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Marine Life Analysis Based on Ocean Water Level Rise and Climate Change Using Underwater Imaging Techniques

Remote Sensing in Earth Systems sciences 2024年第4期7卷 657-669页

作者： Mate, Anuja Dinesh Arulananth, T.S. Sathiya, T. Jyothi, B. Swarna Raja, A. Wasim Yalawar, Mrutyunjaya S. Computer Technology Sou.Venutai Chavan Polytechnic Pune India Department of Electronics and Communication Engineering MLR Institute of Technology Telangana Hyderabad 500043 India Department of Computer Science and Engineering Sona College of Technology Tamil Nadu Salem India Computer Science & amp Engineering Madanapalle Institute of Technology & amp Science Andhra Pradesh Madanapalle India Artificial Intelligence and Data Science Sri Krishna College of Engineering and Technology Coimbatore India Department of Computer Science and Engineering CMR Engineering College Hyderabad India

Forecasting sea levels is crucial for harbour operations and coastal structure design. The oceans make up two-thirds of Earth’s surface;therefore, historically, the marine economy has been extremely diversified as well as abundant. In order to explore as well as harness this difficult environment, prominent businesses and ecological groups are developing and deploying novel gadgets backed by state-of-the-art marine mechatronics solutions. This research proposes a novel method of marine life monitoring with ocean water level rise analysis based on climate changes by underwater imaging using machine learning techniques. Here, the input has been collected as underwater images as well as processed for noise removal and normalisation. Then, these images were segmented for monitoring marine life using U-Net graph cut fuzzy clustering with a spatial neural network. Then this segmented image has been classified using multilayer region-based Q-belief vector neural networks for the analysis of sea level rise analysis based on climate change training. Experimental analysis has been carried out for various marine life monitoring datasets and climate change datasets in terms of training accuracy, specificity, recall, AUC, and Kappa-coefficient. Proposed techniques achieved specificity 93%, training accuracy 91%, AUC 95%, recall 96%, and Kappa-coefficient 90%. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Climate changes Machine learning techniques Marine life monitoring Q-belief vector Water level rise analysis

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Deep learning based classification of motor imagery EEG signals using an improved path finder optimization algorithm

International Journal of Systematic Innovation

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International Journal of Systematic Innovation 2024年第3期8卷 115-124页

作者： Jayashekar, Vishwesh Pandian, Raviraj Basavarajegowda, Rajashekar Mallajamma Department of Computer Science & Engineering GSSS Institute of Engineering and Technology for Women Mysuru Affiliated to VTU Karnataka Belagavi India

Motor Imagery Brain-computer Interfaces (MI-BCIs) are systems based on AI that collect patterns of brain activities in mental movement and translate these movements through external devices. The identification of motor intention by evaluating Electroencephalogram (EEG) signals is an important issue in applications related to Brain-computer Interfaces (BCI). In this paper, an Improved Path Finder Optimization Algorithm (IPFOA) is proposed to improve the process of selecting features. The data is collected from the BCI competition IV 2a dataset and the stage of pre-processing takes place through sliding windows and 6th order Butterworth filter. The feature will be extracted from the pre-processed data using the hybrid Convolutional Neural Network (CNN) and Common Spatial Pattern (CSP) method. After this stage, the required features are selected from the extracted features using the proposed IPFOA algorithm. Finally, the classification of EEG signals takes place using a Stacked autoencoder, a classifier based on a Deep Neural Network. The experimental results show that the proposed approach achieved a better accuracy of 98.40% which is comparatively higher than the existing approaches. © (2024), (Society of Sytematic Innovation). All rights reserved.

