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Öğe A novel approach for spam email detection based on shifted binary patterns(Wiley-Blackwell, 2016-01-11) Kaya, Yılmaz; Ertuğrul, Ömer FarukAdvances in communication allow people flexibility to communicate in various ways. Electronic mail (email) is one of the most used communication methods for personal or business purposes. However, it brings one of the most tackling issues, called spam email, which also raises concerns about data safety. Thus, the requirement of detecting spams is crucial for keeping the users safe and saving them from the waste of time while tackling those issues. In this study, an effective approach based on the probability of the usage of the characters that has similar orders with respect to their UTF-8 value by employing shifted one-dimensional local binary pattern (shifted-1D-LBP) was used to extract quantitative features from emails for spam email detection. Shifted-1D-LBP, which can be described as an ordered set of binary comparisons of the center value with its neighboring values, is a content-based approach to spam detection with low-level information. To validate the performance of the proposed approach, three benchmark corpora, Spamassasian, Ling-Spam, and TREC email corpuses, were used. The average classification accuracies of the proposed approach were 92.34%, 92.57%, and 95.15%, respectively. Analysis and promising experimental results indicated that the proposed approach was a very competitive feature extraction method in spam email filtering.Öğe Gender classification from facial images using gray relational analysis with novel local binary pattern descriptors(Springer Nature, 2016-11-18) Kaya, Yılmaz; Ertuğrul, Ömer FarukGender classification (GC) is one of the major tasks in human identification that increase its accuracy. Local binary pattern (LBP) is a texture method that employed successfully. But LBP suffers a major problem; it cannot capture spatial relationships among local textures. Therefore, in order to increase the accuracy of GC, two LBP descriptors, which are based on (1) spatial relations between neighbors with a distance parameter, and (2) spatial relations between a reference pixel and its neighbor on the same orientation, were employed to extract features from facial images. Additionally, gray relational analysis (GRA) was carried out to identify gender through extracted features. Experiments on the FEI database illustrated the effectiveness of the proposed approaches. Achieved accuracies are 97.14, 93.33, and 92.50% by applying GRA with the nLBPd, dLBPα, and traditional LBP features, respectively. Experimental results indicated that the proposed approaches were very competitive feature extraction methods in GC. Present work also showed that the nLBPd, dLBPα methods were obtained more acceptable results than traditional LBP.Öğe Doküman dili tanıma için yeni bir öznitelik çıkarım yaklaşımı: İkili desenler(Gazi Üniversitesi, 2016-12-14) Kaya, Yılmaz; Ertuğrul, Ömer FarukDoğal dil işlemenin önemli alt konularından biri olan dil tanıma (DT), bir dokümanın içeriğine göre yazıldığı dili belirleme işlemidir. Bu çalışmada, karakterlerin UTF-8 değerlerini birbirleri ile karşılaştırmalar sonucu elde edilen ikili desenler kullanarak yeni bir dil tanıma yaklaşımı, bir boyutlu yerel ikili örüntüler (1B-YİÖ) önerilmiştir. Önerilen yöntem farklı sayıda dillerden oluşan metinler içeren dört veri kümesi ile test edilmiştir. 1B-YİÖ ile dokümanlardan elde edilen öznitelikler kullanılarak farklı makine öğrenmesi yöntemleri ile sınıflandırma işlemi gerçekleştirilmiştir. Dört veri kümesi için sınıflandırma başarıları sırası ile %86.20, %92.75, %100 ve %89.77 olarak gözlenmiştir. Elde edilen sonuçlara göre önerilen öznitelik çıkarım yönteminin dil tanıma için önemli örüntüler sağladığı görülmüştür.Öğe Sine-cosine algorithm-based optimization for automatic voltage regulator system(SAGE, 2019-04-01) Hekimoğlu, BaranA novel design method, sine-cosine algorithm (SCA) is presented in this paper to determine optimum proportional-integral-derivative (PID) controller parameters of an automatic voltage regulator (AVR) system. The proposed approach is a simple yet effective algorithm that has balanced exploration and exploitation capabilities to search the solutions space effectively to find the best result. The simplicity of the algorithm provides fast and high-quality tuning of optimum PID controller parameters. The proposed SCA-PID controller is validated by using a time domain performance index. The proposed method was found efficient and robust in improving the transient response of AVR system compared with the PID controllers based on Ziegler-Nichols (ZN), differential evolution (DE), artificial bee colony (ABC) and bio-geography-based optimization (BBO) tuning methods.