Numerical Analysis of a Tunnel Support Design in Conjunction with Empirical Methods

In this paper, preliminary support design of a tunnel was analyzed by numerical and empirical approaches. The case study for this analysis is a tunnel to be constructed on the Bilecik-Istanbul roadway in Turkey. The rock mass properties of the tunnel route and design support recommendations were obtained by using an empirical approach. The rock mass properties obtained from the empirical method were used as input parameters for the numerical analysis. The empirical and numerical results, in terms of support design, were evaluated. It was seen that the numerical analysis results supported by empirical values were logical and reliable.     

A multinomial logit analysis of risk factors influencing road traffic injury severities in the Erzurum and Kars Provinces of Turkey

A retrospective cross-sectional study is conducted analysing 11,771 traffic accidents reported by the police between January 2008 and December 2013 which are classified into three injury severity categories: fatal, injury, and no injury. Based on this classification, a multinomial logit analysis is performed to determine the risk factors affecting the severity of traffic injuries. The estimation results reveal that the following factors increase the probability of fatal injuries: drivers over the age of 65; primary-educated drivers; single-vehicle accidents; accidents occurring on state routes, highways or provincial roads; and the presence of pedestrian crosswalks. The results also indicate that accidents involving cars or private vehicles or those occurring during the evening peak, under clear weather conditions, on local city streets or in the presence of traffic lights decrease the probability of fatal injuries. This study comprises the most comprehensive database ever created for a Turkish sample. This study is also the first attempt to use an unordered response model to determine risk factors influencing the severity of traffic injuries in Turkey.     

Classification of physiological disorders in apples fruit using a hybrid model based on convolutional neural network and machine learning methods

Neural Computing and Applications - Physiological disorders in apples are due to post-harvest conditions. For this reason, automatic identification of physiological disorders is important in...     

Single-step ahead prediction based on the principle of concatenation using grey predictors

In literature a number of different methods are proposed to improve the prediction accuracy of grey models. However, most of them are computationally expensive, and this may prohibit their extensive use. This paper describes a much simpler scheme, based on the principle of concatenation, in which unit step predictions are concatenated by replacing the missing outputs by their previously predicted values. Despite its extreme simplicity, it is shown that the predicted values thus derived results in a better performance than the methods proposed in the literature. Simulation studies show the effectiveness of the proposed algorithm when applied to nonlinear function predictions.     

Faster RRT-based Nonholonomic Path Planning in 2D Building Environments Using Skeleton-constrained Path Biasing

This paper presents a faster RRT-based path planning approach for regular 2-dimensional (2D) building environments. To minimize the planning time, we adopt the idea of biasing the RRT tree-growth in more focused ways. We propose to calculate the skeleton of the 2D environment first, then connect a geometrical path on the skeleton, and grow the RRT tree via the seeds generated locally along this path. We conduct batched simulations to find the universal parameters in manipulating the seeds generation. We show that the proposed skeleton-biased locally-seeded RRT (skilled-RRT) is faster than the other baseline planners (RRT, RRT*, A*-RRT, Theta*-RRT, and MARRT) through experimental tests using different vehicles in different 2D building environments. Given mild assumptions of the 2D environments, we prove that the proposed approach is probabilistically complete. We also present an application of the skilled-RRT for unmanned ground vehicle. Compared to the other baseline algorithms (Theta*-RRT and MARRT), we show the applicability and fast planning of the skilled-RRT in real environment.     

Equivalent circuit for capacitive micromachined ultrasonic transducers to predict anti-resonances

Equivalent circuit models have been long used to evaluate the dynamics of the capacitive micromachined ultrasonic transducer (CMUT). An important parameter in the characterization of a CMUT is the anti-resonance frequency, which limits the immersion bandwidth. However, there is no equivalent circuit model that can accurately determine the anti-resonance frequency of a membrane. In this work, we present an improved lumped element parametric model for immersed CMUT. We demonstrate that the proposed equivalent circuit model accurately predicts anti-resonance and higher order mode frequencies, in addition to that of the fundamental mode. The proposed circuit model is in good agreement with device characteristics calculated using the finite element method and experimentally measured data.

     

Capitalizing on the Koran to fuel online violent radicalization: A taxonomy of Koranic references in ISIS’s Dabiq

The current study set out to investigate to what extent ISIS is bolstering its jihadist ideology on a ‘cut-and-paste’ or ‘cherry-picked’ version of Islam in their renowned online propaganda magazine Dabiq. The main objective was to examine in a systematic and quantitative way to what extent ISIS utilizes the Koran in an atomistic, truncated and tailored manner to bolster its religious legitimacy. A total of 15 issues of Dabiq and 700 Koranic references were scrutinized. By means of a quantitative analysis we developed an innovative taxonomy of Koranic chapters and verses (i.e. surahs and ayat, respectively) on the basis of their appearance in Dabiq. Our large-scale data analysis provide consistent empirical evidence for severe decontextualization practices of the Koran in three ways: (1) a thin, Medinan-dominated religious layer, (2) ayah mutilation, and (3) clustered versus exclusive mentions. Limitations and implications for future research, policy makers and CVE initiatives are discussed.