Results for 'Hossam Abdel Nasser Zaqout'

72 found
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  1.  82
    ANN Model for Predicting Protein Localization Sites in Cells.Mohammed Nafez Abu Samra, Bilal Ezz El-Din Abed, Hossam Abdel Nasser Zaqout & Samy S. Abu-Naser - 2020 - International Journal of Academic and Applied Research (IJAAR) 4 (9):43-50.
    To automate examination of massive amounts of sequence data for biological function, it is important to computerize interpretation based on empirical knowledge of sequence-function relationships. For this purpose, we have been constructing an Artificial Neural Network (ANN) by organizing various experimental and computational observations as a collection ANN models. Here we propose an ANN model which utilizes the Dataset for UCI Machine Learning Repository, for predicting localization sites of proteins. We collected data for 336 proteins with known localization sites and (...)
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  2. 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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  3. Artificial Neural Network for Predicting Animals Category.Ibrahim M. Nasser & Samy S. Abu-Naser - 2019 - International Journal of Academic and Applied Research (IJAAR) 3 (2):18-24.
    Abstract: In this paper an Artificial Neural Network (ANN) model, was developed and tested for predicting the category of an animal. There is a number of factors that influence the classification of animals. Such as the existence of hair/ feather, if the animal gives birth or spawns, it is airborne, aquatic, predator, toothed, backboned, venomous, has –fins, has-tail, cat-sized, and domestic. They were then used as input variables for the ANN model. A model based on the Multilayer Perceptron Topology was (...)
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  4. 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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  5. Knowledge-Based Systems That Determine the Appropriate Students Major: In the Faculty of Engineering and Information Technology.Samy S. Abu Naser & Ihab S. Zaqout - 2016 - World Wide Journal of Multidisciplinary Research and Development 2 (10):26-34.
    In this paper a Knowledge-Based System (KBS) for determining the appropriate students major according to his/her preferences for sophomore student enrolled in the Faculty of Engineering and Information Technology in Al-Azhar University of Gaza was developed and tested. A set of predefined criterions that is taken into consideration before a sophomore student can select a major is outlined. Such criterion as high school score, score of subject such as Math I, Math II, Electrical Circuit I, and Electronics I taken during (...)
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  6. A Proposed Artificial Neural Network for Predicting Movies Rates Category.Ibrahim M. Nasser, Mohammed Al-Shawwa & Samy S. Abu-Naser - 2019 - International Journal of Academic Engineering Research (IJAER) 3 (2):21-25.
    We proposed an Artificial Neural Network (ANN) in this paper for predicting the rate category of movies. A dataset used obtained from UCI repository created for research purposes. Our ANN prediction model was developed and validated; validation results showed that the ANN model is able to 92.19% accurately predict the category of movies’ rate.
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  7. Predicting Books’ Overall Rating Using Artificial Neural Network.Ibrahim M. Nasser & Samy S. Abu-Naser - 2019 - International Journal of Academic Engineering Research (IJAER) 3 (8):11-17.
    We developed an Artificial Neural Network (ANN) model for predicting the overall rating of books. The prediction is based on some Factors (bookID, title, authors, isbn, language_code, isbn13, # num_pages, ratings_count, text_reviews_count), which used as input variables and (average_rating) as output for our ANN predictive model. Our model established, trained, and validated using data set, which its title is “Goodreads-books”. Model evaluation showed that the ANN model is able to predict correctly 99.90% of the validation instances.
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  8. Artificial Neural Network for Mushroom Prediction.Kamel Jamal Dawood, Mohamed Hussam Zaqout, Riad Mohammed Salem & Samy S. Abu-Naser - 2020 - International Journal of Academic Information Systems Research (IJAISR) 4 (10):9-17.
    Abstract: Predication is an application of Artificial Neural Network (ANN). It is a supervised learning due to predefined input and output attributes. Multi-Layer ANN model is used for training, validating, and testing of the dataset. In this paper, Multi-Layer ANN model was used to train and test the mushroom dataset to predict whether mushroom is edible or poisonous. The Mushrooms dataset was prepared for training, 8124 instances were used for the training. JNN tool was used for training and validating the (...)
