• Journal of the Korean Society of Earth Science Education
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• v.15 no.2
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• pp.235-248
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• 2022

With the changes in the future educational environment, such as the rapid decline of the school-age population and the expansion of students' choice of curriculum, changes are also required in PCK, the expertise of science teachers. In other words, the categories constituting the existing 'consensus-PCK' and the characteristics of 'science PCK' are not fixed, so more categories and characteristics can be added. The purpose of this study is to explore the potential area of science PCK required to cope with changes in the future educational environment in the form of 'Family Resemblance Science PCK (Family Resemblance-PCK, hereafter)' through Wittgenstein's family resemblance approach. For this purpose, in-depth interviews were conducted with three focus groups. In the focus group in-depth interview, participants discussed how the science PCK required for science teachers in future schools in 2030-2045 will change due to changes in the future society and educational environment. Qualitative analysis was performed based on the in-depth interview, and semantic network analysis was performed on the in-depth interview text to analyze the characteristics of 'Family Resemblance-PCK' differentiated from the existing 'consensus-PCK'. In results, the characteristics of Family Resemblance-PCK, which are newly requested along with changes in role expectations of science teachers, were examined by PCK area. As a result of semantic network analysis of Family Resemblance-PCK, it was found that Family Resemblance-PCK expands its boundaries from the existing consensus-PCK, which is the starting point, and new PCK elements were added. Looking at the aspects of Family Resemblance-PCK, [AI-Convergence Knowledge-Contents-Digital], [Community-Network-Human Resources-Relationships], [Technology-Exploration-Virtual Reality-Research], [Self-Directed Learning-Collaboration-Community], etc., form a distinct network cluster, and it is expected that future science teacher expertise will be formed and strengthened around these PCK areas. Based on the research results, changes in the professionalism of science teachers in future schools and countermeasures were proposed as a conclusion.

• The Journal of Society for e-Business Studies
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• v.17 no.4
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• pp.69-93
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• 2012

Various influence-related relationships in Social Network Services (SNS) among users, posts, and user-and-post, can be expressed using links. The current research evaluates the influence of specific users or posts by analyzing the link structure of relevant social network graphs to identify influential users. We applied the concept of mutual interactions proposed for ranking semantic web resources, rather than the voting notion of Page Rank or HITS, to blogosphere, one of the early SNS. Through many experiments with network models, where the performance and validity of each alternative approach can be analyzed, we showed the applicability and strengths of our approach. The weight tuning processes for the links of these network models enabled us to control the experiment errors form the link weight differences and compare the implementation easiness of alternatives. An additional example of how to enter the content scores of commercial or spam posts into the graph-based method is suggested on a small network model as well. This research, as a starting point of the study on identifying influential users in SNS, is distinctive from the previous researches in the following points. First, various influence-related properties that are deemed important but are disregarded, such as scraping, commenting, subscribing to RSS feeds, and trusting friends, can be considered simultaneously. Second, the framework reflects the general phenomenon where objects interacting with more influential objects increase their influence. Third, regarding the extent to which a bloggers causes other bloggers to act after him or her as the most important factor of influence, we treated sequential referencing relationships with a viewpoint from that of PageRank or HITS (Hypertext Induced Topic Selection).

• Trans-
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• v.7
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• pp.19-48
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• 2019

This study was described to examine the meaning of the media exhibition work <70mK>, which aims to capture the topography of the collective consciousness of the Korean people through large-scale interviews. <70mK> edits and organizes interview images of individual beings in mosaic-like layouts and forms, creating video exhibitions and holding exhibitions. The objects in the split frame show the continuity of differences that reveal their own thoughts and personalities. This is a synchronic and conscious collective typology in which the intrinsic nature of the individuals is embodied in a simultaneous and holistic image. Interview images reveal their own form as a actual being and convey the intrinsic nature of one's own as oral information. <70mK> constructs a new individualization by aesthetically structuring the forms and information of life individuals in the extension of a specific group. The beings in the frame are not communicating with each other and are looking straight ahead. it conveys to visitors their relationship and personality as the preindividual reality. It is the repetitive arrangement and composition of heterogeneity and difference that each individual shows, and is a chain operation that includes collective identity behind it. <70mK> constructs the direct images and sounds of individual interviewee, creating a new form of information transfer called Video Art Exhibition. This makes metaphors and perceptions of the meaning and process of transindividual relationships and the meaning of psychic individuation and collective individuation. This is an appropriate case to explain with modern technology and individualization of Gilbert Simondon thought together with the meaning of becoming and relation of individualization. The exhibition space constructed by <70mK> is an aesthetic methodology of the psychic and collective meaning and its relationship to a particular group of individuals through which they are connected. Simondon studied the meaning of the process of individualization and the meaning of becoming, and is a philosopher who positively considered the potential of modern technology. <70mK> is a new individual as structured and generated ethical reality mediated by modern technology mechanisms and network behaviors. It is an case of an aesthetic and practical methodology of how interviews function as 'transduction' in the process of individualization in which technology is cooperated. The direct images and sounds of <70mK> are systems in which the information of life individuals is carried, amplified, accumulated and transmitted. It is also a new individual as a psychic and collective landscape. It is a newly became exhibition art work through the multiple individualization, and is a representation of transindividual meanings and process. The media exhibition art of individualized metastable states leads to new relationships in which viewers perceive the same preindividual reality and feel affectivity. The exhibition space of <70mK> becomes a stage for preparing the actual possibility of the transindividual group beyond the representation of the semantic function.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.69-92
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• 2015

