• Title/Summary/Keyword: 3D digital data

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Computer-aided design and manufacturing-based full mouth rehabilitation for a patient with excessive attrition and restricted vertical dimension: A case report (심한 치아 마모와 수복 공간 부족을 보이는 환자에서 CAD/CAM 기술을 활용한 완전 구강 회복: 증례 보고)

  • Cho, Jun-Ho;Yoon, Hyung-In;Yeo, In-Sung;Han, Jung-Suk
    • The Journal of Korean Academy of Prosthodontics
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    • v.57 no.4
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    • pp.495-505
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    • 2019
  • This study reported the treatment of a patient with excessive worn dentition and limited maxillo-mandibular space for restoration, utilizing the computer-aided design and computer-aided manufacturing (CAD/CAM) technology. After the thorough examination of the patient's occlusal vertical dimension (OVD), full mouth rehabilitation was planned with increase of the OVD. The patient was satisfied with the provisional restorations establishing the increased OVD. The horizontal and vertical data of the patient's jaw relation that the provisional restorations contained were transferred to the definitive metal ceramic fixed prostheses by double scanning and three-dimensional printing. After the fixed restorations were cemented to the abutments, electronic surveying and three-dimensional printing were used to fabricate metal frameworks for the patient's removable partial dentures. The mandibular definitive removable prostheses were delivered to the patient's mouth and the full mouth rehabilitation procedures were completed. The digital technologies used for this case produced fixed and removable restorations satisfactory in masticatory, phonetic and aesthetic functions to both the patient and the dental clinician.

Character Motion Control by Using Limited Sensors and Animation Data (제한된 모션 센서와 애니메이션 데이터를 이용한 캐릭터 동작 제어)

  • Bae, Tae Sung;Lee, Eun Ji;Kim, Ha Eun;Park, Minji;Choi, Myung Geol
    • Journal of the Korea Computer Graphics Society
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    • v.25 no.3
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    • pp.85-92
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    • 2019
  • A 3D virtual character playing a role in a digital story-telling has a unique style in its appearance and motion. Because the style reflects the unique personality of the character, it is very important to preserve the style and keep its consistency. However, when the character's motion is directly controlled by a user's motion who is wearing motion sensors, the unique style can be discarded. We present a novel character motion control method that uses only a small amount of animation data created only for the character to preserve the style of the character motion. Instead of machine learning approaches requiring a large amount of training data, we suggest a search-based method, which directly searches the most similar character pose from the animation data to the current user's pose. To show the usability of our method, we conducted our experiments with a character model and its animation data created by an expert designer for a virtual reality game. To prove that our method preserves well the original motion style of the character, we compared our result with the result obtained by using general human motion capture data. In addition, to show the scalability of our method, we presented experimental results with different numbers of motion sensors.

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.

A Comparative study on Dynamic & Static elastic modulus of cement mortar specimens (시멘트 모르타르 재료의 동탄성계수와 정탄성계수 비교 연구)

  • O, Seon-Hwan;Kim, Hyoung-Soo;Jang, Bo-An;Suh, Man-Cheol
    • Journal of the Korean Geophysical Society
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    • v.3 no.2
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    • pp.127-138
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    • 2000
  • This study was conducted to examine the differences between dynamic and static elastic constants by use of some laboratory tests of cement mortar specimens which have different water/cement mixing ratios. Specific gravity measurement, ultrasonic velocity estimating and uniaxial compression test were adopted to acquire the dynamic and static elastic constants. Digital data acquisition and processing enhanced the accuracy of estimating the velocities of specimens drastically, Also, the method using the gradient of propagation delay time in according to increment of specimen length more enhanced the accuracy than the method using the only one specimen length over total propagation time. The correlation between density and the P and S wave velocity of specimens shows reliable positive relation and the correlation between density and the strength of uniaxial compression has the similar relationship. The dynamic Young's modulus $(E_D)$ is alway greater than the static Young's modulus $(E_S)$ and there is increasing tendency of the ratio $(E_D/E_S)$ according to the increase of density or strength of the specimens. On the other hand, there is no typical relationship between dynamic Poisson's ratio $({\nu}_D)$ and static Poisson's ratio $({\nu}_S)$ and just the ratio of ${\nu}_D/{\nu}_S$ ranges front 69 to 122 %.

