WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://gcris.yasar.edu.tr/handle/123456789/11289
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Publication Workplace Related Determinants on Innovation Success and Characteristics(2011) Halac, Duygu Seckin; Bulut, Cagri; Gencturk, SelinBook Part Women’s Empowerment for Decision-Making Duties in Public Administration(Routledge, 2019) Kutlu Gursel, MeltemPublication What Really Rules Investment Decisions: Head or Heart(2010) Moore, Stephen; Niazi, Ghulam Shabbir Khan; Aktan, Bora; Masood, OmarPublication The Use of Internet Resources by University Students during Their Course Projects Elicitation: A Case Study(2010) Balta, Sabah; Ercan, Tuncay; Sahin, Yasar GuneriPublication Wavelet Feature Extraction for ECG Beat Classification(2014) Karaye, Ibrahim Abdullahi; Saminu, Sani; Ozkurt, NalanReview Victims of Commemoration: The Architecture and Violence of Confronting the Past in Turkey(Intellect Ltd, 2024) Baydar, GulsumEditorial Warehousing 5.0 for the Future of the Logistics Industry(Taylor & Francis Ltd, 2026-01-21) Sgarbossa, Fabio; Grosse, Eric H.; Venkatadri, Uday; Ekren, Banu Y.This editorial introduces and contextualises the International Journal of Production Research Special Issue on 'Warehousing 5.0 for the Future of the Logistics Industry'. Building on the principles of Industry 5.0, the concept of Warehousing 5.0 redefines warehouse operations as human-centric, intelligent, sustainable, and resilient systems. It emphasises the integration of advanced automation and analytics with human well-being, environmental stewardship, and data responsibility - shifting the focus from efficiency alone to a balanced socio-technical paradigm. The Special Issue received 45 submissions, from which 12 papers were accepted after rigorous peer review. Together, these studies advance understanding across four interconnected themes: (T1) Human Factors and Human-Centric Design, (T2) Optimisation and Efficiency in Robotics and Automation, (T3) Energy Efficiency and Sustainable Operations, and (T4) Data-Driven and AI-Enabled Warehousing. The contributions highlight innovations in ergonomic design, collaborative robotics, energy-aware scheduling, stochastic and multi-objective optimisation, wearable sensing, and AI-enabled vision systems, demonstrating how operational efficiency can coexist with human welfare and environmental responsibility. Synthesising across these themes, the editorial identifies key insights on human-technology symbiosis, sustainable digitalisation, and cyber-physical-social integration in warehouses. It also outlines future research directions on adaptive human-robot collaboration, circular logistics, responsible AI, and integrative modelling. The practical and policy implications discussed provide a framework for managers and decision-makers to implement Warehousing 5.0 principles effectively. Collectively, the Special Issue contributes to shaping a new generation of resilient, sustainable, and human-aware warehouses, reinforcing IJPR's leadership in advancing innovative and responsible production and logistics systems.Publication Publication Unexpected Drive as a Reduction of Criminal Responsibility(2013) Donmez, Burcu DemrenArticle undefinedScreenscapingundefinedthe City:Reproduction of the Image of İstanbulin Online TV Series(Art Style Communication & Editions, 2024) Bakan, Omer Can; Yilmaz, AhenkThis article explores the portrayal of Istanbul's urban image in TV series produced for online platforms, examining how these visual narratives influence public perception. By revisiting Kevin Lynch's theories on urban imagery, the study analyzes four prominent TV series set in Istanbul: Persona (Şahsiyet), The Protector (Hakan: Muhafız), Ethos (Bir Başkadır), and The Gift (Atiye). Each series utilizes Lynch's five urban elements path, edge, district, node, and landmark to craft unique visual narratives. Changing urban views and evolving tourism trends driven by digital platforms are transforming the city's image. The study aimed to explore the city image by developing a new perspective towards reading how Istanbul is screened in online TV series. Paths highlight socio-economic disparities by connecting various districts, both urban and rural, while edges, such as the Bosporus and other waterfronts, create physical and symbolic boundaries emphasizing themes of isolation and confinement. Districts portray contrasting social structures, with some series focusing on dense, bustling areas and others on rural. Nodes serve as critical locations for key events and character interactions, weaving the narrative threads together, and landmarks, particularly historical ones like Hagia Sophia Mosque and the Grand Bazaar, ground the stories in Istanbul's rich cultural heritage. The analysis reveals that these TV series not only utilize Istanbul's urban elements to enhance storytelling but also contribute to the evolving perception of the city, depicting it as a place of stark social contrasts, urban dichotomies, and mythical heritage. Through this lens, the study underscores the significant role of visual media in constructing urban narratives, showing how Istanbul's blend of historical grandeur