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24th IEEE International Conference on High Performance computing and Communications, 8th IEEE International Conference on Data science and Systems, 20th IEEE International Conference on Smart City and 8th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Application, HPCC/DSS/SmartCity/DependSys 2022

作者： Nie, Hejing Wen, Yiping Li, Tiancai Ouyang, Sipeng Tian, Muyang School of Computer Science and Engineering Hunan University of Science and Technology China Hunan University of Science and Technology Hunan Key Laboratory for Service Computing and Novel Software Technology China

ISBN: (纸本)9798350319934

Crowdsourced delivery can provide cost-effective deliveries and it is becoming increasingly important in practice. This paper considers a package delivery problem which exploits relays of private cars to transport packages via their commuter routes. Specifically, we propose a method of planning package delivery paths based on the commuter routes of private cars. Using the commuter routes and time constraints as the reference, it can find optimal delivery paths and assign drivers of private cars to transport packages. The simulation experiment results show the validity and effectiveness of such method. © 2022 IEEE.

关键词： Cost effectiveness

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Unified Graph Augmentations for Generalized Contrastive Learning on Graphs 38

Unified Graph Augmentations for Generalized Contrastive Lear...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Zhuo, Jiaming Lu, Yintong Ning, Hui Fu, Kun Niu, Bingxin He, Dongxiao Wang, Chuan Guo, Yuanfang Wang, Zhen Cao, Xiaochun Yang, Liang Hebei Province Key Laboratory of Big Data Calculation School of Artificial Intelligence Hebei University of Technology Tianjin China College of Intelligence and Computing Tianjin University Tianjin China School of Computer Science and Technology Beijing JiaoTong University Beijing China School of Computer Science and Engineering Beihang University Beijing China School of Cybersecurity Northwestern Polytechnical University Xi'an China School of Cyber Science and Technology Shenzhen Campus of Sun Yat-sen University Shenzhen China

In real-world scenarios, networks (graphs) and their tasks possess unique characteristics, requiring the development of a versatile graph augmentation (GA) to meet the varied demands of network analysis. Unfortunately, most Graph Contrastive Learning (GCL) frameworks are hampered by the specificity, complexity, and incompleteness of their GA techniques. Firstly, GAs designed for specific scenarios may compromise the universality of models if mishandled. Secondly, the process of identifying and generating optimal augmentations generally involves substantial computational overhead. Thirdly, the effectiveness of the GCL, even the learnable ones, is constrained by the finite selection of GAs available. To overcome the above limitations, this paper introduces a novel unified GA module dubbed UGA after reinterpreting the mechanism of GAs in GCLs from a message-passing perspective. Theoretically, this module is capable of unifying any explicit GAs, including node, edge, attribute, and subgraph augmentations. Based on the proposed UGA, a novel generalized GCL framework dubbed Graph cOntrastive UnifieD Augmentations (GOUDA) is proposed. It seamlessly integrates widely adopted contrastive losses and an introduced independence loss to fulfill the common requirements of consistency and diversity of augmentation across diverse scenarios. Evaluations across various datasets and tasks demonstrate the generality and efficiency of the proposed GOUDA over existing state-of-the-art GCLs. © 2024 Neural information processing systems foundation. All rights reserved.

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Forecasting Cryptocurrency Prices in the DeFi Ecosystem Using Predictive Models

Forecasting Cryptocurrency Prices in the DeFi Ecosystem Usin...

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2025 International Conference on computing for Sustainability and Intelligent Future, COMP-SIF 2025

作者： Sruthi, Srigiri Saravanan, Deivanai Jyotsna, C. Amrita School of Computing Amrita Vishwa Vidyapeetham Dept. of Computer Science Engineering Bengaluru India

