218 found
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  1. Potato Classification Using Deep Learning.Abeer A. Elsharif, Ibtesam M. Dheir, Alaa Soliman Abu Mettleq & Samy S. Abu-Naser - 2020 - International Journal of Academic Pedagogical Research (IJAPR) 3 (12):1-8.
    Abstract: Potatoes are edible tubers, available worldwide and all year long. They are relatively cheap to grow, rich in nutrients, and they can make a delicious treat. The humble potato has fallen in popularity in recent years, due to the interest in low-carb foods. However, the fiber, vitamins, minerals, and phytochemicals it provides can help ward off disease and benefit human health. They are an important staple food in many countries around the world. There are an estimated 200 varieties of (...)
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  2. Knowledge Based System for Diagnosing Custard Apple Diseases and Treatment.Mustafa M. K. Al-Ghoul, Mohammed H. S. Abueleiwa, Fadi E. S. Harara, Samir Okasha & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (5):41-45.
    There is no doubt that custard apple diseases are among the important reasons that destroy the Custard Apple plant and its agricultural crops. This leads to obvious damage to these plants and they become inedible. Discovering these diseases is a good step to provide the appropriate and correct treatment. Determining the treatment with high accuracy depends on the method used to correctly diagnose the disease, expert systems can greatly help in avoiding damage to these plants. The expert system correctly diagnoses (...)
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  3. The Relationship between Correcting Deviations in Measuring Performance and Achieving the Objectives of Control - The Islamic University as a Model.Abed Alfetah M. AlFerjany, Ashraf A. M. Salama, Youssef M. Abu Amuna, Mazen J. Al Shobaki & Samy S. Abu-Naser - 2018 - International Journal of Engineering and Information Systems (IJEAIS) 2 (1):74-89.
    The study aimed to identify the relationship between correcting the deviations in the measurement of performance and achieving the objectives of control and the performance of the job at the Islamic University in the Gaza Strip. To achieve the objectives of the research, the researchers used the descriptive analytical approach to collect information. The questionnaire consisted of (20) statements distributed to three categories of employees of the Islamic University (senior management, faculty members, their assistants and members of the administrative board). (...)
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  4. The Role of Administrative Procedures and Regulations in Enhancing the Performance of The Educational Institutions - The Islamic University in Gaza is A Model.Ashraf A. M. Salama, Youssef M. Abu Amuna, Mazen J. Al Shobaki & Samy S. Abu-Naser - 2018 - International Journal of Academic Multidisciplinary Research (IJAMR) 2 (2):14-27.
    The study aimed to identify the role of administrative procedures and systems in enhancing the performance of the educational institutions in the Islamic University in Gaza. To achieve the research objectives, the researchers used the analytical descriptive approach to collect information. The researchers used the questionnaire distributed to three categories of employees at the Islamic University (senior management, faculty members, their assistants and members of the administrative board). A random sample of 314 employees was selected and 276 questionnaires were retrieved (...)
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  5. Energy Efficiency Prediction using Artificial Neural Network.Ahmed J. Khalil, Alaa M. Barhoom, Bassem S. Abu-Nasser, Musleh M. Musleh & Samy S. Abu-Naser - 2019 - International Journal of Academic Pedagogical Research (IJAPR) 3 (9):1-7.
    Buildings energy consumption is growing gradually and put away around 40% of total energy use. Predicting heating and cooling loads of a building in the initial phase of the design to find out optimal solutions amongst different designs is very important, as ell as in the operating phase after the building has been finished for efficient energy. In this study, an artificial neural network model was designed and developed for predicting heating and cooling loads of a building based on a (...)
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  6. Fraudulent Financial Transactions Detection Using Machine Learning.Mosa M. M. Megdad, Samy S. Abu-Naser & Bassem S. Abu-Nasser - 2022 - International Journal of Academic Information Systems Research (IJAISR) 6 (3):30-39.
    It is crucial to actively detect the risks of transactions in a financial company to improve customer experience and minimize financial loss. In this study, we compare different machine learning algorithms to effectively and efficiently predict the legitimacy of financial transactions. The algorithms used in this study were: MLP Repressor, Random Forest Classifier, Complement NB, MLP Classifier, Gaussian NB, Bernoulli NB, LGBM Classifier, Ada Boost Classifier, K Neighbors Classifier, Logistic Regression, Bagging Classifier, Decision Tree Classifier and Deep Learning. The dataset (...)
