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.
This document discusses techniques for detecting phishing websites. It proposes using web crawling and YARA rules to analyze website URLs and content to classify websites as phishing or non-phishing. Specifically, it involves capturing the URL, analyzing features like domain length and global rank to generate a score, then using a web crawler and YARA rules to analyze website text and detect if the content is irrelevant or malicious. The goal is to develop an extension that can act as middleware between users and malicious websites to reduce users' risk of exposure while allowing safe browsing.
1) The document describes a smart feedback analysis system that collects feedback about a college from social media websites using web crawling techniques.
2) It analyzes the collected feedback using sentiment analysis and categorizes it as positive or negative. Negative feedback can help the college improve and positive feedback helps with popularity and recruitment.
3) The system first crawls websites to collect feedback data, stores it in a database, and then performs sentiment analysis using naive Bayes classification to categorize the feedback.
IRJET - An Automated System for Detection of Social Engineering Phishing Atta...IRJET Journal
1) The document presents a machine learning approach to detect phishing URLs using logistic regression. It trains a logistic regression model on a dataset of 420,467 URLs that have been classified as either phishing or legitimate.
2) It preprocesses the URLs using tokenization before training the logistic regression model. The trained model is able to classify new URLs with 96% accuracy as either phishing or legitimate based on the URL features.
3) The proposed approach provides an automated way to detect phishing URLs in real-time and help prevent phishing attacks. Future work could involve developing a browser extension using this approach and increasing the dataset size for higher accuracy.
An effective search on web log from most popular downloaded contentijdpsjournal
A Web page recommender system effectively predicts the best related web page to search. While search
ing
a word from search engine it may display some unnecessary links and unrelated data’s to user so to a
void
this problem, the con
ceptual prediction model combines both the web usage and domain knowledge. The
proposed conceptual prediction model automatically generates a semantic network of the semantic Web
usage knowledge, which is the integration of domain knowledge and web usage i
nformation. Web usage
mining aims to discover interesting and frequent user access patterns from web browsing data. The
discovered knowledge can then be used for many practical web applications such as web
recommendations, adaptive web sites, and personali
zed web search and surfing
Detecting Malicious Bots in Social Media Accounts Using Machine Learning Tech...IRJET Journal
The document describes a proposed system to detect malicious bots on Twitter using machine learning techniques. It involves collecting Twitter data, extracting features, and using classification algorithms like random forest and decision tree. The random forest model combines the predictions of multiple decision trees trained on different feature subsets to improve accuracy. Features like account age, tweet frequency, and sentiment are used. The system is evaluated using cross-validation, performance metrics from a confusion matrix like accuracy, and comparisons to other algorithms. The goal is to improve security on social media by identifying bot accounts.
An Extensible Web Mining Framework for Real KnowledgeIJEACS
With the emergence of Web 2.0 applications that bestow rich user experience and convenience without time and geographical restrictions, web usage logs became a goldmine to researchers across the globe. User behavior analysis in different domains based on web logs has its utility for enterprises to have strategic decision making. Business growth of enterprises depends on customer-centric approaches that need to know the knowledge of customer behavior to succeed. The rationale behind this is that customers have alternatives and there is intense competition. Therefore business community needs business intelligence to have expert decisions besides focusing customer relationship management. Many researchers contributed towards this end. However, the need for a comprehensive framework that caters to the needs of businesses to ascertain real needs of web users. This paper presents a framework named eXtensible Web Usage Mining Framework (XWUMF) for discovering actionable knowledge from web log data. The framework employs a hybrid approach that exploits fuzzy clustering methods and methods for user behavior analysis. Moreover the framework is extensible as it can accommodate new algorithms for fuzzy clustering and user behavior analysis. We proposed an algorithm known as Sequential Web Usage Miner (SWUM) for efficient mining of web usage patterns from different data sets. We built a prototype application to validate our framework. Our empirical results revealed that the framework helps in discovering actionable knowledge.
IRJET- A Literature Review and Classification of Semantic Web Approaches for ...IRJET Journal
This document discusses using semantic web approaches for web personalization. It begins with an abstract that outlines how web personalization can help address the problem of information overload by recommending and filtering web pages according to a user's interests. The document then reviews related work on using ontologies and semantic web technologies for personalized e-learning, recommender systems, and other applications. It categorizes different semantic web approaches that have been used for web personalization, including their pros and cons. The overall purpose is to survey semantic web techniques for personalization and how they have been applied in previous research.
An Efficient Hybrid Successive Markov Model for Predicting Web User Usage Beh...Waqas Tariq
With the continued growth and proliferation of Web services and Web based information systems, the volumes of user data have reached astronomical proportions. Analyzing such data using Web Usage Mining can help to determine the visiting interests or needs of the web user. As web log is incremental in nature, it becomes a crucial issue to predict exactly the ways how users browse websites. It is necessary for web miners to use predictive mining techniques to filter the unwanted categories for reducing the operational scope. The first-order Markov model has low accuracy in achieving right predictions, which is why extensions to higher order models are necessary. All higher order Markov model holds the promise of achieving higher prediction accuracies, improved coverage than any single-order Markov model but holds high state space complexity. Hence a Hybrid Markov Model is required to improve the operation performance and prediction accuracy significantly. The present paper introduces An Efficient Hybrid Successive Markov Prediction Model, HSMP. The HSMP model is initially predicts the possible wanted categories using Relevance factor, which can be used to infer the users’ browsing behavior between web categories. Then predict the pages in predicted categories using techniques for intelligently combining different order Markov models so that the resulting model has low state complexity, improved prediction accuracy and retains the coverage of the all higher order Markov model. These techniques eliminates low support states, evaluates the probability distribution and estimates the error associated with each state without affecting the overall accuracy as well as protection of the resulting model. To validate the proposed prediction model, several experiments were conducted and results proven this are claimed in this paper.
This document discusses techniques for detecting phishing websites. It proposes using web crawling and YARA rules to analyze website URLs and content to classify websites as phishing or non-phishing. Specifically, it involves capturing the URL, analyzing features like domain length and global rank to generate a score, then using a web crawler and YARA rules to analyze website text and detect if the content is irrelevant or malicious. The goal is to develop an extension that can act as middleware between users and malicious websites to reduce users' risk of exposure while allowing safe browsing.
1) The document describes a smart feedback analysis system that collects feedback about a college from social media websites using web crawling techniques.
2) It analyzes the collected feedback using sentiment analysis and categorizes it as positive or negative. Negative feedback can help the college improve and positive feedback helps with popularity and recruitment.
3) The system first crawls websites to collect feedback data, stores it in a database, and then performs sentiment analysis using naive Bayes classification to categorize the feedback.
