• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.4
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• pp.237-250
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• 2023

Orthophotos and DEMs were generated by UAV-based aerial photogrammetry and an attempt was made to apply them to detailed investigations for the production of flood traces. The cultivated area located in Goa-eup, Gumi, where the embankment collapsed and inundated inundation occurred due to the impact of 6th Typhoon Sanba in 2012, was selected as rhe target area. To obtain optimal accuracy of UAV photogrammetry performance, the UAV images were taken under the optimal placement of 19 GCPs and then point cloud, DEM, and orthoimages were generated through image processing using Pix4Dmapper software. After applying CloudCompare's CSF Filtering to separate the point cloud into ground elements and non-ground elements, a finally corrected DEM was created using only non-ground elements in GRASS GIS software. The flood level and flood depth data extracted from the final generated DEM were compared and presented with the flood level and flood depth data from existing data as of 2012 provided through the public data portal site of the Korea Land and Geospatial Informatix Corporation(LX).

• Journal of Industrial Convergence
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• v.22 no.4
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• pp.1-9
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• 2024

Smart factories represent production facilities where cutting-edge information and communication technologies are fused with manufacturing processes, reflecting rapid advancements and changes in the global manufacturing sector. They capitalize on the integration of robotics and automation, the Internet of Things (IoT), and the convergence of artificial intelligence technologies to maximize production efficiency in various manufacturing environments. However, the smart factory environment is prone to security threats and vulnerabilities due to various attack techniques. When security threats occur in smart factories, they can lead to financial losses, damage to corporate reputation, and even human casualties, necessitating an appropriate security response. Therefore, this paper proposes a security authentication mechanism for safe communication in the smart factory environment. The components of the proposed authentication mechanism include smart devices, an internal operation management system, an authentication system, and a cloud storage server. The smart device registration process, authentication procedure, and the detailed design of anomaly detection and update procedures were meticulously developed. And the safety of the proposed authentication mechanism was analyzed, and through performance analysis with existing authentication mechanisms, we confirmed an efficiency improvement of approximately 8%. Additionally, this paper presents directions for future research on lightweight protocols and security strategies for the application of the proposed technology, aiming to enhance security.

• The Transactions of the Korea Information Processing Society
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• v.13 no.2
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• pp.48-59
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• 2024

As functions that support virtualization on their own in hardware are developed, user applications having various workloads are operating efficiently in the virtualization system. SR-IOV is a virtualization support function that takes direct access to PCI devices, thus giving a high I/O performance by minimizing the need for hypervisor or operating system interventions. With SR-IOV, network I/O acceleration can be realized in virtualization systems that have relatively long I/O paths compared to bare-metal systems and frequent context switches between the user area and kernel area. To take performance advantages of SR-IOV, network resource management policies that can derive optimal network performance when SR-IOV is applied to an instance such as a virtual machine(VM) or container are being actively studied.This paper evaluates and analyzes the network performance of SR-IOV implementing I/O acceleration is compared with Virtio in terms of 1) network delay, 2) network throughput, 3) network fairness, 4) performance interference, and 5) multi-network. The contributions of this paper are as follows. First, the network I/O process of Virtio and SR-IOV was clearly explained in the virtualization system, and second, the evaluation results of the network performance of Virtio and SR-IOV were analyzed based on various performance metrics. Third, the system overhead and the possibility of optimization for the SR-IOV network in a virtualization system with high VM density were experimentally confirmed. The experimental results and analysis of the paper are expected to be referenced in the network resource management policy for virtualization systems that operate network-intensive services such as smart factories, connected cars, deep learning inference models, and crowdsourcing.

