• Journal of KIISE:Information Networking
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• v.32 no.4
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• pp.515-524
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• 2005

As the number of the mobile nodes (MNs) increases in the networks, the signaling traffic generated by mobility management for MNs will increase explosively, and such a phenomenon will probably affect overall network performance. In this paper, we propose a novel analytical approach using a continuous-time Markov chain model and hierarchical network model for the analysis on the signaling load of representative IPv6 mobility support Protocols such as Mobile IPv6 (MIPv6) and Hierarchical Mobile IPv6 (HMIPv6). According to these analytical modeling, this paper derives the various signaling costs, which are generated by an MN during its average domain residence time when MIPv6 and HMIPv6 are deployed under the same network architecture, respectively. In addition, based on these derived costs, we investigate the effects of various mobility/traffic-related parameters on the signaling costs generated by an MN under MIPv6 and HMIPv6. The analytical results show that as the average moving speed of an MN gets higher and the binding lifetime is set . to the larger value, and as its average packet arrival rate gets lower, the total signaling cost generated during its average domain residence time under HMIPv6 will get relatively lower than that under MIPv6, and that under the reverse conditions, the total signaling cost under MIPv6 will get relatively lower than that under HMIPv6.

• Journal of KIISE
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• v.43 no.12
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• pp.1437-1457
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• 2016

In outsourced databases, the cloud provides an authorized user with querying services on the outsourced database. However, sensitive data, such as financial or medical records, should be encrypted before being outsourced to the cloud. Meanwhile, k-Nearest Neighbor (kNN) query is the typical query type which is widely used in many fields and the result of the kNN query is closely related to the interest and preference of the user. Therefore, studies on secure kNN query processing algorithms that preserve both the data privacy and the query privacy have been proposed. However, existing algorithms either suffer from high computation cost or leak data access patterns because retrieved index nodes and query results are disclosed. To solve these problems, in this paper we propose a new kNN query processing algorithm on the encrypted database. Our algorithm preserves both data privacy and query privacy. It also hides data access patterns while supporting efficient query processing. To achieve this, we devise an encrypted index search scheme which can perform data filtering without revealing data access patterns. Through the performance analysis, we verify that our proposed algorithm shows better performance than the existing algorithms in terms of query processing times.

• Journal of KIISE
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• v.42 no.3
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• pp.307-319
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• 2015

Current ontology studies use the Hadoop distributed storage framework to perform map-reduce algorithm-based reasoning for scalable ontologies. In this paper, however, we propose a novel approach for scalable Web Ontology Language (OWL) Horst Lite ontology reasoning, based on distributed cluster memories. Rule-based reasoning, which is frequently used for scalable ontologies, iteratively executes triple-format ontology rules, until the inferred data no longer exists. Therefore, when the scalable ontology reasoning is performed on computer hard drives, the ontology reasoner suffers from performance limitations. In order to overcome this drawback, we propose an approach that loads the ontologies into distributed cluster memories, using Spark (a memory-based distributed computing framework), which executes the ontology reasoning. In order to implement an appropriate OWL Horst Lite ontology reasoning system on Spark, our method divides the scalable ontologies into blocks, loads each block into the cluster nodes, and subsequently handles the data in the distributed memories. We used the Lehigh University Benchmark, which is used to evaluate ontology inference and search speed, to experimentally evaluate the methods suggested in this paper, which we applied to LUBM8000 (1.1 billion triples, 155 gigabytes). When compared with WebPIE, a representative mapreduce algorithm-based scalable ontology reasoner, the proposed approach showed a throughput improvement of 320% (62k/s) over WebPIE (19k/s).

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.14 no.3
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• pp.68-76
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• 2000

The stabilization control of Inverted Pendulum(IP) system is difficult because of its nonlinearity and structural unstability. Futhermore, a series of conventional techniques such as the pole placement and the optimal control based on the local linearizations have narrow stabilizable regions. At the same time, the fine tunings of their gain parameters are also troublesome. Thus, in this paper, an Evolving Neural Network Controller(ENNC) which its structure and its connection weights are optimized simultaneously by Real Variable Elitist Genetic Algorithm(RVEGA) was presented for stabilization of an IP system with nonlinearity. This proposed ENNC was described by a simple genetic chromosome. And the deletion of neuron, the according to the various flag types. Therefore, the connection weights, its structure and the neuron types in the given ENNC can be optimized by the proposed evolution strategy. And the proposed ENNC was implemented successfully on the ADA-2310 data acquisition board and the 80586 microprocessor in order to stabilize the IP system. Through the simulation and experimental results, we showed that the finally acquired optimal ENNC was very useful in the stabilization control of IP system.

