• Trans-
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• v.12
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• pp.51-79
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• 2022

This study investigates the methods for deriving colors which can serve as a reference to users such as designers and or contents creators who search for online images from the web portal sites using specific words for color planning and more. Two experiments were conducted in order to accomplish this. Digital scenery photos within the geographic scope of Korea were downloaded from web portal sites, and those photos were studied to find out what colors were used to describe daytime and nighttime. Machine learning was used as the study methodology to classify colors in daytime and nighttime, and KSCA was used to derive the color frequency of daytime and nighttime photos and to compare and analyze the two results. The results of classifying the colors of daytime and nighttime photos using machine learning show that, when classifying the colors by 51~100%, the area of daytime colors was approximately 2.45 times greater than that of nighttime colors. The colors of the daytime class were distributed by brightness with white as its center, while that of the nighttime class was distributed with black as its center. Colors that accounted for over 70% of the daytime class were 647, those over 70% of the nighttime class were 252, and the rest (31-69%) were 101. The number of colors in the middle area was low, while other colors were classified relatively clearly into day and night. The resulting color distributions in the daytime and nighttime classes were able to provide the borderline color values of the two classes that are classified by brightness. As a result of analyzing the frequency of digital photos using KSCA, colors around yellow were expressed in generally bright daytime photos, while colors around blue value were expressed in dark night photos. For frequency of daytime photos, colors on the upper 40% had low chroma, almost being achromatic. Also, colors that are close to white and black showed the highest frequency, indicating a large difference in brightness. Meanwhile, for colors with frequency from top 5 to 10, yellow green was expressed darkly, and navy blue was expressed brightly, partially composing a complex harmony. When examining the color band, various colors, brightness, and chroma including light blue, achromatic colors, and warm colors were shown, failing to compose a generally harmonious arrangement of colors. For the frequency of nighttime photos, colors in approximately the upper 50% are dark colors with a brightness value of 2 (Munsell signal). In comparison, the brightness of middle frequency (50-80%) is relatively higher (brightness values of 3-4), and the brightness difference of various colors was large in the lower 20%. Colors that are not cool colors could be found intermittently in the lower 8% of frequency. When examining the color band, there was a general harmonious arrangement of colors centered on navy blue. As the results of conducting the experiment using two methods in this study, machine learning could classify colors into two or more classes, and could evaluate how close an image was with certain colors to a certain class. This method cannot be used if an image cannot be classified into a certain class. The result of such color distribution would serve as a reference when determining how close a certain color is to one of the two classes when the color is used as a dominant color in the base or background color of a certain design. Also, when dividing the analyzed images into several classes, even colors that have not been used in the analyzed image can be determined to find out how close they are to a certain class according to the color distribution properties of each class. Nevertheless, the results cannot be used to find out whether a specific color was used in the class and by how much it was used. To investigate such an issue, frequency analysis was conducted using KSCA. The color frequency could be measured within the range of images used in the experiment. The resulting values of color distribution and frequency from this study would serve as references for color planning of digital design regarding natural scenery in the geographic scope of Korea. Also, the two experiments are meaningful attempts for searching the methods for deriving colors that can be a useful reference among numerous images for content creator users of the relevant field.

• Asia pacific journal of information systems
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• v.22 no.3
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• pp.53-74
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• 2012

