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14th International Conference on Ambient systems, Networks and Technologies Networks, ANT 2023 and The 6th International Conference on Emerging Data and Industry 4.0, EDI40 2023

作者： Yoo, Yegi Chen, Tiantian Jang, Kitae Kim, Inhi Department of Urban Systems Engineering Kongju Natinal University 1223-24 Cheonan-daero Seobuk-gu Cheonan31080 Korea Republic of The Cho Chun Shik Graduate School of Transportation KAIST 193 Munji-ro Yuseong-gu Daejeon34051 Korea Republic of

Social costs increase as traffic problems continue. Driverless vehicles are attracting attention as a way to overcome this issue. Many said that fully autonomous driving is not a distant future. As one of the autonomous vehicle operations, vehicle platooning has been paid attention. Therefore, this study analyzes the effects of vehicle platooning on the road network. As a large-scale network, Jeju island, one of the cities in Korea was selected to test the platooning arrangement. A macro simulation was developed and calibrated based on the collected traffic counts, and then the network and assigned paths were imported to the micro simulation, which is capable of forming the platoon. The analysis was conducted by changing various parameters of the platooning vehicle. According to the investigation, it can be seen that as the market share of autonomous vehicles increases, delays decrease, and speed increases. Traffic efficiency was improved through platooning in general. It is expected that the results of this study can be used as primary data to develop an optimal traffic flow management strategy for cluster operation. © 2023 Elsevier B.V.. All rights reserved.

关键词： Autonomous vehicles

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Prescribed-time stabilization for high-order nonlinear systems with a pre-specified asymmetric output constraint

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Journal of the Franklin Institute 2023年第4期360卷 3545-3574页

作者： Chen, Chih-Chiang Sun, Zong-Yao Xu, Sendren Sheng-Dong Department of Systems and Naval Mechatronic Engineering National Cheng Kung University Tainan70101 Taiwan Institute of Automation Qufu Normal University Shandong Province Qufu273165 China Graduate Institute of Automation and Control National Taiwan University of Science and Technology Taiwan Advanced Manufacturing Research Center National Taiwan University of Science and Technology Taiwan

This article considers the problem of prescribed-time stabilization for a class of uncertain high-order nonlinear systems (i.e., systems in the p-normal form) with a pre-specified asymmetric output constraint. A core ingredient, tangent-type barrier function, is proposed first by skillfully excavating and assimilating the inherent properties of system nonlinearities. Based on the barrier function, as well as a serial of nested signum functions, the celebrated technique of adding a power integrator is renovated finely to establish a new design approach by which a continuous state feedback prescribed-time stabilizer, along with a tangent-type asymmetric barrier Lyapunov function, can be constructed in a systematic fashion, thereby guaranteeing the performance of prescribed-time state convergence and ensuring the fulfillment of pre-specified output constraints surely. Benefiting from the composite characteristics of the presented tangent-type barrier Lyapunov function and the signum functions, the proposed approach further offers a unified nature in design enabling us to organize a prescribed-time stabilizer that is simultaneously valid and executable for the system undergone or free from output constraints, without the need of changing the controller structure. The effectiveness and superiority of the developed approach are illustrated by a numerical example. © 2022 The Franklin Institute

关键词： Lyapunov functions

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A Hybrid Attention-Based Residual Unet for Semantic Segmentation of Brain Tumor

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Computers, Materials & Continua 2023年第7期76卷 647-664页

作者： Wajiha Rahim Khan Tahir Mustafa Madni Uzair Iqbal Janjua Umer Javed Muhammad Attique Khan Majed Alhaisoni Usman Tariq Jae-Hyuk Cha Department of Computer Science COMSATS University IslamabadIslamabad45550Pakistan Department of Electrical and Computer Engineering COMSATS University IslamabadWah CampusPakistan Department of Computer Science HITEC UniversityTaxilaPakistan Department of Computer Science College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Management Information Systems CoBAPrince Sattam Bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia Department of Computer Science Hanyang UniversitySeoul04763Korea

