Results for 'neural technology'

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  1.  10
    Neural Technologies: The Ethics of Intimate Access to the Mind.Ronald M. Green - 2015 - Hastings Center Report 45 (6):36-37.
    Science fiction is fast becoming reality as scientists and engineers seek to develop new ways of directly accessing and controlling our brains through brain-computer and even brain-to-brain interfaces. If such research is to receive continuing public approval and support—and not invite opposition—it must anticipate the special ethical challenges it creates. By pointing to some of the acute concerns raised by neural engineering technologies—around issues of identity, normality, authority, responsibility, privacy, and justice—Eran Klein and colleagues model and stimulate the kind (...)
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  2.  33
    Do Publics Share Experts’ Concerns About Brain–Computer Interfaces? A Trinational Survey on the Ethics of Neural Technology.Matthew Sample, Sebastian Sattler, David Rodriguez-Arias, Stefanie Blain-Moraes & Eric Racine - 2019 - Science, Technology, and Human Values 2019 (6):1242-1270.
    Since the 1960s, scientists, engineers, and healthcare professionals have developed brain–computer interface (BCI) technologies, connecting the user’s brain activity to communication or motor devices. This new technology has also captured the imagination of publics, industry, and ethicists. Academic ethics has highlighted the ethical challenges of BCIs, although these conclusions often rely on speculative or conceptual methods rather than empirical evidence or public engagement. From a social science or empirical ethics perspective, this tendency could be considered problematic and even technocratic (...)
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  3.  36
    Brain-Computer Interfaces and Personhood: Interdisciplinary Deliberations on Neural Technology.Matthew Sample, Marjorie Aunos, Stefanie Blain-Moraes, Christoph Bublitz, Jennifer Chandler, Tiago H. Falk, Orsolya Friedrich, Deanna Groetzinger, Ralf J. Jox & Johannes Koegel - 2019 - Journal of Neural Engineering 16 (6).
    Scientists, engineers, and healthcare professionals are currently developing a variety of new devices under the category of brain-computer interfaces (BCIs). Current and future applications are both medical/assistive (e.g., for communication) and non-medical (e.g., for gaming). This array of possibilities comes with ethical challenges for all stakeholders. As a result, BCIs have been an object of both hope and concern in various media. We argue that these conflicting sentiments can be productively understood in terms of personhood, specifically the impact of BCIs (...)
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  4.  24
    Pragmatism for a Digital Society: The (In)Significance of Artificial Intelligence and Neural Technology.Matthew Sample & Eric Racine - 2021 - In Orsolya Friedrich, Andreas Wolkenstein, Christoph Bublitz, Ralf J. Jox & Eric Racine (eds.), Clinical Neurotechnology meets Artificial Intelligence. Springer. pp. 81-100.
    Headlines in 2019 are inundated with claims about the “digital society,” making sweeping assertions of societal benefits and dangers caused by a range of technologies. This situation would seem an ideal motivation for ethics research, and indeed much research on this topic is published, with more every day. However, ethics researchers may feel a sense of déjà vu, as they recall decades of other heavily promoted technological platforms, from genomics and nanotechnology to machine learning. How should ethics researchers respond to (...)
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  5.  1
    A Radial Basis Function Neural Network Approach to Predict Preschool Teachers’ Technology Acceptance Behavior.Dana Rad, Gilbert C. Magulod, Evelina Balas, Alina Roman, Anca Egerau, Roxana Maier, Sonia Ignat, Tiberiu Dughi, Valentina Balas, Edgar Demeter, Gavril Rad & Roxana Chis - 2022 - Frontiers in Psychology 13.
    With the continual development of artificial intelligence and smart computing in recent years, quantitative approaches have become increasingly popular as an efficient modeling tool as they do not necessitate complicated mathematical models. Many nations have taken steps, such as transitioning to online schooling, to decrease the harm caused by coronaviruses. Inspired by the demand for technology in early education, the present research uses a radial basis function neural network modeling technique to predict preschool instructors’ technology usage in (...)
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  6.  64
    Electron Imaging Technology for Whole Brain Neural Circuit Mapping.Kenneth J. Hayworth - 2012 - International Journal of Machine Consciousness 4 (01):87-108.
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  7. Artificial Neural Network for Forecasting Car Mileage Per Gallon in the City.Mohsen Afana, Jomana Ahmed, Bayan Harb, Bassem S. Abu-Nasser & Samy S. Abu-Naser - 2018 - International Journal of Advanced Science and Technology 124:51-59.
