The document summarizes the research of the Intelligent Systems Group at the Technical University of Madrid. The group conducts research in areas including big data and machine learning, multi-agent systems, social simulation, linked data and semantics, information retrieval, and web and service engineering. Key projects include using Bayesian models for telecommunications network diagnosis, developing personal assistant agents, and simulating behavior in social networks and smart spaces. The group develops tools in areas such as sentiment analysis, semantic search, and linked data visualization.
This document outlines the course structure and content for a Data Science course. The 5 modules cover: 1) introductions to data science concepts and statistical inference using R; 2) exploratory data analysis and machine learning algorithms; 3) feature generation/selection and additional machine learning algorithms; 4) recommendation systems and dimensionality reduction; 5) mining social network graphs and data visualization. The course aims to teach students to define data science fundamentals, demonstrate the data science process, explain necessary machine learning algorithms, illustrate data analysis techniques, and follow ethics in data visualization.
This document summarizes a presentation on natural computing. It begins by defining natural computing as a field that investigates computational systems and algorithms inspired by nature. It then discusses various types of natural computing, including evolutionary computing, neural computing, swarm computing, DNA computing, artificial immune systems, and artificial life. For each type, it provides an overview of the inspiration from nature, basic principles, and examples of applications. The document concludes by discussing the philosophy of natural computing as a multidisciplinary field.
IRJET- Vehicle Seat Vacancy Identification using Image Processing TechniqueIRJET Journal
This document summarizes a research paper that proposes a system to identify vehicle seat vacancy using image processing techniques. A webcam installed in a vehicle captures passenger images and sends them to a server via 3G communication. The server then uses face detection algorithms like Viola-Jones, HOG, and CNN to detect and count faces in the images. This allows the system to calculate the vehicle's seat occupancy. The system can also estimate passengers' gender. The proposed system achieves real-time face detection and could help public transportation companies provide better customer service by displaying seat availability information.
This document is an resume for Abhishek that includes his contact information, education history, coursework, skills, experience, projects, and achievements. It details that he received a Bachelor of Technology in Electronics and Communication Engineering from Indian Institute of Technology Guwahati with a CGPA of 6.62/10 and studied courses including pattern recognition, machine learning, computer vision, and embedded systems. For experience, he worked as an analyst at Axtria and did research at Hanyang University in South Korea on clustering techniques. His projects involved polyp detection in endoscopic video, facial recognition, and a 3 linkage robotic arm.
Face Recognition Smart Attendance System- A SurveyIRJET Journal
This document surveys 15 research papers on face recognition smart attendance systems. It summarizes each paper's methodology, including the databases and images used, feature extraction and matching algorithms like PCA, LDA, CNN, techniques for addressing issues like lighting and pose variations, and the accuracy and limitations of each system. Overall, the papers presented a variety of approaches to developing face recognition systems for automated student attendance, comparing methods like PCA, LDA, HOG, and deep learning algorithms and evaluating factors like recognition rate, robustness, and speed.
Call for Chapters- Edited Book: Real-World Applications of Quantum Computers ...Christo Ananth
It is no surprise that Quantum Computing will prove to be a big change for the world. The practical examples of quantum computing can prove to be a good substitute for traditional computing methods. Quantum computing can be applied to many concepts in today’s era when technology has grown by leaps and bounds. It has a wide beach of applications ranging from Cryptography, Climate Change and Weather Forecasting, Drug Development and Discovery, Financial Modeling, Artificial Intelligence, etc. Giant firms have already begun the process of quantum computing in the field of artificial intelligence. The search algorithms of today are mostly designed according to classical computing methods. While Comparing Quantum Computers with Data Mining with Other Counterpart Systems, we are able to understand its significance thereby applying new techniques to obtain new real-time results and solutions
IRJET - Face Recognition based Attendance System: ReviewIRJET Journal
This document provides a literature review of face recognition-based attendance systems. It summarizes several past studies that developed systems to automatically detect students' faces in images and use face recognition algorithms to mark attendance. The review finds that while many algorithms have been implemented, including Haar Cascade, Viola Jones, Eigenface, PCA, LDA, and LBPH, accurately verifying each student in a classroom remains challenging. The document analyzes the performance of previous systems and the issues that still exist, in order to provide suggestions for improving future work on automatic attendance tracking using face recognition.
The document summarizes the research of the Intelligent Systems Group at the Technical University of Madrid. The group conducts research in areas including big data and machine learning, multi-agent systems, social simulation, linked data and semantics, information retrieval, and web and service engineering. Key projects include using Bayesian models for telecommunications network diagnosis, developing personal assistant agents, and simulating behavior in social networks and smart spaces. The group develops tools in areas such as sentiment analysis, semantic search, and linked data visualization.
This document outlines the course structure and content for a Data Science course. The 5 modules cover: 1) introductions to data science concepts and statistical inference using R; 2) exploratory data analysis and machine learning algorithms; 3) feature generation/selection and additional machine learning algorithms; 4) recommendation systems and dimensionality reduction; 5) mining social network graphs and data visualization. The course aims to teach students to define data science fundamentals, demonstrate the data science process, explain necessary machine learning algorithms, illustrate data analysis techniques, and follow ethics in data visualization.
This document summarizes a presentation on natural computing. It begins by defining natural computing as a field that investigates computational systems and algorithms inspired by nature. It then discusses various types of natural computing, including evolutionary computing, neural computing, swarm computing, DNA computing, artificial immune systems, and artificial life. For each type, it provides an overview of the inspiration from nature, basic principles, and examples of applications. The document concludes by discussing the philosophy of natural computing as a multidisciplinary field.
IRJET- Vehicle Seat Vacancy Identification using Image Processing TechniqueIRJET Journal
This document summarizes a research paper that proposes a system to identify vehicle seat vacancy using image processing techniques. A webcam installed in a vehicle captures passenger images and sends them to a server via 3G communication. The server then uses face detection algorithms like Viola-Jones, HOG, and CNN to detect and count faces in the images. This allows the system to calculate the vehicle's seat occupancy. The system can also estimate passengers' gender. The proposed system achieves real-time face detection and could help public transportation companies provide better customer service by displaying seat availability information.
This document is an resume for Abhishek that includes his contact information, education history, coursework, skills, experience, projects, and achievements. It details that he received a Bachelor of Technology in Electronics and Communication Engineering from Indian Institute of Technology Guwahati with a CGPA of 6.62/10 and studied courses including pattern recognition, machine learning, computer vision, and embedded systems. For experience, he worked as an analyst at Axtria and did research at Hanyang University in South Korea on clustering techniques. His projects involved polyp detection in endoscopic video, facial recognition, and a 3 linkage robotic arm.
