• Journal of Korean Public Health Nursing
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• v.24 no.2
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• pp.237-248
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• 2010

Purpose: The study assessed the effects of a 12-session empowering program to promote health quality of life, decision making self-efficacy, self-care competency, and reasonable medical care utilization among low income women households in one rural area. Methods: A quasi-experimental, one-group pre-posttest design was employed. A total of 28 women enrolled as medicaid recipients in the Public Health Center of W city agreed to participate. The empowering program consisted of 12 sessions addressing health education for self-care of disease, medication management, and counseling for psycho-social support. The intervention was delivered by five nurses and one social worker. Women completed a structured questionnaire measuring the study variables with demographic characteristic before and after the intervention. Data were analyzed by PAWS Statistics 17 utilizing descriptive statistics and paired t-test. Results: After the intervention, significant increases were evident in participant health quality of life (t=-5.83, p<.001), decision making self-efficacy (t=-4.86, p<.001), self-care competency (t=-8.16, p<.001), and reasonable medical care utilization (t=-3.97, p<.001). Conclusion: The 12-session empowering program on health quality of life as well as self-care competency was effective when delivered to low income women households. Further studies with larger numbers of participants and a control group are necessary to validate the results.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.367-376
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• 2022

The purpose of this study is to investigate the current status of work performance of public health doctors(PHDs) involved in quarantine of COVID-19, and to suggest a plan to support PHDs for effective national epidemic prevention and control in the future. As a result of the study, it was found that PHDs mainly performed sample collection, interview, and treatment. 39% of PHDs worked in places without negative pressure facilities, and personal protective equipment and welfare support were poor. In addition, it was investigated that they experienced high-risk infectious diseases, mental distress, exclusion from the decision-making process, conflicts with officials, problems with work guidelines, and lack of prior education. For effective infectious disease management, it is necessary to assign appropriate ranks and to participate in the decision-making process for quarantine, to specify appropriate compensation and regulations, to education, and to support mental health.

• Journal of Environmental Impact Assessment
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• v.5 no.1
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• pp.47-60
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• 1996

Nitrate contamination problems from groundwater supplies have been reported throughout many countries in the world, including Korea. Nitrate salts can induce methemoglobinemia and possibly human gastric cancer. To reduce human health risk from nitrate in groundwater supplies, several nitrate risk-management strategies can be developed based on the acceptable level of human health risk, the reasonableness of nitrate-control cost, and the technical feasibility of nitrate-control methods. However, due to a lack of available information, assessing risk, cost and technical feasibility contains elements of uncertainty. In the present paper, a nitrate risk-management methodology using fuzzy sets in combination with a multiobjective decision-making (MODM) technique is developed to assist decision makers in evaluating, with uncertain information, various nitrate risk-management strategies in order to decide a proper strategy.

• Journal of the Korea Society of Computer and Information
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• v.11 no.2 s.40
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• pp.145-151
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• 2006

In conjunction with the rapid progress of IT(information technology) an increasing amount of data are being generated. The amount of new data is so big and the type of new data generated from clients or sensor devices needed to be in ubiquitous environment is so various that it is hard to manage and control them. Especially data to be occurred in ubiquitous environment are generated through PDA(personal digital assistant) smart phone, mobile device or sensor units etc. Therefore, to manage and control them generated from ubiquitous devices for decision making, we can use data warehouse as an integrated storage. A data warehouse integrates and aggregates data of several different DBMS into one DBMS. Also the updated data from source data have to be effectively propagated to the data warehouse. Therefore, in this paper, we proposed a mode) for an exact and efficient data management methodology in new IT paradigm environment, ubiquitous computing environment, to apply updated data on the warehouse to make decision. We also show brief result compared to conventional methodology.

• Physical Therapy Korea
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• v.27 no.1
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• pp.53-62
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• 2020

Background: Pregnancy-related low back pain (PLBP) has fewer systematic guidelines than pregnancy-related pelvic girdle pain, previous studies have not evaluated physical therapy for this ailment in Korea. Objects: We aimed to provide a detailed account of clinical decision making by Korean physiotherapists while treating PLBP. Methods: In total, 955 questionnaires were distributed mainly in places of continuing education held by the Korean Physical Therapy Association from April to July 2019. The same questionnaire was posted on a website used by physiotherapists. We collected subject information, a specific Vignette typically represent symptoms of PLBP, and responses to multiple questions about decision making, subjective recognition and interest level in the field of women's health physiotherapy (WHPT). Results: The overall response rate was 56% (n = 537); of these, responses to 520 questionnaires were analyzed. Most respondents chose various combinations of physical therapy methods. There were significant differences in subjective recognition levels of WHPT according to gender (p < 0.05), age (p < 0.01), education level (p < 0.01), and clinical experience (p < 0.05). There were significant differences in interest according to gender (p < 0.01) and education level (p < 0.01). With respect to the types of treatment, significant differences were noted in selective rates for "manual therapy", "pain control", and "supportive devices" based on gender. Manual therapy tended to be chosen more with increasing age and clinical experience. With increased education level, there were fewer choices for the use of pain control. Conclusion: This is the first data on how Korean physiotherapists manage PLBP patients using the vignette method. We were able to recognize the Korean physical therapist's decision on PLBP patients, and observed statistically significant correlations. This may aid in developing future research and education plans in the WHPT field.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.12
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• pp.1169-1172
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• 2006

