Throughout this research, imposing the training of an Artificial Neural Network (ANN) to play tic-tac-toe bored game, by training the ANN to play the tic-tac-toe logic using the set of mathematical combination of the sequences that could be played by the system and using both the Gradient Descent Algorithm explicitly and the Elimination theory rules implicitly. And so on the system should be able to produce imunate amalgamations to solve every state within the game course to make better of results (...) of winnings or getting draw. (shrink)

Throughout this research, imposing the training of an Artificial Neural Network (ANN) to play tic-tac-toe bored game, by training the ANN to play the tic-tac-toe logic using the set of mathematical combination of the sequences that could be played by the system and using both the Gradient Descent Algorithm explicitly and the Elimination theory rules implicitly. And so on the system should be able to produce imunate amalgamations to solve every state within the game course to make better of results (...) of winnings or getting draw. (shrink)

Throughout this research, imposing the training of an Artificial Neural Network (ANN) to play tic-tac-toe bored game, by training the ANN to play the tic-tac-toe logic using the set of mathematical combination of the sequences that could be played by the system and using both the Gradient Descent Algorithm explicitly and the Elimination theory rules implicitly. And so on the system should be able to produce imunate amalgamations to solve every state within the game course to make better of results (...) of winnings or getting draw. (shrink)

A hitherto neglected form of explanation is explored, especially its role in population genetics. “Statistically abstractive explanation” (SA explanation) mandates the suppression of factors probabilistically relevant to an explanandum when these factors are extraneous to the theoretical project being pursued. When these factors are suppressed, the explanandum is rendered uncertain. But this uncertainty traces to the theoretically constrained character of SA explanation, not to any real indeterminacy. Random genetic drift is an artifact of such uncertainty, and it is therefore wrong (...) to reify it as a cause of evolution or as a process in its own right. *Received July 2009. †To contact the author, please write to: Department of Philosophy, University of Toronto, 170 St. George St., Toronto, ON M5R 2M8, Canada; e‐mail: [email protected]. (shrink)

Abstract: Background: In spite of the fact that computers continue to improve in speed and functions operation, they remain complex to use. Problems frequently happen, and it is hard to resolve or find solutions for them. This paper outlines the significance and feasibility of building a desktop PC problems diagnosis system. The system gathers problem symptoms from users’ desktops, rather than the user describes his/her problems to primary search engines. It automatically searches global databases of problem symptoms and solutions, and (...) also allows ordinary users to contribute exact problem reports in a structured manner. Objectives: The main goal of this Knowledge Based System is to get the suitable problem desktop PC symptoms and the correct way to solve the errors. Methods: In this paper the design of the proposed Knowledge Based System which was produced to help users of desktop PC in knowing many of the problems and error such as : Power supply problems, CPU errors, RAM dumping error, hard disk errors and bad sectors and suddenly restarting PC. The proposed Knowledge Based System presents an overview about desktop PC hardware errors are given, the cause of fault are outlined and the solution to the problems whenever possible is given out. CLIPS Knowledge Based System language was used for designing and implementing the proposed expert system. Results: The proposed PC desktop troubleshooting Knowledge Based System was evaluated by IT students and they were satisfied with its performance. (shrink)

Publication date: 29 September 2016 Source: Author: Samy S. Abu Naser, Mazen J. Al Shobaki, Youssef M. Abu Amuna This paper aims to measure knowledge management maturity in higher education institutions to determine the impact of knowledge management on high performance. Also the study aims to compare knowledge management maturity between universities and intermediate colleges. This study was applied on five higher education institutions in Gaza strip, Palestine. Asian productivity organization model was applied to measure Knowledge Management Maturity. Second dimension (...) which assess high performance was developed by the authors. The controlled sample was. Several statistical tools were used for data analysis and hypotheses testing, including reliability correlation using Cronbach’s alpha, “ANOVA”, Simple Linear Regression and Step Wise Regression. The overall findings of the current study shows that maturity level is in the second level. Findings also support the main hypothesis and it is sub- hypotheses. The most important factors effecting high performance are: Processes, knowledge management leadership, People, knowledge management Outcomes. Furthermore the current study is unique by the virtue of its nature, scope and way of implied investigation, as it is the first comparative study between universities and intermediate colleges in Gaza Strip that explores the status of knowledge management maturity using the Asian productivity Model. (shrink)

