Since the launch of applications such as DALL-E, Midjourney, and Stable Diffusion, generative artificial intelligence has been controversial as a tool for creating artwork. While some have presented longtermist worries about these technologies as harbingers of fully automated futures to come, more pressing is the impact of generative AI on creative labour in the present. Already, business leaders have begun replacing human artistic labour with AI-generated images. In response, the artistic community has launched a protest movement, which argues that AI (...) image generation is a kind of theft. This paper analyzes, substantiates, and critiques these arguments, concluding that AI image generators involve an unethical kind of labour theft. If correct, many other AI applications also rely upon theft. (shrink)

Conceptual engineering is concerned with the improvement of our concepts. The motivating thought behind many such projects is that some of our concepts are defective. But, if to use a defective concept is to do something wrong, and if to do something wrong one must be in control of what one is doing, there might be no defective concepts, since we typically are not in control of our concept use. To address this problem, this paper turns from appraising the concepts (...) we use to appraising the people who use them. First, I outline several ways in which the use of a concept can violate moral standards. Second, I discuss three accounts of moral responsibility, which I call voluntarism, rationalism, and psychologism, arguing that each allows us to find at least some cases where we are responsible for using defective concepts. Third, I answer an objection that because most of our concepts are acquired through processes for which we are not responsible, our use of defective concepts is a matter of bad luck, and not something for which we are responsible after all. Finally, I conclude by discussing some of the ways we may hold people accountable for using defective concepts. (shrink)

How do we prepare engineering students to make ethical and responsible decisions in their professional work? This paper presents an approach that enhances engineering students’ engagement with ethical reasoning by simulating decision-making in a complex scenario. The approach has two principal inspirations. The first is Anthony Weston’s scenario-based teaching. Weston’s concept of a scenario is a situation that changes in response to choices made by participants, according to an inner logic. Scenarios can dynamically explore open-ended complex problems without imposing predetermined (...) results, allowing students to apply their ethical reasoning in a more realistic fashion. The second inspiration is Thi Nguyen’s theory of games. According to Nguyen, games are the “art of agency,” meaning that they provide a structure under which some result is agreed to be valuable, along with prescribed ways of achieving that result, in a relatively low-stakes and temporary social arrangement. By playing many games, Nguyen argues, we can develop a “library of agency,” that is to say, a set of values and means to achieving them that can inform how we make high-stakes decisions in real life. Engaging with carefully designed game scenarios, then, can enable students to practice making ethical decisions within a structured framework, which unfolds in response to their choices, while their decisions are driven by some defined goal. This roleplaying game–based approach thus allows students to build their own ethical libraries of agency, in preparation for professional decision-making. The approach is illustrated using a specific example recently deployed in a seminar on engineered living materials (building materials that incorporate living tissues). The scenario uses techniques from tabletop roleplaying games (e.g. Dungeons & Dragons) for outcome resolution, adventure design, and character creation. Through the game, students practice making difficult decisions in a humanitarian context. (shrink)

When we encounter extremist rhetoric, we often find it dumbfounding, incredible, or straightforwardly unintelligible. For this reason, it can be tempting to dismiss or ignore it, at least where it is safe to do so. The problem discussed in this paper is that such dismissals may be, at least in certain circumstances, epistemically unjust. Specifically, it appears that recent work on the phenomenon of hermeneutical injustice compels us to accept two unpalatable conclusions: first, that this failure of intelligibility when we (...) encounter extremist rhetoric may be a manifestation of a hermeneutical injustice; and second, that remedying this injustice requires that we ought to become more engaged with and receptive of extremist worldviews. Whilst some theorists might interpret this as a reductio of this framework of epistemic in/justice, we push back against this conclusion. First, we argue that with a suitably amended conception of hermeneutical justice—one that is sensitive to the contextual nature of our hermeneutical responsibilities, and to the difference between understanding a worldview and accepting it—we can bite the bullet and accept that certain extremists are subject to hermeneutical injustice, but without committing ourselves to any unpalatable conclusions about how we ought to remedy these injustices. Second, we argue that bringing the framework of hermeneutical in/justice to bear upon the experience of certain extremists actually provides a new and useful perspective on one of the causes of extremism, and how it might be undermined. (shrink)

