In this paper1 we describe a novel approach to sensor network localization, i.e., two-phase algorithms based on simulated annealing and genetic algorithm. The numerical results presented and discussed in the final par...
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Wireless sensor networks (WSNs) are autonomous ad hoc networks designed and developed for potential applications in monitoring, surveillance, security, etc. The sensor devices that are battery powered should have life...
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作者：
Yang, YiWang, ZeSong, YuJia, ZiyuWang, BoyuJung, Tzyy-PingWan, FengMacau University of Science and Technology
Macao Centre for Mathematical Sciences Respiratory Disease AI Laboratory on Epidemic Intelligence and Medical Big Data Instrument Applications Faculty of Innovation Engineering 999078 China Tianjin University of Technology
School of Electrical Engineering and Automation Tianjin Key Laboratory of New Energy Power Conversion Transmission and Intelligent Control Tianjin300384 China Chinese Academy of Sciences
Beijing Key Laboratory of Brainnetome and Brain-Computer Interface and Brainnetome Center Institute of Automation Beijing100045 China Western University
Department of Computer Science Brain Mind Institute LondonONN6A 3K7 Canada University of California at San Diego
Swartz Center for Computational Neuroscience Institute for Neural Computation La Jolla CA92093 United States University of Macau
Department of Electrical and Computer Engineering Faculty of Science and Technology China University of Macau
Centre for Cognitive and Brain Sciences Centre for Artificial Intelligence and Robotics Institute of Collaborative Innovation 999078 China
Due to the inherent non-stationarity and individual differences present in electroencephalogram (EEG) signals, developing a generalizable model that performs well on new subjects is challenging in EEG-based emotion re...
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Particle filters have recently gained major attention as a powerful diagnostic tool. Their severe drawback is the computational burden closely related to the number of particles used. Therefore, it is often necessary ...
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The paper proposes a novel analysis algorithm of the control part of cyber-physical systems specified by an interpreted Petri net. In particular, the three essential properties of Petri nets are studied: boundedness, ...
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The improvement of computer image analysis techniques in recent years can support the pathologist’s work by the automation of nuclei segmentation, cell population count, computing statistics of morphological features...
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The paper tackles the problem of robust fault detection using Takagi-Sugeno fuzzy models. A model-based strategy is employed to generate residuals in order to make a decision about the state of the process. Unfortunat...
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The paper tackles the problem of robust fault detection using Takagi-Sugeno fuzzy models. A model-based strategy is employed to generate residuals in order to make a decision about the state of the process. Unfortunately, such a method is corrupted by model uncertainty due to the fact that in real applications there exists a model-reality mismatch. In order to ensure reliable fault detection the adaptive threshold technique is used to deal with the mentioned problem. The paper focuses also on fuzzy model design procedure. The bounded-error approach is applied to generating the rules for the model using available measurements. The proposed approach is applied to fault detection in the DC laboratory engine.
A method is developed to solve an optimal node activation problem in sensor networks whose measurements are supposed to be used to estimate unknown parameters of the underlying process model in the form of a partial d...
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The advent of advanced MRI techniques has opened up promising avenues for exploring the intricacies of brain neurophysiology, including the network of neural connections. A more comprehensive understanding of this net...
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The advent of advanced MRI techniques has opened up promising avenues for exploring the intricacies of brain neurophysiology, including the network of neural connections. A more comprehensive understanding of this network provides invaluable insights into the human brain’s underlying structural architecture and dynamic functionalities. Consequently, determining the location of the neural fibers, known as tractography, has emerged as a subject of significant interest to both basic scientific research and practical domains, such as preoperative planning. This work presents a novel tractography method, HyTract, constructed using artificial neural networks and a path search algorithm. Our findings demonstrate that this method can accurately identify the location of nerve fibers in close proximity to the surgical field. Compared with well established methods, tracts computed with HyTract show Mean Euclidean Distance of 9 or lower, indicating a good accuracy in tract reconstruction. Furthermore, its architecture ensures the explainability of the obtained tracts and facilitates adaptation to new tasks.
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