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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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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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Prevention from gas devastation

Prevention from gas devastation

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2020 International Online Conference on engineering Response to COVID-19, IOCER-COVID-19 2020

作者： Datta, Sanghita Sah, Ankita Gautam, Sidharth Das, Upamita Maity, Saikat B. Tech Computer Science Engineering JIS University India

LPG leakages are the most common issues found in household and gas plants. This issue is life threatening not only for the humans in the vicinity but also for the surrounding areas. The idea behind our project is to save the lives of those innocents who can get affected due to the carelessness of certain people. So, as soon as the gas gets detected by the system, the concerned people around will receive messages as well as the alarm rings. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Gas plants

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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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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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brain Tumor Detection using MRI Image Processing techniques

Brain Tumor Detection using MRI Image Processing Techniques

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2024 IEEE International Conference on Innovation and Novelty in engineering and technology, INNOVA 2024

作者： Jadhav, Ambaji S. Pawar, Rashmi Hattaraki, Sunilkumar M. bagali, Shwetha Patil, Rajeshwari S. Patil, bhagyashree Department of Elecrtical and Electronics Engineering B.L.D.E. A’s V.P. Dr. P.G.H. College of Engg. and Tech. Vijayapura India Department of Electronics and Communication Engineering B.L.D.E. A’s V.P. Dr. P.G.H. College of Engg. and Tech. Vijayapura India Department of Computer Science and Engineering Sri Krishna Institute of Technology Bengaluru India

ISBN: (纸本)9798331505134

Medical image processing is highly developed and critical in the medical field, encompassing methods like X-rays, MRI, and CT scans. These techniques help to identify minute defects in the human body. brain tumors, which disrupt normal brain function, are detected through MRI using segmentation, feature extraction, and classification, processes that are time-consuming and depend on the expertise of clinical professionals. computer-aided technology addresses these challenges. This work aims to diagnose brain tumors accurately and quickly using MRI images. Image preprocessing is done using CLAHE and median filter to enhance contrast and eliminate noise. Thresholding is used for segmentation and a lightweight U-net is used for tumor segmentation, achieving high accuracy and efficiency without extensive training data. Finally, an MSD-CNN classifies the tumor, capturing both local and global features for better image recognition. Our proposed model outperforms over existing methods in terms of accuracy, robustness, and efficiency in brain tumor detection. © 2024 IEEE.

关键词： Median filters

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Challenges in Cyber Physical Social Systems and Internet of Things 5

Challenges in Cyber Physical Social Systems and Internet of ...

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5th International Conference on Smart Electronics and Communication, ICOSEC 2024

作者： Revathi, S. Raja, J. Mohanraj, M. Malathi, K. Mallala, balasubbareddy Vidhya, R.G. B.S. Abdur Rahman Crescent Institute of Science and Technology Department of Computer Science Engineering Chennai India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology School of Computing Department of Computer Science and Engineering Chennai India Sri Eshwar college of engineering Department of Computer Science and Business Systems Coimbatore India Saveetha Engineering College Department of Artificial Intelligence and Machine Learning Chennai India Chaitanya Bharathi Institute of Technology Department of Electrical and Electronics Engineering Telangana Hyderabad India Hkbk College of Engineering Department of Ece Bangalore India

ISBN: (纸本)9798331504403

This research analyses the complex dynamics of Cyber-Physical-Social Systems (CPSS), encompassing cyber-physical systems, cybersecurity, the Internet of Things (IoT), and social media. by exploring the interactions among these elements, this study analyses the vulnerabilities, risks, and potential benefits within the CPSS framework. This research study analyses the evolving landscape of cybersecurity by considering various aspects such as data integrity, privacy in the IoT era, and the influence of social media on user behaviour and influence dynamics. The study also introduces innovative strategies to enhance CPSS resilience, including methods to mitigate cyber threats and enhance overall system integrity. Additionally, we investigate how social media shapes CPSS behaviours, offering valuable insights into influence dynamics. This research advances the comprehensive understanding of CPSS to support future studies and advancements in the protection and improvement of interconnected systems. © 2024 IEEE.

关键词： Cyber-Physical Systems Cyber-Physical-Social Systems (CPSS) Cybersecurity Internet of Things (IoT) Social Media

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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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Decoding Water Hyacinth Growth Stages with Deep Learning

Decoding Water Hyacinth Growth Stages with Deep Learning

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Next Generation Communication & Information Processing (INCIP), International Conference on

作者： Maheswari L. Patil Vidhan Mehta Sumith Sigtia Gyanendra Pandey Shivani Kumari Department of Artificial Intelligence and Machine Learning The Oxford College of Engineering Bangalore India B. Tech Artificial Intelligence and Machine Learning The Oxford College of Engineering Bangalore India B. Tech Computer Science and Engineering Dr. B R Ambedkar NIT Jalandhar Punjab India B. Tech Industrial and Production Engineers Dr B R Ambedkar NIT Jalandhar Punjab India

ISBN: (数字)9798331528140

ISBN: (纸本)9798331528157

Eichhornia crassipes, commonly referred to as water hyacinth and thought to be one of the most aggressive aquatic macrophytes, is an emerging threat to both ecosystems and economies. The potential for rapid proliferation induces blockage of waterways, decreased biodiversity, degraded water quality, and reduced fishery and recreational values; it demands advanced monitoring and management techniques. Our research proposes a better approach for identification of water hyacinth growth stages with greater accuracy by applying the latest deep-learning models so as to take more stringent control measures. We enhanced our dataset by incorporating high-resolution images from diverse aquatic environments, including Kaikondrahalli Lake in bangalore and Anasagar Lake in Ajmer, adding to existing images sourced from Kaggle. Three pre-trained CNN models based on transfer learning, namely ResNet50, VGG16, and InceptionV3,have been taken into consideration and evaluated with great care for their efficacy in classification. Among them, InceptionV3outperformed, with training accuracy of 98.43% and testing accuracy of 99.80%. These models were further integrated into a custom SimpleCNN architecture improving the robustness in classification through Ensemble Learning. The performance obtained from the current study notably surpassed the benchmark accuracy of 86.2% set by Dyrmann et al. in their CNN-based multi-class classification study.

关键词： Training Deep learning Accuracy Invasive species biological system modeling Computational modeling Lakes benchmark testing Convolutional neural networks Residual neural networks

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Context-Aware Summarization for PDF Documents using Large Language Models

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

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Expert Clouds and Applications (ICOECA), International Conference on

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

ISBN: (数字)9798350385793

ISBN: (纸本)9798350385809

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.

关键词： Generative AI Databases Large language models Text summarization Portable document format Vectors Context modeling

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