Lisansüstü Eğitim Enstitüsü Diğer Yayınlar Koleksiyonu

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API güvenlik testi araçlarının karşılaştırmalı analizi: özellikler, yetenekler ve performans değerlendirmesi
(BIDGE Publications, 2023-05-24) Çarkçıoğlu, Onur; Çeliktaş, Barış; Çoğun, Hikmet Yeter; Parlar, İshak; Üzmuş, Hasan
Uygulama programlama arayüzleri (API'ler), diğer uygulamalar arasındaki iletişimi kolaylaştıran bileşenlerdir. API'ler, modern web uygulamalarının ayrılmaz bir parçasıdır ve uygulamaların birbirleriyle iletişim kurması ve veri alışverişi yapması için bir araç sağlar. Web uygulamaları ve kullandıkları API'ler, kötü niyetli bilgisayar korsanları için hem çekici hem de kolay erişilebilir hedeflerdir. Bu nedenle, bu uygulamanın güvenliğini sağlamak ve verilerin bütünlüğünü ve gizliliğini korumak çok önemlidir. API servisleri, kullanılabilecek birçok araç için güvenlik testlerine sahiptir. Bu uygulamalardan bazıları ücretsiz olarak kullanılabilen açık kaynak kodlu projelerken, bazıları ise güvenlik odaklı firmaların sunduğu ticari çözümlerdir. Bu bölümde, Postman, Burp Suite, OWASP ZAP, JSON Web Token Toolkit, Security Code Scan, araştırma sırasında kullanılan araçlardan ve bu çalışma sırasında gerçekleştirilen testlerden bazılarıdır. API servislerinin güvenlik testi için kullanılabilecek birçok araç bulunmaktadır. Bu uygulamalardan bazıları ücretsiz olarak kullanılabilen açık kaynak kodlu projelerken bazıları da güvenlik odaklı kuruluşların sunduğu ticari çözümlerdir. Bu bölümde, araştırma sırasında kullanılan araçların detaylı analizleri ve testleri yapılacak olup API testleri açısından avantajlı ve dezavantajları yanları ortaya konnacaktır. Böylece daha güvenli Web uygulamaları ve API geliştirme süreçlerine olumlu katkı sağlanması amaçlanmıştır.
Comparative analysis of supervised, unsupervised, semi-supervised, and reinforcement learning methods for data loss prevention
(BIDGE Publications, 2023-05-24) Vural, Ahmet; Çeliktaş, Barış; Çoğun, Hikmet Yeter; Parlar, İshak; Üzmuş, Hasan
Veri Kaybını Önleme (DLP), veri kaybını, hassas verilerin güvenli olmayan veya uygun olmayan bir şekilde paylaşılmasını, transferini veya kullanılmasını engelleyen bir güvenlik çözümüdür. DLP ayrıca Genel Veri Koruma Yönetmeliği (GDPR) ve diğer düzenleyici gereklilikler gibi düzenlemelere uyum sağlamamıza yardımcı olmaktadır. DLP'nin temel amacı hassas verilerin sızmasını önlemek ve böylece veri sahiplerinin itibarlarını korumak, maliyetleri azaltmak ve iş sürekliliğini sağlamaktır. DLP, veri sızmasını engellemek veya önceden belirlenmiş veri sınıflandırma politikaları kullanarak olayları kaydetmek için bir dizi kural kullanan bir uygulamadır. Bu etiketler genellikle bir program tarafından tanımlanan bilgilere dayalı olarak oluşturmakta ve uygulamaktadır. Bu çalışmamız, DLP sistemlerinde denetimli, denetimsiz, yarı denetimli ve takviyeli öğrenme yöntemlerinin kullanımına odaklanmakta olup, veri sınıflandırması için makine öğrenme algoritmaları aracılığıyla verilerin işlenmesi ve kullanılmasıyla veri ihlallerini ve ihlallerini en aza indirmeyi amaçlamaktadır. Çalışmamızda, makine öğrenme yöntemlerinin yeteneklerine dayalı olarak en uygun seçenekler değerlendirilecektir. Çalışmanın bulguları, denetimli öğrenme yöntemlerinin karşılaştırmalı analizinin DLP için en etkili yaklaşım olduğunu önermektedir, ancak yarı denetimli ve güçlendirme öğrenme yöntemleri sınırlı etiketli veri olduğunda kullanışlı olabilmektedir. Çalışma ayrıca makine öğrenme algoritmaları kullanarak otomatik olarak DLP prensiplerinin oluşturulmasının faydalarını içermektedir. El ile hazırlanan sınıflandırmaların otomatikleştirilmesiyle, sistemin daha verimli olması ve yanlış pozitif değerlerin en aza indirilmesi beklenmektedir. Özetle, bu çalışma kullanıcıların veri işleme standartları veya alışkanlıklarını makine öğrenmeyle birleştirerek bu etiketlerin ve verilerin DLP kurallarında kullanılmasını mümkün kılmaktadır. El ile yapılan