• Title/Summary/Keyword: Decision Support Model

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Estimation of Accident Probability for Dynamic Risk Assessment (동적 위험 분석을 위한 사고확률 추정 방법에 관한 연구)

  • Byeong-Cheol Park;Chae-Og Lim;In-Hyuk Nam;Sung-Chul Shin
    • Journal of the Korean Society of Industry Convergence
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    • v.26 no.2_2
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    • pp.315-325
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    • 2023
  • Recently, various dynamic risk analysis methods have been suggested for estimating the risk index by predicting the possibility of accidents and damage. It is necessary to maintain and support the safety system for responding to accidents by continuously updating the probability of accidents and the results of accidents, which are quantitative standards of ship risk. In this study, when a LNG leakage that may occur in the LN G Fuel Gas Supply System (FGSS) room during LN G bunkering operation, a reliability physical model was prepared by the change in monitoring data as physical parameters to estimate the accident probability. The scenario in which LNG leakage occur were configured with FT (Fault Tree), and the coefficient of the covariate model and Weibull distribution was estimated based on the monitoring data. The possibility of an LNG leakage, which is the top event of FT, was confirmed by changes in time and monitoring data. A method for estimating the LNG leakage based on the reliability physical analysis is proposed, which supports fast decision-making by identifying the potential LNG leakage at the accident.

Retrieve System for Performance support of Vocabulary Clustering Model In Continuous Vocabulary Recognition System (연속 어휘 인식 시스템에서 어휘 클러스터링 모델의 성능 지원을 위한 검색 시스템)

  • Oh, Sang Yeob
    • Journal of Digital Convergence
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    • v.10 no.9
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    • pp.339-344
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    • 2012
  • Established continuous vocabulary recognition system improved recognition rate by using decision tree based tying modeling method. However, since system model cannot support the retrieve of phoneme data, it is hard to secure the accuracy. In order to improve this problem, we remodeled a system that could retrieve probabilistic model from continuous vocabulary clustering model to phoneme unit. Therefore in this paper showed 95.88%of recognition rate in system performance.

Decision-Tree Model of Long-term Abstention from Smoking: Focused on Coping Styles (장기적 금연 지속기간 예측 모형: 스트레스 대처를 중심으로)

  • Suh, Kyung-Hyun;You, Jae-Min
    • Korean Journal of Health Education and Promotion
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    • v.22 no.4
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    • pp.73-90
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    • 2005
  • Objectives: Smokers who had failed to quit smoking were frequently reported that life stress mostly interrupted their abstention. Stress vulnerability model for smoking cessation has been considered, and most of contemporary smoking cessation programs help smokers develop coping strategies for stressful situations. This study aims to investigate the appropriate coping styles for stress of abstention from smoking. The result of investigating the relationship between abstention following smoking cessation program and coping styles would suggest useful information for those who want to stop smoking and health practitioners who help them. Methods: Participants were 69 smokers (62 males, 7 females) participated in a hospitalized smoking cessation program, whose mean age was 44.89 (SD=9.61). Participants took medical test and completed questionnaires and psychological tests including: Fagerstrom Test for Nicotine Dependence and Multidimensional Coping Scale. To identify participants' abstention, researchers followed them for 2 years. To identify whether abstained or not and encourage them to abstain, researchers called them on the telephone once a week for 3 months. After 3 months, they were contacted every other week till 6 months passed since they left smoking cessation program. And they were contacted once a month for other 18months. Researchers also contacted their family to identify their abstention. Data Mining Decision Tree was performed with 37 variables (13 variables for the coping styles and 24 smoking-related variables) by Answer Tree 3.0v Results: Forty four (63.8%) out of sixty nine for 2 weeks, 34 (49.3%) for 6 months, 25 (36.2%) abstained for 1 year, and 22 (31.9%) abstained for 2 years. Participants of this study abstained average of 286.77 days from smoking. Included variables of a Decision Tree model for this study were positive interpretation, emotional expression, self-criticism, restraint and emotional social support seeking. Decision Tree model showed that those (n=9) who did not interpret positively (<=7.5) and criticized themselves (>6.5) abstained 23 days only, while those (n=9) who interpreted positively (>7.5), expressed their emotion freely (>6.5), and sought social support actively (>11.5) abstained 730 days, till last day of the investigation. Conclusion: The results of this study showed that certain coping styles such as positive interpretation, emotional expression, self-criticism, restraint and emotional social support seeking were important factors for long-term abstention from smoking. These findings reiterate the role of stress for abstention from smoking and suggest a model of coping styles for successful abstention from smoking. Despite of limitation of this study, it might help smokers who want to stop smoking and health practitioners who help them.

