In 1993, biologist Margie Profet captured the attention of the popular press with the publication of her radical thesis: menstruation has a function. Traditional theories, she claims, typically view menstruation as a functionless by-product of cyclic flux. The details of Profet's functional account are similarly radical: she argues that menstruation has been naturally selected to defend the female reproductive tract from sperm-borne pathogens. There are a number of weaknesses in Profet's evolutionary analysis. However, I focus on a set of pragmatic (...) problems that arise prior to any details of her evolutionary account. In arguing for the importance of pragmatic considerations, I draw from the linguistic analyses of Nelson Goodman. I conclude that critical investigation of the evolutionary details of Profet's pathogen defense account will be more feasible if and when biologists more frequently feature the female system of pathogen defense in their inductive generalisations. The system needs to be better entrenched before its functional components, such as menstruation, can be thoroughly investigated. (shrink)

In assessing the appropriateness of a scientific community's research effort, Solomon considers a number of "decision vectors," divided into the empirical and non-empirical. Value judgments get sorted as non-empirical vectors. By way of contrast, I introduce Anderson's discussion of the evidential role of value judgments. Like Anderson, I argue that value judgments are empirical in the relevant sense. I argue further that Solomon's decision matrix needs to be reconceptualized: the distinction should not be between the empirical vs. non-empirical, but between (...) the relevant vs. irrelevant. Whether particular value judgments are relevant or not is an empirical question, to be decided on a case-by-case basis. (shrink)

I have argued that political values are beliefs informed, more or less well, by the evidence of experience and that, where relevant and well-supported by evidence, the inclusion of political values in scientific theorizing can increase the objectivity of research. The position I endorse has been called the “values-as-evidence” approach. In this essay I respond to three kinds of resistance to this approach, using examples of feminist political values. Solomon questions whether values are beliefs that can be tested, Alcoff argues (...) that even if our values are beliefs that can be tested, testing them might not be desirable because doing so assigns these important values a contingency that weakens their normative force, and Yap argues that the approach is too idealistic in its articulation of the role of evidence in our political deliberations. In response, I discuss the ways that values can be tested, I analyze the evidential strength of feminist values in science, and I argue that the evidence-based nature of these values is neither a weakness nor an idealization. Problems with political values affecting science properly concern the dogmatic ways that evaluative beliefs are sometimes held—a problem that arises with dogmatism toward descriptive beliefs as well. I conclude that scientists, as with the rest of us, ought to adopt a pragmatically-inclined appreciation of the fallible, inductive process by which we gather evidence in support of any of our beliefs, whether they are described as evaluative or descriptive. (shrink)

While feminist epistemologists have made important contributions to the deconstruction of the traditional representationalist model, some elements of the Cartesian legacy remain. For example, relativism continues to play a role in the underdetermination thesis used by Longino and Keller. Both argue that because scientific theories are underdetermined by evidence, theory choice must be relative to interpretive frameworks. Utilizing Davidson's philosophy of language, I offer a nonrepresentationalist alternative to suggest how relativism can be more fully avoided.

In lieu of an abstract here is the first paragraph: -/- I mean the subtitle of my essay both as praise for the clarity with which Elizabeth Anderson writes about what is at stake in debates about values in science, and as a promise to outline an even more direct route to the heart of the matter. I begin with a quick review of the steps in Anderson’s argument that seem necessary and, indeed, laudable, followed by a brief discussion of (...) those steps in her argument that we might fruitfully skip. The hope is that we will arrive at roughly the same location but with a firmer foothold. (shrink)

Feminist theorists have shown that knowledge is embodied in ways that make a difference in science. Intemann properly endorses feminist standpoint theory over Longino’s empiricism, insofar as the former better addresses embodiment. I argue that a pragmatist analysis further improves standpoint theory: Pragmatism avoids the radical subjectivity that otherwise leaves us unable to account for our ability to share scientific knowledge across bodies of different kinds; and it allows us to argue for the inclusion, not just of the knowledge produced (...) from marginalised bodies, but of the marginalised themselves. (shrink)

: The relationship between facts and values—in particular, naturalism and normativity—poses an ongoing challenge for feminist science studies. Some have argued that the fact/value holism of W.V. Quine's naturalized epistemology holds promise. I argue that Quinean epistemology, while appropriately naturalized, might weaken the normative force of feminist claims. I then show that Quinean epistemic themes are unnecessary for feminist science studies. The empirical nature of our work provides us with all the naturalized normativity we need.

