With the growth of mobile phones, short message service (SMS) became an essential text communication service. However, the low cost and ease use of SMS led to an increase in SMS Spam. In this paper, the characteristics of SMS spam has studied and a set of features has introduced to get rid of SMS spam. In addition, the problem of SMS spam detection was addressed as a clustering analysis that requires a metaheuristic algorithm to find the clustering structures. Three differential evolution variants viz DE/rand/1, jDE/rand/1, jDE/best/1, are adopted for solving the SMS spam problem. Experimental results illustrate that the jDE/best/1 produces best results over other variants in terms of accuracy, false-positive rate and false-negative

HS Saeed, SS Abdul-Jabbar, SG Mohammed, EA Abed, HS Ibrahem, Solid State Technology, 2020

The current study aims to determine the extent of SOMO's interest in governance and whether this interest is sufficient to be reflected in enhancing its organizational reputation, and the field of research was in the oil marketing company SOMO. (109), (105) questionnaires were distributed, (94) forms and (11) forms were not retrieved, and the valid questionnaires had reached (91). The analytical and descriptive approach was used for the study, and the current research has found a positive impact of government on the reputation of the organization, and this research demonstrated the existence of the proposed relationship and the impact between governance and the reputation of the organization.

Abstract:

                The internal audit is considered the safety valve for senior management in all institutions. It aims to protect property, and raise the efficiency and effectiveness of the administrative performance, by following up on compliance with laws and instructions and the application of regulations in a way that increases the administrative performance of the department. The internal audit is possible to determine Weaknesses or imbalances in the administrative performance. To achieve this goal, an analytical descriptive methodology was adopted. The Baghdad Health Department / Al-Rosana was considered as society for this s

      This work addressed the assignment problem (AP) based on fuzzy costs, where the objective, in this study, is to minimize the cost. A triangular, or trapezoidal, fuzzy numbers were assigned for each fuzzy cost. In addition, the assignment models were applied on linguistic variables which were initially converted to quantitative fuzzy data by using the Yager’sorankingi method. The paper results have showed that the quantitative date have a considerable effect when considered in fuzzy-mathematic models.

Background: Poly propylene fibers with and without silane treatment have been used to reinforce heat cure denture base acrylic but, some mechanical properties like transverse strength, impact strength, tensile strength, hardness, wear resistance and wettability. Which are related to the clinical use of the prosthesis are not evaluated yet. The aim of the study is to identify the influence of incorporation of treated and untreated fibers on these properties Materials and methods: Eighty four heat cure acrylic specimens were constructed by conventional flasking technique. They were divided into six groups according to the tests and each group was subdivided into two subgroups control and experimental groups (seven samples for each subgroup

Digital Models of Elevations (DEMs) Using Surfer 16, which are interpolated to create three-dimensional controls for the entire terrain, are typically used in visualization of geospatial entities. The interpolation method used determines how accurate the resulting terrain model will be, hence it is necessary to compare the effectiveness of various approaches in this situation. Numerous generic interpolation techniques, using inverse distance to a power, triangulation as with linear interpolation, the nearest neighbor, and kriging, have been studied. These interpolation techniques produced DEMs. With the aid of SURFER software 16, the primary goal of this effort was to introduce the DEM using a spatial interpolation method and to pre

This research suggests a robust and systematic way for Arabic Sentiment Analysis using a vast dataset of 66,666 text reviews. One of the main advantages of this study is that the dataset was perfectly balanced (33,333 positive samples and 33,333 negative samples). In machine learning, this 50/50 split is important because it eliminates class bias and enables the predictive model to treat both sentiment classes equally. As shown in the values of the metrics — overall accuracy, weighted precision, weighted recall, and F1 score — there is great similarity among them, indicating a stable and reliable assessment of the model's real potential throughout the Arabic dataset. Based on data profile, the average word count per review is 42.3