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Tora, Hakan
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Name Variants
Tora,H.
T., Hakan
Tora, Hakan
H., Tora
H.,Tora
T.,Hakan
Hakan, Tora
T., Hakan
Tora, Hakan
H., Tora
H.,Tora
T.,Hakan
Hakan, Tora
Job Title
Doktor Öğretim Üyesi
Email Address
hakan.tora@atilim.edu.tr
Main Affiliation
Airframe and Powerplant Maintenance
Status
Former Staff
Website
ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
Scholarly Output
53
Articles
11
Citation Count
35
Supervised Theses
15
22 results
Scholarly Output Search Results
Now showing 1 - 10 of 22
Article Yalıtık Sözcüklü Bir Türkçe Konuşma Tanıma Sisteminin Yapay Veri Artırımı ile Tasarımı ve Gerçekleştirimi(2020) Uslu, İbrahim Baran; Tora, Hakan; Sümer, Emre; Türker, Mustafa; Department of Electrical & Electronics Engineering; Airframe and Powerplant MaintenanceBu çalışmada toplamda doksan iki adet sesli komuttan oluşan bir yalıtık sözcüklü Türkçe konuşmatanıma sistemi tasarlanmış ve gerçekleştirilmiştir. Sistem, destek vektör makinesi (SVM) tabanlı olup,eğitimde kullanılan veri kümesi kaydedilen konuşmaların yapay olarak çeşitlendirilip artırılmasıyla eldeedilmiştir. Farklı yapay veri oranlarının tanıma başarımı üzerindeki etkisi incelenmiştir. Akustik öznitelikolarak, mel frekansı kepstral katsayıları (MFCC) kullanılmıştır. Ayrıca, ses aktivitesi tespitinin ve MFCCkatsayılarının tanıma başarımına etkileri de irdelenmiştir. Sonuçta doksan iki yalıtık komut için ortalama%92.6’lık doğrulukla çalışan bir konuşma tanıma sistemi geliştirilmiştirConference Object Citation - WoS: 0An Approach for Perceptual Similarity Detection Between Audios Independent of Genre Via Metadata Extraction and Correlation(Ieee, 2007) Komsu, Fatma; Tora, Hakan; Oeztoprak, Kasim; Tora, Hakan; Tora, Hakan; Airframe and Powerplant Maintenance; Airframe and Powerplant MaintenanceThis study presents an approach for perceptual similarity detection between audios independent of genre. The study is formed of three phases; signal pre-processing as the first phase, metadata extraction via various perceptually compatible features as the second phase, and correlation methodology for similarity identification as the third phase. The performance and relative importance of the selected features for perceptual similarity analysis are presented, as testing results. Moreover, relative importance of preprocessing is introduced. Using the proposed methodology, perceptual similarity detection between genre independent audios is achieved with a 96.85% performance. Contribution highly lies on the independency of genre.Conference Object Citation - WoS: 0Design and Implementation of an Expressive Talking Mobile Robot: Toztorus(Ieee, 2018) Tozan, Ozalp; Tora, Hakan; Uslu, Baran; Unal, Bulcnt; Ceylan, Ece; Computer Engineering; Airframe and Powerplant MaintenanceThis paper is about a brand new robot and all its development stages from the design to the show time. As an undergraduate research project (the LAP program at Atilim University), the robot TozTorUs is the outcome of the dense efforts of a team. With the sensors equipped, it navigates autonomously in the environment in which it is located by avoiding the obstacles. It can understand your questions and answer them using Google's speech technologies. Although it is not a humanoid robot, with eyes and mouth simulator LED displays, it is as friendly as a human. We can also control TozTorUs using a mobile phone. Apart from these, it is able to adjust its height with respect to the visitor's, thus allowing it to make an eye contact with the person. Although TozTorUs is designed for welcoming, it may also be employed for consulting, security and elderly assistance.Article Citation - WoS: 3Citation - Scopus: 3An Unrestricted Arnold's Cat Map Transformation(Springer, 2024) Turan, Mehmet; Goekcay, Erhan; Tora, Hakan; Software Engineering; Mathematics; Airframe and Powerplant MaintenanceThe Arnold's Cat Map (ACM) is one of the chaotic transformations, which is utilized by numerous scrambling and encryption algorithms in Information Security. Traditionally, the ACM is used in image scrambling whereby repeated application of the ACM matrix, any image can be scrambled. The transformation obtained by the ACM matrix is periodic; therefore, the original image can be reconstructed using the scrambled image whenever the elements of the matrix, hence the key, is known. The transformation matrices in all the chaotic maps employing ACM has limitations on the choice of the free parameters which generally require the area-preserving property of the matrix used in transformation, that is, the determinant of the transformation matrix to be +/- 1.\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\pm 1.$$\end{document} This reduces the number of possible set of keys which leads to discovering the ACM matrix in encryption algorithms using the brute-force method. Additionally, the period obtained is small which also causes the faster discovery of the original image by repeated application of the matrix. These two parameters are important in a brute-force attack to find out the original image from a scrambled one. The objective of the present study is to increase the key space of the ACM matrix, hence increase the security of the scrambling process and make a brute-force attack more difficult. It is proved mathematically that area-preserving property of the traditional matrix is not required for the matrix to be used in scrambling process. Removing the restriction enlarges the maximum possible key space and, in many cases, increases the period as well. Additionally, it is supplied experimentally that, in scrambling images, the new ACM matrix is equivalent or better compared to the traditional one with longer periods. Consequently, the encryption techniques with ACM become more robust compared to the traditional ones. The new ACM matrix is compatible with all algorithms that utilized the original matrix. In this novel contribution, we proved that the traditional enforcement