Results for 'Mohammed M. Abu-Saqer'

964 found
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  1. Harnessing Artificial Intelligence for Effective Leadership: Opportunities and Challenges.Sabreen R. Qwaider, Mohammed M. Abu-Saqer, Islam Albatish, Azmi H. Alsaqqa, Basem S. Abunasser & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (8):6-11.
    Abstract: The integration of Artificial Intelligence (AI) into leadership practices is transforming organizational dynamics and This decision-making processes. paper explores how AI can enhance leadership effectiveness by providing data-driven insights, optimizing decision-making, and automating routine tasks. It also examines the challenges leaders face in adopting AI, including ethical considerations, potential biases in AI systems, and the need for upskilling. By analyzing current applications of AI in leadership and discussing future trends, this study aims to provide a comprehensive overview of the (...)
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  2. 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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  3. 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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  4. Impact of Applying Fraud Detection and Prevention Instruments in Reducing Occupational Fraud: Case study: Ministry of Health (MOH) in Gaza Strip.Faris M. Abu Mouamer, Youssef M. Abu Amuna, Mohammed K. H. A. L. I. Khalil & Abedallh Aqel - 2020 - International Journal of Academic Accounting, Finance and Management Research (IJAAFMR) 4 (6):35-45.
    The study aimed to identify the effect of applying detection and prevention tools for career fraud in combating and preventing fraud and reducing its risks through an applied study on Palestinian Ministry of Health in Gaza Strip, Palestine. To achieve the objectives of the study, the researchers used the questionnaire as a main tool to collect data, and the descriptive and analytical approach to conducting the study. The study population consisted of (501) supervisory employees working at MOH in Gaza Strip, (...)
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  5. AI in HRM: Revolutionizing Recruitment, Performance Management, and Employee Engagement.Mostafa El-Ghoul, Mohammed M. Almassri, Mohammed F. El-Habibi, Mohanad H. Al-Qadi, Alaa Abou Eloun, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2024 - International Journal of Academic Applied Research (Ijaar) 8 (9):16-23.
    Artificial Intelligence (AI) is rapidly transforming Human Resource Management (HRM) by enhancing the efficiency and effectiveness of key functions such as recruitment, performance management, and employee engagement. This paper explores the integration of AI technologies in HRM, focusing on their potential to revolutionize these critical areas. In recruitment, AI-driven tools streamline candidate sourcing, screening, and selection processes, leading to more accurate and unbiased hiring decisions. Performance management is similarly transformed, with AI enabling continuous, data-driven feedback and personalized development plans that (...)
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  6. Mango Pests Identification Expert System.Jehad M. Altayeb, Samy S. Abu-Naser, Shahd J. Albadrasawi & Mohammed M. Almzainy - 2023 - International Journal of Engineering and Information Systems (IJEAIS) 7 (6):19-26.
    Mango is an economically significant fruit crop cultivated in various tropical and subtropical regions around the world. However, the productivity and quality of mangoes can be severely impacted by a range of pests. This research paper introduces an innovative approach to identify mango pests using an expert system. The expert system integrates knowledge from entomology and plants to provide accurate identification of common mango pests. The paper outlines the development and implementation of the expert system using Clips shell, which utilizes (...)
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  7. (1 other version)Development and Evaluation of an Expert System for Diagnosing Kidney Diseases.Shahd J. Albadrasawi, Mohammed M. Almzainy, Jehad M. Altayeb, Hassam Eleyan & Samy S. Abu-Naser - 2023 - International Journal of Academic Engineering Research (IJAER) 7 (6):16-22.
    This research paper presents the development and evaluation of an expert system for diagnosing kidney diseases. The expert system utilizes a decision-making tree approach and is implemented using the CLIPS and Delphi frameworks. The system's accuracy in diagnosing kidney diseases and user satisfaction were evaluated. The results demonstrate the effectiveness of the expert system in providing accurate diagnoses and high user satisfaction.
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  8. Expert System for Hair Loss Diagnosis and Treatment Using CLIPS.Mohammed Hazem M. Hamadaqa & Samy S. Abu-Naser - 2021 - International Journal of Academic Engineering Research (IJAER) 5 (5):37-42.