According to Miranda Fricker, a hermeneutical injustice occurs when there is a deficit in our shared tools of social interpretation, such that marginalized social groups are at a disadvantage in making sense of their distinctive and important experiences. Critics have claimed that Fricker's account ignores or precludes a phenomenon I call hermeneutical dissent, where marginalized groups have produced their own interpretive tools for making sense of those experiences. I clarify the nature of hermeneutical injustice to make room for hermeneutical dissent, (...) clearing up the structure of the collective hermeneutical resource and the fundamental harm of hermeneutical injustice. I then provide a more nuanced account of the hermeneutical resources in play in instances of hermeneutical injustice, enabling six species of the injustice to be distinguished. Finally, I reflect on the corrective virtue of hermeneutical justice in light of hermeneutical dissent. (shrink)

When a computer system causes harm, who is responsible? This question has renewed significance given the proliferation of autonomous systems enabled by modern artificial intelligence techniques. At the root of this problem is a philosophical difficulty known in the literature as the responsibility gap. That is to say, because of the causal distance between the designers of autonomous systems and the eventual outcomes of those systems, the dilution of agency within the large and complex teams that design autonomous systems, and (...) the impossibility of fully predicting how autonomous systems will behave once deployed, determining who is morally responsible for harms caused by autonomous systems is unclear at a conceptual level. I review past work on this topic, criticizing prior works for suggesting workarounds rather than philosophical answers to the conceptual problem presented by the responsibility gap. The view I develop, drawing on my earlier work on vicarious moral responsibility, explains why computing professionals are ethically required to take responsibility for the systems they design, despite not being blameworthy for the harms these systems may cause. (shrink)

When you expect something bad to happen, you take action to avoid it. That is the principle of action that underlies J. Y. Lee’s recent paper (2021), which presents a new form of epistemic injustice that arises from anticipating negative consequences for testifying. In this brief reply article occasioned by Lee’s essay, I make two main contributions to the discussion of this idea. The first (§§2–3) is an intervention in the discussion between Lee and Eric Bayruns García regarding the relationship (...) between anticipatory epistemic injustice and Kristie Dotson’s concept of testimonial smothering. The second (§§4–5) is to expand the concept of anticipatory epistemic injustice into the educational context, and to illuminate yet another form of anticipatory epistemic injustice, which I call anticipatory zetetic injustice (§6). (shrink)

This thesis concerns our moral and epistemic responsibilities regarding our concepts. I argue that certain concepts can be morally, epistemically, or socially problematic. This is particularly concerning with regard to our concepts of social kinds, which may have both descriptive and evaluative aspects. Being ignorant of certain concepts, or possessing mistaken conceptions, can be problematic for similar reasons, and contributes to various forms of epistemic injustice. I defend an expanded view of a type of epistemic injustice known as ‘hermeneutical injustice’, (...) where widespread conceptual ignorance puts members of marginalized groups at risk of their distinctive and important experiences lacking intelligible interpretations. Together, I call the use of problematic concepts or the ignorance of appropriate concepts ‘conceptual incapacities’. I discuss the conditions under which we may be responsible for our conceptual incapacities on several major theories of responsibility, developing my own account of responsibility in the process, according to which we are responsible for something just in case it was caused by one of our reasons-responsive constitutive psychological traits. However, I argue that regardless of whether we are responsible for something, we may still be required to take responsibility for it. Whether or not we are responsible for our conceptual incapacities, we are required to reflect critically upon them in a variety of scenarios that throw our use of those concepts into question. I consider the method of conceptual engineering — the philosophical critique and revision of concepts — as one way we might take responsibility for our concepts, or at least, defer that duty to experts. But, this top-down model of conceptual revision is insufficient. Using a pragmatist model of the social epistemology of morality, I argue that conceptual inquiry is a social endeavour in which we are all required to participate, to some degree. (shrink)

While calls to integrate ethics into computer science education go back decades, recent high-profile ethical failures related to computing technology by large technology companies, governments, and academic institutions have accelerated the adoption of computer ethics education at all levels of instruction. Discussions of how to integrate ethics into existing computer science programmes often focus on the structure of the intervention—embedded modules or dedicated courses, humanists or computer scientists as ethics instructors—or on the specific content to be included—lists of case studies (...) and essential topics to cover. While proponents of computer ethics education often emphasize the importance of closely connecting ethical and technical content in these initiatives, most do not reflect in depth on the variety of ways in which the disciplines can be combined. In this paper, I deploy a framework from cross- disciplinary studies that categorizes academic projects that work across disciplines as multidisciplinary, interdisciplinary, or transdisciplinary, depending on the degree of integration. When applied to computer ethics education, this framework is orthogonal to the structure and content of the initiative, as I illustrate using examples of dedicated ethics courses and embedded modules. It therefore highlights additional features of cross-disciplinary teaching that need to be considered when planning a computer ethics programme. I argue that computer ethics education should aim to be at least interdisciplinary—multidisciplinary initiatives are less aligned with the pedagogical aims of computer ethics—and that computer ethics educators should experiment with fully transdisciplinary education that could transform computer science as a whole for the better. (shrink)

