This article explores the history of Vodou from outlawed African dance to revolutionary magic to depoliticized national Haitian religion and popular dance, its present reduction to Diaspora interpersonal healing, and a possible future. My first section, on Kate Ramsey’s The Spirits and the Law: Vodou and Power in Haiti, reveals Vodou as a sociopolitical construction of racist legal oppression of Africana dances rituals, and artistic-political resistance thereto. My second section, on Karen McCarthy Brown’s Mama Lola: A Vodou Priestess in (...) Brooklyn, a “postmodern ethnography” of intersectional oppressions and Black female Haitian resistance in the Diaspora, foregrounds the figure of Gedelia, a feminist variant on Papa Gede, central Vodou spirit (lwa) of resurrection and healing. Finally, my last section, on the “observing participant” analyses of Black dance anthropologist Yvonne Daniel’s Dancing Wisdom: Embodied Knowledge in Haitian Vodou, Cuban Yoruba, and Bahian Candomblé, finds a dancing Gedelia in her centering of Oyá, a warrior spirit of storms and death. On this basis, I propose the figure of tornadic black angels as a possible magical tool (in Vodou, a pwen, or “point”) intended to re-spiritualize and thereby re-politicize the secularized and whitewashed social Latin dance called “salsa” for social justice. (shrink)

rtificial Intelligence (AI) is swiftly becoming a fundamental element in modern healthcare, bringing unparalleled capabilities in diagnostics, treatment planning, patient care, and healthcare management. This paper delves into AI's transformative impact on the healthcare sector, highlighting how it enhances patient outcomes, boosts the efficiency of medical practices, and introduces new ethical and operational challenges. Through an analysis of current applications such as AI-driven diagnostic tools, personalized medicine, and hospital management systems, the paper underscores the significant advancements AI has introduced to (...) the field. However, the integration of AI also presents concerns related to data privacy, algorithmic bias, and the displacement of healthcare professionals. This study provides a thorough overview of these developments, offering insights into AI's future potential to revolutionize healthcare while addressing the ethical considerations necessary for its responsible adoption. The findings suggest that while AI has the potential to transform healthcare delivery, careful consideration of its implications is essential for ensuring its equitable and effective implementation. (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)

Sacrificial dilemmas such as the trolley problem play an important role in experimental philosophy (x-phi). But it is increasingly argued that, since we are not likely to encounter runaway trolleys in our daily life, the usefulness of such thought experiments for understanding moral judgments in more ecologically valid contexts may be limited. However, similar sacrificial dilemmas are experienced in real life by animal research decision makers. As part of their job, they must make decisions about the suffering, and often the (...) death, of many non-human animals. For this reason, a context-specific investigation of so-called “3R dilemmas” (i.e., dilemmas where there is a conflict between the principles of replacement, reduction, and refinement of the use of animals in research) is essential to improve the situation of both non-human animals and human stakeholders. An approach well suited for such investigation is experimental philosophical bioethics (“bioxphi”), which draws on methods similar to x-phi to probe more realistic, practical scenarios with an eye to informing normative debates and ethical policy. In this article, we argue for a need to investigate 3R dilemmas among professional decision-makers using the tools of bioxphi. In a first step, we define 3R dilemmas and discuss previous investigations of professionals’ attitudes in such cases. In a second step, we show how bioxphi is a promising method to investigate the whys and hows of professional decision-making in 3R dilemmas. In a last step, we provide a bioxphi template for 3R dilemmas, give recommendations on its use, explore the normative relevance of data collected by such means, and discuss important limitations. (shrink)