• International Journal of Highway Engineering
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• v.7 no.4 s.26
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• pp.41-47
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• 2005

Traffic data such as traffic volume, speed, and vehicle Class are very important basic data for the plan and design of highway. Based on traffic data, the future service level of a specific highway and geometry of newly constructed or expended road is predicted and determined. The Ministry of Construction & Transportation has simultaneously surveyed coverage count and permanent count at highways since 1985. Traffic volume survey sections were determined at jointed nodes of highways and jointed nodes of highways and other roads such as freeway and local highway. Volume survey was performed at these sections. The premise to decide these sections is assumed that links between jointed nodes of main highways exhibit similar traffic characteristics. Recently, due to the change of highway geometries such as construction of detour road and installations of traffic facilities such as installation of media, traffic characteristics of the existing traffic volume survey sections was changed. To reflect these changes, traffic characteristics at homogeneous road sections was widely evaluated and analyzed. Using Genetic Algorithms, a model was developed for the evaluation of traffic characteristics at homogeneous road sections. Traffic volume survey sections were then determined through the application of the developed model for current traffic system.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.4
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• pp.28-38
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• 2009

In this study, a remote air quality monitoring system for underground spaces was developed by using NDIR-based CO$_2$ sensor. And the remote monitoring system based on wireless sensor networks was installed practically on the subway station platform. More than 6.5 million citizens commutate everyday by the Seoul subway transportation that is the most typical public transportation. They concern about air quality with increasing interest on public health or many workers in subway stations or underground shopping centers. Recently, the Korean Ministry of Environment has operated the air quality monitoring system in some subway stations for testing phase. However, it showed many defects which are large-scale, high-cost and maintenance of precision sensors imported from abroad. Therefore this research includes the reliability test and a theoretical study about the inexpensive commercialized CO$_2$ sensor for reliable measurement of air quality which changes rapidly by the surrounding environments. And then we develop the wireless sensor nodes and the gateway applied for remote air quality monitoring. In addition, web server program was realized to manage air quality in the subway platform. This result will be valuable for a basic research for air quality management in underground spaces for future study.

• 한국지구과학회:학술대회논문집
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• 2006.02a
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• pp.239-244
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• 2006

