We often say that one reason is stronger, or weightier, than another. These are metaphors. What does normative strength or weight really consist in? Scanlon (2014) offers a novel answer to this question. His answer appeals to counterfactuals of various kinds. I argue that appealing to counterfactuals leads to deep problems for his view.

Moorean arguments are a popular and powerful way to engage highly revisionary philosophical views, such as nihilism about motion, time, truth, consciousness, causation, and various kinds of skepticism (e.g., external world, other minds, inductive, global). They take, as a premise, a highly plausible first-order claim (e.g., cars move, I ate breakfast before lunch, it’s true that some fish have gills) and conclude from it the falsity of the highly revisionary philosophical thesis. Moorean arguments can be used against nihilists in ethics (...) (error theorists), too. Recently, error theorists have recognized Moorean arguments as a powerful challenge and have tried to meet it. They’ve argued that moral Moorean premises seem highly credible to us, but aren’t, by offering various debunking explanations. These explanations all appeal to higher-order evidence—evidence of error in our reasoning. I argue that drawing attention to higher-order evidence is a welcome contribution from error theorists, but that the higher-order evidence actually counts further against error theoretic arguments—including their debunking explanations—and further in favor of Moorean arguments and the commonsense views they support. Along the way I answer a few prominent objections to Moorean arguments: that they are objectionably question-begging, rely on categorizing some facts as “Moorean Facts”, and that reports of one’s credence in a proposition bears no interesting relation to that proposition’s credibility. (shrink)

Arguments from disagreement against moral realism begin by calling attention to widespread, fundamental moral disagreement among a certain group of people. Then, some skeptical or anti-realist-friendly conclusion is drawn. Chapter 2 proposes that arguments from disagreement share a structure that makes them vulnerable to a single, powerful objection: they self-undermine. For each formulation of the argument from disagreement, at least one of its premises casts doubt either on itself or on one of the other premises. On reflection, this shouldn’t be (...) surprising. These arguments are intended to support very strong metaphysical or epistemological conclusions about morality. They must therefore employ very strong metaphysical or epistemological premises. But, given the pervasiveness of disagreement in philosophy, especially about metaphysics and epistemology, very strong premises are virtually certain to be the subject of widespread, intractable disagreement—precisely the sort of disagreement that proponents of these arguments think undermine moral claims. Thus, these arguments undermine their own premises. If Chapter 2’s argument is sound, it provides realists with a single, unified strategy for responding to any existing or forthcoming arguments from disagreement. (shrink)

One of the deepest and longest-lasting debates in ethics concerns a version of the Euthyphro question: are choiceworthy things choiceworthy because agents have certain attitudes toward them or are they choiceworthy independent of any agents’ attitudes? Reasons internalists, such as Bernard Williams, Michael Smith, Mark Schroeder, Sharon Street, Kate Manne, Julia Markovits, and David Sobel answer in the first way. They think that all of an agent’s normative reasons for action are grounded in facts about that agent’s pro-attitudes (e.g., her (...) desires, valuing states, normative judgments). According to the most popular brand of internalism, idealizing internalism, an agent’s reasons are grounded, not in her actual pro-attitudes, but rather in what her pro-attitudes would be in suitably idealized conditions. Idealizing internalists presuppose that, for any agent with an irrational set of attitudes, there is one uniquely rational set that that agent would have if she were to undergo the relevant idealizing process. I argue that this assumption is false and that it raises two puzzles for idealizing internalism: one about the existence of practical reasons and another about their normative weight. I argue that idealizing internalists have an adequate solution to the first puzzle but not the second. Indeed, when they try to solve the second puzzle, they confront a dilemma. This second puzzle and the associated dilemma thus constitutes a powerful, but so far unnoticed, difficulty for idealizing internalism. (shrink)

People sometimes knowingly undermine the achievement of their own goals by, e.g., playing the lottery or borrowing from loan sharks. Are these agents acting irrationally? The standard answer is “yes.” But, in a recent award-winning paper, Jennifer Morton argues “no.” On her view, the norms of practical reasoning an agent ought to follow depend on that agent’s resource context (roughly, how rich or poor they are). If Morton is correct, the orthodox view that the same norms of practical rationality apply (...) to all agents needs revision. I argue that Morton’s arguments fail on empirical and philosophical grounds. What’s at stake? If Morton is correct, poverty relief agencies ought to re-design their incentives so resource-scarce agents can rationally respond to them. If I’m correct, resource-scarce agents do act irrationally in the cases under discussion, and we shouldn’t be shy about saying so. Instead of declaring them rational, we should try to understand the causes of their irrational behavior and help them better succeed by their own lights. (shrink)

In his recent article entitled ‘Can We Believe the Error Theory?’ Bart Streumer argues that it is impossible (for anyone, anywhere) to believe the error theory. This might sound like a problem for the error theory, but Streumer argues that it is not. He argues that the un-believability of the error theory offers a way for error theorists to respond to several objections commonly made against the view. In this paper, we respond to Streumer’s arguments. In particular, in sections 2-4, (...) we offer several objections to Streumer’s argument for the claim that we cannot believe the error theory. In section 5, we argue that even if Streumer establishes that we cannot believe the error theory, this conclusion is not as helpful for error theorists as he takes it to be. (shrink)