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Detection Ability of Occlusion Object in Deep Learning Algorithm depending on Image Qualities (영상품질별 학습기반 알고리즘 폐색영역 객체 검출 능력 분석)

  • LEE, Jeong-Min;HAM, Geon-Woo;BAE, Kyoung-Ho;PARK, Hong-Ki
    • Journal of the Korean Association of Geographic Information Studies
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    • v.22 no.3
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    • pp.82-98
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    • 2019
  • The importance of spatial information is rapidly rising. In particular, 3D spatial information construction and modeling for Real World Objects, such as smart cities and digital twins, has become an important core technology. The constructed 3D spatial information is used in various fields such as land management, landscape analysis, environment and welfare service. Three-dimensional modeling with image has the hig visibility and reality of objects by generating texturing. However, some texturing might have occlusion area inevitably generated due to physical deposits such as roadside trees, adjacent objects, vehicles, banners, etc. at the time of acquiring image Such occlusion area is a major cause of the deterioration of reality and accuracy of the constructed 3D modeling. Various studies have been conducted to solve the occlusion area. Recently the researches of deep learning algorithm have been conducted for detecting and resolving the occlusion area. For deep learning algorithm, sufficient training data is required, and the collected training data quality directly affects the performance and the result of the deep learning. Therefore, this study analyzed the ability of detecting the occlusion area of the image using various image quality to verify the performance and the result of deep learning according to the quality of the learning data. An image containing an object that causes occlusion is generated for each artificial and quantified image quality and applied to the implemented deep learning algorithm. The study found that the image quality for adjusting brightness was lower at 0.56 detection ratio for brighter images and that the image quality for pixel size and artificial noise control decreased rapidly from images adjusted from the main image to the middle level. In the F-measure performance evaluation method, the change in noise-controlled image resolution was the highest at 0.53 points. The ability to detect occlusion zones by image quality will be used as a valuable criterion for actual application of deep learning in the future. In the acquiring image, it is expected to contribute a lot to the practical application of deep learning by providing a certain level of image acquisition.

The Role of Digital Knowledge Richness in Green Technology Adoption: A Digital Option Theory Perspective (그린기술 채택에의 디지털 지식풍부성의 역할: 디지털 옵션 이론 관점에서)

  • Yoo, Hosun;Lee, Namyeon;Kwon, Ohbyung
    • The Journal of Information Systems
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    • v.24 no.2
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    • pp.23-52
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    • 2015
  • Purpose This study aims to understand the role of digital knowledge in accepting the green technology. This study combined digital option theory with the second version of the Unified Theory of Acceptance and Use of Technology (UTAUT2). Contrary to other studies in which the UTAUT2 is used to explain IT adoption behavior, we look at the relationship between IT and the UTAUT2 from a new angle, incorporating an important aspect of IT, that is, digitized knowledge richness, as a determinant of the UTAUT2. Design/methodology/approach Grounded in the UTAUT2, a content analysis was conducted to investigate novel constructs dedicated to explaining green technology adoption. In this study, an amended version of the UTAUT2 specific to green technology is offered that better explains the green technology adoption behavior of consumers. Using the items identified by content analysis, we developed a questionnaire with 36 survey items. We measured all the items on a seven-point Likert-type scale. We randomly selected 402 survey respondents from a set of panel data. After a pilot study, we analyzed the main survey data by using PLS 2.0M3 and SPSS 20.0, and employed structural equation modeling to test the hypotheses. Findings The results suggest that the UTAUT2 was found to be extendable to technologies other than conventional IT. Social influence is more significant than conventional utilitarian and hedonic-based constructs such as those utilized in the UTAUT and UTAUT2 in explaining adoption behavior in the context of green technologies. The hypothesized connection between digitized knowledge richness and adoption intention was supported by the results of studies on the role of IT in formation of attitudes toward eco-friendly production. The results also indicate that digital knowledge can also encourage people to try green technology when they learn that their peers are already using the technology successfully.

NONLINEAR CONTRAST ENHANCEMENT ON SUBTRACTION IMAGES (계수공정영상의 비선형 대조도 증강효과에 관한 연구)

