• Title/Summary/Keyword: $A^*$ search algorithm

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Automatic Extraction of Eye and Mouth Fields from Face Images using MultiLayer Perceptrons and Eigenfeatures (고유특징과 다층 신경망을 이용한 얼굴 영상에서의 눈과 입 영역 자동 추출)

  • Ryu, Yeon-Sik;O, Se-Yeong
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.37 no.2
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    • pp.31-43
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    • 2000
  • This paper presents a novel algorithm lot extraction of the eye and mouth fields (facial features) from 2D gray level face images. First of all, it has been found that Eigenfeatures, derived from the eigenvalues and the eigenvectors of the binary edge data set constructed from the eye and mouth fields are very good features to locate these fields. The Eigenfeatures, extracted from the positive and negative training samples for the facial features, ate used to train a MultiLayer Perceptron(MLP) whose output indicates the degree to which a particular image window contains the eye or the mouth within itself. Second, to ensure robustness, the ensemble network consisting of multiple MLPs is used instead of a single MLP. The output of the ensemble network becomes the average of the multiple locations of the field each found by the constituent MLPs. Finally, in order to reduce the computation time, we extracted the coarse search region lot eyes and mouth by using prior information on face images. The advantages of the proposed approach includes that only a small number of frontal faces are sufficient to train the nets and furthermore, lends themselves to good generalization to non-frontal poses and even to other people's faces. It was also experimentally verified that the proposed algorithm is robust against slight variations of facial size and pose due to the generalization characteristics of neural networks.

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A Scalable OWL Horst Lite Ontology Reasoning Approach based on Distributed Cluster Memories (분산 클러스터 메모리 기반 대용량 OWL Horst Lite 온톨로지 추론 기법)

  • Kim, Je-Min;Park, Young-Tack
    • 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).

Driver Route Choice Models for Developing Real-Time VMS Operation Strategies (VMS 실시간 운영전략 구축을 위한 운전자 경로선택모형)

  • Kim, SukHee;Choi, Keechoo;Yu, JeongWhon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.3D
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    • pp.409-416
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    • 2006
  • Real-time traveler information disseminated through Variable Message Signs (VMS) is known to have effects on driver route choice decisions. In the past, many studies have attempted to optimize the system performance using VMS message content as the primary control variable of driver route choice. This research proposes a VMS information provision optimization model which searches the best combination of VMS message contents and display sequence to minimize the total travel time on a highway network considered. The driver route choice models under VMS information provision are developed using a stated preference (SP) survey data in order to realistically capture driver response behavior. The genetic algorithm (GA) is used to find the optimal VMS information provision strategies which consists of the VMS message contents and the sequence of message display. In the process of the GA module, the system performance is measured using micro traffic simulation. The experiment results highlight the capability of the proposed model to search the optimal solution in an efficient way. The results show that the traveler information conveyed via VMS can reduce the total travel time on a highway network. They also suggest that as the frequency of VMS message update gets shorter, a smaller number of VMS message contents performs better to reduce the total travel time, all other things being equal.

Detecting Cadastral Discrepancy Method based on MMAS (MMAS 기법에 의한 지적불부합지 탐색기법)

  • Cho, Sung-Hwan;Huh, Yong
    • Journal of Cadastre & Land InformatiX
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    • v.45 no.2
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    • pp.149-160
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    • 2015
  • This paper suggests the MMAS(Map Matching using Additional Surveying) method to improve the cadastral discrepancy search algorithm that currently does not include corrections of mis-represented parcel data. The MMAS is a method to search for cadastral discrepancy after correcting mis-represented parcel data using nearby anchor points confirmed by surveys. The MMAS first transforms the coordinate system of the digital cadastral map by overlaying anchor points obtained in the field surveying process over the corresponding edges of buildings and facility points on the digital topographic map. Then, it searches for cadastral discrepancy by checking if the area differences exceed the tolerance limit. This method improves the current method for searching for cadastral discrepancy by performing the process after correcting extortion of the digital cadastral map. This helps to identify cadastral discrepancies that are not detectable within the distorted digital cadastral map. With our experiment, this method identified more discrepancies compared to the method without the correcting the distortion of the digital cadastral map. We believe this method will be able to help the national cadastral re-survey by identifying potential cadastral discrepancy more accurately.

