• Korean Journal of Soil Science and Fertilizer
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• v.43 no.6
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• pp.823-827
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• 2010

This study was conducted to assess the propriety of models for soil water characteristics estimation in anthropogenic soil through the measurement of soil water content and soil water matric potential. Soil profile was characterized with four different soil layers. Soil texture was loamy sand for the first soil layer (from soil surface to 30 cm soil depth), sand for the second (30~70 cm soil depth) and the third soil layers (70~120 cm soil depth), and sandy loam for the fourth soil layer (120 cm < soil depth). Soil water retention curve (SWRC), the relation between soil water content and soil water matric potential, took a similar trend between different layers except the layer of below 120 cm soil depth. The estimation of SWRC and air entry value was better in van Genuchten model by analytical method than in Brooks-Corey model with power function. Therefore, it could be concluded that van Genuchten model is more desirable than Brook-Corey model for estimating soil water characteristics of anthropogenic soil accumulated with saprolite.

• Journal of radiological science and technology
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• v.44 no.5
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• pp.545-554
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• 2021

According to the changes of the medical environment of the times, it is necessary to discuss the issues of the doctor's medical guidance and to conduct continuous research so that alternatives can be prepared systematically. Furthermore, in order to enhance the professionalism of radiological technologists and to develop the medical technician system, the new Radiological Technologist Independent Act has been established, which contains the overall contents of the scope of work, professional qualifications, and specialized education of radiological technologists, and provides quality medical services to patients through professional procedures and treatment. In order to increase the level of medical care, the purpose, definition, mission, role, and scope of work specified in the Medical Act, Medical Service Technologists, etc. Act, the Enforcement Decree, and the Enforcement Rules were variously analyzed and new directions were presented. First, the definition of a medical technician should use a generic term so that the factors of conflict and prejudice could be resolved. Second, change the doctor's guide to doctor's prescription; and then legislate the authority to sign and write medical records after examination by radiological technologists, thereby prohibiting unlicensed technicians that seriously endanger patient safety. Third, an accurate definition of radiological technologists' roles should be established; not only selection and management of radiological technologists' work but also procedures and treatment for each radiology field should be specified to suit the current medical system. Fourth, a professional radiological technologists' qualification system and a specialized education system should be established in order to secure human resources that could provide patients trust in procedures and treatment based on professional knowledge and experience in the field of radiology. Fifth, the Education and Evaluation Institute should be operated in Korea education system to educate the professional knowledge and competency for students. In addition, it is necessary to in-depth analysis of foreign cases could be applied to the medical system and education system in Korea; it could strive to nurture systematic human resources.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.10
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• pp.391-398
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• 2021

Since the leased line is a structure that exclusively uses two connected areas for data transmission, a stable quality level and security are ensured, and despite the rapid increase in the number of switched lines, it is a line method that is continuously used a lot in companies. However, because the cost is relatively high, one of the important roles of the network operator in the enterprise is to maintain the optimal state by properly arranging and utilizing the resources of the network leased line. In other words, in order to properly support business service requirements, it is essential to properly manage bandwidth resources of leased lines from the viewpoint of data transmission, and properly predicting and managing leased line usage becomes a key factor. Therefore, in this study, various prediction models were applied and performance was evaluated based on the actual usage rate data of leased lines used in corporate networks. In general, the performance of each prediction was measured and compared by applying the smoothing model and ARIMA model, which are widely used as statistical methods, and the representative models of deep learning based on artificial neural networks, which are being studied a lot these days. In addition, based on the experimental results, we proposed the items to be considered in order for each model to achieve good performance for prediction from the viewpoint of effective operation of leased line resources.

• The Journal of the Acoustical Society of Korea
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• v.40 no.5
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• pp.523-529
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• 2021

In this paper, we designed and developed an Emotional Speech Synthesis Markup Language (SSML) processor. Multi-speaker emotional speech synthesis technology that can express multiple voice colors and emotional expressions have been developed, and we designed Emotional SSML by extending SSML for multiple voice colors and emotional expressions. The Emotional SSML processor has a graphic user interface and consists of following four components. First, a multi-speaker emotional text editor that can easily mark specific voice colors and emotions on desired positions. Second, an Emotional SSML document generator that creates an Emotional SSML document automatically from the result of the multi-speaker emotional text editor. Third, an Emotional SSML parser that parses the Emotional SSML document. Last, a sequencer to control a multi-speaker and emotional Text-to-Speech (TTS) engine based on the result of the Emotional SSML parser. Based on SSML which is a programming language and platform independent open standard, the Emotional SSML processor can easily integrate with various speech synthesis engines and facilitates the development of multi-speaker emotional text-to-speech applications.

