• Journal of the Korea Society of Computer and Information
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• v.23 no.11
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• pp.17-24
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• 2018

Today, we are living in the era of data and information. With the advent of Internet of Things (IoT), the popularity of social networking sites, and the development of mobile devices, a large amount of data is being produced in diverse areas. The collection of such data generated in various area is called big data. As the importance of big data grows, there has been a growing need to share big data containing information regarding an individual entity. As big data contains sensitive information about individuals, directly releasing it for public use may violate existing privacy requirements. Thus, privacy-preserving data publishing (PPDP) has been actively studied to share big data containing personal information for public use, while preserving the privacy of the individual. K-anonymity, which is the most popular method in the area of PPDP, transforms each record in a table such that at least k records have the same values for the given quasi-identifier attributes, and thus each record is indistinguishable from other records in the same class. As the size of big data continuously getting larger, there is a growing demand for the method which can efficiently anonymize vast amount of dta. Thus, in this paper, we develop an efficient k-anonymity method by using Spark distributed framework. Experimental results show that, through the developed method, significant gains in processing time can be achieved.

• Journal of the Korea Society of Computer and Information
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• v.21 no.2
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• pp.43-49
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• 2016

In this paper, we propose the controllability function and service design to efficiently implement the control of the disaster communication network, using Internet of Things(IoT) Technology. In accordance with the spread of Information Communication Technology(ICT), the era for building a disaster communications system without exclusion over the entire areas has emerged. National wireless mesh networks for public safety and disaster relief have been evolving to strengthen the pre-disaster response system using the latest technologies through the convergence of various technologies and services from the viewpoint of the command and control between disaster response agencies. In line with such a technological paradigm shift, the controllability of the objects in the IoT has been emerging as a key quality requirement of a disaster communications system. In this study, the objects are classified by the subject of control according to the IoT component, such as data, network resources and services in order to effectively implement their controllability. In addition, based on the destination of this controllability, technologies and services have been designed that can reduce the damage caused by disasters. Technologies and services that were derived from this study must be implemented in the current disaster safety network systems together with the establishment of an infrastructure for the networks in order that all persons are able to effectively utilize the disaster communications system for their safety.

• International journal of advanced smart convergence
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• v.10 no.3
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• pp.105-112
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• 2021

This study was conducted on 878 retired women in their 50s and 60s across the country using the 7th data from the National Pension Service's KReiS. We used SPSS WIN 18.0, and the analysis results are as follows. First, there were many highly educated people in their 50s or older and those in their 60s and undereducated. Second, families in their 50s had the largest number of members with more than three, while households in their 60s had the largest number of two. Third, both age groups chose themselves and their spouses as responsibilities for preparing for retirement. In addition, more people in their 60s chose the government as their responsibility for preparing for retirement than in their 50s. Both people in their 50s and 60s say they are "not prepared" to prepare for retirement expenses, raising concerns about elderly poverty. Fourth, economic strength, health, and medical care were important for retirement in both age groups as part of their preparations for retirement, and they chose economic strength, health, medical care and job as the things to do in society. Fifth, both people in their 50s and 60s have very low public and private pension subscription rates, requiring special attention from the government and society to their old age. Judging from the above results, both women in their 50s and 60s have retired, but preparations for retirement are very insufficient. Therefore, the government and society need to strengthen the public pension system and create jobs for the elderly.

• Journal of Environmental Health Sciences
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• v.48 no.1
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• pp.44-51
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• 2022

Background: Air pollution is increasing together with industrialization and urbanization. In order to reduce air pollution, public transportation is recommended rather than private cars, and the number of passengers using public transportation is increasing accordingly. This study observes the concentration of indoor pollutants in city buses over time. Through this means, we intend to suggest a plan to manage the indoor air quality in city buses. Objectives: The concentration of indoor pollution in public transportation was investigated from April 2021 to January 2022. Based on this, we evaluated the exposure to indoor pollutants. Methods: Six city bus lines in an industrial city were selected for the research, and indoor pollution was measured through IoT (Internet of Things)-based sensor-type measuring devices. The concentration of pollutants was measured every minute, and statistical data were constructed based on the measurement results. Results: In all the city buses studied, the average concentration of pollutants were below the guidelines. However, some measurement results showed cases of exceeding the guidelines. As a result of the analysis by time zone, there were more cases in which pollutants exceeded the standard value during rush hour compared to at other times. A risk assessment for PM₁₀ was performed by evaluating the excess mortality risk from exposure and the risk from inhalation exposure. Conclusions: All measured indoor pollutants in the city buses did not exceed the guidelines. Also, the risk assessment results were found to be within the level of safety. However, if a city bus is used for a long time, there is a possibility that there may be an impact on the human body due to inhalation exposure, so additional management is required.

