• The KIPS Transactions:PartB
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• v.13B no.2 s.105
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• pp.105-114
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• 2006

In ubiquitous environment where various kinds of computers are embedded in persons, objects and environment and they are interconnected and can be used in my place as necessary, different types of data need to be exchanged between heterogeneous machines through home network. In the environment, the efficient processing, transmission and monitoring of image data are essential technologies. We need to make research not only on traditional image processing such as spatial and visual resolution, color expression and methods of measuring image quality but also on transmission rate on home network that has a limited bandwidth. The present study proposes a new motion vector estimation algorithm for transmitting, processing and controlling image data, which is the core part of contents in home network situation and, using algorithm, implements a real time monitoring system of multi dimensional images transmitted from multiple cameras. Image data of stereo cameras to be transmitted in different environment in angle, distance, etc. are preprocessed through reduction, magnification, shift or correction, and compressed and sent using the proposed metamorphosis hierarchical motion vector estimation algorithm for the correction of motion. The proposed algorithm adopts advantages and complements disadvantages of existing motion vector estimation algorithms such as whole range search, three stage search and hierarchical search, and estimates efficiently the motion of images with high variation of brightness using an atypical small size macro block. The proposed metamorphosis hierarchical motion vector estimation algorithm and implemented image systems can be utilized in various ways in ubiquitous environment.

• The KIPS Transactions:PartD
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• v.11D no.1
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• pp.203-210
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• 2004

A new research of geographic information system has been focused on an open architecture, interoperability and extensibility in their design. In order to process huge data, multidimensional data and heterogeneous geographic format data, these research move away from monolithic system to open structure system managing application layer and user interface layer. Nowadays, many developers have used CORBA middleware for the OGIS systems. However, CORBA middleware has some problems that support only a point-to-point communication and takes a long time to transfer sever data to client. Thus, in this paper, we propose a method on modifying a point-to-point communication and implement the efficient communication method. The proposed method that transfer data from sever to client in one connection support a group communication and reduce a transfer time delay.

• The Journal of the Korea Contents Association
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• v.17 no.5
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• pp.565-573
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• 2017

The ex-post evaluation of governmental crisis management is an important issues since it is necessary to prepare for the future disasters and becomes the cornerstone of our success as well. In this paper, we propose a data cube model with data mining techniques for the analysis of governmental crisis management strategies and ripple effects of foot-and-mouth(FMD) disease using the online news articles. Based on the construction of the data cube model, a multidimensional FMD analysis is performed using on line analytical processing operations (OLAP) to assess the temporal perspectives of the spread of the disease with varying levels of abstraction. Furthermore, the proposed analysis model provides useful information that generates the causal relationship between crisis response actions and its social ripple effects of FMD outbreaks by applying association rule mining. We confirmed the feasibility and applicability of the proposed FMD analysis model by implementing and applying an analysis system to FMD outbreaks from July 2010 to December 2011 in South Korea.

• The Journal of Bigdata
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• v.5 no.2
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• pp.135-143
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• 2020

This paper proposes a pre-processing method and a dimensional reduction method in the analysis of shopping carts where there are many correlations between variables when dividing the types of consumers in the agri-food consumer panel data. Cluster analysis is a widely used method for dividing observational objects into several clusters in multivariate data. However, cluster analysis through dimensional reduction may be more effective when several variables are related. In this paper, the food consumption data surveyed of 1,987 households was clustered using the K-means method, and 17 variables were re-selected to divide it into the clusters. Principal component analysis and factor analysis were compared as the solution for multicollinearity problems and as the way to reduce dimensions for clustering. In this study, both principal component analysis and factor analysis reduced the dataset into two dimensions. Although the principal component analysis divided the dataset into three clusters, it did not seem that the difference among the characteristics of the cluster appeared well. However, the characteristics of the clusters in the consumption pattern were well distinguished under the factor analysis method.

• Journal of KIISE:Databases
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• v.29 no.6
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• pp.453-463
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• 2002

With the prevalence of multi-dimensional data such as images, content-based retrieval of data is becoming increasingly important. To handle multi-dimensional data, multi-dimensional index structures such as the R-tree, Rr-tree, TV-tree, and MVP-tree have been proposed. Numerous research results on how to effectively manipulate these structures have been presented during the last decade. Query processing strategies, which is important for reducing the processing time, is one such area of research. In this paper, we propose query processing algorithms for R-tree based structures. The novel aspect of these algorithms is that they make use of the notion of VP filtering, a concept borrowed from the MVP-tree. The filtering notion allows for delaying of computational overhead until absolutely necessary. By so doing, we attain considerable performance benefits while paying insignificant overhead during the construction of the index structure. We implemented our algorithms and carried out experiments to demonstrate the capability and usefulness of our method. Both for range query and incremental query, for all dimensional index trees, the response time using VP filtering was always shorter than without VP filtering. We quantitatively showed that VP filtering is closely related with the response time of the query.