The explosion of social media data has led to apply text-mining techniques to analyze big social media data in a more rigorous manner. Even if social media text analysis algorithms were improved, previous approaches to social media text analysis have some limitations. In the field of sentiment analysis of social media written in Korean, there are two typical approaches. One is the linguistic approach using machine learning, which is the most common approach. Some studies have been conducted by adding grammatical factors to feature sets for training classification model. The other approach adopts the semantic analysis method to sentiment analysis, but this approach is mainly applied to English texts. To overcome these limitations, this study applies the Word2Vec algorithm which is an extension of the neural network algorithms to deal with more extensive semantic features that were underestimated in existing sentiment analysis. The result from adopting the Word2Vec algorithm is compared to the result from co-occurrence analysis to identify the difference between two approaches. The results show that the distribution related word extracted by Word2Vec algorithm in that the words represent some emotion about the keyword used are three times more than extracted by co-occurrence analysis. The reason of the difference between two results comes from Word2Vec's semantic features vectorization. Therefore, it is possible to say that Word2Vec algorithm is able to catch the hidden related words which have not been found in traditional analysis. In addition, Part Of Speech (POS) tagging for Korean is used to detect adjective as "emotional word" in Korean. In addition, the emotion words extracted from the text are converted into word vector by the Word2Vec algorithm to find related words. Among these related words, noun words are selected because each word of them would have causal relationship with "emotional word" in the sentence. The process of extracting these trigger factor of emotional word is named "Emotion Trigger" in this study. As a case study, the datasets used in the study are collected by searching using three keywords: professor, prosecutor, and doctor in that these keywords contain rich public emotion and opinion. Advanced data collecting was conducted to select secondary keywords for data gathering. The secondary keywords for each keyword used to gather the data to be used in actual analysis are followed: Professor (sexual assault, misappropriation of research money, recruitment irregularities, polifessor), Doctor (Shin hae-chul sky hospital, drinking and plastic surgery, rebate) Prosecutor (lewd behavior, sponsor). The size of the text data is about to 100,000(Professor: 25720, Doctor: 35110, Prosecutor: 43225) and the data are gathered from news, blog, and twitter to reflect various level of public emotion into text data analysis. As a visualization method, Gephi (http://gephi.github.io) was used and every program used in text processing and analysis are java coding. The contributions of this study are as follows: First, different approaches for sentiment analysis are integrated to overcome the limitations of existing approaches. Secondly, finding Emotion Trigger can detect the hidden connections to public emotion which existing method cannot detect. Finally, the approach used in this study could be generalized regardless of types of text data. The limitation of this study is that it is hard to say the word extracted by Emotion Trigger processing has significantly causal relationship with emotional word in a sentence. The future study will be conducted to clarify the causal relationship between emotional words and the words extracted by Emotion Trigger by comparing with the relationships manually tagged. Furthermore, the text data used in Emotion Trigger are twitter, so the data have a number of distinct features which we did not deal with in this study. These features will be considered in further study.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.77-97
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• 2019

