• 국제강구조저널
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• 제18권4호
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• pp.1125-1138
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• 2018

During earthquakes, braces behave in complex manners because of the asymmetric response nature of their responses in tension and compression. Hollow structural sections (HSS) have been popularly used for braces due to their sectional efficiency in compression. The purpose of this study is to accurately simulate the cyclic behavior of rectangular HSS braces using a computationally efficient numerical model. A conceptually efficient and simple physical theory model is used as a basis model. To improve the accuracy of the model, cyclic beam growth and buckling load, as well as the incidences of local buckling and brace fracture are estimated using empirical equations obtained from regression analyses using test data on rectangular HSS braces. The accuracy of the proposed model is verified by comparing actual and simulated cyclic curves of brace specimens with various slenderness and width-to-thickness ratios.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.116-119
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• 2005

As to the synthetical estimation of land covering parameters or the compounded land covering classification for multi-resolution satellite data, former researches mainly adopted linear or nonlinear regression models to describe the regression relationship of land covering parameters caused by the degradation of spatial resolution, in order to improve the retrieval accuracy of global land covering parameters based on 1;he lower resolution satellite data. However, these methods can't authentically represent the complementary characteristics of spatial resolutions among different satellite data at arithmetic level. To resolve the problem above, a new compounded land covering classification method at arithmetic level for multi-resolution satellite data is proposed in this .paper. Firstly, on the basis of unsupervised clustering analysis of the higher resolution satellite data, the likelihood distribution scatterplot of each cover type is obtained according to multiple-to-single spatial correspondence between the higher and lower resolution satellite data in some local test regions, then Parzen window approach is adopted to derive the real likelihood functions from the scatterplots, and finally the likelihood functions are extended from the local test regions to the full covering area of the lower resolution satellite data and the global covering area of the lower resolution satellite is classified under the maximum likelihood rule. Some experimental results indicate that this proposed compounded method can improve the classification accuracy of large-scale lower resolution satellite data with the support of some local-area higher resolution satellite data.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 1994년도 가을 학술발표회 논문집
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• pp.267-272
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• 1994

This work presents a method of optimum design for reinforced concrete building frames with rectangular cross sections. The optimization techniques used is based on the principle of divided parameters. The design variable parameters are divided into two groups, external and internal, and the optimization is also divided into external and internal procedure. This principle overcomes difficulties arising from the presence of two materials in one element, the property peculiar to reinforced concrete. Several search algorithms are tested to verify their accuracy for the external optimization. Among them pattern search algorithms has been found consistent. This work proposes a new method, modified pattern search, and a number of sample problems prove its accuracy and usefulness. Exhaustive search for all local minima in the design spaces for two sample problems has been carried out to understand the nature of the problem. The number of local minima identified is quite more than expected and it has become understood that the researcher's task in this field is to find a better local minimum if not global. The designs produced by the method preposed have been found better than those from other method, and they are in full accord with ACI Building Code Requirments(ACI 318-89).

• ETRI Journal
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• 제32권5호
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• pp.784-794
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• 2010

Automatic facial expression recognition has many potential applications in different areas of human computer interaction. However, they are not yet fully realized due to the lack of an effective facial feature descriptor. In this paper, we present a new appearance-based feature descriptor, the local directional pattern (LDP), to represent facial geometry and analyze its performance in expression recognition. An LDP feature is obtained by computing the edge response values in 8 directions at each pixel and encoding them into an 8 bit binary number using the relative strength of these edge responses. The LDP descriptor, a distribution of LDP codes within an image or image patch, is used to describe each expression image. The effectiveness of dimensionality reduction techniques, such as principal component analysis and AdaBoost, is also analyzed in terms of computational cost saving and classification accuracy. Two well-known machine learning methods, template matching and support vector machine, are used for classification using the Cohn-Kanade and Japanese female facial expression databases. Better classification accuracy shows the superiority of LDP descriptor against other appearance-based feature descriptors.

• 한국소음진동공학회논문집
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• 제18권6호
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• pp.674-680
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• 2008

A new meshless method for obtaining natural frequencies of arbitrarily shaped plates with the free boundary condition is introduced in the paper. In order to improve the characteristics of convergence and accuracy of the method, a special local polar coordinates system is devised and located for each of nodes distributed along the boundary of the plate of interest. In addition, a new way of decreasing the size of the system matrix that gives natural frequencies of the plate is employed to reduce the amount of numerical calculations, which is needed for computing the determinant of the system matrix. Finally the excellence of the characteristics of convergence and accuracy of the method is shown in several case studies, which indicate that natural frequencies by the proposed method are very accurate and converged swiftly to exact values as the number of boundary nodes increases.

