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

共 522 条记录，以下是111-120 订阅

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Evaluation of Teacher Performance using HybPSOFA - A Hybrid Approach

Evaluation of Teacher Performance using HybPSOFA - A Hybrid ...

引用

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

作者： Sanskriti Agarwal Pitchika P N G Phani Kumar Junali Jasmine Jena Suchismita Das Manas Ranjan Nayak Mahendra Kumar Gourisaria School of Computer Engineering KIIT Deemed to be University Bhubaneshwar Odisha India

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

Evaluating teacher performance is essential for enhancing educational quality, but accurately estimating the performance is very challenging due to the complexity and subjectivity of the assessment criteria. It is a good real-time problem where optimization algorithms have utmost application. This paper investigates the use of metaheuristic algorithms, such as Particle Swarm Optimization (PSO), the Firefly Algorithm (FA) and proposed HybPSO-FA approach, to estimate the teacher performance. By combining the strengths of both PSO and Firefly algorithms, the hybrid technique aims to optimize performance estimation while minimizing computational complexity. The results of the proposed method indicate that the hybrid algorithm significantly outperforms the standalone methods in terms of achieving the optimal value for teacher performance evaluation and convergence speed. This study highlights the potential of using hybrid optimization techniques for performance evaluation in academics having various criteria, making them more reliable and efficient for use in educational institutions.

关键词： Performance evaluation visual analytics Metaheuristics Estimation data visualization Real-time systems Reliability Particle swarm optimization Computational complexity Convergence

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A Predictive Modelling for Breast Cancer Classification Using Machine Learning Technique

A Predictive Modelling for Breast Cancer Classification Usin...

引用

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

作者： Aradhana Pattnaik Junali Jasmine Jena Jay Prakash Singh Amiya Ranjan Panda Anjan Bandyopadhyay Mahendra Kumar Gourisaria School of Computer Engineering KIIT Deemed to be University Bhubaneswar Odisha India Dept of Computer Science & Engineering Manipal University Jaipur Jaipur Rajasthan India

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

One of the important health concern all over the globe is Breast Cancer in women. It is a complex disease that requires a thorough diagnosis before treatment can begin. This research paper explores the intervention of AI in treatment of breast cancer leveraged by using data balancing techniques. Using clinical and pathological data, machine learning is a potent tool for predicting its different forms. The effectiveness of several ML algorithms for classification of the same is investigated in this work. Models including Logistic Regression, Support Vector Machines etc. were trained and evaluated on a dataset with pertinent attributes. Some of the evaluation metrics were used to assess the models. Logistic Regression and AdaBoost classifier gave the most accurate outcome with an accuracy of 0.98 and outperformed other models. Efficacy of the models were supported by providing ROC curve of all models and confusion matrix of the best performing models.

关键词： Support vector machines Logistic regression Analytical models Accuracy visual analytics Machine learning Predictive models Prediction algorithms Breast cancer data models

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Optimal Placement of Solar Power Plant by Using AVOA Algorithm

Optimal Placement of Solar Power Plant by Using AVOA Algorit...

引用

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

作者： A. George Klington K. Karthikeyan Department of Computer science Engineering St. Mother Theresa engineering college Tuticorin India Department of Electrical and Electronics Engineering St. Mother Theresa Engineering College Tuticorin India

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

Infrastructure development and its design are more complex because of its constraint on budget and efficiency. By remembering these difficulties, a modified electrical structure is necessary for the nation. The power system structure should not depend on the conventional system. This main criterion is being in our engineer's mind. But, strengthening loads and their necessaries do not accept them to sleep. To face complex structures and constraints-based infrastructure facilities, optimal places for renewable systems are necessary. Here, the optimal placement of solar power plant is taken as the primary concern and its related analysis is made. Even though many algorithms are coming from all over the world. The part of those algorithms is not analyzed in many environments. In this paper, an AVOA algorithm is used for our analysis. This part of our research makes us excited with its results. The IEEE 57 system is used for the analysis.

关键词： Renewable energy sources Heuristic algorithms visual analytics Power system dynamics Stability criteria Voltage System integration Power system stability Robustness Optimization

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Parking Reservation and Smart Allocation using IoT

Parking Reservation and Smart Allocation using IoT

引用

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

作者： JaiAmudhan Dhakshinamoorthy Vishwa Varshini Viswanathan Yamuneswar Annadurai V.P. Dhivya Department of Information Technology K.S. Rangasamy College of Technology Tiruchengode India

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

Smart Parking System with Dynamic Slot Allocation Using IoT and Paging Method: The aim of this proposed parking system is enhancing the user experience within an urban environment and the development of parking efficiency. A traditional system is inefficient regarding poor slot utilization and also cannot perform dynamic re-allocation. The proposed parking system utilizes IR sensors to detect the space in real-time, and it uses Paging Method to optimize slot allocation. A mobile application allows slot pre-booking, receives updates, and processes secure payments. Automatic Number Plate Recognition ensures that only authorized people get access. With a dynamic reallocation of slots depending on the users, it manages time slots effectively. The Billing Module integrates within it to calculate fees automatically for seamless payment processing. This reduces congestion, increases utilization, and provides a scalable solution to the infrastructure of modern urban life.