    Abstract: Background: Hair loss is often a concern for women, men and children. It is normal to lose between 50 and 100 hairs a day, without us noticing it. Usually hair loss is a sign of a medical condition, some of them are hereditary, and some of them are temporary due to disease, stress, cancer treatment, weight loss, and iron deficiency. Objectives: The main goal of this expert system is to obtain an appropriate diagnosis of the cause of hair loss. (...)
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  9.  66
    Harnessing Artificial Intelligence to Enhance Medical Image Analysis.Malak S. Hamad, Mohammed H. Aldeeb, Mohammed M. Almzainy, Shahd J. Albadrasawi, Musleh M. Musleh, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2024 - International Journal of Academic Health and Medical Research (IJAHMR) 8 (9):1-7.
    Abstract: The integration of Artificial Intelligence (AI) into medical imaging marks a transformative advancement in healthcare, significantly enhancing diagnostic accuracy, efficiency, and patient outcomes. This paper delves into the application of AI technologies in medical image analysis, with a particular focus on techniques such as convolutional neural networks (CNNs) and deep learning models. We examine how these technologies are employed across various imaging modalities, including X-rays, MRIs, and CT scans, to improve disease detection, image segmentation, and diagnostic support. Furthermore, the (...)
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  10. 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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  11. Transforming Human Resource Management: The Impact of Artificial Intelligence on Recruitment and Beyond.Hazem A. S. Alrakhawi, Randa Elqassas, Mohammed M. Elsobeihi, Basel Habil, Basem S. Abunasser & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (8):1-5.
    Abstract: The integration of Artificial Intelligence (AI) into Human Resource Management (HRM) is fundamentally transforming how organizations approach recruitment, performance management, and employee engagement. This paper explores the multifaceted impact of AI on HR practices, highlighting its role in enhancing efficiency, reducing bias, and driving strategic decision-making. Through an in-depth analysis of AI-driven recruitment tools, performance management systems, and personalized employee engagement strategies, this study examines both the opportunities and challenges associated with AI in HRM. Ethical considerations, including data privacy, (...)
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  12. Rule Based System for Diagnosing Bean Diseases and Treatment.Mohammed H. S. Abueleiwa, Fadi E. S. Harara, Mustafa M. K. Al-Ghoul, Sami M. Okasha & Samy S. Abu-Naser - 2022 - International Journal of Engineering and Information Systems (IJEAIS) 6 (5):67-74.
    Background: A bean is the seed of one of several genera of the flowering plant family Fabaceae, which are used as vegetables for human or animal food. They can be cooked in many different ways, including boiling, frying, and baking, and are used in many traditional dishes throughout the world. Beans are one of the longest-cultivated plants. Broad beans, also called fava beans, in their wild state the size of a small fingernail, were gathered in Afghanistan and the Himalayan foothills. (...)
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  13. Design Thinking and Its Use in NGOs in Gaza Strip.Rasha O. Owda, Maram Owda, Mohammed N. Abed, Samia A. M. Abdalmenem, Samy S. Abu-Naser & Mazen J. Al Shobaki - 2019 - International Journal of Academic Multidisciplinary Research (IJAMR) 3 (7):41-52.
    The study aimed to identify Design Thinking and its use in NGOs in Gaza Strip. In order to achieve the objectives of the study and to test its hypotheses, the analytical descriptive method was used, relying on the questionnaire as a main tool for data collection. The study society was one of the decision makers in the local NGOs in the Gaza Strip. The study population reached 78 local NGOs in Gaza Strip. The overall inventory of the possible study community (...)
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  14. Learning Computer Networks Using Intelligent Tutoring System.Mones M. Al-Hanjori, Mohammed Z. Shaath & Samy S. Abu Naser - 2017 - International Journal of Advanced Research and Development 2 (1).
    Intelligent Tutoring Systems (ITS) has a wide influence on the exchange rate, education, health, training, and educational programs. In this paper we describe an intelligent tutoring system that helps student study computer networks. The current ITS provides intelligent presentation of educational content appropriate for students, such as the degree of knowledge, the desired level of detail, assessment, student level, and familiarity with the subject. Our Intelligent tutoring system was developed using ITSB authoring tool for building ITS. A preliminary evaluation of (...)
