Search

COVID-19 has had devastating effects worldwide, and vaccines have become the most efficient solution to address the current pandemic situation thus far. After COVID-19 vaccines had been developed, discussions of the various countries’ equality of access gained traction, with patents and pricing forming a significant part of this discourse. Therefore, this study investigates the impact of patents and prices on the accessibility of COVID-19 vaccines in the developing world, using semi-structured interviews with subject-matter experts in this area of focus. Our analysis of these interviews highlights the fact that patents and prices are not the major barriers to accessibility for medical treatments, both generally and specifically in terms of COVID-19; rather, these barriers relate to the lack of local production capacity, technology transfer, infrastructure, local regulations, and supply-chain competencies. These results suggest that rather than focusing on patents and prices, governments should invest more time in improving technology transfer and using compulsory licenses as a negotiation tool. Moreover, the results show that the pricing strategies applied by companies could have different impacts on access, as could accessibility programs such as COVAX.

In this study, the effects of oil, water, glycerol monostearate, carrageenan and alginate concentrations, which have a significant effect on quality parameters in olive oil oleogel-based emulsion (OOE), were investigated and their optimum amounts were determined by mixture design for oleogel production with desired properties. OOE was produced using olive oil, water, glycerol monostearate (GMS), carrageenan and alginate at various concentrations in the range of 0-70%, 30-60%, 0-2%, 0-2% and 0-2%, respectively. The optimum quality parameters of OOE were evaluated in terms of optimum firmness value (5.5-7 N), minimum oil loss and peroxide value. The optimum composition was determined 53.5% olive oil, 43.5% water, 1.1% carrageenan, 0.92% alginate and 0.98% glycerol monostearate (w/w). Produced OOE under determined optimum conditions had 5.81 N firmness, 1.82 meq/O2 peroxide value and 21.02% oil loss value. The margin of error between the experimentally obtained data and the estimated data in the study is average 2%. The results showed that the formulation used in OOE production have significant effects on the created OOE structure and quality parameters. In addition, different formulations to be created with the results of the present study will contribute to increasing the applicability of OOE in different foods. yok

Son yıllarda, yerli ve yabancı turistler açısından farklı lezzetleri deneyimleme arzusu gastronomi turizminin canlanmasına ve seyahat motivasyonunun artmasına neden olmaktadır. Bu çalışma Nevşehir ilinin gastronomi turizmi atılımlarında ve şehir markalaşmasında öne çıkabilecek, şehrin simgesi haline gelebilecek gıda ürünü ve yemeğinin belirlenmesi amacıyla gerçekleştirilmiştir. Araştırmanın evrenini Nevşehir ilinde yaşayanlar oluşturduğundan örneklemi %95 güven düzeyi, %5 güven aralığı sonucunda 384 kişi oluşturmuştur. Basit tesadüfi örnekleme yöntemi üzerinden yapılan çalışmada herkesin örneğe girme şansı olacak şekilde planlanmıştır. Araştırma iki aşamalı olarak gerçekleştirilmiş ve her aşamada farklı anket formları kullanılarak veriler toplanmıştır. Anket formunda Nevşehir’de yaşayıp yaşamadığına dair olan soruya hayır yanıtı veren katılımcıların yanıtları analize dâhil edilmemiştir. Çalışmanın ana iki sorusunu “Sizce Nevşehir ilinin simgesi olabilecek gıda ürünü nedir?” ve “Sizce Nevşehir ilinin simgesi olabilecek yemeği nedir?” oluşturmuştur. Araştırmaya katılan 393 kişiden elde edilen verilere göre Nevşehir’in simgesi olabilecek olan gıdanın %51,7 kabak çekirdeği olarak yanıtlandığı, Nevşehir’in simgesi olabilecek yemeğin ise %50,4 testi kebabı olarak yanıtlandığı tespit edilmiştir. Gastronomi markası olabilmek için rekabet avantajı sağlayan, bölgeyi çekici hale getirebilen ürünler, hizmetler ve simge gastronominin görülmesi ve kalitelerini her yıl yüksek standartlarda tutabilmesi, bölgedeki turizmde istikrarı sağlayabilecek bir unsur olarak değerlendirilebilir.

