Results for 'Abhinav Deol'

19 found
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  1.  8
    Understanding public sentiments and misbeliefs about Sustainable Development Goals: a sentiment and topic modeling analysis.Abhinav Verma & Jogendra Kumar Nayak - 2024 - Journal of Information, Communication and Ethics in Society 22 (2):256-274.
    Purpose Misinformation surrounding the Sustainable Development Goals (SDGs) has contributed to the formation of misbeliefs among the public. The purpose of this paper is to investigate public sentiment and misbeliefs about the SDGs on the YouTube platform. Design/methodology/approach The authors extracted 8,016 comments from YouTube videos associated with SDGs. The authors used a pre-trained Python library NRC lexicon for sentiment and emotion analysis, and to extract latent topics, the authors used BERTopic for topic modeling. Findings The authors found eight emotions, (...)
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  2.  34
    Use of diffusion spectrum imaging in preliminary longitudinal evaluation of amyotrophic lateral sclerosis: development of an imaging biomarker.Kumar Abhinav, Fang-Cheng Yeh, Ahmed El-Dokla, Lisa M. Ferrando, Yue-Fang Chang, David Lacomis, Robert M. Friedlander & Juan C. Fernandez-Miranda - 2014 - Frontiers in Human Neuroscience 8.
  3.  41
    Symbols, Meaning, and Origins of Mind.Abhinav Gautam & Subhash Kak - 2013 - Biosemiotics 6 (3):301-310.
    The mind maps symbols and the extra-symbolic relationships amongst them to specific meanings. When symbols of various levels are placed in a hierarchical ordering, one may look at such ordered classes as distinct worlds where one class represents objects and the other represents the objects’ corresponding meanings. However, such an explanation can only be partial because the number of potential levels in such an ordering is infinite and, therefore, it engenders problems of recursion and infinite regress. There are also logical (...)
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  4.  11
    Radiation, genes and man.M. S. Deol - 1961 - The Eugenics Review 53 (1):46.
  5.  7
    The Mīṇās and Their LiteratureThe Minas and Their Literature.Jeevan Deol - 1998 - Journal of the American Oriental Society 118 (2):172.
  6.  1
    Developmental genetics and lethal factors.M. S. Deol - 1961 - The Eugenics Review 53 (1):46.
  7.  18
    Non-Canonical Compositions Attributed to the Seventh and Ninth Sikh Gurus.Jeevan Singh Deol - 2001 - Journal of the American Oriental Society 121 (2):193-203.
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  8.  20
    Expression unleashed in artificial intelligence.Ekaterina I. Tolstaya, Abhinav Gupta & Edward Hughes - 2023 - Behavioral and Brain Sciences 46:e16.
    The problem of generating generally capable agents is an important frontier in artificial intelligence (AI) research. Such agents may demonstrate open-ended, versatile, and diverse modes of expression, similar to humans. We interpret the work of Heintz & Scott-Phillips as a minimal sufficient set of socio-cognitive biases for the emergence of generally expressive AI, separate yet complementary to existing algorithms.
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  9. Clinical Decisions Using AI Must Consider Patient Values.Jonathan Birch, Kathleen A. Creel, Abhinav K. Jha & Anya Plutynski - 2022 - Nature Medicine 28:229–232.
    Built-in decision thresholds for AI diagnostics are ethically problematic, as patients may differ in their attitudes about the risk of false-positive and false-negative results, which will require that clinicians assess patient values.
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  10.  7
    Cognitive Training for Post-Acute Traumatic Brain Injury: A Systematic Review and Meta-Analysis.Harry Hallock, Daniel Collins, Amit Lampit, Kiran Deol, Jennifer Fleming & Michael Valenzuela - 2016 - Frontiers in Human Neuroscience 10.
  11.  46
    Design of English hierarchical online test system based on machine learning.Chaman Verma, Shaweta Khanna, Sudeep Asthana, Abhinav Asthana, Dan Zhang & Xiahui Wang - 2021 - Journal of Intelligent Systems 30 (1):793-807.
    Large amount of data are exchanged and the internet is turning into twenty-first century Silk Road for data. Machine learning (ML) is the new area for the applications. The artificial intelligence (AI) is the field providing machines with intelligence. In the last decades, more developments have been made in the field of ML and deep learning. The technology and other advanced algorithms are implemented into more computational constrained devices. The online English test system based on ML breaks the shackles of (...)
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  12.  3
    Integration of genome-wide approaches identifies lncRNAs of adult neural stem cells and their progeny in vivo.Alexander D. Ramos, Aaron Diaz, Abhinav Nellore, Ryan N. Delgado, Ki-Youb Park, Gabriel Gonzales-Roybal, Michael C. Oldham, Jun S. Song & Daniel A. Lim - unknown
    Long noncoding RNAs have been described in cell lines and various whole tissues, but lncRNA analysis of development in vivo is limited. Here, we comprehensively analyze lncRNA expression for the adult mouse subventricular zone neural stem cell lineage. We utilize complementary genome-wide techniques including RNA-seq, RNA CaptureSeq, and ChIP-seq to associate specific lncRNAs with neural cell types, developmental processes, and human disease states. By integrating data from chromatin state maps, custom microarrays, and FACS purification of the subventricular zone lineage, we (...)
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  13.  10
    Design of intelligent acquisition system for moving object trajectory data under cloud computing.Ioan-Cosmin Mihai, Shaweta Khanna, Sudeep Asthana, Abhinav Asthana & Yang Zhang - 2021 - Journal of Intelligent Systems 30 (1):763-773.
    In order to study the intelligent collection system of moving object trajectory data under cloud computing, information useful to passengers and taxi drivers is collected from massive trajectory data. This paper uses cloud computing technology, through clustering algorithm and density-based DBSCAN algorithm combined with Map Reduce programming model and design trajectory clustering algorithm. The results show that based on the 8-day data of 15,000 taxis in Shenzhen, the characteristic time period is determined. The passenger hot spot area is obtained by (...)
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  14.  10
    Major Stressors and Coping Strategies of Internal Migrant Workers During the COVID-19 Pandemic: A Qualitative Exploration.Akanksha Srivastava, Yogesh Kumar Arya, Shobhna Joshi, Tushar Singh, Harleen Kaur, Himanshu Chauhan & Abhinav Das - 2021 - Frontiers in Psychology 12.
    COVID-19 forced lockdown in India, leading to the loss of job, crisis of food, and other financial catastrophes that led to the exodus migration of internal migrant workers, operating in the private sector, back to their homes. Unavailability of transport facilities led to an inflicted need to walk back to homes barefooted without lack of any other crucial resources on the way. The woeful state of internal migrant workers walking back, with all their stuff on their back, holding their children, (...)
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  15. On Models, Simulations, and the Relevancy of Biochemistry to Cognitive Functions.S. Franchi - 2013 - Constructivist Foundations 9 (1):141-142.
    Open peer commentary on the article “A Cybernetic Computational Model for Learning and Skill Acquisition” by Bernard Scott & Abhinav Bansal. Upshot: Scott and Bansal’s assessment of the limitations of their work relies on a concept of simulation that I find problematic. It assumes that the ultimate goal of a model is a replication of the phenomena it applies, whereas a limited model produces only simulations. I argue that this position leads to unfortunate epistemological results, and it ends up (...)
     
