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  1. Zeno Paradox, Unexpected Hanging Paradox (Modeling of Reality & Physical Reality, A Historical-Philosophical view).Farzad Didehvar - manuscript
    . In our research about Fuzzy Time and modeling time, "Unexpected Hanging Paradox" plays a major role. Here, we compare this paradox to the Zeno Paradox and the relations of them with our standard models of continuum and Fuzzy numbers. To do this, we review the project "Fuzzy Time and Possible Impacts of It on Science" and introduce a new way in order to approach the solutions for these paradoxes. Additionally, we have a more general discussion about paradoxes, as Philosophical (...)
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  2. The impacts of Logic, Paradoxes in one side and Theory of Computation in the other side.Didehvar Farzad - manuscript
    This is a presentation about the impacts of Logic and Theory of Computation. It starts by some explanations about Theory of Computation and its relations with the other subjects in science. Then we have some explanations about paradoxes and some historical points. In continuation, we present some of the most important paradoxes. Forthcoming, Five subjects around the relations between Logic and Theory of computation is introduced. Finally, we present a new approach to solve P vs NP problem via Paradoxes (Presentation (...)
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  3. Introduction to CAT4. Part 2. CAT2.Andrew Thomas Holster - manuscript
    CAT4 is proposed as a general method for representing information, enabling a powerful programming method for large-scale information systems. It enables generalised machine learning, software automation and novel AI capabilities. It is based on a special type of relation called CAT4, which is interpreted to provide a semantic representation. This is Part 2 of a five-part introduction. The focus here is on defining key mathematical properties of CAT2, identifying the topology and defining essential functions over a coordinate system. The analysis (...)
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  4. Jacques Lacan’s Registers of the Psychoanalytic Field, Applied using Geometric Data Analysis to Edgar Allan Poe’s “The Purloined Letter”.Fionn Murtagh & Giuseppe Iurato - manuscript
    In a first investigation, a Lacan-motivated template of the Poe story is fitted to the data. A segmentation of the storyline is used in order to map out the diachrony. Based on this, it will be shown how synchronous aspects, potentially related to Lacanian registers, can be sought. This demonstrates the effectiveness of an approach based on a model template of the storyline narrative. In a second and more Comprehensive investigation, we develop an approach for revealing, that is, uncovering, Lacanian (...)
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  5. Robots as Powerful Allies for the Study of Embodied Cognition from the Bottom Up.Matej Hoffmann & Rolf Pfeifer - forthcoming - In Albert Newen, Leon De Bruin & Shaun Gallagher (eds.), The Oxford Handbook of 4E Cognition. Oxford University Press.
    A large body of compelling evidence has been accumulated demonstrating that embodiment – the agent’s physical setup, including its shape, materials, sensors and actuators – is constitutive for any form of cognition and as a consequence, models of cognition need to be embodied. In contrast to methods from empirical sciences to study cognition, robots can be freely manipulated and virtually all key variables of their embodiment and control programs can be systematically varied. As such, they provide an extremely powerful tool (...)
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  6. Ranking Theory.Gabriele Kern-Isberner, Niels Skovgaard-Olsen & Wolfgang Spohn - forthcoming - Knauff, M. & Spohn, W. (Eds). The Handbook of Rationality. MIT Press.
    Ranking theory is one of the salient formal representations of doxastic states. It differs from others in being able to represent belief in a proposition (= taking it to be true), to also represent degrees of belief (i.e. beliefs as more or less firm), and thus to generally account for the dynamics of these beliefs. It does so on the basis of fundamental and compelling rationality postulates and is hence one way of explicating the rational structure of doxastic states. Thereby (...)
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  7. Two-level grammars: Some interesting properties of van Wijngaarden grammars.Luis M. Augusto - 2023 - Omega - Journal of Formal Languages 1:3-34.
    The van Wijngaarden grammars are two-level grammars that present many interesting properties. In the present article I elaborate on six of these properties, to wit, (i) their being constituted by two grammars, (ii) their ability to generate (possibly infinitely many) strict languages and their own metalanguage, (iii) their context-sensitivity, (iv) their high descriptive power, (v) their productivity, or the ability to generate an infinite number of production rules, and (vi) their equivalence with the unrestricted, or Type-0, Chomsky grammars.
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  8. Promises and Problems in the Adoption of Self-Sovereign Identity Management from a Consumer Perspective.Marco Hünseler & Eva Pöll - 2023 - IFIP Advances in Information and Communication Technology 671:85-100.