ISBN: (纸本)9798331538538

In the rapidly evolving cryptocurrency markets, accurate price prediction is crucial for investors and traders. This task investigates the efficacy of advanced machine learning and deep learning for forecasting cryptocurrency prices. The proposed idea utilizes Autoregressive Integrated Moving Average (ARIMA) models, Bidirectional Long Short-Term Memory (Bi- LSTM) networks, Gated Recurrent Units (GRU), and Long Short-Term Memory networks improved with Self-Attention (LSTM-Self-Attention). Numerous studies were conducted using the historical data available. Root Mean Squared Error (RMSE) were used to evaluate the models. The study tries to show the impact of outside factors such as economic data and market belief in purchase to improve the precision of the forecast. This research offers investors and policy makers insight that demonstrates the ability of sophisticated machine learning models to navigate the intricacies of cryptocurrency marketplaces. Incorporating these approaches into a single predictive framework enables accurate forecasting and the identification of anomalies in DeFi markets. The findings contribute to the decision making that is strategic DeFi investments, providing tools for better prediction and analysis, and laying the groundwork for future advancements in DeFi analytics. © 2025 IEEE.

关键词： Prediction models

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Analysis on Recent Trends in Augmented and Virtual Reality with Haptic Interferences 11

Analysis on Recent Trends in Augmented and Virtual Reality w...

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11th IEEE International Conference on Cloud computing in Emerging Markets, CCEM 2023

作者： Potluri, Swathi Kumar, N.K. Senthil Department of Computer Science Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Tamil Nadu Chennai India Department of Computer Science & Engineering School of Computing Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Tamil Nadu Chennai India

ISBN: (纸本)9798350360059

Tele-haptics, telemedicine, including training, education, and amusement are a few examples of applications for the sense of touch (haptics). A wide range of multi- and cross-disciplinary sectors are now using and researching haptics. The inclusion of new media kinds, such as music, film, and even aroma, expands the usage of haptics. In order to provide users a more realistic experience, haptics, for instance, are widely employed in virtual reality situations. While haptic interface science has improved throughout the years, that are still a number of barriers that stand in the way of further development. In this overview, the tactile interfaces for virtual reality—which comprise wearables, handhelds, encountered-type devices, props, and mid-air methods—are discussed. This study intends to investigate the current state and potential uses of hands-on material-based haptic technology, with a focus on VR/AR. ©2023 IEEE.

关键词： Virtual environments

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Advanced Offensive Language Detection with mT5 and User-Centric Features

Advanced Offensive Language Detection with mT5 and User-Cent...

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Data science, Agents & Artificial Intelligence (ICDSAAI), International Conference on

作者： Suthiksha P G Sankranthi Varshitha Natarajan S Dept. of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Chennai India

ISBN: (数字)9798331537555

ISBN: (纸本)9798331537562

With the emergence of diverse languages, cultural nuances, and code-mixed content, detecting offensive language on social media has become critical. This paper addresses these challenges with the help of the multilingual T5 (mT5) model, which has been fine-tuned to detect offensive language in code-mixed multilingual texts. The system is designed as a browser-based web extension that offers real-time detection by blurring or concealing offensive content, which leads to continuous improvement. It also integrates user-centric features that enable users to provide feedback on the accuracy of offensive content detection and report any instances of offensive language that go undetected, supporting continuous enhancement. This user-centric approach presents an accurate, efficient, and context-aware offensive language detection experience, which leads to safer and more secure online environments for different communities.

关键词： Accuracy Social networking (online) Hate speech Feature extraction Real-time systems Multilingual Browsers Cultural differences Continuous improvement Security

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Securing Networks: Advanced Detection and Prevention of Address Resolution Protocol Cache Spoofing Attack 3

Securing Networks: Advanced Detection and Prevention of Addr...

