• Title/Summary/Keyword: Image Mark

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Determination of Stress Intensity Factor $K_I$ from Two Fringe Orders by Fringe Multiplication and Sharpening

  • Chen, Lei;Baek, Tae-Hyun
    • Journal of the Korean Society for Nondestructive Testing
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    • v.27 no.6
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    • pp.550-555
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    • 2007
  • Stress intensity factor is one of the most important parameters in fracture mechanics. Both the stress field distribution and the crack propagation are closely related to these parameters. Due to the complexity of actual engineering problems, it is difficult to calculate the stress intensity factor by theoretical formulation, so photoelasticity method is a good choice. In this paper, modified two parameter method is employed to calculate stress intensity factor for opening mode by using data from more than one photoelastic fringe loop. For getting accurate experiment results, the initial fringes are doubled and sharpened by digital image programs from the fringe patterns obtained by a CCD camera. Photoelastic results are compared with those obtained by the use of empirical equation and FEM. Good agreement shows that the methods utilized in experiments are considerably reliable. The photoelastic experiment can be used for bench mark in theoretical study and other experiments.

A Performance Enhancement of Osteoporosis Classification in CT images (CT 영상에서 골다공증 판별 방법의 성능 향상)

  • Jung, Sung-Tae
    • Journal of Korea Multimedia Society
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    • v.19 no.8
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    • pp.1248-1259
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    • 2016
  • Classification methods based on dual energy X-ray absorptiometry, ultrasonic waves, and quantitative computed tomography have been proposed. Also, a classification method based on machine learning with bone mineral density and structural indicators extracted from the CT images has been proposed. We propose a method which enhances the performance of existing classification method based on bone mineral density and structural indicators by extending structural indicators and using principal component analysis. Experimental result shows that the proposed method in this paper improves the correctness of osteoporosis classification 2.8% with extended structural indicators only and 4.8% with both extended structural indicators and principal component analysis. In addition, this paper proposes a method of automatic phantom analysis needed to convert the CT values to BMD values. While existing method requires manual operation to mark the bone region within the phantom, the proposed method detects the bone region automatically by detecting circles in the CT image. The proposed method and the existing method gave the same conversion formula for converting CT value to bone mineral density.

Effect of Skinpassing Conditions on the Surface Characteristics of Hot-dip Galvanized Steel Sheets (용융아연도금강판의 표면특성에 미치는 조질압연 조업조건의 영향)

  • 전선호
    • Journal of the Korean institute of surface engineering
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    • v.34 no.4
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    • pp.327-336
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    • 2001
  • The skinpassing conditions such as roll type, roll force and roll roughness of the work roll were evaluated to give the surface properties of the galvanized steel sheets that were required for automotive and to get rid of the surface defects that caused with the bad control of galvanized coating process parameters. The surface defects of the galvanized steel sheets such as the ripple mark and the scratch were completely removed as the roll force of SPM work roll was increased and the amount of the transfer of roll surface texture to the strip was also gained a lot. The image clarity of electro discharge textured (EDT) coated steel sheets before and after painting was higher than that of the bright (BRT) and shot blasted (SBT) coated steel sheets because of higher PPI value, lower waviness and uniform surface pattern. Since micro-craters transferred on the surface of the galvanized steel sheets played a role of nucleation sites of chromate reaction, Increase of micro-craters was bring to better corrosion resistance with the increase of the roll force and the use of EDT roll at the skin pass mill.

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Weld Quality Evaluation Method for the Resistance Spot Welds using X-ray Transmission Inspection (X-선 투과검사를 이용한 저항 점용접부 품질평가기법)

  • Lee, Jong-Dae;Lee, So-Jeong;Bang, Jung-Hwan;Yoon, Gil-Sang;Kim, Mok-Soon;Kim, Jun-Ki
    • Journal of Welding and Joining
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    • v.32 no.6
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    • pp.1-7
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    • 2014
  • For the resistance spot welds of CR1180 and GA1180 TRIP steels, the weld quality evaluation method using the digitalized X-ray transmission imaging apparatus was investigated in comparison with the crosssectional examination method. In the case of the resistance spot welding of CR1180, three circular regions, such as WZ(white zone), GZ(grey zone) and DZ(dark zone), appeared on X-ray image and they corresponded to the diameters of indentation mark, nugget and corona bond, respectively. The variation of X-ray transmission thickness due to the thickness variation of the weld seemed to be mainly responsible for the formation of those contrasts. The X-ray image contrast formed from the variation of transmission thickness at the outer border line of DZ could also enable the inspections of the notch shape, nonuniformity of the welding pressure and spatter from its sharpness, concentricity and the normal straight line, respectively. The X-ray image of the resistance spot weld of galvannealed GA1180 TRIP steel was very similar to that of CR1180 TRIP steel except the crown shaped outer border line of DZ which was considered to be due to the melting behavior of zinc having the boiling temperature even lower than the melting temperature of steel.

