Search results for: Enes Ergün

Authors: Mustafa Sengul, Enes Sahin, Sertac Arslan

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Pumpjets are one of the marine propulsion systems frequently used in underwater vehicles nowadays. The reasons for frequent use of pumpjet as a propulsion system are that it has higher relative efficiency at high speeds, better cavitation, and acoustic performance than its rivals. Pumpjets are composed of rotor, stator, and duct, and there are two different types of pumpjet configurations depending on the desired hydrodynamic characteristic, which are with accelerating and decelerating duct. Pumpjet with an accelerating channel is used at cargo ships where it works at low speeds and high loading conditions. The working principle of this type of pumpjet is to maximize the thrust by reducing the pressure of the fluid through the channel and throwing the fluid out from the channel with high momentum. On the other hand, for decelerating ducted pumpjets, the main consideration is to prevent the occurrence of the cavitation phenomenon by increasing the pressure of the fluid about the rotor region. By postponing the cavitation, acoustic noise naturally falls down, so decelerating ducted systems are used at noise-sensitive vehicle systems where acoustic performance is vital. Therefore, duct design becomes a crucial step during pumpjet design. This study, it is aimed to optimize the duct geometry of a decelerating ducted pumpjet for a highly speed underwater vehicle by using proper optimization tools. The target output of this optimization process is to obtain a duct design that maximizes fluid pressure around the rotor region to prevent from cavitation and minimizes drag force. There are two main optimization techniques that could be utilized for this process which are parameter-based optimization and gradient-based optimization. While parameter-based algorithm offers more major changes in interested geometry, which makes user to get close desired geometry, gradient-based algorithm deals with minor local changes in geometry. In parameter-based optimization, the geometry should be parameterized first. Then, by defining upper and lower limits for these parameters, design space is created. Finally, by proper optimization code and analysis, optimum geometry is obtained from this design space. For this duct optimization study, a commercial codedparameter-based optimization algorithm is used. To parameterize the geometry, duct is represented with b-spline curves and control points. These control points have x and y coordinates limits. By regarding these limits, design space is generated.

Keywords: pumpjet, decelerating duct design, optimization, underwater vehicles, cavitation, drag minimization

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Authors: Ates Gul Ergun, Melda Tacyildiz

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The current study focuses on the relationship between the personality traits and starting a romantic relationship on social media. It is interested in the study whether there are any personality trait differences between individuals who started their romantic relationships on social media platforms or through circle of friends in daily life. Sixty five participants between the ages of 18-30 filled out a three-question-survey about romantic relationships and social media, with the Big Five Inventory. Four separate independent samples t tests comparing agreeableness and extraversion scores on the environment of participants first interacted (online vs. real-life) and where they fırst meet without interaction (online vs. real-life) were carried out. The results indicated that there was a statistically significant difference between people who had the first interaction with their partner online vs. real-life in terms of extraversion and agreeableness traits. The more extrovert and agreeable traits reported the more people were likely to interact with their partner through circle of friends in real-life. Furthermore, it was found that people who are less agreeable have a tendency to interact with their partners in social media for the first time. However, there was no statistically significant difference between how participants met with their partners without interaction (online vs. real-life) in terms of extraversion and agreeableness traits. This study has shown the relationships between personality traits and starting a romantic relationship on social media versus in real-life but not the reasons behind it. Further research could examine such reasons. In addition, the data only includes Turkish sample. By virtue of the cultural restriction in the present study, it is suggested that the future research should also include different cultures to investigate how people spend time with their friends and also in social media which can be changed according to individualism levels of countries. Overall, the study emphasizes the importance and the role of social media in individual’s lives, and it opens the ways associated with personal traits and social media relationships for further researches.