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

Risk Management Strategies and Investment Behaviors are considered important factors in the investing activities of the retail investors. This study seeks to determine the relationship between Risk Management Strategies and Investment Behavior of Generation Z retail investors. The study is a correlational research and purposive sampling was used to select the respondents for this study. Cochran’s formula was utilized to determine the total sample size or total number of respondents. Spearman’s Rank-Order Correlation was employed to assess the significant relationship of (...) Risk Management Strategies and Investment Behaviors. Based on the results, it showed that risk management strategies have a significant relationship with one or more of the investment behaviors. Risk avoidance has a significant relationship with confirmation bias. Risk reduction has a significant relationship with all of the investment behaviors such as overconfidence, loss-aversion, recency bias, and confirmation bias. Risk transfer shows a significant relationship with only loss-aversion and confirmation bias. And lastly, risk acceptance also has a significant relationship with all of the investment behaviors. This study recommends exploring other types of behavioral biases under cognitive bias and emotional bias to determine their correlation with risk management strategies. Also, broadening the sample size, demographic scope, and geographic scope of the study can improve the generalizability of the study and provide a more comprehensive understanding of the relationship between investment behavior and risk management strategies. The researchers also recommend to utilize interviews and focus group discussions to gain an in-depth understanding of the underlying values and attitudes concerning investment behavior. (shrink)

Abstract: Fast food refers to quick, convenient, and ready-to-eat meals that are usually sold at chain restaurants or take-out establishments. Fast food is often criticized for its unhealthy ingredients, such as high levels of salt, sugar, and unhealthy fats, and its contribution to the growing obesity epidemic. Despite this, fast food remains popular due to its affordability, convenience, and widespread availability. Many fast food chains have attempted to respond to these criticisms by offering healthier options, such as salads and grilled (...) chicken sandwiches, and by using more natural and locally sourced ingredients. The aim in this paper to propose a deep learning model for the classification of fast food dishes. The proposed model, Xception, was trained on natural images and was fine-tuned to make up the fast food meals. The researchers collected the Fast Food V2 dataset from Kaggle depository, the dataset, contained 20,000 images. The dataset has ten labels of food images comprised of Baked Potato, Burger, Crispy Chicken, Donut, Fries, Hot Dog, Pizza, Sandwich, Taco, and Taquito. The dataset was split into three sets: training, validation and testing. The accuracy, F1-score, recall, precision on the separate test set showed that classification of fast food was accuracy (95.13%), Precision (95.34%), Recall (95.13%), and F1-Score (95.14%). (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)

Contemporary republicanism is characterized by three main ideas: free persons, who are not subject to the arbitrary power of others; free states, which try to protect their citizens from such power without exercising it themselves; and vigilant citizenship, as a means to limit states to their protective role. This book advances an economic model of such republicanism that is ideologically centre-left. It demands an exit-oriented state interventionism, one that would require an activist government to enhance competition and resource exit from (...) dominating relationships within markets of all types, be they marital, labour, or residential. The substantial intervention and redistribution necessitated by such an approach make it leftist, while its tendency to work with rather than against the grain of markets makes it centrist. It is, in short, a contribution to progressive republican political thought, but one that is less social-democratic than market-democratic in character. (shrink)

Abstract: The Spotify Status Dataset is a valuable resource that provides real-time insights into the operational status and performance of Spotify, a popular music streaming platform. This dataset contains a wide array of information related to server uptime, user activity, service disruptions, and more, serving as a critical tool for both Spotify's internal monitoring and the broader data analysis community. As digital services like Spotify continue to play a central role in music consumption, understanding the platform's status becomes crucial for (...) ensuring a seamless user experience. This dataset offers numerous research and analysis opportunities, whether you're interested in exploring service availability trends or investigating user behavior patterns during service disruptions. This study highlights the significance of the Spotify Status Dataset, its potential applications, and the valuable insights it can offer to various stakeholders, from Spotify engineers working to enhance service reliability to researchers studying the effects of downtime on user engagement. It invites readers on a journey through this dataset to uncover the secrets of Spotify's operational status and its impact on music enthusiasts worldwide. (shrink)

Deidealization as a topic in its own right has attracted remarkably little philosophical interest despite the extensive literature on idealization. One reason for this is the often implicit assumption that idealization and deidealization are, potentially at least, reversible processes. We question this assumption by analyzing the challenges of deidealization within a menu of four broad categories: deidealizing as recomposing, deidealizing as reformulating, deidealizing as concretizing, and deidealizing as situating. On closer inspection, models turn out much more inflexible than the reversal (...) thesis would have us believe, and deidealization emerges as a creative part of modeling. (shrink)

