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4th IEEE International Conference on Artificial Intelligence in engineering and technology, IICAIET 2022

作者： bajpai, Abhishek Chaubey, Srishti Patro, bdk Verma, Abhineet Rajkiya Engineering College Department of Computer Science and Engineering UP Kannauj India B.Tech Computer Science and Engineering Rajkiya Engineering College UP Kannauj India

ISBN: (数字)9781665468374

ISBN: (纸本)9781665468374

Only 0.3 percent of the total water on Earth is available in rivers and ponds, and the majority of it is polluted to the point where drinking it directly can cause disease. In this paper, we will identify the quality of the river Ganges and check if it is portable and healthy. We aim to classify the water on some parameters using different classification algorithms, such as Random Forest, which is a supervised machine learning algorithm. This model's accuracy is around 99 percent, which is far superior to other approaches taken for water quality prediction. © 2022 IEEE.

关键词： Water quality

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Crime Against Women in India: Statistical Analysis Using Linear Regression 2

Crime Against Women in India: Statistical Analysis Using Lin...

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2nd International Conference on Advanced Computing and Communication technologies, ICACCtech 2024

作者： Mim, Zarin Tasnim Paul, Rittika Foysal, Mollah Md Tohfa, Fairuz Nowshin Mahi, Shah Abrar Bangalore India Bangalore India B-Tech of Computer Science and Engineering East Delta University Chattagram Bangladesh B-Tech of Computer Science and Engineering-Cyber Security Chandigarh University Delhi India

ISBN: (纸本)9798331519056

The crime reports of offenses occurring against women all over India are increasing day by day. It has become one of today's most concerning socio-economic and cultural issues. Crime against women hampers the overall prosperity and development of the nation. This crime violates human rights, impacts women's physical and mental health, and becomes an educational barrier to women's empowerment. This paper surveys the reasons for the influence of reported Crime Against Women (CAW) in 35 states and union territories in India from 2001-2012. The dataset describes different types of Crime Against Women (CAW): rape, kidnapping, abduction, assault on women, insult to the modesty of women, cruelty by husband or relative. This paper also contains a report on the arrested rate for crimes against women in India from 2001-2012. According to the comparison between these two datasets, the person arrest rate is more than the crime against women rate in every state in India. We used machine learning-based linear regression analysis to format the relationship between two datasets, where crime against women is the dependent variable and people arrested rate is the independent variable. This paper discusses two types of linear regression: Simple Linear Regression and Multiple Linear Regression. The relation between these two datasets helps to predict the hot location of crimes, and the activeness of law enforcement regarding the crimes and encourages victims to take action. For the datasets, P-values, R-squared, and adjusted R-squared values are used to evaluate the statistically significant prediction in explaining the variation in crime rates. This prediction is used to reduce the rate of crime against women all over India. © 2024 IEEE.

关键词： Multiple linear regression

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Federated Learning for Kidney Disease Prediction using Combined LSTM and MLP Models

Federated Learning for Kidney Disease Prediction using Combi...

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International Conference on Communication Systems and Network technologies (CSNT)

作者： Anurag Pathak Anshuman Pandey B.Tech in Computer Science (AI & ML) GLA University Mathura Uttar Pradesh India B.Tech in Computer Science GLA University Mathura Uttar Pradesh India

ISBN: (数字)9798331531935

ISBN: (纸本)9798331531942

Kidney disease (KD) is a prevalent global health issue, and early prediction is critical for improving patient outcomes. In this study, we propose a federated learning approach that combines Long Short-Term Memory (LSTM) networks with Multi-Layer Perceptron (MLP) models for kidney disease prediction. The LSTM component captures temporal dependencies in the data, while the MLP enhances the model’s ability to classify based on learned features. The federated learning framework ensures data privacy by keeping patient information decentralized across multiple hospitals. Experimental results show promising accuracy, precision, recall, and F1 score, demonstrating the potential of combining LSTM and MLP for healthcare applications.

关键词： Privacy Solid modeling Accuracy Federated learning Hospitals Predictive models Solids Long short term memory Kidney Diseases

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An electronic warfare approach for deploying a software-based Wi-Fi jammer 5

An electronic warfare approach for deploying a software-base...

