检索结果-内蒙古大学图书馆

A Multi-Model Framework to Explore ADHD Diagnosis from Neuroimaging Data

Journal of Data Science 2024年第2期22卷 191-207页

作者： Ozdemir, Yagmur Yavuz Nukala, Naga Chandra Padmini Molinari, Roberto Deshpande, Gopikrishna Department of Mathematics and Statistics Auburn University Auburn AL United States AU MRI Research Center Department of Electrical and Computer Engineering Auburn University Auburn AL United States Department of Psychological Sciences Auburn University Auburn AL United States Alabama Advanced Imaging Consortium Auburn AL United States Center for Neuroscience Auburn University Auburn AL United States School of Psychology Capital Normal University Beijing China Key Laboratory for Learning and Cognition Capital Normal University Beijing China Department of Psychiatry National Institute of Mental Health and Neurosciences Karnataka India Centre for Brain Research Indian Institute of Science Bangalore India Department of Heritage Science and Technology Indian Institute of Technology Hyderabad India

Attention Deficit Hyperactivity Disorder (ADHD) is a frequent neurodevelopmental disorder in children that is commonly diagnosed subjectively. The objective detection of ADHD based on neuroimaging data has been a complex problem with low ranges of accuracy, possibly due to (among others) complex diagnostic processes, the high number of features considered and imperfect measurements in data collection. Hence, reliable neuroimaging biomarkers for detecting ADHD have been elusive. To address this problem we consider a recently proposed multi-model selection method called Sparse Wrapper AlGorithm (SWAG), which is a greedy algorithm that combines screening and wrapper approaches to create a set of low-dimensional models with good predictive power. While preserving the previous levels of accuracy, SWAG provides a measure of importance of brain regions for identifying ADHD. Our approach also provides a set of equally-performing and simple models which highlight the main feature combinations to be analyzed and the interactions between them. Taking advantage of the network of models resulting from this approach, we confirm the relevance of the frontal and temporal lobes as well as highlight how the different regions interact to detect the presence of ADHD. In particular, these results are fairly consistent across different learning mechanisms employed within the SWAG (i.e. logistic regression, linear and radial-kernel support vector machines) thereby providing population-level insights, as well as delivering feature combinations that are smaller and often perform better than those that would be used if employing their original versions directly. © 2024 The Author(s).

关键词： automated detection functional magnetic resonance imaging interpretability prediction accuracy SWAG

来源：评论

学校读者我要写书评

暂无评论

A Stable Intelligent Model-Based Framework Using Graph Convolutional Networks and MULTIMOORA for Clinical Decision Support Systems

引用

IEEE Transactions on Consumer Electronics 2024年

作者： Zhang, Chao Li, Xiaochuan Bai, Wenhui Sangaiah, Arun Kumar Li, Deyu Shanxi University School of Computer and Information Technology Key Laboratory of Computational Intelligence and Chinese Information Processing Ministry of Education Taiyuan030006 China National Yunlin University of Science and Technology International Graduate Institute of Artificial Intelligence Douliou64002 Taiwan Sunway University School of Engineering and Technology Selangor Petaling Jaya47500 Malaysia Chandigarh University University Centre for Research and Development Punjab Mohali140413 India

Artificial intelligence (AI) is rapidly advancing in consumer electronics, particularly in clinical decision support systems (CDSSs). AI-driven devices enhance the effectiveness of healthcare-related electronics via predictive health analytics, reshaping medical data collection, analysis, and decision-making. Nevertheless, due to the abundance of imprecise, hesitant, and fuzzy information in healthcare data stemming from consumer electronics, AI may misinterpret the data, resulting in erroneous and unstable medical decisions. Therefore, this paper endeavors to establish a stable intelligent medical decision model, employing two essential tools: graph convolutional networks (GCNs) and MULTIMOORA (Multi-Objective Optimization by Ratio Analysis plus the full MULTIplicative form). First, a granular computing (GrC) framework based on GCNs and MULTIMOORA is established. In this framework, GCNs are initially employed to process multi-modal data within the hesitant fuzzy linguistic (HFL) background. Second, a comprehensive HFL information system (IS) is constructed. Third, three types of multi-granularity (MG) HFL methods are developed via MULTIMOORA. To better address the bounded rationality of decision-makers (DMs), regret theory (RT) is utilized to consolidate the multi-modal data. Finally, the efficacy and practically of the proposed decision model are assessed via a case study on medication selections. © 1975-2011 IEEE.

