• Title/Summary/Keyword: Finding error

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Development of Stiffness Estimation Algorithm for Nonlinear Static Analysis of Bilinear Material Model (전단벽 모형화 방법에 따른 구조해석 신뢰성에 대한 고찰)

  • Jung, Sung-Jin;Park, Se-Hee
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.3
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    • pp.718-723
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    • 2017
  • When structural analysis modelling methods of practical fields are investigated, a slab is generally modeled by a finite element mesh using plate elements and a shear wall is modeled using a shell element or wall element for 3-D structural analysis. The point worthy of notice in this practice is that a shear wall is modelled using only one wall or shell element divided by floors and column lines to produce structural models. The modeling method like this can cause analysis errors according to the type of computer programs in use, and these errors reduce the reliability of the analysis results. Therefore, to secure the reliability of structural analysis, studies of the causes of errors and finding reasonable modeling methods are necessary. In this study, the causes of analysis errors according to the modelling methods of a shear wall, which are used in practical fields, were investigated and some considering matters for modelling a shear wall are presented to reduce the analysis errors on these analysis results.

Signal Processing Algorithm to Reduce RWR Electro-Magnetic Interference with Tail Rotor Blade of Helicopter

  • Im, Hyo-Bin;Go, Eun-Kyoung;Jeong, Un-Seob;Lyu, Si-Chan
    • International Journal of Aeronautical and Space Sciences
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    • v.10 no.2
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    • pp.117-124
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    • 2009
  • In the environment where various and complicated threat signals exist, RWR (Radar Warning Receiver), which can warn pilot of the existence of threats, has long been a necessary electronic warfare (EW) system to improve survivability of aircraft. The angle of arrival (AOA) information, the most reliable sorting parameter in the RWR, is measured by means of four-quadrant amplitude comparison direction finding (DF) technique. Each of four antennas (usually spiral antenna) of DF unit covers one of four quadrant zones, with 90 degrees apart with nearby antenna. According to the location of antenna installed in helicopter, RWR is subject to signal loss and interference by helicopter body and structures including tail bumper, rotor blade, and so on, causing a difficulty of detecting hostile emitters. In this paper, the performance degradation caused by signal interference by tail rotor blades has been estimated by measuring amplitude video signals into which RWR converts RF signals in case a part of antenna is screened by real tail rotor blade in anechoic chamber. The results show that corruption of pulse amplitude (PA) is main cause of DF error. We have proposed two algorithms for resolving the interference by tail rotor blades as below: First, expand the AOA group range for pulse grouping at the first signal analysis phase. Second, merge each of pulse trains with the other, that signal parameter except PRI and AOA is similar, after the first signal analysis phase. The presented method makes it possible to use RWR by reducing interference caused by blade screening in case antenna is screened by tail rotor blades.

Analysis of Technical Problem for Soil Compaction by Gyratory Compactor (선회다짐기를 이용한 흙의 다짐시 기술적 문제 분석)

  • Lee, Kwan-Ho;Jang, Tae-Young
    • Journal of the Korean Society of Hazard Mitigation
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    • v.10 no.1
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    • pp.43-48
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    • 2010
  • Proctor test A or D method of compaction is the most common laboratory test for investigation of subgrade soil characteristics, however, compression type using roller is used in the field. The differences between laboratory and field compaction have considerable error as application to subgrade soil properties of laboratory test. The investigation of compacted soil is carried into effect to solve the problem. The gyratory compactor which is made to reproduce the field density of asphalt mixture, coming from traffic loads, has an advance to compact it similar to arrangement of field aggregate particles. This gyratory compactor has several problems of investigation of compacted soil, because it has designed to make initial asphalt specimens. The main objectives of this research are grasping problems when compacted soil test using the gyratory compactor and showing solutions. It has made a comparative study of difference of the percentage of water content and weight, which are before and after compaction, about the pressure of compaction, frequency of compaction and speed of compaction. And it also has investigated finding maximum percentage of water content which not occur change of percentage of water content after compaction and searching how has an effect on drawing compaction curve.

Korean Word Segmentation and Compound-noun Decomposition Using Markov Chain and Syllable N-gram (마코프 체인 밀 음절 N-그램을 이용한 한국어 띄어쓰기 및 복합명사 분리)

  • 권오욱
    • The Journal of the Acoustical Society of Korea
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    • v.21 no.3
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    • pp.274-284
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    • 2002
  • Word segmentation errors occurring in text preprocessing often insert incorrect words into recognition vocabulary and cause poor language models for Korean large vocabulary continuous speech recognition. We propose an automatic word segmentation algorithm using Markov chains and syllable-based n-gram language models in order to correct word segmentation error in teat corpora. We assume that a sentence is generated from a Markov chain. Spaces and non-space characters are generated on self-transitions and other transitions of the Markov chain, respectively Then word segmentation of the sentence is obtained by finding the maximum likelihood path using syllable n-gram scores. In experimental results, the algorithm showed 91.58% word accuracy and 96.69% syllable accuracy for word segmentation of 254 sentence newspaper columns without any spaces. The algorithm improved the word accuracy from 91.00% to 96.27% for word segmentation correction at line breaks and yielded the decomposition accuracy of 96.22% for compound-noun decomposition.

Goal-Directed Reinforcement Learning System (목표지향적 강화학습 시스템)

  • Lee, Chang-Hoon
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.10 no.5
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    • pp.265-270
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    • 2010
  • Reinforcement learning performs learning through interacting with trial-and-error in dynamic environment. Therefore, in dynamic environment, reinforcement learning method like TD-learning and TD(${\lambda}$)-learning are faster in learning than the conventional stochastic learning method. However, because many of the proposed reinforcement learning algorithms are given the reinforcement value only when the learning agent has reached its goal state, most of the reinforcement algorithms converge to the optimal solution too slowly. In this paper, we present GDRLS algorithm for finding the shortest path faster in a maze environment. GDRLS is select the candidate states that can guide the shortest path in maze environment, and learn only the candidate states to find the shortest path. Through experiments, we can see that GDRLS can search the shortest path faster than TD-learning and TD(${\lambda}$)-learning in maze environment.

