207 research outputs found
Ibrahim el-Antaki's divan called Burhanul-Burhan-examination and verification
No full textDoktora TeziBu araştırma, Arap ve İslam kültür mirasına katkı sağlamak amacıyla, şair İbrahim el-Antaki'nin (H. 926-M. 1520) "Burhanu'l-Burhan" adlı divanının yazma nüshasını incelemektedir. Başka bir eseri bulunmayan ve çok tanınmayan yazarın bu eseri, araştırmacılar ve muhakkikler tarafından yeterince ele alınmamıştır. Yazarın şiirleri dönemin toplumsal yapısını, halk kültürünü, geleneklerini ve karakteristik özelliklerini yansıtmasına rağmen, eser uzun süre yazarına atfedilmemiştir. Divan, dönemin toplumsal entelektüel seviyesini ortaya koyması ve günümüz kültürüyle karşılaştırma imkânı sunması bakımından önem arz etmektedir. Araştırmada bilimsel inceleme ilkeleri ve tahkik kuralları çerçevesinde yazarın biyografisi, eserin yazara aidiyeti, divanın anlaşılmayan kasidelerinin ve aruz vezinlerinin tespiti, divandaki aruz, dil ve gramer hatalarının tashihi ile şiirlerdeki Beyan ve Bediî sanatlarının özellikleri incelenmiştir.This research examines the manuscript of the divan named "Burhanu'l-Burhan" by poet Ibrahim al-Antaki (H. 926-A.D. 1520) in order to contribute to the Arab and Islamic cultural heritage. This work of the author, who has no other works and is not very well known, has not been sufficiently studied by researchers and scholars. Although the author's poems reflect the social structure, folk culture, traditions and characteristic features of the period, the work has not been attributed to its author for a long time. The divan is important in terms of revealing the social intellectual level of the period and providing an opportunity for comparison with today's culture. In the research, the following issues were addressed within the framework of scientific examination principles and investigation rules: the author's biography, the work's belonging to the author, the detection of the divan's incomprehensible odes and aruz meters, the correction of aruz, language and grammar errors in the divan, and the characteristics of the arts of Beyan and Bediî in the poems were examined
The Impact of Text Representation and Preprocessing on Author Identification
No full textAuthor identification, one of the popular topics in text classification and natural language processing, basically aims to determine the author of a given text through various analyses. In the literature, different text representation approaches and use of preprocessing steps are considered for author identification problem. This paper aims to comprehensively examine the impact of text representation and preprocessing steps on author identification specifically for Turkish language. For this purpose, the contributions of all possible combinations of different text representation approaches, namely unigram and bigram, together with the preprocessing tasks, including stemming and stop-word removal, to the performance of author identification are investigated. For the experimental evaluation, a brand new dataset is constituted. Also, two different classification algorithms, namely Multinomial Naive Bayes and Sequential Minimal Optimization, are employed. The results of the experimental analysis reveal that using bigram features alone should be avoided. Besides, it is shown that stop-words should be kept inside the text while stemming can be preferred depending on the classification algorithm so that higher performance can be achieved for author identification.Author identification, one of the popular topics in text classification and natural language processing, basically aims to determine the author of a given text through various analyses. In the literature, different text representation approaches and use of preprocessing steps are considered for author identification problem. This paper aims to comprehensively examine the impact of text representation and preprocessing steps on author identification specifically for Turkish language. For this purpose, the contributions of all possible combinations of different text representation approaches, namely unigram and bigram, together with the preprocessing tasks, including stemming and stop-word removal, to the performance of author identification are investigated. For the experimental evaluation, a brand new dataset is constituted. Also, two different classification algorithms, namely Multinomial Naive Bayes and Sequential Minimal Optimization, are employed. The results of the experimental analysis reveal that using bigram features alone should be avoided. Besides, it is shown that stop-words should be kept inside the text while stemming can be preferred depending on the classification algorithm so that higher performance can be achieved for author identification
Experimental and theoretical investigation of the fluid behavior during polymeric fiber formation with and without pressure
No full textThe fabrication of polymeric micro/nanofibers is gaining attention due to their use in an array of applications including tissue engineering scaffolds, nanosensors, and fiber-reinforced composites. Despite their versatile nature, polymeric fibers are widely underutilized due to the lack of reliable, large-scale production techniques. Upon the discovery of centrifugal spinning and, recently, pressurized gyration techniques, new research directions have emerged. Here, we report a comprehensive study detailing the optimal conditions to significantly improve the morphology, homogeneity, and yield of fibers of varying diameters. A series of polymeric fibers was created using a 21 wt.% solution of polyethylene oxide in distilled water and the fluid behavior was monitored inside a transparent reservoir using a high-speed camera. Fabrication of the fibers took less than 1 s. Using centrifugal spinning, we studied the formation of the fibers at three different rotational speeds, and for pressurized gyration, one rotational speed was studied with three different nitrogen gas pressures. Using the pressurized gyration technique at a gas pressure of 0.3 MPa, there was significant improvement in the production yield of the fibers. We found a strong correlation between the variation of pressure and the rate of the solution leaving the reservoir with the improved morphology of the fibers. The use of reduced power techniques, like centrifugal spinning and pressured gyration, to yield high-quality nonwoven nanofibers and microfibers in large quantities is important due to their use in rapidly expanding markets. (C) 2019 Author(s)
