In this study, in order to achieve the before-mentioned study purpose, the importance of developing the new product, the relationship with the design, and the design element for developing the new product were considered. In order to extract the importance of the design element which is applied to the development of the new product design, the research model about the induction of the priority was created, the evaluation items were instituted, and the demonstrative research approach was performed in order to recognize the relationship among those elements. Firstly, in the process of selecting the items for the application, 14 evaluation elements which were extracted through the advanced study data were grouped in 4 kinds of dimensions, and the properties which are related with the Digital TV product were composed up of 36 items. Through the factor analysis, by decreasing the detailed standard for the evaluation of 36 items, the parsimony was secured, and the characteristics which the various items contain induced into one factor. Secondly, the detailed factors which were united into one factor went under the paired comparison as one by one through AHP again, and then the importance degree was generated. First of all, as the first stage of AHP, the decision making factors which affect the whole achievement of purpose of the decision making were classified as in a hierarchical style. From these research results, it was known that the functional factor and esthetic factor in the process of designing the new product are the major affecting variables, and it was confirmed that in case of the Digital TV products group, the factors such as the high quality of picture, big screen, user interface, sound, product reliability, style, size, indoor reproduction, and guarantee are the main factors which influence the need of the consumers in purchasing products.
Art Museum Archives are archives that are created by individuals and organizations that have a sufficient worth that necessitate permanent preservation. Art Museum Archives, which include various medium and types, are archives that have information and evidence based value, and are established and supported for the research of the Art Museum and Art History. For the systematic implementation and application of an Art Museum Archive, there is a need to establish related description elements, and through this not only must information on the individual archives be provided, but through a high utility finding aid, the creation context of the archived document should be provided so that users of the archive can easily access documents. In the case of Korean Art Museum Archives, there is a tendency to focus on the fragmented informational value of an individual archive document, which in reality causes the structural and contextual element characteristic of the document to be destroyed. Therefore this research supports the Hierarchical Description of Art Museum Archives and has the objective of proposing Art Archive Description Elements that promote the preservation of creation context and effective utilization. In addition, because personal records take up a large portion of Art Archives and are very diverse in terms of medium and type, a Description Element that can reflect this is attempted to be proposed.
Journal of the Korean Association of Geographic Information Studies
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v.23
no.4
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pp.52-67
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2020
Recently, the Arctic has been exposed to snow-covered land due to melting permafrost every year, and the Korea Geographic Information Institute(NGII) provides polar spatial information service by establishing spatial information of the polar region. However, there is a lack of spatial information on vegetation sensitive to climate change. This research used a multi-temporal Sentinel-2 image to perform land cover classification of the Ny-Ålesund in Arctic Svalbard. In the pre-processing step, 10 bands and 6 vegetation spectral index were generated from multi-temporal Sentinel-2 images. In image-classification step is consisted of extracting the vegetation area through 8-class land cover classification and performing the vegetation species classification. The image classification algorithm used Random Forest to evaluate the accuracy and calculate feature importance through Out-Of-Bag(OOB). To identify the advantages of multi- temporary Sentinel-2 for vegetation classification, the overall accuracy was compared according to the number of images stacked and vegetation spectral index. Overall accuracy was 77% when using single-time Sentinel-2 images, but improved to 81% when using multi-time Sentinel-2 images. In addition, the overall accuracy improved to about 83% in learning when the vegetation index was used additionally. The most important spectral variables to distinguish between vegetation classes are located in the Red, Green, and short wave infrared-1(SWIR1). This research can be used as a basic study that optimizes input characteristics in performing the classification of vegetation in the polar regions.
This paper elucidates the effect of characteristics of service quality on continuance usage intention of digital healthcare service using mediating factors of user expectation and user utility. First, we classified independent factors into three types such as service system characteristics, user characteristics, and healthcare service characteristics from the previous studies, and investigated the effect of three independent factors on continuance usage intention of digital healthcare service. Second, we analyzed the impact of two mediating factors, user expectation and user utility, on the continuance usage intention. We developed a research model that includes three types of independent factors, mediated factors of user expectation and user utility, and a dependent factor of continuance usage intention. We surveyed a total of 357 samples from digital healthcare service users and analyzed the research model. The research results significantly show that Characteristics of Users is essential factor impacting a dependent factor of Continuance Usage Intention. The results indicate the followings: (1) Characteristics of Users including the variables of Innovation impacts User Expectation, and User Expectation affects Users Utility, and Users Utility also affects Continuance Usage Intention. (2) Characteristics of Service Systems including the variables of Functionality, Compatibility, and Convenience and Characteristics of users of Innovation variable impact the mediating factor of User Expectation, and User Expectation also affects the factor of Continuance Usage Intention. (3) Characteristics of Healthcare Services including the variables of Reliability, Ease of Operation, Safety, and Accuracy impact User Utility, and User Utility also affects Continuance Usage Intention.
Journal of the Korea Institute of Information Security & Cryptology
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v.18
no.6A
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pp.139-149
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2008
The amount of personal information collected by organizations and government agencies is continuously increasing. When a data collector publishes personal information for research and other purposes, individuals' sensitive information should not be revealed. On the other hand, published data is also required to provide accurate statistical information for analysis. k-Anonymity and ${\iota}$-diversity models are popular approaches for privacy preserving data publication. However, they are limited to static data release. After a dataset is updated with insertions and deletions, a data collector cannot safely release up-to-date information. Recently, the m-invariance model has been proposed to support re-publication of dynamic datasets. However, the m-invariant generalization can cause high information loss. In addition, if the adversary already obtained sensitive values of some individuals before accessing released information, the m-invariance leads to severe privacy disclosure. In this paper, we propose a novel technique for safely releasing dynamic datasets. The proposed technique offers a simple and effective method for handling inserted and deleted records without generalization. It also gives equivalent degree of privacy preservation to the m-invariance model.
