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Technology and Policy in Energy and Electric Power (ICT-PEP), International Conference on

作者： Muhammad Afnan Habibi Mochamad Farhan Ali Irfani Langlang Gumilar Arya Kusumawardana Aripriharta Angger Baskoro Study Program of Power Plant Engineering Technology Universitas Negeri Malang Malang Indonesia Department of Electrical Engineering and Informatics Universitas Negeri Malang Malang Indonesia Dept. Electrical Engineering and Computer Sciences National Yang Ming Chiao Tung University Hsinchu Taiwan

This paper conducts a comprehensive analysis of electrical generator performance using Finite Element Analysis (FEA), with a specific emphasis on the role of coil numbers in influencing generator efficiency and functionality. In the context of modern energy systems, where efficient power generation is paramount, this research aims to elucidate the relationship between the number of coils within a generator and its overall performance, including power output and electromagnetic behavior. Through systematic FEA simulations that vary coil numbers while keeping other parameters constant, this study provides valuable insights into the trade-offs associated with increased coil numbers and enhanced efficiency. These findings have significant implications for optimizing generator designs across various applications, from renewable energy systems to industrial power generation, ultimately advancing our understanding of generator dynamics and contributing to more sustainable and efficient power generation technologies.

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Forecasting system using single exponential smoothing with golden section optimization 2

Forecasting system using single exponential smoothing with g...

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2nd International Conference on Vocational Education and Technology, IConVET 2019

作者： Widitriani, N.P.S. Parwita, W.G.S. Meinarni, N.P.S. Study Program of Informatics Engineering STMIK STIKOM Indonesia Denpasar-Bali80225 Indonesia

Puri Wira Mahkota Ltd is a distributor company in the automotive parts industry. Puri Wira Mahkota has an obstacles in preparing weekly order on stock to the primary production unit. They predict total sales of product in the coming period just by using an expectation from stock administration staff then it will be compared with sales data in the previous period without any calculations using a definitive formula. Forecasting calculation could support Puri Wira Mahkota to predict the quantity of product. The purpose of this research is to apply the calculation process that can predict the quantity of product should be produced by the primary production unit every month and also to prevent over stock and out of stock. The method used in the forecasting calculation is Single Exponential Smoothing. To optimize Single Exponential Smoothing we used the Golden Section. The principle of the Golden Section is to reduce the alpha area boundary so it will produce an ideal forecast value with the minimum MAPE (Mean Absolute Percentage Error) level. This research shows the results that the Golden Section finds the optimal forecasting value with a level of MAPE (Mean Absolute Percentage Error) of 43.39%. © 2020 IOP Publishing Ltd. All rights reserved.

关键词： Sales

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Cognitive Ethical Design and Evaluation of Productive Reinforcing Spiral Model to Mitigate the Challenge of Extreme Polarization

Cognitive Ethical Design and Evaluation of Productive Reinfo...

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International Conference on Computer Supported Cooperative Work in Design

作者： Ana Paula Camargo Pimentel Claudia Motta António Correia Jano Moreira De Souza Daniel Schneider Postgraduate Program in Informatics (PPGI) UFRJ Rio de Janeiro Brazil Tércio Pacitti Institute of Computer Applications and Research (NCE) UFRJ Rio de Janeiro Brazil Faculty of Information Technology University of Jyväskylä Jyväskylä Finland Systems Engineering and Computer Science Program/COPPE Federal University of Rio de Janeiro Brazil

ISBN: (数字)9798331513054

ISBN: (纸本)9798331513061

The polarization of ideas is a natural phenomenon of human behavior. When productive, it can generate scenarios for reflection on arguments, opinions, and interactions, but when polarization is extreme, it generates social isolation, manipulation, perception of injustice, unproductive debates, certainties of absolute truths, fanaticism, feelings of hatred, and even wars. Deconstructing the ecosystem of extreme polarization directly benefits social stability. Virtual social environments are excellent scenarios for fostering debates, negotiations, and the exposition of ideas. The objective of this study is to use the same virtual social ecosystem with its empowerment mechanisms and influence attributes to support the creation of tools, functionalities, and simulations to develop healthier systems. The knowledge generated supported the development of a design and cognitive ethical affordances practiced in metacognitive design, optimized navigation, and metacognitive simulations. The cognitive, ethical affordances incorporated into the Productive Reinforcement Spiral method model were part of a metacognitive simulation of collaborative negotiation with a productive reinforcement spiral mechanism, whose description and evaluation of the design are the main objectives of this paper.

