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Recent Trends in computer science and Technology (ICRTCST), International Conference on

作者： Surjeet Kumar Md Shamsher Alam Zeeshan Khursheed Shadan Bashar Neha Kalam Computer Science & Engineering Assistant Professor in Government Engineering College Sheikhpura Bihar India Computer Science and Engineering Associate Professor in R.V.S College of Engineering & Technology Jamshedpur India DGM Jio Platform Limited Mumbai India Master of Computer Application Assistant Professor in R.V.S College of Engineering & Technology Jamshedpur India Computer Science and Engineering Student R.V.S College of Engineering & Technology Jamshedpur India

ISBN: (数字)9798350351378

ISBN: (纸本)9798350351385

In the contemporary digital era, data has evolved into the cornerstone of myriad sectors, encompassing academia, commerce, and medical research. Yet, the acquisition of insights from this expansive reservoir of information has historically demanded a level of proficiency in formal languages such as SQL, thereby imposing a substantial barrier for individuals lacking technical expertise. In response to this pervasive challenge, the advent of Natural Language Interface to Databases (NLIDB) has emerged as a promising and transformative solution. NLIDB offers users the capability to engage with databases through the utilization of their natural language, whether expressed in textual or verbal form. This paradigm shift empowers both seasoned experts and neophytes to effortlessly extract valuable information from databases without the prerequisite of specialized technical skills. In this research paper, we propose an innovative system that capitalizes on an intermediary SQL generation process, facilitating the seamless bridge between natural language input and subsequent database retrieval. This novel approach eliminates the need for users to possess awareness of the intricate underlying complexities of the database management process. By simplifying the interaction between users and databases, our system endeavours to democratize data access and promote the universal utilization of this invaluable resource across diverse domains.

关键词： Structured Query Language Databases Natural languages Semantics Relational databases Manuals Reservoirs

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A Collaborative Health Care System: A Pilot based on Blockchain

A Collaborative Health Care System: A Pilot based on Blockch...

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Blockchain and Distributed Systems Security (ICBDS), IEEE International Conference on

作者： P Bindu Divya Shruti Jadon Dept. of Computer Science and Engineering Student of Cyber Security People’s Education Society University Bengaluru India Dept. of Computer Science Associate Proffesor People’s Education Society Bengaluru India

ISBN: (数字)9798350354348

ISBN: (纸本)9798350354355

Blockchain-driven healthcare system that offers personalized, data-driven treatment options hopes to transform the medical industry. This system aims to increase diagnostic accuracy, treatment efficacy, and data security. It strongly emphasizes the value of interdisciplinary collaboration among medical professionals, enabling various professions to work together to provide comprehensive care for complex medical conditions. It also addresses the ethical and legal concerns that result from cross-specialty cooperation and the exchange of patient data, including as patient privacy and data security.

关键词： Industries Data privacy Privacy Law Collaboration Transforms Decentralized applications Blockchains Stakeholders Medical diagnostic imaging

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Data storage security issues in cloud computing

Data storage security issues in cloud computing

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2021 International Conference on Innovative Practices in Technology and Management, ICIPTM 2021

作者： Singh, Devang Pratap Kaushik, Prakarsh Jain, Manjari Tiwari, Vidushi Rajpoot, Subhadra Amity School of Engineering and Technology Student of Computer Science and Engineering Greater Noida India Amity School of Engineering and Technology Department of Applied Science Greater Noida India

ISBN: (纸本)9780738132891

Cloud computing gives on request administration on their information or data to its customers. Information storage(storing) is among one of the essential administration given by the cloud computing. Cloud specialist organization has the information of information proprietor on their server and client can get to their information from these servers. As information, proprietors and servers are various personalities, the worldview of information storage raises numerous security challenges. A free component is required to ensure that information is effectively facilitated to the cloud storage server. Right now, we will examine the various methods that are utilized for secure information storage on cloud. © 2021 IEEE.

关键词： Cloud storage

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Fakenews AI: Identifying and Flagging Misinformation through Artificial Intelligence

Fakenews AI: Identifying and Flagging Misinformation through...

