• Tunnel and Underground Space
• /
• v.15 no.1 s.54
• /
• pp.28-38
• /
• 2005

According to the recent development of measurement system utilizing one or a set of boreholes, visualization of the explored underground became to be a major issue. It induced even the introduction of monitoring apparatuses on the borehole wall with multi-function tool, but the usage of these was often limited by where is unfavorable rock condition and a few of engineers can approach. And so, a portable type of borehole camera with only the essential function has been investigated and a few of commercial models about this is recently being applied into the field condition. This paper was based on the monitoring results obtained using a commercial model by Dr. Nakagawa. Discontinuities in rock mass were the topic for the visualization, and it was studied how can visualize their three dimensional distribution and what a numerical formulation is needed and how to understand the visualization result. The numerical formulation was based on the geometric correlation between the dip direction / dip of discontinuous plane and the trend / plunge of borehole, a set of the equation of a plane was induced. As field application of this into two places, it is found that the above visualization methodology will be especially an useful geotechlical tool for analyzing the local distribution of discontinuities.

• Progress in Medical Physics
• /
• v.21 no.1
• /
• pp.93-98
• /
• 2010

The aim of this work was to establish the methodology for event positioning by measuring depth of interaction (DOI) information and to evaluate the system sensitivity and spatial resolution of the new detector for I-125 and Tc-99m imaging. For this purpose, a Monte Carlo simulation tool, DETECT2000 and GATE were used to model the energy deposition and light distribution in the detector and to validate this approach. Our proposed detector module consists of a monolithic CsI(Tl) crystal with dimensions of $50.0{\times}50.0{\times}3.0\;mm^3$. The results of simulation demonstrated that the resolution is less than 1.5 mm for both I-125 and Tc-99m. The main advantage of the proposed detector module is that by using 3 mm thick CsI(Tl) with maximum-likelihood position-estimation (MLPE) method, high resolution I-125 imaging and high sensitivity Tc-99m imaging are possible. In this paper, we proved that our new detector to be a reliable design as a detector for a multi-energy SPECT.

• Journal of KIISE:Computing Practices and Letters
• /
• v.16 no.2
• /
• pp.163-176
• /
• 2010

The representative method to efficiently manage the organization's data is to avoid data duplication through the promotion of sharing and reusing existing data. The systematic structuring of existing data and efficient searching should be supported in order to promote the sharing and reusing of data. Without regard for these points, the data for the system development would be duplicated, which would deteriorate the quality of the data. Data taxonomy provides some methods that can enable the needed data elements to be searched quickly with a systematic order of managing data. This paper proposes that the Origin data taxonomy method can best maximize data sharing, reusing, and consolidation, and it can be used for Meta Data Registry (MDR) and Semantic Web efficiently. The Origin data taxonomy method constructs the data taxonomy structure built upon the intrinsic nature of data, so it can classify the data with independence from business classification. Also, it shows a deployment method for data elements used in various areas according to the Origin data taxonomy structure with a data taxonomic procedure that supports the proposed taxonomy. Based on this case study, the proposed data taxonomy and taxonomic procedure can be applied to real world data efficiently.

• Journal of Distribution Science
• /
• v.15 no.3
• /
• pp.61-72
• /
• 2017

Purpose - The ICT development is affecting the consumer behaviors in selecting channel or distribution system. This study aims to advance the theory on the influence and interaction with omni-channel behaviors. Specifically, analyzing moderating variable is category knowledge that effect between propensity of brand loyalty and its precedence factor which is perceived difference, perceived value, authenticity and consumer-brand relationship. Research design, data, and methodology - The subject of this research is consumers who purchase goods in omni-channel situation. The hypothesis of this research is derived from the literature of the preceding research analysis on brand loyalty, omni-channel and consumer behaviors. This study have constructs that were defined operationally with reference to previous studies, and the research model was designed to figure out the structural relationship among perceived difference, perceived value, authenticity, consumer-brand relationship and brand loyalty. From 2016 Sept. 1 to Dec. 31, a questionnaire survey was performed targeting customers using omni-channel. 327 questionnaire survey had conducted. 316 survey data were used for empirical analysis except data that had missing and wrong value. AMOS(structural equation) was used to confirm the hypothesis which developed by researcher. Results - The results of this study are as follows. First, an authenticity has significant effect on brand loyalty. Second, in the omni-channel situation, but perceived differentiation, perceived value, consumer-brand relationship does not affect brand loyalty. According to this result, it is judged that it is easy to search for information in the situation of omni-channel and integrated decision making is done without distinction between channels. Third, category knowledge has moderating effect between brand loyalty and precedence factors. When the category knowledge level is low, preceding factors have a significant effect on brand loyalty. when the category knowledge level is high, the preceding factors did not have a significant effect on brand loyalty except the authenticity. Conclusions - This study finds out omni-channel's phenomenon is different from other distribution channel phenomenon. In the situation of omni-channel, it is suggested that brand loyalty may be relatively low for a certain brand because it raises the knowledge level of the category. Then this study provides a managerial implications based on the role of the moderate effect on category knowledge, brand loyalty and omni-channel.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.22 no.3
• /
• pp.225-232
• /
• 2004