• Journal of Aerospace System Engineering
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• v.14 no.5
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• pp.83-90
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• 2020

Disasters are causing significant damage to the lives and property of our society and are recognized as social problems that need to be solved nationally and globally. The 4th industrial revolution technologies affecting society as a whole such as the Internet of Things(IoT), Artificial Intelligence(AI), Drones(Unmanned Aerial Vehicles), and Big Data are continuously absorbed into the disaster and safety industries as scientific and technological tools for solving social problems. Very soon, twenty-nine domestic UAV-related organizations/companies will complete the construction of a multicopter type small UAV integrated system ('17~'20) that can be operated at disaster and security sites. The current work considers and proposes the mid-to-long term R&D direction of disaster UAV as a strategic asset of the national disaster response system. First, the trends of disaster and safety industry and policy are analyzed. Subsequently, the development status and future plans of small UAV, securing shortage technology, and strengthening competitiveness are analyzed. Finally, step-by-step R&D direction of disaster UAV in terms of development strategy, specialized mission, platform, communication, and control and operation is proposed.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.1-15
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• 2024

The construction of smart communities is a new method and important measure to ensure the security of residential areas. In order to solve the problem of low accuracy in face recognition caused by distorting facial features due to monitoring camera angles and other external factors, this paper proposes the following optimization strategies in designing a face recognition network: firstly, a global graph convolution module is designed to encode facial features as graph nodes, and a multi-scale feature enhancement residual module is designed to extract facial keypoint features in conjunction with the global graph convolution module. Secondly, after obtaining facial keypoints, they are constructed as a directed graph structure, and graph attention mechanisms are used to enhance the representation power of graph features. Finally, tensor computations are performed on the graph features of two faces, and the aggregated features are extracted and discriminated by a fully connected layer to determine whether the individuals' identities are the same. Through various experimental tests, the network designed in this paper achieves an AUC index of 85.65% for facial keypoint localization on the 300W public dataset and 88.92% on a self-built dataset. In terms of face recognition accuracy, the proposed network achieves an accuracy of 83.41% on the IBUG public dataset and 96.74% on a self-built dataset. Experimental results demonstrate that the network designed in this paper exhibits high detection and recognition accuracy for faces in surveillance videos.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.1
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• pp.163-173
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• 2021

In the era of digital transformation, the transportation underprivileged remains as an underprivileged class without the benefits of technological advances. Electric assist devices for the People with disability are inadequate to provide services suitable for the current traffic environment, although the mobility of the People with disability is improved. In this paper, we develop IoT smart mobility by deriving essential elements through user satisfaction surveys to efficiently move physical distances based on the experience of users using existing electric assistive devices. Based on the data collected through user satisfaction survey, quantitative analysis using TF-IFD and qualitative analysis based on QFD are performed to determine the importance of user requirements. For the evaluation of IoT smart mobility design results reflecting essential functions, usability verification is conducted by forming an expert evaluation team in various fields. In the future, we plan to conduct a service design study that can improve mobility convenience and provide mobility service solutions by designing to provide efficient public services by utilizing IoT smart mobility to the People with disability.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.11
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• pp.1337-1342
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• 2019

Medical institutions face the challenge of securing competitiveness among medical institutions due to the rapid spread of ICT convergence, and managing data that is growing at an enormous rate due to the emergence of big data and the emergence of the Internet of Things. The big data paradigm of the medical community is not just about large data or tools and processes for processing and analyzing it, but also means a computerized shift in the way people live, think and study. As the medical data is recently released, the demand for the use of medical data is increasing. Therefore, the research on disease detection system based on public data using open source that can help rational and efficient decision making was conducted. As a result of the experiment, unlike a simple disease inquiry or a symptom inquiry about a single disease provided by a public institution, related diseases are searched by a symptom or a cause.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.179-188
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• 2018

Recently, blockchain technology has been recognized as one of the most important issues for the 4th Industrial Revolution which can be represented by Artificial Intelligence and Internet of Things. Cryptocurrency, named Bitcoin, was the first successful implementation of blockchain, and it triggered the emergence of various cryptocurrencies. In addition, blockchain technology has been applied to various applications such as finance, healthcare, manufacturing, logistics as well as public services. Distributed consensus algorithm is an essential component in blockchain, and it enables all nodes belonging to blockchain network to make an agreement, which means all nodes have the same information. For example, Bitcoin uses a consensus algorithm called Proof-of-Work (PoW) that gives possession of block generation based on the computational volume committed by nodes. However, energy consumption for block generation in PoW has drastically increased due to the growth of computational performance to prove the possession of block. Although many other distributed consensus algorithms including Proof-of-Stake are suggested, they have their own advantages and limitations, and new research works should be proposed to overcome these limitations. For doing this, above all things, we need to establish an evaluation method existing distributed consensus algorithms. Based on this motivation, in this work, we suggest and analyze assessment items by classifying them as efficiency and safety perspectives for investigating existing distributed consensus algorithms. Furthermore, we suggest new assessment criteria and their implementation methods, which can be used for a baseline for improving performance of existing distributed consensus algorithms and designing new consensus algorithm in future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.295-298
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• 2014

In recently, a climatic change(such as subtropical climate and frequent unusual high temperature) and the open-trade policies of agricultural & livestock products are increasing the outbreak risk of highly pathogenic avian influenza(HPAI) and foot and mouth disease(FMD), and accordingly the socio-economic damage and impacts are also increasing due to the cases such as damage from the last 5 times of FMD outbreak(3,800 billion won), from 10 years public control cost of Pine Wilt Disease (PWD)(238.3 billion won), and from the increased invasive pests of exotic plant like isoptera. Therefore, the establishment of new operation strategy of IoT(Internet of Things) based satellite early warning system(SEWS) for plants and animals as a subsystem of national disaster response and management system is being required, where the forensic technology & measures should be applied as a government policy to estimate the post compensation and to carry out the legal responsibility.