In this paper I respond to Mathias Risse's objections to my critique of his views on racial profiling in Philosophy and Public Affairs. I draw on the work of Richard Sampson and others on racial disadvantage in the USA to show that racial profiling likely aggravates racial injustices that are already there. However, I maintain, clarify and defend my original claim against Risse that racial profiling itself is likely to cause racial injustice, even if we abstract from unfair background (...) conditions. I then respond to Levin's claims that there is no serious racial injustice in the contemporary USA and differentiate between Risse's attempt - albeit unsuccessful - to provide an egalitarian justification for racial profiling from the frankly inegalitarian assumptions that underpin the claims of Michael Levin. (shrink)

Liao and Carbonell argue that medical devices are often not merely biased, but rather materialize oppression through the perpetuation of oppression into the present and future (Liao and Carbonell 2...

From a modernist perspective, it may be difficult to ascribe graphics to any form of traditional African art. This could be due to the embrace of western values by Africans, and of modernity on the one hand, and the overwhelming negative influence of westernization on the diverse African cultural practices, on the other hand. However, many elements of the traditional art forms are imbued with icons and symbols which expressions may be viewed as graphical in nature. This paper looks into (...) the dynamics of graphics in the art of the traditional Ibibio society of Nigeria and attempts to appraise form and content. It is aimed at investigating the various symbolic applications in Ibibio traditional art forms and to establish the degree of graphics inter face with these art forms. The paper expounds the term graphics, identifies, and relates it to, salient properties of graphics in the art products of the traditional Ibibio society. It also examines the manner in which societal norms and social institutions are fundamental to the art forms proportionate to the communicative indices. The methodology for this study includes in situ study, formalism, iconographic studies and library research. The paper concludes that graphics is a crucial index in the arts of the traditional Ibibio society of Nigeria and, indeed, Africa. (shrink)

From Tarde to Deleuze and Foucault: The Infinitesimal Revolution -/- ,Palgrave Macmillan: London, 2018; 154 pp.: ISBN 9783319551487 -/- Sergio Tonkonoff,.

We provide a novel defense of the possibility of level-splitting beliefs and use this defense to show that the steadfast response to peer disagreement is not, as it is often claimed to be, unnecessarily dogmatic. To provide this defense, a neglected form of moral disagreement is analysed. Within the context of this particular kind of moral disagreement, a similarly neglected form of level-splitting belief is identified and then defended from critics of the rationality of level-splitting beliefs. The chapter concludes by (...) showing that proponents of the steadfast response to peer disagreement can adopt this form of level-splitting belief in the context of these moral disagreements while exemplifying intellectual humility, rather than dogmatism. (shrink)

In his recent book Error Theory: History, Critique, Defence, Jonas Olson attempts to revive the argument from queerness originally made famous by J.L. Mackie. In this paper, we do three things. First, we eliminate four untenable formulations of the argument. Second, we argue that the most plausible formulation is one that depends crucially upon considerations of parsimony. Finally, we evaluate this formulation of the argument. We conclude that it is unproblematic for proponents of moral non-naturalism—the target of the argument from (...) queerness. (shrink)

End-of-life care has a number of characteristics that make economic evaluation particularly challenging. These include proximity to death, the improbability of survival gain, individuals’ changing priorities, declining cognition and effects on close persons. In view of these particularities of end-of-life care, some researchers have determined that current ‘extra-welfarist’ approaches to defining do not adequately reflect well-being. As a result, suggestions are being made that would see the QALY approach either replaced or subject to significant redefinition. The purported goal of adopting (...) alternative evaluation approaches is to extend the evaluative space ‘beyond’. The purpose of this chapter is to guide the definition of what should be included in the evaluative space in end-of-life care. (shrink)

The truth of every human being is the end his life with death, and this leads to leaving assets and funds for those after him and can lead to hate between the heirs, it has made a point of Islamic law on all aspects of life, including the subject of the inheritance of the deceased. The main problem is how to get the knowledge of the basics of inheritance. This paper reviews work done in the use of expert system software (...) to calculate inheritance in Islam. A proposed expert system was designed and developed using CLIPS language to calculate the inheritance in Islam. (shrink)

In this paper, we present an intelligent tutoring system developed to help students in learning Computer Theory. The Intelligent tutoring system was built using ITSB authoring tool. The system helps students to learn finite automata, pushdown automata, Turing machines and examines the relationship between these automata and formal languages, deterministic and nondeterministic machines, regular expressions, context free grammars, undecidability, and complexity. During the process the intelligent tutoring system gives assistance and feedback of many types in an intelligent manner according to (...) the behavior of the student. An evaluation of the intelligent tutoring system has revealed reasonably acceptable results in terms of its usability and learning abilities are concerned. (shrink)

