Internalist approaches to epistemic justification are, though controversial, considered a live option in contemporary epistemology. Accordingly, if ‘active’ externalist approaches in the philosophy of mind—e.g. the extended cognition and extended mind theses—are _in principle_ incompatible with internalist approaches to justification in epistemology, then this will be an epistemological strike against, at least the _prima facie_ appeal of, active externalism. It is shown here however that, contrary to pretheoretical intuitions, neither the extended cognition _nor_ the extended mind theses are in principle (...) incompatible with two prominent versions of epistemic internalism—viz., accessibilism and mentalism. In fact, one possible diagnosis is that pretheoretical intuitions regarding the incompatibility of active externalism with epistemic internalism are symptomatic of a tacit yet incorrect identification of epistemic internalism with epistemic individualism. Thus, active externalism is not in principle incompatible with epistemic internalism per se and does not significantly restrict one’s options in epistemology. (shrink)

Philosophy of mind and cognitive science (e.g., Clark and Chalmers 1998; Clark 2010; Palermos 2014) have recently become increasingly receptive tothe hypothesis of extended cognition, according to which external artifacts such as our laptops and smartphones can—under appropriate circumstances—feature as material realisers of a person’s cognitive processes. We argue that, to the extent that the hypothesis of extended cognition is correct, our legal and ethical theorising and practice must be updated, by broadening our conception of personal assault so as (...) to include intentional harm towards gadgets that have been appropriately integrated. We next situate the theoretical case for extended personal assault within the context of some recent ethical and legal cases and close with some critical discussion. (shrink)

Two arguments against the compatibility of epistemic internalism and content externalism are considered. Both arguments are shown to fail, because they equivocate on the concept of justification involved in their premises. To spell out the involved equivocation, a distinction between subjective and objective justification is introduced, which can also be independently motivated on the basis of a wide range of thought experiments to be found in the mainstream literature on epistemology. The subjective/objective justification distinction is also ideally suited for providing (...) new insights with respect to central issues within epistemology, including the internalism/externalism debate and the New Evil Demon intuition. (shrink)

Recent thinking within philosophy of mind about the ways cognition can extend has yet to be integrated with philosophical theories of emotion, which give cognition a central role. We carve out new ground at the intersection of these areas and, in doing so, defend what we call the extended emotion thesis: the claim that some emotions can extend beyond skin and skull to parts of the external world.

Our aim is to provide a topography of the relevant philosophical terrain with regard to the possible ways in which knowledge can be conceived of as extended. We begin by charting the different types of internalist and externalist proposals within epistemology, and we critically examine the different formulations of the epistemic internalism/externalism debate they lead to. Next, we turn to the internalism/externalism distinction within philosophy of mind and cognitive science. In light of the above dividing lines, we then examine first (...) the extent to which content externalism is compatible with epistemic externalism; second, whether active externalism entails epistemic externalism; and third whether there are varieties of epistemic externalism that are better suited to accommodate active externalism. Finally, we examine whether the combination of epistemic and cognitive externalism is necessary for epistemology and we comment on the potential ramifications of this move for social epistemology and philosophy of science. (shrink)

Within contemporary philosophy of mind, it is taken for granted that externalist accounts of meaning and mental content are, in principle, orthogonal to the matter of whether cognition itself is bound within the biological brain or whether it can constitutively include parts of the world. Accordingly, Clark and Chalmers (1998) distinguish these varieties of externalism as ‘passive’ and ‘active’ respectively. The aim here is to suggest that we should resist the received way of thinking about these dividing lines. With reference (...) to Brandom’s (1994; 2000; 2008) broad semantic inferentialism, we show that a theory of meaning can be at the same time a variety of active externalism. While we grant that supporters of other varieties of content externalism (e.g., Putnam 1975 and Burge 1986) can deny active externalism, this is not an option for semantic inferentialists: On this latter view, the role of the environment (both in its social and natural form) is not ‘passive’ in the sense assumed by the alternative approaches to content externalism. (shrink)

Cognitive integration is a defining yet overlooked feature of our intellect that may nevertheless have substantial effects on the process of knowledge-acquisition. To bring those effects to the fore, I explore the topic of cognitive integration both from the perspective of virtue reliabilism within externalist epistemology and the perspective of extended cognition within externalist philosophy of mind and cognitive science. On the basis of this interdisciplinary focus, I argue that cognitive integration can provide a minimalist yet adequate epistemic norm of (...) subjective justification: so long as the agent’s belief-forming process has been integrated in his cognitive character, the agent can be justified in holding the resulting beliefs merely by lacking any doubts there was something wrong in the way he arrived at them. Moreover, since both externalist philosophy of mind and externalist epistemology treat the process of cognitive integration in the same way, we can claim that epistemic cognitive characters may extend beyond our organismic cognitive capacities to the artifacts we employ or even to other agents we interact with. This move is not only necessary for accounting for advanced cases of knowledge that is the product of the operation of epistemic artifacts or the interactive activity of research teams, but it can further lead to interesting ramifications both for social epistemology and philosophy of science. (shrink)

