• Journal of Preventive Medicine and Public Health
• /
• v.55 no.5
• /
• pp.428-435
• /
• 2022

Objectives: The Indonesian Ministry of Health launched isoniazid preventive therapy (IPT) in 2016, with general practitioners (GPs) at the frontline of this program. However, the extent to which GPs have internalized this program remains uncertain. The aim of this study was to identify the knowledge and attitudes of GPs towards the IPT program in Indonesia. Methods: This study used an online, self-administered questionnaire distributed via e-mail and social messaging services. A logistic regression model was employed to identify the explanatory variables influencing the level of knowledge and attitudes toward IPT among GPs in Indonesia. An empirical analysis was conducted separately for each response variable (knowledge and attitudes). Results: Of the 418 respondents, 128 (30.6%) had a good knowledge of IPT. Working at a public hospital was the only variable associated with good knowledge, with an adjusted odds ratio (aOR) of 1.69 (95% confidence interval [CI], 1.02 to 2.81). Furthermore, 279 respondents (66.7%) had favorable attitudes toward IPT. In the adjusted logistic regression analysis, good knowledge (aOR, 0.55; 95% CI, 0.34 to 0.89), 1-5 years of work experience (aOR, 2.09; 95% CI, 1.21 to 3.60), and having experienced IPT training (aOR, 0.48; 95% CI, 0.25 to 0.93), were significantly associated with favorable attitudes. Conclusions: In general, GPs in Indonesia had favorable attitudes toward IPT. However, their knowledge of IPT was limited. GPs are an essential element of the IPT program in the country, and therefore, adequate information dissemination to improve their understanding is critical for the long-term viability and quality of the IPT program in Indonesia.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10a
• /
• pp.283-286
• /
• 1996

This study suggests a new methodology for the fault diagnosis based on the signed digraph in developing the fault diagnosis system of a boiler plant. The suggested methodology uses the new model, fault-effect tree. The SDG has the advantage, which is simple and graphical to represent the causal relationship between process variables, and therefore is easy to understand. However, it cannot handle the broken path cases arisen from data uncertainty as it assumes consistent path. The FET is based on the SDG to utilize the advantages of the SDG, and also covers the above problem. The proposed FET model is constructed by clustering of measured variables, decomposing knowledge base and searching the fault propagation path from the possible faults. The search is performed automatically. The fault diagnosis system for a boiler plant, ENDS was constructed using the expert system shell G2 and the advantages of the presented method were confirmed through case studies.

• International Journal of Control, Automation, and Systems
• /
• v.4 no.2
• /
• pp.178-186
• /
• 2006

We propose and analyze a robust adaptive fuzzy controller for nonlinear systems without a priori knowledge of the sign of the input gain function. No assumptions are made about the type of nonlinearities of the system, except that such nonlinearities are smooth. The uncertain nonlinearities are captured by the fuzzy systems that have been proven to be universal approximators. The proposed control scheme completely overcomes the singularity problem that occurs in the indirect adaptive feedback linearizing control. Projection in the estimated parameters and switching in the control input are both not required. The stability of the closed-loop system is guaranteed in the Lyapunov viewpoint.

• Proceedings of the KIEE Conference
• /
• 1991.07a
• /
• pp.678-681
• /
• 1991

In this paper, we propose a robust linear time-invariant feedback compensator design methodology for multivariable system which have both matched and mismatched uncertainties. In order to attack the problem of designing robust compensators guaranteeing uniform ultimate boundedness of every closed-loop system response within an arbitrarily small ball centered at the zero state based solely on the knowledge of the upper norm-bounds of uncertainties, we use an approach based upon the comparison theorem which is an effective approach in studying augmented feedback control systems with both mismatched and matched uncertainties. Through the approach, we draw some sufficient conditions for robust stability, and we give a simple example.

