군집 노이즈 필터링 기반 이동 궤적 정제 기법

김소정(Sojeong Kim),이석훈(Sukhoon Lee) 한국정보기술학회 2020 한국정보기술학회논문지 Vol.18 No.3

The location-based services mainly use GPS coordinates for smartphones and wearable devices. However, GPS coordinates generate noise due to sensor performance and errors and various filters have been studied to removed them. These filters are used to refine the trajectory but still require a manual process to extract the clear trajectory. Therefore, this paper proposes trajectory refinement based on clustered noise reduction algorithm. To this end, we propose a cluster noise reduction algorithm that identifies and removes the points of stay of the user’s trajectory using a Sequenced DBSCAN. In addition, this paper combines the existing filter and the proposed algorithm to find the optimized filter application order. Through experiments, we refine 100 trajectories with 11 combinations of 12 filters. As the result, the proposed method is efficient and accurate, so it is analyzed to be the best optimized combination.

융합 인덱싱 방법에 의한 조인 쿼리 성능 최적화

짜오티엔이(Tianyi Zhao),이용주(Yong-Ju Lee) 한국전자통신학회 2021 한국전자통신학회 논문지 Vol.16 No.1

RDF(Resource Description Framework) 데이터 구조는 그래프로 모델링하기 때문에, 관계형 데이터베이스와 XML 기술의 기존 솔루션은 RDF 모델에 바로 적용하기 어렵다. 우리는 링크 데이터를 더욱 효과적으로 저장하고, 인덱스하고, 검색하기 위해 융합 인덱싱 방법을 제안한다. 이 방법은 HDD(Hard Disk Drive) 와 SSD(Solid State Drive) 디바이스에 기반한 하이브리드 스토리지 시스템을 사용하고, 불필요한 데이터를 필터 하고 중간 결과를 정제하기 위해 분리된 필터 및 정제 인덱스 구조를 사용한다. 우리는 3개의 표준 조인 검색 알고리즘에 대한 성능 비교를 수행했는데, 실험 결과 제안된 방법이 Quad와 Darq와 같은 다른 기존 방법들에 비해 뛰어난 성능을 보인다. Since RDF (Resource Description Framework) triples are modeled as graph, we cannot directly adopt existing solutions in relational databases and XML technology. In order to store, index, and query Linked Data more efficiently, we propose a convergence indexing method combined R*-tree and K-dimensional trees. This method uses a hybrid storage system based on HDD (Hard Disk Drive) and SSD (Solid State Drive) devices, and a separated filter and refinement index structure to filter unnecessary data and further refine the immediate result. We perform performance comparisons based on three standard join retrieval algorithms. The experimental results demonstrate that our method has achieved remarkable performance compared to other existing methods such as Quad and Darq.

Accuracy Refinement Algorithm for Mobile Target Location Tracking by Radio Signal Strength Indication Approach

LAU, Erin-Ee-Lin,CHUNG, Wan-Young The Institute of Electronics, Information and Comm 2008 IEICE transactions on fundamentals of electronics, Vol.91 No.7

<P>A novel RSSI (Received Signal Strength Indication) refinement algorithm is proposed to enhance the resolution for indoor and outdoor real-time location tracking system. The proposed refinement algorithm is implemented in two separate phases. During the first phase, called the pre-processing step, RSSI values at different static locations are collected and processed to build a calibrated model for each reference node. Different measurement campaigns pertinent to each parameter in the model are implemented to analyze the sensitivity of RSSI. The propagation models constructed for each reference nodes are needed by the second phase. During the next phase, called the runtime process, real-time tracking is performed. Smoothing algorithm is proposed to minimize the dynamic fluctuation of radio signal received from each reference node when the mobile target is moving. Filtered RSSI values are converted to distances using formula calibrated in the first phase. Finally, an iterative trilateration algorithm is used for position estimation. Experiments relevant to the optimization algorithm are carried out in both indoor and outdoor environments and the results validated the feasibility of proposed algorithm in reducing the dynamic fluctuation for more accurate position estimation.</P>

딜러니 개선 알고리듬을 이용한 삼차원 구의 보로노이 곡면 삼각화

김동욱 한국산업경영시스템학회 2018 한국산업경영시스템학회지 Vol.41 No.4

Triangulation is one of the fundamental problems in computational geometry and computer graphics community, and it has huge application areas such as 3D printing, computer-aided engineering, surface reconstruction, surface visualization, and so on. The Delaunay refinement algorithm is a well-known method to generate quality triangular meshes when point cloud and/or constrained edges are given in two- or three-dimensional space. In this paper, we propose a simple but efficient algorithm to triangulate Voronoi surfaces of Voronoi diagram of spheres in 3-dimensional Euclidean space. The proposed algorithm is based on the Ruppert’s Delaunay refinement algorithm, and we modified the algorithm to be applied to the triangulation of Voronoi surfaces in two ways. First, a new method to deciding the location of a newly added vertex on the surface in 3-dimensional space is proposed. Second, a new efficient but effective way of estimating approximation error between Voronoi surface and triangulation. Because the proposed algorithm generates a triangular mesh for Voronoi surfaces with guaranteed quality, users can control the level of quality of the resulting triangulation that their application problems require. We have implemented and tested the proposed algorithm for random non-intersecting spheres, and the experimental result shows the proposed algorithm produces quality triangulations on Voronoi surfaces satisfying the quality criterion.

