This supplement provides the full proof of Theorem 2 from "'Adding Up' Reasons" (where the Theorem is stated and a proof is only gestured at).

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)

Since at least the 1960s, deontic logicians and ethicists have worried about whether there can be normative systems that allow conflicting obligations. Surprisingly, however, little direct attention has been paid to questions about how we may reason with conflicting obligations. In this paper, I present a problem for making sense of reasoning with conflicting obligations and argue that no deontic logic can solve this problem. I then develop an account of reasoning based on the popular idea in ethics that reasons (...) explain obligations and show that it solves this problem. (shrink)

How do multiple reasons combine to support a conclusion about what to do or believe? This question raises two challenges: How can we represent the strength of a reason? How do the strengths of multiple reasons combine? Analogous challenges about confirmation have been answered using probabilistic tools. Can reductive and nonreductive theories of reasons use these tools to answer their challenges? Yes, or more exactly: reductive theories can answer both challenges. Nonreductive theories, with the help of a result in confirmation (...) theory, can answer one, and there are grounds for optimism that they can answer the other. (shrink)

Reasons can interact in a variety of ways to determine what we ought to do or believe. And there can be cases where two reasons to do an act or have a belief are individually worse than a reason to not do that act or have that belief, but the reasons together are better than the reason to not do that act or have that belief. So the reasons together―which we can call the accrual of those reasons—can have a strength (...) that is an increasing function of the strengths of the individual reasons. In this paper, we will look at how reasons determine what we ought to do and believe in cases where the accrual of reasons is relevant. Our focus will not primarily be on questions about the nature of individual reasons and their weight. Instead, we will at the outset rely on our pretheoretical grip on what reasons there are and how weighty they are individually and ask the more formal or structural question of how to determine the strength of their accrual based on these facts. In looking at these issues, my goal will not be anything as ambitious as developing a full theory of the accrual of reasons. Rather, my goal will be more modest: I will introducing some of the challenges for providing an adequate model and argue that a promising approach to resolving these challenges involves making use of the familiar distinction in moral philosophy between derivative and non-derivative normative notions. (shrink)

One of the popular albeit controversial ideas in the last century of moral philosophy is that what we ought to do is explained by our reasons. And one of the central features of reasons that accounts for their popularity among normative theorists is that they can conflict. But I argue that the fact that reasons conflict actually also poses two closely related problems for this popular idea in moral philosophy. The first problem is a generalization of a problem in deontic (...) logic concerning the existence of conflicting obligations. The second problem arises from a tension between the fact that reasons can conflict and a model of how reasons explain ‘ought’s that has been widely accepted. Having presented each of these problems, I develop a unified solution to them that is informed by results in both ethics and deontic logic. An important implication of this solution is that we must distinguish between derivative and nonderivative reasons and revise our conception how it is that reasons explain ‘ought’s. (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)

A traditional picture is that cases of deontic constraints--- cases where an act is wrong (or one that there is most reason to not do) even though performing that act will prevent more acts of the same morally (or practically) relevant type from being performed---form a kind of fault line in ethical theory separating (agent-neutral) consequentialist theories from other ethical theories. But certain results in the recent literature, such as those due to Graham Oddie and Peter Milne in "Act and (...) Value", do not sit well this traditional wisdom. My aim in this paper is to argue that both the traditional wisdom and Oddie and Milne are mistaken. I begin by looking more closely at the traditional wisdom and why it fails (§1). Then I develop my account of this fault line in ethical theory and its importance (§2). Finally I show that a diagnosis of where Oddie and Milne go wrong follows as a corollary of this new account (§3). An important upshot will be that discussions of cases of deontic constraints would do best to focus on the account of the nature and importance of the cases identified in this paper rather than continuing to work with the mistaken traditional picture. (shrink)

