication
The document presents a new method for extracting text regions from low resolution display board images using wavelet features. The method divides the input image into 50x50 pixel blocks and extracts wavelet energy features from each block at two resolution levels. These features are used to classify blocks as text or non-text using discriminant functions. Detected text blocks are then merged to extract text regions. The method achieved a 97% detection rate on a variety of 100 low resolution display board images each sized 240x320 pixels.
This document summarizes a research paper that proposes a method for detecting and recognizing faces using the Viola Jones algorithm and Back Propagation Neural Network (BPNN).
The paper first discusses face detection and recognition challenges. It then provides background on Viola Jones algorithm and BPNN. The proposed methodology uses Viola Jones for face detection, converts the image to grayscale and binary, then trains segments or the whole image with BPNN. Results are analyzed using training, testing and validation curves in the MATLAB neural network tool to minimize error. In under 3 sentences, this document outlines the key techniques, proposed method, and analysis approach discussed in the source research paper.
Top 5 most viewed articles from academia in 2019 - gerogepatton
The International Journal of Artificial Intelligence & Applications (IJAIA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Artificial Intelligence & Applications (IJAIA). It is an international journal intended for professionals and researchers in all fields of AI for researchers, programmers, and software and hardware manufacturers. The journal also aims to publish new attempts in the form of special issues on emerging areas in Artificial Intelligence and applications
MobiGIS 2016 workshop report: The Fifth ACM SIGSPATIAL International Workshop...Reza Nourjou, Ph.D.
MobiGIS 2016 workshop report: The Fifth ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems: San Francisco, California, USA - October 31, 2016
Preprocessing Techniques for Image Mining on Biopsy ImagesIJERA Editor
This document discusses preprocessing techniques for image mining on biopsy images. It begins with an introduction to biomedical imaging and image mining. The key steps in image mining are described as image retrieval, preprocessing, feature extraction, data mining, and interpretation. Various preprocessing techniques are then evaluated on biopsy images, including interpolation, thresholding, and segmentation. Bicubic interpolation and Otsu thresholding produced good results for enhancing renal biopsy images. Overall, the document evaluates different preprocessing methods and their effects on biopsy images to help extract meaningful features for disease detection through image mining.
Integrating Web Services With Geospatial Data Mining Disaster Management for ...Waqas Tariq
Data Mining (DM) and Geographical Information Systems (GIS) are complementary techniques for describing, transforming, analyzing and modeling data about real world system. GIS and DM are naturally synergistic technologies that can be joined to produce powerful market insight from a sea of disparate data. Web Services would greatly simplify the development of many kinds of data integration and knowledge management applications. This research aims to develop a Spatial DM web service. It integrates state of the art GIS and DM functionality in an open, highly extensible, web-based architecture. The Interoperability of geospatial data previously focus just on data formats and standards. The recent popularity and adoption of Web Services has provided new means of interoperability for geospatial information not just for exchanging data but for analyzing these data during exchange as well. An integrated, user friendly Spatial DM System available on the internet via a web service offers exciting new possibilities for geo-spatial analysis to be ready for decision making and geographical research to a wide range of potential users.
Text and Object Recognition using Deep Learning for Visually Impaired Peopleijtsrd
This document presents a system to aid visually impaired people using object and text detection with deep learning. Object detection is performed using a convolutional neural network trained on datasets like MS-COCO and PASCAL VOC. Text detection uses a fully convolutional neural network. Detected objects and text are converted to speech using a text-to-speech synthesizer to help visually impaired users understand their surroundings. The system achieves real-time object detection and can detect multiple objects and text in an image with reasonable accuracy depending on lighting and other conditions.
AN ONTOLOGY FOR EXPLORING KNOWLEDGE IN COMPUTER NETWORKSijcsa
This document presents an ontology for exploring knowledge in computer networks that was developed using OWL format. Over 500 concepts related to various aspects of computer networks like scope, scale, topology, etc. were identified and classified. Relationships between concepts were analyzed and over 550 relationships between 33 types of relationships were identified. The ontology was implemented using the Protege tool and can help users search for concepts in the computer networks domain on semantic web applications.
Content-based Image Retrieval System for an Image Gallery Search Application IJECEIAES
Content-based image retrieval is a process framework that applies computer vision techniques for searching and managing large image collections more efficiently. With the growth of large digital image collections triggered by rapid advances in electronic storage capacity and computing power, there is a growing need for devices and computer systems to support efficient browsing, searching, and retrieval for image collections. Hence, the aim of this project is to develop a content-based image retrieval system that can be implemented in an image gallery desktop application to allow efficient browsing through three different search modes: retrieval by image query, retrieval by facial recognition, and retrieval by text or tags. In this project, the MPEG-7-like Powered Localized Color and Edge Directivity Descriptor is used to extract the feature vectors of the image database and the facial recognition system is built around the Eigenfaces concept. A graphical user interface with the basic functionality of an image gallery application is also developed to implement the three search modes. Results show that the application is able to retrieve and display images in a collection as thumbnail previews with high retrieval accuracy and medium relevance and the computational requirements for subsequent searches were significantly reduced through the incorporation of text-based image retrieval as one of the search modes. All in all, this study introduces a simple and convenient way of offline image searches on desktop computers and provides a stepping stone to future content-based image retrieval systems built for similar purposes.
Satellite and Land Cover Image Classification using Deep Learningijtsrd
Satellite imagery is very significant for many applications including disaster response, law enforcement and environmental monitoring. These applications require the manual identification of objects and facilities in the imagery. Because the geographic area to be covered are great and the analysts available to conduct the searches are few, automation is required. The traditional object detection and classification algorithms are too inaccurate, takes a lot of time and unreliable to solve the problem. Deep learning is a family of machine learning algorithms that can be used for the automation of such tasks. It has achieved success in image classification by using convolutional neural networks. The problem of object and facility classification in satellite imagery is considered. The system is developed by using various facilities like Tensor Flow, XAMPP, FLASK and other various deep learning libraries. Roshni Rajendran | Liji Samuel "Satellite and Land Cover Image Classification using Deep Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-5 , August 2020, URL: https://www.ijtsrd.com/papers/ijtsrd32912.pdf Paper Url :https://www.ijtsrd.com/computer-science/other/32912/satellite-and-land-cover-image-classification-using-deep-learning/roshni-rajendran
The document reviews various feature extraction techniques that have been used for content-based image retrieval (CBIR) systems. It discusses several approaches for extracting color, texture, shape and spatial features from images. It also examines different similarity measures and evaluation methods for CBIR systems, including precision, recall and distance metrics. Feature extraction is a key factor for CBIR, and the paper provides an overview of some of the major techniques that have been explored for this task.
Achieving Sustainable Development Goals using Computer VisionAkshat Gupta
This paper discusses how computer vision and image classification techniques can help achieve the UN's Sustainable Development Goals by promoting green economy initiatives. It reviews research on using image binarization and feature extraction for content-based image classification. The paper finds that a local thresholding technique called Niblack's method achieves the highest accuracy for classifying images in a sample dataset. Promoting technologies like this could encourage online transactions and digitization, reducing environmental impact while achieving economic and social benefits in line with sustainable development.
New Research Articles 2019 July Issue International Journal of Artificial Int...gerogepatton
The International Journal of Artificial Intelligence & Applications (IJAIA) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Artificial Intelligence & Applications (IJAIA). It is an international journal intended for professionals and researchers in all fields of AI for researchers, programmers, and software and hardware manufacturers. The journal also aims to publish new attempts in the form of special issues on emerging areas
The document is a call for papers for the International Conference on Machine Learning and Data Analysis (ICMLDA 2008) to be held October 22-24, 2008 in San Francisco, USA. It provides information on submission guidelines and important dates, as well as an overview of topics that will be covered at the conference related to machine learning and data analysis techniques and applications. Accepted papers will be published in the conference proceedings and considered for publication in relevant journals.
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
This curriculum vitae summarizes the career and accomplishments of Dr. Yuan Yan Tang. Dr. Tang holds a Ph.D. in Computer Science from Concordia University and has held prestigious positions including Chair Professor at Hong Kong Baptist University and Dean of the College of Computer Science at Chongqing University. He has organized numerous international conferences and published over 300 papers. Dr. Tang is a fellow of both the IEEE and IAPR, and has received many honors and awards for his scholarly contributions and leadership in his field.
MULTI-LEVEL FEATURE FUSION BASED TRANSFER LEARNING FOR PERSON RE-IDENTIFICATIONgerogepatton
Most of the currently known methods treat person re-identification task as classification problem and used commonly neural networks. However, these methods used only high-level convolutional feature or to express the feature representation of pedestrians. Moreover, the current data sets for person reidentification is relatively small. Under the limitation of the number of training set, deep convolutional networks are difficult to train adequately. Therefore, it is very worthwhile to introduce auxiliary data sets help training. In order to solve this problem, this paper propose a novel method of deep transfer learning, and combines the comparison model with the classification model and multi-level fusion of the
convolution features on the basis of transfer learning. In a multi-layers convolutional network, the characteristics of each layer of network are the dimensionality reduction of the previous layer of results, but the information of multi-level features is not only inclusive, but also has certain complementarity. We can using the information gap of different layers of convolutional neural networks to extract a better feature expression. Finally, the algorithm proposed in this paper is fully tested on four data sets (VIPeR, CUHK01, GRID and PRID450S). The obtained re-identification results prove the effectiveness of the algorithm.
Anatomical Survey Based Feature Vector for Text Pattern DetectionIJEACS
The vital objective of artificial intelligence is to discover and understand the human competences, one of which is the capability to distinguish several text objects within one or more images exhibited on any canvas including prints, videos or electronic displays. Multimedia data has increased rapidly in past years. Textual information present in multimedia contains important information about the image/video content. However it needs to technologically verify the commonly used human intelligence of detecting and differentiating the text within an image, for computers. Hence in this paper feature set based on anatomical study of human text detection system is proposed.
This document presents a critical review report on a course about algorithm design and analysis. It summarizes a paper that studied forecasting techniques based on directed weighted social graphs. The paper generated a social graph from user actions and predicted future activities. It captured user data to create the graph and used rule-based mining for forecasting. Results found the method was more efficient than Apriori and predictions were over 80% accurate. The review critiqued strengths like clear methodology but noted weaknesses such as the title being too broad and lack of recommendations.