Today, growing and changing competitive conditions, products and services, free movement of labor and businesses with the information they develop strategies that create value in order to obtain a competitive advantage. Now, final buyers have the convenience of purchasing the products they demand with the features and conditions they want and at the price they accept. In such an environment, businesses use their supply chain and logistics activities more effectively and efficiently than their competitors. Today, achieving a strategic superiority in a global market where the content and quality of the products are the same is only possible by delivering the desired products to the customer at the desired price, at the desired time, in the desired amount, through the right channel, as quickly as possible and without any damage. In such a situation, the desire to focus on the main activities of the enterprises, the need for effective logistics operations, etc. logistics outsourcing has increasing rapidly for reasons. Businesses can carry out logistics activities requiring expertise thanks to third party logistics (3PL) service providers in the field such as transportation, storage, customs clearance, without investing in logistics. In order for logistics outsourcing to be beneficial, a correct logistics service provider must be selected in accordance with the needs of the business. Selecting the right logistics service provider is important in increasing the benefit of outsourcing. In this study neutrosophic AHP was used to prioritize the factors.

Purpose- In this study, textile goods, of manufactured by a textile company, whether being returned because of defects or not has been investigated by data mining and machine learning techniques. Main purpose of the study is to determine which of the products passing through 15 different production lines during the manufacturing process being defective and faulty at the last stage.Methodology- In this study, there are 250 different variables and 72959 lines of data on the production line. In order to perform a data mining process, it is firstly necessary to understand the data and determine the process. For this, CRISP-DM algorithm has been used. Modelling and classification algorithms are applied to estimate the production of faulty goods. In the model, a supervised learning model based machine learning methods have been used. The dimensions, loops and some statistical features of the data have been examined, and then it has been studied in the Python programming language. The feasibility of model and success rates have been evaluated with findings.Findings- The results of the model show that logistic regression and k-nearest neighbour algorithms give above %90 percentage confusion rate. It has been said that with this model is succesful for predicting defective and faulty product in manufacturing line.Conclusion- It has been tried to predict whether there will be faulty products that reduce quality. With this study, it has been aimed to give a signal to the production line in advance.

Purpose- It is aimed to evaluate the maturity of the business through the transition to digital transformation with Best-Worst Method.Methodology- In this maturity assesstment the weights of the criteria and sub-criteria will be modelled in accordance with the Multi-Criteria-Decision-Making methodology. In this study, digital tansformation process dimensions have been clustered by the experts. In this clustering, the weights of the criteria have been determined by using BWM method. It has been used this method. Because, BWM, in the not-fully-consistent cases with more than three criteria (or alternatives) might bring about multiple optimal solutions. Afterwards, a survey of company employees has been conducted to evaluate the maturity for business.In the model digital transformation criteria were defined for business according to expert opinions. Finally, the maturity of digital transformation of the enterprise has been determined.Findings- The results of the solution shows that the most important criteria is competence of automation and the least important one is inflexible company structure criterion. Furthermore, the sub-criteria that belong to each main criterion have been listed in themselves.Conclusion- The study provides a maturity assessment methodology which is an important part of digital transformation process. This is the first maturity assesstment study under the BWM in the literature.

