2018 IEEE International Conference on Electro/Information Technology (EIT)最新文献_第3页

A New Method for the Segmentation of Algae Images Using Non-Uniform Background Improvement and Support Vector Machine 基于非均匀背景改进和支持向量机的藻类图像分割新方法

2018 IEEE International Conference on Electro/Information Technology (EIT) Pub Date : 2018-05-03 DOI: 10.1109/EIT.2018.8500095

Kyle Dannemiller, E. Salari

引用次数: 4

GPU-Based Parallel Implementation of K-Means Clustering Algorithm for Image Segmentation 基于gpu的图像分割k均值聚类算法并行实现

2018 IEEE International Conference on Electro/Information Technology (EIT) Pub Date : 2018-05-03 DOI: 10.1109/EIT.2018.8500282

Shruti Karbhari, Shadi G. Alawneh

引用次数: 7

A Non-Isolated High Gain Switched-Inductor Switched-Capacitor Step-Up Converter for Renewable Energy Applications 用于可再生能源应用的非隔离高增益开关电感开关电容升压变换器

2018 IEEE International Conference on Electro/Information Technology (EIT) Pub Date : 2018-05-03 DOI: 10.1109/EIT.2018.8500142

Y. Almalaq, A. Alateeq, M. Matin

{"title":"A Non-Isolated High Gain Switched-Inductor Switched-Capacitor Step-Up Converter for Renewable Energy Applications","authors":"Y. Almalaq, A. Alateeq, M. Matin","doi":"10.1109/EIT.2018.8500142","DOIUrl":"https://doi.org/10.1109/EIT.2018.8500142","url":null,"abstract":"This paper presents a novel of a transformerless step-up DC-DC converter based on a switched-inductor (SL) and switched-capacitor (SC) techniques. The main advantage of the proposed SLSC step-up converter is the ability to achieve very high voltage gain (>20) with reasonable voltage stress across the semiconductor switches. The presented paper shows a detailed analysis of the proposed SLSC step-up converter and a comparison considering other published step-up converter topologies. Theoretically, the proposed SLSC step-up converter can boost the input voltage to 23.5 times when $mathbf{D}=0.75$, which D means the duty cycle of the MOSFET. Such a large voltage gain can be used in renewable energy applications such as photovoltaic application to boost the output voltage which the output voltage is low. The proposed converter is analyzed in continuous conduction mode (CCM). The proposed converter has been designed for 12V input voltage, 280V output voltage, 200W rated power, 50kHz switching frequency, and 75% duty cycle. The proposed converter has been simulated in MATLAB/SIMULINK.","PeriodicalId":188414,"journal":{"name":"2018 IEEE International Conference on Electro/Information Technology (EIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129256637","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

Sentiment Analysis Based Fuzzy Decision Platform for the Saudi Stock Market 基于情绪分析的沙特股市模糊决策平台

2018 IEEE International Conference on Electro/Information Technology (EIT) Pub Date : 2018-05-03 DOI: 10.1109/EIT.2018.8500292

Hasan A. Alshahrani, A. Fong

引用次数: 9

SMOTE Implementation on Phishing Data to Enhance Cybersecurity 网络钓鱼数据的SMOTE实施以加强网络安全

2018 IEEE International Conference on Electro/Information Technology (EIT) Pub Date : 2018-05-03 DOI: 10.1109/EIT.2018.8500086

M. Ahsan, Rahul Gomes, A. Denton

引用次数: 28

A Custom Computer-Controlled Fluid Mixing and Dispensing System for Sweat Sensor Testing Applications 定制计算机控制的液体混合和分配系统，用于汗液传感器测试应用

2018 IEEE International Conference on Electro/Information Technology (EIT) Pub Date : 2018-05-03 DOI: 10.1109/EIT.2018.8500209

Andrew Brueck, Kyle Bates, Trent Wood, W. House, Zackary Martinez, Shannon Peters, B. Root, K. Yelamarthi, T. Kaya

引用次数: 0

An Extended Method of Multiple-Camera Calibration for 3D Vehicle Tracking at Intersections 一种面向交叉口车辆三维跟踪的多摄像头标定扩展方法

