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4th IEEE Global Conference on Life Sciences and Technologies, LifeTech 2022

作者： Honma, Hiroki Iida, Yoshiaki Okumura, Yasuyuki Fujii, Katsuyuki Umehira, Masahiro Nanzan University Graduate Program of Mechatronics Graduate School of Science and Engineering Nagoya Japan Nanzan University Physical Education Center Nagoya Japan Nanzan University Faculty of Science and Engineering Department of Mechatronics Nagoya Japan Nanzan University Faculty of Science and Engineering Department of Electronics and Communication Technology Nagoya Japan

ISBN: (纸本)9781665419048

In a basketball game, players must act appropriately according to the position and movement of the player. This needs to be learned through team practice. Therefore, if we can build an environment that allows even one person to practice as a team, the efficiency of practice can be greatly improved. It is effective to use virtual reality (VR) technology to realize team practice alone. This paper proposes a VR-based basketball team practice learning system that provides VR environments similar to the actual team practice environments by arranging players in a virtual space. Focusing on zone defense practice, which is said to be difficult to learn even in team practice, we propose a practice system for orthodox 3-2 zone tactics. In addition, because the distance between the player and the surrounding VR player is important for this system, this paper presents the evaluation result of the 3D virtualization accuracy measured by the experiment. © 2022 IEEE.

关键词： Virtual reality

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Measurement of peripheral nerve magnetostimulation thresholds of a head solenoid coil between 200 Hz and 88.1 kHz

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IEEE Journal of Translational engineering in Health and Medicine 2025年 13卷 275-285页

作者： Barksdale, Alex C. Ferris, Natalie G. Mattingly, Eli Sliwiak, Monika Guerin, Bastien Wald, Lawrence L. Davids, Mathias Klein, Valerie MIT Department of Electrical Engineering and Computer Science CambridgeMA United States Martinos Center for Biomedical Imaging CharlestownMA United States Harvard University Harvard Graduate Program in Biophysics CambridgeMA United States Harvard-MIT Division of Health Sciences and Technology BostonMA United States Harvard Medical School BostonMA United States

Objective: Magnetic fields switching at kilohertz frequencies induce electric fields in the body, which can cause peripheral nerve stimulation (PNS). Although magnetostimulation has been extensively studied below 10 kHz, the behavior of PNS at higher frequencies remains poorly understood. This study aims to investigate PNS thresholds at frequencies up to 88.1 kHz and to explore deviations from the widely accepted hyperbolic strength-duration curve (SDC). Methods and procedures: PNS thresholds were measured in the head of 8 human volunteers using a solenoidal coil at 16 distinct frequencies, ranging from 200 Hz to 88.1 kHz. A hyperbolic SDC was used as a reference to compare the frequency-dependent behavior of PNS thresholds. Results: Contrary to the predictions of the hyperbolic SDC, PNS thresholds did not decrease monotonically with frequency. Instead, thresholds reached a minimum near 25 kHz, after which they increased by an average of 39% from 25 kHz to 88.1 kHz across subjects. This pattern indicates a significant deviation from previously observed behavior at lower frequencies. Conclusion: Our results suggest that PNS thresholds exhibit a non-monotonic frequency dependence at higher frequencies, diverging from the traditional hyperbolic SDC. These findings offer critical data for refining neurodynamic models and provide insights for setting PNS safety limits in applications like MRI gradient coils and magnetic particle imaging (MPI). Further investigation is needed to understand the biological mechanisms driving these deviations beyond 25 kHz. Clinical impact: These findings call for further basic research into biological mechanisms underlying high frequency PNS threshold trends, and supports refinement of safety guidelines for MRI and MPI systems for clinical implementation. © 2013 IEEE.

关键词： Neuroimaging

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Random Number Generator for Securing Data Exchange in Smart Factory: Recent Trends and Best Practices

Random Number Generator for Securing Data Exchange in Smart ...

