The Statistical Analysis of the Earthquake Hazard for Turkey by Generalized Linear Models

WOS: 000418818000044In this paper, 4863 earthquake data of magnitude 4.0 and greater from 1900 to 2014 are statistically analyzed for the earthquake hazard in Turkey. The magnitude-frequency relationship in earthquake risk analysis is often performed by Gutenberg-Richter model. With the use of this model, information about earthquake potential of any region can be obtained by previous data and by estimating parameters such as return periods and possibilities of their occurrence. In this study, the relationship between earthquake numbers and magnitudes is modelled with the Generalized Linear Models as an alternative to Gutenberg-Richter model. Generalized Poisson Regression model and Generalized Negative Binomial Regression models as Generalized Linear Models are utilized in the study. Generalized Poisson Regression model is found as the best model when considering the dispersion parameters and model selection criteria. Exceeding probabilities and return periods are calculated for the selected years depending on yearly average occurrence number of earthquakes estimated with the Gutenberg-Richter and Generalized Poisson Regression models. According to the results, Generalized Poisson Regression model can be employed for seismic risk modelling in Turkey

Using of fractional factorial design (rk-p) in data envelopment analysis to selection of outputs and inputs

WOS: 000362715400017Data envelopment analysis (DEA) is a linear programming based technique for measuring the relative performance of organisational units where the presence of multiple inputs and outputs makes comparisons difficult. We used, Morita and Avkiran propose after it has been developed an input-output selection method that uses fractional factorial design, which is a statistical approach to find an optimal combination. Energy efficiency and greenhouse gas emissions are closely linked in the last two decades. We demonstrate the proposed method using data that increase energy efficiency and heating gas emissions in the European Union (EU) countries

Effects of body mass index and adenotonsillar size on snoring sound intensity levels at highest power

WOS: 000329959100011PubMed: 24268721Objectives: Snoring during sleep is a major clinical symptom of adenoid and tonsil hypertrophy in paediatric patients. The aim of this study was to determine the effects of adenoid and tonsil size on snoring sound frequency and intensity in children. Methods: Twenty-seven patients with adenotonsillar hypertrophy were included the study. Adenoid size was graded from 1+ to 4+ by rigid endoscopy. Patients were staged (I-III) according to body mass index (BMI) and tonsil and adenoid size. Snoring was recorded and analysed. The analysis focused on the highest power frequency (Fmax) and snoring sound intensity levels (SSILs). Results: SSIL and Fmax values for Stage III were significantly higher than those for Stages I and II. BMI for Stage III was higher than for Stages land II, and that for Stage II was higher than for Stage I. The BMI, SSIL, and Fmax values increased at each stage and tonsil/adenoid grade. Conclusions: SSIL seems to be related to Adenoid and Tonsils size and BMI. As stage increased, both Fmax and SSILs increased proportionally. Also, Fmax values shifted to higher frequencies. Physicians and parents should be aware of snoring, and be informed that a higher frequency and intensity may be related to obesity and/or adenotonsillar hypertrophy. Snoring analysis may be a useful tool for detecting cases of Adenoid and Tonsils hypertrophy and/or upper airway obstruction during sleep. (C) 2013 Elsevier Ireland Ltd. All rights reserved