Triangulation of Voronoi Faces of Sphere Voronoi Diagram using Delaunay Refinement Algorithm

Donguk Kim 한국산업경영시스템학회 2018 한국산업경영시스템학회지 Vol.41 No.4

Triangulation is one of the fundamental problems in computational geometry and computer graphics community, and it has huge application areas such as 3D printing, computer-aided engineering, surface reconstruction, surface visualization, and so on. The Delaunay refinement algorithm is a well-known method to generate quality triangular meshes when point cloud and/or constrained edges are given in two- or three-dimensional space. In this paper, we propose a simple but efficient algorithm to triangulate Voronoi surfaces of Voronoi diagram of spheres in 3-dimensional Euclidean space. The proposed algorithm is based on the Ruppert’s Delaunay refinement algorithm, and we modified the algorithm to be applied to the triangulation of Voronoi surfaces in two ways. First, a new method to deciding the location of a newly added vertex on the surface in 3-dimensional space is proposed. Second, a new efficient but effective way of estimating approximation error between Voronoi surface and triangulation. Because the proposed algorithm generates a triangular mesh for Voronoi surfaces with guaranteed quality, users can control the level of quality of the resulting triangulation that their application problems require. We have implemented and tested the proposed algorithm for random non-intersecting spheres, and the experimental result shows the proposed algorithm produces quality triangulations on Voronoi surfaces satisfying the quality criterion.

Market Timing with the VKOSPI Refined Composite Multiscale Entropy Indicator

Joung Keun Cho,Woo Suk Choi 한국산업경제학회 2016 산업경제연구 Vol.29 No.5

대한민국 주식시장의 대표적인 대형주 지수인 코스피 200지수와 추정모델에 기반하지 않은 변동성지수인 VKOSPI 변동성지수 분석을 통해 대형주 주가지수와 변동성지수간 통계적으로 유의한 부(負)의 관계를 확인하였다. 본 연구는 VKOSPI 변동성지수의 비대칭적 정보성격의 존재하에서 의미있는 정보지수로서의 VKOSPI Refined Composite Multiscale Entropy 변동성지표를 활용한 알고리즘 트레이딩 전략을 개발하는데 주안점을 두었다. VKOSPI Refined Composite Multiscale Entropy 지표의 변동에 따른 코스피200 주가지수선물의 Long 및 Short 매매전략이 본 연구에서 개발된 알고리즘 트레이딩 플랫폼을 통하여 외표본 시뮬레이션을 적용하였다. 이를 통해 큰 규모의 VKOSPI Refined Composite Multiscale Entropy 지표변동은 특히 위험회피도 조정국면에서 평균회귀매매전략 (Mean Reversion Trades)의 로직으로 해석되었을 때 양(陽)의 주가지수대비 초과수익률을 실현할 기회에 대한 경험적 증거를 확인할 수 있었다. 이어 VKOSPI Refined Composite Multiscale Entropy 지표의 각각의 매매신호 효율성에 대한 평가를 통해 위험선호도의 하락, 상승 및 정체기간을 포괄하여 주가지수 벤치마크 성과를 초과할 수 있는 알고리즘매매의 플랫폼을 개발하는 연구가 수행되었다. 본 연구는 (1) 2003년부터 2007년말까지를 위험회피도 하락 및 양(陽)의 주가지수수익률국면, (2) 2008년부터 2011년말까지를 위험회피도 상승 및 지수수익률 변동성 확대국면 및 (3) 2012년부터 본 연구데이터의 마지막 기간인 2015년 5월29일 (영업일 기준)까지 미미한 주가지수수익률을 기록한 위험회피도 조정국면으로 연구 대상 기간을 대 분류한 후, VKOSPI지수 분석을 통하여 위험회피도 국면별 비대칭성분석 및 고유의 알고리즘매매 플랫폼을 통한 동적자산배분 전략의 수행하였다. 변동성 지수를 통해 추출된 VKOSPI Refined Composite Multiscale Entropy 기반 매매신호를 바탕으로 한국 주식시장의 변동성지표의 지수수익률간 비대칭성에 기반한 주가지수 벤치마크 수익률을 초과하는 주가지수선물 매매전략을 통해 새로 만든 Entropy 기반 내재변동성 지표의 안정성 및 활용도를 검증한 결과, 지수변동성이 낮고 일정한 최근의 시장상황에서 평균회귀전략 투자지표로서 활용되었을 때 가장 효율적인 것으로 평가되었다. For the KOSPI200 Index (“Index”), a well-known negative and statistically significant relationship exists between the returns of the Index and VKOSPI, the official model-free implied volatility index. Our primary research purpose is to test VKOSPI as an informative and meaningful trading indicator and to generate some timely trading signals. VKOSPI Refined Composite Multiscale Entropy (“VKOSPI RCMSE” or “RCMSE”) as an alternative complexity indicator was derived from the VKOSPI time series. Both long and short positions triggered by large changes in the RCMSE and the trading strategies are evaluated in terms of their ability to generate alpha through an algorithmic trading platform that will outperform the index benchmark in steady risk aversion regime. There is some empirical evidence for expecting opportunities for positive future excess and risk-adjusted returns for long and short positions triggered by large movements in the RCMSE. This finding is more prominent during the periods of steady risk aversions. Trading strategy is tested on the data period from Jan 2, 2003 to May 29, 2015. The time-varying return-volatility relation is used to implement a set of dynamic asset allocation strategies by analyzing the RCMSE with its corresponding Index. With asymmetric volatility phenomenon in the Korean stock market, selected benchmark-outperforming dynamic asset allocation strategies are developed by processing meaningful signals from RCMSE indicator on the Index Futures.