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  16.  14
    Assimilation and Integration of Buddha Consciousness in the Cult of Lord Jagannātha.Sasmita Kar - 2020 - Journal of the Indian Council of Philosophical Research 37 (1):67-82.
    Since time immemorial, Lord Jagannātha has been regarded as the principal deity of Odisha. The land of Odisha (former Kaliṅga) was a meeting place of the Hindus, Buddhists and Jainas. The Buddhists, Jainas, Vaiṣṇavas, the worshippers of Gaṇpati and others came to Purī and found the presence of their own lord in Jagannātha. However, of all religious creeds, Buddhism played an important role in the socio-cultural history of Odisha. During the period of emperor Aśoka, the Śabaras (a tribal people) of (...)
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  17. Early Computer Models of Cognitive Systems and the Beginnings of Cognitive Systems Dynamics.G. Mallen - 2013 - Constructivist Foundations 9 (1):137-138.
    Open peer commentary on the article “A Cybernetic Computational Model for Learning and Skill Acquisition” by Bernard Scott & Abhinav Bansal. Upshot: The target paper acknowledges some early computer modelling that I did in the years 1966–1968 when working with Pask at System Research Ltd in Richmond. In the commentary, I revisit the roots of this kind of modelling and follow the trajectory from then to today’s growing understanding of the dynamics of cognitive systems.
     
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  18. Taking Semantics and Embodiment into Account.J. Stewart - 2013 - Constructivist Foundations 9 (1):139-141.
    Open peer commentary on the article “A Cybernetic Computational Model for Learning and Skill Acquisition” by Bernard Scott & Abhinav Bansal. Upshot: The Computational Theory of Mind suffers from an inherent weakness owing to its difficulty in taking semantics and embodiment properly into account. It is suggested that these difficulties could be alleviated if it were recognized that the fact that the model presented here employs a computer as a tool, to highlight certain key features of its dynamics, does (...)
     
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  19. Quality and Qualifications.G. Zeeuw - 2013 - Constructivist Foundations 9 (1):138-139.
    Open peer commentary on the article “A Cybernetic Computational Model for Learning and Skill Acquisition” by Bernard Scott & Abhinav Bansal. Upshot: The paper is an admirable example of first-order cybernetics. It does not appear to be developed as part of the constructivist paradigm and of second-order cybernetics. It neglects research as the context that generates problems of observation.
     
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