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检索条件"任意字段=International Conference on Computer Technology and Development"

共 99131 条记录，以下是4901-4910 订阅

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Accuracy analysis and development of multi-channel acquisition device for domestic Intelligent Programmable Logic Controller 5

Accuracy analysis and development of multi-channel acquisiti...

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5th international conference on computer Information Science and Artificial Intelligence, CISAI 2022

作者： Liu, Qiang Wang, Yining Co. Ltd. Jiangsu Province Nanjing211106 China

ISBN: (纸本)9781510662520

In this paper, an multi-channel acquisition device suitable for domestic Intelligent Programmable Logic Controller (IPLC) is developed. The GD32F407RE of GigaDevice is used as MCU control system and the AD chip SGM5208 of SGMICRO is used. The upper computer based on Loongson CPU realizes data interaction with the acquisition device through CAN communication. In the experiment, the precision current and voltage source is used to verify and test the developed multi-channel acquisition device. The device can realize the acquisition and transmission of DC analog 0-5V / 0-20mA, achieving a measurement accuracy of 0.1%. The developed multi-channel acquisition device achieves reliable operation in engineering applications. The influencing factors of measurement accuracy and real-time are analyzed, and the software is optimized. The device is designed based on domestic electronic components, which ensures the safety of the chip supply chain. © 2023 SPIE.

关键词： Programmable logic controllers

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Rehabilitation for Stroke Survivors: The development of a Smart Glove 26

Rehabilitation for Stroke Survivors: The Development of a Sm...

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26th international conference on computer and Information technology, ICCIT 2023

作者： Imtiaz, Shatil Humyra, Rahman Sharar Kashem, Md. Rad Khan, Md Fardin Hossain, Md. Sajid Kabir, Md. Humayun American International University Bangladesh Electrical and Electronics Engineering Dhaka1229 Bangladesh

ISBN: (纸本)9798350359015

This research presents the development of a portable arm rehabilitation device designed to continuously monitor and enhance rehabilitation activities. The device incorporates flex sensors, force-sensitive resistors, and accelerometers interfaced with an ESP32 microcontroller to collect data on arm movements. This data is crucial for therapists to fine-tune treatment plans and provide patients with an effective home-based rehabilitation solution. Recent findings have shown the potential of home-based rehabilitation, yet existing technologies are often costly and complex to operate independently. The device aims to bridge this gap by offering a user-friendly and affordable solution. The system integrates various sensors, including flex sensors, force-sensitive resistors, and accelerometers, which are interfaced with an Arduino microcontroller. These sensors capture data related to arm movements, which is essential for therapists to tailor treatment plans and for patients to track their progress. The device aims to bridge the gap between costly and complex rehabilitation technologies and the need for accessible, home-based solutions. The study's novelty lies in its integration of sensor technology into a smart glove and its commitment to providing an affordable and effective rehabilitation solution. The continuous monitoring capabilities of the device offer valuable insights into patients' progress, improving the quality of rehabilitation programs. This work aligns with recent advancements in wearable technology and sensor systems for healthcare applications, emphasizing the importance of accessible rehabilitation solutions. © 2023 IEEE.

关键词： accelerometers ESP32 microcontroller flex sensors force-sensitive resistors healthcare monitoring monitoring portable Rehabilitation smart glove user-friendly wearable

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Digital Twin-based Dynamic Resource Provisioning Using Deep Q-Network on 6G-enabled Mobile Edge Networks 17

Digital Twin-based Dynamic Resource Provisioning Using Deep ...

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17th international conference on COMmunication Systems and NETworkS, COMSNETS 2025

作者： Alex, Suja A. Singh, Neha Adhikari, Mainak St. Xavier's Catholic College of Engineering Department of Information Technology Nagercoil India Indian Institute of Information Technology Lucknow Department of Computer Science Lucknow India Indian Institute of Science Education and Research Thiruvananthapuram School of Data Science Thiruvananthapuram India