关键词： Brain computer Interface Convolutional Neural Networks Deep Learning Electroencephalogram Motor Imagery Path Finder Optimization

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A deep Q-learning model for sequential task offloading in edge AI systems

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Intelligent and Converged Networks 2024年第3期5卷 207-221页

作者： Dong Liu Shiheng Gu Xinyu Fan Xu Zheng Department of Computer Science and Engineering University of Electronic Science and Technology of ChinaChengdu 610000China Shenzhen Institute for Advanced Study University of Electronic Science and Technology of ChinaShenzhen 515100China Department of Information and Software Engineering University of Electronic Science and Technology of ChinaChengdu 610000China

Currently,edge Artificial Intelligence(AI)systems have significantly facilitated the functionalities of intelligent devices such as smartphones and smart cars,and supported diverse applications and *** fundamental supports come from continuous data analysis and computation over these *** the resource constraints of terminal devices,multi-layer edge artificial intelligence systems improve the overall computing power of the system by scheduling computing tasks to edge and cloud servers for *** efforts tend to ignore the nature of strong pipelined characteristics of processing tasks in edge AI systems,such as the encryption,decryption and consensus algorithm supporting the implementation of Blockchain ***,this paper proposes a new pipelined task scheduling algorithm(referred to as PTS-RDQN),which utilizes the system representation ability of deep reinforcement learning and integrates multiple dimensional information to achieve global task ***,a co-optimization strategy based on Rainbow Deep Q-Learning(RainbowDQN)is proposed to allocate computation tasks for mobile devices,edge and cloud servers,which is able to comprehensively consider the balance of task turnaround time,link quality,and other factors,thus effectively improving system performance and user *** addition,a task scheduling strategy based on PTS-RDQN is proposed,which is capable of realizing dynamic task allocation according to device *** results based on many simulation experiments show that the proposed method can effectively improve the resource utilization,and provide an effective task scheduling strategy for the edge computing system with cloud-edge-end architecture.

关键词： edge computing task scheduling reinforcement learning Rainbow Deep Q-Learning(RainbowDQN)

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Sentiment Analysis of Movie Reviews Using Machine Learning

Sentiment Analysis of Movie Reviews Using Machine Learning

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2025 International Conference on Pervasive Computational Technologies, ICPCT 2025

作者： Yadav, Avantika Garg, Payal Jain, Tarun Manipal University Department of Computer Science & Engineering Jaipur India Gl Bajaj Institute of Technology and Management Department of Computer Science & Engineering Greater Noida India

ISBN: (纸本)9798331508685

This paper delves into the critical role that machine learning plays in the accurate classification of sentiments expressed in movie reviews. Throughout the study we research and apply NLP using deep learning and machine learning algorithms to train and test our IMDb 50K movie reviews dataset on different models and feature embedding to compare their accuracies and choose the most optimal model for sentimental analysis. Ultimately, using deep neural network model BERT neural gives us the best accuracy of 94.2% compared to lexicon-based approaches due to the limitations in feature extractions like Bag of Words and TF-IDF. © 2025 IEEE.

关键词： Bag of Words BERT Deep Learning IMDb Dataset Machine Learning Natural Language Processin Sentiment Analysis TF-IDF Training and Testing

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The Evolution and Impact of Price Comparison Websites: A Technological and Economic Analysis 4

The Evolution and Impact of Price Comparison Websites: A Tec...

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

作者： Patidar, Mukesh Vekariya, Daxa Pradhan, Preeti Gupta, Kartik Patidar, Praveen Kumar Khan, Pirmohammad Parul University Parul Institute of Engineering and Technology Department of Computer Science & Engineering Gujarat Vadodara India Madhya Pradesh Indore India Acropolis Institute of Technology and Research Department of Computer Science and Engineering Madhya Pradesh Indore India Parul University Parul Institute of Technology Department of Computer Science & Engineering Gujarat Vadodara India

ISBN: (纸本)9798331518981

Price comparison websites (PCWs) have become integral to the online shopping experience, enabling consumers to make informed decisions by comparing prices, features, and reviews from multiple retailers. These platforms not only benefit consumers by saving time and money but also influence market competition by increasing pricing transparency and driving businesses to optimize their strategies. This research explores the evolution of PCWs, their technological infrastructure, and their business models. Moreover, it examines their impact on consumer behavior, the challenges they pose for retailers, and the future trends shaping the industry. Through an analysis of current practices, technological innovations, and economic effects, this work highlights the growing importance of PCWs in the global e-commerce ecosystem. © 2024 IEEE.

