检索结果-内蒙古大学图书馆

2024 International Congress on Advances in Nuclear Power Plants, ICAPP 2024

作者： Nasim, Imtiaz Agarwal, Vivek Daw, Joshua E. Ji, Mingyue Kumar, Sneha Kasera daho National Laboratory 1955 Fremont Avenue Idaho FallsID83415 United States Department of Electrical & Computer Engineering University of Utah United States Kahlert School of Computing University of Utah United States

ISBN: (纸本)9780894487996

Anomaly detection (AD) in sensor data is critical to ensure uninterrupted functionality of nuclear power plants (NPPs). Consequently, AD model validation through real-world sensor data is important for applications in nuclear facilities. In this paper, we propose an Autoencoder (AE)—a multi-layered neural network, for AD in sensor data from an operational NPP testbed. Since the dataset lacks labels for irregularities, we introduce random noise and label them to effectively train our model. The proposed AE model assigns a higher reconstruction error to the abnormal samples that deviate from those encountered during the training phase and uses the reconstruction loss to detect anomalies in a representative imbalanced dataset. We also introduce an analytical solution—seasonal trend decomposition (STD)—as another AD scheme for identifying irregularities within the same time-series dataset. In contrast to the AE model which relies on reconstruction loss, the STD scheme decomposes the entire dataset into its trend, seasonality, and residual components to pinpoint irregularities. Our findings indicate that the proposed AE and STD models individually achieve recall scores of 97% and 92%, respectively. We validate the performance of the two models on both balanced and imbalanced data. We further solidify the results by picking the combined selected anomalies of the two solutions with an "AND" operator for more reliable predictions. © ICAPP *** rights reserved.

关键词： Nuclear power plants

来源：评论

学校读者我要写书评

暂无评论

Design of a Tunable Frequency-Selective Surface for Microwave Material Measurement Applications 45

Design of a Tunable Frequency-Selective Surface for Microwav...

引用

45th Annual Meeting and Symposium of the Antenna Measurement Techniques Association, AMTA 2023

作者： Howard, Christopher T. Allen, Kenneth W. Hunt, William D. Georgia Tech Research Institute Advanced Concepts Laboratory AtlantaGA United States School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA United States

ISBN: (纸本)9781736235157

In this work, a tunable frequency-selective surface is designed with a center frequency that can be varied with an applied DC voltage. An equivalent circuit representation of the FSS is derived from a finite-difference time-domain (FDTD) simulation of the passive FSS, allowing tuning circuits for the FSS to be designed in common circuit simulation tools such as SPICE. A comparison between the spectral response obtained from FDTD and equivalent circuit modeling (ECM) in SPICE shows that under certain conditions, ECM provides good agreement with full-wave analysis, is less computationally intensive, and provides physical insight. The ECM technique enables rapid design and analysis of various trade-offs, such as those between resonant frequency tunability and bandwidth. The ECM-designed circuit is then validated with full-wave analysis of the designed structure with active components using an FDTD-SPICE hybrid co-simulator. Finally, applicability of the chosen active FSS topology as a metasurface for free-space dielectric material characterization is discussed. © 2023 AMTA.

关键词： Equivalent circuits

来源：评论

学校读者我要写书评

暂无评论

Theoretical Characterization of the Electro-optical Properties of New Molecules for OLED Devices

Theoretical Characterization of the Electro-optical Properti...

引用

Innovative Research in Applied Science, engineering and Technology (IRASET),Conference on

作者： Imane El Mhamedi Zakariae El Madani Abdelhafid Yahya Zakaria El Malki Materials and Systems Control (MMSC) Computer Engineering and Intelligent Electrical Systems (2ISEI) Laboratory High School of Technology (ESTM) University Moulay Ismail Meknes Morocco

ISBN: (数字)9798331532970

ISBN: (纸本)9798331532987

This study focuses on the exploration of five novel π-conjugated organic compounds for potential incorporation into organic light-emitting diodes (OLEDs). The molecular structure of these compounds follows a D-Di-D setup, with a carbazole acting as the D component, and the specific Di component varying based on the donor utilized. Through analysis at the DFT/B3LYP/6-31G (d, p) level, including the determination of HOMO–LUMO energy values, after optimizing the molecules' ground state, the frontier molecular orbital (FMO) was studied using Egap band gap. Utilizing the TD-DFT and ZINDO method the optical properties like absorption (λmax) and emission (λem) were explored. Based on SILVACO-TCAD software, the estimated current-voltage (I-V) characteristics of the two most efficient molecules were obtained. The indices of the studied molecules calculated from these interactions indicates that the molecules have sufficient properties which allow these molecules to be considered promising candidates for use in OLED devices as high-performing active materials.

