Results for 'Nasser Said Gomaa Abdelrasheed'

947 found
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  1. (10 other versions)Collected Papers (on Neutrosophic Theory and Applications), Volume VI.Florentin Smarandache - 2022 - Miami, FL, USA: Global Knowledge.
    This sixth volume of Collected Papers includes 74 papers comprising 974 pages on (theoretic and applied) neutrosophics, written between 2015-2021 by the author alone or in collaboration with the following 121 co-authors from 19 countries: Mohamed Abdel-Basset, Abdel Nasser H. Zaied, Abduallah Gamal, Amir Abdullah, Firoz Ahmad, Nadeem Ahmad, Ahmad Yusuf Adhami, Ahmed Aboelfetouh, Ahmed Mostafa Khalil, Shariful Alam, W. Alharbi, Ali Hassan, Mumtaz Ali, Amira S. Ashour, Asmaa Atef, Assia Bakali, Ayoub Bahnasse, A. A. Azzam, Willem K.M. Brauers, (...)
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  2.  73
    Artificial Intelligence in Digital Media: Opportunities, Challenges, and Future Directions.Basma S. Abu Nasser & Samy S. Abu-Naser - 2024 - International Journal of Academic and Applied Research (IJAAR) 8 (6):1-10.
    Abstract: This research paper explores the transformative impact of artificial intelligence (AI) on digital media, examining both the opportunities it presents and the challenges it poses. The integration of AI into digital media has revolutionized content creation, distribution, and analytics, offering unprecedented levels of personalization, efficiency, and insight. Automated journalism, AI- driven recommendation systems, and advanced audience analytics are among the key areas where AI is making significant contributions. However, the adoption of AI also brings ethical considerations, including concerns about (...)
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  3. 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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  4. 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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  5. 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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  6. Structural and Magnetic Properties of Laxsr1-Xmno3.A. A. Gomaa & A. A. Mohamed - 2018 - International Journal of Engineering and Information Systems (IJEAIS) 2 (12):1-4.
    Abstract: Samples of LaxSr1-xMnO3 (x = 0.5, 0.55, 0.6, 0.66, and 0.7) were prepared by the citrate-nitrate autocombustion method. The prepared nano-particles were investigated and characterized using X-Ray diffraction (XRD) and Transmission Electron Microscopy (TEM) to confirm the formation of the samples in single phase without any impurities and to calculate the particle size. The magnetic susceptibility χM was measured as a function of temperature and magnetic field intensity. From χM(T) and M(H) the saturation magnetization (Ms), remanent magnetization (Mr) and (...)
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  7. Implications and Applications of Artificial Intelligence in the Legal Domain.Besan S. Abu Nasser, Marwan M. Saleh & Samy S. Abu-Naser - 2024 - International Journal of Academic Information Systems Research (IJAISR) 7 (12):18-25.
    Abstract: As the integration of Artificial Intelligence (AI) continues to permeate various sectors, the legal domain stands on the cusp of a transformative era. This research paper delves into the multifaceted relationship between AI and the law, scrutinizing the profound implications and innovative applications that emerge at the intersection of these two realms. The study commences with an examination of the current landscape, assessing the challenges and opportunities that AI presents within legal frameworks. With an emphasis on efficiency, accuracy, and (...)
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  8. 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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  9. 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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  10. 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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  11. (1 other version)Sarcasm Detection in Headline News using Machine and Deep Learning Algorithms.Alaa Barhoom, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2022 - International Journal of Engineering and Information Systems (IJEAIS) 6 (4):66-73.
    Abstract: Sarcasm is commonly used in news and detecting sarcasm in headline news is challenging for humans and thus for computers. The media regularly seem to engage sarcasm in their news headline to get the attention of people. However, people find it tough to detect the sarcasm in the headline news, hence receiving a mistaken idea about that specific news and additionally spreading it to their friends, colleagues, etc. Consequently, an intelligent system that is able to distinguish between can sarcasm (...)
