• Journal of Space Technology and Applications
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• v.4 no.2
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• pp.87-104
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• 2024

CubeSats are being utilized in various fields such as Earth observation, space exploration, and verification of space science and technology due to their low cost, short development period, enhanced mission-oriented performance, and ability to perform various missions through constellation and formation flights. Recently, as the availability of CubeSats has increased and their application areas have expanded, the demand for high-speed transmission of large amounts of data obtained by CubeSats has increased unprecedentedly. Laser-based free space optical communication technology is capable of transmitting large amounts of data at high speeds compared to the existing radio communication methods, and provides various advantages such as use of unlicensed spectrum, low cost, low power, high security characteristics, and of use a small communication platform. For this reason, it is suitable as a high-performance communication technology to support CubeSat missions. In this paper, we will present the core components and characteristics of CubeSat-based space laser communication system, and recent research trends, as well as representative technology development results.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.77-77
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• 2023

네팔은 6천여 개가 넘는 강이 존재하며 불안정한 기후로 인해 산사태와 홍수가 빈번하게 발생하고 있고, 노후된 상수도 시설 문제도 있어 효과적인 물관리 대책이 필요하다. 이 연구는 네팔 카트만두 인근의 소도시인 둘리켈시를 대상지역으로 하여 스마트 물관리 도입 방안에 대한 타당성 연구조사를 수행하였다. 이를 통해 스마트물관리(SWM) 사업계획을 수립하고, 상수도 관리 기술이 둘리켈시 수돗물 공급 전과정에서 수량·수질을 체계적으로 관리할 수 있도록 계기를 마련하는 것을 목표로 하였다. 주요 연구로 국내 스마트물관리 기술의 네팔 적용성 분석, 수운영 자료및 현황 조사, 스마트 물관리 도입을 위한 수도 시설의 설계 방향을 수립하였고, 기술 도입과 확대 방안을 제시하였다. 스마트 물관리 기술의 적용 타당성 분석을 위하여 현장 조사를 수행하였고, 수리 계측데이터의 분석, 수원지, 정수장, 주요 관로에서의 수질을 분석하였다. 이외에 관망수리해석을 기반으로 대상지역 내 공급가능한 수량을 산정하였고, 상수도 공급이 어려운 지역에 대한 추가시설 확보방안을 제시하였다. 현재 조건에서의 상수도 운영, 관리체계를 분석하여 노후화된 상수도 시설의 개선 및 보완 방안, 스마트 물관리 기술 도입 가능성도 제시하고자 하였다. 연구 결과를 기반으로 기본계획과 실시설계를 통하여 스마트 물관리 인프라가 둘리켈시에 도입될 경우, 물 공급의 불균형으로 인한 피해를 최소화하고, 수돗물의 안정적인 공급 및 수질 안정성 확보, 상수관망에서 수질 및 누수 사고에 대처가 가능할 것으로 보이며 인근 카트만두를 비롯한 지방 소도시에도 스마트 물관리 기술적용에 기틀이 될 것으로 기대된다.

• Smart Media Journal
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• v.10 no.2
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• pp.110-118
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• 2021

The Internet of Things (IoT) technology, a key growth engine of the 4th industrial revolution, has grown to a stage where it can autonomously communicate with each other and process data according to space and circumstances. Accordingly, the IT infrastructure becomes increasingly complex and the importance of the monitoring field for maintaining the system stably is increasing. Monitoring technology has been used in the past, but there is a need to find a flexible monitoring system that can respond to the rapidly changing ICT technology. This paper conducts research on designing and testing an open source-based Prometheus monitoring system. We builds a simple infrastructure based on IoT devices and collects data about devices through the Exporter. Prometheus collects data based on pull and then integrates into one dashboard using Grafana and visualizes data to monitor device information.

• Smart Media Journal
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• v.12 no.11
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• pp.67-76
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• 2023

We propose a visualization method to respond to civil complaints through an analysis of the impact of blasting. In order to analyze the impact of blasting on tunnel excavation, we propose a simulation visualization method considering the mutual influence of the construction infrastructure by linking measurement data and 3D BIM model. First, the level of BIM modeling required for simulation was defined. In addition, vibration measurement data were collected for the GTX-A construction site, terrain and structure BIM were created, and a method for visualizing measurement data using blast vibration estimation was developed. Next, a spherical blasting influence source library was developed for visualization of the blasting influence source, and a specification table that could be linked with Revit Dynamo automation logic was constructed. Using this result, a method for easily visualizing the impact analysis of blasting vibration in 3D was proposed.

• Journal of Technology Innovation
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• v.26 no.4
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• pp.199-232
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• 2018

There are increasing needs for understanding and fathoming of business management environment through big data analysis at industrial and corporative level. The research using the company disclosure information, which is comprehensively covering the business performance and the future plan of the company, is getting attention. However, there is limited research on developing applicable analytical models leveraging such corporate disclosure data due to its unstructured nature. This study proposes a text-mining-based analytical model for industrial and firm level analyses using publicly available company disclousre data. Specifically, we apply LDA topic model and word2vec word embedding model on the U.S. SEC data from the publicly listed firms and analyze the trends of business topics at the industrial and corporate levels. Using LDA topic modeling based on SEC EDGAR 10-K document, whole industrial management topics are figured out. For comparison of different pattern of industries' topic trend, software and hardware industries are compared in recent 20 years. Also, the changes of management subject at firm level are observed with comparison of two companies in software industry. The changes of topic trends provides lens for identifying decreasing and growing management subjects at industrial and firm level. Mapping companies and products(or services) based on dimension reduction after using word2vec word embedding model and principal component analysis of 10-K document at firm level in software industry, companies and products(services) that have similar management subjects are identified and also their changes in decades. For suggesting methodology to develop analysis model based on public management data at industrial and corporate level, there may be contributions in terms of making ground of practical methodology to identifying changes of managements subjects. However, there are required further researches to provide microscopic analytical model with regard to relation of technology management strategy between management performance in case of related to various pattern of management topics as of frequent changes of management subject or their momentum. Also more studies are needed for developing competitive context analysis model with product(service)-portfolios between firms.

