检索结果-内蒙古大学图书馆

arXiv 2022年

作者： Dutta, Shamak Wilde, Nils Tokekar, Pratap Smith, Stephen L. The Department of Electrical and Computer Engineering University of Waterloo Canada The Cognitive Robotics Department Delft University of Technology Netherlands The Department of Computer Science University of Maryland United States

We study the sample placement and shortest tour problem for robots tasked with mapping environmental phenomena modeled as stationary random fields. The objective is to minimize the resources used (samples or tour length) while guaranteeing estimation accuracy. We give approximation algorithms for both problems in convex environments. These improve previously known results, both in terms of theoretical guarantees and in simulations. In addition, we disprove an existing claim in the literature on a lower bound for a solution to the sample placement problem. Copyright © 2022, The Authors. All rights reserved.

关键词： Approximation algorithms

来源：评论

学校读者我要写书评

暂无评论

Bayesian Inference for Non-Synchronously Observed Diffusions

arXiv

引用

arXiv 2025年

作者： Jasra, Ajay Kamatani, Kengo Wu, Amin School of Data Science The Chinese University of Hong Kong Shenzhen Shenzhen China Institute of Statistical Mathematics Tokyo190-0014 Japan Statistics Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

We consider the problem of Bayesian inference for bi-variate data observed in time but with observation times which occur non-synchronously. In particular, this occurs in a wide variety of applications in finance, such as high-frequency trading or crude oil futures trading. We adopt a diffusion model for the data and formulate a Bayesian model with priors on unknown parameters along with a latent representation for the the so-called missing data. We then consider computational methodology to fit the model using Markov chain Monte Carlo (MCMC). We have to resort to time-discretization methods as the complete data likelihood is intractable and this can cause considerable issues for MCMC when the data are observed in low frequencies. In a high frequency observation frequencies we present a simple particle MCMC method based on an Euler–Maruyama time discretization, which can be enhanced using multilevel Monte Carlo (MLMC). In the low frequency observation regime we introduce a novel bridging representation of the posterior in continuous time to deal with the issues of MCMC in this case. This representation is discretized and fitted using MCMC and MLMC. We apply our methodology to real and simulated data to establish the efficacy of our methodology. © 2025, CC BY.

关键词： Crude oil

来源：评论

学校读者我要写书评

暂无评论

LMCG-Net: Integrating LLMs and ECG for LVEF-Based Classification for Pacing Patients

LMCG-Net: Integrating LLMs and ECG for LVEF-Based Classifica...

引用

2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Shim, Wonkyeong Park, Namjun Ko, Donggeun Gwag, Hyebin Park, Youngjun Park, Seungjung Kim, Jaekwang Sungkyunkwan University Dept. of Computer Science and Engineering Suwon Korea Republic of Aim Future Ai Seoul Korea Republic of Samsung Changwon Hospital Changwon Korea Republic of Wonju Severance Christian Hospital Kangwon-do Korea Republic of Samsung Medical Center Seoul Korea Republic of Sungkyunkwan University Convergence Program for Social Innovation School of Convergence Seoul Korea Republic of

ISBN: (纸本)9798350386226

Detecting left ventricular systolic dysfunction (LVSD) traditionally relies on expensive and specialized echocardiography, limiting accessibility for many patients. To address this, researchers explore the potential of electrocardiography (ECG), a more affordable and widely available alternative, despite its historically limited performance in cardiac dysfunction detection. In this study, we present a novel approach that integrates a 1D convolutional neural networks (CNNs) with a large-scale language model (LLM) to simultaneously analyze sequential ECG data and non-sequential clinical metadata. To validate our model's effectiveness, we conducted rigorous comparative experiments on both specially collected clinical data and public datasets, achieving an impressive AUROC of 0.97 across both. Our findings underscore the capability of ECG-based AI to accurately predict LVSD including pacemaker patients, offering a rapid and cost-effective alternative to traditional echocardiography. This innovative approach could significantly enhance early diagnosis and management of cardiac dysfunction. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

arXiv

引用

arXiv 2024年

作者： Zeng, Xianlong Gao, Yijing Liu, Ang Song, Fanghao Electrical Engineering and Computer Science Ohio University AthensOH45701 United States Data Science Institute Brown University ProvidenceRI02912 United States Global Urban Studies Program Rutgers University New BrunswickNJ08901 United States

This study introduces a simple yet effective method for identifying similar data points across non-free text domains, such as tabular and image data, using Large Language Models (LLMs). Our two-step approach involves data point summarization and hidden state extraction. Initially, data is condensed via summarization using an LLM, reducing complexity and highlighting essential information in sentences. Subsequently, the summarization sentences are fed through another LLM to extract hidden states, serving as compact, feature-rich representations. This approach leverages the advanced comprehension and generative capabilities of LLMs, offering a scalable and efficient strategy for similarity identification across diverse datasets. We demonstrate the effectiveness of our method in identifying similar data points on multiple datasets. Additionally, our approach enables non-technical domain experts, such as fraud investigators or marketing operators, to quickly identify similar data points tailored to specific scenarios, demonstrating its utility in practical applications. In general, our results open new avenues for leveraging LLMs in data analysis across various domains. © 2024, CC BY.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Towards a Theoretical Framework of Autonomous Systems Underpinned by Intelligence and Systems sciences

