Results for 'Deep learning'

998 found
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  1. Lemon Classification Using Deep Learning.Jawad Yousif AlZamily & Samy Salim Abu Naser - 2020 - International Journal of Academic Pedagogical Research (IJAPR) 3 (12):16-20.
    Abstract : Background: Vegetable agriculture is very important to human continued existence and remains a key driver of many economies worldwide, especially in underdeveloped and developing economies. Objectives: There is an increasing demand for food and cash crops, due to the increasing in world population and the challenges enforced by climate modifications, there is an urgent need to increase plant production while reducing costs. Methods: In this paper, Lemon classification approach is presented with a dataset that contains approximately 2,000 images (...)
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  2.  71
    Using Deep Learning to Detect Facial Markers of Complex Decision Making.Gianluca Guglielmo, Irene Font Peradejordi & Michal Klincewicz - forthcoming - Lecture Notes in Computer Science (Advances in Computer Games 2021).
    In this paper, we report on an experiment with The Walking Dead (TWD), which is a narrative-driven adventure game where players have to survive in a post-apocalyptic world filled with zombies. We used OpenFace software to extract action unit (AU) intensities of facial expressions characteristic of decision-making processes and then we implemented a simple convolution neural network (CNN) to see which AUs are predictive of decision-making. Our results provide evidence that the pre-decision variations in action units 17 (chin raiser), 23 (...)
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  3. Handwritten Signature Verification Using Deep Learning.Eman Alajrami, Belal A. M. Ashqar, Bassem S. Abu-Nasser, Ahmed J. Khalil, Musleh M. Musleh, Alaa M. Barhoom & Samy S. Abu-Naser - 2020 - International Journal of Academic Multidisciplinary Research (IJAMR) 3 (12):39-44.
    Every person has his/her own unique signature that is used mainly for the purposes of personal identification and verification of important documents or legal transactions. There are two kinds of signature verification: static and dynamic. Static(off-line) verification is the process of verifying an electronic or document signature after it has been made, while dynamic(on-line) verification takes place as a person creates his/her signature on a digital tablet or a similar device. Offline signature verification is not efficient and slow for a (...)
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  4. Potato Classification Using Deep Learning.Abeer A. Elsharif, Ibtesam M. Dheir, Alaa Soliman Abu Mettleq & Samy S. Abu-Naser - 2020 - International Journal of Academic Pedagogical Research (IJAPR) 3 (12):1-8.
    Abstract: Potatoes are edible tubers, available worldwide and all year long. They are relatively cheap to grow, rich in nutrients, and they can make a delicious treat. The humble potato has fallen in popularity in recent years, due to the interest in low-carb foods. However, the fiber, vitamins, minerals, and phytochemicals it provides can help ward off disease and benefit human health. They are an important staple food in many countries around the world. There are an estimated 200 varieties of (...)
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  5. Type of Tomato Classification Using Deep Learning.Mahmoud A. Alajrami & Samy S. Abu-Naser - 2020 - International Journal of Academic Pedagogical Research (IJAPR) 3 (12):21-25.
    Abstract: Tomatoes are part of the major crops in food security. Tomatoes are plants grown in temperate and hot regions of South American origin from Peru, and then spread to most countries of the world. Tomatoes contain a lot of vitamin C and mineral salts, and are recommended for people with constipation, diabetes and patients with heart and body diseases. Studies and scientific studies have proven the importance of eating tomato juice in reducing the activity of platelets in diabetics, which (...)
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  6.  42
    Shared Decision‐Making and Maternity Care in the Deep Learning Age: Acknowledging and Overcoming Inherited Defeaters.Keith Begley, Cecily Begley & Valerie Smith - 2021 - Journal of Evaluation in Clinical Practice 27 (3):497–503.
    In recent years there has been an explosion of interest in Artificial Intelligence (AI) both in health care and academic philosophy. This has been due mainly to the rise of effective machine learning and deep learning algorithms, together with increases in data collection and processing power, which have made rapid progress in many areas. However, use of this technology has brought with it philosophical issues and practical problems, in particular, epistemic and ethical. In this paper the authors, (...)
