• Proceedings of the Korean Information Science Society Conference
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• 2007.06c
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• pp.153-158
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• 2007

사용자들의 특성에 맞게 개인화되고 세분화된 위치 기반 서비스를 제공하기 위해서는 방대한 이동 객체의 위치 이력 데이터 집합으로부터 유용한 패턴을 추출하여 의미 있는 지식을 탐사하기 위한 시공간 패턴 탐사가 필요하다. 현재까지 다양한 패턴 탐사 기법들이 제안되었으나 이동 패턴들 중 단순히 시공간 제약이 없는 빈발 패턴만을 추출하기 때문에 한정된 시간 범위와 제한적인 영역 범위 내에서의 빈발 패턴을 탐사하는 문제에는 적용하기 어렵다. 또한 패턴 탐사 수행 시 데이터베이스를 반복 스캔하여 탐사 수행시간이 많이 소요되는 문제를 포함하거나 메모리상에 탐사 대상인 후보 패턴 트리를 생성하는 방법을 통해 탐사 시간을 줄일 수는 있으나 이동 객체 수나 최소지지도 등에 따라 트리를 구성하고 유지하는데 드는 비용이 커질 수 있다. 따라서 이러한 문제를 해결하기 위한 효율적인 패턴 탐사 기법의 개발이 요구됨으로써 선행 작업으로 본 논문에서는 상세 수준의 객체 이력 데이터들의 시간 및 공간 속성을 의미 있는 시간영역과 공간영역 정보로 변환하는 시공간 데이터 일반화 방법을 제안한다. 제안된 방법은 공간 개념 계층에 대한 영역 정보들을 영역 Grid 해쉬 테이블(AGHT:Area Grid Hash Table)로 생성하여 공간 인덱스트리인 R*-Tree의 검색 방법을 이용해 이동 객체의 위치 속성을 2차원 공간영역으로 일반화하고, 시간 개념 계층을 생성하여 이동 객체의 시간적인 속성을 시간 영역으로 일반화함으로써 일반화된 데이터 집합을 형성하여 효율적인 이동 객체의 시간 패턴 마이닝을 유도할 수 있다.의 성능을 기대할 수 있을 것이다.onium sulfate첨가배지(添加培地)에서 가장 저조(低調)하였다. vitamin중(中)에서는 niacin과 thiamine첨가배지(添加培地)에서 근소(僅少)한 증가(增加)를 나타내었다.소시켜 항이뇨 및 Na 배설 감소를 초래하는 작용과, 둘째는 신경 경로를 통하지 않고, 아마도 humoral factor를 통하여 신세뇨관에서 Na 재흡수를 억제하는 작용이 복합적으로 나타내는 것을 알 수 있었다.으로 초래되는 복합적인 기전으로 추정되었다., 소형과와 기형과는 S-3에서 많이 나왔다. 이상 연구결과에서 입도분포가 1.2-5mm인 것이 바람직한 것으로 나타났다.omopolysaccharides로 확인되었다. EPS 생성량이 가장 좋은 Leu. kimchii GJ2의 평균 분자량은 360,606 Da이었으며, 나머지 두 균주에 대해서는 생성 EPS 형태와 점도의 차이로 미루어 보아 생성 EPS의 분자구조와 분자량이 서로 다른 것으로 판단하였다.TEX>개로 통계학적으로 유의한 차이가 없었다. Heat shock protein-70 (HSP70)과 neuronal nitric oxide synthase (nNOS)에 대한 면역조직화학검사에서 실험군 Cs2군의 신경세포가 대조군 12군에 비해 HSP70과 nNOS의 과발현을 보였으며, 이는 통계학적으로 유의한 차이를 보였다(p<0.05). nNOS와 HSP70의 발현은 강한 연관성을 보였고(상관계수 0.91, p=0.000), nNOS를 발현하는 세포가 동시에 HSP70도 발현함을 확인할 수 있었다. 결론: 우리는

• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.467-475
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• 2014

With the development of genomics, wearable device and IT/NT, a vast amount of bio-medical data are generated recently. Also, healthcare industries based on big-data are booming and big-data technology based on bio-medical data is rising rapidly as a core technology for improving the national health and aged society. A pathway is the biological deep knowledge that represents the relations of dynamics and interaction among proteins, genes and cells by a network. A pathway is wildly being used as an important part of a bio-medical big-data analysis. However, a pathway analysis requires a lot of time and effort because a pathway is very diverse and high volume. Also, multidimensional analysis systems for various pathways are nonexistent even now. In this paper, we proposed a pathway analysis system that collects user interest pathways from KEGG pathway database that supports the most widely used pathways, constructs a network based on a hierarchy structure of pathways and analyzes the relations of dynamics and interaction among pathways by clustering and selecting core pathways from the network. Finally, to verify the superiority of our pathway analysis system, we evaluate the performance of our system in various experiments.

