• Journal of Convergence for Information Technology
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• v.9 no.6
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• pp.1-6
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• 2019

In this study, the development of a weight estimation model of electronic scale with nonlinear characteristics is presented using polynomial regression analysis. The output voltage of the load cell was measured directly using the reference mass. And a polynomial regression model was obtained using the matrix and curve fitting function of MS Office Excel. The weight was measured in 100g units using a load cell electronic scale measuring up to 5kg and the polynomial regression model was obtained. The error was calculated for simple($1^{st}$), $2^{nd}$ and $3^{rd}$ order polynomial regression. To analyze the suitability of the regression function for each model, the coefficient of determination was presented to indicate the correlation between the estimated mass and the measured data. Using the third order polynomial model proposed here, a very accurate model was obtained with a standard deviation of 10g and the determinant coefficient of 1.0. Based on the theory of multi regression model presented here, it can be used in various statistical researches such as weather forecast, new drug development and economic indicators analysis using logistic regression analysis, which has been widely used in artificial intelligence fields.

• Journal of Platform Technology
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• v.9 no.2
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• pp.38-45
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• 2021

A frequently used bioimpedance analytical method in Korea is the segmental multi-frequency BIA (SMF-BIA) method, but it is not directly determined at a segmented impedance. This study was to compare SMF-BIA determinations with direct segmented determinations for accuracy and appropriateness of segment parameters. This study is to compare the segment parameters, accuracy and appropriateness of the multi-frequency segmental bioimpedance analysis. To this end, 108 elderly individuals were measured. Segmented bioelectrical measurements obtained from a SMF-BIA (Inbody S10) at 50 kHz and measured with a phase sensitive single frequency device (SF-BIA, bia-101, RJL / akern systems) were compared. The significant difference (%) was demonstrated between single - and multiple frequency determinations of the right upper limb (R = 35.5 ± 6.2%, P < 0.001; Xc = 2.7 ± 7.6%, P < 0.01), left upper limb difference (R= 33. 9 ± 6.0%, P < 0.001; Xc = 2.8 ± 8.3%, P < 0.01), right lower limb difference (R = 18.6 ± 4.3%, P < 0.001; Xc = 25.8 ± 10.0%, P < 0.001), left lower limb difference (R = 18.0 ± 4.7%, P < 0.001; Xc = 31.8%). Of the results determined with the two BIA methods, the impedance measurements of the limbs and whole body showed a high correlation (RA: R = 0. 950, LA: R = 0. 949, RL: R = 0.899, LL: R = 0.88), and in the agreement test, the impedance values of the upper limbs and whole body also showed strong agreement (ICC > 0.9), but in the Xc, the correlation was weak. In conclusion, it was found that although bioimpedance devices had significantly different characteristics and inconsistent cross sectionally, there was a high population level agreement in the upper and lower extremities in determining segmental resistance value changes. But a large error was found on the trunk. Further studies were needed for reducing the error.

• Journal of Platform Technology
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• v.8 no.3
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• pp.10-21
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• 2020

Partial discharge occurs a lot in high-voltage power equipment such as switchgear, transformers, and switch gears. Partial discharge shortens the life of the insulator and causes insulation breakdown, resulting in large-scale damage such as a power outage. There are several types of partial discharge that occur inside the product and the surface. In this paper, we design a predictive model that can predict the pattern and probability of occurrence of partial discharge. In order to analyze the designed model, learning data for each type of partial discharge was collected through the UHF sensor by using a simulator that generates partial discharge. The predictive model designed in this paper was designed based on CNN during deep learning, and the model was verified through learning. To learn about the designed model, 5000 training data were created, and the form of training data was used as input data for the model by pre-processing the 3D raw data input from the UHF sensor as 2D data. As a result of the experiment, it was found that the accuracy of the model designed through learning has an accuracy of 0.9972. It was found that the accuracy of the proposed model was higher in the case of learning by making the data into a two-dimensional image and learning it in the form of a grayscale image.

