• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.11 no.8
• /
• pp.1456-1464
• /
• 2007

The research of skin-tone detection has been conducting continuously to enlarge the importance in security, surveillance and administration of the information and 'Password Control System' for using face and skin recognition in airports, harbors and general companies. As well as tile rapid diffusion of the application range in image communications and an electron transaction using wide range of communication network, the importance of the accurate detection of skin color has been augmenting recently. In this paper, it will set up the boundaries of skin colors using the information of Cb and Cr in YCbCr color model of human skin color which is from hundreds compiled portrait images for each race, and suggest a efficient yet simple structure about the skin detection which has been followed by whether the comprehension of the boundaries of skin or not with adaptive skin-range set. With the possibility of the 1D Processes which does not use any memory, it is able to be applied to relatively small-sized hardware and system such as mobile apparatuses. To add the selective mode, it is not only available the improvement of tie skin detection, but also showing the correspondent results about previous face recognition technologies using complicated algorithm.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.63 no.6
• /
• pp.77-88
• /
• 2021

Duck industry had a rapid growth in recent years. Nevertheless, researches to improve duck house environment are still not sufficient enough. Moisture generation of duck house litter is an important factor because it may cause severe illness and low productivity. However, the measuring process is difficult because it could be disturbed with animal excrements and other factors. Therefore, it has to be calculated according to the environmental data around the duck house litter. To cut through all these procedures, we built several machine learning regression model forecasting moisture generation of litter by measured environment data (air temperature, relative humidity, wind velocity and water contents). 5 models (Multi Linear Regression, k-Nearest Neighbors, Support Vector Regression, Random Forest and Deep Neural Network). have been selected for regression. By using R-Square, RMSE and MAE as evaluation metrics, the best accurate model was estimated according to the variables for each machine learning model. In addition, to address the small amount of data acquired through lab experiments, bootstrapping method, a technique utilized in statistics, was used. As a result, the most accurate model selected was Random Forest, with parameters of n-estimator 200 by bootstrapping the original data nine times.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.4
• /
• pp.551-563
• /
• 2019

This study examined the characteristics of a district through the concept of a block system in the physical aspect of the four land readjustment project districts of Cheongju City in the 1970s. The results of this study are as follows. First, the local road system for accessing the main road network and blocks was well established compared with the current urban development standards. On the other hand, since the access roads to the individual lots in the block were not equipped properly, it was difficult to improve a house. Second, according to the characteristics of the block, the Aspect Ratio of blocks was 1: 2 on average and most of those directions was east-west. The area of block from the 1st to 3rd districts was increasing, but districts 4 were decreasing. This also was changed to the shape of a contemporary block system. The larger the size of the block area, the lower the Jeobdoyul. Third, in terms of the characteristics of the lot array, blocks with a multi-row system of $4{\times}4$ or more were lots up to the 1st to 3rd district, but 4th district was improved greatly. Because blocks close a square shape have become excessively poor with Jeobdoyul, it was judged that it is difficult to improve the residential environment. Moreover, as the type of the residential development by the land readjustment project is standardized considerably and this type of land area is extensive, it can be an alternative to control the urban sprawl of suburbs if it finds the way to improve this type of the residential area considering this characteristic.

• Journal of the Korean Data Analysis Society
• /
• v.20 no.6
• /
• pp.3087-3099
• /
• 2018

Due to the constant changes of companies' global networks, the expansion of global e-commerce as well as the market-oriented global supply chain management, global enterprises are strategically selecting and entering into viable countries able to become global footholds. Therefore, this study aims to scrutinize the trend of changes in the global networks of Korean companies by analyzing the current overseas countries over the past decade. From the analysis, it has been found that there is a significant difference in the priorities of targeting countries among shipping, manufacturing and logistics companies. Logistics companies preferred to enter Germany first while they attached to a lower priority to Singapore. Manufacturing companies had a lower priority to advance to India, while they preferred to advance to Mexico; however, shipping companies were analyzed to prefer to enter the US. In addition, all of these companies identified the importance of securing volume and network by entering overseas markets to achieve economies of scale and scope and to maintain global competitiveness. Joint overseas expansion of manufacturers with shipping and logistics companies can be recommended to facilitate the entry and thus, enhance global competitiveness and service capabilities and also secure new growth engines.

• The Journal of the Korea Contents Association
• /
• v.20 no.12
• /
• pp.567-581
• /
• 2020

While Coronavirus (COVID-19) is popular all over the world, democratic citizenship is strongly highlighted as a factor that has enabled the Republic of Korea to successfully prevent it. Democratic citizenship can also be understood as a civility, which means respecting the individual's individuality, value and freedom, but at the same time pursuing common good based on healthy relationships with others in the community. It is true that despite the need for modern Christianity to practice this civility more gracefully and politely in the public sphere, some churches and Christians have failed to show it during the Corona crisis. Under these circumstances, this study made the following suggestions for the realization of communality through the practice of democratic citizenship beyond the privatization of modern Christianity. First, Christianity needs recognition as a public church and theological establishment of it. Second, modern Christianity needs to recognize the importance of a network society and practice public good more than ever. Third, modern Christianity should be able to provide a new lifestyle for the development of public character in the community. So the New Normal-era church should be able to restore its original churchlikeness by having a Christian identity and communicating gentlemanly in the public domain.

