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International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP)

作者： Narumol Chumuang Nuttawoot Meesang Mahasak Ketcham Worawut Yimyam Jiragorn Chalermdit Nawarat Wittayakhom Patiyuth Pramkeaw Dep. of Digital Media Technology Muban Chombueng Rajabhat University Ratchaburi Thailand Dep. of Management Information System King Mongkut’s University of Technology North Bangkok Thailand Dep. of Business Information Management Phetchaburi Rajabhat University Thailand Media Technology Program King Mongkut’s University of Technology Thonburi Thailand

ISBN: (数字)9781665415545

ISBN: (纸本)9781665446969

In this paper, we presented a separate separation and comparison of data of people with renal impairment. By collecting information on CKD. The data was collected for selection in data mining using the CKD data set from UCI Machine Learn Repository to compare the classification of 400 CKD patients, comprising 25 attributes and dividing into two class, which one is for patients with CKD and those who do not suffer from CKD. In the experimental designing with 5-folds cross validation test, the result is separation by technique as Random Forest shows an accuracy of 100 %, BayesNet 98.75 %, Stochastic Gradient Descent (SGD) 98.25%, Sequential Minimal optimization (SMO) 95.75%, Multinomial Logistic Regression (MLR) 95.75% respectively.

关键词： Machine learning algorithms Predictive models Data models Data mining Forecasting Random forests Kidney

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An Augmented Reality Game's User Experience and Its Effect on Immersion Leading to Intention

An Augmented Reality Game's User Experience and Its Effect o...

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International Conference on ICT For Smart Society (ICISS)

作者： Tanty Oktavia Kawang Utomo Ford Lumban Gaol Takaaki Hosoda Information Systems Management Department BINUS Graduate Program - Master of Information System Management Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Decision Science Department Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (数字)9798350389654

ISBN: (纸本)9798350389661

Since the emergence of Pokémon Go in 2016, the world has been introduced to Augmented Reality (AR) games. Many IT companies have begun developing augmented reality (AR) games due to the great commercial potential in this industry. Certain products may have managed to remain viable in the market, while others were forced to close due to one or two factors. Since the emergence of Pokémon Go, no other game has managed to surpass its unprecedented success. The company responsible for developing Pokémon Go has decided to shut down one of their games due to a lack of consumer interest. The technology of augmented reality (AR) is consistently associated with the concept of immersion. Immersion is a key aspect of the game that allows users to deeply engage and feel fully involved in the experience. This study will employ a quantitative methodology, utilising a questionnaire that will be distributed to and completed by those who have engaged in augmented reality (AR) games. The data will be analysed using Smart PLS to examine the impact of user experience on immersion, which in turn influences intention. After gathering over 200 participants by spreading google form questionnaires and doing data analysis, the findings indicate that only a few aspects of user experience, namely Brand Experience and User Need Experience, have an impact on reasons. Niantic, the developer of Pokémon Go, was unable to replicate their success with a similar augmented reality game called Harry Potter: Wizards Unite. The initial release occurred on June 21, 2019, and the shutdown took place on December 21, 2021. In the beginning, they shown a profound enthusiasm for the game but were unable to sustain it, much as Pokémon Go. According to Niantic CEO John Hanke, the primary reason for the game's shutdown was its immersion. Immersion has a notable impact on User Confirmation, which in turn has a notable impact on Satisfaction, and Satisfaction has a notable impact on Intention. Moreover, there have be

关键词： Surveys Industries Data analysis Games Companies User experience Software Hardware Internet Augmented reality

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Developed Credit Card Fraud Detection Alert systems via Notification of LINE Application

Developed Credit Card Fraud Detection Alert Systems via Noti...

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International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP)

作者： Narumol Chumuang Sansanee Hiranchan Mahasak Ketcham Worawut Yimyam Patiyuth Pramkeaw Sakchai Tangwannawit Dep. of Digital Media Technology Muban Chombueng Rajabhat University Ratchaburi Thailand Dep. of Management Information System King Mongkut’s University of Technology North Bangkok Thailand Dep. of Business Information Management Phetchaburi Rajabhat University Thailand Media Technology Program King Mongkut’s University of Technology Thonburi Thailand

ISBN: (数字)9781665415545

ISBN: (纸本)9781665446969

As nowadays, prevention of fraud is another important issue, researcher have initiated the idea of applying suspicious frauds in credit cards to line application. The objectives of this research are: 1) for developing the suspected credit card fraud via API LINE Notify. 2) Measure the accuracy of the developed system in the notification to prevent suspicious fraud credit card. The measurement method is comprised of five steps which are: 1) Analysis of work systems is a study and analysis of problems to determine needs. 2) system design is the process of designing research tools. 3) Developing a system is the process of developing research tools. 4) A test of the tools is executed 5) Summary of results, discussion results, and suggestions. The measurement results of efficiency, accuracy, and completeness of the data were in a very good level, equal to 86.67%. The results of the measurement of efficiency to the conditions set are very good, equal to 80.00 %. The results of the measurement on time very good, equal to 86.67%. In conclusion, the developed system accomplishes all research goals.

