2045 research outputs found
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Urban politics and the work and labour processes of architecture: Survey research with young architect-workers in Turkey
No full textThere is a general tendency in architecture to insistently see the work andlabour conditions of architects independently from “the production of nature as urban space” (Sert, 2020) embedded in the neoliberal capitalist economic order. However, considering the socio-ecologically crisisprone environments in which we live, understanding the complicated relationship among nature, the urban, and society becomes more crucial than ever before (Heynen, et al., 2006; Harvey, 1996; Smith, 2008). This article aims to question the common trend that treats the production process of urban space as if it were independent of the working conditions of architects. Current architectural theory struggles to find concepts for guiding the complicated relationship of architectural process particularly working conditions of architects with urbanization of nature in the 21st century. Accordingly, as specialized citizens, architects try to rethink ecological and civic imaginaries (Karvonen, 2011) for understanding human embeddedness in space, time, nature, and place (Harvey, 1996;Gandy, 2006). © 2021,Metu Journal of the Faculty of Architecture. All Rights Reserved.WOS:0006780678000092-s2.0-85111506811Arts and Humanities Citation IndexArticleUluslararası işbirliği ile yapılmayan - HAYIRAugustYÖK - 2020-2
Exploring environmental justice: Meaningful participation and Turkey’s small-scale hydroelectricity power plants practices
No full textThis chapter explores the emerging concept of meaningful participation within the framework of environmental justice, with specific reference to Turkey’s recent experience of building several small-scale hydroelectricity power plants (HEPP). The paper scrutinizes the HEPP process, including its entrenched legal framework, and attempts to come up with suggestions to elaborate further on the concept of meaningful participation.WOS:000674508700010Book Citation Index – Social Sciences & HumanitiesArticle; Book ChapterUluslararası işbirliği ile yapılan - EVETOcakYÖK - 2020-2
Fading boundaries: Insights on learning “in between” the classroom spaces
No full textChapter 9Along with the advancements in technology and shifts in approaches to education in our day, school architecture began to undergo significant transformations. Learning beyond the classrooms has emerged as a highlighted concern as well as the children’s interaction with each other and their environment. Articulation of the changing pedagogical approaches and visions of the innovative, student-centered ideas of the twenty-first century through the physical characters of learning spaces has become a significant issue for research regarding the design of contemporary schools. The evolution of the formation of boundaries, borders, and thresholds defining the distinctions and establishing the relationships and hierarchies between the learning spaces at school settings constitutes a critical part of this process, which deserves attention. This chapter aims to search for boundary-related design suggestions for primary schools in Turkey, based on the data obtained through a field study conducted in Istanbul, which aimed to derive the current issues regarding the spatial use patterns in prototype-based, conventionally designed schools. It is believed that the effective inhabitation of spaces beyond the classrooms has a high potential to contribute to the realization of diverse educational activities and the introduction of more permeable physical and visual boundaries can support the enrichment of school environments.2-s2.0-8510735572
An examination of the interplay between technological applications and writing skills/attitudes, and student experience
No full textÇalışmanın amacı teknolojik uygulamaların yazma becerisi ile yazma tutumu arasındaki ilişkisini görmek ve öğrenci deneyimlerini incelemektir. Araştırmanın katılımcılarını kolay erişilebilirliği nedeniyle İstanbul ili Eyüpsultan ilçesi sınırlarında bulunan bir özel okuldaki ’Digital Storytelling’ kulübünü tercih eden ortaokul öğrencileri oluşturmaktadır. Araştırma 2020-2021 eğitim öğretim yılının güz döneminde ‘Digital Storytelling’ kulübünün 8 hafta süren ders kulüp saatlerinde uygulanmıştır. Araştırma verileri; kulüp saatlerinde gözlemci tarafından alınan gözlem notları, katılımcıların dijital ve yazılı halde bulunan ürünleri, kulüp dersi bitiminde uygulanan değerlendirme anketi ve katılımcı görüşlerinin incelenmesinden elde edilmiştir. Bu veriler, tematik içerik analizi yöntemiyle analiz edilmiş ve ana temalar oluşturulmuştur. Araştırmada kulüp vaka olarak ele alınmış ve elde edilen veriler nitel yöntemle betimlenerek bulgular elde edilmiştir. Teknolojik uygulamaların kullanımı ile yazmada yaratıcılık arasında olumlu anlamda bir ilişki olduğu, teknolojik uygulamaların kullanımının yazma motivasyonunu ve yazma becerisini desteklediği bulgularına ulaşılmıştır. Teknolojik uygulamaların kullanımı ile yazma becerisi ve yazma tutumu arasındaki ilişkiyi incelemek amacıyla yapılacak benzer araştırmaların daha geniş bir zaman aralığında ve Türkçe ders saatleri içinde yapılması araştırmanın veri setinin daha kuvvetli olmasını sağlayacaktır. Aynı zamanda araştırmanın yüz yüze eğitim dahilinde yapılması teknolojik uygulamaların kullanımı ile yazma becerisi ve yazma tutumu arasındaki ilişkinin belirlemesinde daha anlamlı bir katkı sağlayacaktır
