检索结果-内蒙古大学图书馆

6th International Conference on Biomedical and Health informatics, ICBHI 2024

作者： Han, Hsieh-Ping Chow, Tong-Hsien Ho, Wen-Hsien PhD Program in Biomedical Engineering Kaohsiung Medical University Kaohsiung807378 Taiwan Department of Sports Science R.O.C. Military Academy Kaohsiung830208 Taiwan Department of Healthcare Administration and Medical Informatics Kaohsiung Medical University Kaohsiung807378 Taiwan

ISBN: (纸本)9783031863226

Basic military training (BMT) is important and initial period for soldiers, especially the military basic throwing performance is one of the key military tactical motor skill. In recent years, machine learning (ML) techniques have been increasingly adopted to analyze extensive datasets and derive meaningful insights. To evaluate the effectiveness of fitness training strategies for military throwing, this study analyzed seven common input features: pull-ups, push-ups, squat concentric/eccentric peak power, squat maximum strength, leg tuck, and a 3 km run. Four data mining models—Random Forest, Multilayer Perceptron, AdaboostM1, and Bagging classifier—were tested to identify the most effective method for predicting performance. The Random Forest model excelled, achieving the highest accuracy, precision, recall, and F1 score, indicating its superiority in this context. These seven attributes were thus identified as key predictors of military throwing performance. However, further research is necessary to establish a definitive ranking and to fully understand the importance of each feature in refining training strategies. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Personnel training

来源：评论

学校读者我要写书评

暂无评论

Innovative web-based microteaching model: To improve the teaching skills of prospective informatics teachers in vocational high schools

引用

Social Sciences and Humanities Open 2025年 11卷

作者： Sugihartini, Nyoman Elmunsyah, Hakkun Nurhadi, Didik Rahmawati, Yuni Vocational Education Doctoral Program Post Graduate School Universitas Negeri Malang Malang Indonesia Informatics Education Study Program Department of Informatics Faculty of Engineering and Vocational Universitas Pendidikan Ganesha Bali Indonesia

Prospective informatics teachers in vocational schools (VS) must master content knowledge, pedagogical skills, and technology integration to achieve learning goals. Therefore, informatics teachers in VS need to innovate to increase students' creativity. However, many prospective informatics teachers experience difficulties in this regard. This research aims to develop and implement the Web-Based Microteaching (WBM) model to improve the teaching skills of prospective informatics teachers at VS. This study uses research and development methods with the ADDIE model approach. The research results show that the WBM model effectively improves prospective informatics teachers' teaching skills, especially in planning lessons and practising basic teaching skills. This innovation is a relevant learning solution in the digital era and positively contributes to the professional development of informatics teachers. The WBM model is an innovation to provide a more intensive and structured practical experience by utilizing web technology as the main media. Through web-based learning, prospective teachers can access material, exercises and feedback independently, which is expected to accelerate pedagogical mastery. © 2025 The Authors

关键词： Microteaching model Prospective informatics teacher Teaching skills Vocational high schools Web-based

来源：评论

学校读者我要写书评

暂无评论

An Introduction to the Three-Body Problem Optimization Algorithm: A Novel Swarm-Based Optimization Method

An Introduction to the Three-Body Problem Optimization Algor...

引用

Disruptive Technologies (ICDT), International Conference on

作者： Ivan Diryana Sudirman Patah Herwanto Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Bandung Indonesia Informatics Engineering Department STMIK IM Bandung Indonesia

ISBN: (数字)9798331519582

ISBN: (纸本)9798331519599

The Three-Body Problem Optimization Algorithm (3BPOA) is a metaheuristic method inspired by how gravity interacts if there are three bodies, a classical physics problem. 3BPOA uses 3 best agents or leaders where these 3 best agents will interact with each other and also influence the movement of the swarm. The interaction of these 3 best bodies or agents is also influenced by the distance between the three. In this study, 3BPOA was tested on the Rastrigrin mathematical function using various scenarios from 5 dimensions to 100 dimensions, also using various population sizes. The test results show that the 3BPOA algorithm has good performance in low dimensions and quite good in medium dimensions. In high dimensions, if using a large population, 3BPOA has good potential.

