Began the process of re-engineering processes in the private sector as a way to assist organizations in re-thinking how to run the business in order to improve production processes and reduce operational cost, to get to compete on a global level. That was a major restructuring by further evolution in the use of technology to support innovative operations.

 Entered the technology in all areas of life and different regulations, This led to use as a change in all aspects The companies achieved success and progress today through the use of resources so as to ensure the wishes of the customers and their needs, and the requirements of the market primarily, Which is reflected on the basis of building strate

The Southern Cowpea Beetle Callosobruchus maculatus (F.) is one of the most widespread insect pests of stored legumes, causing a considerable loss during storage, decreasing the net weight of the crops, and resulting in reduced the quality of the crops. This study has been conducted to determine the lifetime, fertility and life table parameters of C. maculatus by using an alkaloids extract from Moringa oleifera leaves at different concentrations 1000, 2000, and 3000 ppm. The result was shown that the lowest survival rate was 49% at a concentration of 1000, 2000 ppm, as compared with the control which was 77%. The lowest reproductive rate (Ro) was 4.76 female/female/generation at the concentration of 1000 ppm, c

In this paper, we will study non parametric model when the response variable have missing data (non response) in observations it under missing mechanisms MCAR, then we suggest Kernel-Based Non-Parametric Single-Imputation instead of missing value and compare it with Nearest Neighbor Imputation by using the simulation about some difference models and with difference cases as the sample size, variance and rate of missing data.      

Currently, one of the topical areas of application of machine learning methods is the prediction of material characteristics. The aim of this work is to develop machine learning models for determining the rheological properties of polymers from experimental stress relaxation curves. The paper presents an overview of the main directions of metaheuristic approaches (local search, evolutionary algorithms) to solving combinatorial optimization problems. Metaheuristic algorithms for solving some important combinatorial optimization problems are described, with special emphasis on the construction of decision trees. A comparative analysis of algorithms for solving the regression problem in CatBoost Regressor has been carried out. The object of

Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca

Laboratory studies were conducted at the biological control unit, college of Agriculture, University of Baghdad to evaluate some biological aspects of the predator Chilocorus bipustulatus (Coleoptera: Coccinellidae), which is considered one of the most important predators on many insect pests, especially the scale insect, Parlatoria blanchardi, (Homoptera: Diaspididae) on date palms. The results showed that biological parameters of the predator were varied according to different degree of temperature. Egg incubation period was significantly different and reached to 7.5 and 5.44 day at 25 and 30°C respectively, Fertility was the same 100% at both temperature degrees. Larval growth periods were 17.41 and 16.12 day as well as the mortality

An experimental study was conducted to evaluate the effect of AL-coholic extract alkaloid of Cordia myxa leafs in fourth larval stage of lesser grain borer Rhyzopertha dominica. Using alkaline extracts of 8%, the study has been shown clear effect increased in mortality rate for fourth larval stage 93.3% and degressed to 66.6% at 4% concentrate to 13.3% with control treatment .Ahigher percentage of pupal mortality 16.6% at 4% concentrate has been observed, while no natural emergence carried out at concentrates of 4.6% comparing with control treatment of 86.66%, at the same time percentage of deformation has been increased to 16.66% at 4% of extracts and degressed to 6.66% at 6% while no deformation have been shown with control treatment .

Given the importance that the Iraqi banking system in general and Islamic banks in particular, there must be effective supervisory oversight of these banks, as supervisory oversight has an essential and effective role in the development and evaluation of the performance of banks, through the application of legal controls and rules. Banking aimed at making sure that its financial centers are safe, protecting depositors' funds, and achieving both monetary and economic stability. This research studied and evaluates the mechanisms and tools used by the Central Bank of Iraq in the supervision and supervision of these banks. Therefore, the research aimed to measure the type and direction of the relationship between the requirements of supervis

Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm