Sa pagtuturo ng asignaturang Filipino, na tumutuon ng pansin sa wika at panitikan. Bahagi ng usaping pampanitikan ang iba’t ibang halimbawa nito, magmula sa maikling kuwento, kuwentong-bayan, tula, epiko at marami pang iba. Layunin ng pag-aaral na: (1) matuklasan ang nararapat na halimbawang kuwentong-bayan na maaaring maging karagdagang kagamitang pampagtuturo at pagkatuto para sa mga guro at mag-aaral sa sekondarya sa Silangang Distrito sa bayan ng Labo, (2) malaman ang uri ng kagamitang pampagtuturo na paglalapatan ng nasabing kuwentong-bayan batay sa (...) panlasa ng mga gagamit nito, (3) malaman ang antas ng katanggapan batay sa ginagawang karagdagang kagamitang pampagtuturo. Mula sa ginawang pangangalap ng datos mula sa inisyal na sarbey na sinagutan ng mga mag-aaral mula sa ikapitong baytang at mga guro na nagtuturo ng asignaturang Filipino sa antas sekondarya, lumabas na ang alamat ang pinakabasahin at ninanais na makalap at mabuo bilang isang modyul na karagdagang kagamitang pampagtuturo at pagkatuto. Samantala sa kagamitang panturo ay nanguna ang modyul dito upang paglagyan ng napiling uri ng kuwentong-bayan para sa pag-aaral na ito. Sa pangangalap ng mga alamat, napag-alaman na may mga alamat o kasaysayan ang bawat barangay. Malaki ang tyansa na ang kagamitang nabuo sa pag-aaral na ito ang magsilbing daan upang mapreserba at manatiling buhay ang ganitong uri ng akda na sasalamin pamumuhay ng lugar na pinagmulan nito kahit lumipas man ang mahabang panahon. Ang natapos na modyul ng mga alamat ay sinuri at pinagtibay ng mga Filipinong guro mula sa Silangang Distrito sa bayan ng Labo sa pamamagitan ng pagsagot sa sarbey ng antas ng katanggapan. (shrink)

Liberal democracies encourage citizen participation and protect our freedoms, yet these regimes elect politicians and decide important issues with electoral and legislative systems that are less inclusive than other arrangements. Some citizens inevitably have more influence than others. Is this a problem? Yes, because similarly just but more inclusive systems are possible. Political theorists and philosophers should be arguing for particular institutional forms, with particular geographies, consistent with justice. -/- Les démocraties libérales encouragent la participation citoyenne et protègent nos libertés. (...) Pourtant, ces régimes élisent des politiciens et décident de problèmes importants via les systèmes électoral et législatif, qui sont moins inclusifs que d’autres arrangements. Certains citoyens ont inévitablement plus d’influence que d’autres. Est-ce un problème? Oui, parce que des systèmes similairement justes, mais plus inclusifs, sont possibles. Les théoriciens et philosophes politiques devraient ainsi plaider en faveur de formes institutionnelles particulières, aux géographies précises, en cohérence avec la justice. (shrink)

This paper aims at helping trainees to overcome the difficulties they face when dealing with Arduino platform by describing the design of a desktop based intelligent tutoring system. The main idea of this system is a systematic introduction into the concept of Arduino platform. The system shows the circuit boards of Arduino that can be purchased at low cost or assembled from freely-available plans; and an open-source development environment and library for writing code to control the board topic of Arduino (...) platform. The system is adaptive with the trainee’s individual progress. The system functions as a special tutor who deals with trainees according to their levels and skills. Evaluation of the system has been applied on professional and unprofessional trainees in this field and the results were good. (shrink)

Abstract: Smoke detectors are critical devices for early fire detection and life-saving interventions. This research paper explores the application of Artificial Neural Networks (ANNs) in smoke detection systems. The study aims to develop a robust and accurate smoke detection model using ANNs. Surprisingly, the results indicate a 100% accuracy rate, suggesting promising potential for ANNs in enhancing smoke detection technology. However, this paper acknowledges the need for a comprehensive evaluation beyond accuracy. It discusses potential challenges, such as overfitting, dataset size, (...) and class imbalance, and presents strategies employed to address these issues. Additionally, the paper emphasizes the importance of alternative evaluation metrics, including precision, recall, and F1-score, to assess the model's performance comprehensively. Detailed information regarding the model architecture, data preprocessing, and hyperparameter tuning is provided to enhance the reproducibility of the research. The study also discusses ethical considerations and the implications of false positives and false negatives in smoke detection applications. While achieving 100% accuracy is a notable accomplishment, this paper calls for cautious interpretation and further validation in real-world settings. It concludes by highlighting areas for future research and improvement in smoke detection technology, emphasizing the need for practical deployment and the reduction of false alarms. (shrink)

