• Title/Summary/Keyword: Support Decision Making

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Risk Allocation of Private Port Development with Hierarchical Fuzzy Process

  • Seong, Yu-Chang;Youn, Myung-Ou
    • Journal of Navigation and Port Research
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    • v.31 no.4
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    • pp.317-323
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    • 2007
  • As economic trade between Korea and China has been encouraged with the rapid growth of Chinese economy and port competition in Northeast Asia, Korean government is trying to promote development and consolidation of ports to cope with the lack of facilities. Thus, many projects for port development have been propelled including the enactment the 'Private investment promotion law for social overhead capital 1994.' However, there are still some unsettled issues since considerable part of risk is still allocated to the Government when it has to support the private businesses in these port investments whenever unexpected problems arise. Allocation of risk among the participants - in this case especially - is a very subtle issue, however, it was revealed that not many precedent researches were done on the subject. In my previous research, I classified and analyzed 4 principle risks i.e, construction, management, financial and social risk. This research investigates the reasonable allocation of the risks among the participants using the Hierarchial Fuzzy Process. In the result of analysis, responsibility of private party is the most important and it must put the responsibility before Government' roll concerned. Also, this research displayed and proposed the direction of management method on port development in a view of minimizing risk and maximizing initiative of a private party.

Service Failure Management on Internet Shopping Environment by Combining Service Blueprint and FMEA (서비스 청사진과 FMEA의 결합에 의한 인터넷 쇼핑몰 서비스 실패관리)

  • Lee, Hye-Jun;Lee, Dong-Il;Zhang, Yong
    • Journal of Korean Society for Quality Management
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    • v.39 no.2
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    • pp.217-233
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    • 2011
  • This paper introduces service failure management on internet shopping environment. The purpose of this study is to find and improve service failure modes at the time of customer's complaint thereby reducing that. To achieve this purpose, this study combines the Service Blueprint which describes the online shopping process and FMEA which finds each encounter of service failures and proposes how to recover them. First of all this study generates internet shopping process using Service Blueprint then matches customer's purchase decision making process and company's service provide process. After this process customer complaint types in real purchasing process are fell in according to their occurrence and more frequently occurred complaint is more risky. Finally 6 Risk Priority Numbers(unfair exchange/return policies, slow response/poor customer service support, purchase arrived later than promised/deliverly service dissatisfaction, dissatisfaction short period to take back/exchange/cancels order, A/S or handle defective item) are extracted and suggest their improvement.

Reasonable Decision Making for Sustainable Water Supply Source Management (상수원의 지속가능한 관리를 위한 합리적 의사결정 방향)

  • Choi, Ji Yong
    • Journal of Korean Society on Water Environment
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    • v.23 no.4
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    • pp.504-511
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    • 2007
  • Built-out issue of copper processing appearing recently in the Paldang watershed is a critical problem to deteriorate the basic framework of national water management policy as well as to be simply a copper-related problem. Up to now, Korea government has invested hard and relevant upstream areas have been victimized readily in a variety of field to comply its goal of 'Safe Water Supply'. Because of the reason, the desirable water quality level of the Paldang watershed has been maintained regardless of its dense population. Paldang drinking water management policy is based on residents' understanding which is considered as a 'social capital'. The issue raised in the aspect of water quality management policy should be reviewed on the basis of the 'social capital' concept. One regarding semiconductor industry as a potential industry to export many products in 10 years insists that the industry not be a simple private business but be a prominent part for national competitiveness. There is no doubt about this opinion. However, a nation should support environmental right-to-life of its people prior to any other tasks. In other words, it is really risky to give up people's right due to economic benefits. Therefore, it should not happen to trade 'life', the dignity of man, with national competitiveness which is likely to be preferred in these days. In addition, coherent policy not to destroy 'social capital' promoting Paldang drinking water resource management policy should be maintained.