Semi-supervised auto-encoder for facial attributes recognitionTELKOMNIKA JOURNAL
The particularity of our faces encourages many researchers to exploit their features in different domains such as user identification, behaviour analysis, computer technology, security, and psychology. In this paper, we present a method for facial attributes analysis. The work addressed to analyse facial images and extract features in the purpose to recognize demographic attributes: age, gender, and ethnicity (AGE). In this work, we exploited the robustness of deep learning (DL) using an updating version of autoencoders called the deep sparse autoencoder (DSAE). In this work we used a new architecture of DSAE by adding the supervision to the classic model and we control the overfitting problem by regularizing the model. The pass from DSAE to the semi-supervised autoencoder (DSSAE) facilitates the supervision process and achieves an excellent performance to extract features. In this work we focused to estimate AGE jointly. The experiment results show that DSSAE is created to recognize facial features with high precision. The whole system achieves good performance and important rates in AGE using the MORPH II database
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original
contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication. IJCSIT publishes original research papers and review papers, as well as auxiliary material such as: research papers, case studies, technical reports etc.
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
October 2023-Top Cited Articles in IJU.pdfijujournal
International Journal of Ubiquitous Computing (IJU) is a quarterly open access peer-reviewed journal that provides excellent international forum for sharing knowledge and results in theory, methodology and applications of ubiquitous computing. Current information age is witnessing a dramatic use of digital and electronic devices in the workplace and beyond. Ubiquitous Computing presents a rather arduous requirement of robustness, reliability and availability to the end user. Ubiquitous computing has received a significant and sustained research interest in terms of designing and deploying large scale and high performance computational applications in real life. The aim of the journal is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.
October 2022: Top 10 Read Articles in Signal & Image Processingsipij
Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.
January 2023: Top 10 Read Articles in Signal &Image Processing sipij
Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.
September 2022: Top 10 Read Articles in Signal & Image Processingsipij
Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.
July 2022: Top 10 Read Articles in Signal & Image Processingsipij
Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.
April 2023: Top 10 Read Articles in Signal & Image Processingsipij
Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.
June 2022: Top 10 Read Articles in Signal & Image Processingsipij
This article summarizes two papers published in the journal Signal & Image Processing.
The first paper describes a Gaussian mixture model-based speech recognition system developed using MATLAB. It analyzes the accuracy of GMM for modeling speech and the performance of the overall system.
The second paper proposes two new methods for securing images using cryptography and steganography. The first method encrypts an image into ciphertext using S-DES encryption and hides the text in a second image. The second method directly encrypts an image using a key image as the S-DES key and hides the encrypted data in a second image.
August 2022: Top 10 Read Articles in Signal & Image Processingsipij
This document summarizes two papers published in the journal Signal & Image Processing: An International Journal (SIPIJ).
The first paper presents a Gaussian mixture model-based speech recognition system developed using MATLAB. It analyzes the accuracy of Gaussian mixture models for parametric modeling and the performance of the system for recognizing isolated digits 0-9.
The second paper proposes two new methods for secured image steganography that combine cryptography and steganography. The first method encrypts an image into cipher text using S-DES encryption and hides the text in a cover image. The second method directly encrypts an image using a key image as input to S-DES and hides the encrypted data in a cover image.
April 2022: Top Read Articles in Signal & Image Processingsipij
Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.
May 2022: Top Read Articles in Signal & Image Processingsipij
Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.
September 2021 - Top 10 Read Articles in Signal & Image Processingsipij
Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.
June 2021: Top Read Articles in Signal & Image Processingsipij
Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.
December 2021: Top Read Articles in Signal & Image Processingsipij
Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.
July 2021: Top Read Articles in Signal & Image Processingsipij
Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.
November 2021: Top Read Articles in Signal & Image Processingsipij
Signal & Image Processing : An International Journal is an Open Access peer-reviewed journal intended for researchers from academia and industry, who are active in the multidisciplinary field of signal & image processing. The scope of the journal covers all theoretical and practical aspects of the Digital Signal Processing & Image processing, from basic research to development of application.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of Signal & Image processing.
May 2024: Top 10 Read Articles in Software Engineering & Applications Interna...sebastianku31
Welcome To IJSEA ...!!!
Call for papers___!
International Journal of Software Engineering & Applications(IJSEA)
ISSN:0975-3834 [Online]; 0975-4679 [Print]
ERA Indexed, H Index 31
Web Page URL : https://airccse.org/journal/ijsea/ijsea.html
Submission URL :https://airccse.com/submissioncs/home.html
Contact Us : ijseajournal@airccse.org or ijsea@aircconline.com
May 2024: Top 10 Read Articles Posted Url:https://www.academia.edu/119977684/April_2024_Top_10_Read_Articles_in_Software_Engineering_and_Applications_International_Journal_of_Software_Engineering_and_Applications_IJSEA_ERA_Indexed
Home security is of paramount importance in today's world, where we rely more on technology, home
security is crucial. Using technology to make homes safer and easier to control from anywhere is
important. Home security is important for the occupant’s safety. In this paper, we came up with a low cost,
AI based model home security system. The system has a user-friendly interface, allowing users to start
model training and face detection with simple keyboard commands. Our goal is to introduce an innovative
home security system using facial recognition technology. Unlike traditional systems, this system trains
and saves images of friends and family members. The system scans this folder to recognize familiar faces
and provides real-time monitoring. If an unfamiliar face is detected, it promptly sends an email alert,
ensuring a proactive response to potential security threats.
In the era of data-driven warfare, the integration of big data and machine learning (ML) techniques has
become paramount for enhancing defence capabilities. This research report delves into the applications of
big data and ML in the defence sector, exploring their potential to revolutionize intelligence gathering,
strategic decision-making, and operational efficiency. By leveraging vast amounts of data and advanced
algorithms, these technologies offer unprecedented opportunities for threat detection, predictive analysis,
and optimized resource allocation. However, their adoption also raises critical concerns regarding data
privacy, ethical implications, and the potential for misuse. This report aims to provide a comprehensive
understanding of the current state of big data and ML in defence, while examining the challenges and
ethical considerations that must be addressed to ensure responsible and effective implementation.
Cloud Computing, being one of the most recent innovative developments of the IT world, has been
instrumental not just to the success of SMEs but, through their productivity and innovative contribution to
the economy, has even made a remarkable contribution to the economic growth of the United States. To
this end, the study focuses on how cloud computing technology has impacted economic growth through
SMEs in the United States. Relevant literature connected to the variables of interest in this study was
reviewed, and secondary data was generated and utilized in the analysis section of this paper. The findings
of this paper revealed that there have been meaningful contributions that the usage of virtualization has
made in the commercial dealings of small firms in the United States, and this has also been reflected in the
economic growth of the country. This paper further revealed that as important as cloud-based software is,
some SMEs are still skeptical about how it can help improve their business and increase their bottom line
and hence have failed to adopt it. Apart from the SMEs, some notable large firms in different industries,
including information and educational services, have adopted cloud computing technology and hence
contributed to the economic growth of the United States. Lastly, findings from our inferential statistics
revealed that no discernible change has occurred in innovation between small and big businesses in the
adoption of cloud computing. Both categories of businesses adopt cloud computing in the same way, and
their contribution to the American economy has no significant difference in the usage of virtualization.
Energy-constrained Wireless Sensor Networks (WSNs) have garnered significant research interest in
recent years. Multiple-Input Multiple-Output (MIMO), or Cooperative MIMO, represents a specialized
application of MIMO technology within WSNs. This approach operates effectively, especially in
challenging and resource-constrained environments. By facilitating collaboration among sensor nodes,
Cooperative MIMO enhances reliability, coverage, and energy efficiency in WSN deployments.
Consequently, MIMO finds application in diverse WSN scenarios, spanning environmental monitoring,
industrial automation, and healthcare applications.
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication. IJCSIT publishes original research papers and review papers, as well as auxiliary material such as: research papers, case studies, technical reports etc.
With growing, Car parking increases with the number of car users. With the increased use of smartphones
and their applications, users prefer mobile phone-based solutions. This paper proposes the Smart Parking
Management System (SPMS) that depends on Arduino parts, Android applications, and based on IoT. This
gave the client the ability to check available parking spaces and reserve a parking spot. IR sensors are
utilized to know if a car park space is allowed. Its area data are transmitted using the WI-FI module to the
server and are recovered by the mobile application which offers many options attractively and with no cost
to users and lets the user check reservation details. With IoT technology, the smart parking system can be
connected wirelessly to easily track available locations.
Welcome to AIRCC's International Journal of Computer Science and Information Technology (IJCSIT), your gateway to the latest advancements in the dynamic fields of Computer Science and Information Systems.
Computer-Assisted Language Learning (CALL) are computer-based tutoring systems that deal with
linguistic skills. Adding intelligence in such systems is mainly based on using Natural Language
Processing (NLP) tools to diagnose student errors, especially in language grammar. However, most such
systems do not consider the modeling of student competence in linguistic skills, especially for the Arabic
language. In this paper, we will deal with basic grammar concepts of the Arabic language taught for the
fourth grade of the elementary school in Egypt. This is through Arabic Grammar Trainer (AGTrainer)
which is an Intelligent CALL. The implemented system (AGTrainer) trains the students through different
questions that deal with the different concepts and have different difficulty levels. Constraint-based student
modeling (CBSM) technique is used as a short-term student model. CBSM is used to define in small grain
level the different grammar skills through the defined skill structures. The main contribution of this paper
is the hierarchal representation of the system's basic grammar skills as domain knowledge. That
representation is used as a mechanism for efficiently checking constraints to model the student knowledge
and diagnose the student errors and identify their cause. In addition, satisfying constraints and the number
of trails the student takes for answering each question and fuzzy logic decision system are used to
determine the student learning level for each lesson as a long-term model. The results of the evaluation
showed the system's effectiveness in learning in addition to the satisfaction of students and teachers with its
features and abilities.
