• Journal of Soil and Groundwater Environment
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• v.11 no.2
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• pp.45-55
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• 2006

A 2-D unconfined flow model is developed to analyze annual variations of groundwater level and bank filtration rate (BFR) for an experimental riverbank filtration site in Koryeong, Korea. Two types of boundary conditions are examined for the river boundary in the conceptual model: the static head condition that uses the average water level of the river and the dynamic cyclic condition that incorporates annual fluctuation of water level. Simulations show that the estimated BFR ranges $74.3{\sim}87.0%$ annually with the mean of 82.4% for the static head boundary condition and $52.7{\sim}98.1%$ with the mean of 78.5% for the dynamic cyclic condition. The results illustrate that the dynamic cyclic condition should be used for accurate evaluation of BFR. Simulations also show that increase of the distance between the river and the pumping wells slightly decreases BFR up to 4%, and thereby indicate that it is not a critical factor to be accounted for in designing BFR of the bank filtration system. A sensitivity analysis is performed to examine the effects of model parameters such as hydraulic conductivity and specific yield of the aquifer, recharge rate, and pumping rate. The results demonstrate that the average groundwater level and BFR are most sensitive to both the pumping rate and the recharge rate, while the water level of the pumping wells is sensitive to the hydraulic conductivity and the pumping rate.

• The KIPS Transactions:PartA
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• v.12A no.6 s.96
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• pp.557-562
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• 2005

Throughput and latency of interconnection network are important factors of the performance of multiprocessor systems. The dual-link CC-NUMA architecture using point-to-point unidirectional link is one of the popular structures in high-end commercial systems. In terms of optimal path between nodes, several paths exist with the optimal hop count by its native multi-path structure. Furthermore, transaction latency between nodes is affected by congestion of links on the transaction path. Hence the transaction latency may get worse if the transactions make a hot spot on some links. In this paper, I propose a dynamic transaction routing algorithm that maintains the balanced link utilization with the optimal path length, and I compare the performance with the fixed path method on the dual-link CC-NUMA systems. By the proposed method, the link competition is alleviated by the real-time path selection, and consequently, dynamic transaction algorithm shows a better performance. The program-driven simulation results show $1{\~}10\%$ improved fluctuation of link utilization, $1{\~}3\%$ enhanced acquirement of link, and $1{\~}6\%$ improved system performance.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.119-142
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• 2015

With the explosive growth in the volume of information, Internet users are experiencing considerable difficulties in obtaining necessary information online. Against this backdrop, ever-greater importance is being placed on a recommender system that provides information catered to user preferences and tastes in an attempt to address issues associated with information overload. To this end, a number of techniques have been proposed, including content-based filtering (CBF), demographic filtering (DF) and collaborative filtering (CF). Among them, CBF and DF require external information and thus cannot be applied to a variety of domains. CF, on the other hand, is widely used since it is relatively free from the domain constraint. The CF technique is broadly classified into memory-based CF, model-based CF and hybrid CF. Model-based CF addresses the drawbacks of CF by considering the Bayesian model, clustering model or dependency network model. This filtering technique not only improves the sparsity and scalability issues but also boosts predictive performance. However, it involves expensive model-building and results in a tradeoff between performance and scalability. Such tradeoff is attributed to reduced coverage, which is a type of sparsity issues. In addition, expensive model-building may lead to performance instability since changes in the domain environment cannot be immediately incorporated into the model due to high costs involved. Cumulative changes in the domain environment that have failed to be reflected eventually undermine system performance. This study incorporates the Markov model of transition probabilities and the concept of fuzzy clustering with CBCF to propose predictive clustering-based CF (PCCF) that solves the issues of reduced coverage and of unstable performance. The method improves performance instability by tracking the changes in user preferences and bridging the gap between the static model and dynamic users. Furthermore, the issue of reduced coverage also improves by expanding the coverage based on transition probabilities and clustering probabilities. The proposed method consists of four processes. First, user preferences are normalized in preference clustering. Second, changes in user preferences are detected from review score entries during preference transition detection. Third, user propensities are normalized using patterns of changes (propensities) in user preferences in propensity clustering. Lastly, the preference prediction model is developed to predict user preferences for items during preference prediction. The proposed method has been validated by testing the robustness of performance instability and scalability-performance tradeoff. The initial test compared and analyzed the performance of individual recommender systems each enabled by IBCF, CBCF, ICFEC and PCCF under an environment where data sparsity had been minimized. The following test adjusted the optimal number of clusters in CBCF, ICFEC and PCCF for a comparative analysis of subsequent changes in the system performance. The test results revealed that the suggested method produced insignificant improvement in performance in comparison with the existing techniques. In addition, it failed to achieve significant improvement in the standard deviation that indicates the degree of data fluctuation. Notwithstanding, it resulted in marked improvement over the existing techniques in terms of range that indicates the level of performance fluctuation. The level of performance fluctuation before and after the model generation improved by 51.31% in the initial test. Then in the following test, there has been 36.05% improvement in the level of performance fluctuation driven by the changes in the number of clusters. This signifies that the proposed method, despite the slight performance improvement, clearly offers better performance stability compared to the existing techniques. Further research on this study will be directed toward enhancing the recommendation performance that failed to demonstrate significant improvement over the existing techniques. The future research will consider the introduction of a high-dimensional parameter-free clustering algorithm or deep learning-based model in order to improve performance in recommendations.