Approximate Life Cycle Assessment of Classified Products using Artificial Neural Network and Statistical Analysis in Conceptual Product Design (개념 설계 단계에서 인공 신경망과 통계적 분석을 이용한 제품군의 근사적 전과정 평가)

  • 박지형;서광규
    • Journal of the Korean Society for Precision Engineering
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    • v.20 no.3
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    • pp.221-229
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    • 2003
  • In the early phases of the product life cycle, Life Cycle Assessment (LCA) is recently used to support the decision-making fer the conceptual product design and the best alternative can be selected based on its estimated LCA and its benefits. Both the lack of detailed information and time for a full LCA fur a various range of design concepts need the new approach fer the environmental analysis. This paper suggests a novel approximate LCA methodology for the conceptual design stage by grouping products according to their environmental characteristics and by mapping product attributes into impact driver index. The relationship is statistically verified by exploring the correlation between total impact indicator and energy impact category. Then a neural network approach is developed to predict an approximate LCA of grouping products in conceptual design. Trained learning algorithms for the known characteristics of existing products will quickly give the result of LCA for new design products. The training is generalized by using product attributes for an ID in a group as well as another product attributes for another IDs in other groups. The neural network model with back propagation algorithm is used and the results are compared with those of multiple regression analysis. The proposed approach does not replace the full LCA but it would give some useful guidelines fer the design of environmentally conscious products in conceptual design phase.

Building of Collision Avoidance Algorithm based on CBR

  • Park Gyei-Kark;Benedictos John Leslie RM
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2006.11a
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    • pp.39-44
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    • 2006
  • Ship's collision avoidance is a skill that masters of merchant marine vessels have acquired through years of experience and that makes them feel at ease to guide their ship out from danger quickly compared to inexperienced officers. Case based reasoning(CBR) uses the same technique in solving tasks that needs reference from variety of situations. CBR can render decision-making easier by retrieving past solutions from situations that are similar to the one at hand and make necessary adjustments in order to adapt them. In this paper, we propose to utilize the advantages of CBR in a support system for ship's collision avoidance while using fuzzy algorithm for its retrieval of similar navigational situations, stored in the casebase, thus avoiding the cumbersome tasks of creating a new solution each time a new situation is encountered. There will be two levels within the Fuzzy-CBR. The first level will identify the dangerous ships and index the new case. The second level will retrieve cases from casebase and adapt the solution to solve for the output. While CBR's accuracy depends on the efficient retrieval of possible solutions to be adapted from stored cases, fuzzy algorithm will improve the effectiveness of solving the similarity to a new case at hand.

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Smart irrigation technique for agricultural water efficiency against climate change (기후변화 대응 물 효율성 증대를 위한 스마트 관개기술 연구)

  • Kim, Minyoung;Jeon, Jonggil;Kim, Youngjin;Choi, Yonghun
    • Proceedings of the Korea Water Resources Association Conference
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    • 2017.05a
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    • pp.198-198
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    • 2017
  • Climate change causes unpredictable and erratic climatic patterns which affects crop production in agriculture and threatens public health. To cope with the challenges of climate change, sustainable and sound growth environment for crop production should be secured. Recent attention has been given to the development of smart irrigation system using sensors and wireless network as a solution to achieve water conservation as well as improvement in crop yield and quality with less water and labor. This study developed the smart irrigation technique for farmlands by monitoring the soil moisture contents and real-time climate condition for decision-making support. Central to this design is micro-controller which monitors the farm condition and controls the distribution of water on the farm. In addition, a series of laboratory studies were conducted to determine the optimal irrigation pattern, one time versus plug time. This smart technique allows farmers to reduce water use, improve the efficiency of irrigation systems, produce more yields and better quality of crops, reduce fertilizer and pesticide application, improve crop uniformity, and prevent soil erosion which eventually reduce the nonpoint source pollution discharge into aquatic-environment.

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A Study on Open API of Securities and Investment Companies in Korea for Activating Big Data

  • Ryu, Gui Yeol
    • International journal of advanced smart convergence
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    • v.8 no.2
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    • pp.102-108
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    • 2019
  • Big data was associated with three key concepts, volume, variety, and velocity. Securities and investment services produce and store a large data of text/numbers. They have also the most data per company on the average in the US. Gartner found that the demand for big data in finance was 25%, which was the highest. Therefore securities and investment companies produce the largest data such as text/numbers, and have the highest demand. And insurance companies and credit card companies are using big data more actively than banking companies in Korea. Researches on the use of big data in securities and investment companies have been found to be insignificant. We surveyed 22 major securities and investment companies in Korea for activating big data. We can see they actively use AI for investment recommend. As for big data of securities and investment companies, we studied open API. Of the major 22 securities and investment companies, only six securities and investment companies are offering open APIs. The user OS is 100% Windows, and the language used is mainly VB, C#, MFC, and Excel provided by Windows. There is a difficulty in real-time analysis and decision making since developers cannot receive data directly using Hadoop, the big data platform. Development manuals are mainly provided on the Web, and only three companies provide as files. The development documentation for the file format is more convenient than web type. In order to activate big data in the securities and investment fields, we found that they should support Linux, and Java, Python, easy-to-view development manuals, videos such as YouTube.

