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6th International Conference on Recent Trends in Advance Computing, ICRTAC 2023

作者： Margret Sharmila, F. Shree Harini, R. Vityarubbasiri, M. Gopi Krishna, S. Sri Krishna College of Engineering and Technology Department of Computer Science and Business System Coimbatore641008 India

ISBN: (纸本)9798350394702

Early identification and diagnosis of cancerous cells will focus on the symptomatic patients, to give the best way of successful treatment. When the detection of cancer is delayed, then there is a lower chance of survival, high problems with treatment and higher cost estimates. Considering Pancreas Cancer growth, a type of cancer that is difficult to identify because there are less or no symptoms found at the early stage. So, we introduce Artificial Intelligence (AI) technology to identify pancreatic cancer cells. This is the first insight that is provided to detect cancerous cells at the early stage. With the use of technologies, anything is possible, so we use the process of medical imaging analysis, data processing and Machine Learning (ML) for the recognition. Data is collected through MRI and CT scan reports, biomarkers tests, liquid biopsies, endoscopic techniques, early symptom monitoring, and genetic testing which is then categorized into train and test sets. Every training data set is analyzed to provide a standard image to extract the features with the use of OpenCV. Building an AI model with the use of the Convolutional Neural Network (CNN) algorithm with an efficient set of filters. Training the model with the training data set helps to improve the accuracy of predicting results. When it is ready, the testing data set is used to check the accuracy of predictions. Finally, by assessing the model based on the performance metrics from both training and testing datasets, accuracy is achieved. After achieving a certain level of accuracy, and leveraging ML algorithms such as Hybrid models, the system can provide treatment recommendations consistent with a separate training dataset. This training dataset comprises predicted treatments corresponding to the achieved accuracy. After, the system is prepared for deployment. The envisioned process can track the patient's status for future use. © 2023 IEEE.

关键词： Forecasting

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High-Performance Chip design With Parallel Architecture for Magnetic Field Imaging system

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IEEE Transactions on Instrumentation and Measurement 2024年 73卷 1-13页

作者： Lin, Ming-Yi Hsieh, Sheng-Hsien Chen, Ching-Han Lin, Chun-Hung Yuan Ze University Department of Computer Science and Engineering Taoyuan320315 Taiwan National Pingtung University of Science and Technology Program of Artificial Intelligence and Mechatronics Pingtung912301 Taiwan National Central University Department of Computer Science and Information Engineering Taoyuan32001 Taiwan International Games System Company Ltd. New Taipei City248 Taiwan

To address the limitations of typical coil detection systems and enhance the performance of traditional magnetic field imaging (MFI) systems, we propose a MFI system that uses a 4×4 array of anisotropic magnetoresistance (AMR) sensors. The core controller of the proposed system was designed using a pipelined parallelization algorithm and implemented on a high-speed field-programmable gate array (FPGA) in a fully hardware-based architecture. The designed MFI system can achieve parallel acquisition of magnetic field components from the 16-channel AMR sensor array, parallel data processing, parallel data transmission, and parallel computations in a single cycle of only 4 ms. Compared with typical detection systems, the proposed solution not only exhibits superior performance but can also provide dynamic visual representations of sensed information. © 1963-2012 IEEE.

关键词： Parallel architectures

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高功率便携式生物质燃烧驱动温差发电机的研发

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engineering 2023年第5期24卷 192-201,I0005页

作者： Guoneng Li Jie Ying Minbo Yi Youqu Zheng Yuanjun Tang Wenwen Guo Department of Energy and Environment System Engineering Zhejiang University of Science and TechnologyHangzhou 310023China

利用生物质燃烧产生电力是贫困地区解决照明、通讯和医疗等基本需求的重要方式。本文开发和测试了一种高功率便携式生物质燃烧驱动的温差发电机(biomass-combustion-powered thermoelectric generator,BCP-TEG),详细研究了其温差分布、... 详细信息