In this study, the effect of different cooking techniques on chicken tenderloin was investigated. For this purpose, chicken tenderloins were produced with oven, grill, and sous vide cooking techniques and stored at +4°C for seven days. pH, cooking efficiency, color, texture, and sensory analyzes of the samples were carried out. An increase was observed in the pH values of all the cooked samples. It has been determined that the cooking temperature affects the cooking efficiency and the cooking efficiency is low in the samples where the temperature is high. The sous vide method provided a high cooking efficiency. pH values and cooking methods were effective on the color values of the samples. The use of different cooking techniques was found to be important on the hardness, cohesiveness, gumminess, chewiness, and resilience values of chicken tenderloin. It was determined that the panelists preferred the samples cooked on the grill according to the general acceptability criteria in the sensory properties evaluations., Bu çalışmada piliç bonfile etinde farklı pişirme tekniklerinin etkisi incelenmiştir. Bu amaçla fırın, ızgara ve sous vide pişirme teknikleri ile piliç bonfile etleri üretilmiş ve 7 gün boyunca +4°C’de depolanmıştır. Örneklerin pH, pişirme verimi, renk, tekstür ve duyusal analizleri gerçekleştirilmiştir. Pişirilen tüm örneklerin pH değerlerinde artış gözlenmiştir. Pişirme sıcaklığının pişirme verimi üzerinde etkili olduğu, sıcaklığın fazla olduğu örneklerde pişirme veriminin düşük olduğu tespit edilmiştir. Sous vide yöntemi yüksek bir pişirme verimi sağlamıştır. pH değerleri ve pişirme yöntemleri örneklerin renk değerleri üzerinde etkili olmuştur. Piliç bonfile etinin sertlik, kohesivlik, sakızımsılık, çiğnenebilirlik ve anlık elastikiyet değerleri üzerinde farklı pişirme tekniklerinin kullanımı önemli bulunmuştur. Duyusal özellik değerlendirmelerinde panelistlerin genel kabul edilebilirlik kriterlerine göre ızgarada pişirilen örnekleri tercih ettiği belirlenmiştir.

The terms “sustainable development” and “sustainability” have become more popular because of the critical troubles faced through mankind such as growing humankind effect on ecology and the risk of energy source depletion. Solar energy is one of the most rapidly developing sources of sustainable energy available today. The solar panel is the foundation of a photovoltaic system. In this study, the COPRAS and ENTROPY methods have been applied to select the most effective solar panel (100W) for a solar farm design. The five various solar panel brands have been evaluated, and professionals' choices have been dependent on the most important characteristics of the solar panels. From the top panel firms worldwide, the solar panel data utilized in this chapter is obtained. The most effective panel selection has been analyzed to affect the solar panel property potency employing in scales, in conjunction with several competing solar panels from which corporations must choose the top requirements, using COPRAS and ENTROPY techniques.

Because of the effects of nuclear and fossil-based energy on the environment, economics, and security in the world, the need for alternative energy sources has grown steadily and dramatically during the last years. An increasing attraction in renewable power sources, due to rising energy expenses and country-level tax inducement, is driving the research to advance a sequence of improving unified resolutions and novel energy generation equipment. The novel wind turbine installation and the novel wind farm building are critical procedures for long time energy generation. In this chapter, a comprehensive analysis, which combines ARAS and ENTROPY methods, is structured to choose appropriate turbines when improving a wind power plant. The various wind turbine brands were evaluated on different classes (financial, customer satisfaction, environmental, and technical). Data on wind turbines is acquired from 2 MW wind turbine manufacturers.

Considering the environment and human life, the importance of dangerous goods transportation should be carefully considered. Preventing damages during this transportation, anticipating the dangers, and minimizing the risks are vital components for businesses, human life, and the environment. Therefore, reducing/minimizing risks in dangerous goods transportation is a critical element of vital importance. This chapter is aimed to rate the risk factors related to dangerous goods transportation and select the most ideal warehouse locations due to the their importance for human and environmental health. There are a number of factors for that purpose. There are six provinces in the Eastern Black Sea region having the strategic function and structure. According to the decision makers' views and judgments, three provinces are determined in terms of dangerous goods transportation. Picture fuzzy sets-based AHP-TOPSIS methodology was used to analyze the problem of dangerous goods transportation and the most ideal warehouse location selection.

In this study, conjugated linoleic acid (CLA, 3.75%) enriched meatballs were cooked by sous vide (65°C and 95°C). It was determined that there was no significant change in oleic, linoleic, SFA, MUFA and PUFA values. While the amount of CLA isomers decreased significantly with the cooking process, it was determined that lower losses occurred in the sous vide method. The springiness, cohesiveness, resilience and chewiness values of the cooked meatballs with the sous vide method and containing CLA were higher than the other meatball samples. As a result of the study, it is thought that added CLA in foods can be preserved more by prepared with the sous vide method and thus the desired positive biological effects of CLA on human health can be observed.

