In the modern moral luck debate, Kant is standardly taken to be the enemy of moral luck. My goal in this paper is to show that this is mistaken. The paper is divided into six sections. In the first, I show that participants in the moral luck literature take moral luck to be anathema to Kantian ethics. In the second, I explain the kind of luck I am going to focus on here: consequence luck, a species of resultant luck. In (...) the third, I explain why philosophers have taken Kantian ethics to reject moral luck and, in particular, consequence luck. In the fourth, I explain why these philosophers are mistaken, and I set out Kant’s theoretical framework for consequence luck. In the fifth, I clarify and defend this framework, and in the sixth, I interrogate and attack it. (shrink)

It is often assumed that adaptation — a temporary change in sensitivity to a perceptual dimension following exposure to that dimension — is a litmus test for what is and is not a “primary visual attribute”. Thus, papers purporting to find evidence of number adaptation motivate a claim of great philosophical significance: That number is something that can be seen in much the way that canonical visual features, like color, contrast, size, and speed, can. Fifteen years after its reported discovery, (...) number adaptation’s existence seems to be nearly undisputed, with dozens of papers documenting support for the phenomenon. The aim of this paper is to offer a counterweight — to critically assess the evidence for and against number adaptation. After surveying the many reasons for thinking that number adaptation exists, we introduce several lesser-known reasons to be skeptical. We then advance an alternative account — the old news hypothesis — which can accommodate previously published findings while explaining various (otherwise unexplained) anomalies in the existing literature. Next, we describe the results of eight pre-registered experiments which pit our novel old news hypothesis against the received number adaptation hypothesis. Collectively, the results of these experiments undermine the number adaptation hypothesis on several fronts, whilst consistently supporting the old news hypothesis. More broadly our work raises questions about the status of adaptation itself as a means of discerning what is and is not a visual attribute. (shrink)

This article is divided into three sections. In the first and second, I examine Sartorio’s account of the causal structure of the famous Thirsty Traveler thought experiment. I argue that this account does not withstand critical scrutiny. In the third, I turn to a novel kind of moral luck that Sartorio uses the Thirsty Traveler to expose. I expand the scope of my argument to look also at other recently proposed categories of moral luck. I argue that these proposals are (...) overhasty. (shrink)

Visual number adaption is a widely accepted phenomenon. This paper advances an alternative explanation for putative cases of the phenomenon. We propose that such cases may simply reflect observers adapting to the items in perceived displays, rather than their numerical quantity. Three experiments motivate consideration of this novel proposal and call into question the evidential basis for received formulations of the number adaptation hypothesis.

The visual system adapts to a wide range of visual features, from lower-level features like color and motion to higher-level features like causality and, perhaps, number. According to some, adaptation is a strictly perceptual phenomenon, such that the presence of adaptation licenses the claim that a feature is truly perceptual in nature. Given the theoretical importance of claims about adaptation, then, it is important to understand exactly when the visual system does and does not exhibit adaptation. Here, we take as (...) a case study one specific kind of adaptation: visual adaptation to size. Supported by evidence from four experiments, we argue that, despite robust effects of size adaptation in the lab, (1) size adaptation effects are phenomenologically underwhelming (in some cases, hardly appreciable at all), (2) some effects of size adaptation appear contradictory, and difficult to explain given current theories of size adaptation, and (3) prior studies on size adaptation may have failed to isolate size as the adapted dimension. Ultimately, we argue that while there is evidence to license the claim that size adaptation is genuine, size adaptation is a puzzling and poorly understood phenomenon. (shrink)

In Wilmot-Smith’s recent ‘Law, “Ought”, and “Can”,’ he argues that legal obligation does not imply ability. In this short reply, I show that Wilmot-Smith’s arguments do not withstand critical scrutiny. In section 1, I attack Wilmot-Smith’s argument for the claim that allowing for impossible obligations makes for a better legal system, and I introduce positive grounds for thinking otherwise. In section 2, I show that, even if Wilmot-Smith had established that impossible obligations make for a better legal system, his subsequent (...) attack on OIC fails. (shrink)