manuel sınıflandırma, makine öğrenme ile otomatikleştirilebilir, bu da daha iyi kontrollerin yapılmasına olanak sağlamaktadır. Makine öğrenme ve DLP aynı anda kullanıldığında, veri sınıflandırması hatalı olmadan gerçekleştirilecek ve yanlış pozitif alarm sayısı azalacaktır. Dosyaların yapısı ve içeriği kullanıcı alışkanlıklarına göre doğru bir şekilde belirlenecek, ilgili kuralların doğruluğu ve güvenilirliği sağlanacaktır. Kullanıcılar belirli algoritmalar aracılığıyla izlenecek, dosya içeriğinde en sık kullanılan veriler raporlanabilecek ve bunun şirket riski olarak kabul edilebilir olup olmadığı belirlenebilecektir. Sonuç olarak, kurum ve kuruluşlar, veri koruma politikalarını daha verimli ve kullanılabilir hale getirebilecek ve veri kaybı riskini azaltabilecek ve düzenlemelere tabi kişisel verileri kontrol altına alabilecektir.
Self-supervised learning of 3D structure from 2D OCT slices for retinal disease diagnosis on UK biobank scans
(Institute of Electrical and Electronics Engineers Inc., 2025-09-21) Nazlı, Muhammet Serdar; Turkan, Yasemin; Tek, Faik Boray
This study presents a self-supervised learning framework for retinal disease classification using Optical Coherence Tomography (OCT) scans. To balance the contextual richness of 3D volumes with the computational efficiency of 2D architectures, we introduce a quasi-3D input generation strategy. Each input is constructed by stacking three OCT slices, sampled from channel-specific Gaussian distributions centered on the volume midplane, and arranged in a standard three-channel 2D format compatible with existing pre-trained models. These quasi-3D images are used to pre-train a Vision Transformer (ViT-Base) via a Masked Autoencoder (MAE) with a shared masking pattern, encouraging the model to reconstruct masked regions by encoding anatomical continuity across slices. Pre-training is conducted on 10,000 unlabeled OCT volumes from the UK Biobank. The encoder is then fine-tuned on the OCTA-500 dataset for three-class and four-class retinal disease classification tasks, including macular degeneration and diabetic retinopathy. The model achieves 92.57% accuracy on the three-class task, matching the performance of RETFound while using over 150 times less pre-training data and a smaller backbone.
Retinal disease classification from bimodal OCT and OCTA using a CNN-ViT hybrid architecture
(Institute of Electrical and Electronics Engineers Inc., 2025-09-21) Aydın, Ömer Faruk; Tek, Faik Boray; Turkan, Yasemin
Retinal diseases are the leading cause of vision impairment and blindness worldwide. Early and accurate diagnosis is critical for effective treatment, and recent advances in imaging technologies such as Optical Coherence Tomography (OCT) and OCT Angiography (OCTA), have enabled detailed visualization of the retinal structure and vasculature. By leveraging these modalities, this study proposes an advanced deep learning architecture called MultiModalNet for automated multi-class retinal disease classification. MultiModalNet employs a dual-branch design, where OCTA projection maps are processed through a ResNet101 encoder, and cross-sectional slices from the OCT volume (B-scans) are analyzed using a Vision Transformer (ViT-Large). The extracted features from both branches were fused and passed through the fully connected layers for the final classification. Evaluated on the 3-class OCTA-500 dataset, which includes Age-related Macular Degeneration (AMD), Diabetic Retinopathy (DR), and Normal cases, the proposed model achieved state-of-the-art classification accuracy of 94.59 percent, significantly o utperforming single-modality baselines. This result highlights the effectiveness of integrating vascular and structural information to improve the diagnostic performance. The findings suggest that hybrid multi-modal deep learning approaches can play a transformative role in computer-aided ophthalmology, enhancing both clinical decision-making and screening workflows.
Secure and interpretable dyslexia detection using homomorphic encryption and SHAP-based explanations
(Institute of Electrical and Electronics Engineers Inc., 2025-10-25) Harb, Mhd Raja Abou; Çeliktaş, Barış; Eroğlu, Günet
Protecting sensitive healthcare data during machine learning inference is critical, particularly in cloud-based environments. This study addresses the privacy and interpretability challenges in dyslexia detection using Quantitative EEG (QEEG) data. We propose a privacy-preserving framework utilizing Homomorphic Encryption (HE) to securely perform inference with an Artificial Neural Network (ANN). Due to the incompatibility of non-linear activation functions with encrypted arithmetic, we employ a dedicated approximation strategy. To ensure model interpretability without compromising privacy, SHapley Additive exPlanations (SHAP) are computed homomorphically and decrypted client-side. Experimental evaluations demonstrate that the encrypted inference achieves an accuracy of 90.03% and an AUC of 0.8218, reflecting only minor performance degradation compared to plaintext inference. SHAP value comparisons (Spearman correlation = 0.59) validate the reliability of the encrypted explanations. These results confirm that integrating privacy-preserving and explainable AI approaches is feasible for secure, ethical, and compliant healthcare deployments.
Privacy-preserving cyber threat intelligence: a framework combining private information retrieval, federated learning, and differential privacy
(Institute of Electrical and Electronics Engineers Inc., 2025-09-21) Çamalan, Emre; Çeliktaş, Barış
Threat Intelligence Platforms (TIPs) are essential for sharing indicators of compromise (IoCs), but querying them can leak sensitive organizational data. We propose a privacy-preserving framework that combines Private Information Retrieval (PIR), Federated Learning (FL), and Differential Privacy (DP) to mitigate this risk. Our approach addresses both content-level and metadata-level privacy concerns while supporting collaborative learning across organizations. It ensures that sensitive query patterns remain hidden, local threat data never leaves organizational boundaries, and model updates are protected against inference attacks. The framework integrates with existing TIPs such as MISP and OpenCTI, requiring minimal operational changes. We implement a prototype using a simulated Abuse IP dataset and evaluate it on latency, accuracy, and communication overhead. The system supports private queries in under 300 ms and maintains over 95% model accuracy under DP noise. These results indicate that strong privacy can be achieved with minimal performance trade-offs, making the approach viable for real-world CTI environments.
Cross-layer ransomware detection framework for SDN using HMM, LSTM, and Bayesian inference
(Institute of Electrical and Electronics Engineers Inc., 2025-08-28) Serter, Cemal Emre; Çeliktaş, Barış
Ransomware continues to pose a serious threat to endpoint computers as well as network systems, especially in Software Defined Networks (SDN) environments where programmability and centralized control offer novel attack surfaces. In this paper, a cross-layer detection model for ransomware is introduced that integrates host-based behavioral modeling using Hidden Markov Models (HMM), anomaly detection at flow level using Long Short-Term Memory (LSTM) networks, and probabilistic fusion through Bayesian inference. By correlating host and SDN layer anomalies, the system enhances early-stage detection and reduces false positives. A variational Bayesian approximation technique is utilized for decision score stabilization under ambiguous conditions. The model is evaluated with new ransomware datasets and obtains a range between 97.5%-99.92% F1-score across three benchmark datasets with less than 50 ms latency for detection. The hybrid framework gives a promising direction for real-time threat detection in resilient programmable networks.
A multi-criteria evaluation of cybersecurity incident management frameworks: integrating AHP, CMMI and SWOT
(Karyay Karadeniz Yayımcılık Ve Organizasyon Ticaret Limited Şirketi, 2026-01-15) Ağar, Hasan Çağlar; Çeliktaş, Barış
With the growing complexity and frequency of cybersecurity incidents, the selection of an appropriate incident management framework has emerged as a strategic imperative and a nontrivial decision-making problem for organizations operating across diverse sectors. This study presents a multi-dimensional evaluation of four globally recognized frameworks and standards—ISO 27035, NIST 800-61, ITIL v4, and PCI DSS—to determine their effectiveness across 10 rigorously selected key performance parameters. The initial stage of the study involved the identification of 20 preliminary parameters through expert input and literature synthesis. These were then evaluated by 70 cybersecurity professionals using a hybrid decision-making model combining Likert scale scoring, standard deviation filtering, CV score, Z-score normalization and the Analytic Hierarchy Process (AHP) for pairwise comparisons. The top 10 key parameters were derived based on calculated priority weights. To assess each framework, we applied the Capability Maturity Model Integration (CMMI) and visualized results via radar charts and heatmaps, offering comparative insights into operational maturity. Additionally, SWOT analysis was conducted to examine strategic positioning and identify opportunities for improvement. The outcomes not only provide a practical benchmarking guide for practitioners but also introduce a replicable, evidence-based methodology for academic and industry adoption. This work offers a novel and structured lens to evaluate incident management maturity, addressing the pressing need for strategic alignment, automation integration, and adaptive resilience in cybersecurity operations.
