2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA)最新文献_第10页

Comparing the Access Control Mechanism in Database, Cloud and Femtocells 数据库、云和基站访问控制机制的比较

2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA) Pub Date : 2018-03-01 DOI: 10.1109/ICECA.2018.8474933

Harshita R. Jhurani, P. Chandana, Yarram Vijay Kumar Reddy, M. Sharada

引用次数: 0

A Petite Guide to Programming in 64bit X86 Assembly Language for Linux Linux 64位X86汇编语言编程指南

2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA) Pub Date : 2018-03-01 DOI: 10.1109/ICECA.2018.8474886

Vidya Pokale, Madhuri Chavan

引用次数: 0

Secure boot of Embedded Applications - A Review 嵌入式应用程序的安全启动综述

2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA) Pub Date : 2018-03-01 DOI: 10.1109/ICECA.2018.8474730

R. Rashmi, A. Karthikeyan

引用次数: 7

Transitions Between Amorphous and Crystalline States Using Electrical Pulse in Tellurium-Based Semiconductor 利用电脉冲在碲基半导体中实现非晶态和晶态的转换

2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA) Pub Date : 2018-03-01 DOI: 10.1109/ICECA.2018.8474622

T. Chakraborty

引用次数: 0

Design of Distance Based Reactive Routing Clustering Protocol for Heterogeneous Wireless Sensor Networks 异构无线传感器网络中基于距离的响应路由聚类协议设计

2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA) Pub Date : 2018-03-01 DOI: 10.1109/ICECA.2018.8474795

P. Shailaja, A. Karthikeyan

引用次数: 0

A Survey on Maximum Power Point Algorithms for PV System 光伏系统最大功率点算法研究进展

2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA) Pub Date : 2018-03-01 DOI: 10.1109/ICECA.2018.8474644

V. Baghel

引用次数: 0

An Overview of VM Live Migration Strategies and Technologies 虚拟机热迁移策略和技术概述

2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA) Pub Date : 2018-03-01 DOI: 10.1109/ICECA.2018.8474910

Krushi Damania, Shraddha Holmukhe, Videet Singhai, P. Bhavathankar

引用次数: 0

Code Generator for Model- Driven Software Development Using UML Models 使用UML模型的模型驱动软件开发代码生成器

2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA) Pub Date : 2018-03-01 DOI: 10.1109/ICECA.2018.8474690

Molla Kindie Shiferaw, A. Jena

{"title":"Code Generator for Model- Driven Software Development Using UML Models","authors":"Molla Kindie Shiferaw, A. Jena","doi":"10.1109/ICECA.2018.8474690","DOIUrl":"https://doi.org/10.1109/ICECA.2018.8474690","url":null,"abstract":"Models are the most important core of Science, Technology and Designing. Display based ways to deal with software advancement and system building utilize technology to incorporate graphical demonstrating languages. Model driven software development is an approach of using models to automatically create the source code implementation of a software structure. The Model Driven Architecture (MDA) approach has been getting position as the Model Driven Approach of an option since its use of Unified Modeling Language(UML). The MDA solution is to produce all code of a system from models and give attention to maintaining models merely in the software development. But, due to shortage of code production tools and the UML language itself, an accurate MDA does not understand by developers. The critical proposal is to identify system functionality with a Platform Independent Model and next to convert this model into Platform Specific Models and completely generate executable source code from model. Model conversion creates the most important component of MDA approach. Generating models and source code from other models by using MDA technology tools is the key standard of MDA approach. Therefore, manual conversion is an extremely time and other resource consuming work in software development. This paper describes not only generating code from model but also generates model from code or it also describes reverse engineering(Code-Model conversion). Keywords: Model-Driven, Code Generator, Model, Software Development, UML, MDA, platform, Model Transformation.","PeriodicalId":272623,"journal":{"name":"2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA)","volume":"331 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116646379","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

A New Approach for Segmentation and Detection of Brain Tumor in 3D Brain MR Imaging 三维脑磁共振成像中脑肿瘤分割与检测的新方法

2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA) Pub Date : 2018-03-01 DOI: 10.1109/ICECA.2018.8474874

Dr. A. Jagan

{"title":"A New Approach for Segmentation and Detection of Brain Tumor in 3D Brain MR Imaging","authors":"Dr. A. Jagan","doi":"10.1109/ICECA.2018.8474874","DOIUrl":"https://doi.org/10.1109/ICECA.2018.8474874","url":null,"abstract":"Segmentation of brain MR Images plays prime role for measuring and visualizing the brain anatomical structures, analyzing brain tumors, and surgical planning. In the comparable research, outcomes were demonstrated the segmentation and detection of tumor in 2D Brain MR Images by amalgamation of diverse methods and techniques. Conversely, the precise outcomes were not been exhibited in the related researches works for the segmentation and detection of tumor in 3D Brain MR Images. As a result, this proposed work focused on development of an automatic integrated segmentation Frameworkfor detection of tumor in brain 3D MR Images which incorporate the most established improved EM (Expectation Maximization) method and Fuzzy C Means Clustering method. The proposed framework optimally merges the segmentation results of most established method and it exhibits the improvement in brain MR image segmentation. The most popular an anisotropic filter is employed to the improved EM (Expectation Maximization), Fuzzy C Means Clustering Method and Proposed Augmentation Method to improve the quality brain MR image and to produce better segmentation and detection of tumor. The performance results of proposed framework is evaluated on simulated brain Fluid-Attenuated Inversion Recovery MRI images and real brain dataset. The performance results of the proposed research work present superior results than the state-of-the-art methods and the proposed work is quantified with segmentation accuracy, sensitivity and specificity.","PeriodicalId":272623,"journal":{"name":"2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124897000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Discover Cross-Modal Human Behavior Analysis 发现跨模式人类行为分析

2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA) Pub Date : 2018-03-01 DOI: 10.1109/ICECA.2018.8474611

Pravin Tripathi, Pratik P. Watwani, S. Thakur, A. Shaw, S. Sengupta

{"title":"Discover Cross-Modal Human Behavior Analysis","authors":"Pravin Tripathi, Pratik P. Watwani, S. Thakur, A. Shaw, S. Sengupta","doi":"10.1109/ICECA.2018.8474611","DOIUrl":"https://doi.org/10.1109/ICECA.2018.8474611","url":null,"abstract":"Job interviews are a predominant part of any hiring process to evaluate applicants. It is used to evaluate applicant's knowledge, skills, abilities, and behavior in order to select the most suited person for the job. Recruiters make their opinion, on the basis of both verbal and nonverbal communication of an interviewee. Our behavior and communication in daily life are cross-modal in nature. Facial expression, hand gestures and body postures are closely linked to speech and hence enrich the vocal content. Nonverbal communication plays an important role in what we are saying and what we actually mean to say. It carries relevant information that can reveal social construct of a person as diverse as his personality, state of mind, or job interview outcome; they convey information in parallel to our speech. In this paper, we present an automated, predictive expert system framework for the computational analysis of HR Job interviews. The system includes analysis of facial expression, language and prosodic details of the interviewees and thereby quantifies their verbal and nonverbal behavior. The system predicts the rating on the overall performance of the interviewee and on each behavior traits and hence predict their personality and hireability.","PeriodicalId":272623,"journal":{"name":"2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116563931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1