• Journal of the Korean Society of Radiology
• /
• v.15 no.4
• /
• pp.547-554
• /
• 2021

In order to quickly and accurately diagnose pneumonia on a chest X-ray image, different batch sizes of 4, 8, 16, and 32 were applied to the same Xception deep learning model, and modeling was performed 3 times, respectively. As a result of the performance evaluation of deep learning modeling, in the case of modeling to which batch size 32 was applied, the results of accuracy, loss function value, mean square error, and learning time per epoch showed the best results. And in the accuracy evaluation of the Test Metric, the modeling applied with batch size 8 showed the best results, and the precision evaluation showed excellent results in all batch sizes. In the recall evaluation, modeling applied with batch size 16 showed the best results, and for F1-score, modeling applied with batch size 16 showed the best results. And the AUC score evaluation was the same for all batch sizes. Based on these results, deep learning modeling with batch size 32 showed high accuracy, stable artificial neural network learning, and excellent speed. It is thought that accurate and rapid lesion detection will be possible if a batch size of 32 is applied in an automatic diagnosis study for feature extraction and classification of pneumonia in chest X-ray images using deep learning in the future.

• Journal of Korean society of Dental Hygiene
• /
• v.21 no.4
• /
• pp.467-479
• /
• 2021

Objectives: The purpose of this study was to investigate the awareness of the performance and necessity of oral health promotion activities and seek ways to revitalize the professional role of dental hygienists in oral healthcare for the efficient oral care of the elderly. Methods: Eighty-five dental hygienists in charge of oral health promotion projects at public health centers and 38 dental hygienists in network dental clinical trials were investigated for their learning experience, performance experience, feasibility, and necessity of dental hygienists for general and oral health service items for the elderly. The collected data were analyzed using frequency analysis, chi-square test, and Mann-Whitney U test. Results: The degree of performance possibility according to the learning experience and performance experience of the dental hygienist for the whole body and oral health promotion activity items for the elderly showed that the degree of performance possibility was higher among those with experience compared to the non-experienced person, and it was statistically significantly higher (p<0.05). Conclusions: The dental hygienist's professional oral health service is a necessary system to improve practical knowledge and skills and to provide a wide range of professional oral health services for the elderly.

• Journal of Internet Computing and Services
• /
• v.23 no.5
• /
• pp.69-78
• /
• 2022

As the use of Internet of Things (IoT) devices has expanded, digital forensics coverage of the National Police Agency has expanded to smart home areas. Accordingly, most of the existing studies conducted to acquire smart home platform data were mainly conducted to analyze local data of mobile devices and analyze network perspectives. However, meaningful data for evidence analysis is mainly stored on cloud storage on smart home platforms. Therefore, in this paper, we study how to acquire stored in the cloud in a Hey Home Air environment by extracting accessToken of user accounts through a cookie database of browsers such as Microsoft Edge, Google Chrome, Mozilia Firefox, and Opera, which are recorded on a PC when users use the Hey Home app-based "Hey Home Square" service. In this paper, the it was configured with smart temperature and humidity sensors, smart door sensors, and smart motion sensors, and artifacts such as temperature and humidity data by date and place, device list used, and motion detection records were collected. Information such as temperature and humidity at the time of the incident can be seen from the results of the artifact analysis and can be used in the forensic investigation process. In addition, the cloud data acquisition method using OpenAPI proposed in this paper excludes the possibility of modulation during the data collection process and uses the API method, so it follows the principle of integrity and reproducibility, which are the principles of digital forensics.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.34 no.6
• /
• pp.198-210
• /
• 2022

The southern strait of Jeju is a divergence point of the Tsushima Warm Current (TWC), and it is the starting point of the thermohaline circulation in the waters of the Korean Peninsula, affecting the size and frequency of marine disasters such as typhoons and tsunamis, and has a very important oceanographic impact, such as becoming a source of harmful organisms and radioactively contaminated water. Therefore, for an immediate response to these maritime disasters, real-time ocean observation is required. However, compared to other straits, in the case of southern Jeju, such wide area marine observations are insufficient. Therefore, in this study, surface current field of the southern strait of Jeju was calculated using High-Frequency radar (HF radar). the large surface current field is calculated, and post-processing and data improvement are carried out through APM (Antenna Pattern Measurement) and FOL (First Order Line), and comparative analysis is conducted using actual data. As a result, the correlation shows improvement of 0.4~0.7 and RMSE of about 1~19 cm/s. These high-frequency radar observation results will help solve domestic issues such as response to typhoons, verification of numerical models, utilization of wide area wave data, and ocean search and rescue in the future through the establishment of an open data network.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.29 no.5B
• /
• pp.397-408
• /
• 2009

In this study, a stochastic precipitation generation framework for simultaneous simulation of daily precipitation at multiple sites is presented. The precipitation occurrence at individual sites is generated using hybrid-order Markov chain model which allows higher-order dependence for dry sequences. The precipitation amounts are reproduced using Anscombe residuals and gamma distributions. Multisite spatial correlations in the precipitation occurrence and amount series are represented with spatially correlated random numbers. The proposed model is applied for a network of 17 locations in the middle of Korean peninsular. Evaluation statistics are reported by generating 50 realizations of the precipitation of length equal to the observed record. The analysis of results show that the model reproduces wet day number, wet and dry day spell, and mean and standard deviation of wet day amount fairly well. However, mean values of 50 realizations of generated precipitation series yield around 23% Root Mean Square Errors (RMSE) of the average value of observed maximum numbers of consecutive wet and dry days and 17% RMSE of the average value of observed annual maximum precipitations for return periods of 100 and 200 years. The provided model also reproduces spatial correlations in observed precipitation occurrence and amount series accurately.