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

共 568 条记录，以下是11-20 订阅

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Predictive Maintenance for Electric Motors, RPM data, Machine Learning for Proactive Life Cycle Management

Predictive Maintenance for Electric Motors, RPM Data, Machin...

引用

2025 international conference on visual analytics and data visualization, icvadv 2025

作者： Kumar, Mamilla Chetan Brindha, D. Reddy, Ettedi Rishwanth Karunya University Department Cse Coimbatore India

ISBN: (纸本)9798331521394

The research develops predictive maintenance as a solution which prevents unexpected electric motor breakdowns. The objective remains to develop a machine learning algorithm for Remaining Useful Life (RUL) prediction which utilizes RPM (Revolutions Per Minute) values as input data. Past RPM data training of an autoencoder allows detection of anomalies while it predicts motor performance for proactive planning of maintenance activities. Real-time monitoring and visualization becomes possible through the implementation of this solution which functions using Python and streamer application. Their predictive model connects motor deterioration patterns to create double benefits of operational savings through decreased device downtime coupled with accident failure prevention and reactive maintenance improvement to predictive maintenance. The proposed model should be expanded to include new equipment types while new sensor integration will boost accuracy levels. © 2025 IEEE.

关键词： Predictive maintenance

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Design and Evaluation of a Hybrid Adder Employing the Power Gating Method

Design and Evaluation of a Hybrid Adder Employing the Power ...

引用

visual analytics and data visualization (icvadv), international conference on

作者： Sowmiya K S.Praveen Kumar T. Aravind S. Ramya Department of Electronics and Communication Engineering Saveetha Engineering College Chennai India

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

The multiplexers (mux) select the final sum and carry, rendering the CSLA an inefficient area adder. Two rows of ripple carry adders are present. While the suggested AFPL logic can reduce power dissipation in the CBL based SQRT CSLA, the CBL based SQRT CSLA is preferred to address the problems of area efficiency and latency. The major objective is to use AFPL logic to develop a CBL-based SQRT CSLA-hybrid adder that will increase speed and reduce power dissipation.

关键词： Multiplexing visual analytics data visualization Logic gates Rendering (computer graphics) CMOS technology Hybrid power systems Power dissipation Logic Adders

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Lightweight Contextual LLMs for IoT data Interpretation in Smart Cities

Lightweight Contextual LLMs for IoT Data Interpretation in S...

引用

2025 international conference on visual analytics and data visualization, icvadv 2025

作者： Kannadasan, Tamilarasan Independent Researcher TX United States

ISBN: (纸本)9798331521394

While the populations in cities are growing, the need for smart cities to optimize resources and life quality is increasingly a pressing matter. At the heart of this transformation lie the IoT devices creating massive volumes of data to be interpreted in real time. This paper introduces the Lightweight Contextual Large Language Models designed for efficient processing of IoT data in Smart Cities. In the approach proposed, advanced model pruning and knowledge distillation are used, keeping the solution computationally efficient with no sacrifice in interpretative power. We validate our model's effectiveness on the UrbanSensing dataset in anomaly detection, predictive maintenance, and analytics of engagement on tasks involving citizens. Our framework allows feasibility on edge devices with a 40% reduction in inference time and up to 50% decrease in computational overhead, thus guaranteeing scalability and sustainability in real-world smart city applications. The findings bridge the gap from computational efficiency to contextual understandings, thereby offering the premise for enhanced urban resilience and wiser decision-making. © 2025 IEEE.

关键词： Sentiment analysis

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Design and Development of a Mobile Application for Direct Agricultural Market Access

Design and Development of a Mobile Application for Direct Ag...