Segmenting brain tumors in Magnetic Resonance Imaging(MRI)volumes is challenging due to their diffuse and irregular ***,2D and 3D deep neural networks have become famous for medical image segmentation because of the availability of labelled ***,3D networks can be computationally expensive and require significant training *** research proposes a 3D deep learning model for brain tumor segmentation that uses lightweight feature extraction modules to improve performance without compromising contextual information or *** proposed model,called Hybrid Attention-Based Residual Unet(HA-RUnet),is based on the Unet architecture and utilizes residual blocks to extract low-and high-level features from MRI *** and Squeeze-Excitation(SE)modules are also integrated at different levels to learn attention-aware features adaptively within local and global receptive *** proposed model was trained on the BraTS-2020 dataset and achieved a dice score of 0.867,0.813,and 0.787,as well as a sensitivity of 0.93,0.88,and 0.83 for Whole Tumor,Tumor Core,and Enhancing Tumor,on test dataset *** results show that the proposed HA-RUnet model outperforms the ResUnet and AResUnet base models while having a smaller number of parameters than other state-of-the-art ***,the proposed HA-RUnet model can improve brain tumor segmentation accuracy and facilitate appropriate diagnosis and treatment planning for medical practitioners.

关键词： MRI volumes residual Unet BraTs-2020 squeeze-excitation(SE)

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Noise-induced bistability in a simple mutual inhibition system

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Physical Review E 2023年第2期108卷 024108-024108页

作者： Taichi Haruna Tomohiro Shirakawa Department of Information and Sciences School of Arts and Sciences Tokyo Woman's Christian University 2-6-1 Zempukuji Suginami-ku Tokyo 167-8585 Japan. Department of Information and Management Systems Engineering Graduate School of Engineering Nagaoka University of Technology 1603-1 Kamitomioka Nagaoka Niigata 940-2188 Japan.

In this study, we study noise-induced bistability in a simple bivariate mutual inhibition system with slow fluctuating responses to external signals. We give a general condition that the marginal stationary probability density of one of the two variables experiences a transition from a unimodal shape to a bimodal one. We show that the transition occurs even when the stationary probability density of the response to external signals is monotone. The mechanism for the transition is investigated in terms of the calculation of the mean first passage time. We also discuss the genericity of the transition mechanism.

关键词： Fluctuations & noise Intracellular signalling Signaling networks Stochastic differential equations

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System for Automating Medication Orders to the Hospital Pharmacy by Nurses in Peru Through Voice Recognition

System for Automating Medication Orders to the Hospital Phar...

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Software engineering and Computer Science (CSECS), International Conference on

作者： Conrado Moreno-Fernández Fabian Colque-Fernández José Luis Castillo-Sequera Lenis Wong Information Systems Engineering Program Universidad Peruana de Ciencias Aplicadas Lima Perú Department of Computer Science Universidad de Alcalá Alcalá de Henares Spain

ISBN: (数字)9798331522216

ISBN: (纸本)9798331522223

The management of nurses' orders to a Peruvian hospital pharmacy faces efficiency challenges, which affects time spent on patient care. This context highlights the need for a system that optimizes this process. In this sense, a web-based system is proposed for the automation of orders from the nurse's cell phone, which uses a customized model for automatic speech recognition. The development of the system was divided into three stages: first, data collection with 21 orders placed by three nurses and 978 audio recordings to validate the automatic speech recognition model; second, implementation of the system allowing agile order processing; and finally, evaluation of results in terms of time and accuracy. The findings indicate that the processing time ranged from 37.70 to 60.15 seconds, representing a 97%-time reduction in operational tasks. In addition, the Word Error Rate was 10.51%, significantly lower than the 25.05% of Whisper Large V2. These results demonstrate the system's potential for adoption in various hospital contexts.