关键词： TV Metaheuristics Refining Optimization methods Benchmark testing Particle swarm optimization Optimization Physics Thermal stability Standards

来源：评论

学校读者我要写书评

暂无评论

Enhanced Performance and Data Privacy in Lung Nodule Classification via Federated Deep Learning Approach 24

Enhanced Performance and Data Privacy in Lung Nodule Classif...

引用

2024 7th International Conference on Healthcare Service Management, ICHSM 2024

作者： Nguyen, Duc-Khanh Li, Ai-Hsien Adam Lai, Yen-Jun Chiu, Yen-Ling Phan, Dinh-Van Chien, Ting-Ying Chan, Chien-Lung Department of Information Management Yuan Ze University Taoyuan Taiwan Department of Statistics and Informatics University of Economics The University of Danang Danang Viet Nam Division of Cardiology Far Eastern Memorial Hospital New Taipei Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan Department of Radiology Far Eastern Memorial Hospital New Taipei Taiwan Graduate Institute of Medicine and Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan Taiwan Department of Medical Research Far Eastern Memorial Hospital New Taipei Taiwan Department of Computer Science and Engineering Yuan Ze University Taoyuan Taiwan ZDT Group- YZU Joint Research and Development Center for Big Data Taoyuan Taiwan Yuan Ze University Taoyuan Taiwan

ISBN: (纸本)9798400710162

This study explores the feasibility of deep learning for classifying nodule neoplasms, analyzing their performance on two openly available datasets, LUNGx SPIE, and LIDC-IDRI. These datasets offer valuable diversity in image quantity, quality, and malignancy annotation methodologies, posing a real-world challenge for effective model development. To handle the disparities in these diverse datasets, we aim to develop a robust classification model trained using federated learning. This decentralized approach allows model training across datasets without sharing patient data, preserving privacy and overcoming data fragmentation. Our experiments demonstrate that federated learning enables the development of a robust and superior deep learning model compared to individual models trained on limited data. This combination of deep learning, and federated learning holds immense promise for nodule neoplasm classification and can significantly improve patient care and outcomes. © 2024 Copyright held by the owner/author(s).

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Development of A Deep Learning Hybrid Model for Classification of Plastic Waste Objects in the Coastal Environment

Development of A Deep Learning Hybrid Model for Classificati...

引用

Advancement in Data Science, E-learning and Information Systems (ICADEIS), International Conference on

作者： Imran Djafar Indrabayu Syafruddin Syarif Doctoral Program of Electrical Engineering Department Hasanuddin University Dipa Makassar University Makassar Indonesia Department of Informatics Hasanuddin University Makassar Indonesia Department of Electrical Engineering Hasanuddin University Makassar Indonesia

ISBN: (数字)9798331513320

ISBN: (纸本)9798331513337

Plastic, glass, metal, and wood waste has become a global scourge and nightmare to the marine environment and the development of the coastal areas. This paper aims at developing a hybrid model of deep learning technique using Convolutional Neural Networks (CNN) and Vision transformers (ViT) in the performance of detecting underwater waste materials. The model is designed with the use of transfer learning and high-resolution imaging sourced from underwater drones to help overcome the challenges of underwater work such as poor visibility and insufficient ambient light. The local features are extracted using CNNs and the global spatial relationships of the images are attended to by the ViTs. The results achieved a waste detection accuracy rate of about 90%, which is effective even in difficult environmental conditions. The concept is for a waste management system where drones or underwater robotics systems can assist automated waste management, waste treatment processes, and aid marine renovation activities.