Lately in the past couple of years, there are an increasing in the normal rate of playing computer games or video games compared to the E-learning content that are introduced for the safety of our children, and the impact of the video game addictiveness that ranges from (Musculoskeletal issues, Vision problems and Obesity). Furthermore, this paper introduce an intelligent tutoring system for both parent and their children for enhancement the experience of gaming and tell us about the health problems and (...) how we can solve them, with an easy user interface that way can our children be happy and excited about the information and their health. (shrink)

The paper describes the design of an intelligent tutoring system for teaching Introduction to Computer Science-a compulsory curriculum in Al-Azhar University of Gaza to students who attend the university. The basic idea of this system is a systematic introduction into computer science. The system presents topics with examples. The system is dynamically checks student's individual progress. An initial evaluation study was done to investigate the effect of using the intelligent tutoring system on the performance of students enrolled in computer science (...) curriculum at Al-Azhar University, Gaza. The results showed a positive impact on the evaluators. (shrink)

Abstract: The COVID-19 pandemic has posed unprecedented challenges to global healthcare systems, necessitating accurate and timely forecasting of cases for effective mitigation strategies. In this research paper, we present a novel approach to predict COVID-19 cases using Artificial Neural Networks (ANNs), harnessing the power of machine learning for epidemiological forecasting. Our ANNs-based forecasting model has demonstrated remarkable efficacy, achieving an impressive accuracy rate of 97.87%. This achievement underscores the potential of ANNs in providing precise and data-driven insights into the dynamics (...) of the pandemic. However, this paper underscores the critical importance of a comprehensive evaluation beyond accuracy, including metrics such as sensitivity, specificity, and the area under the ROC curve (AUC-ROC), to assess the model's performance robustness. The research paper offers detailed insights into the architecture of the ANN model, encompassing critical hyperparameters, data preprocessing techniques, and regularization strategies employed to optimize model accuracy. Ethical considerations surrounding data privacy and potential biases within the COVID-19 dataset are also addressed. While the achieved accuracy is a significant milestone, this study underscores the dynamic and evolving nature of the pandemic, necessitating continuous model refinement and validation. Furthermore, it emphasizes the importance of considering false positives and false negatives in the context of public health decision-making. In conclusion, this research contributes to the arsenal of tools available for pandemic management by showcasing the potential of ANNs in COVID-19 case forecasting. It encourages ongoing exploration and adaptation of predictive models to enhance their applicability in real-world public health scenarios, ultimately contributing to more effective pandemic control and response efforts. (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)

Abstract: This research focuses on utilizing Artificial Neural Networks (ANNs) to predict Audit Risk accurately, a critical aspect of ensuring financial system integrity and preventing fraud. Our dataset, gathered from Kaggle, comprises 18 diverse features, including financial and historical parameters, offering a comprehensive view of audit-related factors. These features encompass 'Sector_score,' 'PARA_A,' 'SCORE_A,' 'PARA_B,' 'SCORE_B,' 'TOTAL,' 'numbers,' 'marks,' 'Money_Value,' 'District,' 'Loss,' 'Loss_SCORE,' 'History,' 'History_score,' 'score,' and 'Risk,' with a total of 774 samples. Our proposed neural network architecture, consisting of three (...) layers (1 input, 1 hidden, and 1 output), forms the core of this study. While it may seem simple, the power of ANNs lies not in complexity but in their ability to uncover intricate data patterns. The model underwent rigorous training and validation, resulting in remarkable outcomes—an accuracy of 100% and an average error rate of 0.000015. In addition to performance metrics, our research investigates feature importance, revealing the key contributors to Audit Risk prediction. Notably, 'Sector_score,' 'PARA_A,' 'SCORE_A,' 'PARA_B,' 'SCORE_B,' 'TOTAL,' 'numbers,' 'marks,' 'Money_Value,' 'District,' 'Loss,' 'Loss_SCORE,' 'History,' and 'History_score' emerged as the most influential factors, shedding light on the elements crucial for precise risk assessment. This study advances Audit Risk prediction models and highlights the potential of ANNs in strengthening financial system integrity and fraud prevention. The insights gained from our findings offer practical guidance for stakeholders in the audit and financial sectors. (shrink)

Tinnitus is a common condition characterized by the perception of sound in the absence of an external source, with potential negative physical and psychological impacts. Accurate and efficient diagnosis of tinnitus is crucial for appropriate treatment and management. Traditional diagnostic methods have limitations in terms of time, cost, and accuracy. To address these challenges, expert systems have emerged as a promising tool for tinnitus diagnosis. This paper explores the application of expert systems in tinnitus diagnosis, highlighting their potential to improve (...) accuracy and efficiency. By incorporating a knowledge base and rule-based decision-making, expert systems can provide valuable insights for accurate diagnosis and appropriate management of tinnitus. Further research and development in this area can enhance the clinical assessment and treatment of tinnitus, ultimately improving the quality of life for affected individuals. (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)

