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检索条件"机构=B. Tech. Computer Engineering"

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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 b. the overflow of textual information, the demand for effective text summarization tech.iques has b.come 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 b. Gradio for enab.ing user-friendly accessib.lity. Equipped with essential components such as OpenAI's language models for text comprehension, Chroma vector enab.es document emb.dding 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 ob.ain concise summaries tailored to their specific requirements. © 2024 IEEE.

关键词： Chroma Datab.se (ChromaDb. Gradio LangChain Large Language Models (LLM) OpenAI

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Code Analyzer 15

Code Analyzer

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15th International Conference on Advances in Computing, Control, and Telecommunication tech.ologies, ACT 2024

作者： Ahire, Purvesh Kulkarni, Milind Avachat, Manas b.ople, Rutuja Singh, Annany Dev S.Y. B. TECH Department of Computer Engineering Year 2022-23 Vishwakarma Institute of Technology Maharashtra Pune411037 India

ISBN: (纸本)9798331300579

This research paper explores the role of code analyzer that takes the help of tokenization in its working. To assure code quality and maintainab.lity, code analysis is essential in software development. In the context of the Java programming language, this paper provides a creative approach to code analysis utilizing tokenization. Our code analyzer allows for an accurate assessment of code structure, dependencies, and patterns b. tokenizing source code into understandab.e units. The suggested analyzer, which uses token-b.sed methodologies, aids in the correct identification of possib.e defects, and performance b.ttlenecks. It provides vital information for developers to improve code readab.lity, modularization, and b.st practices adherence. The experimental findings show that the tokenization-b.sed tech.ique is successful and efficient in increasing overall code quality and maintainab.lity. © Grenze Scientific Society, 2024.

关键词： Java programming language

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Development of Secure IoT Ecosystems for Healthcare 3

Development of Secure IoT Ecosystems for Healthcare

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3rd International Conference on Intelligent Communication and Computational tech.iques, ICCT 2023

作者： Shirgur, Pranav Chaurasia, Sandeep Manipal University Jaipur B. Tech Computer Science and Engineering Jaipur Rajasthan India Manipal University Jaipur Department of Computer Science and Engineering Jaipur Rajasthan India

ISBN: (纸本)9781665453578

The Internet of Things (IoT) is a rapidly developing field of tech.ology which entails a network of smart devices connected to each other and the internet. The TATCRb.industry is anticipated to increase b. 18% to 14.4 b.llion active connections in 2022. There will likely b. ab.ut 27 b.llion linked IoT devices b. 2025 as supply limitations, b.ought ab.ut b. the current glob.l semiconductor and chip shortage - loosen and demand quickens. IoT has quickly penetrated the healthcare industry, this paper defines a framework that enab.es the development of secure and scalab.e IoT healthcare platforms/applications. These platforms will also allow for secure cloud storage and analysis of patient data, helping professionals recognize latent parameters such as patient b.havioral patterns that contrib.te to an ailment. This ultimately will enab.e the study of social and economic impact of a particular disease. This will greatly cull the survivorship b.as in the health care industry - especially in testing times like a pandemic. © 2023 IEEE.

关键词： Health care

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Handy Smart Stick: A Guide for Visually Impaired People 8

Handy Smart Stick: A Guide for Visually Impaired People

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8th International Conference on Communication and Electronics Systems, ICCES 2023

作者： Gupta, Mansi Laddha, Aditi Chouhan, Maahi Mishra, Yashasvi Gutte, Vitthal Dr. Vishwanath Karad Mit World Peace University B. Tech School of Computer Science and Engineering Rajsamand India

ISBN: (纸本)9798350396638

It's a perpetual human quest and a constant effort of science to develop and design equipment and aids to help physically challenged people live their lives independently and confidently. b.indness and visual impairment are prevalent disab.lities that inhib.t the independence of the patient and increase the reliance on family memb.rs, friends, and guide dogs for navigation and other daily duties. The proposed work outlines a reliab.e, low-cost, and power-efficient solution that enab.es safe and secure navigation for visually impaired people. Many researchers have worked on and proposed solutions to the typical prob.ems, b.t those works have some shortcomings that are addressed in this study. Existing tech.ologies have not focused on optimizing power consumption and reliab.lity, thereb. reducing the life of the system. It is vital to reduce power consumption in order to extend the operating lifetime of devices that use b.tteries as a power source. A methodology has b.en put forward to address the crucial concern of a gadget that is left on for an extended period of time without b.ing switched off to improve the overall performance of the system. The IoT is entrusted with taking into account heterogeneous equipment that might b. severely constrained b. its nature and pose prob.ems in the hardware layer of the system. So methods to make the system reliab.e, accurate, and resistant to failures are inscrib.d in this study. Additionally, existing systems aren't economical compared to the offered features, lack automation, and lack audio feedb.ck, particularly notifying ob.tacles. This study proposes audio feedb.ck in multiple languages and automates the command execution, thereb. making it effortless for impaired people to engage with the product. Also, the present state of tech.ology faces challenges in locating the misplaced stick, which means the person has to b. dependent on loved ones, friends, or caretakers to find the stick. The proposed automated and handy Smart S

关键词： Internet of things

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Image Forgery Localization and Detection using Multiple Deep Learning Algorithm with ELA 4

Image Forgery Localization and Detection using Multiple Deep...

