Pub Date : 2017-09-01DOI: 10.1109/IDAP.2017.8090342
Özcan Çataltas, Kemal Tütüncü
The incredible progress of technology has made the use of communication and information technologies indispensable because of the possibilities it offers. These possibilities increased the security issues on personal information and communication security problems such as phone calls, retrieving e-mail contents, copying private information on computers. Encryption algorithms used in classical security approaches, while ensuring the confidentiality of information, cannot provide the principle of “imprecision” that has become increasingly important in recent times. A coded or encrypted text can be solved by advanced machines when focused on it. So the key point is “do not raise suspicion”. For this reason, steganography and watermarking methods that put the invisibility of the existence of a secret message into the primary goal are especially the focus of interest after 2000's years. In this study, Least Significant Bit (LSB) technique, which is the most basic and commonly used technique in steganography, was applied to 3 different images in different color spaces. When the obtained results were compared according to the image quality evaluation criteria, it has been seen that the images in Hue-Saturation-Intensity (HSI) color spaces had better performances and successes to the other color spaces.
{"title":"Comparison of LSB image steganography technique in different color spaces","authors":"Özcan Çataltas, Kemal Tütüncü","doi":"10.1109/IDAP.2017.8090342","DOIUrl":"https://doi.org/10.1109/IDAP.2017.8090342","url":null,"abstract":"The incredible progress of technology has made the use of communication and information technologies indispensable because of the possibilities it offers. These possibilities increased the security issues on personal information and communication security problems such as phone calls, retrieving e-mail contents, copying private information on computers. Encryption algorithms used in classical security approaches, while ensuring the confidentiality of information, cannot provide the principle of “imprecision” that has become increasingly important in recent times. A coded or encrypted text can be solved by advanced machines when focused on it. So the key point is “do not raise suspicion”. For this reason, steganography and watermarking methods that put the invisibility of the existence of a secret message into the primary goal are especially the focus of interest after 2000's years. In this study, Least Significant Bit (LSB) technique, which is the most basic and commonly used technique in steganography, was applied to 3 different images in different color spaces. When the obtained results were compared according to the image quality evaluation criteria, it has been seen that the images in Hue-Saturation-Intensity (HSI) color spaces had better performances and successes to the other color spaces.","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"31 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":"115267620","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}
Pub Date : 2017-09-01DOI: 10.1109/IDAP.2017.8090173
Erhan Bülbül Ösym, Türkiye Ankara, Aydın Çetin
This work examines the effects of reducing the number of nodes and edges in a grid-graph, which consists of heterogeneous node blocks. An optimization method that reduces the count of nodes and edges is presented. Approaches that make traversing the graph easier by using this method are explained with examples. Efficiency of the method is observed using different pathfinding algorithms.
{"title":"Optimization of Grid-Graphs using Segmentation","authors":"Erhan Bülbül Ösym, Türkiye Ankara, Aydın Çetin","doi":"10.1109/IDAP.2017.8090173","DOIUrl":"https://doi.org/10.1109/IDAP.2017.8090173","url":null,"abstract":"This work examines the effects of reducing the number of nodes and edges in a grid-graph, which consists of heterogeneous node blocks. An optimization method that reduces the count of nodes and edges is presented. Approaches that make traversing the graph easier by using this method are explained with examples. Efficiency of the method is observed using different pathfinding algorithms.","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"1 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":"115545079","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}
Pub Date : 2017-09-01DOI: 10.1109/IDAP.2017.8090254
M. Yildirim, Abdulnasir Yildiz
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.
{"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}
Pub Date : 2017-09-01DOI: 10.1109/IDAP.2017.8090207
Fahad Ahmed, Serkan Öztürk
In this work we investigate the performance of Ad-hoc on-demand distance vector routing (AODV), Dynamic source routing (DSR), Temporary ordered routing (TORA), Optimized link state routing (OLSR) and Geographic routing (GRP) protocols in wireless ad-hoc networks by using OPNET simulation program. In ad-hoc networks consisting of fixed and mobile stations, routing protocols are compared for different packet sizes and different number of stations.