Face Recognition Smart Attendance System- A SurveyIRJET Journal
This document surveys 15 research papers on face recognition smart attendance systems. It summarizes each paper's methodology, including the databases and images used, feature extraction and matching algorithms like PCA, LDA, CNN, techniques for addressing issues like lighting and pose variations, and the accuracy and limitations of each system. Overall, the papers presented a variety of approaches to developing face recognition systems for automated student attendance, comparing methods like PCA, LDA, HOG, and deep learning algorithms and evaluating factors like recognition rate, robustness, and speed.
Call for Chapters- Edited Book: Real-World Applications of Quantum Computers ...Christo Ananth
It is no surprise that Quantum Computing will prove to be a big change for the world. The practical examples of quantum computing can prove to be a good substitute for traditional computing methods. Quantum computing can be applied to many concepts in today’s era when technology has grown by leaps and bounds. It has a wide beach of applications ranging from Cryptography, Climate Change and Weather Forecasting, Drug Development and Discovery, Financial Modeling, Artificial Intelligence, etc. Giant firms have already begun the process of quantum computing in the field of artificial intelligence. The search algorithms of today are mostly designed according to classical computing methods. While Comparing Quantum Computers with Data Mining with Other Counterpart Systems, we are able to understand its significance thereby applying new techniques to obtain new real-time results and solutions
IRJET - Face Recognition based Attendance System: ReviewIRJET Journal
This document provides a literature review of face recognition-based attendance systems. It summarizes several past studies that developed systems to automatically detect students' faces in images and use face recognition algorithms to mark attendance. The review finds that while many algorithms have been implemented, including Haar Cascade, Viola Jones, Eigenface, PCA, LDA, and LBPH, accurately verifying each student in a classroom remains challenging. The document analyzes the performance of previous systems and the issues that still exist, in order to provide suggestions for improving future work on automatic attendance tracking using face recognition.
Advance Clustering Technique Based on Markov Chain for Predicting Next User M...idescitation
According to the survey India is one of the
leading countries in the word for technical education and
management education. Numbers of students are increasing
day by day by the growth rate of 45% per annum. Advancement
in technology puts special effect on education system. This
helps in upgrading higher education. Some universities and
colleges are using these technologies. Weblog is one of them.
Main aim of this paper is to represent web logs using clustering
technique for predicting next user movement and user
behavior analysis. This paper moves around the web log
clustering technique based on Markov chain results .In this
paper we present an ideal approach to web clustering
(clustering web site users) and predicting their behavior for
next visit. Methodology: For generating effective result approx
14 engineering college web usage data is used and an advance
clustering approach is presenting after optimizing the other
clustering approach.Results: The user behavior is predicted
with the help of the advance clustering approach based on the
FPCM and k-mean. Proposed algorithm is used to mined and
predict user’s preferred paths. To predict the user behavior
existing approaches have been used. But the existing
approaches are not enough because of its reaction towards
noise. Thus with the help of ACM, noise is reduced, provides
more accurate result for predicting the user behavior. Approach
Implementation:The algorithm was implemented in MAT
LAB, DTRG and in Java .The experiment result proves that
this method is very effective in predicting user behavior. The
experimental results have validated the method’s effectiveness
in comparison with some previous studies.
Face Recognition Smart Attendance System: (InClass System)IRJET Journal
- The document describes a face recognition system called "InClass" to automate student attendance tracking. It aims to address issues with traditional manual attendance systems like being inaccurate, time-consuming, and difficult to maintain.
- The InClass system uses a CNN face detector to detect and identify students' faces from images captured with a camera. It can handle variations in lighting, angles, and occlusions. Matching faces to a database allows for automated attendance marking.
- The system aims to simplify the attendance process, reduce time and errors compared to existing biometric systems, and make attendance records easily accessible and storable digitally rather than on paper.
Responsible AI in Industry: Practical Challenges and Lessons LearnedKrishnaram Kenthapadi
How do we develop machine learning models and systems taking fairness, accuracy, explainability, and transparency into account? How do we protect the privacy of users when building large-scale AI based systems? Model fairness and explainability and protection of user privacy are considered prerequisites for building trust and adoption of AI systems in high stakes domains such as hiring, lending, and healthcare. We will first motivate the need for adopting a “fairness, explainability, and privacy by design” approach when developing AI/ML models and systems for different consumer and enterprise applications from the societal, regulatory, customer, end-user, and model developer perspectives. We will then focus on the application of responsible AI techniques in practice through industry case studies. We will discuss the sociotechnical dimensions and practical challenges, and conclude with the key takeaways and open challenges.
This PhD research proposal discusses using Bayesian inference methods for multi-target tracking in big data settings. The researcher proposes developing new stochastic MCMC algorithms that can scale to billions of data points by using small subsets of data in each iteration. This would make Bayesian methods computationally feasible for big data. The proposal outlines reviewing relevant literature, developing the theoretical foundations, and empirically validating new algorithms like sequential Monte Carlo on real-world problems to analyze text and user preferences at large scale.
Machine vision refers to technology that allows machines to perceive and interpret visual information like humans. It plays a crucial role in automating visual tasks to enhance efficiency and accuracy across industries. Key concepts include image processing, computer vision, and deep learning. The document outlines the objectives of addressing challenges that hinder adoption of machine vision through developing novel algorithms and frameworks. It reviews the historical development and applications of machine vision as well as theoretical frameworks and challenges such as algorithmic complexity and data and ethical issues.
IRJET- Intelligent Automated Attendance System based on Facial RecognitionIRJET Journal
This document presents a proposed intelligent automated attendance system based on facial recognition. The system aims to automate the attendance marking process in educational institutions to make it faster and less error-prone compared to manual methods. It works by using computer vision techniques like haar cascade classification for face detection and local binary pattern histograms for face recognition. The system architecture involves capturing images, detecting faces, recognizing students by matching faces to a training database, and marking the attendance automatically. Algorithms like haar cascade and local binary patterns are used for face detection and recognition. The proposed system aims to solve issues with existing manual and automated attendance systems like time consumption, errors, and lack of accuracy.
A Novel Feature Selection with Annealing For Computer Vision And Big Data Lea...theijes
Numerous PC vision and medical imaging issues a confronted with gaining from expansive scale datasets, with a huge number of perceptions furthermore, highlights.A novel productive learning plan that fixes a sparsity imperative by continuously expelling variables taking into account a measure and a timetable. The alluring actuality that the issue size continues dropping all through the cycles makes it especially reasonable for enormous information learning. Methodology applies nonexclusively to the advancement of any differentiable misfortune capacity, and discovers applications in relapse, order and positioning. The resultant calculations assemble variable screening into estimation and are amazingly easy to execute. It gives hypothetical assurances of joining and determination consistency. Investigates genuine and engineered information demonstrate that the proposed strategy contrasts exceptionally well and other cutting edge strategies in relapse, order and positioning while being computationally exceptionally effective and adaptable.
