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Improving predictive performance in e-learning through hybrid 2-tier feature selection and hyper parameter-optimized 3-tier ensemble modeling

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International Journal of Information Technology (Singapore) 2024年第8期16卷 5429-5456页

作者： Tirumanadham, N S Koti Mani Kumar S, Thaiyalnayaki M, Sriram Department of Computer Science and Engineering Bharath Institute of Higher Education and Research Department of Information Technology Bharath Institute of Higher Education and Research

The paper presents a new feature selection technique developed in detail here to address improved prediction accuracy not only for the machine-learning algorithm but also for student outcomes related to the learning environment. It is a feature selection methodology, combined with Ridge (L2) regularization and the Boruta optimization clubbed in a two-tier approach named as BR²-2 T, which results in the most effective feature set selection process. To be specific, the present study developed a three-tier ensemble model that consolidates Random Forest with Bayesian Optimization methods Support Vector Machine with random search, and Gradient Boosting with Particle Swam Optimization (PSO) for performing hyperparameter tuning. Some sophisticated techniques applied in this study are the use of Z-score normalization so as to standardize variable distribution, Synthetic Minority Over-sampling Technique (SMOTE) for handling imbalanced dataset and Multiple Imputation by Chained Equations (MICE) for handling messiness among items. The evaluation of the projected approach shows improvement in accuracies, which can attain a maximum of 98.74%. The comparative assessment of the proposed strategy unveiled that predictive modelling of educational outcomes is effectively enhanced more than common methods of topics related to education. The research sharpens student success strategies and educational pedagogy by using powerful algorithms in its direction of decision-making. © Bharati Vidyapeeth's institute of computer Applications and Management 2024.

关键词： Boruta optimization Ensemble model Gradient boosting L2 regularization Multiple imputation by chained equations (MICE) Random forest Support Vector Machine Synthetic minority over-sampling technique (SMOTE)

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Blockchain-Enabled Decentralized Trust Management and Secure Voting system 7

Blockchain-Enabled Decentralized Trust Management and Secure...

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7th International Conference on Circuit Power and computing Technologies, ICCPCT 2024

作者： Minu, R.I. Nagarajan, G. SRM Institute of Science and Technology Department of Computing Technologies Kattankulathur India Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350372816

In the era of digital transformation, trust and security are paramount in ensuring the integrity of various online transactions and processes, including voting systems. Traditional centralized trust management and voting systems have faced challenges related to security, transparency, and accountability. To address these issues, this research introduces a novel Blockchain-Enabled Decentralized Trust Management and Secure Voting System. It leverages blockchain technology, a decentralized and immutable ledger, to enhance trust, transparency, and security in trust management and voting processes. This system combines several key components, including smart contracts, cryptographic techniques, and distributed ledger technology, to create a robust and tamper-resistant infrastructure. In the trust management aspect, the proposed system employs a decentralized reputation system where individuals and entities can build trust through transparent and verifiable interactions. Smart contracts automate trust-building processes and provide a reliable mechanism for dispute resolution. This system allows for trust to be quantified and established in a trustless environment. The secure voting component introduces a tamper-proof and transparent voting system. Through the use of cryptographic keys and digital signatures, voters can securely cast their votes while ensuring anonymity and integrity. All voting transactions are recorded on the blockchain, providing a permanent and auditable record of the election process. Verification of election results becomes accessible to all stakeholders, enhancing transparency and trust in the electoral process. The Blockchain-Enabled Decentralized Trust Management and Secure Voting System represents a significant step towards enhancing trust and security in critical online processes, such as voting. By combining blockchain technology, cryptography, and decentralized trust mechanisms, it offers a promising solution to address the challenges associat

关键词： Decentralized finance

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Toward actionable testing of deep learning models

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science China(Information sciences) 2023年第7期66卷 300-302页

作者： Yingfei XIONG Yongqiang TIAN Yepang LIU Shing-Chi CHEUNG Key Laboratory of High Confidence Software Technologies(Peking University) Ministry of Education School of Computer Science Peking University Department of Computer Science and Engineering The Hong Kong University of Science and Technology School of Computer Science University of Waterloo Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Department of Computer Science and Engineering Southern University of Science and Technology

Deep learning has become an important computational paradigm in our daily lives with a wide range of applications,from authentication using facial recognition to autonomous driving in smart vehicles. The quality of the deep learning models, i.e., neural architectures with parameters trained over a dataset, is crucial to our daily living and economy.