{"title":"Tasarsiz ağlarda yönlendirme protokollerinin başarimlarinin değerlendirilmesi","authors":"Fahad Ahmed, Serkan Öztürk","doi":"10.1109/IDAP.2017.8090207","DOIUrl":"https://doi.org/10.1109/IDAP.2017.8090207","url":null,"abstract":"In this work we investigate the performance of Ad-hoc on-demand distance vector routing (AODV), Dynamic source routing (DSR), Temporary ordered routing (TORA), Optimized link state routing (OLSR) and Geographic routing (GRP) protocols in wireless ad-hoc networks by using OPNET simulation program. In ad-hoc networks consisting of fixed and mobile stations, routing protocols are compared for different packet sizes and different number of stations.","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"59 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":"121375495","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}
Pub Date : 2017-09-01DOI: 10.1109/IDAP.2017.8090216
Emad Soltani Nejad, M. Majma
Failing to make use of multi-path advantages in data center networks (DCNs) has confined accessible resources and increased the possibility of congestion. In this paper, we have presented a new algorithm for traffic engineering (TE) in a modular mode. In the proposed algorithm, the less loaded paths for conduction of current are selected with regard to the present conditions as soon as a current is generated between two hosts, their position is identified in the DCN, and the paths between the two are obtained. Results achieved from the Mininet emulator indicate that the performance of the RMTE method is, on average, 2.3 times better than the algorithm dominantly applied in Equal Cost Multi-Path (ECMP) data centers (DC) respecting improved degrees of efficiency of network links. However, the time during which data is read from OpenFlow switches imposes overflow on the system.
{"title":"RMTE: Robust modular traffic engineering in software-defined data center networks","authors":"Emad Soltani Nejad, M. Majma","doi":"10.1109/IDAP.2017.8090216","DOIUrl":"https://doi.org/10.1109/IDAP.2017.8090216","url":null,"abstract":"Failing to make use of multi-path advantages in data center networks (DCNs) has confined accessible resources and increased the possibility of congestion. In this paper, we have presented a new algorithm for traffic engineering (TE) in a modular mode. In the proposed algorithm, the less loaded paths for conduction of current are selected with regard to the present conditions as soon as a current is generated between two hosts, their position is identified in the DCN, and the paths between the two are obtained. Results achieved from the Mininet emulator indicate that the performance of the RMTE method is, on average, 2.3 times better than the algorithm dominantly applied in Equal Cost Multi-Path (ECMP) data centers (DC) respecting improved degrees of efficiency of network links. However, the time during which data is read from OpenFlow switches imposes overflow on the system.","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"9 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":"121484248","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}
Pub Date : 2017-09-01DOI: 10.1109/IDAP.2017.8090266
Gaffari Çelik, M. F. Talu
Spiking Neural Network (SNN) are 3rd Generation Artificial Neural Networks (ANN) models. The fact that time information is processed in the form of spikes and there are multiple synapses between cells (neurons) are the most important features that distinguish SNN from previous generations. In this study, artificial learning systems which can learn by using basic logical operators such as AND, OR, XOR have been developed in order to understand SNN structure. In SNN, we tried to find optimal values for these parameters by examining the effect of the number of connections between cells and delays between connections to learning success.
{"title":"Spiking neural network applications","authors":"Gaffari Çelik, M. F. Talu","doi":"10.1109/IDAP.2017.8090266","DOIUrl":"https://doi.org/10.1109/IDAP.2017.8090266","url":null,"abstract":"Spiking Neural Network (SNN) are 3rd Generation Artificial Neural Networks (ANN) models. The fact that time information is processed in the form of spikes and there are multiple synapses between cells (neurons) are the most important features that distinguish SNN from previous generations. In this study, artificial learning systems which can learn by using basic logical operators such as AND, OR, XOR have been developed in order to understand SNN structure. In SNN, we tried to find optimal values for these parameters by examining the effect of the number of connections between cells and delays between connections to learning success.","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"1 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":"129800873","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}
Pub Date : 2017-09-01DOI: 10.1109/IDAP.2017.8090282
Yusuf Karabacak, Ali Uysal
In this study, a driver design for the Brush Less Direct Current (BLDC) engine was made. With this driver, BLDC motors are provided to operate in both engine mode and regenerative braking mode. Fuzzy logic controller is used for motor speed control. The STM32F4 Discovery development card has been used to control your drive. Driver tests were conducted on an electric vehicle. Test data were obtained with the aid of a mini computer placed on the vehicle. In regenerative braking mode, the speed of the vehicle slowed down and the battery voltage was shown to be charged at the desired levels. The drive test data was obtained with the aid of an oscilloscope.