In the realm of computer security, the importance of efficient and reliable user authentication methods has
become increasingly critical. This paper examines the potential of mouse movement dynamics as a
consistent metric for continuous authentication. By analysing user mouse movement patterns in two
contrasting gaming scenarios, "Team Fortress" and "Poly Bridge," we investigate the distinctive
behavioral patterns inherent in high-intensity and low-intensity UI interactions. The study extends beyond
conventional methodologies by employing a range of machine learning models. These models are carefully
selected to assess their effectiveness in capturing and interpreting the subtleties of user behavior as
reflected in their mouse movements. This multifaceted approach allows for a more nuanced and
comprehensive understanding of user interaction patterns. Our findings reveal that mouse movement
dynamics can serve as a reliable indicator for continuous user authentication. The diverse machine
learning models employed in this study demonstrate competent performance in user verification, marking
an improvement over previous methods used in this field. This research contributes to the ongoing efforts to
enhance computer security and highlights the potential of leveraging user behavior, specifically mouse
dynamics, in developing robust authentication systems.
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
Image segmentation and classification tasks in computer vision have proven to be highly effective using neural networks, specifically Convolutional Neural Networks (CNNs). These tasks have numerous
practical applications, such as in medical imaging, autonomous driving, and surveillance. CNNs are capable
of learning complex features directly from images and achieving outstanding performance across several
datasets. In this work, we have utilized three different datasets to investigate the efficacy of various preprocessing and classification techniques in accurssedately segmenting and classifying different structures
within the MRI and natural images. We have utilized both sample gradient and Canny Edge Detection
methods for pre-processing, and K-means clustering have been applied to segment the images. Image
augmentation improves the size and diversity of datasets for training the models for image classification
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
This research aims to further understanding in the field of continuous authentication using behavioural
biometrics. We are contributing a novel dataset that encompasses the gesture data of 15 users playing
Minecraft with a Samsung Tablet, each for a duration of 15 minutes. Utilizing this dataset, we employed
machine learning (ML) binary classifiers, being Random Forest (RF), K-Nearest Neighbors (KNN), and
Support Vector Classifier (SVC), to determine the authenticity of specific user actions. Our most robust
model was SVC, which achieved an average accuracy of approximately 90%, demonstrating that touch
dynamics can effectively distinguish users. However, further studies are needed to make it viable option
for authentication systems. You can access our dataset at the following
link:https://github.com/AuthenTech2023/authentech-repo
This paper discusses the capabilities and limitations of GPT-3 (0), a state-of-the-art language model, in the
context of text understanding. We begin by describing the architecture and training process of GPT-3, and
provide an overview of its impressive performance across a wide range of natural language processing
tasks, such as language translation, question-answering, and text completion. Throughout this research
project, a summarizing tool was also created to help us retrieve content from any types of document,
specifically IELTS (0) Reading Test data in this project. We also aimed to improve the accuracy of the
summarizing, as well as question-answering capabilities of GPT-3 (0) via long text
In the realm of computer security, the importance of efficient and reliable user authentication methods has
become increasingly critical. This paper examines the potential of mouse movement dynamics as a
consistent metric for continuous authentication. By analysing user mouse movement patterns in two
contrasting gaming scenarios, "Team Fortress" and "Poly Bridge," we investigate the distinctive
behavioral patterns inherent in high-intensity and low-intensity UI interactions. The study extends beyond
conventional methodologies by employing a range of machine learning models. These models are carefully
selected to assess their effectiveness in capturing and interpreting the subtleties of user behavior as
reflected in their mouse movements. This multifaceted approach allows for a more nuanced and
comprehensive understanding of user interaction patterns. Our findings reveal that mouse movement
dynamics can serve as a reliable indicator for continuous user authentication. The diverse machine
learning models employed in this study demonstrate competent performance in user verification, marking
an improvement over previous methods used in this field. This research contributes to the ongoing efforts to
enhance computer security and highlights the potential of leveraging user behavior, specifically mouse
dynamics, in developing robust authentication systems.
Image segmentation and classification tasks in computer vision have proven to be highly effective using neural networks, specifically Convolutional Neural Networks (CNNs). These tasks have numerous
practical applications, such as in medical imaging, autonomous driving, and surveillance. CNNs are capable
of learning complex features directly from images and achieving outstanding performance across several
datasets. In this work, we have utilized three different datasets to investigate the efficacy of various preprocessing and classification techniques in accurssedately segmenting and classifying different structures
within the MRI and natural images. We have utilized both sample gradient and Canny Edge Detection
methods for pre-processing, and K-means clustering have been applied to segment the images. Image
augmentation improves the size and diversity of datasets for training the models for image classification.
This work highlights transfer learning’s effectiveness in image classification using CNNs and VGG 16 that
provides insights into the selection of pre-trained models and hyper parameters for optimal performance.
We have proposed a comprehensive approach for image segmentation and classification, incorporating preprocessing techniques, the K-means algorithm for segmentation, and employing deep learning models such
as CNN and VGG 16 for classification.
- The document presents 6 different models for defining foot size in Tunisia: 2 statistical models, 2 neural network models using unsupervised learning, and 2 models combining neural networks and fuzzy logic.
- The statistical models (SM and SHM) are based on applying statistical equations to morphological foot data.
- The neural network models (MSK and MHSK) use self-organizing Kohonen maps to cluster foot data and model full and half sizes.
- The fuzzy neural network models (MSFK and MHSFK) incorporate fuzzy logic into the neural network learning process to better account for uncertainty in foot sizes.
The security of Electric Vehicle (EV) charging has gained momentum after the increase in the EV adoption
in the past few years. Mobile applications have been integrated into EV charging systems that mainly use a
cloud-based platform to host their services and data. Like many complex systems, cloud systems are
susceptible to cyberattacks if proper measures are not taken by the organization to secure them. In this
paper, we explore the security of key components in the EV charging infrastructure, including the mobile
application and its cloud service. We conducted an experiment that initiated a Man in the Middle attack
between an EV app and its cloud services. Our results showed that it is possible to launch attacks against
the connected infrastructure by taking advantage of vulnerabilities that may have substantial economic and
operational ramifications on the EV charging ecosystem. We conclude by providing mitigation suggestions
and future research directions.
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
The AIRCC's International Journal of Computer Science and Information Technology (IJCSIT) is devoted to fields of Computer Science and Information Systems. The IJCSIT is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.
Design and optimization of ion propulsion dronebjmsejournal
Electric propulsion technology is widely used in many kinds of vehicles in recent years, and aircrafts are no exception. Technically, UAVs are electrically propelled but tend to produce a significant amount of noise and vibrations. Ion propulsion technology for drones is a potential solution to this problem. Ion propulsion technology is proven to be feasible in the earth’s atmosphere. The study presented in this article shows the design of EHD thrusters and power supply for ion propulsion drones along with performance optimization of high-voltage power supply for endurance in earth’s atmosphere.
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
Comparative analysis between traditional aquaponics and reconstructed aquapon...bijceesjournal
The aquaponic system of planting is a method that does not require soil usage. It is a method that only needs water, fish, lava rocks (a substitute for soil), and plants. Aquaponic systems are sustainable and environmentally friendly. Its use not only helps to plant in small spaces but also helps reduce artificial chemical use and minimizes excess water use, as aquaponics consumes 90% less water than soil-based gardening. The study applied a descriptive and experimental design to assess and compare conventional and reconstructed aquaponic methods for reproducing tomatoes. The researchers created an observation checklist to determine the significant factors of the study. The study aims to determine the significant difference between traditional aquaponics and reconstructed aquaponics systems propagating tomatoes in terms of height, weight, girth, and number of fruits. The reconstructed aquaponics system’s higher growth yield results in a much more nourished crop than the traditional aquaponics system. It is superior in its number of fruits, height, weight, and girth measurement. Moreover, the reconstructed aquaponics system is proven to eliminate all the hindrances present in the traditional aquaponics system, which are overcrowding of fish, algae growth, pest problems, contaminated water, and dead fish.
Null Bangalore | Pentesters Approach to AWS IAMDivyanshu
#Abstract:
- Learn more about the real-world methods for auditing AWS IAM (Identity and Access Management) as a pentester. So let us proceed with a brief discussion of IAM as well as some typical misconfigurations and their potential exploits in order to reinforce the understanding of IAM security best practices.
- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
#Prerequisites:
- Basic understanding of AWS services and architecture
- Familiarity with cloud security concepts
- Experience using the AWS Management Console or AWS CLI.
- For hands on lab create account on [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
# Scenario Covered:
- Basics of IAM in AWS
- Implementing IAM Policies with Least Privilege to Manage S3 Bucket
- Objective: Create an S3 bucket with least privilege IAM policy and validate access.
- Steps:
- Create S3 bucket.
- Attach least privilege policy to IAM user.
- Validate access.
- Exploiting IAM PassRole Misconfiguration
-Allows a user to pass a specific IAM role to an AWS service (ec2), typically used for service access delegation. Then exploit PassRole Misconfiguration granting unauthorized access to sensitive resources.
- Objective: Demonstrate how a PassRole misconfiguration can grant unauthorized access.
- Steps:
- Allow user to pass IAM role to EC2.
- Exploit misconfiguration for unauthorized access.
- Access sensitive resources.
- Exploiting IAM AssumeRole Misconfiguration with Overly Permissive Role
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- Objective: Show how overly permissive IAM roles can lead to privilege escalation.
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- Create role with administrative privileges.
- Allow user to assume the role.
- Perform administrative actions.
- Differentiation between PassRole vs AssumeRole
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Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Discover the latest insights on Data Driven Maintenance with our comprehensive webinar presentation. Learn about traditional maintenance challenges, the right approach to utilizing data, and the benefits of adopting a Data Driven Maintenance strategy. Explore real-world examples, industry best practices, and innovative solutions like FMECA and the D3M model. This presentation, led by expert Jules Oudmans, is essential for asset owners looking to optimize their maintenance processes and leverage digital technologies for improved efficiency and performance. Download now to stay ahead in the evolving maintenance landscape.
Rainfall intensity duration frequency curve statistical analysis and modeling...bijceesjournal
Using data from 41 years in Patna’ India’ the study’s goal is to analyze the trends of how often it rains on a weekly, seasonal, and annual basis (1981−2020). First, utilizing the intensity-duration-frequency (IDF) curve and the relationship by statistically analyzing rainfall’ the historical rainfall data set for Patna’ India’ during a 41 year period (1981−2020), was evaluated for its quality. Changes in the hydrologic cycle as a result of increased greenhouse gas emissions are expected to induce variations in the intensity, length, and frequency of precipitation events. One strategy to lessen vulnerability is to quantify probable changes and adapt to them. Techniques such as log-normal, normal, and Gumbel are used (EV-I). Distributions were created with durations of 1, 2, 3, 6, and 24 h and return times of 2, 5, 10, 25, and 100 years. There were also mathematical correlations discovered between rainfall and recurrence interval.