Keywords: agreeableness, big five, extraversion, romantic relationships, social media

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Authors: Aylin Hasbay Büyükkaragöz, Zehra Büyüktuncer, Tuğçe Nur Balcı, Nevin Ergun

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Purpose: Nutritional supplement usage is widespread among athletes all over the world. However, the usage among disabled athletes is not well-known. This study aimed to evaluate dietary supplement use in disabled athletes, their motivation for consuming supplements, sources of information, and their side effect. Methods: A total of 75 Turkish National Team's disabled athletes (38 female, 37 male) from 5 sport branches (soccer, weight lifting, shooting, table tennis and basketball), aged 13- 55 years, were participated in the study. Nutritional supplement usage was inquired using a questionnaire by a dietitian at their preparation camps. Results: A total of 22.7% of the athletes (18.4% and 27% of, respectively females and males) used some type of dietary supplements. Protein (35.3%), amino acid (29.4%), carnitine (29.4%), creatine (23.5%) and glucosamine (23.5%) were mostly preferred nutritional supplements by all athletes. The most common supplements use was obtained among weightlifters (71.4%), followed by the athletes of soccer (23.5%), table tennis (15.4%), and basketball (6.7%). No nutritional supplement usage was observed among shooters. Total of 41.2% consumers declared more than one reason for taking nutritional supplements. The main motivation for supplement usage was improving athletic performance (63.5%). Other reasons were weight loss, weight gain, muscle development, health protection and nutritional support. Athletes were more likely to get recommendation about nutritional supplement usage from team coaches (48.9%). Of 35.6% athletes reported that they made their own decision about using supplements. Other information sources were health professional, family member, friend and sale manager of sport retail store. Only 3 of 17 athletes reported side effects which were increased urine output, weight gain, loss of appetite and intestinal gas. Conclusions: Nutritional supplement usage was not common among disabled athletes. However, getting information from incompetent sources is disquieting. Considering their health problems, accurate information from competent sources should be provided to disabled athletes. Moreover, long term effects of nutritional supplements among disabled athletes should be examined in further studies.

Keywords: disabled athletes, ergogenic aid, nutritional supplement, vitamin supplementation

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Authors: Zehra Buyuktuncer, Aylin H. Büyükkaragöz, Tuğçe N. Balcı, Nevin Ergun

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Background: Undergoing rigid dietary habits for enhancing athletic performance could lead to eating disorders. High prevalence of eating disorders among female athletes has been already reported. However, the risk of disordered eating among disabled athletes is not known. A better knowledge of the different eating behaviors and their prevalence in disabled athletes would be helpful to understand interactions between eating and health. This study aimed to examine the cognitive restraint, uncontrolled eating and emotional eating behaviors in a disabled athlete population. Method: A total of 70 disabled Turkish national athletes (33 female, 37 male) from 5 sport branches (soccer, weight lifting, shooting, table tennis and basketball) were involved in the study. The cognitive restraint, uncontrolled eating and emotional eating behaviors were assessed using the revised version of Three Factor Eating Questionnaire-R18 (TFEQ-R18). The questionnaires were conducted by dietitian during the preparation camps of athletes. Body weight, height and waist circumference (WC) were measured; and body composition was analyzed by bioelectrical impedance analysis method. Results: The TFEQ scales showed a cognitive dietary restraint score of 13.9±4.2, uncontrolled eating score of 17.7±5.8 and emotional eating score of 4.9±2.5. The mean score of total TFEQ-R18 was 36.5±8.62. Neither total TFEQ-R18 score nor subscale scores differed significantly by gender or sport branches (p>0.05, for each). The scores were also similar in BMI groups (n=63; p>0.05). Total TFEQ, uncontrolled eating and emotional eating scores were significantly higher among the athletes with congenital disabilities compared to the scores of the athletes with acquired disabilities (p<0.05, for each). Moreover, the cognitive dietary restraint score was significantly high in athletes who would like to lose weight (p=0.009). Conclusion: Disabled athletes might have a risk of disordered eating. The different eating behaviors among disabled athletes should be assessed using validated tools to develop personalized nutritional strategies for those athletes.

