2017 International Artificial Intelligence and Data Processing Symposium (IDAP)最新文献_第6页

Overcurrent relay coordination of 154/34,5 kV Hasançelebi substation by league championship algorithm 基于联赛冠军算法的154/34,5 kV hasanelebi变电站过流继电器协调

2017 International Artificial Intelligence and Data Processing Symposium (IDAP) Pub Date : 2017-09-01 DOI: 10.1109/IDAP.2017.8090260

Abubekir Seyyarer, Ozan Akdağ, Cengiz Hark, A. Karcı, C. Yeroğlu

引用次数: 1

Spiking neural network applications 尖峰神经网络的应用

2017 International Artificial Intelligence and Data Processing Symposium (IDAP) Pub Date : 2017-09-01 DOI: 10.1109/IDAP.2017.8090266

Gaffari Çelik, M. F. Talu

引用次数: 1

Tasarsiz ağlarda yönlendirme protokollerinin başarimlarinin değerlendirilmesi

2017 International Artificial Intelligence and Data Processing Symposium (IDAP) Pub Date : 2017-09-01 DOI: 10.1109/IDAP.2017.8090207

Fahad Ahmed, Serkan Öztürk

引用次数: 0

Automated recognition of epilepsy from EEG signals 从脑电图信号自动识别癫痫

2017 International Artificial Intelligence and Data Processing Symposium (IDAP) Pub Date : 2017-09-01 DOI: 10.1109/IDAP.2017.8090254

M. Yildirim, Abdulnasir Yildiz

{"title":"Automated recognition of epilepsy from EEG signals","authors":"M. Yildirim, Abdulnasir Yildiz","doi":"10.1109/IDAP.2017.8090254","DOIUrl":"https://doi.org/10.1109/IDAP.2017.8090254","url":null,"abstract":"In this study, it is aimed to design an automatic pattern recognition system for the detection of epilepsy which distinguishes healthy and seizure electroencephalography (EEG) signals. During the study, 100 EEG signals from patients were used during the opened eyes and healthy epileptic seizures. Each EEG signal consisting of 4096 samples was divided into 256 samples and a total of 3200 signals were obtained. The designed pattern recognition system has been developed in 3 basic parts. In the first part, the power spectral density (PSD) estimation is performed with the periodogram and Welch methods and the frequency domain information of the EEG signals is obtained. In the second part, the feature vectors are found from the frequency domain information obtained in the periodogram and Welch PSD estimation. In the third part, healthy EEG signals from the eigenvectors obtained by using K-Nearest Neighbor Algorithm (K-NN) and Support Vector Machine (SVM) classifiers are distinguished from pathological EEG signals. 5-fold cross-validation method was used in evaluating the accuracy performance of the designed system. The total classification accuracy of the system was found to be 99.66% with K-NN, 99.72% with SVM for periodogram PSD estimation and 99.72% with K-NN, 99.75% with SVM for Welch PSD estimation. The results of the pattern recognition system designed in the study are promising because they are close to the work done with different approaches in the literature. The pattern recognition system designed here is not a diagnostic tool. It is foreseen that physicians may be useful in evaluating preliminary diagnosis.","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121175640","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

Performance evaluation of electrical transmission line detection and tracking algorithms based on image processing using UAV 基于无人机图像处理的输电线路检测与跟踪算法性能评价

2017 International Artificial Intelligence and Data Processing Symposium (IDAP) Pub Date : 2017-09-01 DOI: 10.1109/IDAP.2017.8090302

E. Karakose

{"title":"Performance evaluation of electrical transmission line detection and tracking algorithms based on image processing using UAV","authors":"E. Karakose","doi":"10.1109/IDAP.2017.8090302","DOIUrl":"https://doi.org/10.1109/IDAP.2017.8090302","url":null,"abstract":"Regular control of the electrical transmission lines is important in preventing unwanted accidents and power interruptions. It is very difficult to carry out this process involving the determination of the transmission line, the tower and the plants surrounding the transmission line with human power. Today, there are some studies that use unmanned aerial vehicles to control transmission lines. In this study, the performance evaluation of the algorithms required for monitoring and controlling the transmission lines with image processing is given by using unmanned aerial vehicles. For this, firstly the capabilities of the studies in the literature have been put forward and then inferences have been made on how to overcome the shortcomings of these studies. In addition, some application results on experimental images, necessary hardware architecture and algorithm structure to make line control healthy and highly accurate are given in detail. In particular, the examination of the required stability and control methods performances for the line control realization will contribute to the works in this area.","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126644440","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

A new rail inspection method based on deep learning using laser cameras 基于激光相机深度学习的钢轨检测新方法

2017 International Artificial Intelligence and Data Processing Symposium (IDAP) Pub Date : 2017-09-01 DOI: 10.1109/IDAP.2017.8090245

Yunus Santur, Mehmet Karaköse, E. Akin

{"title":"A new rail inspection method based on deep learning using laser cameras","authors":"Yunus Santur, Mehmet Karaköse, E. Akin","doi":"10.1109/IDAP.2017.8090245","DOIUrl":"https://doi.org/10.1109/IDAP.2017.8090245","url":null,"abstract":"Rail systems are one of the most important transportation methods used in today's world. The abnormalities that occur on railway tracks due to various causes result in breakdowns and accidents. For this reason, railway tracks must be periodically inspected. This study proposes a new approach for rail inspection. Today, the railway inspection process is generally performed using computer vision. But the oil and dust residues occurring on railway surfaces can be detected as an false-positive by the image processing software can lead to loss of time and additional costs in the railway maintenance process. In this study, a hardware and software architecture are presented to perform railway surface inspection using 3D laser camera and deep learning. The use of 3D laser cameras in railway inspection process provides high accuracy rates in real time. The reading rate of laser cameras to read up to 25.000 profiles per second is another important advantage provided in real time railway inspection. Consequently, a computer vision-based approach in which 3D laser cameras that could allow for contact-free and fast detection of the railway surface and lateral defects such as fracture, scouring and wear with high accuracy are used in the railway inspection process was proposed in the study.","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125679770","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: 46

RMTE: Robust modular traffic engineering in software-defined data center networks RMTE:软件定义数据中心网络中健壮的模块化流量工程

2017 International Artificial Intelligence and Data Processing Symposium (IDAP) Pub Date : 2017-09-01 DOI: 10.1109/IDAP.2017.8090216

Emad Soltani Nejad, M. Majma

引用次数: 0

Haber metinlerinin farkli metin madenciliği yöntemleriyle siniflandirilmasi

2017 International Artificial Intelligence and Data Processing Symposium (IDAP) Pub Date : 2017-09-01 DOI: 10.1109/IDAP.2017.8090310

F. Başkaya, Ilhan Aydin

引用次数: 1

Yapay sinir aği ve uydu datalari kullanilarak güneş radyasyonunun tahmini

2017 International Artificial Intelligence and Data Processing Symposium (IDAP) Pub Date : 2017-09-01 DOI: 10.1109/IDAP.2017.8090288

Fatma Kuncan, M. Şahin

引用次数: 0

A preliminary investigation of receiver models in molecular communication via diffusion 分子扩散通信中接收器模型的初步研究

2017 International Artificial Intelligence and Data Processing Symposium (IDAP) Pub Date : 2017-09-01 DOI: 10.1109/IDAP.2017.8090303

Ibrahim Isik, Huseyin Birkan Yilmaz, M. Tagluk

引用次数: 3