• Annals of Clinical Neurophysiology
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• v.2 no.2
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• pp.130-134
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• 2000

Abnormal writing can result from a large variety of neurologic disorders of motor control. Primary writing tremor(PWT) in its pure form denotes occurrence of a disabling tremor induced by writing alone. Therefore PWT is typical task-specific tremor. PWT could be classified as either type A or type B. In a strict sense, type B PWT is not pure form of PWT because it is not task specific. We describe a case of PWT type A. A 53-year-old right handed policeman complained of a 4 year history of shaking of his right hand that interfered with writing. Tremor appeared during writing but not on adopting the hand position normally used for writing.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.2
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• pp.375-380
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• 2012

The current reconstrution project has caused many conflicts due to the problems contretely expressed by the following matters. The results of the analytic hierarchy process showed that the stage of promotion the project shoud most be taken into consideration to resolve the cinflict, the prior task of the successful reconstrution project. In this sense as the stage of project planning. it was analyzed as the most important item of coarse classification.

• Journal of Plant Biology
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• v.35 no.3
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• pp.283-305
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• 1992

Phytoliths (plant stones) mean all types of mineral deposition formed in or between plant cells. However, most of the researches on the phytoliths so far have been focused on the opaline silica bodies (silicified phytoliths) formed by grasses. Therefore, the phytolith is usually refered to opaline silica body in a narrow sense. Phytoliths are very useful in grass classification, and their usefulness as microfossils is also proved in several other fields, including soil science, paleoecology, and archaeology. Recently attention has been paid to the possibility that they might function as carcinogen. The purpose of this review is to present an overview of the nature and analysis of phytoliths and their applications in botany as well as other fields of sciencess.encess.

• Genomics & Informatics
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• v.12 no.4
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• pp.145-150
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• 2014

Recent technical advances, such as chromatin immunoprecipitation combined with DNA microarrays (ChIp-chip) and chromatin immunoprecipitation-sequencing (ChIP-seq), have generated large quantities of high-throughput data. Considering that epigenomic datasets are arranged over chromosomes, their analysis must account for spatial or temporal characteristics. In that sense, simple clustering or classification methodologies are inadequate for the analysis of multi-track ChIP-chip or ChIP-seq data. Approaches that are based on hidden Markov models (HMMs) can integrate dependencies between directly adjacent measurements in the genome. Here, we review three HMM-based studies that have contributed to epigenetic research, from a computational perspective. We also give a brief tutorial on HMM modelling-targeted at bioinformaticians who are new to the field.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.7
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• pp.2957-2962
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• 2011

The purpose of this paper is a semiotic analysis of a dating show on television program, and the attribute contains a variety of social and cultural phenomenons. Analyzed in this study shows relates with TVn's "Love Switch" from cable channel of the text through the classification of gender and thinking of behavior revealed by the structural characteristics of the men and women's appearances. And, how the television culture We rule the world and develop a sense of whether they are examined.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.06a
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• pp.45-46
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• 2018

This paper focuses on human activities monitoring problem using onboard smartphone sensors as data generator. Monitoring such activities can be very important to detect anomalies and prevent disease from patients. Machine learning (ML) algorithms appear to be ideal approaches to use for processing data from smartphone to get sense of how to classify human activities. ML algorithms depend on quality, the quantity and even more important, the properties or features, that can be learnt from data. This paper proposes a mobile virtual reality visualization system that helps to view data representation in a very immersive way so that its quality and discriminative characteristics may be evaluated and improved. The proposed system comes as well with a handy data collecting application that can be accessed directly by the VR visualization part.