Understanding the functional traits of dominant species in urban ecosystems provides insight into species' trait adaptation and ecosystem function in response to fragmented and isolated urban vegetation and reduced biological interactions. This study compared means and variances of environmental factors (geographic, meteorological, and soil attributes) and 4 leaf traits (leaf area, specific leaf area, leaf dry mass content, and leaf shape index) and 7 reproductive traits (fruit width, fruit length, fruit shape, fruit dry weight, fruit dry matter content, seed weight, and seed ratio) measured of 40 Sorbus alnifolia individuals in four mountainous areas south of Seoul downtown, South Korea. We then performed the multivariate analysis of trait combinations. While the measured environmental factors indicated the individuality of the survey sites, the urban vegetation was drier and had a longer growth period. The leaves of S. alnifolia in the urban areas were smaller and heavier, and the fruits produced longer and lighter seeds, showing the traits affected by long urbanization. The study confirmed changes in the growth and reproduction mechanism of the S. alnifolia population under the urban environment, indicating reduced biological interaction due to vegetation fragmentation and isolation. This study provides limited but distinct ecological information about the function and persistence of key species in cities with a reduced scale of biological interactions and many negative environmental factors such as air pollution.
Although CSV means pursuing social and economic values at the same time, research on consumer benefits recognized by consumers, the subject of economic value, is insufficient. The purpose of this study is to investigate the effect of CSV activities of financial companies on purchase intention through consumer benefits and psychological distance for consumers. 265 copies of survey data were collected, and the research hypothesis was verified using SPSS 25.0 and Smart PLS 3.0. As a result of the analysis, first, fairness and authenticity had a positive (+) effect on both social and personal benefits. Second, it was found that the social and personal benefits subjectively perceived by consumers had a positive (+) effect on both purchase intention. Third, it was found that the social benefits perceived by consumers through CSV activities of financial companies had a positive (+) effect on purchase intention through psychological distance, but the mediating effect of personal benefits was not significant. Based on these research results, practical proposals were made to increase the efficiency of CSV activities by grasping the effect of consumers and purchase intentions on CSV activities of financial companies, and conclusions, implications, and future research directions were presented.
Journal of the Korea Academia-Industrial cooperation Society
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v.22
no.4
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pp.140-149
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2021
Most industries have introduced and operate an information security management system (ISMS) or a personal information security management system (PIMS) to suitably protect and maintain customer's information and company trade secrets. This study starts with the premise that it is desirable for every industry considering information security to maintain an ISMS. ISMS can be of different types among various organizations, taking into consideration culture, practical work procedures, and guidelines for information security. This study intends to derive primary control areas of an ISMS for each industry based on organizational size and audit type by analyzing non-conformity trends and control factors according to certification audits for organizations introduced for international ISMS under ISO27001. This study analyzed improvement effects of ISMS through case analyses. It is meaningful as exploratory research, although it was difficult to acquire data for empirical study because few organizations maintain certification in major industrial sectors. The requirements presented the highest frequency of non-conformity for each type from the 2013-initiated ISO27001; the years 2013 to 2020 were extracted as the primary control area. The study found that for primary control areas of ISMS for each of three industries, organizational size and audit type had differences.
This study explored the elementary school teachers' experiences while teaching students with low achievement in science based on the grounded theory. In-depth interviews and analysis were conducted on 13 teachers with experiences in teaching students with low achievement in science within the last three years and more than five years of field experience until the theoretical saturation of data on the teaching experiences for students with low achievement in science. The analysis results were as follows. First, the teaching experiences of elementary school teachers for underachievers in science were classified into 119 concepts, 41 subcategories, and 17 categories. Based on the paradigm model, the categories were structured and presented as causal conditions, contextual conditions, intervening conditions, action/interaction strategies and consequences based on the central phenomenon of 'difficulty in teaching students with low achievement in science'. Second, the core category of elementary school teachers' teaching underachievers in science was assumed to be 'overcoming difficulties and teaching underachievers in science'. And according to the properties and dimensions of the core category, teachers who teaching students with low achievement in science were divided into four types: 'compromising-', 'overcoming-', 'accepting-', and 'conflicting-reality type'. Third, a conditional matrix was presented to summarize and integrate the results of this study by classifying the teaching experience of elementary school teachers for underachievers in science into educational providers and educational demanders. On the basis of these findings, educational implications for teaching students with low achievement in science were discussed.
The Journal of the Convergence on Culture Technology
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v.8
no.5
/
pp.697-703
/
2022
Due to the recent economic downturn caused by Covid-19 and the unstable international situation, many investors are choosing the derivatives market as a means of investment. However, the derivatives market has a greater risk than the stock market, and research on the market of market participants is insufficient. Recently, with the development of artificial intelligence, machine learning has been widely used in the derivatives market. In this paper, reinforcement learning, one of the machine learning techniques, is applied to analyze the scalping technique that trades futures in minutes. The data set consists of 21 attributes using the closing price, moving average line, and Bollinger band indicators of 1 minute and 3 minute data for 6 months by selecting 4 products among futures products traded at trading firm. In the experiment, DNN artificial neural network model and three reinforcement learning algorithms, namely, DQN (Deep Q-Network), A2C (Advantage Actor Critic), and A3C (Asynchronous A2C) were used, and they were trained and verified through learning data set and test data set. For scalping, the agent chooses one of the actions of buying and selling, and the ratio of the portfolio value according to the action result is rewarded. Experiment results show that the energy sector products such as Heating Oil and Crude Oil yield relatively high cumulative returns compared to the index sector products such as Mini Russell 2000 and Hang Seng Index.
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