• The Journal of Korean Society for School & Community Health Education
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• v.21 no.1
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• pp.15-31
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• 2020

Background and objectives: One-person households are the fastest growing family type in Korea. They bring social concerns such as weakened social integration, increasing poverty and social isolation. They are not homogeneous but heterogeneous groups depending on their socio-demographic characteristics including generation. This study compared the life satisfaction level as well as factors affecting it among the three one-person household generations Methods: The 13th wave of the Korea Welfare Panel dataset with 1,187 respondents was utilized. For data analysis Chi-square test, analysis of variance and hierarchical regression analysis were employed. Generations are divided into three, namely young adult (20-39), the middle-aged (40-64) and the elderly (65 and over). Result: The life satisfaction level was highest among the young adult one-person household generation, followed by the middle-aged and the elderly generation. The common factors affecting life satisfaction of the three generations were physical as well as mental health, including self-esteem and depression. However, there were more factors different from generation to generation. As for the young adult, age, religion, and smoking were significant. As for the middle aged and the elderly, gender (male) and income were significant. Additionally, age, home-ownership and drinking were significant to the elderly generation. Conclusions: As there are differences as well as similarities among the three generations, policies for one-person households need to be devised considering these findings. For all generations, both physical and mental health policies are needed. For young adult strengthening social relations, providing decent jobs, and promoting anti-smoking policy are major agenda, and for the middle-aged and the elderly, assisting in social capital accumulation (for male), providing stable jobs and diverse leisure activities, and securing income. Additionally, for the elderly, expanding the social security system and housing support are needed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.2
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• pp.173-178
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• 2019

Recently, the types and amount of data generated, collected, and measured in IoT such as smart home, security, and factory are increasing. The technologies for IoT service include sensor devices to measure desired data, embedded software to control the devices such as signal processing, wireless network protocol to transmit and receive the measured data, and big data and AI-based analysis. In this paper, we focused on developing a gateway for interfacing heterogeneous sensor network protocols that are used in various IoT devices and propose a heterogeneous network interface IoT gateway. We utilized a OpenWrt-based wireless routers and used 6LoWAN stack for IP-based communication via BLE and IEEE 802.15.4 adapters. We developed a software to convert Z-Wave and LoRa packets into IP packet using our Python-based middleware. We expect the IoT gateway to be used as an effective device for collecting IoT big data.

• The Journal of the Convergence on Culture Technology
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• v.8 no.2
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• pp.373-377
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• 2022

Wireless sensor networks are being used in various fields. Wireless sensor networks are applied in many areas, such as security, military detection, environmental management, industrial control, and home automation. There is a problem about the limit of energy that the sensor network basically has. In this paper, we propose the LEACH-CCBD (Low Energy Adaptive Clustering hierarchy - Centrailized with Cluster and Basestation Distance) algorithm that uses energy efficiently by improving network transmission based on LEACH-C among the representative routing protocols. The LEACH-CCBD algorithm is a method of assigning a cluster head to a cluster head by comparing the sum of the distance from the member node to the cluster distance and the distance from the cluster node to the base station with respect to the membership of the member nodes in the cluster when configuring the cluster. The proposed LEACH-CCBD used Matlab simulation to confirm the performance results for each protocol. As a result of the experiment, as the lifetime of the network increased, it was shown to be superior to the LEACH and LEACH-C algorithms.

• Journal of Electrochemical Science and Technology
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• v.13 no.4
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• pp.472-478
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• 2022

Solar energy harvesting is practiced by various nations for the purpose of energy security and environment preservation in order to reduce overdependence on oil. Converting solar energy into electrical energy through Photovoltaic (PV) module can take place either in on-grid or off-grid applications. In recent time Lithium battery is exhibiting its presence in on-grid applications but its role in off-grid application is rarely discussed in the literature. The preliminary capacity and Peukert's study indicated that the battery quality is good and can be subjected for life cycle test. The capacity of the battery was 10.82 Ah at 1 A discharge current and the slope of 1.0117 in the Peukert's study indicated the reaction is very fast and independent on rate of discharge. In this study Lithium Iron Phosphate battery (LFP) after initial characterization was subjected to life cycle test which is specific to solar off-grid application as defined in IEC standard. The battery has delivered just 6 endurance units at room temperature before its capacity reached 75% of rated value. The low life of LFP battery in off-grid application is discussed based on State of Charge (SOC) operating window. The battery was operated both in high and low SOC's in off-grid application and both are detrimental to life of lithium battery. High SOC operation resulted in cell-to-cell variation and low SOC operation resulted in lithium plating on negative electrode. It is suggested that to make it more suitable for off-grid applications the battery by default has to be overdesigned by nearly 40% of its rated capacity.