Background: Uncertainty is the major source of hazards, and it is present in a wide range of business activities. Due to the high level of unpredictability in logistics operations, the logistics sector has traditionally operated in a high-risk environment. These risks have become considerably more complicated as the corporate environment has changed in recent years, such through globalization, environmental concerns, and changes in demand. As a result, in order for a logistics firm to thrive, it is necessary to evaluate and assess the risks associated with logistics. Methods: The Plithogenic Stepwise Weight Assessment Ratio Analysis (SWARA) has been used in this study to assess the logistics risks. The logistics risk considered in this study are transportation-related risks, purchasing-related risks, inventory-related risks, information-related risks, packaging-related risks, operational-related risks, geographical location-related risks, natural disaster-related risks, and organization-related risks. Results: The most significant logistics risks are found to be Inventory-Related Risks, while the least significant are Geographical Location-Related Risks. When compared to the standard SWARA approach, the Plithogenic SWARA method may be employed in group decision-making issues without losing information. Conclusions: The proposed technique will help logistics professionals make informed decisions and manage and analyze risks more efficiently. This study will also contribute to the literature as it is the first time that logistical risks have been addressed by utilizing the Plithogenic SWARA technique.

Sızgıt sıkça ve sevilerek tüketilen,Kapadokya halkı tarafından üretilen geleneksel bir et ürünüdür. Bu çalışmanınamacı geleneksel ve ticari olarak üretilenSızgıt’ın fizikokimyasal ve mikrobiyolojik özelliklerinin belirlenmesidir.Çalışma kapsamında pH, lipid oksidasyonu ve kolesterol düzeyi, protein, yağ venem içeriği, yağ asidi kompozisyonu, toplam aerobik mezofilik bakteri,enterobakter, maya ve küf sayıları, Staphylococcusaureus ve Salmonella sayılarıtespit edilmiştir. Geleneksel olarak üretilen Sızgıt örneklerinin yağ ve kolesterol içeriği ticari olaraküretilen örneklerden daha düşük iken, protein içeriği daha yüksek tespitedilmiştir (P, Sızgıt which is consumed likely and frequently atraditional meat product producing by Cappadocian people. This study aims todetermine the physicochemical and microbiological properties of traditional andcommercial Sızgıt. pH, lipid oxidation andcholesterol level, protein, fat and moisture content, fatty acid composition,aerobic mesophilic bacteria, enterobacteria, mold and yeast, Staphylococcus aureus and Salmonella counts were determined. Fatand cholesterol content of traditional samples had lower than the commercialsamples while the protein content of commercial samples had highest(P

Fuzzy logic inference systems that give effective results about the model in systems that are difficult to establish a model; respectively, it starts with defuzzification the data structurally. Later, it enables the development of approaches to model solutions by extracting rules and then clarifying data. Membership functions, inference methods and performances used are important points that affect the validity and reliability of the system. In the production sector, where modeling is partially difficult, classification of products according to their quality allows the application of fuzzy inference systems. Classification according to quality parameters has been studied extensively in the literature. Recently, artificial intelligence studies have made image processing-based quality classifications possible. There are many membership functions and inference methods with different structures.

The objective of this study was to prepare N-homocysteine conjugate of nisin, and to evaluate the effect of N-homocysteinylation reaction on the antibacterial activity of nisin. Progression of the modification was monitored by measuring free sulfhydryl groups, and by using both acetic acid urea polyacrylamide gel electrophoresis (AAU-PAGE) and tricine sodium dodecyl sulphate polyacrylamide gel electrophoresis (tricine SDS-PAGE). Optimum conditions to attain the maximum N-homocysteinylation degree (6.30%) were determined as 6 mg/mL nisin, 150 mM homocysteine thiolactone, 150 rpm shaker speed, 3.0 pH and 6 hrs reaction time. Antibacterial activity of N-homocysteinylated nisin was determined against Staphylococcus aureus ATCC 6538, Bacillus subtilis ATCC 6633, Lactococcus lactis ssp. cremoris AÜ, Enterococcus faecium ATCC 9097, Listeria monocytogenes NCTC 5348 and Escherichia coli RSKK. Of all the bacteria tested only the growth of E. faecium was inhibited slightly by modified nisin having just about 10% of antibacterial activity of unmodified nisin. Tricine SDS-PAGE analysis applied after trypsin and thermolysin hydrolysis showed that side chains of Lys12 and Lys22 were both modified with homocysteine thiolactone reaction.