引用

IEEE/CAA Journal of Automatica Sinica 2021年第1期8卷 52-63页

作者： Yingxu Wang Ming Hou Konstantinos NPlataniotis Sam Kwong Henry Leung Edward Tunstel Imre JRudas Ljiljana Trajkovic International Institute of Cognitive Informatics and Cognitive Computing Department of Electrical and Computer EngineeringSchulich School of Engineering and Hotchkiss Brain InstituteUniversity of CalgaryCalgary T2N 1N4Canada Toronto Research Centre Defence Research&Development CanadaToronto M3K 2C9Canada Department of Electrical&Computer Engineering University of TorontoToronto M5S3G4Canada Department of Computer Science City University of Hong KongHong KongChina Department of Electrical and Computer Engineering Schulich School of EngineeringUniversity of CalgaryCalgary T2N 1N4Canada Autonomous&Intelligent Systems Department United Technologies Research CenterCT 06108 USA University Research&Innovation Center(EKIK) Óbuda UniversityBudapest H-1034Hungary School of Engineering Science Simon Fraser UniversityBurnaby V5A 1S6Canada

Autonomous systems are an emerging AI technology functioning without human intervention underpinned by the latest advances in intelligence,cognition,computer,and systems *** paper explores the intelligent and mathematical foundations of autonomous *** focuses on structural and behavioral properties that constitute the intelligent power of autonomous *** explains how system intelligence aggregates from reflexive,imperative,adaptive intelligence to autonomous and cognitive intelligence.A hierarchical intelligence model(HIM)is introduced to elaborate the evolution of human and system intelligence as an inductive *** properties of system autonomy are formally analyzed towards a wide range of applications in computational intelligence and systems *** paradigms of autonomous systems including brain-inspired systems,cognitive robots,and autonomous knowledge learning systems are *** in autonomous systems will pave a way towards highly intelligent machines for augmenting human capabilities.

关键词： Autonomous systems(AS) cognitive systems computational intelligence engineering paradigms intelligence science intelligent mathematics

来源：评论

学校读者我要写书评

暂无评论

Thermo-optic Properties in PECVD Silicon Rich Silicon Carbide

Thermo-optic Properties in PECVD Silicon Rich Silicon Carbid...

引用

Novel Optical Materials and Applications, NOMA 2022

作者： Chang, Li-Yang Sunny Pappert, Steve Yu, Paul K.L. Materials Science and Engineering Program University of California 9500 Gilman Drive La Jolla San DiegoCA92093 United States Department of Electrical and Computer Engineering University of California 9500 Gilman Drive La Jolla San DiegoCA92093 United States

We study the thermo-optic coefficient of silicon carbide with different silicon content. We demonstrate a clear trend between the silicon content and the thermo-optic coefficient which measured as high as 1.88×10... 详细信息

ISBN: (纸本)9781557528209

关键词： Silicon carbide

来源：评论

学校读者我要写书评

暂无评论

A weighted multivariate fuzzy time series method for multiple output high-dimensional time series forecasting in IoT applications

A weighted multivariate fuzzy time series method for multipl...

引用

2024 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2024

作者： Bitencourt, Hugo Vinicius De Oliveira Lucas, Patricia Orang, Omid Silva, Petronio Guimaraes, Frederico Gadelha Universidade Federal de Minas Gerais Graduate Program in Electrical Engineering Belo Horizonte31270-901 Brazil Instituto Federal Do Norte de Minas Gerais Salinas Brazil Universidade Federal de Minas Gerais Department of Computer Science Belo Horizonte31270-901 Brazil Instituto Federal Do Norte de Minas Gerais Januária Brazil

ISBN: (纸本)9798350374575

In Internet of Things (IoT) applications, data flows are continuous streams of high-dimensional time series that aggregate various data sources. In this context, decision-making processes frequently encompass multiple factors and criteria that demand forecasting these time series. This paper introduces MO-WMVFTS, a novel multiple-input multiple-output (MIMO) fuzzy time series (FTS) method for tackling this complex scenario. MO-WMVFTS is a hybrid forecasting method that fuses weighted multivariate FTS (WMVFTS) with embedding transformations, designed for IoT applications. To assess the performance of the proposed method, it was applied to the prediction of energy consumption in smart homes and air quality in smart cities. Here, three real-world datasets are used to assess the validity of our proposed approach, and the results obtained are highly competitive when compared to other existing methods. © 2024 IEEE.

关键词： Smart homes

来源：评论

学校读者我要写书评

暂无评论

Psychological Stress Classification Using Extreme Gradient Boosting Algorithm

Psychological Stress Classification Using Extreme Gradient B...