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5th International Conference on Contemporary Computing and Informatics, IC3I 2022

作者： Kaushik, Keshav Negi, Rahul Dev, Prabhav University of Petroleum and Energy Studies School of Computer Science Dehradun India University of Petroleum and Energy Studies B.Tech Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350398267

Some prominent instances have been centered on electronic warfare. For example, the American military has made significant investments in automation through UAV programs, only for competitors like the Iranians to create strategies to interfere with these systems. Iran managed to capture a top-secret U.S. surveil-lance drone by fooling it into descending in the incorrect place by jamming its control signals and providing it with bogus GPS data. In this paper, the authors have focused on the electronic warfare approach for deploying a software-based Wi-Fi jammer. The software-based Wi-Fi jammer can disconnect the targets using the DoS pursuit mode. The paper describes the unique methodology of how software can also be used for jamming wireless signals. © 2022 IEEE.

关键词： Wi-Fi

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An approach for exploiting and mitigating Log4J using Log4Shell vulnerability 3

An approach for exploiting and mitigating Log4J using Log4Sh...

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3rd International Conference on Computation, Automation and Knowledge Management, ICCAKM 2022

作者： Kaushik, Keshav Dass, Alpana Dhankhar, Ayush University of Petroleum and Energy Studies School of Computer Science Dehradun India University of Petroleum and Energy Studies Student B.Tech Computer Science and Engineering Dehradun India

ISBN: (数字)9781665453196

ISBN: (纸本)9781665453196

A new serious flaw has been discovered in log4j, a popular open-source tool used to produce logs within Java programs. The Log4Shell vulnerability, also referred as CVE-2021-44228, enables Remote Code Execution (RCE), enabling attackers to run obfuscated code on the host. A large number of programmes and businesses, including the well-known game Minecraft, employ the well-known utility log4j. Additionally, it is utilised in numerous commercial products as well as several Apache frameworks including Struts2, Kafka, Druid, and Flink. In this paper, the authors have used an approach to exploit the Log4Shell vulnerability and then provided the mitigation methods for the same. © 2022 IEEE.

关键词： Open source software

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Resonating Silence: Music Perception in the Deaf and Hard of Hearing

Resonating Silence: Music Perception in the Deaf and Hard of...

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IEEE UP Section Conference on Electrical computer and Electronics (UPCON)

作者： Mahak Garg Akanksha Yadav Kiran Singh B.Tech Computer Science and Engineering Galgotias University Greater Noida India School of Computer Science & Engineering Galgotias University Greater Noida India

ISBN: (数字)9798350378726

ISBN: (纸本)9798350378733

Music is traditionally considered an auditory experience; however, the perception of music by Deaf and hard-of-hearing individuals challenges this assumption. This paper examines how people who are Deaf engage with music through a multisensory approach, emphasizing vibration, touch, and visual elements. by analyzing data from the Frontier and Kaggle database, the study explores how hearing-impaired individuals interpret and emotionally respond to rhythmic vibrations. Participants, aged 10–40, interacted with a haptic device that produced both musical and non-musical vibrations. Age-based trends emerged: older participants often associated vibrations with musical instruments, while younger participants connected them to common household objects. Emotional responses varied, with younger individuals showing heightened excitement and older participants experiencing greater relaxation. Findings indicate that tactile rhythms can foster meaningful associations and emotions across age groups, providing insights into sensory-based musical experiences for those who are hearing-impaired. This paper synthesizes literature, case studies, and data from the Frontier database to highlight the various ways music can be felt and comprehended beyond hearing. by underscoring the holistic and multisensory dimensions of music, it argues for appreciating sound and music through a broader understanding of sensory experiences.

关键词： Vibrations Visualization Databases Instruments Music Auditory system Real-time systems Haptic interfaces Emotional responses Artificial intelligence

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Context-Aware Summarization for PDF Documents using Large Language Models 4

Context-Aware Summarization for PDF Documents using Large La...

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4th International Conference on Expert Clouds and Applications, ICOECA 2024

作者： Ramprasad, Akshara Sivakumar, P. School of Computer Science and Engineering Vellore Institute of Technology B. Tech Computer Science with specialization in AI & ML Chennai India School of Computer Science and Engineering Vellore Institute of Technology Chennai India

ISBN: (纸本)9798350385793

In an era characterized by the overflow of textual information, the demand for effective text summarization techniques has become increasingly evident. This research study presents a novel solution to address this demand: the development of a PDF Summarizer Generative AI Platform for context-aware text and document summarization. The developed platform empowers users to generate informative summaries from lengthy textual documents. It features an interface powered by Gradio for enabling user-friendly accessibility. Equipped with essential components such as OpenAI's language models for text comprehension, Chroma vector enables document embedding and conversational retrieval chains for contextual understanding, where the platform offers a comprehensive solution. Users can effortlessly upload documents in various formats, including PDFs, and interactively engage with the system to obtain concise summaries tailored to their specific requirements. © 2024 IEEE.

