• Journal of the Korea Society of Computer and Information
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• v.15 no.1
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• pp.31-42
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• 2010

GPM(Generic Product Model) developed by Hitachi in Japan is a common data model to integrate and share life cycle data of nuclear power plants. GPM consists of GPM core model, an abstract model, implementation language for the model and reference library written in the language. GPM core model has a feature that it can construct a semantic network model consisting of relationships among objects. Initial GPM developed and provided GPML as an implementation language to support the feature of the core model, but afterwards the GPML was replaced by GPM-XML based on XML to achieve data interoperability with heterogeneous applications accessing a GPM data model. However, data models written in GPM-XML are insufficient to be used as a semantic network model for lack of studies which support GPM-XML and enable the models to be used as a semantic network model. This paper proposes OWL as the implementation language for GPM core model because OWL can describe ontologies similar to semantic network models and has an abundant supply of technical standards and supporting tools. Also, OWL which can be expressed in terms of RDF/XML based on XML guarantees data interoperability. This paper uses OWL DL, one of three sublanguages of OWL, because it can guarantee complete reasoning and the maximum expressiveness at the same time. The contents of this paper introduce the way how to overcome the difference between GPM and OWL DL, and, base on this way, describe how to convert the reference library written in GPML into ontologies based on OWL DL written in RDF/XML.

• The Journal of the Korea Contents Association
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• v.19 no.1
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• pp.682-695
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• 2019

In recent years, using a connected platform, companies have built and implemented a mobile viral marketing strategy to attract new customers and to have long-term relationships with existing customers. The emergence of interactive Web 2.0 has led to an explosive increase in customer engagement, and practitioners have become interested in connected platform to build close relationships with their customers. However, the study on the effectiveness of various customer influx methods using the connected platform that companies utilize for an increase of customer participation is insufficient. Based on the theoretical study of Sashi (2012), this study analyzes the actual mobile viral promotion of company A's open market shopping mall for the purpose of bringing new customers and having a long-term relationship with the new customers[1]. By analyzing the customer engagement type, the implications for the effectiveness of mobile viral promotion are suggested. First, as a result of the immediate effect of online viral promotion, promotions are partially effective in attracting new customers. Second, as a result of examining the change of customer engagement type in order to find out the long - term effect of online viral promotion, it was found that in most cases, new customers were not become satisfied customers and, Laggard Effect, which takes time to become a satisfied customer, has been confirmed.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.123-132
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• 2020

The EDucation-research Integration through Simulation On the Net (EDISON) platform, which is a web-based platform that provides computational science and engineering simulation execution environments, can offer various analysis environments to students, general users, as well as computational science and engineering researchers. To expand the user base of the simulation environment services, the EDISON platform holds a challenge every year and attempts to increase the competitiveness and excellence of the platform by analyzing the user requirements of the various simulation environment offered. The challenge platform system in the field of computational science and engineering is provided to users in relation to the simulation service used in the existing EDISON platform. Previously, EDISON challenge servicesoperated independently from simulation services, and hence, services such as end-user review and intermediate simulation results could not be linked. To meet these user requirements, the currently in-service challenge platform for computational science and engineering is linked to the existing computational science and engineering service. In addition, it was possible to increase the efficiency of service resources by providing limited services through various analyses of all users participating in the challenge. In this study, by analyzing the simulation and usage environments of users, we provide an improved challenge platform; we also analyze ways to improve the simulation execution environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.830-860
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• 2022

[Introduction] Nowadays, many companies are shifting their businesses online due to the growing trend among customers to buy and shop online, as people prefer online purchasing products. [Problem] Users share a vast amount of information about products, making it difficult and challenging for the end-users to make certain decisions. [Motivation] Therefore, we need a mechanism to automatically analyze end-user opinions, thoughts, or feelings in the social media platform about the products that might be useful for the customers to make or change their decisions about buying or purchasing specific products. [Proposed Solution] For this purpose, we proposed an automated SentiDecpective approach, which classifies end-user reviews into negative, positive, and neutral sentiments and identifies deceptive crowd-users rating information in the social media platform to help the user in decision-making. [Methodology] For this purpose, we first collected 11781 end-users comments from the Amazon store and Flipkart web application covering distant products, such as watches, mobile, shoes, clothes, and perfumes. Next, we develop a coding guideline used as a base for the comments annotation process. We then applied the content analysis approach and existing VADER library to annotate the end-user comments in the data set with the identified codes, which results in a labelled data set used as an input to the machine learning classifiers. Finally, we applied the sentiment analysis approach to identify the end-users opinions and overcome the deceptive rating information in the social media platforms by first preprocessing the input data to remove the irrelevant (stop words, special characters, etc.) data from the dataset, employing two standard resampling approaches to balance the data set, i-e, oversampling, and under-sampling, extract different features (TF-IDF and BOW) from the textual data in the data set and then train & test the machine learning algorithms by applying a standard cross-validation approach (KFold and Shuffle Split). [Results/Outcomes] Furthermore, to support our research study, we developed an automated tool that automatically analyzes each customer feedback and displays the collective sentiments of customers about a specific product with the help of a graph, which helps customers to make certain decisions. In a nutshell, our proposed sentiments approach produces good results when identifying the customer sentiments from the online user feedbacks, i-e, obtained an average 94.01% precision, 93.69% recall, and 93.81% F-measure value for classifying positive sentiments.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.1
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• pp.1-12
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• 2022

