• Journal of Energy Engineering
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• v.23 no.2
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• pp.125-148
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• 2014

This paper performs a historical analysis on the various factors contributing to the current carbon lock-in of Korean electricity industry by using techo-institutional complex. The possibilities of the industry's carbon lock-out toward more sustainable development are also investigated. It turns out that market, firm, consumer, and government factors are all responsible for the development of the carbon lock-in of Korean power industry; the Korean government consistently favoring large power plants based on the economy of scale; below-cost electricity tariff; inflation policy to suppress increases in power price; rapid demand growth in summer and winter seasons; rigidities of electricity tariff; and expansion of gas-fired and imported coal-fired large power plants. On the other hand, except for nuclear power generation and smart grid, environment laws and new and renewable energy laws are the other remaining factors contributing to the carbon lock-out. Considering three key points that Korea is an export-oriented economy, the generation mix is the most critical factor to decide the amounts of carbon emission in the power industry, and the share of industry and commercial power consumption is over 85%, it is unlikely that Korea will achieve the carbon lock-out of power industry in the near future. Therefore, there are needs for more integrated approaches from market, firm, consumer, and government all together in order to achieve the carbon lock-out in the electricity industry. Firstly, from the market perspective, it is necessary to persue more active new and renewable energy penetration and to guarantee consumer choices by mitigating the incumbent's monopoly power as in the OECD countries. Secondly, from the firm perspective, the promotion of distributed energy system is urgent, which includes new and renewable resources and demand resources. Thirdly, from the consumer perspective, more green choices in the power tariff and customer awareness on the carbon lock-out are needed. Lastly, the government shall urgently improve power planning frameworks to include the various externalities that were not properly reflected in the past such as environmental and social conflict costs.

• Geophysics and Geophysical Exploration
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• v.23 no.1
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• pp.22-37
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• 2020

We analyze the comprehensive three-dimensional (3D) magnetic structure characteristics from the seafloor to the deep layer of the Tofua Arc (TA) 12 seamount in the Tonga Arc, Southwestern Pacific, using bathymetric and geomagnetic data, and magnetization vector inversion (MVI) results. The seafloor features surrounding TA 12 highlight a NW-SE-oriented elliptical caldera at the summit of the seamount, two small cones in the depressed area. A large-scale sea valley is present on the western flank of the seamount, extending from these caldera cones to the southwestern base of the seamount. TA 12 seamount exhibits a low magnetic anomaly in the caldera depression, whereas a high magnetic anomaly is observed surrounding the low magnetic anomaly across the caldera summit. It is therefore presumed that there may be a strong magnetic material distribution or magma intrusion in the caldera. The 3D MVI results show that the high anomaly zones are mainly present in the surrounding slopes of the seamount from the seafloor to the -3,000 m (below the seafloor) level, with the magnetic susceptibility intensity increasing as the seafloor level increases at the caldera depression. However, small high anomaly zones are present across the study area near the seafloor level. Therefore, we expect that the magma ascent in TA 12 seamount migrated from the flanks to the depression area. Furthermore, we assume that the complex magnetic distribution near the seafloor is due to the remnant magnetization.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.145-154
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• 2022

Automatic Target Recognition (ATR) technology is emerging as a core technology of Future Combat Systems (FCS). Conventional ATR is performed based on IMINT (image information) collected from the SAR sensor, and various image-based deep learning models are used. However, with the development of IT and sensing technology, even though data/information related to ATR is expanding to HUMINT (human information) and SIGINT (signal information), ATR still contains image oriented IMINT data only is being used. In complex and diversified battlefield situations, it is difficult to guarantee high-level ATR accuracy and generalization performance with image data alone. Therefore, we propose a knowledge graph-based ATR method that can utilize image and text data simultaneously in this paper. The main idea of the knowledge graph and deep model-based ATR method is to convert the ATR image and text into graphs according to the characteristics of each data, align it to the knowledge graph, and connect the heterogeneous ATR data through the knowledge graph. In order to convert the ATR image into a graph, an object-tag graph consisting of object tags as nodes is generated from the image by using the pre-trained image object recognition model and the vocabulary of the knowledge graph. On the other hand, the ATR text uses the pre-trained language model, TF-IDF, co-occurrence word graph, and the vocabulary of knowledge graph to generate a word graph composed of nodes with key vocabulary for the ATR. The generated two types of graphs are connected to the knowledge graph using the entity alignment model for improvement of the ATR performance from images and texts. To prove the superiority of the proposed method, 227 documents from web documents and 61,714 RDF triples from dbpedia were collected, and comparison experiments were performed on precision, recall, and f1-score in a perspective of the entity alignment..

