• Earthquakes and Structures
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• 제18권4호
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• pp.437-449
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• 2020

It is quite apparent that engineering concerns related to the influence of masonry infills on seismic behavior of reinforced concrete (RC) structures is likely to remain relevant in the long term, as infill walls maintain their functionalities in construction practice. Within this framework, the present paper mainly deals with the issue in terms of modal expansion of effective earthquake forces and the resultant modal responses. An adequate determination of spatial distribution of effective earthquake forces over the height of the building is highly essential for both seismic analysis and design. The possible influence of infill walls is investigated by means of modal analyses of two-, three-, and four-bay RC frames with a number of stories ranging from 3 to 8. Both uniformly and non-uniformly infilled frames are considered in numerical analyses, where infill walls are simulated by adopting the model of equivalent compression strut. Consequently, spatial distribution of effective earthquake forces, modal static base shear force response of frames, modal responses of story shears from external excitation vector and lateral floor displacements are obtained. It is found that, infill walls and their arrangement over the height of the frame structure affect the spatial distribution of modal inertia forces, as well as the considered response quantities. Moreover, the amount of influence varies in stories, but is not very dependent to bay number of frames.

• 한국공간구조학회논문집
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• 제16권2호
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• pp.89-96
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• 2016

Cable structures are lightweight structures of flexible type, cable members have only axial stiffness related to tension, they can carry neither bending nor compression. This study is the analysis of cable truss systems are composed of upper and low cables by connecting bracing cables, the structural principle is based on a tensegrity system by using bracing tension members, discontinuous compression members and continuous tension members. A hanging roof of cable truss system is too flexible against vertical loads, most cable members are stabilized by connecting the prestressed upper and lower cable by bracing cables. A cable truss roof system is formed by adding a set of cables with reverse curvature to the suspension cables. With the sets of cables having opposite curvature to each other, cable truss is able to carry vertical load in both upward and downward direction with equal effectiveness, and then a cable truss acts as load bearing elements by the assemble of ridge cables, valley cables and bracing cables. This paper will be shown the geometric non-linear analysis result of cable truss systems with various sag ratio for deflections and tensile forces, the analytical results are compared with the results of other researchers.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.753-754
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• 2008

LiDAR data are acknowledged as very useful method to represent 3-D geographical information. In this paper aquad tree has been utilized to represent the 3-D spatial information. Compression algorithm is implemented based on a given threshold. The efficiency of compress is very high with large threshold values.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권9호
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• pp.3823-3840
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• 2020

Recently, auto-encoder has emerged as the most popular method in convolutional neural network (CNN) based image compression and has achieved impressive performance. In the traditional auto-encoder based image compression model, the encoder simply sends the features of last layer to the decoder, which cannot allocate bits over different spatial regions in an efficient way. Besides, these methods do not fully exploit the contextual information under different receptive fields for better reconstruction performance. In this paper, to solve these issues, a novel auto-encoder model is designed for image compression, which can effectively transmit the hierarchical features of the encoder to the decoder. Specifically, we first propose an adaptive bit-allocation strategy, which can adaptively select an importance channel. Then, we conduct the multiply operation on the generated importance mask and the features of the last layer in our proposed encoder to achieve efficient bit allocation. Moreover, we present an additional novel perceptual loss function for more accurate image details. Extensive experiments demonstrated that the proposed model can achieve significant superiority compared with JPEG and JPEG2000 both in both subjective and objective quality. Besides, our model shows better performance than the state-of-the-art convolutional neural network (CNN)-based image compression methods in terms of PSNR.

• 정보처리학회논문지B
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• 제9B권3호
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• pp.351-358
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• 2002

DCT(Discrete Cosine Transform) 기반 동영상 압축 기법은 블록화 현상과 해상도 변화 시 픽셀의 손상이 생기는 단점이 있다. DWT(Discrete Wavelet Transform)을 기반한 기법은 이러한 문제점을 극복할 수 있다. Wavelet을 기반한 동영상 부호화 기법 중 하나인 SAMCoW(Scalable Adaptive Motion Compensation Wavelet)에서 화면내 부호화와 움직임 보상된 오차 영상은 EZW(Embedded Zerotree Wavelet) 부호화 방식으로 부호화한다. 그러나 움직임 보상된 오차 영상의 wavelet 변환 계수의 특성은 정지 영상의 wavelet 변환 계수의 특성과는 다르다. 신호의 에너지는 대부분의 정지 영상의 경우와는 달리 저주파 대역에 집중되지 않고 오히려 모든 주파수 대역에 고르게 분포한다. 본 논문에서는 이러한 특성을 이용한 새로운 동영상 부호화 방식을 제안하였다. EZW 부호화 대신 고주파 성분이 많이 포함된 영상의 부호화에 효율적이며 계수사이의 대역별 상관관계에 의존하지 않는 공간 부호화를 화면내 부호화와 화면간 부호화에 적용하였다. 공간 부호화는 EZW와는 달리 wavelet 분해를 통해 얻어진 각 대역을 대역간의 상관 관계를 이용하지 않으면서 각 대역내의 중요 계수의 존재 여부와 위치를 점진적으로 부호화하는 기법이다. Wavelet 기반 동영상 부호화에 EZW 부호화 대신 공간 부호화를 적용하였을 때 우수한 성능을 나타내었다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 A
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• pp.175-178
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• 2003

