• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.955-963
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• 2022

The Internet of Things (IoT), combined with various technologies, is rapidly becoming an integral part of our daily life. While it is rapidly taking root in society, security considerations are relatively insufficient, making it a major target for cyber attacks. Since all devices in the IoT environment are connected to the Internet and are closely used in daily life, the damage caused by cyber attacks is also serious. Therefore, encryption communication using a network security protocol must be considered for a service in a more secure IoT environment. A representative network security protocol includes TLS (Transport Layer Protocol) defined by the IETF. This paper analyzes the performance measurement results for TLS version 1.2 and version 1.3 in an IoT device open platform environment to predict the load of TLS, a representative network security protocol, in IoT devices with limited resource characteristics. In addition, by analyzing the performance of each major cryptographic algorithm in version 1.3, we intend to present a standard for setting appropriate network security protocol properties according to IoT device specifications.

• Journal of Korea Trade
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• v.23 no.6
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• pp.113-130
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• 2019

Purpose - This paper investigates applicability of blockchain based bill of lading under the current legal environment. Legal requirements of electronic bill of lading will be analyzed based on the Rotterdam Rules and recently enacted UNCITRAL Model Law on Electronic Transferable Records. Using comparative analysis with the previous registry model for electronic bill of lading, this paper examines the advantages of blockchain based bill of lading. Design/methodology - This research reviewed previous efforts for dematerializing bill of lading with its limitation. Main features of blockchain technology which can make up for deficiencies of registry model also be investigated to analyze whether these features can satisfy the requirements for the legal validity of the negotiable electronic transport record or electronic transferable records under the Rotterdam Rules and the MLETR. Findings - Main findings of this research can be summarized as follows: Blockchain system operated in an open platform can improve transparency and scalability in transfer of electronic bill of lading by assuring easy access for transaction. Distributed ledger technology of blockchain makes it more difficult to forge or tamper with transactions because all participants equally shares identical transaction records. Consensus mechanism and timestamp in a blockchain transaction guarantee the integrity and uniqueness of a transaction. These features are enough to satisfy the requirements of electronic transferable records under the Rotterdam Rules and MLTER. Originality/value - This study has significance in that it provided implications for the introduction of electronic bill of lading by analyzing whether the blockchain based electronic bill of lading model meets the legal requirements under the current legal system prepared prior to the introduction of blockchain technology, and by presenting the advantages of the blockchain based bill of lading model through comparative analysis with the existing registry model.

• Journal of the Korea Society of Computer and Information
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• v.28 no.3
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• pp.67-73
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• 2023

Under the influence of COVID-19, as a measure of social distancing for about two years and one month, non-face-to-face services using ICT element technology are expanding not only to the education sector but to all fields. In particular, as educational programs using the Metaverse platform spread to various fields, educators, and learners have more learning experiences using Edutech, but problems through non-face-to-face learning such as reduced immersion or concentration in education are raising In this paper, to overcome the problems raised through non-face-to-face learning and develop metaverse immersive media digital contents to improve the educational environment, we utilize VR (Virtual Reality) based on an immersive metaverse to provide education / Training contents and the educational environment was established. In this paper, we presented a system to increase immersion and concentration in educational contents in a virtual environment using HMD (Head Mounted Display) for learners who are put into military education/training. Immersion was further improved.

• Journal of Digital Policy
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• v.1 no.2
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• pp.1-8
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• 2022

In case of a dangerous situation, the roof, which serves as an emergency exit, must be open in case of fire according to the Fire Act. However, when the roof door is opened, it has become a place of various incidents and accidents such as illegal entry, crime, and suicide. As a result, it is a reality to close the roof door in terms of facility management to prevent crime, various incidents, and accidents. Accordingly, the government is pushing to legislate regulations on housing construction standards, etc. that mandate the installation of electronic automatic opening and closing devices on rooftop doors. Therefore, in this paper, an intelligent emergency door opening/closing device system is proposed. To this end, an intelligent emergency door opening and closing system was developed by linking wired and wireless access counting and AI image analysis. Finally, it is possible to build a wireless communication-based integrated management platform that provides remote control and history management in a centralized method of device status real-time monitoring and event alarm.

