• Journal of Soil and Groundwater Environment
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• v.7 no.3
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• pp.103-114
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• 2002

Knowledge of soil water retention characteristic is essential for many problems involving water flow and organic solute transport in unsaturated soils. A physico-empirical approach based on the translation of the particle-size distribution (PSD) into a corresponding water retention curve has been accomplished by others using the concept that the pore-size distribution is directly related to PSD. This approach implies that details of a PSD curve may affect the estimation of water retention characteristic (WRC). To determine whether the WRC estimation using the Arya-Paris model could be affected by the selection of a PSD model, four PSD models with one to four fitting parameters were used. The Jaky model with only one fitting parameter had greater WRC estimation ability than other models with greater number of fitting parameters. The better performance of the Jaky model may be explained by the effect of soil structure in field soils.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.1
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• pp.15-21
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• 2023

This paper is a study on the development of an artificial intelligence model that recognizes a hole cup on a golf green. A CNN-based object detection algorithm was used to recognize the hole cup on the green. Also, Apple's CreateML was used to create a model of the object detection algorithm. This paper created a JSON file with 120 training images and annotations to meet the needs of CreateML. In addition, for more accurate learning, data amplification algorithm was used for learning data and 288 learning data were used for learning. By changing the Iterations, Batch size, and Grid size required by CreateML, we found parameter values that improve the performance of the model. A prototype app was developed by applying the developed model, and performance was measured on an actual golf course green using the prototype app. As a result of the measurement, it was found that the hole cup was accurately recognized within 10m, which is the typical golfer's putting distance.

• Biotechnology and Bioprocess Engineering:BBE
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• v.4 no.1
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• pp.51-58
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• 1999

A mathematical model for a three phase fluidized bed bioreactor (TFBBR) was proposed to describe oxygen utilization rate, biomass concentration and the removal efficiency of Chemical Oxygen Demand (COD) in wastewater treatment. The model consisted of the biofilm model to describe the oxygen uptake rate and the hydraulic model to describe flow characteristics to cause the oxygen distribution in the reactor. The biofilm model represented the oxygen uptake rate by individual bioparticle and the hydrodynamics of fluids presented an axial dispersion flow with back mixing in the liquid phase and a plug flow in the gas phase. The difference of setting velocity along the column height due to the distributions of size and number of bioparticle was considered. The proposed model was able to predict the biomass concentration and the dissolved oxygen concentration along the column height. The removal efficiency of COD was calculated based on the oxygen consumption amounts that were obtained from the dissolved oxygen concentration. The predicted oxygen concentration by the proposed model agreed reasonably well with experimental measurement in a TFBBR. The effects of various operating parameters on the oxygen concentration were simulated based on the proposed model. The media size and media density affected the performance of a TFBBR. The dissolved oxygen concentration was significantly affected by the superficial liquid velocity but the removal efficiency of COD was significantly affected by the superficial gas velocity.

• Annual Conference of KIPS
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• 2011.04a
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• pp.163-164
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• 2011

본고에서는 Multi-class Jobs을 Dispatching system 에서 처리하는 경우, Cost performance 을 점근적으로 해석하는 과정에 대해 논의한다. 구체적으로, Job 할당 시스템은 Size-Interval 기반의 스케줄링 기법을 이용하고, Resource failure 에 대비하여 Job duplication 전략을 활용하는 것으로 가정 한다.

• Journal of the Korea Institute of Military Science and Technology
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• v.27 no.3
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• pp.346-354
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• 2024

Deep learning models require high computing power due to a substantial amount of computation. It is difficult to use them in devices with limited computing environments, such as coastal surveillance equipments. In this study, a lightweight model is constructed by analyzing the weight changes of the convolutional layers during the training process based on MobileNet and then pruning the layers that affects the model less. The performance comparison results show that the lightweight model maintains performance while reducing computational load, parameters, model size, and data processing speed. As a result of this study, an effective pruning method for constructing lightweight deep learning models and the possibility of using equipment resources efficiently through lightweight models in limited computing environments such as coastal surveillance equipments are presented.

• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.371-381
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• 2017

The performance of the statistical context-sensitive spelling error correction depends on the quality and quantity of the data for statistical language model. In general, the size and quality of data in a statistical language model are proportional. However, as the amount of data increases, the processing speed becomes slower and storage space also takes up a lot. We suggest the improved statistical language model to solve this problem. And we propose an effective spelling error candidate generation method based on a new statistical language model. The proposed statistical model and the correction method based on it improve the performance of the spelling error correction and processing speed.

• KIEE International Transactions on Power Engineering
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• v.12A no.1
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• pp.1-5
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• 2002

This paper presents the procedure to construct equivalent model of large power system based on nonlinear time simulation responses. It consists of coherency identification, generator aggregation and network reduction. Coherency index that can be directly implemented to this procedure is proposed. Generator aggregation based on detailed model is performed. This procedure can be used to construct equivalent model in PSS/E. It is also possible to reduce the large power system directly from the nonlinear time responses. This procedure is applied to the transient stability analysis of Korea power system that now experiences rapid changes. The equivalent model is compared with the original model in its size, accuracy, speed and performance. This paper shows that the developed equivalent model is a good estimate of the original system.

• The Journal of the Acoustical Society of Korea
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• v.30 no.3
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• pp.123-128
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• 2011

In this paper, we propose the improved noise power estimation in speech enhancement under various noise environments. The previous MS algorithm tracking the minimum value of finite search window uses the optimal power spectrum of signal for smoothing and adopts minimum probability. From the investigation of the previous MS-based methods it can be seen that a fixed size of the minimum search window is assumed regardless of the various environment. To achieve the different search window size, we use the noise classification algorithm based on the Gaussian mixture model (GMM). Performance of the proposed enhancement algorithm is evaluated by ITU-T P.862 perceptual evaluation of speech quality (PESQ) under various noise environments. Based on this, we show that the proposed algorithm yields better result compared to the conventional MS method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.1
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• pp.165-182
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• 2014

An RFID systems employ efficient Anti-Collision Algorithms (ACAs) to enhance the performance in various applications. The EPC-Global G2 RFID system utilizes Frame Slotted Aloha (FSA) as its ACA. One of the common approaches used to maximize the system performance (tag identification efficiency) of FSA-based RFID systems involves finding the optimal value of the frame length relative to the contending population size of the RFID tags. Several analytical models for finding the optimal frame length have been developed; however, they are not perfectly optimized because they lack precise characterization for the timing details of the underlying ACA. In this paper, we investigate this promising direction by precisely characterizing the timing details of the EPC-Global G2 protocol and use it to derive a precise-optimal frame length model. The main objective of the model is to determine the optimal frame length value for the estimated number of tags that maximizes the performance of an RFID system. However, because precise estimation of the contending tags is difficult, we utilize a parametric-heuristic approach to maximize the system performance and propose two simple schemes based on the obtained optimal frame length-namely, Improved Dynamic-Frame Slotted Aloha (ID-FSA) and Exponential Random Partitioning-Frame Slotted Aloha (ERP-FSA). The ID-FSA scheme is based on the tag set estimation and frame size update mechanisms, whereas the ERP-FSA scheme adjusts the contending tag population in such a way that the applied frame size becomes optimal. The results of simulations conducted indicate that the ID-FSA scheme performs better than several well-known schemes in various conditions, while the ERP-FSA scheme performs well when the frame size is small.

• Korean System Dynamics Review
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• v.7 no.1
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• pp.27-49
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• 2006

A system dynamics model is developed to investigate the applicability of the agent based modeling concept in the system dynamics model. The assumed problem is to forecast the size and structure of the organization with the developing market environment. The agent based modeling concept is applied to the organization part, and the other parts of the model such as market, facilities, etc. are developed with the traditional system dynamics technique. The simulation results show the agent based modeling part can be combined with the traditional system dynamics modeling with more precisions. However, the complexity increases and the simulation times are longer than those of the traditional method.