HERMES – Strengthening digital resource sharing during COVID and beyond
No full textHERMES is co-funded by the Erasmus+ Programme of the European Union. This project has been funded with support from the European Commission. Hermes project aims at providing educational institutions high quality, fast and free access to knowledge by building capacity to implement and share a comprehensive vision and wide spread competencies on resource sharing accompanied by an open source system to support effective access to knowledge for all. The project promotes cooperation and partnership among 5 organizations from Italy, the Netherlands, Turkey, Lebanon, and Spain; a national research institution, the worldwide umbrella organization for libraries, and 3 universities. All partners participate in the planned training and dissemination activities and the realization of all outputs. Project Partners : CNR Bologna Research Area library (Italy) is active in the field of software development since many years, having implemented NILDE and ALPE projects, the most important resource sharing projects in Italy for the number of involved institutions (90 Universities and Public Research organisations) and users (870 libraries and their 80.000 users). It coordinates the whole project and leads the realization of the new software. University of Balamand (Lebanon) is a not-for-profit academic institution of higher education active in resource sharing on the National and International levels being part of Lebanese Interlibrary Loan and Document Delivery Services (LIDS) consortium and represented in the IFLA Document Delivery and Resource Sharing standing committee. Its participation to the project is important because it brings the possibility to reach a vast number of potential beneficiaries: the Arabic speaking librarians and users. HERMES will translate in Arabic the training materials and, through specific dissemination activities, invite Arabic speaking librarians and library users to participate to training opportunities offered by the project not only in Lebanon but, being distance courses, potentially in all Arabic countries. University of Cantabria (Spain) cooperated with NILDE in order to ease the international interlibrary loan between Italian and Spanish libraries, and to spread the Resource Sharing Initiative. It brings to the project the experience in Inter Library Loan service being part of the national REBIUN ILL-DD-WG in guidelines of the ILL service, and having participated in NILDE survey on international ILL exchanges. University of Cantabria in particular takes care of the realization of monitoring and evaluation tools for training.MEF University (Turkey) has specific experience in management of digital resources, in fact the great majority of its resources are electronic. MEF brings to the project two aspects: a vision on how users can fully familiarize with how to access the digital resources, and an opportunity to involve Turkish libraries in the project activities. MEF University is responsible of the coordination of training activities foreseen in the project. International Federation of Library Associations and Institutions (IFLA) is based in the Netherlands but it is the global organization representing all library types in over 150 countries including all EU. It brings to the project, a part from an enormous potential in dissemination, a considerable expertise in the development, evaluation and publication of standards and tools designed to work for the entire global library field from which HERMES will benefit in the production of all outputs. Moreover, the Document Delivery and Resource Sharing Section of IFLA brings specific expertise in the project topic: HERMES can count on the potential of IFLA both as a forum for e exchanging experience and in developing tools and guidance that can support colleagues globally. IFLA is responsible for coordinating the production of the publication and for the organization of HERMES final international conference. (Project Duration : From 1/5/2021 to 31/10/2022)Avrupa Birliği Erasmus+ Programı tarafından ortak olarak finanse edilen HERMES projesi herkesin bilgiye etkin erişimini desteklemek için açık kaynak sistemi eşliğinde kapsamlı bir vizyon ve kaynak paylaşımı konusunda geniş kapsamlı yetkinlikleri uygulama ve paylaşma kapasitesini geliştirerek eğitim kurumlarının bilgiye yüksek kaliteli, hızlı ve ücretsiz erişimini sağlamayı amaçlamaktadır. HERMES Projesi, CNR Bologna Research Area library (İtalya), University of Balamand (Lübnan), University of Cantabria (İspanya), MEF University (Türkiye), International Federation of Library Associations and Institutions (IFLA). 5 kuruluşun ortak girişimi ile oluşturulmuştur.
