• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.33-43
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• 2024

This research assessed the applicability of the You Only Look Once (YOLO)v8 and DeepLabv3+ models for the effective detection of compost heaps, identified as a significant source of non-point source pollution. Utilizing high-resolution imagery acquired through Unmanned Aerial Vehicles(UAVs), the study conducted a comprehensive comparison and analysis of the quantitative and qualitative performances. In the quantitative evaluation, the YOLOv8 model demonstrated superior performance across various metrics, particularly in its ability to accurately distinguish the presence or absence of covers on compost heaps. These outcomes imply that the YOLOv8 model is highly effective in the precise detection and classification of compost heaps, thereby providing a novel approach for assessing the management grades of compost heaps and contributing to non-point source pollution management. This study suggests that utilizing UAVs and deep learning technologies for detecting and managing compost heaps can address the constraints linked to traditional field survey methods, thereby facilitating the establishment of accurate and effective non-point source pollution management strategies, and contributing to the safeguarding of aquatic environments.

• Journal of the Korean Society of Radiology
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• v.17 no.6
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• pp.911-917
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• 2023

The method of observing nodular changes on the liver surface using clinical ultrasonography is useful for diagnosing cirrhosis. However, the speckle noise that inevitably occurs in ultrasound images makes it difficult to identify changes in the liver surface and echo patterns, which has a negative impact on the diagnosis of cirrhosis. The purpose of this study is to model the median modified Wiener filter (MMWF), which can efficiently reduce noise in cirrhotic ultrasound images, and confirm its applicability. Ultrasound images were acquired using an ACR phantom and an actual cirrhotic patient, and the proposed MMWF algorithm and conventional noise reduction algorithm were applied to each image. Coefficient of variation (COV) and edge rise distance (ERD) were used as quantitative image quality evaluation factors for the acquired ultrasound images. We confirmed that the MMWF algorithm improved both COV and ERD values compared to the conventional noise reduction algorithm in both ACR phantom and real ultrasound images of cirrhotic patients. In conclusion, the proposed MMWF algorithm is expected to contribute to improving the diagnosis rate of cirrhosis patients by reducing the noise level and improving spatial resolution at the same time.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.508-518
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• 2023

This paper presents a new approach for the automatic mapping of discontinuities in a tunnel face based on its 3D digital model reconstructed by LiDAR scan or photogrammetry techniques. The main idea revolves around the identification of discontinuity areas in the 3D digital model of a tunnel face by segmenting its 2D projected images using a deep-learning semantic segmentation model called U-Net. The proposed deep learning model integrates various features including the projected RGB image, depth map image, and local surface properties-based images i.e., normal vector and curvature images to effectively segment areas of discontinuity in the images. Subsequently, the segmentation results are projected back onto the 3D model using depth maps and projection matrices to obtain an accurate representation of the location and extent of discontinuities within the 3D space. The performance of the segmentation model is evaluated by comparing the segmented results with their corresponding ground truths, which demonstrates the high accuracy of segmentation results with the intersection-over-union metric of approximately 0.8. Despite still being limited in training data, this method exhibits promising potential to address the limitations of conventional approaches, which only rely on normal vectors and unsupervised machine learning algorithms for grouping points in the 3D model into distinct sets of discontinuities.

• Information Systems Review
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• v.24 no.4
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• pp.119-142
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• 2022

Organizations are attempting a digital transformation that converts physical business processing into virtual business processing. Through this digital transformation, organizations are overcoming time and space constraints and creating competitiveness. The digital transformation of this work environment has been accelerated as many organizations have implemented remote work due to the recent COVID-19 pandemic. This study focused on business process virtualizability, which is the result of the rapid digital transformation of the work environment. Business process virtualizability is the resulting quality, such as the suitability or excellence of business processing in a virtual environment. This research model is the effect of process, IT and organizational characteristics on business process virtualizability. As a result of the verification of people who have experienced remote work in a virtual environment, first, it was confirmed that, in terms of process characteristics, sensory requirements affect business process virtualizability, but relationship requirements, synchronism requirements, and identification and control requirements do not. Second, in terms of IT characteristics, it was confirmed that representation and reach affect business process virtualizability. Third, it was confirmed that, in terms of organizational characteristics, job autonomy affects business process virtualizability, but evaluation unfairness does not. This study found that representation and reach of IT had the most significant influence on business process virtualizability, job autonomy was next, and sensory requirements had the lowest influence. This presents practical implications for organizations to increase the success potential of business process virtualizability.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.12 no.3
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• pp.225-233
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• 2007

To verify which loop regions of 18S rRNA gene are suitable as species-specific genetic markers in ciliates, we analyzed the genetic variation of 18S rRNA gene among 9 Euplotes species (Hypotrichia : Ciliophora). In our result, no inter-specific variation was detected from V1, V3 and V5 regions, and the length of V7 and V8 are 44 bp and 79 bp, respectively, which are too short to make genetic marker. In contrast, V2 and V4 may be good candidate segments of species-specific diagnostic molecular markers because these two regions are most variable ($1.75{\sim}20.61%$) and showed good inter-specific phylogeny. Furthermore, the sequences of V2 and V4 are 123 bp and 306 bp, respectively in length which are enough to make species-specific marker.