Purpose- Recently, digital twin technologies have been frequently used in projects in the digital transformation processes of businesses. Indigital twin processes; there are many different reasons for choosing the machines to be used, such as cost, purpose of use of the business,technology level of the business. In this study, it is aimed to prioritize the factors affecting the machines to be used in digital twin processes.Methodology- Digital twin processes has brought the uncertainty process for businesses. This situation requires decision making underuncertainty. The decision-making process under uncertainty requires the examination of many value judgments together.Digital twinprocesses has brought the uncertainty process for businesses. This situation requires decision making under uncertainty. The decision-makingprocess under uncertainty requires the examination of many value judgments together. For this reason, in order to make the right decisionsin projects, the prioritization of the factors affecting the digital transformation processes was carried out by taking expert opinion. In thisstudy, the Spherical Fuzzy AHP method, which was newly introduced to the literature, has been used. For this purpose, 5 important criteriawere determined from the literature and expert opinions. Three expert opinions have been received.Findings- The results of the model have showed that simulation process is the most important criteria for the selection of machines used indigital twin processes. And sensor based systems are the least important criteria for digital twin processes. ,Conclusion- In this study, prioritizing factors in the selection of machines used in digital twin processes have been examined. For this purpose,the mechanization processes to be used in digital twin processes bring many control points in the background. In this study, the prioritizationof the machinery and equipment to be used has been made by taking expert opinion. Opinions have been received from 3 experts in thefield. The Spherical Fuzzy AHP method, which is one of the fuzzy decision-making sets, which has been recently introduced to the literature,has been used. In the study, it is expected to contribute to the literature by using digital twin technology for the first time with a multi-criteriadecision-making methodology.

Warehouses link suppliers and customers throughout the entire supply chain. The location of the warehouse has a significant impact on the logistics process. Even though all other warehouse activities are successful, if the product dispatched from the warehouse fails to meet the customer needs in time, the company may face with the risk of losing customers. This affects the performance of the whole supply chain therefore the choice of warehouse location is an important decision problem. This problem is a multi-criteria decision-making (MCDM) problem since it involves many criteria and alternatives in the selection process. This study proposes an integrated grey MCDM model including grey preference selection index (GPSI) and grey proximity indexed value (GPIV) to determine the most appropriate warehouse location for a supermarket. This study aims to make three contributions to the literature. PSI and PIV methods combined with grey theory will be introduced for the first time in the literature. In addition, GPSI and GPIV methods will be combined and used to select the best warehouse location. In this study, the performances of five warehouse location alternatives were assessed with twelve criteria. Location 4 is found as the best alternative in GPIV. The GPIV results were compared with other grey MCDM methods, and it was found that GPIV method is reliable. It has been determined from the sensitivity analysis that the change in criteria weights causes a change in the ranking of the locations therefore GPIV method was found to be sensitive to the change in criteria weights.

Purpose The Covid-19 pandemic has caused disruptions in many businesses. A difficult process has been experienced for businesses caught unprepared for this situation. The purpose of the study, the difficulties experienced in the business have been mapped in terms of crisis management. Design/methodology/approach For this purpose, crisis management strategies have been discussed in terms of lean six sigma (LSS) strategies. Afterward, LSS strategies have been weighted with the spherical fuzzy analytical hierarchy process (AHP) method, which has been recently introduced to the literature (Gündogdu and Kahraman, 2020). While weighting has been done with the spherical fuzzy AHP method, three experts in the field of LSS at the master blackbelt level have been studied. Findings The Covid-19 process has caused the usual processes of businesses to change. Businesses do not have enough time to adapt their business processes in the Covid-19 process. To eliminate waste and time in the Covid-19 process, the lean methodology was used. At the same time, quality deficiencies have been tried to be eliminated with the six sigma methodology. Therefore, the six sigma methodology and lean techniques should be considered together. With LSS, the adaptation of this process has been wanted to be accelerated. In this context, the criteria in the Covid-19 process were prioritized and losses were reduced in accordance with the LSS methodology. In this study, the most important criterion during the covid-19 pandemic has been determined as “responding to the changing needs of customers” and the least important criterion has been determined as “communication with stakeholders in enterprises.” Research limitations/implications This study has been applied the Covid-19 pandemics. So, it has been evaluated related to these specific criteria. Practical implications Covid-19 crisis management was examined for the first time within the scope of the LSS methodology. The criteria in the Covid-19 process were determined by six sigma expert master black belts. For the first time, spherical fuzzy AHP, one of the multi-criteria decision methods, has been applied to the Covid-19 process. Originality/value This study has been aimed to create a roadmap to apply LSS steps in businesses against a possible second wave of the Covid-19 pandemic. In this context, it is thought that the study will fill the following gaps in the literature: Covid-19 crisis management was examined for the first time within the scope of LSS methodology. The criteria in the Covid-19 process were determined by six sigma expert master black belts. For the first time, spherical fuzzy AHP, one of the multi-criteria decision methods, has been applied to the Covid-19 process.