• Journal of Convergence for Information Technology
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• v.11 no.12
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• pp.1-13
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• 2021

This study tried to suggest ways to improve the indicator system to strengthen the personal information protection. For this purpose, the components of indicator system are derived through domestic and foreign literature, and it was selected as main the diagnostic indicators through FGI/Delphi analysis for personal information protection experts and a survey for personal information protection officers of public institutions. As like this, this study was intended to derive an inspection standard that can be reflected as a separate index system for personal information protection, by classifying the specific IT technologies of the 4th industrial revolution, such as big data, cloud, Internet of Things, and artificial intelligence. As a result, from the planning and design stage of specific technologies, the check items for applying the PbD principle, pseudonymous information processing and de-identification measures were selected as 2 common indicators. And the checklists were consisted 2 items related Big data, 5 items related Cloud service, 5 items related IoT, and 4 items related AI. Accordingly, this study expects to be an institutional device to respond to new technological changes for the continuous development of the personal information management level diagnosis system in the future.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.4
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• pp.28-36
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• 2021

It is known that buried rebars inside concrete structures are protected from corrosion due to passive layer. It is very important to delay the timing of corrosion or evaluate a detection of corrosion initiation for the purpose of cost-beneficiary service life of a structure. In this study, corrosion monitoring was performed on concrete specimens considering 3 levels of cover depth(60 mm, 45 mm, and 30 mm), W/C(water to cement) ratio(40.0%, 50.0%, and 60.0%) and chloride concentration(0.0%, 3.5%, and 7.0%). OCP(Open Circuit Potential) was measured using agar-based socket type sensors. The OCP measurement showed the consistent behavior where the potential was reduced in wet conditions and it was partially recovered in dry conditions. In the case of 30 mm of cover depth for most W/C ratio cases, the lowest OCP value was measured and rapid OCP recovery was evaluated in increasing cover depth from 30 mm to 45 mm, since cover depth was an effective protection against chloride ion ingress. As the chloride concentration increased, the effect on the cover depth tended to be more dominant than the that of W/C ratio. After additional monitoring and physical evaluation of chloride concentration after specimen dismantling, the proposed system can be improved with increasing reliability of the corrosion monitoring.

• Journal of the Korean Institute of Gas
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• v.25 no.3
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• pp.46-52
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• 2021

In this study, the on-site location identification and response system was proposed by accurately checking the location information of rescue requesters in the buildings using the smartphone Wi-Fi AP. The location server was requested to measure the strength of the Wi-Fi AP at least 25 times at 8 different building location points. And the accuracy of the position and the error range were checked by analyzing the coordinate values of the received positions. In addition, the response time was measured by changing the conditions of location information in three groups to compare the response time for saving lives with and without location information. The minimum and maximum error values for the eight cases were found to be at least 4.137 m and up to 14.037 m, respectively, with an average error of 9.525 m. Compared to the base transceiver station (BTS) based position error value of 263m, the range could be reduced by up to 93%. When the location information was given, it took 10 minutes and 50 seconds to save lives; however, when there was no location information at all, rescue process took more than 45 minutes. From this research effort, it was analyzed that the acquisition of the location information of rescuees in the building using the smartphone Wi-Fi AP approach is effective in reducing the life-saving time for on-site responses.

