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Developing a knowledge structure using Outcome based Education in Power Electronics engineering

Procedia computer science 2020年 172卷 1026-1032页

作者： Rathy G.A. Sivasankar P Gnanasambandhan T.G. Associate Professor EE&CE Dept NITTTR Chennai India Assistant Professor EE&CE Dept NITTTR Chennai India Former Professor and Head Computer Science and Engineering Dept NITTTR Chennai

Outcome based education (OBE) is student-centered instruction model that stresses on judging student performance through outcomes. Outcomes include knowledge, skills and behavior. Outcome-Based Education model is being adopted at a fast pace at Technical institutions all over the world. It is considered as a massive leap forward to convalesce technical education and help Engineers compete with their global counterparts. OBE gives more weightage on what the students will be able to ‘do instead of what they will ‘know’. Hence it is important to develop the instructional model to improve knowledge, skill, behaviour of the students. Knowledge structure is the micro level component and the part of the course outcome which will enable the student to gain the confidence of ‘doing’ instead of ‘knowing’. This paper proposes an Instructional Model by developing a knowledge structure in Power Electronics engineering.

关键词： Outcome based Education Programme Educational Objective Programme Outcome Course Outcome Interdisciplinary Core Logics

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Dynamic fingerprint construction and tree generation approach for biometric template protection

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AIP Conference Proceedings 2023年第1期2917卷

作者： Ashoka Rajan Swaminathan Annadurai Abishi Chowdhury Ernest Johnson Assistant Professor School of Computer Science and Engineering Vellore Institute of Technology Chennai India Associate Professor Paul J. Hill School of Business Faculty of Business Administration University of Regina Regina Saskatchewan Canada

This paper proposes a novel security method for protecting biometric fingerprint templates and storing them safely by creating a combined fingerprint template from different fingerprints, thereby creating a new virtual identity during enrolment. However, the second fingerprint image combined would be an image that was dynamically created by merging parts of several different images based on a merging algorithm used. We further extract the minutiae features from the two fingerprints. A combined fingerprint template is produced using the extracted information. Finally, the biometric values from the template are stored in a user-defined tree created. A new virtual identity is thus created to protect biometric templates from hackers and crackers. Even though the hacker has access to the database, they will not be able to match the biometric template with a person’s identity. Thus, when the database is stolen, the method avoids compromising complete minutiae features belonging to a single fingerprint. The proposed method achieves 0.3% FRR and 0.1% FAR. Hence, it balances both the recognition and security of the system.

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A Survey on Automatic Text Summarization Techniques

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Journal of Physics: Conference Series 2021年第1期2040卷

作者： S Hima Bindu Sri Sushma Rani Dutta Assistant Professor Department of Computer Science and Engineering Koneru Lakshmaih University Assistant Professor Department of Computer Science and Engineering Koneru Lakshmaih University.

In recent years, there is a tremendous explosion in the amount of text data on the internet and in the archives of news articles, scientific papers, legal documents and even in online product reviews. Text summarization is playing an important role in automatic content creation, minutes of meeting generation, helping disabled people and also for quick online document reading. To achieve these, several automation techniques have been proposed in various researches. In this regard, performing an exclusive survey on different methods, approaches of automatic text summarization which are published in different articles in most recent three years.

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A review on statistical analysis for data science

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AIP Conference Proceedings 2023年第1期2916卷

作者： Venkat Kumar Perumalla Himanshu Gupta Department of Mathematics Chandigarh University Gharuan - 140413 Mohali Punjab India Assistant (professor) Department of Computer Science and Engineering Chandigarh University Gharuan - 140413 Mohali Punjab India

This study makes a speciality of a way to use the Statistical Analysis for Data science approach to a real-international commercial enterprise scenario. Through this paper, the prominence of the Statistical Learning is known. Statistical Learning helps us, locating out the answer for a statistical inferential trouble through which it is easy to discover a predictive characteristic primarily based on the information we have. Statistical learning performs a distinguished position in the various fields like computer Vision, Speech Recognition, Emotion and Gender identification of Data science.