Findings: Based on findings, the Gumbel approach produced the highest intensity values, whereas the other approaches produced values that were close to each other. The data indicates that 461.9 mm of rain fell during the monsoon season’s 301st week. However, it was found that the 29th week had the greatest average rainfall, 92.6 mm. With 952.6 mm on average, the monsoon season saw the highest rainfall. Calculations revealed that the yearly rainfall averaged 1171.1 mm. Using Weibull’s method, the study was subsequently expanded to examine rainfall distribution at different recurrence intervals of 2, 5, 10, and 25 years. Rainfall and recurrence interval mathematical correlations were also developed. Further regression analysis revealed that short wave irrigation, wind direction, wind speed, pressure, relative humidity, and temperature all had a substantial influence on rainfall.
Originality and value: The results of the rainfall IDF curves can provide useful information to policymakers in making appropriate decisions in managing and minimizing floods in the study area.
An improved modulation technique suitable for a three level flying capacitor ...IJECEIAES
This research paper introduces an innovative modulation technique for controlling a 3-level flying capacitor multilevel inverter (FCMLI), aiming to streamline the modulation process in contrast to conventional methods. The proposed
simplified modulation technique paves the way for more straightforward and
efficient control of multilevel inverters, enabling their widespread adoption and
integration into modern power electronic systems. Through the amalgamation of
sinusoidal pulse width modulation (SPWM) with a high-frequency square wave
pulse, this controlling technique attains energy equilibrium across the coupling
capacitor. The modulation scheme incorporates a simplified switching pattern
and a decreased count of voltage references, thereby simplifying the control
algorithm.
An improved modulation technique suitable for a three level flying capacitor ...
Top 10 Download Article in Computer Science & Information Technology: March 2021
1. Top 10 Download Article
in Computer Science &
Information Technology:
March 2021
International Journal of Computer Science and
Information Technology (IJCSIT)
Google Scholar Citation
ISSN: 0975-3826(online); 0975-4660 (Print)
http://airccse.org/journal/ijcsit.html
2. EDGE DETECTION TECHNIQUES FOR IMAGE SEGMENTATION
Muthukrishnan.R1
and M.Radha2
1
Assistant Professor, Department of Statistics, Bharathiar University, Coimbatore.
2
Research Scholar, Department of Statistics, Bharathiar University, Coimbatore.
ABSTRACT
Interpretation of image contents is one of the objectives in computer vision specifically in image
processing. In this era it has received much awareness of researchers. In image interpretation the
partition of the image into object and background is a severe step. Segmentation separates an image
into its component regions or objects. Image segmentation t needs to segment the object from the
background to read the image properly and identify the content of the image carefully. In this
context, edge detection is a fundamental tool for image segmentation. In this paper an attempt is
made to study the performance of most commonly used edge detection techniques for image
segmentation and also the comparison of these techniques is carried out with an experiment by
using MATLAB software.
KEYWORDS
Computer Vision , Image Segmentation , Edge detection, MATLAB.
For More Details : http://airccse.org/journal/jcsit/1211csit20.pdf
Volume Link : http://airccse.org/journal/ijcsit2011_curr.html
3. REFERENCES
[1] Canny, J. F (1983) Finding edges and lines in images, Master's thesis, MIT. AI Lab. TR-720.
Canny, J. F (1986) “A computational approach to edge detection”, IEEE Transaction on
Pattern Analysis and Machine Intelligence, 8, 679-714.
[2] Courtney. P & N. A. Thacker (2001) “Performance Characterization in Computer
Vision: The Role of Statistics in Testing and Design”, Chapter in: “Imaging and Vision
Systems: Theory, Assessment and Applications”, Jacques Blanc-Talon and Dan
Popescu (Eds.), NOVA Science Books.
[3] Hanzi Wang (2004) Robust Statistics for Computer Vision: Model Fitting, Image
Segmentation and Visual Motion Analysis, Ph.D thesis, Monash University,
Australia.
[4] Huber, P.J. (1981) Robust Statistics, Wiley New York.
[5] Kirsch, R. (1971) “Computer determination of the constituent structure of biological
images”,Computers and Biomedical Research, 4, 315–328.
[6] Lakshmi,S & V.Sankaranarayanan (2010) “A Study of edge detection techniques
forsegmentation computing approaches”, Computer Aided Soft Computing
Techniques for Imaging and Biomedical Applications, 35-41.
[7] Lee, K.. M, Meer, P. & et al. (1998) “Robust Adaptive Segmentation of Range
Images”, IEEE Trans. Pattern Analysis and Machine Intelligence, 20(2), 200-205.
[8] Marr, D & E. Hildreth (1980) “Theory of edge detection”, Proc. Royal Society of
London, B, 207, 187–217.
[9] Marr, D(1982) Vision, Freeman Publishers.
[10] Marr, P & Doron Mintz, D. & et al. (1991) “Robust Regression for Computer
Vision: A Review”, International Journal of Computer Vision, 6(1), 59-70.
[11] Orlando, J, Tobias & Rui Seara (2002) “Image Segmentation by Histogram
Thresholding Using Fuzzy Sets”, IEEE Transactions on Image Processing, Vol.11,
No.12, 1457-1465.
[12] Punam Thakare (2011) “A Study of Image Segmentation and Edge Detection
Techniques”,International Journal on Computer Science and Engineering, Vol 3,
No.2, 899-904.
4. [13] Rafael C. Gonzalez, Richard E. Woods & Steven L. Eddins (2004) Digital Image
ProcessingUsing MATLAB, Pearson Education Ptd. Ltd, Singapore.
[14] Ramadevi, Y & et al (2010) “Segmentation and object recognition using edge
detection techniques”, International Journal of Computer Science and Information
Technology, Vol 2, No.6, 153-161.
[15] Roberts, L (1965) “Machine Perception of 3-D Solids”, Optical and Electro-optical
Information Processing, MIT Press.
[16] Robinson. G (1977) “Edge detection by compass gradient masks”, Computer
graphics and image processing, 6, 492-501.
[17] Rousseeuw, P. J & Leroy, A (1987) Robust Regression and outlier detection, John
Wiley & Sons, New York.
[18] Senthilkumaran. N & R. Rajesh (2009) “Edge Detection Techniques for Image
Segmentation – A Survey of Soft Computing Approaches”, International Journal of
Recent Trends in Engineering, Vol. 1, No. 2, 250-254.
[19] Sowmya. B & Sheelarani. B (2009) “Colour Image Segmentation Using Soft
Computing Techniques”, International Journal of Soft Computing Applications, Issue
4, 69-80.
[20] Umesh Sehgal (2011) “Edge detection techniques in digital image processing using
Fuzzy Logic”, International Journal of Research in IT and Management, Vol.1, Issue
3, 61-66.
[21] Yu, X, Bui, T.D. & et al. (1994) “Robust Estimation for Range Image Segmentation
and Reconstruction”, IEEE trans. Pattern Analysis and Machine Intelligence, 16 (5),
530-538.
5. COMMON PHASES OF COMPUTER FORENSICS INVESTIGATION MODELS
Yunus Yusoff, Roslan Ismail and Zainuddin Hassan
College of Information Technology, Universiti Tenaga Nasional,
Selangor, Malaysia
ABSTRACT
The increasing criminal activities using digital information as the means or targets warrant
for a structured manner in dealing with them. Since 1984 when a formalized process been
introduced, a great number of new and improved computer forensic investigation processes
have been developed. In this paper, we reviewed a few selected investigation processes that
have been produced throughout the years and then identified the commonly shared processes.
Hopefully, with the identification of the commonly shard process, it would make it easier for
the new users to understand the processes and also to serve as the basic underlying concept
for the development of a new set of processes. Based on the commonly shared processes, we
proposed a generic computer forensics investigation model, known as GCFIM.
KEYWORDS
Computer Forensic Models, Computer Forensic Investigation
For More Details : http://airccse.org/journal/jcsit/0611csit02.pdf
Volume Link : http://airccse.org/journal/ijcsit2011_curr.html
6. REFERENCES
[1] M. G. Noblett, M. M. Pollitt & L. A. Presley, (2000) “Recovering and Examining Computer
Forensic Evidence”, Forensic Science Communications, Vol. 2, No. 4.
[2] M. M. Pollitt, (1995) “Computer Forensics: An Approach to Evidence in Cyberspace”, in
Proceeding of the National Information Systems Security Conference, Baltimore, MD, Vol. II, pp.
487-491.
[3] M. M. Pollitt, (2007) “An Ad Hoc Review of Digital Forensic Models”, in Proceeding of the Second
International Workshop on Systematic Approaches to Digital Forensic Engineering (SADFE’07),
Washington, USA.
[4] G. Palmer, (2001) "DTR-T001-01 Technical Report. A Road Map for Digital Forensic Research",
Digital Forensics Workshop (DFRWS), Utica, New York.
[5] M. Reith, C. Carr & G. Gunsh, (2002) “An Examination of Digital Forensics Models”, International
Journal of Digital Evidence, Vol. 1, No. 3.
[6] B. Carrier & E. H. Spafford, (2003) “Getting Physical with the Digital Investigation Process”,
International Journal of Digital Evidence, Vol. 2, No. 2
[7] V. Baryamereeba & F. Tushabe, (2004) “The Enhanced Digital Investigation Process Model”, in
Proceeding of Digital Forensic Research Workshop, Baltimore, MD.
[8] M. K. Rogers, J. Goldman, R. Mislan, T. Wedge & S. Debrota, (2006) “Computer Forensic Field
Triage Process Model”, presented at the Conference on Digital Forensics, Security and Law, pp. 27-
40.
[9] P. Sundresan, (2009) “Digital Forensic Model based on Malaysian Investigation Process”,
International Journal of Computer Science and Network Security, Vol. 9, No. 8.
[10] S. Ciardhuain, (2004) “An Extended Model of Cybercrime Investigation”, International Journal of
Digital Evidence, Vol. 3, No. 1, pp. 1-22.