Jus post Bellum is, like Jus ad Bellum and Jus in Bello, a part of just war theory. Jus post Bellum is distinguished from the other parts of just war theory by being primarily concerned with the principles necessary for securing a just and lasting peace after the end of a war. Traditionally, jus post bellum has focused primarily on three goals: [1] compensating those who have been the victims of unjust aggression, while respecting the rights of the aggressors, [2] (...) punishing and rehabilitating those guilty of war crimes and other violations of the principles of Jus ad Bellum and Jus in Bello and [3] developing measures that will prevent future war and violence (Orend 2000 and May 2012). In this chapter, I outline an account of political forgiveness and explain the role that political forgiveness can have in promoting the goals of jus post bellum. My conception of political forgiveness requires some unpacking. Let me begin with individual forgiveness, which I understand along familiar Butlerian lines as the renunciation of resentment (Butler, Sermon IX in McNaughton 2017: 75-83), though with a bit of a twist. More exactly, ● An individual, I, forgives J for doing F if and only if I renounces all her own warrant for resenting J for doing F. Resentment is a judgment-sensitive attitude, and, therefore, it tends to track judgments concerning its warrant (Scanlon 1998: 20 and Smith 2015). In cases of perfect forgiveness, I’s renunciation causes her to cease feeling resentment toward J for doing F, though, of course, less perfect cases are possible. I reject the idea that there is a sharp discontinuity between individual and political forgiveness, a position argued for by, e.g., Peter Digeser (1998 and 2001). By contrast, I understand political forgiveness as the renunciation of resentment by the relevant political body in question. With greater precision, ● A sovereign political body, P, forgives J for doing F if and only if P renounces all warrant that its citizens have for resenting, as part of their public lives, J for doing F. A little more explanation is in order. Sovereign political bodies, such as national governments, claim degrees of control over the lives of their citizens, in both their public and their private aspects, though the claims with respect to the former tend to be considerably more expansive than the claims with respect to the latter. I assume here that, at least in the case of legitimate governments, these claims of control are often valid. Such governments may reasonably renounce certain grounds for motivating action in the public sphere. For example, governments may renounce all warrant that its citizens have, as part of their public lives, for hating members of marginalized groups. In practice, this means that, while citizens might continue to act in their private lives out of hatred for members of these groups, their appeal to this hatred is seen by the state as irrelevant to matters of law and public policy as well as being wholly out-of-place in public discourse. Political forgiveness toward J for doing F, as I understand it, involves an analogous rejection of resentment, on the part of citizens in their public lives, toward J for doing F. I turn now to the matter of how political forgiveness supports securing a just and lasting peace between former belligerents. With respect to the first goal of jus post bellum, political forgiveness helps to balance compensation for victims and respect for the rights of defeated aggressors by countering the all-too-human tendency to overvalue harms done to oneself and to members of one’s group. As regards the second goal, political forgiveness plays a similar role but also provides a model for rehabilitation by exemplifying among the victorious the behavior to be emulated by the vanquished. Finally, political forgiveness promotes the third goal of jus post bellum by providing a space for nations to meet as moral equals rather than allowing one nation to have the moral high ground over the other. None of this, of course, means that political forgiveness should be unearned or that it should be confused with condonation (Kolnai 1973 and Pettigrove 2004). However, the question of what is required to put oneself in a position to be forgiven as part of jus post bellum is a matter that goes beyond the scope of this chapter. (shrink)

Publication date: 29 September 2016 Source: Author: Samy S. Abu Naser, Mazen J. Al Shobaki, Youssef M. Abu Amuna This paper aims to measure knowledge management maturity in higher education institutions to determine the impact of knowledge management on high performance. Also the study aims to compare knowledge management maturity between universities and intermediate colleges. This study was applied on five higher education institutions in Gaza strip, Palestine. Asian productivity organization model was applied to measure Knowledge Management Maturity. Second dimension (...) which assess high performance was developed by the authors. The controlled sample was. Several statistical tools were used for data analysis and hypotheses testing, including reliability correlation using Cronbach’s alpha, “ANOVA”, Simple Linear Regression and Step Wise Regression. The overall findings of the current study shows that maturity level is in the second level. Findings also support the main hypothesis and it is sub- hypotheses. The most important factors effecting high performance are: Processes, knowledge management leadership, People, knowledge management Outcomes. Furthermore the current study is unique by the virtue of its nature, scope and way of implied investigation, as it is the first comparative study between universities and intermediate colleges in Gaza Strip that explores the status of knowledge management maturity using the Asian productivity Model. (shrink)

The Earth is positioned at the center of the universe in the Ptolemaic model of the universe. The center of the Earth is at the same time the center of the universe in this model. This system, which was constructed according to Aristotelian physics, was accepted as the prevailing theory up to the adoption of the heliocentric universal model in the 16th century. The Earth was at the same time assumed to be completely stationary in the geocentric theory. Movement around (...) its own axis or around another celestial body was out of the question for it. In Antiquity and the Middle Ages when observational instruments like the telescope were not yet in use, this theory was seen to be rationally based on data obtained directly from the senses. In this context, various justifications had been provided about the world being stationary and existing at the center. Representatives from the Peripatetic philosophy in the Muslim world also were seen to accept the geocentric model. In The Book of Healing, Ibn Sīnā (d. 1038 CE) subjected the proofs that had come to him about the Earth being stationary by distinguishing an independent chapter. The 14th century follower of Ibn Sīnā’s philosophy, Najm al-Dīn al-Kātibī addressed this topic in Ḥikmat al-‘ain, and the work’s principle commentators also commented on his assessments. This study will address Ibn Sīnā’s assessments on the Earth being stationary in the geocentric model of the universe and will discuss the reflections of these assessments in Ḥikmat al-‘ain as an Avicennan text. (shrink)