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  15. The Reality of Decision Making in NGOs in Gaza Strip.Rasha O. Owda, Maram Owda, Mohammed N. Abed, Samia A. M. Abdalmenem, Samy S. Abu-Naser & Mazen J. Al Shobaki - 2019 - International Journal of Academic Multidisciplinary Research (IJAMR) 3 (8):1-10.
    The study aimed to identify the reality of decision-making in the local NGOs in Gaza Strip. In order to achieve the objectives of the study and to test its hypotheses, the analytical descriptive method was used, relying on the questionnaire as a main tool for data collection. The study society was one of the decision makers in the local NGOs in Gaza Strip. The study population reached 78 local NGOs in Gaza Strip. A Census Method of the possible study community (...)
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  16. Personal Variables and Their Impact on Promoting Job Creation in Gaza Strip through Business Incubators.Maram O. Owda, Rasha O. Owda, Mohammed N. Abed, Samia A. M. Abdalmenem, Samy S. Abu-Naser & Mazen J. Al Shobaki - 2019 - International Journal of Academic Accounting, Finance and Management Research (IJAAFMR) 3 (8):65-77.
    The study aimed at identifying the personal variables and their effect in promoting job creation in Gaza Strip through business incubators. The researchers used the descriptive analytical approach to achieve the study objectives. The study population consisted of 92 of the pilot projects benefiting from the three business incubators in Gaza Strip (Palestinian Information Technology Incubator, UCAS Technology Incubator and Business and Technology Incubator). The study reached a number of results, the most important of which are the existence of statistically (...)
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  17. 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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  18. AI in Leadership: Transforming Decision-Making and Strategic Vision.Mohran H. Al-Bayed, Mohanad Hilles, Ibrahim Haddad, Marah M. Al-Masawabe, Mohammed Ibrahim Alhabbash, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2024 - International Journal of Academic Pedagogical Research (IJAPR) 8 (9):1-7.
    Abstract: The integration of Artificial Intelligence (AI) into leadership practices is rapidly transforming organizational dynamics and decision-making processes. This paper explores the ways in which AI enhances leadership effectiveness by providing data- driven insights, optimizing decision-making, and automating routine tasks. Additionally, it examines the challenges leaders face when adopting AI, including ethical considerations, potential biases in AI systems, and the need for upskilling. By analyzing current applications of AI in leadership and discussing future trends, this study aims to offer a (...)
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  19. Advancements in Early Detection of Breast Cancer: Innovations and Future Directions.Izzeddin A. Alshawwa, Hosni Qasim El-Mashharawi, Fatima M. Salman, Mohammed Naji Abu Al-Qumboz, Bassem S. Abunasser & Samy S. Abu-Naser - 2024 - International Journal of Academic Engineering Research (IJAER) 8 (8):15-24.
    Abstract: Early detection of breast cancer plays a pivotal role in improving patient prognosis and reducing mortality rates. Recent technological advancements have significantly enhanced the accuracy and effectiveness of breast cancer screening methods. This paper explores the latest innovations in early detection, including the evolution of digital mammography, the impact of 3D mammography (tomosynthesis), and the use of advanced imaging techniques such as molecular imaging and MRI. Furthermore, the integration of artificial intelligence (AI) in diagnostic tools is discussed, highlighting how (...)
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  20. Leveraging Artificial Intelligence for Strategic Business Decision-Making: Opportunities and Challenges.Mohammed Hazem M. Hamadaqa, Mohammad Alnajjar, Mohammed N. Ayyad, Mohammed A. Al-Nakhal, Basem S. Abunasser & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 8 (8):16-23.
    Abstract: Artificial Intelligence (AI) has rapidly evolved, offering transformative capabilities for business decision-making. This paper explores how AI can be leveraged to enhance strategic decision-making in business contexts. It examines the integration of AI-driven analytics, predictive modeling, and automation to improve decision accuracy and operational efficiency. By analyzing current applications and case studies, the paper highlights the opportunities AI presents, including enhanced data insights, risk management, and personalized customer experiences. Additionally, it addresses the challenges businesses face in adopting AI, such (...)
