Dalveren, Gonca Gökçe Menekşe

Profile Picture
Profile URL
https://hdl.handle.net/20.500.14411/7994
Name Variants
Gonca Gökçe Menekşe, Dalveren
Dalveren, Gonca Gokce Menekse
G., Dalveren
G.,Dalveren
D.,Gonca Gökçe Menekşe
Gonca Gokce Menekse, Dalveren
Dalveren, Gonca Gökçe Menekşe
G.G.M.Dalveren
D.,Gonca Gokce Menekse
D., Gonca Gokce Menekse
Dalveren,G.G.M.
Job Title
Doktor Öğretim Üyesi
Email Address
gonca.menekse@atilim.edu.tr
Main Affiliation
Information Systems Engineering
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
0
Research Products
QUALITY EDUCATION4
QUALITY EDUCATION
5
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
1
Research Products
DECENT WORK AND ECONOMIC GROWTH8
DECENT WORK AND ECONOMIC GROWTH
0
Research Products
INDUSTRY, INNOVATION AND INFRASTRUCTURE9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
1
Research Products
REDUCED INEQUALITIES10
REDUCED INEQUALITIES
0
Research Products
SUSTAINABLE CITIES AND COMMUNITIES11
SUSTAINABLE CITIES AND COMMUNITIES
0
Research Products
RESPONSIBLE CONSUMPTION AND PRODUCTION12
RESPONSIBLE CONSUMPTION AND PRODUCTION
1
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
3
Research Products
PARTNERSHIPS FOR THE GOALS17
PARTNERSHIPS FOR THE GOALS
0
Research Products
This researcher does not have a Scopus ID.
This researcher does not have a WoS ID.
Scholarly Output

29

Articles

19

Views / Downloads

54/91

Supervised MSc Theses

3

Supervised PhD Theses

1

WoS Citation Count

226

Scopus Citation Count

314

Patents

0

Projects

0

WoS Citations per Publication

7.79

Scopus Citations per Publication

10.83

Open Access Source

15

Supervised Theses

4

JournalCount
IEEE Access5
Sustainability2
2018 International Symposium on Networks, Computers and Communications, ISNCC 2018 -- 2018 International Symposium on Networks, Computers and Communications, ISNCC 2018 -- 19 June 2018 through 21 June 2018 -- Rome -- 1424272
Journal of Eye Movement Research2
Avrupa Bilim ve Teknoloji Dergisi1
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Scholarly Output Search Results

