Sürdürülebilir Kalkınma Amaçları

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Araştırmacılar(10)

• Baskak, Dilber
• Dağdelen, Buse Özüm
• Gundogdu, Yunus Emre
• Özbey, Sümeyye
• Polat, Berivan Yılmazer
• Solmaz, Adnan
• Tetik, Nevzat
• Yanilmaz, Sumeyye
• Yazdıç, Fadime
• Yücesan, Melih

• MakaleAçık Erişim2026/r/munzur/4719
  Analysis of buildings in Tunceli - Pülümür district with the Canadian seismic screening method

  Gundogdu, Yunus Emre; Polat, Berivan Yilmazer

  This study, which was conducted in the P & uuml;l & uuml;m & uuml;r district of Tunceli, was carried out in an area with high seismic risk due to the region's proximity to the Bing & ouml;l-Yedisu Fault. In the study, the earthquake safety of the existing building stock was assessed using visual inspection methods. In this context, 172 buildings in the P & uuml;l & uuml;m & uuml;r district of Tunceli province were examined in detail in terms of earthquake safety using the Canadian Seismic Screening Method. In the analysis, seismic safety levels of the buildings, structural and nonstructural risks were taken into consideration and seismic priority indexes (SPI) were determined. The results of the study revealed that a large portion of buildings in the P & uuml;l & uuml;m & uuml;r district carry different levels of risk of earthquake. Specifically, the evaluated building stock was entirely constructed before the critical year of 2007 and exhibits high seismic vulnerability. This critical threshold is technically attributed to two main regional factors: the design practices predating the 2007 Turkish Earthquake Code and the absence of ready-mixed concrete technology in Tunceli province prior to that year. Furthermore, based on the method's classification, it is suggested that buildings with a Seismic Priority Index (SPI) greater than 20, which indicates High to Very Hazardous risk levels, should be prioritized for detailed assessment and retrofitting, and that local governments should develop incentive policies for these mitigation efforts.

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  İncele
• Derleme MakaleAçık Erişim2026Scopus SJRQ3/r/munzur/6087
  Afet Direnci Kavramını Anlamak: Direnç Göstergeleri Üzerine PRISMA Yöntemiyle Sistematik Bir İnceleme

  Peker, İskender; Ozbey, Sümeyye

  Doğal ve beşerî faktörlerin bir araya gelmesiyle oluşan afetler, toplumların güvenliği, sürdürülebilir kalkınması ve yaşam kalitesi üzerinde ciddi tehditler oluşturmaktadır. Afetlerin önlenebilmesi veya etkilerinin azaltılabilmesi, toplumların ve kurumların afet direncinin artırılmasıyla doğrudan ilişkilidir. Afetlere dirençli toplumlar, afetlerle karşı karşıya kaldıklarında daha az kayıp yaşamakta, daha hızlı toparlanabilmekte ve yeniden işlevsel hale gelebilmektedir. Afetlerin etkilerinin azaltılması ve toplumsal hazırlığın artırılması amacıyla toplumsal afet direnci kavramına literatürde yer verilmiş olmasına rağmen bu kavrama ilişkin teorik çerçeve sınırlıdır. Kavramın tanımlanması, etkileyen faktörlerin belirlenmesi, hangi yöntemlerle değerlendirilebileceği açık değildir. Bu çalışma, söz konusu kavramsal boşluğu doldurmak amacıyla PRISMA yöntemi kullanılarak kapsamlı bir literatür analizi gerçekleştirmekte ve toplumsal afet direncine dair metodolojik bir çerçeve sunmaktadır. Analiz sonucunda, afetlere karşı kırılganlığın azaltılması için dirençlilikle ilişkili mevcut çalışmalar sistematik biçimde değerlendirilmiş, ayrıca bu kavramın ölçülebilmesi için kullanılabilecek bir dizi ilke ve gösterge sunulmuştur. Sonuç olarak çalışma, afetlere karşı kırılganlığı azaltmaya ve sürdürülebilir bir afet yönetimi yaklaşımı geliştirmeye katkı sunacak kavramsal ve pratik öneriler ortaya koymaktadır.