Data mining through data visualization: a case study on predicting churners on telecomunications data set
No full textBaşarslan, Muhammet Sinan (Dogus Author)Data mining is the process of extracting meaningful information from a large, raw data. These processes are carried out by various, detailed methods. And, the obtained results are used to make various interpretations and to draw conclusions. Deductions can either be made by interpreting the data after various operations or by plotting the data in various forms of graphs. This type of interpretation over graphics is called data mining through data visualization. Generating graphs that can be used to draw various conclusions on a telecommunications data set with the help of some packages included in the R program is presented in the paper. It does not require upper-level math skills to interpret these graphics; and everyone having knowledge about the industry and data set of the graphs has the ability to plot similar graphs and make analysis and interpretations regarding the results obtained on the data set at hand. In this study, R language was preferred as the software infrastructure for data mining applications, and graphs were plotted for interpretation through data visualization with data mining
Turkish-addressed social sciences citation index articles: What does the big picture tell us?
No full textThis study investigates articles in the SSCI written in the English language and published in the ‘Education & Educational Research’ area between 1980 and 2019. In the study, bibliometric methods were used to detect the number of SSCI articles published worldwide, and also the articles with a Turkish author address entered, meaning at least one author provided Turkey as their location. In addition, analysis was conducted according to various variables (e.g., research areas, publication year, number of authors, and source titles). The bibliometric data were obtained from the Web of Science Core Collection database. With regards to the ‘Education & Educational Research’ area, the analysis indicated the dominance of English-speaking countries in terms of the number of SSCI-indexed articles and those that had been cited the most. This finding appears to be affected by the majority of journals indexed in SSCI only accepting articles written in the English language. In terms of the number of SSCI articles published in the area of ‘Education & Educational Research’, Turkey was shown to be ranked seventh worldwide. Within Turkey, the number of SSCI articles for the ‘Education & Educational Research’ area ranked second, after ‘Business & Economics’. In comparison to the overall worldwide trend, the study's findings suggest that Turkish researchers have a tendency towards publishing their articles in mainly Turkey-originated journals with low impact factors. Factors that may affect this tendency and the potential implications of these findings are discussed, together with the limitations of the study and suggestions for further research. © 202
Examining relations between physics-related personal epistemology and motivation in terms of gender
No full text0000-0003-4222-7468WOS: 000467779300010The gender gap continues to exist in physics education. The author examines the gender-related differences in the relations and strengths among personal epistemologies, motivation, and achievement in physics among Turkish high school students. Established questionnaires were used to identify students' personal epistemologies, motivations and achievement in physics. A total of 567 ninth-grade students from three high schools in Mugla Province in Turkey participated in the study. Multigroup structural equation modeling was used to determine the gender differences in the relations and strengths among personal epistemology, motivation, and achievement in physics. Results from the structural equation modeling showed that students' personal epistemologies directly predicted their motivation and indirectly their achievement in physics. Multigroup structural equation modeling analysis showed that the strength of the relations between personal epistemology and motivation varied for female and male students. Implications for future directions are discussed
Açık kaynak kodlu veri madenciliği programları: R’da örnek uygulama
No full textBaşarslan, Muhammet Sinan (Dogus Author)The processes on the way from raw data to meaningful information is called data mining. The data is processed by applying various methods of data mining in order to extract hidden information among raw data. The processed raw data becomes usable in the next steps of data mining. There are many open source and commercial applications to be used in data mining and data processing. In this study, information about data mining programs are given, and a case study on the R program. The R program has been chosen because it has a large preference rate among the users as shown by various graphs.Ham verilerden anlamlı bilgilere geçiş sürecine veri madenciliği denir. Veri, ham veriler arasında gizli bilgileri çıkarmak için çeşitli veri madenciliği yöntemleri uygulanarak işlenir. İşlenmiş ham veriler, veri madenciliğinin bir sonraki aşamasında kullanılabilir hale gelir. Veri madenciliği ve veri işlemede kullanılmak üzere birçok açık kaynak ve ticari uygulama vardır. Bu çalışmada veri madenciliği programları hakkında bilgi verilmiş ve R programı üzerinde bir vaka çalışması sunulmuştur. R programı, çeşitli grafiklerle de gösterildiği üzere kullanıcılar arasında büyük bir tercih oranına sahip olması dolayısıyla seçilmiştir