关键词： Photonic band gap Absorption Stimulated emission Stationary state Organic light emitting diodes Market research Software Orbits Optical devices Organic compounds

来源：评论

学校读者我要写书评

暂无评论

Binary Bleed: Fast Distributed and Parallel Method for Automatic Model Selection

Binary Bleed: Fast Distributed and Parallel Method for Autom...

引用

2024 IEEE High Performance Extreme Computing Conference, HPEC 2024

作者： Barron, Ryan Eren, Maksim E. Bhattarai, Manish Boureima, Ismael Matuszek, Cynthia Alexandrov, Boian S. Theoretical Division Los Alamos National Laboratory Los Alamos United States University of Maryland Baltimore County Department of Computer Science and Electrical Engineering MD United States Advanced Research in Cyber Systems Los Alamos National Laboratory Los Alamos United States

ISBN: (纸本)9798350387131

In several Machine Learning (ML) clustering and dimensionality reduction approaches, such as nonnegative matrix factorization (NMF), RESCAL, and K-Means clustering, users must select a hyper-parameter k to define the number of clusters or components that yield an ideal separation of samples or clean clusters. This selection, while difficult, is crucial to avoid overfitting or underfitting the data. Several ML applications use scoring methods (e.g., Silhouette and Davies Boulding scores) to evaluate the cluster pattern stability for a specific k. The score is calculated for different trials over a range of k, and the ideal k is heuristically selected as the value before the model starts overfitting, indicated by a drop or increase in the score resembling an elbow curve plot. While the grid-search method can be used to accurately find a good k value, visiting a range of k can become time-consuming and computationally resource-intensive. In this paper, we introduce the Binary Bleed method based on binary search, which significantly reduces the k search space for these grid-search ML algorithms by truncating the target k values from the search space using a heuristic with thresholding over the scores. Binary Bleed is designed to work with single-node serial, single-node multi-processing, and distributed computing resources. In our experiments, we demonstrate the reduced search space gain over a naive sequential search of the ideal k and the accuracy of the Binary Bleed in identifying the correct k for NMFk, K-Means pyDNMFk, and pyDRESCALk with Silhouette and Davies Boulding scores. We make our implementation of Binary Bleed for the NMF algorithm available on GitHub. © 2024 IEEE.

关键词： Dimensionality reduction

来源：评论

学校读者我要写书评

暂无评论

A Methodology for Estimating Allocation of Electric Vehicle Grid Interfaces in a Distribution System

A Methodology for Estimating Allocation of Electric Vehicle ...

引用

IEEE Power engineering Society Conference and Exposition in Africa, PowerAfrica

作者： Imanthi Kalanika Subasinghe Ganesh K. Venayagamoorthy Holcombe Department of Electrical and Computer Engineering Clemson University Real-Time Power and Intelligent Systems Laboratory Clemson USA Department of Electrical Electronic and Computer Engineering University of Pretoria South Africa

ISBN: (数字)9798350389388

ISBN: (纸本)9798350389395

The integration of electric vehicles (EVs) into the smart grid has introduced new challenges and opportunities for optimizing power and energy management. This paper presents a simple method using a decision-tree to estimate allocation of electric vehicle grid interfaces (EVGIs) for EV charging/discharging, leveraging the nodal capabilities of a distribution system. The future distribution system will cater for vehicle-to-grid (V2G) transactions in addition to grid-to-vehicle (G2V) transactions, thus EVGIs allowing for bidirectional (G2V/V2G) power flows need to be deployed. The proposed decision-tree method is based on nodal power flow ratings and peak demand at the nodes assuming the nodal voltages are maintained within their stability envelopes by volt-var optimization and other voltage control methods. The allocation of EVGIs in the IEEE 34 test node feeder distribution system using the decision-tree method is illustrated. The EVGI allocation using decision-trees is a simple method that can provide insights of a typical distribution system's capability to support EV integration with emerging smart grid technologies.