Food has savour: a collection of properties (including appearance, aroma, mouth-feel) connected with the pleasure (or displeasure) of eating. After explaining this concept, and outlining a theory of aesthetic pleasure, I argue that, like paradigm examples of art, savour can be assessed relative to a culturally determined set of norms. Also like paradigm examples of art, the assessment of savour has no objective basis in the absence of such cultural norms. My argument in this paper is part of a larger (...) project in which I develop an account of the pleasure of art. It is a virtue (I claim) of my approach that it permits a much greater diversity of artforms than traditional philosophical aesthetics is inclined to allow. This includes food. (shrink)

Kant argued that the perceptual representations of space and time were templates for the perceived spatiotemporal ordering of objects, and common to all modalities. His idea is that these perceptual representations were specific to no modality, but prior to all—they are pre-modal, so to speak. In this paper, it is argued that active perception—purposeful interactive exploration of the environment by the senses—demands premodal representations of time and space.

This is a response to invited and submitted commentary on "The Pleasure of Art," published in Australasian Philosophical Reviews 1, 1 (2017). In it, I expand on my view of aesthetic pleasure, particularly how the distinction between facilitating pleasure and relief pleasure works. In response to critics who discerned and were uncomfortable with the aesthetic hedonism that they found in the work, I develop that aspect of my view. My position is that the aesthetic value of a work of art (...) is its capacity to elicit from a suitably well-informed consumer a specific kind of pleasure. (shrink)

This paper presents a new account of aesthetic pleasure, according to which it is a distinct psychological structure marked by a characteristic self-reinforcing motivation. Pleasure figures in the appreciation of an object in two ways: In the short run, when we are in contact with particular artefacts on particular occasions, aesthetic pleasure motivates engagement and keeps it running smoothly—it may do this despite the fact that the object we engagement is aversive in some ways. Over longer periods, it plays a (...) critical role in shaping how we engage with objects to get this kind of pleasure from them. This account is yoked to a broadly functional understanding of art: it is not the nature of the object that makes it art, but the nature of the response that it is designed to elicit. The view does not, however, rest on individual psychology alone, as some other functional accounts do. Crucially, it is argued that shared cultural context is a key determinant of the pleasure we derive from aesthetic artefacts. The pleasure of art is always communal and communicative. (shrink)

In this essay, I’ll argue, first, that an art object's aesthetic value (or merit) depends not just on its intrinsic properties, but on the response it evokes from a consumer who shares the producer's cultural background. My question is: what is the role of culture in relation to this response? I offer a new account of aesthetic pleasure that answers this question. On this account, aesthetic pleasure is not just a “feeling” or “sensation” that results from engaging with a work (...) of art. It is rather a mental state that facilitates engagement with an artwork, and (in the long run) enables a consumer to learn how to maximize this kind of pleasure. This is where culture comes in. If you belong to a culture, you know how to engage pleasurably with an artwork that is produced so you can engage with it in just this way. The aesthetic value of an artwork is that it plays into such a culture-pleasure nexus. -/- . (shrink)

It is crucial to actively detect the risks of transactions in a financial company to improve customer experience and minimize financial loss. In this study, we compare different machine learning algorithms to effectively and efficiently predict the legitimacy of financial transactions. The algorithms used in this study were: MLP Repressor, Random Forest Classifier, Complement NB, MLP Classifier, Gaussian NB, Bernoulli NB, LGBM Classifier, Ada Boost Classifier, K Neighbors Classifier, Logistic Regression, Bagging Classifier, Decision Tree Classifier and Deep Learning. The dataset (...) was collected from Kaggle depository. It consists of 6362620 rows and 10 columns. The best classifier with unbalanced dataset was the Random Forest Classifier. The Accuracy 99.97%, precession 99.96%, Recall 99.97% and the F1-score 99.96%. However, the best classifier with balanced dataset was the Bagging Classifier. The Accuracy 99.96%, precession 99.95%, Recall 99.98% and the F1-score 99.96%. (shrink)

The Introduction discusses determinables and similarity spaces and ties together the contributions to Color Ontology and Color Science.

