2018 IEEE 38th International Conference on Electronics and Nanotechnology (ELNANO)最新文献_第2页

Study of Parametric Transducer Operation in Pulsed Eddy Current Non-Destructive Testing 脉冲涡流无损检测中参数传感器工作的研究

2018 IEEE 38th International Conference on Electronics and Nanotechnology (ELNANO) Pub Date : 2018-04-24 DOI: 10.1109/ELNANO.2018.8477572

Y. Kuts, S. Maievskyi, A. Protasov, I. Lysenko, O. Dugin

{"title":"Study of Parametric Transducer Operation in Pulsed Eddy Current Non-Destructive Testing","authors":"Y. Kuts, S. Maievskyi, A. Protasov, I. Lysenko, O. Dugin","doi":"10.1109/ELNANO.2018.8477572","DOIUrl":"https://doi.org/10.1109/ELNANO.2018.8477572","url":null,"abstract":"In this article is considered the experimental results of the using the parametric type of an eddy current transducer at two excitation modes - pulsed and harmonic. The flat samples from aluminum alloy and steel with artificial crack-like defects on them were selected as testing objects. The estimation of the amplitude, decrement and natural oscillation frequency of the eddy current transducer signal as informative parameters was performed according to the results of the analysis of experimental signals of the parametric transducer. The results of the comparative analysis of the eddy current transducer signals at harmonic and pulsed excitation are presented by estimating of changes in the signals amplitude values from the crack depth in the testing object. It is shown that the signals of parametric eddy current transducer in the form of damped harmonic oscillations obtained by pulse excitation of the transducer can be used in the eddy current non-destructive testing to estimate the depth of surface cracks. The types of the dependences of the attenuation and the natural oscillation frequency of the eddy current transducer signal from the change in the crack depth in the testing object were established using the experimental data. The analysis of the sensitivities of the informational parameters of the eddy current transducer at pulsed excitation to the crack depth in the testing objects is performed.","PeriodicalId":269665,"journal":{"name":"2018 IEEE 38th International Conference on Electronics and Nanotechnology (ELNANO)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116738094","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

Ultracapacitors Electrobus for Urban Transport 城市交通用超级电容器电动客车

2018 IEEE 38th International Conference on Electronics and Nanotechnology (ELNANO) Pub Date : 2018-04-24 DOI: 10.1109/ELNANO.2018.8477449

A. Hnatov, S. Arhun, O. Ulyanets, S. Ponikarovska

引用次数: 8

Transient Analysis of Electronic Circuits Using Periodic Steady-State Analysis Technique 基于周期稳态分析技术的电子电路暂态分析

2018 IEEE 38th International Conference on Electronics and Nanotechnology (ELNANO) Pub Date : 2018-04-24 DOI: 10.1109/ELNANO.2018.8477503

A. Moskovko, O. Vityaz

引用次数: 4

Analysis of Influence of the Design of the Discharge Chamber on the Ozone Generator Parameters 放电室设计对臭氧发生器参数的影响分析

2018 IEEE 38th International Conference on Electronics and Nanotechnology (ELNANO) Pub Date : 2018-04-24 DOI: 10.1109/ELNANO.2018.8477441

Y. Sokol, V. Kulichenko, R. Tomashevskyi, M. Makhonin

引用次数: 1

Reconstruction of the Gene Regulatory Network by Hybrid Algorithm of Clonal Selection and Trigonometric Differential Evolution 克隆选择与三角差分进化混合算法重建基因调控网络

2018 IEEE 38th International Conference on Electronics and Nanotechnology (ELNANO) Pub Date : 2018-04-24 DOI: 10.1109/ELNANO.2018.8477436

A. Fefelov, V. Lytvynenko, M. Voronenko, S. Babichev, V. Osypenko

引用次数: 4

GaAs Junctionless FinFET Using High-k Dielectric for High-Performance Applications 用于高性能应用的高k介电的GaAs无结FinFET

2018 IEEE 38th International Conference on Electronics and Nanotechnology (ELNANO) Pub Date : 2018-04-24 DOI: 10.1109/ELNANO.2018.8477506

Ajay Kumar, Anuj Chhabra, R. Chaujar

引用次数: 4

Efficient Geometry of Surface Plasmon Resonance Based Fiber Optic Sensor 基于表面等离子体共振的光纤传感器的高效几何结构