关键词： Automation Accuracy Hospitals Error analysis Terminology Transforms Time measurement Artificial intelligence Automatic speech recognition Software engineering

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Ultrasound Stimulation Potentiates management of Diabetic Hyperglycemia

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Ultrasound in Medicine and Biology 2023年第5期49卷 1259-1267页

作者： Chang, Chia-Hsuan Fan, Kang-Chih Cheng, Yuan-Pin Chen, Jung-Chih Chen, Gin-Shin Graduate Degree Program of the College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu City Taiwan Institute of Biomedical Engineering and Nanomedicine National Health Research Institutes Miaoli County Taiwan Division of Endocrinology and Metabolism Department of Internal Medicine National Taiwan University Hospital Hsinchu Branch Hsinchu City Taiwan Graduate Institute of Clinical Medicine College of Medicine National Taiwan University Taipei City Taiwan Electronic Systems Research Division National Chung-Shan Institute of Technology Taoyuan City Taiwan Institute of Biomedical Engineering National Yang Ming Chiao Tung University Hsinchu City Taiwan Department of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu City Taiwan Catholic Mercy Hospital Catholic Mercy Medical Foundation Hsinchu County Taiwan Medical Device Innovation & Translation Center National Yang Ming Chiao Tung University Hsinchu City Taiwan

Objective: Glucose homeostasis is the only way to manage diabetic progression as all medications used do not cure diabetes. This study was aimed at verifying the feasibility of lowering glucose with non-invasive ultrasonic stimulation. Methods: The ultrasonic device was homemade and controlled via a mobile application on the smartphone. Diabetes was induced in Sprague–Dawley rats through high-fat diets followed by streptozotocin injection. The treated acupoint CV12 was at the middle of the xiphoid and umbilicus of the diabetic rats. Parameters of ultrasonic stimulation were an operating frequency of 1 MHz, pulse repetition frequency of 15 Hz, duty cycle of 10% and sonication time of 30 min for a single treatment. Discussion: The diabetic rats exhibited a significant decrease of 11.5% ± 3.6% in blood glucose in 5 min of ultrasonic stimulation (p © 2023 World Federation for Ultrasound in Medicine & Biology

关键词： Glucose

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Discriminative Analysis of Autistic Tendencies at 18 Months of Age Using Eye Gaze Characteristics in 4-, 10-, and 18-month-old Infants

Discriminative Analysis of Autistic Tendencies at 18 Months ...

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IEEE/SICE International Symposium on System Integration

作者： Rena Ueda Hirokazu Doi Akira Furui Koji Shimatani Hideaki Hayashi Toshio Tsuji Graduate School of Advanced Science and Engineering Hiroshima University Hiroshima Japan Department of Information and Management Systems Engineering Nagaoka University of Technology Niigata Japan Graduate School of Biomedical Sciences Nagasaki University Nagasaki Japan Faculty of Health and Welfare Prefectural University of Hiroshima Hiroshima Japan Institute for Datability Science Osaka University Osaka Japan

ISBN: (数字)9798331531614

ISBN: (纸本)9798331531621

Anomalies in motor function and social communication skills constitute early signs of autism spectrum disorder (ASD). In recent years, researchers have paid attention to the possibility of the quantitatively evaluating infants’ social communication skills based on their eye movement. In this paper, we attempt to evaluate ASD risk using infants’ eye movement data by examining the relationship between eye movement patterns at 4, 10, and 18 months of age and ASD risk as assessed by caregivers using a checklist at 18 months of age. A total of 18 eye movement indices were calculated from eye movement data measured by an optical eye tracker. The results revealed an association between ASD risk and eye movement indices. The indices included those related to a preference for social information at 4 months of age, those related to visual exploration of images at 10 months of age, and those indices related to both preference and visual exploration at 18 months of age. These results indicate that eye movement analysis may potentially serve as a means for early screening of ASD risk.

关键词： Visualization Accuracy Tracking Input variables System integration Variable speed drives Optical variables measurement Feature extraction Optical imaging Motors

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Motion Measurement Methods for Nonlinear Analysis of Electrostatic MEMS Resonators

Motion Measurement Methods for Nonlinear Analysis of Electro...