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  7. Classification of Real and Fake Human Faces Using Deep Learning.Fatima Maher Salman & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (3):1-14.
    Artificial intelligence (AI), deep learning, machine learning and neural networks represent extremely exciting and powerful machine learning-based techniques used to solve many real-world problems. Artificial intelligence is the branch of computer sciences that emphasizes the development of intelligent machines, thinking and working like humans. For example, recognition, problem-solving, learning, visual perception, decision-making and planning. Deep learning is a subset of machine learning in artificial intelligence that has networks capable of learning unsupervised from data that is unstructured or unlabeled. Deep learning (...)
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  8. Classification of Alzheimer's Disease Using Convolutional Neural Networks.Lamis F. Samhan, Amjad H. Alfarra & Samy S. Abu-Naser - 2022 - International Journal of Academic Information Systems Research (IJAISR) 6 (3):18-23.
    Brain-related diseases are among the most difficult diseases due to their sensitivity, the difficulty of performing operations, and their high costs. In contrast, the operation is not necessary to succeed, as the results of the operation may be unsuccessful. One of the most common diseases that affect the brain is Alzheimer’s disease, which affects adults, a disease that leads to memory loss and forgetting information in varying degrees. According to the condition of each patient. For these reasons, it is important (...)
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  9. Gender Prediction from Retinal Fundus Using Deep Learning.Ashraf M. Taha, Qasem M. M. Zarandah, Bassem S. Abu-Nasser, Zakaria K. D. AlKayyali & Samy S. Abu-Naser - 2022 - International Journal of Academic Information Systems Research (IJAISR) 6 (5):57-63.
    Deep learning may transform health care, but model development has largely been dependent on availability of advanced technical expertise. The aim of this study is to develop a deep learning model to predict the gender from retinal fundus images. The proposed model was based on the Xception pre-trained model. The proposed model was trained on 20,000 retinal fundus images from Kaggle depository. The dataset was preprocessed them split into three datasets (training, validation, Testing). After training and cross-validating the proposed model, (...)
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  10. Classification of Anomalies in Gastrointestinal Tract Using Deep Learning.Ibtesam M. Dheir & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (3):15-28.
    Automatic detection of diseases and anatomical landmarks in medical images by the use of computers is important and considered a challenging process that could help medical diagnosis and reduce the cost and time of investigational procedures and refine health care systems all over the world. Recently, gastrointestinal (GI) tract disease diagnosis through endoscopic image classification is an active research area in the biomedical field. Several GI tract disease classification methods based on image processing and machine learning techniques have been proposed (...)
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  11. The Relationship between Performance Standards and Achieving the Objectives of Supervision at the Islamic University in Gaza.Ashraf A. M. Salama, Mazen Al Shobaki, Samy S. Abu-Naser, Abed Alfetah M. AlFerjany & Youssef M. Abu Amuna - 2018 - International Journal of Engineering and Information Systems (IJEAIS) 1 (10):89-101.
    The aim of the research is to identify the relationship between the performance criteria and the achievement of the objectives of supervision which is represented in the performance of the job at the Islamic University in Gaza Strip. To achieve the objectives of the research, the researchers used the descriptive analytical approach to collect information. The questionnaire consisted of (22) paragraphs distributed to three categories of employees of the Islamic University (senior management, faculty members, their assistants and members of the (...)
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  12. Expert System for Castor Diseases and Diagnosis.Fatima M. Salman & Samy S. Abu-Naser - 2019 - International Journal of Engineering and Information Systems (IJEAIS) 3 (3):1-10.
    Background: The castor bean is a large grassy or semi-wooden shrub or small tree. Any part of the castor plant parts can suffering from a disease that weakens the ability to grow and eliminates its production. Therefore, in this paper will identify the pests and diseases present in castor culture and detect the symptoms in each disease. Also images is showing the symptom form in this disease. Objectives: The main objective of this expert system is to obtain appropriate diagnosis of (...)
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  13. A Proposed Knowledge Based System for Desktop PC Troubleshooting.Ahmed Wahib Dahouk & Samy S. Abu-Naser - 2018 - International Journal of Academic Pedagogical Research (IJAPR) 2 (6):1-8.
