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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Tsung-Wei Lin Sofia Ormazabal Arriagada Che Lin Graduate Institute of Communication Engineering National Taiwan University (NTU) Taiwan International Graduate Program AIoT NTU Research Center for Information Technology Innovation Academia Sinica Department of Electrical Engineering NTU Center for Advanced Computing and Imaging in Biomedicine NTU Smart Medicine and Health Informatics Program NTU

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Providing robust prognosis predictions for cancers with limited data samples remains a challenge for precision oncology. In this study, we propose a novel approach that combines multi-task learning (MTL) and graph neural networks (GNNs) to address this issue. By representing gene-gene interactions as a graph network, our approach leverages multi-task learning to effectively capture the relationships of genes relevant to the oncogenesis and progression of breast, lung, and colon cancer. We demonstrate that our approach improves the cancer prognosis prediction for cancers with fewer samples, such as colon adenocarcinoma, by leveraging the shared gene-gene interactions across different cancer types, obtaining increases in the area under the precision-recall curve (AUPRC) of 24%. Our work contributes to the field of smart healthcare by demonstrating the potential of MTL and GNNs for enhancing cancer prognosis prediction, even with limited data samples.

关键词： Lungs Genomics Medical services Colorectal cancer Breast Multitasking Oncology Graph neural networks Prognostics and health management Cancer

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Exploring Tourist Feedback on Riau Attractions Through Indonesian Language YouTube Opinion Using Naïve Bayes Algorithm

Exploring Tourist Feedback on Riau Attractions Through Indon...

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2023 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications technology, IAICT 2023

作者： Kurniawan, Rahmad Iskandar, Iwan Lestari, Fitra Harpizon, Habibi Al Rasyid Husti, Ilyas Faculty of Mathematics and Natural Sciences Universitas Riau Department of Computer Science Pekanbaru Indonesia Universitas Islam Negeri Sultan Syarif Kasim Riau Department of Informatics Engineering Pekanbaru Indonesia Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Selangor Bangi Malaysia Graduate Program Universitas Islam Negeri Sultan Syarif Kasim Riau Pekanbaru Indonesia

ISBN: (纸本)9798350313635

YouTube is a widely-used platform in Indonesia, with 93.8% of its users. As such, it presents a valuable opportunity for marketing tourist destinations, particularly in Riau province, which aims to become Indonesia's top Halal travel destination. Tourism is a vital contributor to the economic growth of regions, and each province in Indonesia competes to promote its tourist attractions to attract more visitors every year. However, the large volume of data can challenge the manual analysis of feedback from YouTube's features, such as likes, dislikes, and comments. A literature review suggests that the Naive Bayes algorithm, which uses machine learning, is helpful for sentiment analysis. Therefore, this study aims to analyze public sentiment toward tourist destinations in Riau province by analyzing YouTube comments using the Naïve Bayes algorithm. The study used 1680 opinions collected from 10 YouTube videos showcasing tourist destinations in Riau. The Naive Bayes algorithm classified 60% of the comments as positive, 32% as neutral, and 8% as negative. The experimental results indicated an accuracy and precision of 73%, a recall of 94%, and an F-1 Score of 82%. The study used the word frequency technique to reveal that Riau could become a popular halal tourist destination based on several frequently occurring words in the comments. © 2023 IEEE.

关键词： Sentiment analysis

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Customer Segmentation and Churn Prediction via Customer Metrics

Customer Segmentation and Churn Prediction via Customer Metr...

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IEEE Signal Processing and Communications Applications (SIU)

作者： Tunahan Bozkan Tuna Ç akar Alperen Sayar Seyit Ertuğ rul MEF University Information Technology Graduate Program Istanbul Turkey Computer Engineering Department MEF University Istanbul Turkey Department of Information Technology MEF University Istanbul Turkey

ISBN: (数字)9781665450928

ISBN: (纸本)9781665450935

In this study, it is aimed to predict whether customers operating in the factoring sector will continue to trade in the next three months after the last transaction date, using data- driven machine learning models, based on their past transaction movements and their risk, limit and company data. As a result of the models established, Loss Analysis (Churn) of two different customer groups (Real and Legal factory) wascarried out. It was estimated by the XGBoost model with anF1 Score of 74% and 77%. Thanks to this modeling, it was aimed to increase the retention rate of customers through special promotions and campaigns to be made to these customer groups, together with the prediction of the customerswho will leave. Thanks to the increase in retention rates, a direct contribution to the transaction volume on a company basis was ensured.

