• Korean Institute of Interior Design Journal
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• v.22 no.1
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• pp.211-221
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• 2013

As the result of investigating domestic interior design (interior architecture) field-related laws, it was found that interior design (interior architecture) is not recognized as in independent area due to weak classification standards by Korean standard industrial classification and job classification. Korean standard industrial classification is applied as a standard setting limits to applicable targets and industrial fields for laws related to general administration and industrial policy other than various statistic purposes. Also, the standard industrial classifications regarding the industry field determines the laws or applicable tax rates, government support and such according to the classification, and thus is very important. Moreover, interior architecture field is largely different from general architecture due to specialization and distinct characteristics, but due to the comprehensive concept of architecture industry regulations, it is considered the proper assessment for the professionalism is not conducted. Also, interior architecture field has irrational contradictions that is not independent with a clear definition and industry field classification not only in legal system and trade customs. Therefore, The following is proposed as the plan to strengthen the domestic/international competitiveness and system improvements for interior architecture. (1)interior design (interior architecture) must be amended as an industrial classification that can coexist with architecture. (2)interior design (interior architecture) must be amended as a job classification that can coexist with architecture. (3)Among the design tasks of an architect, approval for the design task field of interior architecture field must be legislated. -In architect design standard contract (the existing architecture design task scope and quality standard table) of a structure, among the tasks by request of the owner, (1)interior design tasks shall be legislated. It should be legislated so that interior design (interior architecture) majors can be included as well. (4)The task field of interior design that coexists with design must be amended. (5)National contract law - among contract method by negotiation, specialty item must be vitalized.

• Explosives and Blasting
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• v.24 no.1
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• pp.63-69
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• 2006

Building tunnels means dealing with what rock is encountered. Relocation of the site of the underground structure is rarely possible. Tunneling engineers and miners have to cope with the quality of the rock mass as it is. Different tunneling philosophies and different rock classification methods have been developed in various countries. Most of the rock classification methods are based on the response of the rock mass to the excavation. Tunnel support requirements could be assessed analytically, supplemented by rock mass classification predictions, and verified by measurements during construction. Rock mass classifications on their own should only be used for preliminary, planning purposes and not for final tunnel support. Design of blast pattern in tunneling projects in Korea is also mostly prepared according to the general rock classification methods such as RMR or Q. They, however, do not take into account the blast performance, and as a consequence, produce poor blasting results. In this paper, the methods of general rock classification and blast design for tunnel excavation in Korea are reviewed, and efforts to develop a new classification method, reflecting the blasting performance, are presented.

• Science of Emotion and Sensibility
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• v.26 no.4
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• pp.3-14
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• 2023

Recently, the effect of using social media on psychological well-being has been highlighted. However, studies exploring factors that may predict the quality of social media relationships are relatively rare. The present study investigated whether social media activity and psychological states, such as loneliness and depression, can predict the quality of social media relationships during the COVID-19 quarantine period using a machine learning technique. Ninety-five participants completed a self-report survey on loneliness, Instagram activity, quality of social media relationships, and depression at different time points (during the self-isolation and after the release of self-isolation). Similarity analyses, including multidimensional scaling (MDS), representational similarity analysis (RSA), and classification analyses, were conducted separately at each point in time. The results of MDS revealed that time spent on social media and depression were distinguished from others in the first dimension, and loneliness and passive use were distinguished from others in the second dimension. We divided the data into two groups based on the quality of social media relationships (high and low), and we conducted RSA on each group. Findings indicated an interaction between the quality of the social media relationships and the situation. Specifically, the effect of self-isolation on the high-quality social media relationship group is more pronounced than that on the low-quality group. The classification results also revealed that the predictors of social media relationships depend on whether or not they are isolated. Overall, the results of this study imply that social media relationship could be well predicted when people are not in isolated situations.