• Journal of the Korean Society of Safety
• /
• v.14 no.2
• /
• pp.52-61
• /
• 1999

This paper proposes the application of fuzzy control for high performance control of induction motor using electric vehicles. A fuzzy controller converts a set of liguistic rules based on expert knowledge into a automatic control strategy. Such controllers have often been found superior to conventional controllers especially when information being processed is inexact and uncertain. A system with fast torque response is very beneficial in applications where direct self control (DSC) is highly desirable. The response of DSC is slower during startup and during change in command torque. Fuzzy control is used for implementation of DSC to improve its slow response. Simulation implementation of the fuzzy logic controller was carried out to verify the behavior of the controller. The simulation results with fuzzy control are compared with those of the conventional DSC. The starting flux and torque response and the responses to the step changes in command torque with fuzzy implementation show a considerable improvement over the conventional control. The steady state responses in both the cases are the same.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.20 no.8
• /
• pp.42-47
• /
• 2006

In this paper, we propose a sliding mode control with the bound estimation for robot manipulators without requiring exact knowledge of the robot dynamics. For the bound estimation, the upper bound of the uncertain nonlinearities of robot dynamics is represented as a Fredholm integral equation of the first kind and we propose an adaptive scheme which is only dependent on the sliding surface function. Also, we prove the asymptotic stability for the robot systems using two important properties in the robot dynamics: skew-symmetry and positive-definiteness of robot parameters.

• Journal of KIISE:Computing Practices and Letters
• /
• v.15 no.12
• /
• pp.978-982
• /
• 2009

This paper proposes a potential-based reinforcement learning, called "RLs-CBDT", which combines multiple RL agents and case-base decision theory designed for decision making in uncertain environment as an expert knowledge in RL. We empirically show that RLs-CBDT converges to an optimal policy faster than pre-existing RL algorithms through a Tetris experiment.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.39 no.4
• /
• pp.386-392
• /
• 1990

This paper discribes a sonar-based certainty grid, the probabilistic representation of the uncertain and incomplete sensor knowledge, for autonomous mobile robot navigation. We use sonar sensor range data to build a map of the robot's surroundings. This range data provides information about the location of the objects which may exist in front of the sensor. From this information, we can compute the probability of being occupied and that of being empty for each cell. In this paper, a new method using Bayesian formula is introduced, which enables us to overcome some difficulties of the Ad-Hoc formula that has been the only way of updating the grids. This new formula can be applied to other kinds of sensors as well as sonar sensor. The validity of this formula in the real world is verified through simulation and experiment. This paper also shows that a wide angle sensor such as sonar sensor can be used effectively to identify the empty area, and the simultaneous use of multiple sensors and fusion in a certainty grid can improve the quality of the map.

• 제어로봇시스템학회:학술대회논문집
• /
• 1994.10a
• /
• pp.189-194
• /
• 1994

Adaptive control systems based upon the command generator tracker(CGT) approach have attracted considerable interest because of the simple structure of its adaptive controller. Some attempts to such improve the adaptive control algorithm, for the sake of the application to broader class of plants, are made. Recently, Su and Sobel(1992) proposed that those schemes can be treated by an unified theory using a metasystem representation with some types of supplementary dynamics. However, in their method, it is difficult to find the dynamic compensator, which is proper and output feedback stabilizable, for the uncertain plant. This paper proposes a new design method of such supplementary dynamics and some parameters of adaptive control system for linear time invariant SISO plants. The method gives a concrete and systematic design method using only a few priori knowledge of the plant.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1997.10a
• /
• pp.181-184
• /
• 1997

This paper propose the systematic procedure of the fuzzy model based controller for the continuous nonlinear system. Fuzzy controller have been successfully applied to many uncertain and complex industrial plants. The design of the fuzzy controller mainly depends on the knowledge from the expert who are familiar with the plant by trial and error. Therefore we need more systematic approach to the design of the fuzzy controller. In this paper, we design fuzzy model based controller applied to the nonlinear system. Unlike the design procedures reported in[8] and[9], we use the nonlinear process directly in designing the controller. This controller has been successfully applied to an inverted pendulum.