• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.342-346
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• 1997

In the recent competitive market situation, the product development lead-time plays a significant role for the success of a manufacting company. One of the most important efforts required is reducing the design lead-time by managing all the necessary technical information related to the design process. In this paper,the data model for an engineering data management system for machine tools is described by applying object-oriented modeling technique. The design objects and their structure are defined regarding the functions such as version control, configuration management, and technical document management, and are implemented using an object-relational database management system. The suggested model takes into special account the characteristics of machining centers.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.198-201
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• 1999

An automated storage and retrieval machinery for high rack warehouse systems is developed in order to stack the various kinds of productions. However, according to increase in the rack height, the long lead time should be taken. In stacker crane systems, the variations of the lifting height and the load generate the vibration of lifting machine, and it makes a Position control to be difficult Therefore, the reduction of vibration will be important factor for saving the lead time and the damage of Productions. This paper deals with a position control of stacker crane in automated high rack warehouse system by using a gain-scheduled control algorithm via a LMI method, where the variations of elastic coefficient of the stacker crane's post are considered.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.378-384
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• 2002

In this paper, we propose a mixed integer optimization approach for solving the inventory problem with variable lead time, reorder point, crashing cost and price -quantity discount. Chang and Chang[15] study a continuous review inventory model in which lead time is a decision variable under price-quantity discount. However, their study cannot find the optimal solution due to the flaws in the modeling and the solution procedure. We present a complete procedure to find the optimal solution for the model. In addition to the above contribution, we also apply the minimax distribution free approach to the model to devise a practical procedure which can be used without specific information on demand distribution.

• Proceedings of the Korea Water Resources Association Conference
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• 2002.05a
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• pp.43-50
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• 2002

Accurate quantitative forecasting of rainfall for basins with a short response time is essential to predict streamflow and flash floods. Previously, neural networks were used to develop a Quantitative Precipitation Forecasting (QPF) model that highly improved forecasting skill at specific locations in Pennsylvania, using both Numerical Weather Prediction (NWP) output and rainfall and radiosonde data. The objective of this study was to improve an existing artificial neural network model and incorporate the evolving structure and frequency of intense weather systems in the mid-Atlantic region of the United States for improved flood forecasting. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters as input. The convective classification and tracking system (CCATS) was used to identify and quantify storm properties such as life time, area, eccentricity, and track. As in standard expert prediction systems, the fundamental structure of the neural network model was learned from the hydroclimatology of the relationships between weather system, rainfall production and streamflow response in the study area. The new Quantitative Flood Forecasting (QFF) model was applied to predict streamflow peaks with lead-times of 18 and 24 hours over a five year period in 4 watersheds on the leeward side of the Appalachian mountains in the mid-Atlantic region. Threat scores consistently above .6 and close to 0.8 ∼ 0.9 were obtained fur 18 hour lead-time forecasts, and skill scores of at least 4％ and up to 6％ were attained for the 24 hour lead-time forecasts. This work demonstrates that multisensor data cast into an expert information system such as neural networks, if built upon scientific understanding of regional hydrometeorology, can lead to significant gains in the forecast skill of extreme rainfall and associated floods. In particular, this study validates our hypothesis that accurate and extended flood forecast lead-times can be attained by taking into consideration the synoptic evolution of atmospheric conditions extracted from the analysis of large-area remotely sensed imagery While physically-based numerical weather prediction and river routing models cannot accurately depict complex natural non-linear processes, and thus have difficulty in simulating extreme events such as heavy rainfall and floods, data-driven approaches should be viewed as a strong alternative in operational hydrology. This is especially more pertinent at a time when the diversity of sensors in satellites and ground-based operational weather monitoring systems provide large volumes of data on a real-time basis.

• Journal of electromagnetic engineering and science
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• v.6 no.4
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• pp.209-216
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• 2006

This paper investigates a distinct set of complex unitary matrices for QPSK differential space time coding. After properly selecting the initial transmission matrix and unitary matrices we find that the different combinations of them could lead different BER performance over slow/fast Rayleigh fading channels and antennas correlated channels. The numerical results show that the proper selection of the initial transmission matrix and the set of unitary matrices can efficiently improve the bit error rate performance, especially for the antennas correlated fading channel. The computer simulations are evaluated over slow and fast Rayleigh fading channels.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.257-258
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• 2007