The research aims to identify the reality of modern methods applied in the process of performance assessments of employees in the municipalities of Gaza-strip, Complete Census method of community study was used, (571) questionnaires were distributed to all members of the community study, (524) questionnaires were recovery with rate of (91.76%). The most important findings of the study: There were statistically significant relationship differences between the applications of modern methods in the performance assessments of employees in the municipalities of Gaza-strip. (...) There was statistically significant relationship between the evaluation criteria that fit the required performance and the application of standards evaluations on performance of employees in the municipalities of Gaza-strip. There was statistically significant relationship between the use of methods, models for the evaluation of appropriate functions and the application of the performance assessments of employees in the municipalities of Gaza-strip. There was statistically significant relationship between the feedback and the application of performance assessments of employees in the municipalities of Gaza-strip. There was statistically significant relationship between the efficient, professional assessors and the application of the performance assessments of employees in the municipalities of Gaza-strip. There was statistically significant relationship between the extent of awareness of subordinates, participation in the evaluation of their performance and the application of the performance assessments of employees in the municipalities of Gaza-strip. The research also concluded a series of recommendations, including: that the design of evaluation models must be done with the participation of the employees and inform them of it, and that a date must be set to provide feedback and discuss the results with them, that they should be allowed grievance in front of an ad hoc committee in accordance with the known system. Direct manager must inform employees of their performance assessment date, discuss the results of the evaluation with them, and others should be involved with the direct manager of employees in their performance evaluation. The application of modern methods of performance evaluation through the good and purposeful planning should be used, analyzing and employing the results in administrative decisions regarding the employees, and the application of modern methods must be used in an effective and efficient performance evaluation. (shrink)

Abstract: In this study, we explore the challenge of identifying and preventing diseases in apple trees, which is a popular activity but can be difficult due to the susceptibility of these trees to various diseases. To address this challenge, we propose the use of Convolutional Neural Networks, which have proven effective in automatically detecting plant diseases. To validate our approach, we use images of apple leaves, including Apple Rot Leaves, Leaf Blotch, Healthy Leaves, and Scab Leaves collected from Kaggle which (...) is part from the Plant Village dataset. We generate a comprehensive training dataset using techniques such as image filtering, compression, and generation. Our model achieves impressive accuracy scores for all classes, with an overall accuracy of 99.93% on a dataset of 10,000 labeled images . (shrink)

Abstract: A corn crop typically refers to a large-scale cultivation of corn (also known as maize) for commercial purposes such as food production, animal feed, and industrial uses. Corn is one of the most widely grown crops in the world, and it is a major staple food for many cultures. Corn crops are grown in various regions of the world with different climates, soil types, and farming practices. In the United States, for example, the Midwest is known as the "Corn (...) Belt" due to its extensive corn production. Corn crops can be grown using a variety of methods, including conventional tillage, no-till farming, and the use of genetically modified crops. Due to its importance, there is a need for discovering the corn diseases and treating them. The aim of this study is to propose a deep learning model for the classification of corn leaf diseases based on Convolutional Neural Network. A model for classifying maize diseases was developed using a dataset for classifying Corn diseases that contains 4 classes of disease. The dataset was collected from Keggel website. The proposed model was trained, validated, and tested. The F1-score (99.83%), Recall (99.83%), precision (99.83%), Accuracy (99.83%). (shrink)

Abstract: In recent years, the outbreak of various poultry diseases has posed a significant threat to the global poultry industry. Therefore, the accurate and timely detection of chicken diseases is critical to reduce economic losses and prevent the spread of diseases. In this study, we propose a method for classifying chicken diseases using a convolutional neural network (CNN). The proposed method involves preprocessing the chicken images, building and training a CNN model, and evaluating the performance of the model. The dataset (...) used in this study comprises chicken images of three different diseases: Newcastle disease, avian influenza, and infectious bursal disease. The proposed method achieved an overall F1-score of 99.04% in classifying the chicken diseases. The results demonstrate the effectiveness of using CNN in classifying chicken diseases and provide a promising approach for early detection and diagnosis of poultry diseases. (shrink)

Abstract: The Knowledge-Based System for Diagnosing Breast Cancer aims to support medical students in enhancing their education regarding diagnosis and counseling. The system facilitates the analysis of biopsy images under a microscope, determination of tumor type, selection of appropriate treatment methods, and identification of disease-related questions. According to the Ministry of Health's annual report in Gaza, there were 7,069 cases of breast cancer between 2009 and 2014, with 1,502 cases reported in 2014. In an era dominated by visual information, where (...) 65% of the population are visual learners, the Knowledge-Based System serves as an effective tool to aid long-term information retention by utilizing visual and textual resources. The system features a user-friendly interface, enabling students to diagnose the disease and expand their understanding. Furthermore, it can be accessed via smartphones. The Knowledge-Based System comprises three primary components: Firstly, it provides specific patient-oriented questions to familiarize students with the questioning process. Secondly, it facilitates the analysis of biopsy sample images to determine their integrity and identify potential infections. Lastly, the system incorporates animated videos illustrating various approaches for treating breast cancer. (shrink)

