Search results for: Gurcan Yazici

Authors: Turgay Ozgur, Bahar Ozgur, Gurcan Yazici

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The aims of the study were to investigate the relationship between the Yo-Yo intermittent recovery test level 1 (YYIR1) and relatively easy to conduct anaerobic power tests such as Sergeant (SJ) and Standing Broad Jump (SBJ), the flexibility Sit&Reach test (S&R) and Hexagon Agility (HA) test in twenty youth soccer players, aged 14 years. Players completed YYIR1 and other performance tests [(SJ), (SBJ] in two consecutive days. The mean YYIR1 distances for the players was 1454 ± 420 m. Peak Anaerobic Power (PAPw) was calculated using SJ (cm) scores. The mean PAPw was 2966,83w. Spearman’s correlation test results revealed that there is a statistically significant negative correlation between HA and YYIR1 tests (r = -0.72, p=0.000) and no significant correlation was found between anaerobic power tests and YYIR1. In conclusion, as a test to measure player’s intermittent aerobic capacity YYIR1 test and anaerobic power test results have not shown significant correlation. Although the YYIR1 test has been used in talent identification, anaerobic qualifications of player’s should be assessed using designated performance tests.

Keywords: yo-yo test, anaerobic power, soccer, sergeant jump test

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Authors: Yağmur Can Gündoğan, Kübra Gürcan Bayrak, Ece Özerdem, Buse Katipoğlu, Erhan Ayas, Rifat Yılmaz

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Eutectic oxide based ceramic matrix composites have a unique microstructure that does not include grain boundary in the form of a continuous network. Because of this, these materials have the properties of perfect high-temperature strength, creep strength, and high oxidation strength. Mechanical properties of them are much related to occurring solidification structures during eutectic reactions. One of the most important production methods of this kind of material is the process of vacuum arc melting. Within scope of this studying, it is aimed to investigate the production of Al₂O₃-YAG-based eutectic ceramics by Arc melting and Spark Plasma Sintering methods for use in aerospace and defense industries where high-temperature environments play an important role and to examine the effects of ZrO₂ and LiF additions on microstructure development and mechanical properties.

Keywords: alumina, composites, eutectic, YAG

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Authors: Bahriye Gülgün, Gökhan Balik, Şükrü Dursun, Kübra Yazici

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The main reasons such as economic growth of society increase of the world population and rapid changes of industrialization cause the amount and the types of pollutants to increase over time. Soil pollution is the typical side effect of industrial activities. As a result of industrial activities, there are large amounts of heavy metal emission every year. Heavy metals are one of the highest pollution sources according to the soil pollution aspect. The usage of hyperaccumulator plants to clean heavy metal polluted soils and the selection of plants for phytoremediation gain importance recently. There are limited numbers of researches on the ornamental plant types of phytoremediation thus; researches on this subject are important. This research is prepared based on the ornamental plant types with phytoremediation abilities.

Keywords: phytoremediation, ornamental plants, landscape reclamation, soil reclamation, environmental pollution

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Authors: Hilmi Yazici

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Just after Ottoman period, new more homogenic republic was struggling to form a national identity and dealing with the cultural and historical background of the nation. This new republic had an aim of modernization and westernization which started in the late ottoman period. In this process, the culture was an important basis to form a new nation and it clearly put forward that the new citizens of the new national republic are to have a modern and national culture. The result of this aimed change was to find the Turkish culture suppressed among the common people of the Anatolia and to take the western modernization and breed this with national culture. So in this context, we can say that this approach separated the people from ottoman culture and its roots to empower the national identity. Repeatedly, it may be said that Turkish folkloric music was an important basis for the new revolution, on the other hand classical Turkish music was alienated with the idea that it didn’t belong to Turkish culture. So the aim of this study is to determine how these efforts to nationalize a new identity and culture was successful and conscious intervention to folkloric Turkish music became efficient.

