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检索条件"任意字段=2025 International Conference on Visual Analytics and Data Visualization, ICVADV 2025"

共 614 条记录，以下是311-320 订阅

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Bibliometric Analysis of Sustainable Digital Technologies for Reducing Waste in the Food Supply Chain

Bibliometric Analysis of Sustainable Digital Technologies fo...

引用

Advanced Research in Computing (ICARC), international conference on

作者： Kavith Balachandra Niles Perera Department of Transport Management and Logistics Engineering Faculty of Engineering University of Moratuwa Katubedda Sri Lanka

ISBN: (数字)9798331530983

ISBN: (纸本)9798331530990

Digital Technologies are significant in improving transparency and reducing wastage in organizational settings. This study examines the digital technologies and innovations involved in the food supply chain. The literature outlines that these technologies can significantly reduce waste and enhance transparency throughout the supply chain. Therefore, this study aims to identify sustainable technologies within the food supply chain that contribute to reducing food waste at sourcing, production, and distribution. This paper’s methodology involves conducting a bibliometric analysis. The analysis uses data from Scopus database articles published between 2004 and 2024 (October). The analysis evaluates the trends in journals, authorship, and keywords to analyze research findings. The visual representations of the above analysis are generated using VOSviewer. This study outlines that literature is discussed more on blockchain and IoT as key technologies. Blockchain improves transparency and traceability. IoT monitors conditions like temperature to prevent spoilage. AI and predictive analytics optimize operations and reduce waste. Mobile apps enhance collaboration and logistics. These technologies offer significant benefits. However, adoption requires customized strategies due to cost and complexity

关键词： Temperature sensors Temperature measurement visualization Technological innovation Supply chains Bibliometrics Production Blockchains Predictive analytics Monitoring

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Concept and Considerations for the Development of an Information database for Efficient international Freight Transport

Concept and Considerations for the Development of an Informa...

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international conference on Computational Cybernetics (ICCC)

作者： Petra Opitz Tamás Haidegger Enikö Nagy John von Neumann Faculty of Informatics Óbuda University Budapest Hungary University Research and Innovation Center (EKIK) Óbuda University Budapest Hungary School of Computing Queen's University Kingston ON John von Neumann Faculty of Informatics Óbuda University Antal Bejczy Center for Intelligent Robotics Budapest Hungary

ISBN: (数字)9798331502461

ISBN: (纸本)9798331502478

international freight transport is a growing market and a crucial component of the global economy, enabling the seamless flow of goods across regions and supporting global trade. However, the industry faces significant challenges, particularly in road transport orchestration, due to the increasing complexity of operations and the demand for real-time decision-making. This study sketched the algorithmic and programming framework to address these challenges by presenting an optimized database architecture designed to improve decision support systems for freight transport. The proposed system architecture may leverage the flexibility and scalability of NoSQL databases to manage large, semi-structured datasets in the future, while REST APIs enable seamless integration and real-time data manipulation. To enhance usability and transparency, the system incorporates advanced data visualization tools, allowing stakeholders to derive actionable insights and improve operational efficiency. By focusing on areas such as real-time tracking, sustainability, and process optimization, this work not only addresses current operational needs but also provides a robust foundation for future developments, including advanced analytics and mobile application integration. This contribution supports the logistics industry's shift toward more adaptive, efficient, and sustainable transport solutions.

关键词： Industries NoSQL databases data visualization Systems architecture Real-time systems visual databases Usability Sustainable development Optimization Logistics

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CricketAnalyzer: a smart camera-based system for accurate ball speed detection in cricket

CricketAnalyzer: a smart camera-based system for accurate ba...

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international conference on Energy, Power, Environment, Control and Computing (ICEPECC 2025)

作者： Tassadaq Hussain Amna Haider Muhammad Haris Center for AI and Big Data Namal University Mianwali Pakistan Pakistan Supercomputing and UCERD Islamabad Pakistan

ISBN: (数字)9781837243150

Accurate and real-time speed detection of moving objects, such as sports balls, is crucial for sports analytics and performance evaluation. Traditional systems, such as radar guns, are used to detect object speed, but they face issues such as high costs, limited flexibility, and dependency on controlled environments. In this work, we introduce an advanced visual camera-based ball speed detection application, CricketAnalyzer. CricketAnalyzer uses the Yolov11 model for object detection and real-time motion analysis. The CricketAnalyzer identifies the ball and calculates its velocity in various scenarios. The CricketAnalyzer application is deployed on the PakSupercomputing cluster, offering a cost-effective, scalable, and highly accurate solution. It also serves as a potential tool for sports analytics and broader use cases.

