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检索条件"机构=Department of Computer Science Technology and Computer Science"

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A Novel Content-based Approach for Fake News Detection using Transformer Model: A Case Study of Covid-19 Dataset 10

A Novel Content-based Approach for Fake News Detection using...

引用

10th International Conference on Web Research, ICWR 2024

作者： Bahmanyar, Razieh Miyaneh, Eynollah Khanjari Iran University of Science and Technology Department of Computer Engineering Tehran Iran

ISBN: (纸本)9798350394986

According to the number of users on social media platforms and the number of followers of published content, Fake news in social media could adversely affect society and governments. In this paper, a new approach to Fake news detection is presented. Our approach is to provide a hybrid model in order to incorporate different types of features each of which is extracted by the corresponding component in the model. A transformer model generates the input of each component, namely sentiment analysis, hate speech detection, and topic modeling. Thereafter, a combination of hidden layers is performed through concatenation, which is then fed into the final classifier used for fake news prediction. We evaluated the proposed model by collecting 2500 Persian data (related to COVID-19) from the social networks complemented by various preprocessing tasks. The results demonstrate a higher accuracy (87%) for the proposed approach compared to the standard baselines. © 2024 IEEE.

关键词： Sentiment analysis

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Comparative Study of Ensemble Stacking Method for Neurodegenarative Disease Classification 11

Comparative Study of Ensemble Stacking Method for Neurodegen...

引用

11th International Conference on Soft Computing and Machine Intelligence, ISCMI 2024

作者： Raseena, P.A. Deepika, M.P. Sabu, M.K. Cochin University of Science And Technology Department of Computer Applications Cochin India

ISBN: (纸本)9798331518127

Neurodegenerative diseases present a current challenge in the accuracy of the diagnosis. Alzheimer's and Parkinson's disease take a number of years to accurately define the growth of the disease. Neural networks are very efficient algorithm to handle the image data. This paper proposes an ensemble stacking method for the classification of Alzheimer's, Parkinson's, and Normal using MRI images. And also compare the performance with other neural networks such as deep neural networks, convolutional neural networks, and VGG16. The proposed model got a better accuracy of 94% than other neural network models. © 2024 IEEE.

关键词： Convolutional neural networks

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Automatic Detection of Diabetic Retinopathy Using CNN and SVM 2

Automatic Detection of Diabetic Retinopathy Using CNN and SV...

引用

2nd IEEE International Conference on Advances in Information technology, ICAIT 2024

作者： Anser Pasha, C.A. Bhargav, K.S. Akki, Ratan Sanath, R. Vismitha, V. Computer Science and Engineering Department Adichunchanagiri Institute of Technology Chikkamagluru India

ISBN: (纸本)9798350383867

Diabetic retinopathy is an eye disease caused by high sugar levels in blood, leaving the retina damaged. Retina is the part of the eye that detects the light and passes electrical signals to the brain. The optic nerve which connects retina and the brain helps the brain form the image of the objects that we see. Out of 5 diabetic patients, one suffers from diabetic retinopathy. Depending on the level of damage caused to retina, the diagnosed person can go through mild vision loss to total vision lost. Adopting automatic detection of diabetic retinopathy helps early diagnosis and reduce burden on the ophthalmologists enabling them to concentrate on higher priority cases. This paper discusses how CNN and SVM can be used to detect diabetic retinopathy with image processing concepts. ©2024 IEEE.

关键词： Ophthalmology

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DL-Based Somnolence Detection for Improved Driver Safety and Alertness Monitoring 5

DL-Based Somnolence Detection for Improved Driver Safety and...

引用

5th IEEE International Conference on Computing, Power, and Communication Technologies, IC2PCT 2024

作者： Neeraja, Peddinti. Kumar, R.G. Kumar, M. Sunil Liyakat, Kazi Kutubuddin Sayyad Vani, M. Sowmya School of Computing Department of Computer Application AP Tirupathi India Siddharth Institute of Engineering & Technology Computer Science and Engineering AP Puttur India School of Computing Department of Computer Science and Engineering AP Tirupathi India Brahmdevdada Mane Institute of Technology Department of Computer Science and Engineering Maharashtra Solapur India

ISBN: (纸本)9798350383522

This abstract explores the utilization of deep learning for detecting driver somnolence, aiming to enhance driver safety and alertness monitoring. It investigates the integration of computer vision, physiological signals, and machine learning algorithms. Key considerations include real-time detection, accuracy, scalability, and driver intervention mechanisms. By leveraging deep learning techniques, effective driver somnolence detection systems can contribute to preventing accidents and promoting safer roads. © 2024 IEEE.

