• Journal of the Korean Association of Geographic Information Studies
• /
• 제20권1호
• /
• pp.1-14
• /
• 2017

A land cover map provides basic information to help understand the current state of a region, but its utilization in the ecological research field has deteriorated due to limited temporal and spatial resolutions. The purpose of this study was to investigate the possibility of using a land cover map with data based on high resolution images acquired by UAV. Using the UAV, 10.5 cm orthoimages were obtained from the $2.5km^2$ study area, and land cover maps were obtained from object-based and pixel-based classification for comparison and analysis. From accuracy verification, classification accuracy was shown to be high, with a Kappa of 0.77 for the pixel-based classification and a Kappa of 0.82 for the object-based classification. The overall area ratios were similar, and good classification results were found in grasslands and wetlands. The optimal image segmentation weights for object-based classification were Scale=150, Shape=0.5, Compactness=0.5, and Color=1. Scale was the most influential factor in the weight selection process. Compared with the pixel-based classification, the object-based classification provides results that are easy to read because there is a clear boundary between objects. Compared with the land cover map from the Ministry of Environment (subdivision), it was effective for natural areas (forests, grasslands, wetlands, etc.) but not developed areas (roads, buildings, etc.). The application of an object-based classification method for land cover using UAV images can contribute to the field of ecological research with its advantages of rapidly updated data, good accuracy, and economical efficiency.

• The Journal of Society for e-Business Studies
• /
• 제23권1호
• /
• pp.65-88
• /
• 2018

This case is an analysis of how a late comer to the market of online dating in Korea, Dorsia, successfully develops its services called Amanda. Since 2010, the online dating market in Korea has been fast growing. Despite its short history, many corporations have attempted to make success in the market. But most of them were unable to gain foothold in a market where the first comer had a huge advantage. Amanda, however, has provided differentiated services to great success in a short period. This paper conducted a semi-structured interview with major executives of Dorsia to acquire data which were then used to interpret based on the theories of business management and psychology. This study presents a strategic insight into how competitiveness can be gained in internet-based businesses in the online dating market, as well as those in markets that have similar traits. Moreover, by identifying issues that need to be addressed in order for Amanda to continue its growth, the study seeks to simultaneously review the issues that need resolution related to online commerce, as well as the great potential of online commerce.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• 제43권1호
• /
• pp.17-26
• /
• 2006

This paper proposes a novel hidden Markov model (HMM)-based gesture recognition method and applies it to an HCI to control a computer game. The novelty of the proposed method is two-fold: 1) the proposed method uses a continuous streaming of human motion as the input to the HMM instead of isolated data sequences or pre-segmented sequences of data and 2) the gesture segmentation and recognition are performed simultaneously. The proposed method consists of a single HMM composed of thirteen gesture-specific HMMs that independently recognize certain gestures. It takes a continuous stream of pose symbols as an input, where a pose is composed of coordinates that indicate the face, left hand, and right hand. Whenever a new input Pose arrives, the HMM continuously updates its state probabilities, then recognizes a gesture if the probability of a distinctive state exceeds a predefined threshold. To assess the validity of the proposed method, it was applied to a real game, Quake II, and the results demonstrated that the proposed HMM could provide very useful information to enhance the discrimination between different classes and reduce the computational cost.

• Journal of Korean Society for Geospatial Information Science
• /
• 제23권4호
• /
• pp.25-33
• /
• 2015

The study of ecosystem assessment(ES) is based on land cover information, and primarily it is performed at the global scale. However, these results as data for decision making have a limitation at the aspects of range and scale to solve the regional issue. Although the Ministry of Environment provides available land cover data at the regional scale, it is also restricted in use due to the intrinsic limitation of on screen digitizing method and temporal and spatial difference. This study of objective is to generate UAV land cover map. In order to classify the imagery, we have performed resampling at 5m resolution using UAV imagery. The results of object-based image segmentation showed that scale 20 and merge 34 were the optimum weight values for UAV imagery. In the case of RapidEye imagery;we found that the weight values;scale 30 and merge 30 were the most appropriate at the level of land cover classes for sub-category. We generated land cover imagery using example-based classification method and analyzed the accuracy using stratified random sampling. The results show that the overall accuracies of RapidEye and UAV classification imagery are each 90% and 91%.

• Economic and Environmental Geology
• /
• 제41권6호
• /
• pp.747-761
• /
• 2008

In order to experiment the acoustic remote classification of seabed sediment, we achieved ground-truth data(i.e. video and grab samples, etc.) and developed post-processing for automatic classification procedure on the basis of 300 kHz MultiBeam Echo Sounder(MBES) backscattering data, which was acquired using KONGBERG Simrad EM3000 at Sock-Cho Port, East Sea of South Korea. Sonar signal and its classification performance were identified with geo-referenced video imagery with the aid of GIS (Geographic Information System). The depth range of research site was from 5 m to 22.7 m, and the backscattering amplitude showed from -36dB to -15dB. The mean grain sizes of sediment from equi-distanced sampling site(50 m interval) varied from 2.86$(\phi)$ to 0.88(\phi). To acquire the main feature for the seabed classification from backscattering amplitude of MBES, we evaluated the correlation factors between the backscattering amplitude and properties of sediment samples. The performance of seabed remote classification proposed was evaluated with comparing the correlation of human expert segmentation to automatic algorithm results. The cross-model perception error ratio on automatic classification algorithm shows 8.95% at rocky bottoms, and 2.06% at the area representing low mean grain size.