关键词： Measurement Analytical models Law Companies Machine learning Predictive models Signal processing

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Applying Smart Glasses in Situated Exploration for Learning English in a National Science Museum

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IEEE Transactions on Learning Technologies 2023年第5期16卷 820-830页

作者： Chen, Hong-Ren Lin, Wen-Shan Hsu, Tien-Yu Lin, Tzu-Chun Chen, Nian-Shing National Taichung University of Education Department of Digital Content and Technology Taichung City40306 Taiwan National Cheng Kung University Institute of International Management Tainan City701 Taiwan National Museum of Nature Science Department of Science Education Taichung City404023 Taiwan Graduate Institute of Library and Information Science National Chung Hsing University Taichung City40306 Taiwan National Taiwan Normal University Program of Learning Sciences Taipei City106 Taiwan

Research on the use of augmented reality technology in museums is mostly limited to scientific knowledge. The use of wearable device technology learning materials to benefit students in the process of English learning has been somewhat explored, along with differences in students' learning styles and their influence on students' learning motivation, but there remains much to be done in this field. This study explored the learning effect of smart glasses integration into the English language dinosaur exhibition at the Museum of Natural Science and investigated their impact on motivation. The experimental group used smart glasses learning strategy to facilitate their learning experience, whereas the control group used a tablet learning strategy. The research results show that: 1) Learning effectiveness and motivation were significantly superior when using smart glasses learning strategy, as compared to using a tablet learning strategy when learning through the English language situated exploration game. 2) The interaction between different learning strategies and learning styles had a significant impact on learning effectiveness. In the smart glasses learning strategy group and the tablet learning strategy group, the learning effectiveness of the kinesthetic students was significantly higher than those of the auditory students. The learning effectiveness of the visual students using the tablet learning strategy was higher than auditory students. 3) The interaction between different learning strategies and learning styles had no significant effect on learning motivation. In terms of learning motivation, visual students were more affected than auditory and kinesthetic students. © 2008-2011 IEEE.

关键词： Glass

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UAV-Aided Data Acquisition Using Gaining-Sharing Knowledge Optimization Algorithm

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Computers, Materials & Continua 2022年第9期72卷 5999-6013页

作者： Rania M Tawfik Hazem A.A.Nomer M.Saeed Darweesh Ali Wagdy Mohamed Hassan Mostafa Wireless Intelligent Networks Center(WINC) School of Engineering and Applied SciencesNile UniversityGiza12677Egypt School of Information Technology and Computer Science(ITCS) Nile UniversityGiza12677Egypt Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Department of Mathematics and Actuarial Science School of Science and EngineeringThe American University in CairoEgypt Electronics and Communications Engineering Department Cairo UniversityEgypt University of Science and Technology Nanotechnology and Nanoelectronics ProgramZewal City of Science and TechnologyOctober Gardens6th of OctoberGiza12578Egypt

Unmanned Aerial Vehicles(UAVs)provide a reliable and energyefficient solution for data collection from the Narrowband Internet of Things(NB-IoT)***,the UAV’s deployment optimization,including locations of the UAV’s stop points,is a necessity to minimize the energy consumption of the UAV and the NB-IoT devices and also to conduct the data collection *** this regard,this paper proposes GainingSharing Knowledge(GSK)algorithm for optimizing the UAV’s *** GSK,the number of UAV’s stop points in the three-dimensional space is encapsulated into a single individual with a fixed length representing an entire *** superiority of using GSK in the tackled problem is verified by simulation in seven *** provides significant results in all seven scenarios compared with other four optimization algorithms used before with the same ***,the NB-IoT is proposed as the wireless communication technology between the UAV and IoT devices.