    Online identification is a common problem but so far resolved unsatisfactorily, as consumers cannot fully control how much data they share and with whom. Self-Sovereign Identity (SSI) technology promises to help by making use of decentralized data repositories as well as advanced cryptographic algorithms and protocols. This paper examines the effects of SSIs on responsible, confident, and vulnerable consumers in order to develop the missing understanding of consumer needs in SSI adoption and define preconditions and necessary considerations for the development (...)
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  9. On the Cognitive Parsimony of Paralogical Arguments and their Impact in Automated Persuasion: Findings and Lessons Learned for Building Automatic Counter-Arguers.Antonio Lieto - 2023 - In Online Lectures. pp. 1-14.
    Persuasive technologies can adopt several strategies to change the attitudes and behaviors of their users. In this work I synthesize the lessons learned from three empirical case studies on automated persuasion that have been carried out in the last decade in the contexts of: persuasive news recommendations, social robotics, and e-commerce, respectively. In particular, such studies have assessed, in the technological domain, the effects of nudging techniques relying on well known persuasive argumentation schemas and on framing strategies. In discussing the (...)
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  10. Classification of Sign-Language Using Deep Learning - A Comparison between Inception and Xception models.Tanseem N. Abu-Jamie & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (8):9-19.
    there is a communication gap between hearing-impaired people and those with normal hearing, sign language is the main means of communication in the hearing-impaired population. Continuous sign language recognition, which can close the communication gap, is a difficult task since the ordered annotations are weakly supervised and there is no frame-level label. To solve this issue, we compare the accuracy of each model using two deep learning models, Inception and Xception . To that end, the purpose of this paper is (...)
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  11. Classification of Sign-Language Using Deep Learning by ResNet.Tanseem N. Abu-Jamie & Samy S. Abu-Naser - 2022 - International Journal of Academic Information Systems Research (IJAISR) 6 (8):25-34.
    American Sign Language, or ASL as its acronym is commonly known, is a fascinating language, and many people outside of the Deaf community have begun to recognize its value and purpose. It is a visual language consisting of coordinated hand gestures, body movements, and facial expressions. Sign language is not a universal language; it varies by country and is heavily influenced by the native language and culture. The American Sign Language alphabet and the British Sign Language alphabet are completely contrary. (...)
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  12. Classification of Sign-language Using VGG16.Tanseem N. Abu-Jamie & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (6):36-46.
    Sign Language Recognition (SLR) aims to translate sign language into text or speech in order to improve communication between deaf-mute people and the general public. This task has a large social impact, but it is still difficult due to the complexity and wide range of hand actions. We present a novel 3D convolutional neural network (CNN) that extracts discriminative spatial-temporal features from photo datasets. This article is about classification of sign languages are not universal and are usually not mutually intelligible (...)
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  13. Classification of Sign-Language Using MobileNet - Deep Learning.Tanseem N. Abu-Jamie & Samy S. Abu-Naser - 2022 - International Journal of Academic Information Systems Research (IJAISR) 6 (7):29-40.
    Abstract: Sign language recognition is one of the most rapidly expanding fields of study today. Many new technologies have been developed in recent years in the fields of artificial intelligence the sign language-based communication is valuable to not only deaf and dumb community, but also beneficial for individuals suffering from Autism, downs Syndrome, Apraxia of Speech for correspondence. The biggest problem faced by people with hearing disabilities is the people's lack of understanding of their requirements. In this paper we try (...)
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  14. Predicting Whether Student will continue to Attend College or not using Deep Learning.Samy S. Abu-Naser, Qasem M. M. Zarandah, Moshera M. Elgohary, Zakaria K. D. AlKayyali, Bassem S. Abu-Nasser & Ashraf M. Taha - 2022 - International Journal of Engineering and Information Systems (IJEAIS) 6 (6):33-45.
    According to the literature review, there is much room for improvement of college student retention. The aim of this research is to evaluate the possibility of using deep and machine learning algorithms to predict whether students continue to attend college or will stop attending college. In this research a feature assessment is done on the dataset available from Kaggle depository. The performance of 20 learning supervised machine learning algorithms and one deep learning algorithm is evaluated. The algorithms are trained using (...)
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  15. 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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  16. 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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  17. 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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  18. A Knowledge Based System for Cucumber Diseases Diagnosis.Nora J. H. Al-Saloul, Hadeel A. El-Hamarnah, Ola I. A. LAfi, Hanan I. A. Radwan & Samy S. Abu-Naser - 2022 - International Journal of Academic Information Systems Research (IJAISR) 6 (5):29-45.