The use of language models in Web applications and other areas of computing and business have grown significantly over the last five years. One reason for this growth is the improvement in performance of language models on a number of benchmarks — but a side effect of these advances has been the adoption of a “bigger is always better” paradigm when it comes to the size of training, testing, and challenge datasets. Drawing on previous criticisms of this paradigm as applied (...) to large training datasets crawled from pre-existing text on the Web, we extend the critique to challenge datasets custom-created by crowdworkers. We present several sets of criticisms, where ethical and scientific issues in language model research reinforce each other: labour injustices in crowdwork, dataset quality and inscrutability, inequities in the research community, and centralized corporate control of the technology. We also present a new type of tool for researchers to use in examining large datasets when evaluating them for quality. (shrink)

In this chapter, I argue that it is impossible to trust the Big Tech companies, in an ethically important sense of trust. The argument is not that these companies are untrustworthy. Rather, I argue that the power to hold the trustee accountable is a necessary component of this sense of trust, and, because these companies are so powerful, they are immune to our attempts, as individuals or nation-states, to hold them to account. It is, therefore, literally impossible to trust Big (...) Tech. After introducing the accounts of trust and power that I deploy, I argue that Big Tech companies have four kinds of power that render them unaccountable: fiscal power, political power, data power, and cognitive power. I conclude by reflecting on recent calls to break up the Big Tech firms, suggesting a new antitrust test in the light of my arguments. (shrink)

Current disputes over the nature and purpose of the university are rooted in a philosophical divide between theory and practice. Academics often defend the concept of a university devoted to purely theoretical activities. Politicians and wider society tend to argue that the university should take on more practical concerns. I critique two typical defenses of the theoretical concept—one historical and one based on the value of pure research—and show that neither the theoretical nor the practical concept of a university accommodates (...) all the important goals expected of university research and teaching. Using the classical pragmatist argument against a sharp division between theory and practice, I show how we can move beyond the debate between the theoretical and practical concepts of a university, while maintaining a place for pure and applied research, liberal and vocational education, and social impact through both economic applications and criticism aimed at promoting social justice. (shrink)

This volume has its roots in two recent developments within mainstream analytic epistemology: a growing recognition over the past two or three decades of the active and social nature of our epistemic lives; and, more recently still, the increasing appreciation of the various ways in which the epistemic practices of individuals and societies can, and often do, go wrong. The theoretical analysis of these breakdowns in epistemic practice, along with the various harms and wrongs that follow as a consequence, constitutes (...) an approach to epistemology that we refer to as non-ideal epistemology. In this introductory chapter we introduce and contextualise the ten essays that comprise this volume, situating them within four broad sub-fields: vice epistemology, epistemic injustice, inter-personal epistemic practices, and applied epistemology. We also provide a brief overview of several other important growth areas in non-ideal epistemology. (shrink)

I argue that according to Kristie Dotson, non-epistemic motives such as social, ethical and material harm can motivate a speaker to smother her testimony. I present this exegesis of Dotson's view of testimonial smothering in response to J. L. Lee's and Trystan Goetze's reply to my commentary of Lee's view that anticipatory epistemic injustice is distinct from testimonial smothering.

In a recent paper, John Fischer develops a new argument against the Principle of Alternative Possibilities (PAP) based on a deterministic scenario. Fischer uses this result (i) to rebut the Dilemma Defense - a well-known incompatibilist response to Frankfurt-type counterexamples to PAP; and (ii) to maintain that: If causal determinism rules out moral responsibility, it is not just in virtue of eliminating alternative possibilities. In this article, we argue that Fischer's new argument against PAP fails, thus leaving points (i) and (...) (ii) unsupported. (shrink)

Logical limits of omnipotence, the problem of evil, and a compelling cosmological argument suggest the position of supreme providence and the foremost creation out of nothing that coheres with the constraints of physics. The Supreme Being possesses everlasting love, perception, and force while governing the universe of probabilistic processes and freewill creatures. For example, the Supreme Being intervenes in the processes of creation by the means of synergism with freewill creatures and cannot meticulously control the created universe.

