Domestication-driven metaorganism evolution in wheat

Plants are not standalone entities but colonized by an immense diversity of eukaryotic and prokaryotic microbes, collectively called the “plant microbiota”. In my PhD thesis, I studied the impact of domestication on the vertically-transmitted (i.e. seedborne) and environmentally-acquired microbial community assembly in the bread wheat Triticum aestivum and its wild progenitors. Furthermore, I disentangled factors shaping seedborne microbial variation in domesticated wheat. In my study, I improved and optimized techniques to increase the accuracy and resolution of amplicon-based sequencing of wheat seeds based on 16S rRNA and ITS marker loci for bacterial and fungal profiling, respectively. Using these techniques, I revealed that: i) Domestication may has conferred a strong role of stochastic processes in the assembly of vertical transmitting microbes, ii) Domestication has not affected the ability of the plant to assemble soil-derived microbial diversity in leaves and roots, iii) Intra- and inter-plant variation is comparable in seedborne microbial communities. This study is, to the best of my knowledge, the most comprehensive study analyzing wheat microbial communities spanning a wide collection of genotypes in details

INVESTIGATION OF THREE DIMENSIONAL SPATIAL ABILITY LEVELS

Spatial ability is an important factor affecting student achievement in science and mathematics education. In this study, it is aimed to investigate the spatial ability levels of students studying in chemistry department. Molecular model spatial ability test prepared for chemistry education was used in the study. The test measures spatial ability in two dimensions: rotation in space and visualization in the mind. In the research, t-test was used to determine whether there is a difference between the gender, class levels and the spatial ability and sub-dimensions of the molecular model. One-way analysis of variance was used to determine whether there was a difference between the achievement levels of the students and the spatial ability and sub-dimensions of the molecular model. No correlation was found between the gender and molecular model spatial ability and sub-dimensions of the students. There was a significant difference between students' class levels and spatial ability and sub-dimensions. As students' class levels increase, their ability to visualize increases. There was also a significant difference between the students' school achievements and the rotation of the molecular model in space with spatial ability and sub-dimensions and visualization in mind. The higher the grade point average, the more the ability to rotate and model the molecular model in space with its spatial ability and sub-dimensions.  Article visualizations

CHEMISTRY WITH METAPHORS: CASE OF KOCAELI (TURKEY) VOCATIONAL SCHOOL

The aim of this study is to investigate the metaphors of chemistry students about chemistry science. For this purpose, a single question was asked to measure their perceptions about chemistry. Qualitative method was adopted in the research. Content analysis was applied to the data obtained. The sample of the study consists of students of Chemistry Program of Kocaeli Vocational School. Data were collected in the fall semester of 2018-2019. 68 students participated in the study. The reliability of the study was found to be 96% according to expert opinion. 32 metaphors were obtained. The metaphors obtained were collected in 7 themes: danger, comprehensive, cumulative, happiness, exploratory, innovative, magical. Only one of the metaphors has been negatively evaluated under the others positive theme. It was observed that “life” metaphor was used the most. Female students produced 25 metaphors and male students produced 11 metaphors. Metaphors for two themes were produced by female students. Female students differ from male students in terms of the metaphors they produce.  Article visualizations

CHEMISTRY STUDENTS' OPINIONS ABOUT TAKING CHEMISTRY EDUCATION AS DISTANCE EDUCATION

The aim of this study is to determine the opinions of the students studying in chemical and chemical processing technologies departments on take chemistry education in the form of distance education. The research sample consists of students studying in chemistry and petrochemical technology programs in Kocaeli Vocational School. It was applied to students studying in related departments in the fall semester of 2018-2019. The sample consists of 149 students. The mixed method has been adopted in the research. Scale and interview questions were prepared with the literature review. The reliability coefficient of the Chemistry Distance Education Scale was 0.945. There was a high correlation between the dimensions of the scale consisting of three dimensions. In quantitative research; a relationship was found between income and chemistry distance education. It was found that students with low income level were eligible for distance education in chemistry. Distance education diminish students' costs of housing and transportation. In addition, there is no relationship between the gender of the students, the type of education, the level of education of the parents, the department and the class. The qualitative research findings are: a large part of the students indicate that the distance education infrastructure is not sufficient. According to the students, chemistry education is considered to be sufficient for theoretical knowledge only as distance education. Students do not want to take laboratory applications as distance education. Distance education cannot eliminate the need to touch materials while adding visuality. It is determined that students are not ready to take chemistry education from distance education as cultural and cognitive.  Article visualizations

Diagnostics, Prognostics and Maintenance Planning in Smart Grid Equipment

Koşul bazlı bakım sistemleri (KBB) arızaların ve kalan ömrün tespit edilmesini ve bakım planlamasının en etkin şekilde yapılmasını hedefleyen bir araştırma alanı olarak son yıllarda ilgi çekmektedir. KBB’de kritik sistemler (şebekeler, üretim sistemleri, ucak motoru, ucak kanadi, kopruler vs.) üzerine yerlestirilen sensorler sayesinde eldeki sistemin sağlık durumu gerçek zamanlı olarak belirlenir. Bu sağlık bilgisine göre ne kadar faydali ömrü kaldığı tespit edilerek ve bakım planlaması yapılır. Akıllı şebekelerde gerek emreamadeliğin arttırılması gerekse bakım maliyetlerinin azaltılması KBB sistemlerinin etkin şekilde şebeke ekipmanlarında uygulanabilmesine bağlıdır. Bu çalışmada KBB’nin şebeke ekipmanları üzerinde uygulama çalışmaları değerlendirilerek KBB uygulaması için potansiyel görülen ekipmanlar ve bunlar için fırsat ve zorlukluları tartışılacaktır

