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Cognitive Robotics and Intelligent Systems (ICC - RObINS), International Conference on

作者： S. Alvin Jesuraj S. V. Evangelin Sonia C. P. Shirley B.Tech Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore Tamil Nadu India Karunya Institute of Technology and Sciences Coimbatore Tamil Nadu India

ISBN: (数字)9798350372748

ISBN: (纸本)9798350372755

This research investigates the application of DenseNet-201, a deep convolutional neural network architecture, in the RSNA-MICCAI brain Tumor Radiogenomic Classification aimed at predicting the genetic subtype of glioblastoma using MRI imaging data. This study demonstrates the effectiveness of DenseNet-201 in accurately classifying glioblastoma cases based on MGMT promoter methylation status, a critical biomarker influencing treatment outcomes. Through comprehensive experimental evaluations, including training, validation, and testing phases, DenseNet-201 exhibits robust performance metrics such as high accuracy, precision, recall, F1-score, and AUC-ROC values. These results highlight the model's ability to effectively distinguish between MGMT promoter methylation-positive and negative glioblastoma cases, offering valuable support for clinical decision-making in treatment planning and prognosis assessment. Leveraging deep learning techniques and MRI imaging data, DenseNet-201 holds promise as a powerful tool for enhancing the understanding of glioblastoma genetics and guiding personalized therapeutic interventions, ultimately contributing to improved patient outcomes in brain cancer management.

关键词： Deep learning Training Magnetic resonance imaging Medical services Genetics Planning Prognostics and health management

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Monitoring state of mind using Natural Language Processing 7

Monitoring state of mind using Natural Language Processing

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7th IEEE International Conference on Advances in Computing, Communication and Control, ICAC3 2021

作者： Saketh, Vemula Sai Khatravath, Srinivas Guntupalli, Yashvanth Kumar PES University B.Tech Computer Science Bangalore India IIT Kharagpur M.Tech Electronics and Electrical Communication Kharagpur India

ISBN: (纸本)9781665426343

State of mind is essential in every person's life to keep their life stable, calm and peaceful. The key factors that contribute towards them are mood, emotion and thoughts. Monitoring them is key to a person's overall development and allows family and friends to support them to a greater extent. One aspect of getting a report on this is using the words being typed by the person on their computer or mobile, browser history, songs and movies played. This paper proposes a sentiment analysis system where information about mood and thoughts are conveyed by means of natural language processing. These logs captured during each time session are classified to gain insights about the person. This reduces the likelihood of any drastic decisions taken by the person and provides a better means of conveying the information and maintaining communication between them and their relations. © 2021 IEEE.

关键词： Sentiment analysis

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Implementing blockchain based Security in EHR Using Ganache

Implementing Blockchain Based Security in EHR Using Ganache

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International Conference on Contemporary Computing and Informatics (IC3I)

作者： Kumar Satyam Ayush Sharma Runumi Devi B.Tech in Computer Science and Engineering Galgotias University Greater Noida Uttar Pradesh India Department of Computer Science and Engineering Galgotias University Greater Noida Uttar Pradesh India

A blockchain-based electronic health record (EHR) system has been proposed to manage patient data and maintain computerized records across different healthcare institutions. The main objective of this system is to provide immediate access to patient health information while addressing concerns about privacy and security. It is developed on the Ethereum network using programming languages, tools, and technologies such as Ganache, Solidity, and ***. The system uses smart contracts to provide security and privacy, and transactions are verified and propagated to the entire decentralized network. The system includes a cryptocurrency wallet (MetaMask) with a centralized privacy system that allows authorized parties to access and secure records quickly. The proposed system aims to achieve several objectives such as allowing users to receive the same data simultaneously, increasing efficiency, building trust, and reducing barriers. It secures data storage by restricting user access and enables the secure transfer of patient medical records. The solution allows for better transparency and ownership of sensitive data, which can be recorded and safeguarded via blockchain technology, therefore assisting the healthcare sector. This paper describes a medical record system and a new protocol that can be used quickly and safely, paving the way for more secure and efficient healthcare systems. Overall, the proposed system offers potential solutions to the challenges associated with traditional EHR systems and has the potential to revolutionize the healthcare industry.

