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Deep Learning-Powered Edge Analytics for IoT-based Sensor Networks 2

Deep Learning-Powered Edge Analytics for IoT-based Sensor Ne...

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2nd international conference on Machine Learning and Autonomous Systems, ICMLAS 2025

作者： Karthikeyan, M. Saravana Subramani, Ponnusamy Selvam, M. Panneer Sworna Kokila, M.L. Vijayalakshmi, R. Sundaravadivel, P. Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Avadi Department of Computer Science and Engineering Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Physics Chennai India Sona College of Technology Department of Electrical and Electronics Engineering Salem India School of Computing SRM Institute of Science and Technology Kattankulathur Faculty of Engineering and Technology Department of Computing Technologies Chennai India Velammal College of Engineering and Technology Department of Computer Science and Engineering Madurai India Saveetha Engineering College Department of Artificial Intelligence and Machine Learning Chennai India

ISBN: (纸本)9798331505745

The rapid expansion of loT-based sensor networks has necessitated the development of efficient edge analytics frameworks to process vast amounts of data in real time while minimizing computational overhead. Deep learning-powered edge computing has emerged as a transformative approach, enhancing data processing capabilities at the network edge while addressing constraints related to latency, bandwidth, and energy consumption. This study introduces a novel algorithm, Lightweight AI Model Compression for Energy-Efficient IoT Edge Devices (LiteEdgeAI), designed to optimize deep learning models for resource-constrained edge environments. The proposed method employs quantization, pruning, and knowledge distillation techniques to achieve significant reductions in model size and computational complexity while maintaining high inference accuracy. To validate the efficiency of LiteEdgeAI, a comparative simulation analysis was conducted against existing state-of-the-art algorithms using key performance metrics such prediction accuracy, energy efficiency and computational complexity. Experimental results demonstrated that LiteEdgeAI outperformed baseline models. The findings highlight the potential of LiteEdgeAI in enabling scalable, low-power, and real-time edge intelligence for IoT-based sensor networks. © 2025 IEEE.

关键词： Deep learning

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ETM fusion algorithm based on log classification 2

ETM fusion algorithm based on log classification

引用

2nd IEEE international conference on Information Technology, Big Data and Artificial Intelligence, ICIBA 2021

作者： Lin, Wenxiang Liu, Desheng Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing China

ISBN: (纸本)9781665428767

With the improvement of computer computing power, the shortcomings of the computational inefficiency of the genetic mining algorithm are compensated, and the genetic mining become a research hotspot. In this paper, for the Evolutionary Tree Miner (ETM) algorithm in noise processing can not find the low-frequency effective path and remove the shortage of noise, an ETM fusion algorithm based on log classification is proposed. The algorithm performs process model mining for high-frequency and low-frequency logs separately, and get model fusion based on alignment ideas, Eventually mining the complete process model. Through the simulation of event log data verification, the improved algorithm achieves more complete process model mining than the original ETM algorithm. © 2021 IEEE.

关键词： Trees (mathematics)

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computer Network Security Defense Model 2

Computer Network Security Defense Model

引用

2021 2nd international conference on Artificial Intelligence, computer Networks and Communications, AICNC 2021

作者： Niu, Yiming Du, Wenyong Tang, Zhenying Customer Service Center of SGCC Tianjin 300309 China

With the rapid development of the Internet industry, hundreds of millions of online resources are also booming. In the information space with huge and complex resources, it is necessary to quickly help users find the resources they are interested in and save users time. At this stage, the content industry's application of the recommendation model in the content distribution process has become the *** content recommendation model provides users with a highly efficient and highly satisfying reading experience, and solves the problem of information redundancy to a certain extent. Knowledge tag personalized dynamic recommendation technology is currently widely used in the field of e-commerce. The purpose of this article is to study the optimization of the knowledge tag personalized dynamic recommendation system based on artificial intelligence algorithms. This article first proposes a hybrid recommendation algorithm based on the comparison between content-based filtering and collaborative filtering algorithms. It mainly introduces user browsing behavior analysis and design, KNN-based item similarity algorithm design, and hybrid recommendation algorithm implementation. Finally, through algorithm simulation experiments, the effectiveness of the algorithm in this paper is verified, and the accuracy of the recommendation has been improved. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Recommender systems

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modelling and Start-up Coordinated Control Strategy for an Off-grid Photovoltaic/Hydrogen/Battery Hybrid System

Modelling and Start-up Coordinated Control Strategy for an O...