Development of Evaluation Model in Business Incubator Using Data Mining Process (데이터마이닝을 이용한 창업보육센터의 평가모델 개발)

  • Lee, Dong-Youb;Kim, Jin-Wook
    • IE interfaces
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    • v.20 no.3
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    • pp.387-394
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    • 2007
  • Numerous countries promote business programs to revitalize local economy, increase employment, and nurture high-tech industries. Recently, a number of business incubators have been established and operated with aims to adapt to changing environment and increase economic competitiveness in Korea. To give satisfactory results of governmental policy, the requirement to develop the evaluation model to support effective operations of business incubators using the objective and rational criteria is growing. The purpose of this study is to develop evaluation model in Business Incubator using Data Mining Process. We suggested the evaluation model of business incubator, 'Score-5 RS' consists of making evaluation factor process using weighted sum and 5-grade classification and analyzing process by Decision Tree algorithm.

An MCDM-Based Integrated Economic Analysis Model for the New Telecommunication Services (다기준 의사결정기법을 활용한 신규통신 서비스의 총체적 사업성 분석)

  • Chang, Haeng-Gorn;Choi, Sang-Hyun;Choi, Yong-Sun;Kim, Soung-Hie
    • IE interfaces
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    • v.5 no.2
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    • pp.3-17
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    • 1992
  • In this study, an integrated economic analysis model to analyze the new telecommunication services is developed. This model considers both the technological and managerial aspests altogether with respect to the profit and public benefit criteria. To encounter the various dynamically changing environments and evaluation criteria, multiple criteria decision making (MCDM)techniques are employed. The model consists of three stages; The first stage surveys related formal or informal data, generates analysis alternatives, and performs acceptabillty test in view of marketing. The second stage generates executive alternatives for each acceptable analysis alternative and checks the executionability in view of telecommunication technologies. The third stage performs the final integrated economic analysis including the profitability analysis. This study offers a basis for the future development of decision support system or expert system on the economic analysis of the new telecommunication services.

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An Intelligent Multi-multivariable Dynamic Matrix Control Scheme for a 160 MW Drum-type Boiler-Turbine System

  • Mazinan, A.H.
    • Journal of Electrical Engineering and Technology
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    • v.7 no.2
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    • pp.240-245
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    • 2012
  • A 160 MW drum-type boiler-turbine system is developed in the present research through a multi-multivariable dynamic matrix control (DMC) scheme and a multi-multivariable model approach. A novel intelligence-based decision mechanism (IBDM) is realized to support both model approach and control scheme. In such case, the responsibility of the proposed IBDM is to identify the best multivariable model of the system and the corresponding multivariable DMC scheme to cope with the system at each instant of time in an appropriate manner.

A Study on the Effects of the Service Quality of Hospital's Decision Support System on Management Performance : the Case of K-University Hospital (병원 의사결정지원시스템의 서비스 품질이 경영성과에 미치는 영향 : K대병원 사례 중심으로)

  • Park, Jin Hee;Kwon, Do Soon;Lee, Miyoung
    • Journal of Information Technology Applications and Management
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    • v.21 no.2
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    • pp.81-98
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    • 2014
  • Recently, due to external environment like the changes in health policy and various healthcare accreditations, along with hospital's internal efforts to improve the quality of medical services, demands for the development of medical information systems are increasing. Some examples are clinical information like DUR (Drug Utilization Review), CVR (Critical Value Report), and automatic benefit processing by treatment purposes, or hospital DSS (Decision Support System) on overall medical practice. Such systems act as a guide in making clinic judgments during practice or in other medical practice, and their effects on the medical treatment improvements are being proven by previous studies. In the reality of increasing attention in the effects of medical treatment improvement, studies related to hospital DDS were mostly focused on clinical, technical, and engineering points of view, and studies focusing on the user viewpoint are very limited. In order to verify the effects of DSS on practice improvements and hospital's management performance, this study used a research model constructed to verify how SERVQUAL of hospital DSS affects hospital management performance in BSC (Balanced Score Card) point of view. To empirically verify the research model, a questionnaire was conducted on the basis of "K-University Hospital's DSS" on clinicians and hospital employees related to system development, and the relationships between the factors were analyzed through path analysis. As a result of path analysis, excluding reactivity, tangibility, confidence, reliability, empathy among service qualities, had partially significant effects on management performance factors (learning and growth, internal process, financial affairs). This study is to prepare the theoretical ground on the management performance analysis of hospital DSS, and suggest the service quality of the system that should be considered in the planning and development stages for improved system.

