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Yasunobu Yamashita,Kensuke Tanioka,Yuki Kawaji,Takashi Tamura,Junya Nuta,Keiichi Hatamaru,Masahiro Itonaga,Takeichi Yoshida,Yoshiyuki Ida,Takao Maekita,Mikitaka Iguchi,Masayuki Kitano 거트앤리버 소화기연관학회협의회 2020 Gut and Liver Vol.14 No.5
Background/Aims: Rosemont classification (RC) with endoscopic ultrasonography (EUS) is important for diagnosing chronic pancreatitis (CP) but is based only on subjective judgement. EUS shear wave measurement (EUS-SWM) is a precise modality based on objective judgment, but its usefulness has not been extensively studied yet. This study evaluated the utility of EUS-SWM for diagnosing CP and estimating CP severity by determining the presence of endocrine dysfunction along with diabetes mellitus (DM). Methods: Between June 2018 and December 2018, 52 patients who underwent EUS and EUS-SWM were classified into two groups according to RC: non-CP (indeterminate CP and normal) and CP (consistent and suggestive of CP). The EUSSWM value by shear wave velocity was evaluated with a median value. The EUS-SWM value was compared with RC and the number of EUS features. The diagnostic accuracy and cutoff value of EUS-SWM for CP and DM and its sensitivity and specificity were calculated. Results: The EUS-SWM value significantly positively correlated with the RC and the number of EUS features. The EUS-SWM values that were consistent and suggestive of CP were significantly higher than that of normal. The area under the receiver operating characteristic (AUROC) curve for the diagnostic accuracy of EUS-SWM for CP was 0.97. The cutoff value of 2.19 had 100% sensitivity and 94% specificity. For endocrine dysfunction in CP, the AUROC was 0.75. The cutoff value of 2.78 had 70% sensitivity and 56% specificity. Conclusions: EUS-SWM provides an objective assessment and can be an alternative diagnostic tool for diagnosing CP. EUS-SWM may also be useful for predicting the presence of endocrine dysfunction.
Model Predictive Control based on ARX Models
Junichiro Kon,Yoshiyuki Yamashita 제어로봇시스템학회 2010 제어로봇시스템학회 국제학술대회 논문집 Vol.2010 No.10
This study proposes linear model predictive control (MPC) based on ARX models in incremental form. Feedforward action for external disturbance can eliminate the effect of unmeasured disturbance, which is popular in process industries. Simulation example illustrates the robust performance of the proposed approach.
Nguyen, Viet Ha,Yamashita, Yoshiyuki,Lee, Moonyong The Society of Chemical Engineers, Japan 2011 Journal of chemical engineering of Japan Vol.44 No.5
<P>Constrained optimal control using an industrial three term controller is remarkably challenging to achieve, even for processes with simple dynamics. In this paper, an optimization based practical approach for the design of an industrial PI controller is developed for optimal servo control of integrating processes with operational constraints. The constrained optimal servo problem is formulated and converted into a simple analytical form, which allows for graphical analysis to be used to find the global optimum, by using a clever parameterization. The Lagrangian multiplier method is then applied to analytically find the optimal PI parameters by solving the equivalent unconstrained optimization problem. The developed method minimizes the optimal performance measure and also explicitly deals with the important control constraints, such as the maximum allowable limits in the controlled variable, the manipulated variable, and the rate of change of the manipulated variable. The proposed method is demonstrated through the example of a CSTR level control system.</P>