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International Conference on BioMedical engineering and informatics (BMEI)

作者： Yang Yang Kelvin Weng Chiong Foong Sim Heng Ong Masakazu Yagi Kenji Takada Graduate School for Integrative Sciences and Engineering Faculty of Dentistry National University of Singapore Singapore Graduate School for Integrative Sciences and Engineering 3Department of Electrical and Computer Engineering National University of Singapore Singapore Singapore Department of Orthodontics and Dentofacial Orthopedics Graduate School of Dentistry Osaka University Osaka Japan The Center for Advance Medical Engineering and Informatics Osaka University Osaka Japan

Current methods that evaluate the functions of masseter muscles (MM) are not suited to fully describing their functional roles. The aim of this study was to develop a method to quantify the deformations of MM in simulated mandibular movements for individual study. A normal adult male subject underwent magnetic resonance (MR) scans of the head at four mandibular positions: mandibular rest (M0), maximum intercuspation (M1), medium jaw-opened (M2), and maximum jaw-opened (M3) positions. The muscle models of the subject were reconstructed from the four sets of MR images, and the deformations of the MM in the three cases, i.e., from M0 to M1, from M0 to M2 and from M2 to M3, were quantified in terms of the displacements of region correspondences between the muscle models before and after the mandibular position changed. The functional activities along the entire body and at specific anatomic compartments of the subject-specific MM were quantified and visualized using the quantified deformation fields. The directions of the active and positive muscle tensions during the simulated mandibular movements were indicated by the resultant directions of the deformations, respectively. The proposed method revealed the anatomic architectural and biomechanical characteristics of the subject-specific MM appropriately and meaningfully in the simulated mandibular movements.

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Matching-based Hybrid Service Trading for Task Assignment over Dynamic Mobile Crowdsensing Networks

arXiv

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arXiv 2023年

作者： Qi, Houyi Liwang, Minghui Hosseinalipour, Seyyedali Xia, Xiaoyu Cheng, Zhipeng Wang, Xianbin Jiao, Zhenzhen The School of Informatics Xiamen University Fujian China Department of Electrical Engineering University at Buffalo-SUNY NY United States The School of Computing Technologies RMIT University MelbourneVIC Australia The School of Future Science and Engineering Soochow University Jiangsu China The Department of Electrical and Computer Engineering Western University ON Canada The iF-Labs Beijing Teleinfo Technology Co. Ltd. CAICT China

By opportunistically engaging mobile users (workers), mobile crowdsensing (MCS) networks have emerged as important approach to facilitate sharing of sensed/gathered data of heterogeneous mobile devices. To assign tasks among workers and ensure low overheads, we introduce a series of stable matching mechanisms, which are integrated into a novel hybrid service trading paradigm consisting of futures trading and spot trading modes, to ensure seamless MCS service provisioning. In futures trading, we determine a set of long-term workers for each task through an overbooking-enabled in-advance many-to-many matching (OIA3M) mechanism, while characterizing the associated risks under statistical analysis. In spot trading, we investigate the impact of fluctuations in long-term workers’ resources on the violation of service quality requirements of tasks, and formalize a spot trading mode for tasks with violated service quality requirements under practical budget constraints, where the task-worker mapping is carried out via onsite many-to-many matching (O3M) and onsite many-to-one matching (OMOM). We theoretically show that our proposed matching mechanisms satisfy stability, individual rationality, fairness, and computational efficiency. Comprehensive evaluations confirm the satisfaction of these properties in practical network settings and demonstrate our commendable performance in terms of service quality, running time, and decision-making overheads, e.g., delay and energy consumption. Copyright © 2023, The Authors. All rights reserved.

关键词： Computational efficiency

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The role of input imaging combination and ADC threshold on segmentation of acute ischemic stroke lesion using U-Net

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European Radiology 2023年第9期33卷 6157-6167页