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Gloss-Free Sign Language Translation using Sign2gpt-Next Technique

Gloss-Free Sign Language Translation using Sign2gpt-Next Tec...

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2024 International Conference on computing and Intelligent Reality Technologies, ICCIRT 2024

作者： Babisha, A. Umarani Srikanth, G. Angel Kiruba, D.R. Sundar, R. Department of Artificial Intelligence and Data Science Panimalar Engineering College Chennai India Department of Computer Science and Engineering Panimalar Engineering College Chennai India Department of Computer Science and Engineering DMI College of Engineering Chennai India Department of Computer Science and Engineering School of Computing Sathyabama Institute of Science and Technology Chennai India

ISBN: (纸本)9798331510299

This work proposes a new approach to convert the data from sign language to spoken language without exposing the data to a gloss layer. Whenever gloss annotations are used which frequently are incomplete and act as an intermediate representation, it is usually found to be a bottleneck in translating sign language videos. In order to avoid this, the authors use a combination of modern machine learning algorithms to arrive at the conclusion. They use Dino-V2 Vision Transformer to implement the function of extracting the spatial features of the input sign language video frames. This model is particularly suitable for learning and visual patterns in general and particularly for capturing fine details of these patterns. Further, a spatio-temporal transformer layer is added to automate the temporal processing of the Sign-Language which helps in the arrangement of the body gestures and limb movements needed at a specific temporal frame. It is then translated into the desired spoken language using a multilingual Generative Pre-trained Transformer (GPT) model. The approach can be said to be a big leap forward in sign language transliteration especially for such situations where few Gloss annotations are available, and making way for better and improved tools for the Deaf and the hard-of-hearing. © 2024 IEEE.

关键词： Audition

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Siamese capsule gorilla troops network-based multimodal sentiment analysis for car reviews

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Soft computing 2024年第13-14期28卷 7627-7647页

作者： Kothuri, Sri Raman RajaLakshmi, N.R. Department of Computer Science and Engineering School of Computing Vel Tech Rangarajan Dr. Sagunthala R & ampD Institute of Science and Technology Avadi Tamil Nadu Chennai600062 India

Sentiment analysis of online car reviews is a significant process in natural language processing. Numerous car enthusiasts and influencers create video reviews of automobiles on platforms for example YouTube. In realistic settings for sentiment analysis within this context, the task includes evaluating spoken reviews, the video content, and the emotions expressed by both the content creators and the viewers as reflected in the comments section. The vulnerability to facing circumstances in real-world scenarios where critical components are necessary for performing sentiment analysis on multimedia car reviews may unexpectedly be absent. To overcome this issue, siamese capsule gorilla troops network-based multimodal sentiment analysis for car reviews is proposed in this research work. Initially, pre-processing and feature extraction are performed on the audio, video and text information. The feature fusion is performed by enhancing spiking neural networks with geometric attention fusion network. The fused feature is fed as an input to siamese capsule gorilla troops network which classifies the emotion states as valence, arousal, and trustworthiness. Also, the algorithm called gorilla troop optimization (GTO) optimizes the classification error of the proposed siamese capsule network. Finally, this research work assesses high- and low-level features across modalities, introduces a novel enhancing spiking neural networks with geometric attention fusion network, enhances classification accuracy through new audio, video, and text embeddings, and boosts system robustness by integrating incomplete multimodal data. The achieved accuracy, precision, recall, and F-score values are 99%, 98.55%, 98.75%, and 98.02%, respectively, for the active multimodal sentimental analysis in car review (MuSe-CaR) dataset. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Sentiment analysis

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STPM: Spatial-Temporal Token Pruning and Merging for Complex Activity Recognition

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IEEE Transactions on Circuits and Systems for Video Technology 2024年第6期35卷 5407-5418页

作者： Su, Yumeng Zhang, Jiachao Yan, Rui Li, Pengpeng Xie, Guosen Shu, Xiangbo Nanjing University of Science and Technology School of Computer Science and Engineering Nanjing210094 China Nanjing Institute of Technology Artificial Intelligence Industrial Technology Research Institute Nanjing211167 China Nanjing University Department of Computer Science and Technology Nanjing210023 China

