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IEEE International Conference on Big Data

作者： Ayumu Hidaka Ryota shin Atsushi Tsuchiya Norihiko Nakabayashi Yukihiko Okada Yohei shida Master’s Program in Service Engineering University of Tsukuba Tsukuba Japan Doctoral Programs in Policy and Planning Sciences University of Tsukuba Tsukuba Japan Yamato Transport Co. Ltd. Minato Japan Yamato Transport Co. Ltd. University of Tsukuba Tsukuba Japan Institute of Systems and Information Engineering Center for Artificial Intelligence Research University of Tsukuba Tsukuba Japan Institute of Systems and Information Engineering University of Tsukuba Tsukuba Japan

Misdelivery in logistic services leads to increased costs and degradation of packages. For deliveries using trucks, erroneous deliveries are prevented by checking identification numbers on packages as the packages pass through delivery points. In recent years, it has become possible to monitor real-time location by attaching GPs receivers to packages, but few concrete efforts have been made to detect anomalies using truck transport data. This study introduces a basic framework for the detection of misdeliveries and a summary of the problems in actual truck misdelivery using special medical supply delivery data provided by a major Japanese logistics company. It is shown that the system can detect erroneous deliveries with high accuracy, even for actual delivery data with coarse resolution owing to the cost of installing the equipment. This study has the potential not only to improve logistics and reduce costs, but also to solve various social problems such as driver shortages.

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supply Chain sustainability in Disruption: sC Intelligence, Customer Knowledge Transfer, and the Mediating Role of Is/IT

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IEEE engineering Management Review 2025年

作者： Ratna, silvia saide, saide Rater, salya svyazhanovna, Baizakova saule Herzavina, Herzavina Faculty of Information Technology Department of Informatics Engineering and Department of Information Systems Banjarmasin Indonesia State Islamic University of Sultan Syarif Kasim Riau Universitas Islam Negeri Sultan Syarif Kasim Riau-UIN SUSKA Riau Department of Information Systems Faculty of Science and Technology Indonesia PRO Knowledge Indonesia Pekanbaru Indonesia Universitas Pahlawan Tuanku Tambusai Indonesia Lembaga Enreach UIN Suska Riau Indonesia Politeknik Aceh Selatan Department of Informatics Engineering Aceh Indonesia Information Communication Technologies Robotics in Arkalyk Pedagogical Institute Master of Natural Sciences Educational Program for the Informatics Computer Science Kazakhstan Universitas Pahlawan Tuanku Tambusai Department of Informatics Engineering Indonesia National Taiwan University of Science and Technology Taiwan

Knowledge resource and information system/technology (Is/IT) capability have been considered to improve firm performance, however there is still a gap regarding the sustainability of supply chain to face and recover from disruption (e.g., COVID-19). Questionnaire-based surveys was adopted and received feedback from sixty (160) Indonesian companies or about 28.07% of response rate. © 1973-2011 IEEE.

关键词： customer knowledge transfer disruption information system/technology (Is/IT) responding knowledge management resource-based view (RBV) supply chain (sC) sustainability supply chain knowledge transfer

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Preprocessing Techniques for Enhancing Vision-Based Detection system for Tire sidewall Extraction

Preprocessing Techniques for Enhancing Vision-Based Detectio...

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International seminar on Research of information Technology and Intelligent systems (IsRITI)

作者： Jia Hao Loo Veronica Lestari Jauw Chin seong Lim Khairul-Rijal sarmin Nunung Nurul Qomariyah Ahmad Nurul Fajar Department of Mechanical Materials and Manufacturing Engineering University of Nottingham Malaysia Malaysia Continental Tyre Technology Centre Malaysia Petaling Jaya Malaysia Computer Science Department School of Computing and Creative Arts Bina Nusantara University Jakarta Indonesia Information System Management Department BINUS Graduate Program-Master Information Systems Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331519643

ISBN: (纸本)9798331519650

This study aims to develop a system for extracting crucial information from tire sidewalls using Optical Character Recognition (OCR). Initially, images of tire were captured manually by smartphone cameras, including Redmi 9T, iPhone 11, and Galaxy s23 Ultra. The captured images are then transferred to a computer for storage. subsequently, these images were cropped according to the boundaries identified by Hough Circle Transform (HCT). The cropped images were then further pre-processed. During the pre-processing phase, geometrical transformation and image sharpening techniques are applied to enhance the clarity and readability of the text images. The text is then extracted using Google Vision, with the extracted text categorized by size, DOT, brand and pattern. The results indicated that the effectiveness of image pre-processing was constrained by the accuracy of circle detection, which reached a maximum rate of 87.1%. This causes parts of the text to be cut out inaccurately, leading to a suboptimal extraction accuracy of 55.65%. It is also observed that the Redmi 9T camera produced inconsistent results compared to other devices. specifically, the iPhone 11 and samsung Galaxy s23 Ultra demonstrated superior extraction accuracies of 69.71% and 66.37%, respectively, whereas the Redmi 9T achieved a lower extraction accuracy of 37.76%.