[11] P. Stephenson, (2003) "A Comprehensive Approach to Digital Incident Investigation.", Information
Security Technical Report, Vol. 8, Issue 2, pp 42-52. International Journal of Computer Science &
Information Technology (IJCSIT), Vol 3, No 3, June 2011 31
[12] N. L. Beebe & J. G. Clark, (2004) “A Hierarchical, Objective-Based Framework for the Digital
Investigations Process”, in Proceeding of Digital Forensic Research Workshop (DFRWS),
Baltimore, Maryland.
[13] M. Kohn, J. H. P. Eloff, & M. S. Olivier, (2006) “Framework for a Digital Forensic Investigation”, in
Proceedings of the ISSA 2006 from Insight to Foresight Conference, Sandton, South Africa.
[14] F. C. Freiling & B. Schwittay, (2007) “Common Process Model for Incident and Computer
Forensics”, in Proceedings of Conference on IT Incident Management and IT Forensics, Stuttgard,
Germany, pp. 19-40.
[15] D. Bem & E. Huebner, (2007) “Computer Forensic Analysis in a Virtual Environment”,
International Journal of Digital Evidence, vol. 6, no. 2, pp. 1-13.
[16] E. S. Pilli, R. C. Joshi, & R. Niyogi, (2010) “Network Forensic frameworks: Survey and research
challenges,” Digital Investigation, Vol. 7, pp. 14-27
7. MACHINE LEARNING METHODS FOR SPAM E-MAIL
CLASSIFICATION
W.A. Awad1
and S.M. ELseuofi2
1
Math.&Comp.Sci.Dept., Science faculty, Port Said University
2
Inf. System Dept.,Ras El Bar High inst.
ABSTRACT
The increasing volume of unsolicited bulk e-mail (also known as spam) has generated a need for reliable anti-
spam filters. Machine learning techniques now days used to automatically filter the spam e-mail in a very
successful rate. In this paper we review some of the most popular machine learning methods (Bayesian
classification, k-NN, ANNs, SVMs, Artificial immune system and Rough sets) and of their applicability to
the problem of spam Email classification. Descriptions of the algorithms are presented, and the comparison
of their performance on the SpamAssassin spam corpus is presented.
KEYWORDS
Spam, E-mail classification, Machine learning algorithms
For More Details : http://airccse.org/journal/jcsit/0211ijcsit12.pdf
Volume Link : http://airccse.org/journal/ijcsit2011_curr.html
8. REFERENCES
[1] M. N. Marsono, M. W. El-Kharashi, and F. Gebali, “Binary LNS-based naïve Bayes inference engine
for spam control: Noise analysis and FPGA synthesis”, IET Computers & Digital Techniques, 2008
[2] Muhammad N. Marsono, M. Watheq El-Kharashi, Fayez Gebali “Targeting spam control on
middleboxes: Spam detection based on layer-3 e-mail content classification” Elsevier Computer
Networks, 2009
[3] Yuchun Tang, Sven Krasser, Yuanchen He, Weilai Yang, Dmitri Alperovitch ”Support Vector
Machines and Random Forests Modeling for Spam Senders Behavior Analysis” IEEE GLOBECOM,
2008
[4] Guzella, T. S. and Caminhas, W. M. ”A review of machine learning approaches to Spam filtering.”
Expert Syst. Appl., 2009
[5] Wu, C. ”Behavior-based spam detection using a hybrid method of rule-based techniques and neural
networks” Expert Syst., 2009
[6] Khorsi. “An overview of content-based spam filtering techniques”, Informatica, 2007
[7] Hao Zhang, Alexander C. Berg, Michael Maire, and Jitendra Malic. "SVM-KNN: Discriminative
nearest neighbour classification for visual category recognition", IEEE Computer Society Conference
on Computer Vision and Pattern Recognition, 2006
[8] Carpinteiro, O. A. S., Lima, I., Assis, J. M. C., de Souza, A. C. Z., Moreira, E. M., & Pinheiro, C. A.
M. "A neural model in anti-spam systems.", Lecture notes in computer science.Berlin, Springer, 2006
[9] El-Sayed M. El-Alfy, Radwan E. Abdel-Aal "Using GMDH-based networks for improved spam
detection and email feature analysis"Applied Soft Computing, Volume 11, Issue 1, January 2011
[10] Li, K. and Zhong, Z., “Fast statistical spam filter by approximate classifications”, In Proceedings of
the Joint international Conference on Measurement and Modeling of Computer Systems. Saint Malo,
France, 2006
[11] Cormack, Gordon. Smucker, Mark. Clarke, Charles " Efficient and effective spam filtering and re-
ranking for large web datasets" Information Retrieval, Springer Netherlands. January 2011
[12] Almeida,tiago. Almeida, Jurandy.Yamakami, Akebo " Spam filtering: how the dimensionality
reduction affects the accuracy of Naive Bayes classifiers" Journal of Internet Services and
Applications, Springer London , February 2011
[13] Yoo, S., Yang, Y., Lin, F., and Moon, I. “Mining social networks for personalized email prioritization”.
In Proceedings of the 15th ACM SIGKDD international Conference on Knowledge Discovery and
Data Mining (Paris, France), June 28 - July 01, 2009
9. IMPORTANCE OF DATA COLLECTION AND VALIDATION FOR
SYSTEMATIC SOFTWARE DEVELOPMENT PROCESS
Mala.V.Patil1
and Dr. A.M.Nageswara Yogi2
1
Research scholar, Anna University, Coimbatore, INDIA
2
Scientist, ADE, Defence Research and Development Organization, Bangalore, INDIA
ABSTRACT
Systematic software development process involves estimation of size, effort, schedule and cost
of a software project and analysis of critical factors affecting these estimates. In literature there
are many methods for software estimation and categorization of critical factors. More than 50%
of the projects undertaken have challenged the initially proposed estimates. Even if we consider
updating estimates at various phases of software development, the percentage of challenged
projects reduces marginally. The reason for such a situation is that the decisions are made on
historical and collected data. Therefore, software data collection to a reasonable accuracy and its
validation is important both for decision making and validating software development process.
In this paper an effort is made to highlight the importance of software data collection. Collected
data is utilized to validate effort estimation model formulated by the authors. Comparison of
effort values obtained from popular estimation models is also made. The data collected has also
helped in identifying the critical factors affecting the estimates.
KEYWORDS
Software Size, Effort, Cost, Schedule, Risk, Estimation.
For More Details : http://airccse.org/journal/jcsit/0411csit20.pdf
Volume Link : http://airccse.org/journal/ijcsit2020_curr.html
10. REFERENCES
[1] Barry W .Boehm, (1981) Software Engineering Economics, Prentice -Hall, Inc., Eaglewood Cliffs,
New Jersey.
[2] Barry W. Boehm, (1988) “A Spiral Model of Software Development and Enhancement”, Computer,
Vol. 21, No. 5, pp. 61-72.
[3] Barry W. Boehm, (1989) “Software Risk Management, tutorial”, IEEE CS Press.
[4] Barry W. Boehm, Bradford Clark, B, Ellis Horowitz, Chris Westland, Ray Madachy, and Richard
Selby, (1995) “Cost Models for Future Software Life Cycle Processes: COCOMO 2.0”, Annals of
software Engineering, Special Volume on Software Process and Product Measurement, pp. 1-35.
[5] Barry W. Boehm, (1996) “Anchoring the software process”, IEEE software, Vol.13, No.4, pp.73-82.
International Journal of Computer Science & Information Technology (IJCSIT), Vol 3, No 2, April
2011 275
[6] Barry W. Boehm, (1991) “Software Risk Management: Principles and Practices”, IEEE Software, Vol.
8, No. 1, pp. 32-41.
[7] Christopher G. Jones, Glen L. Gray, Anna H. gold and David W. Miller, (2010) “Strategies for
Improving Systems Development Project Success”, Issues in Information Systems. Vol. 9, No. 1, pp.
164-173.
[8] Clyde G. Chittister and Y. Y. Haimes, (1996) “System Integration via Software Risk Management”,
IEEE Trans on Systems, Man and Cybernetics, Vol. 26, No. 5, pp. 521-532.
[9] Daniel V. Ferens, (1999) “The Conundrum of Software Estimation Models”, IEEE AES Systems
Magazine, pp. 23-29.
[10] A. Gemmer, (1997) “Risk Management Moving beyond process”, Computer, Vol. 30, No. 5, pp. 33-
41.
[11] H,Hecht, (2003) Systems Reliability and Failure Prevention, Artech House.
[12] Janne Ropponen and Kalle Lyytinen , (2000) “Components of Software Developments Risk: How to
Address Them? A Project Manager Survey”, IEEE Trans. on Software Engineering ,Vol. 26, No. 2,
pp. 98-112.
[13] Jingyue Li, Reidar Conradi, Odd Petter N. Slyngstad, Marco Torchiano, Maurizio Morisio and
Christian Buns, (2008) “ A State-of-the Practice Survey of Risk Management in Development with
Off-the-Shelf Software Components”, IEEE Trans. On Software Engineering, Vol. 34, No.2, pp.271-
286.
[14] M. Jorgensen and K. Molokken, (2006) “How Large are Software Cost Overruns? A Review of the 1994
Chaos Report”, Information and Software Technology, Vol. 48, No. 8, pp. 297-301.
[15] J. Laurenz Eveleens and Chris Verhoef, (2010) “The Rise and Fall of the Chaos Report Figures”, IEEE
Software, Vol. 27, No. 1, pp. 30-36. .
[16] Linda Wallace and Mark Keil,(2004) “Software Project Risks and their effects on Outcomes”, Comm.
of the ACM, Vol. 47, No.4, pp. 68-73.
[17] Mala V Patil and AM Nageswara Yogi, (2010) “Software Development Projects by Engineering
11. Students – Analyses of Difficulties and Effort including Risk Elements”, International Journal of
Computer Applications in Engineering, Technology and Sciences, Vol. 2, No. 2, pp. 132-137.
[18] Mala V Patil and AM Nageswara Yogi, (2010) “Effort Estimation and Risk Analyses for Software
Projects by Data Analyses of Developed Projects”, ACS - International Journal on Computational
Intelligence, Vol. 1, No. 2, pp. 43 -52.
