• Title/Summary/Keyword: second-order feature space

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A Case Study of Layout Plan and Use of Indoor Community Spaces in Rental Apartment Complexes (사례분석을 통한 임대아파트 실내 커뮤니티공간의 배치 및 이용실태)

  • Hwang, Yeon-Sook;Byun, Hea-Ryung;Lee, Song-Hyun;Eo, Sung-Sin
    • Journal of the Korean housing association
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    • v.21 no.4
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    • pp.99-109
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    • 2010
  • The purpose of this study is to provide basic data needed for planning apartment community spaces in order to vitalize rental apartments. Indoor community spaces of 12 rental apartments in Seoul and Kyunggi were examined. The results are as follows. First, the layout types of indoor community spaces in rental apartment complexes were found out to be mostly the building type planned in the piloties of the apartment, or the singular type placed in a singular building. Depending on the layout type, the spaces were mostly concentrated at the outskirt of the complex or the in-between space of the main building, thus lowering their recognition. Thereby, they were not satisfactory for utilization of the spaces and association of residents. Second, Indoor community space legal establishment standard and square measure did not reflect resident's feature except elderly spaces, and there was problem in activation of space. Third, as for the spatial planning of indoor community space, although each space was categorized by the users' age, the furniture and appliance planning considering users was not satisfactory. The area calculation by the type of space did not reflect the users' characteristics, thus causing problems in using the facilities. Fourth, as for the management and programs of the indoor community space, spaces were managed after categorized by the major user classes such as children, seniors, and adolescents. Depending on eagerness of program managers of each apartment complex, the level of program management varied. The survey results showed that, in most cases, almost no programs were used or merely basic management and programs were being provided.

A Study on the Architectural Design Feature for Future School - Focusing on the Space Composition of Educational Space - (사례분석을 통한 미래지향적 학교의 건축 계획적 특성 연구 - 교육공간구성을 중심으로 -)

  • Lee, Ji-You;Lee, Jong-Kuk
    • The Journal of Sustainable Design and Educational Environment Research
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    • v.18 no.2
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    • pp.12-21
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    • 2019
  • In the wake of the fourth industrial revolution, the paradigm of human resources and education required by reality is changing. School buildings are also improving to accommodate changed education and with that move, school building reform policies have been established at home and abroad. The purpose of this study is to present the architectural planning characteristics of Future Schools related to space design. The research methods are as follows: First, the characteristics of Future School planning are compiled through prior research surveys in Korea. Second, the characteristics outlined earlier through advanced case analysis are examined of their application to architectural planning in order to establish the status of utilization factors, and the direction of planning is presented. This study names the school architecture as 'Future School' in reference to the use of the term in the preceding study. This study is meaningful in that it focuses on architectural planning characteristics in Future School planning and on actual application cases of theory.

A numerical method for the study of fluidic thrust-vectoring

  • Ferlauto, Michele;Marsilio, Roberto
    • Advances in aircraft and spacecraft science
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    • v.3 no.4
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    • pp.367-378
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    • 2016
  • Thrust Vectoring is a dynamic feature that offers many benefits in terms of maneuverability and control effectiveness. Thrust vectoring capabilities make the satisfaction of take-off and landing requirements easier. Moreover, it can be a valuable control effector at low dynamic pressures, where traditional aerodynamic controls are less effective. A numerical investigation of Fluidic Thrust Vectoring (FTV) is completed to evaluate the use of fluidic injection to manipulate flow separation and cause thrust vectoring of the primary jet thrust. The methodology presented is general and can be used to study different techniques of fluidic thrust vectoring like shock-vector control, sonic-plane skewing and counterflow methods. For validation purposes the method will focus on the dual-throat nozzle concept. Internal nozzle performances and thrust vector angles were computed for several range of nozzle pressure ratios and fluidic injection flow rate. The numerical results obtained are compared with the analogues experimental data reported in the scientific literature. The model is integrated using a finite volume discretization of the compressible URANS equations coupled with a Spalart-Allmaras turbulence model. Second order accuracy in space and time is achieved using an ENO scheme.