关键词： Accuracy Optical character recognition Text categorization Lighting Transforms Us Department of Transportation Cameras Tires Internet Data mining

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single sheet separation method from piled fabrics using roller hand mechanism

Single sheet separation method from piled fabrics using roll...

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IEEE International Conference on Intelligence and safety for Robotics (IsR)

作者： K. Manabe X. Tong Y. Aiyama Master's Program in Intelligent Interaction Technologies University of Tsukuba Tsukuba Japan Faculty of Engineering Information and Systems University of Tsukuba Tsukuba Japan

ISBN: (纸本)9781665438629;9781665411486

In order to automate the work in a garment factory, we developed a method of single sheet separation from piled fabrics by a roller hand mechanism with a rotating mechanism added to the tip of a robot hand. As a result, we succeeded in separating only single sheet of fabrics with a high probability. It is necessary to eliminate failures for practical use. However, it is difficult to eliminate failure completely due to the characteristics of fabrics. We also devised a method to judgement the success or failure of the separation to improve the reliability of the operation. As a result, the thickness of the fabric could be accurately measured and the confidence level was successfully improved.

关键词： Conferences Clothing Fabrics Production facilities safety Reliability separation processes

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Proposal of position error compensation method that enables immediate work when replacing industrial robots

Proposal of position error compensation method that enables ...

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IEEE International Conference on Intelligence and safety for Robotics (IsR)

作者： R. Yamaguchi Y. Aiyama Master's Program in Intelligent Interaction Technologies University of Tsukuba Tsukuba Japan Faculty of Engineering Information and Systems University of Tsukuba Tsukuba Japan

ISBN: (纸本)9781665438629;9781665411486

In this paper, we propose a method of compensating for absolute position and installation errors of a robot in the robot's workspace when an industrial robot stops working and needs to be replaced in a factory, for example. The proposed method uses multiple markers placed in the workspace and a camera to measure the robot, and estimates the position and orientation of the camera and the robot's link parameters in the workspace. In order to evaluate the proposed method, we compensate the position error of the robot by simulation. As a result, in the case where there is no measurement error of the camera, the hand position error at the work point is less than 0.5[mm]. In the case of the camera measurement error, the results varied depending on the way the measurement error occurred, and some errors were within 0.1 [mm] and some were close to 1 [mm].

关键词： Measurement errors service robots simulation Robot vision systems Measurement uncertainty Position measurement Cameras

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PPM-HC: A method for helping project portfolio management based on topic hierarchy learnings

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International Journal of Business Intelligence and Data Mining 2021年第3期18卷 364-382页

作者： Pinto, Ricardo A.M. Bernardini, Flavia Marcacini, Ricardo M. Graduate Program in Industrial Engineering and Computing Systems Fluminense Federal University Jardim Bela Vista Rio das OstrasRJ Brazil Computing Institute Fluminense Federal University São Domingos NiteróiRJ Brazil Information Systems Federal University of Mato Grosso do Sul P.O. Box 210 Três LagoasMS Brazil

The projects categorisation is a crucial step in the project portfolio management (PPM). Categorising projects allows the organisation to identify categories with a lack or excess of projects, according to its strategic objectives. In this work, we present a new method for project portfolio management based on hierarchical clustering (PPM-HC) to organise the projects at several levels of abstraction. In the PPM-HC, similar projects are allocated to the same clusters and subclusters. PPM-HC automatically learns an understandable topic hierarchy from the project portfolio dataset, thereby facilitating the (human) task of exploring, analysing and prioritising the projects of the organisation. We also proposed a card sorting-based technique which allows the evaluation of the projects categorisation using an intuitive visual map. We carried out an experimental evaluation based on a benchmark dataset and we also presented a real-world case study. The results show that the proposed PPM-HC method is promising. © 2021 Inderscience Enterprises Ltd.

关键词： Investments

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A Comparative study of Implementing Intelligent Internet of Things for Creating Better surveillance and security in Developing Nations 2

A Comparative Study of Implementing Intelligent Internet of ...

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2nd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2022

作者： Ganai, Prince Tehseen Nirmal, Ekanath sitaram Kaushik, Manish Buddhi, Dharam Alam, Tanweer Rafi, shaik Mohammad Shri Jagdishprasad Jhabarmal Tibrewala University Department of Information Technology Rajasthan India Arts Commerce and Science College Savitribai Phule Pune University Department of Political Science Pune India S. S. Jain Subodh P. G. College Master of Computer Applications Jaipur India Uttaranchal University Uit Uttarakhand Dehradun India Islamic University of Madinah Faculty of Computer and Information Systems Madinah Saudi Arabia Sri Mittapalli College of Engineering Department of Computer Science and Engineering Andhrapradesh Guntur India

ISBN: (纸本)9781665437899

In current history, rapid digitization has opened up new technical possibilities, which have already begun to alter the major safety and security sectors and society in general. The digital revolution opened up new opportunities for progress and more effective use of scarce resources, technologies, and operations in several sectors of the safety measurements. The Internet of Things (IoT) reflects the growth of mobile phones, houses, and integrated technologies. Because the items surrounding will have a greater understanding of our interests, ambitions, and requirements, such a development will aid in the creation of a smart environment for humans. since IoT technologies grow more common, security challenges in IoT have gotten a lot of attention from academic and industrial. IoT systems, in comparison to traditional computing environments, have greater inherent problems and, as a result, may have increased security procedures. The existing IoT design, on the other hand, does not adequately handle the heightened security statutory responsibilities by those weaknesses. Mixed methods are used for this paper to collect statistical as well as theory-based information from different sources. Primary quantitative and secondary qualitative methods are used to collect various information. © 2022 IEEE.