Keywords: opera, nationalism in music, Turkish music

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Authors: Murat Yazici

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Anomalies are irregularities found in data that do not adhere to a well-defined standard of normal behavior. The identification of outliers or anomalies in data has been a subject of study within the statistics field since the 1800s. Over time, a variety of anomaly detection techniques have been developed in several research communities. The cluster analysis can be used to detect anomalies. It is the process of associating data with clusters that are as similar as possible while dissimilar clusters are associated with each other. Many of the traditional cluster algorithms have limitations in dealing with data sets containing categorical properties. To detect anomalies in categorical data, fuzzy clustering approach can be used with its advantages. The fuzzy k-Mode (FKM) clustering algorithm, which is one of the fuzzy clustering approaches, by extension to the k-means algorithm, is reported for clustering datasets with categorical values. It is a form of clustering: each point can be associated with more than one cluster. In this paper, anomaly detection is performed on two simulated data by using the FKM cluster algorithm. As a significance of the study, the FKM cluster algorithm allows to determine anomalies with their abnormality degree in contrast to numerous anomaly detection algorithms. According to the results, the FKM cluster algorithm illustrated good performance in the anomaly detection of data, including both one anomaly and more than one anomaly.

Keywords: fuzzy k-mode clustering, anomaly detection, noise, categorical data

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Authors: Gürcan D. Baysal, Ali Tanış

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In this study, samples of plant types including rose hip (Rosa canina L.), jujube (Ziziphus jujube), sea buckthorn (Hippophae rhamnoides), elderberry (Sambucus nigra), apricot (Prunus armeniaca), scots pine (Pinus sylvestris), and cedar of Lebanon (Cedrus libani) were grown using plant supporting units called Ekobox and drip irrigation systems in the Karapınar, Konya region of Turkey to reveal the efficiency of Ekobox and drip irrigation compared against a control with no irrigation. The plant diameter, height, and survival rates were determined, compared with each other, and statistically analyzed. According to the statistical analysis of the results, Ekobox applications resulted in the highest values for survival rate, diameter, and height measurements whereas the lowest values were determined in the control groups. These results indicate that the cultivation of plants with Ekobox may help protect against the loss of fertile soils as an effective mechanism for combating erosion and desertification. These advantages may also lead to a lasting economic effect on the cultivation of plants by locals of the Karapınar, Konya province who suffer from an ever-decreasing underground water level as a result of agricultural consumption.

Keywords: drip irrigation, ekobox, plant diameter, plant height, plant survival rate

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Authors: Alev Erenler, Yeliz Yazici

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It is undoubtful that the development in the technology has been increasing the importance of engineering day by day along with the interest of the profession also. Like in any other genre, the success in engineering career is directly related to the amount of the satisfaction from the profession. Having satisfaction is an important factor for both having psychological health and efficiency. In this concept, the engineers from all steps, like students from different grades, working in related professions and the candidates of engineering have been included in order to define the expectations of the profession and the levels if professional satisfaction. In the concept of the study, the factors such as; the graduated university, the university which has been attending at, the grades of the participants, the reasons behind the choosing the university, the order of the choices and demographic values have planned to examine. It is thought that these factors have a meaningful effect on the professional expectations. It is also aimed to find the similar participants from the working life, and the data is to be compared to candidates of engineering in terms if differentiation of expectations. The related data will be gathered by the help of the scale prepared and developed by the researchers special for this study, titled as ' the professional expectation scale for engineers'. The data is to be analyzed in SPSS program, and the results will be interpreted in relation with the literature.

Keywords: engineering education, engineers' professional expectations, engineering students' professional expectations, students’ university choices

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Authors: Judith Mwakalonge, Geophrey Mbatta, Cuthbert Ruseruka, Gurcan Comert, Saidi Siuhi

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Recent advancements in technology have fostered the development of Electric Vehicles (EVs) that provides relief from transportation dependence on natural fossil fuels as sources of energy. It is estimated that more than 50% of petroleum is used for transportation, which accounts for 28% of annual energy use. Vehicles make up about 82% of all transportation energy use. It is also estimated that about 22% of global Carbon dioxide (CO2) emissions are produced by the transportation sector, therefore, it raises environmental concerns. Governments worldwide, including the United States, are investing in developing EVs to resolve the issues related to the use of natural fossil fuels, such as air pollution due to emissions. For instance, the Bipartisan Infrastructure Law (BIL) that was signed by President Biden on November 15th, 2021, sets aside about $5 billion to be apportioned to all 50 states, the District of Columbia, and Puerto Rico for the development of EV chargers. These chargers should be placed in a way that maximizes their utility. This study aims at studying the charging behaviors of Electric Vehicle (EV) users to establish factors to be considered in the selection of charging locations. The study will focus on social-economic and land use data by studying the relationship between charging time and charging locations. Local factors affecting the charging time and the chargers’ utility will be investigated.