Pedestrian Detection Algorithm using a Gabor Filter Bank (Gabor Filter Bank를 이용한 보행자 검출 알고리즘)

  • Lee, Sewon;Jang, Jin-Won;Baek, Kwang-Ryul
    • Journal of Institute of Control, Robotics and Systems
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    • v.20 no.9
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    • pp.930-935
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    • 2014
  • A Gabor filter is a linear filter used for edge detectionas frequency and orientation representations of Gabor filters are similar to those of the human visual system. In this thesis, we propose a pedestrian detection algorithm using a Gabor filter bank. In order to extract the features of the pedestrian, we use various image processing algorithms and data structure algorithms. First, color image segmentation is performed to consider the information of the RGB color space. Second, histogram equalization is performed to enhance the brightness of the input images. Third, convolution is performed between a Gabor filter bank and the enhanced images. Fourth, statistical values are calculated by using the integral image (summed area table) method. The calculated statistical values are used for the feature matrix of the pedestrian area. To evaluate the proposed algorithm, the INRIA pedestrian database and SVM (Support Vector Machine) are used, and we compare the proposed algorithm and the HOG (Histogram of Oriented Gradient) pedestrian detector, presentlyreferred to as the methodology of pedestrian detection algorithm. The experimental results show that the proposed algorithm is more accurate compared to the HOG pedestrian detector.

Improved Tooth Detection Method for using Morphological Characteristic (형태학적 특징을 이용한 향상된 치아 검출 방법)

  • Na, Sung Dae;Lee, Gihyoun;Lee, Jyung Hyun;Kim, Myoung Nam
    • Journal of Korea Multimedia Society
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    • v.17 no.10
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    • pp.1171-1181
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    • 2014
  • In this paper, we propose improved methods which are image conversion and extraction method of watershed seed using morphological characteristic of teeth on complement image. Conventional tooth segmentation methods are occurred low detection ratio at molar region and over, overlap segmentation owing to specular reflection and morphological feature of molars. Therefore, in order to solve the problems of the conventional methods, we propose the image conversion method and improved extraction method of watershed seed. First, the image conversion method is performed using RGB, HSI space of tooth image for to extract boundary and seed of watershed efficiently. Second, watershed seed is reconstructed using morphological characteristic of teeth. Last, individual tooth segmentation is performed using proposed seed of watershed by watershed algorithm. Therefore, as a result of comparison with marker controlled watershed algorithm and the proposed method, we confirmed higher detection ratio and accuracy than marker controlled watershed algorithm.

Scanning Determination & Observation Features by Sex shown in the Process of Acquiring Visual Information - With the Object of Subway Station Hall Space - (시각정보획득과정에 나타난 주사판정과 성별 주시특성 - 지하철 홀 공간을 대상으로 -)

  • Kim, Jong-Ha;Choi, Gae-Young
    • Korean Institute of Interior Design Journal
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    • v.23 no.6
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    • pp.115-124
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    • 2014
  • This study has carried out scanning tests in order to figure out the features of scanning search by sex of space users, with the result of which the validity of data has been estimated. In this research, the scanning patterns were set up for verifying the typology of scanning paths and then the reason for determining scanning paths and the validity of estimation method were reviewed. Since the observation features depends on sex, the analysis of visual activities for acquiring any information in a space will reveal the intention and purpose of space users. The findings by analyzing the features of scanning pattern by sex which were found at the determination of scanning patterns can be defined as the followings. First, for estimating the process of space-information search, the movement distance at each point of continuative-observation data from the angle of eye-movement has been extracted, on the ground of which the fixation and movement of eye have been defined for the establishment of scanning-cut characteristics. Second, the scanning times were estimated for the extraction of effective observation data that would be used for comparative analysis, which showed that men had more data (3,398.2/64.4%) than women (2,998.2/55.6%). This enables the acknowledgment that the scanning cut of men was relatively less, which indicates that men will acquire more information on space than women in the process of observing any space. Third, men's scanning times (58.0 times/2.02 seconds) were less than those of women (71.9 times/1.39 seconds) while the scanning time of the former was longer than that of the latter, which shows the feature that it takes longer for men than women in scanning while the scanning times of the former is less than those of the latter. Fourth, the observation features can be determined that the combination of this result with the predominance character by sex for a general viewpoint to be employed indicates that while men employ mixed-scanning for observation activities to acquire space-information spending for longer time, women, by concentrated-scanning, focus on a single point for shorter time or stay at one location for a considerably long time for space-information acquirement.

A Novel Phage Display Vector for Easy Monitoring of Expressed Proteins

  • Shin, Young-Chul;Kim, Young-Eun;Cho, Tae-Ju
    • BMB Reports
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    • v.33 no.3
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    • pp.242-248
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    • 2000
  • Phage display of proteins is a powerful tool for protein engineering since a vast library of sequences can be rapidly screened for a specific property. In this study, we develop da new phage display vector that was derived from a pET-25b(+) vector. The pET-25b(+) was modified in order that the expressed protein would have a T7-tag at the amino terminus and GpS (a major coat protein of M13 phage) at the carboxyl terminus. Another vector without the gp8 gene was also constructed. The newly developed phagemid vectors have several advantageous features. First, it is easy to examine whether or not the target proteins are functional and faithfully transported into the periplasmic space. This feature is due to the fact that recombinant proteins are produced abundantly in the pET system. Second, the T7-tag makes it possible to detect any target proteins that are displayed on the surface of filamentous bacteriophage. To verify the utility of the vector, the clones containing the glutathione S-transferase (GST) gene as a target were examined. The result showed that the GST produced from the recombinant vector was successfully transported into the periplasmic space and had the anticipated enzyme activity. Western blot analysis using a T7-tag antibody also showed the presence of the target protein displayed on the surface of the phage. The phages prepared from the recombinant clones were able to bind to glutathione-Sepharose and then eluted with glutathione. These results showed that the new vectors developed in this study are useful for the phage display of proteins.

