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2nd International Conference on Cybernetics and Innovations, ICCI 2023

作者： Yimyam, Worawut Ganokratanaa, Thittaporn Phetchaburi Rajabhat University Department. of Business Information Management Phetchaburi Thailand King Mongkut's University of Technology Thonburi Applied Computer Science Program Bangkok Thailand

ISBN: (纸本)9798350336573

This research aims to study the working principles of IOT devices or Internet of Things in order to promote the use of information technology systems, both hardware and software, with visually impaired people. rehabilitation of persons with disabilities, enhancing the capacity or ability of persons with disabilities to improve their condition or or existing capabilities through the advancement of technology so that people with disabilities have the opportunity to work or live in society to the full potential of the researcher The concept of technology acceptance model (Technology Acceptance Model or TAM) to help further develop This research shows the importance of information technology systems, both hardware and software, to visually impaired people, which is the basis for product development of healthcare service businesses in the future. © 2023 IEEE.

关键词： Alarm systems

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Poultry raising light control system for laying hens and broilers 2

Poultry raising light control system for laying hens and bro...

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2nd International Conference on Cybernetics and Innovations, ICCI 2023

作者： Pinthong, Thidarat Ganokratanaa, Thittaporn Phetchaburi Rajabhat University Department. of Business Information Management Phetchaburi Thailand King Mongkut's University of Technology Thonburi Applied Computer Science Program Bangkok Thailand

ISBN: (纸本)9798350336573

Chicken is an economic animal. one kind At present, it has been raised as a business and has expanded extensively. This is because both domestic and foreign populations have a greater demand for products and processed products from laying hens. which the raising of laying hens must be more attention to the productivity and quality of eggs in order to meet the needs of consumers with high or low temperatures Too low has an effect on the physiological system of laying hens. Reduce egg production or may result in inefficient production. And with the aforementioned problems, technology has been used to help in notifying. Warn whether the temperature in the house is suitable to increase the production of high-quality eggs. © 2023 IEEE.

关键词： Internet of things

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Combining function points software estimation model with ADISSA methodology for systems analysis and design 7

Combining function points software estimation model with ADI...

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7th Israeli Conference on computer Systems and Software Engineering, ICCSSE 1996

作者： Shoval, Peretz Feldman, Ofer Information Systems Program Dept.of Industrial Engineering and Management Israel Dept.of Mathematics and Computer Science Ben-Gurion University of Negev Beer-Sheva84105 Israel

ISBN: (纸本)0818675365

The study proposes a combination of the function points model for software estimation with the ADISSA methodology for systems analysis and design. This combined approach, which is supported by a software tool, enables one to estimate various software metrics, such as size, effort, and duration, in the early stages of systems development, by basing them on the products of a thorough system analysis and design process. © 1996 IEEE.

关键词： Project management

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Diversity-Optimized Group Extraction in Social Networks

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IEEE Transactions on Computational Social Systems 2024年第1期11卷 756-769页

作者： Hsu, Bay-Yuan Chen, Yi-Ling Ho, Ya-Chi Chang, Po-Yuan Chang, Chih-Chieh Shia, Ben-Chang Shen, Chih-Ya National Tsing Hua University Department of Industrial Engineering and Engineering Management Hsinchu30013 Taiwan National Taiwan University of Science and Technology Department of Computer Science and Information Engineering Taipei10607 Taiwan Hsinchu31040 Taiwan Fu Jen Catholic University Department of Business Administration New Taipei City24205 Taiwan National Taiwan University of Science and Technology Management Undergraduate Program Taipei10607 Taiwan National Tsing Hua University Department of Computer Science Hsinchu30013 Taiwan

In this article, we propose to study a novel research problem to boost group performance, that is, social-aware diversity-optimized group extraction (SDGE), which takes into consideration the two important factors: 1) group diversity and 2) social tightness. We prove the NP-hardness of SDGE and propose an effective algorithm, named group shrinking for diversity maximization (GSDM) with a performance guarantee, that is, GSDM is a three-approximation algorithm to the SDGE problem studied in this article. We further propose three effective pruning strategies that are able to boost the efficiency of GSDM but do not deteriorate its performance. We conduct extensive experiments on multiple large-scale real datasets to evaluate the performance of GSDM. The experimental results show that our proposed GSDM outperforms the other baseline approaches significantly, in terms of solution quality and efficiency. Moreover, the experimental results also confirm that our proposed pruning strategies indeed boost the efficiency of the algorithm. © 2014 IEEE.

关键词： Costs

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Improved Chest X-Ray Image Quality Using Median and Gaussian Filter Methods 4

Improved Chest X-Ray Image Quality Using Median and Gaussian...

