• Journal of Korean Library and Information Science Society
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• v.53 no.2
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• pp.305-332
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• 2022

This preliminary study examined the degree programs in data science at the School of Information in the States. The focus of this study was the data science degrees offered at the School of Information awarded by the 64 Library and Information Science (LIS) programs accredited by the American Library Association (ALA) in 2022. In addition, this study examined the degrees, majors, minors, specialized tracks, and certificates in data science, as well as the potential careers after earning a data science degree. Overall, eight Schools of Information (iSchools) offered 12 data science degrees. Data science courses at the School of Information focus on topics such as introduction to data science, information retrieval, data mining, database, data and humanities, machine learning, metadata, research methods, data analysis and visualization, internship/capstone, ethics and security, user, policy, and curation and management. Most schools did not offer traditional LIS courses. After earning the data science degree in the School of Information, the potential careers included data scientists, data engineers and data analysts. The researcher hopes the findings of this study can be used as a starting point to discuss the directions of data science programs from the perspectives of the information field, specifically the degrees, majors, minors, specialized tracks and certificates in data science.

• Journal of Advanced Navigation Technology
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• v.26 no.3
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• pp.172-178
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• 2022

In this paper, water meter AMR(automatic meter reading), one of the core technologies of smart water grid, using LoRa IoT network is studied. The main content of the research is to develop the network system and show the test results that one PC server receives the readings of water meters from multiple households through LoRa communication and stores them in the database, and at the same time sends the data to the web server database through internet. The system also allows users to monitor the meter readings using their smartphones. The hardware and firmware of the main board of the digital water meter are developed. For a PC server program, MDMS(meter data management system) is developed using Visual C#. The app program running on the user's smartphone is also developed using Android Studio. By connecting each developed parts, the total network system is mounted on a flow test bench in the laboratory and tested. For the fields test, 5 places around the university are selected and the transmission distances are tested. The test result show that the developed system can be applied into the real field. The developed system can be expanded to various social safety nets such as monitoring the living alone or elderly with dementia.

• Journal of the Society of Disaster Information
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• v.18 no.2
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• pp.269-279
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• 2022

Purpose: The purpose of this study is to develop a deep learning-based personal protective equipment detection model for disaster prevention at construction sites, and to apply it to actual construction sites and to analyze the results. Method: In the method of conducting this study, the dataset on the real environment was constructed and the developed personal protective equipment(PPE) detection model was applied. The PPE detection model mainly consists of worker detection and PPE classification model.The worker detection model uses a deep learning-based algorithm to build a dataset obtained from the actual field to learn and detect workers, and the PPE classification model applies the PPE detection algorithm learned from the worker detection area extracted from the work detection model. For verification of the proposed model, experimental results were derived from data obtained from three construction sites. Results: The application of the PPE recognition model to construction site brings up the problems related to mis-recognition and non-recognition. Conclusions: The analysis outcomes were produced to apply the object recognition technology to a construction site, and the need for follow-up research was suggested through representative cases of worker recognition and non-recognition, and mis-recognition of personal protective equipment.

• Korean Journal of Psychosomatic Medicine
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• v.30 no.1
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• pp.7-15
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• 2022

Objectives : The purpose of this study is to identify the effect of office workers' stress level and stress vulnerability on heart rate variability (HRV), confirm the significance of objective stress indicators obtained through subjective stress and heart rate variability devices, and examine their effectiveness as an integrated stress measurement tool in community mental health projects. Methods : From June to July in 2020, 929 workers participated in the stress management and mental health promotion project carried out by K hospital, and their recorded database was used for study analysis with their agreements. Multiple linear regression analysis was performed to find out the effects of general stress level, and stress vulnerability on heart rate variability. Results : All general characteristics were found to have a significant effect on SDNN (ln), RMSSD (ln), LF (ln), and HF (ln), but work experience did not significantly affect RMSSD (ln). Stress level and stress vulnerability did not significantly affect heart rate variability, but stress perception, a sub-factor of stress level, was found to have a significant effect on RMSSD (ln) (β=0.118, p=0.023). Conclusions : In this study, stress perception, a sub-factor of stress level, was found to be a factor affecting RMSSD (ln). This indicates an association with the activity of parasympathetic nerves in stressful situations, and more follow-up studies are needed to use it as a direct indicator of chronic stress and integrated stress in the community mental health field.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.466-472
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• 2021

This paper aims to guide experts who manage dementia by exploring the various non-drug interventions and analyzing the effective intervention methods applicable according to the functional level of the elderly with dementia. Fourteen studies were analyzed in this study. Meta-analysis was performed using the means, standard deviations, and the number of samples. Subsequent meta-analysis showed that the Holnis program had the largest effect size in cognitive function, the bakery activity program in memory, and the composite intermediation program with ADL was the largest. In addition, client-centric cognitive stimulation interventions showed the most significant effect sizes, while in depression and BPSD, rhythmic movement activities had the most significant effect size. Elderly with dementia exhibit various symptoms depending on their characteristics and the progress of the disease. Therefore, more efficient arbitration could be provided if the effects of each intervention can be applied differently.

