사용자 세분화 전략에 따른 미래 사무공간 환경 특성 연구

박신영 ( Park Shinyoung ),이재규 ( Lee Jaekyu ) 한국공간디자인학회 2021 한국공간디자인학회논문집 Vol.16 No.8

(Background and Purpose) Office space in the 20th century has been developed around companies or managers, while the positions of members who actually occupy a major proportion of the organization have not been considered. This trend continued in Korea until recently, but changes in office settings became essential since COVID-19 has shifted the mode of work to telecommuting or through autonomous work systems. In particular, the expansion of technologies such as the Internet have changed people's lifestyle and values as well as their work in Korea. Future offices should not be a functional space for work alone, but a human space that reflects a user-centered perspective for a better life. Therefore, it is imperative to integrate individual values through user segmentation strategy and apply them to spaces used by organizations. (Method) First, the definition and characteristics of future office were derived from previous studies on office space characteristics. Second, I confirmed the applicability of office through previous studies that applied user segmentation strategy. Third, according to the user segmentation strategy, future office users were subdivided based on literature data to derive user value. Fourth, by comparing and analyzing the results derived above, an analysis model was created to define future office space characteristics, and a specific design plan was identified by selecting and analyzing advanced cases. (Results) As a result, it was confirmed that the application of the user segmentation strategy is an important process in analyzing office space characteristics in the future, and there is a sufficient possibility of expansion to various space fields. The eight characteristics of the derived future office space were a complex distribution of user values discovered through generational analysis. It has been shown that users not only value communication and sharing, but also want to have an individual's status and the identity within the organization. This means that the trend of shared space should be reconsidered, and it is important for companies to listen to what the members of the organization expect in office space. (Conclusions) Since office space can be considered a small-scale society where new generations that can create innovation and older generations that provide knowhow co-exist, it is important to create an environment where each generation can understand and cooperate with one another. The future office, therefore, needs to include high-quality spaces, and user segmentation strategy can be applied as a methodology to implement optimal design by intensively analyzing organizational members.

아파트 평면의 단위공간 분절방식에 따른 공간구문론적 해석

박순매(Piao, Shun-Mei),윤재신(Yoon, Chae-Shin) 대한건축학회 2017 대한건축학회 학술발표대회 논문집 Vol.37 No.1

Space syntax theory does numerical calculation based on the connection of each unit of the total space. In this process, a plane should be divided intu unit spaces. When space syntax theory is used to analy sis the inside space complex of a building, the total space is redrawn as a convex plane. It means every unit spaces should be divided as a convex if it is a concave one. Therefore, the way of convex plan drawing induces variant syntactic analysis. There are some kinds of convex drawing methodes, and the most popular one is the short line division.There is also a division by function. These concepts have some restriction in the process of redrawing unit spaces, such as laking basis of dividing space, What is more, the process is physical and artificial. This paper tries to import the theory of enclosing balance in the process of dividing space so that some perceptual and psychological clues are annexed to the process.

모양공간 모델을 이용한 영상분할 알고리즘

김대희,안충현,호요성 대한전자공학회 2004 電子工學會論文誌-SP (Signal processing) Vol.43 No.3

MPEG-4 표준에서는 객체 단위의 부호화를 수행하기 위해 자연영상으로부터 비디오 객체를 분리하는 영상분할(segmentation) 기술이 필요하다. 영상분할 방법은 크게 자동 영상분할(automatic segmentation)과 반자동 영상분할(semi-automatic segmentation)의 두 부류로 나눌 수 있다. 지금까지 개발된 대부분의 자동 영상분할 방법은 비디오 객체의 명확한 수학적인 모델을 제시하기 곤란하며 한 화면에서 개별 객체를 추출하기 어렵기 때문에 그 성능에 한계가 있다. 본 논문에서는 이러한 문제점을 극복하기 위해 active contour 알고리즘을 이용한 반자동 영상분할 알고리즘을 제안한다. 초기 곡선으로부터 변화 가능한 모든 곡선의 집합을 모양공간으로 정의하고 그 공간을 선형공간이라고 가정하면, 모양공간(shape space)은 모양 행렬에 의해 행(column) 공간과 남은 빈(left null) 공간으로 나뉘어진다. 본 논문에서 제안하는 알고리즘은 행공간의 모양공간 벡터를 이용하여 초기 곡선으로부터 영상의 특징점까지의 변화를 기술하고 동적 그래프 검색 알고리즘을 이용하여 객체의 세밀한 부분을 묘사한다. 모양 행렬과 객체의 윤곽을 추정하기 위한 SUSAN 연산자의 사용으로 제안한 알고리즘은 저수준 영상처리로부터 생성되는 불필요한 특징점을 무시할 수 있다. 또한, 모양 행렬의 사용으로 생긴 제약은 동적 그래프 검색 알고리즘으로 보상한다. Since the MPEG-4 visual standard enables content-based functionalities, it is necessary to extract video objects from video sequences. Segmentation algorithms can largely be classified into two different categories: automatic segmentation and user-assisted segmentation. In this paper, we propose a new user-assisted image segmentation method based on the active contour. If we define a shape space as a set of all possible variations from the initial curve and we assume that the shape space is linear, it can be decomposed into the column space and the left null space of the shape matrix. In the proposed method, the shape space vector in the column space describes changes from the initial curve to the imaginary feature curve, and a dynamic graph search algorithm describes the detailed shape of the object in the left null space. Since we employ the shape matrix and the SUSAN operator to outline object boundaries, the proposed algorithm can ignore unwanted feature points generated by low-level image processing operations and is, therefore, applicable to images of complex background. We can also compensate for limitations of the shape matrix with a dynamic graph search algorithm.