    In this paper an Artificial Neural Network (ANN) model was used to help cars dealers recognize the many characteristics of cars, including manufacturers, their location and classification of cars according to several categories including: Make, Model, Type, Origin, DriveTrain, MSRP, Invoice, EngineSize, Cylinders, Horsepower, MPG_Highway, Weight, Wheelbase, Length. ANN was used in prediction of the number of miles per gallon when the car is driven in the city(MPG_City). The results showed that ANN model was able to predict MPG_City with (...)
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  8. Diabetes Prediction Using Artificial Neural Network.Nesreen Samer El_Jerjawi & Samy S. Abu-Naser - 2018 - International Journal of Advanced Science and Technology 121:54-64.
    Diabetes is one of the most common diseases worldwide where a cure is not found for it yet. Annually it cost a lot of money to care for people with diabetes. Thus the most important issue is the prediction to be very accurate and to use a reliable method for that. One of these methods is using artificial intelligence systems and in particular is the use of Artificial Neural Networks (ANN). So in this paper, we used artificial neural (...)
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  9.  13
    Convolutional Neural Networks as Aid in Core Lithofacies Classification.Rafael Pires de Lima, Fnu Suriamin, Kurt J. Marfurt & Matthew J. Pranter - 2019 - Interpretation 7 (3):SF27-SF40.
    Artificial intelligence methods have a very wide range of applications. From speech recognition to self-driving cars, the development of modern deep-learning architectures is helping researchers to achieve new levels of accuracy in different fields. Although deep convolutional neural networks have reached or surpassed human-level performance in image recognition tasks, little has been done to transport this new image classification technology to geoscientific problems. We have developed what we believe to be the first use of CNNs to identify lithofacies (...)
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  10.  1
    The Handbook of Brain Theory and Neural Networks.Michael A. Arbib (ed.) - 1998 - MIT Press.
    Choice Outstanding Academic Title, 1996. In hundreds of articles by experts from around the world, and in overviews and "road maps" prepared by the editor, The Handbook of Brain Theory and Neural Networks charts the immense progress made in recent years in many specific areas related to great questions: How does the brain work? How can we build intelligent machines? While many books discuss limited aspects of one subfield or another of brain theory and neural networks, the Handbook (...)
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  11.  9
    Editorial: Bridging the Gap Before and After Birth: Methods and Technologies to Explore the Functional Neural Development in Humans.Marika Berchicci & Silvia Comani - 2015 - Frontiers in Human Neuroscience 9.
  12.  5
    Scientific Images and Their Social Uses: An Introduction to the Concept of ScientismIain Cameron David EdgeLimits of a Modern World: A Study of the "Limits to Growth" DebateRobert McCutcheonThe Atomic BombMargaret Gowing Lorna ArnoldAre Science and Technology Neural?Joan Lipscombe Bill WilliamsAssessment of Technological Decisions--Case StudiesErnest Braun David Collingridge Kate Hinton. Swenson - 1981 - Isis 72 (2):296-297.
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  13.  4
    Prototyping Criptical Neural Engineering — Tentatively Cripping Neural Engineering’s Cultural Practices for Cyborg Survival and Flourishing.Romy Rasper - 2022 - NanoEthics 16 (1):35-49.
    This Discussion Note calls for attention to the cultural practices of Neural Engineering as part of the life sciences as practices and technologies of manufacturing life. Through focusing on Disability, Ableism, and especially Technoableism within the field, I point out instances of onto-epistemological violence, which influence the likelihood of survival of disabled people individually and as a group. By drawing on Crip Technoscience, a method assemblage is introduced that allows to address these issues in an intersectional-kyriarchal understanding of interlocking (...)
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  14.  14
    Comparison of Artificial Neural Networks and Logistic Regression Analysis in Pregnancy Prediction Using the In Vitro Fertilization Treatment.Robert Milewski, Anna Justyna Milewska, Teresa Więsak & Allen Morgan - 2013 - Studies in Logic, Grammar and Rhetoric 35 (1):39-48.
    Infertility is recognized as a major problem of modern society. Assisted Reproductive Technology is the one of many available treatment options to cure infertility. However, the efficiency of the ART treatment is still inadequate. Therefore, the procedure’s quality is constantly improving and there is a need to determine statistical predictors as well as contributing factors to the successful treatment. There is a concern over the application of adequate statistical analysis to clinical data: should classic statistical methods be used or (...)