What makes science trustworthy to the public? This chapter examines one proposed answer: the trustworthiness of science is based at least in part on its independence from the idiosyncratic values, interests, and ideas of individual scientists. That is, science is trustworthy to the extent that following the scientific process would result in the same conclusions, regardless of the particular scientists involved. We analyze this "idiosyncrasy-free ideal" for science by looking at philosophical debates about inductive risk, focusing on two recent proposals (...) which offer different methods of avoiding idiosyncrasy: the high epistemic standards proposal and the democratic values proposal. (shrink)

Abstract: This research delves into the utilization of Artificial Neural Networks (ANNs) as a powerful tool for predicting the overall ratings of books by leveraging a diverse set of attributes. To achieve this, we employ a comprehensive dataset sourced from Goodreads, enabling us to thoroughly examine the intricate connections between the different attributes of books and the ratings they receive from readers. In our investigation, we meticulously scrutinize how attributes such as genre, author, page count, publication year, and reader reviews (...) influence a book's overall rating. Through rigorous analysis and experimentation, we construct an advanced ANN model tailored for predictive analysis in the realm of book ratings. The outcomes of our study reveal the remarkable potential of ANNs in this domain. The ANN model exhibits an impressive level of accuracy when it comes to forecasting book ratings, underlining the efficacy and promise of artificial neural networks in enhancing our understanding and prediction of book evaluations. This research opens up new avenues for leveraging machine learning techniques to gain deeper insights into the dynamics of book ratings and reader preferences. (shrink)

Abstract: 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)

There is a loud and persistent drum beat of support for schools, for citizenship, for diversity and inclusion, and increasingly for labor market readiness with very little critical attention to the assumptions underlying these agendas, let alone to their many internal contradictions. Accordingly, in this book I examine the philosophical, motivational, and practical challenges of education theory, policy, and practice in the twenty-first century. As I proceed, I do not neglect the historical, comparative international context so essential to better understanding (...) where we are, as well as what is attainable in terms of educational justice. I argue that we must constructively critique some of our most cherished beliefs about education if we are to save the hope of real justice from the rhetoric of imagined justice. (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.

Abstract Alzheimer's disease has spread insanely throughout the world. Early detection and intervention are essential to improve the chances of a positive outcome. This study presents a new method to predict a person's likelihood of developing Alzheimer's using a neural network model. The dataset includes 373 samples with 10 features, such as Group,M/F,Age,EDUC, SES,MMSE,CDR ,eTIV,nWBV,Oldpeak,ASF.. A four-layer neural network model (1 input, 2 hidden, 1 output) was trained on the dataset and achieved an accuracy of 98.10% and an average error (...) of 0.01. This study provides a valuable tool for early detection and intervention of Alzheimer's, thus contributing to the field of health and medicine. (shrink)

In this paper I identify and respond to four persistent objections to the idea of wilderness: empirical, cultural, philosophical and environmental. Despite having dogged the wilderness debate for decades, none of these objections withstands scrutiny; rather they are misplaced criticisms that hinder fruitful discussion of the philosophical ramifications of wilderness by needlessly complicating the idea itself. While there may be other justifiable concerns about the idea of wilderness, it is time to move beyond the four discussed in this paper.

Clark and Chalmers (1998) defend the hypothesis of an ‘Extended Mind’, maintaining that beliefs and other paradigmatic mental states can be implemented outside the central nervous system or body. Aspects of the problem of ‘language acquisition’ are considered in the light of the extended mind hypothesis. Rather than ‘language’ as typically understood, the object of study is something called ‘utterance-activity’, a term of art intended to refer to the full range of kinetic and prosodic features of the on-line behaviour of (...) interacting humans. It is argued that utterance activity is plausibly regarded as jointly controlled by the embodied activity of interacting people, and that it contributes to the control of their behaviour. By means of specific examples it is suggested that this complex joint control facilitates easier learning of at least some features of language. This in turn suggests a striking form of the extended mind, in which infants’ cognitive powers are augmented by those of the people with whom they interact. (shrink)

