• The Journal of Art Theory & Practice
• /
• no.2
• /
• pp.147-168
• /
• 2004

This study examined the role of interpretation with various practices in art museums to seek a new meaning and a concept of art museum today. The exploration of interpretation would he a starting point to discuss about on art museums with professionals in each art-related field. While museums recognize the concept of interpretation and the scope of the functions in different levels, the study focused on the practices of collecting and exhibiting that will entrust the museum new realms of activities toward the audience. In particular, its emphases are set force on the information on the collections via the museum's web sites, interpretation policies, and theories and methodologies in exhibition development. Art museum websites well reflect how museums utilize the new medium to enhance the understanding of art works by providing in-depth art historical information, comprehensive contexts, and subject/concept based search methods. In recent decades, these have enacted changes to expand dimensions of interpretive functions in most museums, particularly in the United States and others. In an administrative perspective, Tate Gallery Interpretation Policy became an good example how an art museum put its interpretation philosophy as the basis of interpreting collection and public programs. Tate established functions of intrepretation and education not only within a task-based team but also as an intrer-divisional coorperation to provide an interpretation scheme of information provisions such as guide brochure, audio tour, multimedia content, and library. New environment and trends of museum exhibition, and its development processes stem from communication theories, object interpretation philosophy, display strategies, and various evaluation techniques through audiences, with the communication theories of Shannon and Weaver, Berlo's SMCR(Source-Message-Channel-Receiver) models were perceived as to understand the mechanism to communicate museum exhibits to visitors Suzan vogel's insight into object display strategy helped to conceive the mechanism of object recontextualization. She emphasized that the museum's practice to construe opinions and impressions through object display should be discreet and critical, therefore, the professionals to plan the exhibition should reveal the intention and their practices. For a prevailing new methodology from the field, the interpretive exhibition development processes are articulated as the front-end, formative, and summative evaluation, futhermore the team process in industrial product management models was adapted. These have turned out to be more interactive with visitors and effective to communicate the exhibition concepts and messages, hence resulting in enriched museum experiences. Finally the study concluded that understanding the aspects of interpretation should help art museums to set a framework for current practices to expand its public dimension. It can provide curators with a critical view to website planning and its content. And obviously, the interpretive exhibition development methodology will lead museum exhibition developers to be skilled in its current approaches to thematic exhibition concerning diverse subjects and topics.

• Journal of Korea Multimedia Society
• /
• v.8 no.10
• /
• pp.1369-1382
• /
• 2005

Vehicle segmentation, which extracts vehicle areas from road scenes, is one of the fundamental opera tions in lots of application areas including Intelligent Transportation Systems, and so on. We present a vehicle segmentation approach for still images captured from outdoor CCD cameras mounted on the supporting poles. We first divided the input image into a set of two-dimensional grids and then calculate the feature values of the edges for each grid. Through analyzing the feature values statistically, we can find the optimal rectangular grid area of the vehicle. Our preprocessing process calculates the statistics values for the feature values from background images captured under various circumstances. For a car image, we compare its feature values to the statistics values of the background images to finally decide whether the grid belongs to the vehicle area or not. We use dynamic programming technique to find the optimal rectangular gird area from these candidate grids. Based on the statistics analysis and global search techniques, our method is more systematic compared to the previous methods which usually rely on a kind of heuristics. Additionally, the statistics analysis achieves high reliability against noises and errors due to brightness changes, camera tremors, etc. Our prototype implementation performs the vehicle segmentation in average 0.150 second for each of $1280\times960$ car images. It shows $97.03\%$ of strictly successful cases from 270 images with various kinds of noises.

• Journal of Korea Multimedia Society
• /
• v.10 no.11
• /
• pp.1367-1383
• /
• 2007

A sensor network consists of a network of sensors that can perform computation and also communicate with each other through wireless communication. Some important characteristics of sensor networks are that the network should be self administered and the power efficiency should be greatly considered due to the fact that it uses battery power. In sensor networks, when large amounts of various stream data is produced and multiple queries need to be processed simultaneously, the power efficiency should be maximized. This work proposes a technique to create an index on multiple monitoring queries so that the multi-query processing performance could be increased and the memory and power could be efficiently used. The proposed SMILE tree modifies and combines the ideas of spatial indexing techniques such as k-d trees and R+-trees. The k-d tree can divide the dimensions at each level, while the R+-tree improves the R-tree by dividing the space into a hierarchical manner and reduces the overlapping areas. By applying the SMILE tree on multiple queries and using it on stream data in sensor networks, the response time for finding an indexed query takes in some cases 50% of the time taken for a linear search to find the query.