A challenge in fostering virtual communities is the continuous supply of knowledge, namely members' willingness to contribute knowledge to their communities. Previous research argues that giving away knowledge eventually causes the possessors of that knowledge to lose their unique value to others, benefiting all except the contributor. Furthermore, communication within virtual communities involves a large number of participants with different social backgrounds and perspectives. The establishment of mutual understanding to comprehend conversations and foster knowledge contribution in virtual communities is inevitably more difficult than face-to-face communication in a small group. In spite of these arguments, evidence suggests that individuals in virtual communities do engage in social behaviors such as knowledge contribution. It is important to understand why individuals provide their valuable knowledge to other community members without a guarantee of returns. In virtual communities, knowledge is inherently rooted in individual members' experiences and expertise. This personal nature of knowledge requires social interactions between virtual community members for knowledge transfer. This study employs the social capital theory in order to account for interpersonal relationship factors and identity theory for individual and group factors that may affect knowledge contribution. First, social capital is the relationship capital which is embedded within the relationships among the participants in a network and available for use when it is needed. Social capital is a productive resource, facilitating individuals' actions for attainment. Nahapiet and Ghoshal (1997) identify three dimensions of social capital and explain theoretically how these dimensions affect the exchange of knowledge. Thus, social capital would be relevant to knowledge contribution in virtual communities. Second, existing research has addressed the importance of identity in facilitating knowledge contribution in a virtual context. Identity in virtual communities has been described as playing a vital role in the establishment of personal reputations and in the recognition of others. For instance, reputation systems that rate participants in terms of the quality of their contributions provide a readily available inventory of experts to knowledge seekers. Despite the growing interest in identities, however, there is little empirical research about how identities in the communities influence knowledge contribution. Therefore, the goal of this study is to better understand knowledge contribution by examining the roles of social capital and identity in virtual communities. Based on a theoretical framework of social capital and identity theory, we develop and test a theoretical model and evaluate our hypotheses. Specifically, we propose three variables such as cohesiveness, reciprocity, and commitment, referring to the social capital theory, as antecedents of knowledge contribution in virtual communities. We further posit that members with a strong identity (self-presentation and group identification) contribute more knowledge to virtual communities. We conducted a field study in order to validate our research model. We collected data from 192 members of virtual communities and used the PLS method to analyse the data. The tests of the measurement model confirm that our data set has appropriate discriminant and convergent validity. The results of testing the structural model show that cohesion, reciprocity, and self-presentation significantly influence knowledge contribution, while commitment and group identification do not significantly influence knowledge contribution. Our findings on cohesion and reciprocity are consistent with the previous literature. Contrary to our expectations, commitment did not significantly affect knowledge contribution in virtual communities. This result may be due to the fact that knowledge contribution was voluntary in the virtual communities in our sample. Another plausible explanation for this result may be the self-selection bias for the survey respondents, who are more likely to contribute their knowledge to virtual communities. The relationship between self-presentation and knowledge contribution was found to be significant in virtual communities, supporting the results of prior literature. Group identification did not significantly affect knowledge contribution in this study, inconsistent with the wealth of research that identifies group identification as an important factor for knowledge sharing. This conflicting result calls for future research that examines the role of group identification in knowledge contribution in virtual communities. This study makes a contribution to theory development in the area of knowledge management in general and virtual communities in particular. For practice, the results of this study identify the circumstances under which individual factors would be effective for motivating knowledge contribution to virtual communities.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.1-18
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• 2016

Owing to the extensive use of Web media and the development of the IT industry, a large amount of data has been generated, shared, and stored. Nowadays, various types of unstructured data such as image, sound, video, and text are distributed through Web media. Therefore, many attempts have been made in recent years to discover new value through an analysis of these unstructured data. Among these types of unstructured data, text is recognized as the most representative method for users to express and share their opinions on the Web. In this sense, demand for obtaining new insights through text analysis is steadily increasing. Accordingly, text mining is increasingly being used for different purposes in various fields. In particular, issue tracking is being widely studied not only in the academic world but also in industries because it can be used to extract various issues from text such as news, (SocialNetworkServices) to analyze the trends of these issues. Conventionally, issue tracking is used to identify major issues sustained over a long period of time through topic modeling and to analyze the detailed distribution of documents involved in each issue. However, because conventional issue tracking assumes that the content composing each issue does not change throughout the entire tracking period, it cannot represent the dynamic mutation process of detailed issues that can be created, merged, divided, and deleted between these periods. Moreover, because only keywords that appear consistently throughout the entire period can be derived as issue keywords, concrete issue keywords such as "nuclear test" and "separated families" may be concealed by more general issue keywords such as "North Korea" in an analysis over a long period of time. This implies that many meaningful but short-lived issues cannot be discovered by conventional issue tracking. Note that detailed keywords are preferable to general keywords because the former can be clues for providing actionable strategies. To overcome these limitations, we performed an independent analysis on the documents of each detailed period. We generated an issue flow diagram based on the similarity of each issue between two consecutive periods. The issue transition pattern among categories was analyzed by using the category information of each document. In this study, we then applied the proposed methodology to a real case of 53,739 news articles. We derived an issue flow diagram from the articles. We then proposed the following useful application scenarios for the issue flow diagram presented in the experiment section. First, we can identify an issue that actively appears during a certain period and promptly disappears in the next period. Second, the preceding and following issues of a particular issue can be easily discovered from the issue flow diagram. This implies that our methodology can be used to discover the association between inter-period issues. Finally, an interesting pattern of one-way and two-way transitions was discovered by analyzing the transition patterns of issues through category analysis. Thus, we discovered that a pair of mutually similar categories induces two-way transitions. In contrast, one-way transitions can be recognized as an indicator that issues in a certain category tend to be influenced by other issues in another category. For practical application of the proposed methodology, high-quality word and stop word dictionaries need to be constructed. In addition, not only the number of documents but also additional meta-information such as the read counts, written time, and comments of documents should be analyzed. A rigorous performance evaluation or validation of the proposed methodology should be performed in future works.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.1
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• pp.26-46
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• 2020

