• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 하계학술대회 논문집 B
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• pp.403-405
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• 1997

In this paper, a navigation system based on fuzzy logic controllers is developed for a mobile robot in an unknown environment. The structure of this fuzzy navigation system features sensor system, fuzzy controllers for motion planning and the motion control system for real-time execution.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 하계학술대회 논문집 B
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• pp.561-563
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• 1997

In this paper, we identified the Black-box system with serious nonlinerity and fast dynamics using Neural Network. This NN have new structure and learned by RLS. It identify system in real-time without priori data. We use this NN to 7-DOF vehicle identification.

• 한국농공학회:학술대회논문집
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• 한국농공학회 1999년도 Proceedings of the 1999 Annual Conference The Korean Society of Agricutural Engineers
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• pp.618-624
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• 1999

For many soft ground embankment projects , instrumentation programs for stability and settlement management is being essential . This usually leads to generate large volume of data, which can be used for further research. Database technique is most effective method for data management . Data produced by soft ground embankment instrumentation can not be used by itself but must be reproduced using geotechnical analysis technique. In this study, a intelligent database system for softground called IDSIM was developed to examine applicability intellgent database. . The IDSIM analysis instrumentation data automatically and present results by Web/DB interface successfully.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2002년도 가을 학술발표회 논문집
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• pp.697-704
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• 2002

This paper presents the results of instrumentation of a two-level of soil-reinforced segmental retaining wall. Instrumentation items include the lateral wall displacements and the geogrid strains at several locations. The instrumentation is still long carried in order to examine long-term behavior. The result indicate that the upper wall has a significant effect on the behavior of the lower wall doubling the wall moved. The wall also exhibits significant post-construction movements that had ceased several months after the wall completed. The implication of the findings from this study was discussed in great detail.

• Journal of Korean Neurosurgical Society
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• 제61권3호
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• pp.415-423
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• 2018

Objective : To identify the perioperative factors associated with instrument failure in patients undergoing a partial corpectomy with instrumentation (PCI) for spinal metastasis. Methods : We assessed the one hundred twenty-four patients with who underwent PCI for a metastatic spine from 1987 to 2011. Outcome measure was the risk factor related to implantation failure. The preoperative factors analyzed were age, sex, ambulation, American Spinal Injury Association grade, bone mineral density, use of steroid, primary tumor site, number of vertebrae with metastasis, extra-bone metastasis, preoperative adjuvant chemotherapy, and preoperative spinal radiotherapy. The intraoperative factors were the number of fixed vertebrae, fixation in osteolytic vertebrae, bone grafting, and type of surgical approach. The postoperative factors included postoperative adjuvant chemotherapy and spinal radiotherapy. This study was supported by the National Research Foundation grant funded by government. There were no study-specific biases related to conflicts of interest. Results : There were 15 instrumentation failures (15/124, 12.1%). Preoperative ambulatory status and primary tumor site were not significantly related to the development of implant failure. There were no significant associations between insertion of a bone graft into the partial corpectomy site and instrumentation failure. The preoperative and operative factors analyzed were not significantly related to instrumentation failure. In univariable and multivariable analyses, postoperative spinal radiotherapy was the only significant variable related to instrumentation failure (p=0.049 and 0.050, respectively). Conclusion : When performing PCI in patients with spinal metastasis followed by postoperative spinal radiotherapy, the surgeon may consider the possibility of instrumentation failure and find other strategies for augmentation than the use of a bone graft for fusion.

• Restorative Dentistry and Endodontics
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• 제45권2호
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• pp.21.1-21.12
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• 2020

The aim of this article was to review age-dependent clinical recommendations for appropriate root canal instrumentation techniques. A comprehensive narrative review of canal morphology, the structural characteristics of dentin, and endodontic outcomes at different ages was undertaken instead of a systematic review. An electronic literature search was carried out, including the Medline (Ovid), PubMed, and Web of Science databases. The searches used controlled vocabulary and free-text terms, as follows: 'age-related root canal treatment,' 'age-related instrumentation,' 'age-related chemo-mechanical preparation,' 'age-related endodontic clinical recommendations,' 'root canal instrumentation at different ages,' 'geriatric root canal treatment,' and 'pediatric root canal treatment.' Due to the lack of literature with practical age-based clinical recommendations for an appropriate root canal instrumentation technique, a narrative review was conducted to suggest a clinical algorithm for choosing the most appropriate instrumentation technique during root canal treatment. Based on the evidence found through the narrative review, an age-related clinical algorithm for choosing appropriate instrumentation during root canal treatment was proposed. Age affects the morphology of the root canal system and the structural characteristics of dentin. The clinician's awareness of root canal morphology and dentin characteristics can influence the choice of instruments for root canal treatment.

• 한국전자현미경학회:학술대회논문집
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• 한국현미경학회 2003년도 제34차 춘계학술대회
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• pp.39-39
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• 2003

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 1997년도 동계 학술대회 논문집
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• pp.206-212
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• 1997

• Journal of Biosystems Engineering
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• 제42권2호
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• pp.126-126
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• 2017

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제14권2호
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• pp.73-83
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• 2014

Many recent theoretical developments in the field of machine learning and control have rapidly expanded its relevance to a wide variety of applications. In particular, a variety of portfolio optimization problems have recently been considered as a promising application domain for machine learning and control methods. In highly uncertain and stochastic environments, portfolio optimization can be formulated as optimal decision-making problems, and for these types of problems, approaches based on probabilistic machine learning and control methods are particularly pertinent. In this paper, we consider probabilistic machine learning and control based solutions to a couple of portfolio optimization problems. Simulation results show that these solutions work well when applied to real financial market data.