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

Abstract: Artificial Intelligence (AI) is transforming organizational dynamics by reshaping both structures and processes. This paper examines how AI-driven innovations are redefining organizational frameworks, ranging from shifts in hierarchical models to the adoption of decentralized decision-making. It explores AI's impact on key processes, including workflow automation, data analysis, and decision support systems. Through case studies and empirical research, the paper illustrates the advantages of AI in enhancing efficiency, driving innovation, and fostering agility within organizations. Additionally, it addresses the challenges posed (...) by AI integration, such as resistance to change, ethical concerns, and data security issues. The paper concludes with insights into future trends and implications for organizations navigating the evolving landscape of AI-driven change. (shrink)

In computer science, Artificial Intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. Computer science defines AI research as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. Deep Learning is a new field of research. One of the branches of Artificial Intelligence Science deals with the creation of theories and algorithms that (...) allow the machine to learn by simulating neurons in the human body. Most in-depth learning research focuses on finding high-level methods. The strippers analyze a large data set using linear and nonlinear transformations. The method of deep learning is used in the detection of several diseases including blood cell diseases and their classification using the radiography of blood cells to help decision makers to know the type of blood cell and its associated diseases and the results will be presented in detail and discussed. This thesis is using python language and deep learning to detect blood cell diseases and their classifications. The proposed deep learning model was trained, validated and the tested. The accuracy of proposed model was 98.00%. (shrink)

The study aimed at measuring the dominant pattern of leadership and its relation to the performance of the administrative staff in the Palestinian universities. The study community consists of all the administrative staff from Al-Azhar University and the Islamic University, and through the census of the study society it was found to consist of (655) administrative staff. In order to achieve the objectives of the study, the researchers used the method of random sample in the study, and the study was (...) conducted on a sample of (221) administrative staff of the surveyed universities and the response rate was (82.35%). The study found that there is a high degree of satisfaction with the Dominant Pattern of Leadership in the Palestinian universities in Gaza Strip from the point of view of the administrative staff, which reached (71.67%). There is a high level of performance from the point of view of administrative staff, with a percentage of (82.53%). There is a direct correlation between the dominant pattern of leadership and the functional Performance of Administrative Staff, the absence of differences between the sample according to the gender variable in their perception of the dominant pattern of leadership and the functional Performance of Administrative Staff, the absence of differences in the perception of employees of the dominant pattern of leadership and the functional Performance of Administrative Staff depending on the age variable. There are differences of statistical significance according to the variable of scientific qualification in the Dominant Pattern of Leadership, while there were no differences in performance, the differences in the dominant pattern of leadership according to the scientific qualification were in favor of those who obtained the diploma degree compared to other practical qualifications, the absence of differences in the perception of employees of the dominant pattern of leadership and the functional Performance of Administrative Staff depending on the variable years of service, the absence of differences in the perception of employees of the dominant pattern of leadership and the functional Performance of Administrative Staff depending on the variable level of career (Director, Head of Department, and Administrative Officer). There were differences in the perception of workers to the dominant pattern of leadership depending on the variable of the workplace, where there were differences in favor of workers in deanships and colleges compared with the workers in the technical departments. While there were no differences in job performance according to the workplace variable, the existence of differences in the perception of workers to the dominant pattern of leadership depending on the university in which they work in favor of the Islamic University and the absence of differences in performance between the Islamic University and Al-Azhar University. The study reached a number of recommendations, the most important of which is that the interest of the managements of the Palestinian universities in improving the dominant pattern of leadership, to give universities the opportunity to participate in decision-making, the continued administration of universities interest and continuous improvement of the performance of its employees, enhance the periodic evaluation of job performance and to inform employees and express their opinion, solving workers' problems and giving them the opportunity to contribute to solving their own problems, the use of the staff rotation method periodically and strengthening the democratic the dominant pattern of leadership and empowering university staff. -/- . (shrink)

Abstract: Pistachio nuts are a valuable source of nutrition and are widely cultivated for commercial purposes. The accurate classification of different pistachio varieties is important for quality control and market analysis. In this study, we propose a new model for the classification of different pistachio varieties using Convolutional Neural Networks (CNNs). We collected a dataset of pistachio images form Kaggle depository with two varieties (Kirmizi and Siirt). The images were then preprocessed and used to train a CNN model based on (...) VGG16. We evaluated the performance of the VGG16 on a held-out test set. Our results show that the CNN-based model VGG16 performed very well in terms of accuracy and efficiency. The VGG16 model was able to accurately classify different pistachio varieties with an accuracy of over 99.91%. Additionally, the VGG16 was able to generalize well to new and unseen data, demonstrating its ability to handle variability in the pistachio images. This study highlights the potential of CNNs for the classification of different pistachio varieties, and has important implications for the pistachio industry. The results suggest that this approach can be used to improve the quality control process and enhance market analysis. (shrink)

