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检索条件"任意字段=7th International Conference on Computer and Information Processing Technology, ISCIPT 2022"

共 4197 条记录，以下是541-550 订阅

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Asset Management System with Digital technology: A Case Study of Government Agencies 7

Asset Management System with Digital Technology: A Case Stud...

引用

7th international conference on Digital Arts, Media and technology, DAMT 2022 and 5th ECTI Northern Section conference on Electrical, Electronics, computer and Telecommunications Engineering, NCON 2022

作者： Panjom, Khunanon Chayanitivuth, Chanichnant Leepreecha, Niracha Rujivorakul, Vittayasak Mae Fah Luang University Software Engineering Chiang Rai Thailand

ISBN: (纸本)9781665495103

Developing an asset management system is complex and involves multiple processes, people, and devices, making it difficult to verify the accuracy of the data, including the time required for each step to verify the results. the work proposes adopting digital technology that combines web and mobile applications to simplify the process. From the original (As Is) functional design to the new functional design (To Be), testing with those involved in the equipment inspection process to improve the design. the results showed that the new system with digital technology reduced the total time by 741 minutes or more than 90%. the system also reduces the time involved in reporting and documentation by 1-2 weeks, ensuring that the adoption of digital technology in equipment inspection can significantly reduce time and processes. as well as helping to create sustainability and good governance for the organization © 2022 IEEE.

关键词： information management

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Yuwathi: Early Detection of Breast Cancer and Classification of Mammography Images Using Machine Learning 7

Yuwathi: Early Detection of Breast Cancer and Classification...

引用

7th IEEE international conference for Convergence in technology, I2CT 2022

作者： Munasinghe, Suranga Mahesh Diddugoda, Devindi Fernando, Dinuwan Bhagya Weerasinghe, Lokesha Weerathunga, Ishara Sri Lanka Institute of Information Technology Faculty of Computing Malabe Sri Lanka

ISBN: (纸本)9781665421683

According to the World Health Organization's (WHO) data and records, breast cancer is one of the most common diseases among women. As a result of the mutations of the genes within a cell, the cell starts growing uncontrollably and rapidly. Such a condition is known as cancer. Cancer tumors can be categorized into two major categories, benign and malignant. However, there is no existing solution in practice to automate early breast cancer identification and risk prediction using medical images (Mammograms). this paper discusses automating breast cancer detection, breast density identification, risk prediction, and solution suggestion using machine learning, image processing, and computer vision techniques. All the mentioned features can be accessed using the application "YUWAthI", and a user can take advantage of this application by using a smartphone also a web application. the objectives of the present study are mammographic mass detection without user intervention, identifying pectoral muscles and removing them, training a machine learning model to identify the future risk of breast cancers by obtaining clinical reports from the OCR application and suggesting solutions for the above problems using a computer-aided diagnosis (CADx) system that helps doctors to make decisions swiftly. the algorithms used for breast cancer detection, breast density classification, and future breast cancer risk prediction are Convolutional Neural Network (CNN), CNN and Logistic Regression with the accuracies 97.32%, 71.97% 74.76%, respectively. © 2022 IEEE.

关键词： Image classification

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Bus Route Tracking System 7th

Bus Route Tracking System

引用

7th IFIP TC 12 international conference on Computational Intelligence in Data Science, ICCIDS 2024

作者： Rubesh Muthuvel, R. Nithish Sankar, B. Kasirajan, P. Dheenathayalan, S. Department of Computer Science and Engineering National Engineering College Kovilpatti India

ISBN: (纸本)9783031699856

this research paper explores the challenges faced by daily bus commuters and presents a transformative live route monitoring system designed to address these issues. the project focuses on local buses and utilizes a user-friendly web application integrated with Google Maps. Key features include personalized notifications, precise real-time tracking, and historical performance data for efficient journey planning. the integration of crowd-sourced insights and multimodal functionality enriches user decision-making, while emergency communication, multilingual support, and energy-efficient tracking contribute to an enhanced overall experience. the project also includes a community engagement platform to encourage collaboration and feedback. Accessibility features and offline functionality ensure inclusivity and convenience, while strategic partnerships with local transport authorities bolster system accuracy. © IFIP international Federation for information processing 2024

关键词： Decision making

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the Making of Fractal Art Motion Art Inspired by the Yi Peng Festival Lights 7

The Making of Fractal Art Motion Art Inspired by the Yi Peng...