• Asia pacific journal of information systems
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• v.21 no.2
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• pp.89-116
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• 2011

In collaborative tagging systems such as Delicious.com and Flickr.com, users assign keywords or tags to their uploaded resources, such as bookmarks and pictures, for their future use or sharing purposes. The collection of resources and tags generated by a user is called a personomy, and the collection of all personomies constitutes the folksonomy. The most significant need of the folksonomy users Is to efficiently find useful resources or experts on specific topics. An excellent ranking algorithm would assign higher ranking to more useful resources or experts. What resources are considered useful In a folksonomic system? Does a standard superior to frequency or freshness exist? The resource recommended by more users with mere expertise should be worthy of attention. This ranking paradigm can be implemented through a graph-based ranking algorithm. Two well-known representatives of such a paradigm are Page Rank by Google and HITS(Hypertext Induced Topic Selection) by Kleinberg. Both Page Rank and HITS assign a higher evaluation score to pages linked to more higher-scored pages. HITS differs from PageRank in that it utilizes two kinds of scores: authority and hub scores. The ranking objects of these pages are limited to Web pages, whereas the ranking objects of a folksonomic system are somewhat heterogeneous(i.e., users, resources, and tags). Therefore, uniform application of the voting notion of PageRank and HITS based on the links to a folksonomy would be unreasonable, In a folksonomic system, each link corresponding to a property can have an opposite direction, depending on whether the property is an active or a passive voice. The current research stems from the Idea that a graph-based ranking algorithm could be applied to the folksonomic system using the concept of mutual Interactions between entitles, rather than the voting notion of PageRank or HITS. The concept of mutual interactions, proposed for ranking the Semantic Web resources, enables the calculation of importance scores of various resources unaffected by link directions. The weights of a property representing the mutual interaction between classes are assigned depending on the relative significance of the property to the resource importance of each class. This class-oriented approach is based on the fact that, in the Semantic Web, there are many heterogeneous classes; thus, applying a different appraisal standard for each class is more reasonable. This is similar to the evaluation method of humans, where different items are assigned specific weights, which are then summed up to determine the weighted average. We can check for missing properties more easily with this approach than with other predicate-oriented approaches. A user of a tagging system usually assigns more than one tags to the same resource, and there can be more than one tags with the same subjectivity and objectivity. In the case that many users assign similar tags to the same resource, grading the users differently depending on the assignment order becomes necessary. This idea comes from the studies in psychology wherein expertise involves the ability to select the most relevant information for achieving a goal. An expert should be someone who not only has a large collection of documents annotated with a particular tag, but also tends to add documents of high quality to his/her collections. Such documents are identified by the number, as well as the expertise, of users who have the same documents in their collections. In other words, there is a relationship of mutual reinforcement between the expertise of a user and the quality of a document. In addition, there is a need to rank entities related more closely to a certain entity. Considering the property of social media that ensures the popularity of a topic is temporary, recent data should have more weight than old data. We propose a comprehensive folksonomy ranking framework in which all these considerations are dealt with and that can be easily customized to each folksonomy site for ranking purposes. To examine the validity of our ranking algorithm and show the mechanism of adjusting property, time, and expertise weights, we first use a dataset designed for analyzing the effect of each ranking factor independently. We then show the ranking results of a real folksonomy site, with the ranking factors combined. Because the ground truth of a given dataset is not known when it comes to ranking, we inject simulated data whose ranking results can be predicted into the real dataset and compare the ranking results of our algorithm with that of a previous HITS-based algorithm. Our semantic ranking algorithm based on the concept of mutual interaction seems to be preferable to the HITS-based algorithm as a flexible folksonomy ranking framework. Some concrete points of difference are as follows. First, with the time concept applied to the property weights, our algorithm shows superior performance in lowering the scores of older data and raising the scores of newer data. Second, applying the time concept to the expertise weights, as well as to the property weights, our algorithm controls the conflicting influence of expertise weights and enhances overall consistency of time-valued ranking. The expertise weights of the previous study can act as an obstacle to the time-valued ranking because the number of followers increases as time goes on. Third, many new properties and classes can be included in our framework. The previous HITS-based algorithm, based on the voting notion, loses ground in the situation where the domain consists of more than two classes, or where other important properties, such as "sent through twitter" or "registered as a friend," are added to the domain. Forth, there is a big difference in the calculation time and memory use between the two kinds of algorithms. While the matrix multiplication of two matrices, has to be executed twice for the previous HITS-based algorithm, this is unnecessary with our algorithm. In our ranking framework, various folksonomy ranking policies can be expressed with the ranking factors combined and our approach can work, even if the folksonomy site is not implemented with Semantic Web languages. Above all, the time weight proposed in this paper will be applicable to various domains, including social media, where time value is considered important.