An artwork in one culture and form, say European classical music, cannot be evaluated in the context of another, say Hindustani music. While a person educated in the traditions of European music can rationally evaluate and discuss her response to a string quartet by Beethoven, her response to music in a foreign culture is merely subjective. She might "like" the latter, but her response is merely subjective. In this paper, I discuss the role of artforms: why response can be "objectively" (...) discussed within artforms, but is nonetheless subjective across them. My discussion falls into two parts. First, I offer a psychological account of aesthetic response to art: cultural learning stabilizes this response across individuals who are educated in an artform. Second, I offer a cultural-evolutionary account of the diversity of artforms, adapting Darwin's Principle of the Divergence of Character to explain the multiplicity of art forms. (shrink)

Memory seems intuitively to consist in the preservation of some proposition (in the case of semantic memory) or sensory image (in the case of episodic memory). However, this intuition faces fatal difficulties. Semantic memory has to be updated to reflect the passage of time: it is not just preservation. And episodic memory can occur in a format (the observer perspective) in which the remembered image is different from the original sensory image. These difficulties indicate that memory cannot be preserved content. (...) It is proposed that what is preserved in memory isan underlying "trace", and that in every act of remembering, memorial content is reconstructed from the preserved trace. (shrink)

An object has aesthetic value (henceforth: a-value) because a certain sort of cognitive engagement with it is beneficial. This grounding in mental activity expl.

How many senses do humans possess? Five external senses, as most cultures have it—sight, hearing, touch, smell, and taste? Should proprioception, kinaesthesia, thirst, and pain be included, under the rubric bodily sense? What about the perception of time and the sense of number? Such questions reduce to two. 1. How do we distinguish a sense from other sorts of information-receiving faculties? 2. By what principle do we distinguish the senses? Aristotle discussed these questions in the De Anima. H. P. Grice (...) revived them in 1967. More recently, they have taken on fresh interest as a result of a collection of essays edited by Fiona Macpherson. This entry reviews some approaches to these questions and advances some new ideas for the reader’s consideration. It proposes that the senses constitute an integrated learning system, membership in which answers question 1. It also proposes that the modalities can be distinguished from one another in two ways, by the means of information pick-up and by the kinds of activity that a perceiver undertakes to make use of them. (shrink)

Because culture plays a role in determining the aesthetic merit of a work of art, intrinsically similar works can have different aesthetic merit when assessed in different cultures. This paper argues that a form of aesthetic hedonism is best placed to account for this relativity of aesthetic value. This form of hedonism is based on a functional account of aesthetic pleasure, according to which it motivates and enables mental engagement with artworks, and an account of pleasure-learning, in which it reinforces (...) the appreciation of culture specific ways of engaging with art. (shrink)

What colour does a white wall look in the pinkish light of the late afternoon? Philosophers disagree: they hold variously that it looks pink, white, both, and no colour at all. A new approach is offered. After reviewing the dispute, a reinterpretation of perceptual constancy is offered. In accordance with this reinterpretation, it is argued that perceptual features such as color must always be predicated of perceptual objects. Thus, it might be that in pinkish light, the wall looks white and (...) the light looks pink. The paper concludes by discussing some criteria for object identification in perceptual states. (shrink)

Two questions are addressed in this paper. First, what is it to see? I argue that it is veridical experience of things outside the perceiver brought about by looking. Second, what is it to see a material object? I argue that it is experience of an occupant of a spatial region that is a logical subject for other visual features, able to move to another spatial region, to change intrinsically, and to interact with other material objects. I show how this (...) theory is different from the idea that object-seeing is merely the visual segregation of a region of the visual field. Finally, I argue that we do not object-see objects reflected in mirrors, surfaces of back-lit objects, and depictions of objects. (shrink)