• Journal of Environmental Health Sciences
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• v.47 no.2
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• pp.111-122
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• 2021

Objectives: There was a judgment of acquittal for the manufacturer SK Chemical and the vendor Aekyung regarding humidifier disinfectant (HD) containing 5-chloro-2-methylisothiazol-3(2H)-one/2-methylisothiazol-3(2H)-one (CMIT/MIT). The rationale used in this judgement is discussed here in the light of scientific consideration. Methods: The sentencing document for the judgements was obtained from the Korea Supreme Court Service. In particular, the judgements made by the court related to the risk of HD and external and internal exposure to CMIT/MIT are discussed based on scientific evidence. Results: Rendering a determination in a criminal trial of insufficient evidence of causation, the court dismissed the prosecution's motion that humidifier disinfectant-associated lung injuries (HDLI) and asthma were associated with the utilization of these products. However, CMIT/MIT, a strong sensitizing and corrosive substance, has been reported to be associated with brain toxicity, allergic contact dermatitis, and asthma. Furthermore, the judgment did not consider total consumption amounts or the cumulative dose of CMIT/MIT in the humidifier. Lastly, there are several cases supporting the fact that exposure to water-soluble substances including CMIT/MIT can cause lower respiratory tract diseases. In addition to cases of asthma among the workers exposed to CMIT/MIT, we identified lung injury victims who were exposed to HDs exclusively containing CMIT/MIT. Conclusions: We conclude that there is sufficient evidence supporting the assertion that HDs containing CMIT/MIT cause lung injuries, including asthma, contrary to the court's judgement.

• Journal of Digital Convergence
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• v.17 no.6
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• pp.219-227
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• 2019

This study aims to examine Blockchain research trend using bibliometrics-based network analysis. The data were collected from WoS, Scopus, Korea Citation Index and National science & Technology Information Service, from 2009 to 2018. As results, the number of publications has started increasing rapidly from 2017 and it showed the initial stage of formation of coauthor network. Words often used in the title of the publications were related to application development, controversy and technology development. In addition, the majority of domestic papers are in the subject of social science, while international papers tend to focus on engineering issues. The results of the temporal analysis show that Korean researchers' block chain 3.0 started in 2017 and are rapidly increasing in 2018. The number of citations was associated with publication year in a statistically signifiant way. By examining these research trends, we hope that this paper can be a useful basis for the development of blockchain. Future research is expected to reveal more clearly the knowledge structure and characteristics of blockchain around the world.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2060-2077
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• 2019

Recently, mobile healthcare services have attracted significant attention because of the emerging development and supply of diverse wearable devices. Smartwatches and health bands are the most common type of mobile-based wearable devices and their market size is increasing considerably. However, simple value comparisons based on accumulated data have revealed certain problems, such as the standardized nature of health management and the lack of personalized health management service models. The convergence of information technology (IT) and biotechnology (BT) has shifted the medical paradigm from continuous health management and disease prevention to the development of a system that can be used to provide ground-based medical services regardless of the user's location. Moreover, the IT-BT convergence has necessitated the development of lifestyle improvement models and services that utilize big data analysis and machine learning to provide mobile healthcare-based personal health management and disease prevention information. Users' health data, which are specific as they change over time, are collected by different means according to the users' lifestyle and surrounding circumstances. In this paper, we propose a prediction model of user physical activity that uses data characteristics-based long short-term memory (DC-LSTM) recurrent neural networks (RNNs). To provide personalized services, the characteristics and surrounding circumstances of data collectable from mobile host devices were considered in the selection of variables for the model. The data characteristics considered were ease of collection, which represents whether or not variables are collectable, and frequency of occurrence, which represents whether or not changes made to input values constitute significant variables in terms of activity. The variables selected for providing personalized services were activity, weather, temperature, mean daily temperature, humidity, UV, fine dust, asthma and lung disease probability index, skin disease probability index, cadence, travel distance, mean heart rate, and sleep hours. The selected variables were classified according to the data characteristics. To predict activity, an LSTM RNN was built that uses the classified variables as input data and learns the dynamic characteristics of time series data. LSTM RNNs resolve the vanishing gradient problem that occurs in existing RNNs. They are classified into three different types according to data characteristics and constructed through connections among the LSTMs. The constructed neural network learns training data and predicts user activity. To evaluate the proposed model, the root mean square error (RMSE) was used in the performance evaluation of the user physical activity prediction method for which an autoregressive integrated moving average (ARIMA) model, a convolutional neural network (CNN), and an RNN were used. The results show that the proposed DC-LSTM RNN method yields an excellent mean RMSE value of 0.616. The proposed method is used for predicting significant activity considering the surrounding circumstances and user status utilizing the existing standardized activity prediction services. It can also be used to predict user physical activity and provide personalized healthcare based on the data collectable from mobile host devices.