• Horticultural Science & Technology
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• v.31 no.5
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• pp.640-647
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• 2013

This study was conducted to provide exportation strategy by surveying on preference of Japanese consumers on cut chrysanthemum exported. The survey was conducted two times by a local survey company in Japan, and the surveys were conducted largely on chrysanthemums for casual flowers and the altar. After departmentalizing Japanese consumers per groups the result were analyzed through conjoint and cluster methods, flower colors and shape were used relatively higher rate for selection criteria of flowers in every group in the case of casual flowers. Group 1 comprised of 60 year-old housewives who reside in a small city with high school diploma and annual income less than 300 million yen, and group 2 of 40 year-old housewives who are small city residents with high school diplomas and annual income of 300 million yen show higher rate of use in flower shape than colors. Another group 3 whose members are 50 year-old housewives, small city residents with high school diplomas and annual income of 600 million yen showed higher rate of use colors than the shape for selection criteria of flowers. The consumption characteristics according to the ages of the consumers showed a pronounced tendency. The 40-50 year-old housewives preferred single flowers packed with other flowers, and the 60 year-old housewives double flowers packed with only chrysanthemums. In flower color, the 50-60 year-old housewives preferred white and yellow flowers, and the 40 year-old housewives pink and yellow flowers. Therefore, there are needs for development strategy of new products considering the consumption characteristics of flower shape and color according to the ages of consumer. After analyzing the chrysanthemums for altar by departmentalization of Japanese consumers, every group showed relative higher rate of use for flower shape for selection criteria of flowers. According to the analysis on the consumption characteristics, group 1 which is comprised of 30-40 year-old housewives who reside in small city with high school diplomas and income less than 300 million yen, and the group 2 of 20 year-old housewives who reside in small city with college diplomas and annual income less than 300 million yen. They are very sensitive to the price of the products while the group 3 of 50 year-old housewives who reside in small city with high school diplomas and annual income less than 300 million yen are insensitive to the price. The 30-50 year-old housewives preferred white and pink flowers, and the 20 year-old housewives yellow and pink flowers. In flower shape, the 50 year-old housewives preferred anemone shape, the 30-40 year-old housewives double shape, and the 20 year-old housewives pompon shapes. Therefore, the white, double flowers for the 30-40 year-old housewives and the yellow, pompon flowers for the 20 year-old housewives are needed to be created at the lowest cost, while the white, anemone flowers are needed to created at higher cost with high quality. In light of these results, it is considered that we should understand the types of purchasing products through consumption characteristics of Japanese consumers. Also we should plan, create market-oriented and consumer-oriented products, and should export them in order to expand more exportation.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.169-196
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• 2017

