• 제목/요약/키워드: Decision support model

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

  • 서경현;유제민
    • 보건교육건강증진학회지
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    • 제22권4호
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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.

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

  • 이동엽;김진욱
    • 산업공학
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    • 제20권3호
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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.

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

  • 장행곤;최상현;최용선;김성희
    • 산업공학
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    • 제5권2호
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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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    • 제7권2호
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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.

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

  • 박진희;권두순;이미영
    • Journal of Information Technology Applications and Management
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    • 제21권2호
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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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    • 제10권6호
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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
    • 한국항해항만학회지
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    • 제32권4호
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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.

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

  • 송병준;구제권;송상화;이종연
    • 정보처리학회논문지D
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    • 제18D권5호
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    • pp.371-384
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    • 2011
  • 본 논문은 운송비용과 탄소배출비용을 고려한 최적 운송수단 선정에 대한 물류의사결정 시스템을 설계하고자 한다. 기존 연구는 운송비용과 운송모드별 용량을 고려하여 최적의 운송수단을 선정하였으나, 온실가스 배출규제에 대응하기 위해 운송비용과 용량 뿐만 아니라 탄소배출비용을 통합적으로 고려하여 물류체계를 설계할 필요성이 높아지고 있다. 따라서 본 논문에서는 탄소배출을 고려한 우리나라의 복합운송에 대한 운송수단 선택과 비용과 CO2배출의 Trade-off관계에 대한 접점을 찾아 분석하고 향후 나아갈 방안에 대해 제시하고자 한다. 탄소배출비용을 고려한 최적 운송수단 의사결정 문제는 혼합정수계획 모형으로 모델링되었으며, 운송비용과 탄소배출비용 사이의 관계를 분석하기 위하여 서울-부산 간 컨테이너 운송에 있어서의 다양한 시나리오를 도출하였다. 각각의 시나리오는 개발된 의사결정 시스템을 통하여 분석되었으며, 분석결과 단위 이동 거리당 탄소배출량이 낮은 것으로 알려져 있는 해상운송과 같은 대량운송 수단이 경우에 따라 더 많은 탄소를 배출하는 것으로 나타났다. 대량운송 수단의 경우 항만이나 철도역까지의 트럭운송에서의 우회가 증가된 탄소 배출의 주요 원인이었다. 제안된 물류의사결정 시스템은 녹색물류 및 그린SCM에서의 탄소배출비용과 물류비용사이의 관계를 이해하는데 역할을 할 것으로 기대된다.

Stakeholders Driven Requirements Engineering Approach for Data Warehouse Development

  • Kumar, Manoj;Gosain, Anjana;Singh, Yogesh
    • Journal of Information Processing Systems
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    • 제6권3호
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    • pp.385-402
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    • 2010
  • Most of the data warehouse (DW) requirements engineering approaches have not distinguished the early requirements engineering phase from the late requirements engineering phase. There are very few approaches seen in the literature that explicitly model the early & late requirements for a DW. In this paper, we propose an AGDI (Agent-Goal-Decision-Information) model to support the early and late requirements for the development of DWs. Here, the notion of agent refers to the stakeholders of the organization and the dependency among agents refers to the dependencies among stakeholders for fulfilling their organizational goals. The proposed AGDI model also supports three interrelated modeling activities namely, organization modeling, decision modeling and information modeling. Here, early requirements are modeled by performing organization modeling and decision modeling activities, whereas late requirements are modeled by performing information modeling activities. The proposed approach has been illustrated to capture the early and late requirements for the development of a university data warehouse exemplifying our model's ability of supporting its decisional goals by providing decisional information.

A Grey MCDM Based on DEMATEL Model for Real Estate Evaluation and Selection Problems: A Numerical Example

  • NGUYEN, Phi-Hung;TSAI, Jung-Fa;NGUYEN, Thanh-Tam;NGUYEN, Thi-Giang;VU, Dang-Duong
    • The Journal of Asian Finance, Economics and Business
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    • 제7권11호
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    • pp.549-556
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    • 2020
  • Real estate markets play an essential role in the economic development of both developed and developing countries. Investment decisions in private real estate demand the consideration of several qualitative and quantitative criteria. Especially in Vietnam, demand for housing, apartments are rising which has resulted because of the migration from rural to urban areas. This study aims to determine the influencing factors of the real estate purchasing behavior and then recommend a grey Multi-Criteria Decision Making (MCDM) support model to evaluate real estate alternatives based on a numerical example in Vietnam. A set of essential criteria are identified based on experts' opinion, and the proposed determinants are initial investment, maintenance cost, prestige location, distance to interesting places, parking lot, public transportation, property condition, total area size, number of rooms, and neighbors. The subjective weights were obtained by using the Decision-Making Trial and Evaluation Laboratory (DEMATEL) model, and the Grey Relational Analysis (GRA) technique is employed to prioritize and rank real estate alternatives. The results reveal that this approach can be useful to make purchasing decisions for many kinds of real estate property under uncertain business environments. These findings indicate that the presented hybrid model has advantages in granting flexibility to the preferences of decision makers.