The human history has progressed closely related to land. Mankind started land administration as a tool of governance to make land the object of imposing taxation as well as developing the land administration as a concept of securing property rights. People have drawn boundary lines on the ground to form a land parcel according to the usage and/or ownership. Furthermore, the land administration has been developed as a registering system of cadastral records fer the public announcement of fixed boundary instead of changeable ground boundary. Currently the citizens demand the provision of accurate and diverse information on the land which is assessed to has high property value encouraged by the rapid development in the post-industrial society today. However, even though the fact that the Korean cadastral registers produced during the Land Investigation Project are still practically in use causes land-related disputes and promotes public mistrust because of the changed boundaries by parcel mutation, the expansion and contraction of map sheets and the quality deterioration and damage of map paper, but the ultimate resolution is not yet made so far. The distance difference between boundary points are compared and analyzed using TS surveying method in the research as a methodology to resolve the boundary inconsistency, the current problem of cadastral records. Consequently, I'd say that the new surveying method of registering the coordinates of real ground boundary has been regarded as more efficient than considering the matter on the map regardless of urban or rural areas.

• Journal of Internet Computing and Services
• /
• v.7 no.2
• /
• pp.37-52
• /
• 2006

A mobile device like ceil phone is the necessity of modern people, of ich con be easily connected to a wireless internet through such a mobile device. The demand for a wireless data communication is growing rapidly. However, agencies have not yet completed standardization of a markup language. Due to the development of the Mobile Device, agencies in this field have provided different data formats with each Mobile Device Platform. Traditionally, contents is hand-tailored to suit the target device. A key problem is that the characteristics and capabilities of the mobile device are too diverse to service the most suitable mobile contents. Because of these problems, the need for a re-usable document description language increases. In this paper, we defined Template file that is common data to service mobile devices. We proposed a method that could be an effective wireless web service though design and the implementation of the Call manager & the XSL Generator. In the methodology, when requesting a wireless internet service, a mobile device finds out markup language and a hardware specification of the mobile device through the Call Manager component supports. The XSL Generator component creates the XSL file dynamically that is the most suitable to a device. Finally, contents is serviced to each device by XSLT. It can generate a wireless page more easily by reusing the existing web contents through such course. Therefore, it can save the time and expense for generating a wireless page.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.18 no.6
• /
• pp.1321-1330
• /
• 2023

This study attempts to address the problem of 3D pose estimation for multiple human objects through a single image generated during the character development process that can be used in augmented reality. In the existing top-down method, all objects in the image are first detected, and then each is reconstructed independently. The problem is that inconsistent results may occur due to overlap or depth order mismatch between the reconstructed objects. The goal of this study is to solve these problems and develop a single network that provides consistent 3D reconstruction of all humans in a scene. Integrating a human body model based on the SMPL parametric system into a top-down framework became an important choice. Through this, two types of collision loss based on distance field and loss that considers depth order were introduced. The first loss prevents overlap between reconstructed people, and the second loss adjusts the depth ordering of people to render occlusion inference and annotated instance segmentation consistently. This method allows depth information to be provided to the network without explicit 3D annotation of the image. Experimental results show that this study's methodology performs better than existing methods on standard 3D pose benchmarks, and the proposed losses enable more consistent reconstruction from natural images.

• Journal of Intelligence and Information Systems
• /
• v.26 no.1
• /
• pp.1-21
• /
• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.

• Journal of Intelligence and Information Systems
• /
• v.22 no.2
• /
• pp.57-79
• /
• 2016

