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Design and Development of Low-cost Wearable Electroencephalograms (EEG) Headset

Intelligent Automation & Soft Computing 2023年第3期35卷 2821-2835页

作者： Riaz Muhammad Ahmed Ali M.Abid Anwar Toufique Ahmed Soomro Omar AlShorman Adel Alshahrani Mahmoud Masadeh Ghulam Md Ashraf Naif H.Ali Muhammad Irfan Athanasios Alexiou Department of Electrical Engineering Sukkur IBA University65200SukkurPakistan Department of Electronic Engineering Quaid-e-Awam University of EngineeringScience and TechnologyLarkana77150Pakistan Faculty of Engineering and AlShrouk Trading Company Najran UniversityNajran61441Saudi Arabia Department of Medical Rehabilitation Sciences-Physiotherapy Program College of Applied Medical SciencesNajran UniversityNajran61441Saudi Arabia Computer Engineering Department Yarmouk UniversityIrbid21163Jordan Pre-Clinical Research Unit King Fahd Medical Research CenterKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Medical Laboratory Technology Faculty of Applied Medical SciencesKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Internal Medicine Medical CollegeNajran UniversityNajran61441Saudi Arabia Electrical Engineering Department College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Novel Global Community Educational Foundation HebershamNSW 2770AustraliaAFNP Med AustriaWien2770Austria

Electroencephalogram(EEG)is a method of capturing the electrophy-siological signal of the *** EEG headset is a wearable device that records electrophysiological data from the *** paper presents the design and fab-rication of a customized low-cost Electroencephalogram(EEG)headset based on the open-source OpenBCI Ultracortex Mark IV *** electrode placement locations are modiﬁed under a 10–20 standard *** fabricated headset is then compared to commercially available headsets based on the following para-meters:affordability,accessibility,noise,signal quality,and ***,the data is recorded from 20 subjects who used the EEG Headset,and signals were ***,the participants marked the accuracy,set up time,participant comfort,and participant perceived ease of set-up on a scale of 1 to 7(7 being excellent).Thirdly,the self-designed EEG headband is used by 5 participants for slide *** raw EEG signal is decomposed into a series of band sig-nals using discrete wavelet transform(DWT).Lastly,theseﬁndings have been compared to previously reported *** concluded that when used for slide-changing control,our self-designed EEG headband had an accuracy of 82.0 *** also concluded from the results that our headset performed well on the cost-effectiveness scale,had a reduced setup time of 2±0.5 min(the short-est among all being compared),and demonstrated greater ease of use.

关键词： Brain-computer interface EEG consumer-grade accessibility headset

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Trajectory Learning and Demonstration of a Robot Manipulator Based-on Sensor Fusion from a Hand-held Tool

Trajectory Learning and Demonstration of a Robot Manipulator...

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International Automatic Control Conference

作者： Kai-Tai Song Szu-Chen Ou Institute of Electrical and Control Engineering College of Electrical and Computer Engineering National Yang Ming Chiao Yang Ming Chiao Tung University Hsinchu Taiwan ROC Graduate Degree Program of Robotics National Yang Ming Chiao Tung University Hsinchu Taiwan ROC

ISBN: (数字)9798350354904

ISBN: (纸本)9798350354911

This paper presents a programming system for a robot manipulator using a hand-held demonstration tool. In this system, a user holds the self-designed tool to demonstrate a desired motion path, and the robot arm replicates the learned trajectory. The path-demonstration tool, including optical tags (OT) and an IMU, is designed to collect trajectory data from hand motion. Sensor data fusion allows the system to track accurately the demonstrated trajectory. A calibration procedure is proposed to transform the trajectory from tool’s coordinate system to robot’s coordinate system. A cubic spline-based trajectory planning method is proposed to ensure smooth reproduction of the learned trajectory in both time and space. Experimental results show that the robot is able to replicate squared and curved trajectories collected from the path-demonstration tool. The average position error is within 2.435 mm in XYZ directions and the average orientation error is within 0.65 degrees.

关键词： Trajectory planning Tracking Robot kinematics Transforms Sensor fusion programming Robot sensing systems Manipulators Trajectory Splines (mathematics)

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Study on Dual-band Antennas with a Modified Conical Antenna and a Parasitic Helical Element

Study on Dual-band Antennas with a Modified Conical Antenna ...

