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Nucleation and Growth of Graphene/Mo2c Heterostructures on Cu Through Cvd
No full textWe investigated the chemical vapor deposition synthesis of Mo2C/graphene heterostructures on a partially wetted liquid copper surface, studied the morphology of resulting phases using electron and optical microscopy, and determined the rate-limiting step for the growth of Mo2C on graphene. The morphology of the Mo2C crystals varied from the center to the edge of the copper substrate because of the change in the Mo diffusion pathways owing to the variation in the thickness of the Cu substrate. Thin, hexagonal-shaped crystals of Mo2C were found in the central region, where Cu is the thickest. In addition, the growth pressure substantially affects the nucleation and growth kinetics of both Mo2C and graphene. At high pressures (750 Torr), the graphene layer fully covered the Cu surface and Mo2C crystals formed with a regular shape, while at low pressures (5 Torr), the nucleation of both domains was suppressed, leading to the evolution of Mo2C crystals with irregular shapes. The activation energy for the growth of Mo2C on graphene was calculated to be 3.76 +/- 0.3 eV, and the diffusion of Mo to the Cu surface through uncovered Cu or graphene vacancies/defects was determined to be the rate-limiting step.Air Force Office of ScientificResearch, Grant/Award Number: FA9550-19-1-7048Air Force Office of Scientific ResearchUnited States Department of DefenseAir Force Office of Scientific Research (AFOSR) [FA9550-19-1-7048
Regulated Seasonal Unit Root Process
No full textUnfortunately, time series problems do not appear in data singly. We focus on the joint occurrence of nonstationarity, seasonality and bounded data. Seasonal unit root tests and bounded unit root tests already exist in the literature, yet when all these issues are combined their performance needs improvement. That is why we offer a testing procedure for bounded seasonal unit root processes. The combination of these tests is not straightforward as the nonlinearity coming from bounds causes the limiting distribution of the proposed test statistic to be multivariate Brownian motion while the others have univariate distributions. The simulation exercises reveal that the existing tests, which ignores the presence of bounds or seasonality, suffer significant size problems. Our statistic removes the size distortions and also maintain satisfactory power performance. © 2021 Walter de Gruyter GmbH, Berlin/Boston 2021.Türkiye Bilimsel ve Teknolojik Araştirma Kurumu: 117K26
Does Personality Moderate the Organizational Justice and Job Satisfaction Relationship?
No full text174 erkek) çalışan katılmıştır. Katılımcıların yaş ortalaması 33,12 ve ortalama deneyim süresi 116,46 aydır. Katılımcıların büyük çoğunluğunu sağlık çalışanı, akademisyen, mühendis ve öğretmen grubu oluşturmaktadır. Çalışma için katılımcılar Örgütsel Adalet Ölçeği, İş Tatmini Ölçeği, Büyük Beşli Kişilik Envanteri ve demografik bilgi formunu doldurmuştur. Düzenleyici regresyon analizleri, SPSS için Hayes PROCESS makrosu kullanılarak gerçekleştirilmiştir. Cinsiyet ve yaş, ana çalışma değişkenleri ile ilişkili olduğu için kontrol değişkenleri olarak tüm analizlere dahil edilmiştir. Sonuçlar, örgütsel adalet türlerinin iş tatmininin yordayıcıları olduğunu ve kişilik faktörlerinin algılanan örgütsel adalet ile iş tatmini arasındaki ilişkinin düzenleyicileri olduğunu göstermektedir. Kişilik faktörlerinden yalnızca nevrotikliğin düzenleyici bir etkisi olmamıştır. Bulgular, yöneticilerin, çalışanlarına adil bir çalışma ortamı sağlamak ve onların iş tatminlerini artırmak için farklı kişilik özelliklerine sahip çalışanları için farklı stratejiler uygulaması gerekliliğine dikkat çekmek açısından önem taşımaktadır.Örgütsel adalet algısı ile iş tatmini arasındaki ilişkide kişilik özelliklerinin rolünün incelenmesi, örgütlerin performans düzeylerinin iyileştirilmesi için önemli olabilir. Bu çalışmanın amacı, örgütsel adalet algısı ile iş tatmini arasındaki ilişkide kişilik özelliklerinin düzenleyici etkisini incelemektir. Çalışmaya 392 (218 kadınExamining the role of personality in the relationship between organizational justice perception and job satisfaction might be crucial to improve organizations’ performance levels. The aim of the present study is, therefore, to investigate the moderating effect of personality factors on the relationship between organizational justice perception and