Tilia amurensis is an important honey plant. As T. amurensis mainly distributes mountainous area with various elevations in Korea, accurate prediction of blooming time at the different elevation would benefit forest beekeepers. In this study, we measured time-dependent blooming progress of T. amurensis in Mt. Gariwang area ranging from 500-1500m. Additionally we collected blooming data from web and published literatures and estimated the variation of blooming time relative to the geographic locations. Flowers began to bloom from July 6 to July 22 with full blooming on July 14 in location where elevation is 638m in Mt. G ariwang area in 2021. Based on these databases, a growing degree day (G DD) model was developed for prediction of T. amurensis blooming progress using average daily temperatures. Using the starting date of G DD accumulation of January 1 and base temperature of 5 ℃, blooming period ranging from 10% to 90% of cumulative blooming rate was estimated as 860-1198 degree days (DD). This corresponded to the beginning to the end of July in Mt. Gariwaning area in 2021. This model could explain the phenological variations of T. amurensis flower blooming possibly affected by elevation within geographic area, latitude or year relative to the climate change, and aid forest beekeepers for better timing of nectar foraging by honey bees.

• Computers and Concrete
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• v.33 no.5
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• pp.497-507
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• 2024

In squat reinforced concrete walls, the displacement capacity for lateral deformation is low and the ability to resist the axial load can quickly be lost, generating collapse. This work consists of testing two squat reinforced concrete walls. One of the specimens is built with conventional detailing of reinforced concrete walls, while the second specimen is built applying an alternative design, including stirrups along the diagonal of the wall to improve its ductility. This solution differs from the detailing of beams or coupling elements that suggest building elements equivalent to columns located diagonally in the element. The dimensions of both specimens correspond to a wall with a low aspect ratio (1:1), where the height and length of the specimen are 1.4 m, with a thickness of 120 mm. The alternative wall included stirrups placed diagonally covering approximately 25% of the diagonal strut of the wall with alternative detailing. The walls were tested under a constant axial load of 0.1f'cAg and a cyclic lateral displacement was applied in the upper part of the wall. The results indicate that the lateral strength is almost identical between both specimens. On the other hand, the lateral displacement capacity increased by 25% with the alternative detailing, but it was also able to maintain the 3 complete hysteretic cycles up to a drift of 2.5%, reaching longitudinal reinforcement fracture, while the base specimen only reached the first cycle of 2% with rapid degradation due to failure of the diagonal compression strut. The alternative design also allows 46% more energy dissipation than the conventional design. A model was used to capture the global response, correctly representing the observed behavior. A parametric study with the model, varying the reinforcement amount and aspect ratio, was performed, indicating that the effectiveness of the alternative detailing can double de drift capacity for the case with a low aspect ratio (1.1) and a large longitudinal steel amount (1% in the web, 5% in the boundary), which decreases with lower amounts of longitudinal reinforcement and with the increment of aspect ratio, indicating that the alternative detailing approach is reasonable for walls with an aspect ratio up to 2, especially if the amount of longitudinal reinforcement is high.