关键词： Marketplaces

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Strategies of Passive Design Buildings in Cold and Arid Climates: A Review

Strategies of Passive Design Buildings in Cold and Arid Clim...

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International Conference on Interdisciplinary Approaches in Civil engineering for Sustainable Development, IACESD 2023

作者： Bhargavi, C. Ganesh, C.R. Manoj Kumar, M. Kishore, G.R. Department of Civil Engineering Jyothy Institute of Technology Bengaluru560082 India Department of Computer Science and Engineering Jyothy Institute of Technology Bengaluru India Department of Information Science and Engineering Jyothy Institute of Technology Bengaluru India

ISBN: (纸本)9789819709090

Passive design strategies have gained increasing attention in recent years as a means of improving the energy efficiency and comfort of buildings. These strategies aim to reduce the energy consumption of buildings by utilizing natural resources such as sunlight, wind, and vegetation. This article provides a review of the literature on passive design strategies and their performance in buildings in cold and arid climate zones. Snow regions present unique challenges and opportunities for sustainable building design due to extreme cold temperatures, heavy snowfall, and the need for effective insulation. The review emphasizes about implementation of passive design strategies, including site analysis, building orientation, insulation, snow management, and efficient heating systems. Passive design of buildings in arid climates focuses on utilizing natural elements and strategies to maximize energy efficiency and thermal comfort without relying heavily on mechanical cooling systems. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Energy efficiency

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Empowering Consumers and Sustainability: A Global Review of Right to Repair Policies

Empowering Consumers and Sustainability: A Global Review of ...

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2024 International Conference on Distributed Systems, computer Networks and Cybersecurity, ICDSCNC 2024

作者： Preethish Kumar, M. Usha, B.A. Basavaraj, G.N. Mohan, B.A. Prithvi, G. Rajkumar Bms Institute of Technology and Management Department of Information Science and Engineering Bengaluru India Nagarjuna College of Engineering and Technology Department of Computer Science and Engineering Bengaluru India

ISBN: (数字)9798350375442

ISBN: (纸本)9798350375442

The 'Right to Repair' (R2R) movement has gained significant attention in recent years with the aim empowering consumers to fix their products rather than replacing them when they become faulty. This paper offers a comprehensive analysis of the impact of R2R policies on consumer rights, environmental sustainability, economic outcomes, social implications, and technological advancement in the digital era. Further, this paper discusses the role of open repair ecosystems in fostering innovation, facilitating aftermarket services, and empowering informed consumer choices. It examines the legal and regulatory frameworks surrounding R2R, including recent legislative initiatives at multiple levels. The paper concludes by advocating for R2R as a fundamental aspect of consumer rights and environmental stewardship, highlighting its potential to promote sustainability, foster innovation, and create a more equitable economy. © 2024 IEEE.

关键词： Sustainable development goals

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Automated Disease Detection and Classification in Jackfruit Leaves: An Efficient Deep Learning-Based Approach 3rd

Automated Disease Detection and Classification in Jackfrui...

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3rd International Conference on Trends in Electronics and Health Informatics, TEHI 2023

作者： Saha, Dip Kumar Mahmud Joy, Md. Ashif Reza, Md. Rokonuzzaman Shovon, Reduanul Bari Department of Computer Science and Engineering American International University-Bangladesh Kuratoli Bangladesh Department of Computer Science and Engineering United International University Dhaka Bangladesh Department of Computer Science and Engineering The International University of Scholars Dhaka Bangladesh Department of Computer Science and Engineering Military Institute of Science and Technology Dhaka Bangladesh

