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Automated Subject Allotment to Faculty in an Academic institute Using Maxflow Problem

Automated Subject Allotment to Faculty in an Academic Instit...

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2024 International Conference on Advances in Computing research on science engineering and technology, ACROSET 2024

作者： Sehta, Neha Shah, Naman Acropolis Institute of Technology and Research Department of Computer Science and Engineering Indore India

ISBN: (纸本)9798350388800

Presently, educational organizations are utilizing manual procedures to assign subjects to faculties depending on their own preferences, which gives rise to prejudice and therefore, discontentment. The best approach would be to allocate the most qualified individual to instruct the appropriate course, taking into account their knowledge and experience. Many instructional units rely on manual trial-and-error methods, which are time-consuming, inefficient, and prone to biased judgment. Moreover, the distribution is likely disadvantageous for several academic personnel. This study introduces an automated allocation of subjects to the faculties, taking into account the preferences in an effective way. The subject allocation problem is mapped into a maxflow problem and solved using Edmonds-Karp algorithm. A satisfaction metric can be computed to evaluate the effectiveness of the solution proposed which is average calculated on the distribution of subject as per the choice of faculty. © 2024 IEEE.

关键词： Automation

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Accelerating Cloud Deployment Through Containerization Technologies

Accelerating Cloud Deployment Through Containerization Techn...

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2024 International Conference on Advances in Computing research on science engineering and technology, ACROSET 2024

作者： Lakkadwala, Aayushya Lakkadwala, Prashant Acropolis Institute of Technology and Research Dept. of Computer Science and Engineering Indore India Acropolis Institute of Technology and Research Dept. of Information Technology Indore India

ISBN: (纸本)9798350388800

This research investigates the effectiveness of containerization technologies, with a focus on Docker, in accelerating cloud application deployments. The study examines diverse methodologies aimed at optimizing container image size, refining container orchestration mechanisms for expedited deployments, and evaluating the integration of serverless functions within containers to reduce deployment durations. By synthesizing existing scholarly literature with empirical analyses, this paper aims to elucidate the efficacy of containerization in streamlining cloud deployment processes. It offers insights into optimal practices and identifies prospective avenues for future research and development in the field. © 2024 IEEE.

关键词： Cloud platforms

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Revolutionizing Healthcare with Federated Learning: A Comprehensive Review

Revolutionizing Healthcare with Federated Learning: A Compre...

引用

2024 International Conference on Advances in Computing research on science engineering and technology, ACROSET 2024

作者： Mishra, Snehlata Tondon, Ritu Rathore, Narendra Pal Singh Sage University Computer Science & Engineering Indore India Acropolis Institute of Technology and Reserach Computer Science & Engineering Indore India

ISBN: (纸本)9798350388800

Federated learning has become a game-changing paradigm in healthcare, offering secure and private federated model training across dispersed data sources. This thorough analysis examines the uses, developments, and challenges of federated learning in healthcare. Beginning with an elucidation of its fundamental principles, we examine its potential to revolutionize healthcare delivery by facilitating collaborative model training without data sharing. We survey diverse applications, including disease diagnosis, personalized treatment recommendations, drug discovery, and population health management, highlighting federated learning's impact on improving patient outcomes and healthcare efficiency. Technological advancements, such as differential privacy and secure aggregation, driving federated learning adoption, are explored. Despite its promise, federated learning faces challenges including data heterogeneity, model communication overhead, privacy concerns, and regulatory barriers. We discuss these challenges and propose solutions and future research directions. This review provides a comprehensive understanding of federated learning's role in healthcare, addressing opportunities, limitations, and future prospects. © 2024 IEEE.

关键词： Collaborative learning

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TypeScript: An Open-Source Programming Language with Options for Robust Development and Large-Scale Applications

TypeScript: An Open-Source Programming Language with Options...

引用

2024 International Conference on Advances in Computing research on science engineering and technology, ACROSET 2024

作者： Kushwah, Shreyansh Bansal, Chanchal Rathore, Shreyansh Kate, Vandana Bargal, Divyanshi Vishwakarma, Divesh Acropolis Institute of Technology and Research Dept. of Computer Science and Information Technology Indore India

ISBN: (纸本)9798350388800

JavaScript is widely used for web and application development but is criticized for its dynamic nature. TypeScript, an open-source language developed by Microsoft, addresses theseconcerns by introducing optional static typing. Released in 2012, TypeScript is a syntactical superset of JavaScript, offering features to enhance code quality and support large-scale applications. However, despite its benefits, the adoption of TypeScript is not without challenges. From a research perspective, further investigation is needed to understand the impact of TypeScript on software development practices, its integration with existing JavaScript codebases, and its effectiveness in improving overall software quality and developer productivity. Such research can provide valuable insights into the evolution of programming languages and their adaptation to changing technologies and industry demands. © 2024 IEEE.

关键词： Software quality

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A Machine Learning-Based Approach for Network Optimization in WSNs

A Machine Learning-Based Approach for Network Optimization i...