This study employs machine learning to predict diabetes using a Kaggle dataset with 13 features. Our three-layer model achieves an accuracy of 98.73% and an average error of 0.01%. Feature analysis identifies Age, Gender, Polyuria, Polydipsia, Visual blurring, sudden weight loss, partial paresis, delayed healing, irritability, Muscle stiffness, Alopecia, Genital thrush, Weakness, and Obesity as influential predictors. These findings have clinical significance for early diabetes risk assessment. While our research addresses gaps in the field, further work is needed to enhance (...) model generalizability. (shrink)

Abstract: Context: grapevine leaves are an important agricultural product that is used in many Middle Eastern dishes. The species from which the grapevine leaf originates can differ in terms of both taste and price. Method: In this study, we build a deep learning model to tackle the problem of grape leaf classification. 500 images were used (100 for each species) that were then increased to 10,000 using data augmentation methods. Convolutional Neural Network (CNN) algorithms were applied to build this model (...) specifically using the pre-trained model on top of the VGG16 architecture. Then, dense layers were added to classify the output of the Convolutional layers and classify outputs to the five classes (species) the leaf belonged to. Results: It was found that feature extraction without fine-tuning the convolutional layers yielded poor results, about 86% accuracy, while training the whole network along with some data preprocessing gave the best results, about 99.45% accuracy on the testing dataset. Conclusions: The proposed CNN model is an effective one for the problem of classification of grape leaf species. (shrink)

Abstract: Heart attacks, or myocardial infarctions, are a leading cause of mortality worldwide. Early prediction and accurate analysis of potential risk factors play a crucial role in preventing heart attacks and improving patient outcomes. In this study, we conduct a comprehensive review of datasets related to heart attack analysis and prediction. We begin by examining the various types of datasets available for heart attack research, encompassing clinical, demographic, and physiological data. These datasets originate from diverse sources, including hospitals, research institutions, (...) and public health agencies. Our analysis aims to identify common features, data quality, and potential biases in these datasets. Next, we explore the predictive modeling techniques employed in heart attack prediction. Machine learning algorithms, such as decision trees, support vector machines, and deep neural networks, have gained prominence in predicting heart attacks. We discuss the strengths and limitations of these methods and highlight recent advancements in predictive modeling. Furthermore, we delve into the critical risk factors associated with heart attacks. Factors such as age, gender, hypertension, diabetes, and cholesterol levels are examined for their significance in predicting cardiac events. We also investigate the role of lifestyle factors, including smoking, diet, and physical activity, in heart attack risk assessment. Additionally, this review addresses the importance of data preprocessing and feature engineering in improving prediction accuracy. Feature selection methods, missing data handling, and data scaling techniques are discussed to enhance the robustness of heart attack prediction models. In conclusion, this comprehensive dataset review provides valuable insights into the state of heart attack analysis and prediction. It serves as a resource for researchers and healthcare professionals seeking to better understand the datasets available for heart attack research and the methods employed for accurate prediction. Ultimately, our efforts in dataset analysis and predictive modeling contribute to the advancement of preventive cardiology and the reduction of heart attack-related morbidity and mortality. (shrink)

As these opening quotes acknowledge, the Prisoner’s Dilemma (PD) represents a core puzzle within the formal mathematics of game theory.3 Its rise in conspicuity is evident figure 2.1 above demonstrating a relatively steady rise in incidences of the phrase’s usage between 1960 to 1995, with a stable presence persisting into the twenty first century. This famous two-person “game,” with a stock narrative cast in terms of two prisoners who each independently must choose whether to remain silent or speak, each advancing (...) self-interest at the expense of the other and thereby achieving a mutually suboptimal outcome, mires any social interaction it is applied to into perplexity. The logic of this game proves the inverse of Adam Smith’s invisible hand: individuals acting on self interest will achieve a mutually suboptimal outcome. However, as this chapter illuminates, the assumptions underlying game theory drive this conclusion. (shrink)

The study aimed to identify the leadership features and their relationship to increasing achievement motivation among Palestinian police employees in Gaza Strip in light of the Corona pandemic. To achieve the study’s objectives, the researchers used the descriptive method in its analytical method, using a questionnaire applied to the police officers at the Central Governorate Police Station, whose number is (113) individuals. They were chosen in a stratified, random manner, and the study resulted in a set of results, the most (...) important of which is that the effect of leadership characteristics of Palestinian police employees in Gaza Strip, which came with a relative weight (76.20%), which is, to a large extent, the level of increase in achievement motivation among employees in the Palestinian Police in Gaza Strip. Gaza under the outbreak of the Corona epidemic? Which came with a relative weight (82.40%), which is to a large extent. While it resulted in a positive correlation between the impact of leadership characteristics and the increase in achievement motivation, there are no statistically significant differences between the averages of the study sample's estimates about the impact The leadership characteristics of the Palestinian Police in Gaza Strip are attributed to the variable of the age group, academic qualification, scientific specialization, scientific experience. There are no statistically significant differences between the averages of the estimates of the individuals of the study sample about The achievement motivation in the Palestinian Police in Gaza Strip is attributable to a variable, age group, academic qualification, scientific specialization, scientific experience, and in light of these results the researchers suggested a set of recommendations, the most important of which are: The need to tighten penalties for individuals by the Central Governorate Police Station for violating the instructions issued by the Ministry Interior In light of the outbreak of the Corona epidemic, increased interest in preparing and organizing specialized training courses and programs in the field of dealing with all different segments in order to preserve the lives of people from the Corona epidemic. (shrink)

