Search results for: Alev Erenler
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8

Search results for: Alev Erenler

8 The Perception of ‘School’ as a Positive Support Factor

Authors: Yeliz Yazıcı, Alev Erenler

Abstract:

School is an institution designed to provide learning, teaching places and environments under guidance of selected teachers. School is not just a place or institution but it is a place where complex and living structures are alive and always changing. It is also an undeniable fact that schools have shaped the ideas, future, society as well as the students and their lives. While this is the situation, schools having academic excellence is considered as successful ones. Academic excellence is a composition of excellence in teachers, management and physical environment, also. This is the general perception of the authorities and parents when the excellence is the point but the school is a developing and supporting organism. In this concept, the main aim of this study is to compare student and teacher perceptions of school as a ‘positive support factor’. The study is designed as a quantitative and qualitative design and a questionnaire is applied to both teachers and students via online and face to face meetings. It is aimed to define the perceptions of the participants related to the school as a positive support factor. It means the role of school in establishing self-efficacy, shaping and acquiring the behavior etc. Gathered data is analyzed via SPSS program and the detailed discussion is carried in the frame of the related literature.

Keywords: positive support factor, education, school, student teacher perception

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7 Investigation of Engineers` and Student Engineers` University Choices Effect over Professional Expectations

Authors: Alev Erenler, Yeliz Yazici

Abstract:

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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6 Hawkes Process-Based Reflexivity Analysis in the Cryptocurrency Market

Authors: Alev Atak

Abstract:

We study the endogeneity in the cryptocurrency market over the branching ratio of the Hawkes process and evaluate the movement of self-excitability in the financial markets. We consider a semi-parametric self-exciting point process regression model where the excitation function is assumed to be smooth and decreasing but otherwise unspecified, and the baseline intensity is assumed to be a linear function of the regressors. We apply the empirical analysis to the three largest crypto assets, i.e. Bitcoin - Ethereum - Ripple, and provide a comparison with other financial assets such as SP500, Gold, and the volatility index VIX observed from January 2015 to December 2020. The results depict variable and high levels of endogeneity in the basket of cryptocurrencies under investigation, underlining the evidence of a significant role of endogenous feedback mechanisms in the price formation process.

Keywords: hawkes process, cryptocurrency, endogeneity, reflexivity

Procedia PDF Downloads 50
5 Optimization the Freeze Drying Conditions of Olive Seeds

Authors: Alev Yüksel Aydar, Tuncay Yılmaz, Melisa Özçeli̇k, Tuba Aydın, Elif Karabaş

Abstract:

In this study, response surface methodology (RSM) was used to obtain the optimum conditions for the freeze-drying of Gemlik variety olive seeds of to achieve the desired quality characteristics. The Box Behnken Design (BBD) was applied with three-variable and three replications in the center point. The effects of the different drying parameters including initial temperature of olive seed, pressure and time for freezing on the DPPH activity, total phenolic contents, and oleuropein absorbance value of the samples were investigated. Temperature (50 – 82 °C), pressure (0.2-0.5 mbar), time (6-10 hours) were chosen as independent variables. The analysis revealed that, while the temperature of the product prior to lyophilization and the drying time had no statistically significant effect on DPPH activity (p>0.05), the pressure was more important than the other two variables , and the quadratic effect of pressure had a significant effect on DPPH activity (p<0.05). The R2 and Adj-R2 values of the DPPH activity model were calculated to be 0.8962 and 0.7045, respectively.

Keywords: olive seed, gemlik variety, DPPH, phenolics, optimization

Procedia PDF Downloads 58
4 Information Disclosure And Financial Sentiment Index Using a Machine Learning Approach

Authors: Alev Atak

Abstract:

In this paper, we aim to create a financial sentiment index by investigating the company’s voluntary information disclosures. We retrieve structured content from BIST 100 companies’ financial reports for the period 1998-2018 and extract relevant financial information for sentiment analysis through Natural Language Processing. We measure strategy-related disclosures and their cross-sectional variation and classify report content into generic sections using synonym lists divided into four main categories according to their liquidity risk profile, risk positions, intra-annual information, and exposure to risk. We use Word Error Rate and Cosin Similarity for comparing and measuring text similarity and derivation in sets of texts. In addition to performing text extraction, we will provide a range of text analysis options, such as the readability metrics, word counts using pre-determined lists (e.g., forward-looking, uncertainty, tone, etc.), and comparison with reference corpus (word, parts of speech and semantic level). Therefore, we create an adequate analytical tool and a financial dictionary to depict the importance of granular financial disclosure for investors to identify correctly the risk-taking behavior and hence make the aggregated effects traceable.