• Journal of KIISE:Databases
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• v.35 no.3
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• pp.257-271
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• 2008

Wireless broadcast environments has character that a number of mobile client can receive data streaming from central server no matter how they are so many. Because it is asymmetric bandwidth in that uplink and downlink bandwidth are different. This advantage helps wireless broadcast environments is used in many applications. These applications work almost read operation and need control concurrency using transaction unit. Previous concurrency control scheme in single channel is not adapted in multi channel environments because consistency of data are broken when a mobile client tunes in a broadcast cycle in a channel and then move into another channel and listen to different broadcast cycle with already accessed broadcast cycle. In this paper, we propose concurrency control for read-only mobile transactions in multiple wireless broadcast channel. First of all, we adapt index and data dedicated channel and propose LBCPC(Longest Broadcast Cycle Per Channel) as new unit of consistency. In index dedicated channel, it is repeatedly broadcasted data in same BCPC(Broadcast Cycle Per Channel) until LBCPC. And mobile transaction executes validation using control information every LBCPC. As a result, consistency of data is kept and average response time is shorter than one in single channel because waiting time for restart reduces. And as control information is broadcasted more frequently than in single channel, it is guaranteed currency about data accessed by transaction. Finally, according to the simulation result, we verify performance of our scheme in multi channel as comparing average response time with single channel.

• Journal of Navigation and Port Research
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• v.36 no.6
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• pp.475-480
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• 2012

In order to establish eLoran (enhanced Long Range Navigation) system, it needs the advancement of receiver, transmitter, data channel addition for Loran information, differential Loran sites for compensating Loran-c signal and ASFs (Additional Secondary Factors) database, etc. In addition, the precise synchronization of transmitting station to the UTC (Coordinated Universal Time) is essential if Loran delivers the high absolute accuracy of navigation demanded for maritime harbor entrance. For better timing synchronization to the UTC among transmitting stations, it is necessary to measure and monitor the transmission delay of the station, and the correction information of the transmitting station should be provided to the user's receivers. In this paper we presented the measurement method of absolute delay of Pohang Loran transmitting station and developed a time delay measurement system and a phase monitoring system for Loran station. We achieved -2.23 us as a result of the absolute phase delay of Pohang station and the drift of Loran pulse of the station was measured about 0.3 us for a month period. Therefore it is necessary to measure the delay offset of transmitting station and to compensate the drift of the Loran signal for the high accuracy application of PNT (Positioning, Navigation and Timing).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.2105-2112
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• 2010

The noise component of electrocardiogram is not distributed in a certain frequency band. It is expressed in various types of signals by rater's physical and environmental conditions. Particularly, since the baseline wander is occurred by the mixture of the original signal and 0 ~ 2 [Hz] range of the frequency components according to muscle constraction of part attaching to an electrode and respiration rythm, it makes the ECG signal analysis difficult. Several methods have been proposed to eliminate the wandering effectually. However, they have some problems. In some methods, the high processing time is required due to the computational complexity, while in other cases ECG signal morphology can be distorted. This paper suggests a simple and effective algorithm that eliminates baseline wander with low computational complexity and without distorting signal morphology. First, the algorithm detects and segments a baseline wandering interval using slope analysis and curve point detection, second, approximates the wandering in the interval as a sinusoid, and then subtracts the sinusoid from signal. Finally, ecg signals without baseline wander are obtained. In order to evaluate the performance of the algorithm, several ECG signals with baseline wandering in MIT/BIH ECG database 101, 111, 113, 234 record were chosen and applied to the algorithm. It is found that the algorithm removes baseline wanders effectively without significant morphological distortion.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.12
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• pp.623-634
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• 2016

Most of existing frequent pattern mining methods address time efficiency and greatly rely on the primary memory. However, in the era of big data, the size of real-world databases to mined is exponentially increasing, and hence the primary memory is not sufficient enough to mine for frequent patterns from large real-world data sets. To solve this problem, there are some researches for frequent pattern mining method based on disk, but the processing time compared to the memory based methods took very time consuming. There are some researches to improve scalability of frequent pattern mining, but their processes are very time consuming compare to the memory based methods. In this paper, we present PPFP as a novel disk-based approach for mining frequent itemset from big data; and hence we reduced the main memory size bottleneck. PPFP algorithm is based on FP-growth method which is one of the most popular and efficient frequent pattern mining approaches. The mining with PPFP consists of two setps. (1) Constructing an IFP-tree: After construct FP-tree, we assign index number for each node in FP-tree with novel index numbering method, and then insert the indexed FP-tree (IFP-tree) into disk as IFP-table. (2) Mining frequent patterns with PPFP: Mine frequent patterns by expending patterns using stack based PUSH-POP method (PPFP method). Through this new approach, by using a very small amount of memory for recursive and time consuming operation in mining process, we improved the scalability and time efficiency of the frequent pattern mining. And the reported test results demonstrate them.