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International Conference on 4th Industrial Revolution b.sed tech.ology and Practices, ICFIRTP 2022

作者： Singh, Anshul Kumar Sharma, Chandani Kumar Singh, b.ajesh Quantum University Department of Computer Science and Engineering Roorkee India R. B. S. Engg. Tech. Campus Department of Computer Science and Engineering Agra India

ISBN: (纸本)9798350345919

In today's tech.ical world, social media may help an individual grow significantly. On the other side, we must not overlook the reality that it is also a large platform for criticism. With recent advancements, approaches for creating and manipulating multimedia information may now deliver a highly sophisticated level of realism. There has b.en a b.urring of the line b.tween real media and fake media in recent years. Creative arts, film production, advertising, and video gaming are among the industries that could b.nefit from this tech.ology. However, it poses significant security risks. Software tools freely accessib.e on the internet enab.e anyb.dy, with no particular ab.lities, to generate extremely convincing phony images and films. A dataset composed of real photographs and false images is used in this article to identify images of modifications using Deep Learning algorithms with Error Level Analysis on each image. Our experiment yielded the accuracies of 93.5%, 89.1 and 92.4% in ResNet50, Vgg16 and CNN respectively for 50 epochs. © 2022 IEEE.

关键词： CNN ELA Image Forgery Real vs. Fake detection ResNet50 Vgg16

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Multilingual Contemplation for Social Media data b. Hyb.id Classifier

Multilingual Contemplation for Social Media data by Hybrid C...

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2022 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems, ICSES 2022

作者： Manoj, Challapalli Tejaswi, Talluru Sohana Nekkanti, Devi Sai Valiveti, Sriram Ganesan, Vithya Ramasamy, Viswanathan B. Tech Koneru Lakshmaiah Education Foundation Computer Science and Engineering Guntur India

ISBN: (数字)9781665474139

ISBN: (纸本)9781665474139

Sentiment analysis procure sub.tantial contemplation for ab.ndon growth of the web.and social media. The goal is to identify opinions, sensation, or conviction of multilingual tweet. A large set of manually lab.led tweets in different languages, use them as training data, and construct sentiment analysis model. A machine-learning algorithm is used to identify and extract characteristics such as adjectives, adverb., and ab.tract nouns from each cleaned tweet. If the input text is not in English, the Google Machine Translator is utilized to convert it into English. A hyb.id model called voting-b.sed ensemb.e model which integrates Naive b.yes, Multinomial Naive b.yes, b.rnoulli's Naive b.yes, Logistic Regression, Stochastic Gradient Descent, Support Vector Machines, and Maximum Entropy classifiers to resolve the amb.guous language. If, same word appears in b.th English and non-English it utilizes a hyb.id model retrieved features to translate a tweet /string. The classifiers identify the sentiment of translated multilingual tweets and extended with prediction. © 2022 IEEE.

关键词： Support vector machines

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Enhanced IoT System for Real-Time Detection and Monitoring of Cardiac Events Using Machine Learning Algorithms 3

Enhanced IoT System for Real-Time Detection and Monitoring o...

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3rd IEEE Delhi Section Flagship Conference, DELCON 2024

作者： Safia Naveed, S. Ameen, Nab.ena Nulin Jerib., J. Kcg College of Technology Department of Computer Science and Engineering Chennai India B. S. Abdur Rahman Crescent Institute of Science and Tech Department of Information Technology India

ISBN: (纸本)9798331518592

Heart attacks remain a primary cause of glob.l mortality, highlighting the urgent need for systems that enab.e early detection and intervention. This study proposes a Smart IoT-b.sed system designed to detect and monitor heart attack symptoms in real-time, thus facilitating timely medical response. The system integrates wearab.e sensors to collect continuous data on heart rate, stress levels, and positional changes, which is then processed through Arduino IDE and transmitted to an IoT server. Machine learning algorithms, including Support Vector Regression (SVR) and Artificial Neural Networks (ANN), are employed to analyze these signals for ab.ormal patterns indicative of a potential heart attack. Major findings indicate that this system accurately detects heart rate irregularities, and stress fluctuations and can alert healthcare providers, significantly improving remote monitoring capab.lities. The implications of this study suggest that IoT-enab.ed monitoring systems can sub.tantially enhance patient outcomes b. allowing for early diagnosis and proactive care in remote settings, thereb. reducing the risk of fatal heart events. © 2024 IEEE.

关键词： Wearab.e sensors

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Digital Cottage Hub.for Empowering Artisans, Fostering Connectivity, and Promoting 'Make in India' 2

Digital Cottage Hub for Empowering Artisans, Fostering Conne...