The large amount of data that emerges from the initial connection environment of the Fourth Industrial Revolution is a major factor that distinguishes the Fourth Industrial Revolution from the existing production environment. This environment has two-sided features that allow it to produce data while using it. And the data produced so produces another value. Due to the massive scale of data, future information systems need to process more data in terms of quantities than existing information systems. In addition, in terms of quality, only a large amount of data, Ability is required. In a small-scale information system, it is possible for a person to accurately understand the system and obtain the necessary information, but in a variety of complex systems where it is difficult to understand the system accurately, it becomes increasingly difficult to acquire the desired information. In other words, more accurate processing of large amounts of data has become a basic condition for future information systems. This problem related to the efficient performance of the information system can be solved by building a semantic web which enables various information processing by expressing the collected data as an ontology that can be understood by not only people but also computers. For example, as in most other organizations, IT has been introduced in the military, and most of the work has been done through information systems. Currently, most of the work is done through information systems. As existing systems contain increasingly large amounts of data, efforts are needed to make the system easier to use through its data utilization. An ontology-based system has a large data semantic network through connection with other systems, and has a wide range of databases that can be utilized, and has the advantage of searching more precisely and quickly through relationships between predefined concepts. In this paper, we propose a defense ontology as a method for effective data management and decision support. In order to judge the applicability and effectiveness of the actual system, we reconstructed the existing air force munitions situation management system as an ontology based system. It is a system constructed to strengthen management and control of logistics situation of commanders and practitioners by providing real - time information on maintenance and distribution situation as it becomes difficult to use complicated logistics information system with large amount of data. Although it is a method to take pre-specified necessary information from the existing logistics system and display it as a web page, it is also difficult to confirm this system except for a few specified items in advance, and it is also time-consuming to extend the additional function if necessary And it is a system composed of category type without search function. Therefore, it has a disadvantage that it can be easily utilized only when the system is well known as in the existing system. The ontology-based logistics situation management system is designed to provide the intuitive visualization of the complex information of the existing logistics information system through the ontology. In order to construct the logistics situation management system through the ontology, And the useful functions such as performance - based logistics support contract management and component dictionary are further identified and included in the ontology. In order to confirm whether the constructed ontology can be used for decision support, it is necessary to implement a meaningful analysis function such as calculation of the utilization rate of the aircraft, inquiry about performance-based military contract. Especially, in contrast to building ontology database in ontology study in the past, in this study, time series data which change value according to time such as the state of aircraft by date are constructed by ontology, and through the constructed ontology, It is confirmed that it is possible to calculate the utilization rate based on various criteria as well as the computable utilization rate. In addition, the data related to performance-based logistics contracts introduced as a new maintenance method of aircraft and other munitions can be inquired into various contents, and it is easy to calculate performance indexes used in performance-based logistics contract through reasoning and functions. Of course, we propose a new performance index that complements the limitations of the currently applied performance indicators, and calculate it through the ontology, confirming the possibility of using the constructed ontology. Finally, it is possible to calculate the failure rate or reliability of each component, including MTBF data of the selected fault-tolerant item based on the actual part consumption performance. The reliability of the mission and the reliability of the system are calculated. In order to confirm the usability of the constructed ontology-based logistics situation management system, the proposed system through the Technology Acceptance Model (TAM), which is a representative model for measuring the acceptability of the technology, is more useful and convenient than the existing system.

• Journal of the Korean Society for information Management
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• v.21 no.4 s.54
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• pp.109-131
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• 2004

As there are diverse delivery media and forms of information resources, their management schemes are diverse as well. In library community, cataloguing. rules for describing information resources such as AACR and KCR have been developed. The efforts to automate management of information resources based on these rules resulted in the development of MARC. However, MARC records are restricted in describing the information resources and MARC has various and distinct characteristics of the structural rigidity, which does not support the representation of extended semantic structures that exist among bibliographic entities. Therefore, since the data model for MARC is single-layer data model, it is not appropriate for describing information resources represented by multi-layer data model which can be used to set up the relationships among various objects in digital libraries. In this paper, we propose an a metadata model for digital libraries based on the IFLA FRBR basic model which supports multi-layer data model and a representation scheme based on XML Schema to manage the metadata about old books, old documents, resource related to music, conferences and seminars.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.3
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• pp.159-168
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• 2012

Relation in the new IT environment, such as the SNS, Cloud, Web3.0, has become an important factor. And these relations generate a transaction. However, existing relational database and graph database does not processe graph structure representing the relationships and transactions. This paper, we propose the technique that can be processed concurrently graph structures and transactions in a scalable complex network system. The proposed technique simultaneously save and navigate graph structures and transactions using the Topic Maps data model. Topic Maps is one of ontology language to implement the semantic web(Web 3.0). It has been used as the navigator of the information through the association of the information resources. In this paper, the architecture of the proposed technique was implemented and design using Cassandra - one of column type NoSQL. It is to ensure that can handle up to Big Data-level data using distributed processing. Finally, the experiments showed about the process of storage and query about typical RDBMS Oracle and the proposed technique to the same data source and the same questions. It can show that is expressed by the relationship without the 'join' enough alternative to the role of the RDBMS.

