İstanbul Galata Üniversitesi Kurumsal Akademik Arşivi
DSpace@Galata, İstanbul Galata Üniversitesi tarafından doğrudan ve dolaylı olarak yayınlanan; kitap, makale, tez, bildiri, rapor, araştırma verisi gibi tüm akademik kaynakları uluslararası standartlarda dijital ortamda depolar, Üniversitenin akademik performansını izlemeye aracılık eder, kaynakları uzun süreli saklar ve telif haklarına uygun olarak Açık Erişime sunar.
Güncel Gönderiler
EXPLORING URBAN SPACES THROUGH VIRTUAL SOUNDWALK: DERINKUYU UNDERGROUND CITY
(2025) Nas, Sezin; Saher, Konca; Aytis, Saadet; Mihci, Gurkan
Abstract
Soundscape research plays a vital role in understanding historical environments by complementing visual interpretation and enhancing spatial perception. This study is part of a doctoral research which focuses on uncovering the acoustic identity and soundscape of Derinkuyu Underground City, a unique subterranean heritage site in Cappadocia, Turkey. Adapting the framework of ISO/TS 12913-2:2018, the research integrates soundscape methodologies with virtual reality (VR) to reconstruct the auditory experience of the site. Virtual soundwalk as an innovative method is significant in defining soundscapes and uncovering their historical narratives. This particular study aims to adapt and refine the virtual soundwalk methodology outlined in ISO/TS 12913-2:2018 to describe the soundscape of Derinkuyu Underground City, an urban-scale interior environment. Key interior typologies were identified based on function, scale, and spatial hierarchy, forming a structured VR soundwalk that guides participants through different levels of the city, from the entrance to the deepest, seventh level. The chosen typologies represent the entirety of the city's levels and spaces. The models integrate distinctive sound sources specific to each interior space, establishing a taxonomy and enriching these environments with sound scenarios. The scenarios were auralized using ODEON software and integrated into the virtual reality models. Auralized sound scenarios, developed using ODEON software, were embedded into 3D VR models to simulate the acoustic conditions of the underground spaces. At designated listening points, participants experience immersive reconstructions of historical soundscapes, reflecting the functional and social dynamics of the site. This study underscores the significance of soundscape in interpreting cultural heritage and highlights the potential of VR technology in preserving and experiencing historical acoustic environments. By refining virtual soundwalk methodologies, it contributes to advancing soundscape research and its applications in heritage conservation. © Copyright 2012 - 2025 IIAV - All Rights Reserved.
Effects of the Work Environment on Turnover Intentions among Psychiatric Nurses: The Mediating Role of Burnout
(2025) Işık, Nurten Arslan; Sandıkçı, İrem Nur; Şekeroğlu, Beyza; Demirci, Şevval; Keleş, Dılşa Azizoğlu; Kotyk, Taras
This study examines the impact of the nursing work environment on turnover intention among psychiatric nurses and explores the mediating role of burnout in this relationship. A cross-sectional design was employed, including 168 psychiatric nurses working in various psychiatric hospitals across Turkey. Data were collected using a demographic information form, the Nursing Work Environment Index (NWEI), the Maslach Burnout Inventory (MBI), and the Turnover Intention Scale. Spearman correlation analysis and structural equation modeling (SEM) were used to assess the relationships among the variables. The findings revealed that the nursing work environment negatively affects turnover intention (β = -0.179, p = .009), whereas burnout positively influences turnover intention (β = 0.501, p < .001). Furthermore, burnout significantly mediates the relationship between the work environment and turnover intention (β = -0.221, p < .001). These results highlight the importance of improving the work environment for psychiatric nurses to reduce burnout and mitigate turnover intention. Managerial support, effective leadership, and enhanced resources may play a crucial role in addressing these challenges
Alglerin Sürdürülebilirlik ve Besin Zenginleştirmedeki Yeri
(2025) Anık, Sema; Kestane, Vahibe Uluçay