Kidney stones pose a significant health concern, and early detection can lead to timely intervention and improved patient outcomes. This research endeavours to predict the presence of kidney stones based on urine analysis, utilizing a neural network model. A dataset of 552 urine specimens, comprising six essential physical characteristics (specific gravity, pH, osmolarity, conductivity, urea concentration, and calcium concentration), was collected and prepared. Our proposed neural network architecture, featuring three layers (input, hidden, output), was trained and validated, achieving an impressive (...) accuracy of 98.67% and an average error of 0.012. In addition to model performance, feature importance analysis was conducted to determine the most influential factors in predicting kidney stone presence. The findings underscore the significance of urea concentration, specific gravity, calcium concentration, conductivity, osmolarity, and pH as key indicators. This research contributes to the early diagnosis of kidney stones and demonstrates the potential of neural networks in medical diagnostics. The clinical implications of these findings are discussed, emphasizing the importance of timely intervention in managing kidney stone-related health issues. (shrink)

The research aims to identify the impact of the management requirements on operating of computerized management information systems to improve performance, and discuss the perceptions of respondents to develop the performance of employees in the Gaza Electricity Distribution Company, the researchers used the stratified sample method, (360) questionnaires were distributed on the study sample, (306) questionnaires were recoved with a percentage of (85%). The most important findings of the study: computerized MI have a positive impact on the development of performance (...) in the Gaza Electricity Distribution Company systems. The is statistical significance impact between “the physical, software supplies, human and organizational” requirements for the management and operation of computerized management information systems and performance development in the Gaza Electricity Distribution Company. -/- The research also concluded a series of recommendations: the need to strengthen the company's management interest in the use of computerized management information systems in all its components and elements of being an important variable which contributes to the effect on performance development. It's essential that we develop the infrastructure for information technology in general, and computerized management information systems, in particular for the development of performance. Increased interest in providing the material of equipment and devices used in the computerized management information system requirements. Interest in providing technical inputs to the computerized management information systems through keeping pace with technological means and modern techniques and work on the training of personnel to use those systems. And increased attention to human inputs of computerized management information systems "specialists technicians and end-users" through a variety of disciplines working in the field of computerized management information systems. (shrink)

Both the continuity of the history of Ottoman thought with Islamic thought and its relationship with the "new" movements of thought that emerged in the Western world have not yet been analyzed on a solid ground. In particular, the connection that Ottoman scholars established or failed to establish with the developments in the Western has been handled with various biased and superficial evaluations. One of the critical points that will contribute to a meaningful discussion of this issue is the translation (...) and commentary of Ioannes Cottunius' partial commentary and partial summarization of Aristotle's Physics into Arabic under the title al-Taʿlīm al-s̱ālis̱ by Asʿad al-Yānyawī as a member of the translation committee that established in the Tulip Period. In this study I will share some observations on why this work on Aristotle's physics was chosen for translation at a time when the new understanding of physics was thought to have become widespread in Europe, and whether the translation contains a new interpretation beyond a mere transmission. These determinations, which also include the criticism of some readings in the modern literature, will be largely based on the introduction (muqaddima) of the manuscript. (shrink)

A lot of infants have significant food-related problems, as well as spitting up, rejecting new foods, or not accepting to eat at specific times. These issues are frequently ordinary and are not a sign that the baby is unwell. According to the National Institutes of Health, 25% of generally developing infants and 35% of babies with neurodevelopmental disabilities are tormented by some sort of feeding problem. Some, for example rejecting to eat specific foods or being overly finicky, are momentary and (...) don’t cause any health dangers. This paper proposes an expert system that can be used to successfully diagnose Feeding problems in infants and children. The suggested systems were found to be beneficial approach in addition to existing impartial ones. So far as the authors are aware, this is the initial effort of using an expert system in attaining good performance in a real world application. This expert system was designed and implemented to help parents diagnose these problems and get a recommendation of how to deal with infants and children. (shrink)

In this paper a Knowledge-Based System (KBS) for determining the appropriate students major according to his/her preferences for sophomore student enrolled in the Faculty of Engineering and Information Technology in Al-Azhar University of Gaza was developed and tested. A set of predefined criterions that is taken into consideration before a sophomore student can select a major is outlined. Such criterion as high school score, score of subject such as Math I, Math II, Electrical Circuit I, and Electronics I taken during (...) the student freshman year, number of credits passed, student cumulative grade point average of freshman year, among others, were then used as input data to KBS. KBS was designed and developed using Simpler Level Five (SL5) Object expert system language. KBS was tested on three generation of sophomore students from the Faculty of Engineering and Information Technology of the Al-Azhar University, Gaza. The results of the evaluation show that the KBS is able to correctly determine the appropriate students major without errors. (shrink)

