• Journal of the Korea Society of Computer and Information
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• v.24 no.10
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• pp.183-188
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• 2019

This study is a descriptive research to compare and analyze the current status of disaster-related curriculum between emergency department and nursing department Research and analysis targets were 41 universities which include the emergency department in South Korean by using the universities' internet homepage, finally 30 universities were researched by removing the universities which doesn't upload the curriculum on their homepage, have emergency department or have nursing department. The research data were collected and analyzed by using the universities' internet homepage. The Keyword is 'Disaster', 'Catastrophe', and 'Emergency' to search the name of the subjects. The curriculum calculated as a percentage of frequency by using the status of disaster-related subjects opening, classification of major education, grade, credit, number of class, practical hours, and the total number of subjects. According to the study, 29 universities (96.7%) of emergency department and 19 universities (63.3%) of nursing department has the disaster-related subjects in their curriculum. The current status of the class opening is emergency department at second grade and nursing department as fourth grade. As a subject of major, two credits are the common class credits. Based on the results of the study, knowledge and skills and training courses are necessary to develop the ability to cope with disasters in the disaster field. The curriculum that matches the role of health care resources will be required.

• Journal of Internet Computing and Services
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• v.20 no.4
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• pp.81-90
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• 2019

Since 2015, the government has been striving to strengthen the software capabilities required for future talent through software-oriented university in Korea. In the university selected as a software-oriented university, basic software education is given to all departments such as humanities, social science, engineering, natural science, arts and the sports within the university in order to foster convergent human resources with different knowledge and software literacy. In this paper, we analyze the contents of basic software education for twenty universities selected as software-oriented universities. As a result of analysis, most of the basic software education which is carried out to the students of the non-majors students was aimed at improvement of problem solving ability centered on computational thinking for future society and improvement of convergence ability based on computer science. It uses block-based educational programming language and text-based advanced programming language to adjust the difficulty of programming contents and contents reflecting characteristics of each major. Problem-based learning, project-based learning, and discussion method were used as the teaching and learning methods for problem solving. In the future, this paper will help to establish the systematic direction for basic software education of non-majors students.

• Journal of Internet Computing and Services
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• v.20 no.2
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• pp.109-118
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• 2019

The purpose of this study is to deliver both market-practical and civil-centric political implication for sharing economy by investigating the nature of consumer-adoption for car-sharing service. With the global interest and market proliferation of the sharing economy, various service models for sharing idle resources have also been released in Korea. Particularly, in case of car sharing service, public - private partnership projects are spreading rapidly in various local governments including Seoul, along with the growing demand for alternative transportation system centering on the urban area. This study conducted an empirical study on the process of accepting the car sharing service by analyzing the data collected from users of the car sharing service "Sharing Car(Nanum Car)" of Seoul Metropolitan Government. A survey was conducted on 281 users in their twenties who are in the age of main use among the experienced users of the "Sharing Car(NaNum)" residing in Seoul. The result of analysis on the relationship between these users' perceived value and intention to use the vehicle sharing service would provide implications for establishing consumer(citizen)-centeric policies as well as market implications.

• Journal of Internet Computing and Services
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• v.20 no.2
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• pp.39-49
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• 2019

Advances in IoT data analysis technology have made it easier to analyze situation and provide interactive services based on the context. Most of digital signage application have been used to provide information uni-directionally, but in the future it will evolve to provide personalized content according to the individual user situation and responses. However, it is not easy to modify or apply the existing interactive digital signage platforms due to their hardware dependency. The proposed platform is modularized by dividing main functions into two, the cloud and the edge, so that advertisement resources can be easily generated and registered. Thus, interactive advertisement can be rendered in a timely manner based on sensor analysis results. At the edge, personal data can be processed to minimize privacy issues, and real-time IoT sensor data can be analyzed for quick response to the signage player. The cloud is easier to access and manage by multiple users than edge. Therefore, the signage content generation module improves accessibility and flexibility by handling advertisement contents in the cloud so that multiple users can work together on the cloud platform. The proposed platform was developed and simulated in two aspects. First is the provider who provides the signage service, and second is the viewer who uses the content of the signage. Simulation results show that the proposed platform enables providers to quickly construct interactive signage contents and responses appropriately to the context changes in real-time.

• Journal of Internet of Things and Convergence
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• v.6 no.4
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• pp.27-32
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• 2020

Along with the aging of the population, the number of dementia patients is increasing, and the social and economic burden is also increasing. Currently, the effective way to manage dementia patients is to identify patients with dementia early. However, in rural and island areas where medical staff are scarce, there is a problem that it is difficult to visit a hospital and get an early examination. Therefore, we propose a remote early detection system for dementia to solve the problems. The remote dementia early diagnosis system is a system that allows a patient to receive examination and treatment from a remote dementia expert using remote medical technology based on real-time image communication. The remote early diagnosis system for dementia consists of a local client system used by medical staff at health centers in the island, an image server that transmits, stores and manages images, and an expert client used by remote dementia experts. The local client subsystem satisfies the current medical law's remote collaboration by allowing the patient to use it with the health center's medical staff. In addition, expert clients are used by dementia experts, and can store/manage patient information, analyze patient history information, and predict the degree of dementia progression in the future.