It is a rising trend that the number of users using one of the social media channels, the Social Network Service, so called the SNS, is getting increased. As per to this social trend, more companies have interest in this networking platform and start to invest their funds in it. It has received much attention as a tool spreading and expanding the message that a company wants to deliver to its customers and has been recognized as an important channel in terms of the relationship marketing with them. The environment of media that is radically changing these days makes possible for companies to approach their customers in various ways. Particularly, the social network service, which has been developed rapidly, provides the environment that customers can freely talk about products. For companies, it also works as a channel that gives customized information to customers. To succeed in the online environment, companies need to not only build the relationship between companies and customers but focus on the relationship between customers as well. In response to the online environment with the continuous development of technology, companies have tirelessly made the novel marketing strategy. Especially, as the one-to-one marketing to customers become available, it is more important for companies to maintain the relationship marketing with their customers. Among many SNS, Facebook, which many companies use as a communication channel, provides a fan page service for each company that supports its business. Facebook fan page is the platform that the event, information and announcement can be shared with customers using texts, videos, and pictures. Companies open their own fan pages in order to inform their companies and businesses. Such page functions as the websites of companies and has a characteristic of their brand communities such as blogs as well. As Facebook has become the major communication medium with customers, companies recognize its importance as the effective marketing channel, but they still need to investigate their business performances by using Facebook. Although there are infinite potentials in Facebook fan page that even has a function as a community between users, which other platforms do not, it is incomplete to regard companies' Facebook fan pages as communities and analyze them. In this study, it explores the relationship among customers through the network of the Facebook fan page users. The previous studies on a company's Facebook fan page were focused on finding out the effective operational direction by analyzing the use state of the company. However, in this study, it draws out the structural variable of the network, which customer committment can be measured by applying the social network analysis methodology and investigates the influence of the structural characteristics of network on the business performance of companies in an empirical way. Through each company's Facebook fan page, the network of users who engaged in the communication with each company is exploited and it is the one-mode undirected binary network that respectively regards users and the relationship of them in terms of their marketing activities as the node and link. In this network, it draws out the structural variable of network that can explain the customer commitment, who pressed "like," made comments and shared the Facebook marketing message, of each company by calculating density, global clustering coefficient, mean geodesic distance, diameter. By exploiting companies' historical performance such as net income and Tobin's Q indicator as the result variables, this study investigates influence on companies' business performances. For this purpose, it collects the network data on the subjects of 54 companies among KOSPI-listed companies, which have posted more than 100 articles on their Facebook fan pages during the data collection period. Then it draws out the network indicator of each company. The indicator related to companies' performances is calculated, based on the posted value on DART website of the Financial Supervisory Service. From the academic perspective, this study suggests a new approach through the social network analysis methodology to researchers who attempt to study the business-purpose utilization of the social media channel. From the practical perspective, this study proposes the more substantive marketing performance measurements to companies performing marketing activities through the social media and it is expected that it will bring a foundation of establishing smart business strategies by using the network indicators.

• Journal of Intelligence and Information Systems
• /
• v.26 no.3
• /
• pp.149-169
• /
• 2020

"The Urban Renewal New Deal project", one of the government's major national projects, is about developing underdeveloped areas by investing 50 trillion won in 100 locations on the first year and 500 over the next four years. This project is drawing keen attention from the media and local governments. However, the project model which fails to reflect the original characteristics of the area as it divides project area into five categories: "Our Neighborhood Restoration, Housing Maintenance Support Type, General Neighborhood Type, Central Urban Type, and Economic Base Type," According to keywords for successful urban regeneration in Korea, "resident participation," "regional specialization," "ministerial cooperation" and "public-private cooperation", when local governments propose urban regeneration projects to the government, they can see that it is most important to accurately understand the characteristics of the city and push ahead with the projects in a way that suits the characteristics of the city with the help of local residents and private companies. In addition, considering the gentrification problem, which is one of the side effects of urban regeneration projects, it is important to select and implement urban regeneration types suitable for the characteristics of the area. In order to supplement the limitations of the 'Urban Regeneration New Deal Project' methodology, this study aims to propose a system that recommends urban regeneration types suitable for urban regeneration sites by utilizing various machine learning algorithms, referring to the urban regeneration types of the '2025 Seoul Metropolitan Government Urban Regeneration Strategy Plan' promoted based on regional characteristics. There are four types of urban regeneration in Seoul: "Low-use Low-Level Development, Abandonment, Deteriorated Housing, and Specialization of Historical and Cultural Resources" (Shon and Park, 2017). In order to identify regional characteristics, approximately 100,000 text data were collected for 22 regions where the project was carried out for a total of four types of urban regeneration. Using the collected data, we drew key keywords for each region according to the type of urban regeneration and conducted topic modeling to explore whether there were differences between types. As a result, it was confirmed that a number of topics related to real estate and economy appeared in old residential areas, and in the case of declining and underdeveloped areas, topics reflecting the characteristics of areas where industrial activities were active in the past appeared. In the case of the historical and cultural resource area, since it is an area that contains traces of the past, many keywords related to the government appeared. Therefore, it was possible to confirm political topics and cultural topics resulting from various events. Finally, in the case of low-use and under-developed areas, many topics on real estate and accessibility are emerging, so accessibility is good. It mainly had the characteristics of a region where development is planned or is likely to be developed. Furthermore, a model was implemented that proposes urban regeneration types tailored to regional characteristics for regions other than Seoul. Machine learning technology was used to implement the model, and training data and test data were randomly extracted at an 8:2 ratio and used. In order to compare the performance between various models, the input variables are set in two ways: Count Vector and TF-IDF Vector, and as Classifier, there are 5 types of SVM (Support Vector Machine), Decision Tree, Random Forest, Logistic Regression, and Gradient Boosting. By applying it, performance comparison for a total of 10 models was conducted. The model with the highest performance was the Gradient Boosting method using TF-IDF Vector input data, and the accuracy was 97%. Therefore, the recommendation system proposed in this study is expected to recommend urban regeneration types based on the regional characteristics of new business sites in the process of carrying out urban regeneration projects."