In real-time video communications, the large fluctuation of bits generated from contiguous frames may lead to the buffer oveflow and the delay of transmitting video data. This paper proposes a method that the bits generated from each frame may be in the range of specified fluctuation. The method uses a scene change detector and ignores the time information of detected frames. The experimental results indicate that our scheme achieves average PSNR gain of 2.0dB over TMN8.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.146-146
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• 2022

A flash flood is one of the most hazardous natural events caused by heavy rainfall in a short period of time in mountainous areas with steep slopes. Early warning of flash flood is vital to minimize damage, but challenges remain in the enhancing accuracy and reliability of flash flood forecasts. The forecasters can easily determine whether flash flood is occurred using the flash flood guidance (FFG) comparing to rainfall volume of the same duration. In terms of this, the hydrological model that can consider the basin characteristics in real time can increase the accuracy of flash flood forecasting. Also, the predicted radar rainfall has a strength for short-lead time can be useful for flash flood forecasting. Therefore, using both hydrological models and radar rainfall forecasts can improve the accuracy of flash flood forecasts. In this study, FFG was applied to simulate some flash flood events in the Taehwa river basin by using of SURR model to consider soil moisture, and applied to the flash flood forecasting using predicted radar rainfall. The hydrometeorological data are gathered from 2011 to 2021. Furthermore, radar rainfall is forecasted up to 6-hours has been used to forecast flash flood during heavy rain in August 2021, Wulsan area. The accuracy of the predicted rainfall is evaluated and the correlation between observed and predicted rainfall is analyzed for quantitative evaluation. The results show that with a short lead time (1-3hr) the result of forecast flash flood events was very close to collected information, but with a larger lead time big difference was observed. The results obtained from this study are expected to use for set up the emergency planning to prevent the damage of flash flood.

• Journal of Satellite, Information and Communications
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• v.11 no.3
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• pp.119-122
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• 2016

Feature detection is recognized as an accurate spectrum sensing approach when the information of the desired signal is partly known at the receiver. This type of detection was proposed to overcome large noise environment. Cyclostationary detection is an example of feature detection in spectrum sensing technique in cognitive radio. However, the cyclostationary process calculation requires a lot of processing time and information about the designed signals. On the other hand, energy detection spectrum sensing is widely known as a simple and compact spectrum sensing technique. However, energy detection is highly affected by large noise and lead to high detection error probability. In this paper, the combination of energy detection and cyclostationary is proposed in order to increase the accuracy and decrease the calculation and processing time. The two-layer threshold is utilized in order to reduce the complexity of computation and processing time in cyclostationary which can lead to the improved throughput of the system. The simulation result shows that the implementation of energy-based cyclostationary detector can help to improve the performance of the system while it can considerably reduce the required time for signal detection.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.2
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• pp.89-98
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• 2007

In this paper the economic value of weather forecasts is valuated for profit-oriented enterprise decision-making situations. Value is estimated in terms of monetary profits (or benefits) resulted from the forecast user's decision under the specific payoff structure, which is represented by a profit/loss ratio model combined with a decision function and a value score (VS). The forecast user determines a business-related decision based on the probabilistic forecast, the user's subjective reliability of the forecasts, and the payoff structure specific to the user's business environment. The VS curve for a meteorological forecast is specified by a function of the various profit/loss ratios, providing the scaled economic value relative to the value of a perfect forecast. The proposed valuation method based on the profit/loss ratio model and the VS is adapted for hypothetical sets of forecasts and verified for site-specific probability of precipitation forecast of 12 hour and 24 hour-lead time, which is generated from Korea meteorological administration (KMA). The application results show that forecast information with shorter lead time can provide the decision-makers with great benefits and there are ranges of profit/loss ratios in which high subjective reliability of the given forecast is preferred.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.30-37
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• 2020

In the building construction, the steel-frame work occupies an important position in terms of structure, cost and quality. Especially in Japan, steel frames have traditionally been the main structure of many buildings. For steel-frame works in such positions, this paper investigates an existing steel fabricator to clarify the actual conditions of design decision making process and management method in steel production process. This study focuses on a steel fabricator (Company M in the following sentences), whose main market is Japan and which has facilities in Thailand, China, and Japan. Company M uses QR codes to control the production status of products, and exchanges all information between inside and outside the company via specialized departments in the form of documents. The authors have already analyzed the relationship between production lead time and defect rate based on actual project data at Architectural Institute of Japan in 2016. In 2019, we expressed the process from the confirmation of the design information of the current steel frame to the production by WBS, and clarified the relationship between the production lead time and steel frame product quality structurally. In this paper, the authors reoport the progress of the survey conducted so far, the positioning of the collected data, and the future survey policy.