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  12. Streamlined Book Rating Prediction with Neural Networks.Lana Aarra, Mohammed S. Abu Nasser, Mohammed A. Hasaballah & Samy S. Abu-Naser - 2023 - International Journal of Engineering and Information Systems (IJEAIS) 7 (10):7-13.
    Abstract: Online book review platforms generate vast user data, making accurate rating prediction crucial for personalized recommendations. This research explores neural networks as simple models for predicting book ratings without complex algorithms. Our novel approach uses neural networks to predict ratings solely from user-book interactions, eliminating manual feature engineering. The model processes data, learns patterns, and predicts ratings. We discuss data preprocessing, neural network design, and training techniques. Real-world data experiments show the model's effectiveness, surpassing traditional methods. This research can (...)
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  13. 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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  14. 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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  15. Prediction Heart Attack using Artificial Neural Networks (ANN).Ibrahim Younis, Mohammed S. Abu Nasser, Mohammed A. Hasaballah & Samy S. Abu-Naser - 2023 - International Journal of Engineering and Information Systems (IJEAIS) 7 (10):36-41.
    Abstract Heart Attack is the Cardiovascular Disease (CVD) which causes the most deaths among CVDs. We collected a dataset from Kaggle website. In this paper, we propose an ANN model for the predicting whether a patient has a heart attack or not that. The dataset set consists of 9 features with 1000 samples. We split the dataset into training, validation, and testing. After training and validating the proposed model, we tested it with testing dataset. The proposed model reached an accuracy (...)
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  16. Michel Foucault’s Concept of ‘Critique’ and the Iranian Experience.Nasser Amin - 2022 - Islamic Perspective: Journal of the Islamic Studies and Humanities 27:47-64.
    This paper offers an interpretation and discussion of the later Foucault’s multifaceted concept of ‘critique’. It argues that critique for Foucault is composed of three main elements: the ‘spirit’ (though not all of the substance) of Kant’s understanding of the Enlightenment; the practice of parrhesia that emerged in Ancient Greece and became central to Christian subjectivity; and the transfigurative aesthetic experience of modernity that was most richly depicted by Baudelaire. In the second section, there is a discussion of Foucault’s view (...)
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  17. 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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  18. 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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  19. 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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  20. 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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  21. 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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  22. Gender Prediction from Retinal Fundus Using Deep Learning.Ashraf M. Taha, Qasem M. M. Zarandah, Bassem S. Abu-Nasser, Zakaria K. D. AlKayyali & Samy S. Abu-Naser - 2022 - International Journal of Academic Information Systems Research (IJAISR) 6 (5):57-63.
    Deep learning may transform health care, but model development has largely been dependent on availability of advanced technical expertise. The aim of this study is to develop a deep learning model to predict the gender from retinal fundus images. The proposed model was based on the Xception pre-trained model. The proposed model was trained on 20,000 retinal fundus images from Kaggle depository. The dataset was preprocessed them split into three datasets (training, validation, Testing). After training and cross-validating the proposed model, (...)
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  23. Rough Neutrosophic Sets.Said Broumi, Florentin Smarandache & Mamoni Dhar - 2014 - Neutrosophic Sets and Systems 3:60-65.
    Both neutrosophic sets theory and rough sets theory are emerging as powerful tool for managing uncertainty, indeterminate, incomplete and imprecise information .In this paper we develop an hybrid structure called “ rough neutrosophic sets” and studied their properties.
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  24. 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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  25. (1 other version)Prediction of Heart Disease Using a Collection of Machine and Deep Learning Algorithms.Ali M. A. Barhoom, Abdelbaset Almasri, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2022 - International Journal of Engineering and Information Systems (IJEAIS) 6 (4):1-13.