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3rd International Conference on Integrated Circuits and Communication Systems, ICICACS 2025

作者： Sriharsha, V.V.S. Daule, Viraj Kisan Surya, R. Thangam, S. Amrita Vishwa Vidyapeetham Amrita School of Computing Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798331508456

As the technology advances, an increase in the attacks to manipulate or extract data illegally has also risen. This also includes one such attack known as Address Resolution protocol cache spoofing attack. The Address Resolution protocol Spoofer conducts an in-depth exploration into one of the most significant security vulnerabilities identified in local networks, namely Address resolution protocol cache poisoning. The study implements a system which uses a Python based tool which is able to simulate Address Resolution protocol spoofing attacks on the network traffic of two hosts through a Python library known as the Scapy library. This tool allows the execution of Man In The Middle attacks by forging Address Resolution protocol replies and changing the stream of traffic without setting off any alarm by the user. The tool also has a detection mechanism that alerts the users as soon as it detects attempted spoofing;which hence identifies both the offender and the defensive capabilities in Address Resolution protocol spoofing. Additionally, another layer of security is added by user-defined encryption and decryption of the message being delivered. The study has resulted in a secure network, protecting the data from ARP spoofing. © 2025 IEEE.

关键词： HTTP

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FlexAssist: A Sensor-based Glove for Hand Function Assessment using MAS and QUEST

FlexAssist: A Sensor-based Glove for Hand Function Assessmen...

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Smart Technologies, Communication and Robotics (STCR)

作者： Virupaxappa G Aditya Elango Parikshith Sivakumar Puvvada Charan Sai Thangam S Dept. of Computer Science Engineering Amrita School of Computing Bengaluru Amrita Vishwa Vidyapeetham India

ISBN: (数字)9798350357530

ISBN: (纸本)9798350357547

Rehabilitation for hand motor impairments, such as those resulting from cerebral palsy or stroke, necessitates precise assessment and targeted feedback. This study develops a wearable device for hand rehabilitation that utilizes flex sensors, Arduino Uno, servo motors, and coin vibration motors. The device captures flex sensor data, records it in a CSV file, and processes it offline to classify spasticity and motor functionality. It applies percentage-based thresholds mapped to the Modified Ashworth Scale (MAS) and the Quality of Upper Extremity Skills Test (QUEST). The values after processing help with servo motor adjustments and vibration patterns to deliver feedback, this provides valuable insights for therapy. This cost-effective and portable system helps in addressing limitations of traditional rehabilitation methods and helps in enhancing sensor-based assessment to provide a scalable approach in improving hand motor function.

关键词： Hands Vibrations Flexible printed circuits Medical treatment Spasticity Robot sensing systems Sensor systems Servomotors Extremities Wearable sensors

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An Optimized Fuzzy Based Ant Colony Algorithm for 5G-MANET

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computers, Materials & Continua 2022年第1期70卷 1069-1087页

作者： R.Nithya K.Amudha A.Syed Musthafa Dilip Kumar Sharma Edwin Hernan Ramirez-Asis Priya Velayutham V.Subramaniyaswamy Sudhakar Sengan Department of Computer Science and Engineering Vivekananda College of Engineering for WomenTiruchengode637205Tamil NaduIndia Department of Electronics and Communication Engineering Kongunadu College of Engineering and TechnologyThottiam621215Tamil NaduIndia Department of Information Technology M.Kumarasamy College of EngineeringKarur639113Tamil NaduIndia Department of Mathematics Jaypee University of Engineering and TechnologyGuna473226M.P.India Business and Tourism Faculty Universidad Nacional Santiago Antunez De MayoloHuarazPeru Department of Computer Science and Engineering Paavai Engineering CollegeNamakkal637018Tamil NaduIndia School of Computing SASTRA Deemed UniversityThanjavur613401Tamil NaduIndia Department of Computer Science and Engineering PSN College of Engineering and TechnologyTirunelveli627152Tamil NaduIndia

The 5G demonstrations in a business has a significant role in today’s fast-moving *** in 5G,drives a wireless system intended at an enormously high data rate,lower energy,low latency,and *** this reason,routing protocols of MANET have the possibility of being fundamentally flexible,high performance,and *** 5G communication aims to afford higher data rates and significantly low Over-The-Air *** through supplementary ACO routing processes,a security-aware,fuzzy improved ant colony routing optimization protocol is proposed in *** goal is to develop aMANET routing protocol that could provide a stable packet transmission ratio,less overhead connectivity,and low end-to-end latency in shared standard scenarios and attack *** demonstrates effective results with hybrid architecture and proved to be effective than other state-of-the-art routing protocols of MANETs,like AODV,its routing organization implemented through Optimized Fuzzy based ACO Algorithm for ***-wavelengths are required to perform a significant role in *** research proposed to test the efficiency of MANET consisting of only mmWave User *** reduced packet transmission loss of UEs withmmWave,meaning well-transmitted SNR leads directly to a better packet delivery *** verify results,simulation using the NS-3 simulator mmWave module is used.