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Computer Technologies (ICCTech), International Conference on

作者： Andi Sama Meyliana Yaya Heryadi Taufik Roni Sahroni Computer Science Department Binus Graduate Program - Computer Science Bina Nusantara University Jakarta Indonesia Information System Department School of Information System Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program-Doctor of Computer Science Jakarta Jakarta Indonesia Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350395419

ISBN: (纸本)9798350395426

IT/OT convergence in the form of a Cyber-Physical System (CPS) presents an opportunity to apply recent Information Technology (IT) advancements to Operational Technology (OT). The IT/OT convergence introduces cyber security threats for OT. The OT communication protocols, for example, have limited or no security capabilities for securing data exchange beyond basic authentication. The RNG (Random Number Generator) function is crucial in PLC for producing the encryption keys or the initial seed for security algorithms. The software-based PRNG (Pseudo RNG) is the most common approach for RNG in OT, instead of hardware-based RNG. This study provides a systematic literature review of the most recent evidence in digital transformation to secure data exchange in smart factories, within OT, or across OT and IT settings. It does this by looking at the PRNG on PLC and identifying the most recent trends and best practices. The findings include up-to-date data on author countries' distribution, published journals, research trends, industries, and industry types. The findings also address whether data flow is encrypted or shared in plaintext to ensure secure data transfer between IT and legacy OT environments. This paper concludes that while there is known RNG implementation in the actual embedded system in ICS, there is no evidence in the literature for using RNG in ICS networks for PLC implementation to secure data transfer with encryption.

关键词： Industries Systematics Market research Data transfer Control systems Generators Encryption

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Auxiliary Droop Frequency and Voltage Control for Grid-Forming Applied to Unbalanced Current Compensation

Auxiliary Droop Frequency and Voltage Control for Grid-Formi...

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IEEE International Symposium on Power Electronics for Distributed Generation Systems (PEDG)

作者： A. Marin-Hurtado A. Escobar-Mejía W. Gil-González Electrical Engineering Graduate and Undergraduate Program Universidad Tecnológica de Pereira Pereira Colombia

The virtual synchronous machine (VSM) has been a potential solution to control the grid-forming converters to integrate renewable energies (RES) into the grid. It is responsible for emulating the kinetic energy and static/dynamic properties of conventional synchronous generators to solve the stability problems due to decrease inertia in the systems with high levels of RES. This has been increasing in the distribution grids where is common the single-phase loads and the current unbalance, which causes stability problems as the intensified frequency oscillations and the frequency deviation in the system. The VSM control is common in converters present in the balance system. However, the VSM control implementation in converters present in the unbalanced system is not a straightforward task due as the unbalances intensify the power oscillations to cause the VSM to have abnormal behavior. Nevertheless, the frequency and voltage droops controls are commonly used in the converters present in the unbalanced system, but they are used as grid-following converters. Therefore, this paper proposes an auxiliary droop frequency and voltage control (AFV) scheme to integrate into a virtual synchronous machine (VSM-AFV) in order to improve a four-wire power system’s stability during an unbalanced system. This approach is based on droop frequency and voltage control, and its law control is obtained from a system’s active power and reactive power flow exchange equation. Changes in the active power of the VSM based on unbalances presented in the distribution grid are considered to show the performance of the VSM-AFV. Results show that the VSM-AFV controller presents lower ROCOF, steady-state errors in output reactive power, and output current of a four-leg three-phase voltage source converter (4-LVSC) when compared to the VSM approach.

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Multi-Objective Grouped Grey Wolf Optimization of PID Controllers Applied to a Water Treatment Plant Model

Multi-Objective Grouped Grey Wolf Optimization of PID Contro...