IRJET - An Automated System for Detection of Social Engineering Phishing Atta...IRJET Journal
1) The document presents a machine learning approach to detect phishing URLs using logistic regression. It trains a logistic regression model on a dataset of 420,467 URLs that have been classified as either phishing or legitimate.
2) It preprocesses the URLs using tokenization before training the logistic regression model. The trained model is able to classify new URLs with 96% accuracy as either phishing or legitimate based on the URL features.
3) The proposed approach provides an automated way to detect phishing URLs in real-time and help prevent phishing attacks. Future work could involve developing a browser extension using this approach and increasing the dataset size for higher accuracy.
An effective search on web log from most popular downloaded contentijdpsjournal
A Web page recommender system effectively predicts the best related web page to search. While search
ing
a word from search engine it may display some unnecessary links and unrelated data’s to user so to a
void
this problem, the con
ceptual prediction model combines both the web usage and domain knowledge. The
proposed conceptual prediction model automatically generates a semantic network of the semantic Web
usage knowledge, which is the integration of domain knowledge and web usage i
nformation. Web usage
mining aims to discover interesting and frequent user access patterns from web browsing data. The
discovered knowledge can then be used for many practical web applications such as web
recommendations, adaptive web sites, and personali
zed web search and surfing
Detecting Malicious Bots in Social Media Accounts Using Machine Learning Tech...IRJET Journal
The document describes a proposed system to detect malicious bots on Twitter using machine learning techniques. It involves collecting Twitter data, extracting features, and using classification algorithms like random forest and decision tree. The random forest model combines the predictions of multiple decision trees trained on different feature subsets to improve accuracy. Features like account age, tweet frequency, and sentiment are used. The system is evaluated using cross-validation, performance metrics from a confusion matrix like accuracy, and comparisons to other algorithms. The goal is to improve security on social media by identifying bot accounts.
An Extensible Web Mining Framework for Real KnowledgeIJEACS
With the emergence of Web 2.0 applications that bestow rich user experience and convenience without time and geographical restrictions, web usage logs became a goldmine to researchers across the globe. User behavior analysis in different domains based on web logs has its utility for enterprises to have strategic decision making. Business growth of enterprises depends on customer-centric approaches that need to know the knowledge of customer behavior to succeed. The rationale behind this is that customers have alternatives and there is intense competition. Therefore business community needs business intelligence to have expert decisions besides focusing customer relationship management. Many researchers contributed towards this end. However, the need for a comprehensive framework that caters to the needs of businesses to ascertain real needs of web users. This paper presents a framework named eXtensible Web Usage Mining Framework (XWUMF) for discovering actionable knowledge from web log data. The framework employs a hybrid approach that exploits fuzzy clustering methods and methods for user behavior analysis. Moreover the framework is extensible as it can accommodate new algorithms for fuzzy clustering and user behavior analysis. We proposed an algorithm known as Sequential Web Usage Miner (SWUM) for efficient mining of web usage patterns from different data sets. We built a prototype application to validate our framework. Our empirical results revealed that the framework helps in discovering actionable knowledge.
IRJET- A Literature Review and Classification of Semantic Web Approaches for ...IRJET Journal
This document discusses using semantic web approaches for web personalization. It begins with an abstract that outlines how web personalization can help address the problem of information overload by recommending and filtering web pages according to a user's interests. The document then reviews related work on using ontologies and semantic web technologies for personalized e-learning, recommender systems, and other applications. It categorizes different semantic web approaches that have been used for web personalization, including their pros and cons. The overall purpose is to survey semantic web techniques for personalization and how they have been applied in previous research.
An Efficient Hybrid Successive Markov Model for Predicting Web User Usage Beh...Waqas Tariq
With the continued growth and proliferation of Web services and Web based information systems, the volumes of user data have reached astronomical proportions. Analyzing such data using Web Usage Mining can help to determine the visiting interests or needs of the web user. As web log is incremental in nature, it becomes a crucial issue to predict exactly the ways how users browse websites. It is necessary for web miners to use predictive mining techniques to filter the unwanted categories for reducing the operational scope. The first-order Markov model has low accuracy in achieving right predictions, which is why extensions to higher order models are necessary. All higher order Markov model holds the promise of achieving higher prediction accuracies, improved coverage than any single-order Markov model but holds high state space complexity. Hence a Hybrid Markov Model is required to improve the operation performance and prediction accuracy significantly. The present paper introduces An Efficient Hybrid Successive Markov Prediction Model, HSMP. The HSMP model is initially predicts the possible wanted categories using Relevance factor, which can be used to infer the users’ browsing behavior between web categories. Then predict the pages in predicted categories using techniques for intelligently combining different order Markov models so that the resulting model has low state complexity, improved prediction accuracy and retains the coverage of the all higher order Markov model. These techniques eliminates low support states, evaluates the probability distribution and estimates the error associated with each state without affecting the overall accuracy as well as protection of the resulting model. To validate the proposed prediction model, several experiments were conducted and results proven this are claimed in this paper.
IRJET- Monitoring Suspicious Discussions on Online Forums using Data MiningIRJET Journal
1) The document discusses monitoring suspicious discussions on online forums using data mining techniques. It aims to reduce suspicious activity, notify administrators of malicious users, and identify and convert negative words.
2) It proposes collecting data from forums, analyzing it using naive Bayes classification in Python to identify positive and negative sentiment, and replacing negative words with asterisks while notifying the administrator.
3) The method architecturally involves users logging into a forum, discussions being monitored for suspicious words, and administrators getting notified if detected along with users getting warned. It concludes the objectives of monitoring forums are satisfied.
This document describes a plagiarism checker system that uses the Levenshtein algorithm to detect plagiarism in text documents. The system allows users to import paragraphs to check for plagiarism against a database of stored paragraphs. It analyzes the imported text and ranks how similar it is to texts in the database using the Levenshtein algorithm, which measures the minimum number of single-character edits needed to change one word into another. The system aims to efficiently detect plagiarism in medium to large volumes of student work with less human effort than other plagiarism checkers.
Product Comparison Website using Web scraping and Machine learning.IRJET Journal
This document describes the development of a product comparison website using web scraping and machine learning techniques. The website extracts data like price, features and ratings from multiple e-commerce websites using web scraping. A machine learning algorithm then compares the collected data and provides personalized recommendations to users. The implementation demonstrated that web scraping is effective for collecting product data for comparison. Future work may involve incorporating deep learning models and external data sources to improve recommendations.