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  7. AISC 17 Talk: The Explanatory Problems of Deep Learning in Artificial Intelligence and Computational Cognitive Science: Two Possible Research Agendas.Antonio Lieto - 2018 - In Proceedings of AISC 2017.
    Endowing artificial systems with explanatory capacities about the reasons guiding their decisions, represents a crucial challenge and research objective in the current fields of Artificial Intelligence (AI) and Computational Cognitive Science [Langley et al., 2017]. Current mainstream AI systems, in fact, despite the enormous progresses reached in specific tasks, mostly fail to provide a transparent account of the reasons determining their behavior (both in cases of a successful or unsuccessful output). This is due to the fact that the classical problem (...)
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  8. A Theory Explains Deep Learning.Kenneth Kijun Lee & Chase Kihwan Lee - manuscript
    This is our journal for developing Deduction Theory and studying Deep Learning and Artificial intelligence. Deduction Theory is a Theory of Deducing World’s Relativity by Information Coupling and Asymmetry. We focus on information processing, see intelligence as an information structure that relatively close object-oriented, probability-oriented, unsupervised learning, relativity information processing and massive automated information processing. We see deep learning and machine learning as an attempt to make all types of information processing relatively close to (...)
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  9. A Promethean Philosophy of External Technologies, Empiricism, & the Concept: Second-Order Cybernetics, Deep Learning, and Predictive Processing.Ekin Erkan - 2020 - Media Theory 4 (1):87-146.
    Beginning with a survey of the shortcoming of theories of organology/media-as-externalization of mind/body—a philosophical-anthropological tradition that stretches from Plato through Ernst Kapp and finds its contemporary proponent in Bernard Stiegler—I propose that the phenomenological treatment of media as an outpouching and extension of mind qua intentionality is not sufficient to counter the ̳black-box‘ mystification of today‘s deep learning‘s algorithms. Focusing on a close study of Simondon‘s On the Existence of Technical Objectsand Individuation, I argue that the process-philosophical work (...)
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  10.  55
    Menschengestützte Künstliche Intelligenz: Über die soziotechnischen Voraussetzungen von "deep learning".Rainer Mühlhoff - 2019 - Zeitschrift Für Medienwissenschaft (ZfM) 21 (2):56–64.
    Die aktuellen Erfolge von Künstlicher Intelligenz beruhen nicht nur auf technologischen Fortschritten, sondern auch auf einem grundlegenden soziotechnischen Strukturwandel. Denn maschinelle Lernverfahren wie Deep Learning benötigen eine große Menge Trainingsdaten, die nur über menschliche Mitarbeit gewonnen werden können. In einer Konvergenz von Methoden der Human-Computer-Interaction und der KI ist in den letzten zehn Jahren eine Fülle von Mensch-Maschine-Interfaces und medialen Infrastrukturen entstanden, durch die menschliche kognitive Ressourcen in hybride Mensch-Maschine-Apparate eingespannt werden. Diese Apparate vollbringen im Ganzen jene Leistung, (...)
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  11. Artificial Intelligence in Life Extension: From Deep Learning to Superintelligence.Alexey Turchin, Denkenberger David, Zhila Alice, Markov Sergey & Batin Mikhail - 2017 - Informatica 41:401.
    In this paper, we focus on the most efficacious AI applications for life extension and anti-aging at three expected stages of AI development: narrow AI, AGI and superintelligence. First, we overview the existing research and commercial work performed by a select number of startups and academic projects. We find that at the current stage of “narrow” AI, the most promising areas for life extension are geroprotector-combination discovery, detection of aging biomarkers, and personalized anti-aging therapy. These advances could help currently living (...)
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  12. Enhanced Artificial Intelligence System for Diagnosing and Predicting Breast Cancer Using Deep Learning.Mona Alfifi, Mohamad Shady Alrahhal, Samir Bataineh & Mohammad Mezher - 2020 - International Journal of Advanced Computer Science and Applications 11 (7):1-17.