    Abstract: Background: In spite of the fact that computers continue to improve in speed and functions operation, they remain complex to use. Problems frequently happen, and it is hard to resolve or find solutions for them. This paper outlines the significance and feasibility of building a desktop PC problems diagnosis system. The system gathers problem symptoms from users’ desktops, rather than the user describes his/her problems to primary search engines. It automatically searches global databases of problem symptoms and solutions, and (...)
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  14. Predicting Tumor Category Using Artificial Neural Networks.Ibrahim M. Nasser & Samy S. Abu-Naser - 2019 - International Journal of Academic Health and Medical Research (IJAHMR) 3 (2):1-7.
    In this paper an Artificial Neural Network (ANN) model, for predicting the category of a tumor was developed and tested. Taking patients’ tests, a number of information gained that influence the classification of the tumor. Such information as age, sex, histologic-type, degree-of-diffe, status of bone, bone-marrow, lung, pleura, peritoneum, liver, brain, skin, neck, supraclavicular, axillar, mediastinum, and abdominal. They were used as input variables for the ANN model. A model based on the Multilayer Perceptron Topology was established and trained using (...)
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  15. A Proposed Expert System for Strawberry Diseases Diagnosis.Raed Z. Sababa, Mohammed F. El-Habibi, Mosa M. M. Megdad, Mohammed J. A. AlQatrawi, Mohanad H. Al-Qadi & Samy S. Abu-Naser - 2022 - International Journal of Engineering and Information Systems (IJEAIS) 6 (5):52-66.
    Background: There is no doubt that strawberry diseases are one of the most important reasons that led to the destruction of strawberry plants and their crops. This leads to obvious damage to these plants and they become inedible. Discovering these diseases after a good step for proper and correct treatment. Determining the treatment with high accuracy depends on the method used in the diagnosis. Correctly, expert systems can greatly help in avoiding damage to these plants. The expert system correctly diagnoses (...)
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  16. A Proposed Expert System for Broccoli Diseases Diagnosis.Ola I. A. LAfi, Hadeel A. El-Hamarnah, Nora J. H. Al-Saloul, Hanan I. A. Radwan & Samy S. Abu-Naser - 2022 - International Journal of Engineering and Information Systems (IJEAIS) 6 (5):43-51.
    Background: Broccoli is an edible green plant in the cabbage family (family Brassicaceae, genus Brassica) whose large flowering head, stalk and small associated leaves are eaten as a vegetable. A leaf of Broccoli might be affected of Several Diseases descriped in this paper . When symptoms is encountered, it requires some kind of medical care. If appropriate Survival of Broccoli Diseases is not taken quickly, it can lead to Broccoli to die . Objectives: The main goal of this expert system (...)
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  17. Diabetes Prediction Using Artificial Neural Network.Nesreen Samer El_Jerjawi & Samy S. Abu-Naser - 2018 - International Journal of Advanced Science and Technology 121:54-64.
    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 (...)
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  18. An Expert System for Depression Diagnosis.Izzeddin A. Alshawwa, Mohammed Elkahlout, Hosni Qasim El-Mashharawi & Samy S. Abu-Naser - 2019 - International Journal of Academic Health and Medical Research (IJAHMR) 3 (4):20-27.
    Background: Depression (major depressive disorder) is a common and serious medical illness that negatively affects how you feel, the way you think and how you act. Fortunately, it is also treatable. Depression causes feelings of sadness and/or a loss of interest in activities once enjoyed. It can lead to a variety of emotional and physical problems and can decrease a person’s ability to function at work and at home. Depression affects an estimated one in 15 adults (6.7%) in any given (...)
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  19. Artificial Neural Network for Predicting Car Performance Using JNN.Awni Ahmed Al-Mobayed, Youssef Mahmoud Al-Madhoun, Mohammed Nasser Al-Shuwaikh & Samy S. Abu-Naser - 2020 - International Journal of Engineering and Information Systems (IJEAIS) 4 (9):139-145.