• The Transactions of the Korea Information Processing Society
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• v.7 no.11S
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• pp.3651-3667
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• 2000

Recently, in the distributed multimedia environments based on internet, as radical growing technologies, the most of researchers focus on both streaming technology and distributed object thchnology, Specially, the studies which are tried to integrate the streaming services on the distributed object technology have been progressing. These technologies are applied to various stream service mamgements and protocols. However, the stream service management mexlels which are being proposed by the existing researches are insufficient for suporting the QoS of stream services. Besides, the existing models have the problems that cannot support the extensibility and the reusability, when the QoS-reiatedfunctions are being developed as a sub-module which is suited on the specific-purpose application services. For solving these problems, in this paper. we suggested a QoS Integrated platform which can extend and reuse using the distributed object technologies, and guarantee the QoS of the stream services. A structure of platform we suggested consists of three components such as User Control Module(UCM), QoS Management Module(QoSM) and Stream Object. Stream Object has Send/Receive operations for transmitting the RTP packets over TCP/IP. User Control ModuleI(UCM) controls Stream Objects via the COREA service objects. QoS Management Modulel(QoSM) has the functions which maintain the QoS of stream service between the UCMs in client and server. As QoS control methexlologies, procedures of resource monitoring, negotiation, and resource adaptation are executed via the interactions among these comiXments mentioned above. For constmcting this QoS integrated platform, we first implemented the modules mentioned above independently, and then, used IDL for defining interfaces among these mexlules so that can support platform independence, interoperability and portability base on COREA. This platform is constructed using OrbixWeb 3.1c following CORBA specification on Solaris 2.5/2.7, Java language, Java, Java Media Framework API 2.0, Mini-SQL1.0.16 and multimedia equipments. As results for verifying this platform functionally, we showed executing results of each module we mentioned above, and a numerical data obtained from QoS control procedures on client and server's GUI, while stream service is executing on our platform.

• Information Systems Review
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• v.6 no.2
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• pp.137-159
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• 2004

The next generation information appliances are those that can be connected with other appliances through a wired or wireless network in order to make it possible for them to transmit and receive data between them and to be remotely controlled from inside or outside of the home. Many electronic companies have aggressively invested in developing new information appliances to take the initiative in upcoming home networking era. They require systematic methods for developing new information appliances and sharing the knowledge acquired from the methods. This paper stored the knowledge acquired from developing the information appliances and developed a knowledge management system that supports the companies to use the knowledge and develop their own information appliances. In order to acquire the knowledge, this paper applied two methods for User-Centered Design in stead of using the general ones for knowledge acquisition. This paper suggested new product ideas by analyzing and observing user actions and stored the knowledge in knowledge bases, which included Knowledge from Analyzing User Actions and Knowledge from Observing User Actions. Seven new product ideas, suggested from the User-Centered Design, were made into design mockups and their videos were produced to show the real situations where they would be used in home of the future, which were stored in the knowledge base of Knowledge from Producing New Emotive Life Videos. Finally, data on present development states of future homes in Europe and Japan and newspapers articles from domestic newspapers were collected and stored in the knowledge base of Knowledge from Surveying Technology Developments. This paper developed a web-based knowledge management system that supports the companies to use the acquired knowledge. Knowledge users can get the knowledge required for developing new information appliances and suggest their own product ideas by using the knowledge management system. This will make the results from this research not confined to a case study of product development but extended to playing a role of facilitating the development of the next generation information appliances.

• 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.

• Journal of Life Science
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• v.18 no.8
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• pp.1090-1095
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• 2008

Marbling (intramuscular fat) is an important factor in determining meat quality in Korean beef market. A grain based finishing system for improving marbling leads to inefficient meat production due to an excessive fat production. Identification of intramuscular fat-specific gene might be achieved more targeted meat production through alternative genetic improvement program such as marker assisted selection (MAS). We carried out ddRT-PCR in 12 and 27 month old Hanwoo steers and detected 300 bp PCR product of the inducible cAMP early repressor (ICER) gene, showing highly gene expression in 27 months old. A 1.5 kb sequence was re-sequenced using primer designed base on the Hanwoo EST sequence. We then predicted the open reading frame (ORF) of ICER gene in ORF finder web program. Tissue distribution of ICER gene expression was analysed in eight Hanwoo tissue using realtime PCR analysis. The highest ICER gene expression showed in Small intestine followed by Longissimus dorsi. Interestingly, the ICER gene expressed 2.5 time higher in longissimus dorsi than in same muscle type, Rump. For gene expression analysis in high- and low marbled individuals, we selected 4 and 3 animal based on the muscle crude fat contents (high is 17-32%, low is 6-7% of crude fat contents). The ICER gene expression was analysed using ANOVA model. Marbling (muscle crude fat contents) was affected by ICER gene (P=0.012). Particularly, the ICER gene expression was 4 times higher in high group (n=4) than low group (n=3). Therefore, ICER gene might be a functional candidate gene related to marbling in Hanwoo.