A Survey on Recommendation System based on Knowledge Graph and Machine LearningIRJET Journal
This document provides an overview of recommendation systems based on knowledge graphs and machine learning. It first defines key concepts like recommendation systems, knowledge graphs, meta paths, and knowledge graph embedding. It then discusses standard recommendation approaches like content-based filtering, collaborative filtering, and hybrid filtering. The document focuses on knowledge graph-based recommendation systems, how they address issues with traditional approaches, and how machine learning can be used alongside knowledge graphs. It reviews several papers on using knowledge graphs for recommendations and proposes a comparative study. The document also outlines a proposed recommendation system and potential future research directions in the domain.
IRJET- A Survey on Link Prediction TechniquesIRJET Journal
This document summarizes several techniques for link prediction in networks. It discusses neighborhood-based methods proposed by Lada A. Adamic and Eytan Adar that use similarity scores to predict friendships. It also describes a resource allocation method by Tao Zhou, Linyuan Lu and Yi-Cheng Zhang for missing link prediction that works well on networks with high average degree. Additionally, it outlines an overlapping community detection method called BIGCLAM proposed by Jaewon Yang and Jure Leskovec for massive networks, and status index by Leo Katz to identify popularity. The document concludes that link prediction enhances user experience and social network popularity by addressing the challenges of network size and sparsity.
1) The document presents a system for detecting malicious links using machine learning techniques. It aims to improve the effectiveness of classifiers for identifying dangerous websites.
2) The system utilizes logistic regression as a supervised machine learning algorithm to categorize URLs based on their linguistic properties and behaviors. New attributes are extracted from URLs to train the classifier.
3) The proposed approach aims to identify malicious URLs based solely on their structure and properties, without relying on webpage content. This could lead to significant resource savings and a safer browsing experience for users.
WEB ATTACK PREDICTION USING STEPWISE CONDITIONAL PARAMETER TUNING IN MACHINE ...IJCNCJournal
There is a rapid growth in internet and website usage. A wide variety of devices are used to access
websites, such as mobile phones, tablets, laptops, and personal computers. Attackers are finding more and
more vulnerabilities on websites that they can exploit for malicious purposes. A web application attack
occurs when cyber criminals gain access to unauthorized areas. Typically, attackers look for
vulnerabilities in web applications at the application layer. SQL injection attacks and Cross Site script
attacks is used to access web applications to obtain sensitive data. A key objective of this work is to
develop new features and investigate how automatic tuning of machine learning techniques can improve
the performance of Web Attack detections that use HTTP CSIC datasets to block and detect attacks. The
Stepwise Conditional parameter tuning in machine learning algorithms is a proposed model. This model is
a dynamic and automated parameter choosing and tuning based on the better outcome. This work also
compares two datasets for performance of the proposed model.
Web Attack Prediction using Stepwise Conditional Parameter Tuning in Machine ...IJCNCJournal
There is a rapid growth in internet and website usage. A wide variety of devices are used to access websites, such as mobile phones, tablets, laptops, and personal computers. Attackers are finding more and more vulnerabilities on websites that they can exploit for malicious purposes. A web application attack occurs when cyber criminals gain access to unauthorized areas. Typically, attackers look for vulnerabilities in web applications at the application layer. SQL injection attacks and Cross Site script attacks is used to access web applications to obtain sensitive data. A key objective of this work is to develop new features and investigate how automatic tuning of machine learning techniques can improve the performance of Web Attack detections that use HTTP CSIC datasets to block and detect attacks. The Stepwise Conditional parameter tuning in machine learning algorithms is a proposed model. This model is a dynamic and automated parameter choosing and tuning based on the better outcome. This work also compares two datasets for performance of the proposed model.
A Review on Pattern Discovery Techniques of Web Usage MiningIJERA Editor
In the recent years with the development of Internet technology the growth of World Wide Web exceeded all expectations. A lot of information is available in different formats and retrieving interesting content has become a very difficult task. One possible approach to solve this problem is Web Usage Mining (WUM), the important application of Web Mining. Extracting the hidden knowledge in the log files of a web server, recognizing various interests of web users, discovering customer behavior while at the site are normally referred as the applications of web usage mining. In this paper we provide an updated focused survey on techniques of web usage mining.
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.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Recommendation generation by integrating sequential pattern mining and semanticseSAT Journals
Abstract As the Internet usage keeps increasing, the number of web sites and hence the number of web pages also keeps increasing. A recommendation system can be used to provide personalized web service by suggesting the pages that are likely to be accessed in future. Most of the recommendation systems are based on association rule mining or based on keywords. Using the association rule mining the prediction rate is less as it doesn’t take into account the order of access of the web pages by the users. The recommendation systems that are key-word based provides lesser relevant results. This paper proposes a recommendation system that uses the advantages of sequential pattern mining and semantics over the association rule mining and keyword based systems respectively. Keywords: Sequential Pattern Mining, Taxonomy, Apriori-All, CS-Mine, Semantic, Clustering
Concept drift and machine learning model for detecting fraudulent transaction...IJECEIAES
The document presents a machine learning model for detecting fraudulent transactions in a streaming environment that addresses concept drift. The proposed approach uses the extreme gradient boosting (XGBoost) algorithm and employs four algorithms to continuously detect concept drift in data streams. The approach is evaluated on credit card and Twitter fraud datasets and is shown to outperform traditional machine learning models in terms accuracy, precision, and recall, and is more robust to concept drift. The proposed approach can be utilized as a real-time fraud detection system across different industries.
Semantically Enriched Knowledge Extraction With Data MiningEditor IJCATR
This document discusses using data mining techniques to extract knowledge from data and representing that knowledge in both human-understandable and machine-understandable formats. It uses an input dataset, applies data mining methods like regression using WEKA and SAS, extracts natural language triples about the results, and generates RDF triples to represent the knowledge in a machine-readable format.
IRJET- Noisy Content Detection on Web Data using Machine LearningIRJET Journal
The document presents a study on detecting noisy content on web data using machine learning techniques. It aims to identify and filter out advertisements, irrelevant data and other noisy content when users retrieve information from websites. The study uses algorithms like support vector machines, artificial neural networks, decision trees and k-nearest neighbors to classify web content as noisy or not. A proposed methodology involves training models using these machine learning algorithms and evaluating their performance for noisy content detection on web data.
Semantic Web concepts used in Web 3.0 applicationsIRJET Journal
This document discusses how semantic web concepts can be used in applications for Web 3.0. It provides examples of how semantic web could be applied in areas like medical sciences, search engines, and e-learning. Specifically, it describes how semantic web could help integrate medical data from different sources, enable more accurate medical diagnosis and treatment recommendations based on patient history. It also discusses how a semantic search engine like Swoogle works by tagging web pages with metadata to better understand context and return more relevant search results. Finally, it touches on how a semantic web architecture could enable more sophisticated e-learning systems by linking educational resources.
