• Journal of Chest Surgery
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• v.38 no.11 s.256
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• pp.761-772
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• 2005

Background: Following the implantation of heart valve prostheses, it is important to maintain therapeutic INR to reduce the risk of thromboembolism. The objective of this study was to suggest a practical dosing guideline for Korean outpatients with prosthetic heart valves managed by a pharmacist-run anticoagulation service (ACS). Material and Method: A retrospective chart review was completed for all patients enrolled in the ACS at Seoul National University Hospital from March, 1997 to September, 2000. Patients who were at least 6 months post-valve replacement and had nontherapeutic INR value (less than 2.0 or greater than 3.0) were included. The data on 688 patients (1,782 visits) requiring dosing adjustment without any known drug or food interaction with warfarin were analyzed. The amount of adjusted dose and INR changes based on the INR at the time of the event were calculated. Aortic valve replacements (AVR) patients and mitral or double valve replacement (MVR/DVR) patients were evaluated separately. Result: Two methods for the warfarin dosage adjustment were suggested: Guideline I (mg-based total weekly dose (TWD) adjustment), Guideline II (percentage-based TWD adjustment). The effectiveness of Guideline 1 was superior to Guideline II overall in patients with both AVR and MVR/DVR. Conclusion: The guideline suggested in this study could be useful when the dosage adjustment of wafarin is necessary in outpatients with mechanical heart valves.

• Journal of Korean Society of Environmental Engineers
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• v.33 no.2
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• pp.77-84
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• 2011

This study was conducted to develop a novel combined system of a hybrid rotating biological contactor (RBC) process that was composed of an attached- and suspended- biomass reactor, followed by a settler and a biological aerated filter (BAF) column to treat a high strength slaughter wastewater. Long term influences of organic and nitrogen loading rates were investigated to see how the combined system worked in terms of the removal efficiency. A synthetic wastewater containing a pork cutlet steak source (commercially available) and swine blood was used to feed the combined system. The hybrid RBC process showed excellent removals: about 95% for soluble COD and 85% for ammonium nitrogen. However, the unsettled solids seriously deteriorated the removal efficiency of total COD (TCOD) and total nitrogen (TN) in the RBC process. A significant fraction of the TCOD and suspended solids (SS) was further removed in the BAF column although the effluent quality was still unsatisfactory, giving TCOD 300 mg/L, SS 180 mg/L and TN 59 mg/L. An addition of polyaluminium chloride into the RBC effluent improved the performance of the settler and BAF, producing an excellent quality of final effluent; TCOD 16.5 mg/L, SS 0 mg/L, TN 55.5 mg/L, TP 1.3 mg/L. Therefore, it was confirmed that the combined system of hybrid RBC and BAF could treat a high strength slaughter wastewater excellently.

• 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.

• Journal of Korea Water Resources Association
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• v.52 no.10
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• pp.743-752
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• 2019

The flow in the meandering channel is characterized by the spiral motion of secondary currents that typically cause the erosion along the outer bank. Hydraulic structures, such as spur dike and groyne, are commonly installed on the channel bottom near the outer bank to mitigate the strength of secondary currents. This study is to investigate the effects of submerged vanes installed in a $90^{\circ}$ meandering channel on the development of secondary currents through three-dimensional numerical modeling using the hybrid RANS/LES method for turbulence and the volume of fluid method, based on OpenFOAM open source toolbox, for capturing the free surface at the Froude number of 0.43. We employ the second-order-accurate finite volume methods in the space and time for the numerical modeling and compare numerical results with experimental measurements for evaluating the numerical predictions. Numerical results show that the present simulations well reproduce the experimental measurements, in terms of the time-averaged streamwise velocity and secondary velocity vector fields in the bend with submerged vanes. The computed flow fields reveal that the streamwise velocity near the bed along the outer bank at the end section of bend dramatically decrease by one third of mean velocity after the installation of vanes, which support that submerged vanes mitigate the strength of primary secondary flow and are helpful for the channel stability along the outer bank. The flow between the top of vanes and the free surface accelerates and the maximum velocity of free surface flow near the flow impingement along the outer bank increases about 20% due to the installation of submerged vanes. Numerical solutions show the formations of the horseshoe vortices at the front of vanes and the lee wakes behind the vanes, which are responsible for strong local scour around vanes. Additional study on the shapes and arrangement of vanes is required for mitigate the local scour.