关键词： Electronic health record

来源：评论

学校读者我要写书评

暂无评论

High-speed multiwavelength InGaAs/InP quantum well nanowire array micro-LEDs for next generation optical communications

引用

Opto-Electronic Science 2023年第5期2卷 1-11页

作者： Fanlu Zhang Zhicheng Su Zhe Li Yi Zhu Nikita Gagrani Ziyuan Li Mark Lockrey Li Li Igor Aharonovich Yuerui Lu Hark Hoe Tan Chennupati Jagadish Lan Fu Australian Research Council Centre of Excellence for Transformative Meta-Optical Systems Department of Electronic Materials EngineeringResearch School of PhysicsThe Australian National UniversityCanberra ACT 2601Australia School of Electronic Science and Engineering Southeast UniversityNanjing 210096China Microstructural Analysis Unit University of Technology SydneySydney NSW 2007Australia Australian National Fabrication Facility ACT Node Research School of PhysicsThe Australian National UniversityCanberra ACT 2601Australia ARC Centre of Excellence for Transformative Meta-Optical Systems Faculty of ScienceUniversity of Technology SydneySydney NSW 2007Australia School of Engineering College of Engineering and Computer ScienceThe Australia National UniversityCanberraCanberra ACT 2601Australia

Miniaturized light sources at telecommunication wavelengths are essential components for on-chip optical communication ***,we report the growth and fabrication of highly uniform p-i-n core-shell InGaAs/InP single quantum well(QW)nanowire array light emitting diodes(LEDs)with multi-wavelength and high-speed ***-dimensional cathodoluminescence mapping reveals that axial and radial QWs in the nanowire structure contribute to strong emission at the wavelength of~1.35 and~1.55μm,respectively,ideal for low-loss optical *** a result of simultaneous contributions from both axial and radial QWs,broadband electroluminescence emission with a linewidth of 286 nm is achieved with a peak power of~17μW.A large spectral blueshift is observed with the increase of applied bias,which is ascribed to the band-filling effect based on device simulation,and enables voltage tunable multi-wavelength operation at the telecommunication wavelength ***-wavelength operation is also achieved by fabricating nanowire array LEDs with different pitch sizes on the same substrate,leading to QW formation with different emission ***,high-speed GHz-level modulation and small pixel size LED are demonstrated,showing the promise for ultrafast operation and ultracompact *** voltage and pitch size controlled multi-wavelength highspeed nanowire array LED presents a compact and efficient scheme for developing high-performance nanoscale light sources for future optical communication applications.

关键词： InGaAs/InP quantum well nanowires LEDs

来源：评论

学校读者我要写书评

暂无评论

A survey on scalable consensus algorithms for blockchain technology

Cyber Security and Applications

引用

Cyber Security and Applications 2025年 3卷

作者： Jain, Ankit Kumar Gupta, Nishant Gupta, Brij B. National Institute of Technology Kurukshetra India Department of Computer Science and Information Engineering Asia University Taiwan Taichung 413 China Symbiosis Centre for Information Technology (SCIT) Symbiosis International University Pune India Center for Interdisciplinary Research University of Petroleum and Energy Studies (UPES) Dehradun India

The process of reaching an agreement on a value within a distributed network, known as a consensus problem, is a defining feature of blockchain. This consensus problem can be seen in various applications like load balancing, transaction validation in blockchain, and distributed computing. In recent years, many researchers have provided solutions to this problem. Hence we have presented a survey in which we delved into blockchain consensus algorithms and conducted a comparative analysis of all the consensus algorithms to provide information about each protocol's advantages and drawbacks. This survey starts with the standard proof-of-work consensus protocol applied in bitcoin cryptocurrency and its limitations on the ground of the following parameters: throughput (transactions per second), latency, forks, fault tolerance, double spending attacks, and power consumption. The rest of the consensus algorithms in this paper have been systematically covered to address the limitations of proof-of-work. This paper also covered Raft and PBFT consensus algorithms suitable for permissioned networks. Although the PBFT consensus protocol has a high throughput and a low latency, it has limited node scalability. The PBFT has a low byzantine fault tolerant rate. This paper also covers PoEWAL for blockchain-based IoT applications and WBFT, which prevents corrupt nodes from taking part in consensus. A comparative analysis of the consensus algorithms provides an explicit knowledge of the present research, which also offers guidance for future study. © 2024

关键词： Blockchain technology Byzantine faults Consensus algorithm Latency Throughput