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  9. Developing Artificial Neural Network for Predicting Mobile Phone Price Range.Ibrahim M. Nasser, Mohammed Al-Shawwa & Samy S. Abu-Naser - 2019 - International Journal of Academic Information Systems Research (IJAISR) 3 (2):1-6.
    In this paper an Artificial Neural Network (ANN) model, was developed and tested for predicting the price range of a mobile phone. We used a dataset that contains mobile phones information, and there was a number of factors that influence the classification of mobile phone price. Factors as battery power, CPU clock speed, has dual sim support or not, Front Camera mega pixels, has 4G or not, has Wi-Fi or not, etc…. 20 attributes were used as input variables for the (...)
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  10.  49
    Nasserism and the Impossibility of Innocence.Zeyad El Nabolsy - 2021 - International Politics Reviews 2021:1-9.
    One of the central strengths of Salem's analysis of Nasserism is that she recognizes both its world-historical significance as a progressive nationalist movement, and its severe limitations. In the first section of this paper, I discuss Salem's notion of the "afterlives" of the Nasserist project by drawing attention to one of the most debilitating legacies of that project, namely the transformation of Egyptian politics into petty bourgeois politics. In the second section, I argue that while Salem does not explicitly draw (...)
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  11.  81
    Antibiotic Susceptibility Prediction Using JNN.Ahmed Jabara Abu Oriban, Shaima Naji Abdel-Al, Nourhan Abdel Moneim Fouda & Samy S. Abu-Naser - 2020 - International Journal of Academic Information Systems Research (IJAISR) 4 (11):1-6.
    Abstract: In this research, an Artificial Neural Network (ANN) model was developed and validated to predict efficiency of antibiotics in treating various bacteria types. Attributes that were taken in account are: organism name, specimen type, and antibiotic name as input and susceptibility as an output. A model based on one input layer, one hidden layer, and one output layer concept topology was developed and trained using a data from Queensland government's website. The evaluation shows that the proposed ANN model using (...)
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  12. Lung Cancer Detection Using Artificial Neural Network.Ibrahim M. Nasser & Samy S. Abu-Naser - 2019 - International Journal of Engineering and Information Systems (IJEAIS) 3 (3):17-23.
    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 (...)
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  13. Survey of Rule-Based Systems.Naser Masri, Yousef Abu Sultan, Alaa N. Akkila, Abdelbaset Almasri, Adel Ahmed, Ahmed Y. Mahmoud, Ihab Zaqout & Samy S. Abu-Naser - 2019 - International Journal of Academic Information Systems Research (IJAISR) 3 (7):1-23.
    Rule-Based Systems (RBS) are computer programs based on technologies established by Artificial Intelligence research, which express some characteristics of human knowledge and expertise to perform tasks normally done by human experts. Thus, a Rule -based system has two distinguishing features: a Rule base and an inference engine. The first part, the Rule base, represents facts about the world. The second part, the inference engine, allows new knowledge to be inferred. Most commonly, it can take the form of IF-THEN rules coupled (...)
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  14. Artificial Neural Network for Diagnose Autism Spectrum Disorder.Ibrahim M. Nasser, Mohammed Al-Shawwa & Samy S. Abu-Naser - 2019 - International Journal of Academic Information Systems Research (IJAISR) 3 (2):27-32.
    In this paper an Artificial Neural Network (ANN) model, was developed and tested for diagnosing Autism Spectrum Disorder (ASD). A dataset collected from ASD screening app was used in this paper, it contains ASD tests results based upon questions answers from users. Test data evaluation shows that the ANN model is able to correctly diagnose ASD with 100% accuracy.
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  15. 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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  16. 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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  17. Handwritten Signature Verification Using Deep Learning.Eman Alajrami, Belal A. M. Ashqar, Bassem S. Abu-Nasser, Ahmed J. Khalil, Musleh M. Musleh, Alaa M. Barhoom & Samy S. Abu-Naser - 2020 - International Journal of Academic Multidisciplinary Research (IJAMR) 3 (12):39-44.
    Every person has his/her own unique signature that is used mainly for the purposes of personal identification and verification of important documents or legal transactions. There are two kinds of signature verification: static and dynamic. Static(off-line) verification is the process of verifying an electronic or document signature after it has been made, while dynamic(on-line) verification takes place as a person creates his/her signature on a digital tablet or a similar device. Offline signature verification is not efficient and slow for a (...)