Psychometric properties of the emotional self-efficacy and prosocial behavior scales among Nigerian youths: a cross-cultural validation study
(Genç Bilge Yayıncılık, 2026-01-06) Akaiso, Emmanuel
This study examined the psychometric properties of the Emotional Self-Efficacy and Prosocial Behavior scales, originally developed in Italy, among Nigerian youths residing in urban and semi-urban contexts. A total of 108 participants completed measures assessing empathic ability, problem-solving, and interpersonal communication, alongside the Prosocial Tendencies Measure, which captures helping behaviors across anonymous, public, and emotionally salient situations. The findings demonstrated acceptable internal consistency across all scales, indicating satisfactory reliability within this cultural context. Descriptive analyses showed generally low levels of empathic and problem-solving selfefficacy, while interpersonal communication self-efficacy ranged from low to high. Correlational analyses revealed that empathic, problem-solving, and interpersonal communication self-efficacy were positively associated with prosocial behaviors, particularly in emotionally demanding contexts. Additionally, empathic and problemsolving self-efficacy were positively related to public prosocial actions. Overall, the findings provide preliminary evidence supporting the cross-cultural applicability of these instruments among Nigerian youths and highlight culturally relevant patterns in selfefficacy and prosocial functioning. The study contributes to the limited literature on psychological resources and prosocial development in Sub-Saharan Africa. Future research should employ larger and more diverse samples and explore the roles of resilience, personality traits, and value orientations in shaping prosocial behavior.
The mediating effect of self compassion in the relationship between job stress and burnout levels among employees
(SAGE Publications Inc., 2026-02-13) Günay, Ezgi; Ünver, Buket; Yılmaz, Simay
Objective: This study investigates the role of self-compassion as a mediator in the relationship between job stress and burnout among employees. While job stress is widely recognized as a critical factor leading to burnout, it has been suggested that self-compassion may be associated with a reduction in these negative effects. Method: Participants were 429 actively employed adults living in Turkey (50.6% female). The data were gathered using an online administration of standardized psychological scales, that is, Job Stressor Appraisal Scale, Copenhagen Burnout Scale, and Self-Compassion Scale. Four dimensions of work stress “Role and Workload, Role Inadequacy, Organizational Rules & Practices, and Subordinate Relations” are taken into consideration in the volumetric model. Path analysis with bootstrapping (5,000 resamples) was implemented using Mplus statistical software, with gender, economic condition, and way of working during COVID-19 as covariates. Findings: The model fit was acceptable in path analysis. Role and workload and role inadequacy had a significant direct impact on burnout. Self-compassion had a significant mediating impact on the relationship between role and workload and burnout and the relationship between role inadequacy and burnout. Conversely, for organizational rules and practices and subordinate relations, both direct and mediating effects were non-significant. The model accounted for 21% and 52% for variance in self-compassion and burnout, respectively. Conclusion: This study emphasises the mediating role of self-compassion in the effect of job stressors on burnout. These findings suggest that interventions promoting self-compassion in the workplace may be effective in reducing employee burnout.
Witnessing the end, supporting the living: A qualitative study of palliative caregiving in end-of-life patients in Türkiye
(Cambridge University Press, 2026-02-11) Sert Yurdakul, Selin; Erbay Erşen, Merve; Özel, Dilara
Objectives. Palliative care seeks to enhance the quality of life for individuals with serious illnesses and their families by addressing physical, emotional, and psychological needs. This phenomenological study examines the lived experiences of 8 caregivers in palliative care settings in Türkiye, focusing on the challenges they face, the coping mechanisms they employ, and their reflections on the caregiving role. Special emphasis is given to both psychological and somatic signs of stress, along with the possible advantages of body-oriented resilience techniques. Methods. Using a phenomenological qualitative design, semi-structured interviews were conducted with 8 caregivers providing care to relatives in a hospital-based palliative care unit. Data were collected between February and April 2023 and analyzed through conventional content analysis. Results. Four central themes emerged from inductive coding: harmony in healing, navigating difficulties, resilience in palliative care, and reflections on the finite. The findings reveal a dual reality: palliative caregivers derive meaning and satisfaction from compassionate connections, high-quality clinical care, and peer support, yet they also endure significant burdens, including emotional strain, physical exhaustion, disrupted daily routines, and shifting relational dynamics. Anticipatory grief and chronic stress responses were prevalent, frequently manifesting in both psychological and somatic forms (e.g., sleep disturbances, muscle tension, and autonomic arousal). Despite these challenges, palliative caregivers employed spiritual beliefs, peer interactions, and self-care routines as resilience strategies. Significance of results. The mind–body challenges identified in the study emphasize the need for interventions that focus on self-regulation and resilience, including body-oriented approaches that strengthen internal resources, regulate stress responses, and encourage adaptability. Incorporating such approaches into group-based settings may improve mutual support and enhance both individual and relational well-being. The study highlights the importance of comprehensive, caregiver-centered support systems to reduce burden and improve the overall quality of palliative care.
