• Journal of the Korean Arthroscopy Society
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• v.2 no.2
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• pp.168-172
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• 1998

Discoid lateral menisci were common morphological anomaly and several classifications were proposed. Watanabe et al classified all discoid menisci, as seen arthroscopically, into three types 1) complete 2) incomplete and 3) Wrisberg ligament type. The purpose of this study is to report a rare case of both painful snapping knee joints in 6 year-old female. On arthroscopic examination, complete lateral discoid meniscus which consisted of taut Wrisberg ligament and intact tibial insertion of posterior horn was found, and abnormal anterior cruciate ligament(ACL) which has expanded femoral origin over the posterior articular surface of lateral femoral condyle was also found. At the time of arthroscopic surgery, hypertrophied high-riding Wrisberg ligament was resected, and expanded femoral origin of the anterior cruciate ligament was partially resected nearly to normal margin, and discoid lateral meniscus was saucerized. After these procedures, abnormal snapping sound was disappeared in full range of motion. On the follow-up examination after 1 year, pain and snapping sound were disappeared and any instability and limping were not found.

• Korean Journal of Cognitive Science
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• v.4 no.1
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• pp.177-212
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• 1993

My research is based on the parser for ill-formed input by Mellish in a paper in ACL 27th meeting Proceedings. 1989. My system is composed of two parsers:WFCP and IFCP. When WFCP fails to give the parse tree for the input sentence, the sentence is identified as ill-formed and is parsed by IFCP for error detection and recovery at the syntactic level. My system is indendent of grammatical rules. It does not take into account semantic ill-formedness. My system uses a grammar composed of 25 context-free rules. My system consistes of two major parsing strategies:top-down expection and bottem-up satisfaction. With top-down expectation. rules are retrieved under the inference condition and expaned by inactive arcs. When doing bottom-up parsing. my parser used two modes:Left-Right parsing and Right-to-Left parsing. My system repairs errors sucessfully when the input contains an omitted word or an unknown word substitued for a valid word. Left- corner and right-corner errors are more easily detected and repaired than ill-formed senteces where the error is in teh middle. The deviance note. with repair details, is kept in new inactive arcs which are generated by the error correction procedure. The implementation of my system is quite different from Mellish's. When rules are invoked. my system invokes all rules with minimal inference. My bottom up parsing strategy uses Left-to-Right mode and Right-to-Left mode. My system is bottom-up-parsing-oriented like the chart parser. Errors are repaired in two ways:using top-down hypothesis, and using Need-Chart which keeps the information of expectation and complection of expanded goals by rules. To reduce the number of top-down cycles. all rules are invoked simultaneously and this invocation information is kept in Need-Chart. This idea will be extended for the implementation of multiple error recovery system.