作者： Li, Ya-Hui Lin, Shao-Chieh Chung, Hsiao-Wen Chang, Chia-Ching Peng, Hsu-Hsia Huang, Teng-Yi Shen, Wu-Chung Tsai, Chon-Haw Lo, Yu-Chien Lee, Tung-Yang Juan, Cheng-Hsuan Juan, Cheng-En Chang, Hing-Chiu Liu, Yi-Jui Juan, Chun-Jung Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan Department of Medical Imaging China Medical University Hsinchu Hospital No. 199 Sec. 1 Xinglong Rd. Zhubei City Hsinchu County 302 Hsinchu Taiwan Ph.D. Program in Electrical and Communication Engineering Feng Chia University Taichung Taiwan Department of Electrical Engineering National Taiwan University Taipei Taiwan Department of Management Science National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Biomedical Engineering and Environmental Sciences National Tsing Hua University Hsinchu Taiwan Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Radiology School of Medicine College of Medicine China Medical University Taichung Taiwan Department of Medical Imaging Medical University Hospital Taichung Taiwan Department of Neurology China Medical University Hospital Taichung Taiwan Cheng Ching Hospital Taichung Taiwan Master’s Program of Biomedical Informatics and Biomedical Engineering Feng Chia University Taichung Taiwan Department of Automatic Control Engineering Feng Chia University No. 100 Wenhwa Rd. Seatwen Taichung 40724 Taiwan Department of Biomedical Engineering The Chinese University of Hong Kong ERB1112 11/F William M.W. Mong Engineering Building N.T Shatin Hong Kong Multi-Scale Medical Robotics Center The Chinese University of Hong Kong N.T Shatin Hong Kong Department of Biomedical Engineering National Defense Medical Center Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan

Background: To evaluate the effect of the weighting of input imaging combo and ADC threshold on the performance of the U-Net and to find an optimized input imaging combo and ADC threshold in segmenting acute ischemic stroke (AIS) lesion. Methods: This study retrospectively enrolled a total of 212 patients having AIS. Four combos, including ADC-ADC-ADC (AAA), DWI-ADC-ADC (DAA), DWI-DWI-ADC (DDA), and DWI-DWI-DWI (DDD), were used as input images, respectively. Three ADC thresholds including 0.6, 0.8 and 1.8 × 10^–3 mm²/s were applied. Dice similarity coefficient (DSC) was used to evaluate the segmentation performance of U-Nets. Nonparametric Kruskal–Wallis test with Tukey–Kramer post-hoc tests were used for comparison. A p <.05 was considered statistically significant. Results: The DSC significantly varied among different combos of images and different ADC thresholds. Hybrid U-Nets outperformed uniform U-Nets at ADC thresholds of 0.6 × 10^–3 mm²/s and 0.8 × 10^–3 mm²/s (p <.001). The U-Net with imaging combo of DDD had segmentation performance similar to hybrid U-Nets at an ADC threshold of 1.8 × 10^–3 mm²/s (p =.062 to 1). The U-Net using the imaging combo of DAA at the ADC threshold of 0.6 × 10^–3 mm²/s achieved the highest DSC in the segmentation of AIS lesion. Conclusions: The segmentation performance of U-Net for AIS varies among the input imaging combos and ADC thresholds. The U-Net is optimized by choosing the imaging combo of DAA at an ADC threshold of 0.6 × 10^–3 mm²/s in segmentating AIS lesion with highest DSC. Key Points: • Segmentation performance of U-Net for AIS differs among input imaging combos. • Segmentation performance of U-Net for AIS differs among ADC thresholds. • U-Net is optimized using DAA with ADC = 0.6 × 10^–3mm²/s. © 2023, The Author(s), under exclusive licence to European Society of Radiology.

关键词： Deep Learning Diffusion Magnetic Resonance Imaging Ischemic Stroke Neural Networks, computer Retrospective Study

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A novel rigid object segmentation method based on multiresolution 3-D motion and luminance analysis

A novel rigid object segmentation method based on multiresol...

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IEEE International Conference on Image Processing

作者： T. Papadimitriou K.I. Diamantaras M.G. Strintzis M. Roumeliotis Educational Technology Laboratory University of Macedonia Thessaloniki Greece Department of Informatics Technological Educational Institute of Thessaloniki Sindos Greece Information Processing Laboratory Department Electrical and Computer Engineering Aristotle University of Thessaloniki Thessaloniki Greece Department Applied Informatics University of Macedonia Thessaloniki Greece

ISBN: (纸本)0780362977

We present a new image sequence segmentation method which combines both spatial and temporal information in a multiresolution framework. A region growing technique in a multiresolution scheme outputs an over-segmented partition of the image scene. Pure temporal information is collected for each region using a feature extraction/feature tracking technique. Motion information is further processed in a pyramidal robust motion estimation scheme, in order to calculate more complex motion parameters for each region. Regions obtained from the first step are clustered according to their motion models. This ensures that rigid objects with luminance discontinuities can be segmented correctly. The method has been successfully tested in real imagery and typical examples are presented.