关键词： Surveillance Tools Credit cards Time measurement Natural language processing Artificial intelligence system analysis and design

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The development on obstacle avoidance design for a humanoid robot based on four ultrasonic sensors for the learning behavior and performance

The development on obstacle avoidance design for a humanoid ...

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IEEE International Conference on Industrial Engineering and Engineering management

作者： Ya-Ju Li Wei-Chung Chou Chen-Yuan Chen Bih-Yaw Shih Lien-Tung Chen Pei-Yin Chung Department of Computer Science National Ping Tung University of Education Ping Tung Taiwan Doctoral Program in Management National Kaohsiung First University of Science and Technology Kaohsiung Taiwan Department of Management Information System Yung Ta College of Technology and Commerce Ping Tung Taiwan Department of Information Management Meiho University Ping Tung Taiwan

A behavioral strategy designed for a humanoid robot for the purpose of obstacle avoidance based on four ultrasonic sensors for the learning behavior and performance is proposed and implemented with an autonomous humanoid robot. A mechanical structure with 4 degrees of freedom is designed so that a small-size humanoid robot named ARSR is able to accomplish three types of walking motion. One experiment is presented to illustrate ow the the proposed bipedal structure lets the ARSR move forward, turn left and turn right. Four ultrasonic sensors are mounted on the ARSR to obtain environmental information and detect obstacles. Based on the information obtained from these sensors, a decision tree method is proposed to decide upon one behavior from three possible types of movement: walk forward, turn left and turn right. An experiment is carried out to show how the robot can autonomously avoid obstacles to effectively arrive at its destination. Based on the mechanic design and development, we will get a good agreement for the learning behavior and performance.

关键词： Robot sensing systems Acoustics Legged locomotion Humanoid robots

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Human-Computer Interaction and Knowledge Transfer: Study of E-Learning Achievement 7

Human-Computer Interaction and Knowledge Transfer: Study of ...

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7th International Conference of Computer and Informatics Engineering, IC2IE 2024

作者： Alamsyah, Doni Purnama Othman, Norfaridatul Ahkmaliah Kerta, Johan Muliadi Morika, Doni Ramdhani, Yudi Bina Nusantara University Binus Business School Creativepreneurship Department Jakarta Indonesia Universiti Teknikal Malaysia Melaka Department of Management Technology Melaka Malaysia Bina Nusantara University School of Computer Science Computer Science Department Jakarta Indonesia Bina Nusantara University School of Design Design Interior Department Jakarta Indonesia Satu University Information System Program Bandung Indonesia

ISBN: (纸本)9798331505530

Human-computer interaction influences the effectiveness of e-learning knowledge transfer, so it is necessary to pay attention to user engagement and achievement. The aim of this research is to examine the factors that support e-learning knowledge transfer through achievement and user engagement (self-efficacy, self-confidence, self-esteem). The research method was carried out by surveying e-learning users, namely students, data from students was collected through quantitative questionnaires. The data is then processed using the SmartPLS tool through two tests, namely the PLS Algorithm and Boostrapping. The model was tested using inner and outer tests, and the data was analyzed based on the research hypothesis design. Student interactions with e-learning influence several behaviors that can support e-learning knowledge transfer performance. The research results prove that student e-learning achievement has a positive impact on e-learning knowledge transfer. Several supporting factors play a role in increasing e-learning achievement, namely self-efficacy, self-confidence and self-esteem of students. However, the supporting factors for students are only self-efficacy and self-confidence which are directly able to increase e-learning knowledge transfer. It is known that students who are less able to respect themselves in interacting with e-learning are unable to support knowledge transfer. The rules of human-computer interaction play a role in supporting e-learning knowledge transfer, studies on user behavior need to be considered, especially self-efficacy and self-confidence to support online learning academic performance. © 2024 IEEE.