Utilization of Machine Learning in Computer VisionIRJET Journal
The document discusses the utilization of machine learning in computer vision. It begins by defining machine learning and computer vision, noting they aim to bring human data sensing and understanding capabilities to computers. It then discusses several applications of machine learning in computer vision, such as object detection in images using algorithms like convolutional neural networks. Finally, it concludes that machine learning and computer vision have reduced costs and improved technologies in many fields like healthcare, transportation and more, with emerging areas including life sciences and human activity analysis.
IRJET- Hand Gesture Recognition and Voice Conversion for Deaf and DumbIRJET Journal
This document describes a research project that aims to help deaf and dumb people communicate more easily. It presents a system using hand gesture recognition and voice conversion. The system uses a webcam to detect hand gestures, then converts the gestures to text via image processing and matching to a database of gestures and texts. It also aims to convert the text to voice so deaf people can understand via voice. It reviews previous related work on sign language recognition systems and discusses the proposed system's image processing and matching techniques, including feature extraction using principal component analysis and classification using k-nearest neighbors. The goal is to help reduce communication barriers for deaf and dumb people.
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.
The document discusses hard computing and soft computing. Hard computing uses precise mathematical models and algorithms, while soft computing uses techniques like neural networks and genetic algorithms to handle imprecise or complex problems. Soft computing is needed to solve real-world problems that involve uncertainty, incomplete information, noise, and non-linearity. It can provide approximate solutions and mimic human-like reasoning. The document then provides examples of applications of soft computing in various domains like image processing, automotive systems, bioinformatics, and power systems analysis.
The document outlines a research project evaluating service oriented architecture in e-learning. It discusses goals of surveying e-learning, studying enterprise architectures and requirements, and proposing a service-based learning management system and university management system. The agenda covers topics like e-learning, service oriented architecture, the proposed service architecture, evaluation, and conclusion.
Detection of Malicious Web Links Using Machine Learning Algorithm: A ReviewIRJET Journal
The document provides a review of machine learning techniques used to detect malicious web links. It discusses traditional detection methods like blacklisting and signatures then focuses on machine learning approaches. Common algorithms discussed are decision trees, random forests, SVM, and Naive Bayes. The review compares techniques, datasets, and evaluation metrics. It highlights challenges like data imbalance and lack of generalization. Potential future areas discussed are deep learning, ensemble methods, and explainable machine learning to improve performance in detecting malicious web links.
Yifan Guo is a PhD student at Case Western Reserve University studying machine learning and big data. He received his B.S. from Beijing University of Posts and Telecommunications and his Master's from Northwestern University. His research projects include developing an image recognition system for identifying pill types, building a movie recommendation system using matrix factorization, and designing an algorithm for a nonlinear integer programming transportation problem.
IRJET- Spot Me - A Smart Attendance System based on Face RecognitionIRJET Journal
The article discusses international issues. It mentions that globalization has increased economic interdependence between nations while also raising tensions over immigration and trade. Solutions will require cooperation and compromise and a recognition that isolationism is not a viable strategy in an interconnected world.
Susmit Mohan Joshi is seeking an internship or full-time position as a software engineer. He has a MS in Computer Engineering from RIT with a GPA of 3.33/4 and a bachelor's degree from the University of Mumbai with a GES GPA of 3.8/4. His skills include C++, Java, Matlab, OpenCV, and experience with projects involving facial expression recognition, emotion intensity recognition, and object recognition using techniques like PCA, SVM, and HOG.
This document summarizes a research study that aims to improve planning and operations for paratransit systems using machine learning models. Paratransit currently accounts for 65% of passenger trips but lacks timetables, demand predictions, and other organization. The study will apply machine learning techniques like neural networks to origin-destination data to estimate passenger and trip inferences without automatic fare collection. This could help balance supply and demand for operators and support transportation decision making. The models will be evaluated based on metrics like root mean squared error and their performance in estimating origin-destination values. The overall goal is to develop a framework that can quantify vehicle and passenger behavior to help synchronize intelligent transportation projects.
This document provides an overview of machine learning, including definitions, types, steps, and applications. It defines machine learning as a field that gives computers the ability to learn without being explicitly programmed. The document outlines the main types of machine learning as supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. It also describes the typical steps in a machine learning process as gathering data, preparing data, choosing a model, training, evaluation, and prediction. Examples of machine learning applications discussed include prediction, image recognition, natural language processing, and personal assistants. Popular machine learning languages and packages are also listed.
Innovations in technology has revolutionized financial services to an extent that large financial institutions like Goldman Sachs are claiming to be technology companies! It is no secret that technological innovations like Data science and AI are changing fundamentally how financial products are created, tested and delivered. While it is exciting to learn about technologies themselves, there is very little guidance available to companies and financial professionals should retool and gear themselves towards the upcoming revolution.
In this master class, we will discuss key innovations in Data Science and AI and connect applications of these novel fields in forecasting and optimization. Through case studies and examples, we will demonstrate why now is the time you should invest to learn about the topics that will reshape the financial services industry of the future!
AI in Finance
A survey on Machine Learning and Artificial Neural NetworksIRJET Journal
This research paper provides an overview of machine learning and artificial neural networks. It discusses various machine learning techniques like supervised learning, unsupervised learning, reinforcement learning, and deep learning. It also describes artificial neural networks and how they are used to mimic biological neural networks. The paper reviews several related works applying machine learning and neural networks to tasks like hydrological modeling, facial expression recognition, and cattle detection. It highlights advantages like improved accuracy and automation, as well as limitations like data and computational requirements. Overall, the paper aims to improve knowledge of machine learning and neural networks techniques and their applications.
Call for Papers - Journal of Electrical Systems (JES), E-ISSN: 1112-5209, ind...Christo Ananth
At the forefront of technological innovation and scholarly discourse, the Journal of Electrical Systems (JES) is a peer-reviewed publication dedicated to advancing the understanding and application of electrical systems, communication systems and information science. With a commitment to excellence, we provide a platform for researchers, academics, and professionals to contribute to the ever-evolving field of electrical engineering, communication technology and Information Systems.
The mission of JES is to foster the exchange of knowledge and ideas in electrical and communication systems, promoting cutting-edge research and facilitating discussions that drive progress in the field. We aim to be a beacon for those seeking to explore, challenge, and revolutionize the way we harness, distribute, and utilize electrical energy and information systems..