By introducing the concept of “mental data,” Palermos (2023) highlights an underappreciated aspect of data ethics that policymakers would do well to heed. Sweeping artificial intelligence (AI) legi...

An interesting aspect of Ernest Sosa’s (2017) recent thinking is that enhanced performances (e.g., the performance of an athlete under the influence of a performance-enhancing drug) fall short of aptness, and this is because such enhanced performances do not issue from genuine competences on the part of the agent. In this paper, I explore in some detail the implications of such thinking in Sosa’s wider virtue epistemology, with a focus on cases of cognitive enhancement. A certain puzzle is then highlighted, (...) and the solution proposed draws from both the recent moral responsibility literature on guidance control (e.g., Fischer and Ravizza 1998; Fischer 2012) as well as from work on cognitive integration in the philosophy of mind and cognitive science (e.g., Clark and Chalmers 1998; Clark 2008; Pritchard 2010; Palermos 2014; Carter 2017). (shrink)

periphery looks at you with hate. This phrase in red neon struck the visitors of Landscapes, an exhibition by Domenico Antonio Mancini in the Lia Rumma Gallery in Naples, in 2019. It was not addressed to the public but to the nineteenth-century pictorial views relocated in the last room of the exhibition, as if repainted by the immaterial vandalism of the colored light. The exhibition’s theme was the visibility of contemporary suburban environments, now accessible through Google street view visualizations. Mancini’s (...) non-representational Landscapes are Google addresses, not aesthetically appreciable but pragmatically challenging: the visitor must type on a touch screen to access to the outskirts of Naples, Palermo, Catania, Rome and Milan. The words at the end of the exhibition almost literally replicated a black graffiti drawn on Palazzo Missori in Milan. Are these relocation and remediation just about artification? What happens when, browsing Google street view, I take a close look at that graffiti recalling the political protests during the streets the 1960s? The deictic transitability in space and time of the hypermediated image can activate a fortuitous narrative and an open interpretation by looking back on the present as if it were past. Even a digital landscape is a moral landscape like that of public art for Danto, with a «internal beauty» whose meaning is not already embodied in architectural and artistic media but accessible and shareable through our portable devices. (shrink)

