Добірка наукової літератури з теми "Assertion mining"
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Статті в журналах з теми "Assertion mining"
Cagliero, Luca, Tania Cerquitelli, and Paolo Garza. "Semi-Automatic Ontology Construction by Exploiting Functional Dependencies and Association Rules." International Journal on Semantic Web and Information Systems 7, no. 2 (April 2011): 1–22. http://dx.doi.org/10.4018/jswis.2011040101.
Повний текст джерелаYu, Chi-Hsin, and Hsin-Hsi Chen. "Commonsense Knowledge Mining from the Web." Proceedings of the AAAI Conference on Artificial Intelligence 24, no. 1 (July 5, 2010): 1480–85. http://dx.doi.org/10.1609/aaai.v24i1.7505.
Повний текст джерелаIwanowicz, 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, no. 105 (161) (December 22, 2019): 17–30. http://dx.doi.org/10.5604/01.3001.0013.6053.
Повний текст джерелаBaker-Médard, Merrill S. A. "Conflicting Treasures: contrasting resource use governance in two artisanal gemstone mining sites in Madagascar." Journal of Political Ecology 19, no. 1 (December 1, 2012): 221. http://dx.doi.org/10.2458/v19i1.21728.
Повний текст джерелаAmiri, Esmaeil, Prashant Waiker, Olav Rueppell, and Prashanti Manda. "Using Manual and Computer-Based Text-Mining to Uncover Research Trends for Apis mellifera." Veterinary Sciences 7, no. 2 (May 6, 2020): 61. http://dx.doi.org/10.3390/vetsci7020061.
Повний текст джерелаPalmer, David, and Carolyn Dillian. "Preliminary investigations into the source of brick clay, Brookgreen Plantation, Georgetown County, South Carolina." North American Archaeologist 39, no. 1 (January 2018): 3–24. http://dx.doi.org/10.1177/0197693117749659.
Повний текст джерелаKeerthi, V., and 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, no. 2 (December 10, 2020): 78–82. http://dx.doi.org/10.35940/ijitee.b8270.1210220.
Повний текст джерелаIreland-Piper, Danielle, and 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, no. 1 (September 28, 2021): 101–27. http://dx.doi.org/10.21827/grojil.9.1.101-127.
Повний текст джерелаLaurance, William F., Ana K. M. Albernaz, and Carlos Da Costa. "Is deforestation accelerating in the Brazilian Amazon?" Environmental Conservation 28, no. 4 (December 2001): 305–11. http://dx.doi.org/10.1017/s0376892901000339.
Повний текст джерелаVallée, 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, no. 5 (May 2019): 525–43. http://dx.doi.org/10.1139/cjes-2019-0009.
Повний текст джерелаДисертації з теми "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.
Повний текст джерелаDanese, Alessandro. "System-level functional and extra-functional characterization of SoCs through assertion mining." Doctoral thesis, 2018. http://hdl.handle.net/11562/979447.
Повний текст джерелаGHASEMPOURI, TARA. "Improving ABV by generation and abstraction of PSL assertions." Doctoral thesis, 2016. http://hdl.handle.net/11562/939548.
Повний текст джерелаThe 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.
Книги з теми "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.
Знайти повний текст джерелаFricker, 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.
Повний текст джерелаPelkmans, Mathijs. Introduction. Cornell University Press, 2017. http://dx.doi.org/10.7591/cornell/9781501705137.003.0001.
Повний текст джерелаЧастини книг з теми "Assertion mining"
Vasudevan, Shobha, Lingyi Liu, and Samuel Hertz. "A Comparative Study of Assertion Mining Algorithms in GoldMine." In 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.
Повний текст джерела"Assertion." In 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.
Повний текст джерелаCagliero, Luca, Tania Cerquitelli, and Paolo Garza. "Semi-Automatic Ontology Construction by Exploiting Functional Dependencies and Association Rules." In Semantic Web, 76–96. IGI Global, 2013. http://dx.doi.org/10.4018/978-1-4666-3610-1.ch004.
