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arXiv 2025年

作者： Mishima, Teruyuki Lu, Xiao-Nan Sawa, Masanori Uchida, Yukihiro Accenture Japan Ltd 2-2-2 Nakanoshima Kita-ku Osaka530-0005 Japan Department of Electrical Electronics and Computer Engineering Faculty of Engineering Gifu University 1-1 Yanagido Gifu-shi Gifu501-1193 Japan Graduate School of System Informatics Kobe University 1-1 Rokkodai Nada Kobe Hyogo657-8501 Japan Department of Mathematical Sciences Graduate School of Science Tokyo Metropolitan University 1-1 Minami-Osawa Hachioji Tokyo192-0397 Japan

In this paper we elucidate the advantage of examining the connections between Hilbert-Kamke equations and geometric designs, or Chebyshev-type quadrature, for classical orthogonal polynomials. We first establish a classification theorem for such 5-designs with 6 points. The proof is based on an elementary polynomial identity and some advanced techniques on the computation of the genus of a certain irreducible curve. We then prove a necessary and sufficient condition for the existence of 5-designs with rational points, especially for the Chebyshev measure of the first kind. It is noteworthy that this result presents a completely explicit construction of rational designs. Moreover, we create novel connections among Hilbert-Kamke equations, geometric designs and the Prouhet-Tarry-Escott (PTE) problem. For example, we establish that the 5-designs with 6 points for the Chebyshev measure appear in the famous parametric solution for the PTE problem found by Borwein (2002).MSC Codes 33C45, 05E99, 65D32 (Primary) 12E10, 11E76 (Secondary) Copyright © 2025, The Authors. All rights reserved.

关键词： Geometry

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Immersive Modeling Framework for Training Applications

Immersive Modeling Framework for Training Applications

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International Conference on Advanced Learning Technologies (ICALT)

作者： Vinicius Chrisosthemos Teixeira Carlo Smaniotto Mantovani Alexandre Cardoso Carlos Alexandre dos Santos Márcio Sarroglia Pinho Computer Science Graduate Program School of Technology Pontifical Catholic University of Rio Grande do Sul Porto Alegre Brazil Faculty of Electrical Engineering Federal University of Uberlândia Uberlândia Brazil School of Technology Pontifical Catholic University of Rio Grande do Sul Porto Alegre Brazil

This article describes a framework for modeling and executing training in augmented and virtual reality environments. The framework was designed based on characteristics observed in existing training applications for complex tasks, such as the use of tools, control panels and the need for step-by-step instructions. Unlike other frameworks, in the proposed system, it is possible to create the training entirely within the virtual/augmented environment, avoiding constant switching between 2D and 3D environments. The framework allows for the definition of steps in a training program, each of which includes textual instructions, videos, and 3D objects, static or animated, anchored in the real world. To demonstrate the capabilities of the framework, a training program for operating a Universal Testing Machine was created as a case study. Overall, the proposed framework allows for the creation of effective and efficient AR training programs for a variety of tasks and industries.

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A conceptual framework of deploying a trained CNN model for mobile breast self-screening 18

A conceptual framework of deploying a trained CNN model for ...

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18th International Conference on electrical engineering/Electronics, computer, Telecommunications and Information Technology, ECTI-CON 2021

作者： Roslidar Muchamad, Masduki Khamdan Arnia, Fitri Syukri, Maimun Munadi, Khairul Universitas Syiah Kuala Doctoral Program School of Engineering Post Graduate Program Banda Aceh23111 Indonesia Universitas Syiah Kuala Department of Electrical and Computer Engineering Banda Aceh23111 Indonesia Universitas Syiah Kuala Banda Aceh23111 Indonesia Universitas Syiah Kuala Medical Faculty Banda Aceh23111 Indonesia Universitas Syiah Kuala Banda Aceh23111 Indonesia

ISBN: (纸本)9780738111278

In this article, we propose a conceptual framework of mobile self-screening to detect breast cancer at the initial stage using temperature characteristics. A trained convolutional neural network (CNN) is implemented to extract and classify the breast thermogram. Moreover, a histogram of temperature distribution is also provided to support a recommendation to the user. As we consider the user's data privacy, reliability, low latency, and low cost, we also suggest some recommendations in inferencing the CNN model on the mobile device. Finally, we describe the application overview to demonstrate the feature function. © 2021 IEEE.