关键词： NB-IoT UAV GSK stop points optimization

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Dynamic Terrain Data Exchange in a Collaborative Terrain Editor

Informatica (Slovenia)

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Informatica (Slovenia) 2022年第4期46卷 575-582页

作者： Tarigan, Jos Timanta Sitompul, Opim Salim Zarlis, Muhammad Nababan, Erna Budhiarti Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Information Systems Management Department BINUS Graduate Program Bina Nusantara University Jakarta Indonesia

In a computer supported cooperative work (CSCW), data consistency between collaborating users is a crucial issue. Based on the type of the application, ensuring data consistency can be a lengthy process that takes time and affects the system’s performance. In most 3D application, terrain data are massive due to its size. Exchanging this data may be expensive and may cause significant delay. In a real-time collaborative terrain editor, this issue becomes more significant due to terrain data exchange is consistently occurred between collaborating users. We present a solution to perform a conflict-free dynamic terrain data exchange in a real-time collaborative terrain editor. Our objective is to develop a method that able to ensure data consistency amongst collaborating peers in real-time manner. The main idea of our method is to split the terrain into smaller patches and synchronize the changes efficiently by only exchanging the modified patches. We applied our solution to a collaborative terrain editor application to test its performance in a real-time collaborative editing session. The tests were done in multiple scenarios, using different patch model, brush size (in the terrain editor), and connection setup between server and collaborating clients. The result shows that our protocol is capable to maintain data consistency between collaborating clients in a real-time terrain edition session. The delay is varied and highly depends on the data size and client-server environment setup. The overall test shows that it is possible to perform a collaborative terrain editing with an acceptable response time delay. In this paper, we present our proposed method, the implementation, and the result data from the test. © 2022 Slovene Society Informatika. All rights reserved.

关键词： Electronic data interchange

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Industrial revolution 4.0 on big data adoption factors on social media users and popularity brands 2

Industrial revolution 4.0 on big data adoption factors on so...

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2nd International Conference on Lesson Study of Science technology Engineering and Mathematics 2020, ICOLSSTEM 2020

作者： Sardjono, W. Rama Putra, G. Selviyanti, E. Cholidin, A. Salim, G. Information Systems Management Department Binus Graduate Program-Master of Information Systems Management Bina Nusantara University Jakarta11480 Indonesia Computer Science Study Program Faculty of Mathematics and Natural Sciences Pakuan University Bogor Indonesia Health Department Politeknik Negeri Jember Jember Jawa Timur68124 Indonesia Law Studi Program Faculty of Law University of Muhammadiyah Jakarta Indonesia Post Graduate Program Faculty of Economic Science University of Trisakti Jakarta Indonesia

The purpose of writing this paper is to look at how factors of big data adoption affect the users of social media and brand popularity. The method used in the writing of this paper is by using path analysis and also by doing literature study to find reference material. The results of the analysis indicate that there is influence of big data adoption factors that affect the popularity of the brand. With this research, we get big data model that influence the brand popularity. © 2021 Published under licence by IOP Publishing Ltd.

关键词： Big data

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A task-oriented framework for generative AI in design

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Journal of Creativity 2024年第2期34卷

作者： Furtado, Lara Sucupira Soares, Jorge Barbosa Furtado, Vasco Department of Transportation Engineering Federal University of Ceará Brazil Applied Informatics Graduate Program University of Fortaleza Unifor Brazil ETICE State of Ceará Information Technology Company Brazil

The intersection of Artificial Intelligence and Design disciplines such as Architecture, Urban Planning, Engineering and Product Design has been a longstanding pursuit, with Generative AI (GAI) ushering in a new era of possibilities. The research presented here explores how GAI can enhance creativity and assist Design practitioners with tasks to create products such as, but not limited to, renderings, concepts, construction techniques, materials, data analytics or maps. We apply a framework of combinational, exploratory and transformational creativity to organize how recent advancements in GAI can support each creative category. We propose a conceptual framework of GAI towards transformational creativity, and identify real-world examples to demonstrate GAI's impact, such as transforming sketches into detailed renders, facilitating real-time 3D model generation, predicting trends through analytics and creating images or reports via text prompts. Our work envisions a future where GAI becomes a real-time collaborator to complete certain automated tasks while liberating Designers to focus on transformational innovation. © 2024

关键词： Creative computing Generative artificial intelligence Product Transformational Creativity

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Exploring User Attitudes and Innovative System Design for Remote Lighting Control Systems in Thailand’s Creative Industries

Exploring User Attitudes and Innovative System Design for Re...

