• Title/Summary/Keyword: Phase map

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Comparison of In-Plane Measurement of Phase-Shifting with Time-Average Method (위상이동법과 시간평균법의 면내변위 측정 비교)

  • Kim, Kyoung-Suk;Kim, Dong-Iel;Jung, Hyun-Chul;Kang, Ki-Soo;Lee, Chan-Woo;Yang, Seung-Pil;Jarng, Soon-Suck
    • Journal of the Korean Society for Precision Engineering
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    • v.16 no.10
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    • pp.53-58
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    • 1999
  • Even I the Electronic Speckle Pattern Interferometry(ESPI) method that measure the strain of object within wavelength of light is less visibility than Holographic Interferometry(HI) method, the merits of application, convenience and time-save have made the method practical in industry. However, the existing ESPI methods that are based on dual-exposure, real-time and time-average method have difficulties for accurate measurement, due to irregular intensity and shake of phase. Recently, in order to solve this problem, phase shifting method have been proposed. In this method, the path of reference light in interference is shifted to make improvement in distinction and precision. But this method includes too many noise, caused by the problem of relationship between object and phase. Therefore, a method to reduce noise muse be introduced. In this paper, least square fitting method is proposed. As results, the phase-map is influenced by precise phase shifting and current of notes and speckle pattern obtained by phase shifting method is improved on the existing method driven from time-average method.

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Recent Technologies for the Acquisition and Processing of 3D Images Based on Deep Learning (딥러닝기반 입체 영상의 획득 및 처리 기술 동향)

  • Yoon, M.S.
    • Electronics and Telecommunications Trends
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    • v.35 no.5
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    • pp.112-122
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    • 2020
  • In 3D computer graphics, a depth map is an image that provides information related to the distance from the viewpoint to the subject's surface. Stereo sensors, depth cameras, and imaging systems using an active illumination system and a time-resolved detector can perform accurate depth measurements with their own light sources. The 3D image information obtained through the depth map is useful in 3D modeling, autonomous vehicle navigation, object recognition and remote gesture detection, resolution-enhanced medical images, aviation and defense technology, and robotics. In addition, the depth map information is important data used for extracting and restoring multi-view images, and extracting phase information required for digital hologram synthesis. This study is oriented toward a recent research trend in deep learning-based 3D data analysis methods and depth map information extraction technology using a convolutional neural network. Further, the study focuses on 3D image processing technology related to digital hologram and multi-view image extraction/reconstruction, which are becoming more popular as the computing power of hardware rapidly increases.

Noise Elimination of Speckle Fringe Phasemap (반점 간섭무늬 위상단면도의 잡음제거)

  • 조재완;홍석경;백성훈;김철중
    • Korean Journal of Optics and Photonics
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    • v.5 no.2
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    • pp.217-224
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    • 1994
  • The combination of both phase-shifting convolution and 2-bit quantization smoothing filter was used to reduce speckle noise from saw-tooth speckle fringes phase map, obtained in phase-shifting speckle interferometer. The phase-shifting convolution showed the noise reduction capability of speckle fringe without destroying edge information across 271 jump. Also, it was shown that the 2-bit quantization smoothing filter was superior to average, low-pass filter and median filter in speeding up smoothing process and enhancing SIN ratio. Finally, a path dependent unwrapping algorithm was used to unwrap a noise reduced 271 modulo speckle phasemap. semap.

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Value Structure Model of the Success Factor of ITO Transition (ITO 이행단계 성공요인에 대한 가치체계모형 연구)

  • Cha, Hwan-Ju;Kim, Ja-Hee
    • Journal of the Korean Operations Research and Management Science Society
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    • v.41 no.1
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    • pp.21-39
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    • 2016
  • Although the demand for IT outsourcing (ITO) has increased recently because of the recent recession, concerns about business discontinuity in the transition phase cause companies to hesitate to adopt ITO. Therefore, a guideline to improve the prospects is needed. However, studies on the success factors of the transition phase in ITO are lacking. In this study, we develop an expert hierarchical value map (HVM) of the success of the transition phase in ITO by using cognition scientific methodologies. We empirically verify how success factors affect the success of the transition phase. Specifically, we derive an HVM of main stakeholders by using in-depth interviews and approaches, such as repertory grid technique (RGT) and laddering, based on means-end chain theory. We validate the success factors empirically through a bipolar analysis of RGT. Finally, we determine the most important cluster of success factors through cluster analysis.

Detecting cell cycle-regulated genes using Self-Organizing Maps with statistical Phase Synchronization (SOMPS) algorithm

  • Kim, Chang Sik;Tcha, Hong Joon;Bae, Cheol-Soo;Kim, Moon-Hwan
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.1 no.2
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    • pp.39-50
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    • 2008
  • Developing computational methods for identifying cell cycle-regulated genes has been one of important topics in systems biology. Most of previous methods consider the periodic characteristics of expression signals to identify the cell cycle-regulated genes. However, we assume that cell cycle-regulated genes are relatively active having relatively many interactions with each other based on the underlying cellular network. Thus, we are motivated to apply the theory of multivariate phase synchronization to the cell cycle expression analysis. In this study, we apply the method known as "Self-Organizing Maps with statistical Phase Synchronization (SOMPS)", which is the combination of self-organizing map and multivariate phase synchronization, producing several subsets of genes that are expected to have interactions with each other in their subset (Kim, 2008). Our evaluation experiments show that the SOMPS algorithm is able to detect cell cycle-regulated genes as much as one of recently reported method that performs better than most existing methods.

