• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.39-39
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• 2012

Data assimilation techniques have received growing attention due to their capability to improve prediction in various areas. Despite of their potentials, applicable software frameworks to probabilistic approaches and data assimilation are still limited because the most of hydrologic modelling software are based on a deterministic approach. In this study, we developed a hydrological modelling framework for sequential data assimilation, namely MPI-OHyMoS. MPI-OHyMoS allows user to develop his/her own element models and to easily build a total simulation system model for hydrological simulations. Unlike process-based modelling framework, this software framework benefits from its object-oriented feature to flexibly represent hydrological processes without any change of the main library. In this software framework, sequential data assimilation based on the particle filters is available for any hydrologic models considering various sources of uncertainty originated from input forcing, parameters and observations. The particle filters are a Bayesian learning process in which the propagation of all uncertainties is carried out by a suitable selection of randomly generated particles without any assumptions about the nature of the distributions. In MPI-OHyMoS, ensemble simulations are parallelized, which can take advantage of high performance computing (HPC) system. We applied this software framework for several catchments in Japan using a distributed hydrologic model. Uncertainty of model parameters and radar rainfall estimates is assessed simultaneously in sequential data assimilation.

• Journal of Construction Engineering and Project Management
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• v.5 no.1
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• pp.11-19
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• 2015

This paper presents optimized artificial neural networks (ANNs) claims prediction and decision awareness framework that guides owner organizations in their pre-bid construction project decisions to minimize claims. The framework is composed of two genetic optimization ANNs models: a Claims Impact Prediction Model (CIPM), and a Decision Awareness Model (DAM). The CIPM is composed of three separate ANNs that predict the cost and time impacts of the possible claims that may arise in a project. The models also predict the expected types of relationship between the owner and the contractor based on their behavioral and technical decisions during the bidding phase of the project. The framework is implemented using actual data from international projects in the Middle East and Egypt (projects owned by either public or private local organizations who hired international prime contractors to deliver the projects). Literature review, interviews with pertinent experts in the Middle East, and lessons learned from several international construction projects in Egypt determined the input decision variables of the CIPM. The ANNs training, which has been implemented in a spreadsheet environment, was optimized using genetic algorithm (GA). Different weights were assigned as variables to the different layers of each ANN and the total square error was used as the objective function to be minimized. Data was collected from thirty-two international construction projects in order to train and test the ANNs of the CIPM, which predicted cost overruns, schedule delays, and relationships between contracting parties. A genetic optimization backward analysis technique was then applied to develop the Decision Awareness Model (DAM). The DAM combined the three artificial neural networks of the CIPM to assist project owners in setting optimum values for their behavioral and technical decision variables. It implements an intelligent user-friendly input interface which helps project owners in visualizing the impact of their decisions on the project's total cost, original duration, and expected owner-contractor relationship. The framework presents a unique and transparent hybrid genetic algorithm-ANNs training and testing method. It has been implemented in a spreadsheet environment using MS Excel$^{(R)}$ and EVOLVERTM V.5.5. It provides projects' owners of a decision-support tool that raises their awareness regarding their pre-bid decisions for a construction project.

• International Journal of Control, Automation, and Systems
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• v.6 no.3
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• pp.327-338
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• 2008

A fault tolerant control system design technique has been proposed and analyzed for managing performance degradation in the presence of multiple faults in actuators. The method is based on a control structure with a model reference reconfigurable control design in an inner loop and command input adjustment in an outer loop. The reduced dynamic performance requirements in the presence of different actuator faults are accounted for through different performance reduced (degraded) reference models. The degraded steady-state performances are governed by the reduced levels of command input. The reconfigurable controller is designed on-line automatically in an explicit model reference control framework so that the dynamics of the closed-loop system follow that of the performance reduced reference model under each fault condition. The reduced command input level is determined to prevent potential actuator saturation. The proposed method has been evaluated and analyzed using an aircraft example against actuator faults subject to constraints on the magnitude and slew-rate of actuators.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.1
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• pp.84-99
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• 2014

In this study, determinant input-output variables are identified for calculating Data Envelopment Analysis (DEA) efficiency scores relating to evaluating the efficiency of government-sponsored research and development (R&D) projects. In particular, this study proposes a systematic framework of design and analysis of experiments, called "all possible DEAs", for pinpointing DEA determinant input-output variables. In addition to correlation analyses, two modified measures of time series analysis are developed in order to check the similarities between a DEA complete data structure (CDS) versus the rest of incomplete data structures (IDSs). In this empirical analysis, a few DEA determinant input-output variables are found to be associated with a typical public R&D performance evaluation logic model, especially oriented to a mid- and long-term performance perspective. Among four variables, only two determinants are identified : "R&D manpower" ($x_2$) and "Sales revenue" ($y_1$). However, it should be pointed out that the input variable "R&D funds" ($x_1$) is insignificant for calculating DEA efficiency score even if it is a critical input for measuring efficiency of a government-sonsored R&D project from a practical point of view a priori. In this context, if practitioners' top priority is to see the efficiency between "R&D funds" ($x_1$) and "Sales revenue" ($y_1$), the DEA efficiency score cannot properly meet their expectations. Therefore, meticulous attention is required when using the DEA application for public R&D performance evaluation, considering that discrepancies can occur between practitioners' expectations and DEA efficiency scores.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.11-19
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• 2014