Lightweight video representation techniques have advanced significantly for simple activity recognition, but they still encounter several issues when applied to complex activity recognition: (i) The presence of numerous individuals and varying spatial positions makes it difficult for traditional token pruning methods to maintain accuracy. (ii) Simply discarding entire frames may result in the loss of crucial clues. (iii) To maintain parallel computing, applying the same pruning rate to every frame leads to significant redundancy in frames with low information content. To this end, we propose a lightweight and novel Spatial-Temporal Token Pruning and Merging (STPM) framework, specifically designed for complex action videos where human actors occupy a small spatial resolution within video frames. Our framework considers two critical factors: semantic importance and spatial-temporal redundancy, to further reduce overhead. For semantic importance, STPM captures class-specific attention scores by learning multiple class tokens within the transformer to guide token pruning. For spatial-temporal redundancy, STPM employs an anchor graph and temporal attention to perform spatial and temporal token merging, preserving appearance and temporal cues while eliminating semantic duplication and redundancy. We conduct extensive experiments on JRDB-PAR primarily using recently introduced video transformer backbones, e.g., MViT and ViT. Our framework achieves similar results while requiring 40% less computation. © 1991-2012 IEEE.

关键词： Economic and social effects

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Efficacious Routing Approaches in Vehicular Ad hoc Network: An Empirical Study 1

Efficacious Routing Approaches in Vehicular Ad hoc Network: ...

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1st International Conference on Advances in Electrical, Electronics and Computational Intelligence, ICAEECI 2023

作者： Janet Kumari, J Jesy Thangam, S. Raja, A. Saleem Amrita Vishwa Vidhyapeetham Amrita School of Computing Bengaluru Department of Computer Science and Engineering India University of Technology and Applied Science-Shinas Department of Computer Science and Engineering Oman

ISBN: (纸本)9798350342796

VANET, or Vehicular Ad hoc Network is a transient wireless structure made up of different kinds of vehicles serving as network hubs and the links between them acting as links. VANET is an improving mechanism that has received an amount of growth in the fields of research, academia, and business. A VANET is a mobile network that uses vehicles as terminals. VANETs, similar to spontaneous systems, possess all the main features of independent connectivity, including processing and preservation constraints. To improve safety while driving and other services, a network of VANETs can be established. The effectiveness of VANETs has been demonstrated in numerous real-world applications, such as traffic management and driver-assist systems. Information exchanged over VANETs can undoubtedly help users experience a better driving experience and prevent accidents. academia, and government. VANET is an acronym used to describe the Vehicular ad hoc network that forms over-moving vehicles on the road. Vehicle networks are rapidly emerging as a platform for creating and implementing new and classic applications. VANETs are distinguished by their high mobility, frequently changing topology, and ephemeral, one-time connections. Vehicle interruptions are common due to how dynamic and moving vehicles are at present. Clustering techniques for vehicles that arrange to increase network scalability and connection dependability as VANET introduces vehicles in groups. Subsequently, other clustering strategies and techniques also exist, and it is necessary for a wide range of situations, including information transfer, routing, and detection of accidents. The methods used for vehicle clustering techniques are examined in this study in terms of networking techniques. © 2023 IEEE.

关键词： ant colony optimization hybrid protocol proactive reactive VANET

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Secure Channel Estimation Using Norm Estimation Model for 5G Next Generation Wireless Networks

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computers, Materials & Continua 2025年第1期82卷 1151-1169页

作者： Khalil Ullah Song Jian Muhammad Naeem Ul Hassan Suliman Khan Mohammad Babar Arshad Ahmad Shafiq Ahmad Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming650500China Department of Computer Science Abbottabad University of Science and TechnologyHavelianAbbottabad22500Pakistan Department of Computing and Electronics Engineering Middle East CollegeMuscat124Oman Department of CS&IT Pak-Austria Fachhochschule Institute of Applied Sciences and Technology MangHaripur22621Pakistan Industrial Engineering Department College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia

