检索结果-内蒙古大学图书馆

Learning analytics using deep learning techniques for efficiently managing educational institutes

Materials Today: Proceedings 2022年 51卷 2317-2320页

作者： Ravi Kishore Veluri Indrajit Patra Mohd Naved Veduri Veera Prasad Myla M. Arcinas Shehab Mohamed Beram Abhishek Raghuvanshi Aditya Engineering College(A) Surampalem India An Independent Researcher PhD from NIT Durgapur West Bengal India Department of Business Analytics Jagannath University Delhi-NCR India Associate Professor Behavioral Science Department De La Salle University Philippines Research Scholar Department of Computing and Information Systems Sunway University Malaysia Department of Computer Engineering Mahakal Institute of Technology Ujjain India

Increasing numbers of higher education institutions see themselves as service providers, catering primarily to the needs of its students. The improvement of student performance is a top priority for universities. It is critical to first assess the present situation of the students before designing a program to improve their performance. Higher education administrators face a significant problem in predicting a student's future success. The goal of this study is to learn what factors influence college students' decision on a major. It will be possible to forecast students' behavior, attitudes, and performance with the use of predictive tools and procedures. Predicting student performance ahead of time makes it possible to take proactive measures to raise achievement levels. To obtain a high education standard, several attempts have been made to forecast student performance. However the accuracy of these predictions falls short of the desired level of excellence. Machine learning approaches including Artificial Neural Network, Nave Bayes, and SVM are being studied. A University Data Set from UCI Machinery is used in the experimental investigation.

关键词： Learning analytics Deep learning Educational data mining Machine learning Student performance Classification Prediction

来源：评论

学校读者我要写书评

暂无评论

Effect of geometric heterogeneity using an auxiliary device on the accuracy of complete arch implant scanning: An in vitro study of different clinical simulations

引用

Journal of Prosthetic Dentistry 2023年

作者： Abdelrehim, Aly Sulaiman, Eshamsul Sofian, Hazrina Salleh, Nosizana Mohd Graduate student Department of Restorative Dentistry Faculty of Dentistry Universiti Malaya (UM) Kuala Lumpur Malaysia Associate Professor Department of Restorative Dentistry Faculty of Dentistry Universiti Malaya (UM) Kuala Lumpur Malaysia Senior Lecturer Department of Software Engineering Faculty of Computer Science & Information Technology Universiti Malaya (UM) Kuala Lumpur Malaysia

Statement of problem: Intraoral scanning of implants supporting complete arch prostheses is limited because of the lack of geometric heterogeneity and unique reference points, creating inherent errors in the image stitching process by the scanner software program. Purpose: The purpose of this in vitro study was to evaluate the significance of geometric heterogeneity on complete arch implant scanning by using a novel auxiliary geometric device. Three different clinical simulations were tested to assess its significance. The study also assessed whether scans produced using the auxiliary device would meet a clinically acceptable threshold. Material and methods: A total of 60 scans (n=20) were performed using an intraoral scanner in 3 different clinical simulations: 2 parallel implants, 4 parallel implants, and 4 implants with a 30-degree posterior angulation of the distal implants. Scanning alternated between using the auxiliary geometric scanning device (test groups;4IP+, 4IA+, 2IP+) and not using the device (control groups;4IP-, 4IA-, 2IP-). A reference scan for each model was prepared from a high precision laboratory scanner. The scans were analyzed for accuracy in 3-dimensional deviation, interimplant distance deviation, and angular deviation by using an inspection software program. The effect of the auxiliary device was statistically analyzed by comparing scans of the same group using the paired t test for normally distributed data and the Wilcoxon Signed Rank test when data were not normally distributed (α=.05). Results: Significant effects of the auxiliary geometric device were found in 3-dimensional, distance and angular deviations (P<.05). Scans performed using the device were significantly more accurate in most implant positions (P<.05). Linear and angular deviations were clinically acceptable for all test groups. However, the deviations were above the clinically acceptable threshold for the control groups. Conclusions: Using an auxiliary geometric device sig

