• Journal of Appropriate Technology
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• v.5 no.2
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• pp.70-81
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• 2019

The garment industry is one of the most labor-intensive manufacturing industries, with its sewing process relying almost entirely on manual labor. Its costs highly depend on the efficiency of this production line and thus is crucial to determine the production rate in real-time for line balancing. However, current production tracking methods are costly and make it difficult for many Small and Medium-sized Enterprises (SMEs) to implement them. As a result, their reliance on manual counting of finished products is both time consuming and prone to error, leading to high manufacturing costs and inefficiencies. In this paper, a production tracking system that uses the sewing machines' energy consumption data to track and count the total number of sewing tasks completed through Convolutional Neural Network (CNN) classifiers is proposed. This system was tested on two target sewing tasks, with a resulting maximum classification accuracy of 98.6%; all sewing tasks were detected. In the developing countries, the garment sewing industry is a very important industry, but the use of a lot of capital is very limited, such as applying expensive high technology to solve the above problem. Applied with the appropriate technology, this system is expected to be of great help to the garment industry in developing countries.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.3
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• pp.467-475
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• 2018

Recently earthquakes have been increasing worldwide, and the largest earthquake of 5.8 on the Richter scale occurred on September 12, 2016 in the Gyeongju area. After the earthquake, more than 200 aftershocks have occurred from January 2017 to December 2017. The largest earthquake in 2017 was a 4.3-magnitude earthquake near Pohang on November 15. In this study, we tried to analyze the coordinate change due to the earthquake using the data of the CORS(Continuously Operating Reference Station) in Korea. In order to analyze the change of coordinates due to the earthquake in Pohang area on November 15, 2017, data processing was performed by kinematic method. And from January 2017 to December 2017, observation data of 9 stations in Korea were analyzed by relative positioning method and the change of coordinates due to earthquake was analyzed. As a result of the study, it was possible to estimate the instantaneous coordinate change due to the earthquake through the kinematic positioning, and it was suggested that there is no change in the coordinates of the domestic CORS by the relative positioning results. After the 2017 Gyeongju earthquake, aftershocks continue to occur, and it is necessary to monitor the area continuously.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.10
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• pp.895-903
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• 2018

The purpose of this study is to conduct a comparative analysis on the mental health and health-related quality of life of the community residents who have been affected by the Sewol ferry disaster and to provide a basis for future aids for potential human-caused catastrophe. The study utilized the big data, Korean community health survey data of 3,632 (1,803 in 2018 and 1,829 in 2014) residents in Ansan and Jindo, a victimized community of Sewol ferry disaster, and compared the subjective level of health, amount of appropriate sleep, subjective stress level, stress consulting, depression, depression consulting, and health-related quality of life before and after the disaster. According to the findings, community residents who have been affected by the Sewol ferry disaster did not show any significant difference in terms of subjective health level, amount of appropriate sleep, subjective stress, and health-related quality of life. The study aims to serve as a foundational data for developing a prevention program or policy that aims to support future potential disasters by comparing the mental health and health-related quality of life of the victimized community before and after the disaster. The study suggests that the need for continuous monitoring of mental health and health-related quality of life of the victimized residents is significant, and further studies should be implemented in order to provide better supports for the local community.

• Korean Journal of Environment and Ecology
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• v.37 no.2
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• pp.140-150
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• 2023