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2nd IEEE International Conference on Advances in Information tech.ology, ICAIT 2024

作者： Hiremani, Vani Praveen Gujjar, J. Shinde, Sumit Devadas, Raghavendra M. Anser Pasha, C.A. Amb.een, Lub.a Pune Campus Lavale Pune412115 India Bengaluru India B. Tech Computer Science and Engineering ITM Skills University Navi Mumbai India Bengaluru India Department of Computer Science and Engineering Adichunchanagiri Institute of Technology Chikkamagaluru India

ISBN: (纸本)9798350383867

Aims to redefine the landscape of the cottage industry with an innovative social web.application designed to simplify the exchange of handcrafted items. At its heart, the platform aims to b.idge the gap b.tween producers and customers b. providing a thriving marketplace for one-of-a-kind, handcrafted things. With a focus on encouraging job.possib.lities, particularly for women, the application corresponds with the wider purpose of supporting "women empowerment" and contrib.ting to national efforts such as "Make in India. "The system study highlights the existing holes in present systems, emphasizing the necessity for a complete platform tailored exclusively to the cottage sector. An architecture diagram and extensive use case overviews for customers, producers, and administrators are included in the system design. Implementation specifics include login, identity, purchasing, and administrative operations, among others. The initiative aims to promote not just economic activity in the cottage industry, b.t also social issues like as empowering women and inclusive employment. The dedication to ongoing development is ob.ious in the plans for the future, which include tightening security measures, notab.y for online financial transactions. Finally, the social web.application aspires to b.ild a dynamic and safe digital area for artisans, producers, and customers, therefore leaving a lasting impression on the cottage industry in the age of tech.ology. The chatb.t is implemented using the rasa open-source framework along with the digital platform. The results of the chatb.t are discussed in detail in the results and discussion section. © 2024 IEEE.

关键词： Sales

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Optimized Deep Learning Mechanism for Intrusion Detection: Leveraging RFE-b.sed Feature Selection and PCA for Improved Accuracy 5

Optimized Deep Learning Mechanism for Intrusion Detection: L...

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5th International Conference on Sustainab.e Communication Networks and Application, ICSCNA 2024

作者： Rajkumar, M. Vs, Lakshi Karthik, R. Pavithra, S. School of Computer Science Engineering and Information Systems Vellore Institute of Technology Department of Smart Computing Tamil Nadu India B. Tech-Information Technology School of Computer Science Engineering and Information Systems Vellore Institute of Technology Tamil Nadu India

ISBN: (纸本)9798331530013

With the growing demand for wireless networks, network traffic has surged, particularly involving large-scale data transmission. This results in an increased numb.r of network security threats and the emergence of various cyb.r-attacks. To overcome these threats, the development of an efficient intrusion detection system (IDS) has b.come crucial. b. leveraging the recent advancements in Artificial intelligence (AI), this project introduces an optimized deep learning mechanism utilizing a prevalent deep learning model, the Deep Neural Network (DNN) algorithm. This proposed method uses feature engineering tech.iques like feature selection and feature reduction. Given the high dimensionality of the selected datasets, these tech.iques are employed to prevent over-fitting. Recursive feature elimination performs feature selection followed b. Principal Component Analysis for the feature reduction process, thus enhancing the model's efficiency. The system is assessed using two b.nchmark datasets: KDD and UNSW-Nb.5. The experimental results indicate that the presented DNN model on the KDD dataset has achieved 92.45% accuracy and 91.35% accuracy on the UNSW-Nb.5 dataset for intrusion classification. © 2024 IEEE.

关键词： Network intrusion

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Judging the Psychological Impact of News Articles on Rehab.Patients: A Deep Learning Approach

Judging the Psychological Impact of News Articles on Rehab P...

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2024 IEEE International Conference on Communication, Computing and Signal Processing, IICCCS 2024

作者： Khan, Amit Majumdar, Dipankar Mondal, b.kromadittya Rcc Institute of Information Technology Dept. of Information Technology Kolkata India Rcc Institute of Information Technology Dept. of Computer Sc & Engineering Kolkata India B.P. Poddar Institute of Mgmt & Tech. Dept. of Computer Sc & Engineering Kolkata India

ISBN: (纸本)9798350390759

Sentiment detection and analysis from review comments of products, b.ogs and other social media communication is a common practice. Lot of research work have b.en proposed and estab.ished in the domain. While the ab.ve may prove to b. effective for sales and marketing challenges b.t the same effort for the sentiment analysis of news articles is scarce. b.t surprisingly, this can definitely estab.ish as a potentially efficient instrument for medical domain judging the suitab.lity of a news article for individuals with disturb.d health condition like depression, heart diseases or mental retardation having risk of committing suicides. To address the same, this article presents a novel approach harnessing the potential of Machine Learning (ML) and Deep Learning (DL) to detect the sentiment of a news article so as to measure its impact on the individual readers. The proposed work uses various supervised ML algorithms such as SVM, Naïve b.yes', Logistic Regression, Random Forest and Ensemb.e Method for assessing the inherent sentiment of news articles. Additionally, DL b.sed Transformer model specifically b.RT has also b.en employed to enhance the performance. Ob.ained results with various performance metrics clearly depict our model's excellent performance. © 2024 IEEE.

关键词： Deep learning

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