Prior to this intervention the site used to be a degraded fiscal property, that functioned as a bus yard, a police legal deposit, and a restaurant parking lot. Underneath it runs the Maldonado stream culvert, covered by a concrete slab at a depth of only -20cm. Next to the site is a 5m high railroad embankment. The plot is strategically located at the end of Juan B. Justo avenue and works as a gateway to the Tres de Febrero park (also (...) known as Bosques de Palermo, the Buenos Aires’s biggest green space designed by Charles Thays in 1875). It is situated in the neighborhood of Palermo, an area that underwent a vertiginous residential and commercial expansion since the late 90´s. -/- The design approach is influenced by the adjacent urban fragments: the grounds of the Sociedad Rural Argentina, the surrounding Avenues Santa Fe-Sarmiento; the opening of Darregueyra street expected for the near future, the implementation of historic preservation guidelines for the Tres de Febrero Park, and the proposal for the development of nearby railroad yards. -/- Specifically, the project seeks to minimize the impact of the fast traffic that runs along Bullrich avenue, improving pedestrian and cycle access to the park. At the same time it defines new landscape features, utilizing the earth made available by the tunneling works of a new subway line. -/- The project comprises the structuring of an existing 800 meter long embankment and the transformation of the sidewalk into a public promenade. This is achieved through a wider sidewalk of 12m on average, which is part of a series of longitudinal stripes ranging from high speed to quiet spaces. The first band of grass and aged tipas (tipuana tipu) buffer pedestrian and cyclist from automotive traffic. Cycle traffic is organized on its own lane. The sidewalk itself contains several bays that act as urban lounges. Next, a continuous concrete bench delimits the beginning of the slope, backed by a stripe of grass that works as a soft extension. Finally, plants for contemplation are arranged as undulating traces. Rhythmic use of retaining gabions defines longitudinal segments of varying slope, unifying the spacial criterion. This series is punctuated by an amphitheater and framed by triangular plazas at the corners. -/- Material choices for hard surfaces are constrained by concerns of durability, low cost, and consistency with other ongoing public works. -/- Hard materials, as well as the plant selection needed to be low-maintenance. The palette was kept to reinforced concrete, granitic slabs, and granite stone in large size –forming retaining gabions- and as loose finishing for pavements. Likewise, the lack of a protective enclosure and of continuous surveillance dictated that urban furniture and fixtures be anti-vandalic. The stealing of these components –from inspection lids, to benches, to plants- is a common problem in urban spaces in many Latin American cities. To prevent this, fixtures must be designed according to precise specifications regarding their weight, fixing and anchoring systems, and mechanical parts. -/- Sidewalks are organized through a 6 meter grid made of granitic white slab, infilled with textured combed nonslip concrete modules. Extended bays and corner squares are finished with white and black slabs respectively. These materials are similar to another used in public spaces under construction, in the believe that it creates a collective identification of themselves along the city. -/- The continuous reinforced concrete bench is 1.10 m wide, in order to allow people to use it in non-conventional ways. Further up on the slope, undulating paths separate plant species and provide access for gardening, but are also open to use by the public. They are paved with 2 meter-long precast concrete slabs (smaller and lighter pieces were avoided to deter robbery). As they reach the gabions they connect with sloping paths covered with loose granitic stones. The gabions themselves allow the creation of varying slopes while contributing to retaining the soil, which is reinforced with geosynthetic fabric in the perimeter to avoid landslides originated by strong rains typical of the region. -/- Urban furniture is featured on the wider bays of the sidewalk and at corner plazas. It includes seats, water fountains, bicycle racks, wastepaper baskets. As a counterpoint to the linear concrete bench, groups of concrete seats are arranged informally. These seats are a reinterpretation of the dynamic BKF chair (also known as Butterfly chair), the classic Argentinean design of the 1930’ by Antonio Bonet, Juan Kurchan, and Jorge Ferrari-Hardoy. A few low concrete tables complete these spaces as authentic urban lounges. Lighting design accompanies the general features of the project and creates a new scenography emphasizing night-time usage. -/- Landscape gardening criteria is set up by a selection of various species of high-resistant pasture (grass). The higher the slope, the higher the grass, increasing the final volumetric result. Based on considering the original tipas line (tipuana tipu, a species from the north of Argentina, yellow flowering) as a vertical wall that frames the view, the horizontal stripes contain a single species each, differing in size, shade and flowering periods –adding, in the middle band, a changing color on the big green plane slope in the same chromatic range. The final configuration of the stripe sequence from bottom to top: bermuda grass, bulbine frutescens, euryops pectinatus. The upper band existing native species is reinforced with new samples: paspalum exaltatum + cortadera selloana and ipomea + thumbergia climbing the railway fence. Each sector between gabions has an automated system of drip irrigation. Near the corner plazas, several palms are planted to provide shade and identity to the street-crossing. -/- The intervention proposes an ambivalent effect on the landscape, trascending the merely ornamental by accompanying the motorist in speed, while conforting the pedestrian with spaces for contemplation and urban relax. (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)

Heart palpitations, while often benign, can sometimes be indicative of severe underlying conditions requiring immediate intervention. Accurate and swift diagnosis thus remains a clinical priority. "A CLIPS-Based Expert System for Heart Palpitations Diagnosis" represents a novel approach to addressing this challenge, harnessing the power of artificial intelligence and rule-based expert systems. Specifically, this system applies a suite of 7 if-then rules to evaluate potential heart palpitations causes and assign one of three outcomes: 1) A confirmed diagnosis of heart palpitations, 2) (...) A suspected link to cardiovascular diseases, and 3) A possible association with anxiety or stress disorders. The expert system offers an intuitive user interface, allowing for seamless symptom input and instant diagnosis based on user-provided information. This paper explores the various phases of this expert system's lifecycle, including design, implementation, and evaluation. Furthermore, the study situates the system within the broader discourse on rule-based expert systems for heart palpitations diagnosis, critically analyzing their efficiency, potential pitfalls, and ongoing challenges. Through this research, the value of integrating rule-based expert systems in clinical diagnostic processes is highlighted, illustrating its capacity to enhance diagnostic accuracy and patient outcomes. (shrink)