job satisfaction. In total, 392 (218 female174 male) employees participated in the study. The mean age of the participants was 33.12 and the mean of experience was 116.46 months. The majority of the participants are healthcare professionals, academicians, engineers and teachers. The participants completed the Organizational Justice Scale, Job Satisfaction Index, Big Five Personality Inventory and demographic information form. The moderated regression analyses were conducted by using the Hayes PROCESS macro for SPSS. In all analyses, gender and age were entered as the control variables since they had correlations with the main study variables. Results indicate that types of organizational justice are predictors of job satisfaction and personality factors serve as moderators of the relationship between perceived organizational justice and job satisfaction. Among the personality factors, only neuroticism did not have any moderating effect. The findings might be considerable to draw attention to the necessity of managers to apply different strategies for their employees with different personality traits in order to provide a fair work environment for their employees and to increase their job satisfaction
Eskiyen Bir Sistem için Durum Bazli Bakim Politikalari
No full textThanks to the developing technology, R;D studies and the great support given to the defense industry in our country, the defense industry sector is going further and new domestic and national products are being developed day by day. As well as designing and manufacturing new products, it is also very important that the products delivered to the customer can be supported at minimum cost. Within the scope of this study, there is an optimal maintenance policy by establishing a random decision model that optimizes the inspection time for a critical material that is Markov aging in a complex military system that is actively used in the field. According to the condition of the system, which is periodically examined by the user at t time, the most appropriate of the four maintenance and repair policies determined earlier is applied. Thus, it is aimed to intervene before the system fails and to prevent large costs to be encountered in the future. At the same time, with this maintenance and repair approach, the readiness of the system will be increased and customer satisfaction will be ensured. For these four different maintenance and repair policies, maintenance models have been established with the help of renewal theory under all actions that find the optimal review period. Then, the values of some parameters in these models were changed and their effects on maintenance policies were examined.Gelisen teknoloji, AR-GE çalismalari ve ülkemizde savunma sanayiine verilen büyük destek sayesinde savunma sanayii sektörü daha da ileri gitmekte olup, her geçen gün yerli ve milli yeni ürünler gelistirilmektedir. Yeni ürünlerin tasarlanmasi ve üretilmesi kadar müsteriye teslim edilen ürünlerin minimum maliyetle desteklenebilmesi de çok önemlidir. Bu çalisma kapsaminda sahada aktif olarak kullanilan karmasik yapidaki bir askeri sistemde bulunan ve Markov eskiyen kritik bir malzeme için inceleme zamanini en iyileyen rassal karar modeli kurularak optimal bakim politikasi bulunmaktadir. Kullanici tarafindan periyodik olarak ?? zamanda bir incelenen sistemin durumuna göre daha önce belirlenen dört bakim onarim politikasindan en uygun olani uygulanmaktadir. Böylelikle sistem ariza durumuna geçmeden önce müdahale edilerek ileride karsilasilacak büyük maliyetlerin de önüne geçilmesi hedeflenmektedir. Ayni zamanda bu bakim onarim yaklasimiyla sistemin hazir olabilirligi de arttirilarak müsteri memnuniyeti saglanacaktir. Söz konusu dört farkli bakim onarim politikalari için tüm aksiyonlar altinda yenileme teorisinin yardimiyla optimal inceleme periyodunu bulan bakim modelleri kurulmustur. Daha sonra bu modellerdeki bazi parametrelerin degerleri degistirilerek bakim politikalari üzerindeki etkileri incelenmistir
Experimental and Numerical Investigation on Bending Behavior of Ti-6al Parts Produced by Additive Metal Laser Sintering
