This study investigates asset returns within the Iraq Stock Exchange by employing both the Fama-MacBeth regression model and the Fama-French three-factor model. The research involves the estimation of cross-sectional regressions wherein model parameters are subject to temporal variation, and the independent variables function as proxies. The dataset comprises information from the first quarter of 2010 to the first quarter of 2024, encompassing 22 publicly listed companies across six industrial sectors. The study explores methodological advancements through the application of the Single Index Model (SIM) and Kernel Weighted Regression (KWR) in both time series and cross-sectional analyses. The SIM outperformed the K

The developments in forensic DNA technology have led us to perform this study in Iraqi population as reference database of autosomal Short Tandem Repeat (aSTR) DNA markers . A total of 120 unrelated individuals from Wasit province were analyzed at 15 STR DNA markers. Allele frequencies of DNA typing loci included in the AmpFlSTR1 IdentifilerTM PCR Amplification Kit panel from Applied Biosystems (D3S1358, vWA, FGA, D8S1179, D21S11, D18S51, D5S818, D13S317, D7S820, TH01, TPOX, CSF1PO, D19S433, D2S1338, D16S539) and several forensic efficiency statistical parameters were estimated from all the sample. the combined Matching Probability (CMP) using the 15 STR genetic loci in Iraqi population was estimated at 1 in 2.08286E-18 and the Combined

In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as computer vision, this study proposes a deep learning approach that utilizes a deep learning algorithm.

Ultrasound is a mechanical energy which can generate altering zones of compression and rarefaction along its path in the tissues. Ultrasound imaging can provide a real time screening for blood and multiple organs to aiding the diagnostic and treatment. However, ultrasound has the potential to deposit energy in the blood and tissues causing bio effects which is depending on ultrasound characteristics that including frequency and the amount of intensity. These bio effects include either a stable cavitation presented non thermal effects or inertial cavitation of harmful effect on the tissues. The non-thermal cavitation can add features in diagnostic imaging and treatment more than the inertial cavitation. Ultrasound Contrast agents are a micro

Fractal image compression depends on representing an image using affine transformations. The main concern for researches in the discipline of fractal image compression (FIC) algorithm is to decrease encoding time needed to compress image data. The basic technique is that each portion of the image is similar to other portions of the same image. In this process, there are many models that were developed. The presence of fractals was initially noticed and handled using Iterated Function System (IFS); that is used for encoding images. In this paper, a review of fractal image compression is discussed with its variants along with other techniques. A summarized review of contributions is achieved to determine the fulfillment of fractal ima

In recent years, the linguo-philosophical studies of metaphor have tended to define metaphor as an interaction of the object, that is the referent of conceptualization and some features that are associated with sensual manner realities, whose name is used when resolving the conceptual problem-nominative situation, namely the situation of the formation of a new concept and its verbalization. The objective of this term paper lies in the phenomenon of metaphors used in modern political discourse. In our understanding a metaphor is not only of a linguistic nature, but also political. This paper approaches the subject of conceptual metaphor and political argumentation through the prism of synergies of the political topic, affirmative or negative

The current research is concerned with a pragmatic study of attack and defense acts that are used by President Donald Trump in the American Presidential Debate in 2020. Attack is an attempt to harm or defeat someone, and it is a bold message that the speaker or attacker does not like or disagree with the other antagonist. On the contrary, defense means a person responds to an attack of his or her opponent. After an attack, the politician either negates or fact-checks claims made by his opponents or tries to set the record straight. By the end of the study, it is expected to answer the following questions: What are the most frequent strategies of attack and defense that utilized by President Trump to formulate his speech? What are the reason

In this research, we introduce and study the concept of fibrewise bitopological spaces. We generalize some fundamental results from fibrewise topology into fibrewise bitopological space. We also introduce the concepts of fibrewise closed bitopological spaces,(resp., open, locally sliceable and locally sectionable). We state and prove several propositions concerning with these concepts. On the other hand, we extend separation axioms of ordinary bitopology into fibrewise setting. The separation axioms we extend are called fibrewise pairwise T_0 spaces, fibrewise pairwise T_1 spaces, fibrewise pairwise R_0 spaces, fibrewise pairwise Hausdorff spaces, fibrewise pairwise functionally Hausdorff spaces, fibrewise pairwise regular spaces, fibrewise