    In this paper an Artificial Neural Network (ANN) model was used to help cars dealers recognize the many characteristics of cars, including manufacturers, their location and classification of cars according to several categories including: Buying, Maint, Doors, Persons, Lug_boot, Safety, and Overall. ANN was used in forecasting car acceptability. The results showed that ANN model was able to predict the car acceptability with 99.12 %. The factor of Safety has the most influence on car acceptability evaluation. Comparative study method is (...)
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  20. ASP.NET-Tutor: Intelligent Tutoring System for leaning ASP.NET.Msbah J. Mosa, Islam Albatish & Samy S. Abu-Naser - 2018 - International Journal of Academic Pedagogical Research (IJAPR) 2 (2):1-8.
    ASP.net is one of the most widely used languages in web developing of its many advantages, so there are many lessons that explain its basics, so it should be an intelligent tutoring system that offers lessons and exercises for this language.why tutoring system? Simply because it is one-one teacher, adapts with all the individual differences of students, begins gradually with students from easier to harder level, save time for teacher and student, the student is not ashamed to make mistakes, and (...)
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  21. Prediction of Heart Disease Using a Collection of Machine and Deep Learning Algorithms.Ali M. A. Barhoom, Abdelbaset Almasri, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2022 - International Journal of Engineering and Information Systems (IJEAIS) 6 (4):1-13.
    Abstract: Heart diseases are increasing daily at a rapid rate and it is alarming and vital to predict heart diseases early. The diagnosis of heart diseases is a challenging task i.e. it must be done accurately and proficiently. The aim of this study is to determine which patient is more likely to have heart disease based on a number of medical features. We organized a heart disease prediction model to identify whether the person is likely to be diagnosed with a (...)
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  22. Expert System for Chest Pain in Infants and Children.Randa A. Khella & Samy S. Abu-Naser - 2018 - International Journal of Engineering and Information Systems (IJEAIS) 1 (4):138-148.
    Chest pain is the pain felt in the chest by infants, children and adolescents. In most cases the pain is not associated with the heart. It is mainly recognized by the observance or report of pain by the infant, child or adolescent by reports of distress by parents or care givers. Chest pain is not unusual in children. Lots of children are seen in ambulatory clinics, emergency rooms and hospitals and cardiology clinics. Usually there is a benign cause for the (...)
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  23. An Expert System for Arthritis Diseases Diagnosis Using SL5 Object.Hosni Qasim El-Mashharawi, Izzeddin A. Alshawwa, Mohammed Elkahlout & Samy S. Abu-Naser - 2019 - International Journal of Academic Health and Medical Research (IJAHMR) 3 (4):28-35.
    Background: Arthritis is very common but is not well understood. Actually, “arthritis” is not a single disease; it is an informal way of referring to joint pain or joint disease. There are more than 100 different types of arthritis and related conditions. People of all ages, sexes and races can and do have arthritis, and it is the leading cause of disability in America. More than 50 million adults and 300,000 children have some type of arthritis. It is most common (...)
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  24. Knowledge Based System for the Diagnosis of Dengue Disease.Aysha I. Mansour & Samy S. Abu-Naser - 2019 - International Journal of Academic Health and Medical Research (IJAHMR) 3 (4):12-19.
    Background: Dengue Disease is a mosquito-borne tropical disease caused by the dengue virus, symptoms typically begin three to fourteen days after infection. This may include a high fever, headache, vomiting, muscle and joint pains, and a characteristic skin rash. Dengue serology is applied in different settings, such as for surveillance, in health care facilities in endemic areas and in travel clinics in non-endemic areas. The applicability and quality of serological tests in dengue endemic regions has to be judged against a (...)
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  25. Knowledge Based System for Diabetes Diagnosis Using SL5 Object.Ibtesam M. Dheir, Alaa Soliman Abu Mettleq, Abeer A. Elsharif, Mohammed N. Abu Al-Qumboz & Samy S. Abu-Naser - 2019 - International Journal of Academic Pedagogical Research (IJAPR) 3 (4):1-10.
    Diabetes is a major public health issue that affects the nations of our time to a large extent and is described as a non-communicable epidemic. Diabetes mellitus is a common disease where there is too much sugar (glucose) floating around in your blood. This occurs because either the pancreas can’t produce enough insulin or the cells in body have become resistant to insulin. The concentration in this paper is on diagnosis diabetes by designing a proposed expert system. The main goal (...)