引用

2025 international conference on visual analytics and data visualization, icvadv 2025

作者： Manikandan, G. Nivetha, S.B. Sri Siva Swathika, S.T. Narmthaa, J.B. Rm, Srijhha R.M.K. Engineering College Department of Artificial Intelligence and Data Science Tiruvallur Kavaraipettai India

ISBN: (纸本)9798331521394

In developing countries, the conventional agricultural supply chain relies significantly on middlemen, which often leads to farmers receiving merely 20-40% of the retail price. This system not only diminishes farmers' earnings but also raises prices for consumers. This paper investigates the advantages of direct market access through digital platforms, which eliminate intermediaries and allow farmers to connect directly with consumers and retailers. Utilizing these platforms can boost farmers' incomes by as much as 50%, while also improving transparency and efficiency in the supply chain. The research offers a comprehensive examination of the economic, technological, and social effects of direct market access, as well as addressing major challenges concerning platform adoption, scalability, and connectivity in rural areas. © 2025 IEEE.

关键词： Crops

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A Survey of visualization Techniques for Digital Twins 20th

A Survey of Visualization Techniques for Digital Twins

引用

20th international conference on Computing in Civil and Building Engineering, ICCCBE 2024

作者： Paziraei, Mahsa Motamedi, Ali Québec Université MontréalQCH3C 1K3 Canada

ISBN: (纸本)9783031842078

In today’s fast-evolving technological landscape, digital twins are emerging for understanding and managing complex systems and to assist stakeholders in the process of informed decision-making. Despite the growing importance of this technology, there exists a noticeable gap in the literature, with limited attention devoted to crafting effective visualization techniques tailored specifically to digital twins. To rectify this gap, this paper’s primary objective is to conduct a thorough examination of existing research, encompassing a diverse array of use cases benefiting from various visualization techniques. This comprehensive inquiry has led to the categorization of visualization techniques based on data types, specific use cases, interactivity requirements, and system complexity. The outcomes can be used by researchers and industry practitioners to better design and implement data visualization interfaces for their developed digital twins, allowing visual analytics and heuristic problem solving using integrated data of digital twins. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： visual analytics

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Software Tools and Evaluation Models for visual analytics: Trends, Challenges, and Future Directions

Software Tools and Evaluation Models for Visual Analytics: T...

引用

2025 international conference on visual analytics and data visualization, icvadv 2025

作者： Lakumarapu, Srikanth Sudha, P. Ruba Pajila, P.J. Beslin Sasirekha, K. Vinoth, R. Siva Subramanian, R. Cvr College of Engineering Department of Cse Telangana India S.A Engineering College Dept of Cse India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Dept of Cse India R.M.D Engineering College Dept of Csbs India Rmk College of Engg and Tech Department of Cse India Rmk College of Engg and Tech Dept of Cse India

ISBN: (纸本)9798331521394

visual analytics (VA) is a complex interdisciplinary field which applies data visualization and analysis methods in order to extract knowledge from Big data. This paper aims at presenting an overview of the most common software tools and assessment frameworks for VA with an emphasis on the open source, commercial and specific tools for BI, healthcare and scientific purposes. It discusses the issues that VA has concerning varied data types, their usability and how the system can be expanded to accommodate large data sets. The paper also considers recent trends in AI and machine learning, virtual and augmented reality, and synchronous shared environments. Privacy and data bias issues are also drawn out as ethical concerns. Last, the paper presents the directions of further research to enhance the efficiency and usability of VA tools and make them more ethical in data decision-making. © 2025 IEEE.

关键词： Video analysis

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A data-Driven Approach for Early Detection and Prevention of Diabetes Mellitus Using Machine Learning

A Data-Driven Approach for Early Detection and Prevention of...

引用

2025 international conference on visual analytics and data visualization, icvadv 2025

作者： Nithya, B. Asha, V. Sreeja, S.P. Amit Yadav, V. Aditya, M. Rai, Abhishek New Horizon College of Engineering Department of Mca Bengaluru India

ISBN: (纸本)9798331521394

Diabetes is a common health issue in India that impacts the quality of life and overburdens healthcare resources. Prevention and early detection are the keys to controlling its effects. This research applies Indian demographic and health statistics to forecast diabetes risk through machine learning. KNearest Neighbors (KNN), Logistic Regression, Decision Tree, Support Vector Machine (SVM), and Random Forest were experimented upon for predictive efficiency. Great preprocessing of data was done to manage missing values and features normalization to make the model reliable. Random Forest yielded the maximum accuracy of 94.50% among the algorithms tested, proving the efficiency in predicting diabetes. The results unveil the promise of machine learning in medicine for early diagnosis and focused treatment approaches. © 2025 IEEE.