• The Journal of Industrial Distribution & Business
• /
• v.9 no.5
• /
• pp.63-72
• /
• 2018

Purpose - This work analyzes, in detail, the specification of vector error correction model (VECM) and thus examines the relationships and impact among seven economic variables for USA - balance on current account (BCA), index of stock (STOCK), gross domestic product (GDP), housing price indices (HOUSING), a measure of the money supply that includes total currency as well as large time deposits, institutional money market funds, short-term repurchase agreements and other larger liquid assets (M3), real rate of interest (IR_REAL) and household credits (LOAN). In particular, we search for the main explanatory variables that have an effect on stock and real estate market, respectively and investigate the causal and dynamic associations between them. Research design, data, and methodology - We perform the time series vector error correction model to infer the dynamic relationships among seven variables above. This work employs the conventional augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) unit root techniques to test for stationarity among seven variables under consideration, and Johansen cointegration test to specify the order or the number of cointegration relationship. Granger causality test is exploited to inspect for causal relationship and, at the same time, impulse response function and variance decomposition analysis are checked for both short-run and long-run association among the seven variables by EViews 9.0. The underlying model was analyzed by using 108 realizations from Q1 1990 to Q4 2016 for USA. Results - The results show that all the seven variables for USA have one unit root and they are cointegrated with at most five and three cointegrating equation for USA. The vector error correction model expresses a long-run relationship among variables. Both IR_REAL and M3 may influence real estate market, and GDP does stock market in USA. On the other hand, GDP, IR_REAL, M3, STOCK and LOAN may be considered as causal factors to affect real estate market. Conclusions - The findings indicate that both stock market and real estate market can be modelled as vector error correction specification for USA. In addition, we can detect causal relationships among variables and compare dynamic differences between countries in terms of stock market and real estate market.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.43 no.6
• /
• pp.138-149
• /
• 2015

In order to search for the reasonable planning directions for representing traditional landscape, this study conducted the comparative analysis of the designs on the panels and their constructions from both winners of "The Landscape Design Competitions for City Infrastructure of Minlak(2) District in Uijeongbu" and "The Design Competition for Dongtan(2) District Land Development Phase 1". The representing targets and views, the composition and placement of representing space, the design of representing facilities and landscape planting were examined based on the text, master plans, elevations and cross sections, diagrams, images, and perspective drawings proposed from the competition panels. Then, the landscape constructions were reviewed. The results are as follows: First, the types of the representing targets and views are the agricultural landscape, as the local landscape of target area, which are divided into the life space of a traditional village, the traditional water space, and the traditional culture. Second, as to the composition and placement of representing space, the traditional theme spaces are formulated considering the surrounding land use and the local cultural heritage. However, some spaces were changed to the exercise space or convenient facility spaces required in a neighborhood park. Third, in the case of the representing facilities, a round island in the square pond, a traditional pavilion and Hwagye(terraced flower bed) were made without the facilities designed creatively. Fourth, the application of traditional planting techniques was focused on planting trees in the village forest on an island in the square pond and on Hwagye. Fifth, the traditional representing work has gradually advanced with the selection of subject and experimental facility designs based on the professional references. Sixth, the choice of the realizable subject, the expertise for information analysis and the creative design of the traditional facility are required in the future.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.21 no.3
• /
• pp.523-529
• /
• 2017

In this paper, we propose an efficient sphere decoding scheme that reduces computational complexity by combining receive and transmit ordering techniques in generalized spatial modulation systems, where the indexes of activated transmit antennas as well as the transmit symbols are exploited to transfer information to the receiver. In this scheme, the receive signals are optimally ordered so that the calculation for a candidate solution outside the sphere is terminated early to lower the computational complexity. In addition, the transmit ordering technique is applied to first search for candidate symbols and activated antennas having higher probabilities to further reduce the computational complexity. Simulation results show that the proposed doubly ordered sphere decoding scheme provides the same bit error rate performance with the conventional sphere decoding method and the sphere decoder employing only the receive ordering technique while it requires lower computational complexity.

