• Journal of the Korean Magnetics Society
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• v.15 no.6
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• pp.325-331
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• 2005

The magnetic Hut leakage (MFL) type nondestructive testing (NDT) method is widely used to detect corrosion and defects, mechanical deformation of the underground gas pipelines. The object pipeline is magnetically saturated by the magnetic system with permanent magnet and yokes. Because of the strong magnetic field enough to saturate the pipe, there could be distortion of the sensing signals because of the magnetization of the pipeline itself, To detect the defects precisely, the sensing signals are need to be compensated to eliminate the distortions coming from the media hysteresis. In this paper, the magnetizations of the pipeline in MFL type NDT are analyzed by Preisach model and 3D FEM. The distortions of the sensing signals are analyzed.

• Korean Journal of Materials Research
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• v.8 no.8
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• pp.744-750
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• 1998

Unlike common device, MEMS(micro-electro-mechanical system) device consists of very small mechanical structures which determine the performance of the device. Because of its small mechanical structure inside. MEMS device is very sensitive to thermal stress caused by CTE(coefficient of thermal expansion) mismatch between its components. Therefore, its characteristics are affected by material properties. process temperature. and dimensions of each layer such as chip, adhesive and substrate. In this study. we investigated the change of the thermal stress in the chip attached to a substrate. With computer-aided finite element method (FEM), the computer simulation of the thermal stress was conducted on variables such as bonding material, process temperature, bonding layer thickness and die size. The commercial simulation program, ABAQUS ver5.6, was used. Subsequently 3-layer test samples were fabricated, and their degree of bending were measured by 3-D coordinate measuring machine. The experimental results were in good agreement with the simulation results. This study shows that the bonding layer could be the source of stress or act as the buffer layer for stress according to its elastic modulus and CTE. Solder adhesive layer was the source of stress due to its high elastic modulus, therefore high compressive stress was developed in the chip. And the maximum tensile stress was developed in the adhesive layer. On the other hand, polymer adhesive layer with low elastic modulus acted as buffer layer, and resulted in lower compressive stress. The maximum tensile stress was developed in the substrate.

• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.57-65
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• 2021

We propose a novel method to detect abnormal data of specific symptoms using deep learning in air pollution measurement system. Existing methods generally detect abnomal data by classifying data showing unusual patterns different from the existing time series data. However, these approaches have limitations in detecting specific symptoms. In this paper, we use DeepLab V3+ model mainly used for foreground segmentation of images, whose structure has been changed to handle one-dimensional data. Instead of images, the model receives time-series data from multiple sensors and can detect data showing specific symptoms. In addition, we improve model's performance by reducing the complexity of noisy form time series data by using 'piecewise aggregation approximation'. Through the experimental results, it can be confirmed that anomaly data detection can be performed successfully.

• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.411-417
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• 2021

The field that studies human-computer interaction is called HCI (Human-computer interaction). This field is an academic field that studies how humans and computers communicate with each other and recognize information. This study is a study on hand gesture recognition for human interaction. This study examines the problems of existing recognition methods and proposes an algorithm to improve the recognition rate. The hand region is extracted based on skin color information for the image containing the shape of the human hand, and the center of gravity profile is calculated using principal component analysis. I proposed a method to increase the recognition rate of hand gestures by comparing the obtained information with predefined shapes. We proposed a method to increase the recognition rate of hand gestures by comparing the obtained information with predefined shapes. The existing center of gravity profile has shown the result of incorrect hand gesture recognition for the deformation of the hand due to rotation, but in this study, the center of gravity profile is used and the point where the distance between the points of all contours and the center of gravity is the longest is the starting point. Thus, a robust algorithm was proposed by re-improving the center of gravity profile. No gloves or special markers attached to the sensor are used for hand gesture recognition, and a separate blue screen is not installed. For this result, find the feature vector at the nearest distance to solve the misrecognition, and obtain an appropriate threshold to distinguish between success and failure.

• Applied Chemistry for Engineering
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• v.30 no.4
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• pp.429-434
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• 2019

A lateral flow immunoassay platform utilizing antibody functionalized water soluble CdSe/ZnS semiconductor quantum dots (QDs) was developed for the analysis of human serum amyloid A-1 (hSAA1) in a buffer solution. hSAA1 was chosen as a target protein because it is regarded as a potential biomarker associated with early diagnosis and prognosis in patients of lung cancer. The immunoassay strip on a nitrocellulose membrane was fabricated by spraying two lines composed of a test line with a monoclonal antibody against hSAA1 (10G1) (anti hSAA1) and a control line of anti-chicken IgY. While the CdSe/ZnS QDs synthesized in an organic phase were transferred to a water phase by ligand exchange using carboxylic acid modified alkane thiol. The QDs was then conjugated to monoclonal antibody against hSAA1 (14F8) [anti hSAA1 (14F8)] and used as a fluorescent detection probe. The sequential lateral flow of hSAA1 in different concentration and QDs-anti hSAA1 (14F8) complex allowed to form the surface sandwich complex of anti hSAA1 (10G1)/hSAA1/QD-anti hSAA1 (14F8), which was then analyzed using fluorescence microscope. A 100 nM concentration of hSAA1 protein can be detected by naked eyes under an optimized lateral flow buffer condition with a sensing time of 5 mins.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.583-590
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• 2021