and contemporary vibrancy is instrumentalized and reproduced in the selected TV series. These series collectively shape and reinforce Istanbul's image in the global imagination, highlighting the city's multifaceted nature and its importance as a cultural and historical hub.Article undefinedI WILL HAVE YOU LIVE IN PALACES...undefined THE TRANSFORMATION OF NEIGHBOURHOOD AND URBANIZATION IN TURKISH CINEMA (1960 To1990)(Anadolu Univ, 2018) Sevcan Sonmez, Uyesi; Balci, DilaraIn this article, representation of city and neighborhood in Turkish films between 1960 and 1990 is examined with regard to the fact that cinema is a sociological data depicting change in societies. The transformation of urban life and neighborhood culture can easily be followed in cinema history. With the accelerating urbanization in the 1970s, representation of life in apartmant buildings and slums took the place of traditional neighborhood representations popular in 1960s films. In this article, the impact of urbanization on the transformation of social life and middle class living space in films is analysed over 35 films with the descriptive analysis method. The sample 35 films are not analysed by deep film analyzing methods, yet the impact of urbanization, urban change and social change on individuals and society in this large sample are discussed in this article.Publication Two-Way Real-Time Meteorological Data Analysis and Mapping Information System(2014) Ercan, Tuncay; Samet, R.; Tural, S.Publication Turkey’s Cyprus Policy: A Case of Contextual Europeanisation(2012) Kaliber, AlperPublication Turkey Draft Amplifier and Player of the Founders, Was One of the Real Hidden Hero(2014) Balcioglu, TevfikPublication Turkey, Modern Architectures in History Series(2013) Baydar, GulsumPublication Ttk for the Interrelation of Insurance in the Insurance of Credits (Commercial Recognition) m. 1472 Provisional Loan(2013) Aras, Ecehan YesilovaReview Trilingual Joyce: The Anna Livia Variations(Univ Tulsa, 2019) Ozbilek, Ceren KusdemirPublication Towards Virtualization: A Competitive Business Continuity(2010) Ercan, TuncayPublication Towards a New Approach in Social Simulations: Meta-Language(2009) Albayrak, Raif Serkan; Sueerdem, Ahmet K.Article Time-Based Fire Resistance Performance of Axially Loaded, Circular, Long CFST Columns: Developing Analytical Design Models Using ANN and GEP Techniques(MDPI, 2025-12-06) Nassani, Dia Eddin; Özelmacı Durmaz, Ç. Özge; İpek, Süleyman; Mete Güneyisi, EsraConcrete-filled steel tube (CFST) columns are composite structural elements preferred in various engineering structures due to their superior properties compared to those of traditional structural elements. However, fire resistance analyses are complex due to CFST columns consisting of two components with different thermal and mechanical properties. Significant challenges arise because current design codes and guidelines do not provide clear guidance for determining the time-dependent fire performance of these composite elements. This study aimed to address the existing design gap by investigating the fire behavior of circular long CFST columns under axial compressive load and developing robust, accurate, and reliable design models to predict their fire performance. To this end, an up-to-date database consisting of 62 data-points obtained from experimental studies involving variable material properties, dimensions, and load ratios was created. Analytical design models were meticulously developed using two advanced soft computing techniques: artificial neural networks (ANNs) and genetic expression programming (GEP). The model inputs were determined as six main independent parameters: steel tube diameter (D), wall thickness (ts), concrete compressive strength (fc), steel yield strength (fsy), the slenderness ratio (L/D), and the load ratio (mu). The performance of the developed models was comprehensively compared with experimental data and existing design models. While existing design formulas could not predict time-based fire performance, the developed models demonstrated superior prediction accuracy. The GEP-based model performed well with an R-squared value of 0.937, while the ANN-based model achieved the highest prediction performance with an R-squared value of 0.972. Furthermore, the ANN model demonstrated its excellent prediction capability with a minimal mean absolute percentage error (MAPE = 4.41). Based on the nRMSE classification, the GEP-based model proved to be in the good performance category with an nRMSE value of 0.15, whereas the ANN model was in the excellent performance category with a value of 0.10. Fitness function (f) and performance index (PI) values were used to assess the models' accuracy; the ANN (f = 1.13; PI = 0.05) and GEP (f = 1.19; PI = 0.08) models demonstrated statistical reliability by offering values appropriate for the expected targets (f approximate to 1; PI approximate to 0). Consequently, it was concluded that these statistically convincing and reliable design models can be used to consistently and accurately predict the time-dependent fire resistance of axially loaded, circular, long CFST columns when adequate design formulas are not available in existing codes.