    Breast cancer is the leading cause of death among women with cancer. Computer-aided diagnosis is an efficient method for assisting medical experts in early diagnosis, improving the chance of recovery. Employing artificial intelligence (AI) in the medical area is very crucial due to the sensitivity of this field. This means that the low accuracy of the classification methods used for cancer detection is a critical issue. This problem is accentuated when it comes to blurry mammogram images. In this paper, convolutional (...)
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  13. Empiricism Without Magic: Transformational Abstraction in Deep Convolutional Neural Networks.Cameron Buckner - 2018 - Synthese (12):1-34.
    In artificial intelligence, recent research has demonstrated the remarkable potential of Deep Convolutional Neural Networks (DCNNs), which seem to exceed state-of-the-art performance in new domains weekly, especially on the sorts of very difficult perceptual discrimination tasks that skeptics thought would remain beyond the reach of artificial intelligence. However, it has proven difficult to explain why DCNNs perform so well. In philosophy of mind, empiricists have long suggested that complex cognition is based on information derived from sensory experience, often appealing (...)
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  14. Understanding From Machine Learning Models.Emily Sullivan - forthcoming - British Journal for the Philosophy of Science:axz035.
    Simple idealized models seem to provide more understanding than opaque, complex, and hyper-realistic models. However, an increasing number of scientists are going in the opposite direction by utilizing opaque machine learning models to make predictions and draw inferences, suggesting that scientists are opting for models that have less potential for understanding. Are scientists trading understanding for some other epistemic or pragmatic good when they choose a machine learning model? Or are the assumptions behind why minimal models provide understanding (...)
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  15. Structuring Decisions Under Deep Uncertainty.Casey Helgeson - 2020 - Topoi 39 (2):257-269.
    Innovative research on decision making under ‘deep uncertainty’ is underway in applied fields such as engineering and operational research, largely outside the view of normative theorists grounded in decision theory. Applied methods and tools for decision support under deep uncertainty go beyond standard decision theory in the attention that they give to the structuring of decisions. Decision structuring is an important part of a broader philosophy of managing uncertainty in decision making, and normative decision theorists can both learn (...)
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  16. Human-Aided Artificial Intelligence: Or, How to Run Large Computations in Human Brains? Towards a Media Sociology of Machine Learning.Rainer Mühlhoff - 2019 - New Media and Society 1.
    Today, artificial intelligence, especially machine learning, is structurally dependent on human participation. Technologies such as Deep Learning (DL) leverage networked media infrastructures and human-machine interaction designs to harness users to provide training and verification data. The emergence of DL is therefore based on a fundamental socio-technological transformation of the relationship between humans and machines. Rather than simulating human intelligence, DL-based AIs capture human cognitive abilities, so they are hybrid human-machine apparatuses. From a perspective of media philosophy and (...)
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  17. Deliberation Across Deep Divisions. Transformative Moments.Jürg Steiner Maria Clara Jaramillo, Rousiley C. M. Maia, Simona Mameli - 2006 - Belgrade Philosophical Annual 29 (1):157-178.
    In group discussions of any kind there tends to be an up and down in the level of deliberation. To capture this dynamic we coined the concept of Deliberative Transformative Moments (DTM). In deeply divided societies deliberation is particularly important in order to arrive at peace and stability, but deliberation is also very difficult to be attained. Therefore, we wanted to learn about the conditions that in group discussions across the deep divisions of such societies help deliberation. We organized (...)
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  18. ‘Do Not Block the Way of Inquiry’: Cultivating Collective Doubt Through Sustained Deep Reflective Thinking.Gilbert Burgh, Simone Thornton & Liz Fynes-Clinton - 2018 - In Ellen Duthie, Félix García Moriyón & Rafael Robles Loro (eds.), Parecidos de familia. Propuestas actuales en Filosofía para Niños / Family Resemblances: Current trends in philosophy for children. Madrid, Spain: pp. 47-61.
