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  1. Credit Score Classification Using Machine Learning.Mosa M. M. Megdad & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (5):1-10.
    Abstract: Ensuring the proactive detection of transaction risks is paramount for financial institutions, particularly in the context of managing credit scores. In this study, we compare different machine learning algorithms to effectively and efficiently. The algorithms used in this study were: MLogisticRegressionCV, ExtraTreeClassifier,LGBMClassifier,AdaBoostClassifier, GradientBoostingClassifier,Perceptron,RandomForestClassifier,KNeighborsClassifier,BaggingClassifier, DecisionTreeClassifier, CalibratedClassifierCV, LabelPropagation, Deep Learning. The dataset was collected from Kaggle depository. It consists of 164 rows and 8 columns. The best classifier with unbalanced dataset was the LogisticRegressionCV. The Accuracy 100.0%, precession 100.0%,Recall100.0% and the F1-score (...)
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  • Classification of Rice Using Deep Learning.Mohammed H. S. Abueleiwa & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (4):26-36.
    Abstract: Rice is one of the most important staple crops in the world and serves as a staple food for more than half of the global population. It is a critical source of nutrition, providing carbohydrates, vitamins, and minerals to millions of people, particularly in Asia and Africa. This paper presents a study on using deep learning for the classification of different types of rice. The study focuses on five specific types of rice: Arborio, Basmati, Ipsala, Jasmine, and Karacadag. A (...)
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  • Fish Classification Using Deep Learning.M. N. Ayyad & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (4):51-58.
    Abstract: Fish are important for both nutritional and economic reasons. They are a good source of protein, vitamins, and minerals and play a significant role in human diets, especially in coastal and island communities. In addition, fishing and fish farming are major industries that provide employment and income for millions of people worldwide. Moreover, fish play a critical role in marine ecosystems, serving as prey for larger predators and helping to maintain the balance of aquatic food chains. Overall, fish play (...)
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  • Using Deep Learning to Classify Corn Diseases.Mohanad H. Al-Qadi & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems (Ijaisr) 8 (4):81-88.
    Abstract: A corn crop typically refers to a large-scale cultivation of corn (also known as maize) for commercial purposes such as food production, animal feed, and industrial uses. Corn is one of the most widely grown crops in the world, and it is a major staple food for many cultures. Corn crops are grown in various regions of the world with different climates, soil types, and farming practices. In the United States, for example, the Midwest is known as the "Corn (...)
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  • Fine-tuning MobileNetV2 for Sea Animal Classification.Mohammed Marouf & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (4):44-50.
    Abstract: Classifying sea animals is an important problem in marine biology and ecology as it enables the accurate identification and monitoring of species populations, which is crucial for understanding and protecting marine ecosystems. This paper addresses the problem of classifying 19 different sea animals using convolutional neural networks (CNNs). The proposed solution is to use a pretrained MobileNetV2 model, which is a lightweight and efficient CNN architecture, and fine-tune it on a dataset of sea animals. The results of the study (...)
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  • Pistachio Variety Classification using Convolutional Neural Networks.Ahmed S. Sabah & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (4):113-119.
    Abstract: Pistachio nuts are a valuable source of nutrition and are widely cultivated for commercial purposes. The accurate classification of different pistachio varieties is important for quality control and market analysis. In this study, we propose a new model for the classification of different pistachio varieties using Convolutional Neural Networks (CNNs). We collected a dataset of pistachio images form Kaggle depository with two varieties (Kirmizi and Siirt). The images were then preprocessed and used to train a CNN model based on (...)
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  • Classification of Chicken Diseases Using Deep Learning.Mohammed Al Qatrawi & Samy S. Abu-Naser - 2024 - Information Journal of Academic Information Systems Research (Ijaisr) 8 (4):9-17.
    Abstract: In recent years, the outbreak of various poultry diseases has posed a significant threat to the global poultry industry. Therefore, the accurate and timely detection of chicken diseases is critical to reduce economic losses and prevent the spread of diseases. In this study, we propose a method for classifying chicken diseases using a convolutional neural network (CNN). The proposed method involves preprocessing the chicken images, building and training a CNN model, and evaluating the performance of the model. The dataset (...)
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  • The Role of the Practice of Excellence Strategies in Education to Achieve Sustainable Competitive Advantage to Institutions of Higher Education-Faculty of Engineering and Information Technology at Al-Azhar University in Gaza a Model.Mazen J. Al Shobaki & Samy S. Abu Naser - 2017 - International Journal of Digital Publication Technology 1 (2):135-157.
    This study aims to look at the role of the practice of excellence strategies in education in achieving sustainable competitive advantage for the Higher educational institutions of the faculty of Engineering and Information Technology at Al-Azhar University in Gaza, a model, and the study considered the competitive advantage of educational institutions stems from the impact on the level of each student, employee, and the institution. The study was based on the premise that the development of strategies for excellence in education, (...)