关键词： Neural network models

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Watch from sky: machine-learning-based multi-UAV network for predictive police surveillance

arXiv

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arXiv 2022年

作者： Sugano, Ryusei Shinkuma, Ryoichi Nishio, Takayuki Itahara, Sohei Mandayam, Narayan B. Faculty of Engineering Shibaura Institute of Technology 3-7-5 Toyosu Koto-ku Tokyo135-8548 Japan School of Engineering Tokyo Institute of Technology Japan Graduate School of Informatics Kyoto University Kyoto606-8501 Japan WINLAB Department of Electrical and Computer Engineering Rutgers University United States

This paper presents the watch-from-sky framework, where multiple unmanned aerial vehicles (UAVs) play four roles, i.e., sensing, data forwarding, computing, and patrolling, for predictive police surveillance. Our framework is promising for crime deterrence because UAVs are useful for collecting and distributing data and have high mobility. Our framework relies on machine learning (ML) technology for controlling and dispatching UAVs and predicting crimes. This paper compares the conceptual model of our framework against the literature. It also reports a simulation of UAV dispatching using reinforcement learning and distributed ML inference over a lossy UAV network. Copyright © 2022, The Authors. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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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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IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)

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

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.

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Improving Candle Direction Classification in Forex Market Using Support Vector Machine with Hyperparameters Tuning

Improving Candle Direction Classification in Forex Market Us...

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International Conference on informatics and Computing (ICIC)

作者： Raymond Sunardi Oetama Yaya Heryadi Lukas Wayan Suparta Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department Binus Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Indonesia

ISBN: (纸本)9798350345728

Foreign Exchange market is the world's largest daily currency turnover. Two of the popular currencies Euro and Pound sterling traded against the US Dollar. Since the Russia and Ukraine war started in February 2022, their exchange rates decrease to the lowest rate ever. Even though the general trend is bearish, several daily candles increase for some days making challenges for forex analysts. To solve this problem, classification is applied. The data is labeled downward and upward. By utilizing Linear Kernel and Radial Basis Function (RBF) Kernel-based Support Vector Machines (SVM), the candle direction can be classified and optimized by tuning the Hyperparameters. The accuracy of candle direction classifications are highly improved. After tuning, in general, classification using Linear Models can outperform RBF Models. The best accuracy found on the Pound sterling against US Dollar by using the Linear model is 98.11% and the accuracy becomes 100% on data testing at a ratio of 70:30. Whilst for the Euro against the US Dollar, the best accuracy found the same for both Linear and RBF models on a ratio of 80:20 at 97.53%. However, on data testing, it decreases to 94.51% for Linear Model and 93.41% using RBF Model. The implication of this study is SVM can successfully classify candle direction on pairs in the Forex Market that are affected by a big event that comes for such a long period as long as the hyperparameter is tuned.

关键词： Support vector machines Training Exchange rates Market research Data models Kernel informatics

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A Near-Optimal Category Information Sampling in RFID Systems

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IEEE Transactions on Mobile Computing 2025年

作者： Wang, Xiujun Liu, Zhi Zhou, Xiaokang Liao, Yong Hu, Han Zheng, Xiao Li, Jie Anhui University of Technology School of Computer Science Ma'anshan243032 China Anhui Engineering Research Center for Intelligent Applications and Security of Industrial Internet Ma'anshan243032 China University of Electro-Communications Graduate School of Informatics and Engineering Tokyo182- 8585 Japan Shiga University Faculty of Data Science Hikone522-8522 Japan RIKEN Center for Advanced Intelligence Project Tokyo103-0027 Japan University of Science and Technology of China School of Cyber Science and Technology Hefei China Beijing Institute of Technology School of Information and Electronics Beijing China School of Electronic Information and Electrical Engineering Shanghai200240 China

In many RFID-enabled applications, objects are classified into different categories, and the information associated with each object's category (called category information) is written into the attached tag, allowing the reader to access it later. The category information sampling in such RFID systems, which is to randomly choose (sample) a few tags from each category and collect their category information, is fundamental for providing real-time monitoring and analysis in RFID. However, to the best of our knowledge, two technical challenges, i.e., how to guarantee a minimized execution time and reduce collection failure caused by missing tags, remain unsolved for this problem. In this paper, we address these two limitations by considering how to use the shortest possible time to sample a different number of random tags from each category and collect their category information sequentially in small batches. In particular, we first obtain a lower bound on the execution time of any protocol that can solve this problem. Subsequently, we present a near-OPTimal Category information sampling protocol (OPT-C) that solves the problem with an execution time close to the lower bound. Finally, extensive simulation results demonstrate the superiority of OPT-C over existing protocols, while real-world experiments further validate its practicality. © 2002-2012 IEEE.