This study investigates the dynamics of brick-and-mortar versus click-and-mortar microbusinesses, focusing on the strengths, weaknesses, opportunities, and threats (SWOT) within the local context of Balayan. Ten purposively sampled microbusiness entrepreneurs were examined using the SWOT method. The findings underscore the significance of product assessment, communication, and customer experiences in cultivating trust. Sensory experiences and competitive pricing emerge as strengths, while challenges such as poor sales necessitate strategic interventions. External factors, particularly technological advancements, exert influence on the retail landscape. Key strategies (...) include competitive pricing, flexibility, and an understanding of customer behavior. The study highlights growth potential in tailored experiences but acknowledges the risks posed by e-commerce competition. Additionally, a SWOT strategic plan is developed to leverage internal and external strengths and opportunities while mitigating weaknesses and threats. (shrink)

Looks into evaluation of information provision probability from different sources, based on use of linguistic variables. Formation of functions appurtenant for its unclear variables provides for adoption of decisions by the decision maker, in conditions of nonprobabilistic equivocation. The development of market relations in Ukraine increases the independence and responsibility of enterprises in justifying and making management decisions that ensure their effective, competitive activities. As a result of the analysis, it is determined that the condition of economic facilities can be (...) described and determined by the decision-maker, in the presence of the necessary information. The confidence of the decision-maker in the information received is different and the decisions made have a correspondingly different level of information risk. It is important to substantiate the procedure for assessing the numerical extent of information risk in decision-making based on the information obtained in conditions of uncertainty. The use of a linguistic variable in the processing of expert data presented in the form of a matrix of binary relations of values of the membership function, which allowed to move to further processing of knowledge to support decision-making in the management of industrial, commercial, financial and other activities. As a mathematical model for estimating the numerical measure of information risk when making decisions based on the information obtained in conditions of non-stochastic uncertainty, a model has been developed to model natural language uncertainties, which differs from existing ones by formalizing knowledge taking into account uncertainty of input information. Making such a clear decision in a fuzzy environment has appropriate values of effectiveness and risk. The paper proposes all the functions and accessories of indicators of both quantitative nature and qualitative nature to bring their values in the field of definition to one scale. Then the indicator of the effectiveness of decision-making will be a measure of the clarity of the cross-section of fuzzy subsets, which correspond to the introduced indicators of information risk. The condition of economic facilities can be described and determined by the decision-maker, if the necessary information is available. Decision-making on thenumerical measure of information risk must be determined by a set of basic indicators, which can be both quantitative and qualitative in nature. Predictive values of indicators should be determined in conditions of nonstochastic uncertainty. In this case, the indicators of a quantitative nature can be determined by fuzzy triangular numbers, which implement a high level of confidence in the subjective judgments of experts. Indicators of qualitative nature should be presented in linguistic variables. The values of the indicators of qualitative nature that are predicted must be considered for all fuzzy variable terms-sets of linguistic variables introduced into consideration. For any fuzzy variable, the introduction to the consideration of a clear set of values as carriers of the α-level of its membership function allows to reduce to a single interpretation of the predicted values of indicators of quantitative and qualitative nature in terms of non-stochastic uncertainty. (shrink)

This paper traces two contradicting beliefs about death and immortality in the writings of Rabbi Hayyim Hirschensohn, and examines these opposing beliefs in his Halakhic ruling, in the case of Autopsies. The paper opens by conceptualizing two possible attitudes regarding the relation between this-world and the ʽother-world’, and by analyzing two main beliefs regarding death and immortality in their relation to the body-spirit distinction (the naturalistic and the spiritualistic approach). It demonstrates how Hirschensohn was holding these two different views. The (...) paper then moves to examine whether his halakhic ruling may help us in understanding which approach was Hirschensohn’s favorable belief, by investigating his halakhic ruling regarding autopsies. Hirschensohn permits to perform such surgeries, however subject to some halakhic limitations. The paper concludes that the naturalistic belief regarding death appears to be the more dominant one in his thought. Finally, I point out a few consequences of this paper, for addressing some contemporary ethical dilemmas regarding human corpses. (shrink)