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  18. Plant Seedlings Classification Using Deep Learning.Belal A. M. Ashqar, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2019 - International Journal of Academic Information Systems Research (IJAISR) 3 (1):7-14.
    Agriculture is very important to human continued existence and remains a key driver of many economies worldwide, especially in underdeveloped and developing economies. There is an increasing demand for food and cash crops, due to the increasing in world population and the challenges enforced by climate modifications, there is an urgent need to increase plant production while reducing costs. Preceding instrument vision methods established for selective weeding have confronted with major challenges for trustworthy and precise weed recognition. In this paper, (...)
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  19. Predicting Overall Car Performance Using Artificial Neural Network.Osama M. Al-Mubayyed, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2019 - International Journal of Academic and Applied Research (IJAAR) 3 (1):1-5.
    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 99.62 %. The factor of Safety has the most influence on car acceptability evaluation. Comparative study method is (...)
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  20. Blood Donation Prediction Using Artificial Neural Network.Eman Alajrami, Bassem S. Abu-Nasser, Ahmed J. Khalil, Musleh M. Musleh, Alaa M. Barhoom & S. S. Abu Naser - 2019 - International Journal of Academic Engineering Research (IJAER) 3 (10):1-7.
    The aim of this research is to study the performance of JustNN environment that have not been previously examined to care of this blood donation problem forecasting. An Artificial Neural Network model was built to understand if performance is considerably enhanced via JustNN tool or not. The inspiration for this study is that blood request is steadily growing day by day due to the need of transfusions of blood because of surgeries, accidents, diseases etc. Accurate forecast of the number of (...)
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  21. 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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  22. Prediction of Whether Mushroom is Edible or Poisonous Using Back-Propagation Neural Network.Eyad Sameh Alkronz, Khaled A. Moghayer, Mohamad Meimeh, Mohannad Gazzaz, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2019 - International Journal of Academic and Applied Research (IJAAR) 3 (2):1-8.
    Abstract: Predication is an application of Artificial Neural Network (ANN). It is a supervised learning due to predefined input and output attributes. Multi-Layer ANN model is used for training, validating, and testing of the data. In this paper, Multi-Layer ANN model was used to train and test the mushroom dataset to predict whether it is edible or poisonous. The Mushrooms dataset was prepared for training, 8124 instances were used for the training. JustNN software was used to training and validating the (...)
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  23. The Effects of The Hidden Economy in Sudan And its Reduction Strategies.Abdel Muttalib Ali Ibnouf & Howyda Tahir Hassan Taha - 2019 - International Journal of Academic Accounting, Finance and Management Research (IJAAFMR) 3 (1):44-52.
    Abstract: The economic and social effects of the phenomenon of the hidden economy include that some of the funds practiced by the hidden economic activity result from evasion of payment of taxes owed to the state, which necessarily means the lack of resources available to the state to finance its economic and social development programs. Through the ability to secure goods at prices lower than the prices of goods in the official sector and this is generated by encouraging the growing (...)
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  24. Survey of Intelligent Tutoring Systems Up to the End of 2017.Alaa N. Akkila, Abdelbaset Almasri, Adel Ahmed, Naser Al-Masri, Yousef Abu Sultan, Ahmed Y. Mahmoud, Ihab Zaqout & Samy S. Abu-Naser - 2019 - International Journal of Academic Information Systems Research (IJAISR) 3 (4):36-49.
    The main goals of Intelligent Tutoring Systems (ITS) are: providing highly developed instructional guidance on a one-to-one foundation that is improved than what is attained with traditional computer aided instruction and is analogous to that of a decent human tutor; and developing and testing models of intelligent processes associated with instruction. ITS is a subfield of artificial intelligence. ITS consists of four interacting components: the student model which embodies the student's present knowledge state, the pedagogical module which comprises appropriate instructional (...)
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  25. Predicting Titanic Survivors Using Artificial Neural Network.Alaa M. Barhoom, Ahmed J. Khalil, Bassem S. Abu-Nasser, Musleh M. Musleh & Samy S. Abu Naser - 2019 - International Journal of Academic Engineering Research (IJAER) 3 (9):8-12.
