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On Performance Gauge of Average Multi-Cue Multi-Choice Decision Making:A Converse Lyapunov Approach

IEEE/CAA Journal of Automatica Sinica 2021年第1期8卷 136-147页

作者： Mehdi Firouznia Qing Hui the Department of Electrical and Biomedical Engineering University of VermontBurlingtonVT 05405 USA the Department of Electrical and Computer Engineering University of Nebraska-LincolnLincolnNE 68588 USA

Motivated by the converse Lyapunov technique for investigating converse results of semistable switched systems in control theory,this paper utilizes a constructive induction method to identify a cost function for performance gauge of an average,multi-cue multi-choice(MCMC),cognitive decision making model over a switching time *** shows that such a constructive cost function can be evaluated through an abstract energy called Lyapunov function at initial ***,the performance gauge problem for the average MCMC model becomes the issue of finding such a Lyapunov function,leading to a possible way for designing corresponding computational algorithms via iterative methods such as adaptive dynamic *** order to reach this goal,a series of technical results are presented for the construction of such a Lyapunov function and its mathematical properties are discussed in ***,a major result of guaranteeing the existence of such a Lyapunov function is rigorously proved.

关键词： Cognitive modeling decision making Lyapunov function multi-cue multi-choice tasks performance gauge

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Ergodic Capacity Analysis of RIS-aided System Relying on User Grouping and Fixed Power Allocation 5th

Ergodic Capacity Analysis of RIS-aided System Relying on Use...

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5th International Conference on Communication, Device and Networking, ICCDN 2021

作者： Umamaheswari, Kaveti Fazal-E-Asim Do, Dinh-Thuan Department of Computer Science and Information Engineering College of Information and Electrical Engineering Asia University Taichung41354 Taiwan Department of Tele Informatics Engineering Federal University of Cear ´a Fortaleza Brazil

ISBN: (纸本)9789811920035

In this paper, we focus on the ergodic capacity of RIS-assisted NOMA in wireless communication systems. The closed upper bound of ergodic capacity analysis is obtained for the proposed technique by using both Rayleigh and Rician fading channel environments for multiple users. Compared to simulations, numerical results demonstrate the tightness and effectiveness of our closed-form expressions. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Rayleigh fading

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Patterned graphene oxide via one-step thermal annealing for controlling collective cell migration

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Journal of Materials Chemistry B 2024年第35期12卷 8733-8745页

作者： Huang, Chien-Yu Chen, Chong-You Wei, Chia-Hung Yang, Jia-Wei Lin, Yu-Chien Kao, Chih-Fei Chung, Johnson H. Y. Chen, Guan-Yu Institute of Biomedical Engineering College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Department of Electrical and Computer Engineering College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Department of Biological Science and Technology College of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu300093 Taiwan Intelligent Polymer Research Institute Institute for Innovative Materials University of Wollongong NSW2500 Australia National Yang Ming Chiao Tung University Hsinchu300093 Taiwan

Graphene oxide (GO) is a two-dimensional metastable nanomaterial. Interestingly, GO formed oxygen clusterings in addition to oxidized and graphitic phases during the low-temperature thermal annealing process, which could be further used for biomolecule bonding. By harnessing this property of GO, we created a bio-interface with patterned structures with a common laboratory hot plate that could tune cellular behavior by physical contact. Due to the regional distribution of oxygen clustering at the interface, we refer to it as patterned annealed graphene oxide (paGO). In addition, since the paGO was a heterogeneous interface and bonded biomolecules to varying degrees, arginine-glycine-aspartic acid (RGD) was modified on it and successfully regulated cellular-directed growth and migration. Finally, we investigated the FRET phenomenon of this heterogeneous interface and found that it has potential as a biosensor. The paGO interface has the advantages of easy regulation and fabrication, and the one-step thermal reduction method is suitable for biological applications. We believe that this low-temperature thermal annealing method would make GO interfaces more accessible, especially for the development of nano-interfacial modifications for biological applications, revealing its potential for biomedical applications. © 2024 The Royal Society of Chemistry.

关键词： Biomolecules

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Simultaneous Dual-region Functional Imaging in Miniaturized Two-photon Microscopy

Simultaneous Dual-region Functional Imaging in Miniaturized ...

