检索结果-内蒙古大学图书馆

Development of an Adaptive Artifact Subspace Reconstruction Based on Hebbian/Anti-Hebbian Learning Networks for Enhancing BCI Performance

引用

IEEE Transactions on Neural Networks and Learning Systems 2024年第1期35卷 348-361页

作者： Tsai, Bo-Yu Diddi, Sandeep Vara Sankar Ko, Li-Wei Wang, Shuu-Jiun Chang, Chi-Yuan Jung, Tzyy-Ping Institute of Biomedical Engineering and the Brain Research Center National Yang Ming Chiao Tung University Hsinchu300 Taiwan Hsinchu300 Taiwan College of Biological Science and Technology National Yang Ming Chiao Tung University Hsinchu300 Taiwan Institute of Electrical and Control Engineering Institute of Biomedical Engineering Brain Research Center College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Department of Electronics and Electrical Engineering Hsinchu300 Taiwan Kaohsiung Medical University Department of Biomedical Science and Environment Biology Drug Development and Value Creation Research Center Kaohsiung807 Taiwan Taipei Veterans General Hospital Taipei11217 Taiwan National Yang Ming Chiao Tung University Brain Research Center School of Medicine Taipei112 Taiwan University of California San Diego Swartz Center for Computational Neuroscience San DiegoCA92093 United States

Brain-computer interface (BCI) actively translates the brain signals into executable actions by establishing direct communication between the human brain and external devices. Recording brain activity through electroencephalography (EEG) is generally contaminated with both physiological and nonphysiological artifacts, which significantly hinders the BCI performance. Artifact subspace reconstruction (ASR) is a well-known statistical technique that automatically removes artifact components by determining the rejection threshold based on the initial reference EEG segment in multichannel EEG recordings. In real-world applications, the fixed threshold may limit the efficacy of the artifact correction, especially when the quality of the reference data is poor. This study proposes an adaptive online ASR technique by integrating the Hebbian/anti-Hebbian neural networks into the ASR algorithm, namely, principle subspace projection ASR (PSP-ASR) and principal subspace whitening ASR (PSW-ASR) that segmentwise self-organize the artifact subspace by updating the synaptic weights according to the Hebbian and anti-Hebbian learning rules. The effectiveness of the proposed algorithm is compared to the conventional ASR approaches on benchmark EEG dataset and three BCI frameworks, including steady-state visual evoked potential (SSVEP), rapid serial visual presentation (RSVP), and motor imagery (MI) by evaluating the root-mean-square error (RMSE), the signal-to-noise ratio (SNR), the Pearson correlation, and classification accuracy. The results demonstrated that the PSW-ASR algorithm effectively removed the EEG artifacts and retained the activity-specific brain signals compared to the PSP-ASR, standard ASR (Init-ASR), and moving-window ASR (MW-ASR) methods, thereby enhancing the SSVEP, RSVP, and MI BCI performances. Finally, our empirical results from the PSW-ASR algorithm suggested the choice of an aggressive cutoff range of c =1-10 for activity-specific BCI applications and a moderat

关键词： Electroencephalography

来源：评论

学校读者我要写书评

暂无评论

Navigable Areas Segmentation Method for Unmanned Surface Vehicles in Paddy Fields 11

Navigable Areas Segmentation Method for Unmanned Surface Veh...

引用

11th IEEE Region 10 Humanitarian Technology Conference, R10-HTC 2023

作者： Machida, Kentaro Nakamura, Tetsuya Cai, Jingyong Nguyen-Quang, Thinh Pham, Duc Anh Huy-Dung, Han Nguyen, Huy Hoang Ookawa, Taiichiro Nakajo, Hironori Tokyo University of Agriculture and Technology Dept. of Electrical Engineering and Computer Science Tokyo Japan Yukimai Design Co. Ltd. Tokyo Japan School of Electrical and Electronic Engineering Hanoi University of Science and Technology Hanoi Viet Nam Tokyo University of Agriculture and Technology Dept. of Biological Production Tokyo Japan

ISBN: (纸本)9798350326147

An Unmanned Surface Vehicle (USV) capable of automatic navigation in paddy fields could enhance paddy rice cultivation efficiency. However, flexible navigation is challenging with rule-based methods. This study introduce a deep neural network-based navigable area binary segmentation method, utilizing images from a front camera mounted on a USV. Evaluation with a newly created dataset confirmed that this method could flexibly segment navigable areas, even in rice fields where rule-based methods struggle. © 2023 IEEE.

