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Статті в журналах з теми "Forms and sources of knowledge"
Kremer‐Hayon, Lya. "The Knowledge Teachers Use in Problem Solving Situations: sources and forms." Scandinavian Journal of Educational Research 38, no. 1 (January 1994): 51–63. http://dx.doi.org/10.1080/0031383940380104.
Повний текст джерелаLambert, Ronald D., James E. Curtis, Barry J. Kay, and Steven D. Brown. "The Social Sources of Political Knowledge." Canadian Journal of Political Science 21, no. 2 (June 1988): 359–74. http://dx.doi.org/10.1017/s0008423900056341.
Повний текст джерелаDoloreux, David, and Ekaterina Turkina. "Are winemaker consultants just another source of knowledge for innovation?" Journal of Knowledge Management 21, no. 6 (October 9, 2017): 1523–39. http://dx.doi.org/10.1108/jkm-01-2017-0025.
Повний текст джерелаWiedeman, Alejandra, Susan Barr, Timothy Green, Zhaoming Xu, Sheila Innis, and David Kitts. "Dietary Choline Intake: Current State of Knowledge Across the Life Cycle." Nutrients 10, no. 10 (October 16, 2018): 1513. http://dx.doi.org/10.3390/nu10101513.
Повний текст джерелаCarazo, Alejandro, Kateřina Macáková, Kateřina Matoušová, Lenka Kujovská Krčmová, Michele Protti, and Přemysl Mladěnka. "Vitamin A Update: Forms, Sources, Kinetics, Detection, Function, Deficiency, Therapeutic Use and Toxicity." Nutrients 13, no. 5 (May 18, 2021): 1703. http://dx.doi.org/10.3390/nu13051703.
Повний текст джерелаSieradzka, Katarzyna, and Lidia Kaliszczak. "Sources of Knowledge and Networking as Conditions for Development of Innovative Undertakings in Poland." Central European Review of Economics & Finance 28, no. 6 (December 31, 2018): 39–48. http://dx.doi.org/10.24136/ceref.2018.030.
Повний текст джерелаPolak, Przemysław. "The consequences of the use of online sources of information and mobile devices in university classes." Online Journal of Applied Knowledge Management 6, no. 1 (April 10, 2018): 81–92. http://dx.doi.org/10.36965/ojakm.2018.6(1)81-92.
Повний текст джерелаMilner, B. "Management of Intellectual Resources." Voprosy Ekonomiki, no. 7 (July 20, 2008): 129–40. http://dx.doi.org/10.32609/0042-8736-2008-7-129-140.
Повний текст джерелаWheeler, Billy. "Reliabilism and the Testimony of Robots." Techné: Research in Philosophy and Technology 24, no. 3 (2020): 332–56. http://dx.doi.org/10.5840/techne202049123.
Повний текст джерелаBrondi, Sonia, Giuseppe Pellegrini, Peter Guran, Martin Fero, and Andrea Rubin. "Dimensions of trust in different forms of science communication: the role of information sources and channels used to acquire science knowledge." Journal of Science Communication 20, no. 03 (May 10, 2021): A08. http://dx.doi.org/10.22323/2.20030208.
Повний текст джерелаДисертації з теми "Forms and sources of knowledge"
Penazzi, Leonardo. "The fellow (novel) ; and Australian historical fiction, debating the perceived past (dissertation)." University of Western Australia. School of Social and Cultural Studies, 2008. http://theses.library.uwa.edu.au/adt-WU2008.0070.
Повний текст джерелаAntonakos, Evangelia. "Forms of Generic Common Knowledge." Thesis, City University of New York, 2013. http://pqdtopen.proquest.com/#viewpdf?dispub=3557113.
Повний текст джерелаIn multi-agent epistemic logics, common knowledge has been a central consideration of study. A generic common knowledge (G.C.K.) system is one that yields iterated knowledge I(ϕ): 'any agent knows that any agent knows that any agent knows. . . ϕ' for any number of iterations. Generic common knowledge yields iterated knowledge G.C.K.(ϕ) → I(ϕ) but is not necessarily logically equivalent to it. This contrasts with the most prevalent formulation of common knowledge C as equivalent to iterated knowledge. A spectrum of systems may satisfy the G.C.K. condition, of which C is just one. It has been shown that in the usual epistemic scenarios, G.C.K. can replace conventional common knowledge and Artemov has noted that such standard sources of common knowledge as public announcements of atomic sentences generally yield G.C.K. rather than C.