• Journal of the Korea Society of Computer and Information
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• v.27 no.6
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• pp.53-63
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• 2022

Recently, as digital transformation due to the COVID-19 pandemic accelerates, data to improve individual quality of life is being used in large quantities, and more reinforced non-identification processing procedures are required to utilize the most valuable personal information among data. In Korea, procedures for de-identification measures are presented through amendments to laws and guidelines, but there is no methodology to measure the level of de-identification in the field due to ambiguous processing standards and subjective risk measurement methods. This paper compares and analyzes the current status of policy and guidelines related to de-identification measures proposed at home and abroad to derive complementary points, suggests a data context-based risk measurement method centered on pseudonymized information processing, and verifies its validity. As a result of verification through Delphi survey and focus group interview (FGI), it was confirmed that the need for the proposed methodology and the validity of the indicators were high.

• Journal of the Korea Society of Computer and Information
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• v.27 no.6
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• pp.11-21
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• 2022

Although interest in de-identification measures for the safe use of personal information is growing at home and abroad, cases where de-identified information is re-identified through insufficient de-identification measures and inferences are occurring. In order to compensate for these problems and discover new technologies for de-identification measures, competitions to compete on the safety and usefulness of de-identified information are being held in Korea and Japan. This paper analyzes the safety and usefulness indicators used in these competitions, and proposes and verifies new indicators that can measure usefulness more efficiently. Although it was not possible to verify through a large population due to a significant shortage of experts in the fields of mathematics and statistics in the field of de-identification processing, very positive results could be derived for the necessity and validity of new indicators. In order to safely utilize the vast amount of public data in Korea as de-identified information, research on these usefulness metrics should be continuously conducted, and it is expected that more active research will proceed starting with this thesis.

• Nutrition Research and Practice
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• v.17 no.1
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• pp.103-121
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• 2023

BACKGROUND/OBJECTIVES: The coronavirus disease 2019 (COVID-19) pandemic has affected the entire world population in many ways. This study aimed to analyze the patterns of changes in eating, food purchasing and preparation, physical activity, and subjective health after COVID-19 outbreak by various sociodemographic factors and to understand the factors associated with changes in subjective health. SUBJECTS/METHODS: A cross-sectional survey using a representative sample from Seoul was used for the analysis. The data collection was conducted from September to October 2020. A total of 3,833 citizens aged more than 18 years old participated in the Seoul Food Survey. Descriptive statistics and generalized ordinal logistic regression models were used to understand the changes in health behaviors, health indicators, and subjective general health by various socioeconomic status. RESULTS: It was shown that the changes in household income, food expenditure, food consumption and physical activities differed significantly by age, education, occupation, income, weight, and food security status. Low-income and food-insecure households were affected more severely by the pandemic. Older age, household food insecurity, income reduction, increased home cooking and frequency of having instant foods, decreased physical activity and weight gain were significant factors explaining worse perceived health during the COVID-19 pandemic. CONCLUSIONS: The results suggest that focusing on older populations and low-income families with food insecurity should be prioritized during infectious disease outbreaks. In addition, the role of physical activities and instant food consumption in explaining perceived health should be investigated further in this prolonged battle with the pandemic situation.

• Journal of Software Assessment and Valuation
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• v.15 no.2
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• pp.43-50
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• 2019

With the development of IT technology, computer-related crimes are rapidly increasing, and in recent years, the damage to ransomware infections is increasing rapidly at home and abroad. Conventional security solutions are not sufficient to prevent ransomware infections, and to prevent threats such as malware and ransomware that are evolving, a combination of deep learning technologies is needed to detect abnormal behavior and abnormal symptoms. In this paper, a method is proposed to detect user abnormal behavior using CNN-LSTM model and various deep learning models. Among the proposed models, CNN-LSTM model detects user abnormal behavior with 99% accuracy.

• Journal of Industrial Convergence
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• v.21 no.12
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• pp.45-54
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• 2023

This study aims to examine trends so far and proactively seek future policy directions because the degree of implementation of hyper-connected society and smart technology at home and abroad cannot be overlooked at present in Korea. The method of the study focused on differentiating it from this study through literature research and comparison of major previous studies. As a result of the study, data security and maintenance, enhanced privacy of users and users, and related policy directions for entering a super-aged society were identified in the era of the 4th industrial revolution in Korea according to hyper-connected society and smart technology. Research limitations were difficulties in obtaining data and technical limitations in statistical quantification through trend analysis, although research analysis should be approached through quantitative and quantitative methods. It needs to be supplemented in future studies.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.165-172
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• 2024

In this paper, we designed a smart home system that can be used intuitively and easily in everyday life, such as sending text messages to users, providing various information and scheduling using smart AI, and providing lighting and atmosphere suitable for the atmosphere in situations such as listening to music using neopixels, as well as using ESP32, RFID, and Google Cloude Console using raspberry pie. As a result of the experiment, it was confirmed that security characters were normally sent to users when RFID was recognized on ESP32 connected to Wi-Fi even if the power was reconnected, and smart AI using Neopixel lighting, Raspberry Pie, and voice recognition, which calculated frequency, also changed the recognition rate over distance, but it worked.