• Proceedings of the Korea Contents Association Conference
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• 2014.11a
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• pp.299-300
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• 2014

생명과학분야에서는 생명현상을 이해하기 위해 신호 전달 네트워크에 대한 연구가 진행되고 있다. 하지만 신호전달 네트워크와 임상 정보를 결합하여 질병관점에서 신호 전달 네트워크를 통합하고 결합하는 관점의 연구가 부족하다. 따라서 본 논문에서는 빅데이터 기술을 활용하여 임상 및 신호전달 정보를 연계 분석할 수 있는 시스템을 구축하고자 빅데이터 분석을 위한 임상 및 바이오 정보 통합 데이터베이스를 설계한다. 설계한 임상 및 바이오 정보 통합 데이터베이스는 빅데이터 분석 기술을 적용한 확장 분석 기법 및 통합 분석 시스템 개발에 활용할 수 있다.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.4
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• pp.146-157
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• 2009

In order to implement ontology data searching system, this paper uses some methods that effectively analyse searching options/key words with event process model and design pattern. I will propose some techniques on object-oriented process model that should improve reusability of system and reusability of ontology data which users can obtain more precise searching results. This paper shows that ontology-based data searching can assure users of the precision of searching results. Therefore, ontology-based data searching system on object-oriented design pattern is expected to show high stability and reliability, enhance reusability and scalability of modules and softwares and provide reliable data searching results to users.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.217-217
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• 2023

상수도관망은 사용자에게 고품질의 물을 안정적으로 공급하는 것을 목적으로 하며, 이를 평가하기 위한 지표 중 하나로 압력을 활용한다. 최근 스마트 센서의 설치가 확장됨에 따라 기계학습기법을 이용한 실시간 데이터 기반의 분석이 활발하다. 따라서 어디에서 데이터를 수집하느냐에 대한 센서 위치 결정이 중요하다. 본 연구는 eXtreme Gradient Boosting(XGBoost) 모델을 활용하여 대규모 상수도관망 내 센서 위치를 최적화하는 방법론을 제안한다. XGBoost 모델은 여러 의사결정 나무(decision tree)를 활용하는 앙상블(ensemble) 모델이며, 오차에 따른 가중치를 부여하여 성능을 향상시키는 부스팅(boosting) 방식을 이용한다. 이는 분산 및 병렬 처리가 가능해 메모리리소스를 최적으로 사용하고, 학습 속도가 빠르며 결측치에 대한 전처리 과정을 모델 내에 포함하고 있다는 장점이 있다. 모델 구현을 위한 독립 변수 결정을 위해 압력 데이터의 변동성 및 평균압력 값을 고려하여 상수도관망을 대표하는 중요 절점(critical node)를 선정한다. 중요 절점의 압력 값을 예측하는 XGBoost 모델을 구축하고 모델의 성능과 요인 중요도(feature importance) 값을 고려하여 센서의 최적 위치를 선정한다. 이러한 방법론을 기반으로 상수도관망의 특성에 따른 경향성을 파악하기 위해 다양한 형태(예를 들어, 망형, 가지형)와 구성 절점의 수를 변화시키며 결과를 분석한다. 본 연구에서 구축한 XGBoost 모델은 추가적인 전처리 과정을 최소화하며 대규모 관망에 간편하게 사용할 수 있어 추후 다양한 입출력 데이터의 조합을 통해 센서 위치 외에도 상수도관망에서의 성능 최적화에 활용할 수 있을 것으로 기대한다.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.3
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• pp.159-168
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• 2012

Relation in the new IT environment, such as the SNS, Cloud, Web3.0, has become an important factor. And these relations generate a transaction. However, existing relational database and graph database does not processe graph structure representing the relationships and transactions. This paper, we propose the technique that can be processed concurrently graph structures and transactions in a scalable complex network system. The proposed technique simultaneously save and navigate graph structures and transactions using the Topic Maps data model. Topic Maps is one of ontology language to implement the semantic web(Web 3.0). It has been used as the navigator of the information through the association of the information resources. In this paper, the architecture of the proposed technique was implemented and design using Cassandra - one of column type NoSQL. It is to ensure that can handle up to Big Data-level data using distributed processing. Finally, the experiments showed about the process of storage and query about typical RDBMS Oracle and the proposed technique to the same data source and the same questions. It can show that is expressed by the relationship without the 'join' enough alternative to the role of the RDBMS.