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  AtıfOpenAlex1

  İncele
• MakaleAçık Erişim2026/r/munzur/5934
  Comparative Analysis of the Seismic Risk of Tunceli-Ovacık Rural Building Stock Using Different Rapid Screening Methods

  Polat, Berivan Yılmazer; Ayhan, Ezgi

  Located at the intersection of the Yedisu Segment, a seismic gap, and the active Ovacık Fault, the Tunceli-Ovacık district is a region with a high earthquake risk but an unclear level of structural fragility. This study aims to assess the seismic safety of the rural building stock located in a seismically critical area. To this end, the Turkish Rapid Visual Screening (RVS), based on local parameters, and the Canadian Seismic Survey Method, widely used in international literature, were applied to determine the current condition of the buildings; the earthquake risk of the region was analyzed based on the results obtained. Furthermore, similarities and differences between the methods were comparatively examined to ensure scientific integrity. Within the scope of the study, 209 buildings representing the building typology in the region, 88% of which are masonry-mixed systems, were analyzed using both rapid assessment algorithms. While the overall risk distribution ratios were similar, building-level matching analyses showed a medium level of agreement between the methods. This indicates that the local and universal methods, rather than definitively verifying each other, provide complementary data by focusing on different parameters in the seismic assessment of the rural building stock. This study demonstrates that an integrated risk mapping approach, where different methodologies complement each other, can offer a rapid and reliable decision support mechanism for urban transformation strategies in cities with high earthquake risk, such as Tunceli.

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  İncele
• MakaleYalnız künye2026Scopus SJRQ1/r/munzur/1234
  Enhancing waiting time performance of clinical laboratories for pregnant patients with seasonal respiratory diseases: a simulation-based Lean Six Sigma approach

  Ortíz-Barrios, Miguel; Celani de Souza, Helder Jose; Petrillo, Antonella; Gul, Muhammet; Yücesan, Melih; Navarro-Jiménez, Eduardo; Alfaro-Saíz, Juan-José; Ariza-Ortíz, Andrés

  Purpose – Clinical laboratory performance is critical in managing seasonal respiratory diseases (SRDs); however, prolonged waiting times can lead to patient dissatisfaction and nonquality costs. This challenge is particularly acute for pregnant patients, who face increased health risks from diagnostic delays. This study aims to improve waiting times before sample collection in clinical laboratories serving pregnant patients with SRDs by integrating Lean Six Sigma (LSS) and Discrete-Event Simulation (DES). Design/methodology/approach – The proposed framework was validated in a public clinical laboratory using the DMAIC (Define–Measure–Analyze–Improve–Control) methodology. DES was embedded within the Analyze and Improve phases to model patient flow and assess improvement scenarios before implementation. Findings – The integrated LSS–DES approach resulted in a significant reduction in waiting times. During SRD peak periods, waiting time before sample collection for pregnant patients decreased from 1.01 to 0.10 h per patient. These results demonstrate the framework's effectiveness and practical usefulness for decision-makers seeking performance improvements in resource-constrained healthcare environments. Originality/value – This study enhances existing literature by integrating LSS and DES to address laboratory performance challenges associated with SRDs. The combined LSS-DES used for pregnant patients during outbreak periods is novel. The study offers contextual innovation for a vulnerable population, methodological advancement through embedding DES within the DMAIC cycle, and practical laboratory validation. The framework is particularly valuable for low- and middle-income countries (LMICs), where scalable solutions are essential.

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• MakaleAçık Erişim2026Scopus SJRQ1/r/munzur/1015
  Analyzing Failures In Wind–Solar Hybrid Energy Systems Using a Fuzzy-Based BWM-MARCOS Approach: Challenges and Solutions

  Başhan, Veysi; Yucesan, Melih; Demirel, Hakan; Gul, Muhammet

  The reliability of hybrid renewable energy systems (HRES) depends heavily on the identification and management of potential failure modes. This study employs a fuzzy-based BWM-MARCOS approach to systematically analyze and prioritize failure modes within wind–solar hybrid systems. The model aims to prioritize the failures considering four important risk parameters: (1) severity of the failure on system, staff, and failure, (2) failure occurrence chance, (3) effort and ease of detecting the cause of the failure, and (4) economic impact of the failure. In this context, four key risk indicators were evaluated to rank failures, revealing that SP1 (cell damage), ESS1 (battery degradation), and WT11 (battery fire) are the most critical due to their potential impact on system operations. Sensitivity analysis confirmed the stability of these rankings under varying parameter weights. Additionally, cross-method validation using fuzzy TOPSIS, SAW, and MARCOS demonstrated high correlation coefficients, underscoring the reliability of the results. Tailored mitigation strategies, including advanced diagnostics, durable materials, and robust monitoring systems, are proposed to address these critical failures. While the current methodology applies to various HRES configurations, future research should incorporate real-world operational data and machine learning techniques to enhance predictive capabilities and dynamic risk management.