• Journal of the Korea Convergence Society
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• v.12 no.3
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• pp.177-186
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• 2021

The 2015 revised curriculum is structured around the core competencies of the 21st century, this is in line with the world's flow of education, such as OECD Education 2030. A future practical leading model was studied to provide a variety of creative teaching and learning experiences to elementary and Secondary students using intelligent information technology to cultivate core competencies such as ICT and computing thinking. In order for this practical model to stably settle the school field, the training was planned and operated to strengthen the creative convergence education capacity required by the teachers at the unit school through various types of the training. In particular, a nationwide administrators training program was operated for three years, reflecting the new curriculum, teaching and learning methods, and evaluation that can lead to future convergence talent training. In this paper, the perception of creative convergence education was investigated and analyzed considering the influence that administrators may have on the school field. Based on this, through the three-year operation results of the training, it was intended to establish a new training method for stable access to future creative convergence education under the post-corona era's social issues.

• Journal of the Korea Convergence Society
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• v.12 no.3
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• pp.247-259
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• 2021

This study aimed to look for educational ways to prepare for the future society for education and people of talent who will lead the post-COVID-19 era. To this end, the factors necessary for the type of future talent in the post-COVID-19 era were identified by analyzing Big data. Based on the deducted factors composing the type of talent in the post-COVID-19 era, policy direction according to the emergence of the post-COVID-19 era were deducted through the interviews with the group of experts and delphi survey, and on the basis of this, this study sought for"a plan for the educational change in line with cultivation of people of talent in the post-COVID-19 era. The results of this study are as follows. First, through the big data analytics and analysis of the interviews, convergence, ICT utilization ability, creativity, self-regulated competency and leadership were found to be the factors necessary for the type of talent in the post-COVID-19 era. Second, it considered the innovation of digital education system and the support for vulnerable classes as the issue for cultivation of people of talent in the post-COVID-19 era. Third, the most important policy with regard to the educational direction for cultivation of people of talent in the post-COVID-19 era was cultivation of convergence talents. Convergence is a very important variable in the post-COVID-19 era since it creates new values by connecting things that are separated from each other. Hopefully, this study will build a basis for competency development, education and training in preparation for the post-COVID-19 era.

• Therapeutic Science for Rehabilitation
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• v.10 no.3
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• pp.23-41
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• 2021

Objective : The purpose of this study was to analyze the effects of simultaneous dual-task training to assess executive function in older adults. Methods : We searched the PubMed, EMBASE, Cochrane, Web of Science, and RISS databases of publicated studies in the past decade. Seven studies were selected based on the inclusion and exclusion criteria. Qualitative assessment and meta-analysis were performed for the seven studies. Results : A randomized controlled trial design was used in the selected studies, and PEDro Scores above seven were obtained. The Trial Making Test (TMT) evaluated the effects of dual-task training on executive function in four studies. The Color Trail Test (CTT) was used in two studies, and Stroop test was used in three studies. The effect size for total executive function was 0.38, which was small. The effect sizes for TMT and CTT were 0.37. Stroop Test was 0.34, demonstrating that their effect sizes were also small. Only significant effects in total executive function, TMT, and CTT showed significant effects (all p<0.05). Conclusion : This study confirmed that dual-task training was effective in improving executive function in older adults. To improve the effectiveness of dual-task training, the difficulty of the dual-task training should be considered. It is also necessary to implement assessments that can evaluate performance under dual-task conditions as well as conventional test tools for executive function. In the future, dual-task training could be used as an appropriate intervention for executive function in older adults to delay the onset of dementia.

• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.233-244
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• 2022

One of the most noteworthy topics in recent corporate management is ESG(Environmental, Social, Governance). Although there are many companies that have declared ESG management, KT has declared full-fledged ESG management in 2021 and is sharing its sustainable management strategy with stakeholders. In addition, KT is strengthening ESG management by issuing ESG bonds for the first time in the domestic ICT industry. At a time when the information technology industry became more important due to COVID-19, this study attempted to examine KT's ESG management goals and strategies by dividing them into environmental, social, and governance areas. KT was aiming to achieve environmental integrity through 'environmental management', 'green competence', 'energy resources', and 'eco-friendly projects' in the environmental field. In addition, in the social field, genuine creating social value was pursued through 'social contribution', 'co-growth', and 'human rights management'. Finally, in the governance area, it was aiming for a transparent corporate management system to pursue economic reliability through 'ethics and compliance' and 'risk management'. In particular, KT was promoting its own ESG management by promoting strategies to solve environmental and social problems using AI and BigData technologies based on the characteristics of a digital platform company. This study aims to derive implications for ESG strategy establishment and ESG management development direction through KT's ESG management case in relation to ESG management, which has emerged as a hot topic.

