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检索条件"机构=Computer Applications in Science and Engineering dept."

共 35033 条记录，以下是71-80 订阅

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Machine Learning Techniques for Predicting Ovarian Cancer in its Early Stages Using Biomarkers 6

Machine Learning Techniques for Predicting Ovarian Cancer in...

引用

6th International Conference on Electrical engineering and Information and Communication Technology, ICEEICT 2024

作者： Alam, Mir Jafikul Anawar, Jannat-E Mohi Uddin, Khandaker Mohammad Rahman, Md. Hasibur Rahman, Md. Mahbubur Dhaka International University Dept. of Computer Science and Engineering Dhaka Bangladesh Southeast University Dept. of Computer Science and Engineering Dhaka Bangladesh Bangladesh University of Business and Technology Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350385779

The deadliest gynecological cancer affecting women is ovarian cancer, currently incurable with no effective medication treatments. The key focus of this research is to assess insights for early diagnosis using statistical analysis and machine learning techniques on data from clinical trials obtained from 349 patients. Several techniques, including Random Forest, Decision Tree, Gaussian NB, AdaBoost, and Logistic regression, were applied to find the most reliable factor for ovarian cancer prediction. A clinically evaluated raw dataset of benign samples and malignant ovarian tumor patient data set is used to develop early-stage ovarian cancer predictions, and the effectiveness of ML models was examined utilizing metrics including F1-score, Accuracy, Precision, and Recall. The proposed study shows better outcomes, with the Random Forest classifier exhibiting the highest accuracy for validation at 99% based on the test data of ovarian cancer predictions. Even though early-stage ovarian cancer detection is generally unavailable, cancer diagnosis may be greatly aided by machine learning. © 2024 IEEE.

关键词： Machine learning

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Digital Solutions for Crime Control: A Comprehensive Criminal Identification and Reporting Framework 11

Digital Solutions for Crime Control: A Comprehensive Crimina...

引用

11th International Conference on Reliability, Infocom Technologies and Optimization, ICRITO 2024

作者： Harinee, S. Anand, M. Vijay Dept. of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350350357

This paper presents the design and implementation of a comprehensive Criminal Identification and Reporting System (CIRS) aimed at enhancing law enforcement capabilities and improving public safety. The system enables users, including victims and law enforcement officers, to submit and manage complaints seamlessly through an intuitive online platform. Key features include the storage of user data in a secure database, real-time monitoring of criminal activity using CCTV footage, and advanced facial recognition technology for swift identification of potential offenders. The CIRS facilitates efficient case management by allowing users to track the status of their complaints and providing law enforcement agencies with valuable information to aid in criminal investigations. Moreover, the system assists local government agencies in maintaining records of known criminals, enabling proactive measures to prevent illegal activities. By leveraging cutting-edge technology and providing seamless integration with existing surveillance infrastructure, the CIRS promises to revolutionize criminal identification and reporting processes, ultimately contributing to improved public safety and law enforcement efficiency. © 2024 IEEE.

关键词： Face recognition

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Ensemble model for Detecting Phishing and Trojan using Latest Machine Learning Techniques 12

Ensemble model for Detecting Phishing and Trojan using Lates...

引用

12th IEEE International Conference on Communication Systems and Network Technologies, CSNT 2023

作者： Agrawal, Rahul Rathor, Sandeep Agrawal, Khushabu Gla University Dept. of Computer Engineering and Applications Mathura India

ISBN: (纸本)9781665462617

Machine learning is significant fourth industrial revolution technology that may be habitual to defend Internetconnected devices against cyber threats, assaults, damage, or illegal access. Cyber security computing may become more automated and intelligent than conventional security systems due to security intelligence modeling. Using an ensemble model of machine learning and deep learning, the objective of the proposed work is to identify phishing and Trojan attacks. In this ensemble method, we used the VGG-16 and Random Forest classifier and evaluate the performance to detect the attack. In this work, we have also shown the comparison of the proposed method with the existing attack. © 2023 IEEE.

关键词： Cybersecurity

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A Black-box based Attack Generation Approach to Create the Transferable Patch Attack 7

A Black-box based Attack Generation Approach to Create the T...

