Bu çalışmanın amacı üniversitede çalışanların bakış açısıyla, yöneticilerinin liderlik stillerini inceleyerek, liderlik stilleri ile iş tatmini ve örgütsel bağlılık arasındaki ilişkiyi ve aynı zamanda iş tatmininin liderlik stilleri ile örgütsel bağlılık üzerindeki aracılık etkisini incelemektir. Bunun için, Doğu Anadolu’da bulunan bir üniversitede görev yapan öğretim elemanlarına Çok Faktörlü Liderlik Anketi, İş Tatmini Anketi, Örgütsel Bağlılık Anketi uygulanmıştır. Verilerin analizinde güvenilirlik analizi, faktör analizi, korelasyon analizi, çoklu regresyon analizi ve hiyerarşik regresyon analizi teknikleri kullanılmıştır. Araştırma sonucunda liderlik stilleri ve örgütsel bağlılık arasında pozitif ve anlamlı bir ilişki bulunmuştur. İş tatmininin analize katılması ile liderlik stillerinin örgütsel bağlılığa etkisinin azaldığı ve iş tatmininin kısmi aracılık etkisinin olduğu bulunmuştur (Beta = 0.321; Beta = 0.134).
When the existing structure stock is examined, it can be seen that the majority of buildings have reinforced concrete (RC) carrier systems. This case, combined with the increasing population and the increase in urbanization and industrialization, to be increased the need for concrete, which is the raw material of RC building production, day by day. In line with the stated need, the expected need must be met by taking into account both economic and ecological facts in concrete production without compromising the material mechanical properties of concrete (compressive strength, strain, ductility, etc. in concrete). Within the scope of the study, it is planned to fabricate a total of 4 RC beam specimens using both conventional and natural perlite aggregate. After the loading tests, the load-displacement relationship, energy consumption capacity and damage distributions of the specimens will be investigated. In the light of all test data, the usability of natural perlite aggregate in RC beams will be revealed.
While the number of registered vehicles in Erzincan is approximately 49,000 in 2015, this figure has increased to 59.000 by 2018. The city, which has a population of 139,000, has been one of the cities with the highest population / vehicle . In the current traffic systems, the delay times increased, the densities increased and the blockages started to show. As a result of increasing number of vehicles and transportation demands, there has been a need to improve the intersection and existing access roads throughout the city. In the light of this information; Especially, the intersection of Erzincan Mengücek Gazi Training and Research Hospital with 500 bed capacity was taken into consideration. During the peak periods, 676 vehicle roadside parking spaces were used in the hospital, which is the center of attraction of the city. Expectations and needs of the users were put forward and the intersections were simulated with the Microscopic Simulation Method using AIMSUN program. The most appropriate intersection type has been determined by taking into consideration the factors such as delay, travel time, and stop time and applicability.
After the realization of memristors, researchers have focused on other nonlinear memory elements such as memcapacitors and meminductors. Many circuits are designed to emulate these mem-elements since it is not possible to find these components on the market as discrete circuit elements. This study presents a Differential Difference Current Conveyor (DDCC)-based meminductor circuit emulator able to produce both hard switching and smooth switching behaviors without changing any circuit topology. The proposed meminductor circuit consists of only two DDCCs, a single analogue multiplier, a transistor, and three grounded passive circuit elements. No other circuit elements such as a memristor or memcapacitor were used to obtain meminductive behavior. The frequency dependence, pulse response, transition from smooth switching to hard switching, and Monte Carlo analyses of the proposed meminductor were investigated. A meminductor-based regular spike generator was designed as an application of the proposed meminductor, and a regular spike train was successfully produced.
Türk dillerinde /+CA/ ekinin köken ve işlevi konusunda birçok yorum ve karışıklık söz konudur. Ekin sınırlandırma işlevi bugün neredeyse tüm Türk lehçelerinde kullanılan bazı edatlarla benzerlik ve köken ilişkisi taşıdığını göstermektedir. Türkçenin birçok lehçesinde görülen “cek, çaḳı, çaḳlıġ, çamalı, çekem, çen, çenli, çeyin” gibi benzer veya yakın işlevde olan edatların /+CA/ ile sadece işlev yönüyle mi benzediği, yoksa köken itibarıyla da ilgisinin olup olmadığı izaha muhtaçtır. Bazı edatların “-A kadar” anlamıyla sınır bildiren kullanımlarında olduğu gibi /+CA/ eki yönelme hâli eki alan bir kelimeden sonra kullanıldığında sınırlandırma bildirebilir. Bu çalışmada, eski Türkçe döneminden bugünkü lehçelere ve ağızlara kadar aynı anlamda sınırlandırma bildiren /+gA+çA/ > /+A+çA/ yapıları ile irtibatlı olduğu düşünülen bazı edatlar karşılaştırılmıştır.