The emergence of next generation networks(NextG),including 5G and beyond,is reshaping the technological landscape of cellular and mobile *** networks are sufficiently scaled to interconnect billions of users and *** in academia and industry are focusing on technological advancements to achieve highspeed transmission,cell planning,and latency reduction to facilitate emerging applications such as virtual reality,the metaverse,smart cities,smart health,and autonomous *** continuously improves its network functionality to support these *** input multiple output(MIMO)technology offers spectral efficiency,dependability,and overall performance in *** article proposes a secure channel estimation technique in MIMO topology using a norm-estimation model to provide comprehensive insights into protecting NextG network components against adversarial *** technique aims to create long-lasting and secure NextG networks using this extended *** viability of MIMO applications and modern AI-driven methodologies to combat cybersecurity threats are explored in this ***,the proposed model demonstrates high performance in terms of reliability and accuracy,with a 20%reduction in the MalOut-RealOut-Diff metric compared to existing state-of-the-art techniques.

关键词： Next generation networks massive mimo communication network artificial intelligence 5G adversarial attacks channel estimation information security

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Envisaging the patterns in Blockchain 7

Envisaging the patterns in Blockchain

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7th International Conference on Circuit Power and computing Technologies, ICCPCT 2024

作者： Nagarajan, G. Atmakuri, Sukeerth Nalamati, Sri Satyendra Minu, R.I. Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Chennai India SRM Institute of Science and Technology Department of Computing Technologies Kattankulathur India

ISBN: (纸本)9798350372816

Cryptocurrency is becoming more mainstream, and experts predict that its market size will reach dollar 2.2 trillion by 2026. However, it's also an intangible and highly volatile asset that poses significant challenges for governments, anti-money laundering analysts, and financial crime investigators. Compliance with strict regulations is also a challenge facing virtual asset service providers. The price of Bitcoin hit an all-time high in January 2021, making headlines worldwide. As the popularity of cryptocurrency continues to grow, AML analysts and financial crime investigators face tougher challenges. VASPs are under pressure to comply with tighter regulations, and both parties need to take a proactive approach. Bitcoin visualization is a solution that involves visualizing a Bitcoin block, enabling analysts to clarify complex and dense blocks of transaction data quickly to identify high-risk activity. Instead of looking at historic Bitcoin transactions, analysts can now examine Bitcoin activity in real-time using a powerful Bitcoin network visualization chart showing key connections, combined with a dedicated Bitcoin timeline view featuring precise transaction details as they occur. We conducted a thorough and quantitative assessment of 76 analytics tools, including those proposed in academic research and those endorsed by professionals and blockchain enthusiasts online, to provide a comprehensive analysis of the facets of blockchain data that have been thoroughly investigated. We also identified areas that warrant further exploration in future research. © 2024 IEEE.

关键词： Blockchain Blockchain tools Data parsing Data Visualization Graph Modelling Graph-based analysis

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Elderly Care: Elderly Well-Being Through Volunteer Engagement 4

Elderly Care: Elderly Well-Being Through Volunteer Engagemen...

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4th IEEE International Conference on ICT in Business Industry and Government, ICTBIG 2024

作者： Somani, Vedant Nandi, Trideep Gupta, Priyansh Sethi, Kamal Kumar Acropolis Institute of Technology and Research Computer Science and Engineering Department Indore India

ISBN: (纸本)9798331518981

The growing need to support the well-being of elderly individuals has led to the development of a comprehensive Elderly Care system that leverages volunteer and caretaker involvement. To address the challenges faced by the elderly, the system is designed with three key modules: Elders, Caretakers, and Community Members. It offers critical features such as emergency assistance (SOS), medication reminders, volunteer scheduling, and real-time updates to family members. By focusing on user-friendly design and efficient user experiences, the system ensures that the health and safety of elderly individuals are prioritized. Moreover, it fosters community engagement through a volunteer reward mechanism, encouraging sustained involvement. Evaluation of the system highlights its effectiveness in providing timely interventions and consistent monitoring, significantly enhancing the quality of elderly care. Future enhancements aim to extend its capabilities and scalability, ensuring broader impact and adaptability to the growing needs of elderly care. © 2024 IEEE.

关键词： Caregiver Community care Elderly Care Exercise recommendations Health monitoring Medication alerts Social engagement SOS Volunteer Support

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