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VMATE – Intelligent E-Learning Management System for Educational Institutions

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IOP Conference Series: Materials science and engineering 2021年第1期1042卷

作者： Pudiyadatha Anjali Nunnabhatla Harshita M.D.N. Akash Patlolla Vinith G.S Prasada Reddy Computer Science and Engineering Vardhaman College of Engineering Assistant Professor Computer Science and Engineering Vardhaman College of Engineering

The world is facing a huge health crisis which is demanding to reorganize the way it functions from square one. The spread of the pandemic, the shutdown of education institutions, and the shift to online learning were so fast that it barely gave any time to consider the difficulties faced by students. This is a great opportunity where educational institutions will shift to blended learning; hence it will become a new way of learning where there will be a need to find new ways to deliver the best content by using learning management systems. Therefore, the virtual learning world will create a great impact on the current education system due to the diverse effect of the epidemic. Hence different organizations are tremendously advancing their technology, and it will become more crucial over time. VMATE –Intelligent E-Learning Management System provides an interface for learners, which is of great significance and practical value for the improvement of learning and teaching quality. The use of computers and the Internet has introduced technological conditions for teachers and students who can make good use of online information provided and communicating with others. This can be used by institutions and for different environments, where they can have computer-based instructions, blended-learning, and increased quality and quantity learning. Besides some basic management functions, the system focuses on assignment grading, assessment for various learning courses which makes it suitable to provide personalized grading and detailed feedback.

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The Role of Converged Network in Disruptive Technology

The Role of Converged Network in Disruptive Technology

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Intelligent engineering and Management (ICIEM), International Conference on

作者： Vinay Kumar Divya Singh S. Vikram Singh Tarun Anand Assistant Professor Amity University Greater Noida Campus Computer Science and Engineering Amity University Greater Noida Campus

ISBN: (数字)9781728140971

ISBN: (纸本)9781728140988

In this paper I talk about converge networks and its types, moving on I talk about the technological elements of the converged network. I give a detailed view of the benefits of converged networks and various challenges faced in its implementation while giving an informative view of various characteristics needed by a network to converge. I provide a solution for the challenges faced in converged network using JMX.

关键词： Java Business Convergence Software Hardware TV Switches

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A Survey on Video-based Evidence Analysis and Digital Forensic

A Survey on Video-based Evidence Analysis and Digital Forens...

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International Conference on Computing Methodologies and Communication (ICCMC)

作者： R. V. Mante Reshma Khan Assistant Professor Department of Computer Science & Engineering Government College of Engineering Amravati Maharashtra India M.Tech Scholar Department of Computer Science & Engineering Government College of Engineering Amravati Maharashtra India

ISBN: (数字)9781728148892

ISBN: (纸本)9781728148908

In the past couple of decades, the most emerging domain across the globe is Information Technology [IT]. It has made a significant contribution in cracking the criminal case and preparing the strong cases in the court of justice. IT technologies have become a vital tool for examination and gathering of the digital evidences. As crime rate is increasing day-by-day, in order to reduce the occurrence of crime and bring the culprit of the crime to justice, the computer forensics plays an indispensable role. With the recent technological developments, it has become more powerful and portable. Large amount of data has created stored and accessed everyday. Many technologically advanced devices are acting as repositories for the collected personal information. Such devices remain portable and accessible with a single click or even to the voice command. To have such large-scale information is important to get the conviction for the culprits but at the same time, investigating agencies has to maintain the privacy of the recovered data to make it admissible in the court. This gives rise to the security mechanism for such data. Collection, analysis, investigation and reporting of the digital data come under forensic science, which is a part of digital forensics domain. In this paper, we have presented a review on the existing researches available in the field of video forensic analysis.

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Effects of business intelligence tools on financial performance of it industry

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AIP Conference Proceedings 2024年第1期2971卷

作者： Yeluri S. D. S. Sri Vardhan U. M. Gopal Krishna I. Tejaswini K. Samuel Johnson Israel P. Prathyusha Assistant Professor Department of Computer Science and Engineering Sumathi Reddy Institute of Technology for women Ananthasagar Telangana VIT – AP School of Computer Science & Engineering VIT – AP University Andhra Pradesh India VIT – AP School of Business VIT – AP University Andhra Pradesh India Sumathi Reddy Institute of Technology for Women Warangal Telangana India