• Journal of Life Science
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• v.25 no.3
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• pp.357-367
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• 2015

With the ongoing development of next-generation sequencing (NGS) platforms and advancements in the latest bioinformatics tools at an unprecedented pace, the ultimate goal of sequencing the human genome for less than $1,000 can be feasible in the near future. The rapid technological advances in NGS have brought about increasing demands for statistical methods and bioinformatics tools for the analysis and management of NGS data. Even in the early stages of the commercial availability of NGS platforms, a large number of applications or tools already existed for analyzing, interpreting, and visualizing NGS data. However, the availability of this plethora of NGS data presents a significant challenge for storage, analyses, and data management. Intrinsically, the analysis of NGS data includes the alignment of sequence reads to a reference, base-calling, and/or polymorphism detection, de novo assembly from paired or unpaired reads, structural variant detection, and genome browsing. While the NGS technologies have allowed a massive increase in available raw sequence data, a number of new informatics challenges and difficulties must be addressed to improve the current state and fulfill the promise of genome research. This review aims to provide an overview of major NGS technologies and bioinformatics tools for NGS data analyses.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.1-13
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• 2021

In this study, a time series analysis technique was applied to calibrate and predict traffic data for various purposes, such as planning, design, maintenance, and research. Existing algorithms have limitations in application to data such as traffic data because they show strong periodicity and seasonality or irregular data. To overcome and supplement these limitations, we applied the SARIMA model, an analytical technique that combines the autocorrelation model, the Seasonal Auto Regressive(SAR), and the seasonal Moving Average(SMA). According to the analysis, traffic volume prediction using the SARIMA(4,1,3)(4,0,3) 12 model, which is the optimal parameter combination, showed excellent performance of 85% on average. In addition to traffic data, this study is considered to be of great value in that it can contribute significantly to traffic correction and forecast improvement in the event of missing traffic data, and is also applicable to a variety of time series data recently collected.

• Advanced Industrial SCIence
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• v.1 no.2
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• pp.24-29
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• 2022

Recently, smart farm research that applies IoT technology to various farms is being actively conducted to improve agricultural cooling power and minimize cost reduction. In particular, methods for automatically and remotely controlling environmental information data around smart farms through IoT devices are being studied. This paper proposes a processing model that can maintain an optimal growth environment by monitoring environmental information data collected from smart farms in real time based on machine learning. Since the proposed model uses machine learning technology, environmental information is grouped into multiple blockchains to enable continuous data collection through rich big data securing measures. In addition, the proposed model selectively (or binding) the collected environmental information data according to priority using weights and correlation indices. Finally, the proposed model allows us to extend the cost of processing environmental information to n-layer to a minimum so that we can process environmental information in real time.

• Journal of Platform Technology
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• v.11 no.4
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• pp.50-61
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• 2023

The advancement of various big data technologies has had a tremendous impact on many industries. Diverse big data research studies have been conducted to process and analyze massive data quickly. Under these circumstances, new emerging technologies such as high-capacity persistent memory (PMEM) and Compute Express Link (CXL) have lately attracted significant attention. However, little investigation into a big data "search" platform has been made. Moreover, most big data software platforms have been still optimized for traditional DRAM-based computing systems. This paper first evaluates the basic performance of Intel Optane PMEM, and then investigates both indexing and searching performance of Elasticsearch, a widely-known enterprise big data search platform, on the PMEM-based computing system to explore its effectiveness and possibility. Extensive and comprehensive experiments shows that the proposed Optane PMEM-based Elasticsearch achieves indexing and searching performance improvement by an average of 1.45 times and 3.2 times respectively compared to DRAM-based system. Consequently, this paper demonstrates the high I/O, high-capacity, and nonvolatile PMEM-based computing systems are very promising for big data search platforms.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.935-940
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• 2023

Most text data collected through web scraping for artificial intelligence and big data analysis is generally large and unstructured, so a purification process is required for big data analysis. The process becomes structured data that can be analyzed through a heuristic pre-processing refining step and a post-processing machine refining step. Therefore, in this study, in the post-processing machine refining process, the Korean dictionary and the stopword dictionary are used to extract vocabularies for frequency analysis for word cloud analysis. In this process, "user-defined stopwords" are used to efficiently remove stopwords that were not removed. We propose a methodology for applying the "thesaurus" and examine the pros and cons of the proposed refining method through a case analysis using the "user-defined stop word thesaurus" technique proposed to complement the problems of the existing "stop word dictionary" method with R's word cloud technique. We present comparative verification and suggest the effectiveness of practical application of the proposed methodology.