The fourth industrial revolution represents a revolutionary change in the business environment and its ecosystem, which is a fusion of Information Technology (IT) and other industries. In line with these recent changes, the Ministry of Employment and Labor of South Korea announced 'the Fourth Industrial Revolution Leader Training Program,' which includes five key support areas such as (1) smart manufacturing, (2) Internet of Things (IoT), (3) big data including Artificial Intelligence (AI), (4) information security, and (5) bio innovation. Based on this program, we can get a glimpse of the South Korean government's efforts and willingness to emit leading human resource with advanced IT knowledge in various fusion technology-related and newly emerging industries. On the other hand, in order to nurture excellent IT manpower in preparation for the fourth industrial revolution, the role of educational institutions capable of providing high quality IT education services is most of importance. However, these days, most IT educational institutions have had difficulties in providing customized IT education services that meet the needs of consumers (i.e., learners), without breaking away from the traditional framework of providing supplier-oriented education services. From previous studies, it has been found that the provision of customized education services centered on learners leads to high satisfaction of learners, and that higher satisfaction increases not only task performance and the possibility of business application but also learners' recommendation intention. However, since research has not yet been conducted in a comprehensive way that consider both antecedent and consequent factors of the learner's satisfaction, more empirical research on this is highly desirable. With the advent of the fourth industrial revolution, a rising interest in various convergence technologies utilizing information technology (IT) has brought with the growing realization of the important role played by IT-related education services. However, research on the role of IT education service quality in the context of IT education is relatively scarce in spite of the fact that research on general education service quality and satisfaction has been actively conducted in various contexts. In this study, therefore, the five dimensions of IT education service quality (i.e., tangibles, reliability, responsiveness, assurance, and empathy) are derived from the context of IT education, based on the SERVPERF model and related previous studies. In addition, the effects of these detailed IT education service quality factors on learners' educational satisfaction and their work application/recommendation intentions are examined. Furthermore, the moderating roles of learner position (i.e., practitioner group vs. manager group) and participation motivation (i.e., voluntary participation vs. involuntary participation) in relationships between IT education service quality factors and learners' educational satisfaction, work application intention, and recommendation intention are also investigated. In an analysis using the structural equation model (SEM) technique based on a questionnaire given to 203 participants of IT education programs in an 'M' IT educational institution in Seoul, South Korea, tangibles, reliability, and assurance were found to have a significant effect on educational satisfaction. This educational satisfaction was found to have a significant effect on both work application intention and recommendation intention. Moreover, it was discovered that learner position and participation motivation have a partial moderating impact on the relationship between IT education service quality factors and educational satisfaction. This study holds academic implications in that it is one of the first studies to apply the SERVPERF model (rather than the SERVQUAL model, which has been widely adopted by prior studies) is to demonstrate the influence of IT education service quality on learners' educational satisfaction, work application intention, and recommendation intention in an IT education environment. The results of this study are expected to provide practical guidance for IT education service providers who wish to enhance learners' educational satisfaction and service management efficiency.

• Korean Journal of Construction Engineering and Management
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• v.1 no.2 s.2
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• pp.98-107
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• 2000

Increased use of computers in AEC (Architecture, Engineering and Construction) has expanded the amount of information gained from CAD (Computer Aided Design), PMIS (Project Management Information System), Structural Analysis Program, and Scheduling Program as well as making it more complex. And the productivity of AEC industry is largely dependent on well management and efficient reuse of this information. Accordingly, such trend incited much research and development on ITC (Information Technology in Construction) and CIC (Computer Integrated Construction) to be conducted. In exemplifying such effort, many researchers studied and researched on IFC (Industry Foundation Classes) since its development by IAI (International Alliance for Interoperability) for the product based information sharing. However, in spite of some valuable outputs, these researches are yet in the preliminary stage and deal mainly with conceptual ideas and trial implementations. Research on unveiling the process of the IFC application development, the core of the Design Information management system, and its applicable plan still need be done. Thus, the purpose of this paper is to determine the technologies needed for Design Information management system using IFC, and to present the key roles and the process of the IFC application development and its applicable plan. This system play a role to integrate the architectural information and the structural information into the product model and to group many each product items with various levels and aspects. To make the process model, we defined two activities, 'Product Modeling', 'Application Development', at the initial level. Then we decomposed the Application Development activity into five activities, 'IFC Schema Compile', 'Class Compile', 'Make Project Database Schema', 'Development of Product Frameworker', 'Make Project Database'. These activities are carried out by C++ Compiler, CAD, ObjectStore, ST-Developer, and ST-ObjectStore. Finally, we proposed the applicable process with six stages, '3D Modeling', 'Creation of Product Information', 'Creation and Update of Database', 'Reformation of Model's Structure with Multiple Hierarchies', 'Integration of Drawings and Specifications', and 'Creation of Quantity Information'. The IFCs, including the other classes which are going to be updated and developed newly on the construction, civil/structure, and facility management, will be used by the experts through the internet distribution technologies including CORBA and DCOM.

• Horticultural Science & Technology
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• v.34 no.2
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• pp.342-353
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• 2016