Call for Papers - Utilitas Mathematica, E-ISSN: 0315-3681, indexed in ScopusChristo Ananth
Utilitas Mathematica Journal is a broad scope journal that publishes original research and review articles on all aspects of both pure and applied mathematics. This journal is the official publication of the Utilitas Mathematica Academy, Canada. It enjoys good reputation and popularity at international level in terms of research papers and distribution worldwide. Offers selected original research in Pure and Applied Mathematics and Statistics. UMJ coverage extends to Operations Research, Mathematical Economics, Mathematics Biology and Computer Science. Published in association with the Utilitas Mathematica Academy. The leadership of the Utilitas Mathematica Journal commits to strengthening our professional community by making it more just, equitable, diverse, and inclusive. We affirm that our mission, Promote the Practice and Profession of Statistics, can be realized only by fully embracing justice, equity, diversity, and inclusivity in all of our operations. Individuals embody many traits, so the leadership will work with the members of UMJ to create and sustain responsive, flourishing, and safe environments that support individual needs, stimulate intellectual growth, and promote professional advancement for all
More Related Content
Similar to Edited Book on “Stochastic Processes and Their Applications in Artificial Intelligence”
Advance Clustering Technique Based on Markov Chain for Predicting Next User M...idescitation
According to the survey India is one of the
leading countries in the word for technical education and
management education. Numbers of students are increasing
day by day by the growth rate of 45% per annum. Advancement
in technology puts special effect on education system. This
helps in upgrading higher education. Some universities and
colleges are using these technologies. Weblog is one of them.
Main aim of this paper is to represent web logs using clustering
technique for predicting next user movement and user
behavior analysis. This paper moves around the web log
clustering technique based on Markov chain results .In this
paper we present an ideal approach to web clustering
(clustering web site users) and predicting their behavior for
next visit. Methodology: For generating effective result approx
14 engineering college web usage data is used and an advance
clustering approach is presenting after optimizing the other
clustering approach.Results: The user behavior is predicted
with the help of the advance clustering approach based on the
FPCM and k-mean. Proposed algorithm is used to mined and
predict user’s preferred paths. To predict the user behavior
existing approaches have been used. But the existing
approaches are not enough because of its reaction towards
noise. Thus with the help of ACM, noise is reduced, provides
more accurate result for predicting the user behavior. Approach
Implementation:The algorithm was implemented in MAT
LAB, DTRG and in Java .The experiment result proves that
this method is very effective in predicting user behavior. The
experimental results have validated the method’s effectiveness
in comparison with some previous studies.
Face Recognition Smart Attendance System: (InClass System)IRJET Journal
- The document describes a face recognition system called "InClass" to automate student attendance tracking. It aims to address issues with traditional manual attendance systems like being inaccurate, time-consuming, and difficult to maintain.
- The InClass system uses a CNN face detector to detect and identify students' faces from images captured with a camera. It can handle variations in lighting, angles, and occlusions. Matching faces to a database allows for automated attendance marking.
- The system aims to simplify the attendance process, reduce time and errors compared to existing biometric systems, and make attendance records easily accessible and storable digitally rather than on paper.
Responsible AI in Industry: Practical Challenges and Lessons LearnedKrishnaram Kenthapadi
How do we develop machine learning models and systems taking fairness, accuracy, explainability, and transparency into account? How do we protect the privacy of users when building large-scale AI based systems? Model fairness and explainability and protection of user privacy are considered prerequisites for building trust and adoption of AI systems in high stakes domains such as hiring, lending, and healthcare. We will first motivate the need for adopting a “fairness, explainability, and privacy by design” approach when developing AI/ML models and systems for different consumer and enterprise applications from the societal, regulatory, customer, end-user, and model developer perspectives. We will then focus on the application of responsible AI techniques in practice through industry case studies. We will discuss the sociotechnical dimensions and practical challenges, and conclude with the key takeaways and open challenges.
This PhD research proposal discusses using Bayesian inference methods for multi-target tracking in big data settings. The researcher proposes developing new stochastic MCMC algorithms that can scale to billions of data points by using small subsets of data in each iteration. This would make Bayesian methods computationally feasible for big data. The proposal outlines reviewing relevant literature, developing the theoretical foundations, and empirically validating new algorithms like sequential Monte Carlo on real-world problems to analyze text and user preferences at large scale.
Machine vision refers to technology that allows machines to perceive and interpret visual information like humans. It plays a crucial role in automating visual tasks to enhance efficiency and accuracy across industries. Key concepts include image processing, computer vision, and deep learning. The document outlines the objectives of addressing challenges that hinder adoption of machine vision through developing novel algorithms and frameworks. It reviews the historical development and applications of machine vision as well as theoretical frameworks and challenges such as algorithmic complexity and data and ethical issues.
IRJET- Intelligent Automated Attendance System based on Facial RecognitionIRJET Journal
This document presents a proposed intelligent automated attendance system based on facial recognition. The system aims to automate the attendance marking process in educational institutions to make it faster and less error-prone compared to manual methods. It works by using computer vision techniques like haar cascade classification for face detection and local binary pattern histograms for face recognition. The system architecture involves capturing images, detecting faces, recognizing students by matching faces to a training database, and marking the attendance automatically. Algorithms like haar cascade and local binary patterns are used for face detection and recognition. The proposed system aims to solve issues with existing manual and automated attendance systems like time consumption, errors, and lack of accuracy.
A Novel Feature Selection with Annealing For Computer Vision And Big Data Lea...theijes
Numerous PC vision and medical imaging issues a confronted with gaining from expansive scale datasets, with a huge number of perceptions furthermore, highlights.A novel productive learning plan that fixes a sparsity imperative by continuously expelling variables taking into account a measure and a timetable. The alluring actuality that the issue size continues dropping all through the cycles makes it especially reasonable for enormous information learning. Methodology applies nonexclusively to the advancement of any differentiable misfortune capacity, and discovers applications in relapse, order and positioning. The resultant calculations assemble variable screening into estimation and are amazingly easy to execute. It gives hypothetical assurances of joining and determination consistency. Investigates genuine and engineered information demonstrate that the proposed strategy contrasts exceptionally well and other cutting edge strategies in relapse, order and positioning while being computationally exceptionally effective and adaptable.
Utilization of Machine Learning in Computer VisionIRJET Journal
The document discusses the utilization of machine learning in computer vision. It begins by defining machine learning and computer vision, noting they aim to bring human data sensing and understanding capabilities to computers. It then discusses several applications of machine learning in computer vision, such as object detection in images using algorithms like convolutional neural networks. Finally, it concludes that machine learning and computer vision have reduced costs and improved technologies in many fields like healthcare, transportation and more, with emerging areas including life sciences and human activity analysis.
IRJET- Hand Gesture Recognition and Voice Conversion for Deaf and DumbIRJET Journal
This document describes a research project that aims to help deaf and dumb people communicate more easily. It presents a system using hand gesture recognition and voice conversion. The system uses a webcam to detect hand gestures, then converts the gestures to text via image processing and matching to a database of gestures and texts. It also aims to convert the text to voice so deaf people can understand via voice. It reviews previous related work on sign language recognition systems and discusses the proposed system's image processing and matching techniques, including feature extraction using principal component analysis and classification using k-nearest neighbors. The goal is to help reduce communication barriers for deaf and dumb people.
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.
The document discusses hard computing and soft computing. Hard computing uses precise mathematical models and algorithms, while soft computing uses techniques like neural networks and genetic algorithms to handle imprecise or complex problems. Soft computing is needed to solve real-world problems that involve uncertainty, incomplete information, noise, and non-linearity. It can provide approximate solutions and mimic human-like reasoning. The document then provides examples of applications of soft computing in various domains like image processing, automotive systems, bioinformatics, and power systems analysis.
