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共 1897 条记录，以下是151-160 订阅

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Public-Private Partnerships (PPPs) in Energy: Co-citation analysis Using Network and Cluster visualization

Public-Private Partnerships (PPPs) in Energy: Co-citation An...

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4th International conference on Intelligent Human Systems Integration (IHSI) - Integrating People and Intelligent Systems

作者： Pinilla-De la Cruz, Giovanna Andrea Rabetino, Rodrigo Kantola, Jussi Univ Vaasa VEBIC Wolffintie 34 Vaasa 65200 Finland Univ Vaasa Sch Management Wolffintie 34 Vaasa 65200 Finland Univ Turku Fac Technol Vesilinnantie 5 Turku 20500 Finland

ISBN: (纸本)9783030680176;9783030680169

The nascent field of Public-Private Partnerships (PPPs) in energy has been promoted in recent years as a collective response to the urgent need to shift towards clean and sustainable energy systems. However, the evolution of this domain is limited by the absence of a clear structure and strong connecting elements. By shedding some light on this topic, our research seeks to use intelligent data analytics and computational visualization in co-citation analysis to identify relevant research streams and collaborative networks. The findings reveal current clusters and research strands formed by scholars form based on their co-citation links. The study contributes to the growing body of knowledge in the field via a better understanding of PPPs in energy for its further development.

关键词： Public-Private Partnerships (PPPs) Energy Co-citation analysis VOSviewer Network and cluster visualization

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Risks Factors that Influence a data Center Infrastructure through the TEMAC method 16

Risks Factors that Influence a Data Center Infrastructure th...

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16th Iberian conference on Information Systems and Technologies, CISTI 2021

作者： Tabosa, Fabio G. F. Da Silva, Daniel A. De Sousa, Rafael T. De Deus, Flavio Elias G. Nunes, Rafael Rabelo Elétrica Campus Universitário Darcy Ribeiro Universidade de Brasília Departamento de Energia Brasília Brazil

ISBN: (纸本)9789895465910

The paper presents an analysis of the risk factors that influence a data center infrastructure, by means of the Theory of Meta-Analytic Consolidated Approach (TEMAC). After bibliometric research in the Web of Science and Scopus repositories, 96 relevant results were found. For the analysis of co-authorship, co-citation and bibliographic coupling, heat maps were produced to facilitate the visualization of relevant authors and works. As for the analysis of the frequency of the keywords in the selected articles, terms with high frequency in the two databases were extracted, such as: security;network;risk;energy;management;virtual and service. As a result, 11 highly relevant articles were obtained that presented 10 risk factors that influence the evaluation according to the unique identifiers of 3 functions and 8 categories of the NIST Cybersecurity Framework, being: i) governance;ii) supply chain risk management;iii) identity management and access control;iv) data security;v) information protection processes and procedures;vi) protective technology;vii) anomalies and incidents;viii) continuous security monitoring. © 2021 AISTI.

关键词： Risk management

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Adaptive Cross-Modal Prototypes for Cross-Domain Visual-Language Retrieval

Adaptive Cross-Modal Prototypes for Cross-Domain Visual-Lang...

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IEEE/CVF conference on Computer Vision and Pattern Recognition (CVPR)

作者： Liu, Yang Chen, Qingchao Albanie, Samuel Peking Univ Wangxuan Inst Comp Technol Beijing Peoples R China Peking Univ Natl Inst Hlth Data Sci Beijing Peoples R China Univ Oxford Visual Geometry Grp Oxford England Univ Oxford Dept Engn Sci Oxford England

ISBN: (纸本)9781665445092

In this paper, we study the task of visual-text retrieval in the highly practical setting in which labelled visual data with paired text descriptions are available in one domain (the "source"), but only unlabelled visual data (without text descriptions) are available in the domain of interest (the "target"). We propose the ADAPTIVE CROSS-MODAL PROTOTYPES framework which seeks to enable target domain retrieval by learning cross-modal visual-text representations while minimising both uni-modal and cross-modal distribution shift across the source and target domains. Our approach is built upon two key ideas: first, we encode the inductive bias that the learned cross-modal representations should be compositional with respect to concepts in each modality-this is achieved through clustering pretrained uni-modal features across each domain and designing a careful regularisation scheme to preserve the resulting structure. Second, we employ mutual information maximisation between cross-modal representations in the source and target domains during learning-this provides a mechanism that preserves commonalities between the domains while discarding signal in each that cannot be inferred from the other. We showcase our approach for the task of cross-domain visual-text retrieval, outperforming existing approaches for both images and videos.

关键词： visualization Computer vision Prototypes Pattern recognition Task analysis Mutual information Videos

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Redundancy analysis for Binary data Based on Logistic Responses 16th

Redundancy Analysis for Binary Data Based on Logistic Respon...

