Oğuz, Kaya

Profile Picture
Profile URL
https://hdl.handle.net/20.500.14365/6737
Name Variants
Oguz, K. A. Y. A.
Oguz, K.
Oğuz, K.
Oguz, Kaya
Job Title
Email Address
kaya.oguz@ieu.edu.tr
Main Affiliation
05.05. Computer Engineering
Status
Current Staff
Website
ORCID ID
0000-0002-1860-9127
Scopus Author ID
54902980200
Turkish CoHE Profile ID
3159CF11C7B48EC0
Google Scholar ID
QP0Nj0QAAAAJ
WoS Researcher ID
A-1812-2016
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Kaya_Oguz.jpg (9.04 KB)

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
3
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
0
Research Products
DECENT WORK AND ECONOMIC GROWTH8
DECENT WORK AND ECONOMIC GROWTH
0
Research Products
INDUSTRY, INNOVATION AND INFRASTRUCTURE9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
6
Research Products
REDUCED INEQUALITIES10
REDUCED INEQUALITIES
0
Research Products
SUSTAINABLE CITIES AND COMMUNITIES11
SUSTAINABLE CITIES AND COMMUNITIES
5
Research Products
RESPONSIBLE CONSUMPTION AND PRODUCTION12
RESPONSIBLE CONSUMPTION AND PRODUCTION
0
Research Products
CLIMATE ACTION13
CLIMATE ACTION
0
Research Products
LIFE BELOW WATER14
LIFE BELOW WATER
0
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
0
Research Products
Documents