A Proposed Model for a Web-Based Academic Advising SystemEswar Publications
Student advising is an important and time-consuming effort in academic life. Academic advising has been implemented in order to fill the gap between student and the academic routine, by moving advising, complaining, evaluating, suggesting system from the traditional ways to an automated way. The researcher surveyed the existing literature; as utilized that many institutions have implemented computerized solutions in order to enhance their overall advising experience. In this paper the researcher innovates an automated mechanism for
academic advising in the university system. The paper presents an overview of the development and implementation of a new model of e-Academic Advising System as a web-based application. The proposed model attempts to develop a model that the staff and advisor can access to follow-up the student complaints and suggestions. Also, the students who registered can through complain, evaluate & suggest in any subject. Finally, the head of the department can receive a KPIs reports to follow-up his department. Therefore, a need for a
system that could detect student’s problems and provide them with suitable feedback is raised. The aim of this paper is to implement a system which facilitates and assists academic advisors in their efforts to providing quality, accurate and consistent advising services to their students; also, to explore the design and implementation of a computerized tool to facilitate this process. This paper discussed the required methodologies used in the development of the Academic Advising System, it has been shown that Academic Advising is a Process more than a Final Product or system, a technical vision for Academic Advising System has been provided. The e-Academic Advising web-based developed and implemented by "Ruby on Rails" as a Web framework which runs via the
Ruby programming language and "PostgreSQL" as a Database Engine.
Certain Issues in Web Page Prediction, Classification and Clustering in Data ...IJAEMSJORNAL
Nowadays, data mining which is a part of web mining plays a vital role in various applications such as search engines, health care centers for extracting the individual patient details among huge database, analyzing disease based on basic criteria, education system for analyzing their performance level with other system, social networking, E-Commerce and knowledge management etc., which extract the information based on the user query. The issues are time taken to mine the target content or webpage from the search engines, space complexity and predicting the frequent webpage for the next user based on users’ behaviour.
A Brief Survey on Recommendation System for a Gradient Classifier based Inade...Christo Ananth
Recommender systems are a common and successful feature of modern internet services. (RS). A service that connects users to tasks is known as a recommendation system. Making it simpler for customers and project providers to identify and receive projects and other solutions achieves this. A recommendation system is a strong device that may be advantageous to a business or organisation. This study explores whether recommender systems may be utilised to solve cold-start and data-sparsely issues with recommender systems, as well as delays and business productivity. Recommender systems make it easier and more convenient for people to get information. Over the years, several different methods have been created. We employ a potent predictive regression method known as the slope classifier algorithm, which minimises a loss function by repeatedly choosing a function that points in the direction of the weak hypothesis or the negative gradient. A group that is experiencing trouble handling cold beginnings and data sparsity will send enormous datasets to the suggested systems team. The users have to finish their job by the deadline in order to overcome these challenges.
IRJET - Online Assignment Plagiarism Checking using Data Mining and NLPIRJET Journal
This document presents a proposed system for detecting plagiarism in student assignments submitted online. The system would use data mining algorithms and natural language processing to compare submitted assignments against each other and identify plagiarized content. It would analyze assignments at both the syntactic and semantic levels. The proposed system is intended to more efficiently and accurately detect plagiarism compared to teachers manually reviewing all submissions. The document describes the workflow of the system, including preprocessing of assignments, text analysis, similarity measurement, and algorithms that would be used like Rabin-Karp, KMP and SCAM.
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...IRJET Journal
1) The document discusses the Sungal Tunnel project in Jammu and Kashmir, India, which is being constructed using the New Austrian Tunneling Method (NATM).
2) NATM involves continuous monitoring during construction to adapt to changing ground conditions, and makes extensive use of shotcrete for temporary tunnel support.
3) The methodology section outlines the systematic geotechnical design process for tunnels according to Austrian guidelines, and describes the various steps of NATM tunnel construction including initial and secondary tunnel support.
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTUREIRJET Journal
This study examines the effect of response reduction factors (R factors) on reinforced concrete (RC) framed structures through nonlinear dynamic analysis. Three RC frame models with varying heights (4, 8, and 12 stories) were analyzed in ETABS software under different R factors ranging from 1 to 5. The results showed that displacement increased as the R factor decreased, indicating less linear behavior for lower R factors. Drift also decreased proportionally with increasing R factors from 1 to 5. Shear forces in the frames decreased with higher R factors. In general, R factors of 3 to 5 produced more satisfactory performance with less displacement and drift. The displacement variations between different building heights were consistent at different R factors. This study evaluated how R factors influence
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IRJET- Monitoring Suspicious Discussions on Online Forums using Data MiningIRJET Journal
1) The document discusses monitoring suspicious discussions on online forums using data mining techniques. It aims to reduce suspicious activity, notify administrators of malicious users, and identify and convert negative words.
2) It proposes collecting data from forums, analyzing it using naive Bayes classification in Python to identify positive and negative sentiment, and replacing negative words with asterisks while notifying the administrator.
3) The method architecturally involves users logging into a forum, discussions being monitored for suspicious words, and administrators getting notified if detected along with users getting warned. It concludes the objectives of monitoring forums are satisfied.
This document describes a plagiarism checker system that uses the Levenshtein algorithm to detect plagiarism in text documents. The system allows users to import paragraphs to check for plagiarism against a database of stored paragraphs. It analyzes the imported text and ranks how similar it is to texts in the database using the Levenshtein algorithm, which measures the minimum number of single-character edits needed to change one word into another. The system aims to efficiently detect plagiarism in medium to large volumes of student work with less human effort than other plagiarism checkers.
Product Comparison Website using Web scraping and Machine learning.IRJET Journal
This document describes the development of a product comparison website using web scraping and machine learning techniques. The website extracts data like price, features and ratings from multiple e-commerce websites using web scraping. A machine learning algorithm then compares the collected data and provides personalized recommendations to users. The implementation demonstrated that web scraping is effective for collecting product data for comparison. Future work may involve incorporating deep learning models and external data sources to improve recommendations.
A Survey on Recommendation System based on Knowledge Graph and Machine LearningIRJET Journal
This document provides an overview of recommendation systems based on knowledge graphs and machine learning. It first defines key concepts like recommendation systems, knowledge graphs, meta paths, and knowledge graph embedding. It then discusses standard recommendation approaches like content-based filtering, collaborative filtering, and hybrid filtering. The document focuses on knowledge graph-based recommendation systems, how they address issues with traditional approaches, and how machine learning can be used alongside knowledge graphs. It reviews several papers on using knowledge graphs for recommendations and proposes a comparative study. The document also outlines a proposed recommendation system and potential future research directions in the domain.
