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Citizenship, Media and Activism in Turkey During Gezi Park Protests
No full text[No Abstract Available]Book Citation Index – Social Sciences & Humanitie
Analyzing Turkish war movies (2009-2019): A popular geopolitics approach
No full textCoğrafya ve siyasetin uzun ve samimi ilişkisi jeopolitiğin uluslararası ilişkilerle en sıkı bağlara sahip disiplinlerden birisi olmasına neden olmuştur demek mümkündür. Klasik jeopolitik olarak adlandırılan jeopolitik kuramlar uluslararası ilişkilerdeki realist paradigmanın etkisiyle mekânı devlet merkezli güç politikalarını esas alarak incelemiştir. 1990'lardan sonra dünyada gelişen eleştirel jeopolitik bakış açısı birçok uluslararası eylemin görünen amaçlarından ziyade dile getirilmeyen amaçlara hizmet ettiğini ileri sürmüştür. Eleştirel jeopolitiğe göre devletlerin kültürel ve ideolojik sınırlarını belirleyen güçleri vardır ve bu güçleri coğrafi sınırlarının oldukça ötesindedir. Eleştirel jeopolitiğin alt dalı olan popüler jeopolitik ise jeopolitik bilginin nerede üretildiğine dair geniş kapsamlı bir kavramdır ve popüler medya, romanlar, dergiler ve çizgi filmler gibi çeşitli kültürel formlarda bulunan jeopolitik temsillere atıfta bulunur. Bu bağlamda bu tez de popüler jeopolitiğin araçlarından biri olan sinema hakkındadır. Bu tez 2000 yılından sonra Türkiye'de çekilen asker ve savaş konulu filmlerin mekân üzerinden ortaya çıkan güç dinamiklerine odaklanarak Türkiye'nin neresi ve Türkiye'nin kim olduğunu anlamaya çalışacaktır. Bu tezin temel sorusu ise, 2000 sonrası asker savaş konulu filmlerde kullanılan söylem ve temalar üzerinde Türklük algısını ve Türkiye'nin konumsal mekânı üzerinden kurulan güç dinamiklerinin neler olduğudur. Bu bağlamda bu tezin konusu ise 2009 ile 2019 Türkiye'de sonrası Türkiye'de çekilen asker ve savaş temalı filmler olan Anadolu Kartalları, Dağ 1, Dağ 2, Can Feda, Nefes, Börü, Bölük ve Meteler filmlerinin temsillerinin mekân üzerinden kurduğu kimlik ve güç ilişkilerinin analizini yapmaktır.Due to the close relationship between geography and politics, geopolitics is one of the disciplines with the extensive ties to international relations. Under the influence of the realist paradigm in international relations, classical geopolitics theories examined space in a state-centered, holistic, and power politics-based manner. The critical geopolitical perspective developed in the world after the 1990s has argued that many international actions serve unspoken goals rather than their apparent purposes. According to critical geopolitics, states have powers that determine their cultural and ideological boundaries, and these powers go far beyond their geographical borders. Popular geopolitics, a sub-branch of critical geopolitics, is a broad concept of examining places where geopolitical knowledge is produced, and it deconstructs geopolitical representations found in various cultural forms such as popular media, novels, magazines, and cartoons. In this context, this thesis is about cinema as one of the tools of popular geopolitics. This thesis deconstructs representations of Turkey and Turkishness by focusing on the power dynamics emerging through space in military and war-themed films shot in Turkey after 2000. The main question of this thesis is how the discourses and themes used in post-2000 military and war films can be used to understand perceptions of Turkishness and Turkey's position in the international order. In this context, the subject of this thesis is to analyze the identity and power relations established through space in the representations of the military and war-themed films shot in Turkey between 2009 and 2019, namely Anadolu Kartalları, Dağ 1, Dağ 2, Can Feda, Nefes, Börü, Bölük, and Meteler
3d Printer Selection for the Sustainable Manufacturing Industry Using an Integrated Decision-Making Model Based on Dombi Operators in the Fermatean Fuzzy Environment