The verdicts standard consequentialism gives about what we are obligated to do crucially depend on what theory of value the consequentialist accepts. This makes it hard to say what separates standard consequentialist theories from non-consequentialist theories. This article discusses how we can draw sharp lines separating standard consequentialist theories from other theories and what assumptions about goodness we must make in order to draw these lines. The discussion touches on cases of deontic constraints, cases of deontic options, and cases involved (...) in the so-called "actualism"/"possibilism" debate. What emerges is that there are various interesting patterns relating the different commitments of consequentialism, different principles about obligation and about goodness, and different rules concerning how facts about values determine facts about obligation. (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)

In this chapter, we begin by sketching in the broadest possible strokes the ideas behind two formal systems that have been introduced with to goal of explicating the ways in which reasons interact to support the actions and conclusions they do. The first of these is the theory of defeasible reasoning developed in the seminal work of Pollock; the second is a more recent theory due to Horty, which adapts and develops the default logic introduced by Reiter to provide an (...) account of reasons. However, the implementations are complex enough, in both cases, to prevent anything more than this sketch. And we would not want to give the impression that we think that work on the logic of reasons must follow the path mapped out in either of these theories—indeed, we feel that the field is wide open. In the remainder of the chapter, therefore, will concentrate on a number of issues bearing on the logic of reasons that are either not treated in the work of Pollock and Horty, or whose treatment there is, we feel, either inadequate or incomplete. These are: first, the question of whether it is necessary to understand logical interactions among reasons themselves, rather than simply between reasons and the actions or conclusions they support, and if so, what principles might govern these interactions; second, priority relations among reasons and the notion of reason accrual; and third, some problems posed by undercutting defeat. (shrink)

ABSTRACT:Organismal superposition holds that the same individual both is and is not an organism, as a consequence of organismal pluralism. When coupled with the assumption that death is the cessation of an organism, this entails that there is no unique answer as to whether brain death is biological death. This essay argues that concerns about organismal pluralism and superposition do not undermine a theory of biological death, nor entail any metaphysical indeterminacy about the biological vital status of a brain-dead individual.

There is consensus among computer scientists, logicians, and philosophers that good reasoning with qualitative beliefs must have the structural property of cumulative transitivity or, for short, cut. This consensus is typically explicitly argued for partially on the basis of practical and mathematical considerations. But the consensus is also implicit in the approach philosophers take to almost every puzzle about reasoning that involves multiple steps: philosophers typically assume that if each step in reasoning is acceptable considered on its own, the whole (...) chain of reasoning must also acceptable. In this paper I focus on whether there are good philosophical reasons for thinking that the consensus that good reasoning must satisfy cut is true. My central claim is that we should not accept the consensus—good reasoning might not satisfy cut. In particular, I consider four arguments for the consensus and explain why they are unpersuasive. (§2-5). I then show that the issue of whether good reasoning is cut turns on a substantive yet until now unnoticed question in epistemology (§6). (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)

One family of maximizing act consequentialist theories are actualist direct theories. Indeed, historically there are at least three different forms of actualist direct consequentialism (due to Bentham, Moore, and contemporary consequentialists). This paper is about the logical differences between these three actualist direct theories and the differences between actualist direct theories and their competitors. Three main points emerge. First, the sharpest separation between actualist direct theories and their competitors concerns the so-called inheritance principle. Second, there are a myriad of other (...) logical differences among actualist direct theories. Third, one theory (Moore's theory) stands out among actualist direct theories because it entails a variety of logical principles. This fact may count in favor of that theory. (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.