건축 평면에서 공간 분석 이론의 단위 공간 분절 방식에 대한 비교 연구

박순매(Piao, Shun-Mei),김마리(Kim, Ma-Rie),윤재신(Yoon, Chae-Shin) 대한건축학회 2018 대한건축학회논문집 Vol.34 No.3

This paper explores the structure of space in architecture from a viewpoint that individual unitized spaces are gathered to form the whole. To understand the spatial structure of architecture, firstly we need to understand each unitized spaces, and secondly, one must understand how the following adjacent spaces are connected to form the whole building. this gives salience to a fact that understanding the whole comprehensively. It is the most fundamental bases that must be understood and unitized when understanding the spatial structure of an existing building and designing a new one. It is necessary to hypostatize space as an abstract notion. In regards to this space examines the logical flow of structure within actual space. Hypostasieren process includes the process of shaping space and the shape information. In this process we need to refer to the properties of space and the morphological characteristics of physical elements. The segment of the unitized space is the realization process of the basic space. This study aims to provide a theoretical basis for analysis and design of spatial structure by comparing several representative methods of segmenting unitized space.

Segment Unit 및 건축물 연면적을 고려한 보행 공간 특성

김미의(Kim, Miui),김수연(Kim, SuYoun),이명훈(Lee, MyeongHun) 대한국토·도시계획학회 2013 國土計劃 Vol.48 No.7

The purpose of this study is going to suggest foundational data which could induce revitalization of more practical pedestrian places, analyzing through adding up the amount of number of pedestrians as a variation onto analysis from various approaches which is based on characters, features, or uses of physical spaces in big picture provided by the connectivity of walking spaces. In order to achieve the purpose, targeting the second and third district unit planning in Jongro area, (1) analyzing pedestrian space which includes every usages of three dimensional those buildings through segment unit; (2) investigating the number of pedestrian, a widthㆍlengthㆍarea, and an elements located on the pedestrian road (3) analyzing the network or connectivity of target area analyzing through space syntax analysis; (4) analyzing correlation of walking space’s connectivity and number of pedestrians considering microscopic land use. In conclusion, From the evaluation of all these factors, Segment unit, three dimensional usage, and many minor factors located on pedestrian space are considered to make and control on pedestrians space. And this dissertation will provide many advantages to policy decision-making, planning movement space for pedestrians based on more empirical and elaborate conditions.

Development of Region-based Crop Segmentation Algorithm for Sharp-leaf Crops using UAV-RGB imagery

( Dong-wook Kim ),( Hak-jin Kim ),( Sang-jin Jeong ),( Won Suk Lee ) 한국농업기계학회 2021 한국농업기계학회 학술발표논문집 Vol.26 No.1

Crop segmentation is fundamental and important in agricultural information automation. Many issues, such as crop growth stage prediction, crop line detection, crop density estimation, cover crop identication, leaf disease detection, and crop biomass monitoring, are highly dependent on the performance of crop segmentation algorithms. Under field conditions, crop segmentation for UAV-imagery should be more sophisticated considering low resolution of image, atmospheric interference, varying illumination on each day, and complex backgrounds. Especially, in the cultivation of Korea, a plastic mulch which has been used for restricting weeds and preventing damages from cold weather, makes the backgrounds more complex. In our previous study, ExG-Otsu’s threshold algorithm, which has been very commonly used in RGB images, was used for segmentation of Chinese cabbage and White radish. However, ExG-Otsu’s threshold algorithm showed low accuracy for sharp-leaf crops such as Garlic and Onion because of the complex shape of crops and shadow effect under various illumination conditions. In this study, crop segmentation algorithm that perform for sharp-leaf crops were developed by applying region-based segmentation algorithm with CIE L*a*b* color space. Combining region-based segmentation algorithm based on local density estimation and CIE L*a*b* color space improves the segmentation accuracy when compared with the previous method because the algorithm could removes texture and irregularity. The results showed the potential of using UAV-based RGB imagery for crop segmentation of sharp-leaf crops over the whole growing season in a quantitative manner.