    We provide a Camusian/Peircean notion of inquiry that emphasises an attitude of fallibilism and sustained epistemic dissonance as a conceptual framework for a theory of classroom practice founded on Deep Reflective Thinking (DTR), in which the cultivation of collective doubt, reflective evaluation and how these relate to the phenomenological aspects of inquiry are central to communities of inquiry. In a study by Fynes-Clinton, preliminary evidence demonstrates that if students engage in DRT, they more frequently experience cognitive dissonance and as (...)
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  19. Nietzsche and Eros Between the Devil and God's Deep Blue Sea: The Problem of the Artist as Actor-Jew-Woman.Babette Babich - 2000 - Continental Philosophy Review 33 (2):159-188.
    In a single aphorism in The Gay Science, Nietzsche arrays “The Problem of the Artist” in a reticulated constellation. Addressing every member of the excluded grouping of disenfranchised “others,” Nietzsche turns to the destitution of a god of love keyed to the selfturning absorption of the human heart. His ultimate and irrecusably tragic project to restore the innocence of becoming requires the affirmation of the problem of suffering as the task of learning how to love. Nietzsche sees the eros (...)
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  20. Kizel, A. (2016). “Pedagogy Out of Fear of Philosophy as a Way of Pathologizing Children”. Journal of Unschooling and Alternative Learning, Vol. 10, No. 20, Pp. 28 – 47.Kizel Arie - 2016 - Journal of Unschooling and Alternative Learning 10 (20):28 – 47.
    The article conceptualizes the term Pedagogy of Fear as the master narrative of educational systems around the world. Pedagogy of Fear stunts the active and vital educational growth of the young person, making him/her passive and dependent upon external disciplinary sources. It is motivated by fear that prevents young students—as well as teachers—from dealing with the great existential questions that relate to the essence of human beings. One of the techniques of the Pedagogy of Fear is the internalization of the (...)
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  21. The Exploratory Status of Postconnectionist Models.Miljana Milojevic & Vanja Subotić - 2020 - Theoria: Beograd 2 (63):135-164.
    This paper aims to offer a new view of the role of connectionist models in the study of human cognition through the conceptualization of the history of connectionism – from the simplest perceptrons to convolutional neural nets based on deep learning techniques, as well as through the interpretation of criticism coming from symbolic cognitive science. Namely, the connectionist approach in cognitive science was the target of sharp criticism from the symbolists, which on several occasions caused its marginalization and (...)
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  22. Performance Vs. Competence in Human–Machine Comparisons.Chaz Firestone - 2020 - Proceedings of the National Academy of Sciences 41.
    Does the human mind resemble the machines that can behave like it? Biologically inspired machine-learning systems approach “human-level” accuracy in an astounding variety of domains, and even predict human brain activity—raising the exciting possibility that such systems represent the world like we do. However, even seemingly intelligent machines fail in strange and “unhumanlike” ways, threatening their status as models of our minds. How can we know when human–machine behavioral differences reflect deep disparities in their underlying capacities, vs. when (...)
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  23. Psychopower and Ordinary Madness: Reticulated Dividuals in Cognitive Capitalism.Ekin Erkan - 2019 - Cosmos and History 15 (1):214-241.
    Despite the seemingly neutral vantage of using nature for widely-distributed computational purposes, neither post-biological nor post-humanist teleology simply concludes with the real "end of nature" as entailed in the loss of the specific ontological status embedded in the identifier "natural." As evinced by the ecological crises of the Anthropocene—of which the 2019 Brazil Amazon rainforest fires are only the most recent—our epoch has transfixed the “natural order" and imposed entropic artificial integration, producing living species that become “anoetic,” made to serve (...)
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  24. Automatic Face Mask Detection Using Python.M. Madan Mohan - 2021 - Journal of Science Technology and Research (JSTAR) 2 (1):91-100.
    The corona virus COVID-19 pandemic is causing a global health crisis so the effective protection methods is wearing a face mask in public areas according to the World Health Organization (WHO). The COVID-19 pandemic forced governments across the world to impose lockdowns to prevent virus transmissions. Reports indicate that wearing facemasks while at work clearly reduces the risk of transmission. An efficient and economic approach of using AI to create a safe environment in a manufacturing setup. A hybrid model using (...)