The goal of Business Intelligence is to look into, combine, and logically collect and analyse data from different customer information sources, the environment, competitors, and markets, etc., in order to judge how well businesses in the IT industry are doing. The goal of this study is to find out how Business Intelligence tools affect how well IT companies do financially. The method is a descriptive survey that can’t be used in real life. As part of the study, 420 IT experts from IT companies in Hyderabad were looked into as part of the statistical population. Also, confirmatory factor analysis was used to check the validity of the 25-item questionnaire, and validity analysis was used to gather data. The results showed that Business Intelligence had a big effect on the financial performance system of the organisation. Still, Business Intelligence made IT companies more innovative. Financial Forecasting and Financial Control System affect the financial performance system by 0.11 and 0.05 points, respectively. The Fund Management System affects the financial performance system by -0.07 points. The Financial Performance System is affected by the Internal Audit System by 0.05. The effects of Financial Forecasting, Financial Control System, and Internal Audit System on the organization’s financial performance system. Thus, it can be concluded that Structured Equation Modelling in IBM SPSS AMOS has been used to indirectly examine the impact of Business Intelligence tools on financial performance. Surprisingly, these three elements are required to improve financial performance.

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Secuyolo: Secure Object Detection Framework With Darknet-53 and CBAM in Edge Devices

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Concurrency and Computation: Practice and Experience 2025年第15-17期37卷

作者： P. Lakshmiramana A. Vadivel Computer Science & Engineering GITAM School of Technology (Research Scholar) & Madanapalle Institute of Technology & Science (Assistant Professor) GITAM (Deemed to Be University) Dodballapura Karnataka India Madanapalle Institute of Technology & Science Angallu India Artificial Intelligence and Data Science GITAM School of Technology GITAM (Deemed to Be University) Dodballapura Karnataka India

Object detection in edge computing has emerged as a pivotal solution for processing sensor data locally, thereby minimizing latency and bandwidth consumption. However, this introduces significant privacy concerns, as edge servers may exploit sensitive sensor data. Traditional frameworks often overlook data security and privacy protection, presenting challenges in balancing privacy with computational efficiency in resource-constrained environments. To address these issues and improve performance, we propose SecuYOLO CBAMNet53, a novel framework combining Secure YOLO V3 with Darknet-53 and the CBAM. This model enhances feature extraction capabilities, ensuring privacy protection and accurate real-time object detection on edge devices. Darknet-53 serves as a deep feature extractor, while CBAM boosts discriminative power through channel-wise and spatial attention, improving detection accuracy and handling complex scenes. It integrates YOLOv3 with security measures like data encryption, secure deployment, and differential privacy, safeguarding sensitive information during inference. By classifying data as public or private for smart IoT applications, SecuYOLO CBAMNet53 optimizes performance and prevents privacy breaches. The proposed SecuYOLO, employing Darknet-53 with CBAM as its backbone, achieves outstanding performance in both an average recall of 67.62 and an average precision of 51.2. The model's dynamic recalibration of feature maps and robust security mechanisms ensure reliable object detection and privacy protection, making it suitable for real-world applications.

关键词： attention module data privacy deep learning edge computing object detection YOLOv3

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Review on Crop Prediction Using Deep Learning Techniques

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Journal of Physics: Conference Series 2021年第1期1767卷

作者： M K Dharani R Thamilselvan P Natesan PCD Kalaivaani S Santhoshkumar Assistant Professor Department of Computer science and Engineering Kongu Engineering College Erode Professor and Head Master of Computer Applications Kongu Engineering college Erode Professor and Head Computer Technology (UG) Kongu Engineering college Erode Assistant Professor (SLG) Department of Computer science and Engineering Kongu Engineering College Erode Assistant Professor (SRG) Department of Computer science and Engineering Kongu Engineering College Erode

Agriculture is the very important sector of each country, where the gross domestic pay relies on it. The outcome of the agriculture or crop management was completely based on the end yield and the market rate. The complete factor of the crop yield depends on timely monitoring and suggestion. Artificial intelligence gives a way to monitor the crop and to predict the yield in an automatized outcome. The study has been made on the deep learning and its hybrid techniques such as Artificial neural network, deep neural network and Recurrent neural network. It helped to identify how the technology of artificial intelligence helps to improve the crop yield. The research study clearly gives the idea and need of recurrent neural network and hybrid network in the field of agriculture. It also shows how it outperforms the other networks such as artificial neural network and convolutional neural network. The results were analyzed and the future perspectives were drawn with the obtained outcome.

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