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A Store Recommendation Procedure in Ubiquitous Market for User Privacy (U-마켓에서의 사용자 정보보호를 위한 매장 추천방법)

  • Kim, Jae-Kyeong;Chae, Kyung-Hee;Gu, Ja-Chul
    • Asia pacific journal of information systems
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    • v.18 no.3
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    • pp.123-145
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    • 2008
  • Recently, as the information communication technology develops, the discussion regarding the ubiquitous environment is occurring in diverse perspectives. Ubiquitous environment is an environment that could transfer data through networks regardless of the physical space, virtual space, time or location. In order to realize the ubiquitous environment, the Pervasive Sensing technology that enables the recognition of users' data without the border between physical and virtual space is required. In addition, the latest and diversified technologies such as Context-Awareness technology are necessary to construct the context around the user by sharing the data accessed through the Pervasive Sensing technology and linkage technology that is to prevent information loss through the wired, wireless networking and database. Especially, Pervasive Sensing technology is taken as an essential technology that enables user oriented services by recognizing the needs of the users even before the users inquire. There are lots of characteristics of ubiquitous environment through the technologies mentioned above such as ubiquity, abundance of data, mutuality, high information density, individualization and customization. Among them, information density directs the accessible amount and quality of the information and it is stored in bulk with ensured quality through Pervasive Sensing technology. Using this, in the companies, the personalized contents(or information) providing became possible for a target customer. Most of all, there are an increasing number of researches with respect to recommender systems that provide what customers need even when the customers do not explicitly ask something for their needs. Recommender systems are well renowned for its affirmative effect that enlarges the selling opportunities and reduces the searching cost of customers since it finds and provides information according to the customers' traits and preference in advance, in a commerce environment. Recommender systems have proved its usability through several methodologies and experiments conducted upon many different fields from the mid-1990s. Most of the researches related with the recommender systems until now take the products or information of internet or mobile context as its object, but there is not enough research concerned with recommending adequate store to customers in a ubiquitous environment. It is possible to track customers' behaviors in a ubiquitous environment, the same way it is implemented in an online market space even when customers are purchasing in an offline marketplace. Unlike existing internet space, in ubiquitous environment, the interest toward the stores is increasing that provides information according to the traffic line of the customers. In other words, the same product can be purchased in several different stores and the preferred store can be different from the customers by personal preference such as traffic line between stores, location, atmosphere, quality, and price. Krulwich(1997) has developed Lifestyle Finder which recommends a product and a store by using the demographical information and purchasing information generated in the internet commerce. Also, Fano(1998) has created a Shopper's Eye which is an information proving system. The information regarding the closest store from the customers' present location is shown when the customer has sent a to-buy list, Sadeh(2003) developed MyCampus that recommends appropriate information and a store in accordance with the schedule saved in a customers' mobile. Moreover, Keegan and O'Hare(2004) came up with EasiShop that provides the suitable tore information including price, after service, and accessibility after analyzing the to-buy list and the current location of customers. However, Krulwich(1997) does not indicate the characteristics of physical space based on the online commerce context and Keegan and O'Hare(2004) only provides information about store related to a product, while Fano(1998) does not fully consider the relationship between the preference toward the stores and the store itself. The most recent research by Sedah(2003), experimented on campus by suggesting recommender systems that reflect situation and preference information besides the characteristics of the physical space. Yet, there is a potential problem since the researches are based on location and preference information of customers which is connected to the invasion of privacy. The primary beginning point of controversy is an invasion of privacy and individual information in a ubiquitous environment according to researches conducted by Al-Muhtadi(2002), Beresford and Stajano(2003), and Ren(2006). Additionally, individuals want to be left anonymous to protect their own personal information, mentioned in Srivastava(2000). Therefore, in this paper, we suggest a methodology to recommend stores in U-market on the basis of ubiquitous environment not using personal information in order to protect individual information and privacy. The main idea behind our suggested methodology is based on Feature Matrices model (FM model, Shahabi and Banaei-Kashani, 2003) that uses clusters of customers' similar transaction data, which is similar to the Collaborative Filtering. However unlike Collaborative Filtering, this methodology overcomes the problems of personal information and privacy since it is not aware of the customer, exactly who they are, The methodology is compared with single trait model(vector model) such as visitor logs, while looking at the actual improvements of the recommendation when the context information is used. It is not easy to find real U-market data, so we experimented with factual data from a real department store with context information. The recommendation procedure of U-market proposed in this paper is divided into four major phases. First phase is collecting and preprocessing data for analysis of shopping patterns of customers. The traits of shopping patterns are expressed as feature matrices of N dimension. On second phase, the similar shopping patterns are grouped into clusters and the representative pattern of each cluster is derived. The distance between shopping patterns is calculated by Projected Pure Euclidean Distance (Shahabi and Banaei-Kashani, 2003). Third phase finds a representative pattern that is similar to a target customer, and at the same time, the shopping information of the customer is traced and saved dynamically. Fourth, the next store is recommended based on the physical distance between stores of representative patterns and the present location of target customer. In this research, we have evaluated the accuracy of recommendation method based on a factual data derived from a department store. There are technological difficulties of tracking on a real-time basis so we extracted purchasing related information and we added on context information on each transaction. As a result, recommendation based on FM model that applies purchasing and context information is more stable and accurate compared to that of vector model. Additionally, we could find more precise recommendation result as more shopping information is accumulated. Realistically, because of the limitation of ubiquitous environment realization, we were not able to reflect on all different kinds of context but more explicit analysis is expected to be attainable in the future after practical system is embodied.