No full textIn this study, the bending strength characteristic of test specimens manufactured by the direct metal laser sintering method was investigated for different values of additive manufacturing (AM) parameters. The effect of heat treatment on bending strength was also researched by applying annealing and recrystallization annealing to the Ti-6Al-4V parts after the AM. The difference of bending strength values mainly resulting from the heat treatment processes has been explained by microstructural examinations of the specimens manufactured with default AM parameters set. The completed bending tests were verified by finite element analysis models. Moreover, the comparison of the specimen properties was made by material characterizations and density measurements. As a result of the bending tests, the usage of 180 mu m instead of 140 mu m which is the standard hatch spacing value of the additive machine provided the same level of bending strength with a shorter manufacturing period of time. In addition, higher bending strengths were obtained when the lower-cost annealing heat treatment was applied after the AM. Furthermore, the bending strength values of the specimens verified by the finite element method with a difference of 11.6%.This work has been supported by Gazi University Scientific Research Projects Coordination Unit under grant number 06/2018-19. We would like to thank to the management and staff of TuBTAK SAGE for their important contribution to the study, tests and measurements performed within the scope of the study. In addition, we would like to express our gratitude to the G.o.R. GRUP MEDKAL, FSMVu ALUTEAM and TOBB ETu Biomechanics Laboratory employees, where productions and bending tests were performed.Gazi University Scientific Research Projects Coordination Unit [06/2018-19
Kombine Dogal Gaz Çevrim Santralleri için Entegre Üretim Planlama ve Gün Öncesi Elektrik Piyasasi Teklif Optimizasyonu
No full textElectricity is considered one of the most important inventions on earth. Although electricity generation sources have been diversified over time, natural gas is still one of the most important electricity generation sources in the world in this century. The situation in our country has evolved in a similar way and when we look at the electricity production resources, it is seen that natural gas has the largest share. Installation of natural gas power plants is cheap and fast. At the same time, its thermodynamic efficiency is higher when compared to other power plants. Electricity is not a type of energy that can be stored in large amounts by its nature. Therefore, it is important for the producers to make the right amount of production at the right time in natural gas power plants, as it is the case for all power plants. Within the scope of this study, a production planning model and a bidding model in the day ahead electricity market were developed for a producer with a combined natural gas power plant. These two models are solved in an integrated way, which is new in the literature, and they and present the producer with the results of the proposal decisions under the uncertainty of the market clearing price (MCP) in the day ahead electricity market. Due to the market structure, the day-ahead electricity market collects offer one day before real-time matches. In the study, a scenario-based model is proposed in order to take into account uncertainty in MCP. In the production model, it is aimed to minimize the production costs, the cost of switching the power plant to different production levels, and the maintenance, repair and labor costs. In the model, the operating conditions of the power plant from the previous day, secondary frequency control (SFC) obligations, generation capacities and the start-up situations where the power plant will start operating are taken into account. In the bid model, on the other hand, while maximizing the revenues is aimed, the number of bids, the status of the bids, MCPs and bid prices are taken into consideration. Scenarios were produced according to the expected values and errors, coming from a forecasting model in the scenario- based model presented to eliminate the MCP uncertainty in the model. In the numerical analysis part, scenario-based integrated solutions were obtained by running the model for a certain date, and the significant superiority of these solutions over the solutions found only with the expected values of MCP was shown.Elektrik icat edildiği tarihten itibaren yeryüzündeki en önemli buluşlardan biri olarak kabul edilmektedir. Zamanla elektrik üretim kaynakları çeşitlendirilse de dünyada içinde bulunduğumuz yüzyılda hala en önemli elektrik üretim kaynaklarından biri doğal gazdır. Ülkemizde de durum benzer şekilde evrilmiş ve elektrik üretim kaynaklarına bakıldığı zaman en büyük yüzdeye doğal gazın sahip olduğu