Literatura académica sobre el tema "Assertion mining"
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Artículos de revistas sobre el tema "Assertion mining"
Cagliero, Luca, Tania Cerquitelli y Paolo Garza. "Semi-Automatic Ontology Construction by Exploiting Functional Dependencies and Association Rules". International Journal on Semantic Web and Information Systems 7, n.º 2 (abril de 2011): 1–22. http://dx.doi.org/10.4018/jswis.2011040101.
Texto completoYu, Chi-Hsin y Hsin-Hsi Chen. "Commonsense Knowledge Mining from the Web". Proceedings of the AAAI Conference on Artificial Intelligence 24, n.º 1 (5 de julio de 2010): 1480–85. http://dx.doi.org/10.1609/aaai.v24i1.7505.
Texto completoIwanowicz, Tomasz. "The identification of risks of material misstatement based on key audit matters in line with International Standard on Auditing 701". Zeszyty Teoretyczne Rachunkowości 2019, n.º 105 (161) (22 de diciembre de 2019): 17–30. http://dx.doi.org/10.5604/01.3001.0013.6053.
Texto completoBaker-Médard, Merrill S. A. "Conflicting Treasures: contrasting resource use governance in two artisanal gemstone mining sites in Madagascar". Journal of Political Ecology 19, n.º 1 (1 de diciembre de 2012): 221. http://dx.doi.org/10.2458/v19i1.21728.
Texto completoAmiri, Esmaeil, Prashant Waiker, Olav Rueppell y Prashanti Manda. "Using Manual and Computer-Based Text-Mining to Uncover Research Trends for Apis mellifera". Veterinary Sciences 7, n.º 2 (6 de mayo de 2020): 61. http://dx.doi.org/10.3390/vetsci7020061.
Texto completoPalmer, David y Carolyn Dillian. "Preliminary investigations into the source of brick clay, Brookgreen Plantation, Georgetown County, South Carolina". North American Archaeologist 39, n.º 1 (enero de 2018): 3–24. http://dx.doi.org/10.1177/0197693117749659.
Texto completoKeerthi, V. y T. Anuradha. "A Generator Based Polynomial with Secret Encryption Scheme for Secure Data Sharing and Privacy in Multi-Party/Federated-Cloud Computation". International Journal of Innovative Technology and Exploring Engineering 10, n.º 2 (10 de diciembre de 2020): 78–82. http://dx.doi.org/10.35940/ijitee.b8270.1210220.
Texto completoIreland-Piper, Danielle y Steven Freeland. "Human Rights and Space: Reflections on the Implications of Human Activity in Outer Space on Human Rights Law". Groningen Journal of International Law 9, n.º 1 (28 de septiembre de 2021): 101–27. http://dx.doi.org/10.21827/grojil.9.1.101-127.
Texto completoLaurance, William F., Ana K. M. Albernaz y Carlos Da Costa. "Is deforestation accelerating in the Brazilian Amazon?" Environmental Conservation 28, n.º 4 (diciembre de 2001): 305–11. http://dx.doi.org/10.1017/s0376892901000339.
Texto completoVallée, Marc A., William A. Morris, Stéphane Perrouty, Robert G. Lee, Ken Wasyliuk, Julia J. King, Kevin Ansdell et al. "Geophysical inversion contributions to mineral exploration: lessons from the Footprints project". Canadian Journal of Earth Sciences 56, n.º 5 (mayo de 2019): 525–43. http://dx.doi.org/10.1139/cjes-2019-0009.
Texto completoTesis sobre el tema "Assertion mining"
Skeppstedt, Maria. "Extracting Clinical Findings from Swedish Health Record Text". Doctoral thesis, Stockholms universitet, Institutionen för data- och systemvetenskap, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-109254.
Texto completoDanese, Alessandro. "System-level functional and extra-functional characterization of SoCs through assertion mining". Doctoral thesis, 2018. http://hdl.handle.net/11562/979447.
Texto completoGHASEMPOURI, TARA. "Improving ABV by generation and abstraction of PSL assertions". Doctoral thesis, 2016. http://hdl.handle.net/11562/939548.
Texto completoThe aim of this thesis is to provide efficient methodologies to improve ABV in three domains of generation, abstraction and qualification of PSL assertions. The main contributions of this thesis can be summarized as follows: 1- An automatic mining methodology has been proposed, for capturing behavioral descriptions of a system that can generate set of temporal assertions from execution traces. The approach is particularly suited for mining assertions that describes arithmetic relations between inputs and outputs according to a set of temporal patterns. In comparation with state of the art, assertion miner proposed in this methodology, generates a set of more compact and higher quality assertions. 2- An automatic abstraction methodology has been proposed to reuse assertions originally defined for a given RTL IP, to verify the corresponding TLM model. The methodology can be divided into two main phases, firstly, assertions synthesized into C++ methods and secondly, inserted in the TLM model. The results show that the methodology can abstract and reuse assertions from RTL to TLM and avoid redefinition of assertions which are already exist at RTL. 3- An automatic qualification methodology has been proposed to evaluate the quality of assertions to measure the interestingness of assertions. The approach re-adapts metrics from data mining to measure the quality of assertions based on its activation frequency during simulation runs and the correlation between antecedent and consequent. Experimental result depicts the proposed methodology provides a better estimation of assertions interestingness.
Libros sobre el tema "Assertion mining"
Legal Rights and Natural Resources Center (Philippines), ed. Asserting autonomy: LGUs' right to veto mining. Quezon City, Philippines: Legal Rights and Natural Resources Center-Kasama sa Kalikasan, 2009.