关键词： Convolution neural network deep learning Drowsiness detection transfer learning

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CyberCure - Malware Defense System 4

CyberCure - Malware Defense System

引用

4th International Conference on Innovations in computer science, ICONICS 2024

作者： Shahid, Sardar Zohair Bangash, Muhammad Anas Hussain, Muhammad Rayyan Arshad, Saadia NED University Computer Science and Information Technology Department Karachi Pakistan

ISBN: (纸本)9798331504342

In today's world, the rise of cyber threats highlights the need for solutions that protect sensitive information and uphold system integrity. CyberCure, that is Pakistan's first malware defense system, is designed to meet the demands of cybersecurity by employing a comprehensive and adaptable approach to computer security. With the use of machine learning algorithms, signature based detection, and behavioral analysis, CyberCure offers a powerful defense that responds to both new and emerging threats. CyberCure offers an array of protective features, including four types of scans: quick scan, deep scan, removable device scan, and directory scan. Each scan type is specifically tailored to address different security needs, allowing users to select the proper level of analysis based on the perceived threat or the depth of investigation needed. Along With these scan options is a quarantine feature that safely isolates suspicious files, giving users the ability to remove, recover, or allow files based on a personalized risk assessment. Designed with a simple interface, users of all technical backgrounds can manage their security settings without sacrificing system performance. By improving resource usage, the software minimizes system slowdowns, allowing for a seamless balance between robust protection and everyday functionality. This paper presents CyberCure as a potential meaningful change in strengthening cybersecurity defenses, both within Pakistan and beyond. Its design and features position it as a reliable and effective antivirus solution capable of addressing the growing challenges posed by cyber threats. The insights offered here contribute to the broader conversation around developing advanced antivirus systems that can continuously adapt to the ever-changing landscape of cybersecurity, ensuring the safety of digital assets. © 2024 IEEE.

关键词： Cyber attacks

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Secure User Authentication with Secret Sharing and Smart Contract for Permissioned Blockchain 13

Secure User Authentication with Secret Sharing and Smart Con...

引用

13th IEEE Global Conference on Consumer Electronic, GCCE 2024

作者： Okada, Masamune Mohd Kamal, Ahmad Akmal Aminuddin Fujisawa, Masaya Tokyo University of Science Department of Information and Computer Technology Tokyo Japan

ISBN: (纸本)9798350355079

Blockchains (BCs) have garnered attention owing to their potential applications in a wide range of fields, including finance and the Internet of Things. Nakajima et al. introduced a secure and decentralized storage system using a permissioned BC and secret sharing. However, this method employs conventional password-based user authentication with a single SDK server. In this study, we introduce a secure and decentralized user authentication system that employs secure computation based on Shamir's (2,2) threshold secret sharing and smart contracts. We demonstrate that employing secure computation using secret sharing facilitates user authentication while maintaining the confidentiality of the original password. Furthermore, we show that even if the information registered on the SDK server is known, an attacker will not be able to recover the original password. © 2024 IEEE.

关键词： Authentication Protocol

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Lightweight and High-Accuracy Facial Landmark Detection Network by Applying Artificial Intelligence 1

引用

8th International Conference on Information System Design and Intelligent Applications, ISDIA 2024

作者： Eishah, Hassan Abu Haseebuddin, Mohammad Masih, Raj Kumar Ahmad, Yasir Khamruddin, Mohammad Hossain, Mohammad Alamgir Department of Computer Science College of Engineering & Computer Science Jazan University Jazan Saudi Arabia

ISBN: (数字)9789819765812

ISBN: (纸本)9789819765805

Facial emotion recognition (FER) for tracking and authentication has become a hot topic due to the rapid development of AI and its widespread application. Many different scenarios could benefit from portable facial recognition technology. However, due to limits in size, weight, power source, and notably computing capability, current lightweight mobile phones struggle to meet the accuracy and real-time needs of face recognition monitoring. Thus, issues like face identification monitoring and lightweight implementation are crucial and need fixing quickly. In response to this issue, this paper presents Tiny-HRN+, a lightweight facial recognition method. By plummeting the quantity of parameters and the volume of processing needed, the model is made easier to construct with the help of FN's partial convolution technique. In order to satisfy the demand for high-precision recognition, it employs a parameter-free attention strategy that boosts the model's recognition accuracy by increasing its complexity. We have added a dynamic prediction head to the model to improve its predictive skills, allowing it to better fulfill the needs of detection performance. This has been empirically proven using the freely accessible Wider-Face (WF) dataset. The proposed face recognition method in this paper demonstrates clear lightweight benefits, including the provided variable and calculation loads, the model size of 9.1 MB, an accuracy of 91.15%, and an FPS of 68, and visual verification of the outcomes of detection reveals a noticeably better efficiency compared to other models. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Convolution

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Overview of Emerging Biological Computational Framework for Olfactory Studies Utilizing Contextual Technobiomedical Engineering 2

Overview of Emerging Biological Computational Framework for ...

