The current study aims at identifying the impact of using learning acceleration model on the achievement of mathematics for third intermediategrade students. Forachieving this, the researchers chose the School (Al-Kholood Secondary School for Girls) affiliated to the General Directorate of Babylon Education / Hashemite Education Department for the academic year (2021/2021), The sample reached to (70) female students from the third intermediate grade, with (35) female students for each of the two research groups. The two researchers prepared an achievement test consisting of (25) objective items of multiple choice type, The psychometric properties of the test were confirmed, and after the completion of the experiment, the achievement test was applied to the two research groups at the same time, and after processing the data statistically using the statistical bag, the study concluded thatthat the experimental group students who studied according to learning acceleration model outperformed the students of the control group who studied according to the traditional method. First // Research problem: We live today in an open era, the most prominent characteristic of which is access to knowledge in many forms that are faster, more interesting and attractive, Perhaps what we really need is knowledge that is transformed into projects and works that contribute to changing reality and making the future;Through the study path of the two researchers and their visit to a number of mathematics teachers for the third intermediate grade, and through a questionnaire distributed to them, the researchers concluded that (85%) of the male and female teachers are not satisfied with their students achievement in mathematics, and this was confirmed by the success rates for the past year, which reached to (34.69%), and some studies indicated a decrease in the achievement level as a study ( Al-Ayoubi, 2007) and (Mizban, 2018) study. The two researchers noted that the reason for the low level of achievement is due to most male and female teachers adopting traditional methods of teaching, using few teaching methods, giving ready information to students, not benefiting from the students’ mental capabilities and abilities, and not knowing many teachers of modern strategies and models in teaching mathematics, which emphasizes the positive role for the learner and taking into account the individual differences among students. The two researchers believe that there is an urgent need to keep up with developments in teaching methods and means by relying on modern models and strategies in teaching, as it is no longer acceptable to maintain traditional methods because they are no longer sufficient to meet the educational process requirements, especially that the world is witnessing qualitative and quantitative leaps in all areas of life, and maintain the traditional methods of teaching will inevitably increase the gap between us and developed world countries. In order to address this problem, the two researchers believe that using learning acceleration model in teaching mathematics to the third intermediate grade female students is that it addresses low achievement problem.
This paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO
learning algorithm is more effective and robust than genetic learning algorithm; thi
(3)
In the pandemic era of COVID19, software engineering and artificial intelligence tools played a major role in monitoring, managing, and predicting the spread of the virus. According to reports released by the World Health Organization, all attempts to prevent any form of infection are highly recommended among people. One side of avoiding infection is requiring people to wear face masks. The problem is that some people do not incline to wear a face mask, and guiding them manually by police is not easy especially in a large or public area to avoid this infection. The purpose of this paper is to construct a software tool called Face Mask Detection (FMD) to detect any face that does not wear a mask in a specific
... Show More
(9)
(3)
(14)
(10)
The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com
... Show More
(46)
(34)
Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes
... Show More
(38)
(29)
Abstract:
In this research we discussed the parameter estimation and variable selection in Tobit quantile regression model in present of multicollinearity problem. We used elastic net technique as an important technique for dealing with both multicollinearity and variable selection. Depending on the data we proposed Bayesian Tobit hierarchical model with four level prior distributions . We assumed both tuning parameter are random variable and estimated them with the other unknown parameter in the model .Simulation study was used for explain the efficiency of the proposed method and then we compared our approach with (Alhamzwi 2014 & standard QR) .The result illustrated that our approach
... Show More
(4)
(1)
Time series have gained great importance and have been applied in a manner in the economic, financial, health and social fields and used in the analysis through studying the changes and forecasting the future of the phenomenon. One of the most important models of the black box is the "ARMAX" model, which is a mixed model consisting of self-regression with moving averages with external inputs. It consists of several stages, namely determining the rank of the model and the process of estimating the parameters of the model and then the prediction process to know the amount of compensation granted to workers in the future in order to fulfil the future obligations of the Fund. , And using the regular least squares method and the frequ
... Show More