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Forest fires caused by different environmental and human factors are responsible for the extensive destruction of natural and economic resources. Modern machine learning techniques have become popular in developing very accurate and precise susceptibility maps of various natural disasters to help reduce the occurrence of such calamities. The present study has applied and tested multiple algorithms to map the areas susceptible to wildfire in the Mediterranean Region of Turkey. Besides, the performance of XGBoost, CatBoost, Gradient Boost, AdaBoost, and LightGBM methods for wildfire susceptibility mapping is also examined. The results have revealed the higher testing accuracy of CatBoost (95.47%) algorithm, followed by LightGBM (94.70%), XGBoost (88.8%), AdaBoost (86.0%), and GBM (84.48%) algorithms. Resultant wildfire susceptibility maps provide proper inventories for forest engineers, planners, and local governments for future policies regarding disaster management in Turkey.

The purpose of this study is to evaluate students' perspectives according to various variables about use of smart boards and tablet computers in class rooms, academic performance tasks, distribution of course books, and changes made in exam grading regulation at high schools which came into effect as of academic year 2013-2014 under Faith Project. Formulation and application of measurement techniques and data collection were performed with high school students in Düzce province. A correlational comparative survey method was applied with quantitative research approach in this study. Statistical Package Program SPSS 20.0 was used in data analysis. Descriptive statistics analysis was performed to evaluate frequency values, percentages and arithmetic average values, while, One-Way Variance Analysis (ANOVA) and t-test were used for unrelated sampling. A sample of 606 students was selected from various high schools in Düzce during academic year 2015-2016. Students' viewpoints on the categories defined in measurement scale were determined generally as "I am indecisive" or "I agree".Resultantly, no significant differences were found in students' opinions according to gender and residential area variables. On the other hand, significant differences were detected in students' perspectives on use of smart boards, performance tasks and course books distribution according to the school type variable. Use of smart board was found to be considered more positively in Anatolian high schools, while, performance task and course book distribution were considered more positively in vocational schools. Moreover, it was also found that students' viewpoints on use of tablet computers and distribution of course books showed significant differences according to the variable of class size. Students' viewpoints on use of smart board and tablet computers, performance task, and distribution of course books were found to be viewed more positively in classes with strength of 21-25 students.