of the determinant of the ACM matrix to be one is redundant and can be removed.Conference Object Citation - WoS: 1THE USE OF CUMULANTS FOR VOICED-UNVOICED SEGMENTS IDENTIFICATION IN SPEECH SIGNALS(Ieee, 2014) Uslu, Baran; Tora, Hakan; Airframe and Powerplant MaintenanceIn this study, voiced-unvoiced classification performance of Turkish sounds using skewness and kurtosis is examined. The analyses show that higher order cumulants can be employed as a feature in voiced-unvoiced classification that is vital in speech processing applications. Furthermore, it has been shown that cumulants are also useful for identifying voiced and unvoiced segments in noisy speech signals.Conference Object Citation - WoS: 0Higher Order Statistical Analysis of Turkish Phones(Ieee, 2014) Tora, Hakan; Uslu, Baran; Airframe and Powerplant MaintenanceIn this study, histograms of Turkish phones were examined using higher order cumulants. As is known, phones constituting a language, are composed of letters as vowels and consonants. These letters can also be grouped as voiced and unvoiced phones. It is observed that unvoiced letters show a Gaussian-like distribution and result in small values of skewness and kurtosis. On the other hand, vowels and voiced consonants lead to a non-Gaussian distribution. Voiced and unvoiced phones are related with their skewness and kurtosis values. It is empirically shown that higher order cumulants are likely to be a feature in describing Turkish phones.Article Citation - WoS: 3Citation - Scopus: 6Comparison of Three Different Learning Methods of Multilayer Perceptron Neural Network for Wind Speed Forecasting(Gazi Univ, 2021) Bulut, Mehmet; Tora, Hakan; Buaisha, Dr.magdi; Airframe and Powerplant Maintenance; Electrical-Electronics EngineeringIn the world, electric power is the highest need for high prosperity and comfortable living standards. The security of energy supply is an essential concept in national energy management. Therefore, ensuring the security of electricity supply requires accurate estimates of electricity demand. The share of electricity generation from renewables is significantly growing in the world. This kind of energy types are dependent on weather conditions as the wind and solar energies. There are two vital requirements to locate and measure specific systems to utilize wind power: modelling and forecasting of the wind velocity. To this end, using only 4 years of measured meteorological data, the present research attempts to estimate the related speed of wind within the Libyan Mediterranean coast with the help of ANN (artificial neural networking) with three different learning algorithms, which are Levenberg-Marquardt, Bayesian Regularization and Scaled Conjugate Gradient. Conclusions reached in this study show that wind speed can be estimated within acceptable limits using a limited set of meteorological data. In the results obtained, it was seen that the SCG algorithm gave better results in tests in this study with less data.Conference Object Citation - WoS: 0Naturalness Analysis of the Speech Synthesized by a Tts Card(Ieee, 2016) Tora, Hakan; Uslu, Baran; Airframe and Powerplant MaintenanceIt is known that the performance of a developed text-to-speech (TTS) synthesis system is assessed by subjective tests. These assessments are usually based on the intelligibility and naturalness of the synthesized speech. In this study, an investigation on relating these subjective test results, thus the naturalness of the synthesized speech, to which acoustic features is accomplished. Consequently the features which will increase the performance while synthesizing the speech are determined. Our work is focused especially on the pitch frequency and energy parameters.Conference Object Citation - WoS: 1Recognition of Hand-Sketched Digital Logic Gates(Ieee, 2015) Gul, Nuray; Tora, Hakan; Airframe and Powerplant MaintenanceHand-Sketched circuit recognition is a very useful tool in engineering area. Because most of the engineers prefer to design their circuits on the paper firstly. So, this can cause time wasting and some mistakes. In this study, which is based on the solving these kinds of problems, classification and recognition of the handwritten digital logic gates according to their complex and scalar FDs (Fourier Descriptors) is presented. Test results are obtained as 84.3 % accuracy rate for complex FDs, 98.6 % for scalar FDs. Then these results are compared and decided the optimum FDs type for this study.Article Citation - WoS: 8Citation - Scopus: 9A Novel Data Encryption Method Using an Interlaced Chaotic Transform(Pergamon-elsevier Science Ltd, 2024) Gokcay, Erhan; Tora, Hakan; Software Engineering; Airframe and Powerplant MaintenanceWe present a novel data encryption approach that utilizes a cascaded chaotic map application. The chaotic map used in both permutation and diffusion is Arnold's Cat Map (ACM), where the transformation is periodic and the encrypted data can be recovered. The original format of ACM is a two-dimensional mapping, and therefore it is suitable to randomize the pixel locations in an image. Since the values of pixels stay intact during the transformation, the process cannot encrypt an image, and known-text attacks can be used to get back the transformation matrix. The proposed approach uses ACM to shuffle the positions and values of two-dimensional data in an interlaced and nested process. This combination extends the period of the transformation, which is significantly longer than the period of the initial transformation. Furthermore, the nested process's possible combinations vastly expand the key space. At the same time, the interlaced pixel and value transformation makes the encryption highly resistant to any known-text attacks. The encrypted data passes all random-data tests proposed by the National Institute of Standards and Technology. Any type of data, including ASCII text, can be encrypted so long as it can be rearranged into a two-dimensional format.
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