IRJET- A Survey on Link Prediction TechniquesIRJET Journal
This document summarizes several techniques for link prediction in networks. It discusses neighborhood-based methods proposed by Lada A. Adamic and Eytan Adar that use similarity scores to predict friendships. It also describes a resource allocation method by Tao Zhou, Linyuan Lu and Yi-Cheng Zhang for missing link prediction that works well on networks with high average degree. Additionally, it outlines an overlapping community detection method called BIGCLAM proposed by Jaewon Yang and Jure Leskovec for massive networks, and status index by Leo Katz to identify popularity. The document concludes that link prediction enhances user experience and social network popularity by addressing the challenges of network size and sparsity.
1) The document presents a system for detecting malicious links using machine learning techniques. It aims to improve the effectiveness of classifiers for identifying dangerous websites.
2) The system utilizes logistic regression as a supervised machine learning algorithm to categorize URLs based on their linguistic properties and behaviors. New attributes are extracted from URLs to train the classifier.
3) The proposed approach aims to identify malicious URLs based solely on their structure and properties, without relying on webpage content. This could lead to significant resource savings and a safer browsing experience for users.
WEB ATTACK PREDICTION USING STEPWISE CONDITIONAL PARAMETER TUNING IN MACHINE ...IJCNCJournal
There is a rapid growth in internet and website usage. A wide variety of devices are used to access
websites, such as mobile phones, tablets, laptops, and personal computers. Attackers are finding more and
more vulnerabilities on websites that they can exploit for malicious purposes. A web application attack
occurs when cyber criminals gain access to unauthorized areas. Typically, attackers look for
vulnerabilities in web applications at the application layer. SQL injection attacks and Cross Site script
attacks is used to access web applications to obtain sensitive data. A key objective of this work is to
develop new features and investigate how automatic tuning of machine learning techniques can improve
the performance of Web Attack detections that use HTTP CSIC datasets to block and detect attacks. The
Stepwise Conditional parameter tuning in machine learning algorithms is a proposed model. This model is
a dynamic and automated parameter choosing and tuning based on the better outcome. This work also
compares two datasets for performance of the proposed model.
Web Attack Prediction using Stepwise Conditional Parameter Tuning in Machine ...IJCNCJournal
There is a rapid growth in internet and website usage. A wide variety of devices are used to access websites, such as mobile phones, tablets, laptops, and personal computers. Attackers are finding more and more vulnerabilities on websites that they can exploit for malicious purposes. A web application attack occurs when cyber criminals gain access to unauthorized areas. Typically, attackers look for vulnerabilities in web applications at the application layer. SQL injection attacks and Cross Site script attacks is used to access web applications to obtain sensitive data. A key objective of this work is to develop new features and investigate how automatic tuning of machine learning techniques can improve the performance of Web Attack detections that use HTTP CSIC datasets to block and detect attacks. The Stepwise Conditional parameter tuning in machine learning algorithms is a proposed model. This model is a dynamic and automated parameter choosing and tuning based on the better outcome. This work also compares two datasets for performance of the proposed model.
A Review on Pattern Discovery Techniques of Web Usage MiningIJERA Editor
In the recent years with the development of Internet technology the growth of World Wide Web exceeded all expectations. A lot of information is available in different formats and retrieving interesting content has become a very difficult task. One possible approach to solve this problem is Web Usage Mining (WUM), the important application of Web Mining. Extracting the hidden knowledge in the log files of a web server, recognizing various interests of web users, discovering customer behavior while at the site are normally referred as the applications of web usage mining. In this paper we provide an updated focused survey on techniques of web usage mining.
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.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Recommendation generation by integrating sequential pattern mining and semanticseSAT Journals
Abstract As the Internet usage keeps increasing, the number of web sites and hence the number of web pages also keeps increasing. A recommendation system can be used to provide personalized web service by suggesting the pages that are likely to be accessed in future. Most of the recommendation systems are based on association rule mining or based on keywords. Using the association rule mining the prediction rate is less as it doesn’t take into account the order of access of the web pages by the users. The recommendation systems that are key-word based provides lesser relevant results. This paper proposes a recommendation system that uses the advantages of sequential pattern mining and semantics over the association rule mining and keyword based systems respectively. Keywords: Sequential Pattern Mining, Taxonomy, Apriori-All, CS-Mine, Semantic, Clustering
Concept drift and machine learning model for detecting fraudulent transaction...IJECEIAES
The document presents a machine learning model for detecting fraudulent transactions in a streaming environment that addresses concept drift. The proposed approach uses the extreme gradient boosting (XGBoost) algorithm and employs four algorithms to continuously detect concept drift in data streams. The approach is evaluated on credit card and Twitter fraud datasets and is shown to outperform traditional machine learning models in terms accuracy, precision, and recall, and is more robust to concept drift. The proposed approach can be utilized as a real-time fraud detection system across different industries.
Semantically Enriched Knowledge Extraction With Data MiningEditor IJCATR
This document discusses using data mining techniques to extract knowledge from data and representing that knowledge in both human-understandable and machine-understandable formats. It uses an input dataset, applies data mining methods like regression using WEKA and SAS, extracts natural language triples about the results, and generates RDF triples to represent the knowledge in a machine-readable format.
IRJET- Noisy Content Detection on Web Data using Machine LearningIRJET Journal
The document presents a study on detecting noisy content on web data using machine learning techniques. It aims to identify and filter out advertisements, irrelevant data and other noisy content when users retrieve information from websites. The study uses algorithms like support vector machines, artificial neural networks, decision trees and k-nearest neighbors to classify web content as noisy or not. A proposed methodology involves training models using these machine learning algorithms and evaluating their performance for noisy content detection on web data.
Semantic Web concepts used in Web 3.0 applicationsIRJET Journal
This document discusses how semantic web concepts can be used in applications for Web 3.0. It provides examples of how semantic web could be applied in areas like medical sciences, search engines, and e-learning. Specifically, it describes how semantic web could help integrate medical data from different sources, enable more accurate medical diagnosis and treatment recommendations based on patient history. It also discusses how a semantic search engine like Swoogle works by tagging web pages with metadata to better understand context and return more relevant search results. Finally, it touches on how a semantic web architecture could enable more sophisticated e-learning systems by linking educational resources.