The works of the later Wittgenstein resonate with aspects of the pragmatist tradition in American philosophy. Davidson’s work is similarly informed. We argue that because of their association with the pragmatist tradition, their work can be put to use by philosophers interested in social justice issues, including, for example, feminism, and critical race theory. Philosophers concerned with social justice continue to struggle between the extremes of an untenable foundationalism and a radical relativism. Given their holistic understanding of knowledge, meaning and (...) communication, the work of Wittgenstein and Davidson is particularly suited to dissolving the foundationalist/relativist dichotomy. We explore how this and other features of their work facilitates philosophy for social change. (shrink)

This chapter’s main topic revolves around Davidson’s account of radical interpretation and the concept of triangulation as a necessary feature of communication and the formation of beliefs. There are two important implications of this model of belief formation for feminists studying the effects of social location on knowledge production generally, and the production of scientific knowledge in particular. The first is Davidson’s argument that whatever there is to the meaning of any of our beliefs must be available from the radical (...) interpreter’s external, third-person perspective. The second important implication of triangulation is that Davidson’s model is a holistic one that shows that there is no substantive difference in the triangulation process by which we form beliefs concerning basic descriptive features of the world and beliefs concerning evaluative features of the world. (shrink)

In Clough’s reply paper to me (http://wp.me/p1Bfg0-1aN), she laments how feminist calls for diversity within scientific communities are inadvertently sidelined by our shared feminist empiricist prescriptions. She offers a novel justification for diversity within epistemic communities and challenges me to accept this addendum to my prior prescriptions for biomedical research communities (Goldenberg 2013) on the grounds that they are consistent with the epistemic commitments that I already endorse. In this response, I evaluate and accept her challenge.

While most of healthcare research and practice fully endorses evidence-based healthcare, a minority view borrows popular themes from philosophy of science like underdetermination and value-ladenness to question the legitimacy of the evidence-based movement’s philosophical underpinnings. While the feminist origins go unacknowledged, those critics adopt a feminist reading of the “gap argument” to challenge the perceived objectivism of evidence-based practice. From there, the critics seem to despair over the “subjective elements” that values introduce to clinical reasoning, demonstrating that they do not (...) subscribe to feminist science studies’ normative program——where contextual values can enable good science and justified decisions. In this paper, I investigate why it is that the critics of evidence-based medicine adopt feminist science’s characterization of the problem but resist the productive solutions offered by those same theorists. I suggest that the common feminist empiricist appeal to idealized epistemic communities is impractical for those working within the current biomedical context and instead offer an alternate stream of feminist research into the empirical content of values (found in the work of Elizabeth Anderson and Sharyn Clough) as a more helpful recourse for facilitating the important task of legitimate and justified clinical decision-making. I use a case study on clinical decision-making to illustrate the fruitfulness of the latter feminist empiricist framework. -/- See response by Sharyn Clough: http://wp.me/p1Bfg0-1aN See reply by Maya Goldenberg: http://wp.me/p1Bfg0-1oY. (shrink)

Fact/value holism has become commonplace in philosophy of science, especially in feminist literature. However, that facts are bearers of empirical content, while values are not, remains a firmly-held distinction. I support a more thorough-going holism: both facts and values can function as empirical claims, related in a seamless, semantic web. I address a counterexample from Kourany where facts and values seem importantly discontinuous, namely, the simultaneous support by the Nazis of scientifically sound cancer research and morally unsound political policies. I (...) conclude that even by the criteria available at the time, Nazi cancer research was empirically weak, and the weaknesses in their research are continuous with their moral failures in just the ways predicted by the holism I support. (shrink)

Racist beliefs express value judgments. According to an influential view, value judgments are subjective, and not amenable to rational adjudication. In contrast, we argue that the value judgments expressed in, for example, racist beliefs, are false and objectively so. Our account combines a naturalized, philosophical account of meaning inspired by Donald Davidson, with a prominent social-psychological theory of values pioneered by the social-psychologist Milton Rokeach. We use this interdisciplinary approach to show that, just as with beliefs expressing descriptive judgments, beliefs (...) expressing value judgments have empirical content, or can be inferentially linked to beliefs that do; the truth or falsity of that content can be objectively assigned; and that assignment is amenable to rational assessment. While versions of this objective view of value judgments have been defended by moral realists of various metaphysical stripes, our argument has the virtue of appealing, instead, to accounts that are as naturalistically informed as possible. And, unlike the influential subjective view of value judgments, and racist beliefs more particularly, our arguments are better able to account for instances where rational, persuasive strategies have been effective in reducing the ubiquity of racism in American culture. (shrink)

