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28th International Conference on Knowledge Based and Intelligent information and engineering Systems, KES 2024

作者： Hoshinoa, Sara Itoa, Taiki Matsuzawaa, Takuya Ozawaa, Haruki Arimab, Sumika Degree Program in Systems and Information Engineering University of Tsukuba Japan Institute of Systems and Information Engineering University of Tsukuba Japan

This study aimed to develop an interaction modeling method for high-dimensional industrial data with sparsity. Particularly, we discussed the potential and limitations of Sparse Factorization Machines (SFM) with feature selection capabilities after examining the applicability of Factorization Machines (FMs) to numerical and categorical mixed data like industrial data. FMs has been already a major recommendation engine outperforms SVM because of robustness to the sparse data. However, conventional FMs and SFM based on the L2 norm regularization tolerate huge False-Positives (FPs), which is fatal in the application to real data to which the oracle model is unknown. Therefore, in this study, we focus on the way to automatically reduce the several millions of FPs in interactions while keeping high True-Positives (TPs). For the purpose, SFM with trigonometric inequality (TI) upper boundaries (Atarashi et al., 2021) is improved by two directions. The first is the development of TI_SFM (L1) with an L1 norm for selection of main factors, particularly for FPs reduction of the main factors. The second is the application of adaptive technique for reducing FPs of interactions (combinatorial features). We newly developed "Adaptive SFM" with adaptive technique to introduce data-driven penalty of the interaction term. As the result of numerical evaluations using a mass production oracle interaction model and several simulation data, False-Positives of the main factors (F) and the interactions (F) are significantly reduced, while keeping high level of True-Positives of the main factor () and the interactions (). Concretely, our proposed Adaptive SFM (L1) outperforms the original TI_SFM (L2) as much reducing F and F by over 99% when applying our proposed penalty considering not only the relationship between the explanatory variable and the objective variable, as basic adaptive technique, but also the factor loading indicating the relationship between the latent vector internally opt

关键词： Factorization

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Low-cost real-time environmental noise monitoring system design and implementation

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International Journal of Environmental Studies 2024年第3期81卷 1045-1057页

作者： Hamamcı, Samet Feyyaz Doğru, Ahmet Özgür Graduate School Geographical Information Technologies PhD Program Istanbul Technical University Istanbul Turkey Faculty of Civil Engineering Department of Geomatics Engineering Istanbul Technical University Istanbul Turkey

Environmental noise has a negative impact on human health and well-being. Real-time noise monitoring for effective noise control and management helps to identify noise sources and areas with high noise pollution, and potential mitigation strategies in urban planning. This paper reports work with a pilot scale system that can continuously collect noise data to assess noise levels accurately for real-time monitoring of environmental noise, focusing on hardware and software aspects and potential applications. The system permits the transfer of measurement data to the central server computer, with storage and display there, with the code written using Python. This system includes Web integration, with open source technologies to provide data access, and is based on Wi-Fi communication and a Control Card with Wi-Fi technology. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Noise pollution

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EFFECTS OF REFRACTIVE INDEX AND ASPECT RATIO ON THE PARTICLE IMAGES IN A LEVITATED DROPLET

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Multiphase Science and Technology 2024年第1期36卷 13-26页

作者： Gatete, Eugene Kaneko, Akiko Shen, Biao University of Tsukuba Systems and Information Engineering Graduate School of Science and Technology Degree Program of Engineering Mechanics and Energy 1-1-1 Tennodai Tsukuba Ibaraki305-8573 Japan University of Tsukuba Faculty of Engineering of Information Engineering and Systems 1-1-1 Tennodai Tsukuba Ibaraki305-8573 Japan

A technique using droplets suspended by ultrasound has attracted attention as one of the containerless processing methods. While this can avoid contamination from the container, it is known that ultrasonic levitation creates flow fields inside and outside the droplet. For more precise droplet control, it is desirable to elucidate the internal flow of the droplet, and measurements of the internal flow have been performed using the particle image velocimetry (PIV). The aim of this study is to elucidate the internal flow field behavior by solving optical problems and improving the accuracy of velocity field measurements in levitated droplets. The fluid that is to be investigated is scattered with small tracer particles and illuminated by a laser to capture the flow on a created laser sheet. The curvature distortion is successfully visualized using the PIV approach toward distortion correction using calibration methods. The curvature distortion illustration was performed based on the refractive index and aspect ratio of the simulated droplet in acrylic materials. The fluid flow, affected by droplet curvature and refractive index, has been visualized for both levitated and simulated droplets. The experimental results showed that the droplet curvature can be distorted in two types such as radial and tangential distortions and increase as the refractive index and aspect ratio increases. © 2024 by Begell House, Inc.

关键词： Refractive index

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Optimizing Menu Bundling Strategies Through Apriori Algorithm in Sales Analysis 4

Optimizing Menu Bundling Strategies Through Apriori Algorith...