ISBN: (纸本)9798331531195

The advancement of Digital Twin (DT) technology has enabled the creation of digital replicas of physical entitics, significantly enhancing the functionality and performance of mobile networks. However, this innovative approach also introduces considerable overload and performance challenges for mobile edge networks. To address these issucs, we propose a novel DT-enabled edge architecture for 6G-capable technology, employing a dynamic resource allocation strategy. The proposed approach, termed DT-based Dynamic Resource Provisioning (DT-DRP), leverages the capabilities of DT technology and Decp Reinforcement Learning (DRL) to dynamically allocate incoming tasks from mobile devices to edge devices. An intelligent DT server facilitates this allocation, optimizing resource use and improving network performance. The predictive capabilities of the framework are validated using the K-Nearest Neighbor (KNN) dlassifier at the edge network. Experimental results demonstrate that the proposed DT-DRP framework incorporates mobile devices into the DT network scamlessly, achieving superior performance in terms of minimum latency and high accuracy compared to bascline Q-learning algorithms across two medical datasets and various exccution scenarios. This research underscores the potential of DT technology in 6G networks and highlights its efficacy in enhancing mobile edge computing performance through intelligent resource management. © 2025 IEEE.

关键词： Mobile edge computing

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Application of Wearable Sensors in Physical education for biomedical surveillance and human-machine interface

Application of Wearable Sensors in Physical education for bi...

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2023 Annual international conference on Emerging Research Areas: international conference on Intelligent Systems, AICERA/ICIS 2023

作者： Alsalhy, Mohammed Jameel Ahmed, Ibrahem Hussien, Naseer Ali Hussain, Angham Khalid Hussian, Ahmed Al-Shaikhli, Taha Raad National University of Science and Technology Department of Medical Devices Engineering Technologies Nasiriyah Dhi Qar Iraq Medical Instruments Engineering Techniques Al-farahidi University Baghdad Iraq Information and Communication Technology Research Group Scientific Research Center Al-Ayen University Thi-Qar Iraq Computer Technologies Engineering Al-Turath University College Baghdad Iraq Al-Kunooze University College Technical Computer Engineering Department Basrah Iraq Computer Engineering Techniques Al-Nisour University College Baghdad Iraq

ISBN: (纸本)9798350303452

Continuous biological surveillance requires less mechanical aid and affordable wearable technology and sensors. The health industry benefits greatly from the rapid development and expansion of the Internet of Things (IoT). Measuring the accuracy of physical education systems is a major difficulty for fitness and sports trackers, as human dependability is a primary concern for these technologies. This study supports the use of a portable sensor device for monitoring activities in athletes' training. The proposed method is achieved with the help of monitoring physical education using a wearable sensor device(MPE-Wsd)to track their health. With the Service Level Agreement (SLA) method, processing power requirements are estimated with the help of a server. The article opened with a unique and compelling model for health. The article offers a portable sensor for use at the human-machine interface. It's convenient for both the participants and the doctor to have access to the various sources of information. With this new field of study, policymakers may make the most efficient use of hardware and software designed for the Internet of Things. Provides the network with instantaneous access to large-scale resources while reducing operational and capital expenditures. Many mental and physiological diseases are rising as the global population ages because point-of-care (POC) treatment and continuous disease monitoring are important. The results of the tests validate the technique as being both convenient and economical to employ regularly. © 2023 IEEE.

关键词： Internet of things

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Bridging the Communication Gap: Sign Language Recognition technology for the Speech and Hearing Impaired 36

Bridging the Communication Gap: Sign Language Recognition Te...

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36th international conference on Software Engineering and Knowledge Engineering, SEKE 2024

作者： Ganta, Shivani Shubbar, Safa Timmapuram, Thejeswar Reddy Vangapalli, Lakshmi Poojitha Jilkara, Komal Baheri, Betis Muhajab, Hanan Muhajab, Areej Ghazinour, Kambiz Miner, Stacy Department of Computer Science Kent State University KentOH United States Department of Computer Science College of Engineering and Computer Science Jazan University Jazan Saudi Arabia Computers and Information Technology College Taif University Taif Saudi Arabia CantonNY United States College of Nursing Kent State University KentOH United States