关键词： Chroma Database (ChromaDb) Gradio LangChain Large Language Models (LLM) OpenAI

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Anti-Remote Disk Imaging: A Comprehensive Approach to Prevent Unauthorized Data Access

Anti-Remote Disk Imaging: A Comprehensive Approach to Preven...

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Data science, Agents & Artificial Intelligence (ICDSAAI), International Conference on

作者： K. Venketesh M. Caleb Gunalan Manoj Hariharan R Rahul S Surender R Department of Computer Science and Engineering Kalasalingam Academy of Research and Education Tamilnadu India B.Tech Computer Science and Engineering Kalasalingam Academy of Research and Education Tamilnadu India

ISBN: (数字)9798331537555

ISBN: (纸本)9798331537562

Remote disk imaging is an emerging cybersecurity risk that compromises sensitive information integrity. Malicious actors exploit legitimate tools like dd and Clonezilla to clone and exfiltrate data remotely. This paper introduces a novel anti-remote disk imaging system that integrates process monitoring, dynamic firewall configurations, and full-disk encryption to mitigate unauthorized disk access. Unlike existing singular approaches, our unified solution offers real-time detection, prevention, and administrative alerts. Comparative analyses reveal that our tool outperforms existing techniques with a 92% effectiveness rate and an average response time of 3 seconds while maintaining low resource usage. These results highlight its practicality for safeguarding critical systems in resource-constrained environments. Remote disk imaging poses challenges such as real-time detection, resource constraints, and distinguishing between legitimate and malicious activities. Existing techniques, like full-disk encryption and firewall-based blocking, face limitations in adaptability and performance. This paper introduces a comprehensive system that addresses these challenges by integrating process monitoring, dynamic firewall configurations, and encryption to prevent unauthorized disk imaging.

关键词： Process monitoring Firewalls (computing) Prevention and mitigation Imaging Machine learning Real-time systems Software Encryption Time factors Information integrity

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Customer Analytics using Surveillance Video

arXiv

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arXiv 2025年

作者： Ijjina, Earnest Paul Joshi, Aniruddha Srinivas Kanahasabai, Goutham Priyanka, P. Keerthi Department of Computer Science and Engineering National Institute of Technology Warangal506004 India B.Tech Department of Computer Science and Engineering National Institute of Technology Warangal506004 India

The analysis of sales information, is a vital step in designing an effective marketing strategy. This work proposes a novel approach to analyse the shopping behaviour of customers to identify their purchase patterns. An extended version of the Multi-Cluster Overlapping k-Means Extension (MCOKE) algorithm with weighted k-Means algorithm is utilized to map customers to the garments of interest. The age & gender traits of the customer;the time spent and the expressions exhibited while selecting garments for purchase, are utilized to associate a customer or a group of customers to a garments they are interested in. Such study on the customer base of a retail business, may help in inferring the products of interest of their consumers, and enable them in developing effective business strategies, thus ensuring customer satisfaction, loyalty, increased sales and profits. Copyright © 2025, The Authors. All rights reserved.

关键词： Sales

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Dynamic Website Authentication Using Time-based One-Time Password (TOTP) for Enhanced Security

Dynamic Website Authentication Using Time-Based One-Time Pas...

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Data science, Agents & Artificial Intelligence (ICDSAAI), International Conference on

作者： M Caleb Gunalan bavani K Mathew Hayden Manoj Hariharan R Rahul S B.Tech Computer Science and Engineering Kalasalingam Academy of Research and Education Krishnankoil Tamilnadu India Department of Computer Science and Engineering Kalasalingam Academy of Research and Education Krishnankoil Tamilnadu India

ISBN: (数字)9798331537555

ISBN: (纸本)9798331537562

In today's digital landscape, the proliferation of fake websites poses significant threats to user security, trust, and data integrity. This paper presents a novel solution to address this issue through the implementation of a dynamic website authentication system using Time-based One-Time Password (TOTP) verification. The system allows websites to register securely with a central authentication server, generating unique TOTP codes that users can verify to determine the authenticity of the website. Website owners are issued a secret key upon registration, which is used to generate TOTP codes that refresh every 30 seconds. This project emphasizes user-friendly verification mechanisms and secure key management to protect users from phishing attacks. The system architecture, implementation, and potential applications are discussed, along with future directions for integrating multi-factor authentication and expanding security features.

关键词： Codes Multi-factor authentication Phishing Prevention and mitigation Data integrity Systems architecture Passwords QR codes Registers Servers

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