• Journal of Navigation and Port Research
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• v.48 no.3
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• pp.137-145
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• 2024

Recently, there has been an increase in the use of Automatic Identification Systems. Class A AIS is used for ships engaged in international voyages, while Class B AIS is utilized for smaller vessels navigating domestic coastlines. AtoN AIS is used for aids to navigation, AIS is employed for search and rescue aircraft, and AIS-SART is widely used worldwide. Accordingly, in 2022, the Maritime Safety Committee(MSC) of the International Maritime Organization(IMO) revised the performance standards for the satellite emergency positioning radio beacon(EP IRB) to include AIS signals along with 121.5 MHz for aircraft, which has been used as a homing signal. It was recommended to use together as a homing signal, and from July 1, 2022, it was decided that AIS-EP IRB that satisfies the revised performance standards will replace the existing EP IRB. Consequently, starting from July 1, 2022, it was decided that AIS-EPIRB, which meets the revised performance standards, will replace the existing EP IRB. This paper aims to verify the feasibility of implementing AIS-EPIRB, which has not yet been developed domestically. To achieve this, a dedicated chipset for AIS was used to additionally implement frequency generation of 161.975 MHz and 162.025 MHz and GMSK modulation to satisfy the requirements.

• Information Systems Review
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• v.19 no.3
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• pp.23-45
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• 2017

The ROK military is making a great effort and investment in establishing network-centric warfare, a future battlefield concept, as a major step in the establishment of a basic plan for military innovation. In the military organization level, an advanced process is introduced to shorten the command control time of the military and the business process is improved to shorten the decision time. In the information system dimension, an efficient resource management is achieved by establishing an automated command control system and a resource management information system by using the battle management information system. However, despite these efforts, we must evaluate the present level of informatization in an objective manner and assess the current progress toward the future goal of the military by using objective indicators. In promoting informatization, we must systematically identify the correct areas of improvement and identify policy directions to supplement in the future. Therefore, by analyzing preliminary research, workshops, and expert discussions on the major informatization level evaluation models at home and abroad, this study develops an evaluation model and several indicators that systematically reflect the characteristics of military organizations. The developed informatization level evaluation model is verified by conducting a feasibility test for the troops of the operation class or higher. We expect that this model will be able to objectively diagnose the level of informatization of the ROK military by putting budget and resources into the right place at the right time and to rapidly improve the vulnerability of the information sector.

• Journal of Applied Biological Chemistry
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• v.66
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• pp.402-407
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• 2023

The regulation of platelet aggregation is crucial for maintaining normal hemostasis, but abnormal or excessive platelet aggregation can contribute to cardiovascular disorders such as stroke, atherosclerosis, and thrombosis. Therefore, identifying substances that can control or suppress platelet aggregation is a promising approach for the prevention and treatment of these conditions. Artemisinin, a compound derived from Artemisia or Scopolia plants, has shown potential in various areas such as anticancer and Alzheimer's disease research. However, the specific role and mechanisms by which artemisinin influences platelet activation and thrombus formation are not yet fully understood. This study investigated the effects of artemisinin on platelet activation and thrombus formation. As a result, cAMP production were increased significantly by artemisinin, as well as phosphorylated VASP and IP₃R which are substrates to cAMP-dependent kinase by artemisinin in a significant manner. The Ca²⁺ normally mobilized from the dense tubular system was inhibited due to IP₃R phosphorylation from artemisinin, and phosphorylated VASP by artemisinin aided in inhibiting platelet activity via αIIb/β3 platelet membrane inactivation and inhibiting fibrinogen binding. Finally, artemisinin inhibited thrombin-induced thrombus formation. Therefore, we suggest that artemisinin has importance with cardiovascular diseases stemming from the abnormal platelets activation and thrombus formation by acting as an effective prophylactic and therapeutic agent.

• Journal of the Korean Society for information Management
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• v.41 no.1
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• pp.509-536
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• 2024

The purpose of this study is to develop a metadata AP for managing the person and organization name authority data in the National Debt Redemption Movement Digital Archive, a small-scale digital archive. The design principles and core metadata elements were derived by analyzing person/organization(group or corporateBody) metadata standards, implementation practices, and guidelines of libraries and archives, and mapped to the National Debt Redemption Movement person/organization name thesaurus data and the Wikidata Linked Metadata Model, resulting in 10 elements in the identification area, 14 elements in the content area, 8 elements in the relationship area, and 4 elements in the control area. A simple structure schema was applied so that it can be applied even in small organizations, and for interoperability, the schema was proposed with reference to DublinCore and SKOS schemes, and the applicability was confirmed based on actual data. The results of this study can be utilized as a basis for institutions that recognize the importance of data management but have difficulty in applying it in practice, when they want to prepare a system for managing their own authority data.

• 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.