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CoDAQ: Congressional-Based data Imputation for Aggregate Queries

CoDAQ: Congressional-Based Data Imputation for Aggregate Que...

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2025 IEEE international conference on Big data and Smart Computing, BigComp 2025

作者： Sharaf, Mohamed A. Kochunni, Nishi Helal, Heba El Harrouss, Omar UAE University College of Information Technology Al Ain United Arab Emirates

visual analytics are widely used across various domains, including business intelligence, healthcare, and e-commerce, to provide data-driven insights that enhance decision-making processes. These systems analyze large datasets to generate visualizations that help users identify trends, patterns, and actionable insights. These insights rely heavily on accurate and complete data. However, effectively addressing the challenges posed by missing data is crucial for ensuring the accuracy and reliability of data-driven insights and visualizations. Incomplete datasets often lead to reduced accuracy in visualizations, prompting users to adopt costly imputation strategies to clean the data. This paper presents an innovative approach, 'CoDAQ'-Congressional-Based data Imputation for Aggregate Queries that explores the use of a stratified-based selection technique for imputation to handle missing values within a specified imputation budget effectively. CoDAQ strategically selects cells for imputation by analyzing missing data patterns across different groups, ensuring a structured and representative approach. This technique offers enhanced accuracy and consistency over baseline methods. Our findings illustrate how the proposed technique enhances the utilization of available data, improves the accuracy of visualizations, and reduces bias in analysis, ultimately increasing the performance of visual analytics. © 2025 IEEE.

关键词： Large datasets

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Audio-visual Deepfake Detection With Local Temporal Inconsistencies

Audio-Visual Deepfake Detection With Local Temporal Inconsis...

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international conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Marcella Astrid Enjie Ghorbel Djamila Aouada Interdisciplinary Centre for Security Reliability and Trust (SnT) University of Luxembourg Luxembourg Cristal Laboratory National School of Computer Sciences (ENSI) Manouba University Tunisia

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

This paper proposes an audio-visual deepfake detection approach that aims to capture fine-grained temporal inconsistencies between audio and visual modalities. To achieve this, both architectural and data synthesis strategies are introduced. From an architectural perspective, a temporal distance map, coupled with an attention mechanism, is designed to capture these inconsistencies while minimizing the impact of irrelevant temporal subsequences. Moreover, we explore novel pseudo-fake generation techniques to synthesize local inconsistencies. Our approach is evaluated against state-of-the-art methods using the DFDC and FakeAVCeleb datasets, demonstrating its effectiveness in detecting audio-visual deepfakes.

关键词： Deepfakes visualization Attention mechanisms Signal processing data augmentation Acoustics Speech processing

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Cricket Shot Analysis using Conditional Directed Spatio-Temporal Graph networks

Cricket Shot Analysis using Conditional Directed Spatio-Temp...

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international Image Processing, Applications and Systems conference (IPAS)

作者： Tanu Aneja Brejesh Lall Harsha Malaviya

ISBN: (数字)9798331506520

ISBN: (纸本)9798331506537

Recent Use of Conditional Spatio-temporal Directed Graph Convolutional Networks(Cond ST-DGCN) [8] to represent human pose estimation has significantly helped in capturing varying non-local dependencies between limbs for different actions. This can be immensely helpful in Sports analytics where player pose plays key role in shot evaluation and can help in corrective action. In this article, we propose CondDGCN [8] based framework to explore use of spatial-temporal relation of batsman shot sequences (labelled and annotated 2D cricket dataset [1]) for Cricket shot action recognition by conditioning the graph network on batsman 2D poses. We achieve 97% accuracy for shot recognition and further explore visualization of conditional graph connections to establish importance of particular limbs for shots. The proposed framework uses fine-tuned 2D Pose estimator OpenPose [11] (fine-tuned for cricket dataset [1]) which in turn helps in easy adaptation of our solution to internet cricket videos for shot analytics.

关键词： Limbs Computer vision Graph convolutional networks visual analytics Image processing Pose estimation Directed graphs Computer architecture Sports Videos

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data analytics for Decision Support Systems in Techno-Driven Enterprises

Data Analytics for Decision Support Systems in Techno-Driven...