关键词： Object segmentation Spatial resolution Image segmentation Image resolution Feature extraction Image sequences Layout Robustness Motion estimation Testing

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ROBUST STABILITY CHECKING OF A CLASS OF LINEAR INTERVAL FRACTIONAL ORDER SYSTEM USING LYAPUNOV INEQUALITY

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IFAC Proceedings Volumes 2006年第11期39卷 89-94页

作者： Hyosung Ahn YangQuan Chen Igor Podlubny Center for Self-Organizing and Intelligent Systems (CSOIS) Department of Electrical and Computer Engineering Utah State University Logan UT 84322-4160 USA Department of Applied Informatics and Process Control Technical University of Kosice B. Nemcovej 3 04200 Kosice Slovak Republic

This paper provides a new analytical robust stability checking method of fractional-order linear time invariant interval uncertain system. This paper continues the authors’ previous work (Chen et al., 2005a) where matrix perturbation theory was used. For the new robust stability checking, Lyapunov inequality is utilized for finding the maximum eigenvalue of a Hermitian matrix. Through numerical examples, the usefulness and the effectiveness of the newly proposed method are verified.

关键词： Fractional order linear dynamic systems robust stability interval linear time invariant systems interval matrix

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Decoder choice network for meta-learning

arXiv

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arXiv 2019年

作者： Liu, Jialin Chao, Fei Yang, Longzhi Lin, Chih-Min Shen, Qiang Department of Artificial Intelligence School of Informatics Xiamen University China Department of Computer and Information Sciences Northumbria University United Kingdom Department of Electrical Engineering Yuan Ze University Taiwan Institute of Mathematics Physics and Computer Science Aberystwyth University United Kingdom

Meta-learning has been widely used for implementing few-shot learning and fast model adaptation. One kind of meta-learning methods attempt to learn how to control the gradient descent process in order to make the gradient-based learning have high speed and generalization. This work proposes a method that controls the gradient descent process of the model parameters of a neural network by limiting the model parameters in a low-dimensional latent space. The main challenge of this idea is that a decoder with too many parameters is required. This work designs a decoder with typical structure and shares a part of weights in the decoder to reduce the number of the required parameters. Besides, this work has introduced ensemble learning to work with the proposed approach for improving performance. The results show that the proposed approach is witnessed by the superior performance over the Omniglot classification and the miniImageNet classification tasks. Copyright © 2019, The Authors. All rights reserved.

关键词： Gradient methods

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Niche-clearing-based Variable Mesh Optimization for multimodal problems

Niche-clearing-based Variable Mesh Optimization for multimod...

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World Congress on Nature & Biologically Inspired Computing (NaBIC)

作者： Ricardo Navarro Rafael Falcon Rafael Bello Ajith Abraham Department of Informatics University of Holguin Holguin Cuba Department of Computer Science Central University of Las Villas Santa Clara Cuba Electrical Engineering & Computer Science University of Ottawa Ottawa Canada Vysoka Skola Banska-Technicka Univerzita Ostrava Ostrava CZ

The development of niching methods is a very active research area within multimodal optimization. It includes not only the creation of new methods, but the formalization of hybrid methodologies resulting from the application of basic niching techniques to global optimization metaheuristics. In this paper, we discuss some preliminary results of a recently proposed metaheuristic algorithm, Variable Mesh Optimization (VMO), in the context of multimodal problems. To overcome some of the encountered limitations, a revamped version called Niche-Clearing-based Variable Mesh Optimization (NC-VMO) is put forth. NC-VMO demonstrated its ability to optimize multimodal functions by using a niche clearing technique. Experimental results confirm that the proposed approach is also competitive with other niche-based optimization methods in the literature.

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Clinical Feasibility of Coherence-Based Beamforming to Distinguish Solid from Fluid Hypoechoic Breast Masses

Clinical Feasibility of Coherence-Based Beamforming to Disti...