Molyneux's Question (MQ) concerns whether a newly sighted man would recognize/distinguish a sphere and a cube by vision, assuming he could previously do this by touch. We argue that (MQ) splits into questions about (a) shared representations of space in different perceptual systems, and about (b) shared ways of constructing higher dimensional spatiotemporal features from information about lower dimensional ones, most of the technical difficulty centring on (b). So understood, MQ resists any monolithic answer: everything depends on the constraints faced (...) by particular perceptual systems in extracting features of higher dimensionality from those of lower. Each individual question of this type is empirical and must be investigated separately. We present several variations on MQ based on different levels of dimensional integration—some of these are familiar, some novel adaptations of problems known elsewhere, and some completely novel. Organizing these cases in this way is useful because it unifies a set of disparate questions about intermodal transfer that have held philosophical and psychological interest, suggests a new range of questions of the same type, sheds light on similarities and differences between members of the family, and allows us to formulate a much-augmented set of principles and questions concerning the intermodal transfer of spatiotemporal organization. (shrink)

Automatic detection of diseases and anatomical landmarks in medical images by the use of computers is important and considered a challenging process that could help medical diagnosis and reduce the cost and time of investigational procedures and refine health care systems all over the world. Recently, gastrointestinal (GI) tract disease diagnosis through endoscopic image classification is an active research area in the biomedical field. Several GI tract disease classification methods based on image processing and machine learning techniques have been proposed (...) by diverse research groups in the recent past. However, yet effective and comprehensive deep ensemble neural network-based classification model with high accuracy classification results is not available in the literature. In this thesis, we review ways and mechanisms to use deep learning techniques to research on multi-disease computer-aided detection about gastrointestinal and identify these images. We re-trained five state-of-the-art neural network architectures, VGG16, ResNet, MobileNet, Inception-v3, and Xception on the Kvasir dataset to classify eight categories that include an anatomical landmark (pylorus, z-line, cecum), a diseased state (esophagitis, ulcerative colitis, polyps), or a medical procedure (dyed lifted polyps, dyed resection margins) in the Gastrointestinal Tract. Our models have showed results with a promising accuracy which is a remarkable performance with respect to the state-of-the-art approaches. The resulting accuracies achieved using VGG, ResNet, MobileNet, Inception-v3, and Xception were 98.3%, 92.3%, 97.6%, 90% and 98.2%, respectively. As it appears, the most accurate result has been achieved when retraining VGG16 and Xception neural networks with accuracy reache to 98% due to its high performance on training on ImageNet dataset and internal structure that support classification problems. (shrink)

In this paper, I examine Aristotle's notion of potentiality as it applies to the beginning of life. Aristotle’s notion of natural kinēsis implies that we should not treat the entity at the beginning of embryonic development as human, or indeed as the same as the one that is born. This leads us to ask: When does the embryo turn into a human? Aristotle’s own answer to this question is very harsh. Bracketing the views that lead to this harsh answer, his (...) theory of kinēsis still gives us reason for searching for a replacement answer. Aristotle’s own work unfortunately gives us no help in finding this answer. (shrink)

The sense of touch provides us knowledge of two kinds of events. Tactile sensation (T) makes us aware of events on or just below the skin; haptic perception (H) gives us knowledge of things outside the body with which we are in contact. This paper argues that T and H are distinct experiences, and not (as some have argued) different aspects of the same touch-experience. In other words, T ≠ H. Moreover, H does not supervene on T. Secondly: In T, (...) we are aware of immanent, phenomenal qualities; in H, we come to know of transcendent qualities in things that exist independently of ourselves. Finally: T is non-spatial; it is indexed by parts of the body, but not by position in space. H, by contrast, is spatial. This brings to mind Kant’s contention that things are presented as existing objectively when they are represented spatially. (shrink)