(Proje Süresi : 1/5/2021'den 31/10/2022'ye kadar)Mayı
On the distribution modeling of heavy-tailed disk failure lifetime in big data centers
No full textIt has become commonplace to observe frequent multiple disk failures in big data centers in which thousands of drives operate simultaneously. Disks are typically protected by replication or erasure coding to guarantee a predetermined reliability. However, in order to optimize data protection, real life disk failure trends need to be modeled appropriately. The classical approach to modeling is to estimate the probability density function of failures using nonparametric estimation techniques such as kernel density estimation (KDE). However, these techniques are suboptimal in the absence of the true underlying density function. Moreover, insufficient data may lead to overfitting. In this article, we propose to use a set of transformations to the collected failure data for almost perfect regression in the transform domain. Then, by inverse transformation, we analytically estimated the failure density through the efficient computation of moment generating functions, and hence, the density functions. Moreover, we developed a visualization platform to extract useful statistical information such as model-based mean time to failure. Our results indicate that for other heavy-tailed data, the complex Gaussian hypergeometric distribution and classical KDE approach can perform best if the overfitting problem can be avoided and the complexity burden is overtaken. On the other hand, we show that the failure distribution exhibits less complex Argus-like distribution after performing the Box–Cox transformation up to appropriate scaling and shifting operations.Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) 115C111 - 119E235 / Spanish MINEC TEC2017-88373-R / Generalitat de Catalunya 2017SGR1195WOS:0006595492000082-s2.0-85110818271Science Citation Index ExpandedArticleUluslararası işbirliği ile yapılan - EVETJuneYÖK - 2020-2
Great Recession and news shocks: evidence based on an estimated DSGE model
No full textThis paper examines whether productivity news shocks were among the drivers of the Great Recession. To do this, the Smets and Wouters (Am Econ Rev 97(3):586–606, 2007. https://doi.org/10.1257/aer.97.3.586) model is extended by a generalized preference specification which allows for scaling wealth effects on the labor supply. The resulting model is estimated using Bayesian methods which draw upon the US data from the period 1965Q2 to 2014Q3. There are four main results: (i) Estimation of the model is inconclusive regarding the degree of wealth elasticity of the labor supply. As a result, two complementary versions of the model prevail, each of which has differing implications for the transmission and the quantitative importance of exogenous shocks. (ii) When the degree of wealth elasticity of the labor supply is low, news shocks replace risk premium shocks, suggesting that news shocks are one possible reason for fluctuations in US business cycles. (iii) When the Great Recession period is analyzed through the lenses of the two complementary versions of the model, two explanations emerge as potential reasons behind the deepening of the crisis: worsening credit conditions as well as the collapse of over-optimistic expectations regarding future productivity. (iv) For both model specifications, general developments in productivity are estimated to be positive. Therefore, productivity slowdown is not considered to be among the reasons for the emergence or persistence of the Great Recession.WOS:0006530002000012-s2.0-85106438917Social Sciences Citation IndexArticle; Early AccessUluslararası işbirliği ile yapılmayan - HAYIRMayYÖK - 2020-2
The link between attitudes toward probationers and job burnout in Turkish probation officers
No full textThe goal of the current study was to investigate individual-level factors associated with job burnout among probation officers (POs) and, specifically, to examine if attitudes toward probationers were linked with job burnout in the context of the recently established probation system in Turkey. Participants (N = 115) were recruited from a probation office in Istanbul. Job burnout was assessed via three components: emotional exhaustion, depersonalization, and professional accomplishment. Results of structural equation modeling indicated that more favorable attitudes toward probationers were related to a lower sense of depersonalization and higher experience of professional accomplishment. However, POs' attitudes toward probationers were not associated with emotional exhaustion. Our findings are discussed in light of the present empirical literature on the contextual factors influential in job burnout. Practical implications for burnout prevention point to the potential effectiveness of working on attitudes among POs toward the people they supervise.WOS:0006740150000012-s2.0-8511019188934269425Social Sciences Citation IndexArticle; Early AccessUluslararası işbirliği ile yapılan - EVETTemmuzYÖK - 2020-2
Makine öğrenmesi ve yapay sinir ağları algoritmaları ile kredi risk tahminin yapılması
No full textCredit risk assessment is very important for financial institutions today. The probability that a financial institution customer will not be able to repay the credits used is called credit risk. Financial institutions accept or reject credit applications. Institutions evaluate credit applications according to the personal information of the customers, life situation, loyalty, etc. If these data are below various values, financial institutions reject the application. The organization rejected the application because the client anticipated financial difficulties in the future. In the project, "German Credit" data on the Kaggle platform was used. In this data set, customers information and credit status are found as "good" and "bad". By using these data, it is aimed to evaluate new credit application requests. The data set used was passed through various pre-data processing steps and models such as Logistic Regression, Artificial Neural Networks, K-NN, Support Vector, Naïve Bayes, Decision Trees, Random Forest, LGBM and XGB were trained. The highest accuracy is achieved using the XGB model. (0.74