• Title/Summary/Keyword: 디지털객체

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Edge Enhancement for Vessel Bottom Image Considering the Color Characteristics of Underwater Images (수중영상의 색상특성을 고려한 선박하부 영상의 윤곽선 강조 기법)

  • Choi, Hyun-Jun;Yang, Won-Jae;Kim, Bu-Ki
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.23 no.7
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    • pp.926-932
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    • 2017
  • Image distortion can occur when photographing deep sea targets with an optical camera. This problem arises because sunlight is not sufficiently transmitted due to seawater and various floating particles of dust. Particularly, color distortion takes place, causing green and blue color channels to be over emphasized due to water depth, while distortion of boundaries also occurs due to light refraction by seawater and floating particles of dust. These distortions degrade the overall quality of underwater images. In this paper, we analyze underwater images of the bottom of vessels. Based on the results, we propose a technique for color correction and edge enhancement. Experimental results show that the proposed method increases edge clarity by 3.39 % compared to the effective edges of the original underwater image. In addition, a quantitative evaluation and subjective image quality evaluation were concurrently performed. As a result, it was confirmed that object boundaries became clear with color correction. The color correction and contour enhancement method proposed in this paper can be applied in various fields requiring underwater imaging in the future.

Web viewer for sharing of prosthesis design between laboratory and clinic: Case report (웹뷰어를 이용한 기공실과 진료실 측 간의 보철물 설계 형태의 공유: 증례 보고)

  • Jang, Sung Won;Lee, Ho Jin;Kim, So-Yeun;Lee, Du-Hyeong
    • The Journal of Korean Academy of Prosthodontics
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    • v.60 no.3
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    • pp.276-282
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    • 2022
  • Close communication between clinicians and dental technicians is an important factor in providing successful prostheses. The exchange of opinions with laboratories has mainly been in the form of written prescriptions and a photos, but it has been reported that information transmission may be limited. Currently, as digital technology-based prosthesis fabrication is common, 3D image objects can be stored on the web and can be easily viewed through a mobile web browser. In this article, we introduce cases where the design of the prosthesis was improved by designing the prosthesis using CAD software and reviewing the prosthesis designed with the clinical side through a web viewer. Through this protocol, it was possible to improve the occlusal surface and crown contour, the opposing teeth condition, the size of the gingival embrasure, and the shape of pontic. The process of sharing, discussing, and modifying the prosthesis design with the clinician and technician through a web viewer contributes to reflecting the diversity of oral conditions and individualized needs, thereby helping to make functional and esthetic prostheses.

The Application Methods of FarmMap Reading in Agricultural Land Using Deep Learning (딥러닝을 이용한 농경지 팜맵 판독 적용 방안)

  • Wee Seong Seung;Jung Nam Su;Lee Won Suk;Shin Yong Tae
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.2
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    • pp.77-82
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    • 2023
  • The Ministry of Agriculture, Food and Rural Affairs established the FarmMap, an digital map of agricultural land. In this study, using deep learning, we suggest the application of farm map reading to farmland such as paddy fields, fields, ginseng, fruit trees, facilities, and uncultivated land. The farm map is used as spatial information for planting status and drone operation by digitizing agricultural land in the real world using aerial and satellite images. A reading manual has been prepared and updated every year by demarcating the boundaries of agricultural land and reading the attributes. Human reading of agricultural land differs depending on reading ability and experience, and reading errors are difficult to verify in reality because of budget limitations. The farmmap has location information and class information of the corresponding object in the image of 5 types of farmland properties, so the suitable AI technique was tested with ResNet50, an instance segmentation model. The results of attribute reading of agricultural land using deep learning and attribute reading by humans were compared. If technology is developed by focusing on attribute reading that shows different results in the future, it is expected that it will play a big role in reducing attribute errors and improving the accuracy of digital map of agricultural land.