This essay represents a novel contribution to Nietzschean studies by combining an assessment of Friedrich Nietzsche’s challenging uses of “truth” and the “eternal return” with his insights drawn from Indian philosophies. Specifically, drawing on Martin Heidegger’s Nietzsche, I argue that Nietzsche’s critique of a static philosophy of being underpinning conceptual truth is best understood in line with the Theravada Buddhist critique of “self ” and “ego” as transitory. In conclusion, I find that Nietzsche’s “eternal return” can be understood as a (...) direct inversion of “nirvana”: Nietzsche celebrates profound attachment to each and every moment, independent from its pleasurable or distasteful registry. (shrink)

Rainfall prediction is one of the challenging tasks in weather forecasting. Accurate and timely rainfall prediction can be very helpful to take effective security measures in dvance regarding: on-going construction projects, transportation activities, agricultural tasks, flight operations and flood situation, etc. Data mining techniques can effectively predict the rainfall by extracting the hidden patterns among available features of past weather data. This research contributes by providing a critical analysis and review of latest data mining techniques, used for rainfall prediction. In (...) our proposed system we propose a new forecasting method that uses a Convolutional Neural Network monthly rainfall for a selected location. In our proposed system we are going to forecast the rainfall result based on the mean square error, mean absolute error and root mean square error, which we get in train and test of the dataset based deep learning technique. (shrink)

This paper critically engages Philip Mirowki's essay, "The scientific dimensions of social knowledge and their distant echoes in 20th-century American philosophy of science." It argues that although the cold war context of anti-democratic elitism best suited for making decisions about engaging in nuclear war may seem to be politically and ideologically motivated, in fact we need to carefully consider the arguments underlying the new rational choice based political philosophies of the post-WWII era typified by Arrow's impossibility theorem. A distrust of (...) democratic decision-making principles may be developed by social scientists whose leanings may be toward the left or right side of the spectrum of political practices. (shrink)

Abstract: Accurate stock price prediction is essential for informed investment decisions and financial planning. In this research, we introduce an innovative approach to forecast stock prices using an Artificial Neural Network (ANN). Our dataset, consisting of 5582 samples and 6 features, including historical price data and technical indicators, was sourced from Yahoo Finance. The proposed ANN model, composed of four layers (1 input, 1 hidden, 1 output), underwent rigorous training and validation, yielding remarkable results with an accuracy of 99.84% and (...) an average error of 0.005. Additionally, we conducted a feature importance analysis, identifying the key drivers of stock price prediction, such as "High," "Low," "Open," "Volume"," and "Date." This study not only offers a highly accurate stock price prediction model but also contributes valuable insights into the influential factors affecting stock prices, enhancing the field of financial analysis and investment decision-making that are suitable for the task. (shrink)

Faith has many aspects. One of them is whether absolute logical proof for God’s existence is a prerequisite for the proper establishment and individual acceptance of a religious system. The treatment of this question, examined here in the Jewish context of Rabbi Prof. Eliezer Berkovits, has been strongly influenced in the modern era by the radical foundationalism and radical skepticism of Descartes, who rooted in the Western mind the notion that religion and religious issues are “all or nothing” questions. Cartesianism, (...) which surprisingly became the basis of modern secularism, was criticized by the classical American pragmatists. Peirce, James and Dewey all rejected the attempt to achieve infallible absolute knowledge, as well as the presumptuousness of establishing such a knowledge by means of casting Cartesian hyperbolic doubt. They advocated an alternative approach which was more holistic and humane. This paper lays out Descartes’s approach and the pragmatists’ critique. Despite the place that pragmatic considerations hold in Jewish tradition, some thinkers reject the relevance of these ideas. Yet Berkovits’s thought suggest a different path. He rejected Descartes’ radical skepticism and his radical foundationalism, in favor of a moderate foundationalism, which allows for a belief in God alongside constructive doubts. Similar to Peirce’s conception of the fixation of belief, Berkovits views local doubts (distinct from the hyperbolic doubt) as necessary for thought. Berkovits’s understanding of the biblical human-divine encounter, following Rosenzweig, Buber, and Heschel, is conceptualized here as “encounter theology”. Berkovits criticizes the propositionalist attempts to prove God’s existence logically, as well as the presumptuousness of basing religious belief on the teleological world-order. However, Berkovits’s conception of the ‘caring God’ is not provable, and thus defined as a pragmatic ‘postulate’. The article concludes by considering Berkovits’s “encounter theology”. In contrast to the approach described by Haym Soloveitchik, of halakhic stringency and lack of subjective experience of God’s face, Berkovits’s approach is dialogic through and through. (shrink)

This study employs a neural network to analyze the connection between smoking, drinking, and various health-related factors using a dataset of 5148 samples. Achieving an impressive 99.94% accuracy and an average training error of 0.0016, the model identifies influential factors such as serum aminotransferases, serum creatinine, sex, weight, and triglyceride levels. These findings enhance our understanding of lifestyle choices and their impact on health. This research underscores the potential of machine learning in studying complex health phenomena.