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  21. Artificial Intelligence in Agriculture: Enhancing Productivity and Sustainability.Mohammed A. Hamed, Mohammed F. El-Habib, Raed Z. Sababa, Mones M. Al-Hanjor, Basem S. Abunasser & Samy S. Abu-Naser - 2024 - International Journal of Engineering and Information Systems (IJEAIS) 8 (8):1-8.
    Abstract: Artificial Intelligence (AI) is revolutionizing the agricultural sector by enhancing productivity and sustainability. This paper explores the transformative impact of AI technologies on agriculture, focusing on their applications in precision farming, predictive analytics, and automation. AI-driven tools enable more efficient management of crops and resources, leading to improved yields and reduced environmental impact. The paper examines key AI technologies, including machine learning algorithms for crop monitoring, robotics for automated planting and harvesting, and data analytics for optimizing resource use. Additionally, (...)
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  22. 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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  23. AI-Driven Organizational Change: Transforming Structures and Processes in the Modern Workplace.Mohammed Elkahlout, Mohammed B. Karaja, Abeer A. Elsharif, Ibtesam M. Dheir, Basem S. Abunasser & Samy S. Abu-Naser - 2024 - Information Journal of Academic Information Systems Research (Ijaisr) 8 (8):38-45.
    Abstract: Artificial Intelligence (AI) is revolutionizing organizational dynamics by reshaping both structures and processes. This paper explores how AI-driven innovations are transforming organizational frameworks, from hierarchical adjustments to decentralized decision-making models. It examines the impact of AI on various processes, including workflow automation, data analysis, and enhanced decision support systems. Through case studies and empirical research, the paper highlights the benefits of AI in improving efficiency, driving innovation, and fostering agility within organizations. Additionally, it addresses the challenges associated with AI (...)
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  24. 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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  25. A Proposed Expert System for Obstetrics & Gynecology Diseases Diagnosis.Mohammed F. El-Habibi, Mosa M. M. Megdad, Mohanad H. Al-Qadi, Mohammed J. A. AlQatrawi, Raed Z. Sababa & Samy S. Abu-Naser - 2022 - International Journal of Academic Multidisciplinary Research (IJAMR) 6 (5):305-321.
    Background: Obstetrics and gynaecology are many and common, where a woman suffers from problems related to pregnancy or her reproductive organs. Any part of her body may be affected due to some symptoms that are completely related to the reproductive organs when she is in a critical period for her, whether in her menstrual cycle, pregnancy, or disease conditions. The bulk of cases of diseases related to women and childbirth are dealt with great care and special care, as all diseases (...)
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  26. 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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  27. Ethics in AI: Balancing Innovation and Responsibility.Mosa M. M. Megdad, Mohammed H. S. Abueleiwa, Mohammed Al Qatrawi, Jehad El-Tantaw, Fadi E. S. Harara, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2024 - International Journal of Academic Pedagogical Research (IJAPR) 8 (9):20-25.
    Abstract: As artificial intelligence (AI) technologies become more integrated across various sectors, ethical considerations in their development and application have gained critical importance. This paper delves into the complex ethical landscape of AI, addressing significant challenges such as bias, transparency, privacy, and accountability. It explores how these issues manifest in AI systems and their societal impact, while also evaluating current strategies aimed at mitigating these ethical concerns, including regulatory frameworks, ethical guidelines, and best practices in AI design. Through a comprehensive (...)
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  28. Developing an Expert System to Diagnose Tomato Diseases.Mohanad H. Al-Qadi, Mohammed F. El-Habibi, Mosa M. M. Megdad, Mohammed J. A. AlQatrawi, Raed Z. Sababa & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (5):34-40.
    There is no doubt that tomato diseases are one of the important reasons that destroy the tomato plant and its crops. This leads to clear 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 to avoid damage to these plants. The expert system diagnoses tomato disease correctly to facilitate farmers (...)