关键词： Waste management Deep learning Transfer learning Sea measurements Metals Glass Feature extraction Transformers Convolutional neural networks Drones

来源：评论

学校读者我要写书评

暂无评论

YNote: A Novel Music Notation for Fine-Tuning LLMs in Music Generation

arXiv

引用

arXiv 2025年

作者： Lu, Shao-Chien Yeh, Chen-Chen Cho, Hui-Lin Hsu, Chun-Chieh Hsu, Tsai-Ling Wu, Cheng-Han Shih, Timothy K. Lin, Yu-Cheng Department of Computer Science and Engineering Yuan Ze University Taoyuan Taiwan International Bachelor Program in Informatics Yuan Ze University Taoyuan Taiwan Department of Computer Science and Information Engineering National Central University Taoyuan Taiwan

The field of music generation using Large Language Models (LLMs) is evolving rapidly, yet existing music notation systems, such as MIDI, ABC Notation, and MusicXML, remain too complex for effective fine-tuning of LLMs. These formats are difficult for both machines and humans to interpret due to their variability and intricate structure. To address these challenges, we introduce YNote, a simplified music notation system that uses only four characters to represent a note and its pitch. YNote’s fixed format ensures consistency, making it easy to read and more suitable for fine-tuning LLMs. In our experiments, we fine-tuned GPT-2 (124M) on a YNote-encoded dataset and achieved BLEU and ROUGE scores of 0.883 and 0.766, respectively. With just two notes as prompts, the model was able to generate coherent and stylistically relevant music. We believe YNote offers a practical alternative to existing music notations for machine learning applications and has the potential to significantly enhance the quality of music generation using LLMs. Copyright © 2025, The Authors. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Reconfigurable Compute-In-Memory Design with Adaptive Bit-Precision and Power Adjustment

A Reconfigurable Compute-In-Memory Design with Adaptive Bit-...

引用

Consumer Technology (ICCT-Pacific), International Conference on

作者： I-Chieh Hsu Chun-Fu Chen Dao-Long Huang Yun-Kai Yeh Wei-Chieh Lee Qi-Hua Lin Jinjia Zhou I-Chyn Wey Electrical Engineering Department College of Engineering Chang-Gung University Taiwan School of Electrical Engineering National Taiwan University of Science and Technology Taiwan Master Program in Nano-Electronic Engineering and Design Chang Gung University Taiwan Department of Applied Informatics Faculty of Science and Engineering Hosei University Japan

ISBN: (数字)9798331504120

ISBN: (纸本)9798331504137

With the successful development of artificial intelligence (AI), Convolutional Neural Networks (CNNs) occupy a large amount of computing time and power consumption in the entire AI computing process. However, in traditional von Neumann architectures, the separation of the computing element and memory leads to the memory-wall problem of memory data transmission bandwidth from memory to processing element when executing multiply-accumulate-based CNN operations. The data transmission time and power consumption all are much higher than the CNN computing part. Therefore, this paper proposes a memory-in-computation design that can flexibly adjust energy usage, achieve high energy efficiency, and support multiple operation frequencies. By controlling the switches of each memory row, unnecessary energy consumption is avoided, leading to a reduction in total power consumption by 15% to 60%. Additionally, by adjusting the pulse width, the charging power consumption of capacitors is reduced by 65% per charge cycle.

关键词： Energy consumption Power demand Capacitors Bandwidth In-memory computing Control systems Energy efficiency Convolutional neural networks Data communication Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

Evaluating the Impact of Data Cleaning for Improving Road Damage Detection Through Vision Transformer

Evaluating the Impact of Data Cleaning for Improving Road Da...

引用

IEEE International Conference on Consumer Electronics (ICCE)

作者： Andy Desman Kahlil Muchtar Maulisa Oktiana Maya Fitria Yuwaldi Away Fardian Fardian Hammam Riza Dept. of Electrical and Computer Engineering Universitas Syiah Kuala Banda Aceh Indonesia Dept. of Electrical and Computer Engineering Department of Informatics Universitas Syiah Kuala The Master Program in Artificial Intelligence Universitas Syiah Kuala (USK) Banda Aceh Indonesia Department of Informatics BRIN (National Research and Innovation Agency) Indonesia The Master Program in Artificial Intelligence Universitas Syiah Kuala Banda Aceh Indonesia