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16th conference of the International Federation of Classification Societies, IFCS 2019

作者： Vicente-Villardon, Jose L. Vicente-Gonzalez, Laura Departamento de Estadística Universidad de Salamanca Salamanca Spain

ISBN: (纸本)9783030601034

Redundancy analysis (RDA) is one of the many possible methods to extract and summarize the variation in a set of response variables that can be explained by a set of explanatory variables. The main idea is to use multivariate linear regression to explain the responses as a linear function of the explanatory and then use Principal Component analysis (PCA) or a biplot to visualize the result. When response variables are categorical (binary, nominal, or ordinal), classical linear techniques are not adequate. Some alternatives such as Distance-Based RDA have been proposed in the literature. In this paper, we propose versions of RDA based on generalized linear models with logistic responses. The natural visualization methods for our techniques are the Logistic Biplots, recently proposed. The procedures are illustrated with an application to real data. © 2021, Springer Nature Switzerland AG.

关键词： Principal component analysis

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JUST-Studio: A Platform for Spatio-Temporal data Map Designing and Application Building 22nd

JUST-Studio: A Platform for Spatio-Temporal Data Map Designi...

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22nd International conference on Web Information Systems Engineering (WISE)

作者： Sui, Yuan Li, Ruiyuan Wang, Xu Liu, Jun Tang, Juncheng JD Intelligent Cities Res Beijing Peoples R China Chongqing Univ Chongqing Peoples R China

ISBN: (纸本)9783030915605;9783030915599

With the proliferation of GPS (Global Position System) and other space sensors, there emerged many spatial-temporal (a.k.a. ST) urban applications, such as trajectory visualization and geofence analysis. It is time-consuming and tedious to build these applications from scratch by writing codes only. This paper introduces JUST-Studio, a holistic platform that analyzes spatio-temporal data and builds urban applications with minor efforts. JUST-Studio consists of two main components: service manager and ST-App designer. By this platform, users could: 1) upload their own ST data to the built-in data store, or connect to an existing ST data store and register it as a data source;2) create ST models using ST data and publish ST services;3) make ST base map and build ST applications based on ST services. JUST-Studio is not only capable of making commonly used static map scenes, but also good at rendering dynamic data. In this paper, we will use vehicle trajectories with geofence analysis to build an application for monitoring restricted areas, which is very common in urban traffic applications.

关键词： data virtualization Web mapping Location analysis Application builder

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The Role of Blockchain in Supporting a Green Economy: Mapping the Emerging Literatures

The Role of Blockchain in Supporting a Green Economy: Mappin...

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Sustainable Power and Energy conference (iSPEC)

作者： Syarifuddin Syarifuddin Mahir Pradana Abdul Fadli Kalaloi Cheah Wai Shiang Husny Gibreel Musa Saleh Muhammad Diandra Rahmawan Department of Business Administration Telkom University Bandung Indonesia Department of Communication Telkom University Bandung Indonesia Faculty of Computer Science and Information Technology Universiti Malaysia Sarawak Indonesia International Islamic University Depok Indonesia Telkom University Bandung Indonesia

ISBN: (数字)9798350395075

ISBN: (纸本)9798350395082

This research examines the role of blockchain technology in supporting the green economy and sustainable development through bibliometric analysis using data from the Scopus database, which covers global trends related to “green blockchain” from 2019 to 2024. The results show that blockchain has become an increasingly dominant research topic, especially in the context of sustainability and environmental management. This analysis shows a close association between keywords such as “sustainable development” and “green economy” with the concept of blockchain, which confirms the importance of this technology in supporting the green economy. In addition, technical aspects of blockchain, such as network security and system efficiency, also received significant attention, indicating that blockchain is not only an innovative technology but also has the potential to adapt to specific needs in various sectors, including energy management and digital security. This suggests that blockchain could be a key technology that integrates modern technological systems with global sustainability initiatives. This research makes an important contribution to the literature linking blockchain with sustainability, and encourages further research to optimize the implementation of this technology in support of sustainable development goals and the green economy. Moreover, the in-depth bibliometric analysis in this study offers valuable insights into the development of research trends in this area, providing a solid foundation for further exploration in the future.

关键词： visualization Green products Bibliometrics Network security Market research Solids Blockchains Resource management Sustainable development Energy management

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Visualizing Venice to Visualizing Cities - Advanced Technologies for Historical Cities visualization 2nd

Visualizing Venice to Visualizing Cities - Advanced Technolo...

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2nd International conference on Research and Education in Urban History in the Age of Digital Libraries, UHDL 2019

作者： Huffman, Kristin L. Giordano, Andrea Duke University Durham United States University of Padova Padova35100 Italy

ISBN: (纸本)9783030931858

Using digital methods, the time has arrived for deepening the scholarly analysis of visual and written documents that validate and/or reveal previously unknown urban circumstances. Traditional methodologies of art, architectural and urban history remain the foundation of rigorous digital approaches;the study of a city necessitates scholarly decryption of information and visual sources that connect them to a broader historical context. As new digital tools and applications have become available, iconographic and textual sources– primary data of exceptional value not only from an historical point of view, but also for interpretative inflections – can now be interwoven as a scientific practice. This is the principal objective of Visualizing Venice to Visualizing Cities. © 2021, Springer Nature Switzerland AG.

关键词： visualization

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Designing,analysis and Implementation of Open-source visualization System for High-Definition Remote Sensing data Processing 32

Designing,Analysis and Implementation of Open-source Visuali...

