The estimation of the parameters of linear regression is based on the usual Least Square method, as this method is based on the estimation of several basic assumptions. Therefore, the accuracy of estimating the parameters of the model depends on the validity of these hypotheses. The most successful technique was the robust estimation method which is minimizing maximum likelihood estimator (MM-estimator) that proved its efficiency in this purpose. However, the use of the model becomes unrealistic and one of these assumptions is the uniformity of the variance and the normal distribution of the error. These assumptions are not achievable in the case of studying a specific problem that may include complex data of more than one model. To

The Population growth and decay issues are one of the most pressing issues in many sectors of study. These issues can be found in physics, chemistry, social science, biology, and zoology, among other subjects.

We introduced the solution for these problems in this paper by using the SEJI (Sadiq- Emad- Jinan) integral transform, which has some mathematical properties that we use in our solutions. We also presented the SEJI transform for some functions, followed by the inverse of the SEJI integral transform for these functions. After that, we demonstrate how to use the SEJI transform to tackle population growth and decay problems by presenting two applications that demonstrate how to use this transform to obtain solutions.

Fin

Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.

The  lossy-FDNR  based  aclive  fil ter has an  important   property among  many  design  realizations. 'This includes  a significant reduction in component count particularly in the number  of OP-AMP which consumes   power.  However  the·  problem  of  this   type  is the  large component spreads  which affect the fdter performance.

In  this  paper   Genetic   Algorithm   is  applied   to  minimize   the component  spread   (capacitance  and  resistance  p,read). The minimization of these spreads allow the fil

Clustering algorithms have recently gained attention in the related literature since
they can help current intrusion detection systems in several aspects. This paper
proposes genetic algorithm (GA) based clustering, serving to distinguish patterns
incoming from network traffic packets into normal and attack. Two GA based
clustering models for solving intrusion detection problem are introduced. The first
model coined as handles numeric features of the network packet, whereas
the second one coined as concerns all features of the network packet.
Moreover, a new mutation operator directed for binary and symbolic features is
proposed. The basic concept of proposed mutation operator depends on the most
frequent value

Population density represents an important indicator for determining the growth of the size of urban areas. Population density has a direct impact on the quality of life, and its excessive rise may lead to the deterioration of basic service facilities. The problem of the research is that the increase in the total population densities of the residential neighborhood may reflect negatively on the nature of the services provided to the residents in these shops, and thus the failure to achieve sustainability in the residential locality. The research assumes that the increase in population densities negatively affects the achievement of sustainability in the residential neighborhood.

Honorifics are linguistic expressions which maintain social as well as religious respect to other people. They are linguistic techniques which express politeness to other interlocutors. Semantically speaking, honorifics are of two types: al-Laqab (title) and al-Kuniya (teknonyms) following a specific word order. They form part of the Arab recognitions and are mold into their social and communicative competence.

      The study focuses upon religious and regional honorifics which convey deference and respect. It assumes that religious and cultural recognitions play vital roles in formulating and embedding the sense of honorifics. It is hypothesized that Arab people express respect to religious personalitie