引用

7th International Conference on Intelligent Computing and Control Systems, ICICCS 2023

作者： Agrawal, Khushabu Bhatnagar, Charul GLA University Dept. of Computer Engineering and Applications Mathura India

ISBN: (纸本)9798350397253

Due to the recent advancement of deep learning methodologies, face recognition has seen increased success. However, researchers found that adversarial attacks can be launched against deep learning-based systems. The face recognition systems can be tricked by small changes in an input image. The human visual system is incapable of detecting these changes. In this work, a black-box attack generation method is proposed to create a transferable patch attack (TPA) using the generative adversarial network (GAN) to deceive the current face recognition systems. The generator and discriminator networks are used in the TPA attack to generate the adversarial images. The Labeled Face in the Wild (LFW) dataset is used as input for the proposed TPA attack, which creates the image by adding noise in the form of a patch. These patches are added in such a manner that they are invisible to the naked eye. FaceNet, ArcFace and CosFace face recognition models are used for the attack testing and also the proposed attack is compared to existing attacks. The purpose of this paper is to suggest a black-box attack and increase the transferability of adversarial attacks. In the black-box attack, the attacker doesn't know any information about the target model. The quantitative findings demonstrate that the proposed attack successfully misclassified the most recent FR models and achieved a higher attack success rate. © 2023 IEEE.

关键词： Face recognition

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Machine Learning Classifiers for Predicting the Risk of Cardiovascular Disease in Healthcare 4.0 3

Machine Learning Classifiers for Predicting the Risk of Card...

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3rd International Conference on Communication, Control, and Intelligent Systems, CCIS 2024

作者： Kumari, Palak Kumar, Ashish Chatterjee, Kakali Master of Computer Applications Patna Women's College Patna India National Institute of Technology Patna Dept. of Computer Science and Engineering Patna India

ISBN: (纸本)9798331528201

Cardiovascular disease (CVD) generic phrase used to describe heart or blood vessel illness. Conditions that impact the body's, brain's, or heart's blood flow. Reduced blood flow can result from factors such as blood clots, leading to heart attack, angina, or stroke. Other potential meanings of CVD. These models offer key benefits like clear interpretability and the ability to analyze complex patterns, significantly enhancing the accuracy of cardiovascular disease risk predictions. The demerits of using SVM, LR, K-NN, and MLP for CVD prediction include inter-pretability issues, overfitting risks, data requirements, feature selection challenges, scalability concerns, algorithm complexity, and class imbalance. Collaboration between machine learning experts and healthcare professionals is essential for developing accurate and reliable CVD prediction models that enhance patient care. CVD is a significant health threat, often leading to fatal complications. Early detection is crucial for effective intervention. This study employs SVM (accuracy is 0.84%), LR (accuracy is 0.86%), K-NN (accuracy is 0.94%), and MLP (accuracy is 0.79%) machine learning techniques to enhance CVD detection by addressing outliers and null values, contributing to advancing automatic detection initiatives. © 2024 IEEE.

关键词： Nearest neighbor search

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Hindi News Article's Headline Generation based on Abstractive Text Summarization

Hindi News Article's Headline Generation based on Abstractiv...

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2023 IEEE International Conference on Network, Multimedia and Information Technology, NMITCON 2023

作者： Kumar, Jeetendra Shekhar, Shashi Gupta, Rashmi Atal Bihari Vajpayee University Dept. of Computer Science and Application Bilaspur India Gla University Dept. of Computer Engineering and Applications Mathura India

ISBN: (纸本)9798350300826

Text summarization is a technique that converts large text into shorter ones by keeping its important information. Most of the available summarizers, summarize English language text. The availability of summarizers in other languages is rare. In the proposed work, abstractive text summarization (ATS) for the Hindi language has been used to generate headlines from news text. To build the model, a Hindi news dataset has been used that contains different news articles related to sports, politics, crime, etc. After pre-processing the text, Word2Vec method has been used for word embedding. ATS model has been built using the Seq2Seq model with attention. After that, we have calculated evaluation metrics like ROUGE and BLEU scores of the result summaries. We have also fine-tuned two pre-trained models, indicBART and multi-lingual variant of T5. After result comparison, it was found that the indicBART perform better than the other two models, considered for the experiment. © 2023 IEEE.

关键词： Text processing

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Development of a Multimodal Machine Learning Model for Seizure Detection Using Wearable Devices 1

Development of a Multimodal Machine Learning Model for Seizu...

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1st IEEE International Conference on Advances in Computing, Communication and Networking, ICAC2N 2024

作者： Singh Rathore, Saurabh Pratap Magotra, Sumedha Sruthy, K.V. Sharma, Sonu Kumar Kaur, Gaganpreet Singh, Sailendra ICAPSR Dept. of Management New Delhi India Chandigarh University Dept. of Computer Science Engineering Chandigarh India Dhanalakshmi Srinivasan College Dept. of Computer Science & Engineering Coimbatore India Mangalayatan University Dept. of Comp. Eng & Applications Aligarh India Lovely Professional University Punjab India J.S. University Dept. of Computer Science Shikohabad India

ISBN: (纸本)9798350356816

This research explores the transformative potential of wearable devices designed to automatically detect & predict epileptic seizures, offering continuous monitoring & early detection capabilities. The study focuses on developing a machine learning model tailored for seizure detection in such devices, leveraging multimodal sensors such as Electrodermal Activity (EDA) & Accelerometer (ACC). By measuring skin resistance and identifying irregular heartbeats, which are signs of upcoming seizures, these sensors allow for precise seizure detection. The study intends to demonstrate the effectiveness of this machine learning model in wearable technology with the goal of improving patient outcomes and seizure management. © 2024 IEEE.