关键词： Knowledge transfer

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Deep Learning in Smart Healthcare: A GAN-based Approach for Imbalanced Alzheimer's Disease Classification 19

Deep Learning in Smart Healthcare: A GAN-based Approach for ...

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19th International Conference on Future Networks and Communications, FNC 2024 / 21st International Conference on Mobile systems and Pervasive Computing, MobiSPC 2024 / 14th International Conference on Sustainable Energy information technology, SEIT 2024

作者： Tufail, Hina Ahad, Abdul Puspitasari, Ira Shayea, Ibraheem Coelho, Paulo Jorge Pires, Ivan Miguel Department of Computer Science University of Management and Technology Sialkot Pakistan Information System Study Program Faculty of Science and Technology Universitas Airlangga Indonesia School of Software Northwestern Polytechnical University Shaanxi Xian China Turkey Polytechnic University of Leiria Leiria Portugal Coimbra Portugal Instituto de Telecomunicações Escola Superior de Tecnologia e Gestão de Águeda Universidade de Aveiro Águeda Portugal

Alzheimer's disease (AD) is a type of dementia that leads to memory loss and impairment, which affects patients' lives badly. It is not curable yet, but its progression can be slowed down if detected at earlier stages. In this research study, we propose a transfer learning-based convolutional neural network (CNN) model to classify magnetic resonance imaging (MRI) into one of four stages of Alzheimer's disease. One of the major limitations of the deep learning-based classification model is the non-availability of healthcare datasets related to AD. The widely used Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset has a major class imbalance issue. We propose a generative adversarial network (GAN) based data augmentation technique to overcome the data imbalance. This promotes the investigation of applying GANs to generate synthetic samples for minority classes in Alzheimer's disease datasets to enhance classification performance. The results show the progression in the overall classification process of AD. © 2024 The Authors. Published by Elsevier B.V.

关键词： Generative adversarial networks

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Examining Spurious information through Text Categorization Methods

Examining Spurious Information through Text Categorization M...

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Cybernetics and Innovations (ICCI), International Conference on

作者： Watcharin Warinthaksa Worawut Yimyam Mahasak Ketcham Thittaporn Ganokratanaa Thidarat Pinthong Rajamangala University Of Technology Rattanakosin Nakhonprathom Thailand Dep. of Business Information Management Phetchaburi Rajabhat University Phetchaburi Thailand Dep. of Management Information System King Mongkut’s University of Technology North Bangkok Bangkok Thailand Applied Computer Science Program King Mongkut’s University of Technology Thonburi Bangkok Thailand

ISBN: (数字)9798350370096

ISBN: (纸本)9798350370102

In recent years, deceptive content such as fake news and fake reviews, also known as opinion spams, have increasingly become a dangerous prospect for online users. Fake reviews have affected consumers and stores alike. Furthermore, the problem of fake news has gained attention in 2016, especially in the aftermath of the last U.S. presidential elections. Fake reviews and fake news are a closely related phenomenon as both consist of writing and spreading false information or beliefs. The opinion spam problem was formulated for the first time a few years ago, but it has quickly become a growing research area due to the abundance of user‐generated content. It is now easy for anyone to either write fake reviews or write fake news on the web. The biggest challenge is the lack of an efficient way to tell the difference between a real review and a fake one; even humans are often unable to tell the difference. In this paper, we introduce a new n‐gram model to detect automatically fake contents with a particular focus on fake reviews and fake news.

关键词： Training Technological innovation Social networking (online) Voting Unsolicited e-mail User-generated content Text categorization

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Height Estimation via Stereo Vision system for Unmanned Helicopter Autonomous Landing

Height Estimation via Stereo Vision System for Unmanned Heli...

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2010 International Symposium on Computer,Communication, Control and Automation

作者： Kuo-Hsien Hsia Shao-Fan Lien Juhng-Perng Su Department of Management Information System Far East University Graduate School of Engr.Sci.&Tech.(Doctoral Program) National Yunlin University of Science&Technology Department of Electrical Engineering National Yunlin University of Science&Technology Department of Information Technology Overseas Chinese University

ISBN: (纸本)9781424455652;9781424455669

Auto landing is a very important function of control in the development of autonomous unmanned *** this paper,the stereo vision system is proposed to provide the height information on landing control instead of global positioning system(GPS).GPS provided 3-axis information,but the height error of GPS is usually in meters,which is not accurate enough for *** stereo vision system provided a more accurate height information to correct the error of *** this paper,the stereo vision system is composed of two webcams and the variable baseline method is selected to increase the measurement *** results show that variable baseline method did increase the accuracy of the stereo vision system with the webcams,and that not only provided an authentic piece of height information but also provided another option of sensor for autonomous unmanned helicopter's auto landing control.

