Tora, Hakan

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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

2

ZERO HUNGER
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0

Research Products

14

LIFE BELOW WATER
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1

Research Products

17

PARTNERSHIPS FOR THE GOALS
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1

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5

GENDER EQUALITY
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0

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16

PEACE, JUSTICE AND STRONG INSTITUTIONS
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0

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8

DECENT WORK AND ECONOMIC GROWTH
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0

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4

QUALITY EDUCATION
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0

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6

CLEAN WATER AND SANITATION
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0

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7

AFFORDABLE AND CLEAN ENERGY
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2

Research Products

10

REDUCED INEQUALITIES
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0

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11

SUSTAINABLE CITIES AND COMMUNITIES
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1

Research Products

9

INDUSTRY, INNOVATION AND INFRASTRUCTURE
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0

Research Products

1

NO POVERTY
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0

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3

GOOD HEALTH AND WELL-BEING
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1

Research Products

12

RESPONSIBLE CONSUMPTION AND PRODUCTION
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0

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13

CLIMATE ACTION
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2

Research Products

15

LIFE ON LAND
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0

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This researcher does not have a Scopus ID.
This researcher does not have a WoS ID.
Scholarly Output

57

Articles

11

Views / Downloads

2/0

Supervised MSc Theses

14

Supervised PhD Theses

5

WoS Citation Count

57

Scopus Citation Count

88

WoS h-index

5

Scopus h-index

5

Patents

0

Projects

0

WoS Citations per Publication

1.00

Scopus Citations per Publication

1.54

Open Access Source

7

Supervised Theses

19

Google Analytics Visitor Traffic

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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Start date: 2010

Scholarly Output Search Results

Now showing 1 - 10 of 53
  • Thumbnail Image
    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
    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.
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    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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    Master Thesis
    Hoparlör Bağımsız İzolasyonlu Rakam Tanıma
    (2020) Hamıd, Mohammed Saeed; Tora, Hakan
    Çeşitli konuşma sinyali işleme uygulamalarında VAD, bir ses akışını konuşma etkinliği ve konuşmanın olmadığı zaman aralıklarını içeren zaman aralıklarına bölmek için önemli bir karakter sunar. Bu araştırmada, izole kelime tanıma ile ilgili yeni bir yaklaşım sunduk. İlk aşamada, ses etkinliği algılama (VAD) problem kırma penceresi, Bohman işlevi ve Bartlett-Hann işlevi için üç işlev uygulanmıştır. Hem Bohman fonksiyonu hem de Bartlett-Hann fonksiyonu VAD problemi için önceki çalışmalarda uygulanmamıştır. Öte yandan, perde, MFCC'ler ve enerji, özellik çıkarma teknikleri olarak uygulanır ve bu iki yöntemin yeni yaklaşımlar olduğu SOFTMAX ile birleştirilir. Pitch tabanlı SOFTMAX, SOFTMAX'a bağlanan ve yedi kelimeye göre sınıflandırılan ve% 85 doğrulukla özelliklerle çıkarılan olağanüstü sonuçlar sundu. Ayrıca enerji, özellik çıkarma ve SOFTMAX'a bağlanan bu fonksiyonun çıktısı olarak da uygulanır. Bu çerçeve, yalnızca kullanıcının giriş verilerini kolayca değiştirdiği çeşitli yalıtılmış kelime tanıma işlemlerine kolayca uygulanabilir. Bu çalışmadaki ana katkı, SOFTMAX'ı çeşitli özellik çıkarma teknikleriyle birleştirmiştir. SOFTMAX, (0,1) arasındaki etiketlere girdi özelliklerini analiz eden ve sınıflandırma veya regresyon sorunları için son katman fonksiyonu olarak çeşitli derin öğrenme tekniklerinde kullanılan trend olasılık fonksiyonudur. Elde edilen sonuçlar, özellik çıkarma için uygulanan sesli sinyal işleme teknikleri ile birleştirilmiş çeşitli makine öğrenme ve derin öğrenme teknikleri uygulanarak bu alanda sunulan çeşitli çalışmalarla karşılaştırılmıştır.
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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
    Design and Implementation of an Expressive Talking Mobile Robot: Toztorus
    (Ieee, 2018) Tozan, Ozalp; Tora, Hakan; Uslu, Baran; Unal, Bulcnt; Ceylan, Ece
    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.
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    Conference Object
    Recognition of Characters on Vehicle License Plates;
    (2010) Tora,H.; Bora,K.
    In this study, a simple and effective method is proposed for segmenting alphanumeric and numeric characters on vehicle license plates and recognizing the segmented characters.The proposed approach is basically based on template matching technique. Features used for matching are obtained by scanning the segmented characters from left-to-right, right-to-left, top-to-bottom, and bottom-to-top. The features extracted in this way reveals the fact that how a character is moving and changing along its four-side.The character recognition is accomplished by using this information of the character.Experiments done show that successful results are obtained. ©2010 IEEE.
  • Thumbnail Image
    Master Thesis
    Avuç İçi Tanımlaması
    (2018) Jebrıel, Belal Alı Mesbah; Tora, Hakan
    Bu tez, standart bir veritabanı ve bir temizleyici aracılığıyla avuç izi tanımlanmasının uygunluğunu araştırmaktadır. Bu çalışma, sol el ve sağ el görüntüleri içeren veritabanları CASIA ve IIT için iki öznitelik kümesi kullanmaktadır. Yerel ikili örüntü (YİÖ) ve yönlü gradyan histogram (YGH) öznitelikleri, MATLAB tarafından görüntülerden elde edilmiştir. Eğitim ve test setleri bu özelliklerden oluşturuldu. Çok katmanlı katmanlı bir sinir ağı ve lineer ve kuadratik kernel kullanan destek vektör makineleri (DVM), seçilen veritabanlarında eğitilmiş ve test edilmiştir. Seçilen özellikler deneysel olarak birbirleriyle karşılaştırılmıştır. Her iki sınıflandırıcı için YGH'de daha iyi sonuçlar elde edilmiştir. Ayrıca, sınıflandırıcıların performansı da değerlendirilmiştir. Sinir ağın, her iki veri setinin YİÖ öznitelikleri için SVM'den daha iyi sonuçlar verdiği gözlenmiştir. Ancak, YGH özellikleri için birbirlerine göre çok fazla avantajları yoktur. Anahtar Kelimeler: Avuç izi tanımlama, yerel ikili örüntü (YİÖ), yönlü gradyan histogramı (YGH), sinir ağları, destek vektör makinesi (DVM).
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    Conference Object
    Segmentation of Isolated Words Into Voiced-Unvoiced Sound Components by Kurtosis;
    (Institute of Electrical and Electronics Engineers Inc., 2015) Uslu,B.; Tora, Hakan; Tora,H.; Tora, Hakan; Airframe and Powerplant Maintenance; Airframe and Powerplant Maintenance
    This study presents a new approach to the segmentation of isolated words into their voiced/ unvoiced parts. It is well known that voiced/ unvoiced discrimination has an important role in speech synthesis and coding applications. The offered method makes this discrimination using the kurtosis values of the words. The performance of the proposed approach was tested on Turkish digit recordings from zero to nine. It has been observed that this approach segments the parts successfully in not only clean speech but also in noisy speech. © 2015 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.