    Abstract: Heart diseases are increasing daily at a rapid rate and it is alarming and vital to predict heart diseases early. The diagnosis of heart diseases is a challenging task i.e. it must be done accurately and proficiently. The aim of this study is to determine which patient is more likely to have heart disease based on a number of medical features. We organized a heart disease prediction model to identify whether the person is likely to be diagnosed with a (...)
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  26. 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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  27. 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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  28. Several Similarity Measures of Neutrosophic Sets.Said Broumi & Florentin Smarandache - 2013 - Neutrosophic Sets and Systems 1:54-62.
    Smarandache (1995) defined the notion of neutrosophic sets, which is a generalization of Zadeh's fuzzy set and Atanassov's intuitionistic fuzzy set. In this paper, we first develop some similarity measures of neutrosophic sets. We will present a method to calculate the distance between neutrosophic sets (NS) on the basis of the Hausdorff distance. Then we will use this distance to generate a new similarity measure to calculate the degree of similarity between NS. Finally we will prove some properties of the (...)
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  29. Isolated Single Valued Neutrosophic Graphs.Said Broumi, Assia Bakali, Mohamed Talea & Florentin Smarandache - 2015 - Neutrosophic Sets and Systems 11:74-78.
    Many results have been obtained on isolated graphs and complete graphs. In this paper, a necessary and sufficient condition will be proved for a single valued neutrosophic graph to be an isolated single valued neutrosophic graph.
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  30. Interval Neutrosophic Rough Sets.Said Broumi & Florentin Smarandache - 2015 - Neutrosophic Sets and Systems 7:23-31.
    This Paper combines interval- valued neutrouphic sets and rough sets. It studies roughness in interval- valued neutrosophic sets and some of its properties. Finally we propose a Hamming distance between lower and upper approximations of interval valued neutrosophic sets.
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  31. Afghan EFL Lecturers’ Perceptions of Code-Switching.Abdullah Noori & Nasser Rasoly - 2017 - International Journal for Innovative Research in Multidisciplinary Field 3 (12):52-58.
    Code-switching is explained as switching between two languages at the same time while conversing in the same discourse. The aim of this study is to explore the perceptions of Afghan EFL lecturers toward code- switching. This study used a qualitative research approach in which the data was collected via semi-structured interviews with five EFL lecturers. The lecturers were interviewed to explore their perceptions and reasons for code-switching, and the extent to which they practice code-switching in their classrooms. The results revealed (...)
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  32. Neutrosophic Integer Programming Problem.Mai Mohamed, Mohamed Abdel-Basset, Abdel Nasser Zaied & Florentin Smarandache - 2017 - Neutrosophic Sets and Systems 15:3-7.
    In this paper, we introduce the integer programming in neutrosophic environment, by considering coffecients of problem as a triangulare neutrosophic numbers. The degrees of acceptance, indeterminacy and rejection of objectives are simultaneously considered. The Neutrosophic Integer Programming Problem (NIP) is transformed into a crisp programming model, using truth membership (T), indeterminacy membership (I), and falsity membership (F) functions as well as single valued triangular neutrosophic numbers. To measure the efficiency of the model, we solved several numerical examples.
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  33. Russell's 1927 The Analysis of Matter as the First Book on Quantum Gravity.Said Mikki - manuscript
    The goal of this note is to bring into wider attention the often neglected important work by Bertrand Russell on the foundations of physics published in the late 1920s. In particular, we emphasize how the book The Analysis of Matter can be considered the earliest systematic attempt to unify the modern quantum theory, just emerging by that time, with general relativity. More importantly, it is argued that the idea of what I call Russell space, introduced in Part III of that (...)
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  34. Cosine Similarity Measure of Interval Valued Neutrosophic Sets.Said Broumi & Florentin Smarandache - 2014 - Neutrosophic Sets and Systems 5:15-20.
    In this paper, we define a new cosine similarity between two interval valued neutrosophic sets based on Bhattacharya’s distance [19]. The notions of interval valued neutrosophic sets (IVNS, for short) will be used as vector representations in 3D-vector space. Based on the comparative analysis of the existing similarity measures for IVNS, we find that our proposed similarity measure is better and more robust. An illustrative example of the pattern recognition shows that the proposed method is simple and effective.