Male genital problems and injuries may occur quite simply because of the scrotum and penis are not protected like other organs. Genital problems and injuries normally happen through: recreational activities (like Football, Hooky, biking, basketball), workrelated tasks (like contact to irritating chemicals), downhill drop, and sexual activity. A genital injury frequently causes harsh pain that typically disappear fast without causing enduring harm. Home handling is generally all that is required for trivial problems or injuries. Pain, inflammation, staining, or rashes that (...) are coexist with other symptoms might be a source for concern. Genital problems in men is one of the most common problems which requires fast intervention. In this paper we present an expert system that help men diagnose their genital problems and give them the proper treatment. SL5 Object expert system language was used to design and implement this expert system. (shrink)

This research aims to identify the use of decision support systems as an entry point for operations of re-engineering in the Palestinian universities in Gaza Strip. The researchers used the method of questionnaire to collect data, and the researchers used a sample stratified random way, were (350) questionnaire distributed on the research sample and (312) questionnaire were collected back (89.1%). The study results showed that the most important ones are: there exists statistically significant impact at the level of significance (α (...) ≤ 0.05) for physical requirements, human requirements. technical requirements and regulatory requirements. The results showed also, the presence of statistically significant differences between the averages of the study sample estimates on the use of decision support systems as an entry point for operations of re-engineering in the Palestinian universities in Gaza Strip due to the variable sex in favor of males requirements. Furthermore, the results showed the existence of differences to the variable name of the university and each area of study for the benefit of the Islamic University then Al-Azhar University and then Al-Aqsa University. The study also concluded a series of recommendations including: encourage Palestinian universities in Gaza Strip, which are planning to re-engine Information Systems to start implementing the programs in the radical change as soon as possible. The need for the Palestinian universities in Gaza Strip, to develop the infrastructure for information technology in general, and decision support systems, in particular, when doing re-engineering operations. And the need for a separate unit of decision support systems and organizational structure to allow information to flow seamlessly between colleges and various departments and divisions. And investment of available information in building the capacities of integration techniques, in order to enable them to continue with the re-engineering of Information Systems. (shrink)

Background: Persimmon is a grassy, perennial plant, belonging to the oral platoon, square-shaped leg, bifurcated, erect, and ranging in height from (10 - 201 cm). Home to Europe and Asia. The Persimmon 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 Persimmon plant is the ideal option for the start of gardens, it is prone to some common diseases that affect the plant's growth. (...) Objectives: The main goal of this expert system is to get the appropriate diagnosis of disease and the correct treatment. Methods: In this paper, the design of the proposed Expert System was produced to help Farmers and those interested in agriculture in diagnosing many of the Persimmon diseases such as Persimmon rust, Verticillium wilt, Anthracnose, Powdery mildew, Black Stem Rot, Stem and stolon canker, Septoria leaf spot. The proposed expert system presents an overview of Persimmon diseases are given, the cause of diseases outlined and the treatment of disease whenever possible is given out. CLIPS Expert System language was used for designing and implementing the proposed expert system. Results: The proposed Persimmon diseases diagnosis expert system was evaluated by Agricultural Students at AL Azhar University and some friends interested in agriculture and they were satisfied with its performance. Conclusions: The proposed expert system is very useful for Farmers and those interested in agriculture. (shrink)

People often think of objects teleologically. For instance, we might understand a hammer in terms of its purpose of driving in nails. But how should we understand teleological thinking in the first place? This paper separates mere teleology (simply ascribing a telos) and teleological explanation (thinking something is explained by its telos) by examining cases where an object was designed for one purpose but is now widely used for a different purpose. Across four experiments, we show that teleology judgments and (...) teleological explanation judgments are dissociable, and identify three factors that influenced teleology judgments (and one that did not). (shrink)

Abstract: Background: In spite of the fact that computers continue to improve in speed and functions operation, they remain complex to use. Problems frequently happen, and it is hard to resolve or find solutions for them. This paper outlines the significance and feasibility of building a desktop PC problems diagnosis system. The system gathers problem symptoms from users’ desktops, rather than the user describes his/her problems to primary search engines. It automatically searches global databases of problem symptoms and solutions, and (...) also allows ordinary users to contribute exact problem reports in a structured manner. Objectives: The main goal of this Knowledge Based System is to get the suitable problem desktop PC symptoms and the correct way to solve the errors. Methods: In this paper the design of the proposed Knowledge Based System which was produced to help users of desktop PC in knowing many of the problems and error such as : Power supply problems, CPU errors, RAM dumping error, hard disk errors and bad sectors and suddenly restarting PC. The proposed Knowledge Based System presents an overview about desktop PC hardware errors are given, the cause of fault are outlined and the solution to the problems whenever possible is given out. CLIPS Knowledge Based System language was used for designing and implementing the proposed expert system. Results: The proposed PC desktop troubleshooting Knowledge Based System was evaluated by IT students and they were satisfied with its performance. (shrink)

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 (...) is to get the appropriate diagnosis of disease and the correct treatment. Methods: In this paper the design of the proposed Expert System which was produced to help Farmers in diagnosing many of the broccoli diseases such as : Damping Off,Club root of crucifers or Finger and toe disease,Alternaria leaf spot,Black rot,Downy mildew, and White rust. (shrink)