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Flow regime transition criteria for vertical downward two-phase flow in rectangular channel

  • Chalgeri, Vikrant Siddharudh;Jeong, Ji Hwan
    • Nuclear Engineering and Technology
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    • v.54 no.2
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    • pp.546-553
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    • 2022
  • Narrow rectangular channels are employed in nuclear research reactors that use plate-type nuclear fuels, high heat-flux compact heat exchangers, and high-performance micro-electronics cooling systems. Two-phase flow in narrow rectangular channels is important, and it needs to be better understood because it is considerably different than that in round tubes. In this study, mechanistic models were developed for the flow regime transition criteria for various flow regimes in co-current air-water two-phase flow for vertical downward flow inside a narrow rectangular channel. The newly developed criteria were compared to a flow regime map of downward air-water two-phase flow inside a narrow rectangular channel with a 2.35-mm gap width under ambient temperature and pressure conditions. Overall, the proposed model showed good agreement with the experimental data.

Design and Implementation of a Large-Scale Spatial Reasoner Using MapReduce Framework (맵리듀스 프레임워크를 이용한 대용량 공간 추론기의 설계 및 구현)

  • Nam, Sang Ha;Kim, In Cheol
    • KIPS Transactions on Software and Data Engineering
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    • v.3 no.10
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    • pp.397-406
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    • 2014
  • In order to answer the questions successfully on behalf of the human in DeepQA environments such as Jeopardy! of the American quiz show, the computer is required to have the capability of fast temporal and spatial reasoning on a large-scale commonsense knowledge base. In this paper, we present a scalable spatial reasoning algorithm for deriving efficiently new directional and topological relations using the MapReduce framework, one of well-known parallel distributed computing environments. The proposed reasoning algorithm assumes as input a large-scale spatial knowledge base including CSD-9 directional relations and RCC-8 topological relations. To infer new directional and topological relations from the given spatial knowledge base, it performs the cross-consistency checks as well as the path-consistency checks on the knowledge base. To maximize the parallelism of reasoning computations according to the principle of the MapReduce framework, we design the algorithm to partition effectively the large knowledge base into smaller ones and distribute them over multiple computing nodes at the map phase. And then, at the reduce phase, the algorithm infers the new knowledge from distributed spatial knowledge bases. Through experiments performed on the sample knowledge base with the MapReduce-based implementation of our algorithm, we proved the high performance of our large-scale spatial reasoner.

A MapReduce-Based Workflow BIG-Log Clustering Technique (맵리듀스기반 워크플로우 빅-로그 클러스터링 기법)

  • Jin, Min-Hyuck;Kim, Kwanghoon Pio
    • Journal of Internet Computing and Services
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    • v.20 no.1
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    • pp.87-96
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    • 2019
  • In this paper, we propose a MapReduce-supported clustering technique for collecting and classifying distributed workflow enactment event logs as a preprocessing tool. Especially, we would call the distributed workflow enactment event logs as Workflow BIG-Logs, because they are satisfied with as well as well-fitted to the 5V properties of BIG-Data like Volume, Velocity, Variety, Veracity and Value. The clustering technique we develop in this paper is intentionally devised for the preprocessing phase of a specific workflow process mining and analysis algorithm based upon the workflow BIG-Logs. In other words, It uses the Map-Reduce framework as a Workflow BIG-Logs processing platform, it supports the IEEE XES standard data format, and it is eventually dedicated for the preprocessing phase of the ${\rho}$-Algorithm that is a typical workflow process mining algorithm based on the structured information control nets. More precisely, The Workflow BIG-Logs can be classified into two types: of activity-based clustering patterns and performer-based clustering patterns, and we try to implement an activity-based clustering pattern algorithm based upon the Map-Reduce framework. Finally, we try to verify the proposed clustering technique by carrying out an experimental study on the workflow enactment event log dataset released by the BPI Challenges.

Effect of stress relief heat treatment on the residual stress and hardness of additively manufactured Ti-6Al-4V alloy (응력제거 열처리 공정조건이 적층제조한 Ti-6Al-4V 합금의 잔류응력 및 경도에 미치는 영향)

  • Yeonghwan Song
    • Journal of the Korean Crystal Growth and Crystal Technology
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    • v.33 no.6
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    • pp.282-287
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    • 2023
  • The effect of stress relief heat treatment temperature and duration time on the microstructure, residual stress and Vickers hardness of additively manufactured Ti-6Al-4V alloy using laser powder bed fusion process was clarified. As a result of stress relief heat treatment for 240 minutes at 823 K and 60 minutes or more at 873 K, residual stress was decreased less than 30 MPa without grain growth and phase transformation which causes dimensional distortion and deterioration of mechanical properties. In addition, hardness was increased with increasing heat treatment temperature and duration time. It was deduced that the refinement of acicular martensitic α' phase due to the increasing duration time of isothermal heat treatment at 773~873 K, which was not detected by XRD and phase map analysis using SEM-EBSD, probably increases the hardness.