The document outlines a research project evaluating service oriented architecture in e-learning. It discusses goals of surveying e-learning, studying enterprise architectures and requirements, and proposing a service-based learning management system and university management system. The agenda covers topics like e-learning, service oriented architecture, the proposed service architecture, evaluation, and conclusion.
Detection of Malicious Web Links Using Machine Learning Algorithm: A ReviewIRJET Journal
The document provides a review of machine learning techniques used to detect malicious web links. It discusses traditional detection methods like blacklisting and signatures then focuses on machine learning approaches. Common algorithms discussed are decision trees, random forests, SVM, and Naive Bayes. The review compares techniques, datasets, and evaluation metrics. It highlights challenges like data imbalance and lack of generalization. Potential future areas discussed are deep learning, ensemble methods, and explainable machine learning to improve performance in detecting malicious web links.
Yifan Guo is a PhD student at Case Western Reserve University studying machine learning and big data. He received his B.S. from Beijing University of Posts and Telecommunications and his Master's from Northwestern University. His research projects include developing an image recognition system for identifying pill types, building a movie recommendation system using matrix factorization, and designing an algorithm for a nonlinear integer programming transportation problem.
IRJET- Spot Me - A Smart Attendance System based on Face RecognitionIRJET Journal
The article discusses international issues. It mentions that globalization has increased economic interdependence between nations while also raising tensions over immigration and trade. Solutions will require cooperation and compromise and a recognition that isolationism is not a viable strategy in an interconnected world.
Susmit Mohan Joshi is seeking an internship or full-time position as a software engineer. He has a MS in Computer Engineering from RIT with a GPA of 3.33/4 and a bachelor's degree from the University of Mumbai with a GES GPA of 3.8/4. His skills include C++, Java, Matlab, OpenCV, and experience with projects involving facial expression recognition, emotion intensity recognition, and object recognition using techniques like PCA, SVM, and HOG.
This document summarizes a research study that aims to improve planning and operations for paratransit systems using machine learning models. Paratransit currently accounts for 65% of passenger trips but lacks timetables, demand predictions, and other organization. The study will apply machine learning techniques like neural networks to origin-destination data to estimate passenger and trip inferences without automatic fare collection. This could help balance supply and demand for operators and support transportation decision making. The models will be evaluated based on metrics like root mean squared error and their performance in estimating origin-destination values. The overall goal is to develop a framework that can quantify vehicle and passenger behavior to help synchronize intelligent transportation projects.
This document provides an overview of machine learning, including definitions, types, steps, and applications. It defines machine learning as a field that gives computers the ability to learn without being explicitly programmed. The document outlines the main types of machine learning as supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. It also describes the typical steps in a machine learning process as gathering data, preparing data, choosing a model, training, evaluation, and prediction. Examples of machine learning applications discussed include prediction, image recognition, natural language processing, and personal assistants. Popular machine learning languages and packages are also listed.
Innovations in technology has revolutionized financial services to an extent that large financial institutions like Goldman Sachs are claiming to be technology companies! It is no secret that technological innovations like Data science and AI are changing fundamentally how financial products are created, tested and delivered. While it is exciting to learn about technologies themselves, there is very little guidance available to companies and financial professionals should retool and gear themselves towards the upcoming revolution.
In this master class, we will discuss key innovations in Data Science and AI and connect applications of these novel fields in forecasting and optimization. Through case studies and examples, we will demonstrate why now is the time you should invest to learn about the topics that will reshape the financial services industry of the future!
AI in Finance
A survey on Machine Learning and Artificial Neural NetworksIRJET Journal
This research paper provides an overview of machine learning and artificial neural networks. It discusses various machine learning techniques like supervised learning, unsupervised learning, reinforcement learning, and deep learning. It also describes artificial neural networks and how they are used to mimic biological neural networks. The paper reviews several related works applying machine learning and neural networks to tasks like hydrological modeling, facial expression recognition, and cattle detection. It highlights advantages like improved accuracy and automation, as well as limitations like data and computational requirements. Overall, the paper aims to improve knowledge of machine learning and neural networks techniques and their applications.
Similar to Edited Book on “Stochastic Processes and Their Applications in Artificial Intelligence” (20)
Call for Papers - Journal of Electrical Systems (JES), E-ISSN: 1112-5209, ind...Christo Ananth
At the forefront of technological innovation and scholarly discourse, the Journal of Electrical Systems (JES) is a peer-reviewed publication dedicated to advancing the understanding and application of electrical systems, communication systems and information science. With a commitment to excellence, we provide a platform for researchers, academics, and professionals to contribute to the ever-evolving field of electrical engineering, communication technology and Information Systems.
The mission of JES is to foster the exchange of knowledge and ideas in electrical and communication systems, promoting cutting-edge research and facilitating discussions that drive progress in the field. We aim to be a beacon for those seeking to explore, challenge, and revolutionize the way we harness, distribute, and utilize electrical energy and information systems..