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  AtıfScopus7·WoS7·OpenAlex8

  İncele
• MakaleAçık Erişim2026Scopus SJRQ1/r/munzur/943
  Assessing interrelationships among circular economy implementation strategies

  Ahmadi, Hadi Badri; Gul, Muhammet; Gupta, Himanshu; Yucesan, Melih; Liou, James J.H.

  Strategies for implementing a circular economy (CE) are designed to enhance resource efficiency, minimize the consumption of raw materials, and decrease waste. Although many articles have investigated CE implementation strategies, research focusing on the interactions and interrelationships among these strategies remains scarce. To address this issue, this study develops an evaluation framework, with the aim of assessing the interactions among strategies for CE implementation in the context of the manufacturing sector of an emerging economy using Decomposed Fuzzy Decision-Making Trial and Evaluation Laboratory (DF-DEMATEL) methodology. The findings suggest that “Investment in green technology” is the most critical strategy and should receive the greatest attention for successfully implementing CE. This research helps industrial decision-makers and specialists to invest in the most critical strategies within their supply chains and move towards sustainable development.

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• MakaleAçık Erişim2025/r/munzur/6039
  Endemik Tunceli Sarımsağı (Allium tuncelianum) Toprağından Bacillus velezensis İzolasyonu, Moleküler Tanımlanması ve Antimikrobiyal Özellikleri

  Yazdıç, Ferit Can; Yazdıç, Fadime; Karaman, Altuğ; Yücel, Halit; Kilic, Sükran

  Antibiyotik direnci, yeni antimikrobiyal ajanların keşfini gerektiren, her geçen gün büyüyen küresel bir endişedir. Spor oluşturan gram pozitif bir bakteri olan Bacillus velezensis, lipopeptitler (sürfaktin, fenjisin, iturin) ve poliketidler (difficidin, makrolaktin) gibi biyoaktif bileşikler üretmesiyle bilinmektedir. Bu maddeler geniş spektrumlu antimikrobiyal özellikler göstermekle beraber, bitki patojenlerini baskılar ve bitki büyümesini teşvik eder. Bu çalışmanın amacı, Türkiye'deki endemik Tunceli sarımsağı (Allium tuncelianum (Kollmann) Özhatay, B. Mathew ve Şiraneci) ile ilişkili topraktan B. velezensis'in izolasyonunu, tanımlanmasını ve antimikrobiyal potansiyelini araştırmaktadır. B. velezensis ŞK_B3 suşu, 16S rDNA dizilemesi kullanılarak tanımlandı ve gram pozitif (Staphylococcus aureus, Bacillus subtilis) ve gram negatif (Escherichia coli, Pseudomonas aeruginosa) bakterilere karşı antimikrobiyal aktivite açısından test edildi. Streptomisin ve penisilin gibi standart antibiyotiklere kıyasla orta düzeyde aktivite gösterse de, etkinliği özellikle gram pozitif bakterilere karşı dikkat çekici olduğu tespit edilmiştir. Sonuçlar, özellikle gram pozitif bakterilere karşı orta düzeyde inhibitör aktivitesi olduğunu göstermiştir. Bu da tarımda bir biyokontrol ajanı ve yeni antibiyotik kaynağı olarak potansiyelini vurgulamaktadır. Etkin bileşiklerin aydınlatılması ve antimikrobiyal etkinliğin artırılması için daha ileri çalışmalara ihtiyaç vardır.

  İncele
• MakaleAçık Erişim2025Scopus SJRQ3/r/munzur/5683
  Afet Yönetim Merkezlerinin Risk Yönetimi Performansının Çok Kriterli Karar Verme Yöntemleriyle Değerlendirilmesi: Güneydoğu Anadolu Bölgesi Örneği

