2020 National Conference on Emerging Trends on Sustainable Technology and Engineering Applications (NCETSTEA)最新文献_第5页

Climate policy and intelligent transport systems: Application of new transport technologies to reduce greenhouse emissions 气候政策和智能交通系统:应用新的交通技术减少温室气体排放

2020 National Conference on Emerging Trends on Sustainable Technology and Engineering Applications (NCETSTEA) Pub Date : 2020-02-01 DOI: 10.1109/NCETSTEA48365.2020.9119940

M. F. Nejad, N. Haghdadi, A. Bruce, lain MacGill

{"title":"Climate policy and intelligent transport systems: Application of new transport technologies to reduce greenhouse emissions","authors":"M. F. Nejad, N. Haghdadi, A. Bruce, lain MacGill","doi":"10.1109/NCETSTEA48365.2020.9119940","DOIUrl":"https://doi.org/10.1109/NCETSTEA48365.2020.9119940","url":null,"abstract":"CO2 emission has been considered as a key concern in energy and climate policies. Australia's greenhouse gas emissions have been at the highest level in recent years. As about 20% of CO2 emissions coming from transport sections and 68% emission of the transport section is produced in our roads, an urgent solution to this problem is required. The transport industry is moving fast toward being more intelligent and using new technologies such as Connected and Automated Vehicles and intelligent traffic Control Systems on the roads. In this research, the focus will be on the impact of these technologies on transport and effective strategies to reduce the greenhouse gases in Intelligent Transport Systems (ITS). In this paper, relevant recent works have been reviewed and a machine learning method has been applied to forecast traffic congestion. The effect of different ITS technologies has been assessed based on their gradual impact on the congestion each year. The result shows four years traffic forecast model with different annual impact coming from different ITS technologies.","PeriodicalId":267921,"journal":{"name":"2020 National Conference on Emerging Trends on Sustainable Technology and Engineering Applications (NCETSTEA)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127676703","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: 4

Automatic Detection and Segmentation of Optic Disc (ADSO) of Retinal Fundus Images Based on Mathematical Morphology 基于数学形态学的视网膜眼底图像视盘自动检测与分割

2020 National Conference on Emerging Trends on Sustainable Technology and Engineering Applications (NCETSTEA) Pub Date : 2020-02-01 DOI: 10.1109/NCETSTEA48365.2020.9119931

Niladri Halder, Dibyendu Roy, Rajib Banerjee, Pulakesh Roy, P. P. Sarkar, S. Bandyopadhyay

{"title":"Automatic Detection and Segmentation of Optic Disc (ADSO) of Retinal Fundus Images Based on Mathematical Morphology","authors":"Niladri Halder, Dibyendu Roy, Rajib Banerjee, Pulakesh Roy, P. P. Sarkar, S. Bandyopadhyay","doi":"10.1109/NCETSTEA48365.2020.9119931","DOIUrl":"https://doi.org/10.1109/NCETSTEA48365.2020.9119931","url":null,"abstract":"The main objective of medical image processing field is to design computational tools which will assist quantification and visualization of remarkable pathology and anatomical structure. Diabetic retinopathy is a medical disorder where the retina is damaged due to fluids leak from the blood vessels into the retina of human eye. The identification of optic disk in retinal fundus images and quantitative study of the evolution of its shape and size plays an important role in diagnosing different pathologies, and the abnormalities related to the retina of human eye. Most of the abnormalities which are related to optic disc may leads to a structural changes in the inner and the outer area of the optic disc. Optic disc identification and segmentation on the level of the whole retinal image reduces the detection sensitivity for those parts. In this research, an advanced classification based on hierarchical process for the detection and segmentation of optic disc has been proposed. The exact boundary of optic disc is obtained by calculating the region of interest and applying an innovative morphological transformation based adaptive thresholding. The presented technique helps to reduce the process area needed for segmentation techniques leading to a distinguished performance enhancement and reducing the amount of the needed computational cost for each retinal fundus image. The proposed technique has been evaluated on publicly available data sets of retinal images which are DIARETDB1, DRIVE, HRF, DRIONS-DB, IDRiD and STARE, and a remarkable improvement has been found over the existing techniques in terms of accuracy and processing time.","PeriodicalId":267921,"journal":{"name":"2020 National Conference on Emerging Trends on Sustainable Technology and Engineering Applications (NCETSTEA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130942587","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

