The  transfer of  training  process occupies a great importance in achieving the ultimate goal of participating in the training programs , it  is sure that this does not take place without the support of the working environment for trainees,  and The research aims to personification role the work environment characteristics  of supporting the transfer of training.                                    

The research problem is the weakness transfer of training to the work en

This work aims to see the positive association rules and negative association rules in the Apriori algorithm by using cosine correlation analysis. The default and the modified Association Rule Mining algorithm are implemented against the mushroom database to find out the difference of the results. The experimental results showed that the modified Association Rule Mining algorithm could generate negative association rules. The addition of cosine correlation analysis returns a smaller amount of association rules than the amounts of the default Association Rule Mining algorithm. From the top ten association rules, it can be seen that there are different rules between the default and the modified Apriori algorithm. The difference of the obta

Various speech enhancement Algorithms (SEA) have been developed in the last few decades. Each algorithm has its advantages and disadvantages because the speech signal is affected by environmental situations. Distortion of speech results in the loss of important features that make this signal challenging to understand. SEA aims to improve the intelligibility and quality of speech that different types of noise have degraded. In most applications, quality improvement is highly desirable as it can reduce listener fatigue, especially when the listener is exposed to high noise levels for extended periods (e.g., manufacturing). SEA reduces or suppresses the background noise to some degree, sometimes called noise suppression alg

Sustainable development has recently gained significant attention in the field of water Quality (WQ), which is critical for a healthy lifestyle. Our work suggests an intelligent hybrid model for assessing water quality using a water portability dataset, which was used to evaluate the water quality. The dataset contains physical and chemical features such as pH, Organic Carbon, sulfate, etc. Based on the combination of a Decision Tree Algorithm (DTA) and fuzzy logic Approaches, the findings revealed that sulfate was the most important factor in the model, with an accuracy of 1.00, followed by pH with an accuracy of 0.9667, and solids and chloramines with an accuracy of 0.95. The other parameters achieved a similar accuracy of 0.9167, showing

The research aims to understand the psychological status of and the feeling of loneliness of the trainees (recently released detainees) participating in the training and rehabilitation courses held in the Technical College - Baghdad. The study was conducted on a specimen of (23) trainees. An open questionnaire was adopted which included one question that was ( What was your feeling psychologically and socially before taking part in the training course?) , also the feeling of  loneliness Scale , designed by ( Russel,Peplau, Cutrona /University of California Los Angeles ) was implemented after the courses .

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Background: Implant stability is a mandatory factor for dental implant (DI) osseointegration and long-term success. The aim of this study was to evaluate the effect of implant length, diameter, and recipient jaw on the pre- and post-functional loading stability. Materials and methods: This study included 17 healthy patients with an age range of 24-61 years. Twenty-two DI were inserted into healed extraction sockets to replace missing tooth/ teeth in premolar and molar regions in upper and lower jaws. Implant stability was measured for each implant and was recorded as implant stability quotient (ISQ) immediately (ISQ0), and at 8 (ISQ8) and 12 (ISQ12) weeks postoperatively, as well as post-functional loading (ISQPFL). The pattern of implant

Ad-Hoc Networks are a generation of networks that are truly wireless, and can be easily constructed without any operator. There are protocols for management of these networks, in which the effectiveness and the important elements in these networks are the Quality of Service (QoS). In this work the evaluation of QoS performance of MANETs is done by comparing the results of using AODV, DSR, OLSR and TORA routing protocols using the Op-Net Modeler, then conduct an extensive set of performance experiments for these protocols with a wide variety of settings. The results show that the best protocol depends on QoS using two types of applications (+ve and –ve QoS in the FIS evaluation). QoS of the protocol varies from one prot

In this paper, the memorization capability of a multilayer interpolative neural network is exploited to estimate a mobile position based on three angles of arrival. The neural network is trained with ideal angles-position patterns distributed uniformly throughout the region. This approach is compared with two other analytical methods, the average-position method which relies on finding the average position of the vertices of the uncertainty triangular region and the optimal position method which relies on finding the nearest ideal angles-position pattern to the measured angles. Simulation results based on estimations of the mobile position of particles moving along a nonlinear path show that the interpolative neural network approach outperf

Wellbore instability and sand production onset modeling are very affected by Sonic Shear Wave Time (SSW). In any field, SSW is not available for all wells due to the high cost of measuring. Many authors developed empirical correlations using information from selected worldwide fields for SSW prediction. Recently, researchers have used different Artificial Intelligence methods for estimating SSW. Three existing empirical correlations of Carroll, Freund, and Brocher are used to estimate SSW in this paper, while a fourth new empirical correlation is established. For comparing with the empirical correlation results, another study's Artificial Neural Network (ANN) was used. The same data t