关键词： Productivity Ethics Pathology Spirals Affordances Ecosystems Collaboration Stability analysis Reflection Public healthcare

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On the Dominant Local Metric Dimension of Corona Product Graphs

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IAENG International Journal of Applied Mathematics 2022年第4期52卷

作者： Umilasari, Reni Susilowati, Liliek Slamin Prabhu, Savari Mathematics Department Airlangga University Indonesia Study Program of Informatics Jember University Indonesia Mathematics Department Rajalakshmi Engineering College Tamil Nadu Chennai602105 India

A nontrivial connected graph T which one of the vertex is v, v is said to distinguish two vertex u;t if the distance between v and u is different from v to t, where u,t (Formula Presented) V (T). Metric dimension is one topic in graph theory that uses the concept of distance. Combining the definition of the local metric dimension and dominating set, there is a new term, we called it dominant local metric dimension and symbolized as Ddiml(T). An ordered subset Wl = {w1,w2,…,wn}(Formula Presented)V (T) is called a dominant local resolving set of T if Wl is a local resolving set as well as a dominating set of T. The goal of this paper’s research is to determine precise values of dominant local metric dimension for the corona product graphs. n copies of the graphs P1,P2,…,Pn of P are made to constructed the corona of any two graph T and P. After that, we link the i-th vertex of T to the vertices of Pi, where n is an order of graph T. T corona P is symbolized by T(Formula Presented)P. © 2022,IAENG International Journal of Applied Mathematics. All Rights Reserved.

关键词： Graph theory

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Design of IOT based facial recognition door access control locker services at tourist attractions in Bali 2

Design of IOT based facial recognition door access control l...

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2nd International Conference on Vocational Education and Technology, IConVET 2019

作者： Widiartha, K.K. Ekayana, A.A.G. Study Program of Informatics Engineering STMIK STIKOM Indonesia Denpasar-Bali80225 Indonesia

Safety and comfort are things that everyone wants to get on a trip. Every tourist who wants a vacation to one of the tourist destinations will prioritize these two things. Leisure in travel is influenced by the availability of supporting facilities. From accommodation, restaurants to facilities provided by tourism actors in each tourism object. One problem is the lack of facilities in attractions such as luggage storage (lockers), many tourists in enjoying tourism objects carrying luggage such as backpacks;groceries to backpacks for tourists are classified as backpackers. Of course this will disrupt the comfort of traveling. In the research conducted, researchers wanted to design a system of goods storage services as a form of supporting industry 4.0 in the tourism environment. By designing an image of the storage media of goods by implementing access control for doors in each locker based on image processing supported by a microcontroller. The method used that focuses on facial recognition as image input using the PCA (Principal Component Analysis) method, which can measure the Euclidean distance in an object's face image. The design as a blueprint makes it easier to develop the next item of storage media (lockers).The results of this study indicate that the facial recognition method used is able to extract facial features and be recalibrated to activate the locker that is owned by the face object. © 2020 IOP Publishing Ltd. All rights reserved.

关键词： Principal component analysis

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Backcasting Perspectives on Services of Future Quantum Internet

Backcasting Perspectives on Services of Future Quantum Inter...

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Quantum Software (QSW), IEEE International Conference on

作者： Shota Nagayama Toshihiko Sasaki Akihito Soeda Mercari R4D Mercari Inc Tokyo Japan Graduate School of Media and Governance Keio University Fujisawa Japan Department of Applied Physics Graduate School of Engineering The University of Tokyo Tokyo Japan Principles of Informatics Research Division National Institute of Informatics Tokyo Japan Informatics Program SOKENDAI (The Graduate University for Advanced Studies) Tokyo Japan Department of Physics Graduate School of Science The University of Tokyo Tokyo Japan

ISBN: (数字)9798350368475

ISBN: (纸本)9798350368482

A quantum internet is an emerging quantum information technology, possibly becoming a pinnacle of wide-area distributed system allowed under the laws of physics. The current expansion of quantum technologies would lead to innumerable types of quantum systems, composed of various kinds of quantum devices connected by a dedicated quantum network. However, the (inter)connectivity offered by a quantum internet should ideally be agnostic of the technologies used by each component system. Furthermore, concurrent progresses of the quantum technologies complicate the task of defining what a quantum internet is. In this paper, we adopt a backcasting approach to elucidate what a quantum internet should be. We begin by discussing what we believe to be the requirements of an ultimate distributed quantum system, from which we explain what role a quantum internet would play in achieving this ultimate system. We then lead to more practical requirements on a quantum internet, considering the known and expected constraints in designing a quantum internet. We also organize and categorize the relationship among known quantum network technologies and services relevant to a quantum internet. We hope this document to lay a common ground for all the key stakeholders of a quantum internet, including researchers, industrial enterprises, and policy makers and regulators.

关键词： Quantum system Protocols Quantum mechanics Transportation Logic gates Internet Quantum networks

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Future Glycemic Events Prediction Model Based On Artificial Neural Network

Future Glycemic Events Prediction Model Based On Artificial ...

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2022 International Conference on Innovation and Intelligence for informatics, Computing, and Technologies, 3ICT 2022

作者： Syafrudin, Muhammad Alfian, Ganjar Fitriyani, Norma Latif Hadibarata, Tony Rhee, Jongtae Anshari, Muhammad Sejong University Department of Artificial Intelligence Seoul Korea Republic of Universitas Gadjah Mada Department of Electrical Engineering and Informatics Vocational College Yogyakarta Indonesia Sejong University Department of Data Science Seoul Korea Republic of Curtin University Environmental Engineering Program Miri Malaysia Dongguk University Department of Industrial and Systems Engineering Seoul Korea Republic of Universiti Brunei Darussalam School of Business and Economics Brunei

ISBN: (数字)9781665451932

ISBN: (纸本)9781665451932

Predicting future glycemic events such as hypoglycemia, hyperglycemia, and normal for type 1 diabetes (T1D) remains a significant and challenging issue. In this study, an artificial neural network (ANN)-based model is proposed to predict the future glycemic events of T1D patients. We utilized five T1D patient datasets to build the models and predict future glycemic events with a prediction horizon (PH) of 30 and 60 minutes ahead of time. We applied the data preprocessing method based on the sliding window approach by sliding the blood glucose time-series data from the past 60 minutes (the last 12 data points) as input and using the next 30 and 60 minutes (the next 6 and 12-th data points) as output. All the numeric blood glucose output data are then transformed into a multi-class classification label, such as hypoglycemia, hyperglycemia, and normal. Our proposed model is then used to learn and create the prediction model from the preprocessed blood glucose dataset. Four performance metrics such as accuracy, precision, recall, and f-1 score were utilized to measure the performance of the classification models used in this study, such as Naïve Bayes (NB), Decision Tree (DT), Support Vector Machine (SVM), and K-Nearest Neighbour (KNN). The results showed that our proposed ANN-based model performed better at predicting future glycemic events than other models, with an average accuracy, precision, recall, and f-1 score of 88.649%, 76.661%, 71.731%, 72.609%, and 83.364%, 60.437%, 61.345%, 60.62% for the PH of 30 and 60 minutes, respectively. As a result, knowing this future glycemic event sooner can help patients avoid potentially dangerous conditions and can eventually be used to improve diabetes management. © 2022 IEEE.

关键词： Decision trees

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Single-cell transcriptomics uncovers EGFR signaling-mediated gastric progenitor cell differentiation in stomach homeostasis (vol 14, 3750, 2023)

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NATURE COMMUNICATIONS 2023年第1期14卷 1-16页

作者： Takada, Hitomi Sasagawa, Yohei Yoshimura, Mika Tanaka, Kaori Iwayama, Yoshimi Hayashi, Tetsutaro Isomura-Matoba, Ayako Nikaido, Itoshi Kurisaki, Akira Laboratory of Stem Cell Technologies Graduate School of Science and Technology Nara Institute of Science and Technology Takayama-cho Ikoma Nara Japan Laboratory for Bioinformatics Research RIKEN Center for Biosystems Dynamics Research Wako Saitama Japan Department of Functional Genome Informatics Biological Data Science Medical Research Institute Tokyo Medical and Dental University Bunkyo Tokyo Japan Master’s/Doctoral Program in Life Science Innovation (Bioinformatics) Degree Programs in Systems and Information Engineering Graduate School of Science and Technology University of Tsukuba Tsukuba Ibaraki Japan