Abstract: The efficiency and performance of sorting algorithms play a crucial role in various applications and industries. In this research paper, we present a comprehensive comparative analysis of popular sorting algorithms on datasets of different sizes and characteristics. The aim is to evaluate the algorithms' performance and identify their strengths and weaknesses under varying scenarios. We consider six commonly used sorting algorithms: QuickSort, TimSort, MergeSort, HeapSort, RadixSort, and ShellSort. These algorithms represent a range of approaches and techniques, including divide-and-conquer, hybrid (...) sorting, and simple comparison-based methods. To assess their performance, we employ a diverse set of datasets, including the Iris dataset (1K), student dataset (5.8K), Wine dataset (6.5K), Uniform (10K), Normal (10K), Exponential (10K), Bimodal (10K), Yelp dataset (10K), MNIST dataset (42K), Uniform (100K), Normal (100K), Exponential (100K), Bimodal (100K), Uniform (500K), Normal (500K), Exponential (500K), Bimodal (500K), Uniform (1M), Normal (1M), Exponential (1M), and Bimodal (1M). These datasets cover a wide range of sizes and characteristics, allowing us to analyze the algorithms' performance across different dimensions. We measure and compare several key metrics, including execution time, memory usage, algorithmic complexity and stability. By analyzing these metrics, we gain insights into the efficiency and suitability of each algorithm for different dataset sizes and characteristics. We also discuss the implications of the findings in practical applications. Our results reveal important trade-offs among the sorting algorithms. While some algorithms excel in certain scenarios, others demonstrate better scalability or memory efficiency. We identify the best-performing algorithms for specific dataset characteristics and highlight their strengths and limitations. This research can assist developers and practitioners in selecting appropriate sorting algorithms based on their specific requirements and dataset characteristics. In conclusion, this comparative analysis provides a valuable contribution to the understanding of sorting algorithm performance. The findings contribute insights into the efficiency and suitability of popular sorting algorithms across datasets of different sizes and characteristics. By evaluating key metrics and discussing the implications, we offer guidance for selecting the most appropriate sorting algorithm in various practical scenarios. (shrink)

Abstract: This study introduces a machine learning-based model for predicting student performance using a comprehensive dataset derived from educational sources, encompassing 15 key features and comprising 62,631 student samples. Our five-layer neural network demonstrated remarkable performance, achieving an accuracy of 89.14% and an average error of 0.000715, underscoring its effectiveness in predicting student outcomes. Crucially, this research identifies pivotal determinants of student success, including factors such as socio-economic background, prior academic history, study habits, and attendance patterns, shedding light on the (...) nuanced dynamics of student performance. The key influential features identified in this study offer valuable insights into the complex factors shaping student achievement. These insights are vital for educators, policymakers, and institutions seeking to enhance educational outcomes and promote equitable access to quality education. This research provides a data-driven foundation for proactive interventions, personalized learning strategies, and support systems, ultimately contributing to improved student performance and academic success. The high accuracy of the predictive model and the feature analysis it provides empower decision-makers in the education sector. This model holds significant potential for applications in student performance monitoring, early intervention, and tailored educational strategies. By adopting a data-driven approach, this work advances the field of educational analytics and contributes to the goal of fostering student success and educational equity. (shrink)

The study aimed to know the relationship between the nature of the work and the type of communication among the Employees in the Palestinian universities. A comparative study between Al-Azhar University and Al-Aqsa University. The researchers used the analytical descriptive method through a questionnaire that is randomly distributed among the employees of Al-Azhar and Al-Aqsa universities in Gaza Strip. The study was conducted on a sample of (176) administrative employees from the surveyed universities. The response rate was (85.79%). The study (...) reached a number of results, the most important of which is that there is a high degree of satisfaction with the nature of work prevailing in the Palestinian universities in Gaza Strip from the point of view of the administrative staff, where the percentage was (68.15%). There is an Mean level of communication from the point of view of administrative staff, with a percentage of (67.50%). There is a direct correlation between the nature of the work and the prevailing pattern of communication. There is an absence of differences between the sample according to the gender variable in their perception of the nature of work and the prevailing pattern of communication. There is an absence of differences in the perception of Employees nature of work and the pattern of communication prevailing depending on the variables (age, years of service, job level, and university). There are statistically significant differences between Al-Azhar University and Al-Aqsa University in favor of Al-Azhar University. The study reached a number of recommendations, the most important of which is that the interest of the management of the Palestinian universities in Gaza Strip in general, and Al-Aqsa and Al-Azhar Universities in particular should be provided with a good nature of work and communication. There is a need for continuing the management of universities to pay attention and continuous improvement of the performance of employees. There is an importance of solving the problems of Employees and giving them the opportunity to contribute to solving their own problems. Staff rotation should be used periodically and the need to strengthen the democratic leadership style and empower university Employees. (shrink)

