• Journal of the Korean Society of Safety
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• v.20 no.1 s.69
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• pp.62-67
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• 2005

An eccentrically-loaded single edge crack tension specimen (ESET) is similar to a compact tension(CT) specimen loaded in tension-tension. The standard ESET specimen exhibits advantages over other types of cracked specimen, such as n, single-edge crack, and middle-crack tension specimen. The details of ESET specimen configuration, test procedure, and calculations are described in ASTM E647 standard. However, a difficulty in attaching COD gage to the knife-edge on the front foe of the specimen can be found when the size of ESET specimen is small for rapid cooling and heating in thermal fatigue testing. The finite element analysis is performed for the ESET specimen with projected knife-edge on the front foe and a crack-length-compliance equation is suggested for the new specimen configuration. Calibration test are conducted with 347 stainless steel to compare the measured crack length with the calculated crack length from the suggested compliance expression. The test results showed good agreements with those of analysis.

• Structural Engineering and Mechanics
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• v.54 no.3
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• pp.433-451
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• 2015

This paper focuses on large deflection static behavior of edge cracked simple supported beams subjected to a non-follower transversal point load at the midpoint of the beam by using the total Lagrangian Timoshenko beam element approximation. The cross section of the beam is circular. The cracked beam is modeled as an assembly of two sub-beams connected through a massless elastic rotational spring. It is known that large deflection problems are geometrically nonlinear problems. The considered highly nonlinear problem is solved considering full geometric non-linearity by using incremental displacement-based finite element method in conjunction with Newton-Raphson iteration method. There is no restriction on the magnitudes of deflections and rotations in contradistinction to von-Karman strain displacement relations of the beam. The beams considered in numerical examples are made of Aluminum. In the study, the effects of the location of crack and the depth of the crack on the non-linear static response of the beam are investigated in detail. The relationships between deflections, end rotational angles, end constraint forces, deflection configuration, Cauchy stresses of the edge-cracked beams and load rising are illustrated in detail in nonlinear case. Also, the difference between the geometrically linear and nonlinear analysis of edge-cracked beam is investigated in detail.

• Advances in aircraft and spacecraft science
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• v.2 no.3
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• pp.303-328
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• 2015

A design methodology is presented to develop the hingeless control surfaces for MAV using adhesively bonded Macro Fiber Composite (MFC) actuators. These actuators have got the capability to deflect the trailing edge surfaces of the wing to attain the required maneuverability, besides achieving the set aerodynamic trim condition. A scheme involving design, analysis, fabrication and testing procedure has been adopted to realize the trailing edge morphing mechanism. The stiffness distribution of the composite MAV wing is tailored such that the induced deflection by piezoelectric actuation is approximately optimized. Through ground testing, the proposed concept has been demonstrated on a typical MAV structure. Electromechanical analysis is performed to evaluate the actuator performance and subsequently aeroelastic and 2D CFD analyses are carried out to see the functional requirements of wing trailing edge surfaces to behave as elevons. Efforts have been made to obtain the performance comparison of conventional control surfaces (elevons) with morphing wing trailing edge surfaces. A significant improvement in lift to drag ratio is noticed with morphed wing configuration in comparison to conventional wing. Further, it has been shown that the morphed wing trailing edge surfaces can be deployed as elevons for aerodynamic trim applications.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.3
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• pp.1016-1021
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• 2013

While using the hydrogen mixture gas torch, the glass edge sealing and the shape of the edge sealing parts is affected by many parameters such as flow rate of gas, traveling speed of torch, distance between glass and torch. As the glass edge sealing shape have effects on the insulation and airtightness and strength of the glass panel; the sealing shapes are predicted according to the process parameters. The paper highlight the nonlinear regression equations of the cross-sectional shape of the sealing shape according to the parameters, that is experimentally predicted later compared and verified the equation with the experimental result.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.3
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• pp.89-100
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• 2023

Recently, on-device artificial intelligence (AI) solutions using mobile devices and embedded edge devices have emerged in various fields, such as computer vision, to address network traffic burdens, low-energy operations, and security problems. Although vision transformer deep learning models have outperformed conventional convolutional neural network (CNN) models in computer vision, they require more computations and parameters than CNN models. Thus, they are not directly applicable to embedded edge devices with limited hardware resources. Many researchers have proposed various model compression methods or lightweight architectures for vision transformers; however, there are only a few studies evaluating the effects of model compression techniques of vision transformers on performance. Regarding this problem, this paper presents a performance evaluation of vision transformers on embedded platforms. We investigated the behaviors of three vision transformers: DeiT, LeViT, and MobileViT. Each model performance was evaluated by accuracy and inference time on edge devices using the ImageNet dataset. We assessed the effects of the quantization method applied to the models on latency enhancement and accuracy degradation by profiling the proportion of response time occupied by major operations. In addition, we evaluated the performance of each model on GPU and EdgeTPU-based edge devices. In our experimental results, LeViT showed the best performance in CPU-based edge devices, and DeiT-small showed the highest performance improvement in GPU-based edge devices. In addition, only MobileViT models showed performance improvement on EdgeTPU. Summarizing the analysis results through profiling, the degree of performance improvement of each vision transformer model was highly dependent on the proportion of parts that could be optimized in the target edge device. In summary, to apply vision transformers to on-device AI solutions, either proper operation composition and optimizations specific to target edge devices must be considered.