No full textAntucheviciene, Jurgita/0000-0002-1734-3216; Görçün, Ömer Faruk/0000-0003-3850-6755; küçükönder, hande/0000-0002-0853-8185; Hashemkhani Zolfani, Sarfaraz/0000-0002-2602-3986Three-dimensional printers (3DPs), as critical parts of additive manufacturing (AM), are state-of-the-art technologies that can help practitioners with digital transformation in production processes. Three-dimensional printer performance mostly depends on good integration with artificial intelligence (AI) to outperform humans in overcoming complex tasks using 3DPs equipped with AI technology, particularly in producing an object with no smooth surface and a standard geometric shape. Hence, 3DPs also provide an opportunity to improve engineering applications in manufacturing processes. As a result, AM can create more sustainable production systems, protect the environment, and reduce external costs arising from industries' production activities. Nonetheless, practitioners do not have sufficient willingness since this kind of transformation in production processes is a crucial and irrevocable decision requiring vast knowledge and experience. Thus, presenting a methodological frame and a roadmap may help decision-makers take more responsibility for accelerating the digital transformation of production processes. The current study aims to fill the literature's critical theoretical and managerial gaps. Therefore, it suggests a powerful and efficient decision model for solving 3DP selection problems for industries. The suggested hybrid FF model combines the Fermatean Fuzzy Stepwise Weight Assessment Ratio Analysis (FF-SWARA) and the Fermatean Ranking of Alternatives through Functional mapping of criterion sub-intervals into a Single Interval (FF-RAFSI) approaches. The novel FF framework is employed to solve a critical problem encountered in the automobile manufacturing industry with the help of two related case studies. In addition, the criteria are identified and categorized regarding their influence degrees using a group decision approach based on an extended form of the Delphi with the aid of the Fermatean fuzzy sets. According to the conclusions of the analysis, the criteria "Accuracy" and "Quality" are the most effective measures. Also, the suggested hybrid model and its outcomes were tested by executing robustness and validation checks. The results of the analyses prove that the suggested integrated framework is a robust and practical decision-making tool
Evaluation of Green Marketing Practices of the Logistics Industry in Type-2 Neutrosophic Fuzzy Environment
No full textLojistik endüstrisi, çevresel kirlilikle ilgili dış paydaşların artan endişeleri ve yoğun rekabetçi iş ortamında başarılı olma ihtiyacı nedeniyle Kurumsal Sosyal Sorumluluk (KSS) uygulamalarını benimsemek için önemli bir baskıyla karşılaşmaktadır. İç motivasyonlara ek olarak uluslararası kuruluşlar ve hükümetler, lojistik şirketlerin küresel çevresel kirlilik endişeleri ve lojistik ve taşımacılık endüstrilerinin olumsuz etkilerine uygun bir şekilde KSS uygulamalarını hayata geçirmeleri konusunda büyük bir baskı uygular. Bu nedenle firmalar, rekabetçi iş ortamında varlıklarını sürdürmek ve uluslararası toplumun taleplerini karşılamak amacıyla KSS uygulamaları alanında pratik ve değerli yeşil pazarlama stratejileri geliştirmeye teşvik edilir. Ancak, ilgili literatürde şaşırtıcı ve kritik araştırma boşlukları olduğundan, uygulayıcılar araştırma topluluğunun desteğinden mahrum kalmaktadır. Bu sorunu ele almak için mevcut literatüre dayalı olarak bir dizi kriter geliştirilmiş ve bu kriterlerin önemine dayanarak Delphi, CRITIC ve MACONT prosedürlerini içeren yeni bir karar verme yaklaşımı kullanılarak ağırlıkları daha da değerlendirilmiştir. Bu metodolojilere ek olarak, sonuçlar, aşırı karmaşık belirsizlikleri yönetebilen son derece güçlü, güvenilir ve pratik bir çerçeve sunan Tip-2 Neutrosophic Fuzzy Numbers kullanılarak güçlendirilmiştir. Ayrıca, geliştirilen algoritmanın ileri matematik bilgisi gerektirmeyen son derece pratik, anlaşılır ve kolay uygulanabilir bir yapıya sahip olduğunu belirtmek önemlidir. Çalışmanın temel bulguları, EN9 Arazi Kullanımı kriterinin 0.04673'lik bir önem puanıyla en etkili kriter olduğunu göstermektedir. Ayrıca, SO5 İK politikaları tarafından çalışma yerlerinin değiştirilmesi (0.03446) ve EN4 sera gazı emisyonlarını azaltmaya yatırım yapma (0.03413) kriterleri, ilk önemli faktörü takip etmektedir. Buna ek olarak, çalışmanın alternatiflere ilişkin temel bulgusu, A1 Netlog Co.'nun yeşil pazarlama uygulamaları açısından en uygun firma olduğudur. Önerilen modelin güvenilirliğini ve geçerliliğini doğrulayan bir