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)

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)

Though there have been productive interactions between moral philosophers and deontic logicians, there has also been a tradition of neglecting the insights that the fields can offer one another. The most sustained interactions between moral philosophers and deontic logicians have notbeen systematic but instead have been scattered across a number of distinct and often unrelated topics. This chapter primarily focuses on three topics. First, we discuss the “actualism/possibilism” debate which, very roughly, concerns the relevance of what one will do at (...) some future time to what one ought to do at present (§2). This topic is also used to introduce various modal deontic logics. Second we discuss the particularism debate which, very roughly, concerns whether there can be any systematic general theory of what we ought to do (§3). This topic is also used to introduce various non-modal deontic logics. Third, we discuss collective action problems which concern the connection between the obligations of individuals and the behavior and obligations of groups of individuals (§4).This topic is also used to discuss formal systems that allow us to study the relationship between individuals and groups. The chapter also contains a general discussion of the relation between ethical theory and deontic logic (§1) and a brief consideration of other miscellaneous topics (§5). (shrink)

A moral dilemma is a situation where an agent’s obligations conflict. Debate in this area focuses on the question of whether genuine moral dilemmas exist. This question involves considering not only the nature and significance of dilemmas, but also the connections between dilemmas, the logic of obligation and moral emotions.

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)

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)

The research aims to identify the trends of Palestinian higher educational institutions in Gaza Strip as learning organizations from the perspective of senior management in the Palestinian universities in Gaza Strip. The researchers used descriptive analytical approach and used the questionnaire as a tool for information gathering. The questionnaires were distributed to senior management in the Palestinian universities. The study population reached (344) employees in senior management is dispersed over (3) Palestinian universities. A stratified random sample of (182) employees from (...) the Palestinian universities was selected and the recovery rate was (69.2%). Statistical analysis (SPSS) program was used for analysis and processing the data. The study found the following results: There is an agreement about: the importance of the focus of "organizational structure" with an average approval, the importance of "technological infrastructure" axis with high approval, and the importance of "strategic" with an average approval. The results concluded that the study sample agree on the importance of "organizational dimension" highly. The results showed that the sample believe that the "strategic leadership" level in the universities got medium-approval. There is a fair level agreement about the axis of interest "teams / committees". There is an agreement about the importance of the "human dimension" moderately. The results showed that the sample is highly agreed about the importance of focus of the "knowledge management", and the focus of the "continuing education". They agreed weakly to somewhat about the importance of the focus of "scientific research", moderately agree about the importance of the center of "institutional culture", agree moderately on the importance of "cognitive dimension". The results showed that the sample largely agree on the importance of the focus of "strategic partnerships and alliances". They agree highly on the axis "keep up with the labor market" and on the focus of the importance of "technology incubators". The results showed that the sample moderately agree about the importance of the theme on "consulting and training", the importance of the focus of "social responsibility", and the focus of the "Community dimension". The study found a group of recommendations including: there is a need to provide suitable environment that achieve learning organizations. There is a need to develop the technological infrastructure (hardware, software, networks, databases, and human skills) because of the great advantages that they offer. The universities need to adopt knowledge management in the academic and administrative departments because knowledge is the core of the work of these departments. The establishment of technology incubators in universities to adopt outstanding university research projects, to protect, to supports, and to market them; furthermore, to develop the capabilities and skills of employees in the field of information technology. (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)

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)

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)

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: Classifying sea animals is an important problem in marine biology and ecology as it enables the accurate identification and monitoring of species populations, which is crucial for understanding and protecting marine ecosystems. This paper addresses the problem of classifying 19 different sea animals using convolutional neural networks (CNNs). The proposed solution is to use a pretrained MobileNetV2 model, which is a lightweight and efficient CNN architecture, and fine-tune it on a dataset of sea animals. The results of the study (...) show that the fine-tuned MobileNetV2 model is able to achieve an accuracy of 85% on the classification task, which is competitive with the state-of-the-art methods. Additionally, the study also found that data augmentation and regularization techniques such as dropout were important for preventing overfitting and improving the performance of the model. This study demonstrates the potential of using pretrained models and efficient CNN architectures for classifying sea animals, and it provides insights into the challenges and best practices for solving this important problem in marine biology and ecology. (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: 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)

Semantics for Reasons, by WeaverBryan R and ScharpKevin. Oxford: Oxford University Press, 2019. Pp. 166.