引用

International Conference on Information and Communication Technology Convergence (ICTC)

作者： Maria Mahardini Sakanti Viacheslav Siniaev Aurelia Amaris Win-Jet Luo Suhartono C. Bambang Dwi Kuncoro Graduate Institute of Precision Manufacturing National Chin-Yi University of Technology Taichung Taichung Taiwan Institute of Applied Computer Science ITMO University St. Petersburg Russian Federation Department of Informatics Engineering Faculty of Computer Science Universitas Brawijaya Malang Indonesia Ph.D. Program Prospective Technology of Electrical Engineering and Computer Science National Chin-Yi University of Technology Taichung Taichung Taiwan Department of Refrigeration Air Conditioning and Energy Engineering National Chin-Yi University of Technology Taichung Taiwan

ISBN: (数字)9798350364637

ISBN: (纸本)9798350364644

Stress, as a reaction to threatening situations, can raise heart rate and result in serious conditions that might cause significant damage or even be life-threatening. Traditional methods for evaluating stress, which rely on subjective self-reporting and clinical assessments, often suffer from biases and inconsistencies. Artificial intelligence models have been explored to predict stress levels more accurately. This paper investigates the application of Extreme Gradient Boosting in classifying psychological stress using the WESAD dataset, which includes parameters such as acceleration, electrocardiogram, electromyography, electrodermal activity, temperature, and respiration. The dataset was balanced and sampled to create a manageable subset for experimental. Extreme Gradient Boosting was chosen for its efficiency and scalability in handling complex datasets. The model was trained and validated, achieving a 95% accuracy in predicting stress levels. This study highlights the potential of integrating Extreme Gradient Boosting models into wearable devices for real-time stress monitoring. Future work involves optimizing the model to utilize fewer sensors without decreasing accuracy, ensuring it can be integrated into portable/wearable systems using tiny microcontrollers.

关键词： Accuracy Microcontrollers Psychology Human factors Predictive models Boosting Prediction algorithms Real-time systems Sensors Wearable devices

来源：评论

学校读者我要写书评

暂无评论

The Indoor People Tracking and Counting System

The Indoor People Tracking and Counting System

引用

International Automatic Control Conference

作者： Hao-Pu Lin Chin-Chuan Han Jun-Wei Liao Chong-Han Ciou Yi-Cheng Hong Ming-Lun Tan Ph. D. Program in Material and Chemical Engineering National United University MiaoLi Taiwan Department of Computer Science and Information Engineering National United University MiaoLi Taiwan

COVID-19 outbreaks and becomes serious from 2019 winter. Taking body temperature, wearing masks, recording footprint and avoiding crowds become important tasks and require a lot of manpower support for the prevention of the epidemic in every. In this study, we have integrated the infrared thermometer devices to measure people temperature and the people identities through RGB images at the entrance of buildings. Using the computer vision and deep learning methods, we would like to build a 24/7 and region-wide coverage assistance system to automatically record the footprint of a specific people in the building. We also detect if people taking off their masks in the yard at any time. The processing videos are grabbed from the existing CCTV systems. The developed system also locates the crowd and calculate the number of people in a specified area, and the manager can know the number of people and control the access in real time. It will reduce the burden of manpower. In addition, we have optimized the system performance to handle multiple camera videos and to reduce the hardware cost at the same time.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Effects of Incident Angle on Single-Event Leakage Current Degradation in Heavy-Ion Irradiated 1800 v and 4500 v SiC Power MOSFETs

引用

IEEE Transactions on Nuclear science 2025年

作者： Sengupta, A. Martinella, C. Ball, D.R. Niskanen, K. Senarath, A.S. Islam, S. Harris, P.M. Hutson, J.M. Osheroff, J.M. Sternberg, A.L. Kettunen, H. Kosier, S.L. Grossner, U. Javanainen, A. Galloway, K.F. Schrimpf, R.D. Witulski, A.F. Zürich8092 Switzerland Vanderbilt University Interdisciplinary Materials Science Program NashvilleTN37235 United States Lipscomb University Electrical and Computer Engineering Department NashvilleTN37204 United States NASA/GSFC Code 561.4 GreenbeltMD20771 United States Vanderbilt University Electrical Engineering and Computer Science Department B 351825 NashvilleTN37235 United States University of Jyväskylä Department of Physics Jyväskylä40014 Finland

Experimental heavy-ion responses of two variants of SiC power MOSFETs are evaluated. The devices have similar epitaxial thickness but different doping. The higher doping in the epitaxial region results in lower breakdown voltage, and typically leads to a lower threshold drain voltage at which single-event leakage current (SELC) occurs. Furthermore, the heavy-ion-induced SELC degradation in the drain and gate currents of the SiC MOSFETs exhibit a strong dependence on the heavy-ion's angle of incidence. The devices' behavior significantly alters when irradiated with heavy-ions at different incident angles under the same fixed bias and total fluence, as also confirmed by 3-D Technology computer Aided Design (TCAD) simulations. © 1963-2012 IEEE.

关键词： Power MOSFET

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：