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4th International Conference on Intelligent Cybernetics Technology and Applications, ICICyTA 2024

作者： Tama, Ahmad Sambang Setya Hamami, Faqih Adi, Taufik Nur Telkom University Information Systems Study Program Faculty of Industrial Engineering Bandung Indonesia

ISBN: (纸本)9798331506490

Indonesia, as one of the largest coffee producers and exporters in the world, has experienced significant growth in the number of coffee shops, driven by increasing consumer demand for ready-to-drink coffee. This study aims to enhance sales performance at Authen Café and Space through the implementation of a menu bundling strategy. By utilizing data mining techniques and the Apriori algorithm, customer purchasing patterns were analyzed to identify optimal menu combinations. The data was collected directly at Authen Cafe during the period from April to August 2028. The analysis revealed that bundling strategies, such as combining Ayam Rica-Rica with Es Kopi Susu Karamel, are effective in increasing sales volume and product popularity among consumers. Furthermore, this study evaluated the impact of offering discounts on bundled packages on the café's profitability, demonstrating that this approach can boost net profit without sacrificing profit margins. This research provides significant insights into the application of data-driven marketing strategies within the café'industry and offers guidance for more effective managerial decision-making. © 2024 IEEE.

关键词： Profitability

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Comparative Analysis of Deep Learning Methods for Automated Diagnosis of Pulmonary Diseases from Chest X-Ray Images: A Study Based on ICD-10 2

Comparative Analysis of Deep Learning Methods for Automated ...

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2nd International Conference on Data, information and Computing Science, CDICS 2024

作者： Wijayakusuma, I.G.N. Lanang Sudarma, Made Putra, I. Ketut Gede Darma Sudana, Oka Engineering Study Program Universitas Udayana Bukit Jimbaran Indonesia Electrical Engineering Study Program Universitas Indonesia Bukit Jimbaran Indonesia Information Technology Study Program Universitas Udayana Bukit Jimbaran Indonesia

ISBN: (纸本)9781643685762

This research delves into the comparative assessment of diverse deep learning architectures for the automated identification of pulmonary diseases in chest X-ray images, aligning with the diagnostic framework of the International Classification of Deseases, 10th Revision (ICD-10). The evaluated architectures encompass Convolutional Neural Network (CNN), MobileNetV2, DenseNet, VGG16, and InceptionV3. Through an extensive investigation conducted on a comprehensive dataset comprising 108,948 chest X-ray images, we scrutinize the performance metrics and diagnostic accuracy of each architecture. Notably, our findings reveal MobileNetV2 as the frontrunner, exhibiting an outstanding accuracy rate of 97% for Emphysema disease. This remarkable accuracy underscores the robustness and efficiency of MobileNetV2, even amidst large-scale diasets, positioning it as a promising solution for the automated detection of pulmonary ailments from medical imaging. Additionally, we analyze the computational efficiency and resource requirements of each architecture, providing insights into their practical applicability in real-world clinical settings. The implications of our study extend beyond technical benchmarks, offering valuable insights for healthcare practitioners, researchers, and developers working towards enhancing diagnostic processes in pulmonary healthcare. By elucidating the comparative strengths and limitations of various deep learning architectures, this research contributes to the advancement of computer-aided diagnosis systems, paving the way for more accurate and efficient detection of lung diseases from chest X-ray imaging data. © 2025 The Authors.

关键词： Lung cancer

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Procedural Low-Poly Buildings using L-System for Turn-based Tactic Game ***

Procedural Low-Poly Buildings using L-System for Turn-based ...

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2024 International of Seminar on Application for Technology of information and Communication, iSemantic 2024

作者： Benedict, Augusta Steven Rosyidah, Umi Harisa, Ardiawan Bagus Haryanto, Hanny Universitas Dian Nuswantoro Study Program in Information Engineering Faculty of Computer Science Semarang Indonesia

ISBN: (纸本)9798350366648

One of the critical visual components in video game creation is 3D asset prototypes, which also require significant effort. A procedural model using the L-system method for making low-poly buildings can address this issue. This model produces low-poly buildings based on simple parameters input by the user. The model receives input in the form of axioms, which are then processed according to predetermined L-system rules. After the building is formed, it is saved as a prefab in Unity so that it can be reused and modified by the user. The proposed method is implemented to our turn-based tactic *** and provided as a Unity package (add-on). Experimental results show that the buildings generated by the model have a minimalistic yet functional benefits. © 2024 IEEE.

关键词： Game design

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ESG Investing: A Statistically Valid Approach to Data-Driven Decision Making and the Impact of ESG Factors on Stock Returns and Risk

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IEEE Access 2024年 12卷 69434-69444页

作者： Teja, Kamurthi Ravi Liu, Chuan-Ming National Taipei University of Technology International Program of Electrical Engineering and Computer Science Taipei10608 Taiwan National Taipei University of Technology Department of Computer Science and Information Engineering Taipei10608 Taiwan