Keywords: financial sentiment, machine learning, information disclosure, risk

Procedia PDF Downloads 67
3 Demographic Characteristics and Factors Affecting Mortality in Pediatric Trauma Patients Who Are Admitted to Emergency Service

Authors: Latif Duran, Erdem Aydin, Ahmet Baydin, Ali Kemal Erenler, Iskender Aksoy

Abstract:

Aim: In this retrospective study, we aim to contribute to the literature by presenting the proposals for taking measures to reduce the mortality by examining the demographic characteristics of the pediatric age group patients presenting with trauma and the factors that may cause mortality Material and Method: This study has been performed by retrospectively investigating the data obtained from the patient files and the hospital automation registration system of the pediatric trauma patients who applied to the Adult Emergency Department of the Ondokuz Mayıs University Medical Faculty between January 1, 2016, and December 31, 2016. Results: 289 of 415 patients involved in our study, were males. The median age was 11.3 years. The most common trauma mechanism was falling from the high. A significant statistical difference was found on the association between trauma mechanisms and gender. An increase in the number of trauma cases was found especially in the summer months. The study showed that thoracic and abdominal trauma was relevant to the increased mortality. Computerized tomography was the most common diagnostic imaging modality. The presence of subarachnoid hemorrhage has increased the risk of mortality by 62.3 fold. Eight of the patients (1.9%) died. Scoring systems were statistically significant to predict mortality. Conclusion: Children are vulnerable to trauma because of their unique anatomical and physiological differences compared to adult patient groups. It will be more successful in the mortality rate and in the post-traumatic healing process by administering the patient triage fast and most appropriate trauma centers in the prehospital period, management of the critical patients with the scoring systems and management with standard treatment protocols

Keywords: emergency service, pediatric patients, scoring systems, trauma, age groups

Procedia PDF Downloads 161
2 Crack Growth Life Prediction of a Fighter Aircraft Wing Splice Joint Under Spectrum Loading Using Random Forest Regression and Artificial Neural Networks with Hyperparameter Optimization

Authors: Zafer Yüce, Paşa Yayla, Alev Taşkın

Abstract:

There are heaps of analytical methods to estimate the crack growth life of a component. Soft computing methods have an increasing trend in predicting fatigue life. Their ability to build complex relationships and capability to handle huge amounts of data are motivating researchers and industry professionals to employ them for challenging problems. This study focuses on soft computing methods, especially random forest regressors and artificial neural networks with hyperparameter optimization algorithms such as grid search and random grid search, to estimate the crack growth life of an aircraft wing splice joint under variable amplitude loading. TensorFlow and Scikit-learn libraries of Python are used to build the machine learning models for this study. The material considered in this work is 7050-T7451 aluminum, which is commonly preferred as a structural element in the aerospace industry, and regarding the crack type; corner crack is used. A finite element model is built for the joint to calculate fastener loads and stresses on the structure. Since finite element model results are validated with analytical calculations, findings of the finite element model are fed to AFGROW software to calculate analytical crack growth lives. Based on Fighter Aircraft Loading Standard for Fatigue (FALSTAFF), 90 unique fatigue loading spectra are developed for various load levels, and then, these spectrums are utilized as inputs to the artificial neural network and random forest regression models for predicting crack growth life. Finally, the crack growth life predictions of the machine learning models are compared with analytical calculations. According to the findings, a good correlation is observed between analytical and predicted crack growth lives.

Keywords: aircraft, fatigue, joint, life, optimization, prediction.

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1 Hydroxyapatite Based Porous Scaffold for Tooth Tissue Engineering

Authors: Pakize Neslihan Taslı, Alev Cumbul, Gul Merve Yalcın, Fikrettin Sahin

Abstract:

A key experimental trial in the regeneration of large oral and craniofacial defects is the neogenesis of osseous and ligamentous interfacial structures. Currently, oral regenerative medicine strategies are unpredictable for repair of tooth supporting tissues destroyed as a consequence of trauma, chronic infection or surgical resection. A different approach combining the gel-casting method with Hydroxy Apatite HA-based scaffold and different cell lineages as a hybrid system leads to successively mimic the early stage of tooth development, in vitro. HA is widely accepted as a bioactive material for guided bone and tooth regeneration. In this study, it was reported that, HA porous scaffold preparation, characterization and evaluation of structural and chemical properties. HA is the main factor that exists in tooth and it is in harmony with structural, biological, and mechanical characteristics. Here, this study shows mimicking immature tooth at the late bell stage design and construction of HA scaffolds for cell transplantation of human Adipose Stem Cells (hASCs), human Bone Marrow Stem Cells (hBMSCs) and Gingival Epitelial cells for the formation of human tooth dentin-pulp-enamel complexes in vitro. Scaffold characterization was demonstrated by SEM, FTIR and pore size and density measurements. The biological contraction of dental tissues against each other was demonstrated by mRNA gene expressions, histopatologic observations and protein release profile by ELISA tecnique. The tooth shaped constructs with a pore size ranging from 150 to 300 µm arranged by gathering right amounts of materials provide interconnected macro-porous structure. The newly formed tissue like structures that grow and integrate within the HA designed constructs forming tooth cementum like tissue, pulp and bone structures. These findings are important as they emphasize the potential biological effect of the hybrid scaffold system. In conclusion, this in vitro study clearly demonstrates that designed 3D scaffolds shaped as a immature tooth at the late bell stage were essential to form enamel-dentin-pulp interfaces with an appropriate cell and biodegradable material combination. The biomimetic architecture achieved here is providing a promising platform for dental tissue engineering.

Keywords: tooth regeneration, tissue engineering, adipose stem cells, hydroxyapatite tooth engineering, porous scaffold

Procedia PDF Downloads 204