• Title/Summary/Keyword: Mapping Methodology

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Automatic Mapping Between Large-Scale Heterogeneous Language Resources for NLP Applications: A Case of Sejong Semantic Classes and KorLexNoun for Korean

  • Park, Heum;Yoon, Ae-Sun
    • Language and Information
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    • v.15 no.2
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    • pp.23-45
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    • 2011
  • This paper proposes a statistical-based linguistic methodology for automatic mapping between large-scale heterogeneous languages resources for NLP applications in general. As a particular case, it treats automatic mapping between two large-scale heterogeneous Korean language resources: Sejong Semantic Classes (SJSC) in the Sejong Electronic Dictionary (SJD) and nouns in KorLex. KorLex is a large-scale Korean WordNet, but it lacks syntactic information. SJD contains refined semantic-syntactic information, with semantic labels depending on SJSC, but the list of its entry words is much smaller than that of KorLex. The goal of our study is to build a rich language resource by integrating useful information within SJD into KorLex. In this paper, we use both linguistic and statistical methods for constructing an automatic mapping methodology. The linguistic aspect of the methodology focuses on the following three linguistic clues: monosemy/polysemy of word forms, instances (example words), and semantically related words. The statistical aspect of the methodology uses the three statistical formulae ${\chi}^2$, Mutual Information and Information Gain to obtain candidate synsets. Compared with the performance of manual mapping, the automatic mapping based on our proposed statistical linguistic methods shows good performance rates in terms of correctness, specifically giving recall 0.838, precision 0.718, and F1 0.774.

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Human-like Whole Body Motion Generation of Humanoid Based on Simplified Human Model (단순인체모델 기반 휴머노이드의 인간형 전신동작 생성)

  • Kim, Chang-Hwan;Kim, Seung-Su;Ra, Syung-Kwon;You, Bum-Jae
    • The Journal of Korea Robotics Society
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    • v.3 no.4
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    • pp.287-299
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    • 2008
  • People have expected a humanoid robot to move as naturally as a human being does. The natural movements of humanoid robot may provide people with safer physical services and communicate with persons through motions more correctly. This work presented a methodology to generate the natural motions for a humanoid robot, which are converted from human motion capture data. The methodology produces not only kinematically mapped motions but dynamically mapped ones. The kinematical mapping reflects the human-likeness in the converted motions, while the dynamical mapping could ensure the movement stability of whole body motions of a humanoid robot. The methodology consists of three processes: (a) Human modeling, (b) Kinematic mapping and (c) Dynamic mapping. The human modeling based on optimization gives the ZMP (Zero Moment Point) and COM (Center of Mass) time trajectories of an actor. Those trajectories are modified for a humanoid robot through the kinematic mapping. In addition to modifying the ZMP and COM trajectories, the lower body (pelvis and legs) motion of the actor is then scaled kinematically and converted to the motion available to the humanoid robot considering dynamical aspects. The KIST humanoid robot, Mahru, imitated a dancing motion to evaluate the methodology, showing the good agreement in the motion.

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Methodology of Mapping Quantitative Trait Loci for Binary Traits in a Half-sib Design Using Maximum Likelihood

  • Yin, Zongjun;Zhang, Qin;Zhang, Jigang;Ding, Xiangdong;Wang, Chunkao
    • Asian-Australasian Journal of Animal Sciences
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    • v.18 no.12
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    • pp.1669-1674
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    • 2005
  • Maximum likelihood methodology was applied to analyze the efficiency and statistical power of interval mapping by using a threshold model. The factors that affect QTL detection efficiency (e.g. QTL effect, heritability and incidence of categories) were simulated in our study. Daughter design with multiple families was applied, and the size of segregating population is 500. The results showed that the threshold model has a great advantage in parameters estimation and power of QTL mapping, and has nice efficiency and accuracy for discrete traits. In addition, the accuracy and power of QTL mapping depended on the effect of putative quantitative trait loci, the value of heritability and incidence directly. With the increase of QTL effect, heritability and incidence of categories, the accuracy and power of QTL mapping improved correspondingly.