关键词： visual analytics Urban areas Dynamic scheduling Real-time systems User experience Sensor systems Sensors Mobile applications Resource management License plate recognition

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AI- Powered Emotion Recognition: A Multimodal Approach to Analyzing Human Sentiment

AI- Powered Emotion Recognition: A Multimodal Approach to An...

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

作者： Shalma H Shreya Mukherjee Jainulabudeen S A K Borra Surya Thirumal Reddy Bhanu Budhati Nakka Shiva Krishna Department of Artificial Intelligence and Machine Learning Sphoorthy Engineering College Nadergul Hyderabad Department of Computer Science and Engineering College of Engineering and Technology Anna University Chennai Tamil Nadu India

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

AI-Powered Emotion Recognition: A Multimodal Approach to Analyzing Human Sentiment, we develop an advanced emotion detection system using cutting-edge AI techniques. By leveraging attention-based models, the system effectively analyzes and integrates multiple modalities, including facial expressions, voice tone, and textual sentiment, to deliver an accurate and nuanced understanding of human emotions. Attention mechanisms allow the model to focus on the most significant features across these modalities, capturing tiny emotional cues that may otherwise be overlooked. This multimodal approach not only enhances the accuracy of emotion detection but also improves engagement analysis, making it particularly suited for applications in mental health, education, customer service, and human-robot interaction. Through this project, we aim to showcase the power of AI in providing a more empathetic and emotionally- aware interface, pushing the boundaries of intelligent systems in understanding complexhuman sentiment

关键词： Emotion recognition Accuracy Attention mechanisms Customer services visual analytics Scalability Education Mental health Speech recognition Robustness

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A Review on Development of Farmers Disease Diagnostics and Reporting Using Machine Learning Techniques

A Review on Development of Farmers Disease Diagnostics and R...

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

作者： Moresh M Mukhedkar Vaishali V Thorat Bhakti A Mukhedkar Sonali V Jadhav Nitin A Dawande Chetana V Thorat E&TC Engineering Department School of Engineering and Technology D Y Patil University Pune India Computer Engineering Department School of Engineering and Technology D Y Patil University Pune India Computer Engineering Department Pimpri Chinchwad College of Engg. SPPU Pune University India

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

The Agricultural Portal is a helpful online tool designed to make farming easier and more productive. It gives farmers quick access to important agricultural information, resources, and tools. With features like weather forecasts, advice on managing pests and diseases, tips for keeping soil healthy, crop planning tools, and updates on market prices, this portal covers a wide range of needs. This paper explains how the Agricultural Portal was developed, describes its main features, and shows how it benefits farmers by boosting productivity, helping them make better decisions, and increasing their profits. Built on reliable technology, the portal can be adapted to support farmers of different sizes and locations. It's designed to be easy to use on various devices, including mobile phones and tablets, making it accessible to more people.

关键词： Support vector machines Productivity Reviews visual analytics Weather forecasting Soil Planning Reliability Portals Diseases

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Skin Lesion Detection Using Partial Differential Equations

Skin Lesion Detection Using Partial Differential Equations

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

作者： D. Sree Lakshmi A. Divya Gayathri Yadav Mugada Tanusha Koduru Mownika Bingi Ishwarya Madupu Department of Computer Science and Engineering Prasad V Potluri Siddhartha Institute of Technology Vijayawada India

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

The technique used for image interest segmentation is known as segmentation. Processing pixels with matching attributes helps to accomplish this segmentation. Regions of this image become easier to process through part-based methods while avoiding complete image processing. The standard use of segmentation in pictures involves detecting objects as well as their edges. Technical image segmentation functions to break images into basic elements before creating a simplified understanding for easy analysis. A version of the image with reduced dimensions composed of uniform areas displaying similar visual patterns would serve as the best preference. Every image region must have a smooth intensity value that changes abruptly only at the region boundaries. The main segmentation approaches include one method for detecting original image objects and their contours. Edge detection systems produce matching results through the comparison of deformable curves with object contours by defining energy functional principles.