ISBN: (纸本)1891706594

Sign language is a vital communication medium enabling individuals with speech and hearing impairments to convey thoughts, feelings, and ideas effectively. However, the limited understanding of sign language, outside of the deaf community, can lead to social isolation and barriers to accessing essential services. This paper explores the development of a sign language recognition system to bridge this communication gap by translating sign language gestures into text or spoken language. The proposed system leverages computer vision techniques, including Google’s Media Pipe framework, to capture and analyze hand gestures from video input. By training machine learning models on diverse sign language datasets, the system achieves high accuracy in recognizing American Sign Language (ASL) alphabets, numbers, and medical condition-related gestures. Additionally, the system offers real-time action recognition capabilities, enabling seamless communication between individuals who use sign language and those who do not. Our models are robust to different lighting conditions and varying backgrounds, ensuring consistent performance across various environments. Through integration of advanced technologies, and in collaboration with the deaf community, this research advances autonomy by breaking down communication barriers that will, ultimately, increase accessibility and foster a more inclusive environment for those living with speech and language impairments. © 2024 Knowledge Systems Institute Graduate School. All rights reserved.

关键词： Deep learning

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FarExStance: Explainable Stance Detection for Farsi 31

FarExStance: Explainable Stance Detection for Farsi

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31st international conference on Computational Linguistics, COLING 2025

作者： Zarharan, Majid Hashemi, Maryam Behroozrazegh, Malika Eetemadi, Sauleh Pilehvar, Mohammad Taher Foster, Jennifer School of Computing Dublin City University Ireland Iran University of Science and Technology Iran Dadmatech Tehran Iran School of Computer Science University of Birmingham United Kingdom School of Computer Science and Informatics Cardiff University United Kingdom

ISBN: (纸本)9798891761964

We introduce FarExStance, a new dataset for explainable stance detection in Farsi. Each instance in this dataset contains a claim, the stance of an article or social media post towards that claim, and an extractive explanation which provides evidence for the stance label. We compare the performance of a fine-tuned multilingual RoBERTa model to several large language models in zero-shot, few-shot, and parameter-efficient fine-tuned settings on our new dataset. On stance detection, the most accurate models are the fine-tuned RoBERTa model, the LLM Aya-23-8B which has been fine-tuned using parameter-efficient fine-tuning, and few-shot Claude-3.5-Sonnet. Regarding the quality of the explanations, our automatic evaluation metrics indicate that few-shot GPT-4o generates the most coherent explanations, while our human evaluation reveals that the best Overall Explanation Score (OES) belongs to few-shot Claude-3.5-Sonnet. The fine-tuned Aya-32-8B model produced explanations most closely aligned with the reference explanations. © 2025 Association for Computational Linguistics.

关键词： Computational linguistics

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Research on the Application of computer Big Data technology in English Distance Network Course 6

Research on the Application of Computer Big Data Technology ...

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2023 IEEE 6th international conference on Information Systems and computer Aided Education, ICISCAE 2023

作者： Chunxiu, Yu Guangzhou Huashang Vocational College Guangdong Guangzhou China

ISBN: (纸本)9798350313444

In this paper, an English teaching system based on remote network and embedded software is proposed. The purpose is to further improve the intelligence of English electronic education. This paper presents a design method of speech precision automatic comparison system based on multimode control. Firstly, the overall design framework of speech precision automatic comparison system is developed. TMS320VC5509A is chosen as the core control chip. Then the hardware design of the system is developed, including A/D circuit, external storage circuit, power-on loading circuit, system logic decoding control circuit and LCD interface design. Finally, the hardware assembly and software debugging of the system are completed. The experiment proves that this system has good reliability and good correction rate in English distance teaching. © 2023 IEEE.

关键词： English distance teaching english teaching multimode control phonetic contrast system development

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Advanced Joint Monitoring System Utilizing Real-time Data and KNN Algorithm for Prediction of Joint Health 4

Advanced Joint Monitoring System Utilizing Real-time Data an...