Call for Papers - Utilitas Mathematica, E-ISSN: 0315-3681, indexed in ScopusChristo Ananth
Utilitas Mathematica Journal is a broad scope journal that publishes original research and review articles on all aspects of both pure and applied mathematics. This journal is the official publication of the Utilitas Mathematica Academy, Canada. It enjoys good reputation and popularity at international level in terms of research papers and distribution worldwide. Offers selected original research in Pure and Applied Mathematics and Statistics. UMJ coverage extends to Operations Research, Mathematical Economics, Mathematics Biology and Computer Science. Published in association with the Utilitas Mathematica Academy. The leadership of the Utilitas Mathematica Journal commits to strengthening our professional community by making it more just, equitable, diverse, and inclusive. We affirm that our mission, Promote the Practice and Profession of Statistics, can be realized only by fully embracing justice, equity, diversity, and inclusivity in all of our operations. Individuals embody many traits, so the leadership will work with the members of UMJ to create and sustain responsive, flourishing, and safe environments that support individual needs, stimulate intellectual growth, and promote professional advancement for all
Call for Chapters- Edited Book: Quantum Networks and Their Applications in AI...Christo Ananth
The research on Quantum Networked Artificial Intelligence is at the intersection of Quantum Information Science (QIS), Artificial Intelligence, Soft Computing, Computational Intelligence, Machine Learning, Deep Learning, Optimization, Etc. It Touches On Many Important Parts Of Near-Term Quantum Computing And Noisy Intermediate-Scale Quantum (NISQ) Devices. The research on quantum artificial intelligence is grounded in theories, modelling, and significant studies on hybrid classical-quantum algorithms using classical simulations, IBM Q services, PennyLane, Google Cirq, D-Wave quantum annealer etc. So far, the research on quantum artificial intelligence has given us the building blocks to achieve quantum advantage to solve problems in combinatorial optimization, soft computing, deep learning, and machine learning much faster than traditional classical computing. Solving these problems is important for making quantum computing useful for noise-resistant large-scale applications. This makes it much easier to see the big picture and helps with cutting-edge research across the quantum stack, making it an important part of any QIS effort. Researchers — almost daily — are making advances in the engineering and scientific challenges to create practical quantum networks powered with artificial intelligence
Call for Chapters- Edited Book: Real World Challenges in Quantum Electronics ...Christo Ananth
Most experts would consider this the biggest challenge. Quantum computers are extremely sensitive to noise and errors caused by interactions with their environment. This can cause errors to accumulate and degrade the quality of computation. Developing reliable error correction techniques is therefore essential for building practical quantum computers. While quantum computers have shown impressive performance for some tasks, they are still relatively small compared to classical computers. Scaling up quantum computers to hundreds or thousands of qubits while maintaining high levels of coherence and low error rates remains a major challenge. Developing high-quality quantum hardware, such as qubits and control electronics, is a major challenge. There are many different qubit technologies, each with its own strengths and weaknesses, and developing a scalable, fault-tolerant qubit technology is a major focus of research. Funding agencies, such as government agencies, are rising to the occasion to invest in tackling these quantum computing challenges. Researchers — almost daily — are making advances in the engineering and scientific challenges to create practical quantum computers
Call for Papers- Thematic Issue: Food, Drug and Energy Production, PERIÓDICO ...Christo Ananth
Published since 2004, Periódico Tchê Química (PQT) is a is a triannual (published every four months), international, fully peer-reviewed, and open-access Journal that welcomes high-quality theoretically informed publications in the multi and interdisciplinary fields of Chemistry, Biology, Physics, Mathematics, Pharmacy, Medicine, Engineering, Agriculture and Education in Science.
Researchers from all countries are invited to publish on its pages. The Journal is committed to achieving a broad international appeal, attracting contributions, and addressing issues from a range of disciplines. The Periódico Tchê Química is a double-blind peer-review journal dedicated to express views on the covered topics, thereby generating a cross current of ideas on emerging matters
Call for Papers - PROCEEDINGS ON ENGINEERING SCIENCES, P-ISSN-2620-2832, E-IS...Christo Ananth
Proceedings on Engineering Sciences examines new research and development at the engineering. It provides a common forum for both front line engineering as well as pioneering academic research. The journal's multidisciplinary approach draws from such fields as Automation, Automotive engineering, Business, Chemical engineering, Civil engineering, Control and system engineering, Electrical and electronic engineering, Electronics, Environmental engineering, Industrial and manufacturing engineering, Industrial management, Information and communication technology, Management and Accounting, Management and quality studies, Management Science and Operations Research, Materials engineering, Mechanical engineering, Mechanics of Materials, Mining and energy, Safety, Risk, Reliability, and Quality, Software engineering, Surveying and transport, Architecture and urban engineering.
Call for Papers - Onkologia i Radioterapia, P-ISSN-1896-8961, E-ISSN 2449-916...Christo Ananth
Onkologia I Radioterapia is an international peer reviewed journal which publishes on both clinical and pre-clinical research related to cancer. Journal also provide latest information in field of oncology and radiotherapy to both clinical practitioner as well as basic researchers. Submission for publication can be submitted through online submission, Editorial manager system, or through email as attachment to journal office. For any issue, journal office can be contacted through email or phone for instatnt resolution of issue. Onkologia I Radioterapia is a peer-reviewed scopus indexed medical journal publishing original scientific (experimental, clinical, laboratory), review and case studies (case report) in the field of oncology and radiotherapy. In addition, publishes letters to the Editorial Board, reports on scientific conferences, book reviews, as well as announcements about planned congresses and scientific congresses. Oncology and Radiotherapy appear four times a year. All articles published with www.itmedical.pl and www.medicalproject.com.pl is now available on our new website
Call for Papers - Journal of Indian School of Political Economy, E-ISSN 0971-...Christo Ananth
The journal is published every quarter and contains 200 pages in each issue. It is devoted to the study of Indian economy, polity and society. Research papers, review articles, book reviews are published in the journal. All research papers published in the journal are subject to an intensive refereeing process. Each issue of the journal also includes a section on documentation, which reproduces extensive excerpts of relevant reports of committees, working groups, task forces, etc., which may not be readily accessible, official documents compiled from scattered electronic and/or other sources and statistical supplement for ready reference of the readers. It is now in its nineteenth year of publication. So far, five special issues have been brought out, namely: (i) The Scheduled Castes: An Inter-Regional Perspective, (ii) Political Parties and Elections in Indian States : 1990-2003, (iii) Child Labour, (iv) World Trade Organisation Agreements, and (v) Basel-II and Indian Banks
Call for Papers - Journal of Ecohumanism (JoE), ISSN (Print): 2752-6798, ISSN...Christo Ananth
Journal of Ecohumanism is an Open Access international peer-reviewed journal for scholars, researchers, and students who are interested in the fields of Environmental Humanities, Ecohumanism, Ecology, Literary Theory and Cultural Criticism, Economic and Business Studies, Law and Legal Studies in a broad interdisciplinary field of Social Sciences and Humanities. Journal of Ecohumanism is an Open Access peer reviewed journal, allowing users to freely access, download, copy, distribute, print, search, or link to full-text articles for any lawful purpose without requiring permission from the publisher or author. JoE follows a strict double, blind review policy for all the submissions which is embedded in our general publication ethics and supported by rigorous academic scrutiny of papers published. Materials published in the journal do not necessarily represent the views of its editorial board and reviewers
Call for Papers- Journal of Wireless Mobile Networks, Ubiquitous Computing, a...Christo Ananth
JoWUA is an online peer-reviewed journal and aims to provide an international forum for researchers, professionals, and industrial practitioners on all topics related to wireless mobile networks, ubiquitous computing, and their dependable applications. JoWUA consists of high-quality technical manuscripts on advances in the state-of-the-art of wireless mobile networks, ubiquitous computing, and their dependable applications; both theoretical approaches and practical approaches are encouraged to submit. All published articles in JoWUA are freely accessible in this website because it is an open access journal. JoWUA has four issues (March, June, September, December) per year with special issues covering specific research areas by guest editors. The editorial board of JoWUA makes an effort for the increase in the quality of accepted articles compared to other competing journals
Call for Papers - International Journal of Intelligent Systems and Applicatio...Christo Ananth
International Journal of Intelligent Systems and Applications in Engineering (IJISAE) is an international and interdisciplinary journal for both invited and contributed peer reviewed articles that intelligent systems and applications in engineering at all levels. The journal publishes a broad range of papers covering theory and practice in order to facilitate future efforts of individuals and groups involved in the field. IJISAE, a peer-reviewed double-blind refereed journal, publishes original papers featuring innovative and practical technologies related to the design and development of intelligent systems in engineering. Its coverage also includes papers on intelligent systems applications in areas such as nanotechnology, renewable energy, medicine engineering, Aeronautics and Astronautics, mechatronics, industrial manufacturing, bioengineering, agriculture, services, intelligence based automation and appliances, medical robots and robotic rehabilitations, space exploration and etc.