2018 IEEE 38th International Conference on Electronics and Nanotechnology (ELNANO) Pub Date : 2018-04-24 DOI: 10.1109/ELNANO.2018.8477444

Mitra Abedini, Mohsen Ahmadi, R. Mohammadpour, P. Sasanpour

{"title":"Efficient Geometry of Surface Plasmon Resonance Based Fiber Optic Sensor","authors":"Mitra Abedini, Mohsen Ahmadi, R. Mohammadpour, P. Sasanpour","doi":"10.1109/ELNANO.2018.8477444","DOIUrl":"https://doi.org/10.1109/ELNANO.2018.8477444","url":null,"abstract":"The efficient structure for optical fiber based surface Plasmon resonance sensor has been investigated. The sensor structure is based on removing the cladding of a multimode optical fiber and replacing it with thin film of gold. The incident light inside the fiber will excite surface plasmons which will be resulted in the absorption in specific wavelengths. The absorption behavior is dependent on the dielectric constants at the vicinity of the metallic thin film. Based on the amount of removed cladding and deposition regions on the core structure of the fiber, different configurations can be considered. Based on the computational analysis, we have studied performance of sensor for three different configurations. Our method of study is based on solving wave equation in different sensor geometry and calculating absorption for different available modes using Finite Element Method in COMSOL environment. The results of our study show that, the optimum configuration of sensor considering wavelength sensitivity is for a fiber which half of core and cladding has been removed and the gold thin film is deposited on its surface.","PeriodicalId":269665,"journal":{"name":"2018 IEEE 38th International Conference on Electronics and Nanotechnology (ELNANO)","volume":"133 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132751476","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

Multi-Voltage and Multi-Threshold Low Power Design Techniques for ORCA Processor Based on 14 nm Technology 基于14nm工艺的ORCA处理器多电压多阈值低功耗设计技术

2018 IEEE 38th International Conference on Electronics and Nanotechnology (ELNANO) Pub Date : 2018-04-24 DOI: 10.1109/ELNANO.2018.8477510

Vazgen Melikyan, Meruzhan K. Martirosyan, D. Babayan, V. Janpoladov, Davit Musayelyan

引用次数: 5

Deep Learning Crop Classification Approach Based on Coding Input Satellite Data Into the Unified Hyperspace 基于输入卫星数据编码到统一超空间的深度学习作物分类方法

2018 IEEE 38th International Conference on Electronics and Nanotechnology (ELNANO) Pub Date : 2018-04-24 DOI: 10.1109/ELNANO.2018.8477525

M. Lavreniuk, N. Kussul, A. Novikov

{"title":"Deep Learning Crop Classification Approach Based on Coding Input Satellite Data Into the Unified Hyperspace","authors":"M. Lavreniuk, N. Kussul, A. Novikov","doi":"10.1109/ELNANO.2018.8477525","DOIUrl":"https://doi.org/10.1109/ELNANO.2018.8477525","url":null,"abstract":"To provide reliable crop maps for the same territory each year, it is necessary to collect in-situ data for each year independently. Collecting ground truth data is a very time consuming and challenging task. At present, unfortunately, there is no an adopted approach, how to utilize in-situ and satellite data from previous years for crop mapping in the subsequent years. In this paper, we propose a new deep learning approach using sparse autoencoder based on only satellite data, and a further procedure of neural network fine-tuning based on in-situ data. The possibility of utilizing this deep learning architecture based on translating all available satellite data into the unified hyperspace. The study is carried out for the central part of Ukraine. Obtained results show that this technique is feasible and provides reliable crop classification maps with overall accuracy (OA) of 91.0% and 85.9% for two different experiments. The use of the proposed approach makes it possible to avoid, or decrease, the necessity for collecting in-situ data for each year and for each part of large territory.","PeriodicalId":269665,"journal":{"name":"2018 IEEE 38th International Conference on Electronics and Nanotechnology (ELNANO)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125580704","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

High Dynamic Range Video Camera with Elements of the Pattern Recognition 具有模式识别元素的高动态范围摄像机

2018 IEEE 38th International Conference on Electronics and Nanotechnology (ELNANO) Pub Date : 2018-04-24 DOI: 10.1109/ELNANO.2018.8477556

A. Sergiyenko, P. Serhiienko, Juriy Zorin

引用次数: 3