• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.6
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• pp.2720-2728
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• 2012

Recently flexible mobile terminals which can freely change the shape of their device are coming out with the development of the flexible display, high capacity memory and system integration technology. The display and the antenna configuration of the future terminals will be altered according to the QoS (quality of service) and the communication environment of users. In particular, we present the new emergence of a multimedia language for human and system to communicate over subjective concepts, intention of users. The intension of users is expressed by changing the shape of their mobile terminal. In addition, antenna configuration is also related to shape of terminal and QoS of users. Therefore, we set up a specific usage scenarios for future mobile terminals and propose an adaptive MIMO (multiple-input multiple-output) schemes that can maximize channel capacity and fit to QoS of users simultaneously.

• The Journal of Society for e-Business Studies
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• v.18 no.2
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• pp.153-173
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• 2013

The ontology has been gaining increasing interests by recent arise of the semantic web and related technologies. The focus is mostly on inference query processing that requires high-level techniques for storage and searching ontologies efficiently, and it has been actively studied in the area of semantic-based searching. W3C's recommendation is to use RDFS and OWL for representing ontologies. However memory-based editors, inference engines, and triple storages all store ontology as a simple set of triplets. Naturally the performance is limited, especially when a large-scale ontology needs to be processed. A variety of researches on proposing algorithms for efficient inference query processing has been conducted, and many of them are based on using proven relational database technology. However, none of them had been successful in obtaining the complete set of inference results which reflects the five characteristics of the ontology properties. In this paper, we propose a new index structure called hyper cube index to efficiently process inference queries. Our approach is based on an intuition that an index can speed up the query processing when extensive inferencing is required.

• Journal of KIISE:Software and Applications
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• v.26 no.8
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• pp.939-954
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• 1999

데이타마이닝 분야에서는 대용량의 트랜잭션 데이타베이스와 같은 하나의 데이타베이스로부터 연관 규칙을 찾는 연구가 많이 수행되어왔다. 그러나, 창고형 할인매장이나 백화점 같이 고객 카드를 이용하는 판매점의 등장으로, 단지 트랜잭션에 대한 분석 뿐만이 아니라, 트랜잭션과 고객과의 관계에 대한 분석 또한 요구되고 있다. 즉, 두 개의 데이타베이스로부터 연관 규칙을 찾는 연구가 필요하다. 이 논문에서는 두 데이타베이스 사이에 링크를 생성하여 연관 항목집합을 찾는 알고리즘을 제안한다. 실험 결과, 링크를 이용한 알고리즘은 고객 데이타베이스가 메모리에 거주가능한 크기라면 시간에 따른 분석에 유용함을 보여주었다.Abstract There have been a lot of researches of mining association rules from one database such as transaction database until now. But as the large discount store using customer card emerges, the analysis is not only required about transactions, but also about the relation between transactions and customer data. That is, it is required to search association rules from two databases. This paper proposes an efficient algorithm constructing links from one database to the other. Our experiments show the algorithm using link is useful for temporal analysis of memory-resident customer database.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.1
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• pp.35-40
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• 2008

In this paper, fundamental driving method and selective driving each cells of charged particle type display are described. To fabricate panel, mask patterns with cell area of $500{\mu}m{\times}500{\mu}m$ are designed. Gain of driving voltage due to increase of cell gap is observed on the basis of fundamental driving method. To selectively drive each cells of charged particle type display that is driven by passive matrix method, selective driving of charged particle type display is achieved after establishing interrelation of voltage of select cell and unselect. And than crosstalk of the driven panel is observed. It can be found that the last image is maintained without additional voltage by memory effect.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.1
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• pp.75-80
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• 2005

In this paper, a 3-dimensional analysis of magnetic road and a position sensing system for an autonomous vehicle system is described. Especially, a new position sensing system, end of the important component of an autonomous vehicle, is proposed. In a magnet based autonomous vehicle system, to sense the vehicle position, the sensor measures the field of magnetic road. The field depends on the sensor position of the vehicle on the magnetic road. As the rotation between the magnetic field and the sensor position is highly complex, it is difficult that the relation is stored in memory. Thus, a neural network is used to learn the mapping from th field to the position. The autonomous vehicle system with the proposed position sensing system is tested in experimental setup.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.8
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• pp.181-188
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• 2016