Now showing 1 - 10 of 29
  • Thumbnail Image
    Article
    Citation - WoS: 10
    Citation - Scopus: 20
    Covid-19 and E-Learning: an Exploratory Analysis of Research Topics and Interests in E-Learning During the Pandemic
    (Ieee-inst Electrical Electronics Engineers inc, 2022) Gurcan, Fatih; Dalveren, Gonca Gokce Menekse; Derawi, Mohammad
    E-learning has gained further importance and the amount of e-learning research and applications has increased exponentially during the COVID-19 pandemic. Therefore, it is critical to examine trends and interests in e-learning research and applications during the pandemic period. This paper aims to identify trends and research interests in e-learning articles related to COVID-19 pandemic. Consistent with this aim, a semantic content analysis was conducted on 3562 peer-reviewed journal articles published since the beginning of the COVID-19 pandemic, using the N-gram model and Latent Dirichlet Allocation (LDA) topic modeling approach. Findings of the study revealed the high-frequency bigrams such as "online learn ", "online education ", "online teach " and "distance learn ", as well as trigrams such as "higher education institution ", "emergency remote teach ", "education online learn " and "online teach learn ". Moreover, the LDA topic modeling analysis revealed 42 topics. The topics of "Learning Needs ", "Higher Education " and "Social Impact " respectively were the most focused topics. These topics also revealed concepts, dimensions, methods, tools, technologies, applications, measurement and evaluation models, which are the focal points of e-learning field during the pandemic. The findings of the study are expected to provide insights to researchers and future studies.
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    Conference Object
    Citation - WoS: 6
    Citation - Scopus: 8
    Simulation-Based Environments for Surgical Practice
    (Institute of Electrical and Electronics Engineers Inc., 2017) Dalveren,G.G.M.; Çağıltay,N.E.; Özçelik,E.; Maraş,H.
    Modeling and simulation environments provide several insights about the real situations such as endoscopic surgery. Endoscopic surgery requires both hand skills, so, understanding the effect of using dominant or non dominant hand on mental workload is important to better design, develop and implement modeling and simulation environments to support real-life implementations of surgical procedures. This experimental study presents a simulation application of eye-tracking approach to understand mental workload in different hand conditions: dominant hand, non-dominant hand and both hand. The results of the study show that, performing simulated surgical tasks by both hands compared to dominant hand, increases mental workload which is evident by higher pupil size. Accordingly, to manage the mental-load problems of surgeons while performing complex tasks that require both hand usage simulation-based environments can be used. Consequently, collection of detailed information such as eye-data, can give several insights about the behaviors of the surgeons. Also, their required skills can be improved by development of simulation and training environments. © 2017 IEEE.
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    Article
    4b Fmrı Tabanlı Alzheimer Hastalığının Ön Tespiti için 3b-capsnet ve Rnn Modellerinin Kullanılması
    (2024) İsmail, Ali; Dalveren, Gonca Gökçe Menekşe
    Alzheimer hastalığının (AH) ilerlemesinin erken tahmini, bilişsel gerilemenin daha etkili bir şekilde yavaşlatılmasına yardımcı olabilmektedir. Dinlenme durumu fonksiyonel manyetik rezonans görüntüleme (dd-fMRG) kullanılarak otomatik AH tanısı için evrişimli sinir ağlarına (ESA) dayalı farklı yöntemlerin uygulanmasına yönelik çeşitli çalışmalar yapılmıştır. Bu çalışmalarda tanıtılan yöntemler iki büyük zorlukla karşılaşmaktadır. Birincisi, fMRG veri kümeleri küçük boyutta olduğundan aşırı uyum gözlemlenebilmektedir. İkincisi, fMRG oturumlarının 4 boyutlu (4B) bilgilerinin verimli bir şekilde modellenmesi gerekmektedir. Çalışmalardan bazıları, derin öğrenme yöntemlerini, 4B bilgiyi modellemek için fMRG verilerinden oluşturulan fonksiyonel bağlantı matrislerine veya ayrı 2B dilimler veya 3B hacimler olarak fMRG verilerine uygulamıştır. Ancak bu durumun her iki yöntem türünde de bilgi kaybına neden olduğu gözlemlenmiştir. Bu çalışmada, AD tanısı için fMRG verilerinin uzay-zamansal (4B) bilgilerini modellemek amacıyla Kapsül ağı (CapsNet) ve tekrarlayan sinir ağını (RNN) temel alan yeni bir model önerilmektedir. Önerilen modelin etkinliğini değerlendirmek için deneyler yapılmıştır. Sonuçlara göre, önerilen modelin AH’na karşı normal kontrol (NK) ve geç hafif bilişsel bozukluk (GHBB) ile erken hafif bilişsel bozukluk (EHBB) sınıflandırma görevlerinde sırasıyla %94.5 ve %61.8 doğruluk elde edebildiği görülmüştür.
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    Master Thesis
    4d Fmri'ye Dayalı Alzheimer Hastalığı Tespiti İçın 3d-capsnet ve Rnn Kullanımı
    (2023) Ismaıl, Alı Mohamed Kotb Mohamed Ismaıl Alı Mohamed Kotb Mohamed; Dalveren, Gonca Gökçe Menekşe
