• Title/Summary/Keyword: Subjective Estimation

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A Case Study of Back-analysis Technique in Tunnelling Using Extended Bayesian Method and Relative Convergence Measurement (확장 Baysian 방법과 상대변위를 이용한 터널 역해석 기법의 적용사례연구)

  • Lee In-Mo;Choi Min-Kwang;Cho Kook-Hwan;Lee Geun-Ha;Choi Chung-Sik
    • Journal of the Korean Geotechnical Society
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    • v.21 no.3
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    • pp.109-118
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    • 2005
  • It is a very difficult task to estimate engineering properties of the ground when designing underground structures, especially in tunnelling. Therefore, a feed-back system to combine the data measured in construction field with priorly estimated information at the design stage is necessary. In this paper, 3-dimensional back-analysis in tunnelling, to which only relative convergence is applied as input values, is carried out to estimate the optimum geotechnical parameters. For this purpose, the Extended Bayesian Method (EBM), which appropriately combines the objective information with the subjective one, is applied to optimize engineering parameters and 3-dimensional numerical analysis is carried out to predict a trend of relative convergence occurrence. The data measured from two tunnelling sites are used to verify the applicability of the proposed back-analysis technique. from the results of analysis, the proposed back-analysis technique is verified.

New De-interlacing Algorithm Combining Edge Dependent Interpolation and Global Motion Compensation Based on Horizontal and Vertical Patterns (수평, 수직 패턴에 기반 한 경계 방향 보간과 전역 움직임 보상을 고려한 새로운 순차주사화 알고리즘)

  • 박민규;이태윤;강문기
    • Journal of Broadcast Engineering
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    • v.9 no.1
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    • pp.43-53
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    • 2004
  • In this paper, we propose a robust deinterlacing algorithm which combines edge dependent interpolation (EDI) and global motion compensation (GMC). Generally, EDI algorithm shows a visually better performance than any other deinterlacing algorithm using one field. However, due to the restriction of information in one field, a high duality progressive image from Interlaced sources cannot be acquired by intrafield methods. On the contrary, since algorithms based on motion compensation make use of not only spatial information but also temporal information, they yield better results than those of using one field. However, performance of algorithms based on motion compensation depends on the performance of motion estimation. Hence, the proposed algorithm makes use of mixing process of EDI and GMC. In order to obtain the best result, an adaptive thresholding algorithm for detecting the failure of GMC is proposed. Experimental results indicate that the proposed algorithm outperforms the conventional approaches with respect to both objective and subjective criteria.

No-Reference Image Quality Assessment Using Complex Characteristics of Shearlet Transform (쉬어렛 변환의 복소수 특성을 이용하는 무참조 영상 화질 평가)

  • Mahmoudpour, Saeed;Kim, Manbae
    • Journal of Broadcast Engineering
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    • v.21 no.3
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    • pp.380-390
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    • 2016
  • The field of Image Quality Measure (IQM) is growing rapidly in recent years. In particular, there was a significant progress in No-Reference (NR) IQM methods. In this paper, a general-purpose NR IQM algorithm is proposed based on the statistical characteristics of natural images in shearlet domain. The method utilizes a set of distortion-sensitive features extracted from statistical properties of shearlet coefficients. A complex version of the shearlet transform is employed to take advantage of phase and amplitude features in quality estimation. Furthermore, since shearlet transform can analyze the images at multiple scales, the effect of distortion on across-scale dependencies of shearlet coefficients is explored for feature extraction. For quality prediction, the features are used to train image classification and quality prediction models using a Support Vector Machine (SVM). The experimental results show that the proposed NR IQM is highly correlated with human subjective assessment and outperforms several Full-Reference (FR) and state-of-art NR IQMs.