We address the question whether there is an explanation for the fact that as Fodor put it the micro-level “converges on stable macro-level properties”, and whether there are lessons from this explanation for other issues in the vicinity. We argue that stability in large systems can be understood in terms of statistical limit theorems. In the thermodynamic limit of infinite system size N → ∞ systems will have strictly stable macroscopic properties in the sense that transitions between different macroscopic phases (...) of matter (if there are any) will not occur in finite time. Indeed stability in this sense is a consequence of the absence of fluctuations, as (large) fluctuations would be required to induce such macroscopic transformations. These properties can be understood in terms of coarse-grained descriptions, and the statistical limit theorems for independent or weakly dependent random variable describing the behaviour averages and the statistics of fluctuations in the large system limit. We argue that RNG analyses applied to off-critical systems can provide a rationalization for the applicability of these limit theorems. Furthermore we discuss some related issues as, for example, the role of the infinite-system idealization. (shrink)

A long series of studies in social psychology have shown that the explanations people give for their own behaviors are fundamentally different from the explanations they give for the behaviors of others. Still, a great deal of uncertainty remains about precisely what sorts of differences one finds here. We offer a new approach to addressing the problem. Specifically, we distinguish between two levels of representation ─ the level of linguistic structure (which consists of the actual series of words used in (...) the explanation) and the level of conceptual structure (which consists of the concepts these words are used to express). We then formulate and test hypotheses both about self-other differences in conceptual structure and about self-other differences in the mapping from conceptual structure to linguistic structure. (shrink)

Malaria is a life-threatening disease spread to humans by some types of mosquitoes. It is mostly found in tropical countries. It is preventable and curable. The infection is caused by a parasite and does not spread from person to person. Symptoms can be mild or life-threatening. Mild symptoms are fever, chills and headache. Severe symptoms include fatigue, confusion, seizures, and difficulty breathing. Infants, children under 5 years, pregnant women, travelers and people with HIV or AIDS are at higher risk of (...) severe infection. Discovering this disease is a good step for proper and correct treatment. Determining the treatment with high accuracy depends on the method used in the diagnosis. Correctly, expert systems can greatly help to avoid spreading this disease. The expert system diagnoses malaria disease correctly to facilitate doctors to find the correct treatment based on the appropriate diagnosis. Objectives: An expert system has been established based on CLIPS to diagnose malaria disease. (shrink)

heart attack analysis & prediction dataset is a major cause of death worldwide. Early detection and intervention are essential for improving the chances of a positive outcome. This study presents a novel approach to predicting the likelihood of a person having heart failure using a neural network model. The dataset comprises 304 samples with 11 features, such as age, sex, chest pain type, Trtbps, cholesterol, fasting blood sugar, resting electrocardiogram results, maximum heart rate achieved, exercise-induced angina, oldpeak, ST_Slope, and HeartDisease. (...) A neural network model with four layers (1 input, 2 hidden, 1 output) was trained on the dataset and achieved an accuracy of 88% and an average error of 0078296. The most influential factors in heart failure prediction were found to be oldpeak, ST_Slope, sex, fastingBS, chestPainType, exerciseAngina, cholesterol, restingBP, maxHR, restingBP, and age. This study provides a valuable tool for early detection and intervention of heart failure, thereby contributing to the field of health and medicine. (shrink)

The purpose of the article is to reveal the scientific approach that substantiates the impact of the creation of strategic alliances (SA) on the digital transformation of business and the development of their innovative power based on identified success factors. The aim was achieved using the following methods: abstract logic and typification (for classification of SA's success factors), generalization (to determine the peculiarities of SA's influence on their innovation development), analytical and ranking method (to determine the relationship between the dynamics (...) creating of SA and the degree of acceleration of digital transformation), expert evaluation (to determine the degree of influence of SA success factors by business areas). Implementing a business-integrated approach to understanding digital transformation will accelerate implementation of innovation and organizational change, identifies future prospects for market, customer and business relationships, highlighting the importance of researching the factors that ensure their success. An alternative vision of SA’s success factors is suggested, which are determined by the possibilities the organization of partnerships and organizational culture, integration of business sectors, compatibility of management goals, external relevance, obtaining synergies. Innovation is considered by the authors as an integration factor that reconciles all groups of SA success factors, giving them the necessary focus to solve business problems. The results of the study show that the creation of SA has a significant impact on accelerating and changes priority of digital transformation of business areas involved in strategic partnerships, and the impact of SA on the development of their innovation power is crucial. (shrink)