Classification of Cardiac Beats Using Discrete Wavelet Features

With the growing technology, the tools which continuously monitor the health status of the people are becoming the integral part of our lives. The detection of a cardiac disease or tracking the heart activities for ongoing cardiac conditions is now possible with portable electrocardiography (ECG) monitors. For detection and classification of ECG signals in portable devices, the robust features and efficient classification algorithms are very important. Thus, in this study, a robust feature set based on discrete wavelet transform (DWT) is proposed, and the performance of the classification tools such as artificial neural networks, support vector machines and probabilistic neural networks are compared. After preprocessing, the R peaks are located by the well-known Pan Tompkins algorithm and 200 samples are taken as equivalent R-T interval in the proposed technique. The statistical parameters such as mean, median, standard deviation, maximum, minimum, energy and entropy of DWT coefficients are used as the feature set. The proposed hybrid technique has been tested by classifying three ECG beats as normal, right bundle branch block (Rbbb) and paced beat using the signals from Massachusetts Institute of Technology Beth Israel Hospital (MIT-BIH) arrhythmia database and processed using Matlab 2013 environment. The best accuracy of 99.84% has been obtained by Db4 mother wavelet with artificial neural network as classifier

Yabancı dil öğretimi sürecinde iletişimsel dil öğretim yönteminin uygulanabilirliği konusundaki öğretmen görüşleri

06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır

SURFACE MODEL EXTRACTION FROM THREE DIMENSIONAL SAMPLED DATA

Bu çalışmada üç boyutlu örneklenmiş noktasal verilerden özellikle de medikal alanda MRI ve CT gibi medikal görüntüleme yöntemleri ile elde edilmiş hacimsel veriler kullanılarak ilgili alanların üç boyutlu yüzey modelleri çıkarılmıştır. Kullanılan yöntem "Marching Cubes" algoritmasıdır (Lorensen vd., 1987). Bu sayede büyük miktardaki ham verinin çok daha kısa zamanda ve etkileşimli olarak görüntülenmesi mümkün olmuştur. Çalışma özellikle medikal veri kümeleri üzerine yoğunlaşmış olmasına rağmen uzaklık ve lazer tarama yöntemleri ile alınmış tüm hacimsel mühendislik verileri üçgensel yüzeyler şeklinde modellenebilir. In this study, three-dimensional surface models of volumetric sampled data especially three-dimensional MRI and CT image pages are extracted by using “Marching Cubes†algorithm (Lorensen vd., 1987). By using this method, it is possible to process and interactively display of large amounts of sampled raw data in very short times relative to direct visualization. Although the work has focused on medical datasets, most of engineering data in three-dimensional structure like range-data and laser scans can be easily modeled as triangular surface patches

Endüstri 4.0 perspektifinden Türkiye’de imalat sanayinin durumu : Sakarya imalat sanayi üzerine bir anket çalışması

06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır.Tarihsel süreçte geçirdiğimiz üç büyük endüstri devrimin sonucunda günümüz teknolojisinin ulaştığı son durum artık insan gücüne eskisi kadar gereksinim duymamakta, geçmiş devrimlerin daha geniş kapsamlı ve bütünleşik olarak ortaya çıkan bu son hali Endüstri 4.0 uygulamaları ile birlikte daha çok bilgisayar uygulamalarına ve bu uygulamalardan elde edilen veri ya da bilgilerin kullanılmasında yapay zekanın süreç içerisinde çoğunlukla sahip olması ve tasarlanacak zeki sistemlerin bu tür bir yapının üzerinde oluşturulması hedeflenmektedir. Bu yapı içerisinde internetin tartışmasız sahip olduğu lider durum ve hemen her türlü nesneyi ya da olayı etrafında toplayabilmesi ve buna bağlı olarak insan gücünün artık belki de yalnızca denetleyici yönde ilerleyebileceği anlayışının yerleşmeye başlaması, gelecekte ortaya konacak yeni teknolojilerin Endüstri 4.0 uygulamalarından çokça etkileneceğini şimdiden göstermektedir.As a result of the three great industrial revolutions we have experienced in the historical process, the latest state of the art of today's technology no longer needs human power as much as it used to be, and this final version of the past revolutions has become more comprehensive and integrated with Industry 4.0 applications and more computer applications and data obtained from these applications. It is aimed that artificial intelligence is mostly possessed in the process of using information and that intelligent systems to be designed are created on such a structure. The fact that the internet in this structure is unquestionably a leader and that it can gather around almost any object or event, and that the perception that human power can possibly advance only on the controller side, is already showing that future technologies will be greatly affected by Industry 4.0 applications

The Impact of Macro-Economic Drivers in Housing Markets: The US Cas

This paper analyzes the effect of macro-economic, financial and commodity market indicators on housing markets. We compare the efficiency of the models generated by Generalized Linear Models (GLM) and Multivariate Adaptive Regression Splines (MARS) according to method free measures for estimating the housing market trend. These models are used for the first time to identify the influence of macro-economic indicators on housing markets and the estimation of the trend in housing markets to our best knowledge. The empirical analysis focuses on the US housing market, and the illustration of the proposed models is done through the monthly historical realizations of S\&P/Case-Shiller National Home Price Index (HPI) and the US macro-economic indicators over the period from 1999-January to 2018-June. It contributes to the literature by highlighting the interaction between macro-economic indicators and housing markets and analyzing the mechanism of housing markets. The findings indicate that the house price trends are estimated with more accuracy and these models capture the joint influence of explanatory variables. Further, the MARS method is shown to outperform GLM compared to the prediction and forecasting power