Reconfigurable Composite Printed Antenna For Cognitive Radio Application 用于认知无线电应用的可重构复合印刷天线

2020 National Conference on Emerging Trends on Sustainable Technology and Engineering Applications (NCETSTEA) Pub Date : 2020-02-01 DOI: 10.1109/NCETSTEA48365.2020.9119933

Sukanya Baruah, Bidisha Dasgupta

引用次数: 1

Alzheimer’s Disease Detection using Machine Learning Techniques in 3D MR Images 在3D MR图像中使用机器学习技术检测阿尔茨海默病

2020 National Conference on Emerging Trends on Sustainable Technology and Engineering Applications (NCETSTEA) Pub Date : 2020-02-01 DOI: 10.1109/NCETSTEA48365.2020.9119923

Srinivasan Aruchamy, Amrita Haridasan, Ankit Verma, P. Bhattacharjee, S. Nandy, Siva Ram Krishna Vadali

{"title":"Alzheimer’s Disease Detection using Machine Learning Techniques in 3D MR Images","authors":"Srinivasan Aruchamy, Amrita Haridasan, Ankit Verma, P. Bhattacharjee, S. Nandy, Siva Ram Krishna Vadali","doi":"10.1109/NCETSTEA48365.2020.9119923","DOIUrl":"https://doi.org/10.1109/NCETSTEA48365.2020.9119923","url":null,"abstract":"This study proposes a new method for the detection of Alzheimer’s Disease (AD) using first-order statistical features in 3D brain Magnetic Resonance(MR) images. Alzheimer’s disease is a neurodegenerative disorder that affects elderly people. This is a progressive disease and early detection and classification of AD can majorly help in controlling the disease. Recent studies use voxel-based brain MR image feature extraction techniques along with machine learning algorithms for this purpose. Grey and white matter of the brain gets affected and damaged due to AD and so studying these both prove to be more effective in predicting the disease. The proposed work uses 3D structural brain MR images to separate the white and grey matter MR images, extract 2D slices in the coronal, sagittal and axial directions and select the key slices from them for performing feature extraction on them. Feature extraction is applied on top of these slices to calculate the first-order statistical features and the prominent feature vectors generated by PCA are selected for further study. In the classification phase, different classifiers take the selected features as its input to predict the classes AD (Alzheimer’s Disease) or HC (Healthy Control) based on the observations in the validation set. Experimental results show that the accuracy of 90.9 % compared to other techniques.","PeriodicalId":267921,"journal":{"name":"2020 National Conference on Emerging Trends on Sustainable Technology and Engineering Applications (NCETSTEA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129296316","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

On Effective Placement of Acoustic Emission Sensor in Steel Framed Structure for Damage Detection 声发射传感器在钢架结构损伤检测中的有效放置研究

2020 National Conference on Emerging Trends on Sustainable Technology and Engineering Applications (NCETSTEA) Pub Date : 2020-02-01 DOI: 10.1109/NCETSTEA48365.2020.9119915

A. K. Biswas, Aloke Kumar Datta, P. Topdar, S. Sengupta

引用次数: 1

Parameter Estimation for three core Underground Cable 三芯地下电缆参数估计

2020 National Conference on Emerging Trends on Sustainable Technology and Engineering Applications (NCETSTEA) Pub Date : 2020-02-01 DOI: 10.1109/NCETSTEA48365.2020.9119913

Suman Khandual, Sanhita Mishra, Suchismita Roy, C. Jena, Anand

引用次数: 0

Slotted Microstrip Antenna For Miniaturization 用于小型化的开槽微带天线

2020 National Conference on Emerging Trends on Sustainable Technology and Engineering Applications (NCETSTEA) Pub Date : 2020-02-01 DOI: 10.1109/NCETSTEA48365.2020.9119935

C. Ghosh, A. Sarkar, Swati Bhattacharjee, Sarada Tewary, Rimi Chatterji, Keya Pal, Mrinmoy Chakraborty

引用次数: 2