News Video Shot Boundary Detection using Singular Value Decomposition and Incremental Clustering (특이값 분해와 점증적 클러스터링을 이용한 뉴스 비디오 샷 경계 탐지)

  • Lee, Han-Sung;Im, Young-Hee;Park, Dai-Hee;Lee, Seong-Whan
    • Journal of KIISE:Software and Applications
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    • v.36 no.2
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    • pp.169-177
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    • 2009
  • In this paper, we propose a new shot boundary detection method which is optimized for news video story parsing. This new news shot boundary detection method was designed to satisfy all the following requirements: 1) minimizing the incorrect data in data set for anchor shot detection by improving the recall ratio 2) detecting abrupt cuts and gradual transitions with one single algorithm so as to divide news video into shots with one scan of data set; 3) classifying shots into static or dynamic, therefore, reducing the search space for the subsequent stage of anchor shot detection. The proposed method, based on singular value decomposition with incremental clustering and mercer kernel, has additional desirable features. Applying singular value decomposition, the noise or trivial variations in the video sequence are removed. Therefore, the separability is improved. Mercer kernel improves the possibility of detection of shots which is not separable in input space by mapping data to high dimensional feature space. The experimental results illustrated the superiority of the proposed method with respect to recall criteria and search space reduction for anchor shot detection.

Optimum Structural Design of Tankers Using Multi-objective Optimization Technique (다목적함수 최적화기법을 이용한 유조선의 최적구조설계)

  • 신상훈;장창두;송하철
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.15 no.4
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    • pp.591-598
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    • 2002
  • In the ship structural design, the material cost of hull weight and the overall cost of construction processes should be minimized considering safety and reliability. In the past, minimum weight design has been mainly focused on reducing material cost and increasing dead weight reflect the interests of a ship's owner. But, in the past experience, the minimum weight design has been inevitably lead to increasing the construction cost. Therefore, it is necessary that the designer of ship structure should consider both structural weight and construction cost. In this point of view, multi-objective optimization technique is proposed to design the ship structure in this study. According to the proposed algorithm, the results of optimization were compared to the structural design of actual VLCC(Very Large Crude Oil Carrier). Objective functions were weight cost and construction cost of VLCC, and ES(Evolution Strategies), one of the stochastic search methods, was used as an optimization solver. For the scantlings of members and the estimations of objectives, classification rule was adopted for the longitudinal members, and the direct calculation method, GSDM(Generalized Slope Deflection Method), lot the transverse members. To choose the most economical design point among the results of Pareto optimal set, RFR(Required Freight Rate) was evaluated for each Pareto point, and compared to actual ship.

Low-Power Motion Estimator Architecture for Deep Sub-Micron Multimedia SoC (Deep Submicron 공정의 멀티미디어 SoC를 위한 저전력 움직임 추정기 아키텍쳐)

  • 연규성;전치훈;황태진;이성수;위재경
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.41 no.10
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    • pp.95-104
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    • 2004
  • This paper propose a motion estimator architecture to reduce the power consumption of the most-power-consuming motion estimation method when designing multimedia SoC with deep submicron technologies below 0.13${\mu}{\textrm}{m}$. The proposed architecture considers both dynamic and static power consumption so that it is suitable for large leakage process technologies, while conventional architectures consider only dynamic power consumption. Consequently, it is suitable for mobile information terminals such as mobile videophone where efficient power management is essential. It exploits full search method for simple hardware implementation. It also exploits early break-off method to reduce dynamic power consumption. To reduce static power consumption, megablock shutdown method considering power line noise is also employed. To evaluate the proposed architecture when applied multimedia SoC, system-level control flow and low-power control algorithm are developed and the power consumption was calculated based on thor From the simulation results, power consumption was reduced to about 60%. Considering the line width reduction and increased leakage current due to heat dissipation in chip core, the proposed architecture shows steady power reduction while it goes worse in conventional architectures.