SD Methodological Evaluation of the Visual Cognition to the Urban Landscape (SD 기법을 활용한 주거단지의 시지각적 평가)

  • Hwang J.W.;Chai B.S.;Kwon T.K.;Hong C.U.
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2005.06a
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    • pp.1918-1920
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    • 2005
  • The color and structure of urban constructions is a factor of urban landscape and shows their characteristics. Hence the modern buildings with their materials and external appearance makes up the urban image. But still yet, it was not easy to evaluate the value of visual landscape of buildings with objective measuring method. Most of all, it depends on the subjective estimation of a few talented or high educated experts with a sense of beauty. In relation to this kind of problems, it was tried here in this study to analyse the human response of brain wave pattern (EEG) with use of SD method, while the tested persons watched the urban landscape constructed in a visual reality. The tested persons were 10 adult males and females with no color blindness and intact cognitive function. Light source with color filter was used for color environment in chamber room. The signal of EEG is analysed digitally and grouped into the $\alpha$ and $\beta$ waves. The result showed that relative power of $\alpha$ wave ratio increased in natural landscape scenary clearly. From these results it was possible to evaluate the human response, which was affected by urban color and structure stimulation and it might be useful as an indicator of visual cognition amenity toward the design of urban construction environment.

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Stratification Method Using κ-Spatial Medians Clustering (κ-공간중위 군집방법을 활용한 층화방법)

  • Son, Soon-Chul;Jhun, Myoung-Shic
    • The Korean Journal of Applied Statistics
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    • v.22 no.4
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    • pp.677-686
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    • 2009
  • Stratification of population is widely used to improve the efficiency of the estimation in a sample survey. However, it causes several problems when there are some variables containing outliers. To overcome these problems, Park and Yun (2008) proposed a rather subjective method, which finds outliers before $\kappa$-means clustering for stratification. In this study, we propose the $\kappa$-spatial medians clustering method which is more robust than $\kappa$-means clustering method and also does not need the process of finding outliers in advance. We investigate the characteristics of the proposed method through a case study used in Park and Yun (2008) and confirm the efficiency of the proposed method.

Research about the Animation Manual Application of Cellular Phone that use Multimedia (멀티미디어를 이용한 휴대폰의 애니메이션 매뉴얼 적용에 대한 연구)

  • 오재성;신수길
    • Archives of design research
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    • v.16 no.4
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    • pp.121-128
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    • 2003
  • This is the research to find out which one is the best for using manual among the 3 kinds of methods such as 'Text manual' and 'Animation I' and 'Animation II' which is made by Virtual Realities. Three kinds of methods have been experimented respectively. The manual for 'Animation I' adopt the motion video with basis sound and the additional comment and sound is added on the 'Animation II'. Every 3 manual has been studied and estimated by T-test and additional subjective estimation respectively, and the conclusions are as follows. The 1st answer is that 'Animation manual' is more easier than 'text manual', and the 2nd answer is that 'Animation II' is easier than 'Animation I'. Through post-interview and test, It is known that the animation manuals, which has been showing the multimedia, is more attractive than text manual.

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Pain Nursing Intervention Supporting Method using Collaborative Filtering in Health Industry (보건산업에서 협력적 필터링을 이용한 통증 간호중재 지원 방법)

  • Yoo, Hyun;Jo, Sun-Moon;Chung, Kyung-Yong
    • The Journal of the Korea Contents Association
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    • v.11 no.7
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    • pp.1-8
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    • 2011
  • In modern society, the amount of information has been significantly increased according to the development of Internet and IT convergence technology and that leads to develop information obtaining and searching technologies from lots of data. Although the system integration for medicare has been largely established and that accumulates large amounts of information, there is a lack of providing and supporting information for nursing activities using such established database. In particular, the judgement for the intervention of pains depends on the experience of individual nurses and that leads to make subjective decisions in usual. In this paper, a pain nursing supporting method that uses the existing medical data and performs collaborative filtering is proposed. The proposed collaborative filtering is a method that extracts some items, which represent a high relativeness level, based on similar preferences. A preference estimation method using a user based collaborative filtering method calculates user similarities through Pearson correlation coefficients in which a neighbor selection method is used based on the user preference.