来源：评论

学校读者我要写书评

暂无评论

A Noble Metal High-Entropy Alloy for Mid-Infrared Metasurfaces

引用

engineering 2025年

作者： Nishijima, Yoshiaki Sudo, Teruaki Matsuo, Yasutaka Juodkazis, Saulius Department of Electrical and Computer Engineering of Engineering Yokohama National University Yokohama 240-8501 Japan Research Institute for Electronic Science Hokkaido University Sapporo 001-0020 Japan Optical Sciences Centre and ARC Training Centre in Surface Engineering for Advanced Materials (SEAM) School of Science Swinburne University of Technology Melbourne 3122 VIC Australia Institute of Advanced Sciences (IAS) Yokohama National University Yokohama 240-8501 Japan Institute for Multidisciplinary Sciences (IMS) Yokohama National University Yokohama 240-8501 Japan Precursory Research for Embryonic Science and Technology Japan Science and Technology Agency Tokyo 332-0012 Japan Tokyo Tech World Research Hub Initiative (WRHI) School of Materials and Chemical Technology Tokyo Institute of Technology Tokyo 152-8550 Japan

High-entropy alloys (HEAs) are promising materials for photonic applications. In such applications, permittivity is essential for numerical studies. In this work, we experimentally determine the complex permittivity of an HEA composed of five noble metals—Au, Ag, Cu, Pd, and Pt. The measurements are conducted across a broad wavelength spectrum, spanning the ultraviolet, visible, and mid-infrared regions. The experiments, numerical simulations of reflection spectra, and analysis of absorption and scattering cross-sections reveal the potential for fabricating perfect absorber and emitter metasurfaces using this noble HEA. In addition, crystallography studies clearly show the formation of a uniform material. The lattice constant and electron work function of the alloy are found to be 0.396 nm and 4.8 pm 0.4 eV, respectively—results indicate that the formed HEA alloy is well mixed. © 2025 THE AUTHORS

关键词： High-entropy alloy Metasurfaces Plasmonics

来源：评论

学校读者我要写书评

暂无评论

Document image rectification method combined with semantic segmentation 5

Document image rectification method combined with semantic s...

引用

5th International Conference on Machine Learning, Big Data and Business Intelligence, MLBDBI 2023

作者： Wang, YongWei Xu, ShuangShuang Xiao, Yao Yang, YiGuang Li, Hao Yang, RongZheng Cccc Second Harbor Engineering Company Ltd Hubei Wuhan China Key Laboratory of Large-span Bridge Construction Technology Hubei Wuhan China Cccc Highway Bridge National Engineering Research Centre Co. Ltd Beijing China Zhongnan University of Economics and Law School of Information Engineering Hubei Wuhan China Wuhan University of Engineering Science Department of Computer Science and Artificial Intelligence Hubei Wuhan China R. and D. Ctr. of Transp. Indust. of Intelligent Mfg. Technologies of Transport Infrastructure Hubei Wuhan China

ISBN: (纸本)9798350359930

Proposed a method combined with semantic segmentation for document image rectification to address the limited applicability of traditional correction methods and difficulties in data annotation. Firstly, diverse experimental data are synthesized to create a target document image and its corresponding mask data. Secondly, a semantic segmentation model based on DeepLabV3 is constructed using pre-trained MobileNetV3, ResNet50, and ResNet101 as the backbone networks, respectively, to separate the document page area(ROI) from the image. Then, the document page area is corrected using corner point detection and perspective transformation to complete the document image rectification. The evaluation of the model shows that the DeepLabV3 model with MobileNetV3 as the backbone network has high processing efficiency, with an IOU of 0.983 and a Total Loss of 0.064 on the validation set. Test results demonstrate that the proposed method has better generalization capabilities and can be easily extended to practical engineering. © 2023 IEEE.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

High-Fidelity CFD Verification Workshop 2024 Summary: Spalart-Allmaras QCR2000-R Turbulence Model

High-Fidelity CFD Verification Workshop 2024 Summary: Spalar...

引用

AIAA Aviation Forum and ASCEND, 2024

作者： Diskin, Boris Galbraith, Marshall C. Batten, Paul Holst, Kevin R. Liu, Yi Pandya, Mohagna J. Tarsia Morisco, Cosimo Pandey, Anup Computational Aerosciences Branch NASA Langley Research Center HamptonVA23681 United States Department of Aeronautics & Astronautics Massachusetts Institute of Technology CambridgeMA02139 United States Metacomp Technologies Inc. Westlake VillageCA91361 United States Electrical Engineering and Computer Science University of Tennessee KnoxvilleTN37996 United States Configuration Aerodynamics Branch NASA Langley Research Center HamptonVA23681 United States GammaO Equipe Inria-ONERA – Centre Inria de Saclay Université Paris-Saclay PalaiseauF-91120 France National Institute of Aerospace HamptonVA23666 United States Department of Mechanical and Aerospace Engineering Institute of Engineering Tribhuvan University Bagmati Lalitpur44700 Nepal

