169 research outputs found
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Sampling uncertainty in gridded sea surface temperature products and Advanced Very High Resolution Radiometer (AVHRR) Global Area Coverage (GAC) data
Sea surface temperature (SST) data are often provided as gridded products, typically at resolutions of order 0.05 degrees from satellite observations to reduce data volume at the request of data users and facilitate comparison against other products or models. Sampling uncertainty is introduced in gridded products where the full surface area of the ocean within a grid cell cannot be fully observed because of cloud cover. In this paper we parameterise uncertainties in SST as a function of the percentage of clear-sky pixels available and the SST variability in that subsample. This parameterisation is developed from Advanced Along Track Scanning Radiometer (AATSR) data, but is applicable to all gridded L3U SST products at resolutions of 0.05-0.1 degrees, irrespective of instrument and retrieval algorithm, provided that instrument noise propagated into the SST is accounted for. We also calculate the sampling uncertainty of ~0.04 K in Global Area Coverage (GAC) Advanced Very High Resolution Radiometer (AVHRR) products, using related methods
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Light weight cellular structures based on aluminium
An interesting form of lightweight material which has emerged in the past 2 decades is metallic foam. This paper deals with the basic concepts of making metallic foams and a detailed study of foams produced from Al-SiC. In addition, some aspects of cellular solids based on honeycomb structures are outlined including the concept of producing both two-phase foams and foams with composite walls
Spatial and Temporal Characteristics of Propagating Deformation Bands in AA5182 Alloy at Room Temperature
Determinación de los mecanismos de fractura de un material multicapa de aluminio de alta resistencia y excelente tenacidad a impacto basado en la aleación aeroespacial Al 7075
Measure-Based Inconsistency-Tolerant Maintenance of Database Integrity
[EN] To maintain integrity, constraint violations should be prevented or repaired. However, it may not be feasible to avoid inconsistency, or to repair all violations at once. Based on an abstract concept of violation measures, updates and repairs can be checked for keeping inconsistency bounded, such that integrity violations are guaranteed to never get out of control. This measure-based approach goes beyond conventional methods that are not meant to be applied in the presence of inconsistency. It also generalizes recently introduced concepts of inconsistency-tolerant integrity maintenance.Partially supported by FEDER and the Spanish grants TIN2009-14460-C03 and TIN2010-17139Decker, H. (2013). Measure-Based Inconsistency-Tolerant Maintenance of Database Integrity. Lecture Notes in Computer Science. 7693:149-173. https://doi.org/10.1007/978-3-642-36008-4_7S1491737693Abiteboul, S., Hull, R., Vianu, V.: Foundations of Databases. Addison-Wesley (1995)Abiteboul, S., Vianu, V.: A transaction-based approach to relational database specification. JACM 36(4), 758–789 (1989)Afrati, F., Kolaitis, P.: Repair checking in inconsistent databases: algorithms and complexity. In: 12th ICDT, pp. 31–41. ACM Press (2009)Arenas, M., Bertossi, L., Chomicki, J.: Consistent query answers in inconsistent databases. In: PODS 1999, pp. 68–79. ACM Press (1999)Arieli, O., Denecker, M., Bruynooghe, M.: Distance semantics for database repair. Ann. Math. Artif. Intell. 