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Congress on Evolutionary Computation

作者： Yan Lieven Souza Lúcio Viviana Cocco Mariani Leandro Dos Santos Coelho Electrical Engineering Graduate Program (PPGEE) Federal University of Parana (UFPR) Curitiba Parana Brazil Department of Electrical Engineering Mechanical Engineering Graduate Program (PPGEM) Pontifical Catholic University of Parana (PUCPR) and Federal University of Parana (UFPR) Curitiba Parana Brazil Department of Electrical Engineering Industrial and Systems Engineering Graduate Program (PPGEPS) Pontifical Catholic University of Parana (PUCPR) and Federal University of Parana (UFPR) Curitiba Parana Brazil

A comparison of proportional-integral-derivative (PID) controller tuning for a 2x2 Multiple-Input Multiple-Output (MIMO) water treatment plant model is presented. The PID tuning procedures are based on Multi-Objective Grey Wolf Optimizer (MOGWO) and Multi-Objective Grouped Grey Wolf Optimizer (MOGGWO) are performed under two different initial conditions. The tuning procedure is structured as a multi-objective optimization problem with four objective functions, the integral time-squared error is minimized in each output response, and the integral of the control actions is minimized in each input. MOGWO is a metaheuristic based on the hunting behavior of grey wolves, following the hierarchy and leadership procedures that these animals have, while the proposed MOGGWO is a new version proposed in this study with two different groups with different functionalities. The performance was analyzed by 50 runs based on statistical metrics. MOGGWO can find more local minima since its Pareto front is more dispersed than that found by MOGWO.

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Threshold-Based Electroencephalography Brain-Computer Interface for Robot Arm Control

Threshold-Based Electroencephalography Brain-Computer Interf...

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Asia-Pacific Conference on Intelligent Robot Systems (ACIRS)

作者： Muhammad Ilhamdi Rusydi Elita Amrina Yoan Winata Salisa 'Asyarina Ramadhani Riko Nofendra Electrical Engineering Department Engineering Faculty Program of Engineer Professional Education Graduate School Universitas Andalas Padang Indonesia Industrial Engineering Department Engineering Faculty Program of Engineer Professional Education Graduate School Universitas Andalas Padang Indonesia Electrical Engineering Department Engineering Faculty Universitas Andalas Padang Indonesia

Brain-Computer Interface (BCI) is a technique that uses real-time brain impulses to connect with and control external devices. BCI provides a new method for controlling external devices by translating brain signals into computer commands, facilitating the daily lives of people with disabilities and enhancing their ability to exhibit expected behavior. A Brain-Computer Interface (BCI) system based on Electroencephalography (EEG) was built to control the robotic arm. The EEG signals utilized included both eyes blinking, the right eye, the left eye, and the jaw contraction. EEG data were recorded from seven healthy subjects. The threshold approach is used to classify EEG signals, with the feature employed being the amplitude of the EEG signal. The highest threshold value for the blinking signal was 0.6 mV with an accuracy of 97.9%, while the best threshold value for jaw contraction was 0.4 mV with an accuracy of 93.34 percent. The healthy, inexperienced participants took part in system testing. The total results of testing each robot movement yielded an overall success rate of 84.52 percent. Therefore, it was determined that the system could facilitate the operation of the length robot even if the user lacked prior experience with EEG-based systems.

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Design and Strategy Deployment of SD-WAN Technology: In Indonesia (Case Study: PT. XYZ)

Design and Strategy Deployment of SD-WAN Technology: In Indo...

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2021 International Conference on Green Energy, Computing and Sustainable Technology, GECOST 2021

作者： Pratiwi, Wiwi Gunawan, Dadang Universitas Indonesia Graduate Program of Telecommunication Management Department of Electrical Engineering Jakarta Indonesia

ISBN: (纸本)9781665438650

For large companies with branch offices spread across various regions, it is not enough to rely on traditional wide area network (WAN) technology to connect networks between data centers, head offices, and branch offices that are far apart. This is because traditional WAN operation requires many devices with their own complexities. SDN is a method that separates the Control Plane and the Forwarding Plane. In a traditional network, the two functions above are in the same device. One of the SDN technologies on the network is SD-WAN. Another problem in traditional network is WAN infrastructure primarily uses MPLS, which can be very expensive and has limited bandwidth. With the increasing volume of data, MPLS costs can be quite high the expensive cost. PT. XYZ as a banking company that has branches scattered everywhere must pay attention to this. This paper proposes the suitable design and implementation scenario of SD-WAN technology at PT. XYZ so that the existing network can be integrated. From the proposed design, it can be shown that SD-WAN technology is able to answer the weaknesses of traditional WANs in terms of ease of monitoring, cost efficiency, and flexibility © 2021 IEEE.