    Although the Titanic disaster happened just over one hundred years ago, it still appeals researchers to understand why some passengers survived while others did not. With the use of a machine learning tool (JustNN) and the provided dataset we study which factors or classifications of passengers have a strong relationship with survival for passengers that took that trip on 15th of April, 1912. The analysis seeks to identify characteristics of passengers - cabin class, age, and point of departure – and (...)
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  26. 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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  27. Artificial Neural Network for Lung Cancer Detection.Ola Mohammed Abu Kweik, Mohammed Atta Abu Hamid, Samer Osama Sheqlieh, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2020 - International Journal of Academic Engineering Research (IJAER) 4 (11):1-7.
    Abstract: The effectiveness of cancer prediction system helps the people to know their cancer risk with low cost and it also helps the people to take the appropriate decision based on their cancer risk status. The dataset is collected from the data world website. In this paper, we proposed an Artificial Neural Network for detecting whether lung cancer is found or not in human body. Symptoms were used to diagnose the lung cancer, these symptoms such as Yellow fingers, Anxiety, Chronic (...)
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  28. Parkinson’s Disease Prediction Using Artificial Neural Network.Ramzi M. Sadek, Salah A. Mohammed, Abdul Rahman K. Abunbehan, Abdul Karim H. Abdul Ghattas, Majed R. Badawi, Mohamed N. Mortaja, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2019 - International Journal of Academic Health and Medical Research (IJAHMR) 3 (1):1-8.
    Parkinson's Disease (PD) is a long-term degenerative disorder of the central nervous system that mainly affects the motor system. The symptoms generally come on slowly over time. Early in the disease, the most obvious are shaking, rigidity, slowness of movement, and difficulty with walking. Doctors do not know what causes it and finds difficulty in early diagnosing the presence of Parkinson’s disease. An artificial neural network system with back propagation algorithm is presented in this paper for helping doctors in identifying (...)
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  29. Is Perception Cognitively Penetrable? A Philosophically Satisfying and Empirically Testable Reframing.Gary Lupyan, Dustin Stokes, Fiona Macpherson, Rasha Abdel Rahman & Robert Goldstone - 2013 - Proceedings of the 35th Annual Conference of the Cognitive Science Society 1:91-2.
    The question of whether perception can be penetrated by cognition is in the limelight again. The reason this question keeps coming up is that there is so much at stake: Is it possible to have theory-neutral observation? Is it possible to study perception without recourse to expectations, context, and beliefs? What are the boundaries between perception, memory, and inference (and do they even exist)? Are findings from neuroscience that paint a picture of perception as an inherently bidirectional and interactive process (...)
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  30. Knowledge-Based Systems Survey.Adel Ahmed, Naser Masri, Yousef Abu Sultan, Alaa N. Akkila, Abdelbaset Almasri, Ahmed Y. Mahmoud, Ihab Zaqout & Samy S. Abu-Naser - 2019 - International Journal of Academic Engineering Research (IJAER) 3 (7):1-22.
    Knowledge-Based Systems (KBS) are computer programs based on technologies established by Artificial Intelligence research, which express some characteristics of human knowledge and expertise to perform tasks normally done by human experts. Thus, a knowledge-based system has two distinguishing features: a knowledge base and an inference engine. The first part, the knowledge base, represents facts about the world. The second part, the inference engine, allows new knowledge to be inferred. Most commonly, it can take the form of IF-THEN rules coupled with (...)
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  31. Presence of Amphibian Species Prediction Using Features Obtained From GIS and Satellite Images.Nadia Shaker Habib, Omar Kamal Abu Maghasib, Ahmed Rashad Al-Ghazali, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2020 - International Journal of Academic and Applied Research (IJAAR) 4 (11):13-22.
    The establishment of the transport infrastructure is usually preceded by an EIA procedure, which should determine amphibian breeding sites and migration routes. However, evaluation is very difficult due to the large number of habitats spread over a vast area and the limited time available for field work. An artificial Neural Network (ANN) is proposed for predicting the presence of amphibians species near the water reservoirs based on features obtained from GIS systems and satellite images. The dataset collected from UCI Machine (...)