The translational research community, in general, and the Clinical and Translational Science Awards (CTSA) community, in particular, share the vision of repurposing EHRs for research that will improve the quality of clinical practice. Many members of these communities are also aware that electronic health records (EHRs) suffer limitations of data becoming poorly structured, biased, and unusable out of original context. This creates obstacles to the continuity of care, utility, quality improvement, and translational research. Analogous limitations to sharing objective data in (...) other areas of the natural sciences have been successfully overcome by developing and using common ontologies. This White Paper presents the authors’ rationale for the use of ontologies with computable semantics for the improvement of clinical data quality and EHR usability formulated for researchers with a stake in clinical and translational science and who are advocates for the use of information technology in medicine but at the same time are concerned by current major shortfalls. This White Paper outlines pitfalls, opportunities, and solutions and recommends increased investment in research and development of ontologies with computable semantics for a new generation of EHRs. (shrink)

Cognitive penetration of perception, broadly understood, is the influence that the cognitive system has on a perceptual system. The paper shows a form of cognitive penetration in the visual system which I call ‘architectural’. Architectural cognitive penetration is the process whereby the behaviour or the structure of the perceptual system is influenced by the cognitive system, which consequently may have an impact on the content of the perceptual experience. I scrutinize a study in perceptual learning that provides empirical evidence that (...) cognitive influences in the visual system produce neural reorganization in the primary visual cortex. The type of cognitive penetration can be synchronic and diachronic. (shrink)

This paper critically examines coincidence arguments and evolutionary debunking arguments against non-naturalist realism in metaethics. It advances a version of these arguments that goes roughly like this: Given a non-naturalist, realist metaethic, it would be cosmically coincidental if our first order normative beliefs were true. This coincidence undermines any prima facie justification enjoyed by those beliefs.

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)

As sustainable tourism gains increasing attention, understanding the factors that influence travelers' motivation to engage with sustainable travel agents becomes crucial. This study investigates the moderating effect of social media usage on the relationship between the perceived value of websites and motivational factors for sustainable travel agents. The study proposes that social media usage acts as a moderator in shaping the relationship between the perceived value of websites and motivational factors. This study has utilized smart tourism. Therefore, independent variable motivation (...) in terms of informativeness gratification and gratification acted as moderating variables. This study has utilized an online questionnaire adapted from a standardized questionnaire based on the literature review. Moreover, a total of 146 managers were surveyed in which they were required to respond to 55 items that elicited the 7 variables social media use, Propensity, perceived website value, motivating factors, entertainment gratification, informativeness gratification, sustainable smart tourism. The data were analyzed by SPSS and PLS-SEM. The findings indicated that relevance and importance of social media use and sustainable smart tourism. The result revealed that 7 hypotheses had a significant relationship. 3 hypotheses did not show a moderating effect. Overall, this study extends the understanding of sustainable smart tourism. These findings will benefit travel agents’ managers in Malaysia to better understand the role of social media use and utilize it towards developing sustainable sustainable smart tourism. (shrink)

This study presents a neural network-based model for predicting smoke potential in a specific area using a Kaggle-derived dataset with 15 environmental features and 62,631 samples. Our five-layer neural network achieved an accuracy of 89.14% and an average error of 0.000715, demonstrating its effectiveness. Key influential features, including temperature, humidity, crude ethanol, pressure, NC1.0, NC2.5, SCNT, and PM2.5, were identified, providing insights into smoke occurrence. This research aids in proactive smoke mitigation and public health protection. The model's accuracy and feature (...) analysis empower decision-makers, with potential applications in real-time smoke event monitoring and preparedness strategies. This work contributes to the field of air quality forecasting and environmental stewardship, offering a data-driven approach to address smoke-related challenges and enhance community well-being. (shrink)

Due to the COVID-19 Pandemic, several changes have been forcibly made and observed in various fields and areas of society, one of which include the field of education; the foundation of the formation of intellect and knowledge. After two years of studying indoors and private educational institutions holding virtual classes, the time has finally come for students to be re- adjusted once more to the blended mode of learning; a combination of virtual and in-person classes. Thus, this study aimed to (...) investigate the development of students’ study habits and how these habits could potentially affect the students’ academic achievement or performance. The study utilized a descriptivecorrelational design to examine the impact of study habits to the academic performance of 137 senior high school students. The study made use of the Palsane and Sharma’s Study Habits Inventory, or also known as PSSHI, and using this instrument, the study has been able to procure sufficient results that will answer the present study’s problems. Using linear regression analysis, the present study found that there was a significance between the study habits and academic performance of the senior high school students, thus the study’s null hypothesis was eventually rejected. (shrink)