• Journal of Service Research and Studies
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• v.3 no.2
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• pp.53-60
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• 2013

Datamining from the large data in the form of various techniques for obtaining information have been developed. In recent years one of the most sought areas of pattern recognition and machine learning method is created with most of existing learning algorithms based on categorical attributes to a rule or decision model. However, the real-world data, it may consist of numeric attributes in many cases. In addition it contains attributes with numerical values to the normal categorical attribute. In this case, therefore, it is required processes in order to use the data to learn an appropriate value for the type attribute. In this paper, the domain of the numeric attributes are divided into several segments using learning algorithm techniques of discritization. It is described Clustering with other data mining techniques. Large amount of first cluster with characteristics is similar records from the database into smaller groups that split multiple given finite patterns in the pattern space. It is close to each other of a set of patterns that together make up a bunch. Among the set without specifying a particular category in a given data by extracting a pattern. It will be described similar grouping of data clustering technique to classify the data.

• Spatial Information Research
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• v.19 no.5
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• pp.63-74
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• 2011

Recently, there has been much interest in the spatial query which energy-efficiently acquires sensor readings from sensor nodes inside specified geographical area of interests. The centralized approach which performs the spatial query at a server after acquiring all sensor readings, though simple, it incurs high wireless transmission cost in accessing all sensor nodes. In order to remove the high wireless transmission cost, various in-network spatial indexing schemes have been proposed. They have focused on reducing the transmission cost by performing distributed spatial filtering on sensor nodes. However, these in-network spatial indexing schemes have a problem which cannot optimize both the spatial filtering and the wireless routing among sensor nodes, because these schemes have been developed by simply applying the existing spatial indexing schemes into the in-network environment. Therefore, we propose a new distributed spatial indexing scheme of the GR-tree. The GR-tree which form s a MBR-based tree structure, can reduce the wireless transmission cost by optimizing both the efficient spatial filtering and the wireless routing. Finally, we compare the existing spatial indexing scheme through extensive experiments and clarify our approach's distinguished features.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.2
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• pp.21-28
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• 2010

This paper reports an experimental result on optimizing dissimilarity-based classification(DBC) by simultaneously using a dynamic time warping(DTW) and a multiple fusion strategy(MFS). DBC is a way of defining classifiers among classes; they are not based on the feature measurements of individual samples, but rather on a suitable dissimilarity measure among the samples. In DTW, the dissimilarity is measured in two steps: first, we adjust the object samples by finding the best warping path with a correlation coefficient-based DTW technique. We then compute the dissimilarity distance between the adjusted objects with conventional measures. In MFS, fusion strategies are repeatedly used in generating dissimilarity matrices as well as in designing classifiers: we first combine the dissimilarity matrices obtained with the DTW technique to a new matrix. After training some base classifiers in the new matrix, we again combine the results of the base classifiers. Our experimental results for well-known benchmark databases demonstrate that the proposed mechanism achieves further improved results in terms of classification accuracy compared with the previous approaches. From this consideration, the method could also be applied to other high-dimensional tasks, such as multimedia information retrieval.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.8
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• pp.55-64
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• 2017

In this paper, we propose and implement an IoT based mobile smart monitoring system in the view point of safety inspection for solar power generation. The main features and contributions of proposed system are as follows. First, the proposed system model can evaluate periodically in the view point of safety inspection the conditions of the system and structure of solar power generation. Second, the proposed system automatically re-processes the measurement data of the system and structure for solar power generation and save it into database. Third, using the re-processed and saved information, the proposed system can provide the monitoring information with webpage form to both administrator and owner of solar power generation system, thus they can measure and confirm directly in the view point of safety inspection the conditions of the solar generation structure without visiting those places. Fourth, the provided web pages for the monitoring of solar power generation can be accessed regardless of the system structures. The performance evaluations of the proposed system show that the proposed monitoring system can save efficiently the data received from the sensors installed in the structure of solar power generation into the data base in the collecting server. And the proposed system can support that both administrator and user of solar power generation system access webpage in real time without considering places by using mobile phone and desktop computer and obtain the information for the conditions of the system and structure of solar power generation with graph forms.