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  15. Adaptive Neural Tracking Control for a Two-Joint Robotic Manipulator with Unknown Time-Varying Delays.Jiayao Wang & Yang Cui - 2022 - Complexity 2022:1-12.
    This paper presents an adaptive neural tracking control approach for a two-joint robotic manipulator with unknown time-varying delays. In order to work out the effect of unknown time-varying delays on the two-joint robotic manipulator, the appropriate Lyapunov–Krasovskii functionals and separation technology are chosen to settle this matter. The neural networks work as an approximator that has the advantage of estimating the unknown function in the system. In this paper, Lyapunov stability analysis can prove that all signals of (...)
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  16.  14
    Neural Correlates of Deception.Giorgio Ganis & J. P. Rosenfeld - 2011 - In Judy Illes & Barbara J. Sahakian (eds.), Oxford Handbook of Neuroethics. Oxford University Press.
    This article describes key paradigms employed to assess deception and reviews the main neuroscience-based technologies that have been employed to investigate the neural correlates of deception: electroencephalography, functional magnetic resonance imaging, and transcranial direct current stimulation. Any potential use of neuroscience-based methods to detect deception in real-life situations requires successful classification in single subjects. It describes findings on the single subject performance of these methods and addresses the effects of two factors that are problematic for all deception detection methods, (...)
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  17. Fuzzy Neural Network-Based Evaluation Algorithm for Ice and Snow Tourism Competitiveness.Ying Zhao, Qinghua Zhu & Jiujun Bai - 2021 - Complexity 2021:1-11.
    This paper researches and analyzes the evaluation of the competitiveness of ice and snow tourism, uses the improved fuzzy neural network algorithm to process the system flow diagram of ice and snow tourism development through the function and characteristics of the power system of ice and snow tourism, and finally selects more than 40 indicators of the three subsystems of resources, economy, and culture. Based on the construction of cloud fuzzy neural network model, the above method is used (...)
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  18. Interpersonal Neural Synchronization Predicting Learning Outcomes From Teaching-Learning Interaction: A Meta-Analysis.Liaoyuan Zhang, Xiaoxiong Xu, Zhongshan Li, Luyao Chen & Liping Feng - 2022 - Frontiers in Psychology 13.
    In school education, teaching-learning interaction is deemed as a core process in the classroom. The fundamental neural basis underlying teaching-learning interaction is proposed to be essential for tuning learning outcomes. However, the neural basis of this process as well as the relationship between the neural dynamics and the learning outcomes are largely unclear. With non-invasive technologies such as fNIRS, hyperscanning techniques have been developed since the last decade and been applied to the field of educational neuroscience for (...)
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  19.  39
    Engineering the Brain: Ethical Issues and the Introduction of Neural Devices.Eran Klein, Tim Brown, Matthew Sample, Anjali R. Truitt & Sara Goering - 2015 - Hastings Center Report 45 (6):26-35.
    Neural engineering technologies such as implanted deep brain stimulators and brain-computer interfaces represent exciting and potentially transformative tools for improving human health and well-being. Yet their current use and future prospects raise a variety of ethical and philosophical concerns. Devices that alter brain function invite us to think deeply about a range of ethical concerns—identity, normality, authority, responsibility, privacy, and justice. If a device is stimulating my brain while I decide upon an action, am I still the author of (...)
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  20. Psychological Emotions-Based Online Learning Grade Prediction Via BP Neural Network.Jiongen Xiao, Hongqing Teng, Han Wang & Jianxing Tan - 2022 - Frontiers in Psychology 13.
    With the rapid development of Internet technology and the reform of the education model, online education has been widely recognized and applied. In the process of online learning, various types of browsing behavior characteristic data such as learning engagement and attitude will be generated. These learning behaviors are closely related to academic performance. In-depth exploration of the laws contained in the data can provide teaching assistance for education administrators. In this paper, the random forest algorithm is used to determine (...)
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  21.  2
    Limits of Neural Computation in Humans and Machines.Roman Taraban - 2020 - Science and Engineering Ethics 26 (5):2547-2553.
    Aicardi et al. look to neuroscience to mitigate the limitations of current robotics technology. They propose that robotics technology guided by neuroscience has the capacity to create intelligent robots that function with awareness and capacity for abstraction and reasoning. As neurorobotics extends the capability of robotics technology, it introduces new social and ethical concerns, in particular co-opting civilian applications for military use, conflicts between industry and the academy, and data security. However, here we argue that empirical evidence (...)