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  25.  77
    GPT-3: Its Nature, Scope, Limits, and Consequences.Luciano Floridi & Massimo Chiriatti - 2020 - Minds and Machines 30 (4):681–⁠694.
    In this commentary, we discuss the nature of reversible and irreversible questions, that is, questions that may enable one to identify the nature of the source of their answers. We then introduce GPT-3, a third-generation, autoregressive language model that uses deep learning to produce human-like texts, and use the previous distinction to analyse it. We expand the analysis to present three tests based on mathematical, semantic, and ethical questions and show that GPT-3 is not designed to pass any (...)
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  26. Limits of Trust in Medical AI.Joshua James Hatherley - 2020 - Journal of Medical Ethics 46 (7):478-481.
    Artificial intelligence is expected to revolutionise the practice of medicine. Recent advancements in the field of deep learning have demonstrated success in variety of clinical tasks: detecting diabetic retinopathy from images, predicting hospital readmissions, aiding in the discovery of new drugs, etc. AI’s progress in medicine, however, has led to concerns regarding the potential effects of this technology on relationships of trust in clinical practice. In this paper, I will argue that there is merit to these concerns, since (...)
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  27. Why Attention is Not Explanation: Surgical Intervention and Causal Reasoning About Neural Models.Christopher Grimsley, Elijah Mayfield & Julia Bursten - 2020 - Proceedings of the 12th Conference on Language Resources and Evaluation.
    As the demand for explainable deep learning grows in the evaluation of language technologies, the value of a principled grounding for those explanations grows as well. Here we study the state-of-the-art in explanation for neural models for natural-language processing (NLP) tasks from the viewpoint of philosophy of science. We focus on recent evaluation work that finds brittleness in explanations obtained through attention mechanisms.We harness philosophical accounts of explanation to suggest broader conclusions from these studies. From this analysis, we (...)
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  28.  55
    Aiming AI at a Moving Target: Health.Mihai Nadin - 2020 - AI and Society 35 (4):841-849.
    Justified by spectacular achievements facilitated through applied deep learning methodology, the “Everything is possible” view dominates this new hour in the “boom and bust” curve of AI performance. The optimistic view collides head on with the “It is not possible”—ascertainments often originating in a skewed understanding of both AI and medicine. The meaning of the conflicting views can be assessed only by addressing the nature of medicine. Specifically: Which part of medicine, if any, can and should be entrusted (...)
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  29. Societies of Disindividuated Hyper-Control: On the Question of a New Pharmakon. [REVIEW]Ekin Erkan - 2019 - Rhizomes: Cultural Studies in Emerging Knowledge 35.
    Drawing on Adorno and Horkheimer's oft-quoted 1944 essay, “The Culture Industry: Enlightenment as Mass Deception,” Bernard Stiegler’s The Age of Disruption affirms that the Frankfurt School duo scrupulously envisaged a “new kind of barbarism,” or an inversion of modernity’s Enlightenment project illustrated by our contemporary political semblance. Surveying the critical social fissures that index contemporary Western civil society—from 9/11 to the 2002 Nanterre massacre and the 2015 Charlie Hebdo shooting—Stiegler diagnoses that our epoch is plagued by the “absence of epoch,” (...)
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  30. Apperceptive Patterning: Artefaction, Extensional Beliefs and Cognitive Scaffolding.Ekin Erkan - 2020 - Cosmos and History 16 (1):125-178.
    In “Psychopower and Ordinary Madness” my ambition, as it relates to Bernard Stiegler’s recent literature, was twofold: 1) critiquing Stiegler’s work on exosomatization and artefactual posthumanism—or, more specifically, nonhumanism—to problematize approaches to media archaeology that rely upon technical exteriorization; 2) challenging how Stiegler engages with Giuseppe Longo and Francis Bailly’s conception of negative entropy. These efforts were directed by a prevalent techno-cultural qualifier: the rise of Synthetic Intelligence (including neural nets, deep learning, predictive processing and Bayesian models of (...)