[19] Mark Keil, Paul E. Cule, Kalle Lyytinen, and Roy C. Schmidt, (1998) “A Framework for Identifying
Software Project Risks”, Communication of the ACM, Vol. 4, No. 11, pp. 76-83.
[20] Marvin J. Carr, Suresh L. Konda, Ira Monarch, F. Carol Ulrich and Clay F. Walker, (1993)
“Taxonomy-Based Risk Identification”, Technical Report No. CMU/SEI-93-TR-6, ESC-TR-93- 183.
International Journal of Computer Science & Information Technology (IJCSIT), Vol 3, No 2, April
2011 276
[21] AM Nageswara Yogi, (2006) “A model for Life Cycle Cost Estimation for Defence Equipment”,
Proceeding of International Conference on Trends in Product Life Cycle Modeling, Simulation and
Synthesis PLMSS-2006, pp. 415-423.
[22] AM Nageswara Yogi, Mala V Patil, (2009) “Software Effort Estimation Models and Performance
Analysis with Case Studies,” International Journal of Computer Applications in Engineering,
Technology and Sciences, Vol. 1, No. 2, pp. 558-565.
[23] Rasmita Dash and Rajashree Dash, (2010) “Risk Assessment Techniques for Software Development”,
European Journal of Scientific Research, Vol. 42, No. 4, pp. 615-622.
[24] Robert L. Glass, (2001) “Frequently Forgotten Fundamental Facts about Software Engineering”, IEEE
software, Vol. 18, No. 3, pp. 110-112.
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[26] Roger S. Pressman, (2010) Software Engineering A Practitioner’s Approach, Seventh Edition, Tata
McGraw-Hill.
[27] Dr Roger Sapsford, (2006) Data Collection and Analysis, Amazon. [28] I. Sommerville, (2004)
Software Engineering, Seventh Ed, Addison-Wesley.
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[30] Susan A. Sherer, (1995) “The Three Dimensions of Software Risk: Technical, Organizational and
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[31] Tony Moynihan, (1997) “How Experienced Project Managers Assess Risk”, IEEE Software, Vol. 14,
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[32] Victor R, Basili and David M. Weiss, (1984) “A Methodology for Collecting Valid Software
Engineering Data”, IEEE Trans on software Engineering, Vol. SE-10, No. 6, pp. 728-738.
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Principles and Practice, Tata McGrawHill Pvt. Ltd.
[35] www.developer.com/mgmt/article.php/1463281
12. THE ANALYSIS OF THE TIME TABLE STRUCTURE WITHIN A
STUDENT INFORMATION SYSTEM (SIS)
Dr. Issa S. I. Ottoum Department of Computer information system (CIS) Alzaytoonah
University of Jordan Amman, Jordan
ABSTRACT
This paper will show the result of the analysis and synthesis processes that take place when making a time
table for a University Information System (UIS), especially for SIS.This proposed paper does the comparison
between two methods of designing a time table, shows the advantages and disadvantages of these methods
and more precisely how to implement each of them using programming languages.
KEYWORDS
Student Information System (SIS), Time table, Prerequisite courses, Flowchart.
For More Details : http://airccse.org/journal/jcsit/7115ijcsit08.pdf
Volume Link : http://airccse.org/journal/ijcsit2010_curr.html
13. REFERENCES
[1] http:// www.bu.edu/reg (UIS of Boston University, USA).
[2] http://www.oibs.metu.edu.tr (UIS of Middle East Technical University, Turkey) [3]`
http://www.utdallas.edu (UIS of University of Texas, USA)
[4] http://www.acs.utah.edu/student (UIS of University of Utah, USA)
[5] http://www.sisweb.uccavis.edu (UIS of University of California)
[6] http://www.registar.mit.edu (UIS of MIT, USA)
[7] http://www.epgy.stanford.edu (UIS of Stanford University, USA)
[9] Zhang, L., Lau, S. (2005). Constructing university timetable using constraint satisfaction programming
approach. Proceedings of the International Conference on Computational Intelligence for Modeling ,
Control and Automation and International Conference on Intelligent Agents , Web Technologies and
Internet Commerce Vol-2 ( CIMCA - IAWTIC'06 ), November 28 - 30 , p.55 - 60.
[10] Ho Sheau Fen, ET.al. (2009) University Course Timetable Planning using Hybrid Particle Swam
Optimization. GEC’09 Proceedings of the First ACM / SIGEVO Summit on Generic and Evolutionary
Computation, NY, USA, p.p. 239 - 246.
[11] Beck J.C., Davenport A.J., and Fox M.S. (1988) The ODO Project Towards a Unified Basis for
Constraint-Directed Scheduling. International Journal of Scheduling, 1, p.p. 89 - 125.
[12] http://www.ttable.com (software package TTABLE)
[13] http://timetabler.com/tt4windows (software package TimeTabler4).
[14] Ossyka, A. Mghawish, A. Ottom, E. (2005) Computer-Aided Students Registration System. The
Second International Conference on Information Technology ICIT-2005 (p.p. 291 – 297), Amman,
Jordan.
[15] Francisco Azevedo and Pedro Barahona.Timetabling in constraint logic programming.In Proceedings
of 2nd World Congress on Expert Systems, Estoril, Portugal, Jan 1994.
[16] Developing New Features for a University Information System Dr. Afif J. Almghawish Journal “
Science Series Data Report ”, Vol.4, and No.12. Dec 2012, P.71 - 85.
[17] Supporting Student Information System Validity. Afif J. ALmghawish, Alexandre F. Ossyka,
European Journal of Scientific Research Vol.99 , No.2 April 2013. [18] Andrea Schaerf. A survey of
automated timetabling. Artificial Intelligence Review, 13(2):87 - 127, 1999.
[19] Martin Henz and JörgWürtz.Using Oz for college timetabling. In Proceedings of the 1995 International
Conference on the Practice and Theory of Automated Timetabling, Edinburg Scotland, Aug. 1995
[20] A. Mghawish, Ossyka, I. Ottom, A Novel Approach To Enhance a University Information System,
World of Computer Science and Information Technology Journal (WCSIT) ISSN: 2221-0741 Vol. 3,
No. 7, 130-134, 2013
14. EVALUATION OF INFORMATION RETRIEVAL SYSTEMS
Keneilwe Zuva1
and Tranos Zuva2
1
Department of Computer Science, University of Botswana, Gaborone, Botswana
2
Department of Computer Systems Engineering, Tshwane University Technology, Pretoria,
SA
ABSTRACT
One of the challenges of modern information retrieval is to adequately evaluate Information Retrieval System
(IRS) in order to estimate future performance in a specified application domain. Since there are many
algorithms in literature the decision to select one for usage depends mostly on the evaluation of the systems’
performance in the domain. This paper presents how visual and scalar evaluation methods complement one
another to adequately evaluate information retrieval systems. The visual evaluation methods are capable of
indicating whether one IRS performs better than another IRS fully or partially. An overall performance of
IRS is revealed using scalar evaluation methods. The use of both types of evaluation methods will give a
clear picture of the performance of the IRSs. The Receiver Operator Characteristic (ROC) curve and
Precision-Recall (P-R) curve were used to illustrate the visual evaluation methods. Scalar methods notably
precision, recall, Area Under Curve (AUC) and F measure were used.
KEYWORDS
ROC curve, Precision, Recall, Area Under Curve, Information Retrieval System
For More Details : http://airccse.org/journal/jcsit/0612csit04.pdf
Volume Link : http://airccse.org/journal/ijcsit2012_curr.html
15. REFERENCES
[1] E. Rasmussen, "Evaluation in Information Retrieval," in 3rd International Conference on Music
Information Retrieval, Paris, France, 2002, pp. 45-49.
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Diversity and Practical Relevance," Informatica, vol. 32, pp. 27-38, 2008.
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DC, 2006, pp. 123-127.
[11] K. H. Brodersen, et al., "The binormal assumption on precision-recall curves," in International
Conference on Pattern Recognition, 2010, pp. 4263-4266.
[12] C. Ferri, et al., "Volume Under the ROC surface for Multi-class Problems. Exact Computation and
Evaluation of Approximations," in Proc. of 14th European Conference on Machine Learning, 2003,
pp. 108-120.
[13] C. Drummond and R. C. Holte, "Explicity Representing Expected Cost: An Alternative to ROC
Representation," in In Proceedings of the Six ACM SIGKDD International Conference on Knowledge
Discovery and Data Mining, 2000, pp. 198-207.
[14] S. D. Walter, "Properties of the Summary Receiver Operating Characteristic (SROC) curve for
diagnostic test data," Statistics in Medicine, vol. 21, pp. 1237-1256, 10 April 2002.
[15] K. Jarvelin and J. Kekalainen, "IR evaluation methods for retrieving highly relevant documents," in
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in Information Retrieval, New York NY, 2000, pp. 41-48
16. THE DEVELOPMENT OF ELECTRONIC PAYMENT SYSTEM FOR
UNIVERSITIES IN INDONESIA: ON RESOLVING KEY SUCCESS
FACTORS
Veronica S. Moertini1 , Asdi A. Athuri2,4, Hery M. Kemit3 , Nico Saputro1
1
Informatics Dept., 2
Accounting Dept., 3
IT Bureau, 4
Finance Bureau Parahyangan Catholic
University Bandung – Indonesia moertini, asdi, kemit,
ABSTRACT
It is known that IT projects are high-risk. To achieve project success, the strategies to avoid and reduce risks
must be designed meticulously and implemented accordingly. This paper presents methods for avoiding and
reducing risks throughout the development of an information system, specifically electronic payment system
to handle tuition in the universities in Indonesia. The university policies, regulations and system models are
design in such a way to resolve the project key success factors. By implementing the proposed methods, the
system has been successfully developed and currently operated. The research is conducted in Parahyangan
Catholic University, Bandung, Indonesia.
KEYWORDS
university electronic payment system, tuition payment system, resolving key success factor, ensuring IS
project success.