sağlamlık kontrolü yapılmıştır.The logistics industry encounters significant pressure to adopt CSR practices due to the growing concerns of external stakeholders related to environmental pollution and the need to thrive in a highly competitive business environment. In addition to internal motivations, international bodies and governments exert high pressure on logistics enterprises to implement CSR practices in all business activities of the logistics firms, aligning with global concerns about environmental pollution and the adverse effects of logistics and transportation industries. That's why firms are encouraged to develop practical and valuable green marketing strategies within the domain of CSR practices to stay in the competitive business environment and meet the demands of the international society. However, practitioners are deprived of the support from the research society, as there are surprising and critical research gaps in the relevant literature. To address this, a set of criteria has been developed based on the existing literature and their weights have been further assessed based on their importance in a practical business setting by using a novel decision-making approach including Delphi, CRITIC and MACONT procedures. Besides these methodologies the results have been strengthened with the help of Type-2 Neutrosophic Fuzzy Numbers, providing an incredibly robust, reliable, practical framework that can handle excessively complex uncertainties. Also, it has a very practical, understandable, and easily applicable algorithm without requiring advanced mathematical knowledge. The main findings of the study show that the most influential criterion is EN9 Land usage, with a significance score of 0.04673. Besides, SO5 Changing places of work by HR policies (0.03446) and EN4 Investing in reducing greenhouse gas emissions (0.03413) criteria follow the first important factor. In addition to that, the paper's main finding concerning the alternatives is that A1 Netlog Co. is the most feasible firm concerning green marketing practices. The robustness check confirms the proposed model's reliability and validity
Capacity Planning for Electricity Utility Call Centers: a Time Series Analysis Approach
No full textIEEE SMC; IEEE Turkiye SectionElectric power systems are crucial for modern society, yet their reliability can be challenged by unforeseen disruptions, causing electricity supply disruptions. Call centers are essential for managing customer inquiries during such outages, acting as communication hubs for electricity utility companies. Effective capacity planning is vital for these call centers to maintain efficient operations and meet customer demands promptly. Proper workforce management ensures that enough skilled agents can handle calls effectively and maintain high service quality. Capacity planning begins with analyzing historical data to understand call volumes, patterns, and peak times. This data analysis identifies trends and factors influencing call patterns, enabling accurate forecasting of future demand and optimizing staffing levels. This paper provides a comprehensive overview of quantitative forecasting methods, focusing on Time Series Analysis applied to a dataset from a Turkish electric utility company that exhibits typical seasonal fluctuations. Specifically, the study examines the performance of AutoRegressive Integrated Moving Average and Seasonal AutoRegressive Integrated Moving Average models. Results indicate that both models perform well, with the Seasonal AutoRegressive Integrated Moving Average model demonstrating slightly superior performance compared to the AutoRegressive Integrated Moving Average model. This suggests that the Seasonal AutoRegressive Integrated Moving Average model may be more suitable for forecasting inbound calls at electricity utility call centers. This paper's detailed analysis and methodology offer valuable insights for optimizing operational efficiency, reducing costs, and enhancing customer satisfaction in dynamic and challenging operational scenarios. © 2024 IEEE
Barriers To Gender-Based Pro-Environmental Travel Behavior