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Advancement in Electronics & Communication engineering (AECE), International Conference on

作者： Aman Kumar Rohan Raj Ajay Sharma Abhishek Kumar Shamneesh Sharma School of Computer Science and Engineering Lovely Professional University Phagwara India Delivery and Student Success upGrad Education Private Limited Banglore Karnataka India

ISBN: (数字)9798350364729

ISBN: (纸本)9798350364736

Misinformation has become a pervasive problem in today's society. With the rise of social media and the ease of sharing information, false or misleading information can spread rapidly and have a significant impact on public opinion and decision-making. The challenge of identifying and flagging misinformation has become increasingly difficult, as conventional methods of fact-checking and verification struggle to keep up with the scale and speed of information dissemination. In this study, the author will explore the function of artificial intelligence (AI) in identifying and flagging misinformation, and the potential implications and future directions of the technology, looking at different types of models like Naive Bayes, LR, DT, RF, SVM, and LSTM. The author has tested how well they worked using measures like accuracy, precision, recall, and F1-score. The author has observed that the Decision Tree model is the best one overall. It had the highest accuracy and did the best job at classifying things compared to the other models.

关键词： Radio frequency Support vector machines Accuracy Social networking (online) Decision making Linguistics Decision trees Fake news Long short term memory Random forests

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BERT-Based Approach for Automating Course Articulation Matrix Construction with Explainable AI

arXiv

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arXiv 2024年

作者： Shiferaw, Natenaile Asmamaw Leandre, Simpenzwe Honore Sinha, Aman Rout, Dillip Student Dept. of Computer Science and Engineering C.V. Raman Global University Odisha Bhubaneswar752054 India Faculty Dept. of Computer Science and Engineering C.V. Raman Global University Odisha Bhubaneswar752054 India

Course Outcome (CO) and Program Outcome (PO)/Program-Specific Outcome (PSO) alignment is a crucial task for ensuring curriculum coherence and assessing educational effectiveness. The construction of a Course Articulation Matrix (CAM), which quantifies the relationship between COs and POs/PSOs, typically involves assigning numerical values (0, 1, 2, 3) to represent the degree of alignment. In this study, We experiment with four models from the BERT family: BERT Base, DistilBERT, ALBERT, and RoBERTa, and use multiclass classification to assess the alignment between CO and PO/PSO pairs. We first evaluate traditional machine learning classifiers, such as Decision Tree, Random Forest, and XGBoost, and then apply transfer learning to evaluate the performance of the pretrained BERT models. To enhance model interpretability, we apply Explainable AI technique, specifically Local Interpretable Model-agnostic Explanations (LIME), to provide transparency into the decision-making process. Our system achieves accuracy, precision, recall, and F1-score values of 98.66%, 98.67%, 98.66%, and 98.66%, respectively. This work demonstrates the potential of utilizing transfer learning with BERT-based models for the automated generation of CAMs, offering high performance and interpretability in educational outcome assessment. © 2024, CC BY.

关键词： Cams

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Research on the Coupling of College Academic Style Construction and Great Ideological Politics under the Guidance of the Concept of Three-Whole Parenting

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Applied Mathematics and Nonlinear sciences 2024年第1期9卷

作者： Li, Shanjiang Tang, Laihong Student Affairs Office Hunan University of Information Technology Hunan Changsha410151 China College of Computer Science and Engineering Hunan University of Information Technology Hunan Changsha410151 China

