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)

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)

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: 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 COVID-19 outbreak had a profound impact on many facets of society, particularly on the educational system. Therefore, all educational content must be delivered to students online, and it is the student’s responsibility to adjust to this new norm. Hence, this study sought to investigate if there is a significant relationship between self-efficacy and resilience among senior high school students. This study utilized correlational research, with the 150 grade 12 senior high school students enrolled in 2022-2023 as respondents. Thus, the (...) researchers employed General Self-Efficacy and Resilience Scale. Finally, the statistical analysis reveals that the r coefficient of 0.53 indicates a moderate positive correlation between the variables. The p-value of 0.00, less than 0.05, leads to rejecting the null hypothesis. Hence, a significant relationship exists between self-efficacy and resilience among senior high school students. (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)

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)

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.

Discussion of new axioms for set theory has often focused on conceptions of maximality, and how these might relate to the iterative conception of set. This paper provides critical appraisal of how certain maximality axioms behave on different conceptions of ontology concerning the iterative conception. In particular, we argue that forms of multiversism (the view that any universe of a certain kind can be extended) and actualism (the view that there are universes that cannot be extended in particular ways) face (...) complementary problems. The latter view is unable to use maximality axioms that make use of extensions, where the former has to contend with the existence of extensions violating maximality axioms. An analysis of two kinds of multiversism, a Zermelian form and Skolemite form, leads to the conclusion that the kind of maximality captured by an axiom differs substantially according to background ontology. (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)

(No abstract is available for this citation).

Due to the outbreak of COVID-19 many families experience the threat of the COVID-19. This study aims to explore the lived experiences, challenges, and coping mechanisms of COVID-19 Family Survivors. The study employed the Interpretative Phenomenological Analysis with ten (10) participants. Based on the findings, the following conclusions were drawn: (1) Most of the participants consulted health professionals for their medications and advised herbal medicines in boosting their immune system. (2) Family survivors had to make adaptations to their daily routines (...) and established stringent health standards in their homes, such as separating the parents' and children's rooms, using disposable utensils, and ensuring that every surface of their homes was clean. (3) They were able to meet their necessities due to the generosity of their neighbors. These people were helped financially by their employers, neighbors, churchmates, and loved ones. Similarly, the government offered a different forum for the COVID-19 Family survivors to receive help and assistance. (4) Despite the hardships they faced, COVID-19 family survivors did not lose hope that they would be cured of COVID-19. These people tried their hardest to maintain their health by eating good meals, sleeping early, obtaining enough sunlight in the morning, and carefully selecting the vitamins they took. (5) Finally, despite the difficult battle against COVID19, these individuals grew resilient by building their spiritual lives, exercising their faith, and being brave for the sake of their loved ones. (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)

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)

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)

The recent advances in Large Language Models (LLMs) and their deployment in social settings prompt an important philosophical question: are LLMs social agents? This question finds its roots in the broader exploration of what engenders sociality. Since AI systems like chatbots, carebots, and sexbots are expanding the pre-theoretical boundaries of our social ontology, philosophers have two options. One is to deny LLMs membership in our social ontology on theoretical grounds by claiming something along the lines that only organic or X-type (...) creatures belong in our social world. Second, expand our ontological boundaries. I take the second route and claim LLMs implemented as social chatbots are social agents. Utilizing Brian Epstein's concepts of grounding and anchoring, alongside Dee Peyton's criteria for what makes a property social, I posit that the capacity for conversations is a social property. Further, within a framework where social agency is considered multi-dimensional, akin to agency, possessing a social property is sufficient for attaining social agency. Thus establishing chatbots as social agents. A helpful concept here is Levels of Abstraction (LoA). The LoA framework allows for extracting relevant and important information from the target domain (the social world). For example, the property of being a 'boy' and the capacity for conversation are social properties; hence, they are part of the social domain. LLMs have the capacity for conversations. So, if we focus on the conversational-LoA and not the gender-LoA, then LLMs occupy a dimension of sociality (i.e., conversational dimensions). (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)

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 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.

Set-theoretic and category-theoretic foundations represent different perspectives on mathematical subject matter. In particular, category-theoretic language focusses on properties that can be determined up to isomorphism within a category, whereas set theory admits of properties determined by the internal structure of the membership relation. Various objections have been raised against this aspect of set theory in the category-theoretic literature. In this article, we advocate a methodological pluralism concerning the two foundational languages, and provide a theory that fruitfully interrelates a ‘structural’ perspective (...) to a set-theoretic one. We present a set-theoretic system that is able to talk about structures more naturally, and argue that it provides an important perspective on plausibly structural properties such as cardinality. We conclude the language of set theory can provide useful information about the notion of mathematical structure. (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)

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.

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: 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)

Given how much importance there is of economics and finance in our lives as humans (materialist side is foremost as per Marx), it should be given more importance by Philosophy and Sociology. This brief report is meant to highlight few research paradigms available in Philosophy and Sociology to give its proper social context and provide deep underlying of Risk, Insurance and Finance.