引用

Power Science and Technology (ICPST), IEEE international conference on

作者： Zhangxi Wu Ye Li Jiawei He Bin Li Key Laboratory of Smart Gird of Ministry of Education Tianjin University Tianjin China State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin China

ISBN: (数字)9798350349030

ISBN: (纸本)9798350349047

In this paper, a start-up coordinated control strategy of an off-grid Photovoltaic/Hydrogen/Battery Hybrid System is presented. The hybrid system is applied to produce off-grid power for a proton exchange membrane electrolyzer (PEMEL) and customer’s load. The main energy source of the hybrid system is photovoltaic (PV), and energy storage is required to ensure that the PEMEL works at a good point of power, either the battery energy storage system (BESS) or the hydrogen energy storage system (HESS). These tasks need to be judged during the start-up process of the system and carried out by the energy management system. In this study, the system model is established based on the mathematical relationship of various devices in the hybrid system, and a start-up coordinated control strategy considering the optimal hydrogen production power of the system is proposed. The proposed method is verified in the simulation environment and reaches a good start-up effect and hydrogen production power.

关键词： Photovoltaic systems Protons Hydrogen Production Hybrid power systems Mathematical models Stability analysis

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A Deeply Pipelined FMA Unit for High Performance RISC-V processor

A Deeply Pipelined FMA Unit for High Performance RISC-V Proc...

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Computing, Communication, Perception and Quantum Technology (CCPQT), international conference on

作者： Yu Qi Mengxue Chen Guilan Li Gaosheng Li Meisheng He Bangjian Xu College of Electrical and Information Engineering Hunan University Changsha China School of Transportation Engineering Hunan Institute of Traffic Engineering Hengyang China College of Computer Science and Electronic Engineering Hunan University Changsha China

The open RISC-V instruction set architecture provides a new innovative platform for integrated circuit design, and the multiplier and adder are the core units of the computing unit. This paper designs a high-performance 64-bit floating-point multiply-add operation unit based on the RISC-V floating-point instruction set, which supports single-precision, double-precision and half-precision calculations, and can realize a deep pipeline design with a maximum execution stack of 10 levels. In the VIVADO simulation environment, the function verification of the floating-point multiplication and addition unit is carried out, and each module can meet the correctness requirements. The results show that under the 28nm CMOS process, the longest critical path delay is 500ps, the slack is 0.09, and the operating frequency is 1.67GHz.

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Predictive modelling of Anaemia Using Clinical And Laboratory Data

Predictive Modelling of Anaemia Using Clinical And Laborator...

引用

Advances in Computation, Communication and Information Technology (ICAICCIT), international conference on

作者： M Yaswanth R Ganga Siva Prasad P Mahesh Himanshu Mudgal Pronika Chawla Dept of Computer Science SET MRIIRS Faridabad India Dept of Biotechnology SET MRIIRS Faridabad India

ISBN: (数字)9798331541217

ISBN: (纸本)9798331541224

Anaemia is a widespread medical condition which is characterized by a deficiency of red blood cells or hemoglobin that leads to various health issues. Early diagnosis and the efficient monitoring of anaemia are essential for treatment and prevention of health risks from anaemia. Generally, diagnosis of anaemia involves collection of clinical data from patient and laboratory tests, which are expensive and time-consuming process. With the advancements of machine learning techniques, there are different ways to automate the diagnosis process, which enables faster and accurate anaemia detection based on hematological data. This paper proposes a machine learning system for anaemia detection using Logistic Regression. The objective of this work is creating a web-based platform which predicts anaemia in individuals based on key medical data like gender, hemoglobin levels, MCV (Mean Corpuscular Volume), MCH (Mean Corpuscular hemoglobin), MCHC (Mean Corpuscular Hemoglobin Concentration), aiding for healthcare professionals with better accurate diagnostics. It also addresses the need for accessible and cost-effective tools for settings of resource limited. Even the system offers an automated, faster and non-invasive diagnostic approach.

关键词： Logistic regression Accuracy Red blood cells Prevention and mitigation Anemia Machine learning Predictive models Iron Monitoring Medical diagnostic imaging

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Asteroid Mining Model Based on Global Equity 2

Asteroid Mining Model Based on Global Equity

引用

2nd international conference on Applied Mathematics, Modeling and computer simulation, AMMCS 2022

作者： Shao, Xinru Jiang, Kunyu Wang, Lin Liu, Tao School of Mathematics and Statistics Northeastern University at Qinhuangdao Qinhuangdao066004 China School of Computer and Communication Engineering Northeastern University at Qinhuangdao Qinhuangdao066004 China School of Control Engineering Northeastern University at Qinhuangdao Qinhuangdao066004 China

ISBN: (纸本)9781643683522

By defining global equity and other mathematical methods, this paper constructs an equity distribution system for the asteroid mining industry which uses AHP and weight-based Topsis to construct a global equity evaluation model. This model obtains the equity coefficients of 117 countries, which can provide a thorough guiding reference in the distribution of benefits to some degree. Then, the concept of the relative deprivation coefficient is added to the model to adjust the equity of distribution. The model assigns different priorities to countries in the asteroid mining industry, speeding up mining efficiency while improving equity. What's more, we also combine the models to construct a standard world framework to show the change of global equity coefficient in a century in the phenomenon of ideal asteroid mining. Based on the model we formulate, we conduct an experiment and visualization to show the worldwide change of equity coefficients. © 2022 The authors and IOS Press.