利用生物质燃烧产生电力是贫困地区解决照明、通讯和医疗等基本需求的重要方式。本文开发和测试了一种高功率便携式生物质燃烧驱动的温差发电机(biomass-combustion-powered thermoelectric generator,BCP-TEG),详细研究了其温差分布、功率负载特性和不同层级的效率,并开展了现场应用测试。研究结果发现该温差发电机在自身重量为7.6 kg的条件下可同时产生750 W的热力和23.4 W的电力,热电联供效率达到32.3%。温差发电机的发电净功率密度为2.41 W·kg^(-1),均高于所有基于闭式循环冷却的文献报道结果。此外,利用本文开发的温差发电机燃烧1 kg的木条所发出的电能可充满1个容量为6.2 A·h的3.7 V锂电池。最后,论文详细讨论了BCP-TEG研究领域存在的问题和未来可研究的方向。

关键词：温差发电机热电联供闭式循环锂电池负载特性应用测试功率密度 BCP

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A2Fitness:An Artificial Intelligent Fitness Assistance system Using a Augmented Reality Smart Glasses for Elderly Health-Promotion

A2Fitness:An Artificial Intelligent Fitness Assistance Syste...

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2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Chang, Wan-Jung Chen, Hong-Wen Su, Jian-Ping Liu, Shu-Ching Ou, Yang-Kun Chen, Ming-Che Southern Taiwan University of Science and Technology Department of Electronic Engineering Tainan Taiwan Southern Taiwan University of Science and Technology Department of Product Design Tainan Taiwan

ISBN: (纸本)9798350324174

This paper proposes a fitness assistance system, called A2Fitness, which integrates with an AI subsystem and an AR subsystem. By using A2Fitness, the elderly can wear an AR smart glasses at anytime and anywhere to instantly see the images and correctness of their physical fitness movements. Therefore, A2Fitness is quite suitable as a physical fitness tool for the elderly to effectively promote their own health. © 2023 IEEE.

关键词： Augmented reality

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An Elite Archive-Assisted Multi-Objective Evolutionary Algorithm for mRNA design 13

An Elite Archive-Assisted Multi-Objective Evolutionary Algor...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Hong, Wenjing Chen, Cheng Zhu, Zexuan Tang, Ke Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen China Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen China Southern University of Science and Technology Department of Computer Science and Engineering Shenzhen China

ISBN: (纸本)9798350308365

Messenger RNA (mRNA) vaccines have emerged as highly effective strategies in the prophylaxis and treatment of diseases. mRNA design, a key to the success of mRNA vaccines, in-volves finding optimal codons and increasing secondary structure stability to lengthen mRNA half-life, ultimately enhancing protein expression. Despite receiving widespread attention, most methods primarily rely on manual design, which is time-consuming and labor-intensive. While optimization approaches can alleviate this issue, existing methods still exhibit critical limitations caused by conflicts between codon usage and mRNA structural stability, compounded by the vast design space of mRNA resulting from the presence of synonymous codons. In this paper, a novel multi-objective evolutionary optimization-based mRNA design method is proposed. We first formulate the mRNA design problem as a multi-objective optimization problem and then develop an Elite Archive-Assisted Multi-Objective Evolutionary algorithm for mRNA design, namely EAA-MOED, by incorporating a novel elite archive-assisted method into a weighted optimization framework to improve search efficiency. Experimental studies, involving two state-of-the-art mRNA design methods and five well-known MOEAs, show the competitiveness of the proposed EAA-MOED in mRNA design. © 2024 IEEE.

关键词： Vaccines

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design of a Dog-type Social Robot to Support Children's Reading Activities and Development of a Touch Sensor Module for Users' Touch Interaction 23

Design of a Dog-type Social Robot to Support Children's Read...