Keywords: disabled athletes, eating behaviour, three-factor eating questionnaire-r18, body composition

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Authors: Enes Huylu, Sude Erkin, Nur A. Özdemir, Hatice K. Güney, Cemre S. Atılgan, Hüseyin Y. Altıntaş, Aysemin Top, Muammer Yılman, Özak Durmuş

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Remanufacturing (reman) applications allow manufacturers to contribute to the circular economy and help to introduce products with almost the same quality, environment-friendly, and lower cost. The objective of this study is to present that the carbon footprint of automotive spare parts used in vehicles could be reduced by reman applications based on Life Cycle Analysis which was framed with ISO 14040 principles. In that case, it was aimed to investigate reman applications for 21 parts in total. So far, research and calculations have been completed for the alternator, turbocharger, starter motor, compressor, manual transmission, auto transmission, and DPF (diesel particulate filter) parts, respectively. Since the aim of Ford Motor Company and Ford OTOSAN is to achieve net zero based on Science-Based Targets (SBT) and the Green Deal that the European Union sets out to make it climate neutral by 2050, the effects of reman applications are researched. In this case, firstly, remanufacturing articles available in the literature were searched based on the yearly high volume of spare parts sold. Paper review results related to their material composition and emissions released during incoming production and remanufacturing phases, the base part has been selected to take it as a reference. Then, the data of the selected base part from the research are used to make an approximate estimation of the carbon footprint reduction of the relevant part used in Ford OTOSAN. The estimation model is based on the weight, and material composition of the referenced paper reman activity. As a result of this study, it was seen that remanufacturing applications are feasible to apply technically and environmentally since it has significant effects on reducing the emissions released during the production phase of the vehicle components. For this reason, the research and calculations of the total number of targeted products in yearly volume have been completed to a large extent. Thus, based on the targeted parts whose research has been completed, in line with the net zero targets of Ford Motor Company and Ford OTOSAN by 2050, if remanufacturing applications are preferred instead of recent production methods, it is possible to reduce a significant amount of the associated greenhouse gas (GHG) emissions of spare parts used in vehicles. Besides, it is observed that remanufacturing helps to reduce the waste stream and causes less pollution than making products from raw materials by reusing the automotive components.

Keywords: greenhouse gas emissions, net zero targets, remanufacturing, spare parts, sustainability

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Authors: Asena Biber, Ates Gul Ergun, Seda Bulut

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Based on the literature, there are large numbers of studies investigating the relationship between culture and leadership effectiveness. Although giving effective speeches is vital characteristic for a leader to be perceived as effective, to our knowledge, there is no research study the determinants of perceived effective leader speech. The aim of this study is to find the effects of both culture and voice pitch on perceptions of leader's speech effectiveness. Our hypothesis is that people from high power distance countries will perceive leaders' speech effective when the leader's voice pitch is high, comparing with people from relatively low power distance countries. The participants of the study were 36 undergraduate students (12 Pakistanis, 12 Nigerians, and 12 Turks) who are studying in Turkey. National power distance scores of Nigerians ranked as first, Turks ranked as second and Pakistanis ranked as third. There are two independent variables in this study; three nationality groups that representing three levels of power distance and voice pitch of the leader which is manipulated as high and low levels. Researchers prepared an audio to manipulate high and low conditions of voice pitch. A professional whose native language is English read the predetermined speech in high and low voice pitch conditions. Voice pitch was measured using Hertz (Hz) and Decibel (dB). Each nationality group (Pakistan, Nigeria, and Turkey) were divided into groups of six students who listened to either the low or high pitch conditions in the cubicles of the laboratory. It was expected from participants to listen to the audio and fill in the questionnaire which was measuring the leadership effectiveness on a response scale ranging from 1 to 5. To determine the effects of nationality and voice pitch on perceived effectiveness of leader' voice pitch, 3 (Pakistani, Nigerian, and Turk) x 2 (low voice pitch and high voice pitch) two way between subjects analysis of variances was carried out. The results indicated that there was no significant main effect of voice pitch and interaction effect on perceived effectiveness of the leader’s voice pitch. However, there was a significant main effect of nationality on perceived effectiveness of the leader's voice pitch. Based on the results of Turkey’s HSD post-hoc test, only the perceived effectiveness of the leader's speech difference between Pakistanis and Nigerians was statistically significant. The results show that the hypothesis of this study was not supported. As limitations of the study, it is of importance to mention that the sample size should be bigger. Also, the language of the questionnaire and speech should be in the participant’s native language in further studies.