A pilot study using machine learning methods about factors influencing prognosis of dental implants

  • Ha, Seung-Ryong;Park, Hyun Sung;Kim, Eung-Hee;Kim, Hong-Ki;Yang, Jin-Yong;Heo, Junyoung;Yeo, In-Sung Luke
    • The Journal of Advanced Prosthodontics
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    • v.10 no.6
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    • pp.395-400
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    • 2018
  • PURPOSE. This study tried to find the most significant factors predicting implant prognosis using machine learning methods. MATERIALS AND METHODS. The data used in this study was based on a systematic search of chart files at Seoul National University Bundang Hospital for one year. In this period, oral and maxillofacial surgeons inserted 667 implants in 198 patients after consultation with a prosthodontist. The traditional statistical methods were inappropriate in this study, which analyzed the data of a small sample size to find a factor affecting the prognosis. The machine learning methods were used in this study, since these methods have analyzing power for a small sample size and are able to find a new factor that has been unknown to have an effect on the result. A decision tree model and a support vector machine were used for the analysis. RESULTS. The results identified mesio-distal position of the inserted implant as the most significant factor determining its prognosis. Both of the machine learning methods, the decision tree model and support vector machine, yielded the similar results. CONCLUSION. Dental clinicians should be careful in locating implants in the patient's mouths, especially mesio-distally, to minimize the negative complications against implant survival.

Maritime Transportation Planning Support System for a Car Shipping Company

  • Park, Byung-Joo;Choi, Hyung-Rim;Kim, Hyun-Soo;Jun, Jae-Un
    • Journal of Navigation and Port Research
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    • v.32 no.4
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    • pp.295-304
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    • 2008
  • In order to achieve a sustainable competitive advantage in the expanding maritime transportation market, most shipping companies are making every effort to reduce transportation costs. Likewise, the car shipping companies, which carry more than 80% of total car import and export logistics volume, also do their utmost for transportation cost saving. Until now many researches have been made for efficient maritime transportation, but studies for car shipping companies have rarely been made. For this reason, this study has tried to develop a maritime transportation planning support system which can help to save logistics costs and increase a competitive power of car shipping companies. To this end, instead of manual effort to solve the routing problem of car carrier vessels, this study has used an integer programming model to make an optimal transportation planning at the minimum cost. Also in response to the frequent changes both in the car production schedule and ship's arrival schedule after the completion of transportation planning, this research has developed a decision support system of maritime transportation, so that users can easily modify their existing plans.

Design of a Logistics Decision Support System for Transportation Mode Selection considering Carbon Emission Cost (탄소배출비용을 고려한 물류의 최적 운송수단 의사결정 시스템 설계)

  • Song, Byung-Jun;Koo, Je-Kwon;Song, Sang-Hwa;Lee, Jong-Yun
    • The KIPS Transactions:PartD
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    • v.18D no.5
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    • pp.371-384
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    • 2011
  • This paper considers logistics decision support system which deals with transportation mode selection considering transportation and carbon emission cost. Transportation and carbon emission costs vary with the choice of transportation modes and to become competitive companies need to find proper transportation modes for their logistics services. However, due to the restricted capacity of transportation modes, it is difficult to balance transportation and carbon emission costs when designing logistics network including transportation mode choice for each service. Therefore this paper aims to analyze the trade-off relationship between transportation and carbon emission cost in mode selection of intermodal transportation and to provide optimal green logistics strategy. In this paper, the logistics decision support system is designed based on mixed integer programming model. To understand the trade-off relationship of transportation and carbon emission cost, the system is tested with various scenarios including transportation of containers between Seoul and Busan. The analysis results show that, even though sea transportation combined with trucking is competitive in carbon emission per unit distance travelled, the total cost of carbon emission and transportation for the sea transportation may not have competitive advantage over other transportation modes including rail and truck transportation modes. The sea-based intermodal logistics service may induce detours which have negative impacts on the overall carbon emission. The proposed logistics decision support system is expected to play key role in green logistics and supply chain management.