A Novel FCM Algorithm Incorporating Spatial Information for Color Image Segmentation

Li Ling,Song Yingwei,Yin Zhongnan,Yang Xiuhua 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.8

Fuzzy c-means clustering (FCM) with spatial information (FCM_S) is an effective algorithm for image segmentation. However, the FCM_S algorithm is not used for color image segmentation and also it produces over-segmentation results. In this paper, we present a novel fuzzy c-means algorithm named nFCM_S that incorporates spatial information into the membership function and cluster center function for segmentation of color images. Firstly, HSV color space is used for decomposition of color images. Then, to label the data points reliably, a linearly-weighted sum image is calculated on each HSV component before clustering process. Finally, spatial information is incorporated in the standard FCM algorithm and nFCM_S is applied separately on each component of HSV color space. Experiment results have shown that the nFCM_S algorithm achieves competitive segmentation results compared to other FCM-based algorithms.

공간구문론의 공간분할에서 문제점과 해결방안에 관한 연구

박순매(Piao Shun-Mei),윤재신(Yoon Chae-Shin) 대한건축학회 2007 대한건축학회 학술발표대회 논문집 - 계획계/구조계 Vol.27 No.1

Space syntax theory does numerical calculation based on the connection of each unit of the total space. In this process, a plane should be divided into unit spaces. When space syntax theory is used to analysis the inside space complex of a building, the total space is redrawn as a convex plane. It means every unit spaces should be divided as a convex if it is a concave one. Therefore, the way of convex plan drawing induces variant syntactic analysis. There are some kinds of convex drawing methods, and the most popular one is the short line division. These concepts have some restriction in the process of redrawing unit spaces, such as lacking basis of dividing space. What is more, the process is physical and artificial. This paper tries to import the theory of enclosing balance in the process of dividing space so that some perceptual and psychological clues are annexed to the process.

Scale-space approximated convolutional neural networks for retinal vessel segmentation

Noh, Kyoung Jin,Park, Sang Jun,Lee, Soochahn Elsevier 2019 Computer Methods and Programs in Biomedicine Vol.178 No.-

<P><B>Abstract</B></P> <P>Background and objective: Retinal fundus images are widely used to diagnose retinal diseases and can potentially be used for early diagnosis and prevention of chronic vascular diseases and diabetes. While various automatic retinal vessel segmentation methods using deep learning have been proposed, they are mostly based on common CNN structures developed for other tasks such as classification.</P> <P><B>Methods</B></P> <P>We present a novel and simple multi-scale convolutional neural network (CNN) structure for retinal vessel segmentation. We first provide a theoretical analysis of existing multi-scale structures based on signal processing. In previous structures, multi-scale representations are achieved through downsampling by subsampling and decimation. By incorporating scale-space theory, we propose a simple yet effective multi-scale structure for CNNs using upsampling, which we term <I>scale-space approximated CNN (SSANet)</I>. Based on further analysis of the effects of the SSA structure within a CNN, we also incorporate residual blocks, resulting in a multi-scale CNN that outperforms current state-of-the-art methods.</P> <P><B>Results</B></P> <P>Quantitative evaluations are presented as the area-under-curve (AUC) of the receiver operating characteristic (ROC) curve and the precision-recall curve, as well as accuracy, for four publicly available datasets, namely DRIVE, STARE, CHASE_DB1, and HRF. For the CHASE_DB1 set, the SSANet achieves state-of-the-art AUC value of 0.9916 for the ROC curve. An ablative analysis is presented to analyze the contribution of different components of the SSANet to the performance improvement.</P> <P><B>Conclusions</B></P> <P>The proposed retinal SSANet achieves state-of-the-art or comparable accuracy across publicly available datasets, especially improving segmentation for thin vessels, vessel junctions, and central vessel reflexes.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Conventional CNN structures may cause aliasing in multi-scale feature extraction. </LI> <LI> In the scale-space approximated CNN (SSANet) decimation is replaced with upsampling. </LI> <LI> Upsampling after downsampling is essentially Gaussian blurring in scalespace theory. </LI> <LI> Reduced receptive field is offset with residual blocks that also increase capacity. </LI> <LI> Proposed SSANet shows state-of-the-art accuracy for retinal vessel segmentation. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>

An Effective Orientation-based Method and Parameter Space Discretization for Defined Object Segmentation

( Huy Hoang Nguyen ),( Gueesang Lee ),( Soohyung Kim ),( Hyungjeong Yang ) 한국인터넷정보학회 2013 KSII Transactions on Internet and Information Syst Vol.7 No.12

While non-predefined object segmentation (NDOS) distinguishes an arbitrary self-assumed object from its background, predefined object segmentation (DOS) pre-specifies the target object. In this paper, a new and novel method to segment predefined objects is presented, by globally optimizing an orientation-based objective function that measures the fitness of the object boundary, in a discretized parameter space. A specific object is explicitly described by normalized discrete sets of boundary points and corresponding normal vectors with respect to its plane shape. The orientation factor provides robust distinctness for target objects. By considering the order of transformation elements, and their dependency on the derived over-segmentation outcome, the domain of translations and scales is efficiently discretized. A branch and bound algorithm is used to determine the transformation parameters of a shape model corresponding to a target object in an image. The results tested on the PASCAL dataset show a considerable achievement in solving complex backgrounds and unclear boundary images.