In academia, the term ''inbreeding'' refers to a situation wherein PhDs are employed in the very same institution that trained them during their doctoral studies. Academic inbreeding has a negative perception on the account that it damages both scientific effectiveness and productivity. In this article, the effect of inbreeding on scientific effectiveness is investigated through a case study. This problem is addressed by utilizing Hirsch index as a reliable metric of an academic's scientific productivity. Utilizing the dataset, constructed with academic performance indicators of individuals from the Mechanical and Aeronautical Engineering Departments, of the Turkish Technical Universities, we demonstrate that academic inbreeding has a negative impact on apparent scientific effectiveness through a negative binomial model. This model appears to be the most suitable one for the dataset which is a type of count data. We report chi-square statistics and likelihood ratio test for the parameter alpha. According to the chi-square statistics the model is significant as a whole. The incidence rate ratio for the variable ''inbreeding'' is estimated to be 0.11 and this ratio tells that, holding all the other factors constant, for the inbred faculty, the h-index is about 89% lower when compared to the noninbred faculty. Furthermore, there exists negative and statistically significant correlation with an individual's productivity and the percentage of inbred faculty members at the very same department. Excessive practice of inbreeding adversely affects the overall productivity. Decision makers are urged to limit this practice to a minimum in order to foster a vibrant research environment. Furthermore, it is also found that scientific productivity of an individual decreases towards the end of his scientific career.

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corresponding FIR (finite impulse response) filter. Resulting Abstract-In this paper a fully automatic road detection two images are fused together using Karhounen-Louve algorithm is introduced. It comprises of pre-processing the image transform (KLT) which is based on principal component via a series of wavelet based filter banks and reducing the analysis (PCA). This process underlines the prominent yielding data into a single image which is of the same size as the features of the original image as well as de-noising it, since original optical grayscale satellite image, then utilizing a fuzzy the prominent features appear in both of the wavelet inference algorithm to carry out the road detection which can then be used as an input to a geographical information system for twan image whienoiseades not correla ew cartographic or for other purposes that are in need. We use a between high and low resolutlon scales as it lacks coherence. trous algorithm twice with two different wavelet bases in order to Principal component analysis is a powerful statistical tool filter and de-noise the satellite image. Each wavelet function commonly used for pattern recognition or data compression.resolves features at a different resolution level associated with the This approach takes contextual spatial information into frequency response of the corresponding FIR filter. Resulting account and exploits the complementary characteristics of the two images are fused together using Karhounen-Louve transform passive optical and/or SAR data. Furthermore it is also (KLT) which is based on principal component analysis (PCA). possible to use more than two images to begin with and fuse This process underlines the prominent features of the original them into a single one in this step without any loss of image as well as de-noising it, since the prominent features appear in both of the wavelet transformed images while noise geralit if don sop were justified tomshOw tter does not strongly correlate between scales. Next a fuzzy logic performance at the expense of computational time. On this inference algorithm which is based on statistical information and image obtained thorough wavelet filtering and KLT, road on geometry is used to extract the road pixels. detection is carried out using a fuzzy-logic inference algorithm. Linguistic variables used for this task are mean, Index Terms-road extraction, satellite imagery, fuzzy logic standard deviation which are computed within a 5x5 pixel size image window and also another linguistic variable based on I. INTRODUCTION geometry. The inference algorithm then classifies each pixel rVHTS paper deals with a fully automatic road detection as road or non-road with regard to the fuzzy inference rules 1 algorithm. Road detection algorithms can be classified yielding in a binary image. into two major groups; semi-automatic and automatic.Satellite images used in this paper are passive opticalThe first approach necessitates that the user specify some images which are converted to gray-scale representation prior ini...

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Combustion characteristics in a ramjet combustor with cavity flame-holder is studied numerically. Combustor follows a constant area isolator section and comprises of hydrogen fuel injected sonically upstream of the cavity. Secondary fuel injection is performed at the cavity back wall. A diverging section follows the cavity. These concepts are utilized in many designs. Simulations were performed for an entrance Mach number of 1.4. Stagnation temperature is 702 K, corresponding to a flight Mach number of 3.3. Detailed chemical kinetics is taken into account with a reaction mechanism comprising of 9 species and 25 reaction steps. Turbulence is modeled using Menter's shear stress transport model, which is suitable for high speed internal flows. It is observed that flame anchors at the leading edge of the cavity, and the flame is stabilized in the cavity mode rather than the jet-wake mode. Simulation captures all the essential features of the reacting flow field.

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