This paper is a study on the digitization of an analog 3D pen. The term digital implies features such as homeostasis, transformability, combinability, reproducibility, and convenience of storage. One device that produces a combination of these digital characteristics is a 3D printer, but its industrial use is limited due to low productivity and limitations with materials and physical characteristics. In particular, improvements are required to use 3D printers, such as better user accessibility owing to expertise and skills in modeling software and printers. Complementing this fact is the 3D pen, which is excellent in portability and ease of use, but has a limitation in that it cannot be digitized. Therefore, in order to secure a digitalization capability and ease of use, and to secure the safety of printing materials that pose controversial hazards during the printing process, research problems and alternatives have been derived by combining food, and digitization was demonstrated with a newly developed 3D pen. In order to digitize the 3D pen, a sensor in a structured device detects the motion of an analog 3D pen, and this motion is converted into 3D data (X-Y-Z coordinate values) through a spatial analysis algorithm. To prove this method, the similarity was confirmed by visualization using MeshLab version 1.3.4. It is expected that this food pen can be used in youth education and senior healthcare programs in the future.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.17 no.1
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• pp.21-32
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• 2007

Vuillaume-Okeya presented unsigned receding methods for protecting modular exponentiations against side channel attacks, which are suitable for tamper-resistant implementations of RSA or DSA which does not benefit from cheap inversions. The proposed method was using a signed representation with digits set ${1,2,{\cdots},2^{\omega}-1}$, where 0 is absent. This receding method was designed to be computed only from the right-to-left, i.e., it is necessary to finish the receding and to store the receded string before starting the left-to-right evaluation stage. This paper describes new receding methods for producing SPA-resistant unsigned representations which are scanned from left to right contrary to the previous ones. Our contributions are as follows; (1) SPA-resistant unsigned left-to-right receding with general width-${\omega}$, (2) special case when ${\omega}=1$, i.e., unsigned binary representation using the digit set {1,2}, (3) SPA-resistant unsigned left-to-right Comb receding, (4) extension to unsigned radix-${\gamma}$ left-to-right receding secure against SPA. Hence, these left-to-right methods are suitable for implementing on memory limited devices such as smartcards and sensor nodes

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.7
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• pp.1082-1087
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• 2021

The propeller shaft has different pattern of behaviors at each static, dynamic, and transient condition to a ship shaft system due to the effects of propeller weight and eccentric thrust, which increases the potential risk of bearing failure by causing local load variations. To prevent this, the various research of the shafting system has been conducted with the emphasis on optimizing the relative slope and oil film retention between propeller shaft and stern tube bearing at quasi-static condition, mainly with respect to the Rules for the Classification of Steel Ships. However, to guarantee a stability of the shafting system, it is necessary to consider the dynamic condition including the transient state due to the sudden change in the stern wakefield during rudder turn. In this context, this study cross-validated the ef ect of propeller shaft behavior on the stern tube bearing during port turn operation, which is a typical transient condition, by using the strain gauge method and displacement sensor for 50,000 DWT medium class tanker. And it was confirmed that the propeller eccentric thrust change showing relief the load of the stern tube bearing.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.2
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• pp.93-104
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• 2023

Currently, the permanent road traffic volume surveys under Road Act are conducted using a intrusive Automatic Vehicle Classification (AVC) equipments to classify 12 categories of vehicles. However, intrusive AVC equipment inevitably have friction with vehicles, and physical damage to sensors due to cracks in roads, plastic deformation, and road construction decreases the operation rate. As a result, accuracy and reliability in actual operation are deteriorated, and maintenance costs are also increasing. With the recent development of ITS technology, research to replace the intrusive AVC equipment is being conducted. However multiple equipments or self-built DB operations were required to classify 12 categories of vehicles. Therefore, this study attempted to prepare a method for classifying 12 categories of vehicles using vehicle specification information of the Vehicle Management Information System(VMIS), which is collected and managed in accordance with Motor Vehicle Management Act. In the future, it is expected to be used to upgrade and diversify road traffic statistics using vehicle specifications such as the introduction of a road traffic survey system using Automatic Number Plate Recognition(ANPR) and classification of eco-friendly vehicles.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6A
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• pp.799-808
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• 2008

The analysis of vehicular loads reflecting the domestic traffic circumstances is necessary for the development of adequate design live load models in the analysis and design of cable-supported bridges or the development of fatigue load models to predict the remaining lifespan of the bridges. This study intends to develop an ANN(artificial neural network)-based Bridge WIM system and Influence line-based Bridge WIM system for obtaining information concerning the loads conditions of vehicles crossing bridge structures by exploiting the signals measured by strain gauges installed at the bottom surface of the bridge superstructure. This study relies on experimental data corresponding to the travelling of hundreds of random vehicles rather than on theoretical data generated through numerical simulations to secure data sets for the training and test of the ANN. In addition, data acquired from 3 types of vehicles weighed statically at measurement station and then crossing the bridge repeatedly are also exploited to examine the accuracy of the trained ANN. The results obtained through the proposed ANN-based analysis method, the influence line analysis method considering the local behavior of the bridge are compared for an example cable-stayed bridge. In view of the results related to the cable-stayed bridge, the cross beam ANN analysis method appears to provide more remarkable load analysis results than the cross beam influence line method.