• Journal of the Korea Computer Graphics Society
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• v.4 no.2
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• pp.1-13
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• 1998

The most important goal of character animation is to efficiently control the motions of a character. Until now, many techniques have been proposed for human gait animation, and some techniques have been created to control the emotions in gaits such as "tired walking" and "brisk walking" by using parameter interpolation or motion data mapping. This paper proposes a human running model based on a one-legged hopper with a self-balancing mechanism. The proposed technique exploits genetic programming to optimize movement, and can be easily adopted to various character models. We extend the energy minimization technique to generate various motions in accordance with emotional specification.

• The Journal of the Acoustical Society of Korea
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• v.20 no.6
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• pp.82-86
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• 2001

In this Paper, we Propose synthetic aperture technique for twin-line may. Sin91e-line way is required long aperture size in order to achieve high SNR and angular resolution in shallow water Ultra low frequency signal from far-field has left-right ambiguity at sing1e-line array. To resolve these Problems, we'd like to adopt the synthetic aperture technique to twin-line array. The synthetic aperture method adopts coherent processing of sub-aperture signals at successive tine intervals in the beam domain. The proposed method shows low nile error and improved angular resolution. In simulation result, average sidelobe level is reduced about 7〔dB〕when the array Peformed 5-synthesis.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.6C
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• pp.490-496
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• 2005

In this paper, we propose a self-constructed clustering algorithm based on inference information of the fuzzy model. This method makes it possible to automatically detect and optimize the number of cluster and parameters by using input-output data. The propose method improves the performance of clustering by extended supervised learning technique. This technique uses the output information as well as input characteristics. For effect the similarity measure in clustering, we use the TSK fuzzy model to sent the information of output. In the conceptually, we design a learning method that use to feedback the information of output to the clustering since proposed algorithm perform to separate each classes in input data space. We show effectiveness of proposed method using simulation than previous ones

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.11
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• pp.471-474
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• 2013

In this paper, we propose a distributed parent peer selection method to construct an efficient peer-to-peer(P2P) network topology by considering the capacity of a peer and the hop distance from a data source to the peer. To achieve this goal, we propose a method to combine the two performance metrics to calculate the probability that a peer becomes a parent peer. Using the probability, we propose a method to select a parent peer stochastically by making use of the state information of the neighboring peers that each peer maintains. Through simulation studies, we show that the proposed method drives high capacity peers to support more children peers and makes the diameter of the P2P network shorter than the other methods.

• Journal of the Korea Society of Computer and Information
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• v.17 no.6
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• pp.163-172
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• 2012

Collaborative filtering which is used explicit method in a existing recommedation system, can not only reflect exact attributes of item but also still has the problem of sparsity and scalability, though it has been practically used to improve these defects. This paper proposes the personalized recommendation system using RFM method and k-means clustering in u-commerce which is required by real time accessablity and agility. In this paper, using a implicit method which is is not used complicated query processing of the request and the response for rating, it is necessary for us to keep the analysis of RFM method and k-means clustering to be able to reflect attributes of the item in order to find the items with high purchasablity. The proposed makes the task of clustering to apply the variable of featured vector for the customer's information and calculating of the preference by each item category based on purchase history data, is able to recommend the items with efficiency. To estimate the performance, the proposed system is compared with existing system. As a result, it can be improved and evaluated according to the criteria of logicality through the experiment with dataset, collected in a cosmetic internet shopping mall.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1506-1513
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• 2019

Recently, as the industrial scope of multi-rotor unmanned aerial vehicles(UAV) is greatly expanded, the demands for data collection, processing, and analysis using UAV are also increasing. However, the acoustic data collected by using the UAV is greatly corrupted by the UAV's motor noise and wind noise, which makes it difficult to process and analyze the acoustic data. Therefore, we have studied a method to enhance the target sound from the acoustic signal received through microphones connected to UAV. In this paper, we have extended the densely connected dilated convolutional network, one of the existing single channel acoustic enhancement technique, to consider the inter-channel characteristics of the acoustic signal. As a result, the extended model performed better than the existed model in all evaluation measures such as SDR, PESQ, and STOI.