Abstract: Sarcasm is commonly used in news and detecting sarcasm in headline news is challenging for humans and thus for computers. The media regularly seem to engage sarcasm in their news headline to get the attention of people. However, people find it tough to detect the sarcasm in the headline news, hence receiving a mistaken idea about that specific news and additionally spreading it to their friends, colleagues, etc. Consequently, an intelligent system that is able to distinguish between can sarcasm (...) none sarcasm automatically is very important. The aim of the study is to build a sarcasm model that detect headline news using machine and deep learning and attempt to understand how a computer learns the patterns of sarcasm. The dataset used in this study was collected from Kaggle depository. We examined 21 algorithms of machine learning and one deep learning algorithm for detecting sarcasm in headline news. The evaluation metric used in this study are Accuracy, F1-measure, Recall, Precision, and Time needed for training and evaluation. The deep learning model achieved accuracy (95.27%), recall (96.62%), precision (94.15%), F1-score (95.37%) and time needed to train the mode (400 seconds), with loss of around 0.3398. However, the algorithm of machine learning that achieved the highest F1-Score is Passive Aggressive Classifier. It was the top classier for sarcasm detection among the machine learning algorithms with accuracy (95.50%), recall (96.09 %), precision (94.30%), F1-score (95.19%) and time needed to train the mode (0.31 seconds). (shrink)

Abstract: Sarcasm is commonly used in news and detecting sarcasm in headline news is challenging for humans and thus for computers. The media regularly seem to engage sarcasm in their news headline to get the attention of people. However, people find it tough to detect the sarcasm in the headline news, hence receiving a mistaken idea about that specific news and additionally spreading it to their friends, colleagues, etc. Consequently, an intelligent system that is able to distinguish between can sarcasm (...) none sarcasm automatically is very important. The aim of the study is to build a sarcasm model that detect headline news using machine and deep learning and attempt to understand how a computer learns the patterns of sarcasm. The dataset used in this study was collected from Kaggle depository. We examined 21 algorithms of machine learning and one deep learning algorithm for detecting sarcasm in headline news. The evaluation metric used in this study are Accuracy, F1-measure, Recall, Precision, and Time needed for training and evaluation. The deep learning model achieved accuracy (95.27%), recall (96.62%), precision (94.15%), F1-score (95.37%) and time needed to train the mode (400 seconds), with loss of around 0.3398. However, the algorithm of machine learning that achieved the highest F1-Score is Passive Aggressive Classifier. It was the top classier for sarcasm detection among the machine learning algorithms with accuracy (95.50%), recall (96.09 %), precision (94.30%), F1-score (95.19%) and time needed to train the mode (0.31 seconds). (shrink)

We perceive in many ways. But several dubious presuppositions about the senses mask this diversity of perception. Philosophers, scientists, and engineers alike too often presuppose that the senses (vision, audition, etc.) are independent sources of information, perception being a sum of these independent contributions. We too often presuppose that we can generalize from vision to other senses. We too often presuppose that vision itself is best understood as a passive receptacle for an image thrown by a lens. In this essay (...) we illustrate how reflection on results from the cognitive sciences undermine these (and many other) traditional presuppositions. Our illustration situates the remaining essays in the volume, Perception and its Modalities, which further extend the case against various traditional presuppositions, and offer alternatives ways to understand the senses and their role in perception. While many of the essays in this volume represent competing views and draw on different fields, from conceptual analysis to engineering, most contributors believe that to understand perception properly, we need to treat as foundational the idea that the senses work together. From that agreement, new paradigms for theorizing about perception begin to emerge. (shrink)

Christopher Gauker argues that no concept can be extracted from perceptual experience and that imagistic thought cannot draw boundaries between one kind and another. Here, it is argued, on the contrary, that images have extension and are consequently Fregean concepts. Hume’s theory of abstraction as indifference is offered as an account of extra-sensory concepts. Finally, it is argued that modern theories of sensory data processing run parallel to Kant’s idea of synthesis as a pre-condition for perception.

The capacity to engage with art is a human universal present in all cultures and just about every individual human. This indicates that this capacity is evolved. In this Critical Notice of Denis Dutton's The Art Instinct, I discuss various evolutionary scenarios and their consequences. Dutton and I both reject the "spandrel" approach that originates from the work of Gould and Lewontin. Dutton proposes, following work of Geoffrey Miller, that art is sexually selected--that art-production is a sign of a fit (...) genome in males. I argue that while assortative mating may well have had a role in the evolution of "the art instinct", group selection is a better explanation. I also take issue with Dutton's "cluster concept" approach to defining art, and argue that it is a universal and essential characteristic of art that it is appreciated both for what it expresses and for the way that it expresses. It thus requires a reflexive capacity that is not operative in the appreciation of sport spectacles and pornography. (shrink)