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Eurocon

作者： Mehdi Ghommem Basil Alattar Michael Lherbette Alaaeldin Elhady Eihab Abdel-Rahman Department of Mechanical Engineering American University of Sharjah Sharjah UAE Mechatronics Graduate Program American University of Sharjah Sharjah UAE SmarAct Metrology Rohdenweg Oldenburg Germany Systems Design Engineering University of Waterloo Waterloo Ontario Canada

In this paper, we compare two measurement techniques to analyze the dynamic response of a MEMS resonator, made of a microcantilever beam, that is electrostatically actuated via a side electrode. The first method is based on a combination of Michelson interferometry, knife-edge analysis, and stroboscopic imaging, and is used to dissect the in-plane and out-of-plane motions of the resonator. The second approach follows the motion-induced current method and is based on a transduction mechanism that converts the movement of the resonator to a current signal. The third harmonic of said current is directly related to the in-plane motion of the resonator. Motion-induced current measurements enable the detection of the nonlinear dynamics associated with the motion of the resonator when actuated with high excitation voltages. The optical and electrical measurements show similar nonlinear features in terms of the location of the cyclic-fold bifurcation in the parameter space and the hysteretic region associated with it. These dynamic features can be exploited for sensing purposes.

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PBF-AMP-Onto: an ontology for powder bed fusion additive manufacturing processes 1

PBF-AMP-Onto: an ontology for powder bed fusion additive man...

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1st International Workshop on Semantic Materials Science: Harnessing the Power of Semantic Web Technologies in Materials Science, SeMatS 2024

作者： Pour, Mina Abd Nikooie Tarafder, Prithwish Wiberg, Anton Li, Huanyu Moverare, Johan Lambrix, Patrick Department of Computer and Information Science Linköping University Linköping Sweden Swedish e-Science Research Centre Linköping University Linköping Sweden Department of Management and Engineering Linköping University Linköping Sweden Wallenberg Initiative Materials Science for Sustainability Linköping University Linköping Sweden Wallenberg AI Autonomous Systems and Software Program Linköping University Linköping Sweden

Additive manufacturing is an innovative production approach aimed at creating products that traditional techniques cannot produce with the desired quality and requirements. Throughout the additive manufacturing process, data is either used (such as materials properties, printer characteristics and settings) or generated (such as monitoring data during printing, slicing strategies setting parameters). However, managing such data with complex relationships remains a significant challenge in both research and industry in the additive manufacturing field. To address this issue, we developed a modular ontology that can be used as the basis for a framework that supports decision-making systems, facilitate semanticsaware data management, and enhance the understanding and optimization of additive manufacturing processes. In this paper we focus on one of the state-of-the-art additive manufacturing approaches, i.e., powder bed fusion. To show the use and the feasibility of our approach, we created a knowledge graph for an actual additive manufacturing experiment based on our ontology, and show how queries relevant to domain experts can be answered using this knowledge graph. © 2024 CEUR-WS. All rights reserved.

关键词： Ontology

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Enhanced Prognostics and Health management in Automated Driving systems: Using Graph Neural Networks to Recognize Operational Contexts

Enhanced Prognostics and Health Management in Automated Driv...

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Prognostics and System Health management Conference (PHM)

作者： Peng Su Yeqi Wang Conglei Xiang Erik Wendel Madhav Mishra DeJiu Chen Department of Engineering Design Mechatronics Division KTH Royal Institute of Technology Stockholm Sweden Embedded Systems Master Program of Electrical Engineering and Computer Science (EECS) School KTH Royal Institute of Technology Stockholm Sweden Digital Systems Division RISE Research Institutes of Sweden Gothenburg Sweden

ISBN: (数字)9798350360585

ISBN: (纸本)9798350360592

Prognostics and health management (PHM) is an engineering discipline that aims to maintain system behaviour and function and ensure mission success, safety and effectiveness. Addressing the challenges in prognostics and health management for modern intelligent systems, especially automated driving systems, is complex due to the contextual nature of faults. This complexity necessitates a thorough understanding of spatial, and temporal conditions, and relationships within operational scenarios and life-cycle stages. This paper introduces a framework designed to automatically recognize driving scenarios in automated driving systems using graph neural networks (GNNs). The framework extracts relational data from image frames, constructing graph-based models and transforming unstructured sensory data into structured data with diverse node types and relationships. A specific graph neural network processes the graph model to reveal and detect operational conditions and relationships. The proposed framework is evaluated using the KITTI dataset, demonstrating superior performance compared to conventional feed-forward networks such as MLP, particularly in handling relational data.

关键词： Graph neural networks Data models Safety Complexity theory Data mining Prognostics and health management Intelligent systems

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