• Journal of KIISE
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• v.44 no.4
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• pp.383-391
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• 2017

As we enter a new era of Big Data, the amount of semantic data has rapidly increased. In order to derive meaningful information from this large semantic data, studies that utilize the SWRL(Semantic Web Rule Language) are being actively conducted. SWRL rules are based on data extracted from a user's empirical knowledge. However, conventional reasoning systems developed on single machines cannot process large scale data. Similarly, multi-node based reasoning systems have performance degradation problems due to network shuffling. Therefore, this paper overcomes the limitations of existing systems and proposes more efficient distributed inference methods. It also introduces data partitioning strategies to minimize network shuffling. In addition, it describes a method for optimizing the incremental reasoning process through data selection and determining the rule order. In order to evaluate the proposed methods, the experiments were conducted using WiseKB consisting of 200 million triples with 83 user defined rules and the overall reasoning task was completed in 32.7 minutes. Also, the experiment results using LUBM bench datasets showed that our approach could perform reasoning twice as fast as MapReduce based reasoning systems.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.10
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• pp.575-587
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• 2004

In this paper. a new Fast Expectation-Maximization algorithm(FEM) is proposed. Firstly the K-means algorithm is modified to reduce the number of iterations for finding the initial values that are used as the initial values in EM process. Conventionally the Initial values in K-means clustering are chosen randomly. which sometimes forces the process of clustering converge to some undesired center points. Uniform partitioning method is added to the conventional K-means to extract the proper initial points for each clusters. Secondly the effect of posterior probability is emphasized such that the application of Maximum Likelihood Posterior(MLP) yields fast convergence. The proposed FEM strengthens the characteristics of conventional EM by reinforcing the speed of convergence. The superiority of FEM is demonstrated in experimental results by presenting the improvement results of EM and accelerating the speed of convergence in parameter estimation procedures.

• Proceedings of the Korea Society of Environmental Toocicology Conference
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• 2003.05a
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• pp.194-194
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• 2003

The International Agency for Research on Cancer (IARC, 1989) has classified whole diesel exhaust as probably carcinogenic to humans. Diesel exhaust particulate matter (DPM) adsorbs different chemical substances including PAHs and nitroarenes. DPM is emphasized because it is a major component of diesel exhaust, it is suspected of contributing to a health hazard. Diesel exhaust is a complex mixture of carbon particles and associated organics and inorganics, and it is not known what fraction or combination of fractions cause the health effects [cancer effects, noncancer effects (respiratory tract irritation/inflammation and changes in lung function)] that have been observed with exposure to diesel exhaust. In order to identify which chemical classes are responsible for the majority of the observed biological activities, we performed a particular biological/chemical analysis. Respirable particulate matter (PM2.5: <2.5mm) was collected from diesel engine exhaust using a high-volume sampler equipped with a cascade impactor. Particulate oganic matter was extracted by the dichloromethane/sonication method and the crude extract was fractionated according to EPA recommended procedure into seven fractions by acid-base partitioning and silica gel column chromatography. We examined genotoxic potentials of diesel exhaust particulate matter using novel genotoxicity tests, which are rapid, simple and sensitive methods for assessing DNA-damage at the DNA and chromosomal level (comet assay, in vitro MN test and Ames test). Higher genotoxic potency was observed in non polar fractions and several PAHs were detected by GC-MS, such as 1,2,5,6 dibenzanthracene, chrysene, 1,2-benzanthracene, phenanthrene and fluoranthene.

• Environmental Engineering Research
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• v.14 no.3
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• pp.186-194
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• 2009

Understanding the environmental fate of human and animal pharmaceuticals and their risk assessment are of great importance due to their growing environmental concerns. Although there are many potential pathways for them to reach the environment, effluents from sewage treatment plants (STPs) are recognized as major point sources. In this study, the removal efficiencies of the 43 selected priority pharmaceuticals in a conventional STP were evaluated using two simple models: an equilibrium partitioning model (EPM) and STPWIN$^{TM}$ program developed by US EPA. It was expected that many pharmaceuticals are not likely to be removed by conventional activated sludge processes because of their relatively low sorption potential to suspended sludge and low biodegradability. Only a few pharmaceuticals were predicted to be easily removed by sorption or biodegradation, and hence a conventional STP may not protect the environment from the release of unwanted pharmaceuticals. However, the prediction made in this study strongly relies on sorption coefficient to suspended sludge and biodegradation half-lives, which may vary significantly depending on models. Removal efficiencies predicted using the EPM were typically higher than those predicted by STPWIN for many hydrophilic pharmaceuticals due to the difference in prediction method for sorption coefficients. Comparison with experimental organic carbon-water partition coefficients ($K_{ocs}) revealed that log KOW-based estimation used in STPWIN is likely to underestimate sorption coefficients, thus resulting low removal efficiency by sorption. Predicted values by the EPM were consistent with limited experimental data although this model does not include biodegradation processes, implying that this simple model can be very useful with reliable Koc values. Because there are not many experimental data available for priority pharmaceuticals to evaluate the model performance, it should be important to obtain reliable experimental data including sorption coefficients and biodegradation rate constants for the prediction of the fate of the selected pharmaceuticals.