50, 389–415 (2007)Arni-Bloch, N., Ralyté, J., Léonard, M.: Service–Driven Information Systems Evolution: Handling Integrity Constraints Consistency. In: Persson, A., Stirna, J. (eds.) PoEM 2009. LNBIP, vol. 39, pp. 191–206. Springer, Heidelberg (2009)Bauer, H.: Maß- und Integrationstheorie, 2. Auflage. De Gruyter (1992)Besnard, P., Hunter, A.: Quasi-Classical Logic: Non-Trivializable Classical Reasoning from Inconsistent Information. In: Froidevaux, C., Kohlas, J. (eds.) ECSQARU 1995. LNCS, vol. 946, pp. 44–51. Springer, Heidelberg (1995)Bohanon, P., Fan, W., Flaster, M., Rastogi, R.: A Cost-Based Model and Effective Heuristic for Repairing Constraints by Value Modification. In: Proc. SIGMOD 2005, pp. 143–154. ACM Press (2005)Ceri, S., Cochrane, R., Widom, J.: Practical Applications of Triggers and Constraints: Success and Lingering Issues. In: Proc. 26th VLDB, pp. 254–262. Morgan Kaufmann (2000)Chakravarthy, U., Grant, J., Minker, J.: Logic-based Approach to Semantic Query Optimization. Transactions on Database Systems 15(2), 162–207 (1990)Chomicki, J.: Consistent Query Answering: Five Easy Pieces. In: Schwentick, T., Suciu, D. (eds.) ICDT 2007. LNCS, vol. 4353, pp. 1–17. Springer, Heidelberg (2006)Christiansen, H., Martinenghi, D.: On simplification of database integrity constraints. Fundamenta Informaticae 71(4), 371–417 (2006)Clark, K.: Negation as Failure. In: Gallaire, H., Minker, J. (eds.) Logic and Data Bases, pp. 293–322. Plenum Press (1978)Curino, C., Moon, H., Deutsch, A., Zaniolo, C.: Update Rewriting and Integrity Constraint Maintenance in a Schema Evolution Support System: PRISM++. PVLDB 4, 117–128 (2010)Dawson, J.: The compactness of first-order logic: From Gödel to Lindström. History and Philosophy of Logic 14(1), 15–37 (1993)Decker, H.: The Range Form of Databases and Queries or: How to Avoid Floundering. In: Proc. 5th ÖGAI. Informatik-Fachberichte, vol. 208, pp. 114–123. Springer (1989)Decker, H.: Drawing Updates From Derivations. In: Kanellakis, P.C., Abiteboul, S. (eds.) ICDT 1990. LNCS, vol. 470, pp. 437–451. Springer, Heidelberg (1990)Decker, H.: Extending Inconsistency-Tolerant Integrity Checking by Semantic Query Optimization. In: Bhowmick, S.S., Küng, J., Wagner, R. (eds.) DEXA 2008. LNCS, vol. 5181, pp. 89–96. Springer, Heidelberg (2008)Decker, H.: Answers That Have Integrity. In: Schewe, K.-D., Thalheim, B. (eds.) SDKB 2010. LNCS, vol. 6834, pp. 54–72. Springer, Heidelberg (2011)Decker, H.: Causes of the Violation of Integrity Constraints for Supporting the Quality of Databases. In: Murgante, B., Gervasi, O., Iglesias, A., Taniar, D., Apduhan, B.O. (eds.) ICCSA 2011, Part V. LNCS, vol. 6786, pp. 283–292. Springer, Heidelberg (2011)Decker, H.: Inconsistency-tolerant Integrity Checking based on Inconsistency Metrics. In: König, A., Dengel, A., Hinkelmann, K., Kise, K., Howlett, R.J., Jain, L.C. (eds.) KES 2011, Part II. LNCS, vol. 6882, pp. 548–558. Springer, Heidelberg (2011)Decker, H.: Partial Repairs that Tolerate Inconsistency. In: Eder, J., Bielikova, M., Tjoa, A.M. (eds.) ADBIS 2011. LNCS, vol. 6909, pp. 389–400. Springer, Heidelberg (2011)Decker, H.: Consistent Explanations of Answers to Queries in Inconsistent Knowledge Bases. In: Roth-Berghofer, T., Tintarev, N., Leake, D. (eds.) Explanation-aware Computing, Proc. IJCAI 2011 Workshop ExaCt 2011, pp. 71–80 (2011), http://exact2011.workshop.hm/index.phpDecker, H., Martinenghi, D.: Classifying integrity checking methods with regard to inconsistency tolerance. In: Proc. PPDP 2008, pp. 195–204. ACM Press (2008)Decker, H., Martinenghi, D.: Modeling, Measuring and Monitoring the Quality of Information. In: Heuser, C.A., Pernul, G. (eds.) ER 2009. LNCS, vol. 5833, pp. 212–221. Springer, Heidelberg (2009)Decker, H., Martinenghi, D.: Inconsistency-tolerant Integrity Checking. IEEE TKDE 23(2), 218–234 (2011)Decker, H., Muñoz-Escoí, F.D.: Revisiting and Improving a Result on Integrity Preservation by Concurrent Transactions. In: Meersman, R., Dillon, T., Herrero, P. (eds.) OTM 2010 Workshops. LNCS, vol. 6428, pp. 297–306. Springer, Heidelberg (2010)Dung, P., Kowalski, R., Toni, F.: Dialectic Proof Procedures for Assumption-based Admissible Argumentation. Artificial Intelligence 170(2), 114–159 (2006)Ebbinghaus, H.