The construction of academic style is the central link in implementing the fundamental task of cultivating moral integrity in colleges and universities, and it is also a meaningful way and carrier for realizing the all-embracing, all-encompassing and all-encompassing cultivation of human beings. Based on the four-stage cycle theory of PDCA (Plan-Do-Check-Act), the article constructs a comprehensive evaluation system focusing on the construction of academic style and the evaluation system of the quality of the significant ideological and political cultivation with the goal of value shaping. In the study, the method of variance maximization is adopted to determine the weights of evaluation indexes, and a genetic algorithm is introduced to optimize these weights to solve the optimal linear programming problem of variance maximization. The study establishes a fuzzy comprehensive evaluation and coupled coordination model through this method. Taking University S as an example, the article conducted a comprehensive review of the quality of the academic style construction and the quality of the significant ideological and political education. It used the comprehensive development index to analyze the level of the coupled and coordinated development of the two. The results show that in the construction of academic style, the weight value of students’ learning behavior is 0.2565, while in the evaluation system of the quality of considerable ideological and political education, the weight value of teaching effect is 0.2564. These two fields’ coupling coordination levels increased 1.33 times from 2010 to 2019. This indicates that the higher the level of coupled and coordinated development of college academic style construction and more excellent ideological and political education, the more helpful it is for colleges and universities to realize the goal of cultivating moral character. The study in this paper provides a practical evaluation and optimization framework to promote

关键词： Genetic algorithms

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An Efficient IoT-based Mobile Application for Continuous Monitoring of Patients

An Efficient IoT-based Mobile Application for Continuous Mon...

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Data science and engineering in Healthcare, Medicine and Biology, IEEE EMBS Special Topic Conference on

作者： Shereen Afifi Andrew Emad Radwa Taha Mirza Baig Assistant Professor in Computer science and Engineering German University in Cairo Egypt Senior student in Computer science and Engineering German University in Cairo Egypt Master Candidate in Computer science and Engineering German University in Cairo Egypt Senior Solutions Specialist in Orion Health Auckland New Zealand

Internet of Things (IoT) is gaining much popularity nowadays, especially in the field of healthcare, where different wearables, sensors and data analysis-based systems are connected together. This research work proposes an IoT-based system/application dedicated for continuous monitoring of the patient’s health parameters and vital signs. The designed application can be used by both the patient and the doctor as the doctor can track the patient’s parameters remotely in real-time to facilitate the diagnosis and to early detect patient’s health deterioration. It also enables patients to spend more time in the comfort of their own homes and communicate with their care facilities, aiming to improve the patient’s independent living and support activities of daily life. The biosensors in the smart watch or the mobile phone are utilized to measure the health parameters of the patient, which are then used by the devloped application for further processing, analysis and efficient visualization using charts and diagrams. A notification is sent to the monitoring doctor to facilitate rapid response once any of the patient’s vital signs exceeds the normal range. The developed application could be integrated within an existing hospital system or could be made available to individuals/patients via smartphones for providing support at *** Relevance: Doctors are always in need to have exact health information for their patients to receive care and therapy in a timely manner. The task of ongoing monitoring of patients’ vital signs is carried out by nurses in the interim, but the availability of a skilled and sizable team of nurses is a major concern. Thus, we propose an efficient continuous monitoring system that automates and facilitates the process of remote and continuous monitoring of patients, targeting early detection of patient deterioration while supporting independent living.

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Smart Fashion Recommendation System using Random Forest Algorithm

Smart Fashion Recommendation System using Random Forest Algo...

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Electrical Electronics and Computing Technologies (ICEECT), International Conference on

作者： Shivangi Patel Arneet Kaur Theertha Sudheer Babu Nair Shamneesh Sharma Vikas Verma Nishant Agnihotri School of Computer Science and Engineering Lovely Professional University Punjab India Delivery and Student Success UpGrad Education Private Limited Bangalore Karnataka India

ISBN: (数字)9798350378092

ISBN: (纸本)9798350378108

The fashion sector is expanding quickly in the digital age, and this means that more sophisticated recommendation systems that improve user experiences and expedite the online purchasing process are required. This work proposes a sophisticated and all-inclusive fashion recommendation system that uses machine learning techniques, specifically Random Forest, to enhance suggestion accuracy and efficiency. Users can choose their preferred fit and style using an interactive interface, which enables the system to offer clothes based on their individual profiles. Moreover, Context-based filtering involves personalizing recommendations to users based on a variety of contextual factors which may include user preferences, current fashion trends, occasion, style, body type and others. As a result of the dynamic recommendation process, the recommendations are constantly improved and grow more specific and well-rounded over time. The outcomes showcase the system's capacity to effectively combine various machine learning algorithms to evaluate a wide range of data sources, including user preferences, item features, and contextual information, to provide individualized recommendations.