关键词： Internet of things

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Physarum Route Optimization: Bio-inspired strategies for Mobile Robot Navigation

Physarum Route Optimization: Bio-inspired Strategies for Mob...

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IEEE Latin American Robotics symposium, LARs

作者： Dieisson Martinelli André schneider de Oliveira Vivian Cremer Kalempa Graduate Program in Electrical and Computer Engineering Universidade Tecnológica Federal do Paraná (UTFPR) Curitiba Brazil Department of Information Systems Universidade do Estado de Santa Catarina (UDESC) São Bento do Sul Brazil

ISBN: (数字)9798331508807

ISBN: (纸本)9798331508814

The objective of this project is to explore the applicability of a bioinspired approach, derived from the behavior of the Physarum polycephalum fungus, in optimizing trajectory navigation for mobile robot structures. The precise organism Physarum, which has the capability to quick locate efficient paths among factors in complicated environments, serves as a herbal version for constructing inspired trajectory algorithms. In this project, the development of a trajectory set of rules is proposed, that’s as compared to conventional trajectory introduction techniques, aiming to introduce a novel approach to cellular robot navigation. This work is presented thru a aggregate of experimental observations and computational simulations that show the effectiveness of this bioinspired approach in trajectory choice. As a end result, an set of rules is developed that mimics the behavior of the Physarum and, similarly to conventional navigation algorithms, paves the manner for research and improvement.

关键词： shortest path problem Navigation Heuristic algorithms Memory management MIMICs Dynamic scheduling Organisms Trajectory Mobile robots Resource management

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A Human-Flow Analysis Based on PCA:A Case study on Population Data Near Railway

A Human-Flow Analysis Based on PCA:A Case Study on Populatio...

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Robotics, Automation and Artificial Intelligence (RAAI), IEEE International Conference on

作者： seongIn Kim Takeshi shibuya shingo Toride Yasunori Endo Master’s Programs in Intelligent and Mechanical Interaction Systems University of Tsukuba Tsukuba Japan Faculty of Engineering Information and Systems University of Tsukuba Tsukuba Japan Disaster Information Research Division National Research Institute for Earth Science and Disaster Prevention Tsukuba Japan

The damage caused by natural disasters and accidents is increasing every year. To reduce such damage from spreading, it is important to detect an accident promptly. However, current sensing systems are difficult to use because they have narrow coverage and are specialized in few detectable accidents. In this paper, we propose a method to detect disasters and accidents by calculating the degree of an anomaly in human flow by treating a common human flow as a single large sensor. Human flow can be assumed to have typical patterns in people’s daily life, such as going to work and leaving work. Developing an anomaly detection method of human flow can lead to the discovery of any hidden causes such as accidents and disasters. In this paper, we study a method that aims to detect anomalies in human flow, considering the operational status of railways as an example. We confirm that our method can detect the actual suspension of operations.

关键词： Automation sociology Robot sensing systems Rail transportation sensors statistics Artificial intelligence

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Utilizing Graph Neural Networks for Breast Cancer Prognosis Prediction with High-dimensional Genomic Data

Utilizing Graph Neural Networks for Breast Cancer Prognosis ...

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Annual International Conference of the IEEE engineering in Medicine and Biology society (EMBC)

作者： Tzu-Chen Huang Te-Cheng Hsu Yi-Hsien Hsieh Che-Lin Graduate Institute of Communication Engineering National Taiwan University (NTU) Taipei Taiwan Institute of Communications Engineering National Tsing-Hua University Hsinchu Taiwan Department of Electrical Engineering NTU Taipei Taiwan Master’s Program in Smart Medicine and Health Informatics NTU Taipei Taiwan Center for Computational and Systems Biology NTU Taipei Taiwan

An accurate prediction of breast cancer is essential to help physicians make appropriate treatment recommendations to reduce the chance of excessive treatment, avoiding unnecessary anxiety for patients. Cancer prognosis is highly related to patients’ genomic features, which are high-dimensional in nature. In this study, we utilize a systems biology feature selector for dimension reduction to select 20 prognostic biomarkers that are considered closely related to breast cancer prognosis from the high dimensional RNA sequencing (RNA-seq) data. Furthermore, we establish a graph neural network (GNN) and a multi-layer perception (MLP) graph-level readout method to better extract the underlying gene interactions from the corresponding gene interaction network (GIN). With the help of GINs, the model performs the best among all baseline models, especially in the area under the precision-recall curve (AUPRC) by as large as 23%. The results demonstrate that our approach using GNNs can successfully extract high-dimensional and complicated interactions within genomic data.

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