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23rd IEEE international conference on High Performance computing and Communications, 7th IEEE international conference on Data Science and Systems, 19th IEEE international conference on Smart City and 7th IEEE international conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Wang, Zhen Yao, Nan Liu, Ziquan Zhu, Xueqiong Xue, Hai State Grid Jiangsu Electric Power Co. Ltd. Research Institute Nanjing Jiangsu210000 China

ISBN: (纸本)9781665494571

Vehicles detection from the transmission environment is one of the main challenges causing by various scenarios. Many techniques have been used to detect engineering vehicles. In this paper, we describe the co-learning mechanism to detect the engineering vehicles, which can effectively use for the external invasion risk early warning. this paper studies the problem of label distribution from the perspective of distillation technology, which we call label distribution distillation (Label Assignment Distillation). About Knowledge Distillation (Knowledge Distillation), a common approach is Teacher Model. For target detection, classification and positioning tasks are usually extracted independently, whether or not a priori value is used. On the contrary, we propose classification and positioning prediction and prior knowledge of middle school teachers are incorporated into the loss function. the final performance is validated in our collected dataset to prove the superiority. © 2021 IEEE.

关键词： Object detection Task analysis

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Optimization and Design of Coding Algorithm for Monitoring System Based on Embedded Structure 7

Optimization and Design of Coding Algorithm for Monitoring S...

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7th international conference on Intelligent computing and Signal Processing, ICSP 2022

作者： Huang, Rubing Zhao, Lianyi Anhui Vocational and Technical College School of Information Engineering Hefei China Anhui Water Resources and Hydropower Vocational and Technical College School of Mechanical & Electrical Engineering Hefei China

ISBN: (纸本)9781665478571

In view of the problems of large transmission delay, low video image compression rate, and high network transmission overhead in traditional monitoring systems. According to the characteristics of ARM platform and H.264 encoding algorithm, an algorithm optimization method based on x264 encoder embedded platform is proposed. the New three-step Search method is used to realize motion compensation prediction encoding. Based on streaming media technology, the RTP and RTSP protocol realizes the packaging and real-time transmission of video stream data. the optimized encoder is applied to the embedded video monitoring system, which effectively improves the video encoding efficiency of the system. © 2022 IEEE.

关键词： Signal encoding

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Optimization of Traffic and Time Control with Sensor-Driven Transmission Control System using MANET and Machine Learning 7

Optimization of Traffic and Time Control with Sensor-Driven ...

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7th international conference on Inventive Computation Technologies, ICICT 2024

作者： Kathirvel, N. Vidyalakshmi, R. Raihana, A. Mohanraj, A. Uma, S. Saranya, N. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science And Technology School of Computing Department of Information Technology India Karpagam College of Engineerng Department of Eee Coimbatore India Sri Krishna College of Engineering And Technology Department of Information Technology Coimbatore India Sri Eshwar College of Engineering Department of Computer Science And Engineering India Hindustan College of Engineering And Technology Department of Computer Science And Engineering India

ISBN: (纸本)9798350359299

In the dynamic landscape of modern urban environments, the optimization of transportation and traffic management systems is paramount for ensuring efficiency, sustainability, and the overall well-being of inhabitants. this study introduces an innovative solution through the deployment of a sophisticated network of strategically positioned sensors at crucial locations, encompassing roadway sections, entry and exit points, and parking spaces within a smart city framework. these sensors continuously capture real-time data on traffic flow, vehicle counts, and parking spot occupancy, forming the foundational elements of an intelligent system. Robust machine learning models, notably Convolutional Neural Networks (CNN), VGG19, k-Nearest Neighbors (KNN), and Support Vector Machines (SVM), are employed to process and analyze the acquired sensor data. CNN, renowned for its prowess in image recognition, emerges as the leading performer, achieving an impressive accuracy of 97.6%. this model excels in deciphering complex spatial patterns, significantly enhancing the precision of traffic forecasts. Additionally, performance metrics, encompassing precision, recall, F1 score, and accuracy, underscore the efficacy of each machine learning model. the exceptional precision and recall values across all models showcase their robustness in identifying and predicting traffic situations, while accuracy scores affirm their overall efficiency in optimizing transportation and traffic management within smart city environments. © 2024 IEEE.

关键词： Sensor networks

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Feature Extraction and Preprocessing Techniques on Open-Ended Concept Mapping Activity Log Data 7

Feature Extraction and Preprocessing Techniques on Open-Ende...