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  29. Improving By Ball Burnishing For Internal Turned Surfaces.Asmaa Tharwat Mohammed, Muahmmad Muhammad El-Sayed Kesba & Fayez El-Saied Abu-Gharbia - 2018 - International Journal of Engineering and Information Systems (IJEAIS) 2 (8):39-50.
    Abstract: The paper presented is a work started in summer 2014 for improving surfaces of turned holes. The work was confined to two materials; aluminum alloy and brass alloy. The internal machined surfaces were burnished by ball burnishing tools. Experimental work was carried out on a lathe machine to establish the effect of the internal ball burnishing parameters; namely, burnishing feed rate, speed, force and number of tool passes on the Surface roughness and surface hardness. The operation was carried out (...)
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  30. AI and Ethics in Surveillance: Balancing Security and Privacy in a Digital World.Msbah J. Mosa, Alaa M. Barhoom, Mohammed I. Alhabbash, Fadi E. S. Harara, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2024 - International Journal of Academic Engineering Research (IJAER) 8 (10):8-15.
    Abstract: In an era of rapid technological advancements, artificial intelligence (AI) has transformed surveillance systems, enhancing security capabilities across the globe. However, the deployment of AI-driven surveillance raises significant ethical concerns, particularly in balancing the need for security with the protection of individual privacy. This paper explores the ethical challenges posed by AI surveillance, focusing on issues such as data privacy, consent, algorithmic bias, and the potential for mass surveillance. Through a critical analysis of the tension between security and privacy, (...)
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  31. 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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  32. 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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  33. ITS for Enhancing Training Methodology for Students Majoring in Electricity.Mohammed S. Nassr & Samy S. Abu-Naser - 2019 - International Journal of Academic Pedagogical Research (IJAPR) 3 (3):16-30.
    This thesis focuses on the use of intelligent tutoring system for education and training of students specialized in electricity in the field of technical and vocational education. The use of modern systems in training and education will have a great positive impact in improving the level of students receiving training and education; this will improve the level of the local economy by producing students of professionals who are able to engage in society efficiently, especially for those who have specialized in (...)
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  34. 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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  35. Adaptive Intelligent Tutoring System for learning Computer Theory.Mohammed A. Al-Nakhal & Samy S. Abu Naser - 2017 - European Academic Research 4 (10).
    In this paper, we present an intelligent tutoring system developed to help students in learning Computer Theory. The Intelligent tutoring system was built using ITSB authoring tool. The system helps students to learn finite automata, pushdown automata, Turing machines and examines the relationship between these automata and formal languages, deterministic and nondeterministic machines, regular expressions, context free grammars, undecidability, and complexity. During the process the intelligent tutoring system gives assistance and feedback of many types in an intelligent manner according to (...)
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  36. An Intelligent Tutoring System for Teaching the 7 Characteristics for Living Things.Mohammed A. Hamed & Samy S. Abu Naser - 2017 - International Journal of Advanced Research and Development 2 (1):31-35.
    Recently, due to the rapid progress of computer technology, researchers develop an effective computer program to enhance the achievement of the student in learning process, which is Intelligent Tutoring System (ITS). Science is important because it influences most aspects of everyday life, including food, energy, medicine, leisure activities and more. So learning science subject at school is very useful, but the students face some problem in learning it. So we designed an ITS system to help them understand this subject easily (...)
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  37. Neural Network-Based Water Quality Prediction.Mohammed Ashraf Al-Madhoun & Samy S. Abu-Naser - 2023 - International Journal of Academic Information Systems Research (IJAISR) 7 (9):25-31.
    Water quality assessment is critical for environmental sustainability and public health. This research employs neural networks to predict water quality, utilizing a dataset of 21 diverse features, including metals, chemicals, and biological indicators. With 8000 samples, our neural network model, consisting of four layers, achieved an impressive 94.22% accuracy with an average error of 0.031. Feature importance analysis revealed arsenic, perchlorate, cadmium, and others as pivotal factors in water quality prediction. This study offers a valuable contribution to enhancing water quality (...)
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  38. Knowledge Based System for Diagnosing Lung Cancer Diagnosis and Treatment.Mohammed N. Jamala & Samy S. Abu-Naser - 2023 - International Journal of Academic Information Systems Research (IJAISR) 7 (6):38-45.