关键词： Analytic hierarchy process

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Research on the Improvement of the DPoS Consensus Mechanism Based on the EigenTrust Trust Model 23

Research on the Improvement of the DPoS Consensus Mechanism ...

引用

Proceedings of the 2nd international conference on Signal processing, computer Networks and Communications

作者： Weijun Gao Xiaofang Zhang School of Computer and Communications Lanzhou University of Technology China

ISBN: (纸本)9798400716430

Aiming at the problems of "swing node", poor voting enthusiasm of nodes with small interests, and corruption attack of malicious nodes in traditional DPoS algorithm, this paper proposes an ET-DPoS consensus algorithm based on EigenTrust trust model. Firstly, the algorithm classifies the transactional relationship between nodes, and calculates the direct, indirect and global trust values of nodes under the consideration of the influence of time decay; secondly, in the process of witnessing the nodes' voting, it increases the negative vote link, and utilizes the reputation value to construct a new election evaluation criterion, and dynamically selects the witness nodes according to the size of the evaluation value obtained from each round of calculation to complete the consensus process; lastly, it introduces the concept of node wobbling degree, and according to the size of its value, the node wobbling degree of nodes is calculated. concept, and according to the size of its value, different degrees of punishment restriction measures are made for the swing nodes. simulation results show that the improved consensus algorithm can effectively improve the enthusiasm and fairness of the node election to become a witness node, and reduce the probability of the swing node to do evil.

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Model Reference Adaptive Control for Temperature Regulation of Continuous Stirred Tank Reactor 2

Model Reference Adaptive Control for Temperature Regulation ...

引用

2nd IEEE international conference on Signal, Control and Communication, SCC 2021

作者： Abougarair, Ahmed J. Shashoa, Nasar Aldian Ambark University of Tripoli Electrical and Electronic Engineering Tripoli Libya The Libyan Academy Electrical and Computer Engineering Tripoli Libya

ISBN: (纸本)9781665402705

CSTR (Continuous Stirred Tank Reactor) is a major challenge in process control that has sparked a lot of research in the chemical and control engineering. The nonlinear and coupled nature of CSTR makes designing a robust control with a larger working region difficult. Conventional PID (Proportional Integral Derivative) and adaptive control are described in this work for temperature control. For adaptive control system, the MRAC strategy is utilized and the control law is created by the Lyapunov stability method. Additionally, the robustness and efficacy of the MRAC are confirmed compared with PID controller. The suggested controllers' performance is verified using the steady-state error, time specification criteria and tracking of the reference signal in presence of uncertainty. The simulation results clearly show that the MRAC method provides adequate performance in terms of process functional improvements, and more flexibility, in addition to, improves system-tracking precision in control action compared with the PID. © 2021 IEEE.

关键词： Chemical reactors

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Sustainable Transport Policy Impact Assessment Using Agent-based modelling: A Case Study in Oxford, UK 24

Sustainable Transport Policy Impact Assessment Using Agent-b...

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Proceedings of the 2024 2nd international conference on computer, Internet of Things and Smart City

作者： Maiia Sagdieva Koen H. van Dam Liu Yang Department of Chemical Engineering Imperial College London London United Kingdom Centre for Process Systems Engineering Department of Chemical Engineering Imperial College London London United Kingdom School of Architecture and Design Beijing Jiaotong University Beijing China School of Architecture Southeast University Nanjing Jiangsu China

ISBN: (纸本)9798400714726

The role of transportation in urban ecosystems is crucial, yet traditional approaches have historically favoured car-centric planning, overlooking broader environmental, economic, and social factors. As the impact of sustainable transport strategies has a profound effect on the entire urban network, policymakers and planners require more decision-support tools to navigate the growing complexity of modern transport systems. Traditional four-step transport models typically use aggregate data, missing the fine-grained details of how individuals make travel choices. Agent-based modelling allows for the modelling of individual agents with unique characteristics, providing a more nuanced understanding of travel behaviour. This paper develops a proof-of-concept agent-based model that focuses on the impact assessment of sustainable transportation policies, demonstrating potential insights based on a case study of Oxford. The presented modelling methodology captures high-level urban transport system dynamics based on the behaviour of individual agents, and can potentially be applied to other cases and settings to support assessment of sustainable transport policies.

关键词： Agent-based model

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