The aim behind analyzing the Goodreads dataset is to get a fair idea about the relationships between the multiple attributes a book might have, such as: the aggregate rating of each book, the trend of the authors over the years and books with numerous languages. With over a hundred thousand ratings, there are books which just tend to become popular as each day seems to pass. We proposed an Artificial Neural Network (ANN) model for predicting the overall rating of books. (...) The prediction is based on these features (bookID, title, authors, isbn, language_code, isbn13, # num_pages, ratings_count, text_reviews_count), which were used as input variables and (average_rating) as output variable for our ANN model. Our model were created, trained, and validated using data set in JNN environment, which its title is “Goodreads-books”. Model evaluation showed that the ANN model is able to predict correctly 99.78% of the validation samples. (shrink)

In this paper we argue that dissociative identity disorder (DID) is best interpreted as a causal model of a (possible) post-traumatic psychological process, as a mechanical model of an abnormal psychological condition. From this perspective we examine and criticize the evidential status of DID, and we demonstrate that there is really no good reason to believe that anyone has ever suffered from DID so understood. This is so because the proponents of DID violate basic methodological principles of good causal modeling. (...) When every ounce of your concentration is fixed upon blasting a winged pig out of the sky, you do not question its species' ontological status. James Morrow, City of Truth (1990). (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)

In lieu of an abstract, here is a brief excerpt of the content:130 Feminist Studies 46, no. 1. © 2020 by Feminist Studies, Inc. Laura Bisaillon, Alana Cattapan, Annelieke Driessen, Esther van Duin, Shannon Spruit, Lorena Anton, and Nancy S. Jecker Doing Academia Differently: “I Needed Self-Help Less Than I Needed a Fair Society” A great deal of harm is being done by belief in the virtuousness of work. — Bertrand Russell, “In Praise of Idleness” We are committed to doing (...) academia in particular ways, and not in others. — Brocher Foundation Feminist Collective I had decided that becoming a university professor might be a good fit; friends and colleagues had suggested that I would be valuable to a university, so I prepared for a restructuring of my family life.1 I read Tokarczyk and Fay’s Working-Class Women in the Academy and Babcock and Laschever’s Women Don’t Ask to gather understandings of the milieu I was entering. I now see that my preparations had not shined sufficient light on the social and structural factors that organize the contemporary university.... As it turns out, the restructuring of our lives within the working conditions, priorities, and rationalities of this professional milieu triggered unanticipated and painful effects.... Had Mountz published her article “Women on the Edge” before I decided on a career migration into the university system and, had I been fortunate enough to discover it, I would have made other career choices.2 1. The authors, who describe themselves as the Brocher Foundation Feminist Collective, indicate their personal narratives in this text using italics. 2. Michelle M. Tokarczyk and Elizabeth A. Fay, eds., Working-Class Women in the Academy: Laborers in the Knowledge Factory (Amherst: University of Massachusetts Press, 1993); Linda Babcock and Sara Laschever, Women Don’t Ask: Negotiation and the Gender Divide (Princeton, NJ: Princeton University Bisaillon et al. 131 Introduction: Personal, Professional, and Political We are seven women who met at the Brocher Foundation in Hermance, Switzerland, in July 2017, where we had been selected to spend a few months as research fellows. This competitively awarded opportunity is open to persons fluent in English, from graduate students to senior scholars, with or without academic appointment, whose scholarship advances knowledge about the ethical, legal, and social implications of health and biotechnologies.3 When we found ourselves on the shores of Lake Leman with the gift of time, we began opening up to each other in unexpected, compelling ways. Whatever our vantage point in the hierarchy of the university system, we discovered that there was remarkable overlap in our experiences as women in academia. When we began writing, our authoring team was composed of two graduate students, four faculty members at the assistant professor rank, and one full professor, residing in Canada, the Netherlands, Romania, the United Kingdom, and the United States. Our plural subject position led us to underexplored and imaginative responses to broader social issues, which we share in this article as the “Brocher Foundation Feminist Collective.” We analyze our experiences from our standpoint as women health researchers laboring in the academy. Our similarities and differences were exciting entry points for discussion and analysis: we are all of eastern or western European descent. We have different countries of birth, mother tongues, ages, disciplinary training and career trajectories, relationships to chronic illness and disability, marital status, and experiences with parenthood. We bring the troubles and contradictions we experience as academics into conversation with each other. We seek to productively illustrate and emphasize that the tensions we see around us, and also feel within us, arise as a result of how the academic system is organized, produced, and sustained across time, place, and space. Press, 2003); Alison Mountz, “Women on the Edge: Workplace Stress at Universities in North America,” The Canadian Geographer 60, no. 2 (2016): 205–18. 3. We experienced this fellowship as a valuable opportunity. But we also recognized that our access to it was mediated by social, economic, or other obligations. As countries in the global north continue to tighten their national border regimes, marginalized academics, especially those from the global South, were less likely to succeed in getting a Swiss visa or securing relevant temporal and economic resources. 132 Bisaillon et al. The promise here, we posit... (shrink)

