Tora, Hakan

Profile Picture
Profile URL
https://hdl.handle.net/20.500.14411/8032
Name Variants
Tora,H.
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

Sustainable Development Goals

NO POVERTY1
NO POVERTY
0
Research Products
ZERO HUNGER2
ZERO HUNGER
0
Research Products
GOOD HEALTH AND WELL-BEING3
GOOD HEALTH AND WELL-BEING
1
Research Products
QUALITY EDUCATION4
QUALITY EDUCATION
0
Research Products
GENDER EQUALITY5
GENDER EQUALITY
0
Research Products
CLEAN WATER AND SANITATION6
CLEAN WATER AND SANITATION
0
Research Products
AFFORDABLE AND CLEAN ENERGY7
AFFORDABLE AND CLEAN ENERGY
2
Research Products
DECENT WORK AND ECONOMIC GROWTH8
DECENT WORK AND ECONOMIC GROWTH
0
Research Products
INDUSTRY, INNOVATION AND INFRASTRUCTURE9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
0
Research Products
REDUCED INEQUALITIES10
REDUCED INEQUALITIES
0
Research Products
SUSTAINABLE CITIES AND COMMUNITIES11
SUSTAINABLE CITIES AND COMMUNITIES
1
Research Products
RESPONSIBLE CONSUMPTION AND PRODUCTION12
RESPONSIBLE CONSUMPTION AND PRODUCTION
0
Research Products
CLIMATE ACTION13
CLIMATE ACTION
2
Research Products
LIFE BELOW WATER14
LIFE BELOW WATER
1
Research Products
LIFE ON LAND15
LIFE ON LAND
0
Research Products
PEACE, JUSTICE AND STRONG INSTITUTIONS16
PEACE, JUSTICE AND STRONG INSTITUTIONS
0
Research Products
PARTNERSHIPS FOR THE GOALS17
PARTNERSHIPS FOR THE GOALS
1
Research Products
This researcher does not have a Scopus ID.
This researcher does not have a WoS ID.
Scholarly Output