    The cucumber is a creeping vine that roots in the ground and grows up trellises or other supporting frames, wrapping around supports with thin, spiraling tendrils. The plant may also root in a soilless medium, whereby it will sprawl along the ground in lieu of a supporting structure. The vine has large leaves that form a canopy over the fruits. Among these common diseases, we single out the diseases that affect the cucumber, which is affected by about 22 diseases, with (...)
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  19. Classification of A few Fruits Using Deep Learning.Mohammed Alkahlout, Samy S. Abu-Naser, Azmi H. Alsaqqa & Tanseem N. Abu-Jamie - 2022 - International Journal of Academic Engineering Research (IJAER) 5 (12):56-63.
    Abstract: Fruits are a rich source of energy, minerals and vitamins. They also contain fiber. There are many fruits types such as: Apple and pears, Citrus, Stone fruit, Tropical and exotic, Berries, Melons, Tomatoes and avocado. Classification of fruits can be used in many applications, whether industrial or in agriculture or services, for example, it can help the cashier in the hyper mall to determine the price and type of fruit and also may help some people to determining whether a (...)
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  20. Detection of Brain Tumor Using Deep Learning.Hamza Rafiq Almadhoun & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (3):29-47.
    Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines or software that work and reacts like humans, some of the computer activities with artificial intelligence are designed to include speech, recognition, learning, planning and problem solving. Deep learning is a collection of algorithms used in machine learning, it is part of a broad family of methods used for machine learning that are based on learning representations of data. Deep learning is used as a (...)
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  21. CLIPS - Expert System to Predict Coriander Diseases.Y. I. Aslem & Samy S. Abu-Naser - 2022 - International Journal of Engineering and Information Systems (IJEAIS) 6 (6):89-95.
    Artificial intelligence is one of the most rapidly evolving fields today. It is used in the majority of computer science applications nowadays. Expert systems are one of the most valuable types of AI; they are used to deliver predictions and decisions in order to make scientific, medical, and even architectural challenges easier to address; they will eventually take the place of a human expert. Without having to meet with a genuine human specialist, the user will be able to get a (...)
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  22. Computational logic. Vol. 1: Classical deductive computing with classical logic. 2nd ed.Luis M. Augusto - 2022 - London: College Publications.
    This is the 3rd edition. Although a number of new technological applications require classical deductive computation with non-classical logics, many key technologies still do well—or exclusively, for that matter—with classical logic. In this first volume, we elaborate on classical deductive computing with classical logic. The objective of the main text is to provide the reader with a thorough elaboration on both classical computing – a.k.a. formal languages and automata theory – and classical deduction with the classical first-order predicate calculus with (...)
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  23. Problems and Solutions in Researching Computer Game Assisted Dialogues for Persons with Aphasia.Ylva Backman, Viktor Gardelli & Peter Parnes - 2022 - Designs for Learning 1 (14):46–51.
    In this paper, we describe technological advances for supporting persons with aphasia in philosophical dialogues about personally relevant and contestable questions. A computer game-based application for iPads is developed and researched through Living Lab inspired workshops in order to promote the target group’s communicative participation during group argumentation. We outline some central parts of the background theory of the application and some of its main features, which are related to needs of the target group. Methodological issues connected to the design (...)
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  24. The Form in Formal Thought Disorder: A Model of Dyssyntax in Semantic Networking.Farshad Badie & Luis M. Augusto - 2022 - MDPI AI 3:353–370.
    Formal thought disorder (FTD) is a clinical mental condition that is typically diagnosable by the speech productions of patients. However, this has been a vexing condition for the clinical community, as it is not at all easy to determine what “formal” means in the plethora of symptoms exhibited. We present a logic-based model for the syntax–semantics interface in semantic networking that can not only explain, but also diagnose, FTD. Our model is based on description logic (DL), which is well known (...)
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  25. Diagnosis of Pneumonia Using Deep Learning.Alaa M. A. Barhoom & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (2):48-68.
    Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines or software that work and react like humans. Some of the activities computers with artificial intelligence are designed for include, Speech, recognition, Learning, Planning and Problem solving. Deep learning is a collection of algorithms used in machine learning, It is part of a broad family of methods used for machine learning that are based on learning representations of data. Deep learning is a technique used (...)
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  26. 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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  27. 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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  28. 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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  29. 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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  30. Weakly Free Multialgebras.Marcelo E. Coniglio & Guilherme V. Toledo - 2022 - Bulletin of the Section of Logic 51 (1):109-141.