关键词：

来源：评论

学校读者我要写书评

暂无评论

Hybrid CNN-SVM Classifier for Handwritten Digit Recognition

引用

Procedia computer science 2020年 167卷 2554-2560页

作者： Savita Ahlawat Amit Choudhary Reader Deptt. of Computer Science and Engineering Maharaja Surajmal Institute of Technology New Delhi Associate Professor Deptt. of Computer Science Maharaja Surajmal Institute New Delhi

The aim of this paper is to develop a hybrid model of a powerful Convolutional Neural Networks (CNN) and Support Vector Machine (SVM) for recognition of handwritten digit from MNIST dataset. The proposed hybrid model combines the key properties of both the classifiers. In the proposed hybrid model, CNN works as an automatic feature extractor and SVM works as a binary classifier. The MNIST dataset of handwritten digits is used for training and testing the algorithm adopted in the proposed model. The MNIST dataset consists of handwritten digits images which are diverse and highly distorted. The receptive field of CNN helps in automatically extracting the most distinguishable features from these handwritten digits. The experimental results demonstrate the effectiveness of the proposed framework by achieving a recognition accuracy of 99.28% over MNIST handwritten digits dataset.

关键词： Handwritten digit recognition Hybrid model Convolutional Neural Network Support Vector Machine

来源：评论

学校读者我要写书评

暂无评论

Multipath routing mechanism using embedded architecture of interfaced circuit

引用

Microprocessors and Microsystems 2020年 77卷 103188-103188页

作者： Alappat, Valanto Prathap, Joe Research scholar Faculty of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai India Associate Professor Department of IT RMD Engineering College Chennai India

Mobile Adhoc Network (MANET) is a group of remote compact hubs confining a short term framework without any guidance of any settled communication establishment. In view of confined resources, visit organizes packets and surprising topological changes, proactive gathering designs get high overheads in this condition. To keep the security of compact uniquely selected frameworks various wellbeing endeavors are arranged, for instance, encryption estimations, firewalls et cetera. However there is some degree of threatening exercises. In this work, a Modified IDEA-HMAC based secure disseminated grouping calculation for MAODV routing protocol is proposed for secure message transmission, routing through Cluster based Intrusion Detection System in MANET. This algorithm for Intrusion recognition frameworks are proposed to distinguish any intruder in the system and its vindictive exercises. It is additionally utilized for cluster arrangement, upkeep and purging activities and grouping data for speedy course disclosure, supports and cluster conveyance. The Modified IDEA is utilized for encryption, it is one of the safe and most generally utilized square figures and the cryptographic quality of Modified IDEA depends on a blend of three inconsistent gathering tasks – XOR, expansion and particular duplication and it is secure against powerless key assaults. © 2020

关键词： Cryptography

来源：评论

学校读者我要写书评

暂无评论

Survey on Impact and Learning’s of the Online Courses on the Present Era

引用

Procedia computer science 2020年 172卷 82-91页

作者： T. Anitha Kumari CH. Hemalatha M Subhani Ali R Naresh Assistant Professor Department of Computer Science Engineering HITAM Hyderabad Telangana 501401 India Associate Professor Department of Mechanical Engineering HITAM Hyderabad Telangana 501401 India Assistant Professor Department of Electrical and Electronics Engineering HITAM Hyderabad Telangana 501401 India

Day to day technology is changing to upgrade or adopt technology faculty as well as students preferring online courses like NPTEL. With the fast development of internet techniques, data and communication technology is being more and more employed in curricula, and learning portfolios may be mechanically retrieved and maintained as learners act through e-learning platforms. NPTEL provided open access to hundreds and thousands of learners to take the preferred courses and helped to become experts in a particular area. This paper describes the impact of the online courses (NPTEL) on the learners and challenges and learning’s from the online courses. The participants comprised 114 faculty, who were surveyed regarding their learning experiences, motivation, challenges and intentions to use NPTEL. And what can be improved from the Faculty and student point of view?

关键词： Online courses Learning’s Challenges Motivation

来源：评论

学校读者我要写书评

暂无评论

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

Dynamic fingerprint construction and tree generation approach for biometric template protection

引用

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.

关键词：

来源：评论

学校读者我要写书评

暂无评论

An approach for Protein Secondary Structure prediction using prediction-based language models

An approach for Protein Secondary Structure prediction using...