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

The WHO predicts that by 2030 road accidents will be the 5th leading cause of death. Globally, road accidents account for 1.25 million casualties each year, and road defects cause 34% of these casualties. The road survey process in many countries have several challenges, one of which is detection using cameras that do not have a recognition system. In this study, a model with YOLOS architecture based on Vision Transformer trained on the RDD2022 dataset successfully recognizes road damage well, as indicated by the number of objects detected, bounding box on accurate objects, and the ability to recognize objects with inconsistent shadow and light inference. This research uses assessment parameters such as Average Precision (AP) and Average Recall (AR) to determine the overall performance of the model. The model achieves the highest AP value at Intersection of Union (IoU) 0.5, 0.75, and 0.5-0.95, worth 62.1%, 37.1%, and 36.2% respectively, and the highest AR value in Large, Medium, and Small Areas, worth 42.1%, 60.3%, and 75.4% respectively. The supplementary material can be found through this link: https://***/watch?v=LzkI2e_IORE.

关键词： YOLO Surveys Computer vision Road accidents Roads Manuals Transformers Cameras Cleaning Tuning

来源：评论

学校读者我要写书评

暂无评论

Hybrid IT Project Management Methodology Based on Best Practices of Project Management and Critical Success Factors Influencing IT Project Management 8th

Hybrid IT Project Management Methodology Based on Best Pract...

引用

8th International Conference on Intelligent Technologies, ICIT 2023

作者： Hayashida-Marchinares, Augusto Herrera, Jose Rivera, Luis Rodriguez, Ciro Rodriguez Krupa, Miroslav Ph. D. Program of the Faculty of Systems Engineering and Informatics Universidad Nacional Mayor de San Marcos Lima Peru Laboratory of Mathematical Sciences Center of Sciences and Technologies Universidade Estadual Do Norte Fluminense-UENF Rio de Janeiro Brazil Department of Management Faculty of Business Administration Prague University of Economics and Business Prague Czech Republic

ISBN: (纸本)9789819738588

Information Technology (IT) project management is important for the growth of organizations. It involves planning and executing projects to achieve strategic objectives. This paper reviews IT project management methodologies and critical success factors to identify best practices for project success. This paper uses a literature review and analysis of the current state of the art of IT project management methodologies. A total of 39 articles were selected and reviewed. The results of the review include a comparison of the main IT project management methodologies and the critical success factors for project success. The conclusion of the paper is that Hybrid Project Management Models are a promising approach for IT project management. This approach combines the foundations and best practices of traditional and agile project management methodologies, making it well-suited for the complex and dynamic nature of IT projects. Additionally, the paper identifies the following critical success factors for IT project success: Clear and well-defined project objectives, Effective communication and collaboration between stakeholders, Appropriate risk management and contingency planning, Strong leadership and project management skills and Adequate resources and support. By understanding and addressing these critical success factors, organizations can increase their chances of success in IT projects. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Project management

来源：评论

学校读者我要写书评

暂无评论

The association between urinary tract infections and diet: a literature review

引用

Discover Medicine 2025年第1期2卷 1-17页

作者： Çelik, Haluk Kozan, Esra Caf, Balım Bengisu Çebi, Gizem Koç, Murat Vivosens Inc. San Francisco USA Program of Stem Cell and Tissue Engineering Institute of Graduate Education Istinye University Istanbul Türkiye Department of Health Informatics University of Health Science Hamidiye Institute of Health Sciences Istanbul Türkiye

Urinary tract infections (UTIs) are a significant global health concern, affecting millions worldwide, with particular prevalence among specific vulnerable populations. Women of sexually active age, post-menopausal women, pregnant women, individuals with diabetes, catheterized patients, childs and older indivisuals face heightened risk due to various physiological, hormonal, and anatomical factors. While anatomical abnormalities and behavioral factors contribute to UTI susceptibility, the growing challenge of antibiotic resistance has necessitated exploration of alternative treatment approaches. Non-antibiotic interventions, including probiotics, cranberry products, and natural remedies, are gaining attention for their potential role in UTI prevention and management. Recent studies suggest the efficacy of probiotics and plant extracts in promoting urinary tract health and preventing bacterial colonization. Additionally, research highlights the importance of dietary factors, such as vitamin D and probiotic intake, in reducing UTI susceptibility. This review examines the emerging shift toward non-drug strategies, offering a more comprehensive approach to UTI management while addressing the pressing concern of antibiotic resistance.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：