Öğe Parameter optimization of power system stabilizers via kidney-inspired algorithm(SAGE, 2018-06-25) Ekinci, Serdar; Demiroren, Aysen; Hekimoğlu, BaranThis article describes the application of a new population-based meta-heuristic optimization algorithm inspired by the kidney process in the human body for the tuning of power system stabilizers (PSSs) in a multi-machine power system. The tuning problem of PSS parameters is formulated as an optimization problem that aims at maximizing the damping ratio of the electromechanical modes and the kidney-inspired algorithm (KA) is used to search for the optimal parameters. The efficacy of the KA-based PSS design was successfully tested on a well-known 16-machine, 68-bus power system. The obtained results are evaluated and compared with the other results obtained by the original particle swarm optimization (PSO) and the bat algorithm (BA) methods. From the detailed eigenvalue analysis, the nonlinear simulation studies and some performance indices it has been found out that for damping oscillations, the performance of the proposed KA approach in this study is better than that obtained by other intelligent techniques (PSO and BA). Moreover, the efficiency and the superior performance of the proposed method over the other two algorithms in terms of computation time, convergence rate and solution quality are confirmed.Öğe HPA algoritması ile çok makinalı güç sistemi kararlı kılıcısı tasarımı(Gazi Üniversitesi, 2017-12-08) Ekinci, Serdar; Hekimoğu, BaranBu makale, parçacık sürüsü optimizasyonu (PSO) ve yapay arı kolonisine (ABC) dayalı, çok makinalı güç sisteminde güç sistemi kararlı kılıcısının (PSS) optimal tasarımı için iyimser sonuçlar bulmak için güçlü yetilere sahip HPA tekniği adında yeni bir hibrit yaklaşımı tanımlamaktadır. PSS parametrelerinin en uygun ayarlarının elde edilmesi için PSS parametrelerini seçme problemi, özdeğer tabanlı bir amaç fonksiyonu ile basit bir optimizasyon problemine çevrildi ve HPA tekniği kullanılarak çözüldü. Önerilen HPA tabanlı PSS tasarımının etkinliği özdeğer analizi, zaman domeni simülasyonları ve bazı performans indeksleri aracılığıyla farklı arızalar altındaki 3-makinalı 9-baralı güç sistemi üzerinde doğrulandı. Bu çalışmaların sonuçları, HPA algoritmasının PSS parametrelerinin ayarlanması için alternatif ve daha etkin bir iyileştirici olduğunu ve PSO ile ABC’ye oranla güç sisteminin dinamik kararlılığını büyük oranda artırdığını göstermiştir. Ayrıca hesaplama zamanı, yaklaşım hızı ve çözüm kalitesi açısından HPA algoritmasının PSO ve ABC’ye göre potansiyeli ve üstünlüğü kanıtlanmıştır.Öğe A novel feature extraction approach in SMS spam filtering for mobile communication: one-dimensional ternary patterns(Wiley-Blackwell, 2016-10-19) Kaya, Yılmaz; Ertuğrul, Ömer FarukThe importance and utilization of mobile communication are increasing day by day, and the short message service (SMS) is one of them. Although SMS is a widely used communication way, it brings together a major problem, which is SMS spam messages. SMS spams do not only use vain in the mobile communication traffic but also disturb users. Based on this fact, blacklisting methods, statistical methods which are built on the frequency of occurrence of words or characters, and machine learning methods have been employed. Because punishments and legal laws are not enough to solve this problem and the Group Special Mobile number of SMS spam can easily be changed, a content-based approach must be proposed. Content-based methods showed high success in spam e-mail filtering, but it is hard in the SMS spam filtering because SMS messages are extremely short and generally contains many abbreviations. In this study, an image processing method, local ternary pattern was improved to extract features from SMS messages in the feature extraction stage. In the proposed one-dimensional ternary patterns, firstly, text message was converted to their UTF-8 values. Later, each character (its UTF-8 value) in the message was compared with its neighbors. Two different feature sets were extracted from the results of these comparisons. Finally, some machine learning methods were employed to classify these features. In order to validate the proposed approach, three different SMS corpora were used. The achieved accuracies and other employee performance measures showed that the proposed approach, one-dimensional ternary patterns, can be effectively employed in SMS spam filtering.