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  31.  33
    OPUS-CAT: A State-of-the-Art Neural Machine Translation Engine on Your Local Computer. [REVIEW]Yuri Balashov - 2021 - The ATA Chronicle.
    Neural machine translation (NMT) is one of the success stories of deep learning and artificial intelligence. Revolutionary innovations in the computational architectures made in 2015–2017 have led to dramatic improvements in the quality of machine translation (MT) and changed the field forever. Some professional translators welcome these changes with enthusiasm, others less so. But everyone has to deal with them. Historically, the relationship between human translation and MT has been uneasy and complicated, but an increasing number of players (...)
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  32.  18
    Connectionist models of mind: scales and the limits of machine imitation.Pavel Baryshnikov - 2020 - Philosophical Problems of IT and Cyberspace 2 (19):42-58.
    This paper is devoted to some generalizations of explanatory potential of connectionist approaches to theoretical problems of the philosophy of mind. Are considered both strong, and weaknesses of neural network models. Connectionism has close methodological ties with modern neurosciences and neurophilosophy. And this fact strengthens its positions, in terms of empirical naturalistic approaches. However, at the same time this direction inherits weaknesses of computational approach, and in this case all system of anticomputational critical arguments becomes applicable to the connectionst models (...)
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  33. Machine Intelligence: A Chimera.Mihai Nadin - 2019 - AI and Society 34 (2):215-242.
    The notion of computation has changed the world more than any previous expressions of knowledge. However, as know-how in its particular algorithmic embodiment, computation is closed to meaning. Therefore, computer-based data processing can only mimic life’s creative aspects, without being creative itself. AI’s current record of accomplishments shows that it automates tasks associated with intelligence, without being intelligent itself. Mistaking the abstract for the concrete has led to the religion of “everything is an output of computation”—even the humankind that conceived (...)
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  34.  23
    Mind Matters: Earth to Manning A Reply.Eugene Halton - 2008 - Symbolic Interaction 31 (2):149-154.
    This piece continues ideas developed in my essay, Mind Matters, through responding to the critique of that essay by Peter K. Manning. Manning cannot conceive that human conduct involves full-bodied semiosis rather than disembodied conceptualism, and that the study of human signification requires a full-bodied understanding. The ancient Greek root phren, basis for the concept of phronesis, is rooted in the heart-lungs-solar plexus basis of bodily awareness, and provides a metaphor for a discussion of bio-developmental, biosemiotic capacities as crucial for (...)
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  35.  77
    Diseño pedagógico de la educación digital para la formación del profesorado.Jorge Balladares - 2018 - Relatec 17 (1):41-60.
    This article analyzes the incidence of digital education in teacher training in themodalities of b-learning and e-learning. The research proposed three case studies. The frststudy evaluates the efects of a TIa training course in b-learning mode in the digitalcompetence of teachers in an Ecuadorian university. The second study identifed the keycomponents of the instructional design of a postgraduate program in the e-learningmodality of a Spanish university. The third study established a proposal for instructional re-design of a digital (...)
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  36.  88
    Classification of Alzheimer’s Disease Using Traditional Classifiers with Pre-Trained CNN.Husam R. Almadhoun & Samy S. Abu-Naser - 2021 - International Journal of Academic Health and Medical Research (IJAHMR) 5 (4):17-21.
    Abstract: Alzheimer's disease (AD) is one of the most common types of dementia. Symptoms appear gradually and end with severe brain damage. People with Alzheimer's disease lose the abilities of knowledge, memory, language and learning. Recently, the classification and diagnosis of diseases using deep learning has emerged as an active topic covering a wide range of applications. This paper proposes examining abnormalities in brain structures and detecting cases of Alzheimer's disease especially in the early stages, using features (...)