• Journal of Navigation and Port Research
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• v.46 no.6
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• pp.525-529
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• 2022

In the eLoran system, the Loran Data Channel (LDC) is used to provide precise timing and positioning. The LDC message can be modulated with the Eurofix method, which modulates the transmission time of the 3rd-8th pulse not used for navigation, and the 9th pulse method, which modulates data using the 9th additional pulse after the existing 8 Loran pulses. In this paper, we analyzed the reception performance of the LDC message transmitted from the eLoran transmitter according to the modulation method. The eLoran testbed transmitter in Incheon was set to transmit LDC messages simultaneously with the 9th pulse modulation method and the Eurofix modulation method. Then, the LDC messages stored in the databases of the eLoran differential stations in Incheon and Pyeongtaek were analyzed in terms of the message reception rate according to the modulation method. Using the navigation aid management ship Inseong No. 1, the range of LDC message reception of actual sea users near Incheon Port was also analyzed. The results of this study are expected to be utilized in the full operational capability service after the eLoran pilot service.

• Ecology and Resilient Infrastructure
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• v.9 no.4
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• pp.282-289
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• 2022

Analyzing the impact of climate change on the Korean Peninsula on the forest ecosystem is important for the management of subtropical forest bioresources. In this study, we collected location data and bioclimatic variables of the warm-temperate woody plant species, Myrica rubra and Cyzygium buxifolium, and applied the MaxEnt model based on the collected data to estimate the potential distribution area. Precipitation and temperature seasonality in the warmest quarter were the main environmental factors that determined the distribution of M. rubra, and the main environmental factors for S. buxifolium were precipitation in the warmest quarter and precipitation in the wettest quarter. The results of the MaxEnt model by administrative district, the M. rubra showed an area increase rate of 4.6 - 17.7% in the SSP2-4.5 climate change scenario and 13.8 - 30.5% in the SSP5-8.5 climate change scenario. S. buxifolium showed area increase rates of 4.8 - 32.2% in the SSP2-4.5 climate change scenario and 12.9 - 48.6% in the SSP5-8.5 climate change scenario. This study is meaningful in establishing a database and identifying future potential distribution areas of warm and subtropical plants by applying climate change scenarios.

• Journal of Practical Agriculture & Fisheries Research
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• v.24 no.4
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• pp.53-61
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• 2022

Growing agricultural products in greenhouses controlled by creating suitable climatic conditions and root zone of crop has been an important research and application subject. Appropriate environmental conditions in greenhouse are necessary for optimum plant growth improved crop yields. This study aimed to establish web-based remote monitoring system which monitors crops growth environment and status of crop on a real-time basis by applying to greenhouses IT technology connecting greenhouse equipment such as temperature sensors, soil sensors, crop sensors and camera. The measuring items were air temperature, relative humidity, solar radiation, CO₂ concentration, EC and pH of nutrient solution, medium temperature, EC of medium, water content of medium, leaf temperature, sap flow, stem diameter, fruit diameter, etc. The developed greenhouse monitoring system was composed of the network system, the data collecting device with sensors, and cameras. Remote monitoring system was implemented in a server/client environment. Information on greenhouse environment and crops is stored in a database. Items on growth and environment is extracted from stored information, could be compared and analyzed. So, A integrated monitoring system for smart greenhouse would be use in application practice and understanding the environment and crop growth for smart greenhouse management. sap flow, stem diameter and pant-water relations

• Therapeutic Science for Rehabilitation
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• v.11 no.3
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• pp.23-36
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• 2022

Objectives : This study aimed to provide basic data on intervention strategies that occupational therapists can access by systematically analyzing the intervention and effectiveness for youth with disabilities. Methods : The RISS, PubMed, and Web of Science databases were used to search for papers published between 2006 and 2021. The keywords were "Disability AND Adolescents OR Young adult AND Transition education OR Transition program". Seven papers were selected for analysis, and the full text was reviewed. The keywords and national relations were analyzed and visualized using the WoS (Web of Science) and VOSviewer programs. Results : The participants were classified into five types (ASD or ADHD, ID, DD, and physical disability). The areas used for the intervention were mixed into three categories: occupation (academic), self-management (time), and interaction (personal relations and communication). Sociality and adaptation, quality of life, and at least one of the three categories of daily life activities showed significant improvement. Conclusions : This study can be used as basic data to expand the area where only OTs can contribute while grasping the research trend of the conversion program and presenting the direction of exchange with various experts by organizing the application and its effects.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.77-84
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• 2022

In this paper, we propose a system for monitoring air pollutants such as fine dust using an unmanned aerial vehicle capable of autonomous navigation. The existing air quality management system used a method of collecting information through a fixed sensor box or through a measurement sensor of a drone using a control device. This has disadvantages in that additional procedures for data collection and transmission must be performed in a limited space and for monitoring. In this paper, to overcome this problem, a GPS module for location information and a PMS7003 module for fine dust measurement are embedded in an unmanned aerial vehicle capable of autonomous navigation through flight information designation, and the collected information is stored in the SD module, and after the flight is completed, press the transmit button. It configures a system of one-stop structure that is stored in a remote database through a smartphone app connected via Bluetooth. In addition, an HTML5-based web monitoring page for real-time monitoring is configured and provided to interested users. The results of this study can be utilized in an environmental monitoring system through an unmanned aerial vehicle, and in the future, various pollutants measuring sensors such as sulfur dioxide and carbon dioxide will be added to develop it into a total environmental control system.