Abstract: Online book review platforms generate vast user data, making accurate rating prediction crucial for personalized recommendations. This research explores neural networks as simple models for predicting book ratings without complex algorithms. Our novel approach uses neural networks to predict ratings solely from user-book interactions, eliminating manual feature engineering. The model processes data, learns patterns, and predicts ratings. We discuss data preprocessing, neural network design, and training techniques. Real-world data experiments show the model's effectiveness, surpassing traditional methods. This research can (...) enhance user experience, book catalog organization, and aid publishers, simplifying recommendation processes and providing tailored suggestions based on user preferences. (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)

Papaya is a tropical fruit with a green cover, yellow pulp, and a taste between mango and cantaloupe, having commercial importance because of its high nutritive and medicinal value. The process of sorting papaya fruit based on maturely is one of the processes that greatly determine the mature of papaya fruit that will be sold to consumers. The manual grading of papaya fruit based on human visual perception is time-consuming and destructive. The objective of this paper is to the status (...) classification of papaya fruits if it's mature or partially matured or unmatured. A deep learning technique that was extensively applied to image recognition was used. The trained model achieved an accuracy of 100% on a held-out test set, demonstrating the feasibility of this approach. Classification model of VGG16 achieved a 100% accuracy and 112 seconds of training time. (shrink)

Abstract: Sign language recognition is one of the most rapidly expanding fields of study today. Many new technologies have been developed in recent years in the fields of artificial intelligence the sign language-based communication is valuable to not only deaf and dumb community, but also beneficial for individuals suffering from Autism, downs Syndrome, Apraxia of Speech for correspondence. The biggest problem faced by people with hearing disabilities is the people's lack of understanding of their requirements. In this paper we try (...) to fill this gap. By trying to translate sign language using artificial intelligence algorithms, we focused in this paper using transfer learning technique based on deep learning by utilizing a MobileNet algorithm and compared it with the previous paper results[10a], where we get in the Mobilenet algorithm on the degree of Accuracy 93,48% but the VGG16 the accuracy was 100% For the same number of images (43500 in the dataset in size 64*64 pixel ) and the same data split training data into training dataset (70%) and validation dataset(15%) and testing dataset(15%) and 20 epoch . (shrink)

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

This study aims to identify the strengthening of the global entrepreneurial orientation practice for employees at the University of Palestine, where the researchers used the descriptive and analytical approach, through a questionnaire distributed to a sample of employees at the University of Palestine, where the size of the study population is (234) employees and the sample size is (117) Employees, of whom (90) employees responded. The study found a set of results, the most important of which are: that there is (...) a good degree of global entrepreneurial orientation for employees, as the percentage reached (70.25%), and the results also showed that there are no statistically significant differences in the smart university transformation and their impact on the global entrepreneurial trend according to personal and organizational data. The study presented a set of recommendations, the most important of which are: The need to work to enhance the global entrepreneurial orientation of the university's employees. (shrink)

This paper excavates the practice-oriented background and therapeutic significance of emptiness in the Madhyamaka philosophy attributed to Nāgārjuna and Sengzhao. Buddhist emptiness unravels experiential and linguistic reification through meditation and argumentation. The historical contexts and uses of the word indicate that it is primarily a practical diagnostic and therapeutic concept. Emptiness does not lead to further views or truths but, akin to yet distinct from Ajñāna and Pyrrhonian skepticism, the suspension of assertion. This sense of emptiness as a practice can (...) be traced in the intercultural transmission of Madhyamaka from Nāgārjuna, its paradigmatic philosopher, to Sengzhao 僧肇, its first pivotal indigenous Chinese representative. (shrink)