The shortest path problem as a core combinatorial problem in graph theory that can be applied in various fields such as project scheduling, routing, transportation, network, operation research, and computer science. The main objective of this problem is to find the path having minimum length between any pair of nodes (or vertices). In this study an algorithm was applied in order to find the shortest path having single-valued triangular neutrosophic numbers via score function. A real case study was introduced and solved by this algorithm for the purpose of showing the applicability in real-world problems.

Gastronomi Mirası: Kapadokya Yemekleri kitabının ilk taslakları Kapadokya Üniversitesi Aşçılık Programı’nın ilk mezunları tarafından hazırlanmıştı. Amaç Kapadokya’nın zengin mutfak kültürü ile bu kültürü temsil eden gastronomi ürünlerini yaşatmak ve gelecek kuşaklara aktarmaktı. Kitapta yer alan yemek reçeteleri için birçok yazılı ve sözlü kaynağın yanında, Marcus Gavius Apicius: De Re Coquinaria başlıklı eski bir Roma risalesinden de faydalanıldı. Yıllar içinde olgunlaşan tarifler şeflerimiz tarafından sayısız denemelerle tecrübe edildi. Kapadokya’ya uygun sofra düzeni ve yemek görselleri ise okuyucuya daha iyi bir fikir vermek için özenle tasarlandı. Kapadokya gastronomi mirasını kayıt altına alan bu kitap bölgedeki yüksek kaliteli işletmelerin menülerini oluşturacak ve gastronomi turizminde yeni bir sayfa açacak nitelikte bir çalışma olarak okuyucuları ile buluşuyor. Kapadokya Üniversitesi’nin dünya çapında tanınan şefleri ve akademisyenleri bu çalışmada yer alan tarifleri kullanmak isteyen herkese destek vermekten onur duyacaklardır.

TARAMAWOS WOS:000704525400001 Bu çalışma kapsamında nar (Punica granatum L.) çiçeğinden farklı parametreler altında elde edilen ekstraktların antioksidan aktiviteleri ve toplam fenolik içerikleri üzerine ekstraksiyon koşullarının etkisi incelenmiştir. Nar çiçeklerinden su ve etanol kullanılarak 40-60 °C sıcaklık ve 40-60 dk süre ile ekstraktlar elde edilmiş ve liyofilize edilerek kurutulmuştur. Liyofilize ekstraktların antioksidan aktiviteleri 2,2-difenil-1-pikrilhidrazil (DPPH) radikal giderme aktivitesi ve β-karoten ağartma yöntemleri kullanılarak tespit edilmiştir. Çalışma sonuçları, ekstraktların antioksidan aktivite ve fenolik madde içeriğine ekstraksiyon sırasında kullanılan çözücü, sıcaklık, süre ve bu faktörlerin bazı interaksiyonlarının önemli seviyede etkisi olduğunu göstermiştir. Etanol ile hazırlanan ekstraktların su ile hazırlanan ekstraktlara kıyasla daha yüksek antioksidan aktivite gösterdiği belirlenmiştir. Ayrıca etanol ile hazırlanan ekstraktların toplam fenolik madde içeriği de daha yüksek bulunmuştur. Etanol kullanılarak, 60 °C sıcaklık ve 40 dk sürede gerçekleştirilen ekstraksiyon işlemi ile elde edilen ekstraktların ortalama %85 DPPH radikali giderim aktivitesine ve %70 β-karoten ağartma aktivitesine sahip olduğu belirlenmiştir. Bu ekstraktların ortalama 70.36 mg GAE-g fenolik bileşen içerdiği tespit edilmiştir. Nevşehir Hacı Bektaş Veli Üniversitesi Bilimsel Araştırma Projeleri Koordinasyon Birimi’ne (Proje No: BBAP20F12) teşekkür ederiz.