Programming artificial intelligence to make fairness assessments of texts through top-down rules, bottom-up training, or hybrid approaches, has presented the challenge of defining cross-cultural fairness. In this paper a simple method is presented which uses vectors to discover if a verb is unfair or fair. It uses already existing relational social ontologies inherent in Word Embeddings and thus requires no training. The plausibility of the approach rests on two premises. That individuals consider fair acts those that they would be willing (...) to accept if done to themselves. Secondly, that such a construal is ontologically reflected in Word Embeddings, by virtue of their ability to reflect the dimensions of such a perception. These dimensions being: responsibility vs. irresponsibility, gain vs. loss, reward vs. sanction, joy vs. pain, all as a single vector. The paper finds it possible to quantify and qualify a verb as fair or unfair by calculating the cosine similarity of the said verb’s embedding vector against FairVec—which represents the above dimensions. We apply this to Glove and Word2Vec embeddings. Testing on a list of verbs produces an F1 score of 95.7, which is improved to 97.0. Lastly, a demonstration of the method’s applicability to sentence measurement is carried out. (shrink)

The producers of Automobile products innovated a new thought of designing the two- wheelers in such a way to attract the women. Today most of the women prefer to travel through two-wheelers. A wide variety of two-wheelers of all category light- weighted, medium – weighted and heavy weighted vehicles have been introduced in the market. The objective of the study is to know the preference and satisfaction of women consumers over two-wheelers and the various aspects, which determines the purchase or (...) buying behavior and to know the expectations of women consumers over two-wheelers. The sample size of the study was conducted in Tiruchirappalli city with 75 respondents through Non-Probability Random Sampling Method. The tools and techniques used were simple percentage, chi-square and ANOVA. The obtained result of the study that majority of the women prefer TVS Scooty and most of the respondents prefer two wheelers due to convenient while driving and majority of the respondents have great impact on colour and model prefer the vehicle. New inventions and designs were introduced to meet the requirements of the current day affaires. (shrink)

We sought to compare the implicit and explicit views of a group of Muslim graduates on the fairness of Islamic law. In this preliminary investigation, we used the Electroencephalographic N400 Event Related Potential to detect the participant’s implicit beliefs. It was found that the majority of participants, eight out of ten, implicitly held that Islamic Law was unfair despite explicitly stating the opposite. In seeking to understand what separated these eight participants from the remaining two – the two who both (...) implicitly and explicitly held that Islamic Law was fair – only two distinguishing characteristics could be identified. Both participants had undertaken an in-depth study of a branch of Islamic law that places the spirit of the law above that of a literal interpretation. They had also attended the same seminary, exclusive to the other participants. Of the eight participants, it was discovered that, while they implicitly held Islamic law to be unfair, they also held it to be rational – in the same way they found that it was rational to push a person of a ship in order to save the remaining from drowning, yet unfair. We discuss these preliminary findings and consider theories on how an innate sense of fairness, an aspect of nativism, may come into play when it is not congruent with a participant’s own beliefs. Further, we ask, where such an inconsistency occurs, how does the mind attempt to rectify it – if at all? As a possible contribution to the discussion on theories of nativism vs. empiricism we put forward a hypothesis and methodology for investigation that may produce previously unconsidered data on human nature. (shrink)

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

The essay presents a novel counterexample to Causal Decision Theory (CDT). Its interest is that it generates a case in which CDT violates the very principles that motivated it in the first place. The essay argues that the objection applies to all extant formulations of CDT and that the only way out for that theory is a modification of it that entails incompatibilism. The essay invites the reader to find this consequence of CDT a reason to reject it.