I can be wrong about things I seem to perceive; the conditions might lead me to be mistaken about them. Since I can't rule out the possibility that the conditions are misleading, I can't be sure that I am perceiving this thing in my hand correctly. But suppose that I am able to examine it actively—handling it, looking closer, shining a light on it, and so on. Then, my level of uncertainty goes down; in the limit it is eliminated entirely. (...) Of course, I might be mistaken because I am a brain in a vat, or because some other sceptical scenario obtains. But sceptical scenarios apply not just to this thing in my hand, but to everything all at once. Define "empirical certainty" as the absence of the kind of doubt that spreads to all empirical states of affairs. Sensory exploration, or active examination, can in principle lead to empirical certainty. (shrink)

Molyneux asked whether a newly sighted person could distinguish a sphere from a cube by sight alone, given that she was antecedently able to do so by touch. This, we contend, is a question about general ideas. To answer it, we must ask (a) whether spatial locations identified by touch can be identified also by sight, and (b) whether the integration of spatial locations into an idea of shape persists through changes of modality. Posed this way, Molyneux’s Question goes substantially (...) beyond question (a), about spatial locations, alone; for a positive answer to (a) leaves open whether a perceiver might cross-identify locations, but not be able to identify the shapes that collections of locations comprise. We further emphasize that MQ targets general ideas so as to distinguish it from corresponding questions about experiences of shape and about the property of tangible (vs. visual) shape. After proposing a generalized formulation of MQ, we extend earlier work (“Many Molyneux Questions,” Australasian Journal of Philosophy 2020) by showing that MQ does not admit a single answer across the board. Some integrative data-processes transfer across modalities; others do not. Seeing where and how such transfer succeeds and fails in individual cases has much to offer to our understanding of perception and its modalities. (shrink)

Art is universal across cultures. Yet, it is biologically expensive because of the energy expended and reduced vigilance. Why do humans make and contemplate it? This paper advances a thesis about the psychological origins of perceptual art. First, it delineates the aspects of art that need explaining: not just why it is attractive, but why fine execution and form—which have to do with how the attraction is achieved—matter over and above attractiveness. Second, it states certain constraints: we need to explain (...) pleasure in contemplation, not value extracted from the object by activities other than contemplation. The theory is that aesthetic pleasure is a motivation for learning skills. Two forms of pleasure are postulated. The first accompanies the spontaneous activity necessary for learning a more or less universal basic level of skill. The second accompanies highly skilled activity. This second kind of pleasure is specific to art as such. (shrink)

The author investigates greek ontologies that apparently rely on a conflation of "binary" (x is f) and "monadic" (x is) uses of 'is'. He uses Aristotelian and other texts to support his proposal that these ontologies are explained by the Greeks using two alternative semantic analyses for 'x is F'. The first views it as asserting a relation between x and F, the second as asserting that a "predicative complex" exists, where a predicative complex is a complex consisting of x (...) and F. The article concludes by indicating some uses for the novel concept of predicative complex in aristotelian interpretation. (shrink)

Artificial intelligence (AI), deep learning, machine learning and neural networks represent extremely exciting and powerful machine learning-based techniques used to solve many real-world problems. Artificial intelligence is the branch of computer sciences that emphasizes the development of intelligent machines, thinking and working like humans. For example, recognition, problem-solving, learning, visual perception, decision-making and planning. Deep learning is a subset of machine learning in artificial intelligence that has networks capable of learning unsupervised from data that is unstructured or unlabeled. Deep learning (...) is a technique used to generate face detection and recognize it for real or fake by using profile images and determine the differences between them. In this study, we used deep learning techniques to generate models for Real and Fake face detection. The goal is determining a suitable way to detect real and fake faces. The model was designed and implemented, including both Dataset of images: Real and Fake faces detection through the use of Deep learning algorithms based on neural networks. We have trained dataset which consists of 9,000 images for total in 150 epochs, and got the ResNet50 model to be the best model of network architectures used with 100% training accuracy, 99.18% validation accuracy, training loss 0.0003, validation loss 0.0265, and testing accuracy 99%. (shrink)

Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines or software that work and react like humans. Some of the activities computers with artificial intelligence are designed for include, Speech, recognition, Learning, Planning and Problem solving. Deep learning is a collection of algorithms used in machine learning, It is part of a broad family of methods used for machine learning that are based on learning representations of data. Deep learning is a technique used (...) to produce Pneumonia detection and classification models using x-ray imaging for rapid and easy detection and identification of pneumonia. In this thesis, we review ways and mechanisms to use deep learning techniques to produce a model for Pneumonia detection. The goal is find a good and effective way to detect pneumonia based on X-rays to help the chest doctor in decision-making easily and accuracy and speed. The model will be designed and implemented, including both Dataset of image and Pneumonia detection through the use of Deep learning algorithms based on neural networks. The test and evaluation will be applied to a range of chest x-ray images and the results will be presented in detail and discussed. This thesis uses deep learning to detect pneumonia and its classification. (shrink)

The literature on the metaphysics of gender is partially marked by a tension between conceptions that understand gender categories as importantly at least partly self-determined identities and those that understand them as social or cultural categories imposed upon others as a tool of oppression. I argue that this tension can be mediated by understanding gender categories as essentially contested. I then draw on “radical functionalism” to argue that, while, divorced of context, competing conceptions can simultaneously explicate an essentially contested concept, (...) within context, some conceptions better meet background purposes underlying the use of the concept than others. (shrink)

The senses present their content in the form of images, three-dimensional arrays of located sense features. Peacocke’s “scenario content” is one attempt to capture image content; here, a richer notion is presented, sensory images include located objects and features predicated of them. It is argued that our grasp of the meaning of these images implies that they have propositional content. Two problems concerning image content are explored. The first is that even on an enriched conception, image content has certain expressive (...) limitations. In particular, it cannot express absolute location and time (as opposed to spatiotemporal relations) or logical complexity. Yet, perceptual experience does seem to express certain absolute locations—namely, here and now. How can it do so? Secondly, image content cannot exhaust the significance of perceptual states. This is proved by noting that perception, memory, and anticipation can have the same image content. Yet they have different significance. These problems show that some of the significance of sensory states comes from outside the image. (shrink)

All living things have sensory capacities. Plants, in particular, have sensory receptors, transduce the activations of these receptors, and process these outputs in order to manage actions that demand sensory integration. However, there is a kind of sensory function that plants cannot perform. They cannot sense something as other than themselves. Animals, by contrast, perceive. They experience two kinds of "othering impressions"—impressions of entities as located outside and available for interaction, and hence as distinct from the perceiving subject. First, they (...) represent external entities in a "body scheme" that enables sensorimotor interaction with these entities. Second, higher animals such as mammals and birds and possibly fish, represent these entities as located relative to a "cognitive map." These othering impressions are very important because they are the foundation for the human conceptions of the self and other. (shrink)

Infants and children are suffering from a lots of nausea and vomiting problems. Doctors, usually face various difficulties dealing with these problems because of their similarities. In this paper, we present an expert system to help users in getting the correct diagnosis of problems of nausea and vomiting in infants and children (Gastro-esophageal reflux, Gastroenteritis, Systemic Infection, Bowel obstruction, Tumors, A bleeding disease, tonsillitis, and Hepatitis pharynx). Furthermore, this expert system provide information about the disease and how to deal with (...) it. SL5 Object expert system language was used to design and implement this expert system. (shrink)

Argues that biological organs, including mental capacities, should be identified by homology (not function).

Perception is the ultimate source of our knowledge about contingent facts. It is an extremely important philosophical development that starting in the last quarter of the twentieth century, philosophers have begun to change how they think of perception. The traditional view of perception focussed on sensory receptors; it has become clear, however, that perceptual systems radically transform the output of these receptors, yielding content concerning objects and events in the external world. Adequate understanding of this process requires that we think (...) of perception in new ways—how it operates, the differences among the modalities, and integration of content provided by the individual senses. Philosophers have developed new analytic tools, and opened themselves up to new ways of thinking about the relationship of perception to knowledge. The Oxford Handbook of the Philosophy of Perception is a collection of entries by leading researchers that reviews these new directions in philosophical thought. The Introduction to the Handbook reviews the history of the subject from its beginnings in ancient Greece to the nineteenth century, and the way that science and philosophy have together produced new conceptions during the last hundred years. It shows how the new thinking about perception has led to a complex web of theories. (shrink)