A pineapple is a tropical plant with eatable leafy foods most monetarily critical plant in the family Bromeliaceous. The pineapple is native to South America, where it has been developed for a long time. The acquaintance of the pineapple with Europe in the seventeenth century made it a critical social symbol of extravagance. Since the 1820s, pineapple has been industrially filled in nurseries and numerous tropical manors. Further, it is the third most significant tropical natural product in world creation. In (...) the twentieth century, Hawaii was a prevailing maker of pineapples, particularly for the US, be that as it may, by 2016, Costa Rica, Brazil, and the Philippines represented almost 33% of the world's creation of pineapples. In this paper, machine learning based approach is presented for identifying type pineapple with a dataset that contains 1,311images use 946 images for training, 197 images for validation and 168 images for testing. A deep learning technique that extensively applied to image recognition was used. use 70% from image for training and 30% from image for validation. Our trained model achieved an accuracy of 100% on a heldout test set. (shrink)

Modern military organizations are paternalistic organizations. They typically recognize a duty of care toward military personnel and are willing to ignore or violate the consent of military personnel in order to uphold that duty of care. In this paper, we consider the case for paternalism in the military and distinguish it from the case for paternalism in medicine. We argue that one can consistently reject paternalism in medicine but uphold paternalism in the military. We consider two well-known arguments for the (...) conclusion that military organizations should not be entitled to use experimental drugs on troops without first obtaining the informed consent of those troops. We argue that both of these are unsuccessful, in the absence of an argument for the rejection of paternalism in the military altogether. The case for military paternalism is widely accepted. However, we consider three ways in which it could be challenged. (shrink)

This paper defends the idea that phenomenological approaches to self-consciousness can enrich the current analytic philosophy of perception, by showing how phenomenological discussions of minimal self-consciousness can enhance our understanding of the phenomenology of conscious perceptual experiences. As a case study, I investigate the nature of the relationship between naïve realism, a contemporary Anglophone theory of perception, and experiential minimalism (or, the ‘minimal self’ view), a pre-reflective model of self-consciousness originated in the Phenomenological tradition. I argue that naïve realism is (...) not only compatible with, but can be supplemented with experiential minimalism in a novel way. The suggestion is that there are reasons to combine naïve realism and experiential minimalism. My focus here will be on drawing a connection between the notion of minimal self and two core theoretical commitments of naïve realism, relationalism and transparency. (shrink)

Abstract: Colon cancer is a prevalent and life-threatening disease, necessitating accurate and timely diagnosis for effective treatment and improved patient outcomes. This research paper presents the development of a knowledge-based system for diagnosing colon cancer using the CLIPS language. Knowledge-based systems offer the potential to assist healthcare professionals in making informed diagnoses by leveraging expert knowledge and reasoning mechanisms. The methodology involves acquiring and structuring medical knowledge specific to colon cancer, followed by the implementation of a knowledge- based system using (...) CLIPS. The system's design integrates relevant medical databases and employs advanced reasoning mechanisms to facilitate accurate diagnosis. Evaluation results demonstrate the system's effectiveness, with high accuracy and sensitivity rates compared to existing methods. The findings highlight the potential of knowledge-based systems in improving clinical practice and patient care. The research contributes to the growing field of medical informatics by demonstrating the feasibility and effectiveness of CLIPS-based knowledge systems for colon cancer diagnosis. Future research can focus on enhancing system performance and expanding its scope to encompass other types of cancer diagnoses. (shrink)

Brain tumors pose significant challenges in modern healthcare, with accurate and timely diagnosis crucial for determining appropriate treatment strategies. Artificial intelligence has made significant advancements in recent years. Rule-based expert systems (if-then rule-based systems) have emerged as a promising approach for clinical decision-making in brain tumor diagnosis. In this paper, we present "A CLIPS-Based Expert System for Brain Tumor Diagnosis," which leverages a set of 14 if-then rules to diagnose brain tumors with three possible outcomes: 1) Confirm the diagnosis of (...) a brain tumor, 2) Consider the possibility of a brain tumor that has metastasized, and 3) Consider the possibility of a brain tumor. Our expert system offers a user-friendly interface, enabling users to select symptoms and receive a diagnosis based on the provided information. This paper discusses the expert system's development, implementation, and evaluation, highlighting its potential to facilitate brain tumor diagnosis and decision-making in clinical settings. Additionally, we provide a literature review that contextualizes our expert system within the broader landscape of rule-based expert systems for brain tumor diagnosis, examining their effectiveness, limitations, and challenges. (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)