-D., Flum, J.: Finite Model Theory, 2nd edn. Springer (2006)Embury, S., Brandt, S., Robinson, J., Sutherland, I., Bisby, F., Gray, A., Jones, A., White, R.: Adapting integrity enforcement techniques for data reconciliation. Information Systems 26, 657–689 (2001)Enderton, H.: A Mathematical Introduction to Logic, 2nd edn. Academic Press (2001)Eiter, T., Fink, M., Greco, G., Lembo, D.: Repair localization for query answering from inconsistent databases. ACM TODS 33(2), article 10 (2008)Furfaro, F., Greco, S., Molinaro, C.: A three-valued semantics for querying and repairing inconsistent databases. Ann. Math. Artif. Intell. 51(2-4), 167–193 (2007)Grant, J., Hunter, A.: Measuring the Good and the Bad in Inconsistent Information. In: Proc. 22nd IJCAI, pp. 2632–2637 (2011)Greco, G., Greco, S., Zumpano, E.: A logical framework for querying and repairing inconsistent databases. IEEE TKDE 15(6), 1389–1408 (2003)Guessoum, A., Lloyd, J.: Updating knowledge bases. New Generation Computing 8(1), 71–89 (1990)Guessoum, A., Lloyd, J.: Updating knowledge bases II. New Generation Computing 10(1), 73–100 (1991)Gupta, A., Sagiv, Y., Ullman, J., Widom, J.: Constraint checking with partial information. In: Proc. PODS 1994, pp. 45–55. ACM Press (1994)Hunter, A.: Measuring Inconsistency in Knowledge via Quasi-Classical Models. In: Proc. 18th AAAI &14th IAAI, pp. 68–73 (2002)Hunter, A., Konieczny, S.: Approaches to Measuring Inconsistent Information. In: Bertossi, L., Hunter, A., Schaub, T. (eds.) Inconsistency Tolerance. LNCS, vol. 3300, pp. 191–236. Springer, Heidelberg (2005)Hunter, A., Konieczny, S.: Measuring inconsistency through minimal inconsistent sets. In: Brewka, G., Lang, J. (eds.) Principles of Knowledge Representation and Reasoning (Proc. 11th KR), pp. 358–366. AAAI Press (2008)Hunter, A., Konieczny, S.: On the measure of conflicts: Shapley Inconsistency Values. Artificial Intelligence 174, 1007–1026 (2010)Kakas, A., Mancarella, P.: Database updates through abduction. In: Proc. 16th VLDB, pp. 650–661. Morgan Kaufmann (1990)Kakas, A., Kowalski, R., Toni, F.: The role of Abduction in Logic Programming. In: Gabbay, D., Hogger, C., Robinson, J.A. (eds.) Handbook of Logic in Artificial Intelligence and Logic Programming, vol. 5, pp. 235–324. Oxford University Press (1998)Lee, S.Y., Ling, T.W.: Further improvements on integrity constraint checking for stratifiable deductive databases. In: Proc. VLDB 1996, pp. 495–505. Morgan Kaufmann (1996)Lehrer, K.: Relevant Deduction and Minimally Inconsistent Sets. Journal of Philosophy 3(2,3), 153–165 (1973)Mu, K., Liu, W., Jin, Z., Bell, D.: A Syntax-based Approach to Measuring the Degree of Inconsistency for Belief Bases. J. Approx. Reasoning 52(7), 978–999 (2011)Lloyd, J., Sonenberg, L., Topor, R.: Integrity constraint checking in stratified databases. J. Logic Programming 4(4), 331–343 (1987)Lozinskii, E.: Resolving contradictions: A plausible semantics for inconsistent systems. J. Automated Reasoning 12(1), 1–31 (1994)Ma, Y., Qi, G., Hitzler, P.: Computing inconsistency measure based on paraconsistent semantics. J. Logic Computation 21(6), 1257–1281 (2011)Martinenghi, D., Christiansen, H.: Transaction Management with Integrity Checking. In: Andersen, K.V., Debenham, J., Wagner, R. (eds.) DEXA 2005. LNCS, vol. 3588, pp. 606–615. Springer, Heidelberg (2005)Martinenghi, D., Christiansen, H., Decker, H.: Integrity Checking and Maintenance in Relational and Deductive Databases and Beyond. In: Ma, Z. (ed.) Intelligent Databases: Technologies and Applications, pp. 238–285. IGI Global (2006)Martinez, M.V., Pugliese, A., Simari, G.I., Subrahmanian, V.S., Prade, H.: How Dirty Is Your Relational Database? An Axiomatic Approach. In: Mellouli, K. (ed.) ECSQARU 2007. LNCS (LNAI), vol. 4724, pp. 103–114. Springer, Heidelberg (2007)Meyer, J., Wieringa, R. (eds.): Deontic Logic in Computer Science. Wiley (1994)Nicolas, J.M.: Logic for improving integrity checking in relational data bases. Acta Informatica 18, 227–253 (1982)Plexousakis, D., Mylopoulos, J.: Accommodating Integrity Constraints During Database Design. In: Apers, P.M.G., Bouzeghoub, M., Gardarin, G. (eds.) EDBT 1996. LNCS, vol. 1057, pp. 495–513. Springer, Heidelberg (1996)Rahm, E., Do, H.: Data Cleaning: Problems and Current Approaches. Data Engineering Bulletin 23(4), 3–13 (2000)Sadri, F., Kowalski, R.: A theorem-proving approach to database integrity. In: Minker, J. (ed.) Foundations of Deductive Databases and Logic Programming, pp. 313–362. Morgan Kaufmann (1988)Thimm, M.: Measuring Inconsistency in Probabilistic Knowledge Bases. In: Proc. 25th UAI, pp. 530–537. AUAI Press (2009)Vardi, M.: On the integrity of databases with incomplete information. In: Proc. 5th PODS, pp. 252–266. ACM Press (1986)Wijsen, J.: Database repairing using updates. ACM Trans. Database Syst. 30(3), 722–768 (2005
Copernicus Marine Service Ocean State Report
This is the final version. Available from Taylor & Francis via the DOI in this record
Numerical modelling of grain refinement around highly reactive interfaces in processing of nanocrystallised multilayered metallic materials by duplex technique
Microstructure evolution around highly reactive interfaces in processing of nanocrystallised multilayered metallic materials have been investigated and discussed in the present work. Conditions leading to grain refinement during co-rolling stage of the duplex processing technique are analysed using the multi-level finite element based numerical model combined with three-dimensional frontal cellular automata. The model was capable to simulate development of grain boundaries and changes of the boundary disorientation angle within the metal structure taking into account crystal plasticity formulation. Appearance of a large number of structural elements, identified as dislocation cells, sub-grains and new grains, has been identified within the metal structure as a result of metal flow disturbance and consequently inhomogeneous deformation around oxide islets at the interfaces during the co-rolling stage. These areas corresponded to the locations of shear bands observed experimentally using SEM-EBSD analysis. The obtained results illustrate a significant potential of the proposed modelling approach for quantitative analysis and optimisation of the highly refined non-homogeneous microstructures formed around the oxidised interfaces during processing of such laminated materials
From Architectured Materials to Large-Scale Additive Manufacturing
The classical material-by-design approach has been extensively perfected by materials scientists, while engineers have been optimising structures geometrically for centuries. The purpose of architectured materials is to build bridges across themicroscale ofmaterials and themacroscale of engineering structures, to put some geometry in the microstructure. This is a paradigm shift. Materials cannot be considered monolithic anymore. Any set of materials functions, even antagonistic ones, can be envisaged in the future. In this paper, we intend to demonstrate the pertinence of computation for developing architectured materials, and the not-so-incidental outcome which led us to developing large-scale additive manufacturing for architectural applications
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