Crack detection is very important during the inspection of building structures to determine whether they are safe. Therefore, to ensure the reliability and longevity of buildings, it is necessary to have experts periodically carry out building inspections. Building inspection has traditionally been conducted using human-based visual inspection methods as well as artificial intelligence methods that have shown great success in computer vision in recent years. In this study, 9 different models (Xception, VGG16, ResNet101, InceptionV3, InceptionResNetV2, MobileNetV2, DenseNet169, NASNetMobile, and EfficientNetB6), which have shown significant success in the field of artificial intelligence, are discussed to detect and classify cracks in building structures. In addition, a new fusion model structure called Mobile-DenseNet has been proposed by making block cutting and adding auxiliary layers to the MobileNetV2 and DenseNet169 model structures. With this proposed model structure, cracks in concrete structures were classified. A dataset consisting of concrete surface images was used to detect and classify cracks occurring in concrete structures, and a 99.87 % success rate was achieved with the proposed Mobile-DenseNet model in classifying cracks occurring on the concrete surface. The proposed model outperformed the traditional pretrained model structures in the study in terms of the number of transactions, density, features, complexity, and success accuracy.
This research was carried out to determine the effect of entrepreneurship-based STEM education on secondary school students’ self-regulation skills. The sample of the study consisted of 20 students studying in the 8th grade in the 2019-2020 academic year. Mixed method was preferred and single group pre-test-post-test model was used in the study. “Perceived Self-Regulation Skills Scale” was used to obtain quantitative data. The open-ended “Semi-structured interview form” was used to obtain qualitative data. Pre-and post-test means of quantitative data were compared by paired-sample t test and content analysis method was used to compare the pre-and post-test means of qualitative data. Entrepreneurship-based STEM education was provided to the students for 8 weeks. As a result of the research, there was no significant difference between the pre-and post-test scores of the students’ self-regulation skills, however, there was an increase in favor of the post test. In the qualitative data related to self-regulation skills, an increase was also observed in favor of the post-test regarding the the concept of self-efficacy and the sub-dimensions of self-regulation skills, called “openness” and “seeking”.
In this study, a memristor-based 2-DOF PI controller (2-DOF Mem-PI) was designed for the temperature profile tracking control of a heat flow experiment (HFE) setup. A simulation study is presented in which the performance of the designed controller is compared with a standard 2-DOF PI controller. Compared to 1-DOF control structures, 2-DOF controllers that include an extra adjustable parameter perform better in terms of response to disturbances and improving the transient response of the system. In addition, memristor-based controllers (Mem-PI and 2-DOF Mem-PI) and standard controllers (PI and 2-DOF PI) were compared and it was determined that because of the variable memristance value, the control structures containing memristors showed an adaptive feature. The simulation results demonstrated the success of the proposed controller in temperature profile reference tracking and showed the memristor to be applicable in nonlinear control structures.
Neural networks are a state-of-the-art approach that performs well for many tasks. The activation function (AF) is an important hyperparameter that creates an output against the coming inputs to the neural network model. AF significantly affects the training and performance of the neural network model. Therefore, selecting the most optimal AF for processing input data in neural networks is important. Determining the optimal AF is often a difficult task. To overcome this difficulty, studies on trainable AFs have been carried out in the literature in recent years. This study presents a different approach apart from fixed or trainable AF approaches. For this purpose, the activation function cyclically switchable convolutional neural network (AFCS-CNN) model structure is proposed. The AFCS-CNN model structure does not use a fixed AF value during training. It is designed in a self-regulating model structure by switching the AF during model training. The proposed model structure is based on the logic of starting training with the most optimal AF selection among many AFs and cyclically selecting the next most optimal AF depending on the performance decrease during neural network training. Any convolutional neural network (CNN) model can be easily used in the proposed model structure. In this way, a simple but effective perspective has been presented. In this study, first, ablation studies have been carried out using the Cifar-10 dataset to determine the CNN models to be used in the AFCS-CNN model structure and the specific hyperparameters of the proposed model structure. After the models and hyperparameters were determined, expansion experiments were carried out using different datasets with the proposed model structure. The results showed that the AFCS-CNN model structure achieved state-of-the-art success in many CNN models and different datasets.
