In this paper an Artificial Neural Network (ANN) model, for predicting the performance of a sophomore student enrolled in engineering majors in the Faculty of Engineering and Information Technology in Al-Azhar University of Gaza was developed and tested. A number of factors that may possibly influence the performance of a student were outlined. Such factors as high school score, score of subject such as Math I, Math II, Electrical Circuit I, and Electronics I taken during the student freshman year, number of credits passed, student cumulative grade point average of freshman year, types of high school attended and gender, among others, were then used as input variables for the ANN model. A model based on the Multilayer Perceptron Topology was developed and trained using data spanning five generations of graduates from the Engineering Department of the Al-Azhar University, Gaza. Test data evaluation shows that the ANN model is able to correctly predict the performance of more than 80% of prospective students.

/pdf/predicting-student-performance-using-artificial-neural-4hszli03n8.pdf

Predicting Student Performance Using Artificial Neural Network: in the Faculty of Engineering and Information Technology

Diabetes is one of the most common diseases worldwide where a cure is not found for it yet. Annually it cost a lot of money to care for people with diabetes. Thus the most important issue is the prediction to be very accurate and to use a reliable method for that. One of these methods is using artificial intelligence systems and in particular is the use of Artificial Neural Networks (ANN). So in this paper, we used artificial neural networks to predict whether a person is diabetic or not. The criterion was to minimize the error function in neural network training using a neural network model. After training the ANN model, the average error function of the neural network was equal to 0.01 and the accuracy of the prediction of whether a person is diabetics or not was 87.3%

/pdf/diabetes-prediction-using-artificial-neural-network-2rcpn2ri14.pdf

Diabetes Prediction Using Artificial Neural Network

In this paper, we developed an Artificial Neural Network (ANN) for detect the absence or presence of lung cancer in human body. Symptoms were used to diagnose the lung cancer, these symptoms such as Yellow fingers, Anxiety, Chronic Disease, Fatigue, Allergy, Wheezing, Coughing, Shortness of Breath, Swallowing Difficulty and Chest pain. They were used and other information about the person as input variables for our ANN. Our ANN established, trained, and validated using data set, which its title is “survey lung cancer”. Model evaluation showed that the ANN model is able to detect the absence or presence of lung cancer with 96.67 % accuracy.

https://philpapers.org/archive/NASLCD-5.pdf

Lung Cancer Detection Using Artificial Neural Network

Infants and children suffer from a lot of mouth problems with a wide range of severity, and usually physicians have difficulties dealing with these problems due to their similarities. In this paper an expert system was designed to help users to correctly diagnose mouth problems in infants and children(teething, gingivitis, impetigo, inflamed papillae, mucocele, oral thrush, allergic reaction, chickenpox, hand-foot-mouth disease, strep throat, cold sores, canker sores, gingivostomatitis) with some information about the disease and how to treat it. SL5 Object expert system language was used to design and implement this expert system. Keywords— Artificial Intelligence; Expert Systems; SL5 Object; Mouth problems; infants

An Expert System for Mouth Problems in Infants and Children

The truth of every human being is the end his life with death, and this leads to leaving assets and funds for those after him and can lead to hate between the heirs, it has made a point of Islamic law on all aspects of life, including the subject of the inheritance of the deceased. The main problem is how to get the knowledge of the basics of inheritance. This paper reviews work done in the use of expert system software to calculate inheritance in Islam. A proposed expert system was designed and developed using CLIPS language to calculate the inheritance in Islam.

https://philpapers.org/archive/AKKPES.pdf

Proposed Expert System for Calculating Inheritance in Islam

In this paper we will present the design and development of a proposed expert system that aims to improve the method of selecting the best suitable faculty/major for student planning to be enrolled in Al-Azhar University. The basic idea of our approach is designing a model for testing and measuring the student capabilities like intelligence, understanding, comprehension, mathematical concepts and others, and applying the module results to a rule-based expert system to determine the compatibility of those capabilities with the available faculties/majors in Al-Azhar University. The result is shown as a list of suggested faculties/majors that are most suitable with the student capabilities and abilities.

/pdf/a-proposed-expert-system-for-guiding-freshman-students-in-2uj7ab59b3.pdf

A proposed expert system for guiding freshman students in selecting a major in al-azhar university, gaza

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A proposed expert system for guiding freshman students in selecting a major in al-azhar university, gaza