Bireylerin Covid-19’a dair tükenmişliklerinin algıladıkları Covid-19 riski, dünyaya ilişkin varsayımları ve ebeveyn biçimleri ile ilişkisi
(Türk Psikologlar Derneği, 2023-07-26) Erdem, Büşra; Ünver, Buket
Dünyaya İlişkin Varsayımları Ve Ebeveyn Biçimleri İle İlişkisi Tükenmişlik kavramı özellikle endüstri ve sağlık psikolojisi çatısı altında yer almakla birlikte Covid-19 pandemisi ile birlikte tükenmişlik ve salgın hastalıklar arasındaki ilişki klinik literatürde de dikkat çekmeye başlamıştır. Mevcut çalışma kapsamında bireylerin kitlesel bir dış faktör karşısında (Covid-19 pandemisi), süreç içerisinde yaşayacakları tükenmişlikleri ile olaya dönük algıladıkları risk, anlamsal dünyaları ve algılanan ebeveynlik biçimlerinin ilişkisini araştırmanın, olası pandemiler ya da paylaşılan toplumsal olaylar karşısında yaşanabilecek tükenmişlik olgusuna ve komorbidite tanıların ayrımına dair bütüncül bir bakış açısı sunması beklenmektedir. Bu doğrultuda gerçekleştirilen mevcut çalışmanın temel amacı bireylerin Covid-19’a dair tükenmişlikleri ile algıladıkları Covid-19 riski, dünyaya ilişkin varsayımları (DİV) ve algılanan ebeveynlik biçimlerinin ilişkisinin incelenmesidir. Aynı zamanda, sosyodemografik değişkenler ve Covid-19’a dair değişkenlerin Covid-19 tükenmişliği üzerindeki etkilerinin incelenmesi de araştırmanın diğer amacını oluşturmaktadır. Bu doğrultuda gerçekleştirilen çalışmanın örneklem grubunu 18-65 yaş aralığında yer alan 368 katılımcı (yaş ort. 33.85, SS=9.75; %58:4’ü kadın, %41.6’sı erkek) oluşturmaktadır. Çalışmanın veri toplama araçları Sosyodemografik Bilgi Formu, Koronavirüs Tükenmişlik Ölçeği (COVID-19-BS), Algılanan Covid-19 Risk Ölçeği (CPRS), Dünyaya İlişkin Varsayımlar Ölçeği (DİVÖ) ve Young Ebeveynlik Ölçeği (YEBÖ) şeklindedir. Yapılan analizlere göre kadın olanların, çocuk sahibi olmayanların, düşük eğitim düzeyi ve ekonomik durumu orta-alt ve orta-üste göre düşük ya da yüksek olanların ve anne babası ile yaşayanların Covid-19 tükenmişlik düzeylerinin daha yüksek olduğu görülmüştür. Öte yandan Covid-19’a dair değişkenlerden pozitif tanı alanların, fiziksel/sosyal izolasyon yaşayanların, iş yerinde ve pandemi öncesine göre daha yoğun çalışanların, Covid-19 nedeniyle yakın kaybı yaşayanların ve yakınları risk grubunda olanların Covid-19 tükenmişliklerinin daha yüksek olduğu bulgulanmıştır. Ayrıca yapılan korelasyon analizlerine göre Covid-19 tükenmişliği ile yaş arasında negatif yönde; algılanan Covid-19 riski ve bilişsel/duygusal alt boyutları ile pozitif yönde; DİV’in iyilik, adalet, şans ve kendilik değeri alt boyutları ve toplam DİV puanı ile negatif yönde; algılanan anne ebeveynlik biçimi ile pozitif yönde; algılanan baba ebeveynlik biçiminin ise küçümseyici/kusur bulucu, duygusal bakımdan yoksun bırakıcı, sömürücü/istismar edici ve kötümser/endişeli alt boyutları ile pozitif yönde anlamlı ilişkiler bulunmuştur. Son olarak hiyerarşik regresyon analizine dahil edilen tüm değişkenlerin toplam varyansın %40.8’ini anlamlı olarak [F= 8.690, p<.001] açıkladığı görülmüştür. Sonuçlar COVID 19 tükenmişliği üzerinde sosyodemografik ve Covid-19’a bağlı özelliklerin, algılanan ebeveynlik biçimlerinin, dünyaya ilişkin varsayımların, algılanan Covid19 risk algısının ve yordayıcı gücünün önemli olabileceğini düşündürmektedir. Mevcut bulgular ilgili literatür ışığında tartışılmış, çalışmanın sınırlılıklarına ve gelecek çalışmalar için önerilere yer verilmiştir.
