• 정보처리학회 논문지
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• 제13권7호
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• pp.311-318
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• 2024

인공지능과 인터넷의 발전으로 인한 데이터의 증가로 데이터 관리의 중요성이 부각되고 있는 상황에서, 데이터 검색과 메모리 공간의 효율적 활용이 매우 중요한 시대가 도래하였다. 본 연구에서는 메타데이터를 기반으로 데이터 구조를 분석하여 검색 속도와 메모리 효율을 최적화하는 방안을 연구한다. 연구방법으로는 사진 이미지의 메타데이터를 활용하여 배열, 연결리스트, 딕셔너리, 이진 트리, 그래프의 데이터 구조에 대한 성능을 시간적, 공간적 복잡도를 중심으로 비교하고 분석하였다. 실험을 통해 대규모의 이미지 데이터를 다루는 상황에서 딕셔너리 구조는 수집속도에서, 그래프 구조는 검색 속도에서 가장 우수한 성능을 보여주는 것을 확인할 수 있었다. 본 논문의 결과는 이미지 데이터 검색 속도와 메모리 효율을 최적화하기 위한 데이터 구조를 선택하는데 실용적인 가이드라인을 제시할 것으로 기대한다.

• 터널과지하공간
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• 제12권1호
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• pp.37-42
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• 2002

본 연구에서는 터널의 주요 설계정수인 탄성계수와 측압계수를 산정 할 수 있는 역 해석 알고리즘을 개발하였다. 해석 알고리즘은 범용 유한차분해석 프로그램인 FLAC의 해석과정 내에 직접탐색법 알고리즘을 이용한 FISH 문을 삽입함으로써 구성하였다. 기존 연구에서 사용한 탄성모델에 대하여 본 연구에서 개발한 역 해석 알고리즘의 적합성을 검토하였다. 본 연구에서 개발된 역 해석 알고리즘은 기존 역 해석 기법에 비해 더 적은 반복연산에 더 정확한 결과를 얻을 수 있음을 확인하였다.

• 한국실내디자인학회논문집
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• 제19권6호
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• pp.197-205
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• 2010

For the spatial experience of spectators visiting a museum, the route search of trying to follow the spatial structure or production of exhibition and the information search of trying to see are accomplished at the same time. In such process, the spectator's reaction of visual perception produces the result of emotional reaction and action exchanged between human and space by going through the recognition and perception on the target of environment factor. For the spatial experience of a spectator, the reaction of visual perception which interacts according to the exhibit and exhibition environment within space according to viewing purpose, interest and concern of spectator comes out as visual activity which is an activity to understand the spatial information shown as various activities according to spatial structure and unfolding characteristics of the display. The purpose of this study is to identify The Correlation of Spectator Movement Created According to Structural Form of Exhibition Area Based on Interaction between Exhibition Area Structure and Spectator to utilize as basic material while designing museum exhibition using isovist field which is a quantitative analysis tool of spectator's visual behavior and spatial structure at each exhibition area.

• 천문학회보
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• 제35권2호
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• pp.78.2-78.2
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• 2010

We report the detection of a low-amplitude 380.8-day radial velocity (RV) variations in oscillating K2 III star ${\alpha}$ Ari (HD 12929). We do not found the correlation between RV variations and equivalent widths of chromospheric activity indicators ($H{\alpha}$ and CaII 8662 ${\AA}line$). The bisector analysis shows that bisector velocity span (BVS) and RV variations are not strongly correlated with each other. These result suggest that the RV variations could have been produced either by planetary companion or by the surface spots. If this RV variation is indeed caused by a planetary companion, an orbital solution with a period of P = 381 days, a semi-amplitude of K = 41 m/s, and an eccentricity of e = 0.25 fits the data best. Assuming a possible stellar mass of $M_{\bigstar} = 1.4-5.6 M\odot$, we estimate the minimum mass for the companion of m sini = 1.8-4.5 $M_{Jup}$ with an orbital semi-major axis of 1.2-1.9 AU. If confirmed, our finding gives a support to search for exoplanets around giant stars with multi-periodic oscillations.

• 천문학회보
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• 제41권1호
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• pp.43.2-43.2
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• 2016

We present results of a calibrator search near twenty evolved stars using the Korean VLBI Network (KVN). Our evolved star targets include candidate sources for a Key Science Project (KSP) of the KVN. The KSP plans to investigate the spatial structure and dynamical effects between SiO and H2O maser regions including mass-loss process and development of asymmetry in circumstellar envelopes of evolved stars. For these purposes, we need compact and strong extragalactic sources close to the evolved stars. We carried out 5 observations in order to detect radio continuum sources that can be used for source frequency phase-referencing (SFPR) -based analysis. We observed 153 sources, out of which we detected 29 at 22 GHz and 20 at 43 GHz at signal-to-noise ratios higher than 50 at all baselines. Therefore, we successfully found target and calibrator pairs for the KVN KSP.

• ETRI Journal
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• 제45권1호
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• pp.119-130
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• 2023

We propose a quantized gradient search algorithm that can achieve global optimization by monotonically reducing the quantization step with respect to time when quantization is composed of integer or fixed-point fractional values applied to an optimization algorithm. According to the white noise hypothesis states, a quantization step is sufficiently small and the quantization is well defined, the round-off error caused by quantization can be regarded as a random variable with identically independent distribution. Thus, we rewrite the searching equation based on a gradient descent as a stochastic differential equation and obtain the monotonically decreasing rate of the quantization step, enabling the global optimization by stochastic analysis for deriving an objective function. Consequently, when the search equation is quantized by a monotonically decreasing quantization step, which suitably reduces the round-off error, we can derive the searching algorithm evolving from an optimization algorithm. Numerical simulations indicate that due to the property of quantization-based global optimization, the proposed algorithm shows better optimization performance on a search space to each iteration than the conventional algorithm with a higher success rate and fewer iterations.