The purpose of this study is to determine and rank the road transportation risk factors that are crucial for effective and economic supply chain management. Road transportation risk factors can be defined as equipment related risks, risk to be lost and disappearance, risks related to delivery and packaging, inadequacy of qualified personnel and technical equipment, risks caused from incompatibility to logistic information system/technology, security risk, compulsory reasons, risks originated from regulations and arrangements, risks related to waiting at customs gate and transport infrastructure based risks. Accordingly, fuzzy PIPRECIA as a multi-criteria ranking method was used to prioritize the risk factors. According to the results, while the transport infrastructure based risks criterion was found as the most important, the risk to be lost and disappearance factor was obtained as the least important one.

The incorporation of environmental criteria into the conventional supplier selection practices is essential for organizations seeking to promote green supply chain management. Challenges associated with green supplier selection have been broadly recognized by procurement and supplier management professionals. The development and implementation of practical decision making tools that seek to address these challenges are rapidly evolving. This article contributes to this knowledge area by comparing the application of intuitionistic multi-criteria supplier selection methods in a fuzzy environment. The intuitionistic fuzzy AHP and TOPSIS methods are thoroughly discussed. The methods are then utilized to complete a green supplier evaluation and selection study for an actual company from the paper mill. For this purpose, 3 alternative green suppliers have been identified. To evaluate the alternatives, 10 criteria in three dimensions including supplier performance, environmental protection and supplier risk have been selected. Since the Multi-Criteria Decision Making (MCDM) methods are often used in problem of supplier selection from past to present. The Intuitionistic Fuzzy Sets (IFS) are used to reflect approval, rejection, and hesitation of decision makers by dealing with real life uncertainty, imprecision, vagueness, and linguistic human decisions. The main purpose of this study is to define the weights of criteria with Intuitionistic Fuzzy AHP. After that, the Intuitionistic Fuzzy TOPSIS and AHP method were used to rank alternatives from best to worst. At the end of the study the results related with alternatives were compared and interpreted.

Purpose- In this study, it is aimed to improve the production and quality control processes of a company operating in the textile industry. For this purpose predicting faulty and refund products by using simulation of oversampling and undersampling applications. Methodology– In this study, there are 250 different variables and 72959 lines of data on the production line. These data have been taken from the last 1-year data of the firm. In this study, simulation has been done. New machine learning methods have been used by simulating. The reason for the simulation is that it was easy to detect the refund and faulty conditions made in a large lot group production in previous studies. However, the aim is to investigate whether the accuracy of the prediction algorithms will yield consistent results in terms of the increase in the number of refund and faulty products when production is made in a larger structure. In the simulation method, "oversampling" and "undersampling" methods have been used. While making simulation prediction, in the literature, boosting algorithms, which are used as ensemble machine learning techniques, have been used. In this study, simulation has been done as follows, while the number of production lots increased, refund and faulty products were increased within the same application. The reason for doing this is to investigate whether the prediction status in normal machine learning algorithms can be captured in a larger data stack. This process is called oversampling. Then, the "undersampling" method was applied. According to the “undersampling” method, it is aimed to determine the refund and defect situations in a smaller lot by taking samples of refund and defective products with less frequency. At the end of the study, the results were interpreted by applying boosting algorithms.Findings- As a result of the study, it is concluded that "undersampling" and "oversampling" simulations predict better than usual machine learning methodology.Conclusion- In this study, it has been observed that the ensemble machine learning algorithms (adaboost, xgboost, gradient boosting algorithms), which are one of the ensemble machine learning methods that emerged in 2016, were applied to the production data for the first time and showed success in the prediction of faulty and refund products.