• The Korean Journal of Rheology
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• v.11 no.2
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• pp.82-90
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• 1999

Electrorheological(ER) fluid is a material that shows the dramatic change of rheological properties under an electric field and responds reversibly in a few milliseconds. ER fluid's response to an electric field along with its fast switching capability allows ER devices to be precisely controlled. The real application with ER fluid, however, has many limitations to be overcome; temperature fluctuation, moisture, dust, aggregation, precipitation, and low yield stress, for example. The magnitude and the characteristics of yield stress of ER fluid plays an important role in practical applications. In this research, a dynamic simulation on the squeezing flow of the ER fluid was carried out. Numerical simulation on isolated chains was performed to find out the effect of hydrodynamic and electrostatic force depending on the chain location, the squeezing rate, and the chain structure. Suspension model that is composed of a large number of particles was also investigated. The increase of normal stresses as well as the existence of a yield stress at an earlier stage could be observed, and the effective control of the normal stresses could be achieved at an optimal condition of the hydrodynamic force and the electrostatic force.

• Journal of Korea Port Economic Association
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• v.33 no.1
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• pp.47-59
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• 2017

The objective of this study is to determine the short run and long run dynamics between maritime import volume (IMV), industrial production (IP), and real effective exchange rate (REER) of the Korean Won over the REER of certain major currencies (US Dollar, Chinese Yuan, and Japanese Yen) in Korea's Jeonnam province. The Johansen and Juselius cointegration results reveal that at least one cointegration vector or long-run relationship exists. Hence, this study estimated the long run equilibrium equation, which indicates that both IP and REER are inelastic, although the former is bigger than the latter. Moreover, the dynamic causality analysis reveals short and long-run unidirectional causality from IP and REER to IMV in all three models. Further, in all the models, the results indicate short run unidirectional causality from REER to IP. In addition, the impulse response (IR) results show that the impulse of IP and REER decayed after four months. Additionally, the IR analysis results indicate that the REER of the Korean Won over the REER of Japanese Yen is the biggest with respect to the impact of relative REER on IP, which is the proxy variable of regional real income. Thus, empirical results indicated that real income and REER play an important role in determining the Jeonnam's maritime import demand behavior in the short run and long run. More importantly, substantial actions reducing unexpected fluctuation of the REER and real income based on micro and macro economic policies will increase the imported volume in the ports of the Jeonnam province.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.11
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• pp.24-35
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• 2012

In this paper, we propose a dynamic lane control scheme with a traffic predictor module and a rate controller for reconciling with commercial optical PHY modules in energy efficient optical Ethernet systems. The commercial high speed optical Ethernet system capable of 40/100Gbps employs 4 or 10 multiple optical transceivers over WDM or multiple optical links. Each of the transceivers is always turned on even if the link is idle. To save energy, we propose the dynamic lane control scheme. It allows that several links may be entirely turned off in a low traffic load and frames are handled on the remaining active links. To preserve the byte order even if the number of active links may be changed, we propose a rate controller to be sat on the reconciliation sublayer. The main role of the controller is to insert null byte streams into the xGMII of inactive lanes. For the PHY module, the null input streams corresponding to inactive lanes will be disregarded on inactive PMDs. It is very handy to implement the rate controller module with MAC in FPGA without any modification of commercial PHYs. It is very crucial to determine the number of active links based on the fluctuated traffic load, we provide a simple traffic predictor based on both the current transmission buffer size and the past one with different weighting factors for adapting to the traffic load fluctuation. Using the OMNET++ simulation framework, we provide several performance results in terms of the energy consumption.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.251-258
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• 2012

Recently, NAND Flash memory structure is evolving from SDR (Single Data Rate) to high speed DDR(Double Data Rate) to fulfill the high performance requirement of SSD and SSS. Accordingly, the proper ways of transferring data that latches valid data stably and minimizing data skew between pins by using PHY(Physical layer) circuit techniques have became new issues. Also, rapid growth of speed in NAND flash increases the operating frequency and power consumption of NAND flash controller. Internal voltage variation margin of NAND flash controller will be narrowed through the smaller geometry and lower internal operating voltage below 1.5V. Therefore, the increase of power budge deviation limits the normal operation range of internal circuit. Affection of OCV(On Chip Variation) deteriorates the voltage variation problem and thus causes internal logic errors. In this case, it is too hard to debug, because it is not functional faults. In this paper, we propose new architecture that maintains the valid timing window in cost effective way under sudden power fluctuation cases. Simulation results show that the proposed technique minimizes the data skew by 379% with reduced area by 20% compared to using PHY circuits.