Keywords: culture, leadership effectiveness, power distance, voice pitch

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Authors: Thilina Ranaweera, Enes Makalic, John L. Hopper, Adrian Bickerstaffe

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Data are the primary asset of biomedical researchers, and the engine for both discovery and research translation. As the volume and complexity of research datasets increase, especially with new technologies such as large single nucleotide polymorphism (SNP) chips, so too does the requirement for software to manage, process and analyze the data. Researchers often need to execute complicated queries and conduct complex analyzes of large-scale datasets. Existing tools to analyze such data, and other types of high-dimensional data, unfortunately suffer from one or more major problems. They typically require a high level of computing expertise, are too simplistic (i.e., do not fit realistic models that allow for complex interactions), are limited by computing power, do not exploit the computing power of large-scale parallel architectures (e.g. supercomputers, GPU clusters etc.), or are limited in the types of analysis available, compounded by the fact that integrating new analysis methods is not straightforward. Solutions to these problems, such as those developed and implemented on parallel architectures, are currently available to only a relatively small portion of medical researchers with access and know-how. The past decade has seen a rapid expansion of data management systems for the medical domain. Much attention has been given to systems that manage phenotype datasets generated by medical studies. The introduction of heterogeneous genomic data for research subjects that reside in these systems has highlighted the need for substantial improvements in software architecture. To address this problem, we have developed SPARK, an enabling and translational system for medical research, leveraging existing high performance computing resources, and analysis techniques currently available or being developed. It builds these into The Ark, an open-source web-based system designed to manage medical data. SPARK provides a next-generation biomedical data management solution that is based upon a novel Micro-Service architecture and Big Data technologies. The system serves to demonstrate the applicability of Micro-Service architectures for the development of high performance computing applications. When applied to high-dimensional medical datasets such as genomic data, relational data management approaches with normalized data structures suffer from unfeasibly high execution times for basic operations such as insert (i.e. importing a GWAS dataset) and the queries that are typical of the genomics research domain. SPARK resolves these problems by incorporating non-relational NoSQL databases that have been driven by the emergence of Big Data. SPARK provides researchers across the world with user-friendly access to state-of-the-art data management and analysis tools while eliminating the need for high-level informatics and programming skills. The system will benefit health and medical research by eliminating the burden of large-scale data management, querying, cleaning, and analysis. SPARK represents a major advancement in genome research technologies, vastly reducing the burden of working with genomic datasets, and enabling cutting edge analysis approaches that have previously been out of reach for many medical researchers.

Keywords: biomedical research, genomics, information systems, software

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Authors: M. Qamarul Islam, Ergun Dogan, Mehmet Yazici

