The paper examines key aspects of the use of phraseologi-cal units related to colors in Russian culture and speech. It explores their role in shaping cultural identity, reflecting national characteristics and men-tality. The study analyzes the frequency and contexts of the use of color-related phraseological units in contemporary speech, as well as the influ-ence of media and literature on their popularization. The author highlights the significance of phraseological units in preserving cultural heritage and fostering a deeper understanding of language and culture.
Purpose: The main objective of this paper is, to determine the optimal no. of technicians’ men in a workshop crew of an Industrial System. Theoretical framework: The purpose of applying these tools is to explore their ability to reduce costs and improvements that can be obtained in the process of providing services to the end customer. Design/methodology/approach: The literature structure review was built from analyzing 12 of scientific papers and books, from web sciences and the Elsevier database. The papers were analyzed from descriptive, methodologic, and citation characteristics. Finding: By applying the equation model of the paper, the optimal no. of technician men in the crew of the workshop can be determined when
... Show MoreThis study deals with an important area in the field of linguistics, namely person deixis.
The study aims at: (1) Describing the notion of deixis, its importance, and its place in the field
of linguistics, (2) Presenting a detailed illustration of person deixis, and (3) Conducting an
analysis of person deixis in one of Synge‟s plays Riders to The Sea according to Levinson‟s
model. The most important aim of these three is the third one (the analysis). To achieve this
aim, the researcher depends on Levinson‟s (1983) descriptive approach. According to the
descriptive approach of deixis, the category of person deixis can be defined as the encoding of
the participant roles in the speech situation. This encoding is r
Abstract
Binary logistic regression model used in data classification and it is the strongest most flexible tool in study cases variable response binary when compared to linear regression. In this research, some classic methods were used to estimate parameters binary logistic regression model, included the maximum likelihood method, minimum chi-square method, weighted least squares, with bayes estimation , to choose the best method of estimation by default values to estimate parameters according two different models of general linear regression models ,and different s
... Show MoreThe theory of the psychologist’s Piaget states that man passes through four stages; other says that mankind passes through five. At each stage, human learn new characteristics, values, skills, and cultures from different environment that differ from one society to another. Therefore, the cultures of societies vary according to the diversity of the environments. These environments also vary depending on the circumstances surrounding them, e.g., in war environment, the individual learns what he does not learn from living in safe environment. As the environment changes, the communicative message also changes. This message is subject to person, groups, organizations and parties and directed to a diverse audience in its orientations and bel
... Show MoreWith 549,393 new cases recorded in 2018, bladder cancer is one of the most common malignancies worldwide. Urinary bladder cancer is the cause of about 3 percent of all new cancer diagnoses and 2.1 percent of all cancer deaths. This study aims to evaluate the efficiency of the N-myc downstream-regulated gene 1(NDRG1) as a biomarker for bladder cancer patients in the Iraqi population. One hundred individuals in the case-control study were enrolled and divided into two groups. The first group included 50 patients diagnosed with a bladder mass and investigated by undergoing cystoscopy examination for transurethral resection of bladder tumor (TURB). The second group included 50 healthy individuals who had normal bladder tissue. The resul
... Show MoreThis comprehensive review examines the efficacy and safety of tumor necrosis factor-alpha (TNF-α) inhibitors in treating various autoimmune diseases, and focuses on their application in Iraqi patients. Elevated TNF-α levels are linked to autoimmune disorders, leading to the development of anti-TNF-α therapies such as infliximab, etanercept, adalimumab, certolizumab pegol, and golimumab, which have gained FDA approval for conditions like psoriasis, in¬flammatory bowel disease, ankylosing spondylitis, and rheumatoid arthritis. While these therapies demonstrate sig¬nificant therapeutic benefits, including improved quality of life and disease management, they also carry risks, such as increased susceptibility to infections and pote
... Show MoreIn this research, the problem of ambiguity of the data for the project of establishing the typical reform complex in Basrah Governorate was eliminated. The blurry of the data represented by the time and cost of the activities was eliminated by using the Ranking function and converting them into normal numbers. Scheduling and managing the Project in the Critical Pathway (CPM) method to find the project completion time in normal conditions in the presence of non-traditional relationships between the activities and the existence of the lead and lag periods. The MS Project was used to find the critical path. The results showed that the project completion time (1309.5) dinars and the total cost has reached (33113017769) dinars and the
... Show MoreThe influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic
... Show MoreTwo 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.