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4th International Conference on Informatics, Multimedia, Cyber and information System, ICIMCIS 2022

作者： Kesuma, Lucky Indra Ermatita, Ermatita Erwin, Erwin Sari, Purwita Purabaya, Rudhy Ho Universitas Sriwijaya Doctoral Program in Engineering Faculty of Engineering Palembang Indonesia Universitas Sjakhyakirti India Universitas Sriwijaya Information System Faculty of Computer Science Palembang Indonesia Universitas Sriwijaya Faculty of Computer Science Departement of Computer System Palembang Indonesia Universitas Sriwijaya Informatic Management Faculty of Computer Science Palembang Indonesia Universitas Pembangunan Nasional Veteran Jakarta Information System Faculty of Computer Science Jakarta Indonesia

ISBN: (纸本)9781665473279

The lungs are one of the organs of the body that are responsible for the human respiratory process and are very susceptible to dangerous diseases. For this reason, early detection and diagnosis of lung organs is needed, one of which is through examination of Chest X-Ray (CXR) images. Examination of the results of CXR images is still done manually by doctors and radiologists, this requires time and high accuracy. To facilitate the examination, it is necessary to image quality enhancement in order to get better image quality results so as to produce an accurate diagnosis. The initial stage in this research is to apply the contour improvement technique to the image using Morphology Opening, and followed by noise reduction using Median Filter and Gaussian filter. The results of the two methods of noise reduction are compared with the results of image quality in order to find out the best method that can be applied. The implementation of image quality enhancement results was measured quantitatively using Peak Signal-to-Noise Ratio (PSNR), Mean Square Error (MSE), and Structural Similarity Index Metrics (SSIM). In the Morphology Opening and Median Filter methods, the values obtained are 39.187, 22.252, and 0.952, respectively. Meanwhile, the Morphology Opening and Gaussian Filter methods obtained values of 38.717, 23.917 and 0.956. Based on these results, it can be concluded that both methods are able to improve image quality well. © 2022 IEEE.

关键词： Image quality

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Multilabel Machine Learning System for Predicting Gender and Age Group from Human Gait 2

Multilabel Machine Learning System for Predicting Gender and...

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2nd IEEE International Conference on Interdisciplinary Approaches in Technology and management for Social Innovation, IATMSI 2024

作者： Qomariyah, Nunung Nurul Nurul Fajar, Ahmad Yono, Vincent Kazakov, Dimitar Bina Nusantara University School of Computing and Creative Arts Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program Information System Management Information Systems Management Department Jakarta11480 Indonesia University of York Computer Science Department YO10 5GH United Kingdom

ISBN: (纸本)9798350360523

This paper explores the development of a multilabel machine learning system for predicting both gender and age from human gait patterns. Gait analysis, a non-intrusive method of identifying subtle nuances in human movement, has proven to be a rich source of information related to demographic characteristics. The research extends beyond traditional single-label classification approaches, adopting a multilabel framework to simultaneously predict gender and age *** study evaluates various multilabel machine learning algorithms, with the Random k-labeLsets (RAKEL) algorithm demonstrating superior performance in predicting gender and age labels from human gait datasets. The accuracy of the algorithm can reach up to 87%. We also compared the multilabel approach with several multiclass algorithms such as Decision Tree, Random Forest, Gradient Boosting, K-Neighbors and XGBoost. However, when we also considering the training time, Classifier Chain algorithm showed the best trade off with the accuracy of 86% and the training time is twice faster than the RAKEL algorithm. © 2024 IEEE.

关键词： Gait analysis

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Virtual organization manufacturing resource planning: Flexible multi-objective mathematical programming

Virtual organization manufacturing resource planning: Flexib...

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2014 International Conference on E-Commerce, E-Business and E-Service, EEE 2014

作者： Hsu, Yao Huang, Jih-Jeng Chen, Jhao-Syuan Department of Business and Entrepreneurial Management Kainan University Taoyuan Taiwan Department of Computer Science and Information Management Soochow University Taipei Taiwan Ph.D. Program in Business Feng Chia University Taichung Taiwan

ISBN: (纸本)9781138026469

Optimizing production resource planning significantly affects the profits and competitive advantages of factories by increasing the size and complexity of organizations. Mathematical programming models are mainly used to optimize the allocation of traditional production planning. However, using traditional mathematical programming models to optimize certain types of organizations is difficult because of rigid parameters and new organizational types, such as virtual organizations. Studies have proposed the De Novo programming model and the changeable parameter model, which allow parameter modification. This study proposes a multi-objective flexible mathematical planning model, and combines the De Novo programming model and changeable parameter model to assist virtual organizations with the optimization planning of production resources for factories. The empirical results show that the proposed models produce better resource-planning results than do previous models. This study also provides decision makers with a more flexible operational model. © 2014 Taylor & Francis Group.