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  • Grape Leaf Species Classification Using CNN.Mohammed M. Almassri & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (4):66-72.
    Abstract: Context: grapevine leaves are an important agricultural product that is used in many Middle Eastern dishes. The species from which the grapevine leaf originates can differ in terms of both taste and price. Method: In this study, we build a deep learning model to tackle the problem of grape leaf classification. 500 images were used (100 for each species) that were then increased to 10,000 using data augmentation methods. Convolutional Neural Network (CNN) algorithms were applied to build this model (...)
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  • Classification of Apple Diseases Using Deep Learning.Ola I. A. Lafi & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (4):1-9.
    Abstract: In this study, we explore the challenge of identifying and preventing diseases in apple trees, which is a popular activity but can be difficult due to the susceptibility of these trees to various diseases. To address this challenge, we propose the use of Convolutional Neural Networks, which have proven effective in automatically detecting plant diseases. To validate our approach, we use images of apple leaves, including Apple Rot Leaves, Leaf Blotch, Healthy Leaves, and Scab Leaves collected from Kaggle which (...)
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  • Forest Fire Detection using Deep Leaning.Mosa M. M. Megdad & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (4):59-65.
    Abstract: Forests are areas with a high density of trees, and they play a vital role in the health of the planet. They provide a habitat for a wide variety of plant and animal species, and they help to regulate the climate by absorbing carbon dioxide from the atmosphere. While in 2010, the world had 3.92Gha of forest cover, covering 30% of its land area, in 2019, there was a loss of forest cover of 24.2Mha according to the Global Forest (...)
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  • Classification of Dates Using Deep Learning.Raed Z. Sababa & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (4):18-25.
    Abstract: Dates are the fruit of date palm trees, and it is one of the fruits famous for its high nutritional value. It is a summer fruit spread in the Arab world. In the past, the Arabs relied on it in their daily lives. Dates take an oval shape and vary in size from 20 to 60 mm in length and 8 to 30 mm in diameter. The ripe fruit consists of a hard core surrounded by a papery cover called (...)
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  • Using Deep Learning to Detect the Quality of Lemons.Mohammed B. Karaja & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (4):97-104.
    Abstract: Lemons are an important fruit that have a wide range of uses and benefits, from culinary to health to household and beauty applications. Deep learning techniques have shown promising results in image classification tasks, including fruit quality detection. In this paper, we propose a convolutional neural network (CNN)-based approach for detecting the quality of lemons by analysing visual features such as colour and texture. The study aims to develop and train a deep learning model to classify lemons based on (...)
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  • The Fast Food Image Classification using Deep Learning.Jehad El-Tantawi & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (4):37-43.
    Abstract: Fast food refers to quick, convenient, and ready-to-eat meals that are usually sold at chain restaurants or take-out establishments. Fast food is often criticized for its unhealthy ingredients, such as high levels of salt, sugar, and unhealthy fats, and its contribution to the growing obesity epidemic. Despite this, fast food remains popular due to its affordability, convenience, and widespread availability. Many fast food chains have attempted to respond to these criticisms by offering healthier options, such as salads and grilled (...)
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  • Tomato Leaf Diseases Classification using Deep Learning.Mohammed F. El-Habibi & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (4):73-80.
    Abstract: Tomatoes are among the most popular vegetables in the world due to their frequent use in many dishes, which fall into many varieties in common and traditional foods, and due to their rich ingredients such as vitamins and minerals, so they are frequently used on a daily basis, When we focus our attention on this vegetable, we must also focus and take into consideration the diseases that affect this vegetable, a deep learning model that classifies tomato diseases has been (...)
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  • Using Deep Learning to Classify Eight Tea Leaf Diseases.Mai R. Ibaid & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (4):89-96.
    Abstract: People all over the world have been drinking tea for thousands of centuries, and for good reason. Many types of teas can help you stay healthy by boosting your immune system, reducing inflammation, and even preventing cancer and heart disease. There is sufficient material to show that regularly consuming tea can improve your health over the long term. A deep learning model that categorizes tea disorders has been completed. When focusing on the tea, we must also focus on and (...)
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  • Measuring the Dominant Pattern of Leadership and Its Relation to the Functional Performance of Administrative Staff in Palestinian Universities.Ahmed M. A. FarajAllah, Suliman A. El Talla, Samy S. Abu-Naser & Mazen J. Al Shobaki - 2019 - International Journal of Information Technology and Electrical Engineering 7 (5):13-34.
    The study aimed at measuring the dominant pattern of leadership and its relation to the performance of the administrative staff in the Palestinian universities. The study community consists of all the administrative staff from Al-Azhar University and the Islamic University, and through the census of the study society it was found to consist of (655) administrative staff. In order to achieve the objectives of the study, the researchers used the method of random sample in the study, and the study was (...)