Abstract: This research delves into the utilization of Artificial Neural Networks (ANNs) as a powerful tool for predicting the overall ratings of books by leveraging a diverse set of attributes. To achieve this, we employ a comprehensive dataset sourced from Goodreads, enabling us to thoroughly examine the intricate connections between the different attributes of books and the ratings they receive from readers. In our investigation, we meticulously scrutinize how attributes such as genre, author, page count, publication year, and reader reviews (...) influence a book's overall rating. Through rigorous analysis and experimentation, we construct an advanced ANN model tailored for predictive analysis in the realm of book ratings. The outcomes of our study reveal the remarkable potential of ANNs in this domain. The ANN model exhibits an impressive level of accuracy when it comes to forecasting book ratings, underlining the efficacy and promise of artificial neural networks in enhancing our understanding and prediction of book evaluations. This research opens up new avenues for leveraging machine learning techniques to gain deeper insights into the dynamics of book ratings and reader preferences. (shrink)

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 (...) of winnings or getting draw. (shrink)

Warts and verrucas are common skin conditions caused by the human papillomavirus (HPV) infection. They present as raised, rough, or bumpy growths on the hands, feet, or other areas subjected to friction or pressure. Plantar warts exhibit a rough surface with small black dots, while genital warts have a cauliflower-like appearance. Pain or itchiness may accompany these lesions. Factors such as close contact with infected individuals and immune compromise can impact the severity and spread of warts. Diagnosis is primarily based (...) on clinical examination, and referral to a dermatologist may be necessary for uncertain cases. Treatment options range from over-the-counter remedies to professional interventions. Persistent or symptomatic lesions should be evaluated by a healthcare professional. Improved understanding and effective management of warts and verrucas are essential for optimal patient outcomes. (shrink)

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 (...) by diverse research groups in the recent past. However, yet effective and comprehensive deep ensemble neural network-based classification model with high accuracy classification results is not available in the literature. In this thesis, we review ways and mechanisms to use deep learning techniques to research on multi-disease computer-aided detection about gastrointestinal and identify these images. We re-trained five state-of-the-art neural network architectures, VGG16, ResNet, MobileNet, Inception-v3, and Xception on the Kvasir dataset to classify eight categories that include an anatomical landmark (pylorus, z-line, cecum), a diseased state (esophagitis, ulcerative colitis, polyps), or a medical procedure (dyed lifted polyps, dyed resection margins) in the Gastrointestinal Tract. Our models have showed results with a promising accuracy which is a remarkable performance with respect to the state-of-the-art approaches. The resulting accuracies achieved using VGG, ResNet, MobileNet, Inception-v3, and Xception were 98.3%, 92.3%, 97.6%, 90% and 98.2%, respectively. As it appears, the most accurate result has been achieved when retraining VGG16 and Xception neural networks with accuracy reache to 98% due to its high performance on training on ImageNet dataset and internal structure that support classification problems. (shrink)

Abstract: Potatoes are edible tubers, available worldwide and all year long. They are relatively cheap to grow, rich in nutrients, and they can make a delicious treat. The humble potato has fallen in popularity in recent years, due to the interest in low-carb foods. However, the fiber, vitamins, minerals, and phytochemicals it provides can help ward off disease and benefit human health. They are an important staple food in many countries around the world. There are an estimated 200 varieties of (...) potatoes, which can be classified into a number of categories based on the cooked texture and ingredient functionality. Using a public dataset of 2400 images of potatoes, we trained a deep convolutional neural network to identify 4 types (Red, Red Washed, Sweet, and White).The trained model achieved an accuracy of 99.5% of test set, demonstrating the feasibility of this approach. (shrink)

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 (...) was collected from Kaggle depository. It consists of 6362620 rows and 10 columns. The best classifier with unbalanced dataset was the Random Forest Classifier. The Accuracy 99.97%, precession 99.96%, Recall 99.97% and the F1-score 99.96%. However, the best classifier with balanced dataset was the Bagging Classifier. The Accuracy 99.96%, precession 99.95%, Recall 99.98% and the F1-score 99.96%. (shrink)

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 (...) is a technique used to generate face detection and recognize it for real or fake by using profile images and determine the differences between them. In this study, we used deep learning techniques to generate models for Real and Fake face detection. The goal is determining a suitable way to detect real and fake faces. The model was designed and implemented, including both Dataset of images: Real and Fake faces detection through the use of Deep learning algorithms based on neural networks. We have trained dataset which consists of 9,000 images for total in 150 epochs, and got the ResNet50 model to be the best model of network architectures used with 100% training accuracy, 99.18% validation accuracy, training loss 0.0003, validation loss 0.0265, and testing accuracy 99%. (shrink)