How can we have a sense of the presence of ordinary three-dimensional objects (e.g., an apple on my desk, a partially occluded cat behind a picket fence) when we are only presented with some parts of objects perceived from a particular egocentric viewpoint (e.g., the facing side of the apple, the unoccluded parts of the cat)? This paper presents and defends a novel answer to this question by incorporating insights from two prominent contemporary theories of perception, naïve realism and sensorimotor (...) theory. Naïve realism is the view that perception is fundamentally a matter of obtaining a relation of ‘acquaintance’ with some mind-independent entities (e.g., objects, properties, events). Sensorimotor theory holds that perception involves implicit practical understanding or ‘anticipation’ of the covariance between movements and sensory changes. I argue that perceptual presence is best accounted for in terms of the combination of our direct ‘acquaintance’ with some parts of perceived objects and sensorimotor ‘anticipations’ of how the objects would look different depending on some movements and actions. (shrink)

I argue that a two-dimensional model of social objects is uniquely positioned to deliver explanations for some of the puzzling metaphysical features of words. I consider how a type-token model offers explanations for the metaphysical features of words, but I give reasons to find the model wanting. In its place, I employ an alternative model from social ontology to explain the puzzling data and questions that are generated from the metaphysical features of words. In the end I chart a new (...) path that foregrounds the agent-dependence and social conditions for word kinds. (shrink)

De burgemeester van Etterbeek liet tijdens de afgelopen periode van vrieskou daklozen van straat halen. Soms tegen hun wil in. Omdat het soms nodig is om mensen tegen zichzelf te beschermen.

This research paper presents the development and evaluation of an expert system for diagnosing kidney diseases. The expert system utilizes a decision-making tree approach and is implemented using the CLIPS and Delphi frameworks. The system's accuracy in diagnosing kidney diseases and user satisfaction were evaluated. The results demonstrate the effectiveness of the expert system in providing accurate diagnoses and high user satisfaction.

Vertigo is a common symptom that can result from various underlying diseases and conditions, ranging from benign to severe. Accurate and timely diagnosis of the cause of vertigo is crucial for appropriate management and treatment. In this research, we propose the development of an expert system for vertigo diseases diagnosis, utilizing artificial intelligence (AI) and the proposed Expert System which was produced to help assist healthcare professionals in diagnosing the cause of vertigo based on a patient's symptoms, medical history, and (...) other relevant clinical information. The proposed expert system presents an overview about vertigo diseases are given, the cause of disease is outlined and the treatment or recommendation of disease whenever possible is given out. CLIPS language was used for designing and implementing the proposed expert system. The potential of the proposed expert system lies in its ability to enhance the accuracy and efficiency of vertigo diagnosis, as well as assist in the proper referral and management of patients. (shrink)

This paper argues that it is prudentially wise to defer to groups about how they are essentially constituted and defined. After a few words situating the paper in my greater research project (§1), I articulate the kind of deference I have in mind (§2). Then I offer two conditional arguments on why it is epistemically desirable to let other people tell you how they ought to be identified (§3). The first argument is that people are owed lexical sovereignty because denying (...) it is absurd; the second is that modest skeptics ought to agree with it on the basis of some relatively anodyne and plausible epistemic considerations. (shrink)

Early Confucian “moral psychology” developed in the context of undoing reactive emotions in order to promote relationships of reciprocal recognition. Early Confucian texts diagnose the pervasiveness of reactive emotions under specific social conditions and respond with the ethical-psychological mandate to counter them in self-cultivation. Undoing negative affects is a basic element of becoming ethically noble, while the ignoble person is fixated on limited self-interested concerns and feelings of being unrecognized. Western ethical theory typically accepts equality and symmetry as conditions of (...) disentangling resentment; yet this task requires the asymmetrical recognition of others. Confucian ethics integrates a nuanced and realistic moral psychology with the normatively oriented project of self-cultivation necessary for dismantling complex negative emotions in promoting a condition of humane benevolence that is oriented toward others and achieved through self-cultivation. (shrink)

The article concerns the interpretation of Aquinas' philosophy in the thougt of the swiss theologian Hans Urs Von Balthasar.

