The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.

  In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.

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This paper presents a method to classify colored textural images of skin tissues. Since medical images havehighly heterogeneity, the development of reliable skin-cancer detection process is difficult, and a mono fractaldimension is not sufficient to classify images of this nature. A multifractal-based feature vectors are suggested hereas an alternative and more effective tool. At the same time multiple color channels are used to get more descriptivefeatures.Two multifractal based set of features are suggested here. The first set measures the local roughness property, whilethe second set measure the local contrast property.A combination of all the extracted features from the three colormodels gives a highest classification accuracy with 99.4

The current research sheds light on an important aspect of the great and rapid development in the field of science and technology and modern manufacturing methods as a result of the scientific revolution resulting from the accelerated cognitive development, which prompted designers in general and interior design in particular to exploit and invest in digital technology and the development of digital control in the process of designing the industrial product for the purpose of creativity and innovation through these digital programs Digital models achieve the requirements and desires of the interior designer according to the creative skill using modern software with high efficiency And extreme accuracy that is consistent with the requirem

This study aimed to measure digital stress among students at the University of Baghdad and to identify differences in digital stress based on gender (male–female), academic level (first–fourth year), and field of study (scientific–humanities). The study sample consisted of 200 students from the University of Baghdad. The "Digital Stress" scale, developed by the researcher specifically for this study, was applied, and the descriptive-analytical method was adopted. After administering the scale and analyzing the results using appropriate statistical methods, the findings indicated that university students experience a high level of digital stress, while no statistically significant differences were found in digital stress accord

            Human behavior is one of the topics that has captured the attention of researchers throughout the ages, and motivation is one of the manifestations of this behavior, which indicates the extent of interest in a particular topic and their unwillingness to rush towards a particular topic. The topic of motivation is one of the important topics of interest to the teacher and coach in the field of sports. The aim of this research was identifying the level of motivation for junior students, and the differences in the dimensions of motivation for junior students in squash lessons. We used the descriptive survey method, and the research sample was chosen randomly. Only male of the junior students in the College of Phys

The basic concept of diversity; where two or more inputs at the receiver are used to get uncorrelated signals. The aim of this paper is an attempt to compare some possible combinations of diversity reception and MLSE detection techniques. Various diversity combining techniques can be distinguished: Equal Gain Combining (EGC), Maximal Ratio Combining (MRC), Selection Combining and Selection Switching Combining (SS).The simulation results shows that the MRC give better performance than the other types of combining (about 1 dB compare with EGC and 2.5~3 dB compare with selection and selection switching combining).