引用

International Conference on Data science, Computation and Security, IDSCS 2023

作者： Bhattad, Bharti Sethi, Kamal Kumar Pal Singh Rathore, Narendra Bhanodia, Praveen Mishra, Durgesh Kumar Computer Science Engineering Acropolis Institute of Technology and Research Indore India School of Computer Science and Information Technology Symbiosis University of Applied Sciences Madhya Pradesh Indore India

ISBN: (纸本)9789819709748

With the advancements in interconnected devices and automation, wireless sensor networks have gained substantial importance. Energy constraint is one of the main issues that wireless sensor networks (WSNs) must deal with. Moreover, to enhance the effectiveness, it is necessary to reduce the latency as much as possible. Wireless sensor networks can be optimized for latency and energy consumption using a variety of protocols, with their own pros and cons. This paper investigates different aspects related to wireless sensor networks along with the relevant approaches. The intent of this paper is to present a reinforcement learning-based approach for optimized routing in WSNs. The protocol is designed to cater to the constraints of limited energy and latency, with the evaluation of the proposed algorithm in terms of network lifetime and latency. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Reinforcement learning

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Exploring Agile Methodologies in Educational Software Development- A Comparative Analysis and Project Management Insights 3

Exploring Agile Methodologies in Educational Software Develo...

引用

3rd IEEE International Conference on ICT in Business Industry and Government, ICTBIG 2023

作者： Kate, Vandana Bhalerao, Shilpa Sharma, Vanshika Acropolis Institute of Technology and Research Dept. of Computer Science and Information Technology Indore India Acropolis Institute of Technology and Research Dept. of Computer Science and Technology Indore India

ISBN: (纸本)9798350343274

In the realm of academic research, the task of determining the most suitable Software Development Life Cycle (SDLC) becomes complex, owing to the diverse project requirements, rapidly changing technology, team skills and experience, organizational culture and readiness, flexibility and adaptability needs, and decision-making complexity. It requires a thorough analysis of various factors to make a wise decision that aligns with the project's goals and constraints. A variety of models, including Waterfall, Prototyping, and Spiral, offer distinct sets of advantages and disadvantages. Agile modeling is a flexible and iterative software development strategy that emphasizes collaborative modeling and rapid feedback. The agile philosophy promotes transparency, effective communication, and embracing change to meet evolving project needs efficiently and effectively. An In-Depth Examination of Agile Methodologies versus Conventional Approaches gives a deeper understanding of their respective strengths, weaknesses, and applicability. Also as the educational institutes increasingly recognize the importance of providing industry-relevant skills and preparing students for dynamic work environments, agile methodologies are likely to play a vital role in shaping the future of education and fostering the success of students in their careers. In this paper, we have explored the practical application of well-established Agile methodologies including Scrum, Kanban, Lean, Extreme Programming (XP), Feature Driven Development, and Dynamic Systems Development Method (DSDM) within the context of educational institutions and project management. © 2023 IEEE.

关键词： Project management

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Review and Explore the Transformative Impact of Artificial Intelligence (AI) in Smart Healthcare Systems

Review and Explore the Transformative Impact of Artificial I...

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2024 International Conference on Advances in Computing research on science engineering and technology, ACROSET 2024

作者： Nagar, Sneha Patidar, Mukesh Sheikh, Rashid Singh, Sudhanshu Kashiv, Ashutosh Jain, Ankit Namdeo, Shravan Kumar Paranjpe, Pranav Mandloi, Devendra Singh Indore Institute of Science and Technology Department of Electronics and Communication Engineering Indore India Parul Institute of Engineering and Technology Parul University Department of Computer Science & Engineering Vadodara India Acropolis Institute of Technology and Research Department of Computer Science & Engineering Indore India Indian Institute of Technology Indore Department of Electronics and Communication Engineering Indore India

ISBN: (纸本)9798350388800

Because of its high level of complexity and data collection capabilities, the healthcare industry employs artificial intelligence (AI) more than other sectors. Artificial intelligence is becoming an increasingly important part of our daily routines. AI's features include extremely low error rates, constant accessibility, quick analysis, and real-time data dissemination. This paper examines the crucial role of artificial intelligence in intelligent healthcare systems, with a particular emphasis on enhancing healthcare delivery. Artificial intelligence in healthcare is rapidly evolving, with the potential to significantly enhance patient care, diagnosis, treatment, and cost distribution. It also presents issues of transparency, honesty, and availability. This study will look into the benefits, drawbacks, and other aspects of artificial intelligence in intelligent healthcare systems. © 2024 IEEE.

关键词： Artificial Intelligence (AI) Ethical Considerations Explainable AI (XAI) Healthcare Resource Allocation Healthcare Systems Smart Treatment Planning

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Enhancing Data Security and Data Sensitivity: Leveraging the Synergy of Blockchain Artificial Intelligence 3

Enhancing Data Security and Data Sensitivity: Leveraging the...