Abstract: 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 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 aim behind analyzing Google Stock Prices dataset is to get a fair idea about the relationships between the multiple attributes a day might have, such as: the opening price for each day, the volume of trading for each day. With over a hundred thousand days of trading data, there are some patterns that can help in predicting the future prices. We proposed an Artificial Neural Network (ANN) model for predicting the closing prices for future days. The prediction is (...) based on these features (date, opening price, highest price, lowest price, volume), which were used as input variables and (closing price) as output variable for our ANN model. Our model was created, trained, and validated using data set in JNN environment, which its title is “Google-Stock-Prices”. The model evaluation showed that the ANN model is able to predict correctly 99.48% of the validation samples. (shrink)

This work introduces the framework for selecting architecture in 5G networks, considering various technological, performance, economic, and operational factors. With the emergence of 5G technology, the architecture selection process has become pivotal in meeting diverse requirements for ultra-high-speed connectivity, low latency, scalability, and diverse service demands. The evaluation comprehensively analyses different architecture options, including centralized, distributed, cloud-based, and virtualized architectures. Factors such as network performance, scalability, cost-effectiveness, security, and compatibility are considered within a multi-criteria decision-making framework. Findings reveal each architecture (...) option's diverse strengths and limitations, emphasizing the importance of aligning architectural choices with specific use cases, deployment scenarios, and business objectives. We used the concept of multi-criteria decision-making (MCDM) methodology to control the various criteria. We used the single-valued neutrosophic set (SVNS) to deal with vague and inconsistent data. The SVNS is integrated with the hyperSoft set. The proposed methodology uses a single-valued neutrosophic hyperSoft set (SVNHSS) to select the best 5G architecture. We used the VIKOR method as an MCDM method to rank the alternatives. The proposed framework provides stakeholders with a structured methodology to evaluate and prioritize architecture options, facilitating informed decision-making in the complex landscape of 5G network deployments. (shrink)

The best justification of time-discounting is roughly that it is rational to care less about your more distant future because there is less of you around to have it. I argue that the standard version of this argument, which treats both psychological continuity and psychological connectedness as reasons to care about your future, can only rationalize an irrational—because exploitable—form of future discounting.

The aesthetic theory of AlHasan Ibn AlHaytham, known in Latin as Alhazen , has hardly received any attention in the realm of aesthetic investigations. The aesthetic theory is based on twenty-two criteria, which he describes in his book, Kitab Almanazir, better known in Latin as Optica. To illustrate the notion of beauty presented in Optica, one has to understand Alhazen's cultural encyclopedia based on classical Greek knowledge and Islamic sciences. The Greeks and the Egyptians before them, relied on the concepts (...) of measure and geometry as the foundation of aesthetic criteria. By examining the third chapter of Optica, one can see that Alhazen does not look upon these traditional concepts as the fundamental principles of beauty, but he approaches the problem differently. He addresses it as a continuation of his research theme in Optica--to present a proper theory of vision. He dilates upon his twenty-two characteristics as they can be perceived by sight. Alhazen calls these different characteristics the "visible properties" . Explaining each of these properties and the way they are perceived, Alhazen comes up with a hypothesis of "how to entitle an object to be considered beautiful" and a new interpretation of beauty, which is based upon the visual qualities of visible objects. This search of Alhazen hypothesis is essential for drawing architecture out of the present condition of impasse. (shrink)

This discussion note examines a recent argument for the principle that any counterfactual with true components is itself true. That argument rests upon two widely accepted principles of counterfactual logic to which the paper presents counterexamples. The conclusion speculates briefly upon the wider lessons that philosophers should draw from these examples for the semantics of counterfactuals.

In light of the theme of the 5th World Conference on Women's Studies 2019, 'Activism, Solidarity and Diversity: Feminist Movements Toward Global Sisterhood', this article contends that Sherley Anne Williams's Dessa Rose (1986) is an appeal for an American bond of sisterhood between feminists and womanists. In the process, it examines the relationship between the novel's two Black and White heroines, Dessa Rose and Ruth Sutton respectively, through the lens of Bonnie Thornton Dill's definition of sisterhood in her seminal work, (...) Race, Class, and Gender: Prospects for an All-Inclusive Sisterhood. While discomfort and distrust encircle their first encounter in the Sutton's Glen, equality, reciprocation, and trust adorn their sisterhood in their last encounter in jail. Such a sisterhood is the aftermath of both women's realization that they are both subjects to White men's patriarchy. Williams's use of both heroines as microcosms for Black and White women addresses the widening gap in the 1980s and today between feminists and womanists for an American sisterhood in black and white. (shrink)