关键词： stereo vision system height estimation helicopter landing

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Measuring productivity of software projects: A data envelopment analysis approach

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DECISION SCIENCES 1996年第1期27卷 57-80页

作者： Mahmood, MA Pettingell, KJ Shaskevich, AI Information and Decision Sciences University of Texas–El Paso El Paso TX 79968 E-mail: mmahmood@mail.utep.edu Information and Decision Sciences University of Texas–El Paso El Paso TX 79968 950 Camino Del Rex Las Cruces NM 88001 [?]1Mo Adam Mahmood is a professor of information systems and Ellis and Susan Mayfield Endowed Professor in Business Administration at the University of Texas at El Paso. He received his Ph.D. in management information system from Texas Tech University. His research interests include software engineering information technology in support of superior organizational shategic and ecxlIKlmic perfonnamethe strategic manager's perspectives on information technology and infamation technology for national and inkmatid competitiveness. Dr. Mahtnd has published in Decision SciencesMIS Quarterly Joumal of Management Information SystemsEuropean Joud of Information Systems INFOR-Canadian' Journal of Operation Research and Information Processing and Information and Management among others. He has also edited and published a book in the information technology investment and performance area. He is cmntly serving as editor of the Journal of End-User Computing. He is also serving as guest editor associate editor member of the editorial review board or referee for a number of information systems journals. In addition he has presented research papers served as both a reviewer and discussant chaired sessions and tracks and participated in program committees of several regional national and international conferences.

Current economic conditions are forcing information system departments to focus simultaneously on decreasing costs while increasing software productivity. Improving software productivity is becoming critical because software costs of large in-house software companies have been increasing rapidly. For many organizations, however, measuring software productivity has been a difficult task. Using Data Envelopment Analysis (DEA), this research study investigates the productivity of 78 commercial system projects. The results of this study have practical implications for software project managers undertaking software development. The results showed that the DEA technology can be successfully used to identify efficient and inefficient software projects. Furthermore, within the inefficient group, DEA can also identify factors that affect software productivity in a positive or negative manner, allowing managers to take corrective actions. Based on the findings of this study, the manuscript also provides some practical guidelines for managers to follow in software development.

关键词： Data Envelopment Analysis information systems implementation systems development methodologies

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Image Classification of Forage Plants in Fabaceae Family Using Scale Invariant Feature Transform Method

Image Classification of Forage Plants in Fabaceae Family Usi...

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International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP)

作者： Thidarat Pinthong Worawut Yimyam Narumol Chumuang Mahasak Ketcham Patiyuth Pramkeaw Nattavee Utakrit Dep. of Business Information Management Phetchaburi Rajabhat University Phetchaburi Thailand Dep. of Digital Media Technology Muban Chombueng Rajabhat University Ratchaburi Thailand Dep. of Management Information System King Mongkut’s University of Technology North Bangkok Thailand Dep.Media Technology Program King Mongkut’s University of Technology Thonburi Thaland

ISBN: (数字)9781665415545

ISBN: (纸本)9781665446969

This paper proposes a novel method for the image classification of forage plants in fabaceae family by using Scale Invariant Feature Transform (SIFT) method. The color image extension jpeg color mode RGB adjust the image to 1000x1000 pixels to get a single image of the template file. All of the sample images, four prototype images were standard scaled and rotated. The image was obtained through the image extraction process using SIFT implements and matching dataset of Forage Plants leaves with matching points to evaluate the accuracy of flea leaf identification, it was found that Senna siamea, Clitoria ternatea and Pithecellobium dulce leaves 100% accuracy but Sesbania grandiflora Desv was obtained with 0% accuracy. The total accuracy of all 4 plants 75%, indicated that the photosynthesis of SIFT leaves was suitable for Senna siamea, Clitoria ternatea and Pithecellobium dulce Because it is 100% accurate, but not with Sesbania grandiflora Desv leaves. The accuracy is 0% because the leaves are dark green. The leaves are not clear. And the leaves are slender, evenly spaced leaves, which makes it a very rare feature. While Senna siamea, Clitoria ternatea and Pithecellobium dulce leaves are clear. Leaf edge is unique. Include appropriate techniques for recognition and classification.

关键词： Animals Prototypes Transforms Cows Feeds Standards Image classification

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