• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.167-178
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• 2021

Since 2014, the quality level survey of the defense industry has been carried out annually. The need for this was felt as the quality control policy was inadequately reflected in the survey results. In this study, to secure valid and reliable data, the quality level survey measurement indicators and questionnaires used previously were analyzed and developed as customized papers according to the size of the company. The questionnaire index was simplified through the elimination of unnecessary and redundant items to improve the response rate and reliability. In addition, a comprehensive score was computed based on the improvement index so that the result of the quantitative quality level survey could be calculated. Through this, it was possible to determine the quality level attained by the defense industry. Through the quality level survey, we intend to secure data that can analyze the quality management environment to maintain quality levels of the defense industry and identify ways to establish mid-to-long-term quality management strategies and improve systems to enhance the quality level of the defense industry in the future.

• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.62-70
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• 2021

2020 was a year in which the world spent in disorder due to the pandemic of Coronavirus infection-19(COVID-19). The pandemic was at the beginning of a turning point in history. For examples, the Black Death(Pest) that destroyed the feudal system of medieval Europe in the 14th century, smallpox that led to the destruction of the Inca Empire by Spain in the 17th century, and the Spanish flu that ended World War I early. The great transformation that will come after COVID-19 is presented from various fields and perspectives, but the understanding and direction of the transformation is ambiguous. This study attempts to derive and to analyze core terms based on a network of the future of globalization after COVID-19. Four Networks related to globalization, anti-globalization, and globalization and digitalization after COVID-19 were established respectively. A network integrating four networks was also constructed. The core terms were extracted from the hub nodes, the stress centrality, and the simplified network to which the K-core algorithm was applied. After COVID-19, the changes in globalization were analyzed from the extracted core terms. This study is thought to be meaningful to propose a method of deriving and analyzing core terms based on a network in understanding social changes after COVID-19.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.772-781
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• 2020

A direct shear member resists external forces through the shear transfer of reinforcing bars placed at the concrete interface. The current concrete structural design code uses empirical formulas based on the shear friction analogy, which is applied to the horizontal shear of concrete composite beams. However, in the case of a member with a large amount of reinforcing bars, the shear strength obtained through the empirical formula is lower than the measured value. In this paper, the limit state of newly constructed composite beams on an existing concrete girder is defined using stress field theory, and material constitutive laws are applied to gain horizontal shear strength while considering the tension-stiffening and softening effects of concrete struts. A simplified method of calculating the shear strength is proposed, which was validated by comparing it with the related design code provisions. As a result, it was confirmed that the method generally shows a similar tendency to the experimental results when the shear reinforcing bar yields, unlike the regulations of the design code, where differences in the predicted value of shear strength occur according to the shear reinforcement ratio.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.3
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• pp.59-70
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• 2021

With the recent advancements in the Internet of Things, context-aware system that provides customized services become important to consider. The existing context-aware systems analyze data generated around the user and abstract the context information that expresses the state of situations. However, these datasets is mostly unstructured and have difficulty in processing with simple approaches. Therefore, providing context-aware services using the datasets should be managed in simplified method. One of examples that should be considered as the unstructured datasets is a deep learning application. Processes in deep learning applications have a strong coupling in a way of abstracting dataset from the acquisition to analysis phases, it has less flexible when the target analysis model or applications are modified in functional scalability. Therefore, an abstraction model that separates the phases and process the unstructured dataset for analysis is proposed. The proposed abstraction utilizes a description name Analysis Model Description Language(AMDL) to deploy the analysis phases by each fat client is a specifically designed instance for resource-oriented tasks in edge computing environments how to handle different analysis applications and its factors using the AMDL and Fat client profiles. The experiment shows functional scalability through examples of AMDL and Fat client profiles targeting a vehicle image recognition model for vehicle access control notification service, and conducts process-by-process monitoring for collection-preprocessing-analysis of unstructured data.

• Composites Research
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• v.34 no.4
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• pp.233-240
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• 2021

VaRI(Vacuum assisted Resin Infusion) process, which is cost effective and suitable for manufacturing large-sized composites, is an OoA(Out-of Autoclave) process. For rapid resin infusion in the VaRI process, a DM(distribution media) is placed on top of the fabric. The resin is rapidly supplied in plane direction of the fiber along the DM, and then the supplied resin is impregnated in the out-of-plane direction of fiber. It is difficult to predict the flow of resin because the flow of in-plane direction and the out-of-plane direction occur together, and a 3D numerical analysis program is used to simulate the resin infusion process. However, in order to analyze in 3D, many elements are required in the out-of-plane direction of fabric. And the product size is larger, the longer the analysis time needs. Therefore, in this study, a method was suggested to reduce the time required for flow analysis by simplifying the 3D flow analysis to 2D flow analysis. The usefulness was verified by comparing the 3D flow analysis with the simplified 2D flow analysis at the same conditions. The filling time error was about 7% and the reduction of flow analysis time was about 95%. In addition, by utilizing the constant difference in the flow front between the top, middle, and bottom of the fabric of the 3D analysis, the flow front of the top, middle, and bottom of the fabric can be also predicted in the 2D flow analysis.

• Journal of the Korean Society for information Management
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• v.38 no.4
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• pp.25-46
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• 2021

This study proposed the improvement in the evaluation systems and indicators of small libraries, by analyzing the evaluation indicators of the current small libraries, domestic and foreign ones and domestic other institutions, and gathering opinions from managers of them and experts belonging to related groups, in order to enhance the management quality of small libraries and strengthen the independence of them, based on the evaluation on the activation and substantiality of them. The evaluation systems proposed by this study is divided into Track 1 evaluating small libraries and Track 2 evaluating local governments. The evaluation indicators of small libraries was simplified by eliminating the indicators found from the statistics of Track 1 (small libraries). Track 1 consists of three evaluation areas in regard to the management of small libraries, such as library management, infrastructures and services, 8 evaluation items, 10 evaluation indicators, quantitative (a total of 100 points) and qualitative (a total of 120 points) evaluation. Track 2 consists of 2 evaluation areas in regard to the establishment and enforcement of small library policies and the support for small libraries, such as library management and infrastructures, 4 evaluation items, 5 evaluation indicators and quantitative evaluation (a total of 100 points).

• Journal of Practical Agriculture & Fisheries Research
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• v.22 no.2
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• pp.135-146
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• 2020

In the strawberry cultivation areas and domestic farms, two-spotted spider mites are the most serious pests. It decreases the product yield due to the direct feeding of chlorophyll by the mites resulting in reduced photosynthetic ability of host plant. In this study, a simplified acaricidal effect evaluation system (SAEES) was employed to choose the effective acaricidal products among 10 items based on leaf-dipping bioassay methods. SAEES had the advantage of being able to screen four commercial products with three replications at the same time in the recommended concentration. The susceptible strains (SL_YS) showed a high mortality rate of about 90-100%, whereas the mortality of local strains was differed by each acaricides. It suggests that the acaricide responses of field populations might differ due to spray frequencies and acaricide product. An efficacy index (0.8-1.0) was determined based on the mortality of susceptible strain, which would allow the most effective commercial products to be selected by the range of this index. In summary, SAEES will enable the selection of effective commercial products and contribute to increasing control against T. urticae in strawberries.

• Smart Media Journal
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• v.11 no.5
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• pp.17-25
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• 2022

Korean part-of-speech taggers decompose a compound morpheme into unit morphemes and attach part-of-speech tags. So, here is a disadvantage that part-of-speech for morphemes are over-classified in detail and complex word types are generated depending on the purpose of the taggers. When using the part-of-speech tagger for keyword extraction in deep learning based language processing, it is not required to decompose compound particles and verb-endings. In this study, the part-of-speech tagging problem is simplified by using a Head-Tail tokenization technique that divides only two types of tokens, a lexical morpheme part and a grammatical morpheme part that the problem of excessively decomposed morpheme was solved. Part-of-speech tagging was attempted with a statistical technique and a deep learning model on the Head-Tail tokenized corpus, and the accuracy of each model was evaluated. Part-of-speech tagging was implemented by TnT tagger, a statistical-based part-of-speech tagger, and Bi-LSTM tagger, a deep learning-based part-of-speech tagger. TnT tagger and Bi-LSTM tagger were trained on the Head-Tail tokenized corpus to measure the part-of-speech tagging accuracy. As a result, it showed that the Bi-LSTM tagger performs part-of-speech tagging with a high accuracy of 99.52% compared to 97.00% for the TnT tagger.

• Journal of the korean academy of Pediatric Dentistry
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• v.48 no.4
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• pp.405-413
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• 2021

The purpose of this in vivo study was to assess the clinical screening performance of a quantitative light-induced fluorescence (QLF) device in detecting proximal caries in primary molars. Fluorescence loss, red autofluorescence and a simplified QLF score for proximal caries (QS-proximal) were evaluated for their validity in detecting proximal caries in primary molars compared to bitewing radiography. Three hundred and forty-four primary molar surfaces were included in the study. Carious lesions were scored according to lesion severity assessed by visual-tactile and radiographic examinations. The QLF images were analyzed for two quantitative parameters, fluorescence loss and red autofluorescence, as well as for QS-proximal. For both quantitative parameters and QS-proximal, the sensitivity, specificity and area under receiver operating curve (AUROC) were calculated as a function of the radiographic scoring index at enamel and dentin caries levels. Both quantitative parameters showed fair AUROC values for detecting dentine level caries (△F = 0.794, △R = 0.750). QS-proximal showed higher AUROC values (0.757 - 0.769) than that of visual-tactile scores (0.653) in detecting dentine level caries. The QLF device showed fair screening performance in detecting proximal caries in primary molars compared to bitewing radiography.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.5
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• pp.367-380
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• 2022

In this study, the periodic and simplified update and production way of the ECVAM (Environmental Conservation Value Assessment Map) was presented through the classification of environmental values using KOMPSAT-3A satellite imagery and land cover map. ECVAM is a map that evaluates the environmental value of the country in five stages based on 62 legal evaluation items and 8 environmental and ecological evaluation items, and is provided on two scales: 1:25000 and 1:5000. However, the 1:5000 scale environmental assessment map is being produced and serviced with a slow renewal cycle of one year due to various constraints such as the absence of reference materials and different production years. Therefore, in this study, one of the deep learning techniques, KOMPSAT-3A satellite image, SI (Spectral Indices), and land cover map were used to conduct this study to confirm the possibility of establishing an environmental assessment map. As a result, the accuracy was calculated to be 87.25% and 85.88%, respectively. Through the results of the study, it was possible to confirm the possibility of constructing an environmental assessment map using satellite imagery, optical index, and land cover classification.