引用

作者： Sookkaew, Jirawat Budsri, Pakawad Sukmuang, Rachen University of Phayao Major of Computer Graphic and Multumedia Faculty of Information and Comunication Technology Phayao Thailand

ISBN: (纸本)9781665495103

the purpose of this research is to produce research art. the researcher studied the Yi Peng tradition in terms of the elements of activities that use light as an element, and then design and create a digital fractal art piece based on the research data. By incorporating the play of colors from the people's culture in Lanna's culture. the Lanna Kingdom, which is comprised of various tribes, nationalities, and religions, influences the Lanna's people traditions and beliefs. By introducing a fractal art form of artistic creation combined with cultural inspiration of light in Yi Peng. the resulting work can convey art by utilizing lines and shapes to create images in this art that are suitable for the composition and style of the highlight of fractal art identity style and light of Yi Peng festival perfectly. © 2022 IEEE.

关键词： Fractals

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LLM for Uniform information Extraction Using Multi-task Learning Optimization 7th

LLM for Uniform Information Extraction Using Multi-task Lear...

引用

8th Asia Pacific Web and Web-Age information Management Joint international conference on Web and Big Data

作者： Li, Ying Tan, Zhen Xiao, Weidong Natl Univ Def Technol Natl Key Lab Informat Syst Engn Kaifu Peoples R China

ISBN: (纸本)9789819600540;9789819600557

With the increasing maturity of deep learning technology, large language models have shown excellent performance in the field of natural language processing, but the performance of information extraction is yet to be further improved. In this paper, we use 7B Llama-2 as a base model training to obtain a large language model capable of using natural language to guide information extraction tasks, which can solve the challenges faced by traditional information extraction methods, and also innovatively use multi-task learning optimization to improve the performance of the large model. We performed large-scale pretraining and instruction tuning on the big model LLama-2. Based on the highquality and richly typed training data automatically constructed by ChatGPT, remote supervision, and other algorithms, which contains a total of 1 million entities, relations, and events, we designed corresponding English templates for instruction tuning. Second, we performed supervised fine-tuning of the model using manually labeled high-quality training sets. To further improve the model performance, we innovatively adopt a multi-task learning optimization strategyGradNorm, which can dynamically adjust the weights of different tasks, thus balancing the losses among tasks during the training process and reducing the overall training loss. After information extraction experiments, our model is compared with other models to test the performance of uniform information extraction for large models, and the experimental results show that our model performs well.

关键词： Large Language Model Uniform information Extraction Instruction Fine-tuning Multi-task Learning Optimization

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Design and implementation of a small diving safety detection underwater robot 7

Design and implementation of a small diving safety detection...

引用

2022 7th international conference on information Science, computer technology and Transportation, ISCTT 2022

作者： Ma, Qingqing Cheng, Jinglong Mai, Kaijun Pan, Enting Feng, Xizhe Ye, Zongyuan Institute of computer control technology Guangzhou Huali College Guangzhou China

ISBN: (纸本)9783800760565

In order to test the safety of diving in shallow waters, this design uses a small submersible safety detection underwater robot based on STM32 microcontroller, which can be used as a small cable unmanned underwater robot (ROV, Remote Operated Vehicle) detected in shallow waters. the underwater robot can realize the self-balance of the underwater posture, detect the underwater environment, fuse the sensor data, and send the water detection results to the upper computer display through the wireless module. Brief introduction of hardware structure design, software framework construction, introduce the control algorithm, sensor data collection and diving water hazard judgment. the underwater robot has verified the feasibility and stability of this design. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Machine design

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GRDNet: A Lightweight Railway Foreign Object Intrusion Detection Algorithm 7

GRDNet: A Lightweight Railway Foreign Object Intrusion Detec...