Abstract - The aim of the study is to identify the degree of administrative transparency in the Palestinian higher educational institutions in the Gaza Strip. In the study, the researchers adopted a descriptive and analytical method. The research population consisted of administrative staff, whether academic or administrative, except for those in senior management or the university council. The study population reached 392 employees. A random sample was selected (197). The number of questionnaires recovered was (160) with a recovery rate of (...) (81.2%). The researchers used a questionnaire for the data collection and were treated using SPSS to obtain the results. The results show that there is no significant difference between male responses and female responses due to gender variable. The results also confirm that there is no significant difference between respondents' responses due to the age variable. The results also showed a significant difference between respondents' responses attributed to the university variable. There is a fundamental difference between respondents' responses attributed to the scientifically qualified variable. The results also confirmed a significant difference between respondents' responses attributed to the management level variable. The results also confirmed a significant difference between respondents' responses due to variable years of service. The research reached a number of recommendations, the most important of which is: The necessity of Palestinian universities to adhere to the application of transparency standards in all university activities. The need to benefit from regional and international experience in the application of transparency systems within universities and to examine the possibility of applying these systems in our universities. As well as the need to engage in the program of teaching transparency in universities, as it is confirmed that only five universities participated in this experiment. The importance of raising awareness among the employees of Palestinian universities to clarify the foundations of building transparency and its dimensions to represent the active supporter through workshops and seminars. (shrink)

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 (...) of this expert system is to get the appropriate diagnosing of the illness, dealing with it quickly, and tips for permanent treatment whenever possible is given out. SL5 object expert system language was used for designing and implementing the proposed expert system. (shrink)

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 (...) heart disease or not using the medical features of the person. We used many different algorithms of machine learning such as Gaussian Mixture, Nearest Centroid, MultinomialNB, Logistic RegressionCV, Linear SVC, Linear Discriminant Analysis, SGD Classifier, Extra Tree Classifier, Calibrated ClassifierCV, Quadratic Discriminant Analysis, GaussianNB, Random Forest Classifier, ComplementNB, MLP Classifier, BernoulliNB, Bagging Classifier, LGBM Classifier, Ada Boost Classifier, K Neighbors Classifier, Logistic Regression, Gradient Boosting Classifier, Decision Tree Classifier, and Deep Learning to predict and classify the patient with heart disease. A quite helpful approach was used to regulate how the model can be used to improve the accuracy of prediction of heart diseases in any person. The strength of the proposed model was very satisfying and was able to predict evidence of having a heart disease in a particular person by using Deep Learning and Random Forest Classifier which showed a good accuracy in comparison to the other used classifiers. The proposed heart disease prediction model will enhances medical care and reduces the cost. This study gives us significant knowledge that can help us predict the person with heart disease. The dataset was collected from Kaggle depository and the model is implemented using python. (shrink)

Abstract. Intelligent Tutoring System Builder (ITSB) is an authoring tool designed and developed to aid teachers in constructing intelligent tutoring systems in a multidisciplinary fields. The teacher is needed to create a set of pedagogical fundamentals, which, in line, are inured to automatically build up a broad tutor framework and construct an intelligent tutoring system. In this paper an explanation of the theory and the architecture of the tool is outlined. A presentation of several system components, the requirements of the (...) different components, integration of these components in ITSB tool are shown. Furthermore, implanting of requirements, cognitive principle, and common design fundamentals in the tool to ease the use of teachers. A variety of design matters, an example of building an intelligent tutoring system for teaching Java language using ITSB tool and an evaluation are presented. (shrink)

Abstract : Background: Vegetable agriculture is very important to human continued existence and remains a key driver of many economies worldwide, especially in underdeveloped and developing economies. Objectives: There is an increasing demand for food and cash crops, due to the increasing in world population and the challenges enforced by climate modifications, there is an urgent need to increase plant production while reducing costs. Methods: In this paper, Lemon classification approach is presented with a dataset that contains approximately 2,000 images (...) belong to 3 species at a few developing phases. Convolutional Neural Network (CNN) algorithms, a deep learning technique extensively applied to image recognition was used, for this task. The results: found that CNN-driven lemon classification applications when used in farming automation have the latent to enhance crop harvest and improve output and productivity when designed properly. The trained model achieved an accuracy of 99.48% on a held-out test set, demonstrating the feasibility of this approach. (shrink)

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 (...) none sarcasm automatically is very important. The aim of the study is to build a sarcasm model that detect headline news using machine and deep learning and attempt to understand how a computer learns the patterns of sarcasm. The dataset used in this study was collected from Kaggle depository. We examined 21 algorithms of machine learning and one deep learning algorithm for detecting sarcasm in headline news. The evaluation metric used in this study are Accuracy, F1-measure, Recall, Precision, and Time needed for training and evaluation. The deep learning model achieved accuracy (95.27%), recall (96.62%), precision (94.15%), F1-score (95.37%) and time needed to train the mode (400 seconds), with loss of around 0.3398. However, the algorithm of machine learning that achieved the highest F1-Score is Passive Aggressive Classifier. It was the top classier for sarcasm detection among the machine learning algorithms with accuracy (95.50%), recall (96.09 %), precision (94.30%), F1-score (95.19%) and time needed to train the mode (0.31 seconds). (shrink)