• Journal of Biomedical Engineering Research
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• v.42 no.3
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• pp.80-85
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• 2021

We developed a model to classify the absence of cervical cancer using deep learning from the cervical image to which the histogram equalization algorithm was applied, and to compare the performance of each model. A total of 4259 images were used for this study, of which 1852 images were normal and 2407 were abnormal. And this paper applied Image Sharpening(IS), Histogram Equalization(HE), and Contrast Limited Adaptive Histogram Equalization(CLAHE) to the original image. Peak Signal-to-Noise Ratio(PSNR) and Structural Similarity index for Measuring image quality(SSIM) were used to assess the quality of images objectively. As a result of assessment, IS showed 81.75dB of PSNR and 0.96 of SSIM, showing the best image quality. CLAHE and HE showed the PSNR of 62.67dB and 62.60dB respectively, while SSIM of CLAHE was shown as 0.86, which is closer to 1 than HE of 0.75. Using ResNet-50 model with transfer learning, digital image-processed images are classified into normal and abnormal each. In conclusion, the classification accuracy of each model is as follows. 90.77% for IS, which shows the highest, 90.26% for CLAHE and 87.60% for HE. As this study shows, applying proper digital image processing which is for cervical images to Computer Aided Diagnosis(CAD) can help both screening and diagnosing.

• Journal of Korean Society for Quality Management
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• v.50 no.1
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• pp.77-89
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• 2022

Purpose: In order to improve the audit quality of a company, an in-depth analysis is required to categorize the audit report in the form of a text document containing the details of the external audit. This study introduces a systematic methodology to extract keywords for each group that determines the differences between groups such as 'audit plan' and 'interim audit' using audit reports collected in the form of text documents. Methods: The first step of the proposed methodology is to preprocess the document through text mining. In the second step, the documents are classified into groups using machine learning techniques and based on this, important vocabularies that have a dominant influence on the performance of classification are extracted. In the third step, the association rules for each group's documents are found. In the last step, the final keywords for each group representing the characteristics of each group are extracted by comparing the important vocabulary for classification with the important vocabulary representing the association rules of each group. Results: This study quantitatively calculates the importance value of the vocabulary used in the audit report based on machine learning rather than the qualitative research method such as the existing literature search, expert evaluation, and Delphi technique. From the case study of this study, it was found that the extracted keywords describe the characteristics of each group well. Conclusion: This study is meaningful in that it has laid the foundation for quantitatively conducting follow-up studies related to key vocabulary in each stage of auditing.

• Journal of Korean Society for Atmospheric Environment
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• v.18 no.1
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• pp.25-37
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• 2002

The purpose of the study was to survey the distribution patterns of inorganic elements of PM-10 in the various indoor environments and analyze the pollution patterns of aerosol in various places of indoor environment using a pattern recognition method based on cluster analysis and disjoint principal component analysis. A total of 40 samples in the indoor had been collected using mini-vol portable samplers. These samples were analyzed for their 19 bulk inorganic compounds such as B, Na, Mg, Al, K, Ca, Ti, V, Cr, Fe, Ni, Cu, Zn, As, Se, Cd, Ba, Ce, and Pb by using an ICP-MS. By applying a disjoint principal component analysis, four patterns of the indoor air pollutions were distinguished. The first pattern was identified as a group with high concentrations of PM-10, Na, Mg, and Ca. The second pattern was identified as a group with high concentrations B, Mg, At, Ca, Fe, Cu, and Ba. The third pattern was a group of sites with high concentrations of K, Zn. Cd. The fourth pattern was a group with low concentrations PM-10 and all inorganic elements. This methodology was found to be helpful enough to set the criteria standard of indoor air quality, corresponding pollutants, and classification of indoor environment categories when making an indoor air quality law.

• Quality Improvement in Health Care
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• v.23 no.2
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• pp.69-78
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• 2017

Background: The purpose of this study was to examine associations between classification of the Geriatric Screening for Care-10 (GSC-10) and the Morse Fall Scale (MFS) among elderly inpatients. Methods: Among elderly inpatients aged over 65 admitted to hospital (from November 1, 2016 to July 31, 2017), the data for 5,780 patients (who were evaluated using the Morse Fall Scale and the Geriatric Screening for Care-10) were analyzed using x2-tests and t-tests to examine differences between the GSC-10 and MFS, according to general characteristics of elderly inpatients (i.e., gender) using IBM SPSS Statistics 24. Results: : Scores for the GSC-10 were significantly higher in women than men for depression (p<.001), delirium (p=.048), functional decline (p<.001), incontinence (p<.001), and pain (p<.001). Statistically significant differences in all domains of the GSC-10 for elderly hospitalized patients were found for the classification of fall risk. Conclusion: The findings of this study, as supported by the GSC-10, indicate that the most common problems experienced by the elderly are related to the risk of falling. In order to reduce the incidence of falls in elderly inpatients, customized fall prevention based on the GSC-10 results is necessary.

• Journal of Environmental Impact Assessment
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• v.22 no.3
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• pp.195-201
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• 2013

Local governments are establishing their own greenhouse gas reduction goal and are playing a important role to respond to climatic changes. However, there are difficulties in quantitative analyses such as estimation of future greenhouse gas emission and computation of reduction potential, which are procedures required to establish mid to long term strategies to realize of low carbon society by each local governments. Also, reduction measures must reflect characteristics of each local government, since the reduction power of each local government can differ according to characteristics of each. In order to establish strategies that reflect characteristics of local governments, types of greenhouse gas emission from cities were classified largely into residential city, commercial city, residential commercial city, agriculture and fishery city, convergence city, and industrial city. As a result of analyzing basic unit of greenhouse gas emission by local government during 2007 in terms of per population, household and GRDP based on the type classification, significant results were deduced for each type. To manage the amount of the national greenhouse gas, reduction measures should be focused on the local governments that emits more than the average of each type's GHG emission.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.4
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• pp.66-77
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• 2003

Monitoring data from agricultural reservoirs throughout the country were analyzed to classify agricultural reservoirs according to physical characteristics and COD concentrations, and evaluate the relationships bet-ween water quality items. The physical and chemical data of total 498 reservoirs were analyzed from 1990 to 2001. Average COD, TP, TN, Chl-a, SS concentrations for the reservoirs and pollutant loadings from their watersheds were used for the analysis. It was possible that reservoirs were classified to 4 types using the relationships between the ratios of effective storage per water surface (ST/WS ratio) and COD concentrations. It is recommended that the improvement measures of polluted reservoirs should be performed as following order : integrated consolidation type (complex mechanism type) $\rightarrow$ watershed consolidation type $\rightarrow$ integrated consolidation type (external mechanism type) $\rightarrow$ in-lake consolidation type $\rightarrow$ conservation type and the depth (ST/WS ratio) of reservoir maintained over 5~6 m for water quality improvement. The decision coefficients ($r^2$) between Chl-a and other items (COD, T-P, SS, T-N) were 0.6915, 0.6732, 0.5327, 0.3352, respectively. Therefore, reservoir managers could evaluate the trophic state of reservoirs by COD concentrations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.257-271
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• 2016

The Structural SIMilarity (SSIM) index is one of the most widely-used methods for perceptual image quality assessment (IQA). It is based on the principle that the human visual system (HVS) is sensitive to the overall structure of an image. However, it has been reported that indices predicted by SSIM tend to be biased depending on the type of distortion, which increases the deviation from the main regression curve. Consequently, SSIM can result in serious performance degradation. In this study, we investigate the aforementioned phenomenon from a new perspective and review a constant that plays a big role within the SSIM metric but has been overlooked thus far. Through an experimental study on the influence of this constant in evaluating images with SSIM, we are able to propose a new solution that resolves this issue. In the proposed IQA method, we first design a system to classify different types of distortion, and then match an optimal constant to each type. In addition, we supplement the proposed method by adding color perception-based structural information. For a comprehensive assessment, we compare the proposed method with 15 existing IQA methods. The experimental results show that the proposed method is more consistent with the HVS than the other methods.