关键词： Unmanned surface vehicles

来源：评论

学校读者我要写书评

暂无评论

A Study on Intelligent Optical Bone Densitometry

引用

IEEE Journal of Translational engineering in Health and Medicine 2024年 12卷 401-412页

作者： Meitei, Takhellambam Gautam Chang, Wei-Chun Cheong, Pou-Leng Wang, Yi-Min Sun, Chia-Wei Taipei Medical University Wan Fang Hospital Department of Orthopedic Surgery Taipei110 Taiwan National Yang Ming Chiao Tung University College of Electrical and Computer Engineering Department of Photonics Hsinchu30010 Taiwan National Yang Ming Chiao Tung University Department of Biological Science and Technology Hsinchu30010 Taiwan National Taiwan University Hospital Hsinchu Branch Department of Pediatrics Hsinchu300 Taiwan Institute of Biomedical Engineering College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu30010 Taiwan National Yang Ming Chiao Tung University Medical Device Innovation and Translation Center Taipei City112 Taiwan

Osteoporosis is a prevalent chronic disease worldwide, particularly affecting the aging population. The gold standard diagnostic tool for osteoporosis is Dual-energy X-ray Absorptiometry (DXA). However, the expensive cost of the DXA machine and the need for skilled professionals to operate it restrict its accessibility to the general public. This paper builds upon previous research and proposes a novel approach for rapidly screening bone density. The method involves utilizing near-infrared light to capture local body information within the human body. Deep learning techniques are employed to analyze the obtained data and extract meaningful insights related to bone density. Our initial prediction, utilizing multi-linear regression, demonstrated a strong correlation (r = 0.98, p-value = 0.003∗∗) with the measured Bone Mineral Density (BMD) obtained from Dual-energy X-ray Absorptiometry (DXA). This indicates a highly significant relationship between the predicted values and the actual BMD measurements. A deep learning-based algorithm is applied to analyze the underlying information further to predict bone density at the wrist, hip, and spine. The prediction of bone densities in the hip and spine holds significant importance due to their status as gold-standard sites for assessing an individual's bone density. Our prediction rate had an error margin below 10% for the wrist and below 20% for the hip and spine bone density. © 2013 IEEE.

关键词： Bone

来源：评论

学校读者我要写书评

暂无评论

Automated Detection of Poultry Farms from Aerial Images for Actionable AI System toward Biosecurity Applications

Automated Detection of Poultry Farms from Aerial Images for ...

引用

2023 IEEE Applied Imagery Pattern Recognition Workshop, AIPR 2023

作者： Li, Yu Das, Rana Duong, Cuong Lim, Teng-Teeh Haithcoat, Timothy Ersoy, Ilker Shyu, Chi-Ren University of Missouri Department of Electrical Engineering and Computer Science ColumbiaMO United States University of Missouri Biological Engineering ColumbiaMO United States University of Missouri Plant Science and Technology Extension ColumbiaMO United States University of Missouri Institute for Data Science and Informatics Columbia United States University of Missouri Institute for Data Science and Informatics Electrical Eng. and Computer Science Dept. ColumbiaMO United States

ISBN: (纸本)9798350359527

Poultry productions have shifted towards larger farms and often cluster in certain regions. However, many of the smaller farms with a considerable amount of production are not considered concentrated animal feeding operation under regulation in many regions, and therefore are not required to obtain a permit. As a result, information of these operations is not being recorded and monitored, contributing to an increased risk for biosecurity issues. The development in computer vision and availability of high-resolution remote sensing imagery allows the possibility for automatic localization and operation estimation of the unregistered farms, filling in the missing information needed for biosecurity risk management. The farm information extracted from images can be incorporated with other available geospatial data, such as road networks, watersheds, etc., to build a comprehensive knowledge base for actionable plans. In the current study, we present a framework for automated localization, analysis, and visualization of poultry farms from remote sensing images. A robust machine learning method was developed to computationally link the visual features from remote sensing imagery to Missouri Department of Natural Resources Concentrated Animal Feeding Operation data, to identify the animal farm type, location, and potential capacity in the region. The developed process can be performed automatically on images of different timestamps to analyze temporal and spatial development of poultry production facilities of a region. This research contributes to the effective management and regulation of poultry and potentially other animal farms, providing insights into farm characteristics and capacities while facilitating informed decision-making. © 2023 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Stretchable Electronics Fabrication Techniques for Wearable Glove Sensors using Encapsulated Liquid Metal Paste

Stretchable Electronics Fabrication Techniques for Wearable ...