Fuzzy Clustering Method for the Identification of Joint Sets (절리군 분석을 위한 퍼지 클러스터링 기법)

  • 정용복;전석원
    • Tunnel and Underground Space
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    • v.13 no.4
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    • pp.294-303
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    • 2003
  • The structural behaviour of rock mass structure, such as tunnel or slope is critically dependent on the various characteristics of discontinuities. Therefore, it is important to survey and analyze discontinuities correctly for the design and construction of rock mass structure. One inevitable Procedure of discontinuity survey and analysis is joint set identification from a lot of raw directional joint data. The identification procedure is generally done by a graphical method. This type of analysis has some shortcomings such as subjective identification results, inability to use extra information on discontinuity, and so on. In this study, a computer program for joint set identification based on the fuzzy clustering algorithm was implemented and tested using two kinds of joint data. It was confirmed that fuzzy clustering method is effective and valid for joint set identification and estimation of mean direction and degree of clustering of huge joint data through the applications.

Space-Time Quantization and Motion-Aligned Reconstruction for Block-Based Compressive Video Sensing

  • Li, Ran;Liu, Hongbing;He, Wei;Ma, Xingpo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.1
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    • pp.321-340
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    • 2016
  • The Compressive Video Sensing (CVS) is a useful technology for wireless systems requiring simple encoders but handling more complex decoders, and its rate-distortion performance is highly affected by the quantization of measurements and reconstruction of video frame, which motivates us to presents the Space-Time Quantization (ST-Q) and Motion-Aligned Reconstruction (MA-R) in this paper to both improve the performance of CVS system. The ST-Q removes the space-time redundancy in the measurement vector to reduce the amount of bits required to encode the video frame, and it also guarantees a low quantization error due to the fact that the high frequency of small values close to zero in the predictive residuals limits the intensity of quantizing noise. The MA-R constructs the Multi-Hypothesis (MH) matrix by selecting the temporal neighbors along the motion trajectory of current to-be-reconstructed block to improve the accuracy of prediction, and besides it reduces the computational complexity of motion estimation by the extraction of static area and 3-D Recursive Search (3DRS). Extensive experiments validate that the significant improvements is achieved by ST-Q in the rate-distortion as compared with the existing quantization methods, and the MA-R improves both the objective and the subjective quality of the reconstructed video frame. Combined with ST-Q and MA-R, the CVS system obtains a significant rate-distortion performance gain when compared with the existing CS-based video codecs.

Development of Categorization System for Efficient Calculation of Damage Cost according to Strong Wind (강풍 피해에 따른 피해비용의 효율적인 산정을 위한 분류체계 개발)

  • Song, Chang Young;Lee, Jong Hoon
    • Journal of the Korean Society of Safety
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    • v.31 no.2
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    • pp.127-132
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    • 2016
  • In this study, the plan to construct a disaster information categorization system that can be objectively and efficiently performed was suggested in order to perform disaster management task systematically. Recently, the damage of natural disasters is gradually growing larger and faster, increasing the economic loss. Especially, as for the domestic storm damage, the damage from strong wind was found to be greater than the damage from torrential rain. Also, strong wind was found to be inflicting a great damage on human life, property and agricultural crops, so the necessity to study damage restoration from strong wind is increasing. Nevertheless, the damage items categorized in the domestic disaster year book are often comprehensive or unclear in criteria, and thus fail to reflect items or matters due to actual disaster damage. It is difficult to aggregate damage accurately such that it does not correspond to the national compensation scope or the damage amount is calculated according to subjective judgment of the investigator in charge. As such, if the disaster information management is inadequate by not applying accurate categorization criteria from damage amount calculation, there can be an issue with fairness when paying the damage support aid. Therefore, this study suggested a categorization plan for objective and efficient execution of disaster information management task in order to resolve such issues. It is expected that quick and efficient execution would be possible in disaster information management and task procedure domestically by constructing systematic categorization system related to disaster information.