引用

2nd DMIHER International Conference on Artificial Intelligence in Healthcare, Education and Industry, IDICAIEI 2024

作者： Chaudhri, Shiv Nath Faculty of Engineering & Technology Department of Computer Science and Design Wardha India

ISBN: (纸本)9798331528713

Organoid intelligence (OI), the next paradigm of intelligence, draws inspiration from the biological learning of organs. On the other hand, artificial intelligence (AI) draws its inspiration only from the cognitive processes of the brain. While taking ethical and technological limitations into account, biological learning helps to conceptualize, accept, and apply them. Just as AI helped to make supercomputers possible, OI may help create biocomputers. Even though AI has increased the capabilities of technology to unimaginable heights, it still appears immature and is steadily moving toward cognitive computing to push the envelope even farther. In contrast to AI, OI is a new multidisciplinary computer area that attempts to be more approachable. OI has the ability to produce novel biocomputers, such as organoids, that use parts derived from live organisms to perform computational tasks. Organoids, such as human nasal organoids, are microscopic tissue cultures made from stem cells that mimic some of the functions of real organs. Although they have been used for many different purposes, including drug discovery and illness modeling, scientists are only now beginning to explore their potential for biological information processing. © 2024 IEEE.

关键词： Artificial Intelligence (AI) Biological Information Processing Biological Learning Olfactory Organoids Organoid Intelligence (OI)

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Mindful Meadows: A Mental Health App 8

Mindful Meadows: A Mental Health App

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8th IEEE International Conference on Computing, Communication, Control and Automation, ICCUBEA 2024

作者： Gaikwad, Aryan Nimbolkar, Gayatri Keswani, Roshani Kolhe, Vaishnavi Navale, Geeta.S. Sinhgad Institute of Technology and Science Department of Computer Engineering Pune India

ISBN: (纸本)9798350391770

This paper presents 'Mindful Meadows,' a Flutter-based mobile application designed as an all-inclusive platform for mental health support and wellness. The app uniquely combines various mental health functionalities into a singular, user-friendly interface, eliminating the need for multiple disparate applications. It addresses the diverse needs of individuals seeking mental well-being support. Firstly, it offers specialized tests for different mental conditions, aiding users in self-assessment and awareness. These tests are complemented by a history tracking feature for monitoring mental health progress over time. Another significant component is the inclusion of a serene and soothing music library, curated to promote relaxation and stress relief. Additionally, the app introduces a mental yoga section, providing guided practices aimed at enhancing mental resilience and mindfulness. For community support and interaction, "Mindful Meadows"incorporates a community chat feature, enabling users to connect with others experiencing similar mental health challenges. The app also integrates a responsive chatbot for immediate assistance and guidance. In its commitment to comprehensive care, "Mindful Meadows"offers a unique feature for consulting with therapists. This includes a seamless appointment booking system, facilitating easy access to professional help. Overall, "Mindful Meadow"emerges as a pioneering solution in mental health technology, intertwining professional care, community support, and cutting-edge technology to promote optimal mental wellness. © 2024 IEEE.

关键词： Stress relief

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Industrialized Implementation of Agile Methodology 1

Industrialized Implementation of Agile Methodology

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1st IEEE International Conference on Advances in Computing, Communication and Networking, ICAC2N 2024

作者： Singh, Meeta Nandal, Poonam Bura, Deepa Jindal, Srishty School of Engineering and Technology Department of Computer Science and Engineering Faridabad India

ISBN: (纸本)9798350356816

This paper introduces a guide aimed at aligning academic learning with industry standards in Agile methodology and Scrum framework usage. Targeting students, educators, and industry practitioners, it addresses the prevalent gap between theoretical knowledge and practical *** with an overview of Agile's iterative approach, it delves into Scrum's key elements: sprint planning, daily stand-ups, reviews, and retrospectives. It acknowledges the disconnect between academic curricula and industry demands, especially in Agile contexts. © 2024 IEEE.

关键词： Agile manufacturing systems

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