• Korean Journal of Biological Psychiatry
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• v.18 no.1
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• pp.15-24
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• 2011

Mood disorder is unlikely to be a disease of a single brain region or a neurotransmitter system. Rather, it is now generally viewed as a multidimensional disorder that affects many neural pathways. Growing neuroimaging evidence suggests the anterior cingulate-pallidostriatal-thalamic-amygdala circuit as a putative cortico-limbic mood regulating circuit that may be dysfunctional in mood disorders. Brain-imaging techniques have shown increased activation of mood-generating limbic areas and decreased activation of cortical areas in major depressive disorder(MDD). Furthermore, the combination of functional abnormalities in limbic subcortical neural regions implicated in emotion processing together with functional abnormalities of prefrontal cortical neural regions probably result in the emotional lability and impaired ability to regulate emotion in bipolar disorder. Here we review the biological correlates of MDD and bipolar disorder as evidenced by neuroimaging paradigms, and interpret these data from the perspective of endophenotype. Despite possible limitations, we believe that the integration of neuroimaging research findings will significantly advance our understanding of affective neuroscience and provide novel insights into mood disorders.

• Electronics and Telecommunications Trends
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• v.33 no.5
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• pp.111-120
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• 2018

Agent-based modeling and simulation (ABMS) is a computational method for analyzing research targets through observations of agent-to-agent interactions, and can be applied to multidimensional policy experiments in various fields of social sciences to support policy and decision making. Recently, according to increasing complexity of society and the rapid growth of collected data, the need for high-speed processing is considered to be more important in this field. For this reason, in the ABMS research field, a scalable and large-scale computing infrastructure is becoming an essential element, and cloud computing has been considered a promising infrastructure of ABMS. This paper surveys the technology trends of ABMS tools, cloud computing-based modeling, and simulation studies, and forecasts the use of cloud-computing infrastructure for future modeling and simulation tools. Although fundamental studies are underway to apply and operate cloud computing in the areas of modeling and simulation, new and additional studies are required to devise an optimal cloud computing infrastructure to satisfy the needs of large-scale ABMS.

• Journal of the Korea Society of Computer and Information
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• v.16 no.12
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• pp.71-81
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• 2011

The EMR management services can monitoring the patients' record with any doctors in any hospital by using the internet and smartphones online. To handle the real time, multidimensional, continuous data, database management systems (DBMS) must cope with high insert rates for updates, however the traditional DBMS suffers from processing these kinds of data due to its serious design bottlenecks. So the researchers put forward to Data Stream Management System (DSMS). In this paper we describe the real-time Data Stream Server for Continuity of Care Record (CCR) that including continuos query processor. This system is compiled with DSMS and DBMS in EMR system for processing and monitoring the coming CCR data stream, and also storing the processed result with high-efficiency. The system enables users not only to query stored CCR information from DBMS, but also to execute continue query on real-time CCR Data Stream, and health information can be transferred between different healthcare providers that would reduce medical error. At last, we develop a IPhone mobile application to test the proposed real-time data stream server.

• The KIPS Transactions:PartD
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• v.15D no.1
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• pp.31-40
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• 2008

We generally use lower-dimensional transformations to convert high-dimensional sequences into low-dimensional points in similar sequence matching. These traditional transformations, however, show different characteristics in indexing performance by the type of time-series data. It means that the selection of lower-dimensional transformations makes a significant influence on the indexing performance in similar sequence matching. To solve this problem, in this paper we propose a hybrid approach that integrates multiple transformations and uses them in a single multidimensional index. We first propose a new notion of hybrid lower-dimensional transformation that exploits different lower-dimensional transformations for a sequence. We next define the hybrid distance to compute the distance between the transformed sequences. We then formally prove that the hybrid approach performs the similar sequence matching correctly. We also present the index building and the similar sequence matching algorithms that use the hybrid approach. Experimental results for various time-series data sets show that our hybrid approach outperforms the single transformation-based approach. These results indicate that the hybrid approach can be widely used for various time-series data with different characteristics.

• Journal of The Korean Association of Information Education
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• v.7 no.1
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• pp.113-129
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• 2003

The performance assessment is being importantly recognized and enforced in the education evaluation recently. It is not able to analyze learners synthetically because learners are assessed separately in every subjects and the other activities. On the basis of this problem, we designed and implemented the multi-dimensional processing tool. In this tool, the evaluation results of one subject area have an influence on the other related subject areas. In addition, this system helps teachers to establish and process performance assessment plan by providing all subjects database. And all of the information is processed as a whole and can be used in the counseling and school record. This system is based upon windows and can be extend to web based system later. We expect the performance assessment task can be simplified by using this system and students' ability can be assessed by various methods. This system will contribute to ensure the confidence of public education.