Son yıllarda dünyada gıda üretiminde üst limitlere ulaşılmasına rağmen her 9 kişiden biri yetersiz beslenme ile karşı karşıyadır. İklim değişimi ve nüfus artışı ile durumun daha da kötüleşmesi sürdürülebilir alternatif enerji ve protein kaynaklarına yönelmeyi ihtiyaç haline getirmiştir. Sürdürülebilirlik kavramı, her zaman var olma, geleceğe kalabilme, varlığını devam ettirme olarak açıklanmaktadır. Bir beslenme stratejisi olarak düşünüldüğünde ise düşük çevresel etkiye sahip, protein seçeneklerinin var olduğu yeni alternatif kaynakların arayışı olarak gündeme gelmiştir. Literatürde alternatif protein kaynakları arasında yenilebilir böcekler, yenilebilir alg türleri ve biyoteknolojik yöntemler kullanılarak üretilen sentetik etler bulunmaktadır. Alglerin sucul ortamda doğal olarak yetişebilmeleri, çok uzun zaman güvenli olarak tüketilmeleri, makro ve mikro besin ögesi çeşitliliği ile biyoaktif madde yoğunluğunun yüksek olması, genetik olarak modifiye edilebilmeleri ve ihtiyaç duyulan ögelere göre seçilip çoğaltılabilmeleri gibi nedenlerden dolayı geleceğe yönelik doğal besin alternatifleri arasında yer almaktadır. Bu nedenle günümüzde süt ürünleri, makarna, ekmek vb. tahıl ürünleri gibi insan beslenmesinde sıklıkla tüketilen besinlere çeşitli mikroalg türleri ilave edilerek bu besinlerin makro ve mikro besin ögeleri yönünden zenginleştirilmesi sağlanmaktadır. Mikroalgler sağlıklı bir diyet için yeterince araştırılmamış doğal bir kaynaktır. Bu nedenle yüksek değerli ürünler elde edebilmek için yeni mikroalg suşlarının tanımlanması ve özelliklerinin belirlenmesine ihtiyaç duyulmaktadır. Bu derlemenin amacı, artan dünya nüfusunun gıda ihtiyacını karşılamak için sürdürülebilir ve yenilikçi protein kaynaklarına olan gereksinimi açıklamak ve alglerin sürdürülebilirlik ve besin zenginleştirmede alternatif besin kaynağı olarak kullanılmasının önemini vurgulamaktır.
The Mediating Role of Climate Change Mitigation Behaviors in the Effect of Environmental Values on Green Purchasing Behavior within the Framework of Sustainable Development
(Walter de Gruyter GmbH, 2025) Yilmaz, Gonca
Global environmental challenges, including the depletion of natural resources, pollution, and population growth, have significantly impacted modern lifestyles. The environmental and socioeconomic dimensions of this reality are represented by climate change, one of the major threats facing the planet. People's environmental values and the green behaviors they exhibit based on these values are crucial in mitigating significant environmental problems, such as climate change. In this context, raising environmental awareness and motivating individuals to contribute to sustainable development and the circular economy particularly environmental protection can serve as an effective starting point. In line with this idea, data were collected from 236 participants in Istanbul in 2024 using the convenience sampling method. The data collected through the survey technique in the study were analyzed using the SPSS program and PROCESS, a macro developed for SPSS. In addition, confirmatory factor analysis and path analysis were performed with the Python programming language, and fit index was also presented. The research findings reveal a significant relationship between environmental values and green purchasing behavior. The mediating role of climate change mitigation behavior was also found.
Deep Learning in neuroimaging for neurodegenerative diseases: State-of-the art, Challenges, and Opportunities
(Elsevier B.V., 2025) Akan, Taymaz; Alp, Sait; Ledbetter, Christina Raye; Tafti, Ahmad P.; Arevalo, Octavio; Bhuiyan, Mohammad Alfrad Nobel
Neuroimaging is commonly used to diagnose neurodegenerative diseases (NDDs), providing crucial insights into brain changes before clinical symptoms manifest. Deep learning (DL) for neuroimaging can improve early diagnosis and disease monitoring. Clinical implementation of DL faces challenges in accurately representing realworld data. Recent models, particularly those focused on diagnostic categorization, have achieved high accuracy, but their applicability to patients is limited. Conflicting inferences have been reported, with findings from small cohorts generalizing conclusions without considering inter-scanner, intra- and inter-site variations. A theoretically feasible method involves gathering a comprehensive dataset that encompasses all patient demographics, but this presents practical challenges including harmonization, data incompleteness, class imbalance, and substantial costs. Existing research has also mostly focused on common NDDs like Alzheimer's Disease (AD) and Parkinson's Disease (PD). This contribution expands the literature by looking at a wider range of NDDs, exploring the latest advancements in applying deep learning algorithms to neuroimaging analysis for the diagnosis and monitoring of NDDs, including AD, Frontotemporal Dementia (FTD), Lewy Body Dementia, PD, Huntington's Disease, Amyotrophic Lateral Sclerosis, and Multiple Sclerosis. We emphasize how these approaches are handling spatial/temporal information available in brain volume imaging data. We conclude by discussing the challenges associated with the use of voxel-based, patch-based, ROI-based, and slice-based approaches in brain volume imaging. These challenges are further compounded by issues such as inter-site and inter-scanner variability, class imbalances in medical datasets, and the scarcity of accurately annotated data, all of which impact the performance and generalizability of deep learning models.