Recently, as the amount of spatial information increases, an interest in the study of spatial information processing has been increased. Spatial database systems extended from the traditional relational database systems are difficult to handle large data sets because of the scalability. SpatialHadoop extended from Hadoop system has a low performance, because spatial computations in SpationHadoop require a lot of write operations of intermediate results to the disk, resulting in the performance degradation. In this paper, Spatial Computation Spark(SC-Spark) is proposed, which is an in-memory based distributed processing framework. SC-Spark is extended from Spark in order to efficiently perform the spatial operation for large-scale data. In addition, SC-Spark based on the GPGPU is developed to improve the performance of the SC-Spark. SC-Spark uses the advantage of the Spark holding intermediate results in the memory. And GPGPU-based SC-Spark can perform spatial operations in parallel using a plurality of processing elements of an GPU. To verify the proposed work, experiments on a single AMD system were performed using SC-Spark and GPGPU-based SC-Spark for Point-in-Polygon and spatial join operation. The experimental results showed that the performance of SC-Spark and GPGPU-based SC-Spark were up-to 8 times faster than SpatialHadoop.

• Journal of Korea Multimedia Society
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• v.9 no.10
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• pp.1257-1265
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• 2006

As XML is increasingly used, the need of researches which are related with XML in various fields is also augmented. Many XML document management systems have been actively developed especially for the storage, processing and retrieval of XML documents. The BitCube is a three dimensional bitmap index system that could be manipulated efficiently and improves the performance of document retrieval. However, the site of index is increase rapidly, when a new bit is added to the axis. This problem is caused by its three dimensional memory structure with document, path and word. We suggest a path combining strategy of XML documents in this paper to solve the problem of BitCube that mentioned above. To reduce the size of index, our approach combines sibling nodes that has same ancestor paths, and transforms word axis into value axis. The method reduces the size of index, when the system com poses the three dimensional bitmap index. It also improves the speed of retrieving, and takes efficiency in storage space.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.11
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• pp.521-526
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• 2016

As on-line informal text data have massive in its volume and have unstructured characteristics in nature, there are limitations in applying traditional relational data model technologies for data storage and data analysis jobs. Moreover, using dynamically generating massive social data, social user's real-time reaction analysis tasks is hard to accomplish. In the paper, to capture easily the semantics of massive and informal on-line documents with unsupervised learning mechanism, we design and implement automatic topic extraction systems according to the mass of the words that consists a document. The input data set to the proposed system are generated first, using N-gram algorithm to build multiple words to capture the meaning of the sentences precisely, and Hadoop and Spark (In-memory distributed computing framework) are adopted to run topic model. In the experiment phases, TB level input data are processed for data preprocessing and proposed topic extraction steps are applied. We conclude that the proposed system shows good performance in extracting meaningful topics in time as the intermediate results come from main memories directly instead of an HDD reading.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2001.05a
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• pp.105-106
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• 2001