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7th international conference on Vocational Education and Electrical engineering, ICVEE 2024

作者： Prasetya, Didik Dwi Muhtadi, Muis Azizah, Hanifah Nur Zain, Azlan Mohd State University of Malang Department of Electrical Engineering and Informatics Malang Indonesia Universiti Teknologi Malaysia Faculty of Computing Johor Bahru Malaysia

ISBN: (纸本)9798331505103

Concept maps are graphic representations of unique ideas widely used in learning. Concept mapping activities are often stored in an activity log which contains a record of data based on a particular time. the high activity of concept mapping can form extensive data collection and result in abundant information. An appropriate initial processing action is needed to process the concept mapping log data properly. this study aims to reduce the concept of map activity log data to obtain a reliable and noise-free dataset. this research begins with the data preprocessing stage, the initial technique in data mining that converts raw data into cleaner information and can be used for further processing. the preprocessing phase could be done using the data reduction method or adding a filter example to observe missing data on an attribute by eliminating missing observation data. the principal component analysis algorithm was used to normalize the data to become stable, neither too high nor too low. this study emphasizes that the extracted data could produce high accuracy and shorter processing time. © 2024 IEEE.

关键词： Data assimilation

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A Comprehensive Review Analysis on Osteoarthritis Using Deep Learning and Machine Learning Technologies for Arthritis Detection 7

A Comprehensive Review Analysis on Osteoarthritis Using Deep...

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7th international conference on Circuit Power and computing Technologies, ICCPCT 2024

作者： thomas, Tinu Prince Mary, S. Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Chennai India St. Joseph's College of Engineering and Technology Department of Electronics and Computer Engineering Palai India

ISBN: (纸本)9798350372816

Osteoarthritis is a prevalent degenerative knee joint disease, causing considerable pain and mobility issues, thus impacting the independence and quality of life of millions. Deep learning and Machine Learning techniques have emerged as promising tools for enhancing the diagnosis, prognosis, and treatment of osteoarthritis (OA). these technologies allow for the extraction of valuable insights from medical images, clinical data, and genetic information, thereby improving patient care and management strategies. By employing advanced algorithms, healthcare professionals can improve early detection, and treatment plans, and accurately predict disease progression, ultimately leading to better outcomes for OA patients. this paper proposes a comprehensive review of various DL-based and ML-based methods for OA, spanning the years 2020 to 2024. It aims to provide valuable insights for researchers interested in exploring different models and potentially inspiring the development of integrated approaches for even more effective OA detection. © 2024 IEEE.

关键词： Joints (anatomy)

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Intelligent Chatbot for Educational Institutions 7

Intelligent Chatbot for Educational Institutions

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7th international conference on Circuit Power and computing Technologies, ICCPCT 2024

作者： Reddy, Nandigam Srikar Chaitanya, Naini Pranay Varshitha, Panthangi Sai Varma, Rudhraraju Chaitanya Reddy, Patlolla Karthik Dandu, Jagadeesh B V Raju Institute of Technology Computer Science and Engineering Telangana Narsapur India

ISBN: (纸本)9798350372816

Our project introduces an 'Intelligent Chatbot for Educational Institutions'. Responding to the dynamic landscape of educational technology, we unveil an advanced full-stack chatbot initiative Designed to overhaul academic administration and student information access. Our chatbot leverages sophisticated rule based systems and traditional programming paradigms to ensure optimal efficiency. this chatbot excels at processing natural language queries and furnishing real-time updates on students' academic progress and accomplishments. A notable application of its capabilities lies in swiftly identifying and presenting information about the top performing student in a given academic year, such as the college valedictorian of 2022. this functionality is made possible by a meticulously designed algorithm that systematically analyses academic records, discerns query context, and extracts pertinent data to deliver precise and valuable insights to users, including educators, students, and parents. With a user-friendly interface, the chatbot ensures accessibility for users of all technical proficiencies. Our approach places a premium on accuracy in information retrieval and continuous refinement through iterative enhancements, enabling the chatbot to adapt seamlessly to the evolving educational landscape. this initiative aims to establish a new standard in educational technology by providing an innovative solution that streamlines information dissemination and enriches the academic journey for stakeholders in the educational realm, all achieved with reliance on ML and DL technologies. © 2024 IEEE.

关键词： Educational technology

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Study of Hybrid Energy Dissipation Method via MOV-Liquid Metal in DC Interruption 7

Study of Hybrid Energy Dissipation Method via MOV-Liquid Met...

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7th international conference on Electric Power Equipment - Switching technology, ICEPE-ST 2024

作者： Bai, Chenfei Jia, Ziqi He, Hailong Niu, Chunping Wu, Yi Rong, Mingzhe Xi'an Jiaotong University 7th International Conference on Electric Power Equipment- Switching Technology State Key Lab of Electrical Insulation and Power Equipment Xi'an710049 China

ISBN: (纸本)9798350388947

With the development of DC power systems, Metal oxide varistor (MOV), as the traditional energy dissipation device, is difficult to meet the requirements of enhancing energy dissipation density. Liquid metal based on magnetic pinch effect can dissipate energy with its arc under fault current, it can be used in hybrid with the MOVs to perform as the energy dissipation device in DC breaker. In this paper, the resistance characteristics of liquid metal arcs is summarized, mathematical models for each stage of liquid metal material arcing are established, and the simulation model of medium-voltage DC breaker with hybrid energy dissipation is established. the influence of the arc channel size of the liquid metal energy-dissipating unit and MOV parameters on the hybrid energy dissipation effect is analyzed and the optimal parameter design of the hybrid energy dissipation method for medium-voltage DC breaking is given. the research result shows that the use of hybrid energy dissipation device can increase the energy consumption power density by 24.9% compared with MOVs of the same level. © 2024 IEEE.