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  22.  29
    The Neural Correlates of Work and Play: What Brain Imaging Research and Animal Cartoons Can Tell Us About Social Displays, Self-Consciousness, and the Evolution of the Human Brain.Charles Whitehead - 2008 - Journal of Consciousness Studies 15 (10-11):93-121.
    Children seem to have a profound implicit knowledge of human behaviour, because they laugh at Bugs Bunny cartoons where much of the humour depends on animals behaving like humans and our intuitive recognition that this is absurd. Scientists, on the other hand, have problems defining what this 'human difference' is. I suggest these problems are of cultural origin. For example, the industrial revolution and the protestant work ethic have created a world in which work is valued over play, object intelligence (...)
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  23.  22
    The Multiplicity of Memory Enhancement: Practical and Ethical Implications of the Diverse Neural Substrates Underlying Human Memory Systems.Kieran C. R. Fox, Nicholas S. Fitz & Peter B. Reiner - 2017 - Neuroethics 10 (3):375-388.
    The neural basis of human memory is incredibly complex. We argue that the diversity of neural systems underlying various forms of memory suggests that any discussion of enhancing ‘memory’ per se is too broad, thus obfuscating the biopolitical debate about human enhancement. Memory can be differentiated into at least four major systems with largely dissociable neural substrates. We outline each system, and discuss both the practical and the ethical implications of these diverse neural substrates. In practice, (...)
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  24.  11
    Handbook of Brain Theory and Neural Networks.Michael A. Arbib (ed.) - 1995 - MIT Press.
    Choice Outstanding Academic Title, 1996. In hundreds of articles by experts from around the world, and in overviews and "road maps" prepared by the editor, The Handbook of Brain Theory and Neural Networkscharts the immense progress made in recent years in many specific areas related to two great questions: How does the brain work? and How can we build intelligent machines? While many books have appeared on limited aspects of one subfield or another of brain theory and neural (...)
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  25. The Neural and Psychological Processes of Peer-Influenced Online Donation Decision: An Event-Related Potential Study.Yuchen Ye, Pengtao Jiang & Wuke Zhang - 2022 - Frontiers in Psychology 13.
    With the rapid development of information and communication technology, social media-based donation platforms emerged.1 These platforms innovatively demonstrate peer information on the donation page, which inevitably brings the peer influence into donors’ donation decision process. However, how the peer influence will affect the psychological process of donation decisions are remained unknown. This study used the number of donated peers to examine the effects of peer influence on donors’ donation decisions and extracted event-related potential from electroencephalographic data to explore the (...)
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  26.  13
    Training: Neural Systems and Intelligence Applications.Kay Stanney, Kelly Hale, Sven Fuchs, Angela Baskin & Chris Berka - 2011 - Synesis: A Journal of Science, Technology, Ethics, and Policy 2 (1):T38 - T44.
  27.  8
    Medical Image Segmentation Algorithm Based on Optimized Convolutional Neural Network-Adaptive Dropout Depth Calculation.Feng-Ping An & Jun-E. Liu - 2020 - Complexity 2020:1-13.
    Medical image segmentation is a key technology for image guidance. Therefore, the advantages and disadvantages of image segmentation play an important role in image-guided surgery. Traditional machine learning methods have achieved certain beneficial effects in medical image segmentation, but they have problems such as low classification accuracy and poor robustness. Deep learning theory has good generalizability and feature extraction ability, which provides a new idea for solving medical image segmentation problems. However, deep learning has problems in terms of its (...)
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  28.  29
    Emerging Technologies in the Treatment of Anorexia Nervosa and Ethics: Sufferers’ Accounts of Treatment Strategies and Authenticity.Alina Coman - 2017 - Health Care Analysis 25 (3):212-224.
    New neural models for anorexia nervosa are emerging as a result of increased research on the neurobiology of AN, and these offer a rationale for the development of new treatment technologies such as neuromodulation. The emergence of such treatment technologies raises new ethical questions; however these have been little discussed for AN. In this article, I take an empirical approach and explore how young women who suffer from AN perceive treatment technologies in light of the concept of authenticity. Interview (...)
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  29. Neural Pathways Involved in the Formation of an Image: The Biological Substrate.Julio J. Ramirez - 1988 - Bulletin of Science, Technology and Society 8 (3):318-322.