A evolução da seleção genética de aves e suínos proporcionou aumento no crescimento muscular e no desempenho produtivo, bem como na produção intensiva. Os premixes proporcionam ingredientes, como vitaminas e minerais que são essenciais para o crescimento muscular, redução do estresse, eficiência de diversos metabolismos e o bem-estar animal, contribuindo para uma produção mais sustentável. Deste modo, os premixes desempenham um papel fundamental na otimização do desempenho produtivo e reprodutivo de aves, equinos e suínos. Para formular uma dieta balanceada é (...) necessária a inclusão de vitaminas e minerais, os quais são inseridos em baixas concentrações, em função disto é necessário incluí-los por meio de premix para garantir uma boa homogeneidade dos microingredientes na ração. Os premixes podem ser classificados como: ➢ Vitamínicos, ➢ Minerais e ➢ Minerais-vitamínicos ➢ e conter aminoácidos, antibióticos ou enzimas. (shrink)

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

We assess the state of thinking about gender identities in computer vision through an analysis of how research papers in gender and facial recognition are designed, what claims they make about trans and non-binary people, what values they espouse, and what they describe as ongoing challenges for the field. In our corpus of 50 research papers, the seven papers that consider trans and non-binary identities use questionable assumptions about medicalization as a measure of transness, about gender transition as a linear (...) and bounded process, and about the concept of gender deception. Otherwise, non-normative gender identities are absent and their consideration is in fact hindered by prevailing research values, particularly deeply embedded ones such as performance and accuracy. We point out how the use of shared datasets calcifies binary conceptions of gender. In the way that the field of computer vision conceives of ongoing challenges for its research, it does not yet face questions that trans and non-binary user experiences pose and often falls back on biologically essentialist notions of sex classification. We make two recommendations: that computer vision researchers undertake interdisciplinary work with researchers who study gender as a socio-cultural phenomenon, and that journal editors and conference organizers do the same in peer review and conference acceptance processes. (shrink)

In this book I argue that school integration is not a proxy for educational justice. I demonstrate that the evidence consistently shows the opposite is more typically the case. I then articulate and defend the idea of voluntary separation, which describes the effort to redefine, reclaim and redirect what it means to educate under preexisting conditions of segregation. In doing so, I further demonstrate how voluntary separation is consistent with the liberal democratic requirements of equality and citizenship. The position I (...) defend is not opposed to integration but rather is a justified response to the daily experience of frustration and disappointment with a system that has failed members of marginalized groups for too long. I argue that most voluntary separation experiments in education, far from being motivated by a sense of racial, cultural or religious exclusion, are in fact driven among other things by a desire for a quality education, not to mention community membership and self respect. As such, voluntary separation represents a morally robust pragmatic strategy that is able to answer liberal challenges concerning involuntary stratification, ethnocentrism and democratic deliberation. (shrink)

Abstract: Lemons are an important fruit that have a wide range of uses and benefits, from culinary to health to household and beauty applications. Deep learning techniques have shown promising results in image classification tasks, including fruit quality detection. In this paper, we propose a convolutional neural network (CNN)-based approach for detecting the quality of lemons by analysing visual features such as colour and texture. The study aims to develop and train a deep learning model to classify lemons based on (...) their quality, evaluate the model's performance, compare it to traditional machine learning approaches, and identify key factors that affect the model's performance. The dataset used in the study consists of approximately 2533 images of lemons and an empty surface, divided into training, test, and validation data, and includes images of both good and bad quality lemons under different lighting conditions. The deep learning model achieved an accuracy of 99.74% on the test dataset and outperformed traditional machine learning approaches. The developed model has the potential to improve efficiency and accuracy in lemon quality control in the agriculture and food industry. (shrink)

