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14th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2023

作者： Deshmukh, Vijayalaxmi Dhodamal, Aishwarya Ainapure, Rutuja Yelur, Dipali More, Harshal Department of Computer Science and Engineering RIT Maharashtra Sangli India

Cattle animals are vulnerable to many diseases, which can reduce their productivity and if not detected can lead to death of the cattle. This thesis provides a methodology that how the machine learning can detect cattle diseases that may provide affordable solution to the farmers with scarce in medical facilities to the animals. However, the system provides a user interface on a website in the form of web application and use Machine Learning Logistic Regression to classify the data according to animals, diseased part, symptoms and use image processing to identify the related disease and provide immediate cure for the disease and the option to contact veterinarians near them accordingly. © Grenze Scientific Society, 2023.

关键词： Animals

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Performance Evaluation of Natural Language Processing Algorithms for Sentiment Analysis

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SN computer science 2024年第6期5卷 724页

作者： Silviya, S. H. Annie Faith, S. Julia Seetha, R. Hemalatha, M. Department of Computer Science and Engineering Rajalakshmi Institute of Technology (RIT) Department of Information Technology S.A.Engineering College Department of Information Technology Vellore Institute of Technology Department of Computer Science and Engineering RMD Engineering College

Sentiment analysis can be used to identify if a text’s sentiment is neutral, positive, or negative. One type of natural language processing is sentiment analysis. An interdisciplinary field encompassing linguistics, computer science, and artificial intelligence called “natural language processing” studies how computers and human language interact, with a focus on how to teach computers to process and analyze vast volumes of natural language data. Sentiment analysis, sometimes referred to as opinion mining or emotion artificial intelligence, is the methodical identification, extraction, quantification, and study of affective states and subjective data using natural language processing, text analysis, computational linguistics, and biometrics. Sentiment analysis is frequently used in online and social media platforms, voice of the customer materials (such as reviews and survey replies), and healthcare materials for marketing, customer service, and clinical medicine purposes. This paper discusses different sentiment analysis methods and selects the best approach for a certain task. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Biometrics Computational linguistics Natural language processing Sentiment analysis Text analysis

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Wind forecasting using ANN 1

Wind forecasting using ANN

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1st International Conference on Intelligent Computing and Research Trends, ICRT 2023

作者： Kumar, Ashok Verma, Amit Soni, Dheresh Chaturvedi, Gaurav RIT Department of Electrical Engineering Uttarakhand Roorkee India FOT UTU Department of Electrical Engineering Uttarakhand Dehradun India VlT University School of Computer Science and Engineering Madhya Pradesh Bhopal India RIT Department of Computer Science and Engineering Uttarakhand Roorkee India

ISBN: (纸本)9798350336771

Conceptual Breeze power can be particular as the power shaped by involving wind as asset. This has a non-immaterial impact which carries a ton of critical advantages to the power supply and age industry. A right expectation about the accessible breeze energy fabricate for the next few hours is extremely essential, so that definite readiness and planning of the power bunch from moderate units can be performed. The adjustment of wind speed depends on the upsides of the metrological boundaries which are adaptable in climate, for example, stickiness, temperature, amazing strain, precipitation, dampness content and so on. © 2023 IEEE.

关键词： Weather forecasting

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Exploring Machine learning applications in cyber attacks detection

Exploring Machine learning applications in cyber attacks det...

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2024 International Conference on Electrical, Electronics and Computing Technologies, ICEECT 2024

作者： Rai, Rina Mishra, Aditi Singh, Divya Kumar, Gaurav Kumar, Anuj Arya, Bhupal Madan Mohan Malaviya University of Technology Department of Computer Science Gorakhpur India Parul University Vadodara Department of Computer Science Gujarat Vadodara India University of Lucknow Roorkee Institute of Technology Department of Computer Science Lucknow India Uttaranchal Institute of Technology Department of Computer Science and Engineering Dehradun India Babasaheb Bhimrao Ambedkar University Department of Information Technology Lucknow India RIT Department of Computer Science and Engineering Roorkee India

ISBN: (纸本)9798350378092

Attackers and hackers employ many tactic known as phishing, cyber-attacks, dos attacks DOS attacks, man in middle attacks etc to damage trustworthy URLs as well as important websites. In this research, we discussed various cyber threats, the interrelation of cyber threats, and machine learning types of phishing attacks various techniques to detect cyber phishing by using machine learning, and we have also compared various phishing attacks with a few machine learning techniques with the help of a classification technique like supervised learning in which we apply SVM, random forest and extreme learning machine, the NSL-knowledge discovery is used in the evaluation of intrusion detection method also we have compared the accuracy in which precision-recall is used to find the accuracy and to calculate the performance and we concluded that ELM method give best result in terms of accuracy. © 2024 IEEE.

