• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.21-21
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• 2011

Many Asian countries are suffered from various problems on water, which include the need for increased access to improves water supplies and sanitation through investments in infrastructure and capacity building, the balances water management system between development and ecosystem, and the need to reduce the human populations'vulnerability to water-related disasters, in particular, from climate variability and evolution. Decison makers are the most influential people in policy making and solving global water problems is central issue in eradicating poverty and achieving sustainable development (MDG). They across the world form an integral part of the architecture of national or regional governance. Their role covers a range of decision-making processes including passing legislation, scrutinizing government policy, and representing citizen through the election. We must ensure that these quiet but important issues get the political space, financial priority and public attention they deserve. Regional bodies such as the EU have also enacted legislation which introduces rules on water quality and other enforceable mattera across state boundaries. With this growing body of laws and policies on water issues, the role of decision makers is growing. Recognizing this role, decison makers' platform is essential to provide an opportunity to discuss crucial water issues in each country or region and for the purpose "2010 Parliaments for Water in Asia" has planned and organized to investigate our common issues and goals. During the meeting, we have an opportunity to observe water policy of Bangladesh, Bhutan, China, Mongolia, New Zealand and the Philippines and share the views on what needs to be done to move forward by decision makers for the future of water. In conclusion, the process of developing the decision makers' platform in each region would be ultimately essential point to increase the awareness of the developed and developing countries' roles, knowledge to clarify roles and responsibilities of each stake holders and finally be a major actor for resolving not only water challenges also issues of human settlements.

• 한국경영정보학회:학술대회논문집
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• 2007.06a
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• pp.339-344
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• 2007

In the cut-throat competitive environment of business, large-scale IS investment is becoming inevitable strategic necessity for gaining competitive advantage. However. it bears great deal of risk over all the associated processes so that the investment decisions need to be taken in a greatly careful manner. Nonetheless, Korean organizations are prominently showing risk taking behaviors regarding major is investment, in terms of system downsizing. Although decision theory argues decision makers' rational choice of options through the assessment of risk and benefit, the notable trend toward system downsizing in Korea defies common understandings on IS project risk. Furthermore, it encourages us to investigate many impenetrable characteristics underlying organizational risk taking decisions with IS investment. We found out that there is Significant effect of IS decision makers' risk propensity when they make system downsizing decisions. Moreover. we Identified that IS decision makers do not get a strong pressure of cost savings and have tendencies to mimic competitor's decisions.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.77-86
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• 2022

The destructive impact of contagious diseases outbreaks on all life facets necessitates developing effective solutions to control these diseases outbreaks. This research proposes an end-to-end, data-driven platform which consists of multiple modules that are working in harmony to achieve a concrete goal: early detection of contagious diseases outbreaks (i.e., epidemic diseases detection). Achieving that goal enables decision makers and people in power to act promptly, resulting in robust prevention management of contagious diseases. It must be clear that the goal of this proposed platform is not to predict or forecast the spread of contagious diseases, rather, its goal is to promptly detect contagious diseases outbreaks as they happen. The front end of the proposed platform is a web-based dashboard that visualizes diseases outbreaks in real-time on a real map. These outbreaks are detected via another component of the platform which utilizes data mining techniques and algorithms on gathered datasets. Those gathered datasets are managed by yet another component. Specifically, a mobile application will be the main source of data to the platform. Being a vital component of the platform, the datasets are managed by a DBMS that is specifically tailored for this platform. Preliminary results are presented to showcase the performance of a prototype of the proposed platform.

• Informatization Policy
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• v.25 no.4
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• pp.108-120
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• 2018

With the rise of the Fourth Industrial Revolution and I-Korea 4.0, both of which pursue strategies for industrial innovation and for the solution to social problems, the real estate industry needs to change in order to make effective use of available space in smart environments. The implementation of smart spaces is a promising solution for this. The smart space is defined as a good use of space, whether it be a home, office, or retail store, within a smart environment. To enhance the use of smart spaces, efficient decision-making and well-timed and accurate interaction are required. This paper proposes a smart space based on platform which takes advantage of emerging technologies for the efficient storage, processing, analysis, and utilization of big data. The platform is composed of six layers - collection, transfer, storage, service, application, and management - and offers three service frameworks: activity-based, market-based, and policy-based. Based on these smart space services, decision-makers, consumers, clients, and social network participants can make better decisions, respond more quickly, exhibit greater innovation, and develop stronger competitive advantages.

• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.1
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• pp.45-60
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• 2001

As the advent of the Internet, most of the modern firms are now forced to use the internet as one of telecommunication tools for daily activities, Especially, as the decision units and/or makers in a firm become geographically dispersed due to the globalization trend, the need for integrating them effectively on the Internet is getting attention from researchers and practitioners much more than ever. In literature, this kind of need has been specially conspicuous in the need for coordinating production and marketing activities which are known as one of the typically conflicting with each other in terms of purposes. Lee and Lee(1999) has proposed an interesting coordination environment for production and marketing, named PROMISE. This paper is aimed at improving the coordination algorithm utilized in PROMISE and accordingly proposing a web-driven DSS for the purpose of transforming PROMISE into a web-based decision support platform for production and marketing coordination.