The Eurasian otter (Lutra lutra) is an apex predator of the riparian ecosystem. It is a keystone and an indicator species; consequently, its presence suggests a sustainable water environment. Otter is a keystone species as a predator at the top of the food web in the aquatic environment and an indicator species representing the health of the aquatic environment. Although Eurasian otters disappeared from the Han River urban water system because of anthropogenic activities like habitat destruction, poaching, and environmental pollution in the 1980s, the species were sighted in the Cheonggye Stream, Jungrang Stream, and Seongnae Stream, which are urban sections of the Han River, in 2016 and 2021. Therefore, it is pertinent to assess the habitat potential in the area for conservation and management measures to ensure its permanent presence. However, existing studies on otter habitats focused on natural rivers and reservoirs, and there is a limit to applying them to habitats artificially confined habitats in narrow spaces such as tributaries in urban areas of the Han River. This study selected the Cheonggye Stream, an artificially restored urban stream, to evaluate its potential as a habitat for Eurasian otters in urban water environments using the habitat suitability index (HSI). The HSI was calculated with selected environment attributes, such as the cover, food, and threat, that best describe the L. lutra habitat. According to the results, the confluence area of Seongbuk Stream and Cheonggye Stream and the confluence area of Cheonggye Stream and Jungnang Stream were suitable otter habitats, requiring appropriate conservation efforts. The HSI model suggests a valuable method to assess the habitat quality of Eurasian otters in urban water environments. The study is crucial as it can help rehabilitate the species' populations by identifying and managing potential Eurasian otter habitats in highly urbanized areas of the Han River basin and its tributaries.

• Journal of Appropriate Technology
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• v.5 no.2
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• pp.62-69
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• 2019

Supplying stable electric power is one of the important objectives of the Official Development Assistance (ODA) because it is strongly related with improving living standards and income levels in the region. However, rural areas in many developing countries are not properly connected to national power grids, and even areas connected to national power grids are frequently blacked out due to limitations in power capacity. These lack of electric power is a major obstacle to improving income levels and improving living standards in those areas. The Korea-Tanzania Innovative and Energy Center (iTEC), which was established by Seoul National University in cooperation with the Nelson-Mandela Africa Institute of Science and Technology and Technology (NM-AIST) try to build a small solar power plant using a smart-off grid in rural area of Tanzania, where there is no electricity. 10 kW and 7 kW solar power plants are built in Mkalama Village in Kilimanajaro Region and Ngurdoto Village in Arusha Region to provide power to about 50 households each. In addition, smart monitoring systems were installed to collect data about status of power system and power consumption of each house. iTEC seeks for sustainable improvement the income level and quality of life of rural residents in developing countries through the construction of small solar power plants using smart-off grid, and the implementation of various connected projects.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2021.11a
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• pp.78-80
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• 2021

This study is based on Degree of Recognition and AHP surveys for experts, this study investigates changes in the demand of seafarers in response to changes in the shipping industry environment in which Maritime Autonomous Surface Ships(MASS) emerge according to the application of the fourth industrial revolution technology to ships, and it looks into changes in seafarers' skills. It also analyzes and proposes a plan for cultivating seafarers accordingly. As a result of Degree of Recognition and AHP analysis, it is analyzed that a new training system is required because the current training and education system may cover the job competencies of emergency response, caution and danger navigation, general sailing, cargo handling, seaworthiness maintenance, emergency response, and ship maintenance and management, but jobs such as remote control, monitoring diagnosis, device management capability, and big data analysis require competency for unmanned and shore based control.By evaluating the importance of change factors in the duties of seafarers in Maritime Autonomous Surface Ships, this study provides information on seafarers educational institutions response strategies for nurturing seafarers and prioritization of resource allocation, etc. The importance of factors was compared and evaluated to suggest changes in the duties of seafarers and methods of nurturing seafarers according to the introduction of Maritime Autonomous Surface Ships.It is expected that this study is meaningful as it systematically derived the duties and competency factors of seafarers of Maritime Autonomous Surface Ships from a practical point of view and analyzed the perception level of each relevant expert to diagnose expert-level responses to the introduction of Maritime Autonomous Surface Ships.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.137-144
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• 2023