引用

2022 Opportunity Research Scholars Symposium, ORSS 2022

作者： Hasler, Abigail Votzke, Callen Wilson, Calder Lam, Shirley Kim, Jinyong Johnston, Matthew L. Oregon State University School of Chemical Biological and Environmental Engineering CorvallisOR United States Oregon State University School of Electrical Engineering and Computer Science CorvallisOR United States

ISBN: (纸本)9781665468985

Stretchable electronic circuits and systems will be critical for future wearable devices and smart textiles, where existing printed circuit board (PCB) fabrication approaches severely limit conformal deformation. This is especially true for wearable sensors and actuators for the Internet-of-Things and conformable electronic skins and textiles, all critical for emerging physical human-machine interfaces. This study explores materials and methods for the fabrication of wearable glove sensors using liquid metal paste encapsulated in silicone. Both stencil printing and free-form application are employed along with multiple casting methods, and glove sensors are demonstrated with electronic readout for measuring finger movement. © 2022 IEEE.

关键词： Liquid metals

来源：评论

学校读者我要写书评

暂无评论

Validation of biologically Inspired Tactics to Increase Multi-Agent System Resilience

IEEE Open Journal of Systems Engineering

引用

IEEE Open Journal of Systems engineering 2023年 1卷 164-178页

作者： Watson, Bryan C. Hernandez, Isabella V. Weissburg, Marc J. Bras, Bert Embry-Riddle Aeronautical University Electrical Engineering and Computer Science Department Daytona BeachFL32114 United States Georgia Institute of Technology School of Mechanical Engineering AtlantaGA30332 United States Georgia Institute of Technology School of Civil Engineering AtlantaGA30332 United States Georgia Institute of Technology School of Biological Sciences AtlantaGA30332 United States

There is an urgent need to increase multi-agent systems' resilience. Efforts, however, are hampered by three gaps: current approaches are case study specific, may depend on infrastructure investment, and are often unshared. In response to these needs, we propose 14 biologically inspired Tactics for individual agent design and communication protocols. The Tactics are generalizable and do not depend upon infrastructure investments. The Tactics are applied to a hybrid system dynamic and agent-based model of an electric motor manufacturing supply chain case study. The approach for applying each of the Tactics is clearly described to support future application. Tactic use successfully increased resilience by an average of 6.6%. By reporting a context-neutral solution approach to increase resilience, focusing on agent intervention, and clearly reporting the implementation to a supply chain case study, this article takes an important step toward our goal of using biologically inspired design to increase multi-agent system resilience. © 2023 CCBY.

关键词： Supply chains

来源：评论

学校读者我要写书评

暂无评论

An information-theoretic lower bound in time-uniform estimation

arXiv

引用

arXiv 2024年

作者： Duchi, John C. Haque, Saminul Departments of Statistics and Electrical Engineering Stanford University United States Department of Computer Science Stanford University United States

We present an information-theoretic lower bound for the problem of parameter estimation with time-uniform coverage guarantees. Via a new a reduction to sequential testing, we obtain stronger lower bounds that capture the hardness of the time-uniform setting. In the case of location model estimation, logistic regression, and exponential family models, our Ω(Formula Presented) lower bound is sharp to within constant factors in typical settings. © 2024, CC BY.

关键词： Information theory

来源：评论

学校读者我要写书评

暂无评论

Invertibility of Discrete-Time Linear Systems with Sparse Inputs

Invertibility of Discrete-Time Linear Systems with Sparse In...