A Proposed Model for a Web-Based Academic Advising SystemEswar Publications
Student advising is an important and time-consuming effort in academic life. Academic advising has been implemented in order to fill the gap between student and the academic routine, by moving advising, complaining, evaluating, suggesting system from the traditional ways to an automated way. The researcher surveyed the existing literature; as utilized that many institutions have implemented computerized solutions in order to enhance their overall advising experience. In this paper the researcher innovates an automated mechanism for
academic advising in the university system. The paper presents an overview of the development and implementation of a new model of e-Academic Advising System as a web-based application. The proposed model attempts to develop a model that the staff and advisor can access to follow-up the student complaints and suggestions. Also, the students who registered can through complain, evaluate & suggest in any subject. Finally, the head of the department can receive a KPIs reports to follow-up his department. Therefore, a need for a
system that could detect student’s problems and provide them with suitable feedback is raised. The aim of this paper is to implement a system which facilitates and assists academic advisors in their efforts to providing quality, accurate and consistent advising services to their students; also, to explore the design and implementation of a computerized tool to facilitate this process. This paper discussed the required methodologies used in the development of the Academic Advising System, it has been shown that Academic Advising is a Process more than a Final Product or system, a technical vision for Academic Advising System has been provided. The e-Academic Advising web-based developed and implemented by "Ruby on Rails" as a Web framework which runs via the
Ruby programming language and "PostgreSQL" as a Database Engine.
Certain Issues in Web Page Prediction, Classification and Clustering in Data ...IJAEMSJORNAL
Nowadays, data mining which is a part of web mining plays a vital role in various applications such as search engines, health care centers for extracting the individual patient details among huge database, analyzing disease based on basic criteria, education system for analyzing their performance level with other system, social networking, E-Commerce and knowledge management etc., which extract the information based on the user query. The issues are time taken to mine the target content or webpage from the search engines, space complexity and predicting the frequent webpage for the next user based on users’ behaviour.
A Brief Survey on Recommendation System for a Gradient Classifier based Inade...Christo Ananth
Recommender systems are a common and successful feature of modern internet services. (RS). A service that connects users to tasks is known as a recommendation system. Making it simpler for customers and project providers to identify and receive projects and other solutions achieves this. A recommendation system is a strong device that may be advantageous to a business or organisation. This study explores whether recommender systems may be utilised to solve cold-start and data-sparsely issues with recommender systems, as well as delays and business productivity. Recommender systems make it easier and more convenient for people to get information. Over the years, several different methods have been created. We employ a potent predictive regression method known as the slope classifier algorithm, which minimises a loss function by repeatedly choosing a function that points in the direction of the weak hypothesis or the negative gradient. A group that is experiencing trouble handling cold beginnings and data sparsity will send enormous datasets to the suggested systems team. The users have to finish their job by the deadline in order to overcome these challenges.
IRJET - Online Assignment Plagiarism Checking using Data Mining and NLPIRJET Journal
This document presents a proposed system for detecting plagiarism in student assignments submitted online. The system would use data mining algorithms and natural language processing to compare submitted assignments against each other and identify plagiarized content. It would analyze assignments at both the syntactic and semantic levels. The proposed system is intended to more efficiently and accurately detect plagiarism compared to teachers manually reviewing all submissions. The document describes the workflow of the system, including preprocessing of assignments, text analysis, similarity measurement, and algorithms that would be used like Rabin-Karp, KMP and SCAM.
Similar to Detection of Malicious Web Links Using Machine Learning Algorithm: A Review (20)
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...IRJET Journal
1) The document discusses the Sungal Tunnel project in Jammu and Kashmir, India, which is being constructed using the New Austrian Tunneling Method (NATM).
2) NATM involves continuous monitoring during construction to adapt to changing ground conditions, and makes extensive use of shotcrete for temporary tunnel support.
3) The methodology section outlines the systematic geotechnical design process for tunnels according to Austrian guidelines, and describes the various steps of NATM tunnel construction including initial and secondary tunnel support.
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTUREIRJET Journal
This study examines the effect of response reduction factors (R factors) on reinforced concrete (RC) framed structures through nonlinear dynamic analysis. Three RC frame models with varying heights (4, 8, and 12 stories) were analyzed in ETABS software under different R factors ranging from 1 to 5. The results showed that displacement increased as the R factor decreased, indicating less linear behavior for lower R factors. Drift also decreased proportionally with increasing R factors from 1 to 5. Shear forces in the frames decreased with higher R factors. In general, R factors of 3 to 5 produced more satisfactory performance with less displacement and drift. The displacement variations between different building heights were consistent at different R factors. This study evaluated how R factors influence
A COMPARATIVE ANALYSIS OF RCC ELEMENT OF SLAB WITH STARK STEEL (HYSD STEEL) A...IRJET Journal
This study compares the use of Stark Steel and TMT Steel as reinforcement materials in a two-way reinforced concrete slab. Mechanical testing is conducted to determine the tensile strength, yield strength, and other properties of each material. A two-way slab design adhering to codes and standards is executed with both materials. The performance is analyzed in terms of deflection, stability under loads, and displacement. Cost analyses accounting for material, durability, maintenance, and life cycle costs are also conducted. The findings provide insights into the economic and structural implications of each material for reinforcement selection and recommendations on the most suitable material based on the analysis.
Effect of Camber and Angles of Attack on Airfoil CharacteristicsIRJET Journal
This document discusses a study analyzing the effect of camber, position of camber, and angle of attack on the aerodynamic characteristics of airfoils. Sixteen modified asymmetric NACA airfoils were analyzed using computational fluid dynamics (CFD) by varying the camber, camber position, and angle of attack. The results showed the relationship between these parameters and the lift coefficient, drag coefficient, and lift to drag ratio. This provides insight into how changes in airfoil geometry impact aerodynamic performance.
A Review on the Progress and Challenges of Aluminum-Based Metal Matrix Compos...IRJET Journal
This document reviews the progress and challenges of aluminum-based metal matrix composites (MMCs), focusing on their fabrication processes and applications. It discusses how various aluminum MMCs have been developed using reinforcements like borides, carbides, oxides, and nitrides to improve mechanical and wear properties. These composites have gained prominence for their lightweight, high-strength and corrosion resistance properties. The document also examines recent advancements in fabrication techniques for aluminum MMCs and their growing applications in industries such as aerospace and automotive. However, it notes that challenges remain around issues like improper mixing of reinforcements and reducing reinforcement agglomeration.
Dynamic Urban Transit Optimization: A Graph Neural Network Approach for Real-...IRJET Journal
This document discusses research on using graph neural networks (GNNs) for dynamic optimization of public transportation networks in real-time. GNNs represent transit networks as graphs with nodes as stops and edges as connections. The GNN model aims to optimize networks using real-time data on vehicle locations, arrival times, and passenger loads. This helps increase mobility, decrease traffic, and improve efficiency. The system continuously trains and infers to adapt to changing transit conditions, providing decision support tools. While research has focused on performance, more work is needed on security, socio-economic impacts, contextual generalization of models, continuous learning approaches, and effective real-time visualization.