Call for Papers- Special Issue: Recent Trends, Innovations and Sustainable So...Christo Ananth
Energy Systems Modelling is growing in relevance on providing insights and strategies to plan a carbon-neutral future. The implementation of an effective energy transition plan faces multiple challenges, spanning from the integration of the operations of different energy carriers and sectors to the consideration of multiple spatial and temporal resolutions. Demand-side management has to be applied to multi-carrier energy system models lacks; prosumers is explored only in a limited manner; In General, multi-scale modelling frameworks should be established and considered both in the dimensions of time, space, technology and energy carrier; long term energy system models tend to address uncertainty scarcely; there is a lack of studies modelling uncertainties related to emerging technologies and; modelling of energy consumer behaviour is one of the major aspect of future research. The increased pressure in decarbonizing the energy system has renewed the interest in energy system modelling, with several reviews trying to convey a comprehensive description of the utilized methodologies as well as providing new insights on how they can be used to answer new questions
Call for Papers - Educational Administration: Theory and Practice, E-ISSN: 21...Christo Ananth
The Educational Administration: Theory and Practice publishes prominent empirical and conceptual articles focused on timely and critical leadership and policy issues of educational organizations. The journal embraces traditional and emergent research paradigms, methods, and issues. The journal particularly promotes the publication of rigorous and relevant scholarly work that enhances linkages among and utility for educational policy, practice, and research arenas.
The goal of the editorial team and the journal’s editorial board is to promote sound scholarship and a clear and continuing dialogue among scholars and practitioners from a broad spectrum of education. Educational Administration: Theory and Practice presents prominent empirical and conceptual articles focused on timely and critical leadership and policy issues facing educational organizations. As an editorial team, we embrace traditional and emergent theoretical frameworks, research methods, and topics. We particularly promote the publication of rigorous and relevant scholarly work with utility for educational policy, practice, and research.
The journal’s primary focus is on studies of educational leadership, organizations, leadership development, and policy as they relate to elementary and secondary levels of education. Examinations of leadership and policy that fall outside K-12 are considered insofar as there are meaningful connections to the K-12 arena (e.g., college pipeline). International comparative investigations are welcome to the extent they have implications for a broad audience.s.
Bharatiya Shiksha Shodh Patrika is a half yearly refereed UGC care listed journal of Social Sciences Journal of Education. It is a bilingual (Hindi and English) Journal being published regularly since 1982 by Bharatiya Shiksha Shodh Sansthan, Saraswatikunj, Nirala Nagar, Lucknow, Uttar Pradesh, India. Bharatiya Shiksha Shodh Sansthan is an apex Research Institute of Vidya Bharti. The objective of this Journal is to provide an academic forum for Teachers, Teacher Educators, Research Scholars, Policy Makers. Administrators, other Research Workers to encourage original and critical thinking in the field of Education and allied disciplines through presentation of novel ideas, critical appraisal of contemporary educational problems and views and experiences on improved educational practices. However, articles from other disciplines related to contemporary educational issues of relevance may be accepted for publication subject to the approval of the Review Committee.
Call for Papers - African Journal of Biological Sciences, E-ISSN: 2663-2187, ...Christo Ananth
African Journal of Biological Sciences is an International peer-reviewed, Open Access journal that publishes original research articles as well as review articles in all areas of Biological Sciences. It operates a fully open access publishing model which allows open global access to its published content. This model is supported through Article Processing Charges. For more information on Article Processing charges click here. Its scope embraces Animal Sciences, Biochemistry, Bioinformatics, Biotechnology, Botany, Cell Biology, Developmental Biology, Ecology, Environmental Sciences, Ethno Medicine, Food Science, Freshwater Biology, Genetics, Immunology, Marine Biology, Microbiology, Molecular Biology, Physiology, Plant Sciences, Structural Biology,Toxicology,Zoology etc.
It is essential that authors prepare their manuscripts according to established specifications. Failure to follow them may result in papers being delayed or rejected. Therefore, contributors are strongly encouraged to read the author guidelines carefully before preparing a manuscript for submission. The manuscripts should be checked carefully for grammatical, punctuation errors. All papers are subjected to peer review. All articles published in this journal represent the opinion of the authors and not reflect the official policy of the Journal of African Journal of Biological Sciences
Wind Energy Harvesting: Technological Advances and Environmental ImpactsChristo Ananth
Christo Ananth, Rajini K R Karduri, "Wind Energy Harvesting: Technological Advances
and Environmental Impacts", International Journal of Advanced Research in Basic Engineering Sciences and Technology (IJARBEST), Volume 6,Issue 2,February 2020,pp:77-84
Hydrogen Economy: Opportunities and Challenges for a Sustainable FutureChristo Ananth
Christo Ananth, Rajini K R Karduri, "Hydrogen Economy: Opportunities and Challenges
for a Sustainable Future", International Journal of Advanced Research in Basic Engineering Sciences and Technology (IJARBEST), Volume 6,Issue 2,February 2020,pp:69-76
The Economics of Transitioning to Renewable Energy SourcesChristo Ananth
Christo Ananth, Rajini K R Karduri, "The Economics of Transitioning to Renewable Energy Sources", International Journal of Advanced Research in Basic Engineering Sciences and Technology (IJARBEST), Volume 6,Issue 2,February 2020,pp:61-68
Lifecycle Assessment of Solar PV Systems: From Manufacturing to RecyclingChristo Ananth
Christo Ananth, Rajini K R Karduri, "Lifecycle Assessment of Solar PV Systems: From
Manufacturing to Recycling", International Journal of Advanced Research in Basic Engineering Sciences and Technology (IJARBEST), Volume 6,Issue 2,February 2020,pp:51-60
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
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.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
Software Engineering and Project Management - Introduction, Modeling Concepts...Prakhyath Rai
Introduction, Modeling Concepts and Class Modeling: What is Object orientation? What is OO development? OO Themes; Evidence for usefulness of OO development; OO modeling history. Modeling
as Design technique: Modeling, abstraction, The Three models. Class Modeling: Object and Class Concept, Link and associations concepts, Generalization and Inheritance, A sample class model, Navigation of class models, and UML diagrams
Building the Analysis Models: Requirement Analysis, Analysis Model Approaches, Data modeling Concepts, Object Oriented Analysis, Scenario-Based Modeling, Flow-Oriented Modeling, class Based Modeling, Creating a Behavioral Model.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
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.
