2016 IEEE Region 10 Conference (TENCON)最新文献_第3页

Fuzzy model for predicting electric generation from sea wave energy in Thailand 泰国海浪能发电的模糊预测模型

2016 IEEE Region 10 Conference (TENCON) Pub Date : 2016-11-01 DOI: 10.1109/TENCON.2016.7848518

S. Phaiboon, Khunchai Tanukitwattana

引用次数: 2

Effects of varying fiber length towards packet delay in Passive Optical Network 无源光网络中不同光纤长度对分组时延的影响

2016 IEEE Region 10 Conference (TENCON) Pub Date : 2016-11-01 DOI: 10.1109/TENCON.2016.7848735

N. Radzi, M. A. Ridwan, F. Abdullah, N. M. Din, M. Al-Mansoori, H. Z. Abidin

引用次数: 1

In-orbit results of VELOX-II nanosatellite VELOX-II纳米卫星在轨结果

2016 IEEE Region 10 Conference (TENCON) Pub Date : 2016-11-01 DOI: 10.1109/TENCON.2016.7848740

K. Low, M. Tissera, J. W. Chia

引用次数: 4

Securing vehicular ad-hoc networks from data falsification attacks 保护车载自组织网络免受数据伪造攻击

2016 IEEE Region 10 Conference (TENCON) Pub Date : 2016-11-01 DOI: 10.1109/TENCON.2016.7847967

D. Rawat, B. B. Bista, Gongjun Yan

引用次数: 13

Workspace trajectory tracking control of flexible joint robots based on backstepping method 基于反步法的柔性关节机器人工作空间轨迹跟踪控制

2016 IEEE Region 10 Conference (TENCON) Pub Date : 2016-11-01 DOI: 10.1109/TENCON.2016.7848700

Z. Jiang, Ken Shinohara

引用次数: 13

Pyramid stack data stream mining for handling concept-drifting 处理概念漂移的金字塔堆栈数据流挖掘

2016 IEEE Region 10 Conference (TENCON) Pub Date : 2016-11-01 DOI: 10.1109/TENCON.2016.7847953

Zhuoran Xu, Cuiqin Hou, Yingju Xia, Jun Sun, Hiroya Inakoshi, N. Yugami

引用次数: 0

Joint cyber and physical attacks against topology of electric grids 针对电网拓扑结构的联合网络和物理攻击

2016 IEEE Region 10 Conference (TENCON) Pub Date : 2016-11-01 DOI: 10.1109/TENCON.2016.7848103

Ying Sun, Wen-Tai Li, Wentu Song, C. Yuen

引用次数: 1

A regression model-based approach to fast contingency screening for transient stability 基于回归模型的暂态稳定快速应急筛选方法

2016 IEEE Region 10 Conference (TENCON) Pub Date : 2016-11-01 DOI: 10.1109/TENCON.2016.7848129

M. Chheng, A. Nerves

引用次数: 1

Machine learning algorithm for retinal image analysis 视网膜图像分析的机器学习算法

2016 IEEE Region 10 Conference (TENCON) Pub Date : 2016-11-01 DOI: 10.1109/TENCON.2016.7848208

Santhakumar R, Megha Tandur, E. R. Rajkumar, G. S, Girish Haritz, K. Rajamani

{"title":"Machine learning algorithm for retinal image analysis","authors":"Santhakumar R, Megha Tandur, E. R. Rajkumar, G. S, Girish Haritz, K. Rajamani","doi":"10.1109/TENCON.2016.7848208","DOIUrl":"https://doi.org/10.1109/TENCON.2016.7848208","url":null,"abstract":"Diabetic retinopathy is the most general diabetes complication that affects eyes and results in blindness. It's due to impairment of the arteries a veins located in the fundus of eye (retina) that are composed of light sensitive tissues. The aim of this research work is to design an efficient and sensitive tool for Diabetic Retinopathy using the images acquired from portable fundus camera. The screening tool is based on advanced machine learning and computer vision algorithm which includes patch level prediction. In patch level prediction algorithm will localize the diseased region in the Diabetic Retinopathy image like Hard Exudates and Hemorrhage. The patch level classification uses Support Vector Machine (SVM) machine learning classifier model to predict the potential patch of Hard Exudates and Hemorrhage. In this algorithm, the image is broken into regular rectangular patch. The feature for each patch along with the different class label based on the ground truth is computed and passed to strong classifier SVM. The data sets are split into training dataset and testing dataset. The classifier model is built on training dataset and tested against the test dataset. The performance results of rectangular patch level prediction using SVM the average performance for Hard Exudates was Accuracy 96 %, Sensitivity 94%, Specificity 96%. The average performance for Hemorrhage was Accuracy 85 %, Sensitivity 77%, and Specificity 85%.","PeriodicalId":246458,"journal":{"name":"2016 IEEE Region 10 Conference (TENCON)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123849695","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: 19

Prosodic features of Marathi news reading style 马拉地语新闻阅读风格的韵律特征

2016 IEEE Region 10 Conference (TENCON) Pub Date : 2016-11-01 DOI: 10.1109/TENCON.2016.7848421

Sanket Barhate, S. Kshirsagar, Niramay Sanghvi, Kamini Sabu, P. Rao, N. Bondale

{"title":"Prosodic features of Marathi news reading style","authors":"Sanket Barhate, S. Kshirsagar, Niramay Sanghvi, Kamini Sabu, P. Rao, N. Bondale","doi":"10.1109/TENCON.2016.7848421","DOIUrl":"https://doi.org/10.1109/TENCON.2016.7848421","url":null,"abstract":"Text-to-speech synthesizers present an attractive alternative to reading in hands-free communication scenarios. Speech intelligibility and naturalness are key to the user acceptability of synthesized speech. The accurate modeling of prosody plays an important role in both dimensions. While prosody is language dependent, it is also strongly dependent on the speaking style. In this work, we study the important prosodic features of news reading style in Marathi using publicly available radio broadcasts. Prominence and boundaries are among the important linguistic cues conveyed via a news reader's prosody. Using perception testing, we obtain boundaries and prominent words in broadcast recordings of two female news readers. We measure acoustic parameters known to serve as cues to prominence such as the fundamental frequency, duration and intensity. We also make observations on timing and pitch phenomena at inter- and intra-sentence breaks. Our results indicate that prominence depends strongly on achieved FO span in the word and to a smaller extent on duration increase. Breaks are signaled by pauses and pre-boundary lengthening of the final syllable. We observe that, unlike English, sentence ending in Marathi is not always accompanied by a pitch fall in the final syllable. The implications of these observations on prosody generation are discussed.","PeriodicalId":246458,"journal":{"name":"2016 IEEE Region 10 Conference (TENCON)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121213546","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: 5