{"title":"Fuzzy logic controlled brushless direct current motor drive design and application for regenerative braking","authors":"Yusuf Karabacak, Ali Uysal","doi":"10.1109/IDAP.2017.8090282","DOIUrl":"https://doi.org/10.1109/IDAP.2017.8090282","url":null,"abstract":"In this study, a driver design for the Brush Less Direct Current (BLDC) engine was made. With this driver, BLDC motors are provided to operate in both engine mode and regenerative braking mode. Fuzzy logic controller is used for motor speed control. The STM32F4 Discovery development card has been used to control your drive. Driver tests were conducted on an electric vehicle. Test data were obtained with the aid of a mini computer placed on the vehicle. In regenerative braking mode, the speed of the vehicle slowed down and the battery voltage was shown to be charged at the desired levels. The drive test data was obtained with the aid of an oscilloscope.","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"59 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":"124901083","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}
Pub Date : 2017-09-01DOI: 10.1109/IDAP.2017.8090302
E. Karakose
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.
{"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}
Pub Date : 2017-09-01DOI: 10.1109/IDAP.2017.8090337
Mücahid Barstuğan, R. Ceylan
Sparse representation is a signal processing method which is mostly used in signal compression, noise reduction, and signal and image restoration fields. In this study, sparse representation was used in a different way from the traditional methods. In the proposed method, a hybrid structure was created by combining dictionary learning and ensemble classifier AdaBoost algorithms. The main idea of this method is to obtain the sparse coefficients from an over-complete dictionary and to use the coefficients in the weight update formula of AdaBoost. Support Vector Machines (SVM) classifier was used as weak classifiers of AdaBoost, and AdaBoost-SVM classifier structure was created. Multiplying the sparse coefficients with weight of weak learners process in weight update formula has given satisfying results on imbalanced datasets during the experiments.
{"title":"A discriminative dictionary learning-AdaBoost-SVM classification method on imbalanced datasets","authors":"Mücahid Barstuğan, R. Ceylan","doi":"10.1109/IDAP.2017.8090337","DOIUrl":"https://doi.org/10.1109/IDAP.2017.8090337","url":null,"abstract":"Sparse representation is a signal processing method which is mostly used in signal compression, noise reduction, and signal and image restoration fields. In this study, sparse representation was used in a different way from the traditional methods. In the proposed method, a hybrid structure was created by combining dictionary learning and ensemble classifier AdaBoost algorithms. The main idea of this method is to obtain the sparse coefficients from an over-complete dictionary and to use the coefficients in the weight update formula of AdaBoost. Support Vector Machines (SVM) classifier was used as weak classifiers of AdaBoost, and AdaBoost-SVM classifier structure was created. Multiplying the sparse coefficients with weight of weak learners process in weight update formula has given satisfying results on imbalanced datasets during the experiments.","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"239 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114058677","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}
Pub Date : 2017-09-01DOI: 10.1109/IDAP.2017.8090260
Abubekir Seyyarer, Ozan Akdağ, Cengiz Hark, A. Karcı, C. Yeroğlu
In this study, non-directional overcurrent relay coordination was done in 154/34.5 kV Malatya Teiaş Hasançelebi transformer centre using League Championship Algorithm (LCA). Standard inverse time characteristic based on IEC 255-3 is used for the relay is coordinated. The results obtained by the LCA have been used in virtual model, obtained by DigSilent software for overcurrent relays at the Hasançelebi transformer centre. Then, the overcurrent relay coordination was performed by examining the response of the overcurrent relays to the 3-phase fault currents generated in the model.
{"title":"Overcurrent relay coordination of 154/34,5 kV Hasançelebi substation by league championship algorithm","authors":"Abubekir Seyyarer, Ozan Akdağ, Cengiz Hark, A. Karcı, C. Yeroğlu","doi":"10.1109/IDAP.2017.8090260","DOIUrl":"https://doi.org/10.1109/IDAP.2017.8090260","url":null,"abstract":"In this study, non-directional overcurrent relay coordination was done in 154/34.5 kV Malatya Teiaş Hasançelebi transformer centre using League Championship Algorithm (LCA). Standard inverse time characteristic based on IEC 255-3 is used for the relay is coordinated. The results obtained by the LCA have been used in virtual model, obtained by DigSilent software for overcurrent relays at the Hasançelebi transformer centre. Then, the overcurrent relay coordination was performed by examining the response of the overcurrent relays to the 3-phase fault currents generated in the model.","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"56 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":"126270356","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}
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