  • Lee Keon-Il;Jin Yeun-Hwa
    • Journal of Korean Academy of Oral and Maxillofacial Radiology
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    • v.27 no.2
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    • pp.83-90
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    • 1997
  • This study was performed to demonstrate the effect of linear or nonlinear contrast enhancement on subtraction images. Three different textures were radiograped on dental film. The first radiograph was taken without the presence of an object. the second, which showed trabucular bone, was taken of the molar area of a human. the third radiograph was taken of the coronal part of molars. Each film was digitized into a 1312 x 1024 pixel x 8 bit depth matrix by means of a Nikon 35 mm film scanner(LS-3510AF, Japan) with fixed gain and internal dark current correction to maintain constant illumination. The scanner was interfaced to a Macintosh Le ill computer(Apple Computer, Charlotte, N.C) This resulted in three pairs of images, including different textures-plain, bone and enamel. Digital regular, linearly and nonlinearly enhanced subtraction was performed. Computer software was ,used to simulate lesions in the shape of a 2D-Gaussian curve on each of a pair of images. The each subtraction images were presented in a random sequence to two groups of 10 observers(students and dentists). ROC analysis was used to compare observer performance. The following results were obtained ; 1. All of LCE subtraction, equalized subtraction and regular subtraction images of plain texture were diagnosed the best by far. 2. The data revealed a siginificant LCE effect in both the student group and the expert group. 3. Clinical expertise was a helphul factor for the observers in this study.

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Mesoscale modeling of the temperature-dependent viscoelastic behavior of a Bitumen-Bound Gravels

  • Sow, Libasse;Bernard, Fabrice;Kamali-Bernard, Siham;Kebe, Cheikh Mouhamed Fadel
    • Coupled systems mechanics
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    • v.7 no.5
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    • pp.509-524
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    • 2018
  • A hierarchical multi-scale modeling strategy devoted to the study of a Bitumen-Bound Gravel (BBG) is presented in this paper. More precisely, the paper investigates the temperature-dependent linear viscoelastic of the material when submitted to low deformations levels and moderate number of cycles. In such a hierarchical approach, 3D digital Representative Elementary Volumes are built and the outcomes at a scale (here, the sub-mesoscale) are used as input data at the next higher scale (here, the mesoscale). The viscoelastic behavior of the bituminous phases at each scale is taken into account by means of a generalized Maxwell model: the bulk part of the behavior is separated from the deviatoric one and bulk and shear moduli are expanded into Prony series. Furthermore, the viscoelastic phases are considered to be thermorheologically simple: time and temperature are not independent. This behavior is reproduced by the Williams-Landel-Ferry law. By means of the FE simulations of stress relaxation tests, the parameters of the various features of this temperature-dependent viscoelastic behavior are identified.

A Study on the Decision and Selection of the Star Contents in the Convergence Era (융합시대의 스타콘텐츠 발굴 및 선정에 관한 연구)

  • Rim, Myung-Hwan;Park, Yong-Jae;Heo, Pil-Sun
    • Journal of Information Technology Applications and Management
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    • v.18 no.2
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    • pp.1-21
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    • 2011
  • In this era of convergence, which is characterized by the integration and combination of technology and industries, broadcasting and communications, offline and online, and devices and services, the content industry is also experiencing rapid changes including inter-genre exchange, the creation of new industries, and customized demand. Specifically, IT-based digital content industries such as the online game, e-book, mobile contents and web portal industries are no longer restricted to the boundaries of video, music and games but are being expanded into the realms of education, medicine, fashion and sports thanks to CT innovation of 3D, CG, AR/VR, VFX, etc. As such, various countries have come to recognize the convergent content industry as a new growth engine that will pick up where the IT industry left off, and are forming policies for its development accordingly. This research aims to optimize the system of content taxonomy which is currently genre-focused and unable to support technological development and convergence, and to discover and select star contents to be rigorously developed with governmental support. In this paper, 20 star contents in 8 areas were selected, and these are expected to create tremendous cultural and economic value through ongoing technological and industrial development.

A Study on the Automatic Assembly/Disassembly Procedure for Generating Maintenance Guideline (정비절차 생성을 위한 자동 분해/조립절차 연구)

  • Heo, Gilhwan;Lee, Won;Kwon, Kisang
    • Journal of the Korea Institute of Military Science and Technology
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    • v.18 no.5
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    • pp.594-601
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    • 2015
  • The purpose of this research is to propose a maintenance support system for deciding assembly sequence of the product and appropriate tools that are used to assembly and disassembly of parts in the product when geometric properties of the product. The digital maintenance system (DMS) is developed to generate the maintenance guideline and the initial experiment is conducted especially for an underwater weapon system with cylindrical structure. DMS considers four factors to find the efficient assembly and disassembly procedure automatically: (1) assembly tree, (2) properties of each part, (3) distance from the center of the product, and (4) volume. Based on the factors, DMS simulate the movement of each tool virtually and the properties of tools are investigated to find an appropriate tool for using assembly and disassembly of each part in the product. The proposed approach integrates modeling, simulation, data configuration, and virtual reality to allow a development of preliminary maintenance guidance.