• ETRI Journal
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• 제42권5호
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• pp.658-668
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• 2020

In edge computing, most procedures, including data collection, data processing, and service provision, are handled at edge nodes and not in the central cloud. This decreases the processing burden on the central cloud, enabling fast responses to end-device service requests in addition to reducing bandwidth consumption. However, edge nodes have restricted computing, storage, and energy resources to support computation-intensive tasks such as processing deep neural network (DNN) inference. In this study, we analyze the effect of models with single and multiple local exits on DNN inference in an edge-computing environment. Our test results show that a single-exit model performs better with respect to the number of local exited samples, inference accuracy, and inference latency than a multi-exit model at all exit points. These results signify that higher accuracy can be achieved with less computation when a single-exit model is adopted. In edge computing infrastructure, it is therefore more efficient to adopt a DNN model with only one or a few exit points to provide a fast and reliable inference service.

• 한국정보통신학회논문지
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• 제25권6호
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• pp.799-806
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• 2021

정합은 고유 좌표를 가지고 있는 점군을 전역 좌표로 변환하는 과정이다. 지역 정합은 계산 시간이 오래 걸리고 대략적인 위치를 맞춘 후 정밀 정합을 수행하고, 전역 정합은 정합에 이용할 대응점을 계산하고 한 번에 정합하기 때문에 일반적으로 지역 정합법에 비해 속도가 빠르고, 초기 위치에도 상관이 없다. 전역 정합 방법 중 고속 전역 정합법은 성능이 우수하여 많이 사용하는 방법 중 하나이다. 하지만 정합 정밀도와 속도를 높이기 위해서는 많은 매개변수가 필요하다. 본 논문에서는 이와 같은 매개변수들을 분석하고 실험하여 실제 정합 시 유효하게 작용하는 매개변수를 제안한다. 제안한 결과는 고속 전역 정합법을 활용해야 하는 경우 방향 설정에 도움이 될 것이다.

• International Journal of Aeronautical and Space Sciences
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• 제5권1호
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• pp.94-100
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• 2004

Ionospheric time delay is the biggest error source for single-frequency DGPSapplications, including time transfer and Wide Area Differential GPS (WADGPS).Currently, there are many attempts to develop real-time ionospheric time delayestimation techniques to reduce positioning error due to the ionospheric time delay.Klobuchar model is now widely used for ionosphehc time delay calculation forsingle-frequency users. It uses flat surface at night time and cosine surface atdaytime[1], However, the model was developed for worldwide ionosphere fit, it isnot adequate for local area single-frequency users who want to estimateionospheric time delay accurate1y[2]. Therefore, 3-D ionosphere model usingtomographic estimation has been developed. 3-D tomographic inversion modelshows better accuracy compared with prior a1gorithms[3]. But that existing 3-Dmodel still has problem that it requires many coefficients and measurements forgood accuracy. So, that algorithm has Umitation with many coefficients incontinuous estimation at the small region which is obliged to have fewermeasurements.In this paper, we developed an modified 3-D ionosphehc time delay modelusing tomography, which requires only fewer coefficients. Because the combinationsof our base coefficients correspond to the full coefficients of the existing model, ourmodel has equivalent accuracy to the existing. We confirmed our algorithm bysimulations. The results proved that our modified algohthm can perform continuousestimation with fewer coefficients.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1329-1331
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• 2003

Improvement of the classification accuracy is one of the major concerns in the field of remote sensing application research in recent years. Previous research shows that the accuracy of the conventional classification methods based only on the original spectral information were usually unsatisfied and need to be refined by manual edit. This present paper describes a method of combining the image processing, ancillary data (such as digital elevation model) and expert knowledge (especially the knowledge of local professionals) to improve the efficiency and accuracy of the satellite image classification in hilly land. Firstly, the Landsat TM data were geo-referenced. Secondly, the individual bands of the image were intensitynormalized and the normalized difference vegetation index (NDVI) image was also generated. Thirdly, a set of sample pixels (collected from field survey) were utilized to discover their corresponding DN (digital number) ranges in the NDVI image, and to explore the relationships between land use type and its corresponding spectral features . Then, using the knowledge discovered from previous steps as well as knowledge from local professionals, with the support of GIS technology and the ancillary data, a set of conditional statements were applied to perform the TM imagery classification. The results showed that the integration of image processing and spatial analysis functions in GIS improved the overall classification result if compared with the conventional methods.

• Journal of Information Processing Systems
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• 제17권2호
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• pp.213-226
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• 2021

Given that most of the link prediction algorithms for signed social networks can only complete sign prediction, a novel algorithm is proposed aiming to achieve both link prediction and sign prediction in signed networks. Based on the structural balance theory, the local link tightness and global link tightness are defined respectively by using the structural information of paths with the step size of 2 and 3 between the two nodes. Then the total similarity of the node pair can be obtained by combining them. Its absolute value measures the possibility of the two nodes to establish a link, and its sign is the sign prediction result of the predicted link. The effectiveness and correctness of the proposed algorithm are verified on six typical datasets. Comparison and analysis are also carried out with the classical prediction algorithms in signed networks such as CN-Predict, ICN-Predict, and PSNBS (prediction in signed networks based on balance and similarity) using the evaluation indexes like area under the curve (AUC), Precision, improved AUC', improved Accuracy', and so on. Results show that the proposed algorithm achieves good performance in both link prediction and sign prediction, and its accuracy is higher than other algorithms. Moreover, it can achieve a good balance between prediction accuracy and computational complexity.