关键词： Mathematical programming

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Semantic Visual Simultaneous Localization and Mapping: A Survey

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IEEE Transactions on Intelligent Transportation Systems 2025年第6期26卷 7426-7449页

作者： Chen, Kaiqi Xiao, Junhao Liu, Jialing Tong, Qiyi Zhang, Heng Liu, Ruyu Zhang, Jianhua Ajoudani, Arash Chen, Shengyong Zhejiang University of Technology Institute of Computer Vision College of Computer Science and Technology Hangzhou 310023 China Istituto Italiano di Tecnologia Human-Robot Interfaces and Interaction Laboratory Genoa 16163 Italy National University of Defense Technology College of Intelligence Science and Technology Changsha 410073 China Universitã di Genova Ph.D. Program of National Interest in Robotics and Intelligent Machines (DRIM) Genoa 16126 Italy Hangzhou Normal University School of Information Science and Technology Hangzhou 311121 China Technical University of Denmark Department of Technology Management and Economics Kongens Lyngby 2800 Denmark Tianjin University of Technology Institute of Computer Vision School of Computer Science and Engineering Tianjin 300384 China

Visual Simultaneous Localization and Mapping (vSLAM) is a cornerstone technology in computer vision and robotics, underpinning applications such as autonomous vehicles and robot navigation. While traditional vSLAM systems have shown significant progress in indoor or outdoor environments, their performance often degrades in complex scenes, limiting their adaptability and robustness. Semantic vSLAM, which integrates high-level semantic information into vSLAM systems, has emerged as a promising solution to address these limitations by enabling a richer understanding of the environment. In this paper, we provide a comprehensive review of semantic vSLAM, offering a critical analysis of its evolution, methods, and challenges. We begin by revisiting the development of traditional vSLAM, emphasizing its limitations and the motivation for incorporating semantic information. Subsequently, we delve into the core modules of semantic vSLAM, including semantic extraction, object association, semantic loop closing, back-end optimization, and semantic mapping. Then, we present a performance comparison of semantic vSLAM systems under two different datasets, indoor and outdoor, respectively. Furthermore, we also provide a comparative analysis of widely used SLAM datasets to provide guidance for performance testing and validation. To further enrich the discussion, we identify unresolved challenges in semantic vSLAM, such as long-term semantic perception and association, open and unstructured environments. We propose future research directions, including balancing computational resources and quantifying system risk, large model-based navigation and mapping, and embodied AI SLAM. By providing key insights and forward-looking perspectives, this work aims to stimulate future research and improve the capabilities of semantic vSLAM in real-world applications. © 2000-2011 IEEE.

关键词： localization mapping semantic information Semantic visual SLAM SLAM datasets

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Trend Intelligent Tutoring System 2018-2022 : Systematic Literature Review 3

Trend Intelligent Tutoring System 2018-2022 : Systematic Lit...

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3rd International Conference for Innovation in Technology, INOCON 2024

作者： Suwita, Jaka Prabowo, Harjanto Hendric Spits Warnars, Harco Leslie Meyliana, Meyliana Binus Graduate Program Computer Science Bina Nusantara University Departement of Computer Science Jakarta11480 Indonesia Stmik Insan Pembangunan Department of Information System Tangerang15810 Indonesia Binus Business School Undergraduate Program Bina Nusantara University Management Department Jakarta11480 Indonesia School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia

ISBN: (纸本)9798350381931

ITS is a method of teaching that uses technology to give lessons without the need for an instructor to be there. A systematic literature review (SLR) was conducted in this research to identify the components of an intelligent tutoring system, and the results are presented. The method used in this literature review is the prism method. The steps in the prism method are slr protocol, search for literature, select literature, summarize evidence and disseminate results. The slr protocol stage, it consists of determining a research question, searching for scientific reference sources with the keyword intelligent tutoring system, then sorting out the appropriate articles and making final conclusions. This article gives a detailed look at how the intelligent tutoring system changed over time during the pandemic epoch. Our contribution is complete information on the components of ITS in times of epidemic at universities, with the goal of improving their learning and practical use of the technology. © 2024 IEEE.

关键词： Prisms

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Feasibility study of using social networks platform for learning support: An example of Facebook

Feasibility study of using social networks platform for lear...

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20th International Conference on computers in Education, ICCE 2012

作者： Chan, Chien-Lung Fu, Wen-Erh Lai, K. Robert Tseng, Shu-Fen Department of Information Management Yuan Ze University Taiwan Department of Computer Science and Engineering Yuan Ze University Taiwan Graduate Program in Social Informatics Yuan Ze University Taiwan

ISBN: (纸本)9789810746490

In this study, we explored the students' computer-supported collaborative learning behavior based on the Facebook platform. Sixty two senior college students major in information management took Decision Support System (DSS) class. Besides the lectures and class discussion, the students participated in the DSS Facebook for collaborative learning. We found that students' characteristics (e.g., gender and mindset of learning) are important factors to affect their Facebook usage behavior and learning performance. The students using DSS Facebook more often get better performance in their final projects, learning satisfaction and the online communication behavior survey. We also found that gender affects the usage of social networks platform. For instance, male students use social networks platform several times per week and get better performance in online communication, learning satisfaction and creativity self-efficacy.

关键词： Decision support systems

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