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Analysis of optimization Techniques for Dynamic Neural Networks 3

Analysis of optimization Techniques for Dynamic Neural Netwo...

引用

3rd international conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, IITCEE 2025

作者： Mallegowda, M. Nair, Saanvi Khirwal, Sahil Animesh, Manik Mishra, Vasuman Kanavalli, Anita Ms Ramaiah Institute of Technology Department of Computer Science and Engineering Bengaluru India Ramaiah Institute of Technology Dept. of Cse Bengaluru India

ISBN: (纸本)9798331515911

Models based on dynamic neural networks such as DeBERTa and Vision Transformers ViT have disrupted the two fields. However, there is one complication - their performance requires so much computation which limits its realistic applications. The aim of this study is to propose advanced optimization techniques that can increase the efficiency of these models without compromising their performance. We adopt approaches such as DistilBERT, DeBERTa and Vision Transformer models. Then we carry out detailed empirical analysis of the consequences of these techniques on the model accuracy, time performance, throughput as well as resources consumption. The findings show enhancement models, where some methods improved the throughput by 29% and reduced the GPU usage by 61% at the same or higher accuracy. This reveals the capacity of dynamic neural networks in resource-constrained settings and enhances the overall vision of the use of such models in practice. © 2025 IEEE.

关键词： Neural network models

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An Exploratory Study of Dataset and Model Management in Open Source Machine Learning applications 24

An Exploratory Study of Dataset and Model Management in Open...

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IEEE/ACM 3rd international conference on AI Engineering - Software Engineering for AI (CAIN)

作者： Toma, Tajkia Rahman Bezemer, Cor-Paul Univ Alberta Edmonton AB Canada

ISBN: (纸本)9798400705915

Datasets and models are two key artifacts in machine learning (ML) applications. Although there exist tools to support dataset and model developers in managing ML artifacts, little is known about how these datasets and models are integrated into ML applications. In this paper, we study how datasets and models in ML applications are managed. In particular, we focus on how these artifacts are stored and versioned alongside the applications. After analyzing 93 repositories, we identified the most common storage location to store datasets and models is the file system, which causes availability issues. Notably, large data and model files, exceeding approximately 60 MB, are stored exclusively in remote storage and downloaded as needed. Most of the datasets and models lack proper integration with the version control system, posing potential traceability and reproducibility issues. Additionally, although datasets and models are likely to evolve during the application development, they are rarely updated in application repositories.

关键词： Machine Learning (ML) artifact management ML application development SE4AI

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Research on the optimization Strategy of Command and control System Based on Complex Network Theory 24

Research on the Optimization Strategy of Command and Control...

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3rd international conference on Cyber Security, Artificial Intelligence and Digital Economy (CSAIDE)

作者： Li, Tengda Wang, Gang Du, Chong Fu, Qiang Liu, Xiangyu Air Force Engn Univ Air & Missile Def Coll Xian 710051 Shaanxi Peoples R China

ISBN: (纸本)9798400718212

To deeply analyze the characterization and destruction resistance of the command and control (C2) system, based on the complex network theory, a model of the C2 system is established. The network model of the C2 system is attacked using the method of real-time attack, and it is found that the network is more sensitive to the deliberate attack method and performs poorly. The node-degree based edge-adding method is proposed to enhance the destructibility of the network, and it is found that the policy of low-degree edge-adding method can effectively increase the destructibility of the C2 network system to a certain extent.

关键词： Complex network theory Edge addition strategy C2 system Network efficiency

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Enhanced EEGNet optimization Using Lightweight Deep Neural Network for Detecting Human Stress Levels from Raw EEG Signals Dataset 3

Enhanced EEGNet Optimization Using Lightweight Deep Neural N...