关键词： Hybrid power

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Gesture-based Control of a Bionic Arm - A Prototype Design 7

Gesture-based Control of a Bionic Arm - A Prototype Design

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7th international conference on computing Methodologies and Communication, ICCMC 2023

作者： Pushpalatha, N. Batcha, Sheikameer Yesvanthkrishna, V. Rathinamala, S. Devi, B. Padmini Gomathi, V. Department of Electrical and Electronics Engineering Sri Eshwar College of Engineering Tamilnadu Coimbatore641 202 India Department of Electrical and Electronics Engineering KIT- Kalaignarkarunanidhi Institute of Technology Tamilnadu Coimbatore641 402 India Computer Science and Engineering M.Kumarasamy College of Engineering Tamilnadu Karur India Department of Electrical and Electronics Engineering Dhanalakshmi Srinivasan College of Engineering Tamilnadu Coimbatore641 105 India

ISBN: (纸本)9781665464086

A bionic arm is a robotic hand that can be controlled manually or by machines. It resembles and acts like a human hand. It makes use of AI technology to make decisions and control other hand movements. the primary function of this hand is to ensure that all productions and tasks are flawless. the movement of the hand can be controlled via a wireless medium;it utilises a camera to grasp the gesture or the task that it needs to perform. It can be used for industrial applications where the periodic function is not carried out by the machine;it is specially designed to perform unique tasks. this can be used to accent the words in the understandable mode for deaf people as well;it converts written or stored content into accent. this system performs multiple tasks as per the instructions provided to it as an input. Most applications that humans cannot perform in various situations can be performed by this bionic arm. © 2023 IEEE.

关键词： Bionics

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Investigation of Water Rivulets Formation on the Pressure Side of a Linear Compressor Cascade Under Wet Compression

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Journal of the Institution of Engineers (India): Series C 2024年第4期105卷 877-890页

作者： Narayanan, Deepak Anand, S. Anish, S. Turbomachinery Laboratory Department of Mechanical Engineering National Institute of Technology Karnataka Mangalore575025 India

the interactivity of the droplets with the surface of the blade is of paramount importance for understanding the physical mechanism of wet compression. Investigation of the formation of water rivulets over the compressor blades at various incidence angles is discussed in this paper. By injecting fine water droplets into a compressor cascade, numerical and experimental investigations have been carried out to study the formation of water rivulet and its propagation. the study has been carried out at various incidence angles. through flow visualization, the wall rivulet formation over the blade surface is analyzed. Accumulation of water droplets over the blade surface is found to be less at a higher impact angle where the droplets disintegration is more. Shear forces arising from the neighboring flow drive the wall film toward the trailing edge, forming small rivulets. the amount of deposited water decreases with the increase in water droplet velocity. © the Institution of Engineers (India) 2022.

关键词： Drops

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Cross-Language Code Development with Generative AI: A Source-to-Source Translation Perspective 7

Cross-Language Code Development with Generative AI: A Source...

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7th IEEE international conference on Electronic Information and Communication technology, ICEICT 2024

作者： Rai, Laxmisha Khatiwada, Smriti Deng, Chunrao Liu, Fasheng Shandong University of Science and Technology College of Electronic and Information Engineering Qingdao China Shandong University of Science and Technology College of Transportation Qingdao266590 China The Hong Kong Polytechnic University College of Professional and Continuing Education Hong Kong Hong Kong Shandong Vocational University of Foreign Affairs College of Information Engineering Weihai China

ISBN: (纸本)9798350384437

Since the release of ChatGPT in November 2022, there is growing interest around the world on exploring the capabilities of generative AI tools. In addition to text, image, audio, and video generation, these tools are also able to generate program codes. In this paper, strategies for students, programmers and enthusiasts to understand the prompting methods to generate codes in multiple languages by translating source code written in one language to another target language using generative AI is explored. the prompts are created to test the ability of generative AI to create codes in C, Java, C++, and Python. Some of the methods of generating the complete program using limited original source code statements is presented. In summary, while generating source code in a target language, generative AI tools downplay the significance of accuracy of statements written in original language, syntax, semantics, as well as missing statements in a program. Irrespective of these, generative AI tools are still able to generate complete code in a target language by correcting errors. © 2024 IEEE.

关键词： Semantics

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