Повний текст джерелаButler, Mark. "‘Mines come to bring poverty’: extractive industry in the life of the people in KwaZulu-Natal, South Africa." In Environmental Justice, Popular Struggle and Community Development, 101–16. Policy Press, 2019. http://dx.doi.org/10.1332/policypress/9781447350835.003.0007.
Повний текст джерелаBaldwin, Nicholas, and Amy Lynn Fletcher. "Asteroid Futures." In 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.
Повний текст джерелаWahlang, Maranatha G. T., and Bengt G. Karlsson. "The Body of the Land." In Vernacular Politics in Northeast India, 289–310. Oxford University Press, 2022. http://dx.doi.org/10.1093/oso/9780192863461.003.0012.
Повний текст джерелаCressy, David. "Lundy." In England's Islands in a Sea of Troubles, 27–36. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198856603.003.0003.
Повний текст джерелаТези доповідей конференцій з теми "Assertion mining"
Danese, Alessandra, Jacopo Mocci, and Graziano Pravadelli. "Fault model qualification by assertion mining." In 2016 17th Latin-American Test Symposium (LATS). IEEE, 2016. http://dx.doi.org/10.1109/latw.2016.7483338.
Повний текст джерелаDanese, Alessandro, Valeria Bertacco, and Graziano Pravadelli. "Symbolic assertion mining for security validation." In 2018 Design, Automation & Test in Europe Conference & Exhibition (DATE). IEEE, 2018. http://dx.doi.org/10.23919/date.2018.8342262.
Повний текст джерелаGhasempouri, Tara, Alessandro Danese, Graziano Pravadelli, Nicola Bombieri, and Jaan Raik. "RTL Assertion Mining with Automated RTL-to-TLM Abstraction." In 2019 Forum for Specification and Design Languages (FDL). IEEE, 2019. http://dx.doi.org/10.1109/fdl.2019.8876941.
Повний текст джерелаGhasempouri, Tara, Jan Malburg, Alessandro Danese, Graziano Pravadelli, Goerschwin Fey, and Jaan Raik. "Engineering of an Effective Automatic Dynamic Assertion Mining Platform." In 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.
Повний текст джерелаLiu, Lingyi, Chen-Hsuan Lin, and Shobha Vasudevan. "Word level feature discovery to enhance quality of assertion mining." In the International Conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2429384.2429424.
Повний текст джерелаVasudevan, Shobha, David Sheridan, Sanjay Patel, David Tcheng, Bill Tuohy, and Daniel Johnson. "GoldMine: Automatic assertion generation using data mining and static analysis." In 2010 Design, Automation & Test in Europe Conference & Exhibition (DATE 2010). IEEE, 2010. http://dx.doi.org/10.1109/date.2010.5457129.
Повний текст джерелаChang, Po-Hsien, and Li C. Wang. "Automatic assertion extraction via sequential data mining of simulation traces." In 2010 15th Asia and South Pacific Design Automation Conference ASP-DAC 2010. IEEE, 2010. http://dx.doi.org/10.1109/aspdac.2010.5419813.
Повний текст джерелаHeidari Iman, Mohammad Reza, Jaan Raik, Maksim Jenihhin, Gert Jervan, and Tara Ghasempouri. "A Methodology for Automated Mining of Compact and Accurate Assertion Sets." In 2021 IEEE Nordic Circuits and Systems Conference (NorCAS). IEEE, 2021. http://dx.doi.org/10.1109/norcas53631.2021.9599865.
Повний текст джерелаBoldo, Michele, Nicola Bombieri, Mirco De Marchi, Luca Geretti, Samuele Germiniani, and Graziano Pravadelli. "Risk Assessment and Prediction in Human-Robot Interaction Through Assertion Mining and Pose Estimation." In 2022 IEEE 23rd Latin American Test Symposium (LATS). IEEE, 2022. http://dx.doi.org/10.1109/lats57337.2022.9936899.
Повний текст джерелаCosta, Antonio Anastasio Bruto da, Shriya Dharade, Sudipa Mandal, and Pallab Dasgupta. "AMS-Miner: Mining AMS Assertions Using Interval Arithmetic." In 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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