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4th IEEE International Conference on Electrical, Computer, and Energy Technologies, ICECET 2024

作者： Raveenthiran, Gawsan Sivarajah, Kaanushan Mohamed Riyal, Akash Ahamed Kugathasan, Vethurja Chandrasiri, Sanjeevi Rajendran, Karthiga Sri Lanka Institute of Information Technology Department of Computer Science & Software Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350395914

This paper introduces a novel approach aimed at enhancing online education by placing a central focus on students' emotional well-being and improving their learning experiences. The approach integrates four key machine learning technologies: behavioral expression analysis, a personalized chatbot for emotional support, voice stress detection, and visual content description. Through empirical findings, the study illustrates the effectiveness of these methods in bolstering students' emotional well-being and academic performance. By providing a roadmap for the advancement of online education and emotional support, this research holds promise for delivering substantial benefits to learners worldwide. The study showcases notable advancements in online education, reporting a 30% rise in perceived emotional support and a 25% increase in overall satisfaction. The personalized emotional support chatbot achieved an 85% accuracy in addressing students' emotional needs, while voice stress detection boasted a 90% accuracy in identifying anxiety. Additionally, visual content description led to a 20% improvement in comprehension. These findings highlight the approach's potential to elevate both emotional well-being and academic performance in online learners. © 2024 IEEE.

关键词： Contrastive Learning

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Crafting Tomorrow's Trends with Automated Precision, Efficiency, and Faultless Excellence in Apparel Industry for Medium Scale Businesses 6

Crafting Tomorrow's Trends with Automated Precision, Efficie...

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6th International Conference on Advancements in Computing, ICAC 2024

作者： Hiruni Herath, H.M. Jayaweera, J.M.M.G. Jayasinghe, J.M.Y. Randeni, K.M.T.D. Amarasena, Nelum Chathuranga Rathnayake, Samadhi Chandanathilaka, S.N. Sri Lankan Institute of Information Technology Department of Information Technology Malabe Sri Lanka Sri Lankan Institute of Information Technology Department of Computer Science and Software Engineering Malabe Sri Lanka

ISBN: (纸本)9798331517878

In the evolving landscape of Sri Lanka's apparel industry, the predominance of manual methods in the pre-production phase necessitates innovative technological interventions to enhance efficiency. This research explores the complexities of garment production, addressing critical challenges such as machine breakdowns, maintenance, and workforce management. By employing advanced technologies such as image recognition, loT devices, and machine learning, this study aims to transform pre-production decision-making, optimize sewing machine performance, implement predictive maintenance strategies, and refine workforce optimization. These initiatives, driven by domain expertise and cutting-edge methodologies, not only aim to bridge existing gaps in the industry but also pave the way for significant advancements, ensuring a future characterized by precision, efficiency, and operational excellence. © 2024 IEEE.

关键词： Predictive maintenance

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An Intelligent Platform for Cricket Technique and Performance Improvement 6

An Intelligent Platform for Cricket Technique and Performanc...

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6th International Conference on Advancements in Computing, ICAC 2024

作者： Madushan, Anjana Fernando, Priyantha Mahendra, Hesara Kottage, Nowen Kasthuriarachchi, Sanvitha Rajapaksha, Samantha Sri Lanka Institute of Information Technology Department of Computer Science and Software Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798331517878

In cricket training, preventing injuries and developing skills are of utmost importance, especially concerning the school cricketers. This research presents a web application, 'CricBoost' which would serve to address all these vital issues through a multifaceted strategy. This study offers batsman pose accuracy assessment and correction using MediaPipe and Random Forest algorithm, Analysis of bowling and grip using MediaPipe, VGG16 and Gradient Boost models for classification and Shap for providing suggestions on the optimal methods, Suggestion of Shot selection for Batsman, where YOLOv8 and OpenCV are applied to ball pitch analysis and the player is given suggestions about the right shot to take, and cricket drill recommendation system focused on targeted skill improvement of players. CricBoost will deliver a unique combination that will increase players' technical skills, strategic intelligence, and performance while simultaneously focusing on injury prevention by teaching correct techniques. © 2024 IEEE.

关键词： Cricket (Sports)

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Adaptive design and implementation of automatic modulation recognition accelerator

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Journal of Ambient Intelligence and Humanized Computing 2024年第1期15卷 779-795页

作者： Wang, Bin Wei, Xianglin Wang, Chao Li, Junnan Jiao, Xiang Fan, Jianhua Li, Peng School of Electronics and Information Engineering Nanjing University of Information Science and Technology Nanjing210044 China School of Computer and Software Nanjing University of Information Science and Technology Nanjing210044 China 63rd Research Institute National University of Defense Technology Nanjing210007 China