The hygiene hypothesis offers an explanation for the correlation, well-established in the industrialized nations of North and West, between increased hygiene and sanitation, and increased rates of asthma and allergies. Recent studies have added to the scope of the hypothesis, showing a link between decreased exposure to certain bacteria and parasitic worms, and increased rates of depression and intestinal auto- immune disorders, respectively. What remains less often discussed in the research on these links is that women have higher rates than (...) men of asthma and allergies, as well as many auto-immune disorders, and also depression. The current paper introduces a feminist understanding of gender socialization to the epidemiological and immunological picture. That standards of cleanliness are generally higher for girls than boys, especially under the age of five when children are more likely to be under close adult supervision, is a robust phenomenon in industrialized nations, and some research points to a cross- cultural pattern. I conclude that, insofar as the hygiene hypothesis successfully identifies standards of hygiene and sanitation as mediators of immune health, then attention to the relevant patterns of gender socialization is important. The review also makes clear that adding a feminist analysis of gender socialization to the hygiene hypothesis helps explain variation in morbidity rates not addressed by other sources and responds to a number of outstanding puzzles in current research. Alternative explanations for the sex differences in the relevant morbidity rates are also discussed (e.g., the effects of estrogens). Finally, new sources of evidence for the hygiene hypothesis are suggested in the form of cross-cultural and other natural experiments. (shrink)

Almost everyone who has a limb amputated will experience a phantom limb--the vivid impression that the limb is not only still present, but in some cases, painful. There is now a wealth of empirical evidence demonstrating changes in cortical topography in primates following deafferentation or amputation, and this review will attempt to relate these in a systematic way to the clinical phenomenology of phantom limbs. With the advent of non-invasive imaging techniques such as MEG (magnetoencephalogram) and functional MRI, topographical reorganization (...) can also be demonstrated in humans, so that it is now possible to track perceptual changes and changes in cortical topography in individual patients. We suggest, therefore, that these patients provide a valuable opportunity not only for exploring neural plasticity in the adult human brain but also for understanding the relationship between the activity of sensory neurons and conscious experience. We conclude with a theory of phantom limbs, some striking demonstrations of phantoms induced in normal subjects, and some remarks about the relevance of these phenomena to the question of how the brain constructs a 'body image.'. (shrink)

This comparative examination of Nietzsche and the Islamic philosopher al-Kindi emphasizes their mutual commitment to the recovery of classical Greek and Hellenistic thought and the idea of philosophy as a way of life. Affiliating both thinkers with the Stoic lineage in particular, I examine the ways in which they appropriate common themes such as fatalism, self-cultivation via spiritual exercises, and the banishing of sorrow. Focusing primarily on their respective conceptions of self and nature, I argue that the antipodal worldviews of (...) al-Kindi and Nietzsche can be understood as a bifurcation of Stoic philosophy. (shrink)

The Epicurean account of the origin of language appealed to eighteenth-century thinkers who tried to reconcile a natural history of language with

the biblical account of Adamic name-giving. As a third way between Aristotelian linguistic conventionality and what was perceived as a Platonic supernatural congruence between words and things, Epicurus’

theory allowed for a measure of contingency to emerge in the evolution of initially natural signs. This hypothesis was taken up by authors as different from one another as Leibniz, Vico, Condillac and (...) Mendelssohn. By integrating the Epicurean account of language into their own theories, however, these authors also revived the tensions inherent in the ancient thesis and had to confront the ensuing difficulties in innovative ways. (shrink)

Glucagon-like peptide-1 (GLP-1) receptor agonists, such as semaglutide, and dual GLP-1 and glucose-dependent insulinotropic polypeptide (GIP) receptor agonists, such as tirzepatide, have been found to be effective for treating obesity and diabetes, significantly reducing weight and the risk or predicted risk of adverse cardiovascular events. There is a global shortage of these medications that could last several years and raises questions about how limited supplies should be allocated. We propose a fair-allocation framework that enables evaluation of the ethics of current (...) practices and could guide governments, professional societies, and physicians in allocation decisions. (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)

