Results for 'Nassar Shawwa'

13 found
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  1. ANN for Predicting Mobile Phone Price Range.Fatthy Khillha & Nassar Shawwa - 2020 - 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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  2.  22
    ANN for Predicting Movies Rates Category.Nassar Shawwa & Fatthy Khillha - 2020 - 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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  3.  60
    Analogical Reflection as a Source for the Science of Life: Kant and the Possibility of the Biological Sciences.Dalia Nassar - 2016 - Studies in History and Philosophy of Science Part A 2016 (58):57-66.
    In contrast to the previously widespread view that Kant's work was largely in dialogue with the physical sciences, recent scholarship has highlighted Kant's interest in and contributions to the life sciences. Scholars are now investigating the extent to which Kant appealed to and incorporated insights from the life sciences and considering the ways he may have contributed to a new conception of living beings. The scholarship remains, however, divided in its interest: historians of science are concerned with the content of (...)
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  4.  28
    Hermeneutics and Nature.Dalia Nassar - 2019 - In Michael Förster & Kristin Gjesdal (eds.), The Cambridge Companion to Hermeneutics. Cambridge: Cambridge. pp. 37-74.
    This paper contributes to the on-going research into the ways in which the humanities transformed the natural sciences in the late Eighteenth and early Nineteenth Centuries. By investigating the relationship between hermeneutics -- as developed by Herder -- and natural history, it shows how the methods used for the study of literary and artistic works played a crucial role in the emergence of key natural-scientific fields, including geography and ecology.
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  5.  39
    ANN for Diagnosing Autism Spectrum Disorder.Mohammad Nassar - 2020 - International Journal of Academic Information Systems Research (IJAISR) 3 (12):12-17.
    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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  6. Banana Classification Using Deep Learning.Ahmed F. Al-Daour, Mohammed O. Al-Shawwa & Samy S. Abu-Naser - 2020 - International Journal of Academic Information Systems Research (IJAISR) 3 (12):6-11.
    Abstract: Banana, fruit of the genus Musa, of the family Musaceae, one of the most important fruit crops of the world. The banana is grown in the tropics, and, though it is most widely consumed in those regions, it is valued worldwide for its flavour, nutritional value, and availability throughout the year. Cavendish, or dessert, bananas are most commonly eaten fresh, though they may be fried or mashed and chilled in pies or puddings. They may also be used to flavour (...)
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  7. Type of Grapefruit Classification Using Deep Learning.Mohammed M. Abu-Saqer, Samy S. Abu-Naser & Mohammed O. Al-Shawwa - 2020 - International Journal of Academic Information Systems Research (IJAISR) 4 (1):1-5.
    Fruit has been recognized as a good source of vitamins and minerals, and for their role in preventing vitamin C and vitamin A deficiencies. People who eat fruit as part of an overall healthy diet generally have a reduced risk of chronic diseases. Fruit are important sources of many nutrients, including potassium, fiber, vitamin C and folate (folic acid). One of important types of fruit is Grapefruit . Grapefruit is a tropical citrus fruit known its sweet and somewhat sour taste. (...)
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  8. Analyzing Types of Cherry Using Deep Learning.Izzeddin A. Alshawwa, Hosni Qasim El-Mashharawi, Mohammed Elkahlout, Mohammed O. Al-Shawwa & Samy S. Abu-Naser - 2020 - International Journal of Academic Engineering Research (IJAER) 4 (1):1-5.
    A cherry is the fruit of many plants of the genus Prunus, and is a fleshy drupe (stone fruit), Michigan's Northwest Lower Peninsula is the largest producer of tart cherries in the United States. In fact, grow 75% of the country's variety of mighty Montmorency cherries. We use these Ruby Red Morsels of Joy in over 200 cherry products like Salsas, Chocolate Covered Cherries, Cherry Nut Mixes, and much more. Cherry fruits are rich in vitamins and minerals, and it is (...)
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  9. Classification of Apple Fruits by Deep Learning.Mohammed O. Al-Shawwa & Samy S. Abu-Naser - 2020 - International Journal of Academic Engineering Research (IJAER) 3 (12):1-7.
    Abstract: Apple is a plant species that follows the apple genus, which is a fruit because it contains seeds of the pink family. It is one of the most fruit trees in terms of agriculture. The apple tree is small in length from 3 to 12 meters. Several recent studies have shown many health benefits of apples. It helps with the strengthening of the brain, heart, and stomach. It is used in the treatment of joint pain and limberness. It is (...)
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  10. Apple Fruits Classification Using Deep Learning.Shawwa Mohammad - 2020 - International Journal of Academic Engineering Research (IJAER) 3 (12):1-6.
    Apple is a plant species that follows the apple genus, which is a fruit because it contains seeds of the pink family. It is one of the most fruit trees in terms of agriculture. The apple tree is small in length from 3 to 12 meters. Several recent studies have shown many health benefits of apples. It helps with the strengthening of the brain, heart, and stomach. It is used in the treatment of joint pain and limberness. It is opposite. (...)
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  11.  48
    ANN for Lung Cancer Detection.Nassar AlIbrahim & Murshidy Suheil - 2020 - International Journal of Engineering and Information Systems (IJEAIS) 3 (3):17-21.
    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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  12.  32
    ANN for Predicting Animals Category.Nassar Ibraheem & AlKahlout Mohammad - 2020 - International Journal of Academic and Applied Research (IJAAR) 3 (2):18-23.
    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 developed (...)
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  13.  25
    ANN for Predicting Books’ Overall Rating.Nassar AlIbrahim & Gazaz Ahmed - 2020 - International Journal of Academic Engineering Research (IJAER) 8 (3):1-5.
    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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