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  26. Tic-Tac-Toe Learning Using Artificial Neural Networks.Mohaned Abu Dalffa, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2019 - International Journal of Engineering and Information Systems (IJEAIS) 3 (2):9-19.
    Throughout this research, imposing the training of an Artificial Neural Network (ANN) to play tic-tac-toe bored game, by training the ANN to play the tic-tac-toe logic using the set of mathematical combination of the sequences that could be played by the system and using both the Gradient Descent Algorithm explicitly and the Elimination theory rules implicitly. And so on the system should be able to produce imunate amalgamations to solve every state within the game course to make better of results (...)
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  27. Glass Classification Using Artificial Neural Network.Mohmmad Jamal El-Khatib, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2019 - International Journal of Academic Pedagogical Research (IJAPR) 3 (23):25-31.
    As a type of evidence glass can be very useful contact trace material in a wide range of offences including burglaries and robberies, hit-and-run accidents, murders, assaults, ram-raids, criminal damage and thefts of and from motor vehicles. All of that offer the potential for glass fragments to be transferred from anything made of glass which breaks, to whoever or whatever was responsible. Variation in manufacture of glass allows considerable discrimination even with tiny fragments. In this study, we worked glass classification (...)
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  28. An Intelligent Tutoring System for Learning Introduction to Computer Science.Ahmad Marouf, Mohammed K. Abu Yousef, Mohammed N. Mukhaimer & Samy S. Abu-Naser - 2018 - International Journal of Academic Multidisciplinary Research (IJAMR) 2 (2):1-8.
    The paper describes the design of an intelligent tutoring system for teaching Introduction to Computer Science-a compulsory curriculum in Al-Azhar University of Gaza to students who attend the university. The basic idea of this system is a systematic introduction into computer science. The system presents topics with examples. The system is dynamically checks student's individual progress. An initial evaluation study was done to investigate the effect of using the intelligent tutoring system on the performance of students enrolled in computer science (...)
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  29. Sarcasm Detection in Headline News using Machine and Deep Learning Algorithms.Alaa Barhoom, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2022 - International Journal of Engineering and Information Systems (IJEAIS) 6 (4):66-73.
    Abstract: Sarcasm is commonly used in news and detecting sarcasm in headline news is challenging for humans and thus for computers. The media regularly seem to engage sarcasm in their news headline to get the attention of people. However, people find it tough to detect the sarcasm in the headline news, hence receiving a mistaken idea about that specific news and additionally spreading it to their friends, colleagues, etc. Consequently, an intelligent system that is able to distinguish between can sarcasm (...)
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  30. ARDUINO Tutor: An Intelligent Tutoring System for Training on ARDUINO.Islam Albatish, Msbah J. Mosa & Samy S. Abu-Naser - 2018 - International Journal of Engineering and Information Systems (IJEAIS) 2 (1):236-245.
    This paper aims at helping trainees to overcome the difficulties they face when dealing with Arduino platform by describing the design of a desktop based intelligent tutoring system. The main idea of this system is a systematic introduction into the concept of Arduino platform. The system shows the circuit boards of Arduino that can be purchased at low cost or assembled from freely-available plans; and an open-source development environment and library for writing code to control the board topic of Arduino (...)
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  31. Sarcasm Detection in Headline News using Machine and Deep Learning Algorithms.Alaa Barhoom, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2022 - International Journal of Engineering and Information Systems (IJEAIS) 6 (4):66-73.
    Abstract: Sarcasm is commonly used in news and detecting sarcasm in headline news is challenging for humans and thus for computers. The media regularly seem to engage sarcasm in their news headline to get the attention of people. However, people find it tough to detect the sarcasm in the headline news, hence receiving a mistaken idea about that specific news and additionally spreading it to their friends, colleagues, etc. Consequently, an intelligent system that is able to distinguish between can sarcasm (...)
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  32. Performance Efficiency of University Education from Students Perspective.Samia A. M. Abdalmenem, Rasha O. Owda, Amal A. Al Hila, Samy S. Abu-Naser & Mazen J. Al Shobaki - 2018 - International Journal of Engineering and Information Systems (IJEAIS) 2 (11):10-24.