This study examines the impact of environmental, social, and governance (ESG) factors on economic investment from a statistical perspective, aiming to develop a tested investment strategy that capitalizes on the connection between ESG factors and financial performance. ESG investing: A statistically valid approach to data-driven decision-making (ESGI-SVADDM) investment strategy is based on a rigorous, statistically valid approach that utilizes data, math, statistics, and data science libraries to drive investment decisions, eliminating the need for personal opinions and subjectivity. The process includes establishing an investment thesis, formulating testable hypotheses (HPS), retrieving and refining relevant data, calculating relevant measures, and testing and validating all hypotheses. The study uses S&P 500 stock data and ESG data from Sustainalytics to test the hypotheses. The empirical tests conducted revealed a negative correlation between ESG risk and expected returns, as well as a positive trend in the relationship between ESG risk and the overall risk of stocks. Moreover, the study found that higher ESG risk scores are associated with lower returns for investors, and that adopting a strategy of investing in stocks with low ESG risk and shorting stocks with high ESG risk yields superior returns compared to the market portfolio. © 2013 IEEE.

关键词： Investments

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EESRGAN: Efficient & Effective Super-Resolution Generative Adversarial Network

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IETE Technical Review (Institution of Electronics and Telecommunication Engineers, India) 2024年第2期41卷 200-211页

作者： Tsai, An-Chao Tsou, Cheng-Han Wang, Jhing-Fa International Master Program of Information Technology and Application National Pingtung University Pingtung900 Taiwan Department of Electrical Engineering National Cheng Kung University Tainan Taiwan

In Taiwan, traditional production equipment for the mainframe panels is imported from overseas, and the parameters are adjusted through the operation panel for automated manufacturing. However, these parameters are slightly different from those used in Taiwan, requiring manual recording of warning parameters to ensure quality control. Currently, the only way to capture the operation records of these machines is by manually recording the system panel information, which is a time-consuming and laborious process that is expensive for production line personnel. In this work, we use image recognition to capture and analyze data externally without damaging the machine. This research improves the ESRGAN network to restore the image details and textures of the mainframe panels. It also captures relevant data with Google OCR to convert panel images into parameter values. The captured results are combined with data analysis to provide more accurate standard mainframe panel information. Even under different interference source conditions, data extraction and analysis can still be carried out to output the text files, effectively assisting the production line in recording the machine panel parameters and reducing personnel’s workload. © 2024 IETE.

关键词： Extraction

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Image-Multimodal Data Analysis for Defect Classification: Case Study of Industrial Printing 15th

Image-Multimodal Data Analysis for Defect Classification: Ca...

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15th International KES Conference on Intelligent Decision Technologies, KESIDT 2023

作者： Itou, Hiroki Watanabe, Kyo Arima, Sumika Degree Program in Systems and Information Engineering University of Tsukuba Tsukuba Japan Institute of Systems and Information Engineering University of Tsukuba Tsukuba Japan

ISBN: (纸本)9789819929689

The final goal of this study is an integrated approach of walk-through from the classification of defect products to the feature estimation for preventing the cause of the defects in real-time or proactively. Particularly, this paper introduced the multimodal data analyses to classify the defect images of final products more accurate with inspection logs and factory process data in integrated manner. Particularly, this paper focused on the industrial printing case in which the tiny and faint defects are difficult to be classified accurately. Motivation of this study is to clarify the possibility of image-wise classification instead of pixel-wise semantic segmentation of high annotation cost as well as low accuracy in partial of the similar shape classes in our previous study. It was introduced and numerically evaluated that various data augmentation as pre-process for imbalanced and small samples issue, image-multimodal data analyses with inspection log and/or the factory data, and ensemble of the multimodal and non-multimodal networks. As the result, the maximum accuracy of multimodal analyses is 79.37% of the model with test log and process data with 10 times augmented data. In addition, a confidence-based ensemble model with conditional branch results more accurate, 81.22% in summary of all classes. It is better than segmentation approach of pixel-wise in the previous study. Moreover, importance of additional variables is visualized as cause after multimodal analysis as aimed. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Classification (of information)

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Robot Tele-Operation / Teaching System using VR Device 10

Robot Tele-Operation / Teaching System using VR Device

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10th IEEE International Conference on Cybernetics and Intelligent Systems and IEEE Conference on Robotics, Automation and Mechatronics, CIS-RAM 2023

作者： Ohsato, Minami Aiyama, Yasumichi Master's Program in Systems and Information Engineering Tsukuba Japan University of Tsukuba Inst. of Systemsand Information Engineering Tsukuba Japan

ISBN: (纸本)9798350303087

This paper proposes a "robot tele-teaching system using a VR device"as a new robot teaching method to replace the conventional robot teaching method. Currently we still need teach-pendant to teach industrial robots. It is very inconvenient method. Our novel method consists of two robots and a VR device. One robot is on site instead of the operator. A stereo camera is attached to its end of the robot, which realizes a 3D positionand posture obtained from HMD. The operator can then view the images through the HMD as if he/she are on site. The other manipulating robot is equipped with a gripper and can follow the position and orientation of the gripper-like input device held by the operator. This system is equipped with a correction and auto-teaching function that uses the geometric characteristics of the work object. This significantly reduces the time required for operation. In addition, the teaching points obtained by this system have been successfully used for playback in a real environment. © 2023 IEEE.

关键词： Manipulators

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