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3rd international conference on Integrated Circuits and Communication Systems, ICICACS 2025

作者： Hana, Silabdi Hassan, Raini Faizabadi, Ahmed Rimaz Gubbi, Abdullah Bellary, Mohammed Zakir Manjula, V. International Islamic University Malaysia Kulliyyah of Information & Communication Technology Department of Computer Science Kuala Lumpur Malaysia International Islamic University Malaysia Centre for Unmanned Technologies Kuala Lumpur Malaysia Department of Electronics and Communication Engineering Mangalore India Department of Artificial Intelligence and Machine learning Mangalore India

ISBN: (纸本)9798331508456

Accurate stress detection is essential in neuroscience and healthcare since human stress levels have a substantial impact on general well-being. Although EEG-based stress detection is a popular non-invasive method, real-time applications are limited by the high processing costs of classic feature extraction techniques. This work removes the requirement for intricate feature extraction by presenting an efficient EEGNet framework for real-time stress prediction utilizing raw EEG signals. The suggested approach improves accuracy and efficiency by utilizing Z-score normalization and adjusting batch size. Compared to traditional CNNs, the lightweight EEGNet architecture's depth-wise and separable convolutions ensure computational efficiency by reducing trainable parameters by a factor of ten. The proposed method outperformed current EEGNet-based techniques in stress identification by 5% to 18%. Furthermore, the improved system efficiently handles raw EEG signals, which is suitable for real-time, resource-constrained scenarios. The results shows the effectiveness of model-centric optimization in deep learning and open the door to the creation of more effective stress detection techniques. This work provides a workable solution for real-time non-invasive stress monitoring, highlighting the significance of lightweight frameworks customized for particular applications. © 2025 IEEE.

关键词： Deep neural networks

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optimization design of the ducted fan powered high-lift system based on i-sight platform 3

Optimization design of the ducted fan powered high-lift syst...

引用

3rd international conference on Materials Engineering and Applied Mechanics (ICMEAAE)

作者： Mao, Sen Li, Gang Zhao, Chuangxin Guo, Qiang Feng, Wenliang Xie, Zongming Chengdu Aircraft Ind Grp Co Ltd Chengdu Sichuan Peoples R China

The vertical/short take-off and landing (V/STOL) unmanned aircraft vehicle (UAV) equipped with a ducted fan has a broad application prospect, and the design of the ducted fan-powered high-lift system has become one of the key factors in the design and development. The i-Sight platform is used to optimize the design of the 2D ducted fan-powered high-lift system in the paper. First, the parametric modeling of the main control parameters is carried out, and then the i-Sight platform is built to carry out optimization calculations. Finally, three optimal design points are found for detailed aerodynamic characteristics analysis, and then the optimal scheme is selected. The i-Sight platform is proven to be accurate and efficient. By moving the ducted fan horizontally forward from the initial position to 160 mm, a larger lift coefficient can be obtained, while moving the ducted fan vertically from the initial position to 300 mm, a larger lift resistance ratio can be obtained.

关键词： Unmanned aerial vehicles (UAV)

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2024 3rd international conference on Creative Communication and Innovative Technology, ICCIT 2024

2024 3rd International Conference on Creative Communication ...

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3rd international conference on Creative Communication and Innovative Technology, ICCIT 2024

ISBN: (纸本)9798350367492

The proceedings contain 183 papers. The topics discussed include: FinTech innovation and financial inclusion in Malaysia: a systematic review;AI-driven optimization for startup partnership matching;examining customer behavior for SMEs in mobile food online delivery (MFOD) applications;leveraging environmental management systems and green transformational leadership to enhance employee support for sustainability through ethical behavior;network and server performance monitoring using LibreNMS, Telegram, and UniFi controller;technology integration in cultural heritage preservation enhancing community engagement and effectiveness;enhancing Arabic language teaching through artificial intelligence: assessing effectiveness and educational implications;and unveiling ethical challenges and malpractice in academic research and integrity.

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Research on predictive control system for inspection robots based on digital twins 3

Research on predictive control system for inspection robots ...

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3rd international conference on Robotics, Artificial Intelligence and Intelligent control (RAIIC)

作者： Liu, Yu Liu, Hongwei Liu, Manlu Liu, Xin Southwest Univ Sci & Technol Sch Informat Engn Mianyang 621010 Sichuan Peoples R China Southwest Univ Sci & Technol Robot Technol Used Special Environm Key Lab Sichu Mianyang 621010 Sichuan Peoples R China

ISBN: (纸本)9798350352634;9798350352627

In order to improve the motion stability and monitorability of inspection robots, a digital twin predictive control system for inspection robots based on Unity3D and Robot Operating System (ROS) is proposed. Firstly, with the support of wireless communication technology and ROS system, the mapping of virtual-real space scene and robot state is carried out through TCP/IP protocol;secondly, considering the impact of data communication lag and signal loss on the control system, a predictive control model is constructed to control the robot's motion in order to reduce the reliance on real-time data, and the predictive control model is optimized by using Laguerre's function as well as filtering algorithm to optimize the control response and mitigate control oscillations in time;finally, in the virtual decision space, the physical robot is driven to follow the predicted trajectory in a synchronized mapping manner. The experimental results prove that the digital twin control system has good tracking performance and is stable and reliable. Compared with that before model optimization, the efficiency is improved by 50.93% and the error is reduced by 69.23%.