The prices of chemical products are fluctuated by several factors. The chemical companies can't predict and be ready to all of these changes, so they are exposed to the risk of a profit fluctuation. But they can reduce this risk by making a well-diversified product portfolio. This problem can be thought as the optimization of the product portfolio. We assume that the profits come from the 'spread' between a naphtha and a chemical product. We calculate a mean and a variation of each spread and develop an automatic module to calculate the optimal portion of each product. The theory is based on the Markowitz portfolio management. It maximizes the expected return while minimizing the volatility. At last we draw an investment selection curve to compare each alternative and to demonstrate the superiority. And we suggest that an investment selection curve can be a decision-making tool.

• International Journal of High-Rise Buildings
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• v.12 no.3
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• pp.225-234
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• 2023

Even at this point in the era of digital transformation, we are still facing many problems in the safety sector that cannot prevent the occurrence or spread of human casualties. When you are in an unexpected emergency, it is often difficult to respond only with human physical ability. Human casualties continue to occur at construction sites, manufacturing plants, and multi-use facilities used by many people in everyday life. If you encounter a situation where normal judgment is impossible in the event of an emergency at a life site where there are still many safety blind spots, it is difficult to cope with the existing manual guidance method. New variable guidance technology, which combines artificial intelligence and digital twin, can make it possible to prevent casualties by processing large amounts of data needed to derive appropriate countermeasures in real time beyond identifying what safety accidents occurred in unexpected crisis situations. When a simple control method that divides and monitors several CCTVs is digitally converted and combined with artificial intelligence and 3D digital twin control technology, intelligence augmentation (IA) effect can be achieved that strengthens the safety decision-making ability required in real time. With the enforcement of the Serious Disaster Enterprise Punishment Act, the importance of distributing a smart location guidance system that urgently solves the decision-making delay that occurs in safety accidents at various industrial sites and strengthens the real-time decision-making ability of field workers and managers is highlighted. The smart location guidance system that combines artificial intelligence and digital twin consists of AIoT HW equipment, wireless communication NW equipment, and intelligent SW platform. The intelligent SW platform consists of Builder that supports digital twin modeling, Watch that meets real-time control based on synchronization between real objects and digital twin models, and Simulator that supports the development and verification of various safety management scenarios using intelligent agents. The smart location guidance system provides on-site monitoring using IoT equipment, CCTV-linked intelligent image analysis, intelligent operating procedures that support workflow modeling to immediately reflect the needs of the site, situational location guidance, and digital twin virtual fencing access control technology. This paper examines the limitations of traditional fixed passive guidance methods, analyzes global technology development trends to overcome them, identifies the digital transformation properties required to switch to intelligent variable smart location guidance methods, explains the characteristics and components of AI-based public facility smart fire safety integrated system (ISFS).

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.6
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• pp.627-633
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• 1999

In this paper, we propose a method of cooperative control (T-cell modeling) and selection of group behavior strategy (B-cell modeling) based on immune system in distributed autonomous robotic system (DARS). Immune system is living body's self-protection and self-maintenance system. These features can be applied to decision making of optimal swarm behavior in dynamically changing environment. For applying immune system to DARS, a robot is regarded as a ？3-cell, each environmental condition as an antigen, a behavior strategy as an antibody and control parameter as a T-cell respectively. When the environmental condition (antigen) changes, a robot selects an appropriate behavior strategy (antibody). And its behavior strategy is stimulated and suppressed by other robot using communication (immune network). Finally much stimulated strateby is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and immune network hypothesis, and it is used for decision making of optimal swarm strategy. Adaptation ability of robot is enhanced by adding T-cell model as a control parameter in dynamic environments.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.2
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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.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.4
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• pp.286-295
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• 2007

This paper presents an intelligent PID control for stochastic systems with nonstationary nature. We optimally determine parameters of a PID controller through learning algorithm and propose an online PID control to compensate system errors possibly occurred in realtime implementations. A dynamic Bayesian network (DBN) model for system errors is additionally explored for making decision about whether an online control is carried out or not in practice. We apply our control approach to traffic control of Transmission Control Protocol (TCP) networks and demonstrate its superior performance comparing to a fixed PID from computer simulations.