• Journal of KIISE
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• v.42 no.5
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• pp.591-600
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• 2015

SLA (Service Level Agreement) is an essential factor that must be guaranteed to provide a reliable and consistent service to user in cloud computing environment. Especially, a contract between user and service provider with SLA is important in an environment using a cloud service brokerage. The cloud computing is classified into IaaS, PaaS, and SaaS according to IT resources of the various cloud service. The existing SLA is difficult to reflect the quality factors of service, because it only considers factors about the physical Network environment and have no methodological approach. In this paper, we suggested a method to specify the quality characteristics of software and proposed a mechanism and structure that can exchange SLA specification between the service provider and consumer. We defined a meta-model for the SLA specification in the SaaS level, and quality requirements of the SaaS were described by the proposed specification language. Through case studies, we verified proposed specification language that can present a variety of software quality factors. By using the UDDI-based mediation process and architecture to interchange this specification, it is stored in the repository of quality specifications and exchanged during service binding time.

• Korean Journal of Ecology and Environment
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• v.54 no.3
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• pp.156-169
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• 2021

Traditional morphological identification difficulties, such as phenotypic plasticity, misidentification of cryptic species, and larval stage species, can be compensated for by using DNA analysis techniques, such as DNA barcoding, in surveying zooplankton populations, including species identification. Recently, the rapid development of DNA sequencing techniques has allowed DNA-based community analysis not only for zooplankton assemblages in various aquatic ecosystems but also for the gut contents of zooplankton that are limited by conventional methods such as visual and microscopic identification. Therefore, the application of DNA sequencing can help understand biological interactions through the analysis of zooplankton food sources. The present paper introduces the major DNA-based approaches in zooplankton research topics, including taxonomic approaches by DNA barcoding, community-level approaches by metabarcoding, and gut content analyses, summarizes the analysis methods, and finally suggests the methodological topics that need to be considered for future applications.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.1-14
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• 2024

The most optimal route-search algorithm thus far has introduced a method of applying node labels and link labels. Node labels consider two nodes simultaneously in the optimal route-search process, while link labels consider two links simultaneously. This study proposes a turn-label-based optimal route-search technique that considers two turns simultaneously in the process. Turn-label-based optimal route search guarantees the optimal solution of dynamic programming based on Bellman's principle as it considers a two-turn search process. Turn-label-based optimal route search can accommodate the advantages of applying link labels because the concept of approaching the limit of link labels is applied equally. Therefore, it is possible to reflect rational cyclic traffic where nodes allow multiple visits without expanding the network, while links do not allow visits. In particular, it reflects the additional cost structure that appears in two consecutive turns, making it possible to express the structure of the travel-cost function more flexibly. A case study was conducted on the metropolitan urban railway network consisting of transportation card terminal readers, aiming to examine the scalability of the research by introducing parameters that reflect psychological resistance in travel with continuous pedestrian transfers into turn label optimal path search. Simulation results showed that it is possible to avoid conservative transfers even if the travel time and distance increase as the psychological resistance value for continuous turns increases, confirming the need to reflect the cost structure of turn labels. Nevertheless, further research is needed to secure diversity in the travel-cost functions of road and public-transportation networks.

• Journal of Korean Elementary Science Education
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• v.43 no.2
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• pp.219-232
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• 2024

This study aims to determine the perspectives of pre-service elementary school teachers on the science curriculum in the fourth industrial revolution era. In this study, 128 pre-service elementary school teachers were asked to express their perspectives on the Saber-toothed Tiger Curriculum through photovoice activities. The resulting images were classified into three types: conservative, progressive, and radical perspectives. The number of both conservative and progressive perspectives was similar and high, whereas the number of radical perspectives was l ow. Those who had conservative perspectives on the Saber-toothed Tiger curriculum regarded "Inquiry" as the basis of the science curriculum, which should be maintained regardless of the time period and environment. Similarly, older teachers believed that this curriculum was based on eternal truth, which should be protected. Those who showed progressive perspectives on the Saber-toothed Tiger curriculum regarded a progressive person as someone succeeding to the blood of "New fist," and they showed positive attitudes toward AI-based education such as coding and meta-verse, regarding these practices as part of the teaching and learning method that could replace the existing inquiry-based education. Those who showed radical perspectives on the Saber-toothed Tiger Curriculum assumed critical attitudes toward the rapidly changing political circumstances of science education and criticized conflicts between different social classes formed through progressive curriculum. Based on these results, this study found that pre-service elementary school teachers needed to consider the science curriculum from several different perspectives rather than just one.