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  35. Art, Philosophy, and Creativity.Said Mikki - manuscript
    We reflect on the nature of art, the creative process, and the connection between art and philosophy.
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  36. Art and Objects: A Manifesto.Said Mikki - manuscript
    We develop a series of theses on the philosophical aesthetics of design art. A sketch of an outline of a theory of objects is drawn from within a naturalistic worldview, that of abstract materialism and the general, still ongoing, quest to build a comprehensive philosophy of nature encompassing not only the physical world, but also culture, art, and politics.
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  37. The Historical Lifeworld of Event Ontology.Said Mikki -
    We develop a new understanding of the historical horizon of event ontology. Within the general area of the philosophy of nature, event ontology is a still emerging field of investigation in search for the ultimate materialist ontology of the world. While event ontology itself will not be explicated in full mathematical details here, our focus is on its conceptual interrelation with the dominant current of Idealism in Western thought approached by us as a problem in the history of ideas. Our (...)
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  38. A Bipolar Single Valued Neutrosophic Isolated Graphs: Revisited.Said Broumi, Assia Bakali, Mohamed Talea, Florentin Smarandache & Mohsin Khan - 2017 - International Journal of New Computer Architectures and Their Applications 7 (3):89-94.
    In this research paper, the graph of the bipolar single-valued neutrosophic set model (BSVNS) is proposed. The graphs of single valued neutrosophic set models is generalized by this graph. For the BSVNS model, several results have been proved on complete and isolated graphs. Adding, an important and suitable condition for the graphs of the BSVNS model to become an isolated graph of the BSVNS model has been demonstrated.
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  39. Neutrosophic Refined Similarity Measure Based on Cosine Function.Said Broumi & Florentin Smarandache - 2014 - Neutrosophic Sets and Systems 6:42-48.
    In this paper, the cosine similarity measure of neutrosophic refined (multi-) sets is proposed and its properties are studied. The concept of this cosine similarity measure of neutrosophic refined sets is the extension of improved cosine similarity measure of single valued neutrosophic. Finally, using this cosine similarity measure of neutrosophic refined set, the application of medical diagnosis is presented.
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  40. Predicting Fire Alarms in Smoke Detection using Neural Networks.Maher Wissam Attia, Baraa Akram Abu Zaher, Nidal Hassan Nasser, Ruba Raed Al-Hour, Aya Haider Asfour & Samy S. Abu-Naser - 2023 - International Journal of Academic Information Systems Research (IJAISR) 7 (10):26-33.
    Abstract: This research paper presents the development and evaluation of a neural network-based model for predicting fire alarms in smoke detection systems. Using a dataset from Kaggle containing 15 features and 3487 samples, we trained and validated a neural network with a three-layer architecture. The model achieved an accuracy of 100% and an average error of 0.0000003. Additionally, we identified the most influential features in predicting fire alarms.
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  41. Time, Mathematics, and the Fold: A Post-Heideggerian Itinerary.Said Mikki - manuscript
    A perspective is provided on how to move beyond postmodernism while struggling to do philosophy in the twenty-first century. The ontological structures of time, history, and mathematics are analyzed from the vantagepoint of the Heideggerian theory of nonspatial Fold.
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  42. An Extended TOPSIS Method for the Multiple Attribute Decision Making Problems Based on Interval Neutrosophic Uncertain Linguistics Variables.Said Broumi & Florentin Smarandache - 2015 - Neutrosophic Sets and Systems 8:22-31.
    The interval neutrosophic uncertain linguistic variables can easily express the indeterminate and inconsistent information in real world, and TOPSIS is a very effective decision making method more and more extensive applications. In this paper, we will extend the TOPSIS method to deal with the interval neutrosophic uncertain linguistic information, and propose an extended TOPSIS method to solve the multiple attribute decision making problems in which the attribute value takes the form of the interval neutrosophic uncertain linguistic variables and attribute weight (...)