    AD ilerlemesinin erken tahmin edilmesi, bilişsel gerilemeyi daha etkili bir şekilde yavaşlatmaya yardımcı olabilir. Dinlenme durumu fonksiyonel manyetik rezonans görüntüleme (rs-fMRI) kullanılarak otomatik AD teşhisi için evrişimli sinir ağlarına (CNN'ler) dayalı farklı yöntemlerin uygulanmasına yönelik birkaç çalışma yapılmıştır. Bu çalışmalarda tanıtılan yöntemler 2 büyük zorlukla karşılaşmaktadır. Bu zorluklardan ilki, overfitting ile sonuçlanan küçük boyutlu fMRI veri kümeleridir. İkincisi ise, fMRI verilerinin 4D bilgilerinin verimli bir şekilde modellenmesinin gerekmekte olduğudur. Bazı araştırmalar, 4D bilgilerini modellemek için fMRI verilerinden oluşturulan fonksiyonel bağlantı (FC) matrislerine derin öğrenme yöntemleri uygulamaktadır. Diğerleri ise değerli bilgi kaybına neden olan ayrı 2D dilimler veya 3D hacimler olarak fMRI verilerine uygulamaktadır. Bu çalışmada, AD teşhisi için fMRI verilerinin uzay-zamansal (4D) bilgilerini modellemek için CapsNet-RNN tanıtılmaktadır. Modelde, bir fMRI zaman serisinin hacimlerinden uzamsal özellikleri çıkarmak için, özellikle küçük boyutlu veri kümelerinde overfitting sorununu hafifletmek için geleneksel CNN'lerin bir modifikasyonu olan Kapsül Ağı (CapsNet) kullanılmaktadır. Uzamsal özellikler daha sonra zaman serisi boyunca zamansal ilişkileri modellemek için RNN ile kullanılmaktadır. RNN'ler. Modelimiz AD - NC ve lMCI - eMCI sınıflandırma görevleri için sırasıyla %86,5 ve %61,8 doğruluk elde edebilmiştir.
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    Conference Object
    Citation - WoS: 6
    Simulation-Based Environments for Surgical Practice
    (Ieee, 2017) Dalveren, Gonca Gokce Menekse; Cagiltay, Nergiz Ercil; Ozcelik, Erol; Maras, Hakan
    Modeling and simulation environments provide several insights about the real situations such as endoscopic surgery. Endoscopic surgery requires both hand skills, so, understanding the effect of using dominant or non dominant hand on mental workload is important to better design, develop and implement modeling and simulation environments to support real-life implementations of surgical procedures. This experimental study presents a simulation application of eye-tracking approach to understand mental workload in different hand conditions: dominant hand, non-dominant hand and both hand. The results of the study show that, performing simulated surgical tasks by both hands compared to dominant hand, increases mental workload which is evident by higher pupil size. Accordingly, to manage the mental-load problems of surgeons while performing complex tasks that require both hand usage simulation-based environments can be used. Consequently, collection of detailed information such as eye-data, can give several insights about the behaviors of the surgeons. Also, their required skills can be improved by development of simulation and training environments.
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    Article
    Usability Assessment of Scholarly Publishers' Online Journal Interfaces
    (Springernature, 2023) Peker, Serhat; Dalveren, Gonca Gokce Menekse
    A well-designed and user-friendly online journal interface not only enhances researchers' satisfaction but also bolsters the reputation of academic publishers within the scholarly community. Consequently, the present study undertakes an examination of the usability aspects pertaining to online journal interfaces offered by five prominent academic publishers: Wiley, Sage, Elsevier, Springer, and Taylor & Francis. This investigation encompasses a combination of user testing and post-questionnaire methodologies, aiming to accrue both quantitative and qualitative data concerning user task execution and satisfaction. The research findings spotlight the varying degrees of usability across major academic publishers and emphasize the critical role of design in enhancing researchers' experiences. By identifying both usability strengths and weaknesses, along with offering actionable areas for improvement, this study adds a valuable perspective to the enhancement of academic journal interfaces.
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    Article
    Citation - WoS: 8
    Citation - Scopus: 10
    Evaluation of Ten Open-Source Eye-Movement Classification Algorithms in Simulated Surgical Scenarios
    (Ieee-inst Electrical Electronics Engineers inc, 2019) Dalveren, Gonca Gokce Menekse; Cagiltay, Nergiz Ercil
    Despite providing several insights into visual attention and evidence regarding certain brain states and psychological functions, classifying eye movements is a highly demanding process. Currently, there are several algorithms to classify eye movement events which use different approaches. However, to date, only a limited number of studies have assessed these algorithms under specific conditions, such as those required for surgical training programmes. This study presents an investigation of ten open-source eye-movement classification algorithms using the Eye Tribe eye-tracker. The algorithms were tested on the eye-movement records obtained from 23 surgical residents, who performed computer-based surgical simulation tasks under different hand conditions. The aim was to offer data for the improvement of surgical training programmes. According to the results, due to the different classification methods and default threshold values, the ten algorithms produced different results. Considering the fixation duration, the only common event for all of the investigated algorithms, the binocular-individual threshold (BIT) algorithm resulted in a different clustering compared to the other algorithms. Based on the other set of common events, three clusters were determined by eight algorithms (except BIT and event detection (ED)), distinguishing dispersion-based, velocity-based and modified versions of velocity-based algorithms. Accordingly, it was concluded that dispersion-based and velocity-based algorithms provided different results. Additionally, as it individually specifies the threshold values for the eye-movement data, when there is no consensus about the threshold values to be set, the BIT algorithm can be selected. Especially for such cases like simulation-based surgical skill-training, the use of individualised threshold values in the BIT algorithm can be more beneficial in classifying the raw eye data and thus evaluating the individual progress levels of trainees based on their eye movement behaviours. In conclusion, the threshold values had a critical effect on the algorithm results. Since default values may not always be suitable for the unique features of different data sets, guidelines should be developed to indicate how the threshold values are set for each algorithm.