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  32.  88
    Tumor Classification Using Artificial Neural Networks.Jamal Khamis El-Mahelawi, Jinan Usama Abu-Daqah, Rasha Ibrahim Abu-Latifa, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2020 - International Journal of Academic Engineering Research (IJAER) 4 (11):8-15.
    Abstract: Tumor is a group of diseases that involve abnormal increases in the number of cells, with the potential to invade or spread to other parts of the body. Not all tumors or lumps are cancerous; benign tumors are not classified as being cancer because they do not spread to other parts of the body. There are over 100 different known Tumors that affect humans. Tumors are often described by the body part that they originated in. However, some body parts (...)
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  33. Radical Religious Thought in Black Popular Music. Five Percenters and Bobo Shanti in Rap and Reggae.Martin Abdel Matin Gansinger - 2017 - Hamburg, Germany: Anchor.
    This book is discussing patterns of radical religious thought in popular forms of Black music. The consistent influence of the Five Percent Nation on Rap music as one of the most esoteric groups among the manifold Black Muslim movements has already gained scholarly attention. However, it shares more than a strong pattern of reversed racism with the Bobo Shanti Order, the most rigid branch of the Rastafarian faith, globally popularized by Dancehall-Reggae artists like Sizzla or Capleton. Authentic devotion or calculated (...)
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  34. 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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  35. Mechanism of Development of Pre-Eclampsia Linking Breathing Disorders to Endothelial Dysfunction.Jerath Ravinder, Vernon A. Barnes & Hossam E. Fadel - 2009 - Medical Hypotheses 73:163-166.
    High blood pressure is an important component of pre-eclampsia. The underlying mechanism of development of hypertension in pre-eclampsia is complicated and still remains obscure. Several theories have been advanced including endothelial dysfunction, uteroplacental insufficiency leading to generalized vasoconstriction, increased cardiac output, and sympathetic hyperactivity. Increased blood flow and pressure are thought to lead to capillary dilatation, which damages end-organ sites, leading to hypertension, proteinuria and edema. Additional theories have been put forward based on epidemiological research, implicating immunological and genetic factors. (...)
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  36.  67
    Predicting the Age of Abalone From Physical Measurements Using Artificial Neural Network.Ghaida Riyad Mohammed, Jaffa Riad Abu Shbikah, Mohammed Majid Al-Zamili, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2020 - International Journal of Academic and Applied Research (IJAAR) 4 (11):7-12.
    Abalones have long been a valuable food source for humans in every area of the world where a species is abundant. Predicting the age of abalone is done using physical measurements. The age of abalone is determined by cutting the shell through the cone, staining it, and counting the number of rings through a microscope -- a boring and time-consuming task. Other measurements, which are easier to obtain, are used to predict the age of abalone is using Artificial Neural Network (...)
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  37. Predicting Liver Patients Using Artificial Neural Network.Musleh M. Musleh, Eman Alajrami, Ahmed J. Khalil, Bassem S. Abu-Nasser, Alaa M. Barhoom & S. S. Abu Naser - 2019 - International Journal of Academic Information Systems Research (IJAISR) 3 (10):1-11.
    Liver diagnosis at an early stage is essential for enhanced handling. Precise classification is required for automatic recognition of disease from data samples (utilizing data mining for classification of liver patients from healthy ones). In this study, an artificial neural network model was designed and developed using JustNN Tool for predicting weather a person is a liver patient or not based on a dataset for liver patients. The main factors for input variables are: Age, Gender, Total Bilirubin, Direct Bilirubin, Alkphos (...)
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  38.  93
    Machine Learning Application to Predict The Quality of Watermelon Using JustNN.Ibrahim M. Nasser - 2019 - International Journal of Engineering and Information Systems (IJEAIS) 3 (10):1-8.
    In this paper, a predictive artificial neural network (ANN) model was developed and validated for the purpose of prediction whether a watermelon is good or bad, the model was developed using JUSTNN software environment. Prediction is done based on some watermelon attributes that are chosen to be input data to the ANN. Attributes like color, density, sugar rate, and some others. The model went through multiple learning-validation cycles until the error is zero, so the model is 100% percent accurate for (...)
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  39. Machine Learning and Job Posting Classification: A Comparative Study.Ibrahim M. Nasser & Amjad H. Alzaanin - 2020 - International Journal of Engineering and Information Systems (IJEAIS) 4 (9):06-14.