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)

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)

Abstract: Rice, as a paramount staple crop worldwide, sustains billions of lives. Precise classification of rice types holds immense agricultural, nutritional, and economic significance. Recent advancements in machine learning, particularly Artificial Neural Networks (ANNs), offer promise in enhancing rice type classification accuracy and efficiency. This research explores rice type classification, harnessing neural networks' power. Utilizing a rich dataset from Kaggle, containing 18,188 entries and key rice grain attributes, we develop and evaluate a neural network model. Our neural network, featuring a (...) single hidden layer, achieves remarkable results—a staggering 100% accuracy and a minute average error rate of 0.000001. Beyond performance metrics, we delve into the intricacies of rice type classification through feature importance analysis. The most influential features—'id,' 'Area,' 'MajorAxisLength,' 'MinorAxisLength,' 'Eccentricity,' 'ConvexArea,' 'EquivDiameter,' 'Extent,' 'Perimeter,' 'Roundness,' and 'AspectRatio'—uncover the physiological traits underpinning accurate rice classification. This research contributes to advancing rice classification methods and highlights the potential of ANNs in optimizing agricultural practices, ensuring food safety, and bolstering global trade. (shrink)

Job motivation remains an area of concern among researchers due to the rising issues of poor or lack of motivation among workers. This refers to one’s personal will or drives to perform a task at work. Meanwhile, job satisfaction refers to an employee’s sense of fulfillment with his or her work experience. Therefore, the current study utilized the descriptive- correlational research design to investigate the impact of job motivation on the job satisfaction of accountants. To gather essential data and achieve (...) the objectives of the study, Multidimensional Work Motivational Scale (MWMS) and Minnesota Satisfaction Questionnaire (MSQ) were administered to the target respondents. The collected data were then analyzed using a Multiple Regression Analysis; findings revealed that job motivation has a significant impact on the job satisfaction of accountants. Additionally, the results of this study were carefully evaluated and discussed, and recommendations were made to benefit the stakeholders of the study and contribute to the existing body of knowledge. (shrink)

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

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

The article entitled “Cultural evolution in Vietnam’s early 20th century: A Bayesian networks analysis of Hanoi Franco-Chinese house designs” investigates how diverse cultures and religious creeds influenced the architecture of Hanoi in the early 20th century.

Terraforming is a process of planetary engineering by which the extant environment of a planetary body is transformed into an environment capable of supporting human inhabitants. The question I would like to consider in this paper is whether there is any reason to believe that the terraforming of another planet—for instance, the terraforming of Mars—is morally problematic. Topics related to the human exploration of space are not often discussed in philosophical circles. Nevertheless, there exists a growing body of philosophical literature (...) dedicated to sorting out the moral implications of the use of resources from (and in) space. Most of this literature is produced as environmental philosophy. Questions of .. (shrink)

This study aims to investigate the relationship between job burnout and employee performance in the feed industry during the ASF outbreak. Further, the researchers employed a descriptive-correlational research design in order to analyze the acquired data and produce pertinent findings. Thus, the researchers gathered data from one hundred two (102) feed industry employees. The Maslach Burnout Inventory (MBI) and Individual Work Performance Questionnaire (IWPQ) were employed to ascertain the extent of job burnout experienced by the respondents and evaluate employee performance, (...) respectively. Based on the statistical analysis, there is a significant relationship between job burnout and employee performance. Moreover, the study's findings were thoroughly analyzed and discussed. (shrink)

By deploying the methodology of Judith Butler's notion of performativity, this article intends to understand the possibility of the concept of queerness beyond the possibilities of gender studies and queer theory and to develop a concept transcending the limits of identity. It is undeniable that Foucault's concept of disciplinarity is one of the major precursors of the notion of performativity, which is a more focused tool for what Foucault broadly devised. Both thinkers explain how the subject is a construction by (...) power. They explain how bodies are marked, assigned, and manipulated and expose the banality with which these operations take one for granted. It is through unearthing the disciplinary aspects of performativity in Butler and foreseeing the performative aspects of disciplinarity in Foucault that this article finds its methodological perspective. It is notable that disciplinarity and, as its extension, performativity ultimately exposes the underlying ontology of identity as a 'truth effect' rather than as an apriori truth. The paper critically analyses the artist's identity and the artistic discourse to unravel the queerness or an underlying plurality of aesthetic experience using performativity as a formative tool. (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)