引用

7th international conference on Advanced Algorithms and Control Engineering, ICAACE 2024

作者： Wang, Zhaonan Wei, Lin Meng, Caixia Shi, Lei Gao, Yufei Wang, Qingxian School Of Cyber Science And Engineering Zhengzhou University Zhengzhou China School Of Computer And Artificial Intelligence Zhengzhou University Zhengzhou China Zhengzhou Police College Department Of Image And Network Investigation Technology Zhengzhou China

ISBN: (纸本)9798350361445

Railway intrusion detection using convolutional neural networks has significant results, but it requires a large amount of data and arithmetic power to train and deploy neural network models, and it is still a challenge to improve detection accuracy under limited computational resources. Based on this problem, this paper proposes a lightweight railway foreign object intrusion detection algorithm: GRDNet, which firstly adopts a lightweight backbone network GhostNetV2, and makes use of the decoupled fully connected attention mechanism to aggregate local and long-distance information, which significantly reduces the number of parameters and computation while maintaining the detection performance. Next, a deep feature extractor, RSPPFCSPC, is proposed to reduce the computational effort by decreasing the number of channels in the feature map while maintaining the diversity and effectiveness of the features. Finally, a knowledge distillation algorithm is used to improve the accuracy of foreign object localization and classification and reduce the leakage rate of the model. Experiments show that the proposed method is superior to the state-of-the-art work of each comparison. © 2024 IEEE.

关键词： Object detection

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the research on building electromagnetic environment of communication countermeasure training 7

The research on building electromagnetic environment of comm...

引用

2022 7th international conference on information Science, computer technology and Transportation, ISCTT 2022

作者： Wang, Liying Jiang, Ning Xu, Chi Dept. of Information System Dalian Naval Academy Liaoning Dalian116011 China

ISBN: (纸本)9783800760565

Training is the important way to enhance battle effectiveness. If we want to win the future war, we must put the training in the combat environment similar to the future war. Communication is the most important link in the battlefield, which directly affects the choice and application of combat opportunities, weapons and equipment, and combat methods. this paper discusses the communication countermeasure training environment construction principles, methods and processes, analyzes the similarity index of communication countermeasure training environment, and gives examples to analyze the electromagnetic environment constructed, which can be used for reference to enhance the training effect and improve the combat effectiveness and equipment development of the army. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Construction equipment

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Offensive Language Detection on Telugu Language 7th

Offensive Language Detection on Telugu Language

引用

7th IFIP TC 12 international conference on Computational Intelligence in Data Science, ICCIDS 2024

作者： Kalyan, Kakollu Pavan Naveen, Valiveti Vani, V. Karthik, N. Department of Computer Science and Engineering National Institute of Technology Puducherry Karaikal India

ISBN: (纸本)9783031699818

In the present world a lot of data is generated via twitter, Instagram, WhatsApp etc. in different languages. It is important and necessary task to detect the offensive language among those data to create healthy and good environment among people. And it is even highly challenging task to identify offensive language in low resource languages due to less availability of the classified datasets. this paper aims to detecting of offensive language on a low resource language Telugu. To identify solution for this problem different types of ML models and DL models are used. Based on accuracy of the different models we are going to choose a model. To split the data and train the data and to test the data we have been using stratified k fold cross validation which is an efficient way to split the data and to increase model’s ability to perform better. From basis of this experiments, we can have a model to detect offensive language in Telugu and it must be considered as a small step for future models to work on it. © IFIP international Federation for information processing 2024.

关键词： Deep learning

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Anticipating Future College Admission Cutoffs: An Innovative Predictive Model Incorporating Student Reviews and Historical Admissions Cutoff Data Using Machine Learning 7th

Anticipating Future College Admission Cutoffs: An Innovative...

引用

7th IFIP TC 12 international conference on Computational Intelligence in Data Science, ICCIDS 2024

作者： Girish, Chikkam Umesh, Tata Karthik, N. Vani, V. Department of Computer Science and Engineering National Institute of Technology Puducherry Karaikal609 609 India

ISBN: (纸本)9783031699818

In this era of ever-increasing competition for the higher education opportunities, the capability to predict future college admission cutoff ranks plays an important role in shaping the educational journeys of prospective students. this work presents an innovative predictive model aimed at assisting students in making well-informed decisions when it comes to college selection. the proposed framework harnesses the power of key elements: student-personal reviews and historical admission cutoff, National Institutional Ranking Framework (NIRF) factors. this predictive model combines the student reviews, with the insights of admission cutoff ranks and NIRF scores. this work showcases a comprehensive approach that not only anticipates future admission cutoffs but also empowers students to make enlightened enrolment choices. this study explores the intricate interplay between student feedback and historical trends, providing a comprehensive perspective on the evolving landscape of college admissions. © IFIP international Federation for information processing 2024.

关键词： Adversarial machine learning

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