Background: The social information processing model is one of the most up-to-date cognitive models in the field of interpersonal interactions. This social-interaction-based model can be successfully used to investigate the reasons for emotional and behavioral problems and prevent them in children and adolescents. Objectives: The present study was conducted to investigate the efficacy of the ...

in the present study, five modeling approaches of ra, mlp, mnn, gff, and canfis were applied so as to estimate the radial overcut values in electrochemical drilling process. for these models, four input variables, namely electrolyte concentration, voltage, initial machining gap, and tool feed rate, were selected. the developed models were evaluated in terms of their prediction capability with m...

soil salinity is one of the main environmental problems affecting extensive area in the world. there are some problems with traditional data collection methods for soil studies. using the new methods and techniques such as remote sensing could overcome most of these problems. however using these data in areas with uncommon usages needed some researches to find the best calibration between the d...

1.3. Statistical analysis & Expert systems in toxicological screening: 1-9 1.3.1. CLOUDS-Overlap 1-10 1.3.2. SMART scaling 1-12 1.3.3. Commonly used terms in statistical pattern recognition 1-12 1.3.3.1. Cross-validation 1-12 1.3.3.2. Classification vs. regression 1-12 1.3.3.3. Supervised vs. unsupervised methods 1-13 1.3.4. Pattern recognition techniques 1-13 1.3.5. Principle component analysi...

An important problem in Natural Language Processing is identifying thecorrect sense of a word in a particular context. Thus far, statistical methods have been considered the best techniques in word sense disambiguation. Unfortunately, these methods produce high accuracy results only for a small number of preselected words. The reduced applicability of statistical methods is due basically to the...

Automatic news categorization systems have produced high accuracy, consistency, and flexibility using some natural language processing techniques. These knowledge-based categorization methods are more powerful and accurate than statistical techniques. However, the phrasal pre-processing and pattern matching methods that seem to work for categorization have the disadvantage of requiring a fair a...

Objectives To propose a method to study the effect of exposure settings on image quality and to estimate the potential for dose reduction when introducing dose-reducing measures. Methods Using the framework of visual grading regression (VGR), a log(mAs) term is included in the ordinal logistic regression equation, so that the effect of reducing the dose can be quantitatively related to the eff...

 This paper describes the use of image processing to measure lightness changes of fabric appearance. The lightness changes due to dyeing, washing and exposure to light treatments are studied. These properties are measured by using the changes in the intensity levels of the fabrics image and the L* obtained by a spectrophotometer. For each case, analysis of variance (ANOVA) is carded out and the...