Keywords: electric vehicles, EV charging stations, social economic factors, charging networks

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Authors: Judith Mwakalonge, Geophrey Mbatta, Saidi Siuhi, Gurcan Comert, Cuthbert Ruseruka

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Transportation agencies worldwide continuously monitor their roads' conditions to minimize road maintenance costs and maintain public safety and rideability quality. Existing methods for carrying out road condition surveys involve manual observations of roads using standard survey forms done by qualified road condition surveyors or engineers either on foot or by vehicle. Automated road condition survey vehicles exist; however, they are very expensive since they require special vehicles equipped with sensors for data collection together with data processing and computing devices. The manual methods are expensive, time-consuming, infrequent, and can hardly provide real-time information for road conditions. This study contributes to this arena by utilizing built-in vehicle technologies, drones, and deep learning to automate road condition surveys while using low-cost technology. A single model is trained to capture flexible pavement distresses (Potholes, Rutting, Cracking, and raveling), thereby providing a more cost-effective and efficient road condition monitoring approach that can also provide real-time road conditions. Additionally, data fusion is employed to enhance the road condition assessment with data from vehicles and drones.

Keywords: road conditions, built-in vehicle technology, deep learning, drones

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Authors: Ali Mardani-Aghabaglou, Zia Ahmad Faqiri, Semsi Yazici

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In this study, the effect of permeability reducing admixture (PRA) utilization on fresh properties, compressive strength and sulfate resistance of self-consolidating concrete (SSC) were investigated. For this aim, two different commercial PRA were used at two utilization ratios as %0.1 and %0.2 wt. CEM I 42.5 R type cement and crushed limestone aggregate having Dmax of 15 mm were used for preparing of SCC mixtures. In all mixtures, cement content, water/cement ratio, and flow value were kept constant as 450 kg, 0.40 and 65 ± 2 cm, respectively. In order to obtain desired flow value, a polycarboxylate ether-based high range water reducing admixture was used at different content. T50 flow time, flow value, L-box, and U-funnel of SCC mixture were measured as fresh properties. 1, 3, 7 and 28-day compressive strength of SCC mixture were obtained on 150 mm cubic specimens. To investigate the sulfate resistance of SCC mixture 75x75x285 mm prismatic specimens were produced. After 28-day water curing, specimens were immersed in %5 sodium sulfate solution during 210 days. The length change of specimens was measured at 5-day time intervals up to 210 days. According to the test results, all fresh properties of SCC mixtures were in accordance with the European federation of specialist construction chemicals and concrete systems (EFNARC) critter for SCC mixtures. The utilization of PRA had no significant effect on compressive strength and fresh properties of SCC mixtures. Regardless of PRA type, sulfate resistance of SCC mixture increased by adding of PRA into the SCC mixtures. The length changes of the SCC mixtures containing %1 and %2 PRA were measured as %8 and %14 less than that of control mixture containing no PRA, respectively.

Keywords: permeability reducing admixture, self-consolidating concrete, fresh properties, sulfate resistance

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Authors: Kemal Efe Eseller, Göktuğ Yazici

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Laser-induced breakdown spectroscopy (LIBS) is a rapid optical atomic emission spectroscopy which is used for material identification and analysis with the advantages of in-situ analysis, elimination of intensive sample preparation, and micro-destructive properties for the material to be tested. LIBS delivers short pulses of laser beams onto the material in order to create plasma by excitation of the material to a certain threshold. The plasma characteristics, which consist of wavelength value and intensity amplitude, depends on the material and the experiment’s environment. In the present work, medicine samples’ spectrum profiles were obtained via LIBS. Medicine samples’ datasets include two different concentrations for both paracetamol based medicines, namely Aferin and Parafon. The spectrum data of the samples were preprocessed via filling outliers based on quartiles, smoothing spectra to eliminate noise and normalizing both wavelength and intensity axis. Statistical information was obtained and principal component analysis (PCA) was incorporated to both the preprocessed and raw datasets. The machine learning models were set based on two different train-test splits, which were 70% training – 30% test and 80% training – 20% test. Cross-validation was preferred to protect the models against overfitting; thus the sample amount is small. The machine learning results of preprocessed and raw datasets were subjected to comparison for both splits. This is the first time that all supervised machine learning classification algorithms; consisting of Decision Trees, Discriminant, naïve Bayes, Support Vector Machines (SVM), k-NN(k-Nearest Neighbor) Ensemble Learning and Neural Network algorithms; were incorporated to LIBS data of paracetamol based pharmaceutical samples, and their different concentrations on preprocessed and raw dataset in order to observe the effect of preprocessing.