An irrigated-maize agroecosystem is viewed as an open thermodynamic system upon which solar radiation impresses a large gradient that moves the system away from equilibrium. Following the imperative of the second law of thermodynamics, such agroecosystem resists and reduces the externally applied gradient by using all means of this nature-human coupled system acting together as a nonequilibrium dissipative process. The ultimate purpose of our study is to test this hypothesis by examining the energetics of agroecosystem growth and development. As a first step toward this test, we employed the eddy covariance flux data from 2003 to 2014 at the AmeriFlux NE1 irrigated-maize site at Mead, Nebraska, USA, and analyzed the energetics of this agroecosystem by scrutinizing its radiation, energy and entropy exchange. Our results showed: (1) more energy capture during growing season than non-growing season, and increasing energy capture through growing season until senescence; (2) more energy flow activity within and through the system, providing greater potential for degradation; (3) higher efficiency in terms of carbon uptake and water use through growing season until senescence; and (4) the resulting energy degradation occurred at the expense of increasing net entropy accumulation within the system as well as net entropy transfer out to the surrounding environment. Under the drought conditions in 2012, the increased entropy production within the system was accompanied by the enhanced entropy transfer out of the system, resulting in insignificant net entropy change. Drought mitigation with more frequent irrigation shifted the main route of entropy transfer from sensible to latent heat fluxes, yielding the production and carbon uptake exceeding the 12-year mean values at the cost of less efficient use of water and light.

• Journal of Broadcast Engineering
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• v.22 no.6
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• pp.829-849
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• 2017

Due to the large-scale TV display, the convergence of broadcasting and broadband, and the advancement of signal compression and transmission technology, terrestrial digital broadcasting has evolved into UHD broadcasting capable of providing simultaneous broadcasting of fixed UHD and mobile HD. The Korean standard for terrestrial UHDTV broadcasting is based on ATSC 3.0, the broadcasting standard of North America. The terrestrial UHDTV broadcasting standard chose that as a new AV codec standard, HEVC video codec which can compress with higher efficiency compared to AVC, and MPEG-H 3D audio codec for realistic audio. Also, DASH and MMT are adopted as transmission format instead of MPEG-2 TS to support broadband as well as broadcasting network, and in order to provide 4K UHD/mobile HD service simultaneously ROUTE multiplexing technology is applied. In this paper, we propose an audio/video encoder, which is required to provide HDR/WCG supported high quality video service, 10.2 channel/4 object supporting stereo sound service, fixed UHD and mobile HD simultaneous broadcasting service based on ATSC3.0, also we implemented the ATSC 3.0 LDM system for ROUTE/DASH packager, multiplexing system and physical layer transmission/reception, and verified the service ability by applying it to real time broadcast environment.

• Korean Security Journal
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• no.50
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• pp.175-206
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• 2017

The current study described the history of Islamic extremism and the recent expansion of international Islamic extremism in Indonesia. For doing so, both content analysis of the existing written documents and qualitative interviews were conducted. For the content analysis, media reports and research articles were collected and utilized. For qualitative interviews, Indonesian students and workers in Korea, Korean spouses married to Indonesian, and Korean missionaries in Indonesia were contacted and interviewed. Qualitative interview was conducted between 30 minutes and 2 hours. On the spot, interviews were recorded and later transcribed into written documents. Due to the difficulty of identification of population and the uneasiness of accessability to th study subjects, convenient sampling and snowball sampling were used. According to the results, Islamic extremism in Indonesia had a deep historical root and generally shared similar historical experience with other muslim countries such as Afghanistan, Pakistan, Egypt, and Saudi Arabia where Islamic extremism was deeply rooted in. That is, Islamic extremism began as a reaction to the western imperialism, after independence, Islamic extremism elements were marginalized in the process of construction of the modern nation-state, and Islamic extremist movement was radicalized and became violent during the Soviet-Afghan War. In addition, after 9.11, Islamic extremism in Indonesia was connected to international Islamic extremism network and integrated into such global movement. Such a historical development of Indonesian Islamic extremism was quite organized and robust. Meanwhile, the eastward infiltration and expansion of international Islamic extremism such as IS and Al Qaeda was observed in Indonesia. Particularly, such a worrisome expansion was more clearly visible in the marginalized and underdeveloped countrysides in Indonesia. Such expansion in Indonesia could negatively affect on the security of South Korea. Geographically, Indonesia is proximate to South Korea. This geographical proximity could be a direct security threat to the Korean society, as if Islamic extremism in North Africa and Middle East becomes a direct security threat to Europe. Considering the presence of a large size of Indonesian immigrant workers and communities in South Korea, such a concern is very realistic. The arrest of an Indonesian Islamic extremism supporter in November, 2016, could be a harbinger of the coming trend of Islamic extremism expansion inside South Korea. The Indonesian Islamic community in South Korea could be a passage of Indonesian Islamic extremism into the South Korean society. In this context, it is timely and necessary to pay an attention to the recent trend of Islamic extremism expansion in Indonesia.