This essay first applies the general issue of realism vs. antirealism to theology and the philosophy of religion, distinguishing between several different ”levels’ of the realism dispute in this context. A pragmatic approach to the problem of realism regarding religion and theology is sketched and tentatively defended. The similarities and differences of scientific realism, on the one hand, and religious and/or theological realism, on the other hand, are thereby also illuminated. The concept of recognition is shown to be crucially relevant (...) to the issue of realism especially in its pragmatist articulation. (shrink)

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 (...) the disease. Methods: In this paper, the expert system is designed for the ability of agricultural engineers to detect and diagnose disease of castor like as: seeding blight, alternaria blight, cercospora leaf spot, powdery mildew and wilt. This system presents the disease symptoms, survival and spread, favorable conditions and image for each disease. Clips and Delphi expert system languages are used for designing and implementing the proposed expert system. Results: The expert system in the diagnosis of castor diseases was assessed by farmers and agricultural engineers and they were satisfied and accepted with its quality of performance. Conclusions: The expert system is easy for farmers and people have experience in the plant of castor to detect and diagnosis the symptoms that may face this plant from several disease. (shrink)

My aim here is to make sense of Plato's account of desire in the middle dialogues. To do that I need to unify or reconcile what are at first sight two quite different accounts: the doctrine of eros in the Symposium and the tripartite theory of motivation in the Republic. It may be that the two theories are after all irreconcilable, that Plato simply changed his mind on the nature of human desire after writing the Symposium and before composing the (...) Republic. But that conclusion can be justified only if attempts to reconcile the two theories end in failure. The attempt must be made first. (shrink)

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 (...) none sarcasm automatically is very important. The aim of the study is to build a sarcasm model that detect headline news using machine and deep learning and attempt to understand how a computer learns the patterns of sarcasm. The dataset used in this study was collected from Kaggle depository. We examined 21 algorithms of machine learning and one deep learning algorithm for detecting sarcasm in headline news. The evaluation metric used in this study are Accuracy, F1-measure, Recall, Precision, and Time needed for training and evaluation. The deep learning model achieved accuracy (95.27%), recall (96.62%), precision (94.15%), F1-score (95.37%) and time needed to train the mode (400 seconds), with loss of around 0.3398. However, the algorithm of machine learning that achieved the highest F1-Score is Passive Aggressive Classifier. It was the top classier for sarcasm detection among the machine learning algorithms with accuracy (95.50%), recall (96.09 %), precision (94.30%), F1-score (95.19%) and time needed to train the mode (0.31 seconds). (shrink)

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 (...) strawberry disease to make it easier for farmers to find the right treatment based on the appropriate diagnosis. Objectives: The main goal of this expert system is to get the appropriate diagnosis of disease and the correct treatment. Methods: In this paper the design of the proposed Expert System which was produced to help Farmers and students interested in agriculture strawberry in diagnosing many of the strawberry diseases such as: Leaf Spots, Grey Mold, Red Stele/Red Core, Wilt, Powdery Mildew, Alternaria Spot, Black Root Rot, Anthracnose (black spot), and Angular Leaf Spot. The proposed expert system presents an overview about strawberry diseases are given, the cause of diseases are outlined and the treatment of disease whenever possible is given out. CLIPS language was used for designing and implementing the proposed expert system. Results: The proposed strawberry diseases diagnosis expert system was evaluated by Farmers and they were satisfied with its performance. Conclusions: The Proposed expert system is very useful for Farmers with strawberry problem and students interested in agriculture strawberry. (shrink)

In this paper I defend the traditional interpretations of Kant’s Formula of a Law of Nature from recent attacks leveled by Faviola Rivera-Castro, James Furner, Ido Geiger, Pauline Kleingeld and Sven Nyholm. After a short introduction, the paper is divided into four main sections. In the first, I set out the basics of the three traditional interpretations, the Logical Contradiction Interpretation, the Practical Contradiction Interpretation and the Teleological Contradiction Interpretation. In the second, I examine the work of Geiger, Kleingeld and (...) Nyholm: these three commentators reject the traditional interpretations entirely, but I argue that this rejection is ill-founded. In the third and fourth, I take a detailed look at Furner’s work, work in which he seeks to revise (rather than reject) the traditional interpretations. I argue that, despite his more modest aims, Furner’s revision is also ill-founded. (shrink)

In this paper, I confront Parfit’s Mixed Maxims Objection. I argue that recent attempts to respond to this objection fail, and I argue that their failure is compounded by the failure of recent attempts to show how the Formula of Universal Law can be used to demarcate the category of obligatory maxims. I then set out my own response to the objection, drawing on remarks from Kant’s Metaphysics of Morals for inspiration and developing a novel account of how the Formula (...) of Universal Law can be employed to determine the deontic status of action tokens, action types, and maxims. (shrink)

