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Simultaneously Identifying the System Dynamics and Fault Isolation for Air Data Sensor Failures: A Convex Approach

IFAC-PapersOnLine 2024年第4期58卷 103-108页

作者： J. Noom C.C. de Visser N.S. Ramesh M. Verhaegen Delft University of Technology Department of Mechanical Engineering Delft Center for Systems and Control Delft University of Technology Department of Aerospace Engineering Control and Simulation Division

This paper addresses the key question that when faults occur either the aircraft system dynamics changes due to the fault or these dynamics are unknown (precisely). This question is addressed for the important case of Air Data Sensor failures, due to e.g. icing, for fixed wing aircraft operating in a nominal fight condition. The solution to this question uses basic ideas from subspace Identification to cast this problem in linear least squares problem with convex constraints (nuclear norm and 1-norm constraints). The latter are relaxations of a rank and cardinality constraint. The presented solution is validated using real-life fight test data.

关键词： Signal Identification-based methods Flight control fault detection FDI for linear systems

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GACL-Net:Hybrid Deep Learning Framework for Accurate Motor Imagery Classification in Stroke Rehabilitation

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Computers, Materials & Continua 2025年第4期83卷 517-536页

作者： Chayut Bunterngchit Laith H.Baniata Mohammad H.Baniata Ashraf ALDabbas Mohannad A.Khair Thanaphon Chearanai Sangwoo Kang State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing100190China School of Computing Gachon UniversitySeongnam13120Republic of Korea Computer Science Department Faculty of Information TechnologyThe World Islamic Sciences and Education UniversityAmman11947Jordan Intelligent Systems Department Faculty of Artificial IntelligenceAl-Balqa Applied UniversityAl-Salt19117Jordan IT Infrastructure Department Qatrana Cement CompanyAmman11821Jordan Division of Industrial and Logistics Engineering Technology Faculty of Engineering and TechnologyKing Mongkut’s University of Technology North BangkokRayong CampusRayong21120Thailand

Stroke is a leading cause of death and disability worldwide,significantly impairing motor and cognitive *** rehabilitation is often hindered by the heterogeneity of stroke lesions,variability in recovery patterns,and the complexity of electroencephalography(EEG)signals,which are often contaminated by *** classification of motor imagery(MI)tasks,involving the mental simulation of movements,is crucial for assessing rehabilitation strategies but is challenged by overlapping neural signatures and patient-specific *** address these challenges,this study introduces a graph-attentive convolutional long short-term memory(LSTM)network(GACL-Net),a novel hybrid deep learning model designed to improve MI classification accuracy and ***-Net incorporates multi-scale convolutional blocks for spatial feature extraction,attention fusion layers for adaptive feature prioritization,graph convolutional layers to model inter-channel dependencies,and bidi-rectional LSTM layers with attention to capture temporal *** on an open-source EEG dataset of 50 acute stroke patients performing left and right MI tasks,GACL-Net achieved 99.52%classification accuracy and 97.43%generalization accuracy under leave-one-subject-out cross-validation,outperforming existing state-of-the-art ***,its real-time processing capability,with prediction times of 33–56 ms on a T4 GPU,underscores its clinical potential for real-time neurofeedback and adaptive *** findings highlight the model’s potential for clinical applications in assessing rehabilitation effectiveness and optimizing therapy plans through precise MI classification.

关键词： Motor imagery EEG stroke rehabilitation deep learning brain-computer interface

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An Improved Path Planning Algorithm for USV Based on Voxel Extension 9

An Improved Path Planning Algorithm for USV Based on Voxel E...

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9th International Conference on Computer and Communications, ICCC 2023

作者： Cai, Xin Xue, Zhenfeng Chen, Zhuo Liu, Yong Huzhou University School of Information Engineering Huzhou313000 China Huzhou Institute of Zhejiang University Intelligent Perception and Control Center Huzhou313098 China Zhejiang University Institute of Cyber-Systems and Control Hangzhou310027 China Cssc Systems Engineering Research Institute Beijing100094 China

ISBN: (纸本)9798350317251

In this paper, we propose a corridor generation algorithm based on voxel extension to obtain a safe path for unmanned surface vehicle (USV). Firstly, a dual-drive model is applied to model the USV, and then we design a path planning framework for the front-end and back-end parts. The front-end structure is responsible for finding a series of asymptotically optimal path points and generating safe corridors connected by a series of convex polygons based on these path points. The back-end part takes the safety corridor as a partial constraint and applies numerical optimization methods to generate a smooth trajectory. Finally, we validate and compare the proposed method with the baseline in a simulation environment. © 2023 IEEE.