2018 IEEE International Conference on Electro/Information Technology (EIT) Pub Date : 2018-05-03 DOI: 10.1109/EIT.2018.8500130

Sukriti Subedi, Hua Tang

引用次数: 2

Automatic Tumor Segmentation Using Machine Learning Classifiers 使用机器学习分类器的自动肿瘤分割

2018 IEEE International Conference on Electro/Information Technology (EIT) Pub Date : 2018-05-03 DOI: 10.1109/EIT.2018.8500205

U. Shrestha, E. Salari

{"title":"Automatic Tumor Segmentation Using Machine Learning Classifiers","authors":"U. Shrestha, E. Salari","doi":"10.1109/EIT.2018.8500205","DOIUrl":"https://doi.org/10.1109/EIT.2018.8500205","url":null,"abstract":"Segmentation of liver and tumor from abdominal Computed Tomography (CT) is important for proper planning and treatment of liver disease. Variable size, intensity overlap, and complexity of CT images probe a problem for a radiologist. These issues make accurate and reliable delineation of liver and tumor very difficult and time-consuming. So, an automatic method is desired and beneficial. In this paper, we propose a fully automatic method to segment both liver and tumor using an array of Gabor Filter (Gabor Bank(GB)) and Machine Learning (ML) classifiers: Random Forest (RF) and Deep Neural Network (DNN). First, GB extract pixel level Gabor features from CT images. Secondly, the liver is segmented using ML classifiers trained on Gabor features. Finally, tumor segmentation is done on the segmented liver image using the same approach as in liver segmentation. 31 CT image slices containing hepatic tumors from 3D-IRCADb (3D Image Reconstruction for Comparison of Algorithm Database) were used to validate our proposed method. For liver segmentation, the experimental result showed that the proposed method with RF classifier performed better than DNN, and can achieve high performance of 99.55% accuracy and 99.03% dice similarity coefficient. Also, for tumor segmentation, a similar conclusion was drawn.","PeriodicalId":188414,"journal":{"name":"2018 IEEE International Conference on Electro/Information Technology (EIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131252875","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: 2

Performance Evaluation of State Estimators for Airborne Target Tracking Using Multi Sensor Data Fusion 基于多传感器数据融合的机载目标跟踪状态估计器性能评估

2018 IEEE International Conference on Electro/Information Technology (EIT) Pub Date : 2018-05-03 DOI: 10.1109/EIT.2018.8500078

David S. R. Kondru, M. Celenk

{"title":"Performance Evaluation of State Estimators for Airborne Target Tracking Using Multi Sensor Data Fusion","authors":"David S. R. Kondru, M. Celenk","doi":"10.1109/EIT.2018.8500078","DOIUrl":"https://doi.org/10.1109/EIT.2018.8500078","url":null,"abstract":"The main function of range sensory systems under a given dynamic environment is to detect, discriminate and track a particular target for surveillance in case of a friendly target or an enemy target interception. The combination of two or more sensors will provide better position estimate than a single sensor. In this paper, the advantages of the multi sensor data fusion is presented and compared over conventional single sensor tracking. The state estimation techniques are utilized to enhance position accuracy in a single and multi-sensor environment. The performance of each state estimator is evaluated by considering different target motions along with their nonlinear characteristics. The state estimators presented here varies from simple linear filters such as fixed gain and Kalman filters to complex nonlinear filters such as Particle filter. Two widely used Extended Kalman filter based fusion architectures such as measurement fusion and state vector fusion are explored. The data is simulated from two ground based sensors RADAR and FLIR (forward looking infra red) to examine the fusion process. The RMS error is computed in range, azimuth, and elevation angles. A complete mathematical modeling and simulation is implemented in MATLAB. It is found that fusion architectures have demonstrated better performance in tracking accuracy.","PeriodicalId":188414,"journal":{"name":"2018 IEEE International Conference on Electro/Information Technology (EIT)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132796789","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: 0

Building an Exoskeleton Glove on Virtual Reality Platform 在虚拟现实平台上构建外骨骼手套

2018 IEEE International Conference on Electro/Information Technology (EIT) Pub Date : 2018-05-03 DOI: 10.1109/EIT.2018.8500085

Quazi Irfan, Calvin Jensen, Z. Ni, S. Hietpas

引用次数: 1