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IEEE International Conference on Industrial Engineering and Engineering Management

作者： Thammanoon Jeerasottikule Nagul Cooharojananone Kanokwan Atchariyachanvanich Technopreneurship and Innovation Management Program Graduate School Chulalongkorn University Bangkok Thailand Department of Mathematics and Computer Science Faculty of Science Chulalongkorn University Bangkok Thailand School of Information Technology King Mongkut’s Institute of Technology Ladkrabang Bangkok Thailand

ISBN: (数字)9798350386097

ISBN: (纸本)9798350386103

In this paper, the authors investigate the current state of the lighting design and control sector in Thailand’s creative industry. The government aims to promote the creative industry as a key source of income, but there needs more skilled professionals in the industry. The authors have found that successful cases have used the Internet for remote controlling in the creative industry in other countries. Therefore, the paper will explore the potential of using technology to improve professional efficiency and assess the feasibility of implementing remote lighting control systems via the Internet with Thai lighting designers and lighting console operators. Data will be collected through qualitative in-depth interviews and quantitative surveys. The results have shown a promising acceptance rate of wireless devices for lighting control due to their mobility, flexibility, cost-effectiveness, and positive attitudes toward adopting Internet technology. The authors have also proposed a concept design for an internet-based control system tailored to Thai users, focusing on simplicity, ease of connection, and user-friendliness to accommodate those with limited network configuration knowledge. The proposed system aims to reduce professionals, save time, and increase convenience, leveraging Thailand’s extensive wireless internet coverage. These systems could significantly benefit Thailand’s creative industry by addressing the shortage of skilled professionals and improving efficiency.

关键词： Industries Wireless communication Surveys Knowledge engineering Attitude control Lighting Lighting control Internet Interviews System analysis and design

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IoT-Based Strawberry Disease Detection With Wall-Mounted Monitoring Cameras

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IEEE Internet of Things Journal 2024年第1期11卷 1439-1451页

作者： Lin, Yi-Bing Liu, Chun-You Chen, Wen-Liang Chang, Chia-Hui Ng, Fung-Ling Yang, Krista Hsung, Jerry Department of Computer Science National Yang Ming Chiao Tung University Hsinchu30010 Taiwan China Medical University College of Humanities and Sciences Taichung404 Taiwan National Cheng Kung University MiinWu School of Computing Tainan701 Taiwan Academia Sinica Research Center for Information Technology Innovation Taipei115 Taiwan National Yang Ming Chiao Tung University College of Biological Science and Technology Hsinchu30010 Taiwan National Yang Ming Chiao Tung University Industrial Development Graduate Program College of Biological Science and Technology Hsinchu30010 Taiwan Proto Solution System Company Ltd. Hsinchu302052 Taiwan

This article proposes StrawberryTalk, an Internet of Things (IoT) platform for image-based strawberry disease detection. StrawberryTalk reuses the wall-mounted monitoring cameras without extra hardware cost. The contributions of StrawberryTalk are the utilization of IoT for automatic photo shoot and the wind detection mechanism to eliminate the obscure photos due to the wind effects. Also, the data preprocessing and the infection detection models are manipulated as IoT devices to simplify the implementation of the multicascade artificial intelligence (AI) models. We derive the relationship between the camera zoom factor and the distance between the camera and the strawberries for optimal disease detection. Accuracy of detection may be affected by obscure photos. In terms of eliminating obscure photos due to wind effect, we analytically derive the relationship between the wind alert delay and the number of obscure photos that must be retaken. For the greenhouses in the Bao Mountain, we only need to retake one photo. Based on the experiments, the mean average precision (mAP) of StrawberryTalk (to detect exact spots in a leaf) can be up to 92.37%, which is better than the previous approaches. To detect if a pot has infected leaves, the accuracy of StrawberryTalk can be up to 97.92% at the zoom factor 30×. In commercial operation, it is important to detect all infected strawberry pots. StrawberryTalk is able to detect all infected pots (i.e., recall is 100%) with a camera of zoom factor of 12× . The accuracy is 96.88%. © 2014 IEEE.

关键词： Cameras

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