For More Details : http://airccse.org/journal/jcsit/0411csit02.pdf
Volume Link : http://airccse.org/journal/ijcsit2011_curr.html
17. REFERENCES
[1] Viva News, Transaksi ATM BCA Tak Alami Penyusutan, 22 January 2010,
http://bisnis.vivanews.com/news/read/123599-transaksi_atm_bca_tak_alami_penyusutan [accessed 8
Sep 10]
[2] Oke Zone, Transaksi ATM Mandiri Capai Rp 29,9 T, 27 Sept. 2009,
http://economy.okezone.com/read/2009/09/27/320/260086/320/transaksi-atm-mandiri-capai-rp29-9-t
[accessed 8 Sep 10]
[3] Bisnis Indonesia Online, BCA Tingkatkan Jumlah ATM jadi 7.000, 2 Sept. 2010,
http://web.bisnis.com/keuangan/perbankan/1id205573.html [accessed 8 Sep 10].
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[5] Laghari, K. U. R., Yahia, I. G. B., Crespi, N. Analysis of Telecommunication Management
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[6] Tempo Interaktif Bisnis, Transaksi Internet Bank Permata Tumbuh 30 persen, 19 May 2010,
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[7] Inilai Com, Transaksi Internet Banking Danamon Rp250 M, 17 November 2009,
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rp250- m/ [accessed 8 Sep 10]
[8] Inilah Com, Transaksi Internet Banking BCA Naik 50%, 29 April 2010,
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naik50/ [accessed 8 Sep 10]
[9] Tribun News, Transaksi Internet Banking BRI Selama Ramadhan Naik Drastis, 18 August 2010,
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[accessed 8 Sep 10]
[10] BNI, Penguna BNI SMS Banking Naik 92%, 19 September 2007,
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Industrial Management + Data Systems; 2004; 104, 3/4; ABI/INFORM Global pg. 286.
[13] Tesch, D.; Kloppenborg, T.J.; Frolick, M.N.; It Project Risk Factors: The Project Management
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ABI/INFORM Global, pg. 61.
[14] Raja, J., Velmurgan, M.S., “E-payments: Problems and Prospects”, Journal of Internet Banking and
Commerce, April 2008, vol. 13, no. 1, (http://www.arraydev.com/commerce/jibc/).
[15] He, F., Mykytyn, P.P., “Decision Factors for The Adoption of an Online Payment System by
Customers”, International Journal of E-Business Research, Vol. 3, Issue 4, 2007.
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Internet Banking and Commerce, April 2008, vol. 13, no. 1
(http://www.arraydev.com/commerce/jibc/).
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[19] Ruiz-Martı´nez, A., Ca´novas, O., Go´mez-Skarmeta, A.F., Design and implementation of a generic
per-fee-link framework, Internet Research, Vol. 19 No. 3, 2009, pp. 293-312, Emerald Group Pub.
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[22] Fuller, M.A., Valacich, J.S., George, J.F., Information Systems Project Management A Process and
Team Approach, Pearson Prentice Hall, New Jersey, USA, 2008.
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dominant dozen. Information Systems Management, 23(4), 31.
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[25] Chua, A.Y.K, Exhuming IT projects from their graves: An analysis of eight failure cases and their risk
factors. The Journal of Computer Information Systems, 49(3), 31.
[26] Moertini, V. S., Athuri, A. A., Kemit, H. M., Saputro, N., Electronic Payment System for Universities
in Indonesia: A Framework for Developing System Solution, The 2010 Intl. Conf. on Business and
Digital Enterprises, Gopalan College of Eng & Management, Bangalore, India, 19-21 July 2010.
[27] Pressman, R. S., 2005. Software Engineering A Practitioner’s Approach, McGraw Hill Higher
Education, N.Y., USA, 2005.
[28] Object Management Group, Inc. OMG Unified Modeling Language Specification, v. 1.3, June 1999.
[29] Schach, S.R., 2002. Object-Oriented and Classical Software Engineering, 5th ed. McGraw Hill, US.
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[33] Rocha, B. C. D & Sousa Junior, R.R. Identifying Bank Frauds Using CRISP-DDM and Decision Trees,
19. SECURITY THREATS ON CLOUD COMPUTING VULNERABILITIES
Te-Shun Chou
Department of Technology Systems, East Carolina University, Greenville, NC,
U.S.A.
ABSTRACT
Clouds provide a powerful computing platform that enables individuals and organizations to
perform variety levels of tasks such as: use of online storage space, adoption of business
applications, development of customized computer software, and creation of a “realistic” network
environment. In previous years, the number of people using cloud services has dramatically
increased and lots of data has been stored in cloud computing environments. In the meantime, data
breaches to cloud services are also increasing every year due to hackers who are always trying to
exploit the security vulnerabilities of the architecture of cloud. In this paper, three cloud service
models were compared; cloud security risks and threats were investigated based on the nature of
the cloud service models. Real world cloud attacks were included to demonstrate the techniques
that hackers used against cloud computing systems. In addition,countermeasures to cloud security
breaches are presented.
KEYWORDS
Cloud computing, cloud security threats and countermeasures, cloud service models
For More Details : http://airccse.org/journal/jcsit/5313ijcsit06.pdf
Volume Link : http://airccse.org/journal/ijcsit2013_curr.html
20. REFERENCES
1. DataLossDB Open Security Foundation. http://datalossdb.org/statistics
2. Sophos Security Threat Report 2012. http://www.sophos.com/
3. Amazon.com Server Said to Have Been Used in Sony Attack, May
2011.http://www.bloomberg.com/news/2011-05-13/sony-network-said-to-have-been-
invaded-by-hackersusing-amazon-com-server.html
4. D. Jamil and H. Zaki, “Security Issues in Cloud Computing and Countermeasures,”
International Journal of Engineering Science and Technology, Vol. 3 No. 4, pp. 2672-
2676, April 2011.
5. K. Zunnurhain and S. Vrbsky, “Security Attacks and Solutions in Clouds,” 2nd IEEE
International Conference on Cloud Computing Technology and Science, Indianapolis,
December 2010.
6. W. A. Jansen, “Cloud Hooks: Security and Privacy Issues in Cloud Computing,” 44th
Hawaii International Conference on System Sciences, pp. 1–10, Koloa, Hawaii, January
2011.
7. T. Roth, “Breaking Encryptions Using GPU Accelerated Cloud Instances,” Black Hat
Technical Security Conference, 2011.
8. CERT Coordination Center, Denial of
Service.http://www.packetstormsecurity.org/distributed/denial_of_service.html
9. M. Jensen, J. Schwenk, N. Gruschka, and L. L. Iacono, “On Technical Security Issues
in Cloud Computing,” IEEE International Conference in Cloud Computing, pp. 109-116,
Bangalore, 2009.
10. Thunder in the Cloud: $6 Cloud-Based Denial-of-Service Attack, August
2010.http://blogs.computerworld.com/16708/thunder_in_the_cloud_6_cloud_based_de
ni al_of_service_attack
11. DDoS Attack Rains Down on Amazon Cloud, October
2009.http://www.theregister.co.uk/2009/10/05/amazon_bitbucket_outage/
12. 2011 CyberSecurity Watch Survey, CERT Coordination Center at Carnegie Mellon
University.
13. D. Catteddu and G. Hogben, “Cloud Computing Benefits, Risks and Recommendations
for Information Security,” The European Network and Information Security Agency
(ENISA), November 2009.
21. 14. Insider Threats Related to Cloud Computing, CERT, July 2012. http://www.cert.org/
15. Data Breach Trends & Stats, Symantec, 2012. http://www.indefenseofdata.com/data-
breach-trendsstats/
16. 2012 Has Delivered Her First Giant Data Breach, January
2012.http://www.infosecisland.com/blogview/19432-2012-Has-Delivered-Her-First-
Giant-DataBreach.html
17. A Few Wrinkles Are Etching Facebook, Other Social Sites, USA Today,
2011.http://www.usatoday.com/printedition/life/20090115/socialnetworking15_st.art.h
tm l
18. An Update on LinkedIn Member Passwords Compromised, LinkedIn Blog, June,
2012.http://blog.linkedin.com/2012/06/06/linkedin-member-passwords-
compromised/
19. Dropbox: Yes, We Were Hacked, August 2012. http://gigaom.com/cloud/dropbox-
yes-we-werehacked/
20. Web Based Attacks, Symantec White Paper, February 2009.
21. Symantec Internet Security Threat Report, 2011 Trends, Vol. 17, April 2012.
22. P. P. Ramgonda and R. R. Mudholkar, “Cloud Market Cogitation and Techniques to
Averting SQL Injection for University Cloud,” International Journal of Computer
Technology and Applications, Vol. 3, No. 3, pp. 1217-1224, January, 2012.
23. A. S. Choudhary and M. L. Dhore, “CIDT: Detection of Malicious Code Injection
Attacks on Web Application,” International Journal of Computer Applications, Vol. 52,
No. 2, pp. 19-26, August 2012.
24. Web Application Attack Report For The Second Quarter of
2012.http://www.firehost.com/company/newsroom/web-application-attack-report-
second-quarter-2012
25. Visitors to Sony PlayStation Website at Risk of Malware Infection, July
2008.http://www.sophos.com/en-us/press-office/press-
releases/2008/07/playstation.aspx
26. N. Provos, M. A. Rajab, and P. Mavrommatis, “Cybercrime 2.0: When the Cloud
Turns Dark,” ACM Communications, Vol. 52, No. 4, pp. 42–47, 2009.
27. S. S. Rajan, Cloud Security Series | SQL Injection and SaaS, Cloud Computing
Journal, November 2010.
22. 28. Researchers Demo Cloud Security Issue With Amazon AWS Attack, October 2011.
http://www.pcworld.idg.com.au/article/405419/researchers_demo_cloud_security_issu
e_ amazon_aws_attack/
29. M. McIntosh and P. Austel, “XML Signature Element Wrapping Attacks and
Countermeasures,” 2005 workshop on Secure web services, ACM Press, New York,
NY, pp. 20–27, 2005.
30. N. Gruschka and L. L. Iacono, “Vulnerable Cloud: SOAP Message Security Validation
Revisited,” IEEE International Conference on Web Services, Los Angeles, 2009.
31. A. Tripathi and A. Mishra, “Cloud Computing Security Considerations Interface,” 2011
IEEE International Conference on Signal Processing, Communications and Computing,
Xi'an, China, September 2011.
32. H. C. Li, P. H. Liang, J. M. Yang, and S. J. Chen, “Analysis on Cloud-Based Security
Vulnerability Assessment,” IEEE International Conference on E-Business Engineering,
pp.490-494, November 2010.