    The study aims to identify the efficiency of the university education performance from the perspective of postgraduate and undergraduate students in international and Palestinian universities. The analytical descriptive approach was used for this purpose and the questionnaire was used as a main tool for data collection. The study community consists of: post graduate students, (23850) graduate students and (146355) undergraduate students. The sample of the study was 378 graduate students and 383 undergraduate students. The random stratified sample was used. The (...)
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  33. Breast Cancer Diagnosis and Survival Prediction Using JNN.Mohammed Ziyad Abu Shawarib, Ahmed Essam Abdel Latif, Bashir Essam El-Din Al-Zatmah & Samy S. Abu-Naser - 2020 - International Journal of Engineering and Information Systems (IJEAIS) 4 (10):23-30.
    Abstract: Breast cancer is reported to be the most common cancer type among women worldwide and it is the second highest women fatality rate amongst all cancer types. Notwithstanding all the progresses made in prevention and early intervention, early prognosis and survival prediction rates are still not sufficient. In this paper, we propose an ANN model which outperforms all the previous supervised learning methods by reaching 99.57 in terms of accuracy in Wisconsin Breast Cancer dataset. Experimental results on Haberman’s Breast (...)
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  34. Artificial Neural Network for Forecasting Car Mileage per Gallon in the City.Mohsen Afana, Jomana Ahmed, Bayan Harb, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2018 - International Journal of Advanced Science and Technology 124:51-59.
    In this paper an Artificial Neural Network (ANN) model was used to help cars dealers recognize the many characteristics of cars, including manufacturers, their location and classification of cars according to several categories including: Make, Model, Type, Origin, DriveTrain, MSRP, Invoice, EngineSize, Cylinders, Horsepower, MPG_Highway, Weight, Wheelbase, Length. ANN was used in prediction of the number of miles per gallon when the car is driven in the city(MPG_City). The results showed that ANN model was able to predict MPG_City with 97.50 (...)
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  35. Predictive Analysis of Lottery Outcomes Using Deep Learning and Time Series Analysis.Asil Mustafa Alghoul & Samy S. Abu-Naser - 2023 - International Journal of Engineering and Information Systems (IJEAIS) 7 (10):1-6.
    Abstract: Lotteries have long been a source of fascination and intrigue, offering the tantalizing prospect of unexpected fortunes. In this research paper, we delve into the world of lottery predictions, employing cutting-edge AI techniques to unlock the secrets of lottery outcomes. Our dataset, obtained from Kaggle, comprises historical lottery draws, and our goal is to develop predictive models that can anticipate future winning numbers. This study explores the use of deep learning and time series analysis to achieve this elusive feat. (...)
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  36. Diagnosis of Pneumonia Using Deep Learning.Alaa M. A. Barhoom & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (2):48-68.
    Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines or software that work and react like humans. Some of the activities computers with artificial intelligence are designed for include, Speech, recognition, Learning, Planning and Problem solving. Deep learning is a collection of algorithms used in machine learning, It is part of a broad family of methods used for machine learning that are based on learning representations of data. Deep learning is a technique used (...)
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  37. Effect of Oxygen Consumption of Thylakoid Membranes (Chloroplasts) From Spinach after Inhibition Using JNN.Hisham Ziad Belbeisi, Youssef Samir Al-Awadi, Muhammad Munir Abbas & Samy S. Abu-Naser - 2020 - International Journal of Academic Health and Medical Research (IJAHMR) 4 (11):1-7.
    Abstract: In this research, an Artificial Neural Network (ANN) model was developed and tested to predict effect of oxygen consumption of thylakoid membranes (chloroplasts) from spinach after inhibition. A number of factors were identified that may affect of oxygen consumption of thylakoid membranes from spinach. Factors such as curve, herbicide, dose, among others, as input variables for the ANN model. A model based on multi-layer concept topology was developed and trained using the data from some inhibition of photosynthesis in farms. (...)
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  38. Smoke Detectors Using ANN.Marwan R. M. Al-Rayes & Samy S. Abu-Naser - 2023 - International Journal of Academic Engineering Research (IJAER) 7 (10):1-9.