关键词： Training Measurement Accuracy Machine learning algorithms Soft sensors Clothing Market research Information age Recommender systems Random forests

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Comparative Analysis of Traditional and Machine Learning Based Face Recognition Models

Comparative Analysis of Traditional and Machine Learning Bas...

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Data, Decision and Systems (ICDDS), IEEE International Conference on

作者： Shreya R Akanksha P Mulgund Shravani Hiremath Sri Harshitha A Anjan K Koundinya Department of Computer Science PES University Bengaluru India Department of Computer Science and Engineering PES University Bengaluru India Department of Information Science and Engineering IEEE Student Branch Counsellor BMS Institute of Technology and Management Bengaluru India

Face recognition technology uses methodologies to process images, register them, and compare and verify it with a set of faces it has already registered and labelled. Recent development in visual recognition showcases the immense power of utilising machine learning techniques like deep neural networks, convolutional neural networks to achieve face recognition. Based on a comprehensive literature review it was found that some of the algorithms that provide great performance metrics in a variety of conditions are MTCNN, FaceNet model, Haar cascade, LBPH, hence it was chosen to be the subject of comparison under various conditions in the paper. A machine learning model was constructed which included MTCNN for face detection and FaceNet for face *** Performance of KNN and SVM classifiers has been studied. The second model uses a combination of Haar cascade for face detection and LBPH for face recognition, a traditional face recognition technique. The results highlight that MTCNN, FaceNet and KNN perform exceptionally well. The performance of the other models are also discussed in the results and discussion section. The research not only guides researchers and practitioners in choosing suitable face recognition techniques but also offers ground for future improvements in accuracy and reliability in the field of algorithm developments.

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Designing an AI driven intelligent Tutorial System

Designing an AI driven intelligent Tutorial System

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Recent Trends in computer science and Technology (ICRTCST), International Conference on

作者： Md Shamsher Alam Surjeet Kumar Zeeshan Khursheed Hemant Kumar Mahato Shadan Bashar Anjali Suman Computer Science and Engineering Associate Professor in R.V.S College of Engineering & Technology Jamshedpur India Computer Science and Engineering Assistant Professor in Government Engineering College Sheikhpura Bihar India DGM Jio Platform Limited Mumbai India Master of Computer Application Assistant Professor in NSHM Durgapur India Master of Computer Application Assistant Professor in R.V.S College of Engineering & Technology Jamshedpur India Computer Science & Engineering Student R.V.S College of Engineering & Technology Jamshedpur India

ISBN: (数字)9798350351378

ISBN: (纸本)9798350351385

With the fast-evolving field of education, there is an increase in the demand for intelligent tutorial systems that can adapt to the diverse learning needs of individual students. This research paper explores the design and implementation of an AI-driven Intelligent Tutorial System (ITS) aimed at enhancing the personalized learning experience. The system leverages advanced machine learning algorithms to dynamically adjust instructional content, pace, and assessments based on real-time analysis of individual student performance and preferences. The paper delves into the key components of the proposed ITS, including adaptive learning models, natural language processing capabilities for interactive communication, and data-driven decision-making mechanisms. Emphasis is placed on the seamless integration of AI technologies to create an intuitive and responsive educational *** considerations in the development and deployment of the intelligent tutorial system are discussed, addressing issues related to data privacy, algorithmic bias, and the role of human oversight. The paper also highlights the collaborative potential between AI and human educators, emphasizing the system's capacity to support rather than replace teaching professionals. Through a combination of theoretical frameworks and practical examples, the research examines the potential impact of the AI-driven ITS on student engagement, learning outcomes, and the overall educational experience. Case studies and pilot implementations are presented to illustrate the system's efficacy in diverse educational *** research contributes to the ongoing discourse on AI in education by providing insights into the design principles, implementation challenges, and ethical considerations associated with developing an intelligent tutorial system. The findings aim to inform educators, policymakers, and technologists about the potential of AI to revolutionize personalized learning and contribute to the ong

关键词： Ethics Data privacy Machine learning algorithms Image recognition Decision making Tutorials Market research

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