关键词： Vehicle-to-grid Electric potential Estimation Power system stability Resource management Voltage control Forecasting Energy management Optimization Load flow

来源：评论

学校读者我要写书评

暂无评论

A Hybrid Marine Predator Algorithm for Thermal-aware Routing Scheme in Wireless Body Area Networks

引用

Journal of Bionic engineering 2023年第1期20卷 81-104页

作者： Tao Hai Jincheng Zhou Mohammad Masdari Haydar Abdulameer Marhoon School of Computer and Information Qiannan Normal University for NationalitiesDuyun558000GuizhouChina Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou Duyun558000GuizhouChina Institute for Big Data Analytics and Artificial Intelligence(IBDAAI) Universiti Teknologi MARA40450Shah AlamSelangorMalaysia Department of Computer Engineering Islamic Azad UniversityUrmia BranchUrmiaIran Information and Communication Technology Research Group Scientific Research CenterAl-Ayen UniversityThi-QarIraq College of Computer Sciences and Information Technology University of KerbalaKarbalaIraq

Thermal-aware routing protocols in WBANs consider temperature factors in the routing process for preventing overheating of the tissues surrounding the sensor ***,providing an energy-efficient and thermal-aware routing in WBANs is a challenging *** deal with this problem,this article presents a novel temperature-aware routing protocol that applies Mamdani-based Fuzzy Logic Controllers(FLCs)for selecting the next forwarding node in routing data *** FLCs apply five important input factors such as the priority of the packet,and sensor node's remaining energy,temperature,distance,and link path ***,a new hybrid version of the Marine Predator Algorithm(MPA),named MPAOA is presented by combining the exploration and exploitation phases of the MPA and Arithmetic Optimization Algorithm(AOA).This algorithm is effectively applied for selecting the best possible set of fuzzy rules for FLCs and tuning their fuzzy *** experiments conducted in the Castalia simulator exhibit that the proposed temperature and priority-aware routing scheme can outperform other well-known routing schemes such as LATOR,TTRP,TAEO,ATAR,and EOCC-TARA in terms of metrics such as sensor nodes lifetime,the average temperature of the sensor nodes,and the percentage of the packets routed through non-overheated ***,it is shown that the MPAOA outperforms other algorithms such as Bat Algorithm(BA),Genetic Algorithm(GA),AOA,and MPA regarding the specified metrics.

关键词： WBANs Multi-hop routing Temperature Priority Fuzzy logic Bio-inspiration

来源：评论

学校读者我要写书评

暂无评论

Learning good state and action representations for Markov decision process via tensor decomposition

The Journal of Machine Learning Research

引用

The Journal of Machine Learning Research 2023年第1期24卷 5157-5209页

作者： Chengzhuo Ni Yaqi Duan Munther Dahleh Mengdi Wang Anru R. Zhang Department of Electrical & Computer Engineering Princeton University Laboratory for Information & Decision Systems Massachusetts Institute of Technology Electrical Engineering & Computer Science Department Massachusetts Institute of Technology Department of Biostatistics & Bioinformatics Duke University

The transition kernel of a continuous-state-action Markov decision process (MDP) admits a natural tensor structure. This paper proposes a tensor-inspired unsupervised learning method to identify meaningful low-dimensional state and action representations from empirical trajectories. The method exploits the MDP's tensor structure by kernelization, importance sampling and low-Tucker-rank approximation. This method can be further used to cluster states and actions respectively and find the best discrete MDP abstraction. We provide sharp statistical error bounds for tensor concentration and the preservation of diffusion distance after embedding. We further prove that the learned state/action abstractions provide accurate approximations to latent block structures if they exist, enabling function approximation in downstream tasks such as policy evaluation.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Cyber-Security Knowledge Graph Generation by Hierarchical Nonnegative Matrix Factorization 12

Cyber-Security Knowledge Graph Generation by Hierarchical No...

引用

12th International Symposium on Digital Forensics and Security, ISDFS 2024

作者： Barron, Ryan Eren, Maksim E. Bhattarai, Manish Wanna, Selma Solovyev, Nicholas Rasmussen, Kim Alexandrov, Boian S. Nicholas, Charles Matuszek, Cynthia Los Alamos National Laboratory Theoretical Division Los Alamos United States Los Alamos National Laboratory Advanced Research in Cyber Systems Los Alamos United States University of Maryland Department of Computer Science and Electrical Engineering Baltimore CountyMD United States