This article examines A.J. Heschel’s “Theology of pathos” in light of the critique Eliezer Berkovits raised against it. Heschel’s theology of pathos is the notion of God as the “most moved mover”, who cares deeply for humans, and thus highly influencing their prophetic motivation for human-social improvement. Berkovits, expressing the negative-transcendent theology of Maimonides, assessed that Heschel’s theology of pathos is not systematic, is anthropomorphic, and reflects a foreign Christian influence. However, when checking Berkovits’s own views as a thinker, it (...) turns out that he formulated some immanent theological notions that were overlapping those of Heschel, for example in attributing God the personal trait of caring. Surprisingly, most Heschel’s scholars did not consider this point. This riddle addressed here in two ways: (1) Psychological and Social, on which I understand Berkovits’s critique as a way of coping with his own religious perplexities, and in a wider sense, it is asserted that trans-denominational critique may be a discursive opportunity for mutual corrigibility. (2) Theological, since Heschel and Berkovits indeed faced a similar theological challenge, of rejecting any description of God as anthropomorphism. I thus offer a constructive theological argument for providing a justification to the immanent theologies of both Heschel and Berkovits. (shrink)

I am broadly sympathetic to Dale Matthew’s analysis concerning phenotypic devaluation and disadvantage. However, in what follows, I restrict my remarks to a few areas where I think he either lacks empirical precision, or overstates his case.

In this paper, we introduce and investigate a new class of sets and functions between topological space called neutrosophic semi-supra open set and neutrosophic semi-supra open continuous functions respectively.

This chapter examines: (1) the Black Notebooks in the context of Heidegger's political engagement on behalf of the National Socialist regime and his ambivalence toward some but not all of its political beliefs and tactics; (2) his limited "critique" of vulgar National Socialism and its biologically based racism for the sake of his own ethnocentric vision of the historical uniqueness of the German people and Germany's central role in Europe as a contested site situated between West and East, technological modernity (...) and the Asiatic. Heidegger did not break with radical right-wing Germanist thought, as some scholars have argued. He at most placed National Socialism within his narrative of the history of being, metaphysics, and technology, and thereby relativized it without addressing either its uniqueness or its totalitarian structures and practices. Heidegger formulated his own metaphysical and ontological version of Antisemitism during the National Socialist period. This vision was deeply connected with his understanding of the "history of being" and was intensified during and immediately after the Second World War. Heidegger could perceive no difference between the Shoah and the Allied bombing, defeat, and occupation of Germany. Heidegger's post-war philosophy (of home, history and technology) is deeply shaped by, and remained complicit with, his thinking during this period. (shrink)

Define teleology as the view that requirements hold in virtue of facts about value or goodness. Teleological views are quite popular, and in fact some philosophers (e.g. Dreier, Smith) argue that all (plausible) moral theories can be understood teleologically. I argue, however, that certain well-known cases show that the teleologist must at minimum assume that there are certain facts that an agent ought to know, and that this means that requirements can't, in general, hold in virtue of facts about value (...) or goodness. I then show that even if we grant those 'ought's teleology still runs into problems. A positive justification of teleology looks like it will require an argument of this form: O(X); if X, then O(Y); therefore O(Y). But this form of argument isn't in general valid. I conclude by offering two positive suggestions for those attracted to a teleological outlook. (shrink)

Rawls offers three arguments for the priority of liberty in Theory, two of which share a common error: the belief that once we have shown the instrumental value of the basic liberties for some essential purpose (e.g., securing self-respect), we have automatically shown the reason for their lexical priority. The third argument, however, does not share this error and can be reconstructed along Kantian lines: beginning with the Kantian conception of autonomy endorsed by Rawls in section 40 of Theory, we (...) can explain our highest-order interest in rationality, justify the lexical priority of all basic liberties, and reinterpret Rawls’ threshold condition for the application of the priority of liberty. Perhaps unsurprisingly, this Kantian reconstruction will not work within the radically different framework of Political Liberalism. (shrink)

This paper argues that Immanuel Kant’s practical philosophy contains a coherent, albeit implicit, defense of the legitimacy of capital punishment, one that refutes the most important objections leveled against it. I first show that Kant is consistent in his application of the ius talionis. I then explain how Kant can respond to the claim that death penalty violates the inviolable right to life. To address the most significant objection – the claim that execution violates human dignity – I argue that (...) motives of honor, as Kant conceives it, require a rational person to will her own execution, were she to commit murder. (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)

This article defends the conclusion that the soccer World Cup in Qatar should not be boycotted by rich countries from the Global North. This conclusion is underpinned by considerations about the economic background conditions in guest workers’ home countries. Three arguments are considered for the view that the World Cup should be boycotted. It is argued that each of these arguments is unsound. Section 7 contains a discussion of an argument for a boycott that centers on the process through which (...) Qatar was awarded the World Cup. This argument is rejected. The article lists several ways in which guest workers in Qatar are wronged, but this fact about how guest workers are treated does not justify a boycott by rich countries from the Global North. (shrink)