Structural Analysis and Design of Multi-Storey Symmetric and Asymmetric Shape...IRJET Journal
This document summarizes a research project that aims to compare the structural performance of conventional slab and grid slab systems in multi-story buildings using ETABS software. The study will analyze both symmetric and asymmetric building models under various loading conditions. Parameters like deflections, moments, shears, and stresses will be examined to evaluate the structural effectiveness of each slab type. The results will provide insights into the comparative behavior of conventional and grid slabs to help engineers and architects select appropriate slab systems based on building layouts and design requirements.
A Review of “Seismic Response of RC Structures Having Plan and Vertical Irreg...IRJET Journal
This document summarizes and reviews a research paper on the seismic response of reinforced concrete (RC) structures with plan and vertical irregularities, with and without infill walls. It discusses how infill walls can improve or reduce the seismic performance of RC buildings, depending on factors like wall layout, height distribution, connection to the frame, and relative stiffness of walls and frames. The reviewed research paper analyzes the behavior of infill walls, effects of vertical irregularities, and seismic performance of high-rise structures under linear static and dynamic analysis. It studies response characteristics like story drift, deflection and shear. The document also provides literature on similar research investigating the effects of infill walls, soft stories, plan irregularities, and different
This document provides a review of machine learning techniques used in Advanced Driver Assistance Systems (ADAS). It begins with an abstract that summarizes key applications of machine learning in ADAS, including object detection, recognition, and decision-making. The introduction discusses the integration of machine learning in ADAS and how it is transforming vehicle safety. The literature review then examines several research papers on topics like lightweight deep learning models for object detection and lane detection models using image processing. It concludes by discussing challenges and opportunities in the field, such as improving algorithm robustness and adaptability.
Long Term Trend Analysis of Precipitation and Temperature for Asosa district,...IRJET Journal
The document analyzes temperature and precipitation trends in Asosa District, Benishangul Gumuz Region, Ethiopia from 1993 to 2022 based on data from the local meteorological station. The results show:
1) The average maximum and minimum annual temperatures have generally decreased over time, with maximum temperatures decreasing by a factor of -0.0341 and minimum by -0.0152.
2) Mann-Kendall tests found the decreasing temperature trends to be statistically significant for annual maximum temperatures but not for annual minimum temperatures.
3) Annual precipitation in Asosa District showed a statistically significant increasing trend.
The conclusions recommend development planners account for rising summer precipitation and declining temperatures in
P.E.B. Framed Structure Design and Analysis Using STAAD ProIRJET Journal
This document discusses the design and analysis of pre-engineered building (PEB) framed structures using STAAD Pro software. It provides an overview of PEBs, including that they are designed off-site with building trusses and beams produced in a factory. STAAD Pro is identified as a key tool for modeling, analyzing, and designing PEBs to ensure their performance and safety under various load scenarios. The document outlines modeling structural parts in STAAD Pro, evaluating structural reactions, assigning loads, and following international design codes and standards. In summary, STAAD Pro is used to design and analyze PEB framed structures to ensure safety and code compliance.
A Review on Innovative Fiber Integration for Enhanced Reinforcement of Concre...IRJET Journal
This document provides a review of research on innovative fiber integration methods for reinforcing concrete structures. It discusses studies that have explored using carbon fiber reinforced polymer (CFRP) composites with recycled plastic aggregates to develop more sustainable strengthening techniques. It also examines using ultra-high performance fiber reinforced concrete to improve shear strength in beams. Additional topics covered include the dynamic responses of FRP-strengthened beams under static and impact loads, and the performance of preloaded CFRP-strengthened fiber reinforced concrete beams. The review highlights the potential of fiber composites to enable more sustainable and resilient construction practices.
Survey Paper on Cloud-Based Secured Healthcare SystemIRJET Journal
This document summarizes a survey on securing patient healthcare data in cloud-based systems. It discusses using technologies like facial recognition, smart cards, and cloud computing combined with strong encryption to securely store patient data. The survey found that healthcare professionals believe digitizing patient records and storing them in a centralized cloud system would improve access during emergencies and enable more efficient care compared to paper-based systems. However, ensuring privacy and security of patient data is paramount as healthcare incorporates these digital technologies.
Review on studies and research on widening of existing concrete bridgesIRJET Journal
This document summarizes several studies that have been conducted on widening existing concrete bridges. It describes a study from China that examined load distribution factors for a bridge widened with composite steel-concrete girders. It also outlines challenges and solutions for widening a bridge in the UAE, including replacing bearings and stitching the new and existing structures. Additionally, it discusses two bridge widening projects in New Zealand that involved adding precast beams and stitching to connect structures. Finally, safety measures and challenges for strengthening a historic bridge in Switzerland under live traffic are presented.
React based fullstack edtech web applicationIRJET Journal
The document describes the architecture of an educational technology web application built using the MERN stack. It discusses the frontend developed with ReactJS, backend with NodeJS and ExpressJS, and MongoDB database. The frontend provides dynamic user interfaces, while the backend offers APIs for authentication, course management, and other functions. MongoDB enables flexible data storage. The architecture aims to provide a scalable, responsive platform for online learning.
A Comprehensive Review of Integrating IoT and Blockchain Technologies in the ...IRJET Journal
This paper proposes integrating Internet of Things (IoT) and blockchain technologies to help implement objectives of India's National Education Policy (NEP) in the education sector. The paper discusses how blockchain could be used for secure student data management, credential verification, and decentralized learning platforms. IoT devices could create smart classrooms, automate attendance tracking, and enable real-time monitoring. Blockchain would ensure integrity of exam processes and resource allocation, while smart contracts automate agreements. The paper argues this integration has potential to revolutionize education by making it more secure, transparent and efficient, in alignment with NEP goals. However, challenges like infrastructure needs, data privacy, and collaborative efforts are also discussed.
A REVIEW ON THE PERFORMANCE OF COCONUT FIBRE REINFORCED CONCRETE.IRJET Journal
This document provides a review of research on the performance of coconut fibre reinforced concrete. It summarizes several studies that tested different volume fractions and lengths of coconut fibres in concrete mixtures with varying compressive strengths. The studies found that coconut fibre improved properties like tensile strength, toughness, crack resistance, and spalling resistance compared to plain concrete. Volume fractions of 2-5% and fibre lengths of 20-50mm produced the best results. The document concludes that using a 4-5% volume fraction of coconut fibres 30-40mm in length with M30-M60 grade concrete would provide benefits based on previous research.
