• Nutrition Research and Practice
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• v.8 no.1
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• pp.103-111
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• 2014

This study aims to determine the effect of a trained dedicated dietitian on clinical outcomes among Lebanese hemodialysis (HD) patients: and thus demonstrate a viable developing country model. This paper describes the study protocol and baseline data. The study was a multicenter randomized controlled trial with parallel-group design involving 12 HD units: assigned to cluster A (n = 6) or B (n = 6). A total of 570 patients met the inclusion criteria. Patients in cluster A were randomly assigned as per dialysis shift to the following: Dedicated Dietitian (DD) (n = 133) and Existing Practice (EP) (n = 138) protocols. Cluster B patients (n = 299) received Trained Hospital Dietitian (THD) protocol. Dietitians of the DD and THD groups were trained by the research team on Kidney Disease Outcomes Quality Initiative nutrition guidelines. DD protocol included: individualized nutrition education for 2 hours/month/HD patient for 6 months focusing on renal osteodystrophy and using the Trans-theoretical theory for behavioral change. EP protocol included nutrition education given to patients by hospital dietitians who were blinded to the study. The THD protocol included nutrition education to patients given by hospital dietitian as per the training received but within hospital responsibilities, with no set educational protocol or tools. Baseline data revealed that 40% of patients were hyperphosphatemics (> 5.5 mg/dl) with low dietary adherence and knowledge of dietary P restriction in addition to inadequate daily protein intake ($58.86%{\pm}33.87%$ of needs) yet adequate dietary P intake ($795.52{\pm}366.94$ mg/day). Quality of life (QOL) ranged from 48-75% of full health. Baseline differences between the 3 groups revealed significant differences in serum P, malnutrition status, adherence to diet and P chelators and in 2 factors of the QOL: physical and social functioning. The data show room for improvement in the nutritional status of the patients. The NEMO trial may be able to demonstrate a better nutritional management of HD patients.

• Journal of the Korean Geographical Society
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• v.48 no.5
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• pp.768-785
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• 2013

Count data aggregated into areal units such as administrative boundaries are the most important sources of information for geographic research. Despite of ongoing research on spatial cluster analysis of count data, it has received relatively little attention and besides, it is difficult to comprehend research trends as well as major outcomes and challenges. This study aims to review the research literature conducted during the last two decades, to examine methodological characteristics, and finally to discuss some issues and challenges. Methods for indentifying spatial clusters have been used in various fields including geography, criminology, and epidemiology. However, their methodological features are not only quite distinct from each other, but there are issues related to the statistical reliability. Therefore, these have to be taken into account carefully when particular methods are used, and further empirical research about methodological issues and the development of analysis tools is needed.

• KIISE Transactions on Computing Practices
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• v.21 no.9
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• pp.587-595
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• 2015

Several fields of science have traditionally demanded large-scale workflow support, which requires thousands of central processing unit (CPU) cores. In order to support such large-scale scientific workflows, large-capacity cluster systems such as supercomputers are widely used. However, as users require a diversity of software packages and configurations, a system administrator has some trouble in making a service environment in real time. In this paper, we present a container-based cluster management platform and introduce an implementation case to minimize performance reduction and dynamically provide a distributed computing environment desired by users. This paper offers the following contributions. First, a container-based virtualization technology is assimilated with a resource and job management system to expand applicability to support large-scale scientific workflows. Second, an implementation case in which docker and HTCondor are interlocked is introduced. Lastly, docker and native performance comparison results using two widely known benchmark tools and Monte-Carlo simulation implemented using various programming languages are presented.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.467-477
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• 2004

While recommender systems were used by a few E-commerce sites former days, they are now becoming serious business tools that are re-shaping the world of I-commerce. And collaborative filtering has been a very successful recommendation technique in both research and practice. But there are two problems in personalized recommender systems, it is First-Rating problem and Sparsity problem. In this paper, we solve these problems using the associative relation clustering and “Lift” of association rules. We produce “Lift” between items using user's rating data. And we apply Threshold by -cut to the association between items. To make an efficiency of associative relation cluster higher, we use not only the existing Hypergraph Clique Clustering algorithm but also the suggested Split Cluster method. If the cluster is completed, we calculate a similarity iten in each inner cluster. And the index is saved in the database for the fast access. We apply the creating index to predict the preference for new items. To estimate the Performance, the suggested method is compared with existing collaborative filtering techniques. As a result, the proposed method is efficient for improving the accuracy of prediction through solving problems of existing collaborative filtering techniques.