ISBN: (数字)9781624107160

ISBN: (纸本)9781624107160

This paper summarizes solutions submitted for the Reynolds-averaged Navier-Stokes (RANS) test suite of the High-Fidelity CFD Verification Workshop. The goal of the workshop is to establish standards for verification of computational fluid dynamics (CFD) approaches to simulations of steady and unsteady turbulent flows. The RANS verification studies focus on a one-equation Spalart-Allmar as model with quadratic constitutive relation and rotation correction, SA-neg-QCR2000-R. The verification test cases are a two-dimensional subsonic flow around a Joukowski airfoil, a three-dimensional subsonic flow around an extruded NACA 0012 wing in a tunnel, and a subsonic flow around a wing-body configuration developed for verification of solvers participating in the 5th High-Lift Prediction Workshop. The turbulence model formulation, geometry, flow conditions, grids, and reference solutions are described in detail. Solutions with machine zero residuals for the test cases are computed using seven established CFD solvers on adapted- and fixed-grid families using different discretization approaches. While some noticeable differences between solutions remain, the results achieved by contributing solvers show that different solutions computed for the same RANS model on different grid families can converge to a common limit with grid refinement. The apparent requirements for grid convergence are a well designed family of grids that provide sufficient resolution in important areas and a strong solver capable of deep iterative convergence on each grid. For each test case in the study, the variation between aerodynamic forces computed by different solvers on the finest grids of different families is less than 2%. © 2024, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Computational fluid dynamics

来源：评论

学校读者我要写书评

暂无评论

Right Frontal Gamma Transcranial Alternating Current Stimulation Modulates Optimism Biases

引用

Neuroscience Bulletin 2025年第1期41卷 172-176页

作者： Ziqing Yao Jinwen Wei Gan Huang Linling Li Zhen Liang Li Zhang Haiyan Wu Tifei Yuan Zhiguo Zhang Xiaoqing Hu Department of Psychology The State Key Laboratory of Brain and Cognitive SciencesThe University of Hong KongHong KongSARChina School of Biomedical Engineering Medical SchoolShenzhen UniversityShenzhen518060China Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging Shenzhen UniversityShenzhen518060China Centre for Cognitive and Brain Sciences and Department of Psychology University of MacaoMacao SARChina Shanghai Key Laboratory of Psychotic Disorders Brain Health InstituteNational Center for Mental DisordersShanghai Mental Health CenterShanghai Jiaotong University School of MedicineShanghai210109China School of Computer Science and Technology Harbin Institute of TechnologyShenzhen518055China Peng Cheng Laboratory Shenzhen518055China HKU-Shenzhen Institute of Research and Innovation Shenzhen518063China

Dear Editor,People are often optimistic when forecasting the future,such that they believe they are less likely to encounter adverse life *** phenomenon,known as optimism bias,emerges due to preferential encoding and consolidation of desirable over undesirable information[1,2],engaging frontal brain regions such as the anterior cingulate cortex and inferior frontal gyrus[1].An optimism bias is instrumental in supporting mental health:reduction or absence of optimism biases is associated with mood disorders such as depression,characterized by pessimistic thinking about the future[3].This relationship highlights the potential value of interventions that could enhance optimism bias[4].

关键词： ism such likely

来源：评论

学校读者我要写书评

暂无评论

CNNViT: A robust deep neural network for video anomaly detection

CNNViT: A robust deep neural network for video anomaly detec...

引用

4th International Conference on Distributed Sensing and Intelligent Systems (ICDSIS 2023)

作者： N. Garuda G. Prasad P. P. Dev P. Das E. Ghaderpour Department of Computer Science and Engineering National Institute of Technology Calicut Kattangal Calicut 673601 Kerala India Department of Earth Sciences & CERI Research Centre Sapienza University of Rome P.le Aldo Moro 10587 Rome Italy

ISBN: (数字)9781837240258

Detecting anomalies in videos poses a significant challenge due to the unbounded, infrequent, ambiguous, and irregular nature of abnormal events in real-world scenes. Recently, transformers have shown remarkable modeling capabilities for sequential data. As a result, we endeavor to leverage transformers for video anomaly detection. This paper presents a novel prediction-based method for video anomaly detection called CNNViT by integrating the architectural elements of Convolutional Neural Network (CNN) and Vision Transformer (ViT). The purpose of this fusion is to effectively capture enhanced spatial-temporal information and global features. The effectiveness of the proposed method is evaluated on UCSD Ped2 and CUHK Avenue benchmark datasets. Experimental results demonstrate that the proposed method attains considerably superior performance compared to state-of-the-art techniques.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Record High Temperatures in the Ocean in 2024