충청북도 영동 지역에 분포하는 영동층군은 옥천변성대에 있는 소규모 퇴적분지중의 하나이다. 영동층군의 지질과 고생물에 관한 연구는 옥천변성대의 조구조운동과 관련한 퇴적분지 발달 규명과 아울러 경상분지와의 상호대비가 가능케 함으로써 이 시기의 한반도의 지질을 이해하는데 있어 매우 중요한 정보를 제공해 줄 수 있다(김규봉 등, 1986). 영동층군의 층서고생물학적 연구는 김규봉 등(1986), 전희영 등(1993), 최성자 등(1995)등의 연구가 있다. Shimamura (1927)는 영동층군에서 케이로레피드과(Cherolepidiaceae)에 속하는 식물화석의 산출을 처음 보고하였다. 이후 전희영 등(1993), 최성자 등(1995)이 영동층군에서 케이로레피드과에 속하는 식물화석을 다시 보고함으로써 영동층군에서 식물화석이 많이 산출될 가능성이 확인되었다. 본 연구에서는 식물화석의 연구에 중점을 두고 야외지질조사를 통하여 영동층군의 기존 화석산지와 새로운 화석산지로부터 많은 식물 화석을 채집하였다. 식물 화석은 모두 인상화석으로 보존되었으며 세일층의 층리면에 평행하게 밀집된 상태로 나타나지만 대부분 파편상으로 나타난다. 식물화석은 고환경이나 고생태에 대한 중요한 단서를 제공하고 과거의 기후를 알려주는 중요한 지시자로 사용되고 있다. 특히 케이로레피드과의 식물은 백악기의 대표적인 고기후의 지시자로서 잘 알려져 있다. 케이로레피드과의 식물은 분류상 구과류에 속하며 백악기에 걸쳐 세계적인 분포를 보이고 있는 화석이다. 본 연구는 영동층군에서 산출된 구과류 화석을 대상으로 고생물학적 연구를 수행하여 산출화석의 특징을 기재하고 체계적으로 분류함으로써 산출화석의 고식물학적 의미를 밝히고자 하였다. 또한 산출 화석의 특징과 지질학적 특징을 통해 중생대 백악기 영동지역의 고기후를 해석함으로써 고기후적 및 고생태학적 의미를 연구해 보고자 하였다.에서는 시스템 등급에 영향을 준다. 향후에는 더욱 더 다양한 상호의존 모델들이 정량화될 필요성이 있다고 본다. 진행하였다. 줄여서 보다 더 정확하고, 지능적인 규칙구성요소 추출 방법론을 제시하고 구현하여 지식관리자의 규칙습득에 대한 부담을 줄여 주고자 한다. 도움을 받을 수 있게 되었다.을 거치도록 되어있다. 교통주제도는 국가의 교통정책결정과 관련분야의 기초자료로서 다양하게 활용되고 있으며, 특히 ITS 노드/링크 기본지도로 활용되는 등 교통 분야의 중요한 지리정보로서 구축되고 있다..20{\pm}0.37L$, 72시간에 $1.33{\pm}0.33L$로 유의한 차이를 보였으므로(F=6.153, P=0.004), 술 후 폐환기능 회복에 효과가 있다. 4) 실험군과 대조군의 수술 후 노력성 폐활량은 수술 후 72시간에서 실험군이 $1.90{\pm}0.61L$, 대조군이 $1.51{\pm}0.38L$로 유의한 차이를 보였다(t=2.620, P=0.013). 5) 실험군과 대조군의 수술 후 일초 노력성 호기량은 수술 후 24시간에서 $1.33{\pm}0.56L,\;1.00{\ge}0.28L$로 유의한 차이를 보였고(t=2.530, P=0.017), 술 후 72시간에서 $1.72{\pm}0.65L,\;1.33{\pm}0.3L$로 유의한 차이를 보였다(t=2.540, P=0.016). 6) 대상자의 술 후 폐환기능에 영향을 미치는 요인은 성별로 나타났다. 이에 따른 폐환기능의 차이를 보면, 실험군의 술 후 노력성 폐활량이 48시간에 남자($1.78{\pm}0.61L$)가 여자($1.27{\pm}0.45L$)보다 더 높게 나타났으며 (t=2.170, P=0.042), 72시간에도 역시 남자($2.1

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.121-121
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• 2011

도시유역 물순환 해석 모형(Catchment hydrologic cycle Analysis Tool, CAT)은 기존의 개념적 매개변수 기반의 집중형 수문모형과 물리적 매개변수 기반의 분포형 수문모형의 장점을 최대한 집약하여, 도시유역 개발 전/후의 장/단기적 물순환 변화특성을 정량적으로 평가하고 물순환 개선시설의 효과적인 설계를 지원하기 위한 물순환 해석 모형이다. 이 모형은 수문학적으로 균일하게 판단되는 범위를 소유역으로 분할하여 지형학적 요인에 의한 유출 특성을 객관적으로 반영할 수 있으며, 개발 공간 단위별로 침투, 증발, 지하수 흐름 등의 모의가 가능하도록 하는 링크-노드 방식으로 개발되었다. 모형의 UI(User Interface)는 사용자가 손쉽게 모형을 적용/관리하고, 여러 시나리오를 동시에 효과적으로 모의하여 분석할 수 있도록 설계되었다. 또한, 모든 입/출력 자료를 엑셀이나 텍스트 형식과 연동되도록 하여 프로젝트별 매개변수 관리가 용이하도록 개발하였다. 특히 본 모형에서는 사용자의 목적에 맞는 다양한 물순환 개선시설(침투시설, 저류지, 습지, 빗물저장시설, 리사이클 및 외부급수 등)의 구현 및 모의가 가능하도록 개발하였다. CAT은 수자원의지속적확보기술개발사업(2008 ~ 2011)의 연구 성과로서 한국건설기술연구원에서 개발하였다. 2008년 말에 모형의 기본구조가 개발되었고, 2009년에는 세부 알고리즘인 증발산, 침투, 유역 유출, 지하수 유거, 하도추적 등의 모듈과 사용자 편의시스템이 개발되었다. 2010년에는 우리나라 논의 특성을 반영한 논 유출 해석 모듈 및 저류지, 침투시설, 습지, 빗물이용시설 및 하천에서의 취수와 도수 등과 같은 물순환 개선시설을 평가할 수 있는 모듈을 추가하여 개발하였으며 2010년 3월에 도시유역 물순환 해석 모형 1.0 베타 버전을 출시하였다. 2010년 12월 에는 1.0 베타 버전에 침투해석모듈(Green&Ampt, Horton), 논에서의 개량물꼬 배수, 침투녹지(Bioretention) 및 차집관거 기능을 추가하였고, 기타 GUI의 업그레이드 및 추가를 통하여 1.5 베타 버전을 출시하였다. 현재까지 여러 자연유역과 신도시 개발지역에 대한 적용을 통하여 모형의 적용성을 평가하였다. 본 연구에서는 기존의 자연유역과 신도시 개발지역 외에 농업용 저수지와 논 관개지구가 위치한 유역을 대상으로 모형의 적용성을 평가하고자 하였다. 대상유역은 농업용수 지구이며 농업수리시설의 종류와 규모가 다양할 뿐만 아니라 농촌유역으로써의 대표성을 가지고 기존의 관측자료가 풍부한 점 등을 고려하여 경기도 평택의 이동유역을 선정하였다. 이동유역은 행정구역으로는 경기도 용인시 이동면, 남사면 일원이며 서쪽은 경기도 오산시, 남쪽은 평택시, 안성시 그리고, 북쪽은 용인시와 인접하고 있다. 이동유역 내 주요시설로서 유역면적 $94.4km^2$의 이동저수지와 상류에 용덕저수지($12.41km^2$)와 미산저수지($4.39km^2$), 노곡저수지($2.00km^2$)의 3개 저수지가 위치하며 2개의 유입하천(진위천, 송전천)에 의해 이동저수지로 유입된다.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.10
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• pp.397-406
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• 2014