关键词： Accelerometers

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A Survey on Aspect-based Sentiment Analysis for Online Purchased Product Feedback 10

A Survey on Aspect-based Sentiment Analysis for Online Purch...

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17th INDIACom;2023 10th International Conference on Computing for Sustainable Global Development, INDIACom 2023

作者： Prakash, Yuvraj Sharma, Dilip Kumar Gla University Dept. of Computer Engineering and Applications Mathura India

ISBN: (纸本)9789380544472

Customer review can have a significant impact on the development of a product and the innovations that need to be done in it from time to time. Nowadays, it is really easy to get customer reactions. The organization may examine user opinions that are favorable or unfavorable about the product in the feedback or comments sections of social media and online retail platforms. As the success or failure of a product is directly tied to how well consumers like it, understanding their opinions may help businesses prepare for the future and improve their products. In this research, we explored studies that used aspect-based sentiment analysis to assess user opinions of online sold items. This method employs aspect terms by determining a connection between the terms to analyze the sentiment of the feedback. It means analyzing customer comments and statements about a product and drawing meaning from them. We have discussed articles from the last five years that analyzed the sentiment using Aspect based Sentiment Analysis on social media and e-commerce media. © 2023 Bharati Vidyapeeth, New Delhi.

关键词： Sentiment analysis

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AAF-SCM: An Authenticated Framework for Supply Chain Management

AAF-SCM: An Authenticated Framework for Supply Chain Managem...

引用

2024 IEEE International Conference on Intelligent Systems and Advanced applications, ICISAA 2024

作者： Roy, Prince Kumar, Rajneesh Morshed, Md Neaz Fairleigh Dickinson University Dept. of Applied Computer Science United States Dept. of Computer Science & Engineering India

ISBN: (纸本)9798331539948

The process of a supply chain involves a series of activities that distribute, assemble, and manage products, transferring them from the supplier to the end consumer. It operates as a complex, interconnected network regulated by supply and demand. Security in supply chain management is a crucial aspect of its overall security measures, focusing primarily on maintaining essential end-to-end protection. Without this, several attacks can be used to manipulate data and valuable information from the entire chain of networks. This paper explains how encrypted intermediates can secure the entire SCM by validating each intermediate using public-private key encryption. We also demonstrate and assess how the proposed AAF-SCM model can aid in tracing security breaches or unauthorized data tampering. We also validate this model against nefarious attacks like Fabrication, Assertion, Deletion, and Modification. Finally, we propose opportunities to develop innovative systems that enhance security through intermediary steps. © 2024 IEEE.

关键词： Supply chain management

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A Blockchain-Based Approach for Detecting Counterfeit Pharmaceuticals 15

A Blockchain-Based Approach for Detecting Counterfeit Pharma...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Afrin, Farhina Laboni, Marfi Akter Rimi, Iffat Firozy Rahman, Md Sadekur Habib, Md. Tarek Dept. of Computer Science and Engineering Daffodil International University Dhaka Bangladesh Dept. of Computer Science and Engineering Independent University Dhaka Bangladesh

ISBN: (纸本)9798350370249

Nowadays, the contemplations for improving the item circulation supply structure have been expanded around the world. Simultaneously, it acquires different complexities in the inventory network and things get a lot defiled inside the production network at the hour of cataclysms. For example, alongside the false quality of items, costs to get a colossal illicit raise and unlawful cruel amassing happen to exacerbate things. Henceforth, conveyance costs are present to be uncovered and item data is to be imparted to purchasers. As it is now referenced, dispersion channels are muddled and supply chain management (SCM) is self-sufficiently accomplished in a freeway. For common sense reasons, it has been consistently called attention to that the circulation system isn't straightforward and the dissemination edge is quite high. The motivation behind this examination is to structure a framework that vows the straightforwardness of the item dispersion structure by blockchain on inventory network the board frameworks. This methodology permits organizations just like any purchasers to follow their exchanges, items by upgrading straightforwardness in the Supply Chain Management, accordingly cursing down organizations and gobetweens from selling counterfeit drugs. ©2024 IEEE.

关键词： Blockchain

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