The mediating role of difficulties in positive and negative emotion regulation in the relationship between early maladaptive schemas and cyber dating violence
(European Association for Behavioural and Cognitive Therapies (EABCT), 2023-10-07) Ünver, Buket; İnce, Elif Hazal
Introduction: Cyber dating violence includes all kinds of words, attitudes and behaviors that individuals use against their partners in order to harm the partner in the digital environment. In the present study, it was aimed to examine the mediating role of difficulties in positive emotion regulation and negative emotion regulation in the relationship between early maladaptive schemas and cyber dating violence. Method: The sample of the study consists of 298 individuals between the ages of 18-30 who are in a romantic relationship or have had a romantic relationship in the last 1 year. The data of the research was collected through Demographic Information Form, Cyber Dating Abuse Questionnaire, Young Schema Questionnaire-Short Form, Difficulty in Emotion Regulation Scale-Short Form and Multidimensional Measure of Difficulties in the Regulation of Positive Emotions. Results: Pearson Correlation Analysis was used to determine the relationship between early maladaptive schemas, difficulty in positive emotion regulation, negative emotion regulation and applied and exposed cyber dating violence. As a result of the statistical analyzes, significant relationships were found between four schema areas, disconnection&rejection, impaired autonomy and performance, other-directedness, overvigilance&inhibition, and the digital dating violence both applied and exposed. Mediation analysis revealed that difficulty in positive emotion regulation had a partial mediator role in digital dating violence applied and exposed to four schema domains. In addition, a partial mediating role of difficulty in regulating negative emotion was found between the areas of disconnection&rejection and others-directedness schema areas and the digital dating violence exposed. Dissusion: Individuals with an early life in an unhappy family develop schemas that cause them to turn to strategies such as fear, suppression and sabotage instead of feeling guilty for experiencing and enjoying positive emotions. At this point, the sabotage can be seen as the person being exposed to cyberbullying and/or being a cyberbully. The fact that digital dating violence seen in romantic relationships occurs especially through positive emotion regulation strategies reveals a need for how a positive emotion can be regulated especially in the adolescence and emerging adulthood group. Conclusion: The association of early maladaptive schemas and emotion regulation difficulties with digital dating violence suggests that clinicians may be effective in developing interventions for emotion regulation skills. In particular, in terms of regulation of positive emotions, impulse control, goal-oriented behavior, ability to activate emotional strategies, acceptance of emotions and regulation of targetoriented emotions and behaviors will be important therapeutic targets. Finally, awareness of cyber dating violence, cyberbullying and/or being a cyberbully that can be seen in adolescence and emerging adulthood group should be increased and people should be aware of their possible victimization.