• 한국주거학회논문집
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• 제16권6호
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• pp.65-72
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• 2005

The purpose of this study is to get preeminent data from comparative analysis of multi-family housing unit plans between Korea and China nowadays. Even though Korea and China belong to common cultured band in Asia, there are many different Housing aspects and unit plans. Through this study we want to grasp the characteristics of both nation's apartment unit plans and to contribute for advance into the China apartment market. Analysis target is constructing and lotting out apartment at South Korea and China in 2004, and the space syntax model is used as an analysis tool. First, analyze kind, number and special quality of each room by use area, and second, analyze area and scale of the rooms. Through the integration analysis we know the grade of rank and centrality of each rooms, and search difference of South Korean and Chinese apartment.

• 한국실내디자인학회논문집
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• 제24권2호
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• pp.125-133
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• 2015

Gaze induction characteristics in space vary depending on characteristics of spatial components and display. This study analyzed dominant eye-fixation characteristics of three zones of department store space. Eye-fixation characteristics depending on spatial components and positional relationship can be defined as follows. First, [**.jpg] was used as an extension in the process of storing the image photographed during image data processing for analysis in pixels and due to compressed storage of image data, the image produced with a clear boundary was stored in neutral colors. To remove this problem, the image used in operation was re-processed in black and white and stored in the [**.bmp] format with large capability, at the same time. As the result, the effort caused by unnecessary colors in the program operation process was corrected. Second, the gaze ratio to space area can be indicated as a strength of each gaze zone and when analyzing the gaze strength of the three zones, the left store was a zone with a "little strong" gaze strength of "102.8", the middle space was a zone with an "extremely weak" gaze strength of "89.6" and the right store was a zone with an "extremely strong" gaze strength of "117.2". Third, the IV section had a strong strength of gaze on the middle space and the right store and the V section showed a markedly strong strength of gaze on the left and right stores. This tendency was the same as the VI section with the strongest gaze strength and the right store had a little strong gaze strength than the left store.

• Journal of Information Processing Systems
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• 제17권5호
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• pp.1020-1033
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• 2021

Nowadays, online or mobile social network services (SNS) are very popular and widely spread in our society and daily lives to instantly share, disseminate, and search information. In particular, SNS such as YouTube, Flickr, Facebook, and Amazon allow users to upload billions of images or videos and also provide a number of multimedia information to users. Information retrieval in multimedia-rich SNS is very useful but challenging task. Content-based media retrieval (CBMR) is the process of obtaining the relevant image or video objects for a given query from a collection of information sources. However, CBMR suffers from the dimensionality curse due to inherent high dimensionality features of media data. This paper investigates the effectiveness of the kernel trick in CBMR, specifically, the kernel principal component analysis (KPCA) for dimensionality reduction. KPCA is a nonlinear extension of linear principal component analysis (LPCA) to discovering nonlinear embeddings using the kernel trick. The fundamental idea of KPCA is mapping the input data into a highdimensional feature space through a nonlinear kernel function and then computing the principal components on that mapped space. This paper investigates the potential of KPCA in CBMR for feature extraction or dimensionality reduction. Using the Gaussian kernel in our experiments, we compute the principal components of an image dataset in the transformed space and then we use them as new feature dimensions for the image dataset. Moreover, KPCA can be applied to other many domains including CBMR, where LPCA has been used to extract features and where the nonlinear extension would be effective. Our results from extensive experiments demonstrate that the potential of KPCA is very encouraging compared with LPCA in CBMR.

• 한국전자통신학회논문지
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• 제5권2호
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• pp.152-157
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• 2010

컴퓨터와 인터넷의 발달로 정보의 형태가 다양화 되어 문서 위주의 자료들로부터 이미지, 오디오, 비디오, 음성 등의 모습으로 혼합되어 가고 있다. 하지만 대부분의 검색은 문서 위주로 하기 때문에 이미지, 오디오, 비디오 등은 파일의 이름이 명확하게 설정되어 있지 않을 경우에는 검색을 할 수 없다. 이러한 문제점을 해결하기 위해 문서가 아닌 내용을 기반으로 검색하는 방법을 내용 기반 검색이라고 한다. 그리고 이미지의 내용을 기반으로 검색하는 방법을 내용 기반 이미지 검색이라고 한다. 본 논문에서는 HSI 컬러 공간, ART2 알고리즘, SOM 알고리즘을 이용한 내용 기반 이미지 검색 방법을 제안한다. 제안하는 방법은 학습 대상을 선정하기 위해 원 영상의 특징을 분할한다. 그리고 사용자가 학습 대상을 선정하도록 하기 위해 분할된 특징을 SOM 알고리즘에 적용하여 비슷한 특징을 가지는 영상들로 군집화 한다. 군집화된 영상들에 대해 사용자가 학습 대상을 선정하여 ART2 알고리즘에 적용하여 학습한다. 제안한 방법을 적용하여 이미지 검색을 실험한 결과 제안된 방법은 하나의 이미지가 여러 개의 키워드를 가질 수 있기 때문에 이미지에 포함된 정보를 효과적으로 검색하는 것을 확인하였다.