Color Image Segmentation Based on Edge Salience Map and Region Merging (경계 중요도 맵 및 영역 병합에 기반한 칼라 영상 분할)

  • Kim, Sung-Young
    • Journal of the Korea Society of Computer and Information
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    • v.12 no.3
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    • pp.105-113
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    • 2007
  • In this paper, an image segmentation method which is based on edge salience map and region merging is presented. The edge salience map is calculated by combining a texture edge map with a color edge map. The texture edge map is computed over multiple spatial orientations and frequencies by using Gabor filter. A color edge is computed over the H component of the HSI color model. Then the Watershed transformation technique is applied to the edge salience map to and homogeneous regions where the dissimilarity of color and texture distribution is relatively low. The Watershed transformation tends to over-segment images. To merge the over-segmented regions, first of all, morphological operation is applied to the edge salience map to enhance a contrast of it and also to find mark regions. Then the region characteristics, a Gabor texture vector and a mean color, in the segmented regions is defined and regions that have the similar characteristics, are merged. Experimental results have demonstrated the superiority in segmentation results for various images.

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Fracture Energy and Displacement Field Characteristics of Particulate Reinforced Composites Using DIC Method (DIC법에 의한 입자강화 복합재료의 파괴에너지 및 변위장 특성)

  • Lee, Jeongwon;Na, Seonghyeon;Lee, Sangyoun;Park, Jaebeom;Jung, Gyoodong;Kim, Jaehoon
    • Journal of the Korean Society of Propulsion Engineers
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    • v.21 no.6
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    • pp.15-20
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    • 2017
  • In this study, the fracture energy and displacement fields characteristics of particulate reinforced composite is evaluated. Wedge splitting test was performed at various temperatures. Fracture energy of material is calculated at room temperature, $-40^{\circ}C$ and $-60^{\circ}C$. Displacement and strain fields of specimen surface were visualized by using digital image correlation. The surface displacement fields of the specimens were analyzed by mark tracking method using digital image correlation. The results showed that, the fracture energy was decreased as temperature decreased. The surface displacement fields at room temperature were similar to there at $-40^{\circ}C$. The surface displacement fields at $-60^{\circ}C$ was significantly reduced because of the brittle behavior. The strain fields of the specimen surface decreased as temperature decreased form room temperature to $-60^{\circ}C$.

A Review on Advanced Methodologies to Identify the Breast Cancer Classification using the Deep Learning Techniques

  • Bandaru, Satish Babu;Babu, G. Rama Mohan
    • International Journal of Computer Science & Network Security
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    • v.22 no.4
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    • pp.420-426
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    • 2022
  • Breast cancer is among the cancers that may be healed as the disease diagnosed at early times before it is distributed through all the areas of the body. The Automatic Analysis of Diagnostic Tests (AAT) is an automated assistance for physicians that can deliver reliable findings to analyze the critically endangered diseases. Deep learning, a family of machine learning methods, has grown at an astonishing pace in recent years. It is used to search and render diagnoses in fields from banking to medicine to machine learning. We attempt to create a deep learning algorithm that can reliably diagnose the breast cancer in the mammogram. We want the algorithm to identify it as cancer, or this image is not cancer, allowing use of a full testing dataset of either strong clinical annotations in training data or the cancer status only, in which a few images of either cancers or noncancer were annotated. Even with this technique, the photographs would be annotated with the condition; an optional portion of the annotated image will then act as the mark. The final stage of the suggested system doesn't need any based labels to be accessible during model training. Furthermore, the results of the review process suggest that deep learning approaches have surpassed the extent of the level of state-of-of-the-the-the-art in tumor identification, feature extraction, and classification. in these three ways, the paper explains why learning algorithms were applied: train the network from scratch, transplanting certain deep learning concepts and constraints into a network, and (another way) reducing the amount of parameters in the trained nets, are two functions that help expand the scope of the networks. Researchers in economically developing countries have applied deep learning imaging devices to cancer detection; on the other hand, cancer chances have gone through the roof in Africa. Convolutional Neural Network (CNN) is a sort of deep learning that can aid you with a variety of other activities, such as speech recognition, image recognition, and classification. To accomplish this goal in this article, we will use CNN to categorize and identify breast cancer photographs from the available databases from the US Centers for Disease Control and Prevention.

Comparison of Characteristics of Gamma-Ray Imager Based on Coded Aperture by Varying the Thickness of the BGO Scintillator