The mediator role of schema modes in the relationship between parentification and co-dependency
(European Association for Behavioural and Cognitive Therapies (EABCT), 2023-10-07) Ünver, Buket; Önürme, Beyza; Bayram Kuzgun, Tubanur; Köse Karaca, Bahar; Kahveci, Ceyhun
Introduction: The disruption of the hierarchy between the parent and the child obscures the role of the child in the family. Parentification is characterized by the child taking emotional and/or instrumental responsibilities and caring for parents and siblings. Therefore, lead to significant difficulties in the child's development of a self, and these difficulties may be reflected in the child's romantic relationships in adulthood in the form of difficulties in thinking independently. This situation is conceptualized as codependency and is defined as excessive focus on others, assuming full responsibility, and low selfesteem. It is hoped that discovering the roles of schema modes, which are defined as emotional and behavioral states that emerge suddenly when people are hypersensitive, in these relationship styles will be a significant guide, especially in therapy sessions. Therefore, the main purpose of this study is to determine which schema modes mediate the relationship between parentification and co-dependence. Method: The research was conducted with 355 participants aged 18-69 years. The Sociodemographic Form, Parentification Inventory, Co-Dependency Assessment Scale, and Schema Mode Scale-Short Form were used in the study. Process Macro analysis Model 4 developed by Hayes (2013) was used to test the mediating role of schema modes between parentification and co-dependency. Results: According to the results of the analysis, the level of co-dependency is higher in women. Eight different mediator effect models were tested, including child modes, coping modes, parent modes, and healthy adult mode, between parent-focused parentification and sibling-focused parentification and codependency. The mediating role of the angry child mode, self-aggrandiser mode, and demanding parent mode was found between parent-focused parentification and co-dependency. In addition, the mediating role of the punitive and demanding parent mode was found between sibling-focused parentification and co-dependency. Discussion: It is noteworthy that the same mediating effect between both parent-focused and siblingfocused parentification and co-dependency is the demanding parent mode. The demanding parent mode, which prioritizes the needs of others, predicts co-dependency and shows the mode that should be studied first in treatment. The attention is drawn to the mediating variable between the punitive parenting mode, characterized by self-blaming aspects in individuals who assumed the responsibility of caring for their sibling during childhood, and perfectionism, which is co-dependency. Similarly, it is observed that the self-aggrandiser mode compensates for the emotional deprivation caused by parentification. These modes, which develop in root family interaction, mediate similar imbalances in adult roles. The prominence of the angry child and self-aggrandiser mode suggests that these individuals can be evaluated especially in terms of narcissism in studies and/or therapy sessions that examine the relationship between parentification and co-dependency. Conclusion: The schema modes come from the experiences of their root families and continue actively in the adulthood romantic relationships of individuals who take responsibilities that are not suitable for their developmental level in their childhood. It is thought that this study will enable individuals who experience parentification to define their unhealthy roles and explore their relational problems and will provide a new perspective on the predictor of childhood experiences on adulthood.
Impact of vaccines on the COVID-19 pandemic in Turkey
(2022-06-01) Yelmenoğlu, Elif Deniz; Elmas, Dilara
COVID-19 (coronavirus disease-2019 pandemic continues to threaten public health and this situation is raising great concern all over the world. With the development of different vaccines, it was aimed to end the epidemic and increase community immunity in the past years. The research reduced public anxiety but the extent of the impact of vaccines in the pandemic is should be under investigation. Because the degree of availability of the COVID-19 vaccines was differing both nationally and globally. This makes it important to investigate how effective vaccination is on the epidemic. The main aim of this study is to investigate the possible recovery impact of vaccination on the COVID-19 pandemic in Turkey. In addition, the rates of severe disease during the first 3 doses of vaccination were also examined in this study. The analyses are conducted based on Spearman, Kendall and Pearson's correlation by using the data of the Ministry of Health of the Republic of Turkey. The obtained results showed that there are strong correlations between vaccination and recovery.
The effect of parenting behaviors and cognitive distortions on the romantic relationships
(Livre de Lyon, 2021-01) Patar, Selen; Akçinar, Berna; Škrijelj, Redzep; Bank, Rasim Berker
[No abstract available]
Beyaz yakalı çalışanlarda mükemmeliyetçilik ve tükenmişlik arasındaki ilişkide psikolojik dayanıklılığın aracı rolü
(Institute of Economic Development and Social Research, 2023-06-20) Erbay Erşen, Merve; Akçınar, Berna
Bu araştırmanın amacı, beyaz yaka çalışanlarda mükemmeliyetçi özellikler ile tükenmişlik arasındaki ilişki ve bu ilişkide psikolojik dayanıklılığın aracı rolünü incelemektir. Bu doğrultuda üretim planlama, üretim yönetimi, kalite yönetimi vekontrol, iç denetim, Ar-Ge, bakım onarım, pazarlama gibi alanlarda çalışan kişilere bir çevrim içi anket platformu olan Google Forms aracılığı ile ölçekler ulaştırılmış ve çalışmanın verileri toplanmıştır. Araştırmada Sosyodemografik Özellikler ve Veri Formu, Conor-Davidson Psikolojik Sağlamlık Ölçeği, Çok Boyutlu Mükemmeliyetçilik Ölçeği ve Maslach Tükenmişlik Ölçeği kullanılmıştır. Verilerin analizi için betimleyici istatistikler, Pearson korelasyon analizi ve bir grup tekli ve çoklu regresyon analizi uygulanmıştır. Bu analizlerden elde edilen bulgulara göre, ailesel beklentiler alt boyutu hariç, uyumsuz mükemmeliyetçilik alt boyutları ile tükenmişliğin her iki alt boyutu (duyarsızlaşma ve duygusal tükenme) arasında pozitif yönde korelasyon ilişkisi olduğu görülmektedir. Uyumlu mükemmeliyetçilik alt boyutlarından düzen, duygusal tükenme ile negatif yönde, kişisel standartlar alt boyutu ise duyarsızlaşma ile pozitif yönde korelasyon ilişkisine sahiptir. Ayrıca, bulgular psikolojik dayanıklılığın, uyumsuz mükemmeliyetçilik ve tükenmişlik arasındaki ilişkide kısmi aracılık etkisini ortaya koymaktadır. Sonuçlar değerlendirildiğinde, mükemmeliyetçi özelliklerin uyumlu ve uyumsuz mükemmeliyetçilik olmak üzere iki boyutta ele alınmasının, tükenmişlik kavramını anlamada daha detaylı veri sağlayacağı ve psikolojik dayanıklılık gibi tükenmişliğe tampon etkisi yaratabilecek kavramların ele alınmasının önemli olduğu düşünülmektedir.