Automatic modulation recognition-oriented Deep Neural Networks (ADNNs) have achieved higher recognition accuracy than traditional methods with less labor overhead. However, their high computation complexity usually far exceeds the computation capacity of communication devices built on Field Programmable Gate Array (FPGA) platform. When solving the problem of insufficient resources, the complete operation of FPGA-based accelerator can be achieved by dividing the calculation into several parts and calculating them separately, but this will cause unaccepTable latency. In this backdrop, we develop a new ADNN model, named VT-CNN2+, to promote the recognition accuracy. Then, after stating the resources and latency problems for implementing VT-CNN2+ on the FPGA platform, an adaptive hardware accelerator is put forward. To implement the accelerator, Area folding is introduced to optimize resources consumption. Moreover, Literacy Optimization, Parallelism Optimization, Inter-layer Cascading, Temporary Cache and Data Loading Optimization are adopted to reduce latency. Afterwords, the two components in our accelerator are detailed, i.e., Once-designed module and Re-designed module. Finally, to evaluate the performance and adaptivity of our accelerator, a series of experiments are conducted on two different FPGA platforms, i.e., AX7350 and ZedBoard. Results show that our accelerator can successfully adapt to different FPGA platforms and it can remarkably reduce the processing latency. Moreover, our accelerator’s processing speed of 0.066249s per single data sample with much lower energy consumption is one order of magnitude faster than desktop-level Central Processing Units (CPUs), two orders of magnitude faster than embedded CPUs. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Deep neural networks

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Controllable chaos in the coupled waveguide-optomechanical system with phase shifter

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Science China(Physics,Mechanics & Astronomy) 2025年第4期68卷 26-34页

作者： Deng-Wei Zhang Pei-Qi Qin Li-Li Zheng Zhi-Ming Zhan Xin-You Lü Department of Mathematics and Physics Luoyang Institute of Science and TechnologyLuoyang 471023China School of Computer and Information Engineering School of SoftwareLuoyang Institute of Science and TechnologyLuoyang 471023China School of Artificial Intelligence Jianghan UniversityWuhan 430056China School of Physics Huazhong University of Science and TechnologyWuhan 430074China

We theoretically investigate chaotic dynamics in an optomechanical system composed of a whispering-gallery-mode(WGM)microresonator and a *** find that tuning the optical phase using a phase shifter and modifying the coupling strength via a unidirectional waveguide(IWG)can induce chaotic *** underlying reason for this phenomenon is that adjusting the phase and coupling strength via the phase shifter and IWG bring the system close to an exceptional point(EP),where field localization dynamically enhances the optomechanical nonlinearity,leading to the generation of chaotic *** addition,due to the sensitivity of chaos to phase in the vicinity of the EP,we propose a theoretical scheme to measure the optical phase perturbations using *** work may offer an alternative approach to chaos generation with current experimental technology and provide theoretical guidance for optical signal processing and chaotic secure communication.

关键词： cavity optomechanics chaos exceptional point

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Intelligent Daycare: Enhancing Child Safety with IoT and Machine Learning Innovations 9

Intelligent Daycare: Enhancing Child Safety with IoT and Mac...

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9th International Conference on Communication and Electronics Systems, ICCES 2024

作者： Prathyanga, Amisha Shyaminda, Pasindu Chamikara, Pasan Lakshan, Sachin Thelijjagoda, Samantha Kasthurirathna, Dharshana Sri Lanka Institute of Information Technology Department of Software Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Computer Systems Engineering Malabe Sri Lanka

ISBN: (纸本)9798350377972

Child safety and well-being in daycare settings are important, thus it is vital that the persons in charge be attentive to them. This research tries to solve the problem by introducing a smart and detailed monitoring system that utilizes new technology to enhance safety and support caretakers. The system has various innovative features, such as child missing detection, behavior and facial expression analysis, cry analysis and categorization, and fall detection. Using high-resolution cameras and on-device Edge AI capabilities, it ensures real-time surveillance of children's activities while protecting privacy. The approach integrates behavior and facial expression analysis to assess emotional states, cry recognition to discover childcare needs, as well as a useful fall detection system that can tell the difference between falls and other movements. All these parts synergize to hand over the necessary information to the caregivers on time and in a way that they can act upon. The quantitative experiments in real-time childcare centers show high accuracy through all the components, attesting to the system's reliability and durability. This research has important significance in improving the safety and the frequency response in daycare centers because it gives caregivers automated tools to quickly address the needs of children. While promising, the system has drawbacks, such as potential biases in data models and a reliance on ideal environmental circumstances. Future work intends to improve flexibility across varied daycare situations, improve accuracy through larger datasets, and investigate ethical frameworks for wider application. © 2024 IEEE.

关键词： Fall detection

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Requirements Elicitation for Virtual Reality Products - A Mapping Study 23

Requirements Elicitation for Virtual Reality Products - A Ma...