A Diagnostic Comparison of Turkish and Korean Students' Mathematics Performances on the TIMSS 2011 Assessment
No full textWOS: 000449665400005The purpose of the present study was to analyze an international large-scale data set using a cognitive assessment approach. Although some researchers question the usefulness of international large-scale assessments (e.g., TIMSS), participating countries have continued to use the results from these large-scale assessments to improve their curricula and teaching methods. Despite the common reporting practice-single-score-in these large scale assessments gives useful insights about students' overall performances, they still lack diagnostic information. Cognitive diagnosis models (CDMs) were developed to provide more feedback on students' cognitive strengths and weaknesses. This study retrofitted the TIMSS 2011 eighth grade mathematics assessment by applying a specific CDM called the DINA (the deterministic, inputs, noisy, "and" gate) model to data from South Korea and Turkey. Results of the DINA model were used to make a detailed comparison between students of these two countries
TSCBAS: a novel correlation based attribute selection method and application on telecommunications churn analysis
No full textBaşarslan, Muhammet Sinan (Dogus Author) -- Conference full title: 2018 International Conference on Artificial Intelligence and Data Processing (IDAP); IEEE; Malatya; Turkey; 28 September 2018 through 30 September 2018.Attribute selection has a significant effect on the performance of the machine learning studies by selecting the attributes having significant effect on result, reducing the number of attributes, and reducing the calculation cost. In this study, a new attribute selection method which is a combination of the Rcorrelation coefficient-based attribute selection (RCBAS) and the ρ-correlation coefficient-based attribute selection (ρCBAS) called the Two-Stage Correlation-Based Attribute Selection (TSCBAS) is proposed to select significant attributes. The proposed attribute selection method has been applied to customer churn prediction on a telecommunications dataset for performance evaluation. The dataset used in the study includes real customer call records details for the years 2013 and 2014 obtained from a major telecommunications company in Turkey. Apart from the proposed attribute selection method, four different methods named Rcorrelation coefficient-based attribute selection, ρ-correlation coefficient-based attribute selection, ReliefF, and Gain Ratio have been used for creating five datasets. After that, four classifier algorithms including Random Forest, C4.5 Decision Tree, Naive Bayes and AdaBoost.M1 have been applied. The obtained results have been compared according to the performance metrics comprising Accuracy (ACC), Sensitivity (TPR), Specificity (SPC), F-measure (F), AUC (area under the ROC curve), and run-time. The results of the comparisons show that the proposed attribute selection algorithm outperforms the state of the art methods on customer churn prediction
Densification of rapid carbothermal synthesized and commercial boron carbide by spark plasma sintering
No full textBoron carbide is a structural ceramic material with exceptionally good physical and chemical properties. Thus, boron carbide is proposed for applications in extreme conditions. However synthesizing and sintering of boron carbide is extremely difficult due to its high melting point and strong covalent bonding. Secondary phases, non-uniform composition, complex stoichiometry and powder morphology are problems in most commercial powders as a result of synthesis and powder preparation procedures. Achieving more than 90% TD is difficult due to strong covalent bonding structure and low plasticity of boron carbide. Very high sintering temperatures that approach the melting point are needed for densification. This dissertation seeks to establish an improved understanding on Spark Plasma Sintering (SPS) behaviors of boron carbide and effects of powder properties on final products. Rapid carbothermal reduction (RCR) method was utilized to synthesize boron carbide powder. Submicron boron carbide powders with narrow particle size distribution were synthesized. Free carbon was significantly reduced and near B4C stoichiometry was achieved. Commercial boron carbide powders were also modified by processing in the RCR reactor. Free carbon was reduced to trace amounts; powder morphology and stoichiometry was modified. Commercial, synthesized and modified boron carbide powders were analyzed and characterized using X-Ray diffraction (XRD), electron microscopy, particle size analysis and chemical analyses. Synthesized boron carbide powder had smaller particle size, lower free carbon levels and increased concentration of twinning compared to commercial samples. Standard sintering procedure for boron carbide was established for SPS. Powders were sintered to different temperatures with various dwell times to analyze sintering behavior of boron carbide on SPS without any additives. Synthesized boron carbide powders reached +99% TD at lower temperature and shorter dwell times compared to commercial boron carbide samples. Highly dense materials were produced with limited grain growth. Dense samples were analyzed by XRD and electron microscopy. Knoop hardness tests were applied to dense boron carbide samples. Hardness results showed an improvement with RCR synthesized powders. Results were correlated and powder-sintering-final properties relations were established.Ph.D.Includes bibliographical referencesby Muhammet Fatih Tokso
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