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23rd International Conference on Control, Automation and systems, ICCAS 2023

作者： Kwon, Yongseop Jeong, Seungbin Park, Haeun Lee, Hui Sung Ulsan National Institute of Science and Technology Creative Design Engineering Seoul44919 Korea Republic of Ulsan National Institute of Science and Technology Department of Design Seoul44919 Korea Republic of

ISBN: (纸本)9788993215274

'Read to a Dog' is a program operated in the United Kingdom, the United States, and New Zealand to induce children's interest in reading through children's reading to dogs. This program is a type of animal-assisted therapy (AAT) that uses pets to heal psychological problems, and it can reduce reading rejection and induce interest in reading by providing an environment where children can read confidently and feel comfortable. This study aims to develop a dog-type robot that can be operated in the library based on the research contents of the corresponding 'Read to a Dog'. The purpose of this study is to stimulate children's interest in reading through a reading activity support robot, while giving them with an emotional experience of artificial intelligence through robots. Through robot use environment analysis and user analysis, the appearance shape of the robot is designed and the service requirements are defined. In addition, for touch interaction for emotional communication between children and the dog-type robot, this paper proposes a touch sensor technology using a pressure sensor and Micro Electro Mechanical systems (MEMS) microphone, which can reduce hardware complexity and detect a wide range of touch of a robot. © 2023 ICROS.

关键词： Human robot interaction

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RESEARCH ON LOCA DYNAMIC ANALYSIS MODEL OF REACTOR system 29

RESEARCH ON LOCA DYNAMIC ANALYSIS MODEL OF REACTOR SYSTEM

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2022 29th International Conference on Nuclear engineering, ICONE 2022

作者： Liu, Shuai Harbin Engineering University Harbin China Science and Technology on Reactor System Design Technology Laboratory Chengdu China

ISBN: (纸本)9780791886472

The reactor system has a large scale of components. And the system dynamic analysis model for loss of coolant accidents(LOCA) contains many non-linear factors. The transient calculation analysis takes a long time and the convergence is difficult to guarantee. In this paper, two different analysis models (complete three-loop model and single-loop model) of the reactor loop system are established for comparative analysis. The analysis shows that the calculation error of the main position load in the two different model is within 10%. The decoupling influence of the surge tube and the reactor inlet and outlet on the system dynamic characteristics is within an acceptable range. When the single-loop model is used, it is necessary to decouple the reactor pressure vessel and pressurizer. And the simplified boundary is adapted to simulate its effect on the whole loop. The single-loop dynamic analysis model based on the decoupling criterion can greatly reduce the calculation scale and meet the calculation accuracy, which can be used to calculate the LOCA dynamic characteristics of the reactor system quickly. The model can also be used for seismic analysis of reactor system. And using this model for reactor system dynamic analysis can greatly improve the calculation efficiency. Copyright © 2022 by ASME.

关键词： Loss of coolant accidents

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Deep Learning to Classify Bacterial Species in the same Genus

Deep Learning to Classify Bacterial Species in the same Genu...

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2024 International Conference on Electronics, Information, and Communication, ICEIC 2024

作者： Sheela, Sherin Piang, May Phu Sakorntanant, Sakda Poomrittigul, Suvit Treebupachatsakul, Treesukon School of Engineering King Mongkut's Institute of Technology Ladkrabang Department of Biomedical Engineering Thailand Pathumwan Institute of Technology Faculty of Science and Technology Department of Software Engineering and Information System Bangkok Thailand School of Information Technology King Mongkut's Institute of Technology Ladkrabang Thailand

ISBN: (纸本)9798350371888

Bacterial strains in the same genus share highly similar morphology, gram-staining characteristics, colony sizes, and spatial arrangements. Therefore, identifying them by deep learning can be quite challenging. This study aimed to assess the classification of 7 species of bacteria from 2 genera of Bacillus and Vibrio by using 8 Convolutional Neural Network (CNN) models. We implemented Python programming along with Keras API within the Jupyter Notebook. The models were constructed and evaluated under unbalanced and balanced datasets by augmentation (rotation, flip, etc.). Transfer learning with fine-tuning, and pre-processing of mixup and label smoothing were also applied to reduce overfitting and enhance generalization. Based on the experimental results on private dataset, the results of InceptionResNetV2 emerged as the top-performing model with a notable accuracy of 82.8%, 88.6% precision, 78.4% recall, and 78.0% F1-score when label smoothing was applied at 0.5 on balanced dataset. © 2024 IEEE.

