• Women's Health Nursing
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• v.29 no.4
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• pp.302-316
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• 2023

Purpose: This study aimed to develop and validate a structural model for the quality of life (QoL) among high-risk pregnant women, based on Roy's adaptation model. Methods: This cross-sectional study collected data from 333 first-time mothers diagnosed with a high-risk pregnancy in two obstetrics and gynecology clinics in Cheonan, Korea, or participating in an online community, between October 20, 2021 and February 20, 2022. Structured questionnaires measured QoL, contextual stimuli (uncertainty), coping (adaptive or maladaptive), and adaptation mode (fatigue, state anxiety, antenatal depression, maternal identity, and marital adjustment). Results: The mean age of the respondents was 35.29±3.72 years, ranging from 26 to 45 years. The most common high-risk pregnancy diagnosis was gestational diabetes (26.1%). followed by preterm labor (21.6%). QoL was higher than average (18.63±3.80). Above-moderate mean scores were obtained for all domains (psychological/baby, 19.03; socioeconomic, 19.00; relational/spouse-partner, 20.99; relational/family-friends, 19.18; and health and functioning, 16.18). The final model explained 51% of variance in QoL in high-risk pregnant women, with acceptable overall model fit. Adaptation mode (β=-.81, p=.034) and maladaptive coping (β=.46 p=.043) directly affected QoL, and uncertainty (β=-. 21, p=.004), adaptive coping (β=.36 p=.026), and maladaptive coping (β=-.56 p=.023) indirectly affected QoL. Conclusion: It is essential to develop nursing interventions aimed at enhancing appropriate coping strategies to improve QoL in high-risk pregnant women. By reinforcing adaptive coping strategies and mitigating maladaptive coping, these interventions can contribute to better maternal and fetal outcomes and improve the overall well-being of high-risk pregnant women.

• Nuclear Engineering and Technology
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• v.35 no.4
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• pp.318-335
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• 2003

Expert judgment is frequently employed in the search for the solution to various engineering and decision-making problems where relevant data is not sufficient or where there is little consensus as to the correct models to apply. When expert judgments are required to solve the underlying problem, our main concern is how to formally derive their technical expertise and their personal degree of familiarity about the related questions. Formal methods for gathering judgments from experts and assessing the effects of the judgments on the results of the analysis have been developed in a variety of ways. The most important interest of such methods is to establish the robustness of an expert's knowledge upon which the elicitation of judgments is made and an effective trace of the elicitation process as possible as one can. While the resultant expert judgments can remain to a large extent substantiated with formal elicitation methods, their applicability however is often limited due to restriction of available resources (e.g., time, budget, and number of qualified experts, etc) as well as a scope of the analysis. For this reason, many engineering and decision-making problems have not always performed with a formal/structured pattern, but rather relied on a pertinent transition of the formal process to the simplified approach. The purpose of this paper is (a) to address some insights into the balanced use of formally structured and simplified approaches for the explicit use of expert judgments under resource constraints and (b) to discuss related decision-theoretic issues.

• Smart Media Journal
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• v.10 no.2
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• pp.16-21
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• 2021

Financial time series analysis plays a very important role economically and socially in modern society and is an important task affecting global development, but due to difficulties such as a lot of noise and uncertainty, financial time series analysis prediction is a difficult research topic. In this paper, we propose a market prediction method (MPIL) by converting unstructured data and structured data into images. For market prediction, it analyzes SNS and news data, which is unstructured data for n days, and converts the market data, which is structured data, to an image with the GADF algorithm, and predicts an ultra-short market that predicts the price of n+1 days through image learning. MPIL has an average accuracy of 56%, which is higher than the 50% average accuracy of the model that predicts the market with LSTM by using sentiment analysis used for existing market forecasting.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1816-1819
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• 1997