• Journal of Internet of Things and Convergence
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• v.6 no.4
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• pp.33-38
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• 2020

It was reported that a mobile application was designed to easily provide natural dyeing information such as natural dye related resources, colors and dyed fabrics in 2007. Since studies on the linkage, application, etc. between natural dye dyeing and IoT are still lacking, diversity of information on the change of dyeing pattern by natural dye dyeing is required. In this study, it was to construct dyeing information by natural dyes, e.g., Lithospermum erythrorhizon, on silk, which has been traditionally used as many fibers in Korea. The extraction of the dye from L. erythrorhizon was carried out under pH4. The dried root of L. erythrorhizon showed dark brownish purple. Silk fabric by a without a mordant typically showed a purple dyed pattern. In the staining by sodium tartrate plus citric acid, silk fabric was stained clear brown. Interestingly, the mordant of iron (II) sulfate, the silk fabric was dyed in a light gray color rather than black. When the mordant of aluminum potassium sulfate was treated with L. erythrorhizon-extracted dye, the results were almost the same as when the mordant was not treated. When the degree of dyeing was evaluated numerically, the treatment of the mordant of potassium dichromate was about 50% darker, and the dyeing by iron (II) sulfate was about 75% darker. These results will be helpful in the study of applying various dye colors using L. erythrorhizon, and it will provide information on dyeing controller and database system construction by dyeing parameters such as dyeing degree, pH concentration, and chromaticity change.

• Journal of Internet of Things and Convergence
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• v.7 no.2
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• pp.13-19
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• 2021

It is analyzed that the energy pattern is affected by the social matters of the disease trend where the energy consumption has been reduced following the depression of the national economy. The campaign of social distance for the people has been done by voluntary or legally due to the epidemic of the Coronavirus Disease 2019 (COVID-19). Some economic stimulus policies have been done in some countries including the United States, South Korea, and some others. It is shown the susceptible, infectious, and recovered (SIR) modeling applied by system dynamics (SD) where the logical modeling is constructed with S, I, and R. Especially, the I is connected with Society including Population, Race, and Maturity. In addition, Economy and Politics are connected to Income, GDP, Resources, President, Popularity, Ruling Government, and Leadership. The graph shows the big jump on 2020 April when is the starting month of the S value multiplication. This shows the effect of the COVID-19 and its related post-pandemic trend. The trends of OECD and non-OECD are very similar and the effect of the virus hazards causes significantly to the economic depressions.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.123-132
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• 2020

The EDucation-research Integration through Simulation On the Net (EDISON) platform, which is a web-based platform that provides computational science and engineering simulation execution environments, can offer various analysis environments to students, general users, as well as computational science and engineering researchers. To expand the user base of the simulation environment services, the EDISON platform holds a challenge every year and attempts to increase the competitiveness and excellence of the platform by analyzing the user requirements of the various simulation environment offered. The challenge platform system in the field of computational science and engineering is provided to users in relation to the simulation service used in the existing EDISON platform. Previously, EDISON challenge servicesoperated independently from simulation services, and hence, services such as end-user review and intermediate simulation results could not be linked. To meet these user requirements, the currently in-service challenge platform for computational science and engineering is linked to the existing computational science and engineering service. In addition, it was possible to increase the efficiency of service resources by providing limited services through various analyses of all users participating in the challenge. In this study, by analyzing the simulation and usage environments of users, we provide an improved challenge platform; we also analyze ways to improve the simulation execution environment.

• Journal of the Korean Applied Science and Technology
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• v.38 no.1
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• pp.241-262
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• 2021

This paper reviewed the necessity of a information and communication technology (ICT)-based smart livestock system as a development strategy for the animal life industry in the future. It also predicted the trends of livestock and animal food until 2050, 30 years later. Worldwide, livestock raising and consumption of animal food are rapidly changing in response to population growth, aging, reduction of agriculture population, urbanization, and income growth. Climate change can change the environment and livestock's productivity and reproductive efficiencies. Livestock production can lead to increased greenhouse gas emissions, land degradation, water pollution, animal welfare, and human health problems. To solve these issues, there is a need for a preemptive future response strategy to respond to climate change, improve productivity, animal welfare, and nutritional quality of animal foods, and prevent animal diseases using ICT-based smart livestock system fused with the 4th industrial revolution in various aspects of the animal life industry. The animal life industry of the future needs to integrate automation to improve sustainability and production efficiency. In the digital age, intelligent precision animal feeding with IoT (internet of things) and big data, ICT-based smart livestock system can collect, process, and analyze data from various sources in the animal life industry. It is composed of a digital system that can precisely remote control environmental parameters inside and outside the animal husbandry. The ICT-based smart livestock system can also be used for monitoring animal behavior and welfare, and feeding management of livestock using sensing technology for remote control through the Internet and mobile phones. It can be helpful in the collection, storage, retrieval, and dissemination of a wide range of information that farmers need. It can provide new information services to farmers.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.35-45
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• 2022

Even in recent years, treatment of first-aid patients is still often delayed due to a shortage of medical resources in marginalized areas. Research on automating the analysis of medical data to solve the problems of inaccessibility for medical services and shortage of medical personnel is ongoing. Computer vision-based medical inspection automation requires a lot of cost in data collection and labeling for training purposes. These problems stand out in the works of classifying lesion that are rare, or pathological features and pathogenesis that are difficult to clearly define visually. Anomaly detection is attracting as a method that can significantly reduce the cost of data collection by adopting an unsupervised learning strategy. In this paper, we propose methods for detecting abnormal images on chest X-RAY images as follows based on existing anomaly detection techniques. (1) Normalize the brightness range of medical images resampled as optimal resolution. (2) Some feature vectors with high representative power are selected in set of patch features extracted as intermediate-level from lesion-free images. (3) Measure the difference from the feature vectors of lesion-free data selected based on the nearest neighbor search algorithm. The proposed system can simultaneously perform anomaly classification and localization for each image. In this paper, the anomaly detection performance of the proposed system for chest X-RAY images of PA projection is measured and presented by detailed conditions. We demonstrate effect of anomaly detection for medical images by showing 0.705 classification AUROC for random subset extracted from the PadChest dataset. The proposed system can be usefully used to improve the clinical diagnosis workflow of medical institutions, and can effectively support early diagnosis in medically poor area.