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Optics and the Brain, BRAIN 2024 - Part of Optica Biophotonics Congress: biomedical Optics

作者： Zhang, Zixiao Liu, Shing-Jiuan Mattison, Ben Yang, Weijian Department of Electrical and Computer Engineering University of California Davis DavisCA95616 United States Department of Biomedical Engineering University of California Davis DavisCA95616 United States Biomedical Engineering Graduate Group University of California Davis DavisCA95616 United States

We demonstrate simultaneous dual-region in-vivo imaging of brain activity in mouse cortex through a miniaturized spatial-multiplexed two-photon microscope platform, which doubles the imaging speed. Neuronal signals fr... 详细信息

ISBN: (纸本)9781957171340

关键词： Brain imaging Femtosecond lasers In vivo imaging Multiphoton microscopy Spatial resolution Ultrafast lasers

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TCLaneNet: Task-Conditioned Lane Detection Network Driven by Vibration Information

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年第9期9卷 1-14页

作者： Gong, Yan Jiang, Xinmin Wang, Lu Xu, Lisheng Lu, Jianli Liu, Hao Lin, Lei Zhang, Xinyu School of Computer Science and Engineering Northeastern University Shenyang China College of Medicine and Biomedical Information Engineering Northeastern University Shenyang China School of Vehicle and Mobility Tsinghua University Beijing China Autonomous Driving Department of X Divsion JD Logistics Beijing China Department of Artificial Intelligence School of Informatics Xiamen University Xiamen China

Lane detection is an important task in autonomous driving. However, it poses great challenges in occlusion and low-light conditions. To deal with these problems, we propose to utilize the vibration signals generated when vehicles pass over the vibration marking lines as supervision for lane occlusion prediction, whose features are then used to adaptively adjust the weights of lane detection network to improve its performance. Specifically, we develop a Task-Conditioned Lane Detection Network (TCLaneNet) that consists of the main lane detection branch and an lane occlusion classification branch. To effectively refine the lane detection features, Conditioned Adaptation Modules (CAMs) are proposed to obtain the conditioned parameters (i.e., channel weights) from the feature embedding of the lane occlusion classification task to adjust the lane detection features. In addition, as lane lines are elongated, while the receptive field of the convolution operation is spatially limited, we propose a Contextual Spatial Information Attention Module (CSIAM) to capture the global shape features of the lanes. Substantial experiments have been carried out on a vibration-based lane detection dataset VBLane that we constructed. The dataset consists of synchronously collected visual images and vibration signals, as well as the labels for the lane lines. Experimental results show that the proposed TCLaneNet achieves an Intersection over Union of 94.29%, which is better than the state-of-the-art lane detection methods. In addition, the TCLaneNet is lightweight (0.84 M) and runs in real-time (43.44 FPS), and the vibration information is not needed in the inference phase. Code and data at available on https://***/gongyan1/TCLaneNet. IEEE

关键词： Feature extraction

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Fully Unsupervised Deep-Learning with Dimension Expansion for Nanophotonic Design

Fully Unsupervised Deep-Learning with Dimension Expansion fo...

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2024 Frontiers in Optics, FiO 2024

作者： Huang, Shuo Torfeh, Mahsa Shi, Yonggang Hsu, Chia Wei Stevens Neuroimaging and Informatics Institute University of Southern California Los AngelesCA90033 United States Department of Biomedical Engineering University of Southern California Los AngelesCA90089 United States Department of Electrical and Computer Engineering University of Southern California Los AngelesCA90089 United States

We propose a fully unsupervised deep-learning approach using dimension expansion for nanophotonic design. The neural network generates binary broadband integrated Y-splitters with average efficiency 98% and splitting error 2%, without any pre-generated dataset. © Optica Publishing Group 2024, © 2024 The Author(s)

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Time-Multiplexed Miniaturized Two-Photon Microscopy

Time-Multiplexed Miniaturized Two-Photon Microscopy

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Optics and the Brain, BRAIN 2024 - Part of Optica Biophotonics Congress: biomedical Optics

作者： Liu, Shing-Jiuan Zhang, Zixiao Mattison, Ben Yang, Weijian Department of Electrical and Computer Engineering University of California Davis DavisCA95616 United States Department of Biomedical Engineering University of California Davis DavisCA95616 United States Biomedical Engineering Graduate Group University of California Davis DavisCA95616 United States

We propose a time-multiplexed miniaturized two-photon microscope (TM-MINI2P), enabling a two-fold increase in imaging speed while maintaining a high spatial resolution. Using TM-MINI2P, we conducted high-speed in-vivo... 详细信息

ISBN: (纸本)9781957171340

关键词： Two photon processes

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Resolution enhancement with deblurring by pixel reassignment

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Advanced Photonics 2023年第6期5卷 59-71页

作者： Bingying Zhao Jerome Mertz Boston University Department of Electrical and Computer EngineeringBostonMassachusettsUnited States Boston University Department of Biomedical EngineeringBostonMassachusettsUnited States

Improving the spatial resolution of a fluorescence microscope has been an ongoing challenge in the imaging *** address this challenge,a variety of approaches have been taken,ranging from instrumentation development to image *** example of the latter is deconvolution,where images are numerically deblurred based on a knowledge of the microscope point spread ***,deconvolution can easily lead to noise-amplification *** by postprocessing can also lead to negativities or fail to conserve local linearity between sample and *** describe here a simple image deblurring algorithm based on pixel reassignment that inherently avoids such artifacts and can be applied to general microscope modalities and fluorophore *** algorithm helps distinguish nearby fluorophores,even when these are separated by distances smaller than the conventional resolution limit,helping facilitate,for example,the application of single-molecule localization microscopy in dense *** demonstrate the versatility and performance of our algorithm under a variety of imaging conditions.