关键词： Motion planning

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Improving VANET Localization Performance with Data Verification: Challenges and Solutions

Improving VANET Localization Performance with Data Verificat...

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2024 International Conference on Decision Aid Sciences and Applications, DASA 2024

作者： Ahmed, Amjed Abbas Kadhim, Aqeel Kamil Najim, Ali Hamza Ali Alheeti, Khattab M. Mohd Satar, Nurhizam Safie Abdallah Hashim, Aisa Hassan Universiti Kebangsaan Malaysia Center for Cyber Security Faculty of Information Science and Technology Bangi Malaysia Department of Computer Techniques Engineering Baghdad Iraq Department of Computer Technical Engineering Baghdad Iraq Department of Computer Technical Engineering Al-Diwaniyah Iraq College of Computer and Information Technology Computer Networking Systems Department University of Anbar Anbar Iraq Center for Cyber Security Faculty of Information Science and Technology Bangi43600 Malaysia International Islamic University Malaysia Faculty of Engineering Department of Electrical and Computer Engineering Selangor Malaysia

ISBN: (纸本)9798350369106

In VANETs, the important and effective applications of vehicle localization include safety and communication applications. Thus, it is difficult to get very accurate localization in the dynamic and often very fluctuating environment of VANET. This research responds to this challenge with a keen thrust on improving vehicle localization using the Mobility Data Verification process. The primary goal of this work is to achieve high accuracy of vehicle positioning within VANET by checking the coherence of mobility data of moving vehicles. Hence, we present a concept that builds upon Mobility Data Verification to provide real-time location details from vehicles. Both GPS and onboard sensors feed this method, which uses a multi-level verification to flag out or eliminate the errors of deliberately spoofed data points. We use simulations to evaluate and validate the effectiveness of the proposed verification approach. As the proposed system, our previously developed and fine-tuned weighted localization (OWL) strategy does so. The performance evaluation results suggest that our proposed solution is feasible to distinguish automobiles that are not trustworthy and improve the performance of the localization algorithm. © 2024 IEEE.

关键词： Vane pumps

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Smart Water-Powered Renewable Energy System with IoT Integration

Smart Water-Powered Renewable Energy System with IoT Integra...

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2024 International Conference on Decision Aid Sciences and Applications, DASA 2024

作者： Ahmed, Amjed Abbas Najim, Ali Hamza Ibraheem, Ahmed Salman Ali Alheeti, Khattab M. Mohd Satar, Nurhizam Safie Abdallah Hashim, Aisha Hassan Universiti Kebangsaan Malaysia Center for Cyber Security Faculty of Information Science and Technology Bangi Malaysia Department of Computer Techniques Engineering Baghdad Iraq Department of Computer Technical Engineering Al-Diwaniyah Iraq Department of Computer Technical Engineering Baghdad Iraq College of Computer and Information Technology Computer Networking Systems Department University of Anbar Anbar Iraq Center for Cyber Security Faculty of Information Science and Technology Bangi43600 Malaysia International Islamic University Malaysia Faculty of Engineering Department of Electrical and Computer Engineering Selangor Malaysia

ISBN: (纸本)9798350369106

An advanced hybrid renewable energy collecting and storage system prototype that utilizes water flow as its primary power source. Additionally, the system incorporates an energy monitoring system based on the Internet of Things (IoT) technology. The device effectively harnesses energy from the movement of water, storing it for future use in low-voltage applications. It demonstrates a maximum daily energy capture capacity of about 100Wh. The energy monitoring system, based on the Internet of Things (IoT), enables the real-time and remote monitoring of energy harvesting and usage. We thoroughly assessed the energy harvesting component across different situations to identify the crucial parameters that impact energy output. The results of our study demonstrate that several elements, including the spatial separation 'between the energy harvester and the water source, Water flow' speed, sensor orientation, and sensor density, all play significant roles in determining the quantity of energy collected. This research shows that it is possible to integrate IoT technology with hydropower renewable energy systems. It provides significant perspectives on enhancing energy extraction efficiency in practical scenarios. © 2024 IEEE.