Optimum design of plane steel frames with PR-connections using refined plastic hinge analysis and genetic algorithm

Yun, Young Mook,Kang, Moon Myung,Lee, Mal Suk Techno-Press 2006 Structural Engineering and Mechanics, An Int'l Jou Vol.23 No.4

A Genetic Algorithm (hereinafter GA) based optimum design algorithm and program for plane steel frames with partially restrained connections is presented. The algorithm was incorporated with the refined plastic hinge analysis method, in which geometric nonlinearity was considered by using the stability functions of beam-column members and material nonlinearity was considered by using the gradual stiffness degradation model that included the effects of residual stress, moment redistribution by the occurrence of plastic hinges, partially restrained connections, and the geometric imperfection of members. In the genetic algorithm, a tournament selection method and micro-GAs were employed. The fitness function for the genetic algorithm was expressed as an unconstrained function composed of objective and penalty functions. The objective and penalty functions were expressed, respectively, as the weight of steel frames and the constraint functions which account for the requirements of load-carrying capacity, serviceability, ductility, and construction workability. To verify the appropriateness of the present method, the optimum design results of two plane steel frames with fully and partially restrained connections were compared.

An Improved PSO Algorithm Based CommunityTopic Refinement Strategy for Social Network

Lin Cui,Caiyin Wang,Xiaoyin Wu 보안공학연구지원센터 2016 International Journal of Future Generation Communi Vol.9 No.1

Aiming at the division roughness of topic classification existing in the most online social networks community, the improved particle swarm optimization algorithm is applied to refine community topics and concepts of community seeds and community topic are also introduced. In this paper, first of all, the explicit links existing in the community are mined, and the basic community structure is constructed, then the community content is deeply analyzed, according to implicit feature between nodes under online community, community topic categories are elaborately refined until structure is stable. Experiments show that this proposed algorithm can accelerate the convergence of the node and greatly improves the topic mining accuracy of online social network compared with the state-of-art CR2NDAS model and PLSA model.

기하학적 해싱을 이용한 딜러니 개선 알고리듬의 가속화

김동욱(Donguk Kim) (사)한국CDE학회 2017 한국CDE학회 논문집 Vol.22 No.2

Delaunay refinement algorithm is a classical method to generate quality triangular meshes when point cloud and/or constrained edges are given in two- or three-dimensional space. It computes the Delaunay triangulation for given points and edges to obtain an initial solution, and update the triangulation by inserting steiner points one by one to get an improved quality triangulation. This process repeats until it satisfies given quality criteria. The efficiency of the algorithm depends on the criteria and point insertion method. In this paper, we propose a method to accelerate the Delaunay refinement algorithm by applying geometric hashing technique called bucketing when inserting a new steiner point so that it can localize necessary computation. We have tested the proposed method with a few types of data sets, and the experimental result shows strong linear time behavior.

유전자 탐색기법을 활용한 기업신용평점모형의 지식 정제방법

신택수(Taek Soo Shin),한인구(In Goo Han) 한국경영학회 2002 經營學硏究 Vol.31 No.6

Credit rating for commercial loans is an important task for loan officers of a bank who usually use a credit-rating teble(CRT) based on a point system. However, the loan decision making using such a table has its limitations as follows. First, CRT needs a few critical judgments for commercial loans. For example, the judgments consist of knowledge.acwuisition on the criteria such as variable selection, weights between variables. cut-offs between intercals within each variable, and relative value at each interval of the variables for caredit rating. The first level criteria such as quantitative and qualitative variables need to be expressed on interval scales to assess a credit score for each variable. However, the variables present a problem in terms of measutability. This problem renders it impractical to directly applly theretical or human expertise-based choice strategies to unstructured choice problems. The objective of this study is to presesnt an optimal knowledge acquisition and refinement method of the CRT using genetic algorithms(GAs). In our proposed model, the GAs search the optimal criteria for the CRT applied to credit rating process. For the purpose, the CRT and the GAs are integrated to extract and refine the knowledge of multi-criteria for the CRT. The obtained knowledge supports to find optimal parameters of the CRT for loan officers` decision making. Our experimental results show that the knowledge acquisition and refinement method using the GAs are effective for the CRT as a multi-attribute decision problem.