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  37. Should DBS for Psychiatric Disorders Be Considered a Form of Psychosurgery? Ethical and Legal Considerations.Devan Stahl, Laura Cabrera & Tyler Gibb - 2018 - Science and Engineering Ethics 24 (4):1119-1142.
    Deep brain stimulation, a surgical procedure involving the implantation of electrodes in the brain, has rekindled the medical community’s interest in psychosurgery. Whereas many researchers argue DBS is substantially different from psychosurgery, we argue psychiatric DBS—though a much more precise and refined treatment than its predecessors—is nevertheless a form of psychosurgery, which raises both old and new ethical and legal concerns that have not been given proper attention. Learning from the ethical and regulatory failures of older forms of (...)
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  38.  41
    IoT Based Intruder Prevention Using Fogger.T. Krishna Prasath - 2021 - Journal of Science Technology and Research (JSTAR) 2 (1):81-90.
    Anamoly detection in videos plays an important role in various real-life applications. Most of traditional approaches depend on utilizing handcrafted features which are problem-dependent and optimal for specific tasks. Nowadays, there has been a rise in the amount of disruptive and offensive activities that have been happening. Due to this, security has been given principal significance. Public places like shopping centers, avenues, banks, etc. are increasingly being equipped with CCTVs to guarantee the security of individuals. Subsequently, this inconvenience is making (...)
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  39. The Social Trackways Theory of the Evolution of Human Cognition.Kim Shaw-Williams - 2014 - Biological Theory 9 (1):1-11.
    Only our lineage has ever used trackways reading to find unseen and unheard targets. All other terrestrial animals, including our great ape cousins, use scent trails and airborne odors. Because trackways as natural signs have very different properties, they possess an information-rich narrative structure. There is good evidence we began to exploit conspecific trackways in our deep past, at first purely associatively, for safety and orienteering when foraging in vast featureless wetlands. Since our own old trackways were recognizable they (...)
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  40. Making AI Meaningful Again.Jobst Landgrebe & Barry Smith - 2021 - Synthese 198 (March):2061-2081.
    Artificial intelligence (AI) research enjoyed an initial period of enthusiasm in the 1970s and 80s. But this enthusiasm was tempered by a long interlude of frustration when genuinely useful AI applications failed to be forthcoming. Today, we are experiencing once again a period of enthusiasm, fired above all by the successes of the technology of deep neural networks or deep machine learning. In this paper we draw attention to what we take to be serious problems underlying current (...)
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  41. Why Be Random?Thomas Icard - 2021 - Mind 130 (517):fzz065.
    When does it make sense to act randomly? A persuasive argument from Bayesian decision theory legitimizes randomization essentially only in tie-breaking situations. Rational behaviour in humans, non-human animals, and artificial agents, however, often seems indeterminate, even random. Moreover, rationales for randomized acts have been offered in a number of disciplines, including game theory, experimental design, and machine learning. A common way of accommodating some of these observations is by appeal to a decision-maker’s bounded computational resources. Making this suggestion both (...)
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  42. Faith as Extended Knowledge.Kegan J. Shaw - 2017 - Religious Studies:1-19.
    You don’t know that p unless it’s on account of your cognitive abilities that you believe truly that p. Virtue epistemologists think there’s some such ability constraint on knowledge. This looks to be in considerable tension, though, with putative faith- based knowledge. For it can easily seem that when you believe something truly on the basis of faith this isn't because of anything you're competent to do. Rather faith-based beliefs are a product of divine agency. Appearances notwithstanding, I argue in (...)
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  43.  59
    Review of Jesse S. Summers and Walter Sinnott-Armstrong, Clean Hands? Philosophical Lessons From Scrupulosity[REVIEW]Noell Birondo - 2020 - Notre Dame Philosophical Reviews 3.
    Philosophical lessons come in many different shapes and sizes. Some lessons are big, some are small. Some lessons go deep and have a big impact, some are shallow and have almost none. Some lessons are not really philosophical at all or would not really be lessons for an audience of academic philosophers. I mention these truisms not to disparage this informative book on 'moral OCD' (moral obsessive-compulsive disorder, or 'Scrupulosity') but rather to emphasize how difficult it can be to (...)