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IEEE Symposium (IUS) Ultrasonics

作者： Alycen Wiacek Eniola Falomo Kelly Myers Ole Marius Hoel Rindal Kelly Fabrega-Foster Susan Harvey Muyinatu A. Lediju Bell Department of Electrical and Computer Engineering Johns Hopkins University Baltimore MD Department of Radiology and Radiological Science Johns Hopkins Medicine Baltimore MD Department of Informatics University of Oslo Oslo Norway Department of Computer Science Johns Hopkins University Baltimore MD

Ultrasound imaging is often used in conjunction with mammography, particularly for patients with dense breast tissue, which causes an increased amount of acoustic clutter, obscuring lesions of interest, and contributing to the false positive rate of breast ultrasound. Coherence-based imaging methods, such as short-lag spatial coherence (SLSC) and robust short-lag spatial coherence (R-SLSC), display the coherence of backscattered ultrasound signals instead of their amplitude or brightness information, which offers opportunities to reduce acoustic clutter. This paper focuses on SLSC and R-SLSC beamforming applied to three in vivo masses in the female breast: (1) cyst, (2) fibroadenoma, and (3) ductal carcinoma in situ (DCIS). Contrast is improved by up to 7.8 dB with SLSC imaging and 4.86 dB with R-SLSC imaging in fluid-filled regions. However, contrast is degraded in coherence-based images of solid hypoechoic lesions because coherence is displayed in these regions with pathologically determined solid content. This interesting finding indicates the potential of coherence-based imaging to assist with the differentiation between solid and fluid-filled hypoechoic breast masses. Examples of duplex mode B-mode and R-SLSC images are shown to convey clinical potential.

关键词： Coherence Breast Imaging Solids Ultrasonic imaging Signal to noise ratio Array signal processing

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Collaborative Authentication for 6G Networks: An Edge Intelligence based Autonomous Approach

arXiv

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arXiv 2023年

作者： Fang, He Xiao, Zhenlong Wang, Xianbin Xu, Li Hanzo, Lajos The School of Electronic and Information Engineering Soochow University Soochow215301 China The Department of Informatics and Communication Engineering School of Informatics Xiamen University Xiamen361005 China The Department of Electrical and Computer Engineering Western University LondonONN6A 5B9 Canada The College of Computer and Cyber Security The Fujian Provincial Key Laboratory of Network Security and Cryptology Fujian Normal University Fuzhou350117 China School of Electronics and Computer Science University of Southampton SO17 1BJ United Kingdom

The conventional device authentication of wireless networks usually relies on a security server and centralized process, leading to long latency and risk of single-point of failure. While these challenges might be mitigated by collaborative authentication schemes, their performance remains limited by the rigidity of data collection and aggregated result. They also tend to ignore attacker localization in the collaborative authentication process. To overcome these challenges, a novel collaborative authentication scheme is proposed, where multiple edge devices act as cooperative peers to assist the service provider in distributively authenticating its users by estimating their received signal strength indicator (RSSI) and mobility trajectory (TRA). More explicitly, a distributed learning-based collaborative authentication algorithm is conceived, where the cooperative peers update their authentication models locally, thus the network congestion and response time remain low. Moreover, a situation-aware secure group update algorithm is proposed for autonomously refreshing the set of cooperative peers in the dynamic environment. We also develop an algorithm for localizing a malicious user by the cooperative peers once it is identified. The simulation results demonstrate that the proposed scheme is eminently suitable for both indoor and outdoor communication scenarios, and outperforms some existing benchmark schemes. Copyright © 2023, The Authors. All rights reserved.

关键词： Authentication

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Tackling heavy-tailed noise in distributed estimation: Asymptotic performance and tradeoffs

Tackling heavy-tailed noise in distributed estimation: Asymp...

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Telecommunications Forum (TELFOR)

作者： Dragana Bajovic Dusan Jakovetic Soummya Kar Manojlo Vukovic Department of Power Electronic and Communication Engineering Faculty of Technical Sciences University of Novi Sad Department of Mathematics and Informatics Faculty of Sciences University of Novi Sad Department of Electrical and Computer Engineering Carnegie Mellon University Department of Fundamental Sciences Faculty of Technical Sciences University of Novi Sad

ISBN: (数字)9798350391060

ISBN: (纸本)9798350391077

We present an algorithm for distributed estimation of an unknown vector parameter θ ∗ ∈ ℝ M in the presence of heavy-tailed observation and communication noises. Heavy-tailed noises frequently appear, e.g., in densely deployed Internet of Things (IoT) or wireless sensor network systems. The presented algorithm falls within the class of consensus+innovation estimators and combats the effect of the heavy-tailed noises by adding general nonlinearities in the consensus and innovations update parts. We present results on almost sure convergence and asymptotic normality of the estimator. In addition, we provide novel analytical studies that reveal interesting tradeoffs between the system noises and the underlying network topology.

关键词： Technological innovation Wireless sensor networks Heavily-tailed distribution Network topology Noise Estimation Vectors Telecommunications Internet of Things Convergence

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