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There is a growing body of evidence that non-normal data is more prevalent in nature than the normal one. Examples can be quoted from, but not restricted to, the areas of Economics, Finance and Actuarial Science. The non-normality considered here is expressed in terms of fat-tailedness and asymmetry of the relevant distribution. In this study a skew t distribution that can be used to model a data that exhibit inherent non-normal behavior is considered. This distribution has tails fatter than a normal distribution and it also exhibits skewness. Although maximum likelihood estimates can be obtained by solving iteratively the likelihood equations that are non-linear in form, this can be problematic in terms of convergence and in many other respects as well. Therefore, it is preferred to use the method of modified maximum likelihood in which the likelihood estimates are derived by expressing the intractable non-linear likelihood equations in terms of standardized ordered variates and replacing the intractable terms by their linear approximations obtained from the first two terms of a Taylor series expansion about the quantiles of the distribution. These estimates, called modified maximum likelihood estimates, are obtained in closed form. Hence, they are easy to compute and to manipulate analytically. In fact the modified maximum likelihood estimates are equivalent to maximum likelihood estimates, asymptotically. Even in small samples the modified maximum likelihood estimates are found to be approximately the same as maximum likelihood estimates that are obtained iteratively. It is shown in this study that the modified maximum likelihood estimates are not only unbiased but substantially more efficient than the commonly used moment estimates or the least square estimates that are known to be biased and inefficient in such cases. Furthermore, in conventional regression analysis, it is assumed that the error terms are distributed normally and, hence, the well-known least square method is considered to be a suitable and preferred method for making the relevant statistical inferences. However, a number of empirical researches have shown that non-normal errors are more prevalent. Even transforming and/or filtering techniques may not produce normally distributed residuals. Here, a study is done for multiple linear regression models with random error having non-normal pattern. Through an extensive simulation it is shown that the modified maximum likelihood estimates of regression parameters are plausibly robust to the distributional assumptions and to various data anomalies as compared to the widely used least square estimates. Relevant tests of hypothesis are developed and are explored for desirable properties in terms of their size and power. The tests based upon modified maximum likelihood estimates are found to be substantially more powerful than the tests based upon least square estimates. Several examples are provided from the areas of Economics and Finance where such distributions are interpretable in terms of efficient market hypothesis with respect to asset pricing, portfolio selection, risk measurement and capital allocation, etc.

Keywords: least square estimates, linear regression, maximum likelihood estimates, modified maximum likelihood method, non-normality, robustness

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Authors: Wang Heng, Zhong Zhaoping, Guo Feihong, Wang Jia, Wang Xiaoyi

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Flow of gas and particles in fluidized beds is complex and chaotic, which is difficult to measure and analyze by experiments. Some bed materials with bad fluidized performance always fluidize with fluidized medium. The material and the fluidized medium are different in many properties such as density, size and shape. These factors make the dynamic process more complex and the experiment research more limited. Numerical simulation is an efficient way to describe the process of gas-solid flow in fluidized bed. One of the most popular numerical simulation methods is CFD-DEM, i.e., computational fluid dynamics-discrete element method. The shapes of particles are always simplified as sphere in most researches. Although sphere-shaped particles make the calculation of particle uncomplicated, the effects of different shapes are disregarded. However, in practical applications, the two-component systems in fluidized bed also contain sphere particles and non-sphere particles. Therefore, it is needed to study the two component flow of sphere particles and non-sphere particles. In this paper, the flows of mixing were simulated as the flow of molding biomass particles and quartz in fluidized bad. The integrated model was built on an Eulerian–Lagrangian approach which was improved to suit the non-sphere particles. The constructed methods of cylinder-shaped particles were different when it came to different numerical methods. Each cylinder-shaped particle was constructed as an agglomerate of fictitious small particles in CFD part, which means the small fictitious particles gathered but not combined with each other. The diameter of a fictitious particle d_fic and its solid volume fraction inside a cylinder-shaped particle α_fic, which is called the fictitious volume fraction, are introduced to modify the drag coefficient β by introducing the volume fraction of the cylinder-shaped particles α_cld and sphere-shaped particles α_sph. In a computational cell, the void ε, can be expressed as ε=1-〖α_cld α〗_fic-α_sph. The Ergun equation and the Wen and Yu equation were used to calculate β. While in DEM method, cylinder-shaped particles were built by multi-sphere method, in which small sphere element merged with each other. Soft sphere model was using to get the connect force between particles. The total connect force of cylinder-shaped particle was calculated as the sum of the small sphere particles’ forces. The model (size=1×0.15×0.032 mm3) contained 420000 sphere-shaped particles (diameter=0.8 mm, density=1350 kg/m3) and 60 cylinder-shaped particles (diameter=10 mm, length=10 mm, density=2650 kg/m3). Each cylinder-shaped particle was constructed by 2072 small sphere-shaped particles (d=0.8 mm) in CFD mesh and 768 sphere-shaped particles (d=3 mm) in DEM mesh. The length of CFD and DEM cells are 1 mm and 2 mm. Superficial gas velocity was changed in different models as 1.0 m/s, 1.5 m/s, 2.0m/s. The results of simulation were compared with the experimental results. The movements of particles were regularly as fountain. The effect of superficial gas velocity on cylinder-shaped particles was stronger than that of sphere-shaped particles. The result proved this present work provided a effective approach to simulation the flow of two component particles.