• Journal of Ocean Engineering and Technology
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• v.36 no.5
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• pp.313-325
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• 2022

Recently around the world, coastal erosion is paying attention as a social issue. Various constructions using low-crested and submerged structures are being performed to deal with the problems. In addition, a prediction study was researched using machine learning techniques to determine the wave attenuation characteristics of low crested structure to develop prediction matrix for wave attenuation coefficient prediction matrix consisting of weights and biases for ease access of engineers. In this study, a deep neural network model was constructed to predict the wave height transmission rate of low crested structures using Tensor flow, an open source platform. The neural network model shows a reliable prediction performance and is expected to be applied to a wide range of practical application in the field of coastal engineering. As a result of predicting the wave height transmission coefficient of the low crested structure depends on various input variable combinations, the combination of 5 condition showed relatively high accuracy with a small number of input variables defined as 0.961. In terms of the time cost of the model, it is considered that the method using the combination 5 conditions can be a good alternative. As a result of predicting the wave transmission rate of the trained deep neural network model, MSE was 1.3×10^-3, I was 0.995, SI was 0.078, and I was 0.979, which have very good prediction accuracy. It is judged that the proposed model can be used as a design tool by engineers and scientists to predict the wave transmission coefficient behind the low crested structure.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.542-558
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• 2023

A digital focus index (DFI) is a value used to determine image focus in scientific apparatus and smart devices. Automatic focus (AF) is an iterative and time-consuming procedure; however, its processing time can be reduced using a general processing unit (GPU) and a multi-core processor (MCP). In this study, parallel architectures of a minimax search algorithm (MSA) are applied to two DFIs: range algorithm (RA) and image contrast (CT). The DFIs are based on a histogram; however, the parallel computation of the histogram is conventionally inefficient because of the bank conflict in shared memory. The parallel architectures of RA and CT are constructed using parallel reduction for MSA, which is performed through parallel relative rating of the image pixel pairs and halved the rating in every step. The array size is then decreased to one, and the minimax is determined at the final reduction. Kernels for the architectures are constructed using open source software to make it relatively platform independent. The kernels are tested in a hexa-core PC and an embedded device using Lenna images of various sizes based on the resolutions of industrial cameras. The performance of the kernels for the DFIs was investigated in terms of processing speed and computational acceleration; the maximum acceleration was 32.6× in the best case and the MCP exhibited a higher performance.

• Journal of Industrial Convergence
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• v.21 no.4
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• pp.73-80
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• 2023

This study aims to explore college students' perception for offline class using the online platform Padlet as a tool in liberal arts class during the COVID-19 lockdown. Thirty seven students participated in the study, and quantitative and qualitative methods were used. The statistical results and analysis for open-ended questions are as follows; Firstly, the participants showed satisfaction as the highest variable followed by learning effect, then motivation but participation rated the lowest(p< .001). Secondly, there was statistical significance except participation depending on gender(p< .001). Female students felt higher satisfaction, learning effect, and motivation than male students. Thirdly, there was statistical significance between freshmen and senior depending on grade(p< .001). Freshmen felt higher satisfaction, participation, learning effect, and motivation than seniors. Fourthly, qualitative analysis showed participants felt positive about using Padlet as a education tool in offline class. Finally, the pedagogical implication and suggestions were discussed.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.453-453
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• 2023