• Korean Journal of Construction Engineering and Management
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• v.25 no.3
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• pp.17-26
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• 2024

Quality management work at construction sites demands substantial time and effort, involving the preparation of documents in Excel, approval processes, and the execution of quality tests. These Excel-based tasks include printing quality test reports, performing quality tests, generating and approving test reports, and preparing management ledgers. This division of processes extends the duration of work and diminishes efficiency. Accordingly, a cloud-based construction site quality management system was developed to enhance the productivity of quality management work. The purpose of this study is to analyze the productivity of the construction site quality management system, which is in the early stages of implementation at construction sites. This study implemented the construction site quality management system at a road construction site and scrutinized subsequent alterations in the quality management workflow before and after the implementation. Additionally, a survey was conducted among quality control engineers to collect data on work time both before and after the introduction of the construction site quality management system. Based on the collected data, the Monte-Carlo simulation method was applied to analyze the productivity improvement effect of the construction site quality management system, and the results were presented. The results of this study can serve as foundational data for future research endeavors focused on the automation of quality management works.

• Journal of Industrial Convergence
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• v.22 no.6
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• pp.51-59
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• 2024

The purpose of the paper is to suggest government policies that are practically helpful to small business owners in pandemic situations such as COVID-19. To this end, keyword frequency analysis and word cloud analysis of text mining analysis were performed by crawling news articles centered on the keywords "COVID-19 Support for Small Businesses", "The Impact of Small Businesses by Response System to COVID-19 Infectious Diseases", and "COVID-19 Small Business Economic Policy", and major issues were identified through LDA topic modeling analysis. As a result of conducting LDA topic modeling, the support policy for small business owners formed a topic label with government cash and financial support, and the impact of small business owners according to the COVID-19 infectious disease response system formed a topic label with a government-led quarantine system and an individual-led quarantine system, and the COVID-19 economic policy formed a topic label with a policy for small business owners to acquire economic crisis and self-sustainability. Focusing on the organized topic label, it was intended to provide basic data for small business owners to understand the damage reduction policy for small business owners and the policy for enhancing market competitiveness in the future pandemic situation.

• Journal of The Korean Association For Science Education
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• v.44 no.1
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• pp.77-86
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• 2024

This study analyzed students' discourse and learning to investigate the impact of using Google Docs in science classes. The researcher, who is also a science teacher, conducted classes for 49 second-year middle school students. The classes included one using Google Docs and another using traditional paper worksheets covering identical content. Students' discourse collected from each class was compared and analyzed using Epistemic Network Analysis (ENA). The findings indicated that in the class using Google Docs, the proportion of discourse related to task was higher compared to the traditional class. More specifically, discourse regarding taking and uploading photos was prominent. However, such discourse did not lead to peer learning as intended by the teacher. An analysis based on achievement levels revealed that the class utilizing Google Docs had a relatively higher proportion of discourse from lower-achieving students. Additionally, differences were observed in the types of utterances and connection structures between the higher and lower-achieving students. The higher-achieving students took a leading role in providing suggestions and explanations, while the lower-achieving students played a role in transcribing them, with this tendency being more pronounced in the class using Google Docs. Lastly, students' changes in perception regarding the cause of static electricity were visualized using ENA. Based on the research findings, this study proposes strategies to enhance collaborative learning using Google Docs, including the use of open-ended problems to allow diverse opinions and outputs, and exploring the potential use of ENA to assess the learning effects of conceptual learning.

• The Transactions of the Korea Information Processing Society
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• v.13 no.3
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• pp.91-101
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• 2024

The utilization of container virtualization technology ensures the consistency and portability of data-intensive and memory volatile workflows. Kubernetes serves as the de facto standard for orchestrating these container applications. Cloud users often overprovision container applications to avoid container restarts caused by resource shortages. However, overprovisioning results in decreased CPU and memory resource utilization. To address this issue, oversubscription of container resources is commonly employed, although excessive oversubscription of memory resources can lead to a cascade of container restarts due to node memory scarcity. Container restarts can reset operations and impose substantial overhead on containers with high memory volatility that include numerous stateful applications. This paper proposes a technique to mitigate container restarts in a memory oversubscription environment based on Kubernetes. The proposed technique involves identifying containers that are likely to request memory allocation on nodes experiencing high memory usage and temporarily pausing these containers. By significantly reducing the CPU usage of containers, an effect similar to a paused state is achieved. The suspension of the identified containers is released once it is determined that the corresponding node's memory usage has been reduced. The average number of container restarts was reduced by an average of 40% and a maximum of 58% when executing a high memory volatile workflow in a Kubernetes environment with the proposed method compared to its absence. Furthermore, the total execution time of a container workflow is decreased by an average of 7% and a maximum of 13% due to the reduced frequency of container restarts.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.4
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• pp.155-165
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• 2024