Abstract: Dates are the fruit of date palm trees, and it is one of the fruits famous for its high nutritional value. It is a summer fruit spread in the Arab world. In the past, the Arabs relied on it in their daily lives. Dates take an oval shape and vary in size from 20 to 60 mm in length and 8 to 30 mm in diameter. The ripe fruit consists of a hard core surrounded by a papery cover called (...) the tartar that separates the core from the fleshy part that is eaten. Historians disagreed about the place of its origin, so some historians expressed their belief that it had originated around the Arabian Gulf, and some of them say that the oldest known information about palm trees was in Babylon 4 thousand years ago BC. It is known about the ancient Egyptians using dates in wine. Dates contain a high nutritional value and are considered a basic food for man since ancient times. The fruits of dates are considered the highest fruits in containing sugars. These components vary according to the nature of the fruit, whether it is wet, semi-dry or dry, as well as according to the environmental conditions surrounding the trees. The components of the fruits also differ in different varieties and increase the percentage of sugars in dates is 70-78% of the fruit’s components. These sugars are characterized by their rapid absorption and transfer into the blood directly, digestion and burning. 10 dates (about 100 grams) per day provide a person with all his daily needs of magnesium, manganese, copper, sulfur and half of his needs of calcium and potassium. In this paper we presented a system that recognize the nine types of dates based on deep learning using python on Colab, and classifying using a dataset contain 1350 images. Our trained model achieved an accuracy of 99.44% on a proven test set. (shrink)

In this article I examine two basic questions: first, what constitutes a gifted person, and secondly, is there justification in making special educational provision for gifted children, where special provision involves spending more on their education than on the education of ‘normal’ children? I consider a hypothetical case for allocating extra resources for the gifted, and argue that gifted children are generally denied educational justice if they fail to receive an education that adequately challenges them. I further argue that an (...) adequately challenging education is essential to human flourishing, but that most children can be adequately challenged in schools in ways that promote flourishing without doing so at the expense of other children. (shrink)

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

The concept of interactional expertise – characterized by sociologists Harry Collins and Robert Evans as the ability to speak the language of a discipline without the corresponding ability to practice – can serve as a powerful way of breaking down expert/non-expert dichotomies and providing a role for new voices in specialist communities. However, in spite of the vast uptake of this concept and its potential to fruitfully address many important issues related to scientific expertise, there has been surprisingly little critical (...) analysis of it. We seek to remedy this situation by considering potential benefits of interactional expertise and the ways in which the current conception can – and cannot – realize those benefits. In particular, we argue that interactional expertise hasn’t reached its full potential for addressing who ought to be involved in scientific research and decision-making, largely owing to an unnecessarily restrictive way of operationalizing the concept. In its place, we offer a broader, more pluralistic account of interactional expertise – one that is in line with the original spirit of the concept, but also captures the diversity that we see as being an important aspect of interactional experts and the value they can bring to the table. (shrink)

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

Abstract: The emergence of the novel coronavirus (COVID-19) in 2019 has presented the world with an unprecedented global health crisis. The rapid and widespread transmission of the virus has strained healthcare systems, disrupted economies, and challenged societies. In response to this monumental challenge, the intersection of technology and healthcare has become a focal point for innovation. This research endeavors to leverage the capabilities of Artificial Neural Networks (ANNs) to develop an advanced predictive model for forecasting the spread of COVID-19. It (...) involves the collection, analysis, and integration of diverse datasets encompassing epidemiological, clinical, and social factors that influence the virus's dissemination. (shrink)

The traditional use of conventional media by businesses for audience targeting has shifted with the rise of influencer marketing, notably on platforms like TikTok, posing challenges in content adaptation and technological adaptation. Albert Bandura's Social Cognitive Theory examines factors shaping purchasing behavior, particularly relevant for young professionals. A quantitative correlational study focused on young professionals engaging with TikTok and influenced by Filipino TikTok creators, revealing education level as a key determinant of purchasing behavior. Extended TikTok engagement positively correlates with increased (...) purchasing likelihood. Filipino TikTok influencers significantly impact young professionals' purchasing decisions, emphasizing the need for tailored marketing strategies targeting this demographic. Recommendations were provided for effective influencer and digital marketing strategies targeting young professionals. (shrink)