상수관망의 수질사고와 이상상황 발생시 대응을 위해서는 급수구역에 설치되어 있는 자동수질측정기, 정밀여과장치, 재염소주입설비, 자동드레인 등의 계측·제어설비들 간의 유기적인 정보공유를 통한 제어를 필요로 한다. 스마트 상수관망 운영플랫폼은 이러한 인프라 시설의 운영방안을 고려하여 분산되어 있는 계측데이터를 통합감시 및 제어하는 시스템으로 개발되었다. 상수관망 운영플랫폼은 능동형 분석 제어기술을 도입하여, 스마트 상수관망 인프라 설비를 최적제어할 수 있도록 구현하였다. 통합운영 플랫폼은 PostgreSQL, PostGIS, GeoServer, OpenLayers 등의 기술을 활용하여 개발하였다. 플랫폼은 계측감시, 시설관리, 운영제어 등의 기능으로 구성되며, 상수도 업무지원을 위한 관망해석 및 네트워크 분석 기능을 지원한다. 본 시스템은 스마트 상수도 구축사업을 통해 구축한 유량·수질모니터링 장비와 수질관리를 위해 도입된 재염소, 자동드레인 설비의 운영상태를 실시간 조회하는 모니터링 프로그램과, 관망해석 프로그램 그리고 대상설비의 최적제어를 위한 운영관리 프로그램으로 구성되어 있다. 모니터링 프로그램은 현장에서 측정되고 있는 유량, 수압, 수질, 펌프운전 등의 상태를 실시간으로 감시하고 클라우드 데이터베이스에 저장·관리하는 기능을 수행한다. 관망해석 프로그램은 EPA_Net모형과 연계되어 관망수리·수질해석을 수행하는 부분으로 재염소설비의 염소 추가주입이나 자동드레인을 통한 배제시 나타나게되는 관의 수리·수질변화를 클라우드 컴퓨팅 환경에서 분석하고 결과를 가시화 하는 기능을 갖고 있다. 운영관리 프로그램은 재염소 주입이 필요할 경우 주입량의 산정하는 부분과 관망 파손이나 수질사고 발생시 최적 단수예상지역을 도출하는 기능을 보유하고 있다. 향후 스마트 상수관망의 능동형 수질관리를 추진하는 지자체에 도입하여 인프라운영관리 기술 확보 및 수질관리 능력 개선과 실시간 감시 및 위기 대응능력 향상에 기여할 것으로 기대된다.

• Journal of IKEEE
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• v.26 no.1
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• pp.62-66
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• 2022

Recently, there have been many research efforts based on data-based deep learning technologies to deal with the interference problem between heterogeneous wireless communication devices in unlicensed frequency bands. However, existing approaches are commonly based on the use of complex neural network models, which require high computational power, limiting their efficiency in resource-constrained network interfaces and Internet of Things (IoT) devices. In this study, we address the problem of classifying heterogeneous wireless technologies including Wi-Fi and ZigBee in unlicensed spectrum bands. We focus on a data-driven approach that employs a supervised-learning method that uses received signal strength indicator (RSSI) data to train Deep Convolutional Neural Networks (CNNs). We propose a simple measurement methodology for collecting RSSI training data which preserves temporal and spectral properties of the target signal. Real experimental results using an open-source 2.4 GHz wireless development platform Ubertooth show that the proposed sampling method maintains the same accuracy with only a 10% level of sampling data for the same neural network architecture.

• Design Convergence Study
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• v.16 no.5
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• pp.125-140
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• 2017

This study explores potential capability of a machine learning approach for monitoring urban morphology based on an evident case study. The case study conveys year 2006 investigations on interpreting urban morphology of Boston Main Streets by applying a machine learning approach. From the lesson of the precedent study, in 2016, another field research and interview was conducted to compare changes in urban situation, data commons culture, and technology innovation during the decade. This paper describes open possibilities to advance urban monitoring for morphological changes. Most of all, a multi-participatory data platform enables managing urban data system in real time. Second, collaboration with machines with artificial intelligence can intervene the framework of the urban management system as well as transform it through new demands of innovative industries. Recently, urban regeneration became a dominant urban planning strategy in Korean, therefore, urban monitoring is on demand. It is timely important to correspond to in-situ problems based on empirical research.