Diagnosing flatulence involves a thorough assessment of an individual's symptoms, medical history, and, if necessary, the use of diagnostic tests. Healthcare providers gather information about the patient's medical background and conduct a physical examination to identify any signs of gastrointestinal issues. Dietary habits are evaluated, and potential triggers are identified through an elimination diet. Diagnostic tests such as breath tests, stool analysis, or imaging studies may be performed to further investigate the underlying causes of excessive flatulence. Accurate diagnosis is crucial (...) for effective management and treatment of flatulence, enabling individuals to gain control over their symptoms and address any underlying conditions. (shrink)

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 (...) to produce Pneumonia detection and classification models using x-ray imaging for rapid and easy detection and identification of pneumonia. In this thesis, we review ways and mechanisms to use deep learning techniques to produce a model for Pneumonia detection. The goal is find a good and effective way to detect pneumonia based on X-rays to help the chest doctor in decision-making easily and accuracy and speed. The model will be designed and implemented, including both Dataset of image and Pneumonia detection through the use of Deep learning algorithms based on neural networks. The test and evaluation will be applied to a range of chest x-ray images and the results will be presented in detail and discussed. This thesis uses deep learning to detect pneumonia and its classification. (shrink)

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 (...) certain type of fruit meets their nutritional requirement. In this paper, machine learning based approach is presented for classifying and identifying 10 different fruit with a dataset that contains 6847 images use 4793 images for training, 1027 images for validation and 1027 images for testing. A deep learning technique that extensively applied to image recognition was used. We used 70% from image for training and 15% from image for validation 15% for testing. Our trained model achieved an accuracy of 100% on a held-out test set, demonstrating the feasibility of this approach. (shrink)

In many areas, technology has facilitated many things, diagnosing diseases, regulating traffic and teaching students in schools rely on Intelligent systems to name a few. At present, traditional classroom-based education is no longer the most appropriate in schools. From here, the idea of intelligent e-learning for students to increase their culture and keep them updated in life began. E-learning has become an ideal solution, relying on artificial intelligence, which has a footprint in this through the development of systems based on (...) education without a teacher taking into account the individual differences of students. This study describes intelligent tutoring system for teaching the Data Manipulation Language (DML) Commands Using SQLite to non IT students to overcome the difficulties they face. The System was built as education system by using the researcher own authoring tool that based on mobile and web App. The basic idea of this system is a systematic introduction into the concept of Database and its DML query. The system presents the topic of DML Commands, help student to execute what they are learn from the system content using the practical part of the system and administers automatically adapted at run time to the student’s individual growth. The system was assessed by a group of teachers and students and the outcome showed as 91% from the database specialists, 94% from Diploma students group and 89% from the secondary school students group. (shrink)

Infants and children are suffering from a lots of nausea and vomiting problems. Doctors, usually face various difficulties dealing with these problems because of their similarities. In this paper, we present an expert system to help users in getting the correct diagnosis of problems of nausea and vomiting in infants and children (Gastro-esophageal reflux, Gastroenteritis, Systemic Infection, Bowel obstruction, Tumors, A bleeding disease, tonsillitis, and Hepatitis pharynx). Furthermore, this expert system provide information about the disease and how to deal with (...) it. SL5 Object expert system language was used to design and implement this expert system. (shrink)

Abstract: In this research, an Artificial Neural Network (ANN) model was developed and tested to predict effect of oxygen consumption of thylakoid membranes (chloroplasts) from spinach after inhibition. A number of factors were identified that may affect of oxygen consumption of thylakoid membranes from spinach. Factors such as curve, herbicide, dose, among others, as input variables for the ANN model. A model based on multi-layer concept topology was developed and trained using the data from some inhibition of photosynthesis in farms. (...) The evaluation of testing the dataset shows that the ANN model is capable of correctly predicting the effect of oxygen consumption of thylakoid membranes (chloroplasts) from spinach after inhibition with 100% accuracy. (shrink)

Proponents of the utilitarian animal welfare argument (AWA) for veganism maintain that it is reasonable to expect that adopting a vegan diet will decrease animal suffering. In this paper I argue otherwise. I maintain that (i) there are plausible scenarios in which refraining from meat-consumption will not decrease animal suffering; (ii) the utilitarian AWA rests on a false dilemma; and (iii) there are no reasonable grounds for the expectation that adopting a vegan diet will decrease animal suffering. The paper is (...) divided into four sections. In the first, I set out the utilitarian AWA in its original form. I give some background and I distinguish it from other, related arguments. In the second, I discuss the causal impotence objection, a popular objection to the utilitarian AWA. I explain how the objection works by means of a conceptual distinction between consumers and producers. In the third, I explain how proponents of the utilitarian AWA respond to this objection. In particular, I set out in some detail what I call the expected utility response. In the fourth and final section, I use the three objections noted above to explain why I do not find this response convincing. (shrink)

This paper presents the design and development of intelligent tutoring system for teaching Oracle. The Oracle Intelligent Tutoring System (OITS) examined the power of a new methodology to supporting students in Oracle programming. The system presents the topic of Introduction to Oracle with automatically generated problems for the students to solve. The system is dynamically adapted at run time to the 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. (shrink)