Defects in gastric progenitor cell differentiation are associated with various gastric disorders, including atrophic gastritis, intestinal metaplasia, and gastric cancer. However, the mechanisms underlying the multilineage differentiation of gastric progenitor cells during healthy homeostasis remain poorly understood. Here, using a single-cell RNA sequencing method, Quartz-Seq2, we analyzed the gene expression dynamics of progenitor cell differentiation toward pit cell, neck cell, and parietal cell lineages in healthy adult mouse corpus tissues. Enrichment analysis of pseudotime-dependent genes and a gastric organoid assay revealed that EGFR-ERK signaling promotes pit cell differentiation, whereas NF-κB signaling maintains gastric progenitor cells in an undifferentiated state. In addition, pharmacological inhibition of EGFR in vivo resulted in a decreased number of pit cells. Although activation of EGFR signaling in gastric progenitor cells has been suggested as one of the major inducers of gastric cancers, our findings unexpectedly identified that EGFR signaling exerts a differentiation-promoting function, not a mitogenic function, in normal gastric homeostasis.

关键词： Adult stem cells Stem-cell differentiation Stem-cell niche

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A Development of Object Detection System based on Deep Learning Approach to Support the Laparoscope Manipulating Robot (LMR)

A Development of Object Detection System based on Deep Learn...

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2022 International Electrical engineering Congress, iEECON 2022

作者： Sonsilphong, Suphachoke Sonsilphong, Amornthep Hormdee, Daranee Khampitak, Kovit Khon Kaen University Data Science Health Informatics Program Academic Affairs Faculty of Medicine Khon Kaen Thailand Rajamangala University of Technology Isan Department of Electrical Engineering Khon Kean Thailand Khon Kaen University Embedded System RD Group Department of Computer Engineering Faculty of Engineering Khon Kean Thailand Khon Kean University Faculty of Medicine Department of Obstetrics and Gynecology Khon Kean Thailand

ISBN: (纸本)9781665402064

This paper presents the development of an object detection system based on the deep learning approach of computer vision to support the laparoscopic surgical robotic position control system. The system comprises two main phases, the training phase, and the real-time operating phase. In the training phase, a modified YOLOv4 algorithm is proposed to be adopted within the Darknet framework for training the weights of detection models. The best detection model is then selected to be assigned to the object detector in the real-time operating phase. The validation result of the detection model across the experiment datasets is 90% accuracy on average during the training phase. To validate the viability of real-time object detection, the proposed system was implemented in two test-cases of gynecologic surgery with the soft-body cadavers. © 2022 IEEE.

关键词： Laparoscopy

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Surgical Instrument Detection for Laparoscopic Surgery using Deep Learning 19

Surgical Instrument Detection for Laparoscopic Surgery using...

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19th International Conference on Electrical engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2022

作者： Boonkong, Apiwat Hormdee, Daranee Sonsilphong, Suphachoke Khampitak, Kovit Khon Kaen University Embedded System RandD Group Computer Engineering Khon Kaen Thailand Khon Kaen University Data Science and Health Informatics Program Academic Affairs Khon Kaen Thailand Khon Kaen University Faculty of Medicine Department of Obstetrics and Gynecology Khon Kaen Thailand

ISBN: (纸本)9781665485845

Laparoscopic surgery has transformed conventional open surgery. Robot-Assisted laparoscopic surgery which is minimally invasive is effective for operations in limited space. Nevertheless, the robotic system which is utilized in such surgery can inflict impair to the surgical instruments, organs, or tissues as a consequence of the narrow field of view and space available to operate, and insufficient tactile response. In laparoscopy, the surgeon observes what he operates via digital images which are displayed on a monitor. In addition to the surgeon's expertise, the image-guided surgery system could offer him significant support if that system is capable of understanding those images. Computer Vision has been able to proceed due to the emergence of Machine Learning, and especially Deep Learning. This paper applies Deep Learning for surgical instrument detection for laparoscopic surgery. The fastest model, based on results trained on the COCO 2017 Dataset on TensorFlow Framework, for each of 4 algorithms-Faster-RCNN, SSD, CenterNet and EfficientDet-from Model Zoo, along with YOLOv4 on Darknet Framework, have been investigated in this work. The evaluation metrics used are Precision, Recall and F1-score. The results reveal that each model plays its part well;however, YOLOv4 seemed to breakthrough this statement by offering grate result for all three accuracy metrics. © 2022 IEEE.

关键词： Laparoscopy

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