关键词： Wide area networks

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DEEP-LEARNING-BASED MAGNETIC RESONANCE SIMULTANEOUS MULTISLICE IMAGING USING HOLOGRAPHIC IMAGE DECODING

arXiv

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arXiv 2024年

作者： Ito, Satoshi Sato, Yuki Endo, Naoya Ouchi, Shohei Graduate Program in Information Electrical and Electronic Systems Engineering Utsunomiya University Japan Department of Innovative Electrical and Electronic Engineering National Institute of Technology Oyama Japan

Simultaneous multislice (SMS) imaging is a one of the acceleration technique of magnetic resonance imaging. SMS requires accurate sensitivity distributions in the slice plane for each receiving coil. This requirement is difficult to satisfy in practice, limiting the applications of this imaging technique. Here, images are reconstructed by applying deep learning and amplitude modulation to each slice image. Simulation experiments show that image reconstruction can be achieved for both real- and complex-valued images. Image quality tends to decrease with increasing number of simultaneously acquired images. It is also shown that a larger difference in the phase modulation coefficients between slices tends to increase the quality of the reconstructed images. Simulation experiments and initial MR imaging experiments show promising results for this method. Copyright © 2024, The Authors. All rights reserved.

关键词： Holography

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UC3M-PUCPR at SemEval-2022 Task 11: An Ensemble Method of Transformer-based Models for Complex Named Entity Recognition 16

UC3M-PUCPR at SemEval-2022 Task 11: An Ensemble Method of Tr...

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16th International Workshop on Semantic Evaluation, SemEval 2022

作者： Schneider, Elisa Terumi Rubel Rivera-Zavala, Renzo M. Martinez, Paloma Moro, Claudia Paraiso, Emerson Cabrera Graduate Program on Informatics Pontifícia Universidade Catolica do Paraná Brazil Computer Science and Engineering Department Universidad Carlos III de Madrid Spain

ISBN: (纸本)9781955917803

This study introduces the system submitted to the SemEval 2022 Task 11: MultiCoNER (Multilingual Complex Named Entity Recognition) by the UC3M-PUCPR team. We proposed an ensemble of transformer-based models for entity recognition in cross-domain texts. Our deep learning method benefits from the transformer architecture, which adopts the attention mechanism to handle the long-range dependencies of the input text. Also, the ensemble approach for named entity recognition (NER) improved the results over baselines based on individual models on two of the three tracks we participated in. The ensemble model for the code-mixed task achieves an overall performance of 76.36% F1-score, a 2.85 percentage point increase upon our individually best model for this task, XLM-RoBERTa-large (73.51%), outperforming the baseline provided for the shared task by 18.26 points. Our preliminary results suggest that contextualized language models ensembles can, even if modestly, improve the results in extracting information from unstructured data. © 2022 Association for Computational Linguistics.

关键词： Deep learning

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Analysis of the Need for Passengers' Connectivity Aboard the Ship by using Kano Model

Analysis of the Need for Passengers' Connectivity Aboard the...

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2021 International Conference on Green Energy, Computing and Sustainable Technology, GECOST 2021

作者： Pardomuan, Remon Suryanegara, Muhammad Universitas Indonesia Graduate Program in Telecommunications Management Department of Electrical Engineering Jakarta Indonesia

ISBN: (纸本)9781665438650

This paper aims to analyze passenger needs for network connectivity on the ship during traveling at the shipping line of Indonesian XYZ Company. The current connectivity infrastructure on board is supported by VSAT technology, but limited only for the ship's crew. Meanwhile, the passengers have difficulty to connect mobile cellular services while sailing. Therefore, providing the service over such a connectivity to the passengers can be an added values for the XYZ Company. This study uses Kano Model of the 11 attributes, and collect a primary data from 138 passengers sailing at PQR ship. It results recommendations portraying the passenger's need for shipping telecommunications during the sailing trip. © 2021 IEEE.

关键词： Ships

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