In this article, it has been aimed to examine Nietzsche’s main critique towards different understandings of morals in his era. With this criticism, it is aimed to integrally understand the opinions -which are articulated directly or metaphorically- towards morals which have been encountered. In here, while keeping in mind the difference between the concepts of immoralism and amoralism, Nietzsche’s views are interpreted. Being parallel to that aim mentioned above, it has been investigated if there is a thinking in Nietzsche which (...) can be seen as a kind of understanding of morals (maybe as the understanding of morals without morals) or not. And finally, it has been thought that if Nietzsche’s views on morals have any value for the 21st century and upcoming 22nd century human or not, whether there’s something left to learn for this human from his critiques or not. (shrink)

Abstract. Intelligent Tutoring System Builder (ITSB) is an authoring tool designed and developed to aid teachers in constructing intelligent tutoring systems in a multidisciplinary fields. The teacher is needed to create a set of pedagogical fundamentals, which, in line, are inured to automatically build up a broad tutor framework and construct an intelligent tutoring system. In this paper an explanation of the theory and the architecture of the tool is outlined. A presentation of several system components, the requirements of the (...) different components, integration of these components in ITSB tool are shown. Furthermore, implanting of requirements, cognitive principle, and common design fundamentals in the tool to ease the use of teachers. A variety of design matters, an example of building an intelligent tutoring system for teaching Java language using ITSB tool and an evaluation are presented. (shrink)

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

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

Abstract: Fish are important for both nutritional and economic reasons. They are a good source of protein, vitamins, and minerals and play a significant role in human diets, especially in coastal and island communities. In addition, fishing and fish farming are major industries that provide employment and income for millions of people worldwide. Moreover, fish play a critical role in marine ecosystems, serving as prey for larger predators and helping to maintain the balance of aquatic food chains. Overall, fish play (...) a vital role in supporting human well-being and the health of our planet. . Fishes have a lots of types such that: Red Mullet, Sea Bass, Striped Red Mullet and Shrimp. Each of them has its own shape and characteristics that differ from other types. We proposed a system that recognize nine types of fishes using deep learning. We trained the model with a dataset that contain 9000 images that were slit into 6300 images for training, 1350 for validation and 1350 for testing. The proposed model achieved accuracy (99.68%), precision (99.69%), recall (99.68%), and f1-score (99.68%). This indicates that our proposed model can effectively predicate and classify different types of fish with very high accuracy. (shrink)

Abstract: Classifying sea animals is an important problem in marine biology and ecology as it enables the accurate identification and monitoring of species populations, which is crucial for understanding and protecting marine ecosystems. This paper addresses the problem of classifying 19 different sea animals using convolutional neural networks (CNNs). The proposed solution is to use a pretrained MobileNetV2 model, which is a lightweight and efficient CNN architecture, and fine-tune it on a dataset of sea animals. The results of the study (...) show that the fine-tuned MobileNetV2 model is able to achieve an accuracy of 85% on the classification task, which is competitive with the state-of-the-art methods. Additionally, the study also found that data augmentation and regularization techniques such as dropout were important for preventing overfitting and improving the performance of the model. This study demonstrates the potential of using pretrained models and efficient CNN architectures for classifying sea animals, and it provides insights into the challenges and best practices for solving this important problem in marine biology and ecology. (shrink)

Abstract: In this study, we explore the challenge of identifying and preventing diseases in apple trees, which is a popular activity but can be difficult due to the susceptibility of these trees to various diseases. To address this challenge, we propose the use of Convolutional Neural Networks, which have proven effective in automatically detecting plant diseases. To validate our approach, we use images of apple leaves, including Apple Rot Leaves, Leaf Blotch, Healthy Leaves, and Scab Leaves collected from Kaggle which (...) is part from the Plant Village dataset. We generate a comprehensive training dataset using techniques such as image filtering, compression, and generation. Our model achieves impressive accuracy scores for all classes, with an overall accuracy of 99.93% on a dataset of 10,000 labeled images . (shrink)

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

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)

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)

Abstract: People all over the world have been drinking tea for thousands of centuries, and for good reason. Many types of teas can help you stay healthy by boosting your immune system, reducing inflammation, and even preventing cancer and heart disease. There is sufficient material to show that regularly consuming tea can improve your health over the long term. A deep learning model that categorizes tea disorders has been completed. When focusing on the tea, we must also focus on and (...) take into account the diseases that harm it. The aim of this paper is to diagnose tea diseases based on a dataset containing 8000 picture and 8 classes .The model gave the final accuracy test with an F1-score of 99.41% in an estimated time 3 second, as with these results it proved its effectiveness and good ability in the classification test. (shrink)