Deep Learning Based Digital Staining Method in Fourier Ptychographic Microscopy Image (Fourier Ptychographic Microscopy 영상에서의 딥러닝 기반 디지털 염색 방법 연구)

  • Seok-Min Hwang;Dong-Bum Kim;Yu-Jeong Kim;Yeo-Rin Kim;Jong-Ha Lee
    • Journal of the Institute of Convergence Signal Processing
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    • v.23 no.2
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    • pp.97-106
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    • 2022
  • In this study, H&E staining is necessary to distinguish cells. However, dyeing directly requires a lot of money and time. The purpose is to convert the phase image of unstained cells to the amplitude image of stained cells. Image data taken with FPM was created with Phase image and Amplitude image using Matlab's parameters. Through normalization, a visually identifiable image was obtained. Through normalization, a visually distinguishable image was obtained. Using the GAN algorithm, a Fake Amplitude image similar to the Real Amplitude image was created based on the Phase image, and cells were distinguished by objectification using MASK R-CNN with the Fake Amplitude image As a result of the study, D loss max is 3.3e-1, min is 6.8e-2, G loss max is 6.9e-2, min is 2.9e-2, A loss max is 5.8e-1, min is 1.2e-1, Mask R-CNN max is 1.9e0, and min is 3.2e-1.

Detection of Steel Ribs in Tunnel GPR Images Based on YOLO Algorithm (YOLO 알고리즘을 활용한 터널 GPR 이미지 내 강지보재 탐지)

  • Bae, Byongkyu;Ahn, Jaehun;Jung, Hyunjun;Yoo, Chang Kyoon
    • Journal of the Korean Geotechnical Society
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    • v.39 no.7
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    • pp.31-37
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    • 2023
  • Since tunnels are built underground, it is impossible to check visually the location and degree of deterioration of steel ribs. Therefore, in tunnel maintenance, GPR images are generally used to detect steel ribs. While research on GPR image analysis employing artificial neural networks has primarily focused on detecting underground pipes and road damage, there have been limited applications for analyzing tunnel GPR data, specifically for steel rib detection, both internationally and domestically. In this study, a one-step object detection algorithm called YOLO, based on a convolutional neural network, was utilized to automate the localization of steel ribs using GPR data. The performance of the algorithm is then analyzed. Two datasets were employed for the analysis. A dataset comprising 512 original images and another dataset consisting of 2,048 augmented images. The omission rate, which represents the ratio of undetected steel ribs to the total number of steel ribs, was 0.38% for the model using the augmented data, whereas the omission rate for the model using only the original data was 7.18%. Thus, from an automation standpoint, it is more practical to employ an augmented dataset.

A study on the policy of de-identifying unstructured data for the medical data industry (의료 데이터 산업을 위한 비정형 데이터 비식별화 정책에 관한 연구)

  • Sun-Jin Lee;Tae-Rim Park;So-Hui Kim;Young-Eun Oh;Il-Gu Lee
    • Convergence Security Journal
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    • v.22 no.4
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    • pp.85-97
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    • 2022
  • With the development of big data technology, data is rapidly entering a hyperconnected intelligent society that accelerates innovative growth in all industries. The convergence industry, which holds and utilizes various high-quality data, is becoming a new growth engine, and big data is fused to various traditional industries. In particular, in the medical field, structured data such as electronic medical record data and unstructured medical data such as CT and MRI are used together to increase the accuracy of disease prediction and diagnosis. Currently, the importance and size of unstructured data are increasing day by day in the medical industry, but conventional data security technologies and policies are structured data-oriented, and considerations for the security and utilization of unstructured data are insufficient. In order for medical treatment using big data to be activated in the future, data diversity and security must be internalized and organically linked at the stage of data construction, distribution, and utilization. In this paper, the current status of domestic and foreign data security systems and technologies is analyzed. After that, it is proposed to add unstructured data-centered de-identification technology to the guidelines for unstructured data and technology application cases in the industry so that unstructured data can be actively used in the medical field, and to establish standards for judging personal information for unstructured data. Furthermore, an object feature-based identification ID that can be used for unstructured data without infringing on personal information is proposed.