Where did we come from? Why are we here? Where are we going? How should we live? I am sure that whoever is reading my words now has probably, at least once, asked these existential questions [1]. Among them, which one resonates the most? Probably the first question. You are not the only one since it has occupied minds of mankind since the dawn of history. But, why does it have such significance? Simply because its answer impacts everything else including (...) the other three questions. Our lives would become profoundly different based on our answer. There are only two possible answers, each of which has proponents. Theists give the affirmative answer while atheists give the negative one. This controversy involves both philosophical and scientific arguments. The scope of this paper will revolve more around philosophical argumentation than empirical scientific dialogue, into which it shall not dive deeply. The paper gathers different types of arguments, cosmological, moral, and fine-tuning arguments. This way, it introduces a reader new to the controversy to the types of arguments used, and, to readers familiar with the controversy, it gives insight about each type of argument through criticism. Each argument type has a lot of details. However, I care more about presenting the core of each type. My aim in this paper is equipping the reader with a firm foundation for their future search in pursuit of the truth. The main focus shall be on the existence of a first cause. Nonetheless, there shall be also a brief discussion about its attributes. The paper’s methodology for each type of argument is showing evidence for both theistic and atheistic views. Then a collective critical evaluation of each side’s arguments to show which side argues more soundly. (shrink)

The best-known argument for Evidential Decision Theory (EDT) is the ‘Why ain’cha rich?’ challenge to rival Causal Decision Theory (CDT). The basis for this challenge is that in Newcomb-like situations, acts that conform to EDT may be known in advance to have the better return than acts that conform to CDT. Frank Arntzenius has recently proposed an ingenious counter argument, based on an example in which, he claims, it is predictable in advance that acts that conform to EDT will do (...) less well than acts that conform to CDT. We raise two objections to Arntzenius’s example. We argue, first, that the example is subtly incoherent, in a way that undermines its effectiveness against EDT; and, second, that the example relies on calculating the average return over an inappropriate population of acts. (shrink)

(No abstract is available for this citation).

We describe the earliest occurrences of the Liar Paradox in the Arabic tradition. e early Mutakallimūn claim the Liar Sentence is both true and false; they also associate the Liar with problems concerning plural subjects, which is somewhat puzzling. Abharī (1200-1265) ascribes an unsatisfiable truth condition to the Liar Sentence—as he puts it, its being true is the conjunction of its being true and false—and so concludes that the sentence is not true. Tūsī (1201-1274) argues that self-referential sentences, like the (...) Liar, are not truth-apt, and defends this claim by appealing to a correspondence theory of truth. Translations of the texts are provided as an appendix. (shrink)

The paper argues that on three out of eight possible hypotheses about the EPR experiment we can construct novel and realistic decision problems on which (a) Causal Decision Theory and Evidential Decision Theory conflict (b) Causal Decision Theory and the EPR statistics conflict. We infer that anyone who fully accepts any of these three hypotheses has strong reasons to reject Causal Decision Theory. Finally, we extend the original construction to show that anyone who gives any of the three hypotheses any (...) non-zero credence has strong reasons to reject Causal Decision Theory. However, we concede that no version of the Many Worlds Interpretation (Vaidman, in Zalta, E.N. (ed.), Stanford Encyclopaedia of Philosophy 2014) gives rise to the conflicts that we point out. (shrink)

Al-Taftāzānī introduces the Liar Paradox, in a commentary on al-Rāzī, in a short passage that is part of a polemic against the ethical rationalism of the Muʿtazila. In this essay, we consider his remarks and their place in the history of the Liar Paradox in Arabic Logic. In the passage, al-Taftāzānī introduces Liar Cycles into the tradition, gives the paradox a puzzling name—the fallacy of the “irrational root” —which became standard, and suggests a connection between the paradox and what it (...) tells us about truth and falsehood, and arguments for divine voluntarism and what they tell us about the nature of goodness and badness. On this last point, we also discuss a passage from al-Rāzī, which suggests similar connections. (shrink)

The paper offers a model of Kant's claim that unity of consciousness entails objectivity of experience. This claim has nothing especially to do with thought, language or the categories but is a general truth about arbitrary signaling systems of the sort modeled in the paper. In conclusion I draw some consequences for various forms of idealism.

Karl Marx states in Capital that “man, if not as Aristotle thought a political animal, is at all events a social animal” (Marx, 1992, 444). That Marx draws from Aristotle’s work has been long-recognized, but one could argue that Marx’s very conception of man—what he calls “species-being”—is a derivative of Aristotle’s theory of the good life. This article explores the Aristotelian underpinnings of Marx’s political philosophy and argues that Marx’s theory of species-being and human emancipation supervenes upon Aristotle’s theory of (...) eudaimonia. The consequence of such a rethinking suggests that the Aristotelian good life itself is possible only in the communist society of Marx’s imaginings and, as such, is a state that must be realized—whether by nature or revolution—for human flourishing. Inspired by Aristotle’s assertion that “friendship exists to the extent that what is just exists” (Aristotle, 1991a, 527), this article draws from several of Aristotle’s and Marx’s texts to situate man as an inherently social being, whose need of other men serves both to edify and realize a common end toward which the state is oriented: the life of virtuous activity performed by and in an association of equals. (shrink)