This study was initiated to evaluate green color retention under three different soil systems. Several turfgrasses were evaluated in multi-layer, USGA, and mono-layer systems. Turfgrass entries were comprised of three cultivars of Korean lawngrass (Zoysia japonica Steud.) as warm-season grass (WSG) and three blends and three mixtures of Kentucky bluegrass (KB, Poa pratensis L.), perennial ryegrass (PR, Lolium perenne L.), and tall fescue (TF, Festuca arundinacea Schreb.) as cool-season grass (CSG). Significant differences were observed in visual turf color and green color retention among soil systems and turfgrasses. Both the multi-layer and USGA systems were highly associated with better color ratings and longer color retention, as compared with the mono-layer system. Seasonal variation of visual turf color greatly occurred from late December to early spring. CSG exhibited longer color retention than did WSG. The latter maintained green color for approximately 6 months, regardless of the soil system. Spring green-up of Korean lawngrass occurred from early to middle May, while it underwent discoloration from late October to early November. Among the CSGs green-up occurred between early March and early April and leaf color was maintained until middle December to early February. Therefore, the CSGs were green for 8.5 to 11 months, depending on turfgrass and soil system. The mean period of green color duration across all soil systems was approximately 10-11, 9-10 and 8.5-9.0 months for PR, KB and TF, respectively. As for the CSG mixtures, the greater the proportion of PR, the longer the green color retention, while the higher the proportion of TF, the shorter the color retention. There was greater variation in green color duration among the CSGs than the WSGs. Across soil systems, color retention differences of 2 to 6 days were observed for the Korean lawngrass, but 7 to 36 days for the CSGs. These results demonstrate that green color retention varied greatly according to soil systems and also among turfgrasses. Selections of turfgrass and soil system should be made using a concept-oriented approach, when establishing garden, park, soccer field, golf course and other sports field. Information obtained in this study can be used to select soil systems and turfgrasses based on the expected degree of leaf color retention.

• Horticultural Science & Technology
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• v.31 no.3
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• pp.259-268
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• 2013

This study was carried out to evaluate the visual turfgrass's color quality, winter color, and spring green-up under three different soil systems and to make a practical use for sports turf design and construction. Several turfgrasses were evaluated in multi-layer, USGA and mono-layer systems. Turfgrass entries in the study comprised of 3 cultivars from Korean lawngrass (Zoysia japonica Steud.) of typical warm-season grass (WSG) and 3 blends and 3 mixtures from Kentucky bluegrass (KB, Poa pratensis L.), perennial ryegrass (PR, Lolium perenne L.), and tall fescue (TF, Festuca arundinacea Schreb.) of cool-season grass (CSG). Significant differences were observed in the turfgrass's color quality, winter color, and spring green-up in the study. Seasonal variation of visual turf color greatly occurred according to soil systems and turfgrasses. Multi-layer and USGA systems were highly associated with better visual color ratings, as compared with mono-layer system. Regardless of soil system, visual turf color in all entries was better from spring to fall than in winter. Great color differences were observed during a period of early December to early spring. CSG produced a better color quality over WSG in any soil system. Overall color ratings for CSG were KB > PR > Mixtures > TF. As for a winter color, its ranking was USGA > multi-layer > mono-layer system. No difference was found in winter among cultivars of Korean lawngrass, being completely brown, but great differences among CSG. Rated best for winter color was PR, followed by CSG mixtures, KB and finally TF in order. It was generally conceded that fast green-up in spring was greatly related with multi-layer over mono-layer system and also CSG over WSG. Among CSG, TF had a fastest green-up. PR was also fast in green-up, but poor in color uniformity. KB, however, was the slowest due to shallow rooting system, when compared with other CSGs. These results demonstrate color differences were greatly variable according to soil systems and also among turfgrass species. A precise decision should be made in selecting turfgrass species and soil system. Multi-layer and USGA systems were considered as the suitable one for turfgrass color quality, winter color and spring green-up. It is a great necessity to combine proper soil system, right turfgrass species, and appropriate mixing rates by a concept-oriented approach, when establishing garden, parks, soccer field, and golf courses and so on.

• Journal of Gifted/Talented Education
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• v.25 no.2
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• pp.339-358
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• 2015

This study was to examine perceptions of information technology(IT) competencies among gifted and non-gifted students(i.e., information science high school students and technical high school students). Of the 370 high school students surveyed from 3 high schools(i.e., gifted academy, information science high school, and technical high school) in three metropolitan cities, Korea, 351 students completed and returned the questionnaires yielding a total response rate of 94.86%. High school students recognized the IT professional competence as being most important when recruiting IT employees. And they considered that practice-oriented education was the most importantly needed to improve their IT skills. In addition, the most important sub-factors of IT core competencies among gifted academy students and information science high school students were basic software skills. Also Technical high school students responded that the main network and security capabilities were the most importantly needed to do so. Finally, the most appropriate training courses for enhancing IT competencies were recognized differently among gifted and non-gifted students. Gifted academy students responded that the 'algorithm' was the mostly needed for enhancing IT competencies, whereas information science high school students responded that 'data structures' and 'computer architecture' were mostly needed to do. For technical high school students, they responded that a 'programming language' course was the most needed to do so. Results are discussed in relations to IT corporate and school settings.