• Proceedings of the KWS Conference
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• 2002.10a
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• pp.612-619
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• 2002

The dynamic behavior of Al-Mg alloys plasma was very unstable and this instability was closely related to the unstable motion of keyhole during laser irradiation. The keyhole fluctuated both in size and shape and its fluctuation period was about 440 ${\mu}{\textrm}{m}$. This instability has been estimated to be caused by the evaporation phenomena of metals with different boiling point and latent heats of vaporization. Therefore, the authors have conducted the spectroscopic diagnostics of plasma induced in the pulsed YAG laser welding of Al-Mg alloys in air and argon atmospheres. In the air environment, the identified spectra were atomic lines of Al, Mg, Cr, Mn, Cu, Fe and Zn, and singly ionized Mg line, as well as strong molecular spectrum of AlO, MgO and AIH. It was confirmed that the resonant lines of Al and Mg were strongly self-absorbed, in particular in the vicinity of pool surface. The self-absorption of atomic Mg line was more eminent in alloys containing higher Mg. These facts showed that the laser-induced plasma was relatively a low temperature and high density metallic vapor. The intensities of molecular spectra of AlO and MgO were different each other depending on the power density of laser beam. Under the low power density irradiation condition, the MgO band spectra were predominant in intensity, while the AlO spectra became much stronger in higher power density. In argon atmosphere the band spectra of MgO and AlO completely vanished, but AlH molecular spectra was detected clearly. The hydrogen source was presumably the hydrogen solved in the base Metal, absorbed water on the surface oxide layer or H$_2$ and $H_2O$ in the shielding gas. The temporal change in spectral line intensities was quite similar to the fluctuation of keyhole. The time average plasma temperature at 1 mm high above the surface of A5083 alloy was determined by the Boltzmann plot method of atomic Cr lines of different excitation energy. The obtained electron temperature was 3, 280$\pm$150 K which was about 500 K higher than the boiling point of pure aluminum. The electron number density was determined by measuring the relative intensities of the spectra1lines of atomic and singly ionized Magnesium, and the obtained value was 1.85 x 1019 1/㎥.

• Korean Journal of Agricultural and Forest Meteorology
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• v.9 no.2
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• pp.75-87
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• 2007

Groundwater recharge rates were estimated and compared in a headwater catchment at the Gwangneung Supersite using three different methods: water-table fluctuation (WTF), mass balance, and hydrograph separation techniques. Data were obtained during the rainy season from June to September 2005. Two different WTF methods estimated the groundwater recharge rate as 25.9% and 23.6%. The mass balance calculation of chloride ions indicated recharge rates of 13.4% on average. Baseflow separation using chloride ion as a tracer from six storm hydrographs produced a 14.0% net baseflow rate on average. Because of the implicit assumption of a long-term steady state without storage change, recharge rates calculated by mass balance and hydrograph separation were smaller than those done with WTF methods, which include the amount of increased storage due to the water-level rise. Subsequently, the WTF method is superior to others in the estimation of groundwater recharge rate to comprehend the dynamic characteristics of the hydrologic cycle.

• International Journal of Control, Automation, and Systems
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• v.5 no.6
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• pp.643-651
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• 2007

The various blood pressure simulators have been proposed to evaluate and improve the performance of the automatic sphygmomanometer. These have some problems such as the deviation of the actual blood pressure waveform, limitation in the blood pressure condition of the simulator, or difficulty in displaying the blood flow. An improved simulator using disturbance observer is proposed to supplement the current problems of the blood pressure simulator. The proposed simulator has an artificial arm model capable of feeding appropriate fluids that can generate the blood pressure waveform to evaluate the automatic sphygmomanometer. A controller was designed and thereafter, simulation was performed to control the output signal with respect to the reference input in the fluid dynamic model using the proposed proportional control valve. To minimize the external fluctuation of pressure applied to the artificial arm, a disturbance observer was designed on the plant. A hybrid controller combined with a proportional controller and feed-forward controller was fabricated after applying a disturbance observer to the control plant. Comparison of the simulations between the conventional proportional controller and the proposed hybrid controller indicated that even though the former showed good control performance without disturbance, it was affected by the disturbance signal induced by the cuff. The latter exhibited an excellent performance under both situations.