检索结果-内蒙古大学图书馆

3rd International Conference on Applied Artificial Intelligence and Computing, ICAaiC 2024

作者： Aakash, Kasukurthy Reyana, A. Karunya Institute of Technology and Sciences Division of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350375190

With the increasing scrutiny of Bitcoin and other cryptocurrencies in recent years, there is a growing significance in studying methods to predict their values, including sentiment analysis on Twitter-collected data. The primary objective is to perform sentiment analysis on Bitcoin prices and examine the predictive accuracy of various machine learning algorithms. The approach cleans up Twitter data that is relevant to Bitcoin. Followed by quantifying people's opinions on Bitcoin using sentiment analysis. With this data and Bitcoin's price history, a binary target variable for price movement is built to specify the price variations. In order to predict the changes in Bitcoin price, several machine learning models are developed and evaluated. Among these models are Long Short-Term Memory networks, Decision Trees, Random Forests, and Linear Discriminant Analysis are mostly applied. The proposed approach is the enhanced Random Forest base classifier to improve the prediction accuracy. With an F1-score of 64% and 70% accuracy, the Enhanced Random Forest model performs better than the existing models. This model illustrates how sentiment analysis and machine learning may be combined to forecast cryptocurrency prices. © 2024 IEEE.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Al-Proctored Exam Portal with Mobile Companion Application 3

Al-Proctored Exam Portal with Mobile Companion Application

引用

3rd International Conference on Applied Artificial Intelligence and Computing, ICAaiC 2024

作者： Daniel, Ronald C Caleb Andrew, H. Karunya Institute of Technology and Sciences Division of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350375190

Upholding academic integrity during exams has always been difficult in the world of online learning. We provide a novel approach to solve this problem: an ai-proctored exam Portal combined with a mobile companion app. This solution uses artificial intelligence for proctoring and enables instructors to prepare and conduct exams safely. The site includes elements like multiple-choice exams, written assessments with a question bank, and integrated course modules with quizzes and videos. With the use of ai algorithms, the exam process is tracked in real time, and each student receives a thorough report. Additionally, the mobile companion app improves the assessment process's integrity by acting as an additional monitoring tool and giving a side view of the student during the test. This article describes the architecture, functionality, and use of the ai-Proctored Exam Portal and its accompanying mobile application, emphasizing the platform's effectiveness in guaranteeing transparent and equitable testing in the online learning environment. © 2024 IEEE.

关键词： E-learning

来源：评论

学校读者我要写书评

暂无评论

Social Media Text Analysis for Disaster Management Using DistilBERT Model

Social Media Text Analysis for Disaster Management Using Dis...

引用

2024 International Conference on science, Technology, engineering and Management, ICSTEM 2024

作者： Varghese, Sherin R. Juliet, Sujitha Athish, N.S. Division of Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore India

ISBN: (纸本)9798350376913

There is no doubt on the fact that disasters like floods, earthquakes and other man-made ones have a destructive impact on human lives. Timely response is crucial to minimize the casualties and aid recovery. Social media in such times, are vital as people share experiences, news and request assistance. This study investigates the efficiency of Transformer-based models for fine-grained sentiment analysis of disaster tweets on social media. Five models, including Distil-BERT, are compared and analyzed using Twitter data. The analysis categorises tweets into ten classes reflecting human sentiments during a disaster. Model performance is evaluated using accuracy, precision, recall, F1-score and execution time. While all the models demonstrate strong performance, Distil-BERT achieved comparable accuracy with a significant reduction in training and execution time (45%-55%). These findings suggest the potential of Distil-BERT (Distilled BERT) as the core component in disaster management applications;enabling organizations to gain a deeper understanding of the multifaceted public sentiment during disasters and make informed decisions for improved public aid and resource allocation. © 2024 IEEE.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

Quorum-based Tier Approach: Integrating PBFT and PoS in a Hybrid Consensus Mechanism 3

Quorum-based Tier Approach: Integrating PBFT and PoS in a Hy...

引用

3rd International Conference on Automation, Computing and Renewable Systems, ICACRS 2024

作者： Abinivesh, S. Isravel, Deva Priya Dhas, Julia Punitha Malar Division of Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore India

ISBN: (纸本)9798331532420

Blockchain technology is an advanced system centered around the concept of a shared and immutable ledger, emphasizing decentralization, security, and transparency. Transactions on a blockchain are securely linked through cryptographic hashes, forming blocks. A fundamental component of blockchain is the consensus mechanism, which comes in various types, each with its own advantages and limitations. For instance, Proof of Work (PoW) faces challenges related to energy consumption, while Proof of Stake (PoS) is susceptible to certain attacks. This paper proposes a hybrid consensus mechanism that integrates Practical Byzantine Fault Tolerance (PBFT) and Proof of Stake (PoS) using a quorum-based tier approach. This new hybrid model combines the refined features of both PoS and PBFT to create a hierarchical structure for reaching consensus. Nodes are categorized into high-tier and low-tier groups, with the consensus process primarily involving high-tier nodes. Low-tier nodes serve as backups in situations like network issues or node failures. Through experimentation it is evident that the hybrid consensus mechanism achieves a balance between decentralization and energy efficiency. The results demonstrate that this newly developed mechanism outperforms several existing consensus algorithms in terms of throughput and latency. © 2024 IEEE.