• Archives of design research
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• v.16 no.4
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• pp.385-394
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• 2003

An investigation by KRNIC (Korea Network Information Center) on the real state of usage of internet has shown that 96.9％ of children investigated had experiences of using internet. Especially the firstly ranked item that had been answered by children as a necessity of internet was 'Studying to solve tasks' rated by 83.9％. As seen from the research result, the need as a homework sonics is actually so dominant that it cannot be ignored when considering the profitability at the area of education contents, but any profound research has not been accomplished yet. Internet has been positioned as a more effective and fruitful learning tool, and also all activities done by users for exploring informations and choosing learning items under the on-line circumstances are based on the successive mutual reactions between users and computers. Up to now much of the web based learning circumstances has been introducing the User Interface using metaphor, and the same is found dominantly from the sites for children. But in spite of the availability of metaphor mentioned above the current status is much lack of profound researches about metaphor interface; and what is more, in the case of the site for elementary school students the gap of the ability recognizing metaphor is very large between lower classes and higher classes according to the degree of mental growth but that is used to be simply ignored, then a common concept is adapted to interface for all grades of classes and moreover for infant and kindergarten without any objections. Based on foregoing problems this research has put the main focus on the groping and presenting desirable directions on the prospect design of interface for children-oriented sites by analyzing the status of practical usage of metaphor interface in the field of the sites for children-oriented learning sites with concentration upon homework supporting domains.

• Journal of Korea Multimedia Society
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• v.14 no.1
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• pp.54-75
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• 2011

PoC(Push-to-talk Over Cellular) is an integrated technology of group voice calls, video calls and internet based multimedia services. If a PoC user can not participate in the PoC session for various reasons such as an emergency situation, lack of battery capacity, then the user can use the PoC Box which has a similar functionality to the MM Box in the MMS(Multimedia Messaging Service). The RTSP(Real-Time Streaming Protocol) method is recommended to be used when there is a transmission session between the PoC box and a terminal. Since the existing VOD service uses a wired network, the packet size of RTSP-based VOD service is huge, however, the PoC service has wireless communication environments which have general characteristics to be used in RTSP method. Packet loss in a wired communication environments is relatively less than that in wireless communication environment, therefore, a buffering latency occurs in PoC service due to a play-out delay which means an asynchronous play of audio & video contents. Those problems make a user to be difficult to find the information they want when the media contents are played-out. In this paper, the following techniques and methods were proposed and their performance and superiority were verified through testing: cross-over dual reception buffering technique, advance partition multi-reception buffering technique, and on-demand multi-reception buffering technique, which are designed for effective picking up of information in media content being transmitted in short amount of time using RTSP when a user searches for media, as well as for reduction in playback delay; and same-priority packetization transmission method and priority-based packetization transmission method, which are media data packetization methods for transmission. From the simulation of functional evaluation, we could find that the proposed multiple receiving buffering and packetizing methods are superior, with respect to the media retrieval inclination, to the existing single receiving buffering method by 6-9 points from the viewpoint of effectiveness and excellence. Among them, especially, on-demand multiple receiving buffering technology with same-priority packetization transmission method is able to manage the media search inclination promptly to the requests of users by showing superiority of 3-24 points above compared to other combination methods. In addition, users could find the information they want much quickly since large amount of informations are received in a focused media retrieval period within a short time.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.151-171
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• 2015