When I act on something, three kinds of idea (or representation) come into play. First, I have a non-visual representation of my goals. Second, I have a visual description of the kind of thing that I must act upon in order to satisfy my goals. Finally, I have an egocentric position locator that enables my body to interact with the object. It is argued here that these ideas are distinct. It is also argued that the egocentric position locator functions in (...) the same way as a demonstrative, and that the involvement of such demonstratives in visual content negates naive realism. (This is a nearly final draft of a paper that is to be published in Raftopoulos and Machamer (eds), Perception, Realism, and the Problem of Reference (forthcoming from Cambridge UP. It is a shorter revised version of "Visual Reference", posted earlier.). (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)

Life expectancy prediction, a pivotal facet of public health and policy formulation, has witnessed remarkable advancements owing to the integration of neural network models and comprehensive datasets. In this research, we present an innovative approach to forecasting life expectancy in diverse countries. Leveraging a neural network architecture, our model was trained on a dataset comprising 22 distinct features, acquired from Kaggle, and encompassing key health indicators, socioeconomic metrics, and cultural attributes. The model demonstrated exceptional predictive accuracy, attaining an impressive 99.27% (...) and an average error of 0.0034, underscoring the potency of deep learning in tackling complex, real-world challenges. Furthermore, our study delved into feature importance analysis, identifying critical determinants such as HIV/AIDS prevalence, income composition of resources, and socioeconomic status that significantly influence life expectancy. These findings provide actionable insights for healthcare policymakers and practitioners, emphasizing the importance of addressing health disparities, promoting economic development, and implementing targeted interventions. This research bridges the gap between data-driven methodologies and global health, offering a robust predictive tool and enriching our understanding of the multifaceted dynamics that shape life expectancy across nations. (shrink)

Hunger is a psychological state that serves physiological energy homeostasis. I argue that it is a pure underived desire to eat and examine its role in homeostasis. After scene-setting explanations of homeostasis and desire, I argue that hunger is a close phenomenological match with underived desire. Then, I show why desire is an apt instrument for energy homeostasis. Finally, I argue that energy homeostasis is a multi-factorial future-regarding behavioural strategy. Hunger is a special purpose sensory state that serves only to (...) implement the strategy. Thus, it is a sensory desire. I conclude by reflecting on the credibility of this desire. (shrink)

What is the relationship between color experience and color? Here, I defend the view that it is semantic: color experience denotes color in a code innately known by the perceiver. This semantic theory contrasts with a variety of theories according to which color is defined as the cause of color experience (in a special set of circumstances). It also contrasts with primary quality theories of color, which treat color as a physical quantity. I argue that the semantic theory better accounts (...) for the kinds of knowledge we have regarding both the color of objects that we see and of the colors themselves. (shrink)

Argues that Aristotle regarded the universe, or Totality, as a single substance with form and matter, and that he regarded this substance together with the Prime Mover as a self-mover.

Background: The castor bean is a large grassy or semi-wooden shrub or small tree. Any part of the castor plant parts can suffering from a disease that weakens the ability to grow and eliminates its production. Therefore, in this paper will identify the pests and diseases present in castor culture and detect the symptoms in each disease. Also images is showing the symptom form in this disease. Objectives: The main objective of this expert system is to obtain appropriate diagnosis of (...) the disease. Methods: In this paper, the expert system is designed for the ability of agricultural engineers to detect and diagnose disease of castor like as: seeding blight, alternaria blight, cercospora leaf spot, powdery mildew and wilt. This system presents the disease symptoms, survival and spread, favorable conditions and image for each disease. Clips and Delphi expert system languages are used for designing and implementing the proposed expert system. Results: The expert system in the diagnosis of castor diseases was assessed by farmers and agricultural engineers and they were satisfied and accepted with its quality of performance. Conclusions: The expert system is easy for farmers and people have experience in the plant of castor to detect and diagnosis the symptoms that may face this plant from several disease. (shrink)