일반적인 정보 검색은 색인어를 통해 이루어지는데 이런 경우 사용자는 정보를 검색하기 위해 데이터베이스에 저장된 정보들이 가지고 있는 색인어를 정확하게 입력해야 한다. 그러나 일반 사용자가 색인어를 정확하게 입력하기는 어렵고, 특히 찾고자 하는 분야가 전문 분야에서 사용되는 용어일 때는 더욱 그러하다. 이럴 때 시소러스와 같은 지식구조를 이용해서 색인어를 탐색하여 검색의 효율을 높일 수 있다. 최근 들어 정보기술 분야의 연구가 활발함에 따라 정보자로의 생산이 급격히 증가하고 이를 관련 주제 분야의 연구정보로 활용하는 경우가 증가하고 있다. 따라서 IT 분야의 정보를 관리할 수 있는 시스템의 개발이 시급하다. 또한 IT 분야와 같은 전문분야일 때 검색 시스템에서 사용할 용어의 관리에 대한 연구의 필요성이 증가하고 있다. 본 논문에서는 IT분야의 정보를 검색할 수 있는 IT 업체정보검색시스템에서 정보 검색시에 생기는 용어간의 불일치 문제를 해결하고, 각 용어들간의 계층 관계를 나타내어 정보 검색시 검색어의 확장을 도울 수 있는 용어 관리 시스템의 구조를 제안하고 그에 대한 검색 알고리즘을 제시한다. 제안된 구조는 사용자의 검색어에 대한 동의어 관계나 상위어, 하위어 등의 계층 관계를 파악하여 검색의 범위에 추가함으로써 검색 효율을 높일 수 있다. 또한 새로운 용어의 생성이나 삭제와 같은 연산이 발생했을 때 시스템을 동적으로 확장할 수 있도록 구현하였다. 제안된 시스템은 단어간의 계층 구조를 효율적으로 검색하기 위하여 객체-관계형 데이터베이스를 사용하였다. 또한 메모리 상주 DBMS를 사용하여 많은 사용자들이 동시에 접근하는 환경에서도 빠른 검색 성능을 유지할 수 있도록 하였다. 제시된 방법은 정보기술 분야뿐만 아니라 다른 전문용어 분야의 연구로도 그 범위를 확장 할 수 있다.자기자본비용의 조합인 기회자본비용으로 할인함으로써 현재의 기업가치를 구할 수 있기 때문이다. 이처럼 기업이 영업활동이나 투자활동을 통해 현금을 창출하고 소비하는 경향은 해당 비즈니스 모델의 성격을 규정하는 자료도로 이용될 수 있다. 또한 최근 인터넷기업들의 부도가 발생하고 있는데, 기업의 부실원인이 어떤 것이든 사회전체의 생산력의 감소, 실업의 증가, 채권자 및 주주의 부의 감소, 심리적 불안으로 인한 경제활동의 위축, 기업 노하우의 소멸, 대외적 신용도의 하락 등과 같은 사회적·경제적 파급효과는 대단히 크다. 이상과 같은 기업부실의 효과를 고려할 때 부실기업을 미리 예측하는 일종의 조기경보장치를 갖는다는 것은 중요한 일이다. 현금흐름정보를 이용하여 기업의 부실을 예측하면 기업의 부실징후를 파악하는데 그치지 않고 부실의 원인을 파악하고 이에 대한 대응 전략을 수립하며 그 결과를 측정하는데 활용될 수도 있다. 따라서 본 연구에서는 기업의 부도예측 정보 중 현금흐름정보를 통하여 '인터넷기업의 미래 현금흐름측정, 부도예측신호효과, 부실원인파악, 비즈니스 모델의 성격규정 등을 할 수 있는가'를 검증하려고 한다. 협력체계 확립, ${\circled}3$ 전문인력 확보 및 인력구성 조정, 그리고 ${\circled}4$ 방문보건사업의 강화 등이다., 대사(代謝)와 관계(關係)있음을 시사(示唆)해 주고 있다.ble nutrient (TDN) was highest in booting stage (59.7%); however no significant difference was found among other stages. The concentrations of Ca and P were not different among mature stages. Accordi

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.3
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• pp.12-26
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• 2017

The objective of this study was to develop a runoff analysis system of the Nakdong River watershed using the GRM (Grid-based Rainfall-runoff Model), a physically-based distributed rainfall-runoff model, and to assess the system run time performance according to Microsoft Azure VM (Virtual Machine) settings. Nakdong River watershed was divided into 20 sub-watersheds, and GRM model was constructed for each subwatershed. Runoff analysis of each watershed was calculated in separated CPU process that maintained the upstream and downstream topology. MoLIT (Ministry of Land, Infrastructure and Transport) real-time radar rainfall and dam discharge data were applied to the analysis. Runoff analysis system was run in Azure environment, and simulation results were displayed through web page. Based on this study, the Nakdong River real-time runoff analysis system, which consisted of a real-time data server, calculation node (Azure), and user PC, could be developed. The system performance was more dependent on the CPU than RAM. Disk I/O and calculation bottlenecks could be resolved by distributing disk I/O and calculation processes, respectively, and simulation runtime could thereby be decreased. The study results could be referenced to construct a large watershed runoff analysis system using a distributed model with high resolution spatial and hydrological data.