DEVS-Based Simulation Model Development for Composite Warfare Analysis of Naval Warship (함정의 복합전 효과도 분석을 위한 DEVS 기반 시뮬레이션 모델 개발)

  • Mi Jang;Hee-Mun Park;Kyung-Min Seo
    • Journal of the Korea Society for Simulation
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    • v.32 no.4
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    • pp.41-58
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    • 2023
  • As naval warfare changes to composite warfare that includes simultaneous engagements against surface, underwater, and air enemies, performance and tactical analysis are required to respond to naval warfare. In particular, for practical analysis of composite warfare, it is necessary to study engagement simulations that can appropriately utilize the limited performance resources of the detection system. This paper proposes a DEVS (Discrete Event Systems Specifications)-based simulation model for composite warfare analysis. The proposed model contains generalized models of combat platforms and armed objects to simulate various complex warfare situations. In addition, we propose a detection performance allocation algorithm that can be applied to a detection system model, considering the characteristics of composite warfare in which missions must be performed using limited detection resources. We experimented with the effectiveness of composite warfare according to the strength of the detection system's resource allocation, the enemy force's size, and the friendly force's departure location. The simulation results showed the effect of the resource allocation function on engagement time and success. Our model will be used as an engineering basis for analyzing the tactics of warships in various complex warfare situations in the future.

A Study to Improve the Trustworthiness of Data Repositories by Obtaining CoreTrustSeal Certification (CoreTrustSeal 인증 획득을 통한 데이터 리포지토리의 신뢰성 향상을 위한 연구)

  • Hea Lim Rhee;Jung-Ho Um;Youngho Shin;Hyung-jun Yim;Na-eun Han
    • Journal of the Korean Society for information Management
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    • v.41 no.2
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    • pp.245-268
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    • 2024
  • As the recognition of data's value increases, the role of data repositories in managing, preserving, and utilizing data is becoming increasingly important. This study investigates ways to enhance the trustworthiness of data repositories through obtaining CoreTrustSeal (CTS) certification. Trust in data repositories is critical not only for data protection but also for building and maintaining trust between the repository and stakeholders, which in turn affects researchers' decisions on depositing and utilizing data. The study examines the CoreTrustSeal, an international certification for trustworthy data repositories, analyzing its impact on the trustworthiness and efficiency of repositories. Using the example of DataON, Korea's first CTS-certified repository operated by the Korea Institute of Science and Technology Information (KISTI), the study compares and analyzes four repositories that have obtained CTS certification. These include DataON, the Physical Oceanography Distributed Active Archive Center (PO.DAAC) from NASA, Yareta from the University of Geneva, and the DARIAH-DE repository from Germany. The research assesses how these repositories meet the mandatory requirements set by CTS and proposes strategies for improving the trustworthiness of data repositories. Key findings indicate that obtaining CTS certification involves rigorous evaluation of organizational infrastructure, digital object management, and technological aspects. The study highlights the importance of transparent data processes, robust data quality assurance, enhanced accessibility and usability, sustainability, security measures, and compliance with legal and ethical standards. By implementing these strategies, data repositories can enhance their reliability and efficiency, ultimately promoting wider data sharing and utilization in the scientific community.