关键词： category information sampling execution time lower bound near-optimal protocol RFID systems

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The role of input imaging combination and ADC threshold on segmentation of acute ischemic stroke lesion using U-Net

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European Radiology 2023年第9期33卷 6157-6167页

作者： Li, Ya-Hui Lin, Shao-Chieh Chung, Hsiao-Wen Chang, Chia-Ching Peng, Hsu-Hsia Huang, Teng-Yi Shen, Wu-Chung Tsai, Chon-Haw Lo, Yu-Chien Lee, Tung-Yang Juan, Cheng-Hsuan Juan, Cheng-En Chang, Hing-Chiu Liu, Yi-Jui Juan, Chun-Jung Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan Department of Medical Imaging China Medical University Hsinchu Hospital No. 199 Sec. 1 Xinglong Rd. Zhubei City Hsinchu County 302 Hsinchu Taiwan Ph.D. Program in Electrical and Communication Engineering Feng Chia University Taichung Taiwan Department of Electrical Engineering National Taiwan University Taipei Taiwan Department of Management Science National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Biomedical Engineering and Environmental Sciences National Tsing Hua University Hsinchu Taiwan Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Radiology School of Medicine College of Medicine China Medical University Taichung Taiwan Department of Medical Imaging Medical University Hospital Taichung Taiwan Department of Neurology China Medical University Hospital Taichung Taiwan Cheng Ching Hospital Taichung Taiwan Master’s Program of Biomedical Informatics and Biomedical Engineering Feng Chia University Taichung Taiwan Department of Automatic Control Engineering Feng Chia University No. 100 Wenhwa Rd. Seatwen Taichung 40724 Taiwan Department of Biomedical Engineering The Chinese University of Hong Kong ERB1112 11/F William M.W. Mong Engineering Building N.T Shatin Hong Kong Multi-Scale Medical Robotics Center The Chinese University of Hong Kong N.T Shatin Hong Kong Department of Biomedical Engineering National Defense Medical Center Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan

Background: To evaluate the effect of the weighting of input imaging combo and ADC threshold on the performance of the U-Net and to find an optimized input imaging combo and ADC threshold in segmenting acute ischemic stroke (AIS) lesion. Methods: This study retrospectively enrolled a total of 212 patients having AIS. Four combos, including ADC-ADC-ADC (AAA), DWI-ADC-ADC (DAA), DWI-DWI-ADC (DDA), and DWI-DWI-DWI (DDD), were used as input images, respectively. Three ADC thresholds including 0.6, 0.8 and 1.8 × 10^–3 mm²/s were applied. Dice similarity coefficient (DSC) was used to evaluate the segmentation performance of U-Nets. Nonparametric Kruskal–Wallis test with Tukey–Kramer post-hoc tests were used for comparison. A p <.05 was considered statistically significant. Results: The DSC significantly varied among different combos of images and different ADC thresholds. Hybrid U-Nets outperformed uniform U-Nets at ADC thresholds of 0.6 × 10^–3 mm²/s and 0.8 × 10^–3 mm²/s (p <.001). The U-Net with imaging combo of DDD had segmentation performance similar to hybrid U-Nets at an ADC threshold of 1.8 × 10^–3 mm²/s (p =.062 to 1). The U-Net using the imaging combo of DAA at the ADC threshold of 0.6 × 10^–3 mm²/s achieved the highest DSC in the segmentation of AIS lesion. Conclusions: The segmentation performance of U-Net for AIS varies among the input imaging combos and ADC thresholds. The U-Net is optimized by choosing the imaging combo of DAA at an ADC threshold of 0.6 × 10^–3 mm²/s in segmentating AIS lesion with highest DSC. Key Points: • Segmentation performance of U-Net for AIS differs among input imaging combos. • Segmentation performance of U-Net for AIS differs among ADC thresholds. • U-Net is optimized using DAA with ADC = 0.6 × 10^–3mm²/s. © 2023, The Author(s), under exclusive licence to European Society of Radiology.