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  30.  16
    Analysis of Artificial Neural Networks Training Models for Airfare Price Prediction.Kuptsova E. A. & Ramazanov S. K. - 2020 - Artificial Intelligence Scientific Journal 25 (3):45-50.
    Air transport is playing an increasing role in the world economy every year. This is facilitated by technological development and the latest developments in the aviation industry, globalization. This paper provides an overview of artificial neural network training methods for airfare predicting. The articles for 2017-2019 were analyzed in order to determine the model with the most accurate prediction. The researchers conducted research on open data collected by themselves and set themselves the goal of creating a model that would (...)
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  31.  11
    Statistical Approach to Neural Network Imaging of Karst Systems in 3D Seismic Reflection Data.Daniel R. Ebuna, Jared W. Kluesner, Kevin J. Cunningham & Joel H. Edwards - 2018 - Interpretation: SEG 6 (3):B15-B35.
    The current lack of a robust standardized technique for geophysical mapping of karst systems can be attributed to the complexity of the environment and prior technological limitations. Abrupt lateral variations in physical properties that are inherent to karst systems generate significant geophysical noise, challenging conventional seismic signal processing and interpretation. The application of neural networks to multiattribute seismic interpretation can provide a semiautomated method for identifying and leveraging the nonlinear relationships exhibited among seismic attributes. The ambiguity generally associated with (...)
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  32. 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 assert (...)
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  33.  20
    Public Understanding of Neural Prosthetics in Germany: Ethical, Social, and Cultural Challenges.Katsiaryna Laryionava & Dominik Gross - 2011 - Cambridge Quarterly of Healthcare Ethics 20 (3):434-439.
    Since the development of the first neural prosthesis, that is, the cochlear implant in 1957, neural prosthetics have been one of the highly promising, yet most challenging areas of medicine, while having become a clinically accepted form of invasiveness into the human body. Neural prosthetic devices, of which at least one part is inserted into the body, interact directly with the nervous system to restore or replace lost or damaged sensory, motor, or cognitive functions. This field is (...)
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  34. A BP Neural Network-Based GIS-Data-Driven Automated Valuation Framework for Benchmark Land Price.Lei Wu, Yu Zhang, Yongchang Wei & Fangyu Chen - 2022 - Complexity 2022:1-14.
    The automated valuation of benchmark land price plays an essential role in regulating land demand in Chinese real-estate market as the big data are currently accumulated rapidly. However, this problem becomes highly challenging due to the multidimension, large volume, and nonlinearity of the land price-influencing factors. In this paper, an effective data-driven automated valuation framework is proposed for valuing real estate assets by combining a GIS and neural network technologies. This framework can automatically obtain the values of spatial factors (...)
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  35. The Complex Neural Network Model for Mass Appraisal and Scenario Forecasting of the Urban Real Estate Market Value That Adapts Itself to Space and Time.Leonid N. Yasnitsky, Vitaly L. Yasnitsky & Aleksander O. Alekseev - 2021 - Complexity 2021:1-17.
    In the modern scientific literature, there are many reports about the successful application of neural network technologies for solving complex applied problems, in particular, for modeling the urban real estate market. There are neural network models that can perform mass assessment of real estate objects taking into account their construction and operational characteristics. However, these models are static because they do not take into account the changing economic situation over time. Therefore, they quickly become outdated and need frequent (...)
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  36. Translation Mechanism of Neural Machine Algorithm for Online English Resources.Yanping Ye - 2021 - Complexity 2021:1-11.
    At the level of English resource vocabulary, due to the lack of vocabulary alignment structure, the translation of neural machine translation has the problem of unfaithfulness. This paper proposes a framework that integrates vocabulary alignment structure for neural machine translation at the vocabulary level. Under the proposed framework, the neural machine translation decoder receives external vocabulary alignment information during each step of the decoding process to further alleviate the problem of missing vocabulary alignment structure. Specifically, this article (...)
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  37.  28
    Ethics in the Clinical Application of Neural Implants.Cynthia S. Kubu & Paul J. Ford - 2007 - Cambridge Quarterly of Healthcare Ethics 16 (3):317-321.
    Once a neural implant has shown some efficacy during initial research trials, it begins to enter the world of clinical application. This culminates when the implant becomes approved for a particular indication. However, the ethical challenges continue as the technology is adopted as a standard of practice. Patient eligibility criteria, as documented by inclusion and exclusion criteria with any new treatment, are not always clearly quantified and defined. These vagaries can result in considerable debate regarding who should or (...)