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第32届中国控制与决策会议

作者： HAN Peng LI Yan WANG Ying LI Linqi MA Haotian WANG Jinkuan School of Computer and Communication Engineering Northeastern University at Qinhuangdao School of Control Engineering Northeastern University at Qinhuangdao

ISBN: (数字)9781728158556

ISBN: (纸本)9781728158563

The big data characteristics of Marine High-Definition Remote Sensing（MHDRS） has result in the obstacle of the real-time processing,effective decision-making and low efficiency information *** at this problem,this paper analyzes the visualization and control integrate system,and establishes a visually analytic system to process the different source of Remote Sensing（RS） data as well as its storage based on the MHDRS *** result shows that the new method enhances the analysis and sharing with high efficiency.

关键词： RS Images Geographic Information System data visualization Open Source System B/S structure

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5th International conference on Intelligent Computing and Applications, ICICA 2019

5th International Conference on Intelligent Computing and Ap...

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5th International conference on Intelligent Computing and Applications, ICICA 2019

ISBN: (纸本)9789811555657

The proceedings contain 71 papers. The special focus in this conference is on Intelligent Computing and Applications. The topics include: Performance Estimation and analysis Over the Supervised Learning Approaches for Motor Imagery EEG Signals Classification;fully Automated Digital Mammogram Segmentation;empirical Study of Computational Intelligence Approaches for the Early Detection of Autism Spectrum Disorder;Intelligent Monitoring of Bearings Using Node MCU Module;image Denoising Using Various Image Enhancement Techniques;energy Consumption analysis and Proposed Power-Aware Scheduling Algorithm in Cloud Computing;relationship Between Community Structure and Clustering Coefficient;digital Image Forensics-Image Verification Techniques;energy Efficient data Centre Selection Using Service Broker Policy;using Automated Predictive Analytics in an Online Shopping Ecosystem;design and Development of Home Automation System;performance analysis Study of Stochastic Computing Based Neuron;Scheduling of Parallel Tasks in Cloud Environment Using DAG MODEL;GREENIE—Smart Home with Smart Power Transmission;ANAVI: Advanced Navigation Assistance for Visually Impaired;THIRD EYE—Shopfloor data Processing and visualization Using Image Recognition;A Hybrid Search Group Algorithm and Pattern Search Optimized PIDA Controller for Automatic Generation Control of Interconnected Power System;Fractional Order PID Controlled PV Fed Quadratic Boost Converter TZ Source Inverter Fed Permanent Magnet Brushless Motor Drive;co-ordinate Measurement of Roll-Cage Using Digital Image Processing;peformance analysis of Joysticks Used in Infotainment Control System in Automobiles;Probabilistic Principal Component analysis (PPCA) Based Dimensionality Reduction and Deep Learning for Cancer Classification;blockchain Technology for data Sharing in Decentralized Storage System;Understanding Concepts of Blockchain Technology for Building the DApps;chennai Water Crisis—data analysis.

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Visual Analytic Study on Vehicle Target Detection Driven by CiteSpace

Visual Analytic Study on Vehicle Target Detection Driven by ...

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Computer Information Science and Application Technology (CISAT), International conference on

作者： Hongwei Wang Shuaitao Ren Hua Zhou Chuang Kong College of Big Data and Intelligent Engineering Southwest Forestry University Kunming China

ISBN: (数字)9798350375107

ISBN: (纸本)9798350375114

As a critical issue in computer vision and image processing, vehicle target detection plays a vital role in boosting vehicle recognition accuracy and information extraction efficiency, directly influencing applications such as autonomous driving, traffic monitoring, and safety management. This study employs CiteSpace tool to conduct an extensive visualization analysis of 2,641 scientific publications on vehicle target detection from the Web of Science Core Collection between 2019 and 2024, aiming to uncover research dynamics, core topics, collaboration networks, and future trends in this field. By designing a meticulous search strategy, we focus on the most authoritative SCI and SSCI literature and utilize CiteSpace version 6.3.1 for in-depth data mining and analysis. The findings reveal that deep learning, feature extraction, autonomous driving, and intelligent sensing technologies hold central positions in vehicle target detection, with significant contributions from authors like Li, Wei. A prolific research team, led by Yang, Jian, Zhang, Yu, and He, You, has emerged. Keyword analysis discloses that “object detection,” “deep learning,” and “feature extraction” are the most recurrent research foci, while “aerial vehicle” constitutes a persistent research hotspot, indicating the growing importance of drone technology and novel deep learning models, such as “Swin Transformer,” in enhancing detection efficiency and intelligence. Furthermore, the study identifies auto-target recognition and detection techniques in low-observable environments as key areas of interest, with a technological development trend leaning towards more intelligent and efficient solutions. Integration of drone systems and interdisciplinary technology fusion are expected to significantly advance vehicle target detection technology. This research not only quantifies the growth of research activities but also predicts potential future directions through keyword burst analysis, providing valuable in

关键词： Deep learning Target recognition Collaboration Object detection Market research Feature extraction Transformers Sensors Autonomous vehicles Drones

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