Development Process and Methods of Audit and Certification Toolkit for Trustworthy Digital Records Management Agency (신뢰성 있는 전자기록관리기관 감사인증도구 개발에 관한 연구)

  • Rieh, Hae-young;Kim, Ik-han;Yim, Jin-Hee;Shim, Sungbo;Jo, YoonSun;Kim, Hyojin;Woo, Hyunmin
    • The Korean Journal of Archival Studies
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    • no.25
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    • pp.3-46
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    • 2010
  • Digital records management is one whole system in which many social and technical elements are interacting. To maintain the trustworthiness, the repository needs periodical audit and certification. Thus, individual electronic records management agency needs toolkit that can be used to self-evaluate their trustworthiness continuously, and self-assess their atmosphere and system to recognize deficiencies. The purpose of this study is development of self-certification toolkit for repositories, which synthesized and analysed such four international standard and best practices as OAIS Reference Model(ISO 14721), TRAC, DRAMBORA, and the assessment report conducted and published by TNA/UKDA, as well as MoRe2 and current national laws and standards. As this paper describes and demonstrate the development process and the framework of this self-certification toolkit, other electronic records management agencies could follow the process and develop their own toolkit reflecting their situation, and utilize the self-assessment results in-house. As a result of this research, 12 areas for assessment were set, which include (organizational) operation management, classification system and master data management, acquisition, registration and description, storage and preservation, disposal, services, providing finding aids, system management, access control and security, monitoring/audit trail/statistics, and risk management. In each 12 area, the process map or functional charts were drawn and business functions were analyzed, and 54 'evaluation criteria', consisted of main business functional unit in each area were drawn. Under each 'evaluation criteria', 208 'specific evaluation criteria', which supposed to be implementable, measurable, and provable for self-evaluation in each area, were drawn. The audit and certification toolkit developed by this research could be used by digital repositories to conduct periodical self-assessment of the organization, which would be used to supplement any found deficiencies and be used to reflect the organizational development strategy.

A study on Multiple Entity Data Model Design for Visual-Arts Archives and Information Management in the case of the KS X ISO 23081 Multiple Entity Model (시각예술기록정보 관리를 위한 데이터모델 설계 KS X ISO 23081 다중 엔티티 모델의 적용을 중심으로)

  • Hwang, Jin-hyun;Yim, Jin-hee
    • The Korean Journal of Archival Studies
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    • no.33
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    • pp.155-206
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    • 2012
  • Interests in archives management are getting expanded from the public sector into the cultural and artistic field for the ten years after legislation of "Act on the Management of Public Archives" in 1999. However, due to lack of recognition on the importance of archives in the cultural and artistic field, it is rather frequent that information is kept scattered or archives are lost. As an example, absence of precise contract documents or notes of bestowal keeps people from locating great amount of cultural properties, and because of it these creative properties are in the risk of thefts, the closed-door auctioning, or trades in unofficial channels. As how a nation manages cultural and artistic creation inside the nation reflects its cultural level, it can be said that one of the indexes to notice the extent of a nation's cultural level is to take a look at how they are circulated. This study started from this point. Growing economy and rising interests in culture and art made the society more cognizant of the importance and value that visual artworks have, but the archives and information which are showing the context of these artworks and are produced in the course of social interaction are relatively disregarded because too much emphasis lies on the work itself. It is harder to find archives or documentations in Korea than in other advanced countries about the artists themselves or philosophical discourse on the background of the artworks. There is not so much interest to preserve the archives and information produced after the exhibition also, and they are used for no more than promotion or reference. Hereupon, the researcher recognized the importance of visual arts archives and believed that systemic management on them are high in need. And metadata is an essential way for the systemic management, as recently management on artworks or their archives are conducted using the system of the agencies even though they are not produced electronically. The objective of this study is to manage visual arts archives systematically by designing a data model reflecting traits of visual arts archives. Metadata are needed in the every course of archives from acquisition to management, preservation and application. Visual arts archives find its rich value only when a systemic relationship is established among information on artist, artwork and events including exhibition. By establishing a Multiple Entity Data Model, in which artworks, artists and events (exhibitions) make relationship all together, metadata for management on visual arts archive gets more efficiency and at the same time explanatory trait of the archive gets higher. For this reason we, in the study, tried to design a data model by setting each as an independent entities and designating relations between them, in order to find a way to manage visual arts archives more systematically.