A Study on the Mapping Guideline of IDEF for UMM Adaptation (UMM 적용을 위한 IDEF 매핑 방법에 대한 연구)

  • Shin Kitae;Park Chankwon;Sim Eoksu;Kim Eungab
    • Korean Management Science Review
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    • v.21 no.2
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    • pp.61-77
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    • 2004
  • As various methodologies for business process analysis and design have been conducted in many organizations by their own ways, those methodologies are not compatible each other. In order to reduce the cost of analysis for organizations. some mapping methods between different methodologies need to be developed. UMM(UN/CEFACT Modeling Methodology) that has an object-oriented point of view. can overcome the limits of existing bottom-up approaches and make it reasonable. It also simplifies the business and administrative procedures. IDEF( Integrated Definition Language) with a structural point of view that has been widely used as a system analysis and design method, needs to be mapped to UMM in order to reuse the existing IDEF models. In this study, we propose a guideline that deals with procedures of utilizing IDEF models from which we want to derive the UMM models for developing an electronic commerce system including electronic documents exchange. By comparing IDEF and UMM, we analyze the differences between those two methodologies. Based on these differences. we suggest the basic strategies for mapping method from IDEF to UMM. We also propose a mapping guideline that can make UMM results from the modeling results of IDEF. We can take an advantage of the existing IDEF analysis design results when we adopt UMM methodology for electronic business system. Many analysts who are familiar with the IDEF methodology can develop UMM work-flow by utilizing their existing results and skills.

Hardware/Software Partitioning Methodology for Reconfigurable System (재구성형 시스템을 위한 하드웨어/소프트웨어 분할 기법)

  • Kim, Jun-Yong;Ahn, Seong-Yong;Lee, Jeong-A.
    • The KIPS Transactions:PartA
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    • v.11A no.5
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    • pp.303-312
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    • 2004
  • In this paper, we propose a methodology solving the problem of the hardware-software partitioning in reconfigurable systems using a Y-chart design space exploration and implement a simulator according to the methodology. The methodology generates a mapping set between tasks and hardware elements using the hardware element model and the application model. We evaluate the throughput by simulating cases in each mapping set. With the throughput evaluation result, we can select the mapping case with the highest throughput. We also propose an heuristic improving the simulation time by reducing the mapping set on the basis of the relationship between workload and parallelism. Simulation results show that we can reduce the size of mapping set which poses difficulties on hardware-software partitioning by up to 80%.

Genetic Algorithm-based Hardware Resource Mapping Technique for the latency optimization in Wireless Network-on-Chip (무선 네트워크-온-칩에서 지연시간 최적화를 위한 유전알고리즘 기반 하드웨어 자원의 매핑 기법)

  • Lee, Young Sik;Lee, Jae Sung;Han, Tae Hee
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2016.05a
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    • pp.174-177
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    • 2016
  • Wireless network-on-chip (WNoC) can alleviate critical path problem of existing typical NoCs by integrating radio-frequency module on router. In this paper, core-connection-aware genetic algorithm-based core and WIR mapping methodology at small world WNoC is presented. The methodology could optimize the critical path between cores with heavy communication. The 33% of average latency improvement is achieved compared to random mapping methodology.

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The Synthesizing Implementation of Iterative Algorithms on Processor Arrays (순환 알고리즘의 Processor Array에로의 합성 및 구현)

  • 이덕수;신동석
    • Journal of the Korean Institute of Navigation
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    • v.14 no.4
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    • pp.31-39
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    • 1990
  • A systematic methodology for efficient implementation of processor arrays from regular iterative algorithms is proposed. One of the modern parallel processing array architectures is the Systolic arrays and we use it for processor arrays on this paper. On designing the systolic arrays, there are plenty of mapping functions which satisfy necessary conditions for its implementation to the time-space domain. In this paper, we sue a few conditions to reduce the total number of computable mapping functions efficiently. As a results of applying this methodology, efficient designs of systolic arrays could be done with considerable saving on design time and efforts.