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2022 IEEE International Workshop on Electromagnetics: Applications and Student Innovation Competition, iWEM 2022

作者： Hirohara, Ryuji Fusazaki, Shinpei Noguchi, Keisuke Kanazawa Institute of Technology Graduate Program in Electrical Engineering and Electronics Ishikawa Nonoichi Japan DOCOMO CS Hokuriku Inc. Management Planning Section Network Management Department Ishikawa Kanazawa Japan

ISBN: (数字)9781665432382

ISBN: (纸本)9781665432382

With the start of the 5G operations, it will become more important to apply communication systems to automo-biles, which has been promoted in recent years as connected cars. Multi-band antennas are required to reduce the in-vehicle space which is occupied by communication equipment. We de-signed dual-band antennas for the sub-6 GHz 5G bands and the intelligent transport systems (ITS) especially the driving safety support system (DSSS) by loading helical elements to modified conical antennas (MCA), and conducted simulations and meas-urements. As a result, the antenna satisfied the sub-6 and ITS DSSS bands in the simulations. There were slightly differences between the calculated and measured results. © 2022 IEEE.

关键词： Intelligent systems

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Characterizing and Mitigating Chemomechanical Degradation in High-Energy Lithium-Ion Battery Cathode Materials

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Accounts of Materials Research 2022年第5期3卷 511-524页

作者： Norman S.Luu Kyu-Young Park Mark C.Hersam Department of Materials Science and Engineering Northwestern UniversityEvanstonIllinois 60208United States Graduate Institute of Ferrous and Energy Materials Technology Pohang University of Science and TechnologyPohangKyungbuk 37673Republic of Korea Department of Chemistry and Department of Electrical and Computer Engineering Northwestern UniversityEvanstonIllinois 60208United

Lithium-ion batteries(LIBs)are nearly ubiquitous energy storage solutions,powering devices ranging from consumer electronics to electric *** advance these applications,current LIB research efforts are directed toward improving energy and power densities,cyclic lifetimes,charging speeds,and *** parameters are intrinsically tied to properties of the active electrode materials,such as the redox mechanism,chemical composition,and crystal *** particularly challenging issue is that the active electrode materials that possess higher theoretical energy densities are generally more susceptible to degradation during cycling.A notable example is the family of layered multicomponent transition metal oxides,which is the incumbent class of active LIB cathode materials for electric *** increase their theoretical capacities,the transition metal fraction in these materials is trending toward higher Ni ***,Ni-rich chemistries suffer from electrochemical,crystallographic,and mechanical degradation that increase in severity with increasing Ni ***,alternative high-energy cathode materials,including overlithiated layered oxides and disordered rock salt materials,present additional stability challenges that must be overcome before they can be realistically incorporated into LIB *** chemomechanical degradation in high-energy LIB cathode materials occurs at multiple length *** defects,such as antisite defects or vacancies,are commonly generated during electrochemical cycling and can contribute to the loss of cyclable active *** both the primary and secondary particle level,electrochemical cycling also induces significant volumetric changes and state-of-charge heterogeneity,generating regions of high stress and strain that are precursors to mechanical ***,at the electrode level,nonuniform charge transfer reactions throughout the electrode can lead to locally overcharged regions that become

关键词： Battery electrode cycling

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Base on GAN Combined with CNN Architecture to Generate Brain Stroke CT Images 24

Base on GAN Combined with CNN Architecture to Generate Brain...

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8th International Conference on Medical and Health Informatics, ICMHI 2024

作者： Shih, Guan-Yu Ting, Hsien-Wei Chen, Yi-Xiang Chien, Ting-Ying Department of Computer Science and Engineering Yuan Ze University Taoyuan City Taiwan Graduate Program inBiomedical Informatics Yuan Ze University Taoyuan City Taiwan Department of Neurosurgery Taipei Hospital Ministry of Health and Welfare New Taipei City242 Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taoyuan City Taiwan