Considerable recent research in neurosciences has dealt with the topic of consciousness, even though there is still disagreement about how to identify and classify conscious states. Recent behavioral work on the topic also exists. We survey recent behavioral and neuroscientific literature with the aims of commenting on strengths and weaknesses of the literature and mapping new directions and recommendations for experimental psychologists. We reconcile this literature with a view of human information processing (Cowan, 1988; Cowan et al., 2024) in which (...) a capacity-limited focus of attention is embedded within the activated portion of long-term memory, with dual bottom-up and top-down control of the focus of attention. None of the many extant theories fully captures what we propose as the organization of conscious thought at cognitive and neural levels. It seems clear that information from various cognitive functions, based on signals from various brain areas, is integrated into a conscious whole. In our new proposal, the integration involves funneling information to a hub or focus of attention neurally centered in the parietal lobes and functionally connected to areas representing the currently attended information. This funneling process (bringing information from diverse sensory and frontal sources to contact a small parietal area where attended information is coordinated and combined) may be the converse of global broadcasting, from other proposals (Baars et al., 2021; Baars & Franklin, 2003; Dehaene & Changeux, 2011). The proposed system incorporates many principles from previous research and theorization and strives toward a resolution of the relation between consciousness and attention. Keywords: consciousness, attention, embedded processes model, experimental psychology, neuroscience. (shrink)

A choice function C is rational iff: if it allows a path through a sequence of decisions with a particular outcome, then that outcome is amongst the ones that C would have chosen from amongst all the possible outcomes of the sequence. This implies, and it is the strongest definition that implies, that anyone who is irrational could be talked out of their own preferences. It also implies weak but non-vacuous constraints on choices over ends. These do not include alpha (...) or beta. (shrink)

A decision problem where Causal Decision Theory (CDT) declines a free $1,000, with the foreseeable effect that the agent is $1,000 poorer, and in no other way better off, than if she had taken the offer.

Causal Decision Theory reckons the choice-worthiness of an option to be completely independent of its evidential bearing on its non-effects. But after one has made a choice this bearing is relevant to future decisions. Therefore it is possible to construct problems of sequential choice in which Causal Decision Theory makes a guaranteed loss. So Causal Decision Theory is wrong. The source of the problem is the idea that agents have a special perspective on their own contemplated actions, from which evidential (...) connections that observers can see are either irrelevant or invisible. (shrink)

Abstract. Suppose that the word of an eyewitness makes it 80% probable that A committed a crime, and that B is drawn from a population in which the incidence rate of that crime is 80%. Many philosophers and legal theorists have held that if this is our only evidence against those parties then (i) we may be justified in finding against A but not against B; but (ii) that doing so incurs a loss in the accuracy of our findings. This (...) paper argues against (ii). It argues that accuracy considerations can motivate taking different attitudes towards individualized and statistical evidence even across cases where they generate the same probability that the defendant is guilty. (shrink)

I begin and conclude the article by arguing that culturalisation has contributed significantly to the decline of the Left and its universal ideals. In the current climate of public opinion, ‘race’ is no longer used, at least openly, as a scientific truth to justify racism. Instead, ‘culture’ has become the mysterious term that has made the perpetuation of racist discourse possible. ‘Culture’, in this newracist worldview, is the unquestioned set of traits continually attributed to the non-White Other, essentially to de-world (...) her Being and de-individualise her personhood. In other words, ‘culture’, as it is used in the old anthropological sense, is the magic incantation with which the Other is demonised, mystified, and/or ridiculously oversimplified. I focus on the phenomenon of ‘culturalisation’ as a common new-racist method of de-politicising the Other’s affairs and surrounding socio-political phenomena. The article is an attempt to discredit the paradigm of ‘culture’ as a pseudo-concept used commonly in cultural racism. This cultural racism routinely assumes ‘culture’ to be a natural given almost exactly as the pseudo-scientific paradigm ‘race’ was (and is still) used in some discourses of biological racism. If mentality X attributes categorical differences to different groups of people based on A and A is assumed to be natural, ahistorical, and/or metaphysical, then X is a racist mentality. Obviously, A does not have to be skin-color or ‘blood’ in order for X to be racist. (shrink)

Andy Egan's Smoking Lesion and Psycho Button cases are supposed to be counterexamples to Causal Decision Theory. This paper argues that they are not: more precisely, it argues that if CDT makes the right call in Newcomb's problem then it makes the right call in Egan cases too.