    Abstract: Smoke detectors are critical devices for early fire detection and life-saving interventions. This research paper explores the application of Artificial Neural Networks (ANNs) in smoke detection systems. The study aims to develop a robust and accurate smoke detection model using ANNs. Surprisingly, the results indicate a 100% accuracy rate, suggesting promising potential for ANNs in enhancing smoke detection technology. However, this paper acknowledges the need for a comprehensive evaluation beyond accuracy. It discusses potential challenges, such as overfitting, dataset size, (...)
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  39. Classification of A few Fruits Using Deep Learning.Mohammed Alkahlout, Samy S. Abu-Naser, Azmi H. Alsaqqa & Tanseem N. Abu-Jamie - 2022 - International Journal of Academic Engineering Research (IJAER) 5 (12):56-63.
    Abstract: Fruits are a rich source of energy, minerals and vitamins. They also contain fiber. There are many fruits types such as: Apple and pears, Citrus, Stone fruit, Tropical and exotic, Berries, Melons, Tomatoes and avocado. Classification of fruits can be used in many applications, whether industrial or in agriculture or services, for example, it can help the cashier in the hyper mall to determine the price and type of fruit and also may help some people to determining whether a (...)
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  40. Diagnosis of Blood Cells Using Deep Learning.Ahmed J. Khalil & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (2):69-84.
    In computer science, Artificial Intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. Computer science defines AI research as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. Deep Learning is a new field of research. One of the branches of Artificial Intelligence Science deals with the creation of theories and algorithms that (...)
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  41. Developing an Expert System to Computer Troubleshooting.Faten El Kahlout & Samy S. Abu-Naser - 2023 - International Journal of Academic Information Systems Research (IJAISR) 7 (6):16-26.
    There is no doubt that Computer troubleshooting is important for organizations and companies and for personal use level. Sound cards troubles is one of the most annoying problems in computers. It causes damage and troubles in computers to persons, organizations and firms. Correctly, expert systems can greatly help to avoid damage to these computers. designed to diagnose and troubleshoot issues related to sound cards in computer systems. The expert system is developed using a combination of rule-based and machine learning approaches, (...)
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  42. ITS for Data Manipulation Language (DML) Commands Using SQLite.Mahmoud Jamal Abu Ghali & Samy S. Abu-Naser - 2019 - International Journal of Engineering and Information Systems (IJEAIS) 3 (3):57-92.
    In many areas, technology has facilitated many things, diagnosing diseases, regulating traffic and teaching students in schools rely on Intelligent systems to name a few. At present, traditional classroom-based education is no longer the most appropriate in schools. From here, the idea of intelligent e-learning for students to increase their culture and keep them updated in life began. E-learning has become an ideal solution, relying on artificial intelligence, which has a footprint in this through the development of systems based on (...)
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  43. Streamlined Book Rating Prediction with Neural Networks.Lana Aarra, Mohammed S. Abu Nasser, Mohammed A. Hasaballah & Samy S. Abu-Naser - 2023 - International Journal of Engineering and Information Systems (IJEAIS) 7 (10):7-13.
    Abstract: Online book review platforms generate vast user data, making accurate rating prediction crucial for personalized recommendations. This research explores neural networks as simple models for predicting book ratings without complex algorithms. Our novel approach uses neural networks to predict ratings solely from user-book interactions, eliminating manual feature engineering. The model processes data, learns patterns, and predicts ratings. We discuss data preprocessing, neural network design, and training techniques. Real-world data experiments show the model's effectiveness, surpassing traditional methods. This research can (...)
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  44. Predicting Fire Alarms in Smoke Detection using Neural Networks.Maher Wissam Attia, Baraa Akram Abu Zaher, Nidal Hassan Nasser, Ruba Raed Al-Hour, Aya Haider Asfour & Samy S. Abu-Naser - 2023 - International Journal of Academic Information Systems Research (IJAISR) 7 (10):26-33.
    Abstract: This research paper presents the development and evaluation of a neural network-based model for predicting fire alarms in smoke detection systems. Using a dataset from Kaggle containing 15 features and 3487 samples, we trained and validated a neural network with a three-layer architecture. The model achieved an accuracy of 100% and an average error of 0.0000003. Additionally, we identified the most influential features in predicting fire alarms.
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  45. The Level of Promotion of Entrepreneurship in Technical Colleges in Palestine.Mazen J. Al Shobaki, Samy S. Abu-Naser, Youssef M. Abu Amuna & Suliman A. El Talla - 2018 - International Journal of Engineering and Information Systems (IJEAIS) 2 (1):168-189.
