OpenMETU (Middle East Technical University)
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Mekanik metamalzemelerin hesaplamalı modellenmesi
No full textThis thesis presents a comprehensive multiscale stability analysis of periodic porous metamaterials composed of hyperelastic, viscoelastic, and electro-mechanical materials. In this framework, two advanced methodologies, the Bloch-Floquet wave analysis and Refined Eigen Analysis (REA), are implemented and systematically validated for both hyperelastic and finite viscoelastic constitutive models, clarifying their applicability across different loading rates and types of material behavior. Key instability mechanisms are investigated, including relaxation-induced buckling, where the loss of instantaneous stiffness under constant deformation triggers pattern transformation. Furthermore, the effect of mechanical pre-straining on microscopic stability is also explored, showing that initial tensile or compressive loading moderately shifts critical strain thresholds without altering deformation modes. In addition, electro-mechanical effects are examined in periodic metamaterials, revealing that prescribed spatial electric fields can qualitatively modify critical mode shapes and post-buckling patterns. Subsequently, snap-through and snap-back instabilities in biholar metamaterials under inhomogeneous lateral confinement are analyzed. Arc-length simulations confirm that the intrinsic mechanical response is characterized by snap-back behavior with no inherent hysteresis, while displacement-controlled dynamic simulations produce pseudo-hysteretic responses arising from geometric nonlinearities, inertial effects, and the applied loading protocol. For viscoelastic configurations, fully nonlinear rate-dependent simulations capture snap-through instabilities, showing that higher loading rates delay the onset of instability and enhance dissipation, with deformation concentrated in specific ligament regions. To conclude, the findings collectively advance the understanding of how geometry, rate-dependence, and multi-physics couplings govern the unstable behavior, providing validated computational tools and design strategies for programmable mechanical metamaterials.Bu çalışma, hiperelastik, viskoelastik ve elektromekanik malzemelerden oluşan, periyodik gözenekli metamalzemelerin kapsamlı, çok ölçekli kararlılık analizini sunmaktadır. Bu çerçevede, Bloch-Floquet dalga analizi ve Detaylandırılmış Özdeğer Analizi (DÖA) adlı iki gelişmiş yöntem, hiperelastik ve geometrik olarak doğrusal olmayan viskoelastik yapı modelleri için uygulanmış ve sistematik olarak doğrulanmıştır. Bu yöntemlerin farklı yükleme hızları ve malzeme davranışları için uygulanabilirliği açıklığa kavuşturulmuştur. Gevşeme kaynaklı burkulma dahil olmak üzere temel kararsızlık mekanizmaları incelenmiştir. Bu mekanizmada, sabit deformasyon altında rijitliğin anlık kaybı, desen dönüşümünü tetiklemektedir. Ayrıca, mikroskobik kararlılık üzerinde mekanik ön gerinimin etkisi de araştırılmış ve ön çekme veya basma gerinimlerinde, deformasyon şekillerini değiştirmeden kritik gerinim eşiklerini orta derecede değiştirdiği gösterilmiştir. Ek olarak, periyodik metamalzemelerde elektromekanik etkiler incelenmiş ve belirlenen elektrik alanlarının kritik asal şekil değişimlerini ve burkulma sonrası desenleri nitel olarak değiştirebileceği ortaya konmuştur. Sonrasında, homojen olmayan yanal sınırlama altında iki tür dairesel delikli metamalzemelerde ani sıçrama ve ani bırakma kararsızlıkları analiz edilmektedir. Yay uzunluğu benzetimleri, içsel mekanik tepkinin, enerji tüketmeyen ani bırakma davranışı ile karakterize olduğunu doğrularken, yer değiştirme kontrollü dinamik benzetimler, geometrik ve atalet etkilerinden ve yükleme protokolünden kaynaklanan görünüşte enerji tüketen tepkileri üretmektedir. Viskoelastik konfigürasyonlarda, tamamen doğrusal olmayan hıza bağlı benzetimler ani sıçrama kararsızlıklarını yakalamakta ve daha yüksek yükleme hızlarının kararsızlık başlangıcını geciktirdiğini, enerji kaybını artırdığını ve deformasyonun belirli bağ bölgelerinde yoğunlaştığını göstermektedir. Sonuç olarak, bulgular, geometri, hız etkileri ve çoklu fizik etkileşimlerinin kararsızlık davranışını nasıl yönettiğine dair anlayışı bütüncül olarak geliştirerek, programlanabilir mekanik metamalzemeler için doğrulanmış hesaplama araçları ve tasarım stratejileri sağlamaktadır.Ph.D. - Doctoral Progra
SAVAŞ SANATLARI ANTRENÖRLERİNİN ANTRENÖRLÜK FELSEFELERİ VE UYGULAMALARI
No full textThe philosophical foundations of coaching have been broadly examined within sport science literature; however, limited attention has been given to Martial Arts. Martial Arts present a unique context where physical performance is closely intertwined with moral, cultural, and pedagogical dimensions, emphasizing discipline, self-regulation, and holistic development. This study addresses this gap by investigating the coaching philosophies of martial arts coaches and the extent to which these philosophies align with their practices in Türkiye. A qualitative research design was employed, utilizing semi-structured interviews with 10 experienced coaches across six martial arts disciplines (Aikido, Judo, Karatedo, Sayokan, Archery, and Capoeira), focus group interviews with youth athletes, and 14 field observations. Thematic analysis by MaxQDA identified two overarching domains: values for athletes and values for self. Coaches consistently emphasized personal and character development (e.g., discipline, resilience, respect), physical and athletic growth (e.g., technical mastery, injury prevention), and social-communal values (e.g., family cohesion, identity). Continuing professional development and role modeling were also central to their philosophies. However, discrepancies emerged between articulated philosophies and observed practices, often shaped by contextual, structural, and experiential constraints. The findings underscore the complexity of Martial Arts coaching philosophies and the interplay between values, beliefs, and practices. It can be concluded that there is partial alignment between coaching philosophies and actual practices. By providing a culturally specific perspective, this study contributes to the literature on coaching studies and sport pedagogy, offering implications for coach education, youth development, and bridging the gap between theory and practice.Antrenörlüğün felsefi temelleri spor bilimi literatüründe geniş ölçüde incelenmiş olsa da, savaş (dövüş) sanatlarına sınırlı düzeyde ilgi gösterilmiştir. Savaş sanatları, fiziksel performansın disiplin, öz-denetim ve bütüncül gelişimi vurgulayan ahlaki, kültürel ve pedagojik boyutların iç içe geçtiği özgün bir bağlam sunar. Bu çalışma, Türkiye’de savaş sanatları eğitmenlerinin antrenörlük felsefelerini ve bu felsefelerin uygulamalarla ne ölçüde örtüştüğünü inceleyerek söz konusu boşluğu ele almaktadır. Çalışmada nitel araştırma deseni benimsenmiştir. Altı farklı savaş sanatı disiplininde (Aikido, Judo, Karatedo, Sayokan, Okçuluk ve Capoeira) çalışan 10 deneyimli antrenörle yarı yapılandırılmış görüşmeler, antrenörlerin sporcularıyla odak grup görüşmeleri ve 14 alan gözlemi ile veriler toplanmıştır. Tematik analiz, iki temel alanı ortaya koymuştur: savaş sanatları antrenörlük bağlamının sporculara yönelik değerleri ve antrenörlerin kendilerine yönelik değerleri. Antrenörler, kişisel ve karakter gelişimini (örn., disiplin, dayanıklılık, saygı), fiziksel ve atletik gelişimi (örn., teknik ustalık, sakatlanmayı önleme) ve sosyal-toplumsal değerleri (örn., aile bütünlüğü, kimlik) sürekli olarak vurgulamıştır. Sürekli mesleki gelişim ve rol model olma da felsefelerinin merkezinde yer almıştır. Bununla birlikte, dile getirilen antrenörlük felsefeleri ile gözlemlenen uygulamalar arasında, çoğunlukla bağlamsal, yapısal ve deneyimsel sınırlılıklardan kaynaklanan farklılıklar da ortaya çıkmıştır. Bulgular, savaş sanatları antrenörlük felsefelerinin karmaşıklığını ve değerler, inançlar ile uygulamalar arasındaki etkileşimi vurgulamaktadır. Antrenörlük felsefeleri ile gerçek uygulamalar arasında kısmi bir uyum olduğu sonucuna varılabilir. Kültüre özgü bir bakış açısı sunan bu çalışma, antrenörlük çalışmaları ve spor pedagojisi literatürüne katkı sağlayarak antrenör eğitimi, gençlik gelişimi ve teori ile pratik arasındaki boşluğun kapatılmasına yönelik çıkarımlar sunmaktadır.M.S. - Master of Scienc
Data Mining on the Fundamental Factors Influencing Mathematics Achievement: Traditional and Modern Perspectives
No full textAssessing achievement is a complex task due to its dependence on multiple factors and the hierarchical structure of educational data, yet surveys like TIMSS offer valuable insights into its determining factors like students' mathematics anxiety. However, disregarding the nested structure of data and ignoring the assumptions of models causes poor performance such as inaccurate predictions and biased estimates. Our research utilises linear mixed models (LMMs) and machine learning (ML) techniques (e.g., REEM-tree and GP boosting) especially chosen for their abilities to model nested data and capture non-linear relationships. This study is a pioneer in the literature as these ML algorithms are implemented for the first time in TIMSS. Accordingly, mathematical tendency and emotional factors are the two primary predictors of mathematics achievement across all methods, acknowledging the possibility of potential bias due to reliance on self-report responses. However, there are variations in the effect size of the students' origins among the methods. This indicates different algorithms yield distinct results according to their inner processes and priorities, such as revealing statistical significance of predictors or contributing to predictive performance. Moreover, gender has a negligible impact across all models in our analysis, caused by cultural differences in the sample. Overall, while LMMs are widely accepted, ML methods remain competitive alternatives in prediction and flexibility. All three methods yield similar benchmarks, yet ML methods offer slightly better performance in RMSE, MAE, and MAPE while exhibiting high predictive power and capturing nonlinearity and interaction. Although they take more computation time, parallel processing mitigates this in larger datasets. Consequently, ML methods and LMMs concurrently provide broader and more precise insights in terms of predictive and inferential gains
Integrating digital skills in talent management: A comprehensive bibliometric analysis
No full textBackground
Integrating digital skills and Information and Communication Technology (ICT) into organizational practices is crucial for maintaining a competitive edge. However, existing research has not yet provided a systematic and comprehensive mapping of how digital skills and ICT collectively reshape talent management practices. Addressing this gap, this study examines how digitalization transforms talent management, with a focus on digital skills, ICT, and technological innovation.