引用

Emerging Trends in Information Technology and engineering (ic-ETITE), Conference on

作者： Leo Dencelin Xavier Ramkumar Thirunavukarasu Department of Computer Science & Engineering Satyabhama Institute of Science and Technology Chennai India Associate Professor and Head School of Information Technology and Engineering VIT Vellore India

ISBN: (数字)9781728141428

ISBN: (纸本)9781728141435

Prediction based language models are considered as one of the major concepts in Natural Language processing which gains knowledge from unstructured text data. Extracting insights from sequential data such as biological sequences is an important problem in genomics, proteomics and classifying the secondary structures of protein, helps the researchers in aiding to understand protein functions. This is considered as one of the important preliminaries of Drug development. Traditional techniques such as sequential models, probabilistic techniques and statistical approaches were widely applied in structure prediction which extracts insights from sequence of amino acid. However, handheld feature extraction becomes a tedious task, which eventually leads to less accuracy. Our novel approach creates vectors using word embeddings which is assumed to consider contextual information of amino acids thereby improving the accuracy of secondary structure prediction approach. This is considered as an optimistic solution for secondary structure prediction problem. In this approach a variation of word embeddings - Continuous Bag of Words (CBOW) method is proposed which retains the sequential information of all amino acid in the protein chain. This vector is used as input features of Deep Neural Network classifier and class labels are classified into Helix, Sheet, Coil. We have tested this NLP based approach on GenBank dataset. The infrastructure required for this analysis was leveraged from Google Colab.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Feeling Recognition by Facial Expression Using Deep Learning

引用

Journal of Physics: Conference Series 2021年第1期1717卷

作者： Dr. Shalini Gupta Dr. Shubha Jain Associate Professor Computer Science and Engineering Department Kanpur Institute of Technology KANPUR Associate Professor Computer Science and Engineering Department Axis Institute of Technology and Management KANPUR

The visible appearance of the emotion state, personality, purpose, psychological feature activity and psychopathology of an individual is the Facial expression. This plays an outgoing role in social affairs. Automatic recognition of facial expressions will be a vital part of natural human-machine interfaces. It should even be applied in activity science and in clinical apply. Fellows in nurturing automatic facial features Recognition system must perform detection and placement of faces during a disordered scene, facial feature extraction and facial features classification. Emotion recognition by facial features utilizes a Deep Learning system, which is enforced victimization Convolution Neural Network (CNN). The CNN model of the project relies on LeNet design. Kaggle facial features dataset with seven facial features labels as fear, anger, happy, surprise, sad, neutral and disgust is employed during this project. The system achieved 60.37 accuracy.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Centralized and Reliable Digital Twin Models for Smart City's Buildings Protection during Disaster

Centralized and Reliable Digital Twin Models for Smart City'...

引用

Computational Modelling, Simulation and Optimization (ICCMSO), International Conference on

作者： Md.Sameeruddin Khan R. Chinnaiyan S Balachandar S.Jafar Ali Ibrahim N.S.Kalyan Chakravarthy C. Kalaiarasan R Divya Dean School of CSE & IS Presidency University Bengaluru INDIA Professor School of CSE&IS Presidency University Bengaluru INDIA VTU-RC Department of MCA CMR Institute of Technology Bengaluru INDIA Department of IoT School of Computer Science and Engineering Vellore Institute of Technology Vellore Tamilnadu India School of CSE QIS College of Engineering & Technology Ongole AP Associate Dean School of CSE & IS Presidency University Bengaluru INDIA

Digital Twin is one of the fast-growing technology digitalization space which needs to complete Smart City's problem areas. Digital twin is virtual representation of physical things or assets or process in a connected network. The data from Physical asset or things IOT Devices, Sensors, Cameras needs to be collected in a large cloud store which contains the engineering data like machine diagrams or flow charts, building blueprint, building electrical map or waterline map, Building information Model, 3D images, computer Aided Design (CAD), controls data IOT Sensors, IOT Gateway, Drones, Cameras, etc. and supporting data. This research paper narrates the different types of digital twin with a use case of Smart Building and how it should be protected during disaster time with different technologies and dataset

关键词： Solid modeling Three-dimensional displays Smart buildings Computational modeling Urban areas Data models Digital twins

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：