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Araştırmacılar(12)

• Askin, Ali
• Celik, Erkan
• Gul, Muhammet
• Kaya, Sema Kayapinar
• Mete, Süleyman
• Öner, Mahir
• Özdemir, Yasal
• Polat, Elifcan Göçmen
• Senel, Bilgin
• Senel, Mine
• Susam, Selim Orhun
• Ünlükal, Ceren

• MakaleYalnız künye2026Scopus SJRQ2/r/munzur/1504
  A Bernstein polynomial estimation of the moment generating function

  Susam, Selim Orhun

  We study Bernstein polynomial smoothing for nonparametric estimation of the moment generating function (MGF) of a distribution supported on (Formula presented.). We prove strong consistency of the Bernstein-smoothed MGF estimator and show that, when the smoothing degree m grows sufficiently fast, it shares the same (Formula presented.) asymptotic normal distribution as the empirical MGF estimator, with variance (Formula presented.). A second-order bias–variance expansion reveals that Bernstein smoothing yields a bias of order (Formula presented.) and a variance-reduction term of order (Formula presented.). This leads to the optimal smoothing rate (Formula presented.) for pointwise mean squared error (MSE) minimization. Simulation results confirm that the Bernstein estimator is especially effective in challenging boundary-dominated settings, notably for U-shaped beta models and for larger positive t values. Overall, Bernstein polynomial smoothing provides a simple, theoretically justified, and practically effective tool for nonparametric MGF estimation on compact supports.

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• MakaleYalnız künye2026Scopus SJRQ4/r/munzur/1459
  Smart logistics with a maturity assessment perspective

  Göçmen Polat, Elifcan; Derse, Onur

  The logistics sector is influenced by digitalisation and technological advancement in improving sustainability and efficiency. Logistics companies, which are highly capable of incorporating innovative technologies into their business flows, have made profound impacts, ultimately leading to a transformation in logistics services. In this context, this study presents the current and target maturity levels to make an international logistics company smarter and provides recommendations as an improvement road map for the logistics sector. Within the scope of this research, nine dimensions and 36 maturity items of the smart logistics (SL) concept are discussed to assess the maturity levels using the weighted maturity score calculation model (WMSC), in which evaluation of all maturity items using the capability maturity model (CMM) maturity levels and calculation of the criteria weights using fuzzy DEMATEL (F-DEMATEL) is integrated. Computational results show that warehouse management systems and material flow control systems have lower maturity levels. Thus, product picking by voice, integrating the warehouse management system, ensures real-time updates and data integration, reducing stockouts and overstock.

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• MakaleYalnız künye2026Scopus SJRQ2/r/munzur/1350
  A bias-corrected partial bernstein copula approach for nonparametric regression

  Susam, Selim Orhun

  Multivariate Bernstein polynomials yield smooth, boundary–bias–free estimators for copulas and their derivatives. The classical partial Bernstein copula derivative of Janssen et al. (2016) suffers from an uncorrected first–order bias that can dominate the mean squared error (MSE) in moderate samples. We introduce a simple double–difference correction that removes the entire leading bias term while increasing the variance by a small fixed multiplicative factor only. When this bias–reduced partial derivative is plugged into the copula based regression integral, the resulting estimator achieves substantially smaller bias and uniformly lower MSE than the classical version. Analytic bias–variance expansions are provided, and a comprehensive Monte Carlo study shows up to 50% reductions in MSE across a range of Bernstein copula degrees. A real data application to the mcycle dataset further demonstrates the practical advantages of the method, with the smoothing parameters selected by least squares cross validation (LSCV).

  AtıfScopus1·WoS1·OpenAlex1

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• MakaleYalnız künye2026Scopus SJRQ3/r/munzur/1250
  A multi-parametric unit distribution via Bernstein polynomials

  Susam, Selim Orhun

  This study develops the method of constructing a multi-parametric distribution on the unit interval using Bernstein polynomials and investigates its key statistical properties. The performance of the proposed distribution’s parameter estimators was evaluated by Monte Carlo simulation under both maximum-likelihood (MLE) and minimum-distance frameworks, with the MLE approach generally yielding lower estimation error. A real data example illustrates the advantages of the construction method. The results reveal that the Bernstein distribution provides superior goodness-of-fit to the dataset compared with competing models.

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• 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 SJRQ2/r/munzur/913
  Risk Assessment via Hazard Scenario in Cereal Production Under Rising CO

  Susam, Selim Orhun; Peker, Ayse Esra; Hudaverdi, Burcu

  Global food security has been seriously threatened by air pollution and climate change. The impact of CO on crop output is complicated because of its interactions with temperature, nutrient availability, and other pollutants, even though it is necessary for photosynthesis. This study develops a copula-based hazard modeling framework to assess how increasing CO concentrations affect cereal production risk across multiple crops. By integrating hazard scenario analysis with localized dependence measures, we estimate both failure probabilities and dynamic associations between CO emissions and cereal yields. A novel localized version of Kendall’s implemented via a Bernstein copula approximation, enables flexible modeling of heterogeneous and nonlinear dependence structures. As the relationship between CO emissions and crop-specific yields changes in both density and direction, it may indicate asymmetries or nonlinearities that are missed by measures of global dependence. Empirical results reveal distinct crop-specific responses. While CO levels enhance yields for rice, millet, and sugar beet, they reduce or destabilize production for rye and lentil, indicating asymmetric sensitivities. Failure probabilities increase with the time horizon, reflecting the accumulation of climate-related production risk. The findings emphasize the significance of integrating probabilistic hazard modeling into climate-resilient agricultural planning and food security policies, as crop-specific risk exposure has increased in recent time periods.