In this dissertation we study mathematical properties of generic common knowledge and compare them to the traditional common knowledge notion. In particular, we contrast the modal G.C.K. logics of McCarthy (e.g. M4) and Artemov (e.g. [special characters omitted]) with C-systems (e.g. [special characters omitted]) and present a joint C/G.C.K. implicit knowledge logic [special characters omitted] as a conservative extension of both. We show that in standard epistemic scenarios in which common knowledge of certain premises is assumed, whose conclusion does not concern common knowledge (such as Muddy Children, Wise Men, Unfaithful Wives, etc.), a lighter G.C.K.can be used instead of the traditional, more complicated, common knowledge. We then present the first fully explicit G.C.K. system LP n(LP). This justification logic realizes the corresponding modal system [special characters omitted] so that G.C.K., along with individual knowledge modalities, can always be made explicit.
Mahmud, Zakaria. "Source of New and Advance Scientific Knowledge of Software Practitioners." Thesis, Blekinge Tekniska Högskola, Institutionen för programvaruteknik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-4345.
Повний текст джерелаC/O TALUKDER MAMUN SÄRLAGATAN 13B 214 48, MALMO. Phone: 0733499525
Zeng, Xiaoming. "New forms of power sources for welding applications." Thesis, University of Liverpool, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.316628.
Повний текст джерелаPerkins, Arland Early. "School Principals’ Sources of Knowledge." Digital Commons @ East Tennessee State University, 2014. https://dc.etsu.edu/etd/2353.
Повний текст джерелаZhang, Ping. "Learning from Multiple Knowledge Sources." Diss., Temple University Libraries, 2013. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/214795.
Повний текст джерелаPh.D.
In supervised learning, it is usually assumed that true labels are readily available from a single annotator or source. However, recent advances in corroborative technology have given rise to situations where the true label of the target is unknown. In such problems, multiple sources or annotators are often available that provide noisy labels of the targets. In these multi-annotator problems, building a classifier in the traditional single-annotator manner, without regard for the annotator properties may not be effective in general. In recent years, how to make the best use of the labeling information provided by multiple annotators to approximate the hidden true concept has drawn the attention of researchers in machine learning and data mining. In our previous work, a probabilistic method (i.e., MAP-ML algorithm) of iteratively evaluating the different annotators and giving an estimate of the hidden true labels is developed. However, the method assumes the error rate of each annotator is consistent across all the input data. This is an impractical assumption in many cases since annotator knowledge can fluctuate considerably depending on the groups of input instances. In this dissertation, one of our proposed methods, GMM-MAPML algorithm, follows MAP-ML but relaxes the data-independent assumption, i.e., we assume an annotator may not be consistently accurate across the entire feature space. GMM-MAPML uses a Gaussian mixture model (GMM) and Bayesian information criterion (BIC) to find the fittest model to approximate the distribution of the instances. Then the maximum a posterior (MAP) estimation of the hidden true labels and the maximum-likelihood (ML) estimation of quality of multiple annotators at each Gaussian component are provided alternately. Recent studies show that it is not the case that employing more annotators regardless of their expertise will result in improved highest aggregating performance. In this dissertation, we also propose a novel algorithm to integrate multiple annotators by Aggregating Experts and Filtering Novices, which we call AEFN. AEFN iteratively evaluates annotators, filters the low-quality annotators, and re-estimates the labels based only on information obtained from the good annotators. The noisy annotations we integrate are from any combination of human and previously existing machine-based classifiers, and thus AEFN can be applied to many real-world problems. Emotional speech classification, CASP9 protein disorder prediction, and biomedical text annotation experiments show a significant performance improvement of the proposed methods (i.e., GMM-MAPML and AEFN) as compared to the majority voting baseline and the previous data-independent MAP-ML method. Recent experiments include predicting novel drug indications (i.e., drug repositioning) for both approved drugs and new molecules by integrating multiple chemical, biological or phenotypic data sources.
Temple University--Theses
Maynard, Diana Gabrielle. "Term recognition using combined knowledge sources." Thesis, Manchester Metropolitan University, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.311203.
Повний текст джерелаRyder, Katherine Ann. "Alternate forms of knowledge in polysubstance use subgroups /." Oklahoma City : [s.n.], 1999. http://library.ouhsc.edu/epub/theses/Ryder-Katherine-Ann.pdf.
Повний текст джерелаMonkhouse, Wendy. "Forms of ancient Egyptian knowledge : studies in transmission." Thesis, University College London (University of London), 2008. http://discovery.ucl.ac.uk/1444231/.
Повний текст джерелаStevenson, Robert Mark. "Multiple knowledge sources for word sense disambiguation." Thesis, University of Sheffield, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.310763.
Повний текст джерелаКниги з теми "Forms and sources of knowledge"
Knowledge, forms, the aviary. Boise: Ahsahta Press, Boise State University, 2006.
