FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2892917419> ?p ?o ?g. }

• W2892917419 endingPage "1585" @default.
• W2892917419 startingPage "1571" @default.
• W2892917419 abstract "Accurate yield prediction in integrated circuit manufacturing enables accurate estimation of production cost and early detection of processing problems. It is known that defects tend to be clustered and a chip is likely to be defective if its neighbors are defective. This neighborhood effect is not well captured in traditional yield modeling approaches. We propose a new yield prediction model, called adjacency-clustering which addresses, for the first time, the neighborhood effect, and delivers prediction results that are significantly better than state-of-the-art methods. Adjacency-clustering (AC) model is a form of the Markov random field minimum energy model (MRF) that is primarily known in the context of image segmentation. AC model is a novel use of MRF for identifying defect patterns that enable diagnosis of failure causes in the manufacturing process. In this paper we utilize the defect patterns obtained by the AC model for yield prediction. We compare the performance of the AC model to that of leading yield prediction models including the Poisson, the negative binomial, the Poisson regression, and negative binomial regression models, on real data sets and on simulated data sets. The results demonstrate that the adjacency-clustering model captures the neighborhood effect and delivers superior prediction accuracy. Moreover, the concept and methodology of adjacency-clustering are not limited to integrated circuit manufacturing. Rather, it is applicable in any context where a neighborhood effect is present, such as disease risk mapping and energy consumption prediction. The e-companion is available at https://doi.org/10.1287/opre.2018.1741 ." @default.
• W2892917419 created "2018-10-05" @default.
• W2892917419 creator A5007210055 @default.
• W2892917419 creator A5085640376 @default.
• W2892917419 date "2018-11-01" @default.
• W2892917419 modified "2023-09-25" @default.
• W2892917419 title "Adjacency-Clustering and Its Application for Yield Prediction in Integrated Circuit Manufacturing" @default.
• W2892917419 cites W143236119 @default.
• W2892917419 cites W1965086212 @default.
• W2892917419 cites W1973972741 @default.
• W2892917419 cites W1979091955 @default.
• W2892917419 cites W1985135956 @default.
• W2892917419 cites W1985914844 @default.
• W2892917419 cites W1986096063 @default.
• W2892917419 cites W2002087022 @default.
• W2892917419 cites W2013347084 @default.
• W2892917419 cites W2013469283 @default.
• W2892917419 cites W2014079126 @default.
• W2892917419 cites W2016973091 @default.
• W2892917419 cites W2020286945 @default.
• W2892917419 cites W2020607720 @default.
• W2892917419 cites W2024879715 @default.
• W2892917419 cites W2035969035 @default.
• W2892917419 cites W2036331394 @default.
• W2892917419 cites W2046045084 @default.
• W2892917419 cites W2051946048 @default.
• W2892917419 cites W2056367065 @default.
• W2892917419 cites W2060300972 @default.
• W2892917419 cites W2065579159 @default.
• W2892917419 cites W2069948346 @default.
• W2892917419 cites W2080375462 @default.
• W2892917419 cites W2083474207 @default.
• W2892917419 cites W2085391922 @default.
• W2892917419 cites W2090359754 @default.
• W2892917419 cites W2098054201 @default.
• W2892917419 cites W2104441235 @default.
• W2892917419 cites W2104550562 @default.
• W2892917419 cites W2107884096 @default.
• W2892917419 cites W2108644900 @default.
• W2892917419 cites W2109854662 @default.
• W2892917419 cites W2111081435 @default.
• W2892917419 cites W2111991188 @default.
• W2892917419 cites W2112222533 @default.
• W2892917419 cites W2116935750 @default.
• W2892917419 cites W2131791960 @default.
• W2892917419 cites W2133240300 @default.
• W2892917419 cites W2147965279 @default.
• W2892917419 cites W2155475871 @default.
• W2892917419 cites W2156952342 @default.
• W2892917419 cites W2165899972 @default.
• W2892917419 cites W2167943787 @default.
• W2892917419 cites W2461051203 @default.
• W2892917419 cites W2573548085 @default.
• W2892917419 cites W3102998284 @default.
• W2892917419 cites W4231856837 @default.
• W2892917419 cites W4244769743 @default.
• W2892917419 doi "https://doi.org/10.1287/opre.2018.1741" @default.
• W2892917419 hasPublicationYear "2018" @default.
• W2892917419 type Work @default.
• W2892917419 sameAs 2892917419 @default.
• W2892917419 citedByCount "7" @default.
• W2892917419 countsByYear W28929174192019 @default.
• W2892917419 countsByYear W28929174192020 @default.
• W2892917419 countsByYear W28929174192021 @default.
• W2892917419 countsByYear W28929174192022 @default.
• W2892917419 crossrefType "journal-article" @default.
• W2892917419 hasAuthorship W2892917419A5007210055 @default.
• W2892917419 hasAuthorship W2892917419A5085640376 @default.
• W2892917419 hasConcept C100906024 @default.
• W2892917419 hasConcept C105795698 @default.
• W2892917419 hasConcept C110484373 @default.
• W2892917419 hasConcept C11413529 @default.
• W2892917419 hasConcept C124101348 @default.
• W2892917419 hasConcept C144024400 @default.
• W2892917419 hasConcept C149923435 @default.
• W2892917419 hasConcept C151730666 @default.
• W2892917419 hasConcept C153180895 @default.
• W2892917419 hasConcept C154945302 @default.
• W2892917419 hasConcept C199335787 @default.
• W2892917419 hasConcept C202444582 @default.
• W2892917419 hasConcept C2779343474 @default.
• W2892917419 hasConcept C2908647359 @default.
• W2892917419 hasConcept C33923547 @default.
• W2892917419 hasConcept C41008148 @default.
• W2892917419 hasConcept C73269764 @default.
• W2892917419 hasConcept C73555534 @default.
• W2892917419 hasConcept C86803240 @default.
• W2892917419 hasConcept C89600930 @default.
• W2892917419 hasConcept C9652623 @default.
• W2892917419 hasConceptScore W2892917419C100906024 @default.
• W2892917419 hasConceptScore W2892917419C105795698 @default.
• W2892917419 hasConceptScore W2892917419C110484373 @default.
• W2892917419 hasConceptScore W2892917419C11413529 @default.
• W2892917419 hasConceptScore W2892917419C124101348 @default.
• W2892917419 hasConceptScore W2892917419C144024400 @default.
• W2892917419 hasConceptScore W2892917419C149923435 @default.
• W2892917419 hasConceptScore W2892917419C151730666 @default.
• W2892917419 hasConceptScore W2892917419C153180895 @default.

• next