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  38. Hacking the Brain: Brain–Computer Interfacing Technology and the Ethics of Neurosecurity.Marcello Ienca & Pim Haselager - 2016 - Ethics and Information Technology 18 (2):117-129.
    Brain–computer interfacing technologies are used as assistive technologies for patients as well as healthy subjects to control devices solely by brain activity. Yet the risks associated with the misuse of these technologies remain largely unexplored. Recent findings have shown that BCIs are potentially vulnerable to cybercriminality. This opens the prospect of “neurocrime”: extending the range of computer-crime to neural devices. This paper explores a type of neurocrime that we call brain-hacking as it aims at the illicit access to and (...)
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  39.  50
    How Are Neural Signals Related to Each Other and to the World?Christoph von der Malsburg - 2002 - Journal of Consciousness Studies 9 (1):47-60.
    The core of this paper is a discussion of how the physical signals of the nervous system acquire significance and meaning on the basis of relationships with each other and with the environment. Signal relations are discussed in terms of coherence , prediction, intentionality, inner reality and meaning. The original and most basic type of signal relation has the form of temporal correlations on coarser or finer time scales, and all other relations must ultimately be built up by the brain (...)
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  40.  72
    Why Build a Virtual Brain? Large-Scale Neural Simulations as Test-Bed for Artificial Computing Systems.Matteo Colombo - 2015 - In D. C. Noelle, R. Dale, A. S. Warlaumont, J. Yoshimi, T. Matlock, C. D. Jennings & P. P. Maglio (eds.), Proceedings of the 37th Annual Conference of the Cognitive Science Society. Cognitive Science Society. pp. 429-434.
    Despite the impressive amount of financial resources invested in carrying out large-scale brain simulations, it is controversial what the payoffs are of pursuing this project. The present paper argues that in some cases, from designing, building, and running a large-scale neural simulation, scientists acquire useful knowledge about the computational performance of the simulating system, rather than about the neurobiological system represented in the simulation. What this means, why it is not a trivial lesson, and how it advances the literature (...)
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  41.  4
    A Seismic Facies Classification Method Based on the Convolutional Neural Network and the Probabilistic Framework for Seismic Attributes and Spatial Classification.Zhege Liu, Junxing Cao, Yujia Lu, Shuna Chen & Jianli Liu - 2019 - Interpretation 7 (3):SE225-SE236.
    In the early stage of oil and gas exploration, due to the lack of available drilling data, the automatic seismic facies classification technology mainly relies on the unsupervised clustering method combined with the seismic multiattribute. However, the clustering results are unstable and have no clear geologic significance. The supervised classification method based on manual interpretation can provide corresponding geologic significance, but there are still some problems such as the discrete classification results and low accuracy. To solve these problems, inspired (...)
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  42.  4
    Karl Jaspers and Artificial Neural Nets: On the Relation of Explaining and Understanding Artificial Intelligence in Medicine.Christopher Poppe & Georg Starke - 2022 - Ethics and Information Technology 24 (3).
    Assistive systems based on Artificial Intelligence are bound to reshape decision-making in all areas of society. One of the most intricate challenges arising from their implementation in high-stakes environments such as medicine concerns their frequently unsatisfying levels of explainability, especially in the guise of the so-called black-box problem: highly successful models based on deep learning seem to be inherently opaque, resisting comprehensive explanations. This may explain why some scholars claim that research should focus on rendering AI systems understandable, rather than (...)
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  43.  26
    Technology Report: Intelligent Summoner. [REVIEW]Robert E. Macneel - 1995 - Artificial Intelligence and Law 3 (4):277-285.
    Trial Courts all over the world have a common problem concerning how to regulate the number of jurors to summon so that there is a sufficient but not excess supply available for scheduled trials. Many trials end abruptly just before jurors are selected for voir dire. The reasons for this are diverse, including last minute settlements, guilty pleas, continuances, unavailability of witnesses, etc. This typically results in one-third to one-half of all summoned jurors never experiencing any activity at all — (...)
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  44.  6
    Walking Gait Phase Detection Based on Acceleration Signals Using Voting-Weighted Integrated Neural Network.Lei Yan, Tao Zhen, Jian-Lei Kong, Lian-Ming Wang & Xiao-Lei Zhou - 2020 - Complexity 2020:1-14.