Keywords: machine learning, laser-induced breakdown spectroscopy, medicines, principal component analysis, preprocessing

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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: Canan Gunay Yazici, Zubeyir Sarı, Devrim Tarakci

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Background: Hippotherapy considered as global techniques used in rehabilitation of children with cerebral palsy as it improved gait pattern, balance, postural control, balance and gross motor skills development but it encounters some problems (such as the excess of the cost of horses' care, nutrition, housing). Hippotherapy simulator is being developed in recent years to overcome these problems. These devices aim to create the effects of hippotherapy made with a real horse on patients by simulating the movements of a real horse. Objectives: To evaluate the efficacy of hippotherapy simulator on gross motor functions, sitting postural control and dynamic balance of children with cerebral palsy (CP). Methods: Fourteen children with CP, aged 6–15 years, seven with a diagnosis of spastic hemiplegia, five of diplegia, two of triplegia, Gross Motor Function Classification System level I-III. The Horse Riding Simulator (HRS), including four-speed program (warm-up, level 1-2-3), was used for hippotherapy simulator. Firstly, each child received Neurodevelopmental Therapy (NDT; 45min twice weekly eight weeks). Subsequently, the same children completed HRS+NDT (30min and 15min respectively, twice weekly eight weeks). Children were assessed pre-treatment, at the end of 8th and 16th week. Gross motor function, sitting postural control, dynamic sitting and standing balance were evaluated by Gross Motor Function Measure-88 (GMFM-88, Dimension B, D, E and Total Score), Trunk Impairment Scale (TIS), Pedalo® Sensamove Balance Test and Pediatric Balance Scale (PBS) respectively. Unit of Scientific Research Project of Marmara University supported our study. Results: All measured variables were a significant increase compared to baseline values after both intervention (NDT and HRS+NDT), except for dynamic sitting balance evaluated by Pedalo®. Especially HRS+NDT, increase in the measured variables was considerably higher than NDT. After NDT, the Total scores of GMFM-88 (mean baseline 62,2 ± 23,5; mean NDT: 66,6 ± 22,2; p < 0,05), TIS (10,4 ± 3,4; 12,1 ± 3; p < 0,05), PBS (37,4 ± 14,6; 39,6 ± 12,9; p < 0,05), Pedalo® sitting (91,2 ± 6,7; 92,3 ± 5,2; p > 0,05) and Pedalo® standing balance points (80,2 ± 10,8; 82,5 ± 11,5; p < 0,05) increased by 7,1%, 2%, 3,9%, 5,2% and 6 % respectively. After HRS+NDT treatment, the total scores of GMFM-88 (mean baseline: 62,2 ± 23,5; mean HRS+NDT: 71,6 ± 21,4; p < 0,05), TIS (10,4 ± 3,4; 15,6 ± 2,9; p < 0,05), PBS (37,4 ± 14,6; 42,5 ± 12; p < 0,05), Pedalo® sitting (91,2 ± 6,7; 93,8 ± 3,7; p > 0,05) and standing balance points (80,2 ± 10,8; 86,2 ± 5,6; p < 0,05) increased by 15,2%, 6%, 7,3%, 6,4%, and 11,9%, respectively, compared to the initial values. Conclusion: Neurodevelopmental therapy provided significant improvements in gross motor functions, sitting postural control, sitting and standing balance of children with CP. When the hippotherapy simulator added to the treatment program, it was observed that these functions were further developed (especially with gross motor functions and dynamic balance). As a result, this pilot study showed that the hippotherapy simulator could be a useful alternative to neurodevelopmental therapy for the improvement of gross motor function, sitting postural control and dynamic balance of children with CP.

Keywords: balance, cerebral palsy, hippotherapy, rehabilitation

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