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3rd IEEE International Conference on ICT in Business Industry and Government, ICTBIG 2023

作者： Jain, Vikas Chouhan, Sachin Kate, Vandana Nigam, Nidhi Bhalerao, Shilpa Acropolis Institute of Technology & Research Dept of Computer Science and Information Technology Indore India

ISBN: (纸本)9798350343274

Data security and sensitivity have become significant challenges for organizations worldwide in the digital transformation era. Protecting sensitive user data from cyber-attacks, breaches, and information exposure is of utmost concern. This research paper explores the potential of integrating blockchain, artificial intelligence (AI), and machine learning (ML) technologies to enhance data protection and ensure confidentiality. The introduction provides an overview of data sensitivity and the growing importance of data security in the digital age. It delves into blockchain technology, emphasizing its decentralized, immutable ledger for secure authentication, access control, and tamper-proof data storage. The paper presents various use scenarios, illustrating how blockchain safeguards sensitive user data, including medical records, financial information, and personal identifiers. It further examines AI's role in data security, showcasing its capability to detect threats, analyze anomalies, and authenticate users, thereby blocking unauthorized access to confidential information. Additionally, the study explores machine learning for data sensitivity management, highlighting its prowess in formulating access control policies and data categorization. The research underscores how blockchain, AI, and machine learning synergize to create a comprehensive data security architecture, enabling businesses to leverage the immutability of blockchain and the intelligent data protection of AI/ML. Real-world examples demonstrate the effectiveness of this synergy in enhancing data security and safeguarding against modern threats. © 2023 IEEE.

关键词： Blockchain

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Use of IOT in computer Control Using Hand Gesture Using AT Mega 328 over the Cloud 3

Use of IOT in Computer Control Using Hand Gesture Using AT M...

引用

3rd IEEE International Conference on ICT in Business Industry and Government, ICTBIG 2023

作者： Rathod, Ishwarlal Rathod, Kunal Gupta, Neha Symbiosis University of Applied Sciences Computer Science and Information Technology Indore India Acropolis Institute of Technology and Research Computer Science and Engineering Indore India

ISBN: (纸本)9798350343274

In the realm of remote control, my preference is computer manipulation through hand gestures. Recent strides in technology showcase the feasibility of using manual gestures on Arduino platforms, facilitated by cloud computing. A Wi-Fi-based hand gesture computer control system was developed using an ESP-01 Wi-Fi module and an Arduino microcontroller, enabling remote control and monitoring without geographical constraints or time limitations. The ESP8266 Wi-Fi module played a crucial role in establishing wireless communication with an Android application (S Remote) for transmitting commands to regulate domestic appliances. The AT mega 328 AVR series Microcontroller R3, lacking built-in Wi-Fi, required the ESP-01 Wi-Fi module for wireless communication and programming. The Arduino IDE facilitated programming, incorporating ESP-01 and LCD components. Hand gesture-controlled robots and PC/laptop hand gesture control systems, both utilizing Arduino technology, exemplify similar applications. The Human Machine Interface (HMI) concept involves physical components and software enabling communication between users and machines. HMI devices, including LED indicators and touch screens, traditionally use keyboards and mice. This research implemented a hand gesture controller using Arduino technology, specifically for web browser features, video playback, and VLC media player audio adjustments. The ESP-01 Wi-Fi module, configured via AT instructions through a UART serial connection, played a key role in integrating a hand gesture system for effective computer control. Users can perform actions like playing or pausing videos and adjusting audio amplitude within the VLC media player solely through manual gestures. © 2023 IEEE.

关键词： Wi-Fi

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A Comprehensive Machine Learning Based Ensemble Model for Prediction of Possible Diseases and Recommending Medicines 3

A Comprehensive Machine Learning Based Ensemble Model for Pr...

引用

3rd IEEE International Conference on ICT in Business Industry and Government, ICTBIG 2023

作者： Jangde, Priyanka Sethi, Kamal Kumar Singh, Narendra Pal Bhanodia, Praveen Mishra, Durgesh Computer Science and Engineering Acropolis Institute of Technology and Research Indore India Symbiosis University of Applied Sciences Indore India

ISBN: (纸本)9798350343274

Many instances remain untreated globally due to the lack and unavailability of medical services. In this regard, efficient monitoring and analysis of medical records will be helpful in timely identification and prediction of diseases. To enable a quicker and more precise diagnosis, a platform that keeps track of a patient's medical history and makes illness predictions based on the patient's present symptoms is needed. Early disease prediction allows users to determine the severity of a condition and take appropriate action timely. Thus, anticipation of illness in its early stage becomes essential but it's difficult for doctors to anticipate outcomes precisely and accurately based only on symptoms. Availability of medical data and its analysis with the help of machine learning techniques can help the healthcare system for appropriate predictions and recommendations of diseases. In this paper, based on the patient's symptoms and medical records, a general illness prediction system is proposed. Using the input image for disease prediction, we applied an ensemble model exploiting the KNN, SVM, Naïve bayes and deep learning techniques to accurately predict diseases. The proposed model superseded the existing techniques with 98% accuracy on experimental study performed using benchmark datasets. © 2023 IEEE.

关键词： Diseases

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