    In abstract algebraic logic, many systems, such as those paraconsistent logics taking inspiration from da Costa's hierarchy, are not algebraizable by even the broadest standard methodologies, as that of Blok and Pigozzi. However, these logics can be semantically characterized by means of non-deterministic algebraic structures such as Nmatrices, RNmatrices and swap structures. These structures are based on multialgebras, which generalize algebras by allowing the result of an operation to assume a non-empty set of values. This leads to an interest in (...)
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  31. 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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  32. 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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  33. Retina Diseases Diagnosis Using Deep Learning.Abeer Abed ElKareem Fawzi Elsharif & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (2):11-37.
    There are many eye diseases but the most two common retinal diseases are Age-Related Macular Degeneration (AMD), which the sharp, central vision and a leading cause of vision loss among people age 50 and older, there are two types of AMD are wet AMD and DRUSEN. Diabetic Macular Edema (DME), which is a complication of diabetes caused by fluid accumulation in the macula that can affect the fovea. If it is left untreated it may cause vision loss. Therefore, early detection (...)
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  34. Diagnosis of Blood Cells Using Deep Learning.Ahmed J. Khalil & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (2):69-84.
    In computer science, Artificial Intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. Computer science defines AI research as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. Deep Learning is a new field of research. One of the branches of Artificial Intelligence Science deals with the creation of theories and algorithms that (...)
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  35. A Proposed Expert System for Broccoli Diseases Diagnosis.Ola I. A. LAfi, Hadeel A. El-Hamarnah, Nora J. H. Al-Saloul, Hanan I. A. Radwan & Samy S. Abu-Naser - 2022 - International Journal of Engineering and Information Systems (IJEAIS) 6 (5):43-51.
    Background: Broccoli is an edible green plant in the cabbage family (family Brassicaceae, genus Brassica) whose large flowering head, stalk and small associated leaves are eaten as a vegetable. A leaf of Broccoli might be affected of Several Diseases descriped in this paper . When symptoms is encountered, it requires some kind of medical care. If appropriate Survival of Broccoli Diseases is not taken quickly, it can lead to Broccoli to die . Objectives: The main goal of this expert system (...)
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  36. Age and Gender Classification Using Deep Learning - VGG16.Aysha I. Mansour & Samy S. Abu-Naser - 2022 - International Journal of Academic Information Systems Research (IJAISR) 6 (7):50-59.
    Abstract: Age and gender classification has been around for a long time, and efforts are still being made to improve the findings. This has been the case since the inception of social media platforms. Visible understanding has become more important in the computer vision society with the emergence of AI increase in performance and help train a model to achieve age and gender classification. Although these networks built for the mobile platform are not always as accurate as the larger, more (...)
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  37. Classification of Age and Gender Using ResNet - Deep Learning.Aysha I. Mansour & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (8):20-29.
    Age and gender classification has become relevant to an increasing amount of applications, particularly since the rise of social platforms and social media. Even Nevertheless, contrast to the large performance improvements recently reported for the closely related task of audio. In this research, we show that performance on these tasks can be significantly improved by learning representations using deep convolutional neural networks (CNN). where we get in the ResNet the training accuracy was 98% ,validation accuracy 95%, testing accuracy 96% .Testing (...)
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  38. 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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  39. 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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  40. Artificial Intelligence and the Notions of the “Natural” and the “Artificial.”.Justin Nnaemeka Onyeukaziri - 2022 - Journal of Data Analysis 17 (No. 4):101-116.
    This paper argues that to negate the ontological difference between the natural and the artificial, is not plausible; nor is the reduction of the natural to the artificial or vice versa possible. Except if one intends to empty the semantic content of the terms and notions: “natural” and “artificial.” Most philosophical discussions on Artificial Intelligence (AI) have always been in relation to the human person, especially as it relates to human intelligence, consciousness and/or mind in general. This paper, intends to (...)
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  41. A Proposed Expert System for Passion Fruit Diseases.Hanan I. A. Radwan, Hadeel A. El-Hamarnah, Nora J. H. Al-Saloul, Ola I. A. LAfi & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (5):24-33.
    Plant diseases are numerous in the world of agriculture. These diseases cause a lot of trouble to most farmers. Among these common diseases, we single out the diseases that affect the Passion fruit, which is affected by about seven diseases, with different symptoms for each disease. Today, technology is facilitating human life in all areas of life, and among these facilities are expert system, a computer program that uses artificial-intelligence methods to solve problems within a specialized domain that ordinarily requires (...)