    The study aimed to identify the level of promotion of entrepreneurship in the technical colleges in Palestine. The analytical descriptive method was used in the study. A questionnaire of 41 items was randomly distributed to the technical colleges in the Gaza Strip. The random sample consisted of (275) employees from the mentioned colleges, and the response rate were (74.5%). The results of the study showed that the technical colleges achieved a high level of promotion of entrepreneurship with a relative weight (...)
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  46. Predicting Player Power In Fortnite Using Just Nueral Network.Al Fleet Muhannad Jamal Farhan & Samy S. Abu-Naser - 2023 - International Journal of Engineering and Information Systems (IJEAIS) 7 (9):29-37.
    Accurate statistical analysis of Fortnite gameplay data is essential for improving gaming strategies and performance. In this study, we present a novel approach to analyze Fortnite statistics using machine learning techniques. Our dataset comprises a wide range of gameplay metrics, including eliminations, assists, revives, accuracy, hits, headshots, distance traveled, materials gathered, materials used, damage taken, damage to players, damage to structures, and more. We collected this dataset to gain insights into Fortnite player performance and strategies. The proposed model employs advanced (...)
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  47. Fintech: Creative Innovation for Entrepreneurs.Youssef M. Abu Amuna, Samy S. Abu-Naser, Mazen J. Al Shobaki & Yasser A. Abu Mostafa - 2019 - International Journal of Academic Accounting, Finance and Management Research (IJAAFMR) 3 (3):8-15.
    The article studies the impact of Fintech on entrepreneurship in Arabic region by using Crowdfunding platforms as the field of study. The article focuses on Arabic Crowdfunding platforms. The population of (12) platforms consist of: individuals, entrepreneurs, investors, employees at Crowdfunding platforms. Descriptive and quantitative approach used in this article, and a questionnaire used as a tool to collect primary data. The results indicate an impact for Fintech on entrepreneurship in general and obvious obstacles to use it widely in Arabic (...)
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  48. Mint Expert System Diagnosis and Treatment.Mosa M. M. Megdad, Mohammed N. Ayyad, Mohanad H. Al-Qadi, Mohammed F. El-Habibi, Mohammed J. A. AlQatrawi, Raed Z. Sababa & Samy S. Abu-Naser - 2022 - International Journal of Academic Information Systems Research (IJAISR) 6 (5):22-28.
    Background: Mint is a grassy, perennial plant, belonging to the oral platoon, fast growing and spreading, its leaves are green in color, fragrant, tart, refreshing, square-shaped leg, bifurcated, erect, ranging in height from (10 - 201 cm). Home to Europe and Asia. The mint plant has many benefits, the most important of which are pain relief, treatment of gallbladder disorders, the expulsion of gases, anti-inflammatory, and relaxing nerves. While the mint plant is the ideal option for the start of gardens, (...)
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  49. Predicting Heart Disease using Neural Networks.Ahmed Muhammad Haider Al-Sharif & Samy S. Abu-Naser - 2023 - International Journal of Academic Information Systems Research (IJAISR) 7 (9):40-46.
    Cardiovascular diseases, including heart disease, pose a significant global health challenge, contributing to a substantial burden on healthcare systems and individuals. Early detection and accurate prediction of heart disease are crucial for timely intervention and improved patient outcomes. This research explores the potential of neural networks in predicting heart disease using a dataset collected from Kaggle, consisting of 1025 samples with 14 distinct features. The study's primary objective is to develop an effective neural network model for binary classification, identifying the (...)
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  50. An Intelligent Tutoring System for Teaching French.Randa Amer Khella & Samy S. Abu-Naser - 2018 - International Journal of Academic Multidisciplinary Research (IJAMR) 2 (2):9-13.
    The paper depicts the blueprint of an electronic wise indicating system for demonstrating learning French to understudies to overcome the inconveniences they go up against. The fundamental idea of this structure is a proficient introduction into learning French. The system shows the purpose of learning French and coordinates thusly made issues for the understudies to clarify. The system is logically balanced at run time to the understudy’s individual progress. The system gives unequivocal help to adaptable presentation to learners.
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