Знайти повний текст джерелаKelsey, Karla. Knowledge, forms, the aviary. Boise. ID: Ahsahta Press, Boise State University, 2007.
Знайти повний текст джерелаTirosh, Dina, ed. Forms of Mathematical Knowledge. Dordrecht: Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-017-1584-3.
Повний текст джерелаKoethe, John. Scepticism, knowledge, and forms of reasoning. Ithaca, NY: Cornell University Press, 2006.
Знайти повний текст джерелаScepticism, knowledge, and forms of reasoning. Ithaca, N.Y: Cornell University Press, 2005.
Знайти повний текст джерелаT.S. Eliot's use of popular sources. Lewiston: E. Mellen Press, 1997.
Знайти повний текст джерелаPlato on knowledge and forms: Selected essays. Oxford: Clarendon Press, 2003.
Знайти повний текст джерелаFINE, GAIL. Plato on Knowledge and Forms: Selected Essays. Oxford: Oxford University Press, 2003.
Знайти повний текст джерелаWiegandt, Ellen, ed. Mountains: Sources of Water, Sources of Knowledge. Dordrecht: Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-6748-8.
Повний текст джерелаservice), SpringerLink (Online, ed. Mountains: Sources of Water, Sources of Knowledge. Dordrecht: Springer, 2008.
Знайти повний текст джерелаЧастини книг з теми "Forms and sources of knowledge"
Bréard, Andrea. "On the Transmission of Mathematical Knowledge in Versified Form in China." In Scientific Sources and Teaching Contexts Throughout History: Problems and Perspectives, 155–85. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-5122-4_7.
Повний текст джерелаMaybin, Jo. "Knowledge Sources." In Producing Health Policy, 38–63. London: Palgrave Macmillan UK, 2016. http://dx.doi.org/10.1007/978-1-349-78654-1_3.
Повний текст джерелаHarper, Donald. "The Textual Form of Knowledge: Occult Miscellanies in Ancient and Medieval Chinese Manuscripts, Fourth Century B.C. to Tenth Century A.D." In Looking at it from Asia: the Processes that Shaped the Sources of History of Science, 37–80. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-3676-6_2.
Повний текст джерелаGreilich, Susanne. "Spanische Enzyklopädie-Übersetzungen als Orte der selbstbewussten Partizipation an aufgeklärter Wissensproduktion." In Übersetzungskulturen der Frühen Neuzeit, 337–54. Berlin, Heidelberg: Springer Berlin Heidelberg, 2021. http://dx.doi.org/10.1007/978-3-662-62562-0_16.
Повний текст джерелаvan Bakel, Ruud, Teodor Aleksiev, Daniel Daza, Dimitrios Alivanistos, and Michael Cochez. "Approximate Knowledge Graph Query Answering: From Ranking to Binary Classification." In Lecture Notes in Computer Science, 107–24. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72308-8_8.
Повний текст джерелаSrzednicki, Jan. "Sources of Knowledge." In To Know or Not to Know, 37–61. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-017-3542-1_3.
Повний текст джерелаBerghofer, Philipp. "Sources of knowledge." In The Husserlian Mind, 315–26. London: Routledge, 2021. http://dx.doi.org/10.4324/9780429243790-30.
Повний текст джерелаJohannesson, Paul, and Erik Perjons. "Knowledge Types and Forms." In An Introduction to Design Science, 21–38. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10632-8_2.
Повний текст джерелаJohannesson, Paul, and Erik Perjons. "Knowledge Types and Forms." In An Introduction to Design Science, 23–40. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-78132-3_2.
Повний текст джерелаWimsatt, William C. "Forms of Aggregativity." In Human Nature and Natural Knowledge, 259–91. Dordrecht: Springer Netherlands, 1986. http://dx.doi.org/10.1007/978-94-009-5349-9_14.
Повний текст джерелаТези доповідей конференцій з теми "Forms and sources of knowledge"
Fan, I. S., G. Li, M. Lagos-Hernandez, P. Bermell-Garci´a, and M. Twelves. "A Rule Level Knowledge Management System for Knowledge Based Engineering Applications." In ASME 2002 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2002. http://dx.doi.org/10.1115/detc2002/cie-34501.
Повний текст джерелаXu, Y., and K. L. Yung. "Forms of Static Friction, Sliding Friction and Rolling Friction." In World Tribology Congress III. ASMEDC, 2005. http://dx.doi.org/10.1115/wtc2005-64050.
Повний текст джерелаRezer, Tatiana. "Digital Learning Environments and New Forms of Didactogeny." In The Public/Private in Modern Civilization, the 22nd Russian Scientific-Practical Conference (with international participation) (Yekaterinburg, April 16-17, 2020). Liberal Arts University – University for Humanities, Yekaterinburg, 2020. http://dx.doi.org/10.35853/ufh-public/private-2020-77.