关键词： harvesting renewable energy IoT storage energy water flow energy

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Vehicle Trajectory-Based Intersection Classification Using Deep Transfer Learning 5

Vehicle Trajectory-Based Intersection Classification Using D...

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5th International Conference on Intelligent Computing, Communication, Networking and Services, ICCNS 2024

作者： Kased, Abanoub Rabee, Rana Fahmy, Akram Mohamed, Hussein Yacoub, Marco Elhenawy, Mohammed Ashqar, Huthaifa I. Alsobeh, Anas Masoud, Mahmoud Hassan, Abdallah A. Minia University Faculty of Engineering Computers and Systems Department Minia Egypt Australia Arab American University Civil Engineering Department Jenin Palestine School of Computing Southern Illinois University Carbondale CarbondaleIL United States Center for Smart Mobility and Logistics King Fahd University of Petroleum and Minerals Department of Information Systems and Operations Management Dhahran Saudi Arabia

ISBN: (纸本)9798350354690

This document is a model and instructions for M-TEX. The accelerated expansion of global road networks necessitates the availability of accurate and up-to-date cartographic data for connected and automated vehicles. Conventional mapping techniques, such as satellite imagery and field surveys, are inher-ently time-consuming and labor-intensive. This study proposes a novel approach that makes use of the ubiquity of GPS-embedded devices to facilitate the efficient updating of road maps. We present a classifier that identifies the types of intersections from vehicle trajectories, which represents a crucial initial step in the generation of automated maps. The methodology employs five distinct convolutional deep neural network architectures for the detection and classification of road intersection types. The experimental results, which were obtained using three real-world vehicle trajectory datasets, demonstrate classification accuracy levels that range from 84 % to 91 %. It is noteworthy that these results were achieved using less than 10% of the data that is typically required for comparable accuracy levels, which highlights the efficiency of the feature extraction approach that was employed. This research contributes to the advancement of intelligent transportation systems by offering a more efficient and scalable method for road network mapping and updating. © 2024 IEEE.

关键词： Convolutional neural networks

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InGaN multiple quantum well based light-emitting diodes with indium composition gradient InGaN quantum barriers

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Optoelectronics Letters 2024年第2期20卷 89-93页

作者： SANG Xien XU Yuan YIN Mengshuang WANG Fang LIOU Juin J LIU Yuhuai National Center for International Joint Research of Electronic Materials and Systems International Joint-Laboratory of Electronic Materials and Systems of Henan ProvinceSchool of Electrical and Information EngineeringZhengzhou UniversityZhengzhou 450001China Institute of Intelligence Sensing Zhengzhou UniversityZhengzhou 450001China Research Institute of Industrial Technology Co. Ltd.Zhengzhou UniversityZhengzhou 450001China Zhengzhou Way Do Electronics Co. Ltd.Zhengzhou 450001China School of Electrical and Information Engineering North Minzu UniversityYinchuan 750001China1

To improve the internal quantum efficiency(IQE)and light output power of In Ga N light-emitting diodes(LEDs),we proposed an In-composition gradient increase and decrease In Ga N quantum barrier *** analysis of its P-I graph,carrier concentration,and energy band diagram,the results showed that when the current was 100 m A,the In-composition gradient decrease quantum barrier(QB)structure could effectively suppress electron leakage while improving hole injection efficiency,resulting in an increase in carrier concentration in the active region and an improvement in the effective recombination rate in the quantum well(QW).As a result,the IQE and output power of the LED were effectively improved.