33. Amazon: Hey Spammers, Get Off My
Cloud!http://voices.washingtonpost.com/securityfix/2008/07/amazon_hey_spammers_g
et_off_my.html
34. W. Jansen and T. Grance, “Guidelines on Security and Privacy in Public Cloud
Computing,” Computer Security Division, Information Technology Laboratory,
National Institute of Standards and Technology, Special Publication 800-144, December
2011.
35. Tackling the Insider Threat http://www.bankinfosecurity.com/blogs.php?postID=140
36. “Cloud Security Risks and Solutions,” White Paper, BalaBit IT Security, July 2010.
37. S. J. Stolfo, M. B. Salem, and A. D. Keromytis, “Fog computing: Mitigating Insider Data
Theft Attacks in the Cloud,” IEEE Symposium on Security and Privacy Workshops, pp.
125-128, San Francisco, CA, 2012.
38. M. Jensen, C. Meyer, J. Somorovsky, and J. Schwenk, “On the Effectiveness of XML
Schema Validation for Countering XML Signature Wrapping Attacks,” First
International Workshop on Securing Services on the Cloud, Milan, Italy, September
2011.
39. S. Gajek, M. Jensen, L. Liao, and J. Schwenk, “Analysis of Signature Wrapping Attacks and
Countermeasures,” IEEE International Conference on Web Services, pp. 575–582, Miami,
Florida, July 2009.
23. COST BREAKDOWN OF PUBLIC CLOUD COMPUTING AND PRIVATE
CLOUD COMPUTING AND SECURITY ISSUES
Swarnpreet Singh1
and Tarun Jangwal2
1
Assistant Professor, CT Institute of Engineering and Management Technology, Jalandhar
2
Assistant Professor, CT Institute of Engineering and Management Technology, Jalandhar.
ABSTRACT
The focus of this paper is to distinguish between the issues of private and public cloud computing and what
are the challenges faced during Building up your own private and public cloud. which computing out if above
two should be implemented in an organization.[12]
KEYWORDS
Public vs. Private cloud computing, Issues in private and public Cloud computing
For More Details : http://airccse.org/journal/jcsit/0412csit02.pdf
Volume Link : http://airccse.org/journal/ijcsit2012_curr.html
24. REFRENCES
[1] Michael Armbrust, Armando Fox, Rean Griffith, Anthony D. Joseph, Randy Katz, Andy Konwinski,
Gunho Lee, Dav id Patterson, Ariel Rabkin, Ion Stoica, and Matei Zaharia “Clearing the clouds away
from the true potential and obstacles posed by this computing capability” communications of the ac m
| april 2010 | vol. 53 | no. 4
[2] Michael Armbust et al., “Above the Cloud computing: A Berkeley View of Cloud Computing,
“technical report, University of California, Berkeley, EECS Department,Feb. 10, 2009,
http://www.eecs.berkeley.edu/Pubs/TechRpts/2009/EECS-2009-28.html .
[3] Eric Hand, “‘Cloud Computing’ Is Being Pitched as a New Nirvana for Scientists Drowning in Data.
But Can It Deliver?” Nature 449,no. 7165 (2007): 963; Geoffrey Fowler and Ben Worthen, “The
Internet Industry Is On a Cloud very soon—Whatever That May Mean,” Wall Street Journal, Mar.
26,2009, http://online.wsj.com/article/SB123802623665542725.html (accessed July 14, 2009);
Stephen Baker, “Google and the Wisdom of the Clouds,” Business Week (Dec. 14, 2007),
http://www.msnbc.msn.com/id/22261846/ .
[4] Gartner, “Gartner Says Worldwide IT Spending on Pace to Supass $3.4 Trillion in 2008,” press release,
Aug. 18,2008, ttp://www.gartner.com/it/page.jsp?id=742913 .
[5] Wyatt Kash, “USA.gov, Gobierno USA.gov move into the Internet cloud, “Government Computer
News, Feb. 23, 2009,http://gcn.com/articles/2009/02/23/gsa-sites-to-move-to-
thecloud.aspx?s=gcndaily_240209.
[6] Derek Gottfrid, “Self-Service, Prorated Super Computing Fun! “online posting, New York Times
Open, Nov. 1, 2007, http://open.blogs.nytimes.com/2007/11/01/self-service-prorated-
supercomputing-fun/?scp=1&sq=self%20service%20prorated&st=cse .
[7] OCLC Online Computing Library Center, “few years ago OCLC announces strategy to move library
management services to Web scale,” press release, Apr. 23,
2009,http://www.oclc.org/us/en/news/releases/200927.htm .
[8]. DuraSpace, “Fedora Commons and DSpace Foundation Join Together to Create DuraSpace
Organization,” press release, May 12, 2009, http://duraspace.org/documents/pressrelease.pdf .
[9] The European Network and Information Security Agency (ENISA), “Cloud Computing: Benefits,
Risks and Recommendations for Information
[10] NIST, January 2010. http://www.nist.gov/
[11] P. Mell and T. Grance, “Effectively and Securely: Using the cloud computing Paradigm,” NIST,
Information technology Laboratory, Boulder, December 2009.
[12] Michael Vizard, Public Versus Private Cloud Distinction Starts to Blur available on:
http://www.itbusinessedge.com/cm/blogs/vizard/public-versus-private-cloud-distinction-starts-
toblur/?cs=45246
[13] Tom bittman, The Spectrum of Private to Public Cloud Services : avialabe on:
http://blogs.gartner.com/thomas_bittman/2009/04/08/the-spectrum-of-private-to-public-cloudservices
[14] Ed Moyle ,Private cloud computing security issues
http://searchcloudsecurity.techtarget.com/tip/Private-cloud-computing-security-issues [15] Bill
Claybrook | Computerworld US | available on:
http://features.techworld.com/datacentre/3236805/private-cloud-builders-need-to-prepare-for-
25. problems
[16] Mike Klein,Three Benefits of Public Cloud Computing Available on on
http://resource.onlinetech.com/three-benefits-of-public-cloud-computing/
[17] Available on : http://blog.virtual.com/2011/private-vs-public-cloud-computing-solutions-
financialcomparison
[18] David Floyer , Private Cloud is more Cost Effective than Public Cloud for Organizations over $1B
Available on :
http://wikibon.org/wiki/v/Private_Cloud_is_more_Cost_Effective_than_Public_Cloud_for_Organiza
tions_over_$1B
[19] Swarnpreet singh , Ritu bagga, “Challenges among Public Cloud Computing “ SUS National
Conference on Advance Computer Trends. Page 23 issue 5 Decemeber 2011
[20] Stapel, Elizabeth. "Mean, Median, Mode, and Range." Purple math. Available on:
http://www.purplemath.com/modules/meanmode.htm
[21] “Private v/s Public Cloud – Which one is for me?” Friday, August 12, 2011. Available from:
http://www.tatvasoft.com/blog/2011/08/enterpise-application-public-private-cloud.html
[22] Peter Mell Timothy Grance "A NIST Definition of Cloud Computing". National Institute of Science
and Technology. NIST Special Publication 800-145 Retrieved 21 October 2011.
[23] Alan Stevens” When hybrid clouds are a mixed blessing”. Posted in Data Centre, 29th June 2011 10:00
GMTFree whitepaper – 2011 Lippis Report .Available from:
http://www.theregister.co.uk/2011/06/29/hybrid_cloud/
26. INCREASING THE TRANSISTOR COUNT BY CONSTRUCTING A TWO-LAYER
CRYSTAL SQUARE ON A SINGLE CHIP
Haissam El-Aawar Associate Professor, Computer Science/Information Technology
Departments Lebanese International University – LIU Bekaa-Lebanon
ABSTRACT
According to the Moore’s law, the number of transistor should be doubled every 18 to 24 months. The main
factors of increasing the number of transistor are: a density and a die size. Each of them has a serious physical
limitation; the first one “density” may be reached “Zero” after few years, which causes limitation in
performance and speed of a microprocessor, the second one “die size” cannot be increased every 2 years, it
must be fixed for several years, otherwise it will affect the economical side. This article aims to increase the
number of transistors, which increase the performance and the speed of the microprocessor without or with a
little bit increasing the die size, by constructing a two-layer crystal square for transistors, which allows
increasing the number of transistors two additional times. By applying the new approach the number of
transistors in a single chip will be approximately doubled every 24 months according to Moore’s Law without
changing rapidly the size of a chip (length and width), only the height of a chip must be changed for putting
the two layers.
KEYWORDS
Moore’s Law, Crystal square, Density, Die size, Number of transistors, Feature size, Design complexity.
For More Details : http://airccse.org/journal/jcsit/7315ijcsit08.pdf
Volume Link : http://airccse.org/journal/ijcsit2015_curr.html
27. REFERENCES
[1] John L.Hennessy and David A.Patterson, “Computer Architecture, A Quantitative Approach”, 5th ed.,
pp. 17-26, 2011.
[2] Gorden E.Moore, “cramming more Components onto Integrated Circuits”, Electronics, Vol. 38, No. 8,
April 19, 1965.
[3] Jane Laudon, Kenneth Laudon, “Essentials of Management Information Systems”, Chapter 4: IT
Infrastructure: Hardware and Software, 10th ed., 2012.
[4] Steve Gilheany, “Evolution of Intel Microprocessors: 1971 to 2007”.
[5] Wolfgang Arden, “Future roadblocks and solutions in silicon technology as outlined by the ITRS
roadmap” in Mterials Science in Semiconductor Processing, vol. 5 issue 4-5 August – October, 2002,
pp. 313-319.
[6] Jan M. Rabaey, “Design at the end of Silicon Roadmap”, Keynotes Address III, University of
California, Berkelev, IEEE, ASP-DAC 2005.
[7] Damon Poeter, “Intel’s Gelsinger Sees Clear Path to 10nm Chips”, June 30, 2008.
[8] Hasan S., Humaria, Asghar M., “Limitation of Silicon Based Computation abd Future Prospects” in
Proceedings of Second International Conference on Communication Software and Networks, 2010.
ICCSN’10, pp. 599-561.
[9] Robert W.Keyes, “Physical limits of silicon transistors and circuits”, September 2005.
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