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  42. Widening Access to Applied Machine Learning With TinyML.Vijay Reddi, Brian Plancher, Susan Kennedy, Laurence Moroney, Pete Warden, Lara Suzuki, Anant Agarwal, Colby Banbury, Massimo Banzi, Matthew Bennett, Benjamin Brown, Sharad Chitlangia, Radhika Ghosal, Sarah Grafman, Rupert Jaeger, Srivatsan Krishnan, Maximilian Lam, Daniel Leiker, Cara Mann, Mark Mazumder, Dominic Pajak, Dhilan Ramaprasad, J. Evan Smith, Matthew Stewart & Dustin Tingley - 2022 - Harvard Data Science Review 4 (1).
    Broadening access to both computational and educational resources is crit- ical to diffusing machine learning (ML) innovation. However, today, most ML resources and experts are siloed in a few countries and organizations. In this article, we describe our pedagogical approach to increasing access to applied ML through a massive open online course (MOOC) on Tiny Machine Learning (TinyML). We suggest that TinyML, applied ML on resource-constrained embedded devices, is an attractive means to widen access because TinyML leverages low-cost and globally (...)
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  43. Using simulation in the assessment of voting procedures: An epistemic instrumental approach.Marc Jiménez Rolland, Julio César Macías-Ponce & Luis Fernando Martínez-Álvarez - 2022 - Simulation: Transactions of the Society for Modeling and Simulation International 98 (2):127-144.
    In this paper, we argue that computer simulations can provide valuable insights into the performance of voting methods on different collective decision problems. This could improve institutional design, even when there is no general theoretical result to support the optimality of a voting method. To support our claim, we first describe a decision problem that has not received much theoretical attention in the literature. We outline different voting methods to address that collective decision problem. Under certain criteria of assessment akin (...)
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  44. 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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  45. Classification of Real and Fake Human Faces Using Deep Learning.Fatima Maher Salman & Samy S. Abu-Naser - 2022 - International Journal of Academic Engineering Research (IJAER) 6 (3):1-14.
    Artificial intelligence (AI), deep learning, machine learning and neural networks represent extremely exciting and powerful machine learning-based techniques used to solve many real-world problems. Artificial intelligence is the branch of computer sciences that emphasizes the development of intelligent machines, thinking and working like humans. For example, recognition, problem-solving, learning, visual perception, decision-making and planning. Deep learning is a subset of machine learning in artificial intelligence that has networks capable of learning unsupervised from data that is unstructured or unlabeled. Deep learning (...)
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  46. Classification of Alzheimer's Disease Using Convolutional Neural Networks.Lamis F. Samhan, Amjad H. Alfarra & Samy S. Abu-Naser - 2022 - International Journal of Academic Information Systems Research (IJAISR) 6 (3):18-23.
    Brain-related diseases are among the most difficult diseases due to their sensitivity, the difficulty of performing operations, and their high costs. In contrast, the operation is not necessary to succeed, as the results of the operation may be unsuccessful. One of the most common diseases that affect the brain is Alzheimer’s disease, which affects adults, a disease that leads to memory loss and forgetting information in varying degrees. According to the condition of each patient. For these reasons, it is important (...)
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  47. F Things You (Probably) Didn't Know About Hexadecimal.Lloyd Strickland & Owain Daniel Jones - 2022 - The Mathematical Intelligencer 45.
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  48. A Study of Obstacles in Plagiarism Software Subscribing by Colleges in Tamil Nadu.A. Subaveerapandiyan & N. Sakthivel - 2022 - DESIDOC Journal of Library and Information Technology 42 (5):318-324.
    This article attempts to comprehend the current issues and hurdles that Indian colleges affiliated with Tamil Nadu State Universities encounter when trying to subscribe to a software that detects plagiarism. The study’s goals are to determine whether colleges employ anti-plagiarism software, whether they ensure that their student-given assignments are free of copyright infringement, whether tutors teach about academic misconduct, and what people seem to think of anti-plagiarism software. We surveyed for this study and distributed the questionnaires among college administrators, principals, (...)
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  49. 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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  50. Bayesvl: an R package for user-friendly Bayesian regression modelling.Quan-Hoang Vuong, Minh-Hoang Nguyen & Manh-Toan Ho - 2022 - VMOST Journal of Social Sciences and Humanities 64 (1):85-96.
    Compared with traditional statistics, only a few social scientists employ Bayesian analyses. The existing software programs for implementing Bayesian analyses such as OpenBUGS, WinBUGS, JAGS, and rstanarm can be daunting given that their complex computer codes involve a steep learning curve. In contrast, this paper introduces a new open software for implementing Bayesian network modelling and analysis: the bayesvl R package. The package aims at providing an intuitive gateway for beginners of Bayesian statistics to construct and analyse mathematical models in (...)
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