关键词： diodes quantum gradient

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3D Nano-printed Coupler with Parabolic Reflectors

3D Nano-printed Coupler with Parabolic Reflectors

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Huang, Huiyu Shi, Zhitian Wei, Jinlong Zhong, Chuan Talli, Giuseppe Kuschnerov, Maxim Cheng, Qixiang Penty, Richard Centre for Photonic Systems Electrical Engineering Division Department of Engineering University of Cambridge United Kingdom Huawei Technologies Duesseldolf GmbH European Research Center Riesstraße 25 Duesseldolf Munich80992 Germany

We show a low-loss, broadband self-aligning structure designed for coupling standard SMF28-fibre to chip with a 50μm aligning tolerance. A coupling loss of as low as 1.6dB is measured from fiber to the polymeric stru... 详细信息

ISBN: (纸本)9781957171258

关键词： 3D printing

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Towards Augmenting Mental Health Personnel with LLM Technology to Provide More Personalized and Measurable Treatment Goals for Patients with Severe Mental Illnesses 17th

Towards Augmenting Mental Health Personnel with LLM Technol...

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17th EAI International Conference on Pervasive Computing Technologies for Healthcare, PervasiveHealth 2023

作者： James, Lorenzo J. Maessen, Maureen Genga, Laura Montagne, Barbara Hagenaars, Muriel A. Van Gorp, Pieter M. E. Industrial Engineering and Information Systems Eindhoven University of Technology Eindhoven Netherlands Treatment Center for Personality Disorders GGZ Centraal Center for Mental Health Care Disorders Amersfoort Netherlands Department of Clinical Psychology Universiteit Utrecht Utrecht Netherlands

ISBN: (纸本)9783031597169

Mobile health (mHealth) tools are increasingly being used in various mental health domains to monitor patients with Severe Mental Illnesses (SMI), with the aim of potentially increasing patient engagement with their treatment. Patients with SMI who are prescribed Flexible Assertive Community Treatment (FACT) create a treatment plan together with their case manager, which serves as the leading document describing the goals that will be worked on during treatment. In order to incorporate the treatment plan goals of a patient in an mHealth application, the treatment plan goals need to be measurable. However, in previous work, we discovered that on average, only 25% of the available treatment plans include measurable goals. We have developed a protocol for making measurable goals with patients with SMI to address this issue. However, we anticipate low adoption of the protocol due to the potentially time-consuming nature of the steps involved. To mitigate this, we are exploring the use of AI to generate measurable treatment plan goals for patients with SMI and introduce a new workflow. In our exploratory study, we created a prototype of a system that may enable case managers and patients with SMI to generate measurable treatment plan goals using Large Language Models. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering 2024.

关键词： Diseases

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A Contextualized Acceptance Model for Proactive Smart Services

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Schmalenbach Journal of Business Research 2022年第3期74卷 345-387页

作者： Graf-Drasch, Valerie Röglinger, Maximilian Wenninger, Annette Hosseini, Sabiölla Research Center Finance & Information Management Branch Business & Information Systems Engineering of the Fraunhofer FIT University of Hohenheim Schloß Hohenheim 1 Stuttgart 70599 Germany Branch Business & Information Systems Engineering of the Fraunhofer FIT Research Center Finance & Information Management University of Bayreuth Wittelsbacherring 10 Bayreuth 95444 Germany Research Center Finance & Information Management Alter Postweg 1 Augsburg 86159 Germany

Thanks to digital technologies, information about customer needs and contexts is becoming accessible ever more easily and service providers are more closely connected to customers. This development enables services to act on behalf of customers and to proactively initiate the customer interactions. Such services are so-called proactive smart services (PASS) and are a subgroup of smart services. Research suggests that service providers often face the challenge to gain customers’ acceptance of innovative services. In response to this call for action and the change in customer interaction, which can have far-reaching consequences in the lives of customers, we examined the antecedents that explain customers’ acceptance of PASS using a contextualized approach. Hence, we identified PASS-specific antecedents, developed a contextualized acceptance model (UTAUT2-PASS) while drawing from general acceptance theory, and validated it empirically. A comparison of our contextualized model with UTAUT2 as an established yet uncontextualized model confirmed the outperformance of our contextualized model. Our findings advance the academic understanding of PASS and help service providers design PASS for customer acceptance. © 2022, The Author(s).

关键词： Contextualization Factor Analysis Proactive Smart Services Technology Acceptance

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