ISBN: (纸本)9798350330366

Much of human knowledge in cybersecurity is encapsulated within the ever-growing volume of scientific papers. As this textual data continues to expand, the importance of document organization methods becomes increasingly crucial for extracting actionable insights hidden within large text datasets. Knowledge Graphs (KGs) serve as a means to store factual information in a structured manner, providing explicit, interpretable knowledge that includes domain-specific information from the cybersecurity scientific literature. One of the challenges in constructing a KG from scientific literature is the extraction of ontology from unstructured text. In this paper, we address this topic and introduce a method for building a multi-modal KG by extracting structured ontology from scientific papers. We demonstrate this concept in the cybersecurity domain. One modality of the KG represents observable information from the papers, such as the categories in which they were published or the authors. The second modality uncovers latent (hidden) patterns of text extracted through hierarchical and semantic non-negative matrix factorization (NMF), such as named entities, topics or clusters, and keywords. We illustrate this concept by consolidating more than two million scientific papers uploaded to arXiv into the cyber-domain, using hierarchical and semantic NMF, and by building a cyber-domain-specific KG. © 2024 IEEE.

关键词： Cybersecurity

来源：评论

学校读者我要写书评

暂无评论

Fabrication of sub-diffraction limit high-aspect-ratio nanostructures via laser direct writing

引用

Chinese Optics Letters 2025年第3期23卷 149-154页

作者：陈国梁滕厚安陈建詹其文 School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Zhangjiang Laboratory International Institute for Sustainability with Knotted Chiral Meta Matter WPI-SKCM2 Hiroshima University

High-aspect-ratio structures with heights or depths significantly exceeding their lateral dimensions hold broad application potential across various *** production of these structures is challenging,requiring meticulous control over materials,scale,and *** introduce an economical and efficient approach for fabricating high-aspect-ratio nanostructures using a two-photon polymerization *** approach achieves feature sizes of around 37 nm with an aspect ratio of 10:1 using commercial *** advantages over traditional techniques,our approach simplifies operation and enhances design flexibility,facilitating the creation of smaller,more complex,and high-aspect-ratio *** capabilities of this approach are demonstrated by producing arrays of three-dimensional microstructures that exhibit submicron scales,extensive periodicity,and pronounced aspect *** developments open new possibilities for applications in biomedical,precision engineering,and optical microdevice manufacturing.

关键词： Beam splitters Femtosecond lasers Laser arrays Microstructures Nanostructures Ultrafast lasers

来源：评论

学校读者我要写书评

暂无评论

Generative AI-empowered Effective Physical-Virtual Synchronization in the Vehicular Metaverse

Generative AI-empowered Effective Physical-Virtual Synchroni...

引用

2023 IEEE International Conference on Metaverse Computing, Networking and Applications, MetaCom 2023

作者： Xu, Minrui Niyato, Dusit Zhang, Hongliang Kang, Jiawen Xiong, Zehui Mao, Shiwen Han, Zhu Nanyang Technological University School of Computer Science and Engineering Singapore639798 Singapore Peking University School of Electronics Beijing100871 China Guangdong University of Technology School of Automation Guangzhou510006 China Singapore University of Technology and Design Pillar of Information Systems Technology and Design Singapore487372 Singapore Auburn University Department of Electrical and Computer Engineering AuburnAL36849-5201 United States University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

ISBN: (纸本)9798350333336

Metaverse seamlessly blends the physical world and virtual spaces through ubiquitous communication and computing equipment and infrastructure. In intelligent transportation systems, the vehicular Metaverse can provide a fully immersive and hyperreal travel experience (e.g., via augmented reality head-up displays, AR-HUDs) to drivers and passengers in autonomous vehicles (AVs) through roadside units (RSUs). However, providing real-time and immersive services requires effective physical-virtual synchronization between AVs and virtual simulators. This paper proposes a generative AI-empowered physical-virtual synchronization framework for the vehicular Metaverse. In physical-to-virtual synchronization, digital twin (DT) tasks generated by AVs are offloaded for execution in RSUs with future route generation. In virtual-to-physical synchronization, virtual simulators customize diverse and personalized AR content via generative AI models based on user preferences. Furthermore, we propose a multi-task enhanced auction-based mechanism to match and price AVs and virtual simulators for RSUs to provide real-time and effective services. Finally, property analysis and experimental results demonstrate that the proposed mechanism is strategy-proof and adverse-selection free while increasing social surplus. © 2023 IEEE.

关键词： Augmented reality

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：