No full textThis chapter aims to rationally analyze responsible travel behavior from the sustainability and development perspective, indicating barriers and implications toward tourists’ pro-environmental behavior. Based on sustainability, the triple bottom line shows possible ways to move from the previous travel behavior via sustainable behavior, highlighting the ‘Go Green’ concept influencing marketing, communication, and policies. Gender implications become important keys to sustainable behavior patterns via marketing, communication, and policies. Also, the chapter integrates the current practice of the United Nations via sustainable development goals with implementation as a part of travel behavior. Thus, the viewpoints analyze the different marketing, communication, and policy approaches via different dimensions; values, social norms, and travel constraints through sustainable travel behavior. Furthermore, the scope of different gender perceptions is from the lens of tourists via attitudes, behavior, and characteristics. Hence, the chapter conceptualizes gender-based pro-environment and concludes with coherent predictions of pro-environment behavior. © The Editors and Contributors Severally 2024
Navigating Financial Cycles: Economic Growth, Bureaucratic Autonomy, and Regulatory Governance in Emerging Markets
No full textApaydin, Fulya/0000-0001-7208-5857Political decisions over economic growth policies influence the degree of bureaucratic autonomy and regulatory governance dynamics. Yet, our understanding of these processes in the Global South is somewhat limited. The article studies the post-Global Financial Crisis period and relies on elite interviews and secondary sources from Turkey. It problematizes how an economic growth model dependent on foreign capital inflows, which are contingent on global financial cycles, influences the trajectory of bureaucratic autonomy. Specifically, we argue that dependence on foreign capital flows for economic growth creates an unstable macroeconomic policy environment: while the expansionary episode of the global financial cycle masks conflicts between the incumbent and bureaucracy, the contractionary episode threatens the political survival of the incumbent. In the case of Turkey, this has incentivized the ruling coalition to resort to executive aggrandizement to control monetary policy and banking regulation, which resulted in a dramatic decay of the autonomy of the regulatory agencies since 2013.Spanish Ministry of Science, Innovation and Universities [PGC2018-093719-A-I00]The earlier versions of this paper were presented at ECPR General Conference 2021 and the PSA General Conference in 2022. We would like to thank the participants and discussants on these occasions. We are grateful to Emmanuel Mathieu, Isik Ozel, and Kutsal Yesilkagit for their comments and feedback on the earlier versions. We are grateful to five anonymous referees whose critical and detailed suggestions have contributed to development of the article. Finally, we are thankful to David Levi-Faur for his guidance and patience since the initial submission. This study was supported by The Spanish Ministry of Science, Innovation and Universities, grant no. PGC2018-093719-A-I00.Social Science Citation Inde
Hb-Egf Promotes Progenitor Cell Proliferation and Sensory Neuron Regeneration in the Zebrafish Olfactory Epithelium
No full textFuss, Stefan H/0000-0002-3076-1121Maintenance and regeneration of the zebrafish olfactory epithelium (OE) are supported by two distinct progenitor cell populations that occupy spatially discrete stem cell niches and respond to different tissue conditions. Globose basal cells (GBCs) reside at the inner and peripheral margins of the sensory OE and are constitutively active to replace sporadically dying olfactory sensory neurons (OSNs). In contrast, horizontal basal cells (HBCs) are uniformly distributed across the sensory tissue and are selectively activated by acute injury conditions. Here we show that expression of the heparin-binding epidermal growth factor-like growth factor (HB-EGF) is strongly and transiently upregulated in response to OE injury and signals through the EGF receptor (EGFR), which is expressed by HBCs. Exogenous stimulation of the OE with recombinant HB-EGF promotes HBC expansion and OSN neurogenesis in a pattern that resembles the tissue response to injury. In contrast, pharmacological inhibition of HB-EGF membrane shedding, HB-EGF