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  • Vegetable Classification Using Deep Learning.Mostafa El-Ghoul & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (4):105-112.
    Abstract: Vegetables are an essential component of a healthy diet and play a critical role in promoting overall health and well- being. Vegetables are rich in important vitamins and minerals, including vitamin C, folate, potassium, and iron. They also provide fiber, which helps maintain digestive health and prevent chronic diseases. We are proposing a deep learning model for the classification of vegetables. A dataset was collected from Kaggle depository for Vegetable with 15000 images for 15 different classes. The data was (...)
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  • The Reality of Using Social Networks in Technical Colleges in Palestine.Samy S. Abu-Naser, Mazen J. Al Shobaki, Youssef M. Abu Amuna & Suliman A. El Talla - 2018 - International Journal of Engineering and Information Systems (IJEAIS) 2 (1):142-158.
    The study aimed to identify the reality of the use of social networks in the technical colleges in Palestine, where the variables of social networks were included. The analytical descriptive method was used in the study. A questionnaire consisting of (12) items was randomly distributed to college workers Technology in the Gaza Strip. The sample of the study consisted of (205) employees of these colleges. The response rate was 74.5%. The results showed a high degree of approval for the dimensions (...)
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  • The Reality of Technical Education in Palestine.Suliman A. El Talla, Samy S. Abu-Naser, Mazen J. Al Shobaki & Youssef M. Abu Amuna - 2017 - International Journal of Engineering and Information Systems (IJEAIS) 1 (10):102-117.
    The study aimed to identify the reality of technical education in Palestine. The analytical descriptive method was used in the study. A questionnaire which consisted of 41 paragraphs was distributed randomly to the technical colleges in Gaza Strip. Random sample of (275) employees of these colleges were used, and the response rate was (74.5%). The results showed a high degree of approval for the dimensions of technical education with a relative weight of 76.07%. The ranking and relative weight was as (...)
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  • Identifying Fish Species Using Deep Learning Models on Image Datasets.Mohammed N. Jamala, Mohammed Al Deeb & Samy S. Abu-Naser - 2025 - International Journal of Academic Information Systems Research (IJAISR) 9 (1):1-9.
    Abstract: Accurate identification of marine species is critical for effective fishery management, biodiversity conservation, and the aquaculture industry. Traditional methods of fish identification rely on expert knowledge and manual labor, making them time- consuming, expensive, and error-prone. In this research, we explore a machine learning-based approach to automate the classification of nine fish species using image recognition techniques. The fish species under study include Black Sea Sprat, Gilt- Head Bream, Horse Mackerel, Red Sea Bream, Shrimp, Trout, Striped Red Mullet, Sea (...)
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  • The Reality of the Application of e-DMS in Governmental Institutions - an Empirical Study on the PPA.Mazen J. Al-Shobaki, Samy S. Abu-Naser & Mohammed Khair I. Kassab - 2017 - International Journal of Engineering and Information Systems 1 (2):1-14.
    The research aims to identify the status of the application of electronic document management system in governmental institutions – the study was applied on the Palestinian Pension Agency. The population of this study is composed of all employees in the Palestinian Pension Agency. In order to achieve the objectives of the study, the researchers used the descriptive and analytical approach, through which try to describe the phenomenon of the subject of the study, analyze the data and the relationship between the (...)
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  • Proposed Model for Learning Organization as an Entry to Organizational Excellence from the Standpoint of Teaching Staff in Palestinian Higher Educational Institutions in Gaza Strip.Amal A. Al Hila, Mazen J. Al Shobaki, Samy S. Abu-Naser & Youssef M. Abu Amuna - 2017 - International Journal of Education and Learning 6 (1):1-26.
    The research aims to design a proposed model of learning organizations as an entry point to achieve organizational excellence in the Palestinian universities of Gaza Strip. A random sample of workers were selected from the Palestinian universities consist of (286) employees at recovery rate of (70.3%). The study concluded with a set of results the most important of which: there is a statistically significant relationship between the components of learning organizations and achieving organizational excellence in the Palestinian universities of Gaza (...)
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  • The Degree of Administrative Transparency in the Palestinian HEI.Mazen J. Al-Shobaki, Samy S. Abu-Naser & Tarek M. Ammar - 2017 - International Journal of Engineering and Information Systems (IJEAIS) 1 (2):35-52.
    Abstract - The aim of the study is to identify the degree of administrative transparency in the Palestinian higher educational institutions in the Gaza Strip. In the study, the researchers adopted a descriptive and analytical method. The research population consisted of administrative staff, whether academic or administrative, except for those in senior management or the university council. The study population reached 392 employees. A random sample was selected (197). The number of questionnaires recovered was (160) with a recovery rate of (...)
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