Cyberattack technology is evolving to an unpredictable degree, and it is a situation that can happen 'at any time' rather than 'someday'. Infrastructure that is becoming hyper-connected and global due to cloud computing and the Internet of Things is an environment where cyberattacks can be more damaging than ever, and cyberattacks are still ongoing. Even if damage occurs due to external influences such as cyberattacks or natural disasters, intelligent self-recovery must evolve from a cyber resilience perspective to minimize downtime of cyber assets (OS, WEB, WAS, DB). In this paper, we propose an intelligent self-recovery technology to ensure sustainable cyber resilience when cyber assets fail to function properly due to a cyberattack. The original and updated history of cyber assets is managed in real-time using timeslot design and snapshot backup technology. It is necessary to secure technology that can automatically detect damage situations in conjunction with a commercialized file integrity monitoring program and minimize downtime of cyber assets by analyzing the correlation of backup data to damaged files on an intelligent basis to self-recover to an optimal state. In the future, we plan to research a pilot system that applies the unique functions of self-recovery technology and an operating model that can learn and analyze self-recovery strategies appropriate for cyber assets in damaged states.

• Journal of the Korean GEO-environmental Society
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• v.16 no.4
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• pp.5-12
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• 2015

Civil engineers have taken the numerous slope monitoring data for an engineering project subjected to hazard potential of slide. However, the topics on how to deal with and draw out proper information from the data related to the slope behavior have not been widely discussed. Recently, several researchers had installed the real-time monitoring system to cope with slope failure; however they are mainly focused on the hardware system installation. Therefore, this study tries to show how the measured data could be grouped and connected each other. The basic idea of analyzing method studied in this paper came from the clustering, which is the part of data mining analysis. Therefore, at the base of classification of time series data, the authors suggest three mathematical data analyzing methods; Average Index of different displacement ($AD_{i,j}$), Difference of average relative displacement ($\overline{RD}_{i,j}$) and Coordinate system of average and relative displacement ($\overline{RD}$, AD). These analyzing methods are based on the statistical method and failure mechanism of slope. Therefore they showed clustering relationships of the similar parts of the slope which makes the same sliding mechanism.

• Convergence Security Journal
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• v.24 no.1
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• pp.51-57
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• 2024

Although industrial control systems (ICSs) recently keep evolving with the introduction of Industrial IoT converging information technology (IT) and operational technology (OT), it also leads to a variety of threats and vulnerabilities, which was not experienced in the past ICS with no connection to the external network. Since various control command messages are sent to field devices of the ICS for the purpose of monitoring and controlling the operational processes, it is required to guarantee the message integrity as well as control center authentication. In case of the conventional message integrity codes and signature schemes based on symmetric keys and public keys, respectively, they are not suitable considering the asymmetry between the control center and field devices. Especially, compromised node attacks can be mounted against the symmetric-key-based schemes. In this paper, we propose message authentication scheme based on double hash chains constructed from cryptographic hash function without introducing other primitives, and then propose extension scheme using Merkle tree for multiple uses of the double hash chains. It is shown that the proposed scheme is much more efficient in computational complexity than other conventional schemes.

• Smart Media Journal
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• v.12 no.11
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• pp.57-66
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• 2023

In this paper, we present a study on an AI-based system utilizing the CCTV system within city buses to predict the intentions of boarding and alighting passengers, with the aim of preventing accidents. The proposed system employs the YOLOv7 Pose model to detect passengers, while utilizing an LSTM model to predict intentions of tracked passengers. The system can be installed on the bus's CCTV terminals, allowing for real-time visual confirmation of passengers' intentions throughout driving. It also provides alerts to the driver, mitigating potential accidents during passenger transitions. Test results show accuracy rates of 0.81 for analyzing boarding intentions and 0.79 for predicting alighting intentions onboard. To ensure real-time performance, we verified that a minimum of 5 frames per second analysis is achievable in a GPU environment. his algorithm enhance the safety of passenger transitions during bus operations. In the future, with improved hardware specifications and abundant data collection, the system's expansion into various safety-related metrics is promising. This algorithm is anticipated to play a pivotal role in ensuring safety when autonomous driving becomes commercialized. Additionally, its applicability could extend to other modes of public transportation, such as subways and all forms of mass transit, contributing to the overall safety of public transportation systems.