• Clinical and Experimental Pediatrics
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• v.52 no.6
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• pp.680-688
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• 2009

Purpose : Cysteinyl leukotrienes are important proinflammatory mediators in asthma. Recently, it was suggested that a promoter polymorphism in the genes encoding for leukotriene C4 synthase (LTC4S), a key enzyme in the leukotriene synthetic pathway, and cysteinyl leukotriene receptor 1 (CysLTR1) might be associated with aspirin-intolerant asthma. We investigated whether polymorphisms in LTC4S and CysLTR1 genes or their interactions were associated with the asthma phenotype, lung function, or bronchial hyperreactivity (BHR) in Korean children. Methods : A total of 856 asthmatic children and 254 non-asthmatic controls were enrolled; a skin prick test, lung function test and bronchial provocation test were performed. Of those enrolled, 395 children underwent exercise challenge tests. The LTC4S A(-444)C and CysLTR1 T(＋927)C were genotyped by polymerase chain reaction-restriction fragment length polymorphism analysis. Results : Of those enrolled, 699 children were classified as having atopic asthma and 277 children, as having exercise-induced asthma (EIA). LTC4S and CysLTR1 polymorphisms were not associated with atopic asthma, EIA, or asthma per se. Lung function and BHR were not significantly different between the wild type (AA or TT) and the variant (AC＋CC or TC＋CC) genotypes in asthmatics, atopic asthmatics, and EIA (＋) asthmatics, while total eosinophil counts were higher in the variant type of LTC4S than in the wild type in atopic asthmatics. There were no associations between the gene-gene interactions of LTC4S and CysLTR1 genotypes and the asthma phenotypes. Conclusion : LTC4S A(-444)C and CysLTR1 T(＋927)C polymorphisms and their gene-gene interactions are not associated with asthma phenotype, lung function, or BHR in Korean children.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.95-112
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• 2021

In university education, the choice of major class plays an important role in students' careers. However, in line with the changes in the industry, the fields of major subjects by department are diversifying and increasing in number in university education. As a result, students have difficulty to choose and take classes according to their career paths. In general, students choose classes based on experiences such as choices of peers or advice from seniors. This has the advantage of being able to take into account the general situation, but it does not reflect individual tendencies and considerations of existing courses, and has a problem that leads to information inequality that is shared only among specific students. In addition, as non-face-to-face classes have recently been conducted and exchanges between students have decreased, even experience-based decisions have not been made as well. Therefore, this study proposes a recommendation system model that can recommend college major classes suitable for individual characteristics based on data rather than experience. The recommendation system recommends information and content (music, movies, books, images, etc.) that a specific user may be interested in. It is already widely used in services where it is important to consider individual tendencies such as YouTube and Facebook, and you can experience it familiarly in providing personalized services in content services such as over-the-top media services (OTT). Classes are also a kind of content consumption in terms of selecting classes suitable for individuals from a set content list. However, unlike other content consumption, it is characterized by a large influence of selection results. For example, in the case of music and movies, it is usually consumed once and the time required to consume content is short. Therefore, the importance of each item is relatively low, and there is no deep concern in selecting. Major classes usually have a long consumption time because they have to be taken for one semester, and each item has a high importance and requires greater caution in choice because it affects many things such as career and graduation requirements depending on the composition of the selected classes. Depending on the unique characteristics of these major classes, the recommendation system in the education field supports decision-making that reflects individual characteristics that are meaningful and cannot be reflected in experience-based decision-making, even though it has a relatively small number of item ranges. This study aims to realize personalized education and enhance students' educational satisfaction by presenting a recommendation model for university major class. In the model study, class history data of undergraduate students at University from 2015 to 2017 were used, and students and their major names were used as metadata. The class history data is implicit feedback data that only indicates whether content is consumed, not reflecting preferences for classes. Therefore, when we derive embedding vectors that characterize students and classes, their expressive power is low. With these issues in mind, this study proposes a Net-NeuMF model that generates vectors of students, classes through network analysis and utilizes them as input values of the model. The model was based on the structure of NeuMF using one-hot vectors, a representative model using data with implicit feedback. The input vectors of the model are generated to represent the characteristic of students and classes through network analysis. To generate a vector representing a student, each student is set to a node and the edge is designed to connect with a weight if the two students take the same class. Similarly, to generate a vector representing the class, each class was set as a node, and the edge connected if any students had taken the classes in common. Thus, we utilize Node2Vec, a representation learning methodology that quantifies the characteristics of each node. For the evaluation of the model, we used four indicators that are mainly utilized by recommendation systems, and experiments were conducted on three different dimensions to analyze the impact of embedding dimensions on the model. The results show better performance on evaluation metrics regardless of dimension than when using one-hot vectors in existing NeuMF structures. Thus, this work contributes to a network of students (users) and classes (items) to increase expressiveness over existing one-hot embeddings, to match the characteristics of each structure that constitutes the model, and to show better performance on various kinds of evaluation metrics compared to existing methodologies.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.149-161
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• 2014