The natural user interface/experience (NUI/NUX) is used for the natural motion interface without using device or tool such as mice, keyboards, pens and markers. Up to now, typical motion recognition methods used markers to receive coordinate input values of each marker as relative data and to store each coordinate value into the database. But, to recognize accurate motion, more markers are needed and much time is taken in attaching makers and processing the data. Also, as NUI/NUX framework being developed except for the most important intuition, problems for use arise and are forced for users to learn many NUI/NUX framework usages. To compensate for this problem in this paper, we didn't use markers and implemented for anyone to handle it. Also, we designed multi-modal NUI/NUX framework controlling voice, body motion, and facial expression simultaneously, and proposed a new algorithm of mouse operation by recognizing intuitive hand gesture and mapping it on the monitor. We implement it for user to handle the "hand mouse" operation easily and intuitively.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.6 no.4
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• pp.8-16
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• 2003

In terms of climate change communities have only during the 1990s begun to recognize that all greenhouse gas(GHG) emissions are directly or indirectly generated locally, through acts of agency, production or consumption. This has provided a boost to the role of local places in the debate since GHGs can be allocated and made understood locally and hence form the basis for specific policies, programs, plans and projects. The objectives of this study are to define a framework for making Environmentally Friendly City through enhancing integrated energy-urban policies and present framework to do comprehensive evaluation on energy related policies response and also explore the interrelation between energy related activities in each sector and policy and applies to Seoul mega city in Korea. Despite the growing recognition of the seriousness of urban environmental problems and their contribution to global environmental and social concerns, most analysts continue to study cities in parts rather than as a whole; we study sectoral sub-systems such as transport, air pollution or energy. While specialization is useful for detailed thinking, we also need to see each issue in the context of how each city works environmentally, economically, socially and politically. We therefore need integrative approaches to study of cities and need to understand how they function as systems. These framework presented in this study allows an organized and systematic analysis. These research results can provide useful, credible and timely input into the urban planning process. This study will be a helpful exercise to draw some policy implications of other cities in Korea and also East Asia that are in a similar stage with the these cities and developing plans on how to address them.

• Journal of Broadcast Engineering
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• v.21 no.1
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• pp.11-23
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• 2016

Recent days, touch interaction interface is the most widely used interaction interface to communicate with digital devices. Because of its usability, touch technology is applied almost everywhere from watch to advertising boards and it is growing much bigger. However, this technology has a critical weakness. Normally, touch input device needs a contact surface with touch sensors embedded in it. Thus, touch interaction through general objects like books or documents are still unavailable. In this paper, a human-object interaction framework based on RGB-D camera is proposed to overcome those limitation. The proposed framework can deal with occluded situations like hovering the hand on top of the object and also moving objects by hand. In such situations object recognition algorithm and hand gesture algorithm may fail to recognize. However, our framework makes it possible to handle complicated circumstances without performance loss. The framework calculates the status of the object with fast and robust object recognition algorithm to determine whether it is an object or a human hand. Then, the hand gesture recognition algorithm controls the context of each object by gestures almost simultaneously.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.11
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• pp.718-724
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• 2017

Considerable efforts have been made to expand the boundaries of domestic offshore plant industries, which have focused on the construction of the structures, to the engineering field. On the other hand, time domain analysis, which is one of the most important areas in designing floating offshore plants, relies mainly on the information given by foreign companies. As an early design of the Dynamic Positioning System (DPS) is mostly conducted by several specialized companies, domestic ship builders need to spend time and money to reflect the analysis into the hull shape design. This paper presents the framework required to analyze time domain performance of floating type offshore structures, which are equipped with DPS. To easily perform time domain analysis, framework generates the required input data for the solver, and is modularized to test the control algorithm and performance of a certain DPS. The effectiveness of the developed framework was verified by a simulation with a model ship and the total time for the entire analysis work was reduced by 50% or more.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.3
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• pp.125-134
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• 2014

This paper proposes a multi-agent message transport architecture to support application areas which need fast message communications for close collaboration among agents. In the FIPA(Foundation of Intelligent Physical Agents) agent platform, all message transfer services among agents are in charge of a conceptual entity named ACC(Agent Communication Channel). In our multi-agent message transport architecture, the ACC is represented as a set of system agents named MTSA(Message Transfer Service Agent). The MTSA enables close collaboration among agents by supporting asynchronous communication, by using Reactor pattern to handle agent input messages efficiently, and by selecting optimal message transfer protocols according to the relative positional relationships of sender agents and receiver agents. The multi-agent framework SMAF(Small Multi-Agent Framework), which is implemented on the proposed multi-agent message transport architecture, shows better performance on message transfer among agents than JADE(Java Agent Development Environment) which is a well-known FIPA-compliant multi-agent framework. The faster the speed of message transfer of a multi-agent architecture becomes, the wider application areas the architecture can support.

• The Journal of the Korea Contents Association
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• v.10 no.6
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• pp.134-143
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• 2010

This paper proposes a framework for classifying metric-based software quality prediction models, especially case of software criticality, into four types. Models are classified along two vectors: input metric forms and the necessity of past project data. Each type has its own characteristics and its strength and weakness are compared with those of other types using newly defined criteria. Through this qualitative evaluation each organization can choose a proper model to suit its environment. My earlier studies of criticality prediction model implemented specific models in each type and evaluated their prediction performances. In this paper I analyze the experimental results and show that the characteristics of a model type is the another key of successful model selection.