An experimental study was performed on fıve reinforced concrete (RC) columns to investigate the structural behavior of highly corroded RC columns. Four of the RC columns were corroded using an accelerated corrosion method for different corrosion levels at longitudinal bars as 15.4, 20.2, 27.3 and 28.3%. RC columns were tested under cyclic load for a constant axial load ratio of 0.40. After the loading test, the actual corrosion levels were obtained by extracting the longitudinal bars and stirrups following the breaking of the RC columns. Load-displacement curves, ductility ratios and energy absorption capacities oftested RC columns were obtained. Test results revealed that the ductility ratios of corroded RC columns should be determined in accordance with energy-based or bilateral failure criteria due to the misleading of increased ductility ratios of corroded RC columns based on the displacement method.
In this study, a four rotor Unmanned Aerial Vehicle (UA V) that is called Quadrotor (Micro UAV), is used to test and show effectiveness of 2 DOF PI controller for path tracking of Micro UAV for different reference routes such as zigzag and inclined circle routes. Then, a well-tuned conventional PI controller is also applied to show the performance and priority of 2 DOF PI controller for the same reference routes. Micro UAV is a low cost system and equipped with sonar, GPS and inertia sensors as well. The dynamic structure of Micro UAV is handled with two different separated model dynamics that are inner and outer loops. Both controllers are applied and compared in terms of path tracking performance experimentally for different reference routes.
Eski Türk edebiyatında mesneviler birer anlatma esasına dayalı metin türü olarak sahada geniş yer bulmuş ve özellikle dönem edebiyatının geniş halk kitleleri ile buluştuğu bir alan olmuştur. Klasik Türk edebiyatının saray ekseninden uzaklaşarak geniş coğrafyalara yayıldığı mesnevi alanında şüphesiz Türk edebiyatı eşsiz eserlere sahiptir. Tüm mesneviler arasında ise akıllara ilk olarak Leyla ve Mecnun gelmektedir. Neredeyse her yüzyılda karşılaşılan bir hikâye olan bu mesnevi, birçok şair tarafından işlense de Fuzûlî ile bu mesnevinin özdeşleşmiş olması herkesçe kabul gören bir gerçektir. Eldeki çalışma, adı geçen mesnevide iki ana karakter olan Leylâ ve Mecnûn dışındakileri ele almakta ve mesneviye farklı bir açıdan yaklaşmaktadır. Mesnevi, çalışmamızda “ağyâr” eksenli olarak ele alınmıştır. Âşık ve maşuk tasvirleri aşkı anlamak için bir çıkış noktası olarak görünse de aşkı anlamak için neyin aşk olduğunun yanında nelerin aşk olmadığını da iyice irdelemek gerekir. Bu sebeple çalışmamız âşık ve maşuk dışında kalan ve “ağyâr” olarak tabir ettiğimiz kişi ve kavramlara odaklanmaktadır. “Ağyâr”, yabancılar anlamında olup Leylâ ve Mecnûn dışındaki tüm tip ve kavramları kapsayan temel bir unsur olarak çalışmamızda yer bulacaktır.
In the literature, only one empirical model is available as a nondestructive method for the prediction of seismic performance levels of corroded reinforced concrete (RC) columns as a function of the initial corrosion crack width at lower corrosion levels. Because of the ruptured transverse reinforcement bars at higher corrosion levels, the structural behavior may turn brittle in terms of shear failure. Therefore, in this study, higher corrosion levels for a different concrete strength level from that empirical model were studied. To do this, four RC columns were subjected to accelerated corrosion, and the widths of initial corrosion cracks were measured. The corroded RC columns were then tested under combined constant axial load and cyclic lateral displacement excursions. After the cyclic loading test, the actual corrosion levels at each reinforcement bar were obtained by extracting the reinforcement bars from the concrete. Test results showed that the prediction of seismic performance levels of corroded RC columns based on initial corrosion crack widths were limited owing to the nonlinear increase in the crack width with the increase in the corrosion levels. New empirical models were developed to predict the remaining energy capacities and seismic performance levels of the corroded RC columns.
Carbonation and chloride penetration, which occur as a result of various environmental effects in reinforced concrete structures, cause reinforcement bar corrosion. Physical and chemical deterioration processes caused by corrosion lead to section losses in pitting or homogeneous forms of reinforcement bar. With section losses, decreases are observed in the material characteristic properties of the reinforcement bar such as yielding strength, ultimate/failure strength and strain property. Within the scope of the current study, it was aimed to examine the models used in the existing literature to predict the mechanical properties of corroded reinforcement bars such as yielding strength, ultimate/failure strength and elasticity modulus, as a function of the corrosion ratio. For this purpose, an analytical study will be carried out on reinforcement bars with different reinforcement diameters, corrosion ratios and corrosion types. From the research to be conducted, it is expected that the prediction performances of the corrosion ratios taken into account in the studies in which previous models were developed will show a appropriate harmony with different corrosion ratios.