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)

Experimental philosophers have gathered impressive evidence for the surprising conclusion that philosophers' intuitions are out of step with those of the folk. As a result, many argue that philosophers' intuitions are unreliable. Focusing on the Knobe Effect, a leading finding of experimental philosophy, we defend traditional philosophy against this conclusion. Our key premise relies on experiments we conducted which indicate that judgments of the folk elicited under higher quality cognitive or epistemic conditions are more likely to resemble those of the (...) philosopher. We end by showing how our experimental findings can help us better understand the Knobe Effect. (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. 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: 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)

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 (...) to classify memory loss and to know the patient at what level and his assessment of Alzheimer's disease through CT scans of the brain. In this thesis, we review ways and techniques to use deep learning classification to classifying the Alzheimer's Disease The proposed method used to improve patient care, reduce costs, and allow fast and reliable analysis in large studies. The model will be designed using Python language for implementing the system, which is very useful for doctors, classifying the Alzheimer's Disease, was used. The model used 70% from image for training and 30% from image for validation, our trained model achieved an accuracy of 100% on a held-out test set. (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)

ASP.net is one of the most widely used languages in web developing of its many advantages, so there are many lessons that explain its basics, so it should be an intelligent tutoring system that offers lessons and exercises for this language.why tutoring system? Simply because it is one-one teacher, adapts with all the individual differences of students, begins gradually with students from easier to harder level, save time for teacher and student, the student is not ashamed to make mistakes, and (...) more. Therefore, in this paper, we describe the design of an Intelligent Tutoring System for teaching ASP.net to help students learn ASP.net easily and smoothly. Tutor provides beginner level in ASP.net. Finally, we evaluated our tutor and the results were excellent by students and teacher. (shrink)

Buildings energy consumption is growing gradually and put away around 40% of total energy use. Predicting heating and cooling loads of a building in the initial phase of the design to find out optimal solutions amongst different designs is very important, as ell as in the operating phase after the building has been finished for efficient energy. In this study, an artificial neural network model was designed and developed for predicting heating and cooling loads of a building based on a (...) dataset for building energy performance. The main factors for input variables are: relative compactness, roof area, overall height, surface area, glazing are a, wall area, glazing area distribution of a building, orientation, and the output variables: heating and cooling loads of the building. The dataset used for training are the data published in the literature for various 768 residential buildings. The model was trained and validated, most important factors affecting heating load and cooling load are identified, and the accuracy for the validation was 99.60%. (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)

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)

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)

This review delves into the influence of big data analytics on project management effectiveness and project success rates. By examining applications, accomplishments, hindrances, and emerging developments in the context of big data analytics and project management, this review provides insights into its transformative potential. Results indicate that big data analytics fosters improved project performance, more robust risk management, and heightened adaptability. However, challenges related to data quality, privacy, and project manager training remain to be addressed. This review underscores the value (...) of data-driven decision-making for both practitioners and researchers in the project management field. (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)

Justo antes de la pandemia por COVID-19, la Organización Mundial de la Salud definió unas prioridades de trabajo para la década 2020-2030. Un grupo interdisciplinario de profesionales de la salud reflexiona sobre estas prioridades, determinando unas categorías de análisis y, desde una perspectiva bioética, analiza cada una de ellas, ve su pertinencia, algunos eventos causales, las implicaciones que pueden tener si no son enfrentadas adecuadamente y hace sugerencias sobre la forma de llevarlas a cabo. En esta primera entrega se analiza (...) el primer grupo de prioridades estratégicas: “poblaciones más sanas”. En las conclusiones se destaca la conveniencia de acometer cada una de ellas de una manera colaborativa, gubernamental y privada; de reestructurar el sector salud con base en estas prioridades, aprovechando la experiencia obtenida en la lucha contra el COVID-19. La relación del ser humano con el medio ambiente también debe cambiar, apelando a la responsabilidad humana por el cuidado del planeta. (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)

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: 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)