• 모자간호학회지
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• v.2 no.1
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• pp.5-20
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• 1992

This study was undertaken to identify the levels and affecting factors of the maternal role attainment(MRA) in the primipara during the postpartum period. The healthy ninety primiparous from the one university hospital and two local clinics in KwangJu city were selected and two Semantic Differential Scales (SD-Myself as Mothers, SD-My Baby) and the Pharis Self Confidence Scale were used in this study. Questionnaires were distributed at the 3rd days and the 4-6 weeks of the primiparous not showing any complication after normal delivery. The data collected were analysed statistically using t-test, Pearson's Product Moment Correlation Coefficient and ANOVA. The results obtained were summarized as follows; 1) On the 3rd day after the delivery, the scores of SD-myself as mother, SD-baby and Pharis Self Confidence were 70.6 points, 73.6 points and 78.6 points, respectively, showing the low level of MRA. 2) On the 4-6 weeks after delivery, the score of SD-myself as mother, SD-baby and Pharis Self Confidence were 72.8 points, 77.9 points, and 86.9 points, respectively, indicating the moderate level of MRA. 3) The mean scores of the SD scale and the Pharis Self Confidence during the postpartum periods were higher than those of the 3rd days, showing the SD-myself as mother (t=-2.09, P<.05), SD-baby(t=-4.12, P<.001), Pharis Self Confidence(t=-6.59, P<.001), respectively. 4) Positive correlations (r=.24$\sim$.69) were shown in the concepts related to the MRA and the cognitive-motor skill components and cognitive-affective skill components of the MRA became harmonious over time. 5) The relationships between the score of the MRA and the demographic and obstetric variables were as follows ; a) the score of the MRA in the twenties was higher than those of the thirties. b) the group with higher educational background showed higher MRA socres than the group with lower one. c) those who wanted pregnancy sustenance had higher MRA scores than those who did not. d) the group that did think of festus-feature represented higher MRA scores than those who did not. e) the group of mothers who have the daughters showed higher MRA scores than those who have boys. It can be concluded from the results that the MRA in the primiparous increased gradually, and that the cognitive-motor skills and cognitive-affective skills became harmonious over time. The level of the MRA was affected partly by the mothers general, obstetrical variables. Following suggestion were made oil the basis of the present study ; a) The longitudinal study on the MRA is needed. b) Multivariate analyses should be done for the identification of the factors influcening on the MRA. c) Education program for primiparous mother should be designed and developed to improve the MRA.

• Spatial Information Research
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• v.22 no.1
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• pp.65-73
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• 2014

Recently indoor navigation with indoor map such as Indoor Google Maps is served. For the services, constructing indoor data are required. CityGML and IFC are widely used as standards for representing indoor data. The data models contains spatial information for the indoor visualization and analysis, but indoor navigation requires semantic and topological information like graph as well as geometry. For this reason, IndoorGML, which is a GML3 application schema and data model for representation, storage and exchange of indoor geoinformation, is under standardization of OGC. IndoorGML can directly describe geometric property and refer elements in external documents. Because a lot of data in CityGML or IFC have been constructed, a huge amount of construction time and cost for IndoorGML data will be reduced if CityGML can help generate data in IndoorGML. Thus, this paper suggest practical use of CityGML including deriving from and link to CityGML. We analyze relationships between IndoorGML and CityGML. In this paper, issues and solutions for linkage of IndoorGML and CityGML are addressed.

• Journal of the Korean Society for information Management
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• v.32 no.2
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• pp.131-152
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• 2015

This study described the results of converting RDB to RDF ontology by each of R2RML method and Non-R2RML method. This study measured the size of the converted data, the conversion time per each tuple, and the response speed to queries. The STNet, a structured terminology dictionary based on RDB, was served as a test bed for converting to RDF ontology. As a result of the converted data size, Non-R2RML method appeared to be superior to R2RML method on the number of converted triples, including its expressive diversity. For the conversion time per each tuple, Non-R2RML was a little bit more faster than R2RML, but, for the response speed to queries, both methods showed similar response speed and stable performance since more than 300 numbers of queries. On comprehensive examination it is evaluated that Non-R2RML is the more appropriate to convert the dynamic RDB system, such as the STNet in which new data are steadily accumulated, data transformation very often occurred, and relationships between data continuously changed.