关键词： Phishing

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Real Time Fruit Recognition and Calories Estimation Using CNN and Model Deployment on Amazon's AWS 3

Real Time Fruit Recognition and Calories Estimation Using CN...

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3rd International Conference on Innovative Sustainable Computational Technologies, CISCT 2023

作者： Roy, Vikas Kumar Roy, Ganpati Kumar Thakur, Vasu Baliyan, Nikhil Goyal, Nupur Chauhan, Yash Ruprecht Karl University of Heidelberg Department of Data and Computer Science Germany Sharda University Department of Computer Science and Engineering Greater Noida India RIT Roorkee Department of Computer Science and Engineering Uttarakhand Roorkee India Graphic Era Deemed to Be University Department of Mathematics Dehradun India Graphic Era Deemed to Be University Department of Computer Science Engineering Dehradun India

ISBN: (纸本)9798350303360

To carry out vigorous and effective fruit recognition in farming is difficult since there are a number of variations. Lately, various deep-learning approaches presented an outstanding result in numerous visual-guided agricultural usage. These approaches need labelling on training data, which is a tedious work. This study presented a customized five layers CNN architecture and various pretrained deep learning algorithms i.e., VGG-16, DenseNet-121 and InceptionV3are used to recognise the fruit and their calories for helping farmers, patients and peoples to estimate the fruit calories for their health and in farming. The model is trained and validated on integrated datasets which is downloaded from Kaggle and IEEE dataport having 10 classes of different fruits. After extensive experiments, highest accuracy obtained was 99.60% by five layers of CNN and proposed deep learning model has been deployed on Amazon AWS EC2 instance using WinSCP, PuTTY and PuTTYgen. Flask (Python Framework), HTML, CSS and JavaScript is used for website development and connected to its parent website which help users to recognize the fruit and their calories. © 2023 IEEE.

关键词： Fruits

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A Study on computer-Aided Diagnosis of Human Brain Tumor Detection and Classification using Binary Genetic Algorithm and Deep Learning Techniques 14

A Study on Computer-Aided Diagnosis of Human Brain Tumor Det...

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14th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2023

作者： Prashantha, S.J. Prakash, H.N. Padmajadevi, G. Department of Computer Science and Engineering NCE Hassan Visvesvaraya Technological University Belagavi India Department of Computer Science and Engineering RIT Hassan Visvesvaraya Technological University Belagavi India Department of Electronics and Communication and Engineering MCE Hassan Visvesvaraya Technological University Belagavi India

computer-aided detection (CAD) frameworks enable doctors diagnose faster and more accurately. The objective of paper is to present a hybrid learning approach for a CAD system for automatically detecting brain tumors using magnetic resonance (MR) images. The methodology focuses on four computational techniques: (1) the Conventional and deep learning (DL) for Feature Extraction (2) select a deep features by last fully connected layer and conventional optimal feature sets are from Genetic Algorithm (GA) (3) combine the features that were chosen by employing a fusion approach and (4) the support vector machine (SVM) is used to classify inputs as either normal or abnormal. A total of 125 flair MR images, 50 normal and 75 abnormal, were used in the experiments. These images were taken from a real-world of brain MRI dataset. The results demonstrated that the proposed method efficiency compared with the other MR images state of the art techniques. The outcomes demonstrated how specific and robust the proposed hybrid technique. At last, some probable next steps are proposed. © Grenze Scientific Society, 2023.

关键词： Genetic algorithms

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Understanding Sign Language Recognition: An Overview

Understanding Sign Language Recognition: An Overview

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2024 International Conference on Electrical, Electronics and Computing Technologies, ICEECT 2024

作者： Saini, Shivani Prjapati, Meenu Arya, Bhupal Sharma, Ravinder Kumar Kumar, Manoj Professional University Department of Mathematics Lovely Jalandhar India Uttranchal University School of Appliedand Life Sciences India Roorkee Roorkee Institute of Technology Computer Science and Engineering RIT Roorkee India Chandigarh University India Department of Mathematics India Roorkee Institute of Technology CSE RIT Roorkee Roorkee India