availability, and EGFR signaling strongly attenuate or delay injury-induced HBC activity and OSN restoration without affecting maintenance neurogenesis by GBCs. Thus, HB-EGF/EGFR signaling appears to be a critical component of the signaling network that controls HBC activity and, consequently, repair neurogenesis in the zebrafish OE.Scientific and Technological Research Council of Turkey (TUEBITAK) [119Z081, BIDEB 2211-A]Work on this study was supported by The Scientific and Technological Research Council of Turkey (TUEBITAK) Grant Number 119Z081 to SHF. YK acknowledges support from TUEBITAK-BIDEB 2211-A. The authors are grateful to Umut Sahin for valuable suggestions and reagents
Optimizing soft robot design and tracking with and without evolutionary computation: an intensive survey
No full textSoft robotic devices are designed for applications such as exploration, manipulation, search and rescue, medical surgery, rehabilitation, and assistance. Due to their complex kinematics, various and often hard-to-define degrees of freedom, and nonlinear properties of their material, designing and operating these devices can be quite challenging. Using tools such as optimization methods can improve the efficiency of these devices and help roboticists manufacture the robots they need. In this work, we present an extensive and systematic literature search on the optimization methods used for the mechanical design of soft robots, particularly focusing on literature exploiting evolutionary computation (EC). We completed the search in the IEEE, ACM, Springer, SAGE, Elsevier, MDPI, Scholar, and Scopus databases between 2009 and 2024 using the keywords "soft robot," "design," and "optimization." We categorized our findings in terms of the type of soft robot (i.e., bio-inspired, cable-driven, continuum, fluid-driven, gripper, manipulator, modular), its application (exploration, manipulation, surgery), the optimization metrics (topology, force, locomotion, kinematics, sensors, and energy), and the optimization method (categorized as EC or non-EC methods). After providing a road map of our findings in the state of the art, we offer our observations concerning the implementation of the optimization methods and their advantages. We then conclude our paper with suggestions for future research.TUBIdot;TAK within the scope of the 2232-B International Fellowship for Early Stage Researchers Program [121C145]This work is funded by TUB & Idot;TAK within the scope of the 2232-B International Fellowship for Early Stage Researchers Program number 121C145.Science Citation Index Expande
Improving Covid-19 Detection: Leveraging Convolutional Neural Networks in Chest X-Ray Imaging
No full textThe Society of Photo-Optical Instrumentation Engineers (SPIE)The global impact of the COVID-19 pandemic has significantly disrupted healthcare systems w orldwide. Amidst challenges, there is a crucial demand for efficient me thodologies to ex pedite di sease de tection. Th is research underscores the potential of Deep Neural Networks in enhancing pandemic management over the past five years. Focusing on Artificial Intelligence (AI) application in COVID-19 detection through X-ray imaging, this research advocates using Visual Geometry Group (VGG’16), a Convolutional Neural Network (CNN) used for image classification w ith m ultiple l ayers. T hese C NNs a ct a s c lassifier-based sy stems, tr eating im ages as structured data arrays to identify and learn patterns. Quantifying the model’s effectiveness t hrough t he a ccuracy s core, t his r esearch r eveals a 0 .90% accuracy, indicating the model’s accurate detection of COVID-19 cases in X-ray images. Additionally, the study highlights a significant a chievement w ith a l ess t han 1 0% f alse p ositive r ate, c rucial f or r eliable a nd p rompt COVID-19 diagnoses in the healthcare industry. In conclusion, this research presents an AI-driven approach, utilizing VGG’16 and convolutional neural networks to enhance the efficiency an d ac curacy of CO VID-19 de tection in X-ray imaging. The high accuracy score and low false positive rate positions this methodology as a valuable contribution, offering robust pandemic management and healthcare decision-making. © 2024 SPIEEuropean Commission, EC; Erasmus+, (101082683); Erasmus