关键词： Diagnosis

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A Hybrid B-Tree and Enhanced Merkle Hash Tree Approach for Secure Cloud data Management

A Hybrid B-Tree and Enhanced Merkle Hash Tree Approach for S...

引用

2025 international conference on visual analytics and data visualization, icvadv 2025

作者： Thiruneelakandan, S. Eliyas, Sherin Sathish Kumar, M. Hindustan Institute of Technology and Science Department of Computer Application TamilNadu Chennai India Hindustan Institute of Technology and Science Department of Computer Applications TamilNadu Chennai India

ISBN: (纸本)9798331521394

data security, integrity verification, and efficient retrieval issues are much more pronounced with large datasets in cloud storage systems. The angle of this paper is the proposal of hybrid architecture of AES, EMHT, B-tree indexing, and POR techniques to complete the optimization of cloud operations. The way the system was evaluated against the traditional approaches was based on several key metrics such as encryption time, integrity verification time, update time, and memory usage for datasets up to the 15GB limit. The experimental results show that the proposed system has 6.50% less verification time and 38.44% better update time when compared to existing methods without compromising the effectiveness of encryption. These indicate that the proposed approach is cost-effective, secure, and scalable in a large-scale cloud storage environment. The contribution of this paper is a practical solution for future enhanced data management and security in modern cloud systems. © 2025 IEEE.

关键词： Information management

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Improving Handwritten Stenography Recognition Using Domain Specific Encoding and Synthetic data Augmentation

Improving Handwritten Stenography Recognition Using Domain S...

引用

2025 international conference on visual analytics and data visualization, icvadv 2025

作者： Nivetha, S. Kamatchi, C. Bala Hindustan Institute of Technology and Science Department of Computer Applications India

ISBN: (纸本)9798331521394

Handwritten form of stenography recognition is a challenging task due to high variations in shorthand symbols and a lack of annotated datasets. A strong baseline for stenographic text recognition, leveraging the newly created LION dataset of shorthand manuscripts. To alleviate symbol ambiguity as well as low-resource constraints in this domain, incorporating stenographic domain expertise is proposed through encoding schemes and synthetic data generation. In the experiments, a Gated-CNN-BGRU architecture is used, trained with Connectionist Temporal Classification (CTC) loss. Pre-train on synthetic data and fine-tuning on real data greatly improve CER and WER. The experiments showed the effectiveness of stenography-specific encoding schemes in improving WER (Word Error Rate) over baseline models by up to 10% when using Melin-based encodings. This work opens pathways for transcribing historical stenographic manuscripts more effectively. © 2025 IEEE.

关键词： Deep learning

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Smart Energy Forecasting: Energy Consumption Prediction in data Centers

Smart Energy Forecasting: Energy Consumption Prediction in D...

引用

2025 international conference on visual analytics and data visualization, icvadv 2025

作者： Kumar, Kanapareddy Nithin Chethan, C. Priya, S. School of Computing Srm Institute of Science and Technology Department of Computing Technologies Kattankulathur603203 India

ISBN: (纸本)9798331521394

The rapid expansion of data centers has been driven by the growing demand for digital services. As a consequence, the energy usage follows the real challenges in terms of cost and environmental effect. As a result, this study proposes a hybrid technique for predicting energy consumption in data centers that combines machine learning approaches, notably Long Short-Term Memory (LSTM) networks and Auto-Regressive Integrated Moving Average (ARIMA) models. This approach builds a model capable of accurately capturing both short-term variations and long-term trends in energy consumption. As a model for optimizing energy use in data centers, the suggested approach would save costs while potentially contributing to sustainability through improved operational efficiency. This research also shows the need for real-time prediction techniques in energy management while making decisions that support processes with a visual dashboard and alert system for mitigating risks of overconsumption of energy. © 2025 IEEE.

关键词： Risk perception

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