  Gul, Mervegül; Ozbey, Sümeyye

  Afetler, insanların günlük hayat akışını kesintiye uğratan fiziksel ekonomik ve sosyal kayıplara sebep olan doğal teknolojik veya insan kaynaklı olayların sonuçlarıdır. Ulusal düzeyde afet risklerinin oluşumunu önlemek ve riskleri azaltmak yerel düzeyde yapılan çalışmalara bağlıdır. Afet yönetim merkezleri, afetlerden sonra oluşabilecek can ve mal kaybının önüne geçilebilmesinde yerelin kritik bileşenidir. Etkilenen bölgelerdeki afet yönetim merkezlerinin, afet ve acil durumlara hazırlık düzeyi acil durumların afete dönüşmesini engeller. Türkiye’nin Güneydoğu Anadolu Bölgesi, deprem, heyelan, sel, terör ve çığ gibi bir çok afete maruziyet yaşayan bir bölgedir. Yerelin afet hazırlığının artırılması için çalışma kapsamında Güneydoğu Anadolu Bölgesinde 4 şehir olan Gaziantep, Mardin, Diyarbakır ve Kilis illerinin AFAD (Afet ve Acil Durum Müdürlüğü) merkezlerinin afet risk yönetimi performansları Çok Kriterli Karar Verme Yöntemi (ÇKKV) ile değerlendirildi. Risk yönetimi performansı kriterlerinin önem ağırlıklarını belirlemede AHP (Analytical Hierarchy Process) yöntemi ve illerin hazırlık düzeyinin karşılaştırılması için TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) yöntemiyle sıralama yapılmıştır. Çalışma sonuçlarında afet yönetim merkezlerinin risk yönetimi performansının değerlendirilmesinde en önemli kriter riski belirleme, hazırlık düzeyi en yüksek il olarak Mardin ili belirlenmiştir. Çalışmanın bölgenin sürdürülebilir kalkınmasını tehlikeye atan afet potansiyeli olan kırılganlıkların belirlenmesinde, afetlere karşı dirençliliğin artırılması ve afet hazırlık planları için bir araç olması hedeflenmektedir.

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  İncele
• Kitap BölümüYalnız künye2025/r/munzur/2038
  Bayesian Best–Worst Method Application for Assessing the Potential Effecting Areas of Climate Change: A Case Study in Turkey

  Konurhan, Zekeriya; Yücesan, Melih; Gul, Muhammet

  ‘Climate Change’ is a term used to refer to global changes in the Earth's average temperature and the consequences of changes in temperature. More clearly, it demonstrates changes in temperature and weather patterns over time. The emergence of this situation directly or indirectly affects irreparable damages and major/minor disasters in many areas. Determining the answer to the question of which of these areas has an impact at what level of importance will provide guidance on which one should be prioritized in carrying out an effective treatment. Therefore, in this study, this problem is ad-dressed as a multi-criteria decision problem using Bayesian Best–Worst Method. The potential impacts have been categorized under 8 main areas and weighted via participating of 8 competent experts (geography, emergency disaster management, geomorphologist, climate scientist etc.) in the field of climate change. The study results determined that B (Ecosystems and Water Resources) has the most critical impact area, with 0.200. The least essential domain is G4 (Adaptation and Resilience Strategies in the Tourism Industry), which weighs 0.012. The results showed that they provide important clues regarding which impacts should be addressed first.

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• MakaleAçık Erişim2025Scopus SJRQ2/r/munzur/1927
  Forecasting daily natural gas consumption with regression, time series and machine learning based methods

  Yucesan, Melih; Pekel, Engin; Celik, Erkan; Gul, Muhammet; Serin, Faruk

  An effective short-term natural gas forecasting method contributes to social contributions and allows industrial chain elements to function effectively and minimize economic losses. We dealt with a comparative framework on the applicability of different methods in daily natural gas service (NGS) consumption forecasting. In this context, time series, machine learning, evolutionary and population-based approaches, and their hybrid versions are applied to the NGS data. Hybridized approaches are tested in the scope of NGS consumption forecasting for the first time in the literature in this study. The case of Turkey is handled, and its NGS data is used to demonstrate the comparative framework’s applicability. The comparative study is assessed in the lights of common forecasting accuracy measures of mean absolute percentage error (MAPE), R-squared (R2), and mean squared error (MSE). According to each method’s results, the seasonal autoregressive integrated moving average with exogenous regressors (SARIMAX) and artificial neural network (ANN) hybrid model provides the most dominant performance with respect to MAPE. The lowest error was obtained with a MAPE value of 0.357 in this hybrid model constructed under seven neurons in its ANN structure. This model is followed by another hybrid model, autoregressive integrated moving average (ARIMA)-ANN, with a MAPE value of 0.5 under nine neurons in terms of accuracy performance. The worst performance value belongs to the Genetic algorithm-ANN hybrid model with a MAPE value of approximately 26%.

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  AtıfScopus16·WoS19·OpenAlex22

  İncele