关键词： Neural network models

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Bioinspired magnetic cilia:from materials to applications

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Microsystems & Nanoengineering 2023年第6期9卷 107-128页

作者： Seongjin Park Geonjun Choi Minsu Kang Woochan Kim Jangho Kim Hoon Eui Jeong Department of Mechanical Engineering Ulsan National Institute of Science and Technology(UNIST)Ulsan44919Republic of Korea Department of Convergence Biosystems Engineering Chonnam National UniversityGwangju61186Republic of Korea Interdisciplinary Program in IT-Bio Convergence System Chonnam National UniversityGwangju61186Republic of Korea

Microscale and nanoscale cilia are ubiquitous in natural systems where they serve diverse biological *** artificial magnetic cilia have emerged as a highly promising technology with vast potential applications,ranging from soft robotics to highly precise *** this review,we comprehensively discuss the roles of cilia in nature and the various types of magnetic particles utilized in magnetic cilia;additionally,we explore the top-down and bottom-up fabrication techniques employed for their ***,we examine the various applications of magnetic cilia,including their use in soft robotics,droplet and particle control systems,fluidics,optical devices,and ***,we present our conclusions and the future outlook for magnetic cilia research and development,including the challenges that need to be overcome and the potential for further integration with emerging technologies.

关键词： magnetic overcome precise

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A Multi-Agent Garage Service Search and Recommendation with Hybrid MLs and LLMs

A Multi-Agent Garage Service Search and Recommendation with ...

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2025 International Conference on Computer, Electrical and Communication engineering, ICCECE 2025

作者： Shuvo, Mahfuzur Rahman Rahman, Ashifur Akuthota, Vishwanath Paul, Tanay Islam, Mahfujul Ashraf, Md Sadi Roy, Prosenjit Reza, Md Tanzim International American University Department of Management Information System United States Chittagong University of Engineering and Technology Department of Computer Science and Engineering Bangladesh TechOptima Hyderabad India Brac University Department of Computer Science and Engineering Bangladesh Prairie View A & M University Department of Computer Science TX United States

ISBN: (纸本)9798331513894

The automobile service industry's explosive growth highlights the need for creative approaches to boost operational effectiveness and user experience. This study introduces a Hybrid Garage Assistance system, integrating Classical Machine Learning (ML) techniques with Generative AI to optimize garage service discovery and analysis. The system employs sophisticated data processing methods, including Term Frequency-Inverse Document Frequency (TF-IDF) vectorization and regex-based service detection, to extract actionable insights from unstructured garage *** to the system are machine learning models Random Forest (RF) and XGBoost (XGB) which achieve high precision and recall in classifying garage services. A hybrid search mechanism, combining cosine similarity with ML-driven predictions, ensures the delivery of highly personalized search results. To further refine decision-making, the system incorporates Generative AI models such as Perplexity for web-based research, Gemini for location-specific analysis, Mistral for email sending and GPT-4 for detailed service recommendations and dall-e for creating user specific parts images. These advanced tools provide users with comprehensive information that enables them to make well-informed decisions about garage *** evaluation of the system is conducted using robust metrics, including precision, recall, F1-score, and system latency. Experimental results reveal a precision of 85%, recall of 70.8%, and an F1-score of 77.2%, demonstrating the efficacy of integrating classical ML with generative AI. The system's average latency of 5.9 seconds ensures a seamless and responsive user *** hybrid framework highlights the potential of blending classical ML and Large Language Models (LLMs) to enhance search and recommendation functionalities, offering a scalable and robust blueprint for future advancements in the automotive service sector. The system's Propose a Multi-Agent system With high accuracy,

关键词： Inverse problems

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