• Genomics & Informatics
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• v.8 no.4
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• pp.170-176
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• 2010

The Ribonucleotide reductases (RNR) are essential enzymes that catalyze the conversion of nucleotides to deoxynucleotides in DNA replication and repair in all living organisms. The RNRs operate by a free radical mechanism but differ in the composition of subunit, cofactor required and regulation by allostery. Based on these differences the RNRs are classified into three classesclass I, class II and class III which depend on oxygen, adenosylcobalamin and S-adenosylmethionine with an iron sulfur cluster respectively for radical generation. In this article thirty seven sequences belonging to each of the three classes of RNR were analyzed by using various tools of bioinformatics. Phylogenetic analysis, dot-plot comparisons and motif analysis was done to identify a number of differences in the three classes of RNRs. In this research article, we have attempted to decipher evolutionary relationship between the three classes of RNR by using bioinformatics approach.

• Journal of Korea Multimedia Society
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• v.8 no.12
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• pp.1605-1612
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• 2005

This paper presents the knowledge and experience we obtained by employing multiprocessor systems as a computer simulation design verification to study high-performance computing system. This paper also describes a case study of symmetric multiprocessors (SMP) kernel on a 32 CPUs CC-NUMA architecture using an actual architecture. A small group of CPUs of CC-NUMA, high-performance computer system, is clustered into a processing node or cluster. By simulating the system design verification tools; we discussed SMP OS kernel on a CC-NUMA multiprocessor architecture performance which is $32\%$ of the total execution time and remote memory access latency is occupied $43\%$ of the OS time. In this paper, we demonstrated our simulation results for multiprocessor, high-performance computing system performance, using simulation-based design verification.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.4
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• pp.416-421
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• 2011

Recently there has been increase in need for high precision and high speed machining due to economic and environmental reasons. It is a very important issue that determines the optimal preload that is to be applied to bearings in order to satisfy the performance required in bearings according to its operation conditions. This study introduces a variable preload device that can automatically adjust the preload applied in a machine tool spindle using centrifugal force as opposed in existing rubber instrument. In this study, the deformation of the rubber device by the centrifugal force is analyzed and it is discussed that the proposed device can be worked properly through changes of the collar density.

• The Bulletin of The Korean Astronomical Society
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• v.36 no.2
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• pp.146.2-146.2
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• 2011

In this study, we have derived the abundances of several elements ? Na, Mg, Al, Si, Ca, Sc, Ti, V, Cr, Mn, Co, Ni - for the six F G K type stars in IC 2391 and the seven stars in NGC 6475. The spectra of those stars are taken from UVES POP archive data, of which resolution is 80,000. To derive the abundances of those elements, TAME (Tools for Automatic Measurement of Equivalent-widths), Kurucz stellar atmospheric model, and MOOG code are used. The stellar parameters (effective temperature, log g, metallicity, microturbulent velocity) are determined from the iron lines. The results provide the abundance differences of chemical elements between two open clusters, IC 2391 (a member of Gould Belt) and NGC 6475 (non-member of it), which would lead to better understanding about Gould Belt.

• The Korean Journal of Applied Statistics
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• v.11 no.2
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• pp.389-401
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• 1998

This paper introduces CybeRClass(Cyber Regression Class). CybeRClass uses the technique of animation arid voice to teach regression analysis. The structure of this system make it possible to extend to multivariate analysis methods such as discriminant analysis and cluster analysis. Tools for multimedia is Multimedia ToolBook, and Xlisp-Stat is used for statistical computation and statistical graphics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1825-1844
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• 2019

Political campaigns circulate manipulative opinions in online communities to implant false beliefs and eventually win elections. Not only is this type of manipulation unfair, it also has long-lasting negative impacts on people's lives. Existing tools detect political manipulation based on a supervised classifier, which is accurate when trained with large labeled data. However, preparing this data becomes an excessive burden and must be repeated often to reflect changing manipulation tactics. We propose a practical detection system that requires moderate groundwork to achieve a sufficient level of accuracy. The proposed system groups opinions with similar properties into clusters, and then labels a few opinions from each cluster to build a classifier. It also models each opinion with features deduced from raw data with no additional processing. To validate the system, we collected over a million opinions during three nation-wide campaigns in South Korea. The system reduced groundwork from 200K to nearly 200 labeling tasks, and correctly identified over 90% of manipulative opinions. The system also effectively identified transitions in manipulative tactics over time. We suggest that online communities perform periodic audits using the proposed system to highlight manipulative opinions and emerging tactics.