• Science of Emotion and Sensibility
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• v.7 no.4
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• pp.57-65
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• 2004

In this paper, we present a hybrid approach which incorporates color, texture and shape in content-based image retrieval. Colors in each image are clustered into a small number of representative colors. The feature descriptor consists of the representative colors and their percentages in the image. A similarity measure similar to the cumulative color histogram distance measure is defined for this descriptor. The co-occurrence matrix as a statistical method is used for texture analysis. An optimal set of five statistical functions are extracted from the co-occurrence matrix of each image, in order to render the feature vector for eachimage maximally informative. The edge information captured within edge histograms is extracted after a pre-processing phase that performs color transformation, quantization, and filtering. The features where thus extracted and stored within feature vectors and were later compared with an intersection-based method. The content-based retrieval system is tested to be effective in terms of retrieval and scalability through experimental results and precision-recall analysis.

• Tribology and Lubricants
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• v.33 no.2
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• pp.65-70
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• 2017

In vertical hydro/hydraulic power turbine-generator applications, traditionally, cylindrical turbine guide bearings (TGBs) are widely used to provide turbine runner shafts with smooth rotation guides and supports. All existing cylindrical TGBs with simple plain pads have drawbacks such as having no pressure generation and film stiffness at the no-load condition and in addition, at the low-load/low-eccentricity condition, having very low film stiffness values and lacking design credibility in the stiffness values themselves. In this paper, in order to fundamentally improve the low-load/low-eccentricity performance of conventional cylindrical TGBs and thus enhance their design-application availability and usefulness, we propose to introduce a rotation-directional leading-edge taper to each partitioned pad, i.e., a pad leading-edge taper. We perform a design analysis of lubrication performance on $4-Pad{\times}4-Row$ cylindrical TGBs to verify an engineering/technical usefulness of the proposed pad leading-edge taper. Analysis results show that by introducing the leading-edge taper to each pad of the cylindrical TGB one can expect a constant high average direct stiffness with a high degree of design credibility, regardless of load value, even at the low-load/low-eccentricity condition and also control the average direct stiffness value by exploring the taper height as a design parameter. Therefore, we conclude that the proposed pad leading-edge tapers are greatly effective in more accurately predicting and controlling rotordynamic characteristics of vertical hydro-power turbine-generator rotor-bearing systems to which cylindrical TGBs are applied.

• Korean Journal of Construction Engineering and Management
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• v.25 no.2
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• pp.36-44
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• 2024

This paper presents the application of Convolutional Neural Networks (CNNs) and Region of Interest (ROI) techniques for concrete crack analysis. Surfaces of concrete structures, such as beams, etc., are exposed to fatigue stress and cyclic loads, typically resulting in the initiation of cracks at a microscopic level on the structure's surface. Early detection enables preventative measures to mitigate potential damage and failures. Conventional manual inspections often yield subpar results, especially for large-scale infrastructure where access is challenging and detecting cracks can be difficult. This paper presents data collection, edge segmentation and ROI techniques application, and analysis of concrete cracks using Convolutional Neural Networks. This paper aims to achieve the following objectives: Firstly, achieving improved accuracy in crack detection using image-based technology compared to traditional manual inspection methods. Secondly, developing an algorithm that utilizes enhanced Sobel edge segmentation and ROI techniques. The algorithm provides automated crack detection capabilities for non-destructive testing.

• Proceedings of the Korean Vacuum Society Conference
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• 2016.02a
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• pp.294.2-294.2
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• 2016

Graphene, a sigle atomic layered structure of graphite, has drawn many scientific interests for attractive future electronics and optoelectronics beyond silicon-based technology because of its robust physical, optical, and electrical properties. But high metal-graphene contact resistance prevents the successful integration of high speed graphene devices and circuits, although pristine graphene is known to have a novel carrier transport property. Meanwhile, in the recently reported metal-graphene contact studies, there are many attempts to reduce the metal-graphene contact resistance, such as doping and one-dimensional edge contact. However, there is a lack of quantitative analysis of the edge contact scheme through variously designed patterns with different metal contact. We first investigate the effets of edge contact (metal-graphene interface) on the contact resistance in terms of edge pattern design through patterning (photolithography + plasma etching) and electral measurements. Where the contact resistance is determined using the transfer length method (TLM). Finally, we research the role of metal-kind (Palladium, Copper, and Tianium) on the contact resistance through the edge-contacted devices, eventually minimizing contact resistance down to approximately $23{\Omega}{\cdot}{\mu}m$ at room temperature (approximately $19{\Omega}{\cdot}{\mu}m$ at 100 K).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.3
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• pp.553-563
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• 1996

Detecting edges is one of issues with essentialimprotance in the area of image analysis. An edge in an image is a boundary or contour at which a significant change occurs in image intensity. Edge detection has been studied in many addlications such as imagesegmentation, robot vision, and image compression. In this paper, we propose an automatic threshold selection scheme for edge detection and show its application to noise elimination. The scheme suggested here applied statistical properties of the noise estimated from a noisy image to threshold selection. Since a selected threshold value in the scheme depends on not the characgreistic of an orginal image but the statistical feature of added noise, we can remove ad-hoc manners used for selecting the threshold value as well as decide the value theoretically. Furthermore, that shceme can reduce the number of edge pixels either generated or lost by noise. an application of the scheme to noise elimination is shown here. Noise in the input image can be eliminated with considering the direction of each edge pixedl on the edge map obtained by applying the threshold selection scheme proposed in this paper. Achieving significantly improved results in terms of SNR as well as subjective quality, we can claim that the suggested method works well.