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Cryptocurrency PricePrediction using LSTM

Cryptocurrency PricePrediction using LSTM

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International Conference on Computing and Networking technology (ICCNT)

作者： Swaraj Deo Gaurav Kumar Swayam Soni Gurmeet Singh B.Tech III Year School of Computing Science and Engineering Galgotias University Greater Noida India School of Computer Science and Engineering Galgotias University Greater Noida India

This paper focuses on utilizing the Long Short-Term Memory (LSTM) algorithm to forecast the prices of cryptocurrencies. that is implemented through the model, which will allow us to keep tabs on the fluctuating prices of the various coins that are available. As various cryptocurrencies are available for trading and investment and they are regarded as a type of digital asset. because trading and investing should be done after the knowledge of the market and trends, So, to solve this problem there should be analysis before trading any pair. Our goal is to present accurate prediction based on the dataset of the selected cryptocurrency. Hence, the proposed model is built and it concentrate mostly on technical analysis of the crypto coins which is the major indicator and most suitable for the prediction models. The proposed LSTM model achieves a variance regression score of 0.95 on test data of the bitcoin which serves as a representative cryptocurrency that is used in the model.

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Machine Learning Neural Network Handwriting Recognition

SSRN

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SSRN 2022年

作者： Vyas, Tanishq B.Tech Computer Science Vellore Institute of Technology Bhopal University Madhya Pradesh Bhopal India

The paper talks about one of the applications of machine learning, neural network handwriting recognition. For decades machine learning had shown its application in various things. Whether it is medical science, management companies, stocks or computer science. It is accurately shown results in the industries. Some applications even saved human time and money. From mathematical concepts to computer science, Machine learning has been applied to various things. © 2022, The Authors. All rights reserved.

关键词： Machine learning

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A Novel Mobile Application to Empower Visually Impaired Individuals to Perform Independent Day-to-Day Activities

A Novel Mobile Application to Empower Visually Impaired Indi...

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International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)

作者： Dewanshi Paul Ankit Kumar Patel Dhanush R Amutha S B.Tech Electronics and Computer Engineering School of Electronics Engineering Vellore Institute of Technology Chennai India School of Electronics Engineering Vellore Institute of Technology Chennai India School of Computer Science and Engineering Vellore Institute of Technology Chennai India

ISBN: (数字)9798350376425

ISBN: (纸本)9798350376432

People with visual impairments struggle or require assistance from others to perform day-to-day activities. Hence, people with visual impairments suffer from a lack of independence and quality of life. For this purpose, the app proposed in the paper is a unique, creative, innovative mobile application that will aid people with visual impairments in becoming independent and improving their quality of life. This paper introduces the novel mobile application’s three key features: QR (Quick Response) code scanning, OCR (Object Character Recognition), and an Indoor Object Navigation System. The QR code scanning feature allows users to make informed decisions quickly by providing comprehensive information about products or their environment. The OCR functionality reads out the printed text aloud and helps the users understand written content with the help of audio. The indoor object finder or navigation system is a noteworthy advancement in Assistive technology. The system allows users to select a target object and then move their camera around their surroundings; once the object is detected, the app provides voice instructions about the directions of the target object to guide users towards it. by integrating these complex technologies, the novel mobile application provides an innovative approach to some of the issues encountered by those with visual impairments. The application aims to increase user independence, improve functionality, and build confidence to improve their daily experiences and engagements with the world around them.

关键词： Indoor navigation Visual impairment Optical character recognition QR codes Streaming media Cameras Real-time systems Mobile applications Text to speech Character recognition

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Improving Scalability Using blockchain in banking Sector

SSRN

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SSRN 2023年

作者： Krishna, Siva Rama K. Sagar, Vidya K. Subhani, Mahaboob S.K. Department of Computer Science and Engineering Andhra Loyola Institute of Engineering and Technology ALIET Vijayawada India IV B.Tech Department of Computer Science and Engineering Andhra Loyola Institute of Engineering and Technology ALIET JNTUK Vijayawada India

The blockchain is an encrypted database that is distributed across numerous computers and serves as a virtual record of transactions and contracts. This technology supports bitcoin transactions and has already upended the financial industry. Since blockchain technology has the potential to improve data security, provide a decentralized and transparent network, and lower operational costs, the goal of this study is to examine how it can affect the financial industry. blockchain's extraordinary properties make it a potential technology for determining the financial sector's future despite its limits. © 2023, The Authors. All rights reserved.