• Journal of Korean Society on Water Environment
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• v.36 no.6
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• pp.636-650
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• 2020

A modeling system that can consider the overall water environment and be used to integrate hydrology, water quality, and aquatic ecosystem on a watershed scale is essential to support decision-making in integrated water resources management (IWRM). In adapting imported models for evaluating the unique water environment in Korea, a platform perspective is becoming increasingly important. In this study, a modeling platform is defined as an ecosystem that continuously grows and provides sustainable values through voluntary participation- and interaction-of all stakeholders- not only experts related to model development, but also model users and decision-makers. We assessed the conceptual values provided by the IWRM modeling platform in terms of openness, transparency, scalability, and sustainability. I We also reviewed the technical aspects of functional and spatial integrations in terms of socio-economic factors and user-centered multi-scale climate-forecast information. Based on those conceptual and technical aspects, we evaluated potential modeling platforms such as Source, FREEWAT, Object Modeling System (OMS), OpenMI, Community Surface-Dynamics Modeling System (CSDMS), and HydroShare. Among them, CSDMS most closely approached the values suggested in model development and offered a basic standard for easy integration of existing models using different program languages. HydroShare showed potential for sharing modeling results with the transparency expected by model user-s. Therefore, we believe that can be used as a reference in development of a modeling platform appropriate for managing the unique integrated water environment in Korea.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.527-535
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• 2021

Traditional business intelligence (BI) systems have been used widely as tools for better decision-making on time. On the other hand, building a data warehouse (DW) for the efficient analysis of rapidly growing data is time-consuming and complex. In particular, the ETL (Extract, Transform, and Load) process required to build a data warehouse has become much more complex as the BI platform moves to a cloud environment. Various BI solutions based on the NoSQL database, such as MongoDB, have been proposed to overcome these ETL issues. Decision-makers want easy access to data without the help of IT departments or BI experts. Recently, self-service BI (SSBI) has emerged as a way to solve these BI issues. This paper proposes a self-service BI system with farming data using the MongoDB cloud as DW to support the selection of new crops by return-farmers. The proposed system includes functions to provide insights to decision-makers, including data visualization using MongoDB charts, reporting for advanced data search, and monitoring for real-time data analysis. Decision makers can access data directly in various ways and can analyze data in a self-service method using the functions of the proposed system.

• Journal of Platform Technology
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• v.11 no.3
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• pp.45-55
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• 2023

This paper presents a model that supports decision-makers in the Korean film industry to maximize the success of online movies. To achieve this, we collected historical box office movies and clustered them into types to propose a model predicting each type's online box office performance. We considered various features to identify factors contributing to movie success and reduced feature dimensionality for computational efficiency. We systematically classified the movies into types and predicted each type's online box office performance while analyzing the contributing factors. We used automated machine learning (AutoML) techniques to automatically propose and select machine learning algorithms optimized for the problem, allowing for easy experimentation and selection of multiple algorithms. This approach is expected to provide a foundation for informed decision-making and contribute to better performance in the film industry.

• The Journal of Bigdata
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• v.5 no.1
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• pp.11-27
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• 2020

In this paper, we developed a big data platform to store, process, and analyze effectively on such education longitudinal study data. And it was applied to the Seoul Education Longitudinal Study(SELS) to confirm its usefulness. The developed platform consists of data preprocessing unit and data analysis unit. The data preprocessing unit 1) masking, 2) converts each item into a factor 3) normalizes / creates dummy variables 4) data derivation, and 5) data warehousing. The data analysis unit consists of OLAP and data mining(DM). In the multidimensional analysis, OLAP is performed after selecting a measure and designing a schema. The DM process involves variable selection, research model selection, data modification, parameter tuning, model training, model evaluation, and interpretation of the results. The data warehouse created through the preprocessing process on this platform can be shared by various researchers, and the continuous accumulation of data sets makes further analysis easier for subsequent researchers. In addition, policy-makers can access the SELS data warehouse directly and analyze it online through multi-dimensional analysis, enabling scientific decision making. To prove the usefulness of the developed platform, SELS data was built on the platform and OLAP and DM were performed by selecting the mathematics academic achievement as a measure, and various factors affecting the measurements were analyzed using DM techniques. This enabled us to quickly and effectively derive implications for data-based education policies.

• Journal of the Earthquake Engineering Society of Korea
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• v.22 no.3
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• pp.201-210
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• 2018

The improvement in computing systems and sensor technologies devotes to conduct data-driven structural health monitoring algorithms for existing civil infrastructures. Despite of the development of techniques, the uncertainty oriented from the measurement results in the discrepancy to the actual structural parameters and let engineers or decision makers hesitate to adopt such techniques. Many studies have shown that the modal identification results can be affected by the uncertainties due to the applied methods and the types of loading. This paper aims to compare the performance of modal identification methods using Structural Modal Identification Toolsuite (SMIT) which has been developed to facilitate multiple identification methods with a user-friendly designed platform. The data fed into SMIT processes three stages for the comprehensive identification including preprocessing, eigenvalue estimation, and post-processing. The seismic and white noise response for shear frame model was obtained from numerical simulation. The identified modal parameters is compared to the actual modal parameters. In order to improve the quality of coherence in identified modal parameters, several hurdles including modal phase collinearity and extended modal amplitude coherence were introduced. Numerical simulation conducted on the 5 dof shear frame model were used to validate the effectiveness of using these parameters.