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    Article
    Citation - WoS: 21
    Citation - Scopus: 26
    Detecting Latent Topics and Trends in Software Engineering Research Since 1980 Using Probabilistic Topic Modeling
    (Ieee-inst Electrical Electronics Engineers inc, 2022) Gurcan, Fatih; Dalveren, Gonca Gokce Menekse; Cagiltay, Nergiz Ercil; Soylu, Ahmet
    The landscape of software engineering research has changed significantly from one year to the next in line with industrial needs and trends. Therefore, today's research literature on software engineering has a rich and multidisciplinary content that includes a large number of studies; however, not many of them demonstrate a holistic view of the field. From this perspective, this study aimed to reveal a holistic view that reflects topics, trends, and trajectories in software engineering research by analyzing the majority of domain-specific articles published over the last 40 years. This study first presents an objective and systematic method for corpus creation through major publication sources in the field. A corpus was then created using this method, which includes 44 domain-specific conferences and journals and 57,174 articles published between 1980 and 2019. Next, this corpus was analyzed using an automated text-mining methodology based on a probabilistic topic-modeling approach. As a result of this analysis, 24 main topics were found. In addition, topical trends in the field were revealed. Finally, three main developmental stages of the field were identified as: the programming age, the software development age, and the software optimization age.
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    Article
    Citation - WoS: 9
    Citation - Scopus: 7
    The Underlying Reasons of the Navigation Control Effect on Performance in a Virtual Reality Endoscopic Surgery Training Simulator
    (Taylor & Francis inc, 2019) Cagiltay, Nergiz Ercil; Ozcelik, Erol; Berker, Mustafa; Dalveren, Gonca Gokce Menekse; Menekse Dalveren, Gonca Gokce
    Navigation control skills of surgeons become very critical for surgical procedures. Strategies improving these skills are important for developing higher-quality surgical training programs. In this study, the underlying reasons of the navigation control effect on performance in a virtual reality-based navigation environment are evaluated. The participants' performance is measured in conditions: navigation control display and paper-map display. Performance measures were collected from 45 beginners and experienced residents. The results suggest that navigation display significantly improved performance of the participants. Also, navigation was more beneficial for beginners than experienced participants. The underlying reason of the better performance in the navigation condition was due to lower number of looks to the map, which causes attention shifts between information sources. Accordingly, specific training scenarios and user interfaces can be developed to improve the navigation skills of the beginners considering some strategies to lower their number of references to the information sources.
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    Article
    Citation - WoS: 28
    Citation - Scopus: 45
    Digital Transformation Strategies, Practices, and Trends: a Large-Scale Retrospective Study Based on Machine Learning
    (Mdpi, 2023) Gurcan, Fatih; Boztas, Gizem Dilan; Dalveren, Gonca Gokce Menekse; Derawi, Mohammad
    The purpose of this research is to identify the areas of interest, research topics, and application areas that reflect the research nature of digital transformation (DT), as well as the strategies, practices, and trends of DT. To accomplish this, the Latent Dirichlet allocation algorithm, a probabilistic topic modeling technique, was applied to 5350 peer-reviewed journal articles on DT published in the last ten years, from 2013 to 2022. The analysis resulted in the discovery of 34 topics. These topics were classified, and a systematic taxonomy for DT was presented, including four sub-categories: implementation, technology, process, and human. As a result of time-based trend analysis, "Sustainable Energy", "DT in Health", "E-Government", "DT in Education", and "Supply Chain" emerged as top topics with an increasing trend. Our findings indicate that research interests are focused on specific applications of digital transformation in industrial and public settings. Based on our findings, we anticipate that the next phase of DT research and practice will concentrate on specific DT applications in government, health, education, and economics. "Sustainable Energy" and "Supply Chain" have been identified as the most prominent topics in current DT processes and applications. This study can help researchers and practitioners in the field by providing insights and implications about the evolution and applications of DT. Our findings are intended to serve as a guide for DT in understanding current research gaps and potential future research topics.