A Concept Analysis on Patient-Centered Care in Hospitalized Older Adults with Multimorbidity (복합질환을 가진 입원노인 대상 환자중심간호 개념분석)

  • Son, Youn-Jung;Yoon, Heun-Keung
    • Journal of Korean Critical Care Nursing
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    • v.12 no.2
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    • pp.61-72
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    • 2019
  • Purpose : The aim of this study was to explore the attributes, antecedents, and consequences of patient-centered care (PCC) for older adults with multimorbidity in acute care hospitals. Methods : The concept analysis performed by Walker and Avant was used to analyze PCC. Fifteen studies from the literature related to PCC appear in systematic literature reviews in the fields of theology, medicine, psychology, and nursing. Results : PCC in acute care hospitals was defined according to the five attributes of 'maintaining patient autonomy', 'empowering self-care', 'individualized and relationship-based care', 'shared decision-making', and 'creating a homelike environment'. Antecedents of PCC were found to be a respect for patients' preferences, qualifications of the nursing staff, care coordination and integration, and organizational support. Consequences of effective PCC were a functional status; health-related quality of life; satisfaction with care, mortality, and medical costs from the perspective of the patient and family; and quality of care and therapeutic relationships from nurses' viewpoints. Conclusion : PCC as defined by the results of this study will contribute to the foundation of institutionalization and the creation of a safe and healthy acute care hospital culture focused on patients' preferences and values.

Comparison of Bayesian Methods for Estimating Parameters and Uncertainties of Probability Rainfall Distribution (확률강우분포의 매개변수 및 불확실성 추정을 위한 베이지안 기법의 비교)

  • Seo, Youngmin;Park, Jaeho;Choi, Yunyoung
    • Journal of Environmental Science International
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    • v.28 no.1
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    • pp.19-35
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    • 2019
  • This study investigates the performance of four Bayesian methods, Random Walk Metropolis (RWM), Hit-And-Run Metropolis (HARM), Adaptive Mixture Metropolis (AMM), and Population Monte Carlo (PMC), for estimating the parameters and uncertainties of probability rainfall distribution, and the results are compared with those of conventional parameter estimation methods; namely, the Method Of Moment (MOM), Maximum Likelihood Method (MLM), and Probability Weighted Method (PWM). As a result, Bayesian methods yield similar or slightly better results in parameter estimations compared with conventional methods. In particular, PMC can reduce parameter uncertainty greatly compared with RWM, HARM, and AMM methods although the Bayesian methods produce similar results in parameter estimations. Overall, the Bayesian methods produce better accuracy for scale parameters compared with the conventional methods and this characteristic improves the accuracy of probability rainfall. Therefore, Bayesian methods can be effective tools for estimating the parameters and uncertainties of probability rainfall distribution in hydrological practices, flood risk assessment, and decision-making support.

Traffic Emission Modelling Using LiDAR Derived Parameters and Integrated Geospatial Model

  • Azeez, Omer Saud;Pradhan, Biswajeet;Jena, Ratiranjan;Jung, Hyung-Sup;Ahmed, Ahmed Abdulkareem
    • Korean Journal of Remote Sensing
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    • v.35 no.1
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    • pp.137-149
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    • 2019
  • Traffic emissions are the main cause of environmental pollution in cities and respiratory problems amongst people. This study developed a model based on an integration of support vector regression (SVR) algorithm and geographic information system (GIS) to map traffic carbon monoxide (CO) concentrations and produce prediction maps from micro level to macro level at a particular time gap in a day in a very densely populated area (Utara-Selatan Expressway-NKVE, Kuala Lumpur, Malaysia). The proposed model comprised two models: the first model was implemented to estimate traffic CO concentrations using the SVR model, and the second model was applied to create prediction maps at different times a day using the GIS approach. The parameters for analysis were collected from field survey and remote sensing data sources such as very-high-resolution aerial photos and light detection and ranging point clouds. The correlation coefficient was 0.97, the mean absolute error was 1.401 ppm and the root mean square error was 2.45 ppm. The proposed models can be effectively implemented as decision-making tools to find a suitable solution for mitigating traffic jams near tollgates, highways and road networks.