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024
Edited Book on “Stochastic Processes and Their Applications in Artificial Intelligence”
1. Dr. Christo Ananth
Samarkand State
Uzbekistan
List of topics (but not limited to):
1. Auto Regressive Techniques, Processes and its Artificial Intelligence Solutions
2. Brownian motion processes and its Machine Learning
3. Correlation AI related Models and Stochastic Processes in Control Theory
4. Differential Equations, Computer vision and Artificial Intelligence
5. Discrete Time-Dynamics, Stochastic Processes and Artificial Intelligence
6. Dynamic Bayesian Networks and its Modelling in Artificial Intelligence
7. Gaussian Modelling with Expected Maximization and its Role in Artificial Intelligence
8. Information Processing, Learning and Artificial Intelligence
9. Markov Chain Monte Carlo Methods and its Relevance to Artificial Intelligence
10. Markov decision processes and its Artificial Intelligence
11. Pattern Recognition, Imaging Models and Artificial Intelligence
12. Poisson processes and its Artificial Intelligence
13. Principal Component Analysis, Solutions and Artificial Intelligence Tools
14. Random Walk Processes and its Machine Learning
15. Reinforcement Learning Methods and Artificial Intelligence Models
16. State Space Models & Equa
17. Subspace Methods, Trajectories and its Artificial Intelligence Solutions
18. Supervised Learning Approaches and its Artificial Intelligence Involved
19. Transfer Functions, Stability Problems and its Artificial Intelli
20. Unsupervised Models and Artificial Intelligence Solutions
NB: There are no submission or acceptance fees
accepted based on a double blind peer review editorial process
Abstracting and Indexing:
to indices including
Call for Book Chapters
Stochastic Processes and Their
Applications in Artificial Intelligence
Submission of chapter(s)
via this e-mail only:
line: Submission to
Christo Ananth
Samarkand State University
Uzbekistan
List of topics (but not limited to):
Techniques, Processes and its Artificial Intelligence Solutions
Brownian motion processes and its Machine Learning
Correlation AI related Models and Stochastic Processes in Control Theory
Differential Equations, Computer vision and Artificial Intelligence
Dynamics, Stochastic Processes and Artificial Intelligence
Dynamic Bayesian Networks and its Modelling in Artificial Intelligence
Gaussian Modelling with Expected Maximization and its Role in Artificial Intelligence
Processing, Learning and Artificial Intelligence
Markov Chain Monte Carlo Methods and its Relevance to Artificial Intelligence
Markov decision processes and its Artificial Intelligence
Pattern Recognition, Imaging Models and Artificial Intelligence
processes and its Artificial Intelligence
Principal Component Analysis, Solutions and Artificial Intelligence Tools
Random Walk Processes and its Machine Learning
Reinforcement Learning Methods and Artificial Intelligence Models
State Space Models & Equations and its Application in Machine Learning
Subspace Methods, Trajectories and its Artificial Intelligence Solutions
Supervised Learning Approaches and its Artificial Intelligence Involved
Transfer Functions, Stability Problems and its Artificial Intelli
Unsupervised Models and Artificial Intelligence Solutions
no submission or acceptance fees
accepted based on a double blind peer review editorial process
and Indexing: So long as they meet the required criteria, all IGI Global publications are submitted for indexing
to indices including Web of Science, Scopus, Inspec, PsycINFO, Ei Compendex
September 28, 2022:
October 12, 2022:
December 11, 2022:
January 24, 2023:
Marc
Mar
Publication of Chap
Call for Book Chapters
Stochastic Processes and Their
Applications in Artificial Intelligence
Submission of chapter(s) along with TURNITIN
mail only: dr.christoananth@gmail.com
line: Submission to SPAAI
Dr. Anbazhagan N
Alagappa University, Karaikudi
India
Techniques, Processes and its Artificial Intelligence Solutions
Brownian motion processes and its Machine Learning
Correlation AI related Models and Stochastic Processes in Control Theory
Differential Equations, Computer vision and Artificial Intelligence Models
Dynamics, Stochastic Processes and Artificial Intelligence
Dynamic Bayesian Networks and its Modelling in Artificial Intelligence
Gaussian Modelling with Expected Maximization and its Role in Artificial Intelligence
Processing, Learning and Artificial Intelligence
Markov Chain Monte Carlo Methods and its Relevance to Artificial Intelligence
Markov decision processes and its Artificial Intelligence
Pattern Recognition, Imaging Models and Artificial Intelligence
Principal Component Analysis, Solutions and Artificial Intelligence Tools
Random Walk Processes and its Machine Learning
Reinforcement Learning Methods and Artificial Intelligence Models
tions and its Application in Machine Learning
Subspace Methods, Trajectories and its Artificial Intelligence Solutions
Supervised Learning Approaches and its Artificial Intelligence Involved
Transfer Functions, Stability Problems and its Artificial Intelligence
Unsupervised Models and Artificial Intelligence Solutions
no submission or acceptance fees for chapters submitted to this book for publication. All chapters are
accepted based on a double blind peer review editorial process
So long as they meet the required criteria, all IGI Global publications are submitted for indexing
Web of Science, Scopus, Inspec, PsycINFO, Ei Compendex
Important Dates
September 28, 2022: Proposal Submission
October 12, 2022: Notification of Acceptance
December 11, 2022: Full Chapter Submission
January 24, 2023: Review Results Returned
rch 7, 2023: Final Accept
arch 21, 2023: Final Chap
hapters shall happen after
igi-global.com
Editors
Call for Book Chapters
Stochastic Processes and Their
Applications in Artificial Intelligence
TURNITIN Report (less than 15
dr.christoananth@gmail.com with a subject
SPAAI – IGI Global
Anbazhagan N
Alagappa University, Karaikudi - 630003
National University of Singapore
Gaussian Modelling with Expected Maximization and its Role in Artificial Intelligence
for chapters submitted to this book for publication. All chapters are
So long as they meet the required criteria, all IGI Global publications are submitted for indexing
Web of Science, Scopus, Inspec, PsycINFO, Ei Compendex, and more.
Important Dates
Proposal Submission Deadline
Notification of Acceptance
Full Chapter Submission
Review Results Returned
eptance Notification
hapter Submission
er Final Chapter Submissio
global.com
• Chapter Length:
Maximum
• Desired Figures and Illustrations:
10
• Please include Proper Affiliation
Details and academic email ID for all
authors of the Chapter
Applications in Artificial Intelligence
less than 15%)
with a subject
Dr. Mark Goh
National University of Singapore
Singapore
for chapters submitted to this book for publication. All chapters are
So long as they meet the required criteria, all IGI Global publications are submitted for indexing
ssionView publication stats
Chapter Length:
Maximum 25 Pages
Desired Figures and Illustrations:
Please include Proper Affiliation
Details and academic email ID for all
authors of the Chapter
National University of Singapore
So long as they meet the required criteria, all IGI Global publications are submitted for indexing
Desired Figures and Illustrations:
Please include Proper Affiliation
Details and academic email ID for all