    In this paper, we investigated multiple machine learning classifiers which are, Multinomial Naive Bayes, Support Vector Machine, Decision Tree, K Nearest Neighbors, and Random Forest in a text classification problem. The data we used contains real and fake job posts. We cleaned and pre-processed our data, then we applied TF-IDF for feature extraction. After we implemented the classifiers, we trained and evaluated them. Evaluation metrics used are precision, recall, f-measure, and accuracy. For each classifier, results were summarized and compared with (...)
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  40. Predicting Whether a Couple is Going to Get Divorced or Not Using Artificial Neural Networks.Ibrahim M. Nasser - 2019 - International Journal of Engineering and Information Systems (IJEAIS) 3 (10):49-55.
    In this paper, an artificial neural network (ANN) model was developed and validated to predict whether a couple is going to get divorced or not. Prediction is done based on some questions that the couple answered, answers of those questions were used as the input to the ANN. The model went through multiple learning-validation cycles until it got 100% accuracy.
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  41. Suggestions to Enhance the Scholarly Search Engine: Google Scholar.Ibrahim M. Nasser, Mohammed M. Elsobeihi & Samy S. Abu Naser - 2019 - International Journal of Engineering and Information Systems (IJEAIS) 3 (3):11-16.
    The scholarly search engine Google Scholar (G.S.) has problems that make it not a 100% trusted search engine. In this research, we discussed a few drawbacks that we noticed in Google Scholar, one of them is related to how does it perform (add articles) option for adding new articles that are related to the registered researchers. Our suggestion is an attempt for making G.S. more efficient by improving the searching method that it uses and finally having trusted statistical results.
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  42. Web Application for Generating a Standard Coordinated Documentation for CS Students’ Graduation Project in Gaza Universities.Ibrahim M. Nasser & Samy S. Abu-Naser - 2017 - International Journal of Engineering and Information Systems (IJEAIS) 1 (6):155-167.
    The computer science (CS) graduated students suffered from documenting their projects and specially from coordinating it. In addition, students’ supervisors faced difficulties with guiding their students to an efficient process of documenting. In this paper, we will offer a suggestion as a solution to the mentioned problems; that is an application to make the process of documenting computer science (CS) student graduation project easy and time-cost efficient. This solution will decrease the possibility of human mistakes and reduce the effort of (...)
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  43.  16
    Complex Modulus of Waste Tires Reinforced Polystyrene.Mahmoud Abdel-Halim Abdel-Goad - 2018 - International Journal of Engineering and Information Systems (IJEAIS) 2 (8):11-18.
    Abstract: In this work, polystyrene/waste tires composites were prepared by incorporating of waste tires into polydisperse commercial polystyrene in a melt-mixing method. The rheological characterization of PS and PS/composite have been studied and compared. These properties were studied using ARES-Rheometer under nitrogen atmosphere in parallel plate geometry with diameter 8 mm. The measurements are carried out over a wide range of temperatures ranged from 120°C to 220°C and frequencies from 100 to 0.1 radians per second. The complex modulus (G*) were (...)
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  44.  76
    Dynamic and Complex Viscosity of Polystyrene/ Waste Tires Composites.Mahmoud Abdel-Halim Abdel-Goad - 2018 - International Journal of Engineering and Information Systems (IJEAIS) 2 (8):12-17.
    Abstract: In this work, polystyrene/waste tires composites were prepared using the melt-mixing method. The viscoelastic properties of PS and PS/composite have been evaluated and compared. These properties were studied using ARES-Rheometer under nitrogen atmosphere in parallel plate geometry with diameter 8 mm. The measurements are carried out over a wide range of temperatures ranged from 120°C to 220°C and frequencies from 100 to 0.1 radians per second. The dynamic and complex viscosity of the PS composites were studied and compared with (...)
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  45.  16
    Dynamic Mechanical Analysis for Waste Tires Reinforced Polystyrene: Shear Compliance.Mahmoud Abdel-Halim Abdel-Goad - 2018 - International Journal of Engineering and Information Systems (IJEAIS) 2 (8):51-54.