引用

Advances in Atmospheric Sciences 2025年第6期42卷 1092-1109页

作者： Lijing CHENG John ABRAHAM Kevin E.TRENBERTH James REAGAN Huai-Min ZHANG Andrea STORTO Karina VON SCHUCKMANN Yuying PAN Yujing ZHU Michael E.MANN Jiang ZHU Fan WANG Fujiang YU Ricardo LOCARNINI John FASULLO Boyin HUANG Garrett GRAHAM Xungang YIN Viktor GOURETSKI Fei ZHENG Yuanlong LI Bin ZHANG Liying WAN Xingrong CHEN Dakui WANG Licheng FENG Xiangzhou SONG Yulong LIU Franco RESEGHETTI Simona SIMONCELLI Gengxin CHEN Rongwang ZHANG Alexey MISHONOV Zhetao TAN Wangxu WEI Huifeng YUAN Guancheng LI Qiuping REN Lijuan CAO Yayang LU Juan DU Kewei LYU Albertus SULAIMAN Michael MAYER Huizan WANG Zhanhong MA Senliang BAO Henqian YAN Zenghong LIU Chunxue YANG Xu LIU Zeke HAUSFATHER Tanguy SZEKELY Flora GUES National Key Laboratory of Earth System Numerical Modeling and Application Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China University of St.Thomas School of EngineeringMinnesota 55105USA NSF National Center for Atmospheric Research BoulderColorado 80307USA University of Auckland Auckland 0630New Zealand National Oceanic and Atmospheric Administration National Centers for Environmental InformationSilver SpringMaryland 20910USA National Oceanic and Atmospheric Administration National Centers for Environmental InformationAshevilleNC 28801USA National Research Council(CNR)Institute of Marine Sciences(ISMAR) Rome 00133Italy Mercator Ocean International Toulouse 31400France Department of Earth and Environmental Science University of PennsylvaniaPhiladelphiaPennsylvania 19104USA Institute of Oceanology Chinese Academy of SciencesQingdao 266071China National Marine Environmental Forecasting Center Ministry of Natural Resources of ChinaBeijing 100081China North Carolina Institute for Climate Studies(NCICS) North Carolina State UniversityAshevilleNC 28804USA Oceanographic Data Center Chinese Academy of SciencesQingdao 266071China College of Oceanography Hohai UniversityNanjing 210098China National Marine Data and Information Service Tianjin 300171China Istituto Nazionale di Geofisica e Vulcanologia Sede di BolognaBologna 40128Italy South China Sea Institute of Oceanology Chinese Academy of SciencesGuangzhou 510301China ESSIC/CISESS-MD University of MarylandCollege ParkMD 20740USA Computer Network Information Center Chinese Academy of SciencesBeijing 100083China Eco-Environmental Monitoring and Research Center Pearl River Valley and South China Sea Ecology and Environment AdministrationMinistry of Ecology and EnvironmentGuangzhou 510611China National Meteorological Information Center China Meteorological AdministrationBeijing 100081China International Research Center of Big Data for Sustainable Development Goals Beijing 100094China Xiamen Universit

Heating in the ocean has continued in 2024 in response to increased greenhouse gas concentrations in the atmosphere,despite the transition from an El Ni?o to neutral conditions. In 2024, both global sea surface temperature(SST) and upper2000 m ocean heat content(OHC) reached unprecedented highs in the historical record. The 0–2000 m OHC in 2024exceeded that of 2023 by 16 ± 8 ZJ(1 Zetta Joules = 1021 Joules, with a 95% confidence interval)(IAP/CAS data), which is confirmed by two other data products: 18 ± 7 ZJ(CIGAR-RT reanalysis data) and 40 ± 31 ZJ(Copernicus Marine data,updated to November 2024). The Indian Ocean, tropical Atlantic, Mediterranean Sea, North Atlantic, North Pacific, and Southern Ocean also experienced record-high OHC values in 2024. The global SST continued its record-high values from2023 into the first half of 2024, and declined slightly in the second half of 2024, resulting in an annual mean of 0.61°C ±0.02°C(IAP/CAS data) above the 1981–2010 baseline, slightly higher than the 2023 annual-mean value(by 0.07°C ±0.02°C for IAP/CAS, 0.05°C ± 0.02°C for NOAA/NCEI, and 0.06°C ± 0.11°C for Copernicus Marine). The record-high values of 2024 SST and OHC continue to indicate unabated trends of global heating.

关键词： ocean heat content sea surface temperature ocean temperature global warming climate

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：