ISBN: (纸本)9789819739363

Jackfruit is the national fruit of Bangladesh, and one of the most consumed fruits in India, Sri Lanka, Philippines, Indonesia, Malaysia, Australia, and many more countries. The every year due to diseases jackfruit production stays lower than the expectation. The early identification of these diseases is crucial for agricultural productivity, and our research showcases the effectiveness of deep learning techniques in addressing this issue. This study introduces an innovative approach to detect and classify two common jackfruit leaf diseases, algal spot and black spot, combining the YOLOv8 object detection model and the EfficientNetB7 pre-trained deep convolutional neural network model. The models trained on 6,360 images of those two diseases and our methodology achieved an accuracy of 99.9% on training and 99.5% on testing. This work represents a valuable contribution to agriculture, emphasizing the synergy between cutting-edge technology and age-old challenges, with the potential to positively impact the agricultural industry and global food security. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Citrus fruits

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Resource Profiling for Virtualized Radio Access Networks 18

Resource Profiling for Virtualized Radio Access Networks

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18th IEEE International Conference on Advanced Networks and Telecommunications Systems, ANTS 2024

作者： Tella, Rajashekhar Reddy Gupta, Utkarsh Venkateswarlu, Gudepu Chintapalli, Venkatarami Reddy Tamma, Bheemarjuna Reddy Kondepu, Koteswararao IIT Dharwad Department of Computer Science and Engineering Dharwad India National Institute of Technology Department of Computer Science and Engineering Kerala Calicut India IIT Hyderabad Department of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798350391725

The mobile networks are rapidly evolving, transitioning from specialized hardware to fully virtualized platforms that run on commercial off-the-shelf (COTS) hardware powered by general-purpose processors. Mobile operators are increasingly adopting Network Functions Virtualization (NFV) to take advantage of virtualization benefits, such as ease of deployment, flexibility, and cost savings. A crucial component of this transformation is the implementation of virtualized Radio Access Network (vRAN) solutions, which provide a cost-effective way to deploy the 5G and beyond RAN as a containerized network function (CNF) on COTS hardware. vRAN is more efficient than traditional RAN, as it allows multiple base station workloads to be multiplexed on the same hardware, potentially co-located with other workloads. However, ensuring consistent performance of vRAN workloads in this consolidated environment is challenging due to the high variability and unpredictability arising from contentions for shared system resources such as CPU cores, Last Level Cache (LLC), and Memory Bandwidth. Thus, there is a strong need to understand the vRAN components if they are affected by any system resource. This paper presents an understanding of how the next-generation scalable processors can be used to run the vRAN components and presents a detailed analysis of the controllable knobs such as CPU, LLC, Memory Bandwidth, and energy consumption. The proposed vRAN profiling shows that the observed throughput varies significantly based on the number of pinned CPU cores (e.g., up to 250 {Mbits} / {sec}), and also similar performance observed with other system resources - LLC allocation and Memory Bandwidth. © 2024 IEEE.

关键词： Radio access networks

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Enhancing User Experience and Integrating Passwordless FIDO-Based Authentication through Bluetooth Low Energy (BLE) 3

Enhancing User Experience and Integrating Passwordless FIDO-...

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3rd IEEE International Conference on Blockchain and Distributed Systems Security, ICBDS 2024

作者： Rathi, Snehal Oswal, Harsh D'Souza, Ansfred Pratham, Shaantanu Khedkar, Vijayshri BRACTs Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India Department of Computer Science & Engineering Pune India

ISBN: (纸本)9798350354348

Traditional password-based authentication methods confront several issues such as security weaknesses, user inconvenience, and susceptibility to various attacks, e.g. phishing. These issues are solved with newly created industry standards such as Web Authentication, CTAP (Client to Authenticator Protocol), FIDO (Fast Identity Online), and W3C guidelines that deliver reliable and interoperable authentication solutions. This research explores how the FIDO, Web Authentication, CTAP, and W3C standards can be blended to revolutionize authentication practices. The proposed method should increase the security and usability of the authentication process without requiring passwords. Our technology facilitates this by establishing secure connections over Bluetooth, offering seamless UX - between a mobile device (in your pocket) and single desktop while maintaining the strongest security postures through structured authentication experiences. © 2024 IEEE.

关键词： Authentication Protocol

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