ISBN: (纸本)9798400716874

In recent years, many fields have expanded their research methods through the integration of artificial intelligence. In the current medical field, it is widely used in image recognition to diagnose patient symptoms, train clinical prediction models, and improve clinical workflow processes to avoid missing treatment opportunities. These methods have all achieved good results so far. Now, generative AI is also impacting the development of the medical field, not only generating prescriptions that match patient conditions but also being applied in generating medical images for data augmentation and simulating various pathological conditions, thereby aiding in training deep learning models. Stroke is a leading cause of death or disability, ranking as the second leading cause of death worldwide, next to cancer. If cancers were categorized individually, stroke would surpass all single diseases, making it a primary focus of research in brain disease treatment. There are already studies where generative AI has been used to create medical images, which are then manually evaluated by doctors to determine if they were generated by AI. In this project, we plan to generate CT images of strokes using generative AI and use a trained model (to diagnose stroke) to improve accuracy. Through this project, we hope to solve the problem of scarce stroke CT images while also providing support for training stroke-related models. © 2024 Copyright ACM.

关键词： Deep learning

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Automatic 2D Material Detection in Optical Images using Deep Learning Based computer Vision 4

Automatic 2D Material Detection in Optical Images using Deep...

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AI and Optical Data Sciences IV 2023

作者： Ramezani, Fereshteh Parvez, Sheikh Fix, J. Pierce Battaglin, Arthur Whyte, Seamus Borys, Nicholas J. Whitaker, Bradley Electrical and Computer Engineering Department Montana State University Bozeman United States Department of Physics Montana State University Bozeman United States Materials Science Program Montana State University Bozeman United States Optical Technology Center Montana State University Bozeman United States

ISBN: (纸本)9781510659810

computer vision algorithms can quickly analyze numerous images and identify useful information with high accuracy. Recently, computer vision has been used to identify 2D materials in microscope images. 2D materials have important fundamental properties allowing for their use in many potential applications, including many in quantum information science and engineering. In order to use these materials for research and product development, single-layer 2D crystallites must be prepared through an exfoliation procedure and then identified using reflected light optical microscopy. Performing these searches manually is a time-consuming and tedious task. Deploying deep learning-based computer vision algorithms for 2D material search can automate the flake detection task with minimal need for human intervention. In this work, we have implemented a new deep learning pipeline to classify crystallites of 2D materials based on coarse thickness classifications in reflected-light optical micrographs. We have used DetectorRS as the object detector and trained it on 177 images containing hexagonal boron nitride (hBN) flakes of varying thickness. The trained model achieved a high detection accuracy for the rare category of thin flakes ( © 2023 SPIE.

关键词： Object detection

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NCU-IISR/AS-GIS: Using BERTScore and Snippet Score to Improve the Performance of Pretrained Language Model in BioASQ 10b Phase B

NCU-IISR/AS-GIS: Using BERTScore and Snippet Score to Improv...

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2022 Conference and Labs of the Evaluation Forum, CLEF 2022

作者： Ting, Hao-Hsuan Zhang, Yu Han, Jen-Chieh Tsai, Richard Tzong-Han Interdisciplinary Program of Electrical Engineering and Computer Science National Central University Taiwan Department of Computer Science and Information Engineering National Central University Taiwan IoX Center National Taiwan University Taiwan Research Center for Humanities and Social Sciences Academia Sinica Taiwan

This paper presents our system for the BioASQ10b Phase B task. For ideal answers, we used the fine-tuned BioBERT model on the MNLI dataset to construct sentence embeddings and combined it with BERTScore to select sentences from the provided Snippets as answers. For the exact answers, we also used the BioBERT model and used the snippet scores generated from the ideal answer selection model to predict the exact answers for factoid and list questions. The exact answers of our fifth test batch ranked second place. In addition, the ideal answers we submitted achieved first place in the ROUGE score in all test batches from batch second to fifth. © 2022 Copyright for this paper by its authors.