As a contribution to a wider discussion on moral discernment in theological anthropology, this paper seeks to answer the question “What is the impact of mental illness on an individual’s ability to make moral decisions?” Written from a clinical psychiatric perspective, it considers recent contributions from psychology, neuropsychology and imaging technology. It notes that the popular conception that mental illness necessarily robs an individual of moral responsibility is largely unfounded. Most people who suffer from mental health problems do not lose (...) the capacity to make moral decisions, and mental illness on its own rarely explains anti-social or criminal behaviour. Moreover, the assumptions of some scientists, that recent developments in neuropsychology and brain imaging suggest biological determinism, must be treated with caution. (shrink)

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

What follows is an attempt to do some conceptual housekeeping around the notion of secret law as provided by Christopher Kutz (2013). First I consider low-salience (or merely obscure) law, suggesting that it fails to capture the legal and moral facts that are at stake in the case which Kutz used to motivate it. Then I outline a theoretical contrast between mere obscurity and secrecy, in contrast to the 'neutral' account of secrecy provided by Sissela Bok (1989). The upshot of (...) the two sections is that low-salience law is neither secret law nor necessarily problematic, though it closely resembles a kind of law that is both secret and problematic: namely, those legal obscurities that subvert manifest interests related to the informational needs of citizens. The ensuing argument undermines the fiction of constructive presence found in Austin and Blackstone. (shrink)

This paper sets mathematics among the sciences, despite not being empirical, because it studies relations of various sorts, like the sciences. Each empirical science studies the relations among objects, which relations determining which science. The mathematical science studies relations as such, regardless of what those relations may be or be among, how relations themselves are related. This places it at the extreme among the sciences with no objects of its own (A Subject with no Object, by J.P. Burgess and G. (...) Rosen). Examples are discussed. The historical development of written mathematics from algorithms on clay tablets to theorems with proofs is said to show that application of algorithms to specific problems and theorems to scientific objects is like allegorical interpretation. Mathematics fits into the modern scientific context because the sciences, beginning with Galileo, have been constructed in imitation of mathematics. Viewing mathematics this way does not solve any ontological problems, but it does show how mathematics avoids them. Epistemological problems, insuperable for object realism, are simplified. For example, we have access to relations among any objects that we can consider objectively, first physical objects and then mathematical objects of greater and greater abstraction. (shrink)

Experiential acquaintance is an alleged relation between ourselves and our experiences that has sometimes been hypothesised as necessary for knowledge of our experiences. This paper begins with a clarification of ‘acquaintance’ and an explanation of ‘experience’ that focuses attention on a famous, but flawed, argument by G. E. Moore. It goes on to critically examine several recent arguments concerning experiential acquaintance and to show how internalist foundationalism can respond to a famous Sellarsian dilemma without appeal to a relation of acquaintance (...) with our experiences. It concludes that we can dispense with experiential acquaintance. (shrink)

A well known and referenced global result is the nilpotent characterisation of the finite p-groups. This un doubtedly transends into neutrosophy. Hence, this fact of the neutrosophic nilpotent p-groups is worth critical studying and comprehensive analysis. The nilpotent characterisation depicts that there exists a derived series (Lower Central) which must terminate at {ϵ} (an identity), after a finite number of steps. Now, Suppose that G(I) is a neutrosophic p-group of class at least m ≥ 3. We show in this paper (...) that Lm−1(G(I)) is abelian and hence G(I) possesses a characteristic abelian neutrosophic subgroup which is not supposed to be contained in Z(G(I)). Furthermore, If L3(G(I)) = 1 such that pm is the highest order of an element of G(I)/L2(G(I)) (where G(I) is any neutrosophic p-group) then no element of L2(G(I)) has an order higher than pm. (shrink)

There at least three ways of thinking about rationality: instrumental, substantive, and intentional. By far, the instrumental account is most influential. This essay proposes that intentional rationality can provide substantive accounts with room to breathe, and in a way that is facially distinct from instrumental accounts. I suggest that the intentionality of a judgment is made up of what it is about and the orientation through which it is judged, while irrationality is the subversion of a strict supporting connection between (...) the judgment and its corresponding set of coordinated attitudes (reasons). It follows that irrational intentionality is made up of episodic states where a judgment is subverted because of a misalignment between what it is about and the way the judge is oriented towards its contents. Four examples of irrational intentionality are considered: passivity towards ends, constitutive ignorance towards facts, delirious paranoia towards objects, and a disjunctive orientation towards categorizations. (shrink)