Keywords: computational fluid dynamics, discrete element method, fluidized bed, multiphase flow

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Authors: Nur A. Özdemir, Sude Erkin, Hatice K. Güney, Cemre S. Atılgan, Enes Huylu, Hüseyin Y. Altıntaş, Aysemin Top, Özak Durmuş

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Carbon emissions produced during a product’s life cycle, from extraction of raw materials up to waste disposal and market consumption activities are the major contributors to global warming. In the light of the science-based targets (SBT) leading the way to a zero-carbon economy for sustainable growth of the companies, carbon footprint reporting of the purchased goods has become critical for identifying hotspots and best practices for emission reduction opportunities. In line with Ford Otosan's corporate sustainability strategy, research was conducted to evaluate the carbon footprint of purchased products in accordance with Scope 3 of the Greenhouse Gas Protocol (GHG). The purpose of this paper is to develop a systematic and transparent methodology to calculate carbon footprint of the products produced by automotive OEMs (Original Equipment Manufacturers) within the context of automobile supply chain management. To begin with, primary material data were collected through IMDS (International Material Database System) corresponds to company’s three distinct types of vehicles including Light Commercial Vehicle (Courier), Medium Commercial Vehicle (Transit and Transit Custom), Heavy Commercial Vehicle (F-MAX). Obtained material data was classified as metals, plastics, liquids, electronics, and others to get insights about the overall material distribution of produced vehicles and matched to the SimaPro Ecoinvent 3 database which is one of the most extent versions for modelling material data related to the product life cycle. Product life cycle analysis was calculated within the framework of ISO 14040 – 14044 standards by addressing the requirements and procedures. A comprehensive literature review and cooperation with suppliers were undertaken to identify the production methods of parts used in vehicles and to find out the amount of scrap generated during part production. Cumulative weight and material information with related production process belonging the components were listed by multiplying with current sales figures. The results of the study show a key modelling on carbon footprint of products and processes based on a scientific approach to drive sustainable growth by setting straightforward, science-based emission reduction targets. Hence, this study targets to identify the hotspots and correspondingly provide broad ideas about our understanding of how to integrate carbon footprint estimates into our company's supply chain management by defining convenient actions in line with climate science. According to emission values arising from the production phase including raw material extraction and material processing for Ford OTOSAN vehicles subjected in this study, GHG emissions from the production of metals used for HCV, MCV and LCV account for more than half of the carbon footprint of the vehicle's production. Correspondingly, aluminum and steel have the largest share among all material types and achieving carbon neutrality in the steel and aluminum industry is of great significance to the world, which will also present an immense impact on the automobile industry. Strategic product sustainability plan which includes the use of secondary materials, conversion to green energy and low-energy process design is required to reduce emissions of steel, aluminum, and plastics due to the projected increase in total volume by 2030.

Keywords: automotive, carbon footprint, IMDS, scope 3, SimaPro, sustainability

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