    Lung cancer is a serious and deadly disease that affects the lungs, which are responsible for taking in oxygen and expelling carbon dioxide from the body. The disease can develop in any part of the lungs and is usually caused by smoking or exposure to certain chemicals. The main Objective: of this expert system is to provide an accurate diagnosis of lung cancer and the appropriate treatment options. In this paper, Methods: we present the design and implementation of an expert (...)
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  39. 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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  40. 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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  41. 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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  42. Predictive Modeling of Obesity and Cardiovascular Disease Risk: A Random Forest Approach.Mohammed S. Abu Nasser & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 7 (12):26-38.
    Abstract: This research employs a Random Forest classification model to predict and assess obesity and cardiovascular disease (CVD) risk based on a comprehensive dataset collected from individuals in Mexico, Peru, and Colombia. The dataset comprises 17 attributes, including information on eating habits, physical condition, gender, age, height, and weight. The study focuses on classifying individuals into different health risk categories using machine learning algorithms. Our Random Forest model achieved remarkable performance with an accuracy, F1-score, recall, and precision all reaching 97.23%. (...)
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  43. 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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  44. Breast Cancer Knowledge Based System.Mohammed H. Aldeeb & Samy S. Abu-Naser - 2023 - International Journal of Engineering and Information Systems 7 (6):46-51.
    Abstract: The Knowledge-Based System for Diagnosing Breast Cancer aims to support medical students in enhancing their education regarding diagnosis and counseling. The system facilitates the analysis of biopsy images under a microscope, determination of tumor type, selection of appropriate treatment methods, and identification of disease-related questions. According to the Ministry of Health's annual report in Gaza, there were 7,069 cases of breast cancer between 2009 and 2014, with 1,502 cases reported in 2014. In an era dominated by visual information, where (...)
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  45. 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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  46. 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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  47. Artificial Neural Network for Predicting COVID 19 Using JNN.Walaa Hasan, Mohammed S. Abu Nasser, Mohammed A. Hasaballah & Samy S. Abu-Naser - 2023 - International Journal of Academic Engineering Research (IJAER) 7 (10):41-47.
    Abstract: The emergence of the novel coronavirus (COVID-19) in 2019 has presented the world with an unprecedented global health crisis. The rapid and widespread transmission of the virus has strained healthcare systems, disrupted economies, and challenged societies. In response to this monumental challenge, the intersection of technology and healthcare has become a focal point for innovation. This research endeavors to leverage the capabilities of Artificial Neural Networks (ANNs) to develop an advanced predictive model for forecasting the spread of COVID-19. It (...)
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  48. An intelligent tutoring system for teaching advanced topics in information security.Ali O. Mahdi, Mohammed I. Alhabbash & Samy S. Abu Naser - 2016 - World Wide Journal of Multidisciplinary Research and Development 2 (12):1-9.
    Recently there is an increasing technological development in intelligent tutoring systems. This field has become interesting to many researchers. In this paper, we present an intelligent tutoring system for teaching information security. This intelligent tutoring systems target the students enrolled in Advanced Topics in Information Security in the faculty of Engineering and Information Technology at Al-Azhar University in Gaza. Through which the student will be able to study the course and solve related problems. An evaluation of the intelligent tutoring systems (...)
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  49. 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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  50. Leveraging Artificial Neural Networks for Cancer Prediction: A Synthetic Dataset Approach.Mohammed S. Abu Nasser & Samy S. Abu-Naser - 2023 - International Journal of Academic Engineering Research (IJAER) 7 (11):43-51.
    Abstract: This research explores the application of artificial neural networks (ANNs) in predicting cancer using a synthetically generated dataset designed for research purposes. The dataset comprises 10,000 pseudo-patient records, each characterized by gender, age, smoking history, fatigue, and allergy status, along with a binary indicator for the presence or absence of cancer. The 'Gender,' 'Smoking,' 'Fatigue,' and 'Allergy' attributes are binary, while 'Age' spans a range from 18 to 100 years. The study employs a three-layer ANN architecture to develop a (...)
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