In this paper an Artificial Neural Network (ANN) model was used to help cars dealers recognize the many characteristics of cars, including manufacturers, their location and classification of cars according to several categories including: Buying, Maint, Doors, Persons, Lug_boot, Safety, and Overall. ANN was used in forecasting car acceptability. The results showed that ANN model was able to predict the car acceptability with 99.12 %. The factor of Safety has the most influence on car acceptability evaluation. Comparative study method is (...) suitable for the evaluation of car acceptability forecasting, can also be extended to all other areas. (shrink)

In this paper an Artificial Neural Network (ANN) model was used to help cars dealers recognize the many characteristics of cars, including manufacturers, their location and classification of cars according to several categories including: Make, Model, Type, Origin, DriveTrain, MSRP, Invoice, EngineSize, Cylinders, Horsepower, MPG_Highway, Weight, Wheelbase, Length. ANN was used in prediction of the number of miles per gallon when the car is driven in the city(MPG_City). The results showed that ANN model was able to predict MPG_City with 97.50 (...) % accuracy. The factor of DriveTrain has the most influence on MPG_City evaluation. Similar studies can be carried out for the evaluation of other characteristics of cars. (shrink)

This paper posits that our understanding of reality is shaped by our cognitive tools, particularly our inclination to establish hierarchies of importance. By examining the nature of causation and correlation, the text argues that correlation is a more primordial concept, preceding causation in human cognition. This framework is applied to the analysis of human motivation, where the concepts of procreation, meaning, and power are evaluated as potential core drivers. Ultimately, the paper proposes continuity as the most self-serving core, underlying human (...) behavior and emotions. The implications of this finding for understanding human nature and the potential for future cognitive evolution are briefly explored. (shrink)

The use of social networks such as Facebook, Twitter, and YouTube in the society has become ubiquitous. The advent of communication technologies alongside other unification trends and notions such as media convergence and digital content allow the users of the social network to integrate these networks in their everyday life. There have been several attempts in the literature to investigate and explain the use of social networks such as Facebook and WhatsApp by university students in the Arab region. However, little (...) research has been done on how university students utilise online audiovisual materials in their academic activities in the UAE. This research aims to elucidate the use of YouTube as a learning aid for university students in the UAE. We adopt the technology acceptance model (TAM) as the theoretical framework for this investigation. A quantitative methodology is employed to answer the research question. Primary data consisting of 221 correspondents were analysed, covering patterns of using YouTube as an academic audiovisual learning aid. Statistical techniques including descriptive, correlations, regression tests were used to analyse the data. The study concluded that students use YouTube as a learning tool for their academic studies and enriching their general knowledge; and there is a positive relationship between the use of YouTube videos in academic settings and the students’ overall performance. This study can shed light for teachers, curriculum designers, government entities, and other stakeholders on how to best utilise and integrate the online technology — YouTube — as a learning aid. (shrink)

Cardiovascular diseases, including heart disease, pose a significant global health challenge, contributing to a substantial burden on healthcare systems and individuals. Early detection and accurate prediction of heart disease are crucial for timely intervention and improved patient outcomes. This research explores the potential of neural networks in predicting heart disease using a dataset collected from Kaggle, consisting of 1025 samples with 14 distinct features. The study's primary objective is to develop an effective neural network model for binary classification, identifying the (...) presence or absence of heart disease. The neural network architecture includes an input layer, a hidden layer, and an output layer, designed to capture intricate relationships within the dataset. Rigorous training and validation processes, accompanied by data preprocessing steps, ensure the model's robustness and generalization capabilities. The results demonstrate promising performance, with an accuracy of 92% and an average error of 0.062. Moreover, an analysis of feature importance highlights key predictors, including "oldpeak," "thalach," "trestbps," "ca," "thal," "cp," "chol," "sex," "restecg," "age," "slope," "fbs," and "exang." This research contributes to the field of predictive healthcare by leveraging neural networks to enhance heart disease prediction. The developed model offers the potential for early identification of individuals at risk, facilitating timely medical interventions and ultimately improving public health. Further exploration of machine learning techniques in healthcare promises to reshape disease prediction and prevention strategies. (shrink)

Abstract: The present research was aimed to explore the nature of Children on the Street’s relationship with Society and its impacts such as living conditions, basic needs; behaviour of people and police, education, harassment. Using the purposive and convenience sampling technique, forty children on the street were selected for interviews from the areas, Golra Shareef and Bari Imam of Islamabad. Interview based questionnaire has been used as research tool and based on that questionnaire, analysis is provided in chapter four with (...) details. The results indicate that the main factors behind pushing children to the street are poverty, unemployment, orphaned, and disability, which leads these children towards terrorism and many other social evils. Such children are viewed negatively by the people and are considered a social burden. This research revealed that most of the children on the street face harassment but females face more than males. Children on the street are abused physically by police as well. It also focused that the behavior of society towards street children is not positive. Street is the most dangerous and threatening place for physical and sexual abuse. (shrink)