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16th Innovations in software engineering Conference, ISEC 2023

作者： Karre, Sai Anirudh Mittal, Raghav Reddy, Raghu Software Engineering Research Center International Institute of Information Technology India

ISBN: (纸本)9798400700644

software practitioners use various requirement elicitation methods to produce a well-defined product. These methods impact the software product's eventual traits and target a particular audience segment. Virtual Reality(VR) products are no different from this influence. With the notable rise in product offerings across various domains, VR has become an essential technology for the future. Nevertheless, the type of methods practiced for requirement elicitation still has not been thoroughly studied. This paper presents a mapping study on requirement elicitation methods practiced by VR practitioners in academia and industry. We consolidated our observations based on their popularity in the practitioner community. Further, we present our insights on the necessary and sufficient conditions to conduct VR requirement elicitation using the identified methods to benefit the VR practitioner community. © 2023 ACM.

关键词： Virtual reality

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Simulation of unmanned survey path planning in debris flow gully based on GRE-Bat algorithm

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Journal of Mountain Science 2024年第12期21卷 4062-4082页

作者： LIU Dunlong FENG Duanguo SANG Xuejia ZHANG Shaojie YANG Hongjuan College of Software Engineering Chengdu University of Information TechnologyChengdu 610225China State Key Laboratory of Mountain Hazards and Engineering Resilience Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu 610299China

Unmanned aerial vehicle(UAV)paths in the field directly affect the efficiency and accuracy of payload data *** planning of UAV advancing along river valleys in wild environments is one of the first and most difficult problems faced by unmanned surveys of debris flow *** study proposes a new hybrid bat optimization algorithm,GRE-Bat(Good point set,Reverse learning,Elite Pool-Bat algorithm),for unmanned exploration path planning of debris flow sources in outdoor *** the GRE-Bat algorithm,the good point set strategy is adopted to evenly distribute the population,ensure sufficient coverage of the search space,and improve the stability of the convergence accuracy of the ***,a reverse learning strategy is introduced to increase the diversity of the population and improve the local stagnation problem of the *** addition,an Elite pool strategy is added to balance the replacement and learning behaviors of particles within the population based on elimination and local perturbation *** demonstrate the effectiveness of the GRE-Bat algorithm,we conducted multiple simulation experiments using benchmark test functions and digital terrain *** to commonly used path planning algorithms such as the Bat Algorithm(BA)and the Improved Sparrow Search Algorithm(ISSA),the GRE-Bat algorithm can converge to the optimal value in different types of test functions and obtains a near-optimal solution after an average of 60 *** GRE-Bat algorithm can obtain higher quality flight routes in the designated environment of unmanned investigation in the debris flow gully basin,demonstrating its potential for practical application.

关键词： Bat algorithm Unmanned surveys Debris flow gully Path planning Unmanned aerial vehicle Reverse learning

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Integrating Data Protection at Interface of RISC-V Processor Core

Integrating Data Protection at Interface of RISC-V Processor...

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2024 Panhellenic Conference on Electronics and Telecommunications, PACET 2024

作者： Mach, Jan Kohutka, Lukas Cicak, Pavel Slovak University of Technology Institute of Computer Engineering and Applied Informatics Slovakia Information Systems and Software Engineering Slovak University of Technology Institute of Informatics Slovakia

ISBN: (纸本)9798350318845

Fulfilling increasing performance demands of space and automotive applications can be problematic as high dependability is required. Memory is one of the most radiationsensitive parts, so it is often protected with information redundancy. This paper describes an integration of error correction and detection techniques into the interface of RISC-V processor to protect the data stored in the memory. We also provide a hardware-software interface for reporting errors and software routines for correcting data in memory. Our solution has a negligible impact (-3.9%) on the overall performance of the core with a small area and power consumption overhead. © 2024 IEEE.

关键词： Error correction

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LLMaaS: Serving Large-Language Models on Trusted Serverless Computing Platforms

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2025年第2期6卷 405-415页

作者： Cai, Zinuo Ma, Rongbo Fu, Yicheng Zhang, Weishan Ma, Ruhui Guan, Haibing Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering Shanghai200240 China Qingdao Institute of Software College of Computer Science and Technology Qingdao266555 China

In recent years, the emergence of large-language models (LLMs) has profoundly transformed our production and lifestyle. These models have shown tremendous potential in fields, such as natural language processing, speech recognition, and recommendation systems, and are increasingly playing crucial roles in applications such as human-computer interaction and intelligent customer service. Efficient inference solutions for LLMs in data centers have been extensively researched, with a focus on meeting users' quality of service requirements. In this article, we focus on two additional requirements that responsible LLM inference should meet under QoS conditions: security throughout the model execution process and low maintenance requirements for the inference system. Therefore, we propose LLMaaS, a trusted model inference platform based on a serverless computing platform aimed at providing inference as a service for LLMs. First, we design a trusted serverless computing platform based on software guard extension (SGX), which includes distributed identity verification and SGX device plugins to ensure the security and trustworthiness of the inference process. Additionally, to reduce the maintenance requirements of the system, we enhance the SGX-based deep learning computing framework, including replacing PyTorch and using a greedy algorithm for graph partitioning. We conduct tests on four typical large models, and the experimental results demonstrate that, with minimal overhead and user code modifications, we can ensure the security of model execution. © 2020 IEEE.

关键词： Quality of service

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