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  44. Affording Sustainability: Adopting a Theory of Affordances as a Guiding Heuristic for Environmental Policy.O. Kaaronen Roope - 2017 - Frontiers in Psychology 8.
    Human behavior is an underlying cause for many of the ecological crises faced in the 21st century, and there is no escaping from the fact that widespread behavior change is necessary for socio-ecological systems to take a sustainable turn. Whilst making people and communities behave sustainably is a fundamental objective for environmental policy, behavior change interventions and policies are often implemented from a very limited non-systemic perspective. Environmental policy-makers and psychologists alike often reduce cognition ‘to the brain,’ focusing only to (...)
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  45. Toolmaking and the Evolution of Normative Cognition.Jonathan Birch - 2021 - Biology and Philosophy 36 (1):1-26.
    We are all guided by thousands of norms, but how did our capacity for normative cognition evolve? I propose there is a deep but neglected link between normative cognition and practical skill. In modern humans, complex motor skills and craft skills, such as toolmaking, are guided by internally represented norms of correct performance. Moreover, it is plausible that core components of human normative cognition evolved as a solution to the distinctive problems of transmitting complex motor skills and craft skills, (...)
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  46. Dialogic Teaching: Discussing Theoretical Contexts and Reviewing Evidence From Classroom Practice.Sue Lyle - 2008 - Language and Education 22 (3):222-240.
    Drawing on recent developments in dialogic approaches to learning and teaching, I examine the roots of dialogic meaning-making as a concept in classroom practices. Developments in the field of dialogic pedagogy are reviewed and the case for dialogic engagement as an approach to classroom interaction is considered. The implications of dialogic classroom approaches are discussed in the context of educational research and classroom practice. Dialogic practice is contrasted with monologic practices as evidenced by the resilient of the IRF as (...)
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  47. The Post-Human Media Semblance: Predictive Catastrophism.Ekin Erkan - 2020 - Rhizomes: Cultural Studies in Emerging Knowledge 36.
    Since the advent of media archeology, a deep-seated bifurcation has found one end of the field arguing for the interventionist and appropriative weaponization of media whereas the other side has championed a “total war” with technology itself, insisting that new media’s military-industrial roots inherently color its drivability. Here, I implore a moment within the cultural history of net.art and post-internet art to examine how contemporaneous queries about control after militarism and decentralization, as prognosticated by Paul Virilio and Gilles Deleuze, (...)
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  48.  71
    How I Found My Way to the Written Word Through Visual Art.Laura Donkers - 2014 - Philosophy Study 4 (7):511-519.
    The author’s practice-led research explores “the act of living.” In order to advance this idea, the author has acquired skills in investigation and expressed her thinking through a descriptive and explanatory visual language. The author’s learning journey, while not unique, has not been an ordinary one. Initial academic failure to achieve in the school education system contributes to choosing a life working on the land and harbouring the belief that she is unable to learn academically. Still, the author has (...)
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  49.  42
    American Identity, Slides From Five Lectures.David Kolb - manuscript
    What does it mean to be a modern American today? These slides summarize the discussion from five lectures delivered in winter 2019 at the University of Oregon's Osher Lifelong Learning Institute. The lectures themselves are available on YouTube -/- Just how different is American from other cultural identities? We have thought of ourselves as the specially modern nation, spreading the revolutionary gospel of freedom from traditional restrictions. Some condemn this American exceptionalism, while others celebrate it. Don't take sides too (...)
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    Quantum Physics: An Overview of a Weird World: A Primer on the Conceptual Foundations of Quantum Physics.Marco Masi - 2019 - Indy Edition.
    This is the first book in a two-volume series. The present volume introduces the basics of the conceptual foundations of quantum physics. It appeared first as a series of video lectures on the online learning platform Udemy.]There is probably no science that is as confusing as quantum theory. There's so much misleading information on the subject that for most people it is very difficult to separate science facts from pseudoscience. The goal of this book is to make you able (...)
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