ISBN: (纸本)9798350378092

Communication is only the way which is used by human to express their needs, feelings and thoughts to people mostly by speech. But this world also has the people with some disability like deaf and dumb people. For these people communication is not possible by speech. The only language which is used by deaf and dumb people to communicate with each other is Sign Language. Sign Language is completely different from generally spoken languages, it has its own grammar. Different body parts are involved in sign language but the important parameters are hand gestures, body movement and also facial expression. Many researches have been done in sign language recognition. But still Sign Language Recognition (SLR) is the most challenging area for practitioners and researchers, because sign language is not an international language. For e.g., Indian Sign Language is differed from Ethiopian Sign Language, Chinese Sign Language, American Sign Language and other country's sign language. The SLR is mostly required because of its ability to remove the communication barrier for deaf and dumb people. This review paper contains various techniques of AI (Artificial Intelligence) used for SLR for human understanding that have employed in recent past. The main approaches are i) Vision based ii) Glove based. In vision-based approach one or more camera is used to capture the image sequence, and then image processing is used to recognize the signs. In glove-based approach instrumental gloves with sensor is used to track the hand movement © 2024 IEEE.

关键词： Audition

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Method for Job Recommendation based on Machine Learning and Deep Learning Model 2

Method for Job Recommendation based on Machine Learning and ...

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2nd International Conference on Automation, Computing and Renewable Systems, ICACRS 2023

作者： Singh, Deepak Patel, Nagendra Singh, Upendra Department of Computer Science & Engineering RIT M.P. Rewa India Department of Information Technology Shri G. S. Institute of Technology and Science Indore India

ISBN: (纸本)9798350340235

In the modern digital era, the integration of machine learning (ML) and deep learning (DL) in job recommendation systems offers a transformative approach to bridging candidates with appropriate job opportunities. Traditional job matching techniques, reliant on human evaluation, are often fraught with inefficiencies and inaccuracies, especially given the extensive volume of job seekers and openings. This study introduces an innovative job recommendation methodology that synergistically combines the capabilities of ML and DL models. Our proposed model leverages the adaptability of ML algorithms to process diverse datasets and the power of DL neural networks to discern intricate patterns within vast data troves. Initial findings demonstrate an improved recommendation accuracy and a reduction in the "cold start" problem often encountered in recommendation systems. Furthermore, the study addresses fairness concerns, ensuring that proposed model provides equitable suggestions across various demographics. By integrating these cutting-edge technologies, our method not only enhances the job-seeking experience for candidates but also streamlines recruitment processes for employers. The overarching aim is to foster a more efficient, transparent, and inclusive job market. © 2023 IEEE.

关键词： CNN deep learning job-seeking machine learning Random Forest Classifier TF-IDF

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Price Prediction of Bitcoin and Ethereum - A Machine Learning Approach

Price Prediction of Bitcoin and Ethereum - A Machine Learnin...

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Artificial Intelligence and Knowledge Discovery in Concurrent engineering (ICECONF), International Conference on

作者： Sriman B Tamil Iniyal T Thasmiya J Taariq Ziyaadh J Sri Ranjani Teju Thomas S Department of Computer Science and Engineering Rajalakshmi Institute of Technology (RIT) Chennai

India is rapidly moving towards the digitization of money in all aspects. Cryptocurrency has grown widely in India and around the world among investors for financial activities like buying, selling, and trading. According to the report submitted in 2021 by the United Nations Conference on Trade and Development, 7.3% of Indians owned cryptocurrency in 2021. In the past two years, i.e., 2020 and 2021, the value of global currencies have been falling due to the poor run of stock markets. So the investors found it very hard to cope with the economical issues. This in turn has led to a renewal of interest in digital currency. Our main target is to implement the efficient machine learning and deep learning- based models specifically Convolutional Neural Network (CNN), long short term memory(LSTM) and Gated Recurrent Units (GRU) to handle the price volatility of bitcoin and ethereum and to produce high accuracy.

关键词： Online banking Biological system modeling Bitcoin Learning (artificial intelligence) Predictive models Logic gates Knowledge discovery

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Expression of Concern for: Wind forecasting using ANN

Expression of Concern for: Wind forecasting using ANN

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Intelligent Computing and Research Trends (ICRT), International Conference on

作者： Ashok Kumar Amit Verma Dheresh Soni Gaurav Chaturvedi Department of Electrical Engineering RIT Roorkee Uttarakhand India Department of Electrical Engineering FOT UTU Dehradun Uttarakhand India School of Computer Science and Engineering VlT University Bhopal Madhya Pradesh India Department of Computer Science and Engineering RIT Roorkee Uttarakhand India

ISBN: (数字)9798350336771

ISBN: (纸本)9798350336788

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