  • Seoryeong Park;Mark D. Hammig;Manhee Jeong
    • Journal of Radiation Protection and Research
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    • v.47 no.4
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    • pp.214-225
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    • 2022
  • Background: The conventional cerium-doped Gd2Al2Ga3O12 (GAGG(Ce)) scintillator-based gamma-ray imager has a bulky detector, which can lead to incorrect positioning of the gammaray source if the shielding against background radiation is not appropriately designed. In addition, portability is important in complex environments such as inside nuclear power plants, yet existing gamma-ray imager based on a tungsten mask tends to be weighty and therefore difficult to handle. Motivated by the need to develop a system that is not sensitive to background radiation and is portable, we changed the material of the scintillator and the coded aperture. Materials and Methods: The existing GAGG(Ce) was replaced with Bi4Ge3O12 (BGO), a scintillator with high gamma-ray detection efficiency but low energy resolution, and replaced the tungsten (W) used in the existing coded aperture with lead (Pb). Each BGO scintillator is pixelated with 144 elements (12 × 12), and each pixel has an area of 4 mm × 4 mm and the scintillator thickness ranges from 5 to 20 mm (5, 10, and 20 mm). A coded aperture consisting of Pb with a thickness of 20 mm was applied to the BGO scintillators of all thicknesses. Results and Discussion: Spectroscopic characterization, imaging performance, and image quality evaluation revealed the 10 mm-thick BGO scintillators enabled the portable gamma-ray imager to deliver optimal performance. Although its performance is slightly inferior to that of existing GAGG(Ce)-based gamma-ray imager, the results confirmed that the manufacturing cost and the system's overall weight can be reduced. Conclusion: Despite the spectral characteristics, imaging system performance, and image quality is slightly lower than that of GAGG(Ce), the results show that BGO scintillators are preferable for gamma-ray imaging systems in terms of cost and ease of deployment, and the proposed design is well worth applying to systems intended for use in areas that do not require high precision.

Calibration of ShadowCam

  • David Carl Humm;Mallory Janet Kinczyk;Scott Michael Brylow;Robert Vernon Wagner;Emerson Jacob Speyerer;Nicholas Michael Estes;Prasun Mahanti;Aaron Kyle Boyd;Mark Southwick Robinson
    • Journal of Astronomy and Space Sciences
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    • v.40 no.4
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    • pp.173-197
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    • 2023
  • ShadowCam is a high-sensitivity, high-resolution imager provided by NASA for the Danuri (KPLO) lunar mission. ShadowCam calibration shows that it is well suited for its purpose, to image permanently shadowed regions (PSRs) that occur near the lunar poles. It is 205 times as sensitive as the Lunar Reconnaissance Orbiter Camera (LROC) Narrow Angle Camera (NAC). The signal to noise ratio (SNR) is greater than 100 over a large part of the dynamic range, and the top of the dynamic range is high enough to accommodate most brighter PSR pixels. The optical performance is good enough to take full advantage of the 1.7 meter/pixel image scale, and calibrated images have uniform response. We describe some instrument artifacts that are amenable to future corrections, making it possible to improve performance further. Stray light control is very challenging for this mission. In many cases, ShadowCam can image shadowed areas with directly illuminated terrain in or near the field of view (FOV). We include thorough qualitative descriptions of circumstances under which lunar brightness levels far higher than the top of the dynamic range cause detector or stray light artifacts and the size and extent of the artifact signal under those circumstances.

Study on Relationship between Elderly Group Lifestyle and Selection Attributes in the Health Functional Foods (실버층 라이프스타일에 따른 건강기능식품 선택속성에 관한 연구)

  • Lee, Myung Sook;Kim, Sook Eung
    • Korean Journal of Clinical Pharmacy
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    • v.25 no.4
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    • pp.286-295
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    • 2015
  • Objective: This experiment is to study how elderly group and their various lifestyles interact with health functional foods, according to their selection behavior. Different lifestyles will be observed closely, as well as how different health conditions and consumer involvements will affect critical decision making in selecting health functional foods. Method: Theories and discoveries from original advanced research were compared parallel to the new study. Results: First, cluster analysis and exploratory analysis were performed amongst different elder lifestyles. Lifestyle exploratory analysis was used for healthy, unique, leisure, and economical-style elders. Cluster analysis was used for material trend oriented, health oriented, complacent oriented-style elders. Health Functional Foods' selection trait Exploratory Factor Analysis showed that product's originality (function, uniqueness, specialty, compatibility, distributor, expiration date), quality (amount, daily dose, visual representation, accessibility, portability, natural ingredients), and popularity (product container, brand image, taste and smell, advertised product, domestic or import, well-known function) were the three main causes. Secondly, the amount of benefits for the elderly group health lifestyle were affected by 'Interest in health', 'Notability of the health functional food', and 'Functionality approved mark'. Specifically, the importance of, 'Interest in health', 'Notability of health functional food', and 'Functionality approved mark' were noticeably high within health oriented elders. Lastly, after examining the data from elder lifestyle's relationship with health functional food selection trait, all three different results showed equal importance. If you closely examine material trend oriented elderly group, selection trait showed distinctively high regards in 'Fundamental Attribute', 'Typical Attribute', and 'Cognitive Attribute'. Health oriented elders showed their distinctively high regards in 'Natural Attribute', and less consideration in 'Typical Attribute' and 'Cognitive Attribute'. Complacent oriented-style elderly group showed less focus on 'Fundamental Attribute', and even less in 'Typical Attribute', and 'Cognitive Attribute'. Health oriented elderly group concluded with above data from the fact that they showed most importance and involvement in health beneficial products that are scientifically proven. Material trend oriented elderly group showed balanced traits in their concluded data, showing that they prefer function, safety, as well as the brand image and their reputation. Also, they consider the products' outer elements, such as design and product name, in order to sense inner functions. Conclusion: So, Silver Business corporations must develop products to fulfill the market demands, and strategize marketing plans to better target the correct audience.