Goetz outlined legal models of identical entities that include natural persons who are identical to a coregency and natural persons who are identical to a general partnership. Those entities cohere with the formula logic of relative identity. This essay outlines the coexistence of relative identity and numerical identity in the models of identical legal entities, which is impure relative identity. These models support the synthesis of Relative Trinitarianism and Social Trinitarianism, which I call Relative-Social Trinitarianism.

In this paper, I argue that a commitment to science and the methodo- logical commitment to causal closure do not require a rejection of the idea that the choices of souls explain the occurrence of certain events in the physical world. Stated slightly differently, I maintain that one can both affirm science and believe that souls causally interfere in the course of events in the physical world. Such an affirmation and belief are compatible. In short, science vis-à-vis the methodological principle (...) of causal closure poses no problem for souls as explanatory agents. (shrink)

This essay proposes an ontological model in which a legal person such as a polity possesses natural unity from group properties that emerge in the self-organization of the human population. Also, analysis of customary legal persons and property indicates noncontradictory paradoxes that include Aristotelian essence of an entity, relative identity over time, ubiquitous authority, coinciding authorities, and identical entities. Mathematical modeling helps to explain the logic of the paradoxes.

This paper models God and time in the framework of modern physics. God bridges and simultaneously exists in (1) a universe with infinite tenseless time and (2) a created parallel universe with tensed time and a point origin. The primary attributes of God are inexhaustible love, inexhaustible perception, and inexhaustible force. The model also incorporates modern physics theories that include relativity, the conservation of energy, quantum mechanics, and multiverse geometry. For example, creation out of nothing and divine intervention are subject (...) to physical processes and likewise nomological possibility. I will call this model semiclassical theism. (shrink)

This paper briefly proposes a weak relative identity strategy for the doctrine of the Trinity called the general partnership model. This model develops a logically consistent metaphysical constitution for the orthodox Christian doctrines of one divine substance and three divine persons. Moreover, the model rejects the rigid use of absolute identity in Trinitarian doctrine while modeling relative identity with an analogy of general partnerships in the United States.

We evaluate classical probability in relation to the random generation of a Shakespearean sonnet by a typing monkey and the random generation of universes in a World Ensemble based on various multiverse models involving eternal inflation. We calculate that it would take a monkey roughly 10^942 years to type a Shakespearean sonnet, which pushes the scenario into a World Ensemble. The evaluation of a World Ensemble based on various models of eternal inflation suggests that there is no middle ground between (...) eternal Poincare-Zermelo recurrence and a 0 probability in regards to the natural generation of the initial conditions of the universe. (shrink)

Denton proposes a hypothesis of frontloaded teleological evolution while Denton suggests that a vast amount of junk DNA is incompatible with his model of teleology and perhaps any model of teleology. This paper outlines a hypothesis for a vast amount of junk DNA with no selective constraints, and proposes that the junk DNA is compatible with teleological evolution that included occasional intervention during the history of adaptive evolution. And this paper introduces a hypothesis for the necessity of intervention in the (...) history of adaptive evolution. And both the hypothesis of junk DNA and the hypothesis for the necessity of intervention meet the criteria of falsifiability according to Popper. (shrink)

This note briefly discusses the observation of elapsed time in a flat universe while exploring the argument of past-eternal time versus emergent time in cosmology. A flat universe with an incomplete past forever has a finite age. Despite an infinite number of Planck time coordinates independent of phenomena and endless expansion, a flat universe never develops an age with an infinite number of Planck times. This observation indicates the impossibility of infinitely elapsed time in the future or past, which limits (...) acceptable scientific models of cosmology. (shrink)

I agree with Michael Buratovich concerning the validity of the serial endosymbiosis theory, and that neo-Darwinian mechanics alone do not explain the grand history of universal phylogeny (PSCF 57, no. 2 [June 2005]: 98-113). However, I disagree with the Buratovich hypothesis that the hierarchal transfer of ribosomal protein small unit (rps) genes from mitochondrial genomes to nuclear genomes indicates inbuilt Intelligent Design (ID) instead of neo-Darwinian mechanics, where inbuilt ID involves "purposeful forces that are wholly natural in their scope and (...) activity.". (shrink)

In the beginning, the Spirit of God stirred absolute nothingness. The stirring generated waves that turned into physical matter with relative space-time and the other laws of nature. Then God dispersed the matter that eventually formed into galaxies. Roughly ten billion years later, God intervened to bring forth the first cellular life, and God continued to orchestrate mutations and natural selection that culminated with the formation of anatomically modern humans.

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)

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)