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  43. Predicting Audit Risk Using Neural Networks: An In-depth Analysis.Dana O. Abu-Mehsen, Mohammed S. Abu Nasser, Mohammed A. Hasaballah & Samy S. Abu-Naser - 2023 - International Journal of Academic Information Systems Research (IJAISR) 7 (10):48-56.
    Abstract: This research paper presents a novel approach to predict audit risks using a neural network model. The dataset used for this study was obtained from Kaggle and comprises 774 samples with 18 features, including Sector_score, PARA_A, SCORE_A, PARA_B, SCORE_B, TOTAL, numbers, marks, Money_Value, District, Loss, Loss_SCORE, History, History_score, score, and Risk. The proposed neural network architecture consists of three layers, including one input layer, one hidden layer, and one output layer. The neural network model was trained and validated, achieving (...)
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  44. 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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  45. Handwritten Signature Verification using Deep Learning. [REVIEW]Eman Alajrami, Belal A. M. Ashqar, Bassem S. Abu-Nasser, Ahmed J. Khalil, Musleh M. Musleh, Alaa M. Barhoom & Samy S. Abu-Naser - manuscript
    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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  46. On Neutrosophic Implications.Said Broumi & Florentin Smarandache - 2014 - Neutrosophic Sets and Systems 2:9-17.
    In this paper, we firstly review the neutrosophic set, and then construct two new concepts called neutrosophic implication of type 1 and of type 2 for neutrosophic sets. Furthermore, some of their basic properties and some results associated with the two neutrosophic implications are proven.
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  47. Soft Interval-Valued Neutrosophic Rough Sets.Said Broumi & Florentin Smarandache - 2015 - Neutrosophic Sets and Systems 7:69-80.
    In this paper, we first defined soft intervalvalued neutrosophic rough sets(SIVN- rough sets for short) which combines interval valued neutrosophic soft set and rough sets and studied some of its basic properties. This concept is an extension of soft interval valued intuitionistic fuzzy rough sets( SIVIF- rough sets). Finally an illustartive example is given to verfy the developped algorithm and to demonstrate its practicality and effectiveness.
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  48. Knowledge and Belief in the Letter of Paul the Persian.Said Hayati - 2016 - In Dietmar W. Winkler (ed.), Syrische Studien. LIT Verlag. pp. 63-73.
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  49. Classification of plant Species Using Neural Network.Muhammad Ashraf Al-Azbaki, Mohammed S. Abu Nasser, Mohammed A. Hasaballah & Samy S. Abu-Naser - 2023 - International Journal of Engineering and Information Systems (IJEAIS) 7 (10):28-35.
    Abstract: In this study, we explore the possibility of classifying the plant species. We collected the plant species from Kaggle website. This dataset encompasses 544 samples, encompassing 136 distinct plant species. Recent advancements in machine learning, particularly Artificial Neural Networks (ANNs), offer promise in enhancing plant Species classification accuracy and efficiency. This research explores plant Species classification, harnessing neural networks' power. Utilizing a rich dataset from Kaggle, containing 544 entries, we develop and evaluate a neural network model. Our neural network, (...)
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  50. Livro eletrônico, acesso e autonomia: Potenciais e desafios.Miguel Said Vieira - 2011 - Quaestio: Revista de Estudos Em Educação 13 (2):p - 203.
    Este trabalho é uma breve análise do livro eletrônico ― tomado como meio de comunicação relevante para a educação e a cultura no futuro próximo ― centrada nos potenciais e desafios que ele apresenta em relação a acesso e autonomia. A análise visa apontar tendências gerais relativas às características das plataformas de leitura (dispositivos leitores e softwares), particularmente para leitores. Essas tendências são extrapoladas a partir de um pequeno número de exemplos ou casos já existentes. O trabalho avalia as restrições (...)
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