• Journal of Wetlands Research
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• v.24 no.1
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• pp.38-43
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• 2022

Smart sewage treatment plant means creating a safe and clean water environment by establishing an ICT-based real-time monitoring, remote control management and intelligent system for the entire sewage treatment process. The core technology of such a smart sewage treatment plant can be operation control technology using measuring instruments. This research team analyzed and suggested the operation control technologies necessary for the establishment of the intelligent business by referring to the intelligent research projects of the sewage treatment plant in progress in Korea. As a result of the analysis, a total of six removal technologies were presented, including control by scale, reflow water control, linked treated water control, chemical quantity control, winter operation control, and total organic carbon control. By size, standards that can be classified into small and medium-sized large-scale are presented, and in the case of reflow water control, the location of water quality and flow sensors capable of managing reflow water is suggested. In the case of the linked treated water control, the influence and control points of the linked treated water on the sewage treatment plant were presented, and in the case of the chemical injection volume control, a system capable of optimizing the amount of chemical injection according to the introduction of an intelligent sewage treatment plant was presented. In the case of winter operation, the sensors and pumps to be controlled are suggested when considering the decrease in nitrification due to the decrease in water temperature. In the case of total organic carbon control, an interlocking system considering the total amount of pollution in the future was proposed. These operation control scenarios are expected to be used as basic data to be used in intelligent sewage treatment algorithms and scenarios in the future.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.4
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• pp.113-126
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• 2021

This study was conducted to analyze the forest status and deforestation area changes of the DMZ region in North Korea based on satellite images. Using growing and non-growing season's RapidEye satellite images, land cover of the North Korean DMZ was classified into stocking land(conifer, deciduous, mixed), deforested land(unstocked mountain, cultivated mountain, bare mountain), and non-forest areas. Deforestation rates in the Yeonan-baecheon, Beopdong-Pyeonggang, Heoyang-Geumgang and Tongcheon-Goseong district were calculated as 14.24%, 16.75%, 5.98%, and 16.63% respectively. Forest fire and land use change of forest were considered as the main causes of deforestation of DMZ. Changes in deforestation area were analyzed through Google Earth images. As a results, it was shown that the area of deforestation was on a decreasing trend. This study can be used as basic data for establishing inter-Korean border region's forest cooperation strategies by providing forest spatial information on the North Korea's DMZ.

• Journal of Practical Agriculture & Fisheries Research
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• v.23 no.2
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• pp.51-61
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• 2021

As a result of examining the germination rate between ginseng varieties, Jagyongjong varieties had the highest germination rate, and Yeonpung. had the lowest germination rate. In the ginseng seed germination rate experiment, the highest germination rate and growth condition were shown in artificial soil conditions of the ratio of Peatmoss 6.5: Pearlite 2: Masato 1.5. Good soil conditions require adequate soil moisture forces during the incubation period. The cultivation of ginseng medicinal crops requires optimal soil breathability, soil pH, and soil stabilization, which are important for root breathing. Microbial activity in the soil has a great influence on the growth of ginseng. The optimum pH of the soil for ginseng cultivation is 5.0-5.5 As a result of the experiment, the soil remained in an appropriate range after a month. In general, when the EC concentration value of the soil for ginseng cultivation is 0.2 mS/cm or more, growth deteriorates, and when the EC concentration value is 0.5 mS/cm or more, concentration obstacles such as root decay occur. As a result of the analysis, the higher the concentration value of EC, the more likely it is to interfere with ginseng growth.