    Human gait phase recognition is a significant technology for rehabilitation training robot, human disease diagnosis, artificial prosthesis, and so on. The efficient design of the recognition method for gait information is the key issue in the current gait phase division and eigenvalues extraction research. In this paper, a novel voting-weighted integrated neural network is proposed to detect different gait phases from multidimensional acceleration signals. More specifically, it first employs a gait information acquisition system to collect different IMU sensors (...)
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  45. Images and Constructs: Can the Neural Correlates of Self Be Revealed Through Radiological Analysis?Stan Klein - 2013 - International Journal of Psychological Research 6:117-132.
    In this paper I argue that radiological attempts to elucidate the properties of self -- an endeavor currently popular in the social neurosciences -- are fraught with conceptual difficulties. I first discuss several philosophical criteria that increase the chances we are posing the “right” questions to nature. I then discuss whether these criteria are met when empirical efforts are directed at one of the central constructs in the social sciences – the human self. In particular, I consider whether recent attempts (...)
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  46.  2
    Ukrainian Dactyl Alphabet Gesture Recognition Using Convolutional Neural Networks with 3d Convolutions.Kondratiuk S. S. - 2019 - Artificial Intelligence Scientific Journal 24 (1-2):94-100.
    The technology, which is implemented with cross platform tools, is proposed for modeling of gesture units of sign language, animation between states of gesture units with a combination of gestures. Implemented technology simulates sequence of gestures using virtual spatial hand model and performs recognition of dactyl items from camera input using trained on collected training dataset set convolutional neural network, based on the MobileNetv3 architecture, and with the optimal configuration of layers and network parameters. On the collected (...)
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  47. Data-Driven Technology in Event-Based Vision.Ruolin Sun, Dianxi Shi, Yongjun Zhang, Ruihao Li & Ruoxiang Li - 2021 - Complexity 2021:1-19.
    Event cameras which transmit per-pixel intensity changes have emerged as a promising candidate in applications such as consumer electronics, industrial automation, and autonomous vehicles, owing to their efficiency and robustness. To maintain these inherent advantages, the trade-off between efficiency and accuracy stands as a priority in event-based algorithms. Thanks to the preponderance of deep learning techniques and the compatibility between bio-inspired spiking neural networks and event-based sensors, data-driven approaches have become a hot spot, which along with the dedicated hardware (...)
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  48.  68
    Expert Networks: Paradigmatic Conflict, Technological Rapproachement. [REVIEW]R. C. Lacher - 1993 - Minds and Machines 3 (1):53-71.
    A rule-based expert system is demonstrated to have both a symbolic computational network representation and a sub-symbolic connectionist representation. These alternate views enhance the usefulness of the original system by facilitating introduction of connectionist learning methods into the symbolic domain. The connectionist representation learns and stores metaknowledge in highly connected subnetworks and domain knowledge in a sparsely connected expert network superstructure. The total connectivity of the neural network representation approximates that of real neural systems and hence avoids scaling (...)
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  49. Adaptive Orthogonal Characteristics of Bio-Inspired Neural Networks.Naohiro Ishii, Toshinori Deguchi, Masashi Kawaguchi, Hiroshi Sasaki & Tokuro Matsuo - 2022 - Logic Journal of the IGPL 30 (4):578-598.
    In recent years, neural networks have attracted much attention in the machine learning and the deep learning technologies. Bio-inspired functions and intelligence are also expected to process efficiently and improve existing technologies. In the visual pathway, the prominent features consist of nonlinear characteristics of squaring and rectification functions observed in the retinal and visual cortex networks, respectively. Further, adaptation is an important feature to activate the biological systems, efficiently. Recently, to overcome short-comings of the deep learning techniques, orthogonality for (...)
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  50.  3
    Network Security Situation Awareness Forecasting Based on Statistical Approach and Neural Networks.Pavol Sokol, Richard Staňa, Andrej Gajdoš & Patrik Pekarčík - forthcoming - Logic Journal of the IGPL.
    The usage of new and progressive technologies brings with it new types of security threats and security incidents. Their number is constantly growing.The current trend is to move from reactive to proactive activities. For this reason, the organization should be aware of the current security situation, including the forecasting of the future state. The main goal of organizations, especially their security operation centres, is to handle events, identify potential security incidents, and effectively forecast the network security situation awareness. In this (...)
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