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

Abstract: Tomatoes are among the most popular vegetables in the world due to their frequent use in many dishes, which fall into many varieties in common and traditional foods, and due to their rich ingredients such as vitamins and minerals, so they are frequently used on a daily basis, When we focus our attention on this vegetable, we must also focus and take into consideration the diseases that affect this vegetable, a deep learning model that classifies tomato diseases has been (...) proposed. The aim of this paper is to diagnose tomato diseases based on a dataset containing 11000 picture and 11 classes. The model gave the final accuracy test with Accuracy (99.87%), F1-score (99.87%), Recall (99.87%), and Precision (99.88%) in an estimated time 1.36 second, as with these results it proved its effectiveness and good ability in the classification of the testing data. (shrink)

Abstract: Forests are areas with a high density of trees, and they play a vital role in the health of the planet. They provide a habitat for a wide variety of plant and animal species, and they help to regulate the climate by absorbing carbon dioxide from the atmosphere. While in 2010, the world had 3.92Gha of forest cover, covering 30% of its land area, in 2019, there was a loss of forest cover of 24.2Mha according to the Global Forest (...) Watch institute. Discovery and classification depend on human experience and effort, so the error in the results of this process can lead to forest fires and disasters. Therefore, deep learning algorithms from artificial intelligence and machine learning sciences have been applied to help specialists avoid false or inaccurate diagnoses when detecting Forest fires in images using a pre-trained convolutional neural network called VGG16. The model was customized to fit the Forest fires classification and then applied to a dataset consisting of (14,000) of the Forests collected from the Kaggle depository. We trained, validated, and tested the modified VGG16 model. The proposed VGG16 model obtained Precision (99.96%), Recall (99.96%), and F1-Score (99.96%). (shrink)

One critique of the early Daoist texts associated with Laozi and Zhuangzi is that they neglect the human and lack a proper sense of ethical personhood in maintaining the primacy of an impersonal dehumanizing “way.” This article offers a reconsideration of the appropriateness of such negative evaluations by exploring whether and to what extent the ethical sensibility unfolded in the Zhuangzi is aporetic, naturalistic, and/or religious. As an ethos of cultivating life and free and easy wandering by performatively enacting openness (...) and responsiveness to things in an immanent this-worldly context, the Zhuangzi is oriented toward the relational attunement of disposition and practice rather than toward metaphysics or religion in a transcendent sense. It consequently suggests an immanent anarchic ethics without principles while neither forgetting nor reifying the sacred and the mundane in its playful illumination of the biospiritual dynamics of cultivating life. (shrink)

This study was conducted with the aim of developing the academic work in the Palestinian universities. No one can deny the technological stage that we are witnessing in the present era. Our mission is to use this development to develop the educational process. The Artificial Intelligence of the most important branches of computer science, which is interested in the development of computer software in order to make them simulate intelligent human, recently it emerged promised based on artificial intelligence applications are (...) intelligent tutoring system one of the most prominent of these applications is the most useful in the field of education. Intelligent tutoring system are programs that are helping the student and the teacher in the educational process, so that the student exploits these systems to increase his education and the acquisition of scientific skills, and we are not exaggerating if we say that the future of the development of the educational process is through the development of intelligent private teaching systems because it adapts to me intellectual level of the student as well as easy to use and available 24 hours every day. In this study, a smart tutor was designed using the ITSB tool developed by Prof. Sami Abu Nasser to develop the process of teaching the computer skills course. This course is a university course that teaches students of Israa University on different samples of students. After completion of the course, and evaluate the special lecturers who studied the course and used the system in the process of teaching and arrived at a set of conclusions and recommendations make sure that the use of the tutor Smart smartphone is important in the development of laboratory teaching has positive results in improving the level of scientific student . (shrink)

As the journal is effectively defunct, I am uploading a full-text copy, but only of my abstract and article, and some journal front matter. -/- Note that the pagination in the PDF version differs from the official pagination because A4 and 8.5" x 11" differ. -/- Traditionally, imperatives have been handled with deontic logics, not the logic of propositions which bear truth values. Yet, an imperative is issued by the speaker to cause (stay) actions which change the state of affairs, (...) which is, in turn, described by propositions that bear truth values. Thus, ultimately, imperatives affect truth values. In this paper, we put forward an idea that allows us to reason with imperatives using classical logic by constructing a one-to-one correspondence between imperatives and a particular class of declaratives. (shrink)

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)

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)

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.