This study examined the concepts of the Internet of Things(IoT), the major issue and IoT trend in the domestic and international market. also reviewed the advent of IoT era which caused a 'Paradigm Shift'. This study proposed a solution for the appropriate corresponding strategy in terms of Enterprise. Global competition began in the IoT market. So, Businesses to be competitive and responsive, the government's efforts, as well as the efforts of companies themselves is needed. In particular, in order to cope with the dynamic environment appropriately, faster and more efficient strategy is required. In other words, proposed a management strategy that can respond the IoT competitive era on tipping point through the vision of paradigm shift. We forecasted and proposed the emergence of paradigm shift through a comparative analysis of past management paradigm and IoT management paradigm as follow; I) Knowledge & learning oriented management, II) Technology & innovation oriented management, III) Demand driven management, IV) Global collaboration management. The Knowledge & learning oriented management paradigm is expected to be a new management paradigm due to the development of IT technology development and information processing technology. In addition to the rapid development such as IT infrastructure and processing of data, storage, knowledge sharing and learning has become more important. Currently Hardware-oriented management paradigm will be changed to the software-oriented paradigm. In particular, the software and platform market is a key component of the IoT ecosystem, has been estimated to be led by Technology & innovation oriented management. In 2011, Gartner announced the concept of "Demand-Driven Value Networks(DDVN)", DDVN emphasizes value of the whole of the network. Therefore, Demand driven management paradigm is creating demand for advanced process, not the process corresponding to the demand simply. Global collaboration management paradigm create the value creation through the fusion between technology, between countries, between industries. In particular, cooperation between enterprises that has financial resources and brand power and venture companies with creative ideas and technical will generate positive synergies. Through this, The large enterprises and small companies that can be win-win environment would be built. Cope with the a paradigm shift and to establish a management strategy of Enterprise process, this study utilized the 'RTE cyclone model' which proposed by Gartner. RTE concept consists of three stages, Lead, Operate, Manage. The Lead stage is utilizing capital to strengthen the business competitiveness. This stages has the goal of linking to external stimuli strategy development, also Execute the business strategy of the company for capital and investment activities and environmental changes. Manege stage is to respond appropriately to threats and internalize the goals of the enterprise. Operate stage proceeds to action for increasing the efficiency of the services across the enterprise, also achieve the integration and simplification of the process, with real-time data capture. RTE(Real Time Enterprise) concept has the value for practical use with the management strategy. Appropriately applied in this study, we propose a 'IoT-RTE Cyclone model' which emphasizes the agility of the enterprise. In addition, based on the real-time monitoring, analysis, act through IT and IoT technology. 'IoT-RTE Cyclone model' that could integrate the business processes of the enterprise each sector and support the overall service. therefore the model be used as an effective response strategy for Enterprise. In particular, IoT-RTE Cyclone Model is to respond to external events, waste elements are removed according to the process is repeated. Therefore, it is possible to model the operation of the process more efficient and agile. This IoT-RTE Cyclone Model can be used as an effective response strategy of the enterprise in terms of IoT era of rapidly changing because it supports the overall service of the enterprise. When this model leverages a collaborative system among enterprises it expects breakthrough cost savings through competitiveness, global lead time, minimizing duplication.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.253-266
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• 2018

This paper proposes a methodology applying sequence tagging methodology to improve the performance of NER(Named Entity Recognition) used in QA system. In order to retrieve the correct answers stored in the database, it is necessary to switch the user's query into a language of the database such as SQL(Structured Query Language). Then, the computer can recognize the language of the user. This is the process of identifying the class or data name contained in the database. The method of retrieving the words contained in the query in the existing database and recognizing the object does not identify the homophone and the word phrases because it does not consider the context of the user's query. If there are multiple search results, all of them are returned as a result, so there can be many interpretations on the query and the time complexity for the calculation becomes large. To overcome these, this study aims to solve this problem by reflecting the contextual meaning of the query using Bidirectional LSTM-CRF. Also we tried to solve the disadvantages of the neural network model which can't identify the untrained words by using ontology knowledge based feature. Experiments were conducted on the ontology knowledge base of music domain and the performance was evaluated. In order to accurately evaluate the performance of the L-Bidirectional LSTM-CRF proposed in this study, we experimented with converting the words included in the learned query into untrained words in order to test whether the words were included in the database but correctly identified the untrained words. As a result, it was possible to recognize objects considering the context and can recognize the untrained words without re-training the L-Bidirectional LSTM-CRF mode, and it is confirmed that the performance of the object recognition as a whole is improved.