• Journal of the Korea Society of Computer and Information
• /
• 제19권2호
• /
• pp.193-200
• /
• 2014

Due to the advent of ubiquitous computing environment, it is becoming a part of our common life style. And tremendous information is cumulated rapidly. In these trends, it is becoming a very important technology to find out exact information in a large data to present users. Collaborative filtering is the method based on other users' preferences, can not only reflect exact attributes of user but also still has the problem of sparsity and scalability, though it has been practically used to improve these defects. In this paper, we propose clustering method by user's features based on SOM for predicting purchase pattern in u-Commerce. it is necessary for us to make the cluster with similarity by user's features to be able to reflect attributes of the customer information in order to find the items with same propensity in the cluster rapidly. The proposed makes the task of clustering to apply the variable of featured vector for the user's information and RFM factors based on purchase history data. To verify improved performance of proposing system, we make experiments with dataset collected in a cosmetic internet shopping mall.

• Journal of the Korean BIBLIA Society for library and Information Science
• /
• 제31권1호
• /
• pp.257-284
• /
• 2020

The purpose of this study is to derive differentiation strategy through strategy competition analysis on public libraries in order to enhance the competitiveness and efficiency of libraries. To that end, this study conducted a status analysis, management resources analysis, external and internal environment analysis on four public libraries located in Jung-gu, Incheon to identify the situation of strategy competition, and conducted a competitor analysis, customer segment analysis, and customer value analysis of four public libraries through various library related statistical data, national library operation evaluation data, library user satisfaction surveys, and interview with chief librarian and senior librarians. As the result, this study suggests three differentiation strategies by library. First of all, the four public libraries need to provide customized services targeting different target users within the region. Secondly, public libraries need to develop active library services that directly visit passive users, who are information have-nots, considering geographical accessibility and the composition of the population in the region. Last, public libraries should form a cultural community that cooperate with the local community and develop various programs that reflect the identity of the region.

• Journal of Intelligence and Information Systems
• /
• 제16권2호
• /
• pp.109-128
• /
• 2010

The purpose of our research is to figure out the 'non-financial value' of consumers applying networks amongst consumer groups, the data-based marketing strategy to the analysis and delve into the ways for enhancing effectives in marketing activities by adapting the value to the marketing. To verify the authenticity of the points, we did the empirical test on the consumer group using 'the Essence Cosmetics Products' of high involvement that is deeply affected by consumer perceptions and the word-of-mouth activities. 1) The empirical analysis reveals the following features. First, the segmented market for 'Essence Consumer' is composed of several independent networks, each network shows to have the consumers that is high degree centrality and closeness centrality. Second, the result proves the authenticity of the non-financial value for boosting corporate profits by the high degree centrality and closeness centrality consumer's word-of-mouth activities. Lastly, we verify that there lies a difference in the network structure of 'Essence Cosmetics Market'per each product origin(domestic, foreign) and demographic characteristics. It does, therefore, indicate the need to consider the features applying mutually complementary for the network targeting.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• 제20권2호
• /
• pp.95-111
• /
• 2021

As the population decreases in an aging society, the average age of drivers increases. Accordingly, the elderly at high risk of being in an accident need autonomous-driving vehicles. In order to secure driving safety on the road, several technologies to respond to various obstacles are required in those vehicles. Among them, technology is required to recognize static obstacles, such as poor road conditions, as well as dynamic obstacles, such as vehicles, bicycles, and people, that may be encountered while driving. In this study, we propose a deep neural network algorithm capable of simultaneously detecting these two types of obstacle. For this algorithm, we used 1,418 road images and produced annotation data that marks seven categories of dynamic obstacles and labels images to indicate road damage. As a result of training, dynamic obstacles were detected with an average accuracy of 46.22%, and road surface damage was detected with a mean intersection over union of 74.71%. In addition, the average elapsed time required to process a single image is 89ms, and this algorithm is suitable for personal mobility vehicles that are slower than ordinary vehicles. In the future, it is expected that driving safety with personal mobility vehicles will be improved by utilizing technology that detects road obstacles.

• Journal of vocational education research
• /
• 제37권5호
• /
• pp.55-78
• /
• 2018

The purpose of this study is to investigate the recognition of the professionalism required for strengthening the effective career guidance capacity of the secondary career teachers who are required to prepare for the coming fourth industrial revolution era. Based on these research objectives, we derived the required roles(8), the required competencies(20), and the contents(23) for enhancing professionalism by the required competencies, based on this, the questionnaire was composed and 217 respondents were collected and analyzed. First, the t-test was conducted to confirm the statistically significant difference between the current level and the important level of each content item by each role. As a result, it was found that in all roles except role of 'administrator' The t-value is statistically significant and the t-value distribution is high. Second, the demand value calculation and the priority ranking using the Borich demand calculation formula were found, and as a result, the directionality between the t value and the Borich demand was in agreement. Third, as a result of prioritizing using the Locus for Focus model, the contents of all 5 (middle school 7, high school 2) education contents were given priority. Fourth, three middle schools and five high schools were derived from the subordinate. Finally, we confirmed the relevance of the contents of education to actual educational necessity. Although this study has many limitations and limitations due to the fact that there are few prior data due to the segmentation of the subject related to the 4th Industrial Revolution and career guidance, it is necessary to develop educational training program I hope to be able to use it as basic data of various follow-up studies and make some suggestions.