Buscar texto completoFricker, Elizabeth. Inference to the Best Explanation and the Receipt of Testimony. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198746904.003.0017.
Texto completoPelkmans, Mathijs. Introduction. Cornell University Press, 2017. http://dx.doi.org/10.7591/cornell/9781501705137.003.0001.
Texto completoCapítulos de libros sobre el tema "Assertion mining"
Vasudevan, Shobha, Lingyi Liu y Samuel Hertz. "A Comparative Study of Assertion Mining Algorithms in GoldMine". En Machine Learning in VLSI Computer-Aided Design, 609–45. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-04666-8_20.
Texto completo"Assertion". En Encyclopedia of Machine Learning and Data Mining, 70. Boston, MA: Springer US, 2017. http://dx.doi.org/10.1007/978-1-4899-7687-1_37.
Texto completoCagliero, Luca, Tania Cerquitelli y Paolo Garza. "Semi-Automatic Ontology Construction by Exploiting Functional Dependencies and Association Rules". En Semantic Web, 76–96. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-3610-1.ch004.
Texto completoButler, Mark. "‘Mines come to bring poverty’: extractive industry in the life of the people in KwaZulu-Natal, South Africa". En Environmental Justice, Popular Struggle and Community Development, 101–16. Policy Press, 2019. http://dx.doi.org/10.1332/policypress/9781447350835.003.0007.
Texto completoBaldwin, Nicholas y Amy Lynn Fletcher. "Asteroid Futures". En Advances in Human and Social Aspects of Technology, 291–301. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-6772-2.ch020.
Texto completoWahlang, Maranatha G. T. y Bengt G. Karlsson. "The Body of the Land". En Vernacular Politics in Northeast India, 289–310. Oxford University Press, 2022. http://dx.doi.org/10.1093/oso/9780192863461.003.0012.
Texto completoCressy, David. "Lundy". En England's Islands in a Sea of Troubles, 27–36. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198856603.003.0003.
Texto completoActas de conferencias sobre el tema "Assertion mining"
Danese, Alessandra, Jacopo Mocci y Graziano Pravadelli. "Fault model qualification by assertion mining". En 2016 17th Latin-American Test Symposium (LATS). IEEE, 2016. http://dx.doi.org/10.1109/latw.2016.7483338.
Texto completoDanese, Alessandro, Valeria Bertacco y Graziano Pravadelli. "Symbolic assertion mining for security validation". En 2018 Design, Automation & Test in Europe Conference & Exhibition (DATE). IEEE, 2018. http://dx.doi.org/10.23919/date.2018.8342262.
Texto completoGhasempouri, Tara, Alessandro Danese, Graziano Pravadelli, Nicola Bombieri y Jaan Raik. "RTL Assertion Mining with Automated RTL-to-TLM Abstraction". En 2019 Forum for Specification and Design Languages (FDL). IEEE, 2019. http://dx.doi.org/10.1109/fdl.2019.8876941.
Texto completoGhasempouri, Tara, Jan Malburg, Alessandro Danese, Graziano Pravadelli, Goerschwin Fey y Jaan Raik. "Engineering of an Effective Automatic Dynamic Assertion Mining Platform". En 2019 IFIP/IEEE 27th International Conference on Very Large Scale Integration (VLSI-SoC). IEEE, 2019. http://dx.doi.org/10.1109/vlsi-soc.2019.8920331.
Texto completoLiu, Lingyi, Chen-Hsuan Lin y Shobha Vasudevan. "Word level feature discovery to enhance quality of assertion mining". En the International Conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2429384.2429424.
Texto completoVasudevan, Shobha, David Sheridan, Sanjay Patel, David Tcheng, Bill Tuohy y Daniel Johnson. "GoldMine: Automatic assertion generation using data mining and static analysis". En 2010 Design, Automation & Test in Europe Conference & Exhibition (DATE 2010). IEEE, 2010. http://dx.doi.org/10.1109/date.2010.5457129.
Texto completoChang, Po-Hsien y Li C. Wang. "Automatic assertion extraction via sequential data mining of simulation traces". En 2010 15th Asia and South Pacific Design Automation Conference ASP-DAC 2010. IEEE, 2010. http://dx.doi.org/10.1109/aspdac.2010.5419813.
Texto completoHeidari Iman, Mohammad Reza, Jaan Raik, Maksim Jenihhin, Gert Jervan y Tara Ghasempouri. "A Methodology for Automated Mining of Compact and Accurate Assertion Sets". En 2021 IEEE Nordic Circuits and Systems Conference (NorCAS). IEEE, 2021. http://dx.doi.org/10.1109/norcas53631.2021.9599865.
Texto completoBoldo, Michele, Nicola Bombieri, Mirco De Marchi, Luca Geretti, Samuele Germiniani y Graziano Pravadelli. "Risk Assessment and Prediction in Human-Robot Interaction Through Assertion Mining and Pose Estimation". En 2022 IEEE 23rd Latin American Test Symposium (LATS). IEEE, 2022. http://dx.doi.org/10.1109/lats57337.2022.9936899.
Texto completoCosta, Antonio Anastasio Bruto da, Shriya Dharade, Sudipa Mandal y Pallab Dasgupta. "AMS-Miner: Mining AMS Assertions Using Interval Arithmetic". En 2018 31st International Conference on VLSI Design and 2018 17th International Conference on Embedded Systems (VLSID). IEEE, 2018. http://dx.doi.org/10.1109/vlsid.2018.98.
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