关键词： Computational linguistics

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Hyperbolic Diffusion Procrustes Analysis for Intrinsic Representation of Hierarchical Data Sets

Hyperbolic Diffusion Procrustes Analysis for Intrinsic Repre...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Ya-Wei Eileen Lin Yuval Kluger Ronen Talmon Viterbi Faculty of Electrical and Computer Engineering Technion Interdepartmental Program in Computational Biology and Bioinformatics Yale University Applied Math Program Yale University Department of Pathology School of Medicine Yale University

In this paper, we present Hyperbolic Diffusion Procrustes Analysis (HDPA), a new method for informative representation of hierarchical datasets based on hyperbolic geometry, diffusion geometry, and Procrustes analysis. Our method jointly embeds multiple datasets in a product manifold of hyperbolic spaces, where the data's hidden common hierarchical structure is provably recovered. In addition, our method generates an intrinsic embedding that accommodates the joint representation of multiple datasets with different features, acquired by different equipment, at different sites, or under different environmental conditions. Experimental results demonstrate the efficacy of HDPA on three biomedical datasets comprising heterogeneous gene expression and mass cytometry data.

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Constructing a Segmentation Model for Patients with Leukoaraiosis Using Deep Learning Algorithms 24

Constructing a Segmentation Model for Patients with Leukoara...

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8th International Conference on Medical and Health Informatics, ICMHI 2024

作者： Lo, Li-Ting Tsai, Yi-Chia Chang, Yi-Jou Ting, Hsien-Wei Chien, Ting-Ying Department of Computer Science and Engineering Yuan Ze University Taoyuan City Taiwan Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan City Taiwan Department of Neurosurgery Taipei Hospital Ministry of Health and Welfare New Taipei City242 Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taoyuan City Taiwan

ISBN: (纸本)9798400716874

Many patients with leukoaraiosis (LA) exhibit mild and difficult-to-detect symptoms in the early stages, and due to the lack of effective detection methods, the optimal timing for treatment is often missed. This not only makes later treatment more difficult but, in severe cases, can even lead to mild to severe dementia. Therefore, in addition to relying on radiologists to manually interpret magnetic resonance imaging (MRI) scans, finding more effective detection methods has become extremely urgent. This study aimed to combine image processing and deep learning technologies to develop a model capable of accurately identifying and segmenting white matter hyperintensities (WMHs) to assist doctors in the early diagnosis of LA. We first performed efficient preprocessing on MR image slices from two different series and used the ResNet18 model to identify key slices containing WMHs, ultimately achieving precise segmentation of WMH areas with the U-Net model. This research focused on developing innovative preprocessing techniques, improving the accuracy by 12.3% with a limited dataset through preprocessing. Ultimately, the ResNet18 model achieved an F1 score of 0.829, while the U-Net model’s intersection over union (IoU) and Dice coefficient reached 0.750 and 0.857, respectively, showing the potential of this architecture. We propose improvements in the final chapter to construct a more comprehensive model. © 2024 Copyright ACM.

关键词： Deep learning

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Extreme Fast Charging Station for Multiple Vehicles with Sinusoidal Currents at the Grid Side

Extreme Fast Charging Station for Multiple Vehicles with Sin...

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2022 IEEE Transportation Electrification Conference and Expo, Asia-Pacific, ITEC Asia-Pacific 2022

作者： Brandao, Dener A. De L. Parreiras, Thiago M. Pires, Igor A. Filho, Braz De J. Cardoso Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Belo Horizonte Brazil Institute of Technological Sciences Universidade Federal de Itajuba Itabira Brazil Department of Electronics Engineering Universidade Federal de Minas Gerais Belo Horizonte Brazil Department of Electrical Engineering Universidade Federal de Minas Gerais Belo Horizonte Brazil

ISBN: (数字)9781665492065

ISBN: (纸本)9781665492065

As the electrical vehicle fleet grows, extreme fast charging (XFC) stations for multiple vehicles will be increasingly needed. The challenges for the implementation of many XFC stations in the electric power system are many and it is necessary to use converters that reduce the negative impacts on the electric grid, meet the standards and recommendations, and that are technically and economically viable. This work proposes an XFC station for multiple vehicles that has a very low current harmonics injection at the grid side, with a Total Demand Distortion (TDD) of 0.62% without using sinusoidal filter, provides galvanic isolation for each input/output port, and can provide additional features such as Distributed Energy Resources (DER) integration and ancillary services. This is achieved by combining a bidirectional low switching frequency grid-connected active front-end with high switching frequency SiC-based dc/dc converters in the vehicles side. After a brief description of the proposed system and its control, simulation results are presented to validate the XFC. © 2022 IEEE.

关键词： Rectifying circuits

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