Optimizing Business Management Process Workflows: The Dynamic Influence of Mi...IRJET Journal
The document discusses optimizing business management processes through automation using Microsoft Power Automate and artificial intelligence. It provides an overview of Power Automate's key components and features for automating workflows across various apps and services. The document then presents several scenarios applying automation solutions to common business processes like data entry, monitoring, HR, finance, customer support, and more. It estimates the potential time and cost savings from implementing automation for each scenario. Finally, the conclusion emphasizes the transformative impact of AI and automation tools on business processes and the need for ongoing optimization.
Multistoried and Multi Bay Steel Building Frame by using Seismic DesignIRJET Journal
The document describes the seismic design of a G+5 steel building frame located in Roorkee, India according to Indian codes IS 1893-2002 and IS 800. The frame was analyzed using the equivalent static load method and response spectrum method, and its response in terms of displacements and shear forces were compared. Based on the analysis, the frame was designed as a seismic-resistant steel structure according to IS 800:2007. The software STAAD Pro was used for the analysis and design.
Cost Optimization of Construction Using Plastic Waste as a Sustainable Constr...IRJET Journal
This research paper explores using plastic waste as a sustainable and cost-effective construction material. The study focuses on manufacturing pavers and bricks using recycled plastic and partially replacing concrete with plastic alternatives. Initial results found that pavers and bricks made from recycled plastic demonstrate comparable strength and durability to traditional materials while providing environmental and cost benefits. Additionally, preliminary research indicates incorporating plastic waste as a partial concrete replacement significantly reduces construction costs without compromising structural integrity. The outcomes suggest adopting plastic waste in construction can address plastic pollution while optimizing costs, promoting more sustainable building practices.
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.
Build the Next Generation of Apps with the Einstein 1 Platform.
Rejoignez Philippe Ozil pour une session de workshops qui vous guidera à travers les détails de la plateforme Einstein 1, l'importance des données pour la création d'applications d'intelligence artificielle et les différents outils et technologies que Salesforce propose pour vous apporter tous les bénéfices de l'IA.
Height and depth gauge linear metrology.pdfq30122000
Height gauges may also be used to measure the height of an object by using the underside of the scriber as the datum. The datum may be permanently fixed or the height gauge may have provision to adjust the scale, this is done by sliding the scale vertically along the body of the height gauge by turning a fine feed screw at the top of the gauge; then with the scriber set to the same level as the base, the scale can be matched to it. This adjustment allows different scribers or probes to be used, as well as adjusting for any errors in a damaged or resharpened probe.
Blood finder application project report (1).pdfKamal Acharya
Blood Finder is an emergency time app where a user can search for the blood banks as
well as the registered blood donors around Mumbai. This application also provide an
opportunity for the user of this application to become a registered donor for this user have
to enroll for the donor request from the application itself. If the admin wish to make user
a registered donor, with some of the formalities with the organization it can be done.
Specialization of this application is that the user will not have to register on sign-in for
searching the blood banks and blood donors it can be just done by installing the
application to the mobile.
The purpose of making this application is to save the user’s time for searching blood of
needed blood group during the time of the emergency.
This is an android application developed in Java and XML with the connectivity of
SQLite database. This application will provide most of basic functionality required for an
emergency time application. All the details of Blood banks and Blood donors are stored
in the database i.e. SQLite.
This application allowed the user to get all the information regarding blood banks and
blood donors such as Name, Number, Address, Blood Group, rather than searching it on
the different websites and wasting the precious time. This application is effective and
user friendly.
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.
Generative AI Use cases applications solutions and implementation.pdfmahaffeycheryld
Generative AI solutions encompass a range of capabilities from content creation to complex problem-solving across industries. Implementing generative AI involves identifying specific business needs, developing tailored AI models using techniques like GANs and VAEs, and integrating these models into existing workflows. Data quality and continuous model refinement are crucial for effective implementation. Businesses must also consider ethical implications and ensure transparency in AI decision-making. Generative AI's implementation aims to enhance efficiency, creativity, and innovation by leveraging autonomous generation and sophisticated learning algorithms to meet diverse business challenges.
https://www.leewayhertz.com/generative-ai-use-cases-and-applications/
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.
Tools & Techniques for Commissioning and Maintaining PV Systems W-Animations ...Transcat
Join us for this solutions-based webinar on the tools and techniques for commissioning and maintaining PV Systems. In this session, we'll review the process of building and maintaining a solar array, starting with installation and commissioning, then reviewing operations and maintenance of the system. This course will review insulation resistance testing, I-V curve testing, earth-bond continuity, ground resistance testing, performance tests, visual inspections, ground and arc fault testing procedures, and power quality analysis.
Fluke Solar Application Specialist Will White is presenting on this engaging topic:
Will has worked in the renewable energy industry since 2005, first as an installer for a small east coast solar integrator before adding sales, design, and project management to his skillset. In 2022, Will joined Fluke as a solar application specialist, where he supports their renewable energy testing equipment like IV-curve tracers, electrical meters, and thermal imaging cameras. Experienced in wind power, solar thermal, energy storage, and all scales of PV, Will has primarily focused on residential and small commercial systems. He is passionate about implementing high-quality, code-compliant installation techniques.
Software Engineering and Project Management - Software Testing + Agile Method...Prakhyath Rai
Software Testing: A Strategic Approach to Software Testing, Strategic Issues, Test Strategies for Conventional Software, Test Strategies for Object -Oriented Software, Validation Testing, System Testing, The Art of Debugging.
Agile Methodology: Before Agile – Waterfall, Agile Development.
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.
Open Channel Flow: fluid flow with a free surfaceIndrajeet sahu
Open Channel Flow: This topic focuses on fluid flow with a free surface, such as in rivers, canals, and drainage ditches. Key concepts include the classification of flow types (steady vs. unsteady, uniform vs. non-uniform), hydraulic radius, flow resistance, Manning's equation, critical flow conditions, and energy and momentum principles. It also covers flow measurement techniques, gradually varied flow analysis, and the design of open channels. Understanding these principles is vital for effective water resource management and engineering applications.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELijaia
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
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
- An overly permissive IAM role configuration can lead to privilege escalation by creating a role with administrative privileges and allow a user to assume this role.
- Objective: Show how overly permissive IAM roles can lead to privilege escalation.
- Steps:
- Create role with administrative privileges.
- Allow user to assume the role.
- Perform administrative actions.
- Differentiation between PassRole vs AssumeRole
Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)