The export of domestic public services to overseas markets contains many potential obstacles, stemming from different export procedures, the target services, and socio-economic environments. In order to alleviate these problems, the business incubation platform as an open business ecosystem can be a powerful instrument to support the decisions taken by participants and stakeholders. In this paper, we propose an ontology model and its implementation processes for the business incubation platform with an open and pervasive architecture to support public service exports. For the conceptual model of platform ontology, export case studies are used for requirements analysis. The conceptual model shows the basic structure, with vocabulary and its meaning, the relationship between ontologies, and key attributes. For the implementation and test of the ontology model, the logical structure is edited using Prot$\acute{e}$g$\acute{e}$ editor. The core engine of the business incubation platform is the simulator module, where the various contexts of export businesses should be captured, defined, and shared with other modules through ontologies. It is well-known that an ontology, with which concepts and their relationships are represented using a shared vocabulary, is an efficient and effective tool for organizing meta-information to develop structural frameworks in a particular domain. The proposed model consists of five ontologies derived from a requirements survey of major stakeholders and their operational scenarios: service, requirements, environment, enterprise, and county. The service ontology contains several components that can find and categorize public services through a case analysis of the public service export. Key attributes of the service ontology are composed of categories including objective, requirements, activity, and service. The objective category, which has sub-attributes including operational body (organization) and user, acts as a reference to search and classify public services. The requirements category relates to the functional needs at a particular phase of system (service) design or operation. Sub-attributes of requirements are user, application, platform, architecture, and social overhead. The activity category represents business processes during the operation and maintenance phase. The activity category also has sub-attributes including facility, software, and project unit. The service category, with sub-attributes such as target, time, and place, acts as a reference to sort and classify the public services. The requirements ontology is derived from the basic and common components of public services and target countries. The key attributes of the requirements ontology are business, technology, and constraints. Business requirements represent the needs of processes and activities for public service export; technology represents the technological requirements for the operation of public services; and constraints represent the business law, regulations, or cultural characteristics of the target country. The environment ontology is derived from case studies of target countries for public service operation. Key attributes of the environment ontology are user, requirements, and activity. A user includes stakeholders in public services, from citizens to operators and managers; the requirements attribute represents the managerial and physical needs during operation; the activity attribute represents business processes in detail. The enterprise ontology is introduced from a previous study, and its attributes are activity, organization, strategy, marketing, and time. The country ontology is derived from the demographic and geopolitical analysis of the target country, and its key attributes are economy, social infrastructure, law, regulation, customs, population, location, and development strategies. The priority list for target services for a certain country and/or the priority list for target countries for a certain public services are generated by a matching algorithm. These lists are used as input seeds to simulate the consortium partners, and government's policies and programs. In the simulation, the environmental differences between Korea and the target country can be customized through a gap analysis and work-flow optimization process. When the process gap between Korea and the target country is too large for a single corporation to cover, a consortium is considered an alternative choice, and various alternatives are derived from the capability index of enterprises. For financial packages, a mix of various foreign aid funds can be simulated during this stage. It is expected that the proposed ontology model and the business incubation platform can be used by various participants in the public service export market. It could be especially beneficial to small and medium businesses that have relatively fewer resources and experience with public service export. We also expect that the open and pervasive service architecture in a digital business ecosystem will help stakeholders find new opportunities through information sharing and collaboration on business processes.