A Study on the Characteristics of Observation seen in the Process of Perception and Recognition of Space (공간의 지각과 인지과정에 나타난 주시메커니즘 특성 연구)

  • Kim, Jong-Ha
    • Korean Institute of Interior Design Journal
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    • v.22 no.6
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    • pp.108-118
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    • 2013
  • This study has analyzed the process of space information perceived and recognized through the estimation of observation frequency and number according to the time range of observation data acquired from observation experiment with the object of hospital lobby. The followings are the results analyzed at this study. First, the continual observation of 3 and 6 times was attentive and conscious for probing to find an object rather than for acquiring exact information and that of 9 times could be regarded as the time for acquiring visual appreciation. However, the repetitive occurrence of high and low frequencies can be thought of repetitive acts for visual appreciation. Second, the continual observation of 3 and 6 times had the highest observation frequency of II, while that of 9 times had the highest observation frequency of III. In case of 3 and 6 times, the observation frequency had the tendency to become a little higher after being low since V, and in case of 9 times it had the repetition of becoming low and high and from IX it characteristically got higher. This feature can be thought to be the process that the subject repeats the fixation and movement of observation at a visual activity for perception and recognition. In the process of first observation, the observation frequency was the highest after 20 seconds or so, but since then, it gets lower and repeatedly gets higher and lower as time passes. After 90 seconds, the frequency showed the tendency of getting higher continuously. Third, the examination of changing features of frequency may show the characteristics of exploration for and attention to space but if the observation frequency is not associated with observation times for analysis there will a limitation that the features of observation frequency cannot be clarified. Accordingly, the simultaneous analysis of both is very effective for estimating the observation characteristics seen at the processes of perception and recognition. Fourth, the general analysis of the both revealed: with the progress of observation time the discontinuous space exploration decreased, and as the observation time got longer the fixed attention to a specific spot increased. Fifth, in order to estimate the observation characteristics by the change of time range the observation frequency and times by trend line was analyzed, which approach seems to be an appropriate technique that can comprehensively show the overall flow of time series data.

Learning Multiple Instance Support Vector Machine through Positive Data Distribution (긍정 데이터 분포를 반영한 다중 인스턴스 지지 벡터 기계 학습)

  • Hwang, Joong-Won;Park, Seong-Bae;Lee, Sang-Jo
    • Journal of KIISE
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    • v.42 no.2
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    • pp.227-234
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    • 2015
  • This paper proposes a modified MI-SVM algorithm by considering data distribution. The previous MI-SVM algorithm seeks the margin by considering the "most positive" instance in a positive bag. Positive instances included in positive bags are located in a similar area in a feature space. In order to reflect this characteristic of positive instances, the proposed method selects the "most positive" instance by calculating the distance between each instance in the bag and a pivot point that is the intersection point of all positive instances. This paper suggests two ways to select the "most positive" pivot point in the training data. First, the algorithm seeks the "most positive" pivot point along the current predicted parameter, and then selects the nearest instance in the bag as a representative from the pivot point. Second, the algorithm finds the "most positive" pivot point by using a Diverse Density framework. Our experiments on 12 benchmark multi-instance data sets show that the proposed method results in higher performance than the previous MI-SVM algorithm.