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Mapping Heterogenous Ontologies for the HLP Applications - Sejong Semantic Classes and KorLexNoun 1.5 - (인간언어공학에의 활용을 위한 이종 개념체계 간 사상 - 세종의미부류와 KorLexNoun 1.5 -)

  • Bae, Sun-Mee;Im, Kyoung-Up;Yoon, Ae-Sun
    • Korean Journal of Cognitive Science
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    • v.21 no.1
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    • pp.95-126
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    • 2010
  • This study proposes a bottom-up and inductive manual mapping methodology for integrating two heterogenous fine-grained ontologies which were built by a top-down and deductive methodology, namely the Sejong semantic classes (SJSC) and the upper nodes in KorLexNoun 1.5 (KLN), for HLP applications. It also discusses various problematics in the mapping processes of two language resources caused by their heterogeneity and proposes the solutions. The mapping methodology of heterogeneous fine-grained ontologies uses terminal nodes of SJSC and Least Upper Bounds (LUB) of KLN as basic mapping units. Mapping procedures are as follows: first, the mapping candidate groups are decided by the lexfollocorrelation between the synsets of KLN and the noun senses of Sejong Noun Dfotionaeci(SJND) which are classified according to SJSC. Secondly, the meanings of the candidate groups are precisely disambiguated by linguistic information provided by the two ontologies, i.e. the hierarchicllostructures, the definitions, and the exae les. Thirdly, the level of LUB is determined by applying the appropriate predicates and definitions of SJSC to the upper-lower and sister nodes of the candidate LUB. Fourthly, the mapping possibility ic inthe terminal node of SJSC is judged by che aring hierarchicllorelations of the two ontologies. Finally, the ituorrect synsets of KLN and terminologiollocandidate groups are excluded in the mapping. This study positively uses various language information described in each ontology for establishing the mapping criteria, and it is indeed the advantage of the fine-grained manual mapping. The result using the proposed methodology shows that 6,487 LUBs are mapped with 474 terminal and non-terminal nodes of SJSC, excluding the multiple mapped nodes, and that 88,255 nodes of KLN are mapped including all lower-level nodes of the mapped LUBs. The total mapping coverage is 97.91% of KLN synsets. This result can be applied in many elaborate syntactic and semantic analyses for Korean language processing.

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Integration of ERS-2 SAR and IRS-1 D LISS-III Image Data for Improved Coastal Wetland Mapping of southern India

  • Shanmugam, P.;Ahn, Yu-Hwan;Sanjeevi, S.;Manjunath, A.S.
    • Korean Journal of Remote Sensing
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    • v.19 no.5
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    • pp.351-361
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    • 2003
  • As the launches of a series of remote sensing satellites, there are various multiresolution and multi-spectral images available nowadays. This diversity in remotely sensed image data has created a need to be able to integrate data from different sources. The C-band imaging radar of ERS-2 due to its high sensitivity to coastal wetlands holds tremendous potential in mapping and monitoring coastal wetland features. This paper investigates the advantages of using ERS-2 SAR data combined with IRS-ID LISS-3 data for mapping complex coastal wetland features of Tamil Nadu, southern India. We present a methodology in this paper that highlights the mapping potential of different combinations of filtering and integration techniques. The methodology adopted here consists of three major steps as following: (i) speckle noise reduction by comparative performance of different filtering algorithms, (ii) geometric rectification and coregistration, and (iii) application of different integration techniques. The results obtained from the analysis of optical and microwave image data have proved their potential use in improving interpretability of different coastal wetland features of southern India. Based visual and statistical analyzes, this study suggests that brovey transform will perform well in terms of preserving spatial and spectral content of the original image data. It was also realized that speckle filtering is very important before fusing optical and microwave data for mapping coastal mangrove wetland ecosystem.