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4th international conference on Innovative Practices in technology and Management, ICIPTM 2024

作者： Antony Joseph Rajan, D. Raman, Ramakrishnan Mookherjee, Ujal Kumar Vekariya, Daxa Ganeshbabu, T.R. Rajmohan, M. Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India Maharashtra Pune India Maharashtra Pune India Parul University Faculty of Engineering and Technology Parul Institute of Engineering and Technology Gujarat Vadodara India Department of Electronics and Communication Tamil Nadu Namakkal India Hindustan Institute of Technology and Science Department of Electronics and Communication Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350307757

This research proposes a novel strategy for the field of tele-orthopedics by incorporating a K-Nearest Neighbors (KNN) algorithm into a Raspberry Pi-based remote joint monitoring system. The KNN model can provide accurate predictions about the present condition of the joint health of orthopedic patients by using real-time data from sensors that capture joint movement measures. The technology makes it easier for medical experts to intervene at the appropriate moment, which in turn makes it possible to design treatment programs that are more individualized and data-driven. The solution enables patients and healthcare practitioners to communicate without interruptions by using a protected platform hosted in the cloud. The malleability and interpretability of the KNN algorithm contribute to a sophisticated framework for tele-orthopedics, which offers precise insights into the development of orthopedic therapies. This study lays a framework for future developments in remote patient monitoring for orthopedic treatment. It proves that it is possible to use machine learning in telemedicine, which is a significant contribution to the field. © 2024 IEEE.

关键词： Orthopedics

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Performance Improvement of Model View Controller based Applications through Linda's-Key

Performance Improvement of Model View Controller based Appli...

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2023 international conference on Signal Processing, Computation, Electronics, Power and Telecommunication, IConSCEPT 2023

作者： Suhas Reddy, P. Anala, Jayanth Krishnamurthy, Vallidevi Balasubramanian, Surendiran Sujithra Kanmani, R. School of Computer Science and Engineering Vellore Institute of Technology Chennai India School of Computer Science and Engineering Vellore Institute of Technology Vellore India National Institute of Technology Puducherry Department of Computer Science and Engineering India

ISBN: (纸本)9798350312126

The Model-View-Controller (MVC) design pattern is widely used in software engineering for developing user interfaces. While MVC offers many benefits, handling data in a way that is efficient and effective can be a challenge. One approach to optimising the performance of MVC applications is converting lists to dictionaries. This paper discusses the benefits and drawbacks of this approach and presents the findings of recent research on this topic. The main advantage of converting lists to dictionaries is that it can improve the performance of MVC applications by offering faster access times and making code easier to read and maintain. However, there are drawbacks to this approach, such as increased memory usage and slower performance for certain operations. Several studies have been conducted on the performance of MVC applications when using lists versus dictionaries, with varying results. This paper overviews this research and highlights the implications for MVC development. © 2023 IEEE.

关键词： Data handling

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EPipe: Pipeline Inference Framework with High-quality Offline Parallelism Planning for Heterogeneous Edge Devices 24

EPipe: Pipeline Inference Framework with High-quality Offlin...

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43rd international conference on computer-Aided Design, ICCAD 2024

作者： Xiong, Yi Liu, Weihong Zhang, Rui Zu, Yulong Zhu, Zongwei Zhou, Xuehai School of Computer Science and Technology University of Science and Technology of China China Suzhou Institute for Advanced Research University of Science and Technology of China China School of Software Engineering University of Science and Technology of China China

ISBN: (纸本)9798400710773

Pipeline parallelism is essential for edge computing as it effectively consolidates the limited resources of edge devices, enabling the deployment of large Deep Neural Network (DNN) models and accelerating inference processes without compromising the performance of models. Accurate computation and communication latency estimation on heterogeneous edge devices is essential for searching for a superior parallelism plan. However, existing heterogeneous pipeline inference approaches either incur substantial resource wastage during online parallelism planning, as they utilize profiling strategies that occupy physical devices;or rely on cost models with inadequate representational capabilities, leading to inaccurate predictions, thereby harming the result of pipeline planning. This paper proposes EPipe, a novel pipeline inference framework that supports high-quality offline planning in heterogeneous edge environments. EPipe integrates two core components: the Task-Device Co-analyzer (TDC) and the Multi-pipeline Parallelism Planner (MPP). TDC utilizes an undirected connected graph to depict the compatibility of DNNs across device groups and precisely estimates inference and communication latencies through fine-grained modeling. Based on TDC, MPP utilizes a dynamic programming-based genetic algorithm to explore multi-pipeline solutions, extending beyond traditional single-pipeline methods. A comprehensive experimental evaluation on an edge testbed confirms the effectiveness of EPipe, demonstrating significant speedups in inference tasks for both task streams and single tasks. © 2024 Copyright is held by the owner/author(s).

关键词： Edge detection

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