关键词： Decentralized control

来源：评论

学校读者我要写书评

暂无评论

A Novel Framework for Iris Disease Detection Using MobileNetV2 and CNN with Streamlit Interface 10

A Novel Framework for Iris Disease Detection Using MobileNet...

引用

10th International Conference on Communication and Signal Processing, ICCSP 2024

作者： Abinay Shri, J. Denisha, M. Karunya Institute of Technology and Sciences Division of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350353068

'Iris Disease Detection' project is a comprehensive approach to iris health assessment that combines deep learning techniques with image processing methodologies. The system consists of a Streamlit-based web application and a Mobile Net V2 and CNN Classifier, which use OpenCV and KMeans clustering for effective image analysis. The dataset, derived from medical imaging platforms, includes hundreds of high-resolution photos of the iris, annotated with detailed diagnostic information about a wide range of iris health problems. The project includes both normal and diseased irises, as well as those with cataracts, glaucoma, and iritis. The Streamlit web application provides a user-friendly interface for uploading iris images, which undergo preprocessing, grayscale conversion, and Gaussian blur before applying the Hough Circles method to detect the iris region. The system generates visualizations, including the original image, identified iris, and segmented representation achieved through KMeans clustering. The machine learning component enhances the accuracy of 95 percentage and reliability of iris detection, offering a holistic solution for iris disease detection. © 2024 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Deep Learning Approaches in Anticipating Diabetic Retinopathy Progression 10

Deep Learning Approaches in Anticipating Diabetic Retinopath...

引用

10th International Conference on Communication and Signal Processing, ICCSP 2024

作者： Thanush, M. Denisha, M. Karunya Institute of Technology and Sciences Division of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350353068

One of the most prevalent complications caused by diabetes that still causes loss of vision and blindness worldwide is diabetic retinopathy. For treatments to be effective, early and correct identification is essential. Despite advancements in medicine, a complex automated solution is still required to address the impending threat of blindness due to the difficult early diagnosis of diabetes-related retinopathy, a key contributor to visual impairment. Using a well-selected diabetic retinopathy dataset, our novel approach applies transfer learning techniques using EfficientNetB3, ResNet50, and DenseNet169. Our model is strengthened by a new hybrid oversampling method that addresses class imbalance, and its training incorporates cutting-edge components like differential regularization, adaptive dropout, and Adamax optimization for increased *** results demonstrate the remarkable sensitivity, specificity, accuracy, and F1 score of our model at various degrees of retinopathy severity, establishing a new standard for diagnostic dependability in the identification of diabetic retinopathy. By utilizing cutting-edge deep learning architectures, our method establishes a strong basis upon which future developments will be built. These developments will include adaptive optimization strategies, ensemble learning to improve resilience, and self-supervised pre-training, all of which will accelerate the ongoing advancement of diabetic retinopathy detection accuracy. © 2024 IEEE.

关键词： Diagnosis

来源：评论

学校读者我要写书评

暂无评论

Stroke Rehabilitation using Virtual Reality 3

Stroke Rehabilitation using Virtual Reality

引用

3rd International Conference on Applied Artificial Intelligence and Computing, ICAaiC 2024

作者： John, Nived Melvin Sangeetha, R. Karunya Institute of Technology and Sciences Division of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350375190

A specialized virtual reality platform, designed for desktop use, has emerged to assist in the recovery of stroke patients' impaired limbs. The proposed system integrates a mixed reality headset for computational power, enabling users to interact within a virtual environment. Inside this setting, two separate rehab protocols have been carefully developed, addressing various facets of hand mobility, including reach, velocity, and power. Through the implementation of performance-based target levels, the proposed system aims to enhance patient motivation and tailor exercises to individual requirements. Initial clinical trials involved the monitoring of movement using these systems, revealing issues related to patient motivation. However, objective evaluations demonstrated notable improvements in the majority of hand parameters for each patient over the course of the training period, corroborated by positive subjective feedback from the patients. This research study offers detailed perspectives on the creation and implementation of this state-of-the-art VR rehabilitation innovation. © 2024 IEEE.