    Abstract: Polystyrene/waste tires composites were prepared in this study by incorporating small particles of waste tires into polydisperse commercial polystyrene (PS) in a melt-mixing method. The dynamic mechanical properties of PS and PS/composite were studied using ARES-Rheometer under nitrogen atmosphere in parallel plate geometry with diameter 8 mm. The measurements were carried out over a wide range of temperatures ranged from 120°C to 220°C and frequencies from 100 to 0.1 radians per second. The shear compliance of PS composite were studied (...)
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  46.  17
    Dynamic Mechanical Properties of Bitumen Composites: Part II.Mahmoud Abdel-Halim Abdel-Goad - 2018 - International Journal of Academic and Applied Research (IJAAR) 2 (3):5-8.
    Abstract: Waste polyethylene (PE) bags were reused in the modification of commercially available bitumen. The bitumen/PE blend was prepared by mixing homogenously commercial bitumen with waste PE in the molten state. The samples of bitumen blend and bitumen base were rheologically analyzied. The rheological properties such as complex modulus, shear compliance, torque and complex viscosity of bitumen and bitumen blend were studied using an ARES- Rheometer (Rheometric Scientific, Co.) in the dynamic mode, plate-plate geometry with diameter 8 mm. The measurements (...)
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  47.  44
    Molecular Characterization of Polystyrene/ Waste Tires Composites.Mahmoud Abdel-Halim Abdel-Goad - 2018 - International Journal of Engineering and Information Systems (IJEAIS) 4 (2):33-36.
    In this work, polystyrene/waste tires composites were prepared using the melt-mixing method.. The effect of the preparation conditions of the PS/waste tires composite is investigated in this work by using Gel permeation chromatography (GPC) technique. Stability at elevated temperatures were found to increase with the addition of waste tires to PS as confirmed by the results. GPC results indicate that the preparation conditions of the PS/waste tires composite has no effect on the Ps chains as indicated by GPC technique. The (...)
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  48.  18
    Rheological Characteristics of Waste Polyvinyl Chloride-Bitumen Composites: Part II.Mahmoud Abdel-Halim Abdel-Goad & Ijarw Ijeais - 2018 - International Journal of Engineering and Information Systems (IJEAIS) 2 (2):13-17.
    Abstract— Waste Polyvinyl chloride-bitumen composites were prepared in the molten state by addition waste PVC pipes to commercial bitumen in different concentrations. The original material of the pure bitumen and bitumen composites are rheologically characterized. The viscoelastic properties such as shear compliance, torque and viscosity were measured and compared. These properties were studied using an ARES- Rheometer (Rheometric Scientific, Co.) equipment. The measurements were performed in the dynamic mode, plate-plate geometry of 25 mm diameter over the temperature range from –10 (...)
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  49.  31
    Rheological Characteristics of Waste Polyvinyl Chloride-Bitumen Composites: Part III.Mahmoud Abdel-Halim Abdel-Goad & Ijarw Ijeais - 2018 - International Journal of Engineering and Information Systems (IJEAIS) 2 (2):18-21.
    Abstract— Waste Polyvinyl chloride-bitumen composites were prepared in the molten state by addition waste PVC pipes to commercial bitumen in different concentrations. The original material of the pure bitumen and bitumen composites are rheologically characterized. The viscoelastic properties such as shear compliance, torque and viscosity were measured and compared. These properties were studied using an ARES- Rheometer (Rheometric Scientific, Co.) equipment. The measurements were performed in the dynamic mode, plate-plate geometry of 25 mm diameter over the temperature range from –10 (...)
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  50.  22
    Rheological Characterization of Bitumen/Waste Polyethylene Composites: Part III.Mahmoud Abdel-Halim Abdel-Goad - 2018 - International Journal of Engineering and Information Systems (IJEAIS) 2 (2):1-10.
    Waste polyethylene (PE) bags were reused in the modification of commercially available bitumen. The bitumen/PE blend was prepared by mixing homogenously commercial bitumen with waste PE in the molten state. The samples of bitumen blend and bitumen base were rheologically analyzied. The rheological properties such as complex modulus, shear compliance, torque and complex viscosity of bitumen and bitumen blend were studied using an ARES- Rheometer (Rheometric Scientific, Co.) in the dynamic mode, plate-plate geometry with diameter 8 mm. The measurements were (...)
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