Objective
This study investigates how digitalization transforms talent management practices, emphasizing the role of digital skills, ICT, and technological innovation. It aims to identify key practices that align talent strategies with organizational goals while fostering continuous learning and development.
Methods
A comprehensive bibliometric analysis using the Web of Science database, complemented by an in-depth literature review, to examine theoretical foundations, emerging trends, and key contributors in talent management research.
Results
Findings highlight the benefits of a technology-driven approach to talent management, including improved talent acquisition, enhanced training and development programs, and increased employee retention.
Conclusions
Integrating digital skills and ICT into human resource practices is crucial for promoting continuous learning. This study offers practical recommendations for organizations and provides valuable insights for researchers and practitioners navigating the digital transformation of talent management
Exploring attitudes and behavioural intentions towards e-scooter use in Türkiye: Differences between users and non-users
Full text linkE-scooters, as a relatively recent emerging mode of transport, have gained considerable significance for research in recent years, including attitudes and behavioural intentions of the public towards these vehicles. To enhance our understanding, it is essential to examine the roles of previous e-scooter experience and gender on attitudes and behavioural intentions. In order to address this need, the present study aimed to investigate the attitudes and behavioural intentions towards e-scooters of 443 young adults between 18 and 25 years old in Türkiye. Prior experience with e-scooters was found to enhance perceived behavioural control and usefulness, as well as behavioural intention. Males exhibited higher perceived behavioural control and greater behavioural intention than females. Additionally, positive attitudes and greater perceived behavioural control were related to greater behavioural intention. Finally, this study highlights the significance of prior experience with e-scooters and gender as two factors influencing young road users' perception of e-scooter use in Türkiye. The findings provide important inputs for future policy and the development of intervention programmes for safe and inclusive implementation of e-scooters
Benchmarking Deep Learning Models For Automated Waste Classification
No full textRecycling is essential for reducing waste, conserving resources, and promoting a more sustainable and efficient use of materials. However, manual sorting is inefficient, prone to human error, and limits recycling efficiency. This study develops an automated waste sorting system using image recognition and deep learning to enhance recycling efficiency and accessibility.To achieve this, three deep learning models - google/vit-base-patch16-224, Falconsai/nsfw image detection, and microsoft/resnet-50 - are compared to determine the most suitable one based on accuracy and computational efficiency. The selected model powers an intelligent recycling system that uses image recognition to efficiently categorize waste, reducing costs, enhancing material value, and supporting large-scale waste management. This research highlights the potential of AI-driven sorting to improve recycling, reduce environmental impact, and promote sustainability
Innovative Hybrid Science Education: Integrating Citizen Science and Digital Learning for Future-Ready Teachers
Full text linkThis study explores the integration of a real-time mobile air quality monitoring citizen science project within a hybrid instructional model for pre-service science teachers. Responding to challenges posed by the COVID-19 pandemic, the research investigates how this innovative approach impacts participants' technological proficiency, scientific literacy, environmental attitudes, and readiness for interdisciplinary teaching. Using a single-case study design with multiple data sources, the research involved 12 pre-service science teachers in a 14-week course combining online and face-to-face instruction. Data collection included interviews, focus groups, observations, research reports and validated scales.Findings reveal significant improvements in participants' appreciation of online education, technological proficiency and TPACK development, scientific literacy, environmental awareness, and interdisciplinary teaching readiness. The study demonstrates how integrating citizen science and digital learning in a hybrid model can effectively prepare future science educators to meet 21st-century challenges. Moreover, it addresses equity issues in science education by showcasing how accessible technology and citizen science projects can democratize scientific inquiry and environmental monitoring, particularly crucial during crises. This research contributes valuable insights to the ongoing dialogue about best practices in science teacher education, offering a replicable model for innovative, technology-enhanced learning experiences