• The KIPS Transactions:PartB
• /
• v.12B no.1 s.97
• /
• pp.47-56
• /
• 2005

A moving object has a various features that its spatial location, shape, and size are changed as time goes. In addition, the moving object has both temporal feature and spatial feature. It is one of the highly interested feature information in video data. In this paper, we propose an efficient content-based multimedia information retrieval system, so tailed ECoMOT which enables user to retrieve video data by using a trajectory information of moving objects in video data. The ECoMOT includes several novel techniques to achieve content-based retrieval using moving objects' trajectories : (1) Muitiple trajectory modeling technique to model the multiple trajectories composed of several moving objects; (2) Multiple similar trajectory retrieval technique to retrieve more similar trajectories by measuring similarity between a given two trajectories composed of several moving objects; (3) Superimposed signature-based trajectory indexing technique to effectively search corresponding trajectories from a large trajectory databases; (4) convenient trajectory extraction, query generation, and retrieval interface based on graphic user interface

• Journal of the Korean Chemical Society
• /
• v.51 no.5
• /
• pp.459-470
• /
• 2007

The structural equation modeling techniques were used to assess a model of chemistry learning strategy based on self-handicapping tendency and goal orientation. Data were collected during chemistry lessons in two high schools. In the optimal model II-2 of this research, the self-handicapping tendency was negatively related to the use of self-efficacy. The learning goal was positively related to the use of self-efficacy and to learning strategy. The performance- approach goal was positively related to self-efficacy but presented an negative relationship to learning strategy. The performance-avoidance goal was negatively related to self-efficacy but presented an positive relationship to learning strategy. Besides affecting the learning strategy through self-efficacy indirectly, the learning goal, performance-approach goal, and performance-avoidance goal affected learning strategy directly. The self-handicapping tendency and performance- avoidance goal were a negative predictors of self-efficacy, but the learning goal and performance-approach goal were a positive predictors. And the self-efficacy affected learning strategy positively. The implications of these findings for learning strategy in chemistry are discussed. Although the paths model of relationships of the motivations to learn and learning strategies in chemistry education as mentioned above is established, the more systematic search for the higher self-efficacy and learning strategy in different courses and curriculums may be needed.

• Journal of The Korean Association For Science Education
• /
• v.35 no.3
• /
• pp.383-393
• /
• 2015

This study analyzed the 6th grade elementary science textbook 'Science stories' reading process of students by utilizing eye movement tracking techniques. Participants read 3 articles in the new experimental science textbooks and solved 9 problems about each article. By understanding and academic achievement results, participants were divided into high-groups, middle-groups, and low-groups. The results of eye movement characteristics of the high-groups and low-groups had the following differences. Number of fixations and number of regressions were higher in high-groups. Average fixation duration and average regressive fixation duration were longer in low-groups. Fixation time for the key sentence of the article was longer in high-groups. Analysis of a scan path and post-interview, high-groups had frequent regression between sentences and they knew where the core of the article is and paid much attention there. In contrast low-groups are sequentially read most articles and some of them had a leap of abnormal range. Problem-solving approach is also different between groups. In conclusion reading style is associated with the science stories comprehension and students who had more regressions, much core search process, effective attention distribution, high concentration showed better understanding results. Also words or sentences used in textbooks are associated with science stories comprehension.

• The Journal of Bigdata
• /
• v.4 no.2
• /
• pp.23-34
• /
• 2019

Recently, the crime that utilizes the digital platform is continuously increasing. About 140,000 cases occurred in 2015 and about 150,000 cases occurred in 2016. Therefore, it is considered that there is a limit handling those online crimes by old-fashioned investigation techniques. Investigators' manual online search and cognitive investigation methods those are broadly used today are not enough to proactively cope with rapid changing civil crimes. In addition, the characteristics of the content that is posted to unspecified users of social media makes investigations more difficult. This study suggests the site-based collection and the Open API among the content web collection methods considering the characteristics of the online media where the infringement crimes occur. Since illegal content is published and deleted quickly, and new words and alterations are generated quickly and variously, it is difficult to recognize them quickly by dictionary-based morphological analysis registered manually. In order to solve this problem, we propose a tokenizing method in the existing dictionary-based morphological analysis through WPM (Word Piece Model), which is a data preprocessing method for quick recognizing and responding to illegal contents posting online infringement crimes. In the analysis of data, the optimal precision is verified through the Vote-based ensemble method by utilizing a classification learning model based on supervised learning for the investigation of illegal contents. This study utilizes a sorting algorithm model centering on illegal multilevel business cases to proactively recognize crimes invading the public economy, and presents an empirical study to effectively deal with social data collection and content investigation.