58

Articles

11

Views / Downloads

216/2226

Supervised MSc Theses

15

Supervised PhD Theses

5

WoS Citation Count

57

Scopus Citation Count

88

Patents

0

Projects

0

WoS Citations per Publication

0.98

Scopus Citations per Publication

1.52

Open Access Source

7

Supervised Theses

20

JournalCount
2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 - Proceedings -- 2014 22nd Signal Processing and Communications Applications Conference, SIU 2014 -- 23 April 2014 through 25 April 2014 -- Trabzon -- 1060533
22nd IEEE Signal Processing and Communications Applications Conference (SIU) -- APR 23-25, 2014 -- Karadeniz Teknik Univ, Trabzon, TURKEY3
ICECS 2017 - 24th IEEE International Conference on Electronics, Circuits and Systems -- 24th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2017 -- 5 December 2017 through 8 December 2017 -- Batumi -- 1346752
24th IEEE International Conference on Electronics, Circuits and Systems (ICECS) -- DEC 05-08, 2017 -- Batumi, GEORGIA2
24th Signal Processing and Communication Application Conference (SIU) -- MAY 16-19, 2016 -- Zonguldak, TURKEY2
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Now showing 1 - 10 of 58
  • Thumbnail Image
    Master Thesis
    Konvolutional Nöral Ağ Kullanarak Hasta Elma Ağağı Yapraklarinin Segmentasyon
    (2020) Al-mashhadanı, Alı; Tora, Hakan
    Tarım alanında, uzmanın gözü hastalığı erken bir aşamada tanımlayamayabilir veya doğru bir şekilde teşhis edemeyebilir. Bitki hastalığının yanlış teşhisi genellikle yanlış tedavinin seçilmesine ve bu da mahsulün kaybına neden olur. Bu nedenle, hastalıklı yaprağın otomatik segmentasyon sistemi bu sorunu çözmek için son derece gereklidir. Bu tez Bitki Patolojisi 2020 segmentasyonunda derin öğrenme nin cesaretini görüntüler - FGVC7 veri seti elma kabuğu gibi birden fazla elma foliar hastalığı belirtileri yüksek çözünürlüklü renkli görüntüler içeren, sedir elma pas, ve sağlıklı yapraklar. Önerilen segmentasyon algoritması, U-Net ve ResNet olmak üzere iki farklı mimari kullanılarak yapılan anlamsal segmentasyon yaklaşımıdır. Her iki ağın sonuçları Pixel Accuracy, IoU, F1-Score ve Recall ölçümleri kullanılarak değerlendirilmiş ve karşılaştırma ResNet'in bu amaca yönelik verimliliğini göstermiştir.
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    Conference Object
    Citation - Scopus: 2
    Real Time Infrared Image Enhancement;
    (2012) Akdeniz,N.; Tora,H.
    This study evaluates the implementation of Balanced Contrast Limited Adaptive Histogram Equalization (BCLAHE) for infrared images (IR) on an embedded platform. The aim was to achieve real time performance for the operator display target application. The system configured for this aim is a dual processor media application device OMAP3530, which consists of an ARM and a DSP processor. System is configured so that hardware sources are used efficiently and various performance improvement techniques are investigated. Performance analysis is done over IR images with different dynamic range. © 2012 IEEE.
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    Conference Object
    Citation - WoS: 1
    THE USE OF CUMULANTS FOR VOICED-UNVOICED SEGMENTS IDENTIFICATION IN SPEECH SIGNALS
    (Ieee, 2014) Uslu, Baran; Tora, Hakan
    In 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.
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    Article
    Citation - Scopus: 1
    Vowel Classification Based on Waveform Shapes
    (ASTES Publishers, 2019) Tora,H.; Karacor,G.; Uslu,B.
    Vowel classification is an essential part of speech recognition. In classical studies, this problem is mostly handled by using spectral domain features. In this study, a novel approach is proposed for vowel classification based on the visual features of speech waveforms. In sound vocalizing, the position of certain organs of the human vocal system such as tongue, lips and jaw is very effective on the waveform shapes of the produced sound. The motivation to employ visual features instead of classical frequency domain features is its potential usage in specific applications like language education. Even though this study is confined to Turkish vowels, the developed method can be applied to other languages as well since the shapes of the vowels show similar patterns. Turkish vowels are grouped into five categories. For each vowel group, a time domain speech waveform with an interval of two pitch periods is handled as an image. A series of morphological operations is performed on this speech waveform image to obtain the geometric characteristics representing the shape of each class. The extracted visual features are then fed into three different classifiers. The classification performances of these features are compared with classical methods. It is observed that the proposed visual features achieve promising classification rates. © 2019 Advances in Science, Technology and Engineering Systems.All rights reserved.
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    Conference Object
    Producing Synthetic Speech From Turkish Text Via a Single Sound Synthesizer Ic;
    (2010) Tora,H.; Cengizler,Ç.
    In this study, new speech sounds were created for Turkish letters from the allophones listed in SpeakJet Magnevation complex sound synthesizer IC, which is intended for English, by selecting and paring the most similiar phonems. Consequently, Turkish Text to Speech synthesizer was implemented with minimum enviroment elements and no physical modification on IC. Paring based on SAMPA showed that all Turkish phonems can be obtained from English allophones with high compatibility. The text to speech and paring algorithm presented herein is developed to be embedded in a microcontroller and capable to vocalize a random Turkish text with SpeakJet IC.
  • Thumbnail Image
    Conference Object
    Higher Order Statistical Analysis of Turkish Phones
    (Ieee, 2014) Tora, Hakan; Uslu, Baran
    In 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.
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    Article
    Citation - WoS: 7
    Citation - Scopus: 10
    Comparison of Three Different Learning Methods of Multilayer Perceptron Neural Network for Wind Speed Forecasting
    (Gazi Univ, 2021) Bulut, Mehmet; Tora, Hakan; Buaisha, Dr.magdi; Buaisha, Magdi
    In 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.
  • Thumbnail Image
    Conference Object
    Naturalness Analysis of the Speech Synthesized by a Tts Card
    (Ieee, 2016) Tora, Hakan; Uslu, Baran
    It 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.
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    Conference Object
    Design and Implementation of an Expressive Talking Mobile Robot: Toztorus
    (Institute of Electrical and Electronics Engineers Inc., 2018) Tozan,O.; Tora,H.; Uslu,B.; Una,B.; Ceylan,E.
    This 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. © 2018 IEEE.
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    Conference Object
    Citation - Scopus: 1
    Performance Evaluation of Self Organizing Neural Networks for Clustering in Esm Systems;
    (IEEE Computer Society, 2014) Gencol,K.; Tora,H.
    Electronic Support Measures (ESM) system is an important function of electronic warfare which provides the real time projection of radar activities. Such systems may encounter with very high density pulse sequences and it is the main task of an ESM system to deinterleave these mixed pulse trains with high accuracy and minimum computation time. These systems heavily depend on time of arrival analysis and need efficient clustering algorithms to assist deinterleaving process in modern evolving environments. On the other hand, self organizing neural networks stand very promising for this type of radar pulse clustering. In this study, performances of self organizing neural networks that meet such clustering criteria are evaluated in detail and the results are presented. © 2014 IEEE.