Abstract: In this research, the Artificial Neural Network (ANN) model was developed and tested to predict the rate of treatment expenditure on an individual or family in a country. A number of factors have been identified that may affect treatment expenses. Factors such as age, grade level such as primary, preparatory, secondary or college, sex, size of disability, social status, and annual medical expenses in fixed dollars excluding dental and outpatient clinics among others, as input variables for the ANN model. (...) A model based on the multi-layer Perceptron topology was developed and trained using data on 5574 cases. The evaluation of the test data shows that the ANN model is capable of predicting correctly Medical Expenses. (shrink)

With the shortage of physicians and surgeons and increase in demand worldwide due to situations such as the COVID-19 pandemic, there is a growing interest in finding solutions to help address the problem. A solution to this problem would be to use neurotechnology to provide them augmented cognition, senses and action for optimal diagnosis and treatment. Consequently, doing so can negatively impact them and others. We argue that applying neurotechnology for human enhancement in physicians and surgeons can cause injustices, and (...) harm to them and patients. In this paper, we will first describe the augmentations and neurotechnologies that can be used to achieve the relevant augmentations for physicians and surgeons. We will then review selected ethical concerns discussed within literature, discuss the neuroengineering behind using neurotechnology for augmentation purposes, then conclude with an analysis on outcomes and ethical issues of implementing human augmentation via neurotechnology in medical and surgical practice. (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)

The Black woman has always been portrayed in clichéd images in the white media, stereotyping them in a racist and sexist manner. In Black Women Image Makers, Mary Helen Washington dwells upon such unfair portrayals as the tragic mulatto, the hot blooded exotic whore and the strong Black Mammy. And this is probably why the black mother frequently appears in literature as a figure of towering strength. In Zora Neale Hurston’s Their Eyes Were Watching God (1937), an old grandmother, a (...) former slave, accurately describes her position in this society: "De nigger woman is de mule uh de world so fur as Ah can see". The black mother is not a woman with power, not a liberated woman, but a mule, picking up the burdens that everyone else has thrown down and refused to carry. To outsiders, the Negro mother appears to be the one-dimensional Rock of Gibraltar – strong of back, long of arm, incapable of destruction. The proposed paper would study the black mothers as portrayed in Alice Walker’s novels, The Third Life of Grange Copeland and Meridian. To Walker, the Black mother is an individual – profound, tragic, mysterious, sacred, and unfathomable – strong in many, but not in all ways. She claims that the assertion of the black mother as a superwoman is a myth, and she feels that the black mother isn’t always strong. A black man does have a history of ignoring his responsibilities, but the black mother has had no choice in any matter; she has had to pick up the burdens that no one else would carry. In her fiction, Walker introduces the real-feeling, caring, uncaring, disappointed, indifferent black mother to the world. (shrink)

Abstract: Over the past fifty years in developing world, the role of the state intervention in promoting economic growth and social progress has been a subject of disputing among political elites, international development experts and policy analysts. Recognition of the economic growth success of East Asia has led to new thinking on what developmental states idea should be accomplished. The observable optimism performance of East Asian Tigers on the contextual of developmental states is keen in the fact that economic growth (...) can be achievable when states commitment is concerned with respect to capitalist based economy. Since Tanzania is in a unique position of possessing some resources in which other East Asian Tigers did not posses thou their commitment and high standard of responsibility were imperative to their success. It is in this line therefore this paper attempts to draw attentions of Tanzanian Elites and Policy makers on how they can learn from the story of development states in East Asia so as to invent it into the development agenda in building sustainable development for the people of Tanzania. (shrink)

Abstract: Breast cancer is reported to be the most common cancer type among women worldwide and it is the second highest women fatality rate amongst all cancer types. Notwithstanding all the progresses made in prevention and early intervention, early prognosis and survival prediction rates are still not sufficient. In this paper, we propose an ANN model which outperforms all the previous supervised learning methods by reaching 99.57 in terms of accuracy in Wisconsin Breast Cancer dataset. Experimental results on Haberman’s Breast (...) Cancer Survival dataset show the superiority of proposed method by reaching 88.24 % in terms of accuracy. The results are the best reported ones obtained from Artificial Neural Network using JNN environment without any preprocessing of the dataset. (shrink)