Generation of Feature Map for Improving Localization of Mobile Robot based on Stereo Camera (스테레오 카메라 기반 모바일 로봇의 위치 추정 향상을 위한 특징맵 생성)

  • Kim, Eun-Kyeong;Kim, Sung-Shin
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.13 no.1
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    • pp.58-63
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    • 2020
  • This paper proposes the method for improving the localization accuracy of the mobile robot based on the stereo camera. To restore the position information from stereo images obtained by the stereo camera, the corresponding point which corresponds to one pixel on the left image should be found on the right image. For this, there is the general method to search for corresponding point by calculating the similarity of pixel with pixels on the epipolar line. However, there are some disadvantages because all pixels on the epipolar line should be calculated and the similarity is calculated by only pixel value like RGB color space. To make up for this weak point, this paper implements the method to search for the corresponding point simply by calculating the gap of x-coordinate when the feature points, which are extracted by feature extraction and matched by feature matching method, are a pair and located on the same y-coordinate on the left/right image. In addition, the proposed method tries to preserve the number of feature points as much as possible by finding the corresponding points through the conventional algorithm in case of unmatched features. Because the number of the feature points has effect on the accuracy of the localization. The position of the mobile robot is compensated based on 3-D coordinates of the features which are restored by the feature points and corresponding points. As experimental results, by the proposed method, the number of the feature points are increased for compensating the position and the position of the mobile robot can be compensated more than only feature extraction.

A Heterogeneous-carrier Selectable Routing Scheme Based on Normalized Location and Transmission Characteristics (MCS-NLTC) for Multi-carrier MANETs at Sea (다중매체로 이루어진 해상 자율망에서 이종 매체 선택이 가능하고 정규화된 위치와 전송특성에 의한 라우팅)

  • Son, Joo-Young
    • Journal of Navigation and Port Research
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    • v.38 no.4
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    • pp.343-348
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    • 2014
  • A routing scheme called MCS-NLTC using a self-configuration marine network model and the diversity and heterogeneity of broadband wireless access technologies is newly proposed. The MCS-NLTC algorithm selects optimal nodes and carriers for every hop in optimal routes based on not conventional hop counts but normalized distances to destination ships (location information of destination ships). Normalized transmission characteristics of applications and carriers are considered to get optimal routes as well. The location information enhances convergence speed to get destinations, which makes the route search time faster. Evaluated performances are compared with those of the schemes based on max-win (OMH-MW), and normalized transmission characteristics (MCS-NTC).

On Estimating Position and Velocity of Mobile Stations by Path-loss Data Base in a Cellular System (셀룰라 이동 통신 시스템에서 경로손실 데이터 베이스를 이용한 이동국의 위치와 속도 추정 방식)

  • Lee, Sang-Hun;Chung, Woo-Gon;Choi, Hyung-Jin
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.35S no.11
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    • pp.19-27
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    • 1998
  • To achieve the required services in the next-generation cellular telephone systems, the size of the cell become smaller and/or is of mixed macrocells and microcells. For more efficient system control, We make use of the mobile position and velocity information, provided that the mobility information is relatively accurate. In this paper, we propose an improved version of path-loss measurement algorithm introduced in literature[11]. The microcellular structure with severe multipath fading, reflection and refraction make mobile position and velocity estimation very difficult. In the proposed method, the pre-recorded path-loss informations, called the discrete position data base, are searched to estimate the position. Velocity estimation is obtained as a difference of the position values with respect to the time difference. Moving average filter is applied to smooth the estimated velocity and to reduce the error in the estimates. We also propose a method to simplify system implementation by reducing search area for discrete area database.

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