2016 IEEE Region 10 Conference (TENCON)最新文献

2016 IEEE Region 10 Conference (TENCON) Pub Date : 2016-11-24 DOI: 10.1109/TENCON.2016.7848435

A. Kouzani, S. Adams, Russell Oliver, Y. Nguwi, B. Hemsley, S. Balandin

引用次数: 11

Automatic image classification in intravascular optical coherence tomography images 血管内光学相干断层成像的自动图像分类

2016 IEEE Region 10 Conference (TENCON) Pub Date : 2016-11-22 DOI: 10.1109/TENCON.2016.7848275

Mengdi Xu, Jun Cheng, D. Wong, A. Taruya, A. Tanaka, Jiang Liu, N. Foin, P. Wong

{"title":"Automatic image classification in intravascular optical coherence tomography images","authors":"Mengdi Xu, Jun Cheng, D. Wong, A. Taruya, A. Tanaka, Jiang Liu, N. Foin, P. Wong","doi":"10.1109/TENCON.2016.7848275","DOIUrl":"https://doi.org/10.1109/TENCON.2016.7848275","url":null,"abstract":"Vulnerable plaque detection to identify plaque is important in coronary heart disease diagnosis. Currently, it is conducted through manual reading of intravascular optical coherence tomography (IVOCT) images by an interventional cardiologist. However, human reading and understanding is highly subjective. An objective and automated assessment of plaque status is highly needed. This paper proposes a method for automatic image classification in IVOCT images based on different lesion types. In the proposed method, we first use detail-preserving anisotropic diffusion to remove speckle noise in IVOCT images. It removes the noise without losing details. Then, the IVOCT images are transformed to polar coordinates for feature extraction. In particular, Fisher vector and other texture features including local binary pattern and histogram of oriented gradients are studied. Finally, a support vector machine classifier is obtained to classify the IVOCT images into five groups: Normal (normal), FP (fibrous plaque), FA (fibroatheroma), PR (plaque rupture), and FC (fibrocalcific plaque). These five groups are obtained according to lesion characteristics. We evaluate the proposed method in a dataset of 1,000 images with five groups. Experimental results show that the proposed method achieves an average accuracy of 90% in image classification. The proposed automatic IVOCT image classification method can be used to save time and cost of cardiologist.","PeriodicalId":246458,"journal":{"name":"2016 IEEE Region 10 Conference (TENCON)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129689316","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: 8

GaN based μLED drive circuit for Visible Light Communication (VLC) with improved linearity using on-chip optical feedback 基于GaN的μLED可见光通信(VLC)驱动电路，利用片上光反馈改善线性度

2016 IEEE Region 10 Conference (TENCON) Pub Date : 2016-11-22 DOI: 10.1109/TENCON.2016.7848683

A. Zuhdi, J. McKendry, R. Henderson, E. Gu, M. Dawson, I. Underwood

引用次数: 2

Application of hybrid artificial neural network algorithm for the prediction of standardized precipitation index 混合人工神经网络算法在标准化降水指数预测中的应用

2016 IEEE Region 10 Conference (TENCON) Pub Date : 2016-11-22 DOI: 10.1109/TENCON.2016.7848588

Kavina S. Dayal, R. Deo, A. Apan

引用次数: 7

Coil design guidelines for high efficiency of wireless power transfer (WPT) 高效无线电力传输(WPT)线圈设计指南

2016 IEEE Region 10 Conference (TENCON) Pub Date : 2016-11-01 DOI: 10.1109/TENCON.2016.7848098

J. Sampath, A. Alphones, H. Shimasaki

引用次数: 40

Performance analysis of media-based cache via analytical and simulation model 通过分析和仿真模型对基于介质的高速缓存进行性能分析

2016 IEEE Region 10 Conference (TENCON) Pub Date : 2016-11-01 DOI: 10.1109/TENCON.2016.7848206

Mingzhou Xie, Jun Xu, Li Xia

引用次数: 2

A real-time Health Monitoring and warning system for bridge structures 桥梁结构实时健康监测预警系统

2016 IEEE Region 10 Conference (TENCON) Pub Date : 2016-11-01 DOI: 10.1109/TENCON.2016.7848598

I. Khemapech, Watsawee Sansrimahachai, Manachai Toahchoodee

{"title":"A real-time Health Monitoring and warning system for bridge structures","authors":"I. Khemapech, Watsawee Sansrimahachai, Manachai Toahchoodee","doi":"10.1109/TENCON.2016.7848598","DOIUrl":"https://doi.org/10.1109/TENCON.2016.7848598","url":null,"abstract":"Engineering structure has been regarded as one of the physical aspects of societal and civil development and evolution. It also impacts life quality and safety of the civilian. Despite of its own weight (dead load) and live load, structural members are also significantly affected by disaster and environment. Proper inspection and detection are thus crucial both during regular and unsafe events. An Enhanced Structural Health Monitoring System Using Stream Processing and Artificial Neural Network Techniques (SPANNeT) has been developed and is described in this paper. SPANNeT applies wireless sensor network, real-time data stream processing and artificial neural network based upon the measured bending strain. Major contributions include an effective, accurate and energy-aware data communication and damage detection of the engineering structure. SPANNeT has been tested and evaluated by means of computer-based simulation, test-bed and on-site levels. According to the measurements, the observed maximum values are 25 to 30 microstrains during normal operation. The given protocol provides at least 90% of data communication reliability. SPANNeT is capable of real-time data report, monitoring and warning efficiently conforming to the predefined thresholds which can be adjusted regarding user's requirements and structural engineering characteristics.","PeriodicalId":246458,"journal":{"name":"2016 IEEE Region 10 Conference (TENCON)","volume":"35 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":"115767737","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: 13

Energy harvesting aware protocol for 802.11-based Internet of Things network 基于802.11的物联网网络能量收集感知协议

2016 IEEE Region 10 Conference (TENCON) Pub Date : 2016-11-01 DOI: 10.1109/TENCON.2016.7848228

Lukman Rosyidi, R. F. Sari

引用次数: 5

Simplified design method of a filtered Smith predictor for unstable and integrative plants with dead-time 不稳定综合植物死期滤波Smith预测器的简化设计方法

2016 IEEE Region 10 Conference (TENCON) Pub Date : 2016-11-01 DOI: 10.1109/TENCON.2016.7848685

Ryoichiro Haruyama, R. Tanaka, Y. Ishida

引用次数: 1

Hidden Markov Model based human activity recognition using shape and optical flow based features 基于形状和光流特征的隐马尔可夫模型人类活动识别

2016 IEEE Region 10 Conference (TENCON) Pub Date : 2016-11-01 DOI: 10.1109/TENCON.2016.7848028

M. Kolekar, D. Dash

引用次数: 46