关键词： blockchain

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Lung Cancer Detecting using Radiomics Features and Machine Learning Algorithm

Lung Cancer Detecting using Radiomics Features and Machine L...

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technological Advancements in Computational sciences (ICTACS), International Conference on

作者： M.N. Rajesh Nikita Tanni Z. Tanveer baig Electronics and Communication Engineering Jain (Deemed-to be-University) Bengaluru India B.Tech in Computer Science and Engineering (Data Science) Christ (Deemed to be University) Bengaluru India Dept of IT Amity University Taskent Uzbekistan

Lung Cancer Incidence across the globe is the second leading cancer type tallying to about 2,206,771 during 2020 and is estimated to rise to about 3,503,378 by 2040 for both male and female sexes and for all ages accounting to 11.4% as per Globocan 2020 [1]. It is the leading death-causing cancer. Lung Cancer [2] in broad terms encompasses Trachea, bronchus as well as lungs. Purpose: The study is aimed to understand Radiomics based approach in the identification as well as classification of CT Images with Lung Cancer when Machine Learning (ML) algorithms are applied. Method: CT Image from LIDC-IDRI [4] Dataset has been chosen. CT Image Dataset was balanced and image features by PyRadiomics library were collected. Various ML features classification algorithms are utilized to create models and matrices adopted in judging their accuracies. The models, distinctive capacity is assessed by receiver operating characteristics (ROC) analysis. Result: The Accuracy scores and ROC-AUC values obtained for various Classification Model are as follows, for Ada boosting, the accuracy score was 0.9993 ROC-AUC was 0.9993 and followed by GbM, the accuracy score was 0.9993, was 0.9992. Conclusion: Extracting texture parameters on CT images as well as linking the Radiomics method with ML would categorize Lung Cancer commendably.

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An electronic warfare approach for deploying a software-based Wi-Fi jammer

An electronic warfare approach for deploying a software-base...

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International Conference on Contemporary Computing and Informatics (IC3I)

作者： Keshav Kaushik Rahul Negi Prabhav Dev School of Computer Science University of Petroleum and Energy Studies Dehradun India B.Tech Computer Science and Engineering University of Petroleum and Energy Studies Dehradun India

Some prominent instances have been centered on electronic warfare. For example, the American military has made significant investments in automation through UAV programs, only for competitors like the Iranians to create strategies to interfere with these systems. Iran managed to capture a top-secret U.S. surveil-lance drone by fooling it into descending in the incorrect place by jamming its control signals and providing it with bogus GPS data. In this paper, the authors have focused on the electronic warfare approach for deploying a software-based Wi-Fi jammer. The software-based Wi-Fi jammer can disconnect the targets using the DoS pursuit mode. The paper describes the unique methodology of how software can also be used for jamming wireless signals.

关键词： Performance evaluation Wireless networks Poles and towers Switches Virtual machining Software Security

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Twitter sentiments analysis using machine learninig methods

Twitter sentiments analysis using machine learninig methods

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2020 International Conference for Emerging technology, INCET 2020

作者： Mandloi, Lokesh Patel, Ruchi Meidcaps University B.Tech Computer Science and Engineering Indore India Meidcaps University Dept. Computer Science and Engineering Indore India

ISBN: (纸本)9781728162218

Analysis of sentiments is the method of deciding whether the sentiments in the text is positive, negative or neutral. It is also known as material polarity or mining of opinions. The growth and advancement in social media platforms engaged a huge number of users. Social media platform like twitter where users can post their tweets in 280 characters. because of the limited number of characters in tweets, it becomes easy for the sentiment analysis. On Twitter 550 millions of tweets are posted daily. Twitter also represents all age group people and also a fair representation of gender. Therefore, the sentiment analysis of twitter data becomes somewhat general sentiments of society. In this paper, we will compare various Machine Learning methods like the Naïve bayes Classification method, Support Vector Machine Classification Method and Maximum Entropy Classification method. We will see how sentiments analysis is done by this classification algorithm and what is the accuracy and precision in these cases. © 2020 IEEE.

关键词： Sentiment analysis

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