• Tunnel and Underground Space
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• v.13 no.4
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• pp.279-286
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• 2003

Many trials to set up the correlation between the rock mass classification and the earth resistivity have been carried out to design tunnel support type based on the interpreted electrical resistivity acquired by surface electrical survey. But it is hard to find reports on the comparison of the real rock support type determined during the excavation with the electrical resistivity by the inversion of the survey data acquired before the tunneling. In this study, the rock mass classification based on the face mapping data and the resistivity inversion data are investigated to see if it is possible to design reliably the rock support type based on the surface electrical survey. To get the quantitative correlation, rock engineering indices such as RCR(rock condition rating), N(Rock mass number), Q-system and RMR(rock mass rating) are calculated. Since resistivity data has low resolution, Kriging method as a post processing technique which minimizes the estimated variance is used to improve resolution. The result of correlation analysis shows that the 2D electrical resistivity survey is appropriate to see the general trend of the geology in the sense of rock type, though there might be some local area where these two factors do not coincide. But the correlation between the result of 3D survey and the rock mass classification turns out to be very high, and then 3D electrical resistivity survey can make it possible to set up more reliable rock support type.

• Journal of the Korean Society for Library and Information Science
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• v.45 no.2
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• pp.251-275
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• 2011

In this paper, we propose a novel kernel called a semantic parse tree kernel that extends the parse tree kernel previously studied to extract protein-protein interactions(PPIs) and shown prominent results. Among the drawbacks of the existing parse tree kernel is that it could degenerate the overall performance of PPI extraction because the kernel function may produce lower kernel values of two sentences than the actual analogy between them due to the simple comparison mechanisms handling only the superficial aspects of the constituting words. The new kernel can compute the lexical semantic similarity as well as the syntactic analogy between two parse trees of target sentences. In order to calculate the lexical semantic similarity, it incorporates context-based word sense disambiguation producing synsets in WordNet as its outputs, which, in turn, can be transformed into more general ones. In experiments, we introduced two new parameters: tree kernel decay factors, and degrees of abstracting lexical concepts which can accelerate the optimization of PPI extraction performance in addition to the conventional SVM's regularization factor. Through these multi-strategic experiments, we confirmed the pivotal role of the newly applied parameters. Additionally, the experimental results showed that semantic parse tree kernel is superior to the conventional kernels especially in the PPI classification tasks.

• Archives of design research
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• v.19 no.3 s.65
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• pp.131-142
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• 2006

The purpose of this study is to develop an online community construct, which proposes an inclusive illustration of the structure of online communities, for online community designers. This study reviewed researches from psychology, sociology, management engineering, and practical reports to understand the characteristics and dynamics of online communities. The proposed online community construct visualizes the cognitive, affective, and behavioral aspects of online community. As the notion of community originates from geographical groups, and with the assumption that geographical community shares identical characteristics with online community, this study reviewed researches about geographical communities as a starting-point. Then the study went through three main perspectives (1) online community attributes, (2) sense of online community and (3) challenges of online community. Then this study proposed an online community construct that encompasses the reviewed frameworks. The online community can be seen as a congregation of members from two sources. One is from the 'Shared Goal' that meets the personal needs. Given the shared goal, members gather into the community without personal relationship and have more chances to feel the sense of belonging to their needs fulfillment or benefit. This befitting tendency leads to strengthening of membership. Public online forums fall under this classification. The other source is from the emotional connections that are already initiated by personal and casual contacts in the real world. The network of emotional connection can evolve into an online congregation of people under faint boundaries. Although there is no (or weak) shared goal, members are strongly bound to other members. Personal homepage or web log (blog) can be classified as an example of relationship-oriented community.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1341-1348
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• 2013

To solve the classification problems, various data mining techniques have been applied to database marketing, credit scoring and market forecasting. In this paper, we compare various techniques such as bagging, boosting, LASSO, random forest and support vector machine with the daily lens transaction data. The classical techniques-decision tree, logistic regression-are used too. The experiment shows that the random forest has a little smaller misclassification rate and standard error than those of other methods. The performance of the SVM is good in the sense of misclassfication rate and bad in the sense of standard error. Taking the model interpretation and computing time into consideration, we conclude that the LASSO gives the best result.