引用

IEEE Conference on Decision and Control

作者： Kyle Poe Enrique Mallada René Vidal Applied Mathematics and Computational Science Group University of Pennsylvania PA Mallada is with the Department of Electrical and Computer Engineering Johns Hopkins University MD Departments of Electrical and Systems Engineering Radiology Computer and Information Science Statistics and Data Science University of Pennsylvania PA

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

One of the fundamental problems of interest for discrete-time linear systems is whether its input sequence may be recovered given its output sequence, a.k.a. the left inversion problem. Many conditions on the state space geometry, dynamics, and spectral structure of a system have been used to characterize the well-posedness of this problem, without assumptions on the inputs. However, certain structural assumptions, such as input sparsity, have been shown to translate to practical gains in the performance of inversion algorithms, surpassing classical guarantees. Establishing necessary and sufficient conditions for left invertibility of systems with sparse inputs is therefore a crucial step toward understanding the performance limits of system inversion under structured input assumptions. In this work, we provide the first necessary and sufficient characterizations of left invertibility for linear systems with sparse inputs, echoing classic characterizations for standard linear systems. The key insight in deriving these results is in establishing the existence of two novel geometric invariants unique to the sparseinput setting, the weakly unobservable and strongly reachable subspace arrangements. By means of a concrete example, we demonstrate the utility of these characterizations. We conclude by discussing extensions and applications of this framework to several related problems in sparse control.

关键词： Linear systems Geometry Sufficient conditions Systematics Heuristic algorithms Standards

来源：评论

学校读者我要写书评

暂无评论

UAV Swarms for Joint Data Ferrying and Dynamic Cell Coverage via Optimal Transport Descent and Quadratic Assignment

UAV Swarms for Joint Data Ferrying and Dynamic Cell Coverage...

引用

Conference on Local computer Networks (LCN)

作者： Kai Cui Lars Baumgärtner Mustafa Burak Yilmaz Mengguang Li Christian Fabian Benjamin Becker Lin Xiang Maximilian Bauer Heinz Koeppl Departments of Electrical Engineering and Information Technology Computer Science and Mechanical Engineering Technische Universität Darmstadt Darmstadt Germany

Both data ferrying with disruption-tolerant networking (DTN) and mobile cellular base stations constitute important techniques for UAV-aided communication in situations of crises where standard communication infrastructure is unavailable. For optimal use of a limited number of UAVs, we propose providing both DTN and a cellular base station on each UAV. Here, DTN is used for large amounts of low-priority data, while capacity-constrained cell coverage remains reserved for emergency calls or command and control. We optimize cell coverage via a novel optimal transport-based formulation using alternating minimization, while for data ferrying we periodically deliver data between dynamic clusters by solving quadratic assignment problems. In our evaluation, we consider different scenarios with varying mobility models and a wide range of flight patterns. Overall, we tractably achieve optimal cell coverage under quality-of-service costs with DTN-based data ferrying, enabling large-scale deployment of UAV swarms for crisis communication.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Spatial Coherence Loss: All Objects Matter in Salient and Camouflaged Object Detection

arXiv

引用

arXiv 2024年

作者： Yang, Ziyun Choy, Kevin Farsiu, Sina The Biomedical Engineering Department Duke University DurhamNC27705 United States The Biomedical Engineering Electrical and Computer Engineering Ophthalmology and Computer Science Departments Duke University DurhamNC27705 United States

Generic object detection is a category-independent task that relies on accurate modeling of objectness. We show that for accurate semantic analysis, the network needs to learn all object-level predictions that appear at any stage of learning, including the pre-defined ground truth (GT) objects and the ambiguous decoy objects that the network misidentifies as foreground. Yet, most relevant models focused mainly on improving the learning of the GT objects. A few methods that consider decoy objects utilize loss functions that only focus on the single-response, i.e., the loss response of a single ambiguous pixel, and thus do not benefit from the wealth of information that an object-level ambiguity learning design can provide. Inspired by the human visual system, which first discerns the boundaries of ambiguous regions before delving into the semantic meaning, we propose a novel loss function, Spatial Coherence Loss (SCLoss), that incorporates the mutual response between adjacent pixels into the widely-used single-response loss functions. We demonstrate that the proposed SCLoss can gradually learn the ambiguous regions by detecting and emphasizing their boundaries in a self-adaptive manner. Through comprehensive experiments, we demonstrate that replacing popular loss functions with SCLoss can improve the performance of current state-of-the-art (SOTA) salient or camouflaged object detection (SOD or COD) models. We also demonstrate that combining SCLoss with other loss functions can further improve performance and result in SOTA outcomes for different applications. The codes will be released to https://***/TBD upon acceptance. Copyright © 2024, The Authors. All rights reserved.

关键词： Object recognition

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：