Polyvagal theory and interoception-based interventions: approaches to strengthen mental resilience
(Psikiyatride Güncel Yaklaşımlar, 2026) Candaş Demir, Merve Umay; Hasateş, Mahmut Can
Humans survive by establishing healthy bonds, and these bonds provide emotional regulation, especially in the caregiver-infant relationship. Polyvagal Theory suggests that the autonomic nervous system supports survival by assessing environmental and internal safety signals. Interoception plays a crucial role in this process, referring to the ability to sense the body's internal states. In recent years, interoception-based therapies have proven effective in the treatment of psychopathologies, especially post-traumatic stress disorder. Interoceptive-based interventions, such as trauma-informed yoga, can improve individuals who do not respond to traditional treatment by enhancing emotional regulation and body awareness. The aim of this study is to examine the effects of humanto-human relationships on mental health in the digitalized world, within the framework of Polyvagal Theory. In particular, it emphasizes the important role of interoception in the bond we establish with ourselves and its significance in psychotherapy. The study proposes an approach that supports mental health by discussing the therapeutic effects of interoception and the role of these skills in improving communication between individuals. The study also offers suggestions on how interoception-based interventions can be utilized in clinical practice. Such therapies help individuals form healthier bonds with both themselves and others.
TURSpider veri kümesinde Temsilcilerin Karışımı Tabanlı Text-to-SQL çalışması
(IEEE, 2025) Kanburoğlu, Ali Buğra; Tek, Faik Boray
Bu çalışma, Türkçe Text-to-SQL için geliştirilen TURSpider veri kümesi üzerindeki deneyleri ele almaktadır. TURSpider, çeşitli zorluk seviyelerine sahip SQL sorgularını içeren geniş kapsamlı bir Türkçe veri kümesidir ve bu alandaki araştırmalar için önemli bir kaynak niteliğindedir. Çalışmada, geri bildirim odaklı temsilcilerin karışımı yaklaşımının (ing. feedback driven Mixture-of-Agents - MoAF) başarımı incelenmiştir. MoAF yapısında, birden fazla büyük dil modeli (BDM) iş birligi içinde çalışarak SQL oluşturma başarımını artırmayı hedeflemektedir. Bu yapıda temsilci (ing. agent) işbirliği, modellerin birbirinden ögrenmesini ve geri bildirim mekanizmaları aracılığıyla hataların düzeltilmesini sağlamaktadır. Deney sonuçlarına göre, MoAF yaklaşımı ile %60.63 yürütme doğruluğuna ulaşılmış ve TURSpider veri kümesi üzerindeki en iyi sonuç elde edilmiştir.
Theta and Beta1 frequency band values predict dyslexia classification
(John Wiley and Sons Ltd, 2025-12-29) Eroğlu, Günet; Harb, Mhd Raja Abou
Dyslexia, impacting children's reading skills, prompts families to seek cost-effective neurofeedback therapy solutions. Utilising machine learning, we identified predictive factors for dyslexia classification. Employing advanced techniques, we gathered 14-channel Quantitative Electroencephalography (QEEG) data from 200 participants, achieving 99.6% dyslexic classification accuracy through cross-validation. During validation, 48% of dyslexic children's sessions were consistently classified as normal, with a 95% confidence interval of 47.31 to 48.68. Focusing on individuals consistently diagnosed with dyslexia during therapy, we found that dyslexic individuals exhibited higher theta values and lower beta1 values compared to typically developing children. This study pioneers machine learning in predicting dyslexia classification factors, offering valuable insights for families considering neurofeedback therapy investment.

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