Persons think. Bodies, time-slices of persons, and brains might also think. They have the necessary neural equipment. Thus, there seems to be more than one thinker in your chair. Critics assert that this is too many thinkers and that we should reject ontologies that allow more than one thinker in your chair. I argue that cases of multiple thinkers are innocuous and that there is not too much thinking. Rather, the thinking shared between, for example, persons and their bodies is (...) exactly what we should expect at the intersection of part sharing and the supervenience of the mental on the physical. I end by responding to the overcrowding objection, the personhood objection, the personal-pronoun reference problem and the epistemic objection. (shrink)

Academic excellence and intelligence are commonly lauded as commendable attributes synonymous with success. However, a disconcerting trend has surfaced within educational institutions, challenging the prevailing narrative of scholastic accomplishment—smart shaming. This research delves into the increasing concern of smart shaming within educational settings, particularly at Immaculate Conception College of Balayan, Inc., questioning the predominant emphasis on academic excellence and intelligence. A qualitative case study design, along with judgmental sampling, was employed to examine fifteen (15) student leaders who had experienced smart (...) shaming on campus. Thematic analysis revealed that sarcastic remarks including "edi wow," "Okay ikaw na matalino," "bidabida," and "sipsip" were a prevalent manifestation of smart shaming, adversely affecting emotional well-being, academic and leadership prowess, mental health, and self-perception. Coping mechanisms, predominantly centered around ignoring and focusing on goals, were identified. The findings underscore the imperative for educators to remain vigilant regarding instances of smart shaming in classrooms, promoting open communication to ensure student well-being. Additionally, guidance counselors play a pivotal role in aiding students in effectively navigating the repercussions of smart shaming. This study advocates for proactive programs and interventions to address and alleviate the deleterious effects of smart shaming on students. (shrink)

There is an increase in the use of in-door wireless networking solutions via Wi-Fi and this increase infiltrated and utilized Wi-Fi enable devices, as well as smart mobiles, games consoles, security systems, tablet PCs and smart TVs. Thus the demand on Wi-Fi connections increased rapidly. Rule Based System is an essential method in helping using the human expertise in many challenging fields. In this paper, a Rule Based System was designed and developed for diagnosing the wireless connection problems and attain (...) a precise decision about the cause of the problem. SL5 Object expert system language was used in developing the rule based system. An Evaluation of the rule based system was carried out to test its accuracy and the results were promising. (shrink)

I suspect the answer to the question in the title of this paper is no. But the scope of my paper will be considerably more limited: I will be concerned with whether certain types of considerations that are commonly cited in favor of dynamic semantics do in fact push us towards a dynamic semantics. Ultimately, I will argue that the evidence points to a dynamics of discourse that is best treated pragmatically, rather than as part of the semantics.

Abstract: Artificial Intelligence (AI) is revolutionizing the agricultural sector by enhancing productivity and sustainability. This paper explores the transformative impact of AI technologies on agriculture, focusing on their applications in precision farming, predictive analytics, and automation. AI-driven tools enable more efficient management of crops and resources, leading to improved yields and reduced environmental impact. The paper examines key AI technologies, including machine learning algorithms for crop monitoring, robotics for automated planting and harvesting, and data analytics for optimizing resource use. Additionally, (...) it addresses challenges such as data privacy, technology adoption barriers, and the ethical implications of AI in farming. By integrating AI into agricultural practices, the industry can achieve greater efficiency and sustainability, paving the way for future advancements. (shrink)

The theoretical foundations of climate science have received little attention from philosophers thus far, despite a number of outstanding issues. We provide a brief, non-technical overview of several of these issues – related to theorizing about climates, climate change, internal variability and more – and attempt to make preliminary progress in addressing some of them. In doing so, we hope to open a new thread of discussion in the emerging area of philosophy of climate science, focused on theoretical foundations.

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

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

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

Corruptionism is the view that following physical death, the human being ceases to exist but their soul persists in the afterlife. Survivalism holds that both the human being and their soul persist in the afterlife, as distinct entities, with the soul constituting the human. Each position has its defenders, most of whom appeal both to metaphysical considerations and to the authority of St Thomas Aquinas. Corruptionists claim that survivalism violates a basic principle of any plausible mereology, while survivalists tend to (...) reject the principle, though without as much detail as one would like. In this paper I examine both the key exegetical issues and the mereological question, arguing that Aquinas cannot be shown to have supported the principle in question, and that the principle should be rejected on independent grounds. If correct, some key planks in support of survivalism are established, with others to await further examination. (shrink)

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