“Remember your humanity. Forget the rest”. (Bertrand Russell in Russell-Einstein Manifesto) In a nutshell, this review is not trying to propagate rocket science or eureka moment that scientifically finds the cure for all the ills of economic inequality like penicillin does for infections. This review is a basic but effective exploration into the true nature of social realities. This review holistically elaborates how economic inequality is leading to increasing polarization in our societies. Two important drivers of increasing inequality are highlighted (...) here as finance and technology and their contributions to higher polarization is detailed. A case study of polarization is followed along with the conclusion. (shrink)

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)

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)

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)

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)

In this article, I examine a new concept of “Twin Memory’ which has emerged in memory classification research of conscious and unconscious memory representations. It is to analyse the presence of twin memory among the various memory systems, and also to provide a platform for the twin memory “anatomy” in the field of cognitive science, neuropsychology and neuroscience.

This paper is aiming to investigate the physical substrate of conscious process. It will attempt to find out: How does conscious process establish relations between their external stimuli and internal stimuli in order to create reality? How does consciousness devoid of new sensory input result to its new quantum effects? And how does conscious process gain mass in brain? This paper will also try to locate the origins of consciousness at the level of neurons along with the quantum effects of (...) conscious process. (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)

Malone Dies marks the point where Samuel Beckett foremost turns to “metaphysical destruction” of “untrue self,” and Derrida’s critique of the notion of “self-presence” of the subject. In this article, I examine Beckett’s literary absurdities to his readers’ concerns of “abuse” through them. For this investigation Malone Dies posits a stream of conflicting “linguistic nihilism” to the concerns of deconstructing “untrue self,” arguably, which will reflect how abuse of Beckettian readers is stimulated. In this context, abuse is specific forms of (...) emotional tensions aroused by the readers encounter with the Beckettian intersubjectivity. In particular, the existential model of abuse will be analysed as a part of beyond “self-deconstruction” autonomy. (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.

Beckett’s philosophical indebtedness has long been recognised – especially in conjunction with Dante, Descartes and Geulincx. In this article, I examine Beckettian universal values of Enlightenment, which will be exposed as self-serving mystifications that rationalize and instrumentalize the meaning of life. In this context, the awareness of the Enlightenment nature of Beckett’s writing in Waiting for Godot will be analysed along with the freedom appeal of his reader as he strives to attain the enlightenment.

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)

This paper tries to identify the missing link in between human consciousness and unconsciousness processes as precursors of self-development. Further through boundless and countless holistic representation to reality projecting upon the worst humanitarian crisis it offers an insight to derive the desirable solution to it, mainly with human-environment consciousness.

“Play” in biological beings and AI systems, presented as a dissertation at the University of Sussex, critically examines the concept of play in both natural and artificial entities. He differentiates between how biological organisms like humans and animals engage in play, characterized by spontaneity and exploration, versus AI systems, which are more structured and bound by rules when engaging in "games." His study explores the philosophical, psychological, neuroscientific and ethical dimensions of play, looking into how these activities influence learning, behavior, (...) and adaptation in both domains. (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)

Set-theoretic and category-theoretic foundations represent different perspectives on mathematical subject matter. In particular, category-theoretic language focusses on properties that can be determined up to isomorphism within a category, whereas set theory admits of properties determined by the internal structure of the membership relation. Various objections have been raised against this aspect of set theory in the category-theoretic literature. In this article, we advocate a methodological pluralism concerning the two foundational languages, and provide a theory that fruitfully interrelates a `structural' perspective (...) to a set-theoretic one. We present a set-theoretic system that is able to talk about structures more naturally, and argue that it provides an important perspective on plausibly structural properties such as cardinality. We conclude the language of set theory can provide useful information about the notion of mathematical structure. (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: 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)

The ancient names of Assam were Kamrupa and Pragjyotisa, which had been inhabited by the Kirata or Mongoloid people before the Aryan culture could spread its influence over the North Eastern part of India. Before the advent of the Aryan civilization, the Austric-Mongolian and Dravidian culture was the prevalent culture of the people of this area. According to some scholar, the Aryans advent in North East India was occurrence of the pre-Buddhist period. The period of the Brahmins was followed by (...) the Buddhist period, so far as the cultural history of India is concerned. In comparatively, ancient inscriptions of Assam, we find that, the high caste Aryans like Brahmans, Shatriyas and Kalitas entered into Assam and began to settle here even during the Pre-Christian era. The mention of Kamrupa and Devoka in the Allahabad pillar inscription of the Gupta king Samudragupta has an important bearing on the Aryanisation of North East India. In the domain of political system, it is all probable that the ancient Assam populated by the non-Khmer group of the Austric and the Tibeto-Burman people was in tribal state of society. Narakasura and Bhagadutta, the legendary kings of Assam were probably the first monarchical rulers and they were in all probability the Aryanised or Hunduised Mongoloid persons. In other words, the tribal political system of Assam was changed into monarchical system by the influence of the Aryan culture. (shrink)

It is standard in set theory to assume that Cantor's Theorem establishes that the continuum is an uncountable set. A challenge for this position comes from the observation that through forcing one can collapse any cardinal to the countable and that the continuum can be made arbitrarily large. In this paper, we present a different take on the relationship between Cantor's Theorem and extensions of universes, arguing that they can be seen as showing that every set is countable and that (...) the continuum is a proper class. We examine several principles based on maximality considerations in this framework, and show how some (namely Ordinal Inner Model Hypotheses) enable us to incorporate standard set theories (including ZFC with large cardinals added). We conclude that the systems considered raise questions concerning the foundational purposes of set theory. (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)