Abstract: The incorporation of Artificial Intelligence (AI) into educational technology has dramatically transformed learning through Intelligent Tutoring Systems (ITS). These systems utilize AI to offer personalized, adaptive instruction tailored to each student's needs, thereby improving learning outcomes and engagement. This paper examines the development and impact of ITS, focusing on AI technologies such as machine learning, natural language processing, and adaptive algorithms that drive their functionality. Through various case studies and applications, it illustrates how ITS have revolutionized traditional educational methods (...) and addresses the challenges and limitations, including data privacy and system biases. The discussion also covers future directions in ITS development, highlighting emerging trends and potential advancements. The goal is to provide a thorough understanding of how ITS use AI to enhance educational experiences and suggest avenues for future research in this evolving field. (shrink)

I wish to defend the claim that given the content and structure of any moral theory we are likely to find palatable, there is no way of uniquely breaking down that theory into either consequentialist or deontological elements. Indeed, once we examine the actual structure of any such theory more closely, we see that it can be classified in either way arbitrarily. Hence if we ignore the metaethical pronouncements often made by adherents of the consequentialist-deontological distinction, we are quickly led (...) to the conclusion that this distinction contributes nothing of consequence to an understanding of moral theory. I will try to show that there are basically two reasons for this. First, what we mean by the terms endemic to the consequentialist-deontological distinction have no unique references to particular states of affairs in actual cases of moral decision making. Hence we may justify any such concrete moral decision by reference to typically consequentialist or deontological reasoning indifferently. Second, scrutiny of actual and viable moral theories reveals a much finer-grained structure than the consequentialist-deontological taxonomy can capture. And it is this structure, rather than simple attention to consequences or principles, that determines practical moral decision making. We would thus do better to develop the richer vocabulary of causes and constituents, goals and effects, states and events (mental, social, or physical). So in the end, the consequentialist-deontological distinction is irrelevant at the normative level of actual moral reasoning, whereas at the metaethical level it crudely schematizes two opposing types of dummy theory, neither of which is convincing, upon reflection, to any practicing moral philosopher. (shrink)

In this paper we provide a defence of cosmopolitanism from a liberal perspective, examining its moral underpinnings, including moral obligations predicated on a belief in common humanity and the fundamental dignity of human people, cultural capacities that include an embrace of pluralism and a fallibilist disposition, and pragmatist resolve in finding humanitarian solutions to real problems that people face. We also scrutinise the ideal of cosmopolitanism by considering the ‘deeply religious’ as the sort of people about whom it may be (...) said that irreconcilable tensions exist between certain types of commitment and/or belonging and what the demands of cosmopolitanism involve. (shrink)

In this paper, I offer an expansionist view of the Frickerian central case of testimonial injustice, citing examples from the South Asian context. To defend this expansionist position, I provide an argument in three parts. First, I argue that credibility deficit and credibility excess are entangled with each other in such a way that often, one produces the other. Secondly, I contend that we should not say that systematic testimonial injustice is a consequence of credibility deficit only because of the (...) entanglement between them. I also contend that for being the central case of testimonial injustice, identity prejudice should not be necessarily negative; it can be positive as well. Propounding a twofold condition of the status of a knower, the last part claims that testimonial injustice occurs when one of the two conditions remains unmet. (shrink)

(摘要)在哲学史上，许多学者阐释了《存在与时间》的碎片化和"失败"，海德格尔本人对此也提出了三 种阐辛辛《存在与时间》因出版条件导致了偶然的不完整性，这种不完整性后来又作为存在历史的一部分而被提出。在思想(或未思)与偶然的经验意义上或存在者意义上生存着的 "作者"之间，存在着"间隙"，关于这个"间隙"的研究表明:在海德格尔的哲学生涯中，他对《存在与时间》的重要性做出的最好阐樨蕴含着一种关于&q uot;生活与著作"之间关系的理解，其中包含对生活经历的批判性理解和反思在内的理解，这种理解不同于海德格尔本人所坚持的更接近于解释学视角和阐择策略的理解。.