关键词： Deep Learning Diffusion Magnetic Resonance Imaging Ischemic Stroke Neural Networks, computer Retrospective Study

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Relationship between number of annotations and accuracy in segmentation of the erector spinae muscle using Bayesian U-Net in torso CT images

Relationship between number of annotations and accuracy in s...

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International Forum on Medical Imaging in Asia 2021, IFMIA 2021

作者： Wakamatsu, Yuichi Kamiya, Naoki Zhou, Xiangrong Hara, Takeshi Fujita, Hiroshi Department of Media Informatics Graduate School of Information Science and Technology Aichi Prefectural University 1522-3 Ibaragabasama Nagakute-shi Aichi480-1198 Japan Department of Information Systems Graduate School of Information Science and Technology Aichi Prefectural University 1522-3 Ibaragabasama Nagakute-shi Aichi480-1198 Japan Department of Electrical Electronic and Computer Engineering Faculty of Engineering Gifu University 1-1 Yanagido Gifu-shi Gifu501-1193 Japan

ISBN: (数字)9781510644212

ISBN: (纸本)9781510644205

Supervised learning for image segmentation requires annotated images. However, image annotation has the problem that it is time-consuming. This problem is particularly significant in the erector spinae muscle segmentation due to the large size of the muscle. Therefore, this study considers the relationship between the number of annotated images used for training and segmentation accuracy of the erector spinae muscle in torso CT images. We use Bayesian U-Net, which has shown high accuracy in thigh muscle segmentation, for the segmentation of the erector spinae muscle. In the network training, we limit the number of slices for each case and the number of cases to 100%, 50%, 25%, and 10%. In the experiment, we use 30 torso CT images, including 6 cases for the test dataset. Experimental results are evaluated by the mean Dice value of the test dataset. Using 100% of the slices per case, the segmentation accuracy with 100%, 50%, 25%, and 10% of the cases was 0.934, 0.927, 0.926, and 0.890, respectively. On the other hand, using 100% of the cases, the segmentation accuracy with 100%, 50%, 25%, and 10% of the slices per case was 0.934, 0.934, 0.933, and 0.931, respectively. Furthermore, the segmentation accuracy with 100% of the cases and 10% of the slices per case was higher than that of the previous method. We showed that it is feasible to achieve high segmentation accuracy with a limited number of annotated images by selecting several slices from a limited number of cases for training. © 2021 SPIE.

关键词： Image segmentation

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Personnel System Development with Integrated Military Education Information System (MEIS) in Supporting the Personnel Position and Career 7

Personnel System Development with Integrated Military Educat...

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7th International Conference on ICT for Smart Society, ICISS 2020

作者： Setyaningrum, Leli Supangkat, Suhono H. Warnars, Harco Leslie Hendric Spits Abraham, Juneman Abdurachman, Edi Bina Nusantara University Doctorate Program of Computer Science Jakata Barat11530 Indonesia Institut Teknologi Bandung School of Electrical Engineering and Informatics Bandung40132 Indonesia Nusantara University Graduate Program Doctor of Computer Science Bina Computer Science Department BINUS Jakarta11530 Indonesia Bina Nusantara University BINUS Faculty of Humanities Psychology Department Jakarta11480 Indonesia

ISBN: (纸本)9781665404228

Personnel and education data very important for organizations, including the military. All data related to military personnel will give effect positions and careers in the military field. The integration of personnel and education data can assist in processing and decision making. An analysis is needed so that the developed system can be useful for the long term. Analysis with IT balanced scorecard and COBIT® 2019, will be able to help and fill the gaps in the existing system based on the objectives of the military organization itself. It is shown that the domains BAI05 (Managed Organizational Change) and DSS02 (Managed Service Requests and Incidents) are still not being implemented well. The system developed will have the features and capabilities to support the organization in achieving its goals, including in the field of staffing and education. Besides, it provides convenience in making decisions in terms of positions related to personnel careers. © 2020 IEEE.

关键词： Decision making

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