关键词： image deblurring microscopy bio-imaging image reconstruction optical resolution

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Open-Source Online Mission-Planning in Emergent Environments with PDDL for Multi-robot Applications 13th

Open-Source Online Mission-Planning in Emergent Environments...

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13th Mining Humanistic Data Workshop, MHDW 2024, 9th Workshop on 5G-Putting Intelligence to the Network Edge, 5G-PINE 2024 and 1st Workshop on AI in Applications for Achieving the Green Deal Targets, AI4GD 2024 held as parallel events of the IFIP WG 12.5 International Workshops on Artificial Intelligence Applications and Innovations, AIAI 2024

作者： Michailidis, Iakovos T. Michailidis, Panagiotis Kosmatopoulos, Elias Bassiliades, Nick Information Technologies Institute Thessaloniki Greece Department of Electrical and Computer Engineering Democritus University of Thrace Xanthi Greece School of Informatics Aristotle University of Thessaloniki Thessaloniki Greece

ISBN: (纸本)9783031632266

The current study focuses on the development of an open-source framework which is outsourcing the lack of expressivity of the standardized Planning Domain Definition Language – PDDL, leveraging the capacity and flexibility of the hosting environment in Python 3.8. The implementation was based on the definition and logic of a PDDL domain modeling an object stacking/collecting problem, in specified order and locations, by a fleet of autonomous synergetic vehicles by a centralized management agent. A PDDL-parser was utilized to instantiate the solver. Random changes were imposed in the fully-observable environment during mission execution. The proposed framework considered dynamic replanning of the currently valid mission, every time the state space – and consequently the corresponding state graph representation – is stochastically changed. Appropriate test scenarios were defined, to validate the capacity of the implemented framework and establish that it could serve as an interoperable and extensible foundation for other add-ons and graph-searching tools. The evidence from the simulation results indicates the speed and flexibility of the implemented environment for emulating the dynamic replanning problems in highly emergent scenario cases where the state space changes stochastically. © IFIP International Federation for Information Processing 2024.

关键词： Autonomous agents

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Machine Learning Prediction Models of Optimal Time for Aortic Valve Replacement in Asymptomatic Patients

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Intelligent Automation & Soft Computing 2023年第7期37卷 455-470页

作者： Salah Alzghoul Othman Smadi Ali Al Bataineh Mamon Hatmal Ahmad Alamm Biomedical Engineering Department The Hashemite UniversityZarqaJordan Department of Electrical and Computer Engineering Norwich UniversityNorthfieldVermont05663USA Department of Biochemistry and Molecular Biology The Hashemite UniversityZarqaJordan National Centre for Big Data Science and Artificial Intelligence AmmanJordan

Currently,the decision of aortic valve replacement surgery time for asymptomatic patients with moderate-to-severe aortic stenosis(AS)is made by healthcare professionals based on the patient’s clinical biometric records.A delay in surgical aortic valve replacement(SAVR)can potentially affect patients’quality of *** using ML algorithms,this study aims to predict the optimal SAVR timing and determine the enhancement in moderate-to-severe AS patient survival following *** study represents a novel approach that has the potential to improve decision-making and,ultimately,improve patient *** analyze data from 176 patients with moderate-to-severe aortic stenosis who had undergone or were indicated for *** divide the data into two groups:those who died within the first year after SAVR and those who survived for more than one year or were still alive at the last *** then use six different ML algorithms,Support Vector Machine(SVM),Classification and Regression Tree(C and R tree),Generalized Linear(GL),Chi-Square Automatic Interaction Detector(CHAID),Artificial Neural Net-work(ANN),and Linear Regression(LR),to generate predictions for the best timing for *** results showed that the SVM algorithm is the best model for predicting the optimal timing for SAVR and for predicting the post-surgery survival *** optimizing the timing of SAVR surgery using the SVM algorithm,we observed a significant improvement in the survival period after *** study demonstrates that ML algorithms generate reliable models for predicting the optimal timing of SAVR in asymptomatic patients with moderate-to-severe AS.

关键词： Aortic stenosis aortic valve replacement machine learning survival period enhancement artificial intelligence in cardiology

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