关键词： Mixed reality

来源：评论

学校读者我要写书评

暂无评论

Machine learning Approaches for Autism Spectrum Disorder Prediction 10

Machine learning Approaches for Autism Spectrum Disorder Pre...

引用

10th International Conference on Communication and Signal Processing, ICCSP 2024

作者： Harish Sree Prasanna Kumar, D. Malardhas, Julia Punitha Devapriya, I. Karunya Institute of Technology and Sciences Division of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350353068

The neurodevelopmental illness known as autism spectrum disorder is a lifelong condition marked by a persistent or limited development of social-communication skills, cognitive abilities, activities, and behavior. The symptoms of autism are easier to see and identify in children between the ages of two and three. A prediction system based on traditional machine learning techniques, such as support vector machines, random forests, multiple layer perceptrons, naive Bayes, convolution neural networks, and deep neural networks, accounts for most of the research on autism spectrum disorder. Accuracy, precision, and recall are among the performance indicators used to verify the proposed models. This study investigated and evaluated the prediction of autism spectrum disorders using standard criteria including application type, simulation method, comparison approach, and input data. The purpose of this work is to offer a consolidated framework for autism spectrum disorder prediction to researchers. With the best results, the random forest method performed better than traditional machine learning algorithms. 97.8% accuracy percentage was achieved. Readers can better comprehend the underlying mechanisms and structures of the investigated frameworks with the aid of these work flow representations. © 2024 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Enhanced air Quality Prediction Using Optimized Sarimax Model for Coimbatore Region

Enhanced Air Quality Prediction Using Optimized Sarimax Mode...

引用

2024 International Conference on science, Technology, engineering and Management, ICSTEM 2024

作者： Revanth, Bande Manoranjitham, R. Division of Computer Science and Engineering Karunnya Institute of Technology and Sciences Coimbatore India

ISBN: (纸本)9798350376913

This research delves into examining the forecast of air quality in Coimbatore, India, according to data gleaned from the Central Pollution Control Board (CPCB) specific to the area. The gathered information underwent a preprocessing step, using interpolation to ensure uniformity and completeness. Forecasting methods such as Seasonal Autoregressive Integrated Moving Average with Exogenous Regressors (SARIMAX) and Long Short-Term Memory (LSTM) models were utilized to predict air quality levels. The SARIMAX model was fine-tuned through a grid search process, while the LSTM underwent hyperparameter adjustments to improve air quality predictions. Performance evaluation of these models involved metrics like R-squared, Mean absolute error, and Root mean square error. Based on the selected evaluation criteria, the outcome shows that SARIMAX outperformed LSTM in Coimbatore when it came to predicting the air quality. This analysis improves our understanding of air quality patterns in Coimbatore. Highlights SARIMAX's effectiveness as a modeling tool for atmospheric science applications. © 2024 IEEE.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

A novel approach to detect, analyze and block adversarial web pages

引用

International Journal of Information Technology (Singapore) 2024年第6期16卷 3617-3622页

作者： Kumar, M. Ranjith Naik, Darshana A. Kapila, Neha Mohan, Chinnem Rama Prasad, Ch Raghava Shelke, Chetan Rao, C. V. Guru School of Computer Science and Engineering Vellore Institute of Technology Department of Computer Science and Engineering M S Ramaiah Institute of Technology Department of Electronics and Electrical Engineering Lovely Professional University Department of Computer Science and Engineering Narayana Engineering College Electronics and Communication Engineering Koneru Lakshmaiah Education Foundation Alliance College of Engineering and Design Alliance University School of CS & amp AI SR Universtity

The phenomenon of distraction is very common, and its adverse effects are seen among people. The major cause underlying this issue is the ease with which adversarial web sites and web pages can be accessed. It is of utmost importance to locate, evaluate, and actively block such web pages in an effort to comprehensively and globally solve this societal issue. Thus, the given paper proposes an extension or plug-in to detect, analyze, and block websites smartly. The proposed approach takes keywords entered by the user as input into consideration, which eventually leads to the generation of web pages and web links. The filtering of web links is done by the proposed extension, followed by the extraction of features, the utilization of support vector machines (SVM) for binary classification, and the summarization of textual data using natural language processing (NLP). Lastly, the precise results corresponding to relevant web links are presented to the users, which will increase their productivity, thereby reducing their distraction levels under all working circumstances. The performance of the proposed approach is validated against existing recent studies based on evaluation metrics such as adversarial website detection time (ms) and accuracy (%). © Bharati Vidyapeeth's Institute of computer Applications and Management 2024.

关键词： Adversarial web pages Distraction Natural language processing (NLP) Support vector machine (SVM) Text summarization

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：