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  AtıfWoS1·OpenAlex1

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• MakaleAçık Erişim2026Scopus SJRQ2/r/munzur/632
  Bernstein-smoothed estimation and bootstrap inference for the lower-tail Spearman's rho curve

  Lyu, Guanjie; Ouimet, Frédéric; Susam, Selim O.

  This paper studies a Bernstein-smoothed plug-in estimator for the lower-tail Spearman's rho curve, a rank-based measure of local concordance defined through a normalized copula integral over the lower-left square (Formula presented.). The estimator applies the lower-tail Spearman functional to the empirical Bernstein copula and introduces a degree parameter that controls finite-sample regularization. The contribution is target-specific estimation and inference for the lower-tail Spearman's rho curve rather than a new general-purpose copula estimator. We establish uniform strong consistency on compact intervals away from zero whenever (Formula presented.). Under a target-specific integrated Bernstein-bias condition and (Formula presented.), we derive functional weak convergence with the same first-order Gaussian limit as the empirical copula-based estimator; this degree regime includes (Formula presented.). For inference, we justify a smoothed beta bootstrap based on sampling from the empirical beta copula and construct pointwise confidence intervals from the absolute centred bootstrap root. Monte Carlo experiments for the Farlie–Gumbel–Morgenstern, Gaussian, Clayton, and Frank copulas assess pointwise coverage over the threshold grid and show that Bernstein smoothing generally reduces integrated variance and often lowers mean integrated squared error under weak to moderate dependence. Additional common-sample experiments compare the proposed estimator with the empirical beta and empirical checkerboard Bernstein copula estimators in terms of pointwise error, integrated error, computation time, selected degrees, numerical stability, and pointwise coverage. A sensitivity analysis shows that (Formula presented.) is a simple theoretically admissible default that avoids the most severe oversmoothing. A descriptive application to the Loss–ALAE insurance claims data illustrates how the lower-tail Spearman's rho curve can reveal local dependence features that are not captured by the global Spearman correlation.

  İncele
• Kitap BölümüYalnız künye2026/r/munzur/593
  Current Trends and Future Perspectives for Post-Disaster Assembly Areas

  Polat, Elifcan Göçmen; Polat, Erkan

  Disasters bring about significant material damage and social disruptions, affecting entire communities or specific groups. These events can halt daily life and human activities, often exceeding the handling capacity of the affected population. For effective disaster management, all stages-including prevention, mitigation, preparation, response, and recovery must be spatially planned. The identification of post-disaster assembly areas is critically important for minimizing loss of life and property. This study examines theoretical and practical research on assembly areas from the literature. In determining suitable assembly areas, factors such as population density, accessibility, proximity to hazard sources, land type, and access to essential services and methods as Geographical Information Systems (GIS) and Multi-Criteria Decision Making (MCDM) provide valuable framework for addressing assembly area selection challenges. Findings from the literature indicate that the assembly areas should be reassessed in the context of evolving needs and regulatory requirements.

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• MakaleYalnız künye2025/r/munzur/6010
  Risk assessment in cheese production process using failure mode and effects analysis and intuitionistic fuzzy topsis

  Ünlükal, Ceren; Şenel, Mine; Şenel, Bilgin; Avarbek, Kenan

  The aim of this study is to evaluate the cheese production process, which plays a significant role in the milk and dairy industry, in terms of physical, chemical, and microbiological risks using the integrated Failure Mode and Effects Analysis (FMEA) and Intuitionistic Fuzzy TOPSIS (IF-TOPSIS) methods. Although the classical FMEA method is a widely used analytical technique that helps identify and reduce potential risks in processes, it has some drawbacks: such as the possibility that different failure modes may have the same risk priority values (RPN) and risk factor weights. To address this shortcoming, the intuitionistic fuzzy set theory was used to determine the RPN values. This study aimed to identify failures that may occur at critical steps in the production chain, their possible causes, their impact on product quality, and the priority of preventive actions. The study demonstrates that the intuitionistic fuzzy multi-criteria decision-making (MCDM) approach is an effective tool for food safety and quality management in the dairy products industry.

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• MakaleYalnız künye2025Scopus SJRQ2/r/munzur/2147
  A flexible parameter estimation method for the Farlie-Gumbel-Morgenstern copula: a simulation study

  Susam, Selim Orhun

  This research presents a minimum distance method based on the Bernstein empirical copula process for estimating the dependence parameter of the Farlie-Gumbel-Morgenstein copula. Also, this study examines its performance through a comprehensive Monte Carlo simulation study. The findings in this paper demonstrate that selecting the optimal degree of the Bernstein empirical copula has a significant impact on the performance of the new estimation method. The proposed estimator achieves optimal performance in terms of mean squared error (MSE) for the parameter range (Formula presented.) in small sample sizes, while outside this range, its performance varies depending on the degree of the Bernstein empirical copula. Finally, we apply the new method to real data for illustrative purposes.

  AtıfScopus3·WoS4·OpenAlex3

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