关键词： 5G attacks D2D communications MANET mmWave security

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Python And Opencv For Sign Language Recognition

Python And Opencv For Sign Language Recognition

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2023 IEEE International Conference on Device Intelligence, computing and Communication Technologies, DICCT 2023

作者： Srinivasan, R. Kavita, R. Kavitha, M. Mallikarjuna, Basetty Bhatia, Sandeep Agarwal, Bhawna Ahlawat, Vinay Goel, Amit Veltech University Chennai Dept of Computer Science and Engineering India Galgotias University School of Computing Science and Engineering Uttar Pradesh Greater Noida India Birla Institute of Technology Mesra Jaipur Center India Kiet Ncr Delhi Department of Cse Uttar Pradesh India

ISBN: (纸本)9781665474924

Hearing-impaired people cannot communicate with normal people easily. Most people are not aware of sign language recognition. To support this, machine learning and CV can be used to create an impact on the impaired. This can be improved into automatic editors, in which the person can easily understand the sign language of the impaired people by just using hand sign recognition. In non-verbal communication, hand gesture always being an important mode of communication and it plays a vital role to bridge gap between deaf and dumb people. Several sign language recognition systems have been developed but the systems are not flexible and cost-effective. Physically challenged people can express their emotions and feelings through sign language. In this paper, we develop a sign detector that can detect signs and numbers and also other signs that are used in sign language with the help of OpenCV and Keras modules in python. By using this technology, we can understand what they want to convey through sign language which is not a common language to communicate with people. OpenCV and Keras of python are the modules used to achieve our work and the proposed work proved to be a user-friendly approach to communication by using Python language to recognize sign languages for hearing-impaired persons. © 2023 IEEE.

关键词： Python

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A Species-based Particle Swarm Optimization with Adaptive Population Size and Deactivation of Species for Dynamic Optimization Problems

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ACM Transactions on Evolutionary Learning and Optimization 2023年第4期3卷 1-25页

作者： Yazdani, Delaram Yazdani, Danial Yazdani, Donya Omidvar, Mohammad Nabi Gandomi, Amir H. Yao, Xin Department of Computer Engineering Mashhad Branch Azad University Mashhad*** Iran Faculty of Engineering & Information Technology University of Technology Sydney Ultimo2007 Australia AI Lab British Antarctic Survey CambridgeCB3 0ET United Kingdom School of Computing Leeds University Business School University of Leeds LeedsLS2 9JT United Kingdom Obuda University Budapest1034 Hungary Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China School of Computer Science University of Birmingham BirminghamB15 2TT United Kingdom

Population clustering methods, which consider the position and fitness of individuals to form sub-populations in multi-population algorithms, have shown high efficiency in tracking the moving global optimum in dynamic optimization problems. However, most of these methods use a fixed population size, making them inflexible and inefficient when the number of promising regions is unknown. The lack of a functional relationship between the population size and the number of promising regions significantly degrades performance and limits an algorithm’s agility to respond to dynamic changes. To address this issue, we propose a new species-based particle swarm optimization with adaptive population size and number of sub-populations for solving dynamic optimization problems. The proposed algorithm also benefits from a novel systematic adaptive deactivation component that, unlike the previous deactivation components, adapts the computational resource allocation to the sub-populations by considering various characteristics of both the problem and the sub-populations. We evaluate the performance of our proposed algorithm for the Generalized Moving Peaks Benchmark and compare the results with several peer approaches. The results indicate the superiority of the proposed method. © 2023 Copyright held by the owner/author(s).

关键词： Resource allocation

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