关键词： Image segmentation Accuracy Partial differential equations Image edge detection visual analytics Feature extraction Wavelet analysis Skin Mathematical models Lesions

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Sentiment Analysis in Financial Markets: Using NLP to Predict Stock Price from News and Social Media data

Sentiment Analysis in Financial Markets: Using NLP to Predic...

引用

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

作者： S T Surulivel M Ashfaq Sultan K Ajithkumar S Selvabaskar School of Management SASTRA Deemed University Thanjavur Tamil Nadu India

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

This research explores the application of NLP techniques to forecast changes in stock prices by applying sentiment analysis based on views expressed by the public in 51 news stories and 28 social media posts. Investor sentiment plays a crucial role in influencing market volatility and price trends. This study specifically focuses on Tesla Inc. (TSLA) as a case study, collecting data for a period of one month (October 1 to November 2). Sentiment data was sourced from Alpha Vantage for news articles and Reddit for social media posts. Sentiment scoring was conducted using VADER and TextBlob, with polarity values between -1 (negative) to +1 (positive). The correlation analysis between sentiment scores and Tesla's daily closing prices actually presents a weak positive correlation, with the VADER social media sentiment scoring the highest correlation value of +0.2332. The results indicate that, although social media sentiments present a moderate association with stock price movements, news data is neutral. This study highlights real-time public sentiment as a supplementary tool for financial forecasting and, thus, draws significant implications for investment strategies and market trend analysis.

关键词： Sentiment analysis Correlation Accuracy Social networking (online) Mood visual analytics Predictive models Market research Real-time systems Stock markets

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Multi-Factor Authentication for Secured Financial Transactions Through Spatio-TGCN Model

Multi-Factor Authentication for Secured Financial Transactio...

引用

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

作者： Bhagwan Jagwani Abbasov Habib Hasan Kuldeep Agnihotri Khushbu Jain Anvesh Perada D. Gobinath Department of Management PSIT College of Higher Education Kanpur Uttar Pradesh India Department of Mathematics and ICT Baku Eurasian University Azerbaijan ISBA Group of Institutes Indore Madhya Pradesh India Department of Commerce and Management ISBA Group of Institutes Indore Madhya Pradesh India Department of Electrical and Computer Engineering Drexel University Philadelphia Pennsylvania USA Department of AIML CMR University Bangalore Puducherry India

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

In the information economy, online financial transactions must be secure. Digital platforms for everyday transactions put financial services customers at danger of fraud and unauthorized access. This research integrated machine learning and multi-factor authentication to secure online financial transactions. System steps include data preparation, feature extraction, and model training. data preparation includes data normalization, label encoding, white space removal, and socket information removal. Feature extraction strengthens variable association to improve model predictive ability. The suggested model uses spatio- TGCN for training. We found that the proposed model outperforms GCN and CNN. Comparing to other models, the framework's 91.40% accuracy rate suggests it could safeguard online financial transactions. This method may make internet financial transactions safer.

关键词： Training Multi-factor authentication Accuracy visual analytics Sockets White spaces Feature extraction Encoding data models Fraud

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Delay-Phase Optimization for Hybrid Precoding in WideBand Massive MIMO System*

Delay-Phase Optimization for Hybrid Precoding in WideBand Ma...

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

作者： T Siva Kumar V Dinesh T Gowsik R Ajay Raghav V Mahendran Department of Electronics and Communication Engineering M.Kumarasamy College of Engineering Karur Tamilnadu India

ISBN: (数字)9798331521394

ISBN: (纸本)9798331521400

The ultra-wideband nature of terahertz (THz) communication introduces unique challenges, such as beam splitting and frequency-dependent steering vector mismatches, which can significantly degrade the performance of massive MIMO systems. This paper proposes a timedelay hybrid precoding architecture to mitigate the effects of beam squint and angular spread in THz wideband systems. By modeling the THz channel using both path-based and cluster-based approaches,the proposed architecture introduces frequency-dependent phase shiftsto align with the clustered channel characteristics. Extensive simulations validate the superiority of the proposed method, demonstrating a 12 percentage improvement in achievable data rates compared to conventional hybrid precoding methods under clustered channel conditions. Additionally, the proposed approach maintains over 90percantage of the theoretical maximum achievable rate, even in scenarios with high angular spread. The results highlight the efficiency of the proposed architecture in optimizing spectral efficiency and mitigating array gain loss, making it a promising solution for future 6G wireless networks.

关键词： Training Spectral efficiency Precoding Wireless networks visual analytics Massive MIMO Vectors Wideband Terahertz communications Ultra wideband technology

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