• Journal of Intelligence and Information Systems
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• v.7 no.2
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• pp.35-49
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• 2001

Over the years, cluster analysis has become a popular tool for marketing and segmentation researchers. There are various methods for cluster analysis. Among them, K-means partitioning cluster analysis is the most popular segmentation method. However, because the cluster analysis is very sensitive to the initial configurations of the data set at hand, it becomes an important issue to select an appropriate starting configuration that is comparable with the clustering of the whole data so as to improve the reliability of the clustering results. Many programs for K-mean cluster analysis employ various methods to choose the initial seeds and compute the centroids of clusters. In this paper, we suggest a methodology to evaluate various clustering programs. Furthermore, to explore the usability of the methodology, we evaluate four clustering programs by using the methodology.

• Journal of Korea Multimedia Society
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• v.8 no.1
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• pp.79-87
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• 2005

In e-commerce applications, a public key cryptosystem is an important and indispensible element for the basic security operations such as authentication, digital signaturing, and key distribution. In wired network environments, the public key infrastructure certificate, which is based on X.509 specification, has been widely used. On the other hand, it still remains difficult to use the certificate information in wireless network environments due to the inherent limitations of the hand-held devices such as low computational power and short battery life. In this paper, we facilitate a codesign approach by implementing a software public-key cryptosystem and classifying its internal computation overheads quantitatively using a software profiling technique. Moreover, we propose a method to analyze the profiled data and apply it to the problem of software/hardware partitioning in a codesign approach. As an illustrative example, we analyze the computational overheads of an EC-Elfagamal application and examine a critical computational path.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.657-660
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• 2007

The growth of Web comics is very noticeable in Korean comic market as the 21st century is entered. In amongst these1 trends, the scroll comics had established it self as one of the main stream form for expression, outside the form of the traditional published comics, so it is providing a new visual experience for the readers. The scroll method uses the large vertical space that is uncomparable to the column compartment of the printed comics, and its uses of animation-like techniques, innovative partitioning, flob styles and narration partition positioning, the limitless canvas and the scroll bar of the web page, is leading the digital comic age. However, it is still very uncertain whether the 'scroll comics' will still be valid in the age of Web2.0. It is concerning that even though there are limitless potential in the realms of digital and web, the web comics seem to be bound to one particular medium, 'scroll'. In this report, the form of expression in the scroll centered web comics will be analyzed, and based on this, the future evolution of digital comics shall be investigated.

• Journal of KIISE:Information Networking
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• v.37 no.1
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• pp.50-56
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• 2010

This paper proposes a data gathering method by adapting the mobile sink to prolong the whole operation time of large WSNs. After partitioning a network into several clusters, a mobile sink visits each cluster and collects data from it. An efficient protocol improves the energy efficiency by delivering messages from the mobile sink to the cluster head as well as reduces the data gathering delay, which is the disadvantage of the mobile sink. For the scalability of sensor network, the network architecture should support the multihop transmission in the duster rather than the single hop transmission. The process for the data aggregation linked to the travelling path is proposed to improve the energy consumption of intermediate nodes. The experiment results show that the proposed model is more efficient than legacy methods in the energy consumption and the data gathering time.

• Journal of KIISE:Databases
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• v.34 no.6
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• pp.518-527
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• 2007

It is an important issue to find out the difference between RDF documents, because RDF documents are changed frequently. When RDF documents contain blank nodes, we need a matching technique for blank nodes in the change detection. Blank nodes have a nested form and they are used in most RDF documents. A RDF document can be modeled as a graph and it will contain many subtrees. We can consider a change detection problem as a minimum cost tree matching problem. In this paper, we propose a change detection technique for RDF documents using the labeling scheme for blank nodes. We also propose a method for improving the efficiency of general triple matching, which used predicate grouping and partitioning. In experiments, we showed that our approach was more accurate and faster than the previous approaches.

• Journal of Korean Neurosurgical Society
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• v.44 no.6
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• pp.358-363
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• 2008

Objective : This study was performed to assess the efficacy of GKS in patients with ten or more brain metastases. Methods : From Aug 2002 to Dec 2007, twenty-six patients (13 men and 13 women) with ten or more cerebral metastatic lesions underwent GKS. The mean age was 55 years (32-80). All patients had Karnofsky performance status (KPS) score of 70 or better. According to recursive partitioning analysis (RPA) classification, 3 patients belonged to class I and 23 to class II. The location of primary tumor was lung (21), breast (3) and unknown (2). The mean number of the lesions per patient was 16.6 (10-37). The mean cumulated volume was 10.9 cc (1.0-42.2). The median marginal dose was 15 Gy (9-23). Overall survival and the prognostic factors for the survival were retrospectively analyzed by using Kaplan Meier method and univariate analysis. Results : Overall median survival from GKS was 34 weeks (8-199). Local control was possible for 79.5% of the lesions and control of all the lesions was possible in at least 14 patients (53.8%) until 6 months after GKS. New lesions appeared in 7 (26.9%) patients during the same period. At the last follow-up, 18 patients died; 6 (33.3%) from systemic causes, 10 (55.6%) from neurological causes, and 2 (11.1 %) from unknown causes. Synchronous onset in non-small cell lung cancer (p=0.007), high KPS score (${\geq}80$, p=0.029), and controlled primary disease (p=0.020) were favorable prognostic factors in univariate analysis. Conclusion : In carefully selected patients, GKS may be a treatment option for ten or more brain metastases.