görülmektedir. Doğal gaz elektrik santrallerinin kurulumları görece olarak ucuz ve hızlıdır. Aynı zamanda diğer elektrik santralleriyle kıyaslandığında termodinamik verimliliği daha yüksektir. Elektrik doğası gereği yüksek miktarlar için depolanabilen bir enerji türü değildir. Dolayısıyla, bütün elektrik santrallerinde olduğu gibi doğal gaz santrallerinde de üretimin doğru zamanda doğru miktarda yapılması üretici için önem kazanmaktadır. Bu çalışma kapsamında kombine doğal gaz çevrim santraline sahip bir üretici için üretim planlama modeli ve gün öncesi elektrik piyasasında teklif modeli oluşturulmuştur. Oluşturulan bu iki model literatürde daha önce rastlanmadığı şekilde entegre olarak çözülmüş ve üreticiye hem üretim çizelgesi hem de gün öncesi elektrik piyasasında piyasa takas fiyatı (PTF) belirsizliği altında teklif kararlarıyla ilgili sonuçlar sunmaktadır. Gün öncesi elektrik piyasası, piyasa yapısı gereği gerçek zamanlı eşleşmelerden bir gün önce teklifleri toplamaktadır. Çalışmada PTF ile ilgili belirsizliği göz önüne almak için senaryo bazlı bir teklif oluşturma modeli önerilmektedir. PTF belirsizliğini gidermek için sunulan senaryo bazlı modelde bir tahmin modeli sonucu elde edilen beklenen değer ve hataya göre senaryolar üretilmiştir. Üretim modelinde üretim maliyetleri, santralin farklı üretim seviyelerine geçme maliyeti ve bakım onarım ve işçilik maiyetlerini en azlamak amaçlanmaktadır. Modelde bir önceki günden santralin çalışma durumları, sekonder frekans kontrol (SFK) yükümlülükleri, üretim kapasiteleri ve santralin çalışmaya başlayacağı kalkış durumları göz önüne alınmıştır. Teklif modelinde ise gelirlerin en çoklanması amaçlanırken, teklif sayıları, tekliflerin verilme durumları, PTF'ler ve teklif fiyatları göz önünde bulundurulmaktadır. Nümerik analiz kısmında belirli bir tarih için model çalıştırılarak senaryo bazlı entegre çözümler elde edilmiş ve bu çözümlerin sadece beklenen değerle bulunacak çözümlere göre önemli bir üstünlüğü gösterilmiştir
Educational Needs in Post Graduate Public Health Medicine Specialty Training in Novel Coronavirus Disease (covid-19) Fight
No full textObjective: The aim of this study was to evaluate the educational needs of public health specialists and students in training during the COVID-19 pandemic. The curriculum of the public health specialty education was assessed in terms of responsiveness to problems during a pandemic. Material and Method: Data was collected from public health specialists and students within the context of Public Health Proficiency Board monitoring and evaluation work, using a data collection form created on a web-based platform between 12 and 31 May 2020. Results: Among 170 participants, 57 were specialists and 133 were in training to be specialists. Of the participants, 67.6% female and 32.4% male. Participating in this study during a time of pandemic, 89.4% stated that they worked in the frontlines in pandemic control. Of these 71.8% (n=109) stated that they faced difficulties during the pandemic. Top two difficulties were burnout (n=59) and anxiety of contracting the disease (n=58). Specialty training was sufficient according to 26% of the participants. Residents of public health specialty training program and graduates of the program differed in their views of the content of specialty training (p=0.04). Conclusion: In conclusion, we find it advisable to organize training activities to address the educational needs of students’ training in public health that emerged during the pandemic process. © 2022, Nobelmedicus. All rights reserved
Deep Learning Based Hybrid Computational Intelligence Models for Options Pricing
No full textOptions are commonly used by traders and investors for hedging their investments. They also allow the traders to execute leveraged trading opportunities. Meanwhile accurately pricing the intended option is crucial to perform such tasks. The most common technique used in options pricing is Black-Scholes (BS) formula. However, there are slight differences between the BS model output and the actual options price due to the ambiguity in defining the volatility. In this study, we developed hybrid deep learning based options pricing models to achieve better pricing compared to BS. The results indicate that the proposed models can generate more accurate prices for all option classes. Compared with BS using annualized 20 intraday returns as volatility, 94.5% improvement is achieved in option pricing in terms of mean squared error
