Copulas are very efficient functions in the field of statistics and specially in statistical inference. They are fundamental tools in the study of dependence structures and deriving their properties. These reasons motivated us to examine and show  various types of copula functions and their families. Also, we separately explain each method that is used to construct each copula in detail with different examples. There are various outcomes that show the copulas and their densities with respect to the joint distribution functions. The aim is to make copulas available to new researchers and readers who are interested in the modern phenomenon of statistical inferences.

This study assesses the short-term and long-term interactions between firm performance, financial education and political instability in the case of Malaysia Small to Medium Enterprises (SMEs). The simultaneous insertion of financial education and political instability within the study is done intentionally to inspect the effect of these two elements in one equation for the Malaysian economy. Using the bound testing methodology for cointegration and error correction models, advanced within an autoregressive distributed lag (ARDL) framework, we examine whether a long-run equilibrium connection survives between firm performance and the above mentioned independent variables. Using this method, we uncover evidence of a positive long-term link b

The denoising of a natural image corrupted by Gaussian noise is a problem in signal or image processing.  Much work has been done in the field of wavelet thresholding but most of it was focused on statistical modeling of wavelet coefficients and the optimal choice of thresholds.  This paper describes a new method for the suppression of noise in image by fusing the stationary wavelet denoising technique with adaptive wiener filter. The wiener filter is applied to the reconstructed image for the approximation coefficients only, while the thresholding technique is applied to the details coefficients of the transform, then get the final denoised image is obtained by combining the two results. The proposed method was applied by usin

Mobile-based human emotion recognition is very challenging subject, most of the approaches suggested and built in this field utilized various contexts that can be derived from the external sensors and the smartphone, but these approaches suffer from different obstacles and challenges. The proposed system integrated human speech signal and heart rate, in one system, to leverage the accuracy of the human emotion recognition. The proposed system is designed to recognize four human emotions; angry, happy, sad and normal. In this system, the smartphone is used to   record user speech and send it to a server. The smartwatch, fixed on user wrist, is used to measure user heart rate while the user is speaking and send it, via Bluetooth,

Several symptoms of hypothyroidism characterized by low

FT3 and FT4 were classified into hypothyroidism and Hoffman's syndrome .It was accepted that free radical generation and lipid peroxidation are associated with  many diseases. Creatine kinase in serum is affected by thyroid hormones. This study was undertaken to investigate the relationship between  malondialdehyde  as a general lipid peroxidation marker and CK activity in patients with primary hypothyroidism and Hoffman's syndrome which indicatees hypothyroidism with undetectable FT3 and FT4 in serum with elevated values of  TSH.

The study revealed that MDA is within the normal range, while CK activities in sera of Hoffman's syndrome were increas

There are large numbers of weakness in the generated keys of security algorithms. This paper includes a new algorithm to generate key of 5120 bits for a new proposed cryptography algorithm for 10 rounds that combine neural networks and chaos theory (1D logistic map). Two methods of neural networks (NN) are employed as Adaline and Hopfield and the results are combined through several sequential operation. Carefully integrating high quality random number generators from neural networks and chaos theory to obtain suitable key for randomness and complexity.

      Faintly continuous (FC) functions, entitled faintly S-continuous and faintly δS-continuous functions have been introduced and investigated via a -open and -open sets. Several characterizations and properties of faintly S-continuous and faintly -Continuous functions were obtained. In addition, relationships between faintly s- Continuous and faintly S-continuous function and other forms of FC function were investigated. Also, it is shown that every faintly  S-continuous is weakly S-continuous. The Convers is shown to be satisfied only if the co-domain of the function is almost regular.

The aim of the current study is to identify the level of goal conflict with twelfth-grade students in South Sharqiah/ Sultanate of Oman according to gender and specialization. The study used the descriptive method. A scale of (28) items was developed and divided into six dimensions: time pressure, goal achievement, limit of power, limit of budget, incompatible strategies, and unclear task. To validate the scale, it was piloted (40) students. The scale was administered to a sample of (402) students (209) males in the Governorate of South Sharqiah. The results showed that the conflict level was high in “unclear task”, and an average conflict level in “limit of power”. Other dimensions (goal achievement, time pressure, limit of powe

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.