Sharing Error Allowances for the Analysis of Approximation Schemes (근사접근법 분석을 위한 오차허용치의 분배방법)

  • Kim, Joon-Mo;Goo, Eun-Hee
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.46 no.5
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    • pp.1-7
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    • 2009
  • When constructing various mobile networks including sensor networks, the problem of finding the layout or graph to interconnect the terminals or nodes of the network may come up. Providing a common scheme that can be applied to the kind of problems, and formulating the bounds of the run time and the result of the algorithm from the scheme, one may evaluate precisely the plan of constructing analogous network systems. This paper, dealing with EMST(Euclidean Minimum Spanning Tree) that represents such problems, provides the scheme for constructing EMST by parallel processing over distributed environments, and the ground for determining the maximum difference of the layout or the graph produced from the scheme: the difference from EMST. In addition, it provides the upper bound of the run time of the algorithm from the scheme.

An Improvement of the P2P Streaming Network Topology Algorithm Using Link Information (연결 정보를 이용한 P2P 스트리밍 네트워크 구조의 개선)

  • Lee, Sang-Hoon;Han, Chi-Geun
    • Journal of the Korea Society of Computer and Information
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    • v.17 no.5
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    • pp.49-57
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    • 2012
  • In P2P streaming management, peer's churning and finding efficient topology architecture optimization algorithm that reduces streaming delay is important. This paper studies a topology optimization algorithm based on the P2P streaming using peer's link information. The proposed algorithm is based on the estimation of peer's upload bandwidth using peer's link information on mesh-network. The existing algorithm that uses the information of connected links is efficient to reduce message overload in the point of resource management. But it has a risk of making unreliable topology not considering upload bandwidth. And when some network error occurs in a server-closer-peer, it may make the topology worse. In this paper we propose an algorithm that makes up for the weak point of the existing algorithm. We compare the existing algorithm with the proposed algorithm using test data and analyze each simulation result.

Inversion of Resistivity Tomography Data Using EACB Approach (EACB법에 의한 전기비저항 토모그래피 자료의 역산)

  • Cho In-Ky;Kim Ki-Ju
    • Geophysics and Geophysical Exploration
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    • v.8 no.2
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    • pp.129-136
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    • 2005
  • The damped least-squares inversion has become a most popular method in finding the solution in geophysical problems. Generally, the least-squares inversion is to minimize the object function which consists of data misfits and model constraints. Although both the data misfit and the model constraint take an important part in the least-squares inversion, most of the studies are concentrated on what kind of model constraint is imposed and how to select an optimum regularization parameter. Despite that each datum is recommended to be weighted according to its uncertainty or error in the data acquisition, the uncertainty is usually not available. Thus, the data weighting matrix is inevitably regarded as the identity matrix in the inversion. We present a new inversion scheme, in which the data weighting matrix is automatically obtained from the analysis of the data resolution matrix and its spread function. This approach, named 'extended active constraint balancing (EACB)', assigns a great weighting on the datum having a high resolution and vice versa. We demonstrate that by applying EACB to a two-dimensional resistivity tomography problem, the EACB approach helps to enhance both the resolution and the stability of the inversion process.

Design and Implementation of RSSI-based Intelligent Location Estimation System (RSSI기반 지능형 위치 추정 시스템 설계 및 구현)

  • Lim, Chang Gyoon;Kang, O Seong Andrew;Lee, Chang Young;Kim, Kang Chul
    • Journal of Internet Computing and Services
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    • v.14 no.6
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    • pp.9-18
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    • 2013
  • In this paper, we design and implement an intelligent system for finding objects with RFID(Radio Frequency IDentification) tag in which an mobile robot can do. The system we developed is a learning system of artificial neural network that uses RSSI(Received Signal Strength Indicator) value as input and absolute coordination value as target. Although a passive RFID is used for location estimation, we consider an active RFID for expansion of recognition distance. We design the proposed system and construct the environment for indoor location estimation. The designed system is implemented with software and the result related learning is shown at test bed. We show various experiment results with similar environment of real one from earning data generation to real time location estimation. The accuracy of location estimation is verified by simulating the proposed method with allowable error. We prepare local test bed for indoor experiments and build a mobile robot that can find the objects user want.

Feature Extraction by Optimizing the Cepstral Resolution of Frequency Sub-bands (주파수 부대역의 켑스트럼 해상도 최적화에 의한 특징추출)

  • 지상문;조훈영;오영환
    • The Journal of the Acoustical Society of Korea
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    • v.22 no.1
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    • pp.35-41
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    • 2003
  • Feature vectors for conventional speech recognition are usually extracted in full frequency band. Therefore, each sub-band contributes equally to final speech recognition results. In this paper, feature Teeters are extracted indepedently in each sub-band. The cepstral resolution of each sub-band feature is controlled for the optimal speech recognition. For this purpose, different dimension of each sub-band ceptral vectors are extracted based on the multi-band approach, which extracts feature vector independently for each sub-band. Speech recognition rates and clustering quality are suggested as the criteria for finding the optimal combination of sub-band Teeter dimension. In the connected digit recognition experiments using TIDIGITS database, the proposed method gave string accuracy of 99.125%, 99.775% percent correct, and 99.705% percent accuracy, which is 38%, 32% and 37% error rate reduction relative to baseline full-band feature vector, respectively.