Повний текст джерелаWu, Qi, Peng Wang, Chunhua Shen, Anthony Dick, and Anton Van Den Hengel. "Ask Me Anything: Free-Form Visual Question Answering Based on Knowledge from External Sources." In 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2016. http://dx.doi.org/10.1109/cvpr.2016.500.
Повний текст джерелаVeira, Neil, Brian Keng, Kanchana Padmanabhan, and Andreas Veneris. "Unsupervised Embedding Enhancements of Knowledge Graphs using Textual Associations." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/725.
Повний текст джерелаSimari, Gerardo I. "From Data to Knowledge Engineering for Cybersecurity." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/896.
Повний текст джерелаXiao, Chunyang, Marc Dymetman, and Claire Gardent. "Symbolic Priors for RNN-based Semantic Parsing." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/585.
Повний текст джерелаSkyrius, Rimvydas. "Human Factors in Person-Technology Relations in Business Decision Making." In 2002 Informing Science + IT Education Conference. Informing Science Institute, 2002. http://dx.doi.org/10.28945/2573.
Повний текст джерелаLin, Linyu, Pascal Rouxelin, Paridhi Athe, Nam Dinh, and Jeffrey Lane. "Development and Assessment of Data-Driven Digital Twins in a Nearly Autonomous Management and Control System for Advanced Reactors." In 2020 International Conference on Nuclear Engineering collocated with the ASME 2020 Power Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/icone2020-16813.
Повний текст джерелаZamiri, Majid, Andreia Artifice, Elsa Marcelino-Jesus, Joao Sarraipa, and Ricardo Jardim-Goncalves. "A Future Trend in Sensing Enterprise Systems." In ASME 2018 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/imece2018-88530.
Повний текст джерелаЗвіти організацій з теми "Forms and sources of knowledge"
Schwartz, Richard, and John Makhoul. Combining Multiple Knowledge Sources for Speech Recognition. Fort Belvoir, VA: Defense Technical Information Center, September 1988. http://dx.doi.org/10.21236/ada198928.
Повний текст джерелаMadnick, Stuart, and Michael Siegel. Context Interchange: Using Knowledge About Data to Integrate Disparate Sources. Fort Belvoir, VA: Defense Technical Information Center, October 1999. http://dx.doi.org/10.21236/ada372091.
Повний текст джерелаZamora, Antonio. 41. DISCOVERY, SEARCH, AND COMMUNICATION OF TEXTUAL KNOWLEDGE RESOURCES IN DISTRIBUTED SYSTEMS a. Discovering and Utilizing Knowledge Sources for Metasearch Knowledge Systems. Office of Scientific and Technical Information (OSTI), March 2008. http://dx.doi.org/10.2172/946818.
Повний текст джерелаLarson, Steven L., John H. Ballard, Fende Meng, Decheng Jin, Kai Guo, Liangmei Chen, Zikri Arslan, et al. Influences of U sources and forms on its bioaccumulation in Indian mustard and sunflower. Engineer Research and Development Center (U.S.), June 2020. http://dx.doi.org/10.21079/11681/37275.
Повний текст джерелаBohus, Dan, and Alex Rudnicky. Integrating Multiple Knowledge Sources for Utterance-Level Confidence Annotation in the CMU Communicator Spoken Dialog System. Fort Belvoir, VA: Defense Technical Information Center, November 2002. http://dx.doi.org/10.21236/ada461099.
Повний текст джерелаArlitsch, Kenning. Data set supporting the dissertation Semantic Web Identity in Academic Organizations: Search engine entity recognition and the sources that influence Knowledge Graph Cards in search results. Montana State University ScholarWorks, 2016. http://dx.doi.org/10.15788/m2f590.
Повний текст джерелаMilek, Karen, and Richard Jones, eds. Science in Scottish Archaeology: ScARF Panel Report. Society of Antiquaries of Scotland, September 2012. http://dx.doi.org/10.9750/scarf.06.2012.193.
Повний текст джерелаSanz, E., P. Alonso, B. Haidar, H. Ghaemi, and L. García. Key performance indicators (KPIs). Scipedia, 2021. http://dx.doi.org/10.23967/prodphd.2021.9.002.
Повний текст джерелаYatsymirska, Mariya. SOCIAL EXPRESSION IN MULTIMEDIA TEXTS. Ivan Franko National University of Lviv, February 2021. http://dx.doi.org/10.30970/vjo.2021.49.11072.
Повний текст джерелаJudith, Meyer, and David Keller. H - Requirement No. 1. OceanNETs, September 2020. http://dx.doi.org/10.3289/oceannets_d10.1.
Повний текст джерела