This paper initiates a dialogue between classical Islamic philosophy and late modern European thought, by focusing on two peripheral, ‘heretical’ figures within these traditions: Abū Bakr Muḥammad ibn Zakariyāʾ al-Rāzī and Friedrich Nietzsche. What affiliates these thinkers across the cultural and historical chasm that separates them is their mutual fascination with, and profound indebtedness to, ancient Greek and Hellenistic philosophy. Given the specific themes, concerns and doctrines that they appropriate from this common source, I argue that al-Rāzī and Nietzsche should (...) be read as Epicureans and seen in relation to their predecessor as part of the subterranean tradition of philosophical naturalism. However, while each figure appropriates the philosophy of Epicurus, they ultimately transform it in important ways: al-Rāzī offers us a qualified “Platonic” Epicureanism, while Nietzsche forges a radicalized “Dionysian” Epicureanism. The point of such a comparative examination is twofold. First, analyzing the divergent paths of these “wayward” Epicureans sheds new light on the historical trajectory of naturalism as a philosophical stance (as well as its current prospects and limitations). Second, by initiating a dialogue between the classical Islamic and modern European philosophical traditions, we can better understand the antagonisms and shared concerns between these two horizons, as well as the ambiguities and self-questioning that occur within them. (shrink)

In 1951 John Rawls expressed these convictions about the fundamental issues in metaethics: [T]he objectivity or the subjectivity of moral knowledge turns, not on the question whether ideal value entities exist or whether moral judgments are caused by emotions or whether there is a variety of moral codes the world over, but simply on the question: does there exist a reasonable method for validating and invalidating given or proposed moral rules and those decisions made on the basis of them? For (...) to say of scientific knowledge that it is objective is to say that the propositions expressed therein may be evidenced to be true by a reasonable and reliable method, that is, by the rules and procedures of what we may call "inductive logic"; and, similarly, to establish the objectivity of moral rules, and the decisions based upon them, we must exhibit the decision procedure, which can be shown to be both reasonable and reliable, at least in some cases, for deciding between moral rules and lines of conduct consequent to them.1 In this passage Rawls reconfigured the issue of moral objectivity and so reoriented the practice of metaethics from linguistic analysis to rational methodology. In so doing, his work has provided inspiration to philosophers as disparate in normative views as Thomas Nagel,2 Richard Brandt3, Alan Gewirth4, and David Gauthier.5 Rawls replaced the Moorean question, Do moral terms refer? with the Rawlsian question, Can moral judgments be the outcome of a rational and reliable procedure? He later gave a resoundingly positive answer to this question6 and later still, a more tentative one.7 Rawls' considered qualification of his earlier enthusiasm about the extent to which moral philosophy could be "part of the theory of rational choice"8 is a tribute to the seriousness with which he took his critics' objections. (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)

The genesis of time is explained in the spirit of constructivism combined with the activity approach to cognition. The cardinal temporal categories of present, past, and fu- ture are discussed in terms of action-thoughts understood as elementary units of activity whose structure is determined by linguistic semiosis. Husserl’s tripartite model of the phenomenology of time (prime perception, retention, protention) is applied to the ana- lysis of the subject’s experience of his actions. It is demonstrated that, while our lived present is (...) composed of the actually performed actions, our past and future are construc- ted by reflexive action-thoughts in the cognitive domain of language. It is emphasized that the construction of a temporal sequence that unites what is and what already or still is not, is possible only in linguistic semiosis. The analogy with Husserl’s tripartite structure of the time-consciousness flow helps elucidate the triad ‘present-past-future’ as an instance of the epistemological trap of language: ‘past’ and ‘future’ are mental const- ructs that belong to the present just as any other act of thinking. (shrink)

Socioeconomic status refers to the family's social and economic standing in society. It is measured by combining an individual or group's economic and social position, which is often based on income, education, and occupation. It significantly affects academic performance and even one's health status. The pandemic changed the educational system, causing a huge transition from traditional learning methods to online learning. This shift resulted in confusion, burden, and difficulty among students from different walks of life. This study was conducted to (...) determine the academic stress on online learning among nursing students in relation to their economic status and their ability to access technology. The study utilized a quantitative-correlational method aided by a standard questionnaire. Two hundred thirty-six University of Bohol nursing students enrolled in the second semester of SY 2021–2022 were included in the study by random selection. Data revealed a significant correlation between economic status and the level of stress related to academic expectations and a significant correlation between economic status and access to technology after being subjected to the Spearman rho test of correlation. However, no significant correlation was found between access to technology and the respondents' level of academic stress. (shrink)