Using the vision system, robotic tasks in unstructured environments can be accompished, which reduces greatly the cost and steup time for the robotic system to fit to he well-defined and structured working environments. This paper proposes a dynamic control scheme for robot manipulator with eye-in-hand camera configuration. To perfom the tasks defined in the image plane, the camera motion Jacobian (image Jacobian) matrix is used to transform the camera motion to the objection position change. In addition, the dynamic learning controller is designed to improve the tracking performance of robotic system. the proposed control scheme is implemented for tasks of tracking moving objects and shown to outperform the conventional visual servo system in convergence and robustness to parameter uncertainty, disturbances, low sampling rate, etc.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.555-558
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• 1995

In designing the anti-sway controller for crane system in the industrial field, one of the basic problem is to keep the stability of system, even if the mathematical model of the plant is not exact and disturbance exists. Form this point of view, a two-degree-of-freedom(2DOF) servo controller effact to the system in which the integral compensation is effctive only when a modeling error and/or a disturbance input exist. In this paper, the change of load weight and variation of wire rope length considered as the structured uncertainty, and design the 2DOF servo contorller using independently the informations of reference signal and control output with both feedforward and feedback. The effectivenss is proved through the results for the anti-sway system in the system with the position control of trolley.

• The Journal of Korean Society for School & Community Health Education
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• v.14 no.1
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• pp.25-36
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• 2013

Objectives: The study was performed to investigate job-seeking stress for university students who have a major in healthcare. Methods: For the analysis, 10 fourth-year students who are willing to get a job were interviewed. Interviews were conducted from October 2011 to November 2011 for 2 weeks. The data were collected with semi-structured open-ended questions and analysed by the method of Consensual Qualitative Research(CQR). Results: The main reasons for the job-seeking stress for students were insufficient preparation for getting a job, uncertainty, anxiety, pressure, and age. A reinforcing factor for stress was family. Conclusions: Universities should provide educational, psychological, and economic supports to job-seeking students majoring healthcare because of their relatively fewer opportunities for getting a job compared to those who have a major in non-healthcare.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.284-287
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• 2001

This paper presents the robust control simulation of a composite beam using self-sensing actuators(SSA). The self-sensing actuator is a new concept for intelligent material, where a single piezoelectric element simultaneously functions as both a sensor and an actuator. In a practical implementation of the self-sensing actuator an electrical bridge circuit is used to measure strain. The circuit could provide significant information about strain in the element if it were well-balanced. Our aim is design a robust controller which guarantees that the performance of a self-sensing actuator is robust against perturbation of the bridge balance and to confirm the advantages of this technique. Simulation results show that the self-sensing actuator driven by the designed controller exhibits excellent performance in suppressing the vibration of a composite beam.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.6
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• pp.729-737
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• 1998

In this paper, using $\mu$ synthesis algorithm with structured uncertainty, we design controller and apply it for the Two-Inertia resonance(TMS: Two Mass Spring) system. The TMS system is one of the simplest models which generate a torsional vibration. In this system, it is required to design a controller achieving the control performance while suppressing the torsional vibration. Furthermore, when vibration frequency for the system is varying by reason of parameter variations, we should consider parameter variations in controller design. Then, we design two other controller schemes of the PI controller and the standard $H_{\infty}$ controller and compare these controllers with the controller designed by the $\mu$ synthesis robust control method by using simulations and experiments.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.205-210
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• 2004

This paper deals with rule extraction from data using rough set theory. We construct the rule base in a hierarchical granulation structure by applying core as a classification criteria at each level. When more than one core exist, the coverage is used for the selection of an appropriate one among them to increase the classification rate and accuracy. In Addition, a probabilistic approach is suggested so that the partially useful information included in inconsistent data can be contributed to knowledge reduction in order to decrease the effect of the uncertainty or vagueness of data. As a result, the proposed method yields more proper and efficient rule base in compatability and size. The simulation result shows that it gives a good performance in spite of very simple rules and short conditionals.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.22-22
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• 2000

This study investigates the use of mixed $H_2/H_{\infty}$ and $\mu$-synthesis to construct a robust controller for the benchmark problem. The model treated in the problem is a coupled three-inertia system which reflects the dynamics of mechanical vibrations. We, first adopt the mixed $H_2/H_{\infty}$ the to design a feedback controller K(s). Next, $\mu$-synthesis method is applied to the overall system to make use of structured parametric uncertainty.