关键词： digital twin Unity 3D predictive control model laguerre function

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Defensive Strategies Against CAN-Bus Infiltrations 3

Defensive Strategies Against CAN-Bus Infiltrations

引用

3rd IEEE international conference on Industrial Electronics: Developments and applications, ICIDeA 2025

作者： Sharma, Pratham Seema Rana, Prashant Singh Singh, Mukesh Kumar, Amit Anand, Ashima Thapar Inst. of Engg. And Technology Department of Computer Science Punjab Patiala India Thapar Inst. of Engg. And Technology Department of E & I Engg. Punjab Patiala India

ISBN: (纸本)9798331533205

The Computerization of vehicles rapidly accelerated, and as vehicle networks link to external networks, automotive security becomes a critical issue. The controller Area Network (CAN) bus is the most widely used internal control network in automobiles, facing growing vulnerabilities. With the development of networked and self-driving technology, the sealing nature of automotive internal control networks is eroding, leaving the security standards inadequate by modern benchmarks. This paper aims to provide a brief overview of the defence strategies against CAN Bus infiltrations, identify current limitations to these existing strategies, and discuss the challenges of enhancing the security in automotive embedded systems. © 2025 IEEE.

关键词： Proportional control systems

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A Review of Big Data applications Based on RISC-V 24

A Review of Big Data Applications Based on RISC-V

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3rd international conference on Algorithms, Data Mining, and Information Technology, ADMIT 2024

作者： Gao, Yue Cui, Enfang Li, Tianzheng China Telecom Research Institute Beijing China

ISBN: (纸本)9798400718120

With the rapid development of big data technology, there is an increasing demand for underlying computing architectures. RISC-V, as an open-source instruction set architecture, has shown tremendous potential and advantage in the field of big data due to its openness, flexibility, and cost-effectiveness, especially the characteristics of RISC-V instruction set being concise, modular, and extensible. The article first reviews the technical background of RISC-V and its current status in the field of big data, highlighting its performance advantages in processing large-scale data sets. It further analyzes the integration and adaptation of the big data core software stack on the RISC-V platform and discusses its optimization. Finally, the article looks forward to the role of RISC-V in the future development of big data technology, providing a forward-looking perspective for research in related fields. © 2024 Copyright held by the owner/author(s).

关键词： Data integration

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A Novel Heat Dissipation optimization Design Scheme of Printed Circuit Board 3

A Novel Heat Dissipation Optimization Design Scheme of Print...

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3rd international conference on Energy, Power and Electrical Technology, ICEPET 2024

作者： Hou, Daizheng Zhang, Yanfei Zhou, Yafu Dalian University of Technology School of Mechanical Engineering Dalian116024 China

ISBN: (纸本)9798350352658

In order to enhance the thermal reliability of the Printed Circuit Board (PCB) in the Vehicle control Unit (VCU) and prevent overheating-induced damage that could lead to VCU failure, this study focuses on optimizing the heat dissipation of a vehicle controller's PCB. The proposed approach involves constructing thermal resistance and thermal path models for the chip, utilizing an electrothermal mixing method to simulate the PCB. Subsequently, a thermal test bench was utilized to measure the overall board temperature using a thermal imager, which was then compared to simulation results from the electric heating mixture. The study concludes with a PCB heat dissipation optimization design that considers copper foil thickness, thermal hole placement, and the structure of fin type radiator to enhance heat dissipation. By optimizing the PCB layout and incorporating heat sinks, the temperature distribution across the board is effectively reduced. Experimental findings indicate a 16.02°C decrease in the maximum PCB temperature post-optimization compared to pre-optimization levels, showcasing a successful optimization outcome. © 2024 IEEE.

关键词： Velocity control

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