This paper describes a active audition system for robot-human interface in real environment. We propose a strategy for a robust sound localization and for -talking speech recognition(60-300cm) based on 2-dimensional microphone array. We consider spatial features, the relation of position and interaural time differences, and realize speaker tracking system using fuzzy inference profess based on inference rules generated by its spatial features.

• 한국통신학회논문지
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• 제19권11호
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• pp.2264-2275
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• 1994

본 논문에서는 블록 분류와 코딩과 함께 신경회로망을 이용한 영상압축을 보였다. 오차 역전파 알고리즘으로 학습되는 다층구조 신경회로망은 정규화된 영상데이타를 감소된 공간 중복성을 가지는 은닉층의 값으로 변환하는데 사용된다. 기본적으로 영상압축은 입력층과 출력층의 뉴런보다 적은 수의 은닉층 뉴런에 의해 얻어진다. 여기에 시각체계의 민감도에 따른 영상블럭 복잡성에 따라 적응적으로 압축되므로 블록을 분류한다. 또한 은닉뉴런의 양자화된 값은 효과적인 전송을 위해 entropy coding을 이용한 경우 화질의 큰 저하없이 약 25:1의 압축률을 얻었다.

• 한국통신학회논문지
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• 제29권3C호
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• pp.387-397
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• 2004

영상의 주파수 정보와 공간 정보를 동시에 제공하는 웨이브렛 변환(Wavelet transform)은 영상압축에 매우 효과적임이 밝혀졌고, 최근 들어 웨이브렛 변환 방법으로 다해상도 분해된 영상에 여러 가지 부호화 알고리즘을 적용하는 것에 대해 많은 연구가 진행되고 있다. 본 논문에서는, 웨이브렛 변환으로 다해상도 분해된 적외선 영상에 픽셀간의 상관도와 '0' 정보를 모아 효과적으로 압축할 수 있는 양자화 기법인 쿼드트리 기반 블록 양자화(Quadtree based block quantization)를 적용하여 영상을 압축하는 방법을 제안한파. 웨이브렛 변환된 계수는 스케일간 상잔도가 놀고, 집중도가 높기 때문에 쿼드트리를 적용할 경우 효과적으로 데이터량을 줄일 수 있다. 실험영상으로 256${\times}$256 크기의 8〔bit〕 적외선영상을 이용하고, DCT 압축기법과 제안한 기법을 비교 평가한다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.459-462
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• 2003

Selectivity estimation of queries not only provides useful information to the query processing optimization but also may give users with a preview of processing results. In this paper, we investigate the problem of selectivity estimation in the context of a spatial dataset. Although several techniques have been proposed in the literature to estimate spatial query result sizes, most of those techniques still have some drawback in the case that a large amount of memory is required to retain accurate selectivity. To eliminate the drawback of estimation techniques in previous works, we propose a new method called MW Histogram. Our method is based on two techniques: (a) MinSkew partitioning algorithm that processes skewed spatial datasets efficiently (b) Wavelet transformation which compression effect is proven. We evaluate our method via real datasets. With the experimental result, we prove that the MW Histogram has the ability of providing estimates with low relative error and retaining the similar estimates even if memory space is small.

• 한국산학기술학회논문지
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• 제5권1호
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• pp.38-43
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• 2004

We designed and implemented a medical image query system, including a relational database and DBMS (database management system), which can visualize image data and can achieve spatial, attribute, and mixed queries. Image data used in querying can be visualized in slice, MPR(multi-planner reformat), volume rendering, and overlapping on the query system. To reduce spatial cost and processing time in the system. brain images are spatially clustered, by an adaptive Hilbert curve filling, encoded, and stored to its database without loss for spatial query. Because the query is often applied to small image regions of interest(ROI's), the technique provides higher compression rate and less processing time in the cases.