In order to answer the questions successfully on behalf of the human in DeepQA environments such as Jeopardy! of the American quiz show, the computer is required to have the capability of fast temporal and spatial reasoning on a large-scale commonsense knowledge base. In this paper, we present a scalable spatial reasoning algorithm for deriving efficiently new directional and topological relations using the MapReduce framework, one of well-known parallel distributed computing environments. The proposed reasoning algorithm assumes as input a large-scale spatial knowledge base including CSD-9 directional relations and RCC-8 topological relations. To infer new directional and topological relations from the given spatial knowledge base, it performs the cross-consistency checks as well as the path-consistency checks on the knowledge base. To maximize the parallelism of reasoning computations according to the principle of the MapReduce framework, we design the algorithm to partition effectively the large knowledge base into smaller ones and distribute them over multiple computing nodes at the map phase. And then, at the reduce phase, the algorithm infers the new knowledge from distributed spatial knowledge bases. Through experiments performed on the sample knowledge base with the MapReduce-based implementation of our algorithm, we proved the high performance of our large-scale spatial reasoner.

• Journal of Biomedical Engineering Research
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• v.18 no.4
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• pp.429-438
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• 1997

Mechanical valve is one of the most widely used implantable artificial organs of which the reliability is so important that its failure means the death of patient. Therefore early noninvasive detection is essentially required, though mechanical valve failure with thrombosis is the most common. The objective of this paper is to detect the thrombosis formation by spectral analysis and neural network. Using microphone and amplifier, we measured the sound from the mechanical valve which is attached to the pneumatic ventricular assist device. The sound was sampled by A/D converter(DaqBook 100) and the periodogram is the main algorithm for obtaining spectrum. We made the thrombosis models using pellethane and silicon and they are thrombosis model on the valvular disk, around the sewing ring and fibrous tissue growth across the orifice of valve. The performance of the measurment system was tested firstly using 1 KHz sinusoidal wave. The measurement system detected well 1KHz spectrum as expected. The spectrum of normal and 5 kinds of thrombotic valve were obtained and primary and secondary peak appeared in each spectrum waveform. We find that the secondary peak changes according to the thrombosis model. So to distinguish the secondary peak of normal and thrombotic valve quantatively, 3 layer back propagation neural network, which contains 7, 000 input node, 20 hidden layer and 1 output was employed The trained neural network can distinguish normal and valve with more than 90% probability. As a conclusion, the noninvasive monitoring of implanted mechanical valve is possible by analysing the acoustical spectrum using neural network algorithm and this method will be applied to the performance evaluation of other implantable artificial organs.