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Advances in Computer Science, Electrical, Electronics, and Communication Technologies (CE2CT), international conference on

作者： Rakshitha Priya S Asmita Namjoshi Mahesh Mane Irshadullah Asim Mohammed Rashmitha Shettigar Department of AIML NITTE University (Deemed to Be University) NMAMIT NITTE Udupi Karnataka India SRM Institute of Science and Technology Chennai TamilNadu India Tilak Maharashtra Vidyapeeth Pune India Automotive Design and Development/Engineering Symbiosis School for Online and Digital Learning Pune Maharashtra India FuelCell Energy Inc Syed Ali Chabutra Hyderabad India Department of IT/CS Thakur Ramnarayan college of arts and commerce Mumbai Maharashtra India

ISBN: (数字)9798331518578

ISBN: (纸本)9798331518585

In the digital transformation era the emergence of data analytics plays a significant role in enhanced decision making process in Techno driven Enterprises. The study examines about the impact of data analytics in decision support system to emphasise the role of data analytics on operational tactical and strategical decision making. The big data artificial intelligence and machine learning leverages modern DSS to process large amount of unstructured and structured data optimised performance and extraction of actionable insights in the businesses. The decision support system involves visualisation techniques real time processing of data and predictive analytics that empower the enterprise to make agile and informed decisions. Moreover, the study examines the challenges in security integration and data quality to offer solutions for enhanced and effective decision making. The findings of the study necessitate data driven culture in techno driven enterprises for maintaining competitive edge in the technological landscape.

关键词： Decision support systems data analysis data integrity data visualization Machine learning Market research Real-time systems Security Resource management Predictive analytics

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Emerging Trends and Analytical Perspectives in the Development of New Smartphones

Emerging Trends and Analytical Perspectives in the Developme...

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Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA), international conference on

作者： M C S Geetha Edric Jeffrey Sam Department of MCA Kumaraguru College of Technology Coimbatore India Department of Data Science Kumaraguru College of Liberal Arts and Science Coimbatore India

ISBN: (数字)9798331525439

ISBN: (纸本)9798331525446

With a brand offering more than 30 models, choosing a smartphone can be overwhelming for consumers. This study introduces a data-driven framework to streamline the decision-making process by showing only the top-performing models based on user-defined criteria such as budget, battery life, and performance. The research employs a comparative approach, analysing raw sales data to identify high-performing models while leveraging visualization techniques for intuitive representation. Predictive algorithms and real-time insights improve the accuracy and personalization of *** findings show that this framework reduces consumer confusion significantly, improves decision satisfaction, and aligns with modern consumer-centric strategies. However, data quality and model scalability are some of the challenges that need to be addressed for wider adoption. This study shows how a focused, data-driven approach can simplify smartphone selection, offering tailored solutions that empower users and improve their experience. Future work involves integrating user feedback and broader datasets to further develop and scale up the framework.

关键词： visual analytics Scalability Decision making Predictive models Prediction algorithms Real-time systems data models Batteries Telecommunication computing Performance analysis

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Temporal Dynamics of Consumer Engagement in E-Commerce

Temporal Dynamics of Consumer Engagement in E-Commerce

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Computing for Sustainability and Intelligent Future (COMP-SIF), international conference on

作者： Gomathi Thiyagarajan Swathi. Y Department of Computer Applications CMR Institute of Technology Bengaluru India Department of Computer Science and Engineering Gopalan College of Engineering and Management Bengaluru India

ISBN: (数字)9798331538538

ISBN: (纸本)9798331538545

This paper explores into an indepth analysis of consumer behavior on an e-commerce platform, extending the study period to include November 2019 through February 2020. Looking at user interactions that come under the categories of views, carts, purchases, and removals from cart along with process discovery visualizations will help identify complex patterns of engagement, measure the impact of interface changes and quantify marketing intervention's successes. This research uses sophisticated data analytics through process mining to provide recommendations for improving the e-commerce journey through increased user satisfaction and better conversion rates.

关键词： Process mining data analysis Consumer behavior data visualization Electronic commerce Sustainable development

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Scheduling Policies in Edge Computing for Real-Time Video analytics

Scheduling Policies in Edge Computing for Real-Time Video An...

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Intelligent data Communication Technologies and Internet of Things (IDCIoT), international conference on

作者： Shreevatsan S S Yasasree Lasya Annambhotla Anaswara Reji Shinu M Rajagopal Department of Computer Science and Engineering Amrita School of Computing Bengaluru Amrita Vishwa Vidyapeetham India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527556

This study compares different scheduling algorithms used in edge computing for real-time video processing. Instead of sending video data to cloud servers, the video is processed directly at the edge, reducing delays and saving bandwidth. The focus is on how different scheduling methods manage resources, prioritize tasks, and reduce the time it takes to analyze video. The algorithms are tested in simulated environments to understand how they impact system efficiency and performance. The goal of this work is to find the best scheduling policies for real-time video processing at the edge, improving overall system performance and scalability.

关键词： Scheduling algorithms visual analytics System performance Scalability Streaming media Load management Real-time systems Servers Edge computing Testing

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