Sürdürülebilir Kalkınma Amaçları
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- MakaleYalnız künye2026Scopus SJRQ4Smart 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.
- MakaleYalnız künye2025Scopus SJRQ4Spearman dependence function-based goodness-of-fit test for the gene's relation
Susam, Selim Orhun; Hudaverdi, Burcu
A gene network represents the relationship between different groups of genes with various functions, aiming to depict how genes collaborate and influence each other’s activities within a biological system. This relationship can be effectively explained using copulas. Therefore, it is crucial to determine which copula best fits the gene data and provide the most accurate explanation of the relationships between gene groups. In this study, our objective is to introduce a Spearman dependence function-based goodness-of-fit test using Bernstein polynomial approximation. We apply this test to identify a copula model that can effectively explain the relationships between gene groups. A Monte Carlo simulation study is conducted to assess the performance of the proposed test. Next, we analyse histone gene groups using data from yeast cell regulation, as provided by Eisen et al. (1998). Specifically, we investigate the dependence model structures of gene interactions for eight histone genes.
AtıfScopus2WoS2OpenAlex2
İncele - MakaleYalnız künye2025Scopus SJRQ4Deep learning-based hybrid traffic flow prediction model for freight transport
Utku, Anıl; Kaya, Sema Kayapinar; Can, Umit
Urban freight transportation is crucial to sustaining domestic and international trade and fulfilling the regular requirements of community companies and customers. Therefore, this study developed an efficient convolutional neural network (CNN) and long short-term memory (LSTM) based hybrid deep learning model for predicting traffic flow in freight transportation. The number of freight trucks that would travel along 663 Street in Anderlecht, Belgium, and their average speed was predicted. The created model was compared with support vector machine (SVM), linear regression (LR), multilayer perceptron (MLP), random forest (RF), LSTM, and CNN using the success measures. The critical finding of this study is that combining the feature extraction ability of the 1D CNN model with the learning ability of the LSTM model from multivariate traffic data increases the traffic density prediction success compared to other traditional methods. Based on the results of the experiments, the CNN-LSTM model outperformed all the other models employed in this study. With this model, freight density can be successfully predicted, assisting in planning freight transport activities.
- MakaleYalnız künye2023Scopus SJRQ3Uncovering the gap between intention and behaviour towards knowledge sharing: Evidence from a hybrid healthcare institution
Uyan, Umut; Şanal, Musa
This study set out to test an integrative model towards knowledge sharing (KS) practices in health institutions, which have recently been referred to as knowledge-intensive organisations. The model assesses the relative contributions of various organisational and relational factors in explaining knowledge sharing intention (KSI), as well as the moderating effects of both socio-cognitive factors and the nature of knowledge to be shared on the relationship between KSI and knowledge sharing behaviour (KSB). The data utilised in the research were obtained from a health institution designed as a public-private partnership through the survey questionnaires. Findings suggest that highly formalised and hierarchical organisational structures negatively affect KSI, whereas constructive communication climate and organisational integration enhance it. The relationship between facilitating tools and technologies, which is the last of the organisational factors examined, and KSI was non-significant. Two out of the three relational factors, trust and affiliation, positively predicted KSI, but no statistically significant relationship was found between normative beliefs and KSI. Finally, the results suggest that the perceived reciprocity eases the translation of the intention towards KS into actual sharing behaviour, whereas the perceived power loss weakens the mentioned relationship.
AtıfScopus5WoS5OpenAlex4İncele - MakaleYalnız künye2023Scopus SJRQ4Development of a best-worst method based MCDM approach for solar power plant location selection: an application to Tunceli, Turkey
Aykac, Yunus Emre; Yucesan, Melih; Gul, Muhammet
Solar energy stands out with its increasing potential in the world. The decision to choose the location of a solar power plant is very important due to the investment return. In this study, a solar power plant site selection for Tunceli, Turkey is studied with a two-stage multi-criteria decision-making approach. In the first stage, the importance levels of the determined nine factors are obtained by the best-worst method (BWM). In the second stage, the most appropriate site is selected among the eight districts of Tunceli. As a result of the first stage, solar and fault line emerged as the most and least important factor, respectively. The second stage showed that Pertek district is the most suitable place. A comparative framework has been created including five different MCDM methods, which strengthens the final decision's accuracy and reveals whether each method's results are correlated.
AtıfScopus5OpenAlex3İncele - MakaleYalnız künye2020Scopus SJRQ4Development and application of a novel hybrid occupational risk assessment model
Gul, Muhammet
Occupational Risk Assessment (ORA) is so crucial for safety management in the weapons industry since numerous hazards may lead to human casualties. Therefore, occupational health and safety stakeholders suggest proactive approaches in reducing risks to an acceptable level. Therefore, this paper aims to develop a novel hybrid ORA model for the weapons industry. The approach merges TODIM with Fine-Kinney concept. Risk parameters used in traditional Fine-Kinney method are weighted by Fuzzy Analytic Hierarchy Process (FAHP). Then, hazards and associated risks are prioritised using the approach. As an illustration, the gun and rifle assembly line of a weapon factory is handled. The application is carried out to improve operational safety and protect employee health. From both theoretical and practice aspects, it contributes to the literature by handling the problem in an integrated style of Fine-Kinney, FAHP and TODIM and by improving overall safety level of the observed factory and by suggesting potential action plans.
AtıfScopus4İncele - MakaleYalnız künye2018Scopus SJRQ3Investigation of dose and development time for thin e-beam resist poly(methyl methacrylate) for large area dense nanopattern applications
Göktaş, Oktay; Çakıroğlu, Dilek; Yıldırım, Özal; Göktaş, Nebile Işık
With the advance of nanotechnology, the demand for very dense nanopatterns over large areas continuously increases. Electron beam lithography is one of the main tools to realise this type of nanopattern. In this study we investigate the effect and interrelation of dose and development time for electron beam resist poly(methyl methacrylate) (PMMA) for the realisation of very large area and very dense nanopatterns. For this purpose a pattern consisting of a lattice of holes with radius of 80 nm and lattice constant of 200 nm has been designed, electron beam lithography is realised on a thin resist and a detailed SEM image inspection of the pattern is recorded. Hough transform, a pattern recognition method for the digital images, is applied to SEM images to measure the radii of the holes on the images. Interrelation between dose and development time is investigated. It is found that for a very large area of dense nanopatterns the lithographic process works better for development times shorter than typically used ones.
- DergiInternational Journal of Nanotechnology
- DergiInternational Journal of Reliability and Safety
- DergiInternational Journal of Knowledge Management Studies
- DergiInternational Journal of Multicriteria Decision Making
- DergiInternational Journal of Data Mining and Bioinformatics
- DergiInternational Journal of Management and Decision Making