42

Citations

950

h-index

8

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Documents

36

Citations

637

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Scholarly Output

49

Articles

19

Views / Downloads

96/136

Supervised MSc Theses

6

Supervised PhD Theses

1

WoS Citation Count

520

Scopus Citation Count

822

Patents

0

Projects

10

WoS Citations per Publication

10.61

Scopus Citations per Publication

16.78

Open Access Source

18

Supervised Theses

7

JournalCount
2019 Medıcal Technologıes Congress (Tıptekno)3
3rd International Informatics and Software Engineering Conference, IISEC 20222
2024 Innovations in Intelligent Systems and Applications Conference, ASYU 2024 -- 2024 Innovations in Intelligent Systems and Applications Conference, ASYU 2024 -- 16 October 2024 through 18 October 2024 -- Ankara -- 2045622
26th IEEE Signal Processing and Communications Applications Conference, SIU 20182
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Now showing 1 - 10 of 49
  • Thumbnail Image
    Article
    Citation - WoS: 2
    Citation - Scopus: 2
    The Effect of Emotional Faces on Reward-Related Probability Learning in Depressed Patients
    (Elsevier B.V., 2024) Keskin-Gokcelli, D.; Kizilates-Evin, G.; Eroglu-Koc, S.; Oğuz, Kaya; Eraslan, C.; Kitis, O.; Gonul, A.S.
    Background: Existing research indicates that individuals with Major Depressive Disorder (MDD) exhibit a bias toward salient negative stimuli. However, the impact of such biased stimuli on concurrent cognitive and affective processes in individuals with depression remains inadequately understood. This study aimed to investigate the effects of salient environmental stimuli, specifically emotional faces, on reward-associated processes in MDD. Methods: Thirty-three patients with recurrent MDD and thirty-two healthy controls (HC) matched for age, sex, and education were included in the study. We used a reward-related associative learning (RRAL) task primed with emotional (happy, sad, neutral) faces to investigate the effect of salient stimuli on reward-related learning and decision-making in functional magnetic resonance imaging (fMRI). Participants were instructed to ignore emotional faces during the task. The fMRI data were analyzed using a full-factorial general linear model (GLM) in Statistical Parametric Mapping (SPM12). Results: In depressed patients, cues primed with sad faces were associated with reduced amygdala activation. However, both HC and MDD group exhibited reduced ventral striatal activity while learning reward-related cues and receiving rewards. Limitations: The patients'medication usage was not standardized. Conclusions: This study underscores the functional alteration of the amygdala in response to cognitive tasks presented with negative emotionally salient stimuli in the environment of MDD patients. The observed alterations in amygdala activity suggest potential interconnected effects with other regions of the prefrontal cortex. Understanding the intricate neural connections and their disruptions in depression is crucial for unraveling the complex pathophysiology of the disorder. © 2024 Elsevier B.V.
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    Article
    Citation - WoS: 40
    Citation - Scopus: 70
    Perspectives on the Gap Between the Software Industry and the Software Engineering Education
    (IEEE-Inst Electrical Electronics Engineers Inc, 2019) Oguz, Damla; Oguz, Kaya
    The gap between the software industry and software engineering education was first mentioned three decades ago, in 1989. Since then, its existence has been regularly reported on and solutions to close it have been proposed. However, after thirty years this gap resists all efforts for closure. In this study we assert that the gap between industry and academia exists for several reasons that are related and intertwined. To take a broader look at the problem from the perspective of all related entities, we (i) provide a detailed overview of the profession and identify the entities, (ii) extract the causes that stem from these entities and discuss what each entity should do, (iii) report and analyze the results of a questionnaire that has been conducted with students and recent graduates, (iv) emphasize the highlights of the interviews conducted with students, recent graduates and academics, (v) and compile a list of skills that are sought by the industry by analyzing the software engineering job advertisements. We further contribute to finding solutions by considering all entities involved, which provides an opportunity to access all of them, so that each can find out what they can do to acknowledge and narrow the gap. Our study concludes that the gap requires constant attention and hard work for all of the entities involved, and therefore all should be on the lookout for new technologies, learn to embrace the changes and adapt to them, so that the gap is kept at a minimum.
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    Article
    Estimating the Difficulty of Tartarus Instances
    (Pamukkale Univ, 2021) Oguz, Kaya
    Tartarus is a commonly used benchmark problem for genetic programming. However, it has never been fully explored for its difficulty tuning property. Using the data from a previous study in which we have executed millions of Tartarus instances, we contribute to the literature with an equation to estimate their difficulty. Our approach uses four metrics that are embedded into the equation. These metrics are related to the number of clusters and clusters sizes, the distances of boxes to the edges of the board grid, the number of boxes around the agent, and the minimum number of actions for the agent to reach the largest cluster. The coefficients of these metrics have been fit to the data using the general linear model and a mean residual error of similar to 0.1 has been achieved. This is the first study that can estimate the difficulty of a Tartarus board without modifying the problem in any way.
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    Conference Object
    Citation - Scopus: 1
    Detection and Evaluation of Activation Instances as Change Points in Functional Mr Images
    (Institute of Electrical and Electronics Engineers Inc., 2018) Candemir C.; Oguz K.; Korukoglu S.; Gonul A.S.
    Change point analysis is an efficient method for understanding the unexpected behavior of the data used in many different disciplines including medical imaging. It is important to find the instances the activations occur as much as finding the activation areas in the analysis of functional magnetic resonance imaging (fMRI). Change point detection algorithms can be used to find the activation instances. In this study, a regression based point detection method is proposed to find the activation instances in fMRI experiments. The proposed method is applied to a fMRI experiment which includes a motor task. A linear based evaluation method is also proposed. The analyses show that the activations are in accordance with the established methods in the literature. © 2018 IEEE.
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    Article
    Citation - Scopus: 2
    A Comparison of Neural Networks for Real-Time Emotion Recognition From Speech Signals
    (2009) Ünlütürk, Mehmet Süleyman; Oguz K.; Atay C.
