Autorías: Imad Kadhim Khlaif, Talib Faisal Shnawa. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 1, 2022. Artículo de Revista en Dialnet.

In this research, optical communication coding systems are designed and constructed by utilizing Frequency Shift Code (FSC) technique. Calculations of the system quality represented by signal to noise ratio (S/N), Bit Error Rate (BER),and Power budget are done. In FSC system, the data of Nonreturn- to–zero (NRZ ) with bit rate at 190 kb/s was entered into FSC encoder circuit in transmitter unit. This data modulates the laser source HFCT-5205 with wavelength at 1310 nm by Intensity Modulation (IM) method, then this data is transferred through Single Mode (SM) optical fiber. The recovery of the NRZ is achieved using decoder circuit in receiver unit. The calculations of BER and S/N for FSC system a

This paper introduces some properties of separation axioms called α -feeble regular and α -feeble normal spaces (which are weaker than the usual axioms) by using elements of graph which are the essential parts of our α -topological spaces that we study them. Also, it presents some dependent concepts and studies their properties and some relationships between them.

Companies seek to enhance investor confidence by achieving the highest level of transparency in disclosure of financial and non-financial information (SASB standards) for Iraqi insurance companies listed on the financial market. The aim of the research is to identify the extent of the ability of financial and non-financial information to enhance transparency in reporting, which is reflected in Investor confidence. And the standards of sustainability development accounting issued by (SASB) through the electronic questionnaire that was distributed. Companies seek to achieve a set of goals, the most important of which is to enhance investor confidence by improving transparency in disclosure. Concerning the employment of financial an

Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.