Software as a Service (SaaS) has become one of the fastest-growing software business models in recent years. Even during the economic downturn following the pandemic, the SaaS business has emerged as a crucial model for IT companies. The revenue structure of SaaS, which is based on the subscription economy model, ensures that users pay only for the services used. In other words, SaaS operates on a subscription-based billing model, thus providing subscribers access to software uploaded to cloud computers via the Internet. This study aimed to explore the manner by which software-solution firms have to counteract the decline in profit and loss sales caused by changing their business-model orientation from on-premise deployment software to subscription-based software. Additionally it analyzes a method for selecting a subscription-based pricing model and rapidly recovering the investment costs via quantitative business-viability assessment. By calculating subscription fees via a more quantitative business-viability evaluation instead of focusing on conventional business-planning methods that rely on qualitative methods, companies are expected to be equipped in providing services to customers at reasonable costs. This strategy will facilitate them in leading emerging growth sectors.

• Journal of Korea Port Economic Association
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• v.40 no.1
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• pp.31-59
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• 2024

In June 2016, the term "Fourth Industrial Revolution" was first used at the World Economic Forum in Davos, Switzerland, and it gained worldwide attention. Consequently, the importance of smart ports has increased as the shipping industry has been incorporating various Fourth Industrial Revolution technologies. Currently, major countries around the world are working to achieve digital transformation in the maritime and port industry by establishing comprehensive smart ports. However, the smartification of domestic ports in South Korea is currently limited to a few areas such as Busan, Incheon, and Gwangyang, focusing on port automation. In this context, this study performed keyword analysis to identify key components of smart ports and conducted Analytic Hierarchy Process (AHP) analysis among relevant stakeholders to determine the priorities for the Introduction of smart ports in South Korea. The analysis revealed that universities prioritized automation, intelligenceization, informatization and environmentalization in that order. Research institutes prioritized informatization, intelligenceization, automation and environmentalization. Government agencies prioritized informatization, automation, intelligenceization and environmentalization, while private sector enterprises prioritized automation, intelligenceization, informatization, and environmentalization.

• Journal of Internet of Things and Convergence
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• v.10 no.3
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• pp.19-24
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• 2024

Recent advances in large-scale data processing technologies such as big data, cloud computing, and artificial intelligence have increased the demand for high-performance storage devices in data centers and enterprise environments. In particular, the fast data response speed of storage devices is a key factor that determines the overall system performance. Solid state drives (SSDs) based on the Non-Volatile Memory Express (NVMe) interface are gaining traction, but new bottlenecks are emerging in the process of handling large data input and output requests from multiple hosts simultaneously. SSDs typically process host requests by sequentially stacking them in an internal queue. When long transfer length requests are processed first, shorter requests wait longer, increasing the average response time. To solve this problem, data transfer timeout and data partitioning methods have been proposed, but they do not provide a fundamental solution. In this paper, we propose a dual queue based scheduling scheme (DQBS), which manages the data transfer order based on the request order in one queue and the transfer length in the other queue. Then, the request time and transmission length are comprehensively considered to determine the efficient data transmission order. This enables the balanced processing of long and short requests, thus reducing the overall average response time. The simulation results show that the proposed method outperforms the existing sequential processing method. This study presents a scheduling technique that maximizes data transfer efficiency in a high-performance SSD environment, which is expected to contribute to the development of next-generation high-performance storage systems