    Speech and emotion recognition improve the quality of human computer interaction and allow easier to use interfaces for every level of user in software applications. In this study, we have developed two different neural networks called emotion recognition neural network (ERNN) and Gram-Charlier emotion recognition neural network (GERNN) to classify the voice signals for emotion recognition. The ERNN has 128 input nodes, 20 hidden neurons, and three summing output nodes. A set of 97920 training sets is used to train the ERNN. A new set of 24480 testing sets is utilized to test the ERNN performance. The samples tested for voice recognition are acquired from the movies " Anger Management" and " Pick of Destiny" . ERNN achieves an average recognition performance of 100%. This high level of recognition suggests that the ERNN is a promising method for emotion recognition in computer applications. Furthermore, the GERNN has four input nodes, 20 hidden neurons, and three output nodes. The GERNN achieves an average recognition performance of 33%. This shows us that we cannot use Gram-Charlier coefficients to discriminate emotion signals. In addition, Hinton diagrams were utilized to display the optimality of ERNN weights.
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    Master Thesis
    Application of Agile Software Development Practices in Software Engineering Education
    (İzmir Ekonomi Üniversitesi, 2022) Akkanat, Mert; Oğuz, Kaya
    Çevik yazılım geliştirme uygulamaları, ortaya çıktıklarından beri birçok yazılım şirketinde yaygın olarak kullanılmaktadır. Çevik ilkeler, yüz yüze iletişimin bilgiyi diğer ekip üyelerine iletmenin en iyi yolu olduğunu vurgular. Ancak 2020 yılında ortaya çıkan küresel salgın, uygulamaların yüz yüze yerine online olarak uygulanmasını zorunlu kılmıştır. Bu çalışmanın kapsamı, Çevik yazılım metodolojilerinin yazılım eğitimine etkisini analiz etmektir. Etkiyi analiz etmek için, takım proje ödevi içeren üçüncü sınıf yazılım mühendisliği kursuna Çevik yazılım yöntemleri uygulanmıştır. Dersin 2021-2022 eğitim-öğretim yılı güz döneminde 15 takım oluşturan 59 öğrenci yer aldı. Bu ekiplerden ikisi, Scrum metodolojisine dayalı Çevik uygulamaların uygulanmasına katılmak için gönüllü oldu. Bu tezin amacı, iki ekibi herhangi bir Çevik uygulama uygulamamış ancak spesifikasyon, tasarım, uygulama ve test faaliyetlerinden oluşan temel kurallar içeren süreci takip eden diğer ekiplerle karşılaştırmaktır. Her iki grup arasındaki farklılıklar ile bu çalışma, Çevik uygulamaların üniversite eğitimine uygun olduğunu ortaya koymayı beklemektedir. Aşağıdaki yöntemler iki gönüllü takım üzerinde uygulanmıştır: 1. Sprint planlama toplantıları, 2. Günlük toplantılar, 3. Haftalık toplantılar, 4. Geriye dönük toplantılar 5. Eşli programlama oturumları 6. Kod inceleme oturumları Çevik yazılım geliştirme yöntemlerinin katkılarını izlemek için TPS ve GitHub günlükleri kullanılır. Ayrıca haftalık toplantı notları, ikili programlama takip formları, kod incelemelerine ilişkin yorumlar ve sprint geriye dönük dokümanları Google Drive'da ortak bir dizinde tutulmaktadır. Dönem sonunda hem çevik uygulamalara hem de çevrimiçi performanslarına odaklanan iki anket yapılmıştır ve sonuçlar incelenip Çevik uygulamaların, üniversite eğitiminde uygulanmaya uygun olduğunu göstermektedir.
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    Conference Object
    Design, Execution, and Analysis of Fmri Experiments
    (IEEE, 2019) Oguz, Kaya
    Functional magnetic resonance imaging aims to correlate brain functions with the regions of the brain. To find out the region responsible for a brain function, the brain should be exposed to stimuli related to the function, and the changes in time should be monitored. To acquire images that change over time makes it more complex and difficult to extract deductions from functional images than structural images. To get the design right, it is necessary to ask the right questions, to give the correct stimuli at the right times, and to analyze the obtained data according to the design of the experiment. As a result, the design of the experiment affects the whole process. This paper presents a wide view of the complete process in the design, execution and the analysis of fMRI experiments, along with the related software and hardware requirements, as well as mentioning the challenges involved.
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    Article
    Citation - WoS: 10
    Citation - Scopus: 11
    Prediction of Local Scour Around Bridge Piers Using Hierarchical Clustering and Adaptive Genetic Programming
    (Taylor & Francis Inc, 2022) Oguz, Kaya; Bor Türkben, Aslı; Bor, Aslı
    The physics of local scour around bridge piers is fairly complex because of multiple forces acting on it. Existing empirical formulas cannot cover all scenarios and soft computing methods require ever greater amounts of data to cover all cases with a single formula or a neural network. The approach proposed in this study brings together observations from over 40 studies, grouping similar observations with hierarchical clustering, and using genetic programming with adaptive operators to evolve formulas specific to each cluster to predict the scour depth. The resulting formulas are made available along with a basic web-based user interface that finds the closest cluster for newly presented data and finds the scour depth using the formula for that cluster. All formulas have R-2 scores over 0.8 and have been validated with validation and testing sets to reduce overfitting. When compared to existing empirical formulas, the generated formulas consistently record higher R-2 scores.
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    Conference Object
    Citation - Scopus: 3
    Digital Recognition and Evaluation of the Clock Drawing Test
    (Institute of Electrical and Electronics Engineers Inc., 2018) Oguz K.; Canliturk B.; Kabar C.; Durukan O.; Ozceylan B.
    Dementia affects the lives of millions of people. Digital recognition and evaluation of the Clock Drawing Test that is used for diagnosis will remove subjective manual evaluation and will increase the awareness and early diagnosis. The proposed system evaluates the clocks drawn to the paper and loaded to it by extracting their graphical features. Besides image processing methods, artificial neural networks are used to detect the numbers. The results of the system are in accordance with the manual evaluation for 35 clocks drawn by healthy subjects. © 2018 IEEE.
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    Doctoral Thesis
    Generating Meaningful Interactions Between Non-Playable Game Characters for Adaptive Gameplay
    (İzmir Ekonomi Üniversitesi, 2023) Uludağli, Muhtar Çağkan; Oğuz, Kaya
    Bu tez bilgisayar oyunlarında oyuncu olmayan karakterler (OOK'lar) tarafından kullanılan karar verme yöntemlerini sunar, ve bu tür OOK toplulukları tarafından kullanılacak bir çizge oluşturucu algoritması önerir. Tezde öncelikle oyunlarda OOK'lar için hangi karar verme yöntemlerinin kullanıldığını bulmak için literatür taraması yapılmıştır. Bilgisayar oyunları için kullanılan bu yöntemleri tanımlamakta, literatürdeki karar verme yöntemlerini sunmakta ve ayrıca ayrıntılı bir taksonomi oluşturmaktayız. Literatürü gözden geçirdiğimizde, oyunlarda OOK toplulukları tarafından kullanılabilecek bir sosyal ağ oluşturmanın uygun bir yolu olmadığını gördük. Biz de bu amaçla AnatoliA adında bir çizge oluşturucu yarattık. Tezde, bu algoritma için temel varsayımlarımızı ortaya koyuyor, algoritmamızı sunuyor ve modelimizin ayrıntılı analizini yapıyoruz. Sonuçlarımız, AnatoliA'nın bazı temel ölçümlerde daha önceki bazı çizge oluşturuculardan daha iyi performans verdiğini gösteriyor. Tezimizin son bölümü olarak, algoritmamızın farklı kullanım yollarını da değerlendiriyor ve gelecekteki yapılabilecek iyileştirmeleri tartışıyoruz.