• Journal of Electrical Engineering and Technology
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• v.7 no.2
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• pp.184-192
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• 2012

The torque and unbalanced magnetic forces in permanent magnet machines are resultants of the tangential, axial and normal magnetic forces, respectively. Those are in general influenced by pole-teeth-winding configuration. A study of the torque and unbalanced magnetic forces of a small flux concentrating permanent magnet transverse flux machine (FCPM-TFM) in segmented compact structure is presented in this paper. By using FLUX3D software from Cedrat, Maxwell stress tensor has been solved. Finite element (FE-) magneto static study followed by transient analysis has been conducted to investigate the influence of unsymmetrical winding pattern, in respect to the rotor, on the performance of the FCPM-TFM. Calculating the magnetic field components in the air gap has required an introduction of a 2D grid in the middle of the air gap, whereby good estimations of the forces are obtained. In this machine, the axial magnetic forces reveal relatively higher amplitudes compared to the normal forces. Practical results of a prototype motor are demonstrated through the analysis.

• Journal of Internet Computing and Services
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• v.11 no.1
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• pp.129-141
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• 2010

In this paper, we present a wearable intelligent device based on multi-sensor for monitoring human activity. In order to recognize multiple activities, we developed activity recognition algorithms utilizing an image sensor and a 3-axis accelerometer sensor. We proposed a grid?based optical flow method and used a SVM classifier to analyze data acquired from multi-sensor. We used the direction and the magnitude of motion vectors extracted from the image sensor. We computed the correlation between axes and the magnitude of the FFT with data extracted from the 3-axis accelerometer sensor. In the experimental results, we showed that the accuracy of activity recognition based on the only image sensor, the only 3-axis accelerometer sensor, and the proposed multi-sensor method was 55.57%, 89.97%, and 89.97% respectively.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.143-148
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• 2022

Brain tumor classification is an important process that allows doctors to plan treatment for patients based on the stages of the tumor. To improve classification performance, various CNN-based architectures are used for brain tumor classification. Existing methods for brain tumor segmentation suffer from overfitting and poor efficiency when dealing with large datasets. The enhanced CNN architecture proposed in this study is based on U-Net for brain tumor segmentation, RefineNet for pattern analysis, and SegNet architecture for brain tumor classification. The brain tumor benchmark dataset was used to evaluate the enhanced CNN model's efficiency. Based on the local and context information of the MRI image, the U-Net provides good segmentation. SegNet selects the most important features for classification while also reducing the trainable parameters. In the classification of brain tumors, the enhanced CNN method outperforms the existing methods. The enhanced CNN model has an accuracy of 96.85 percent, while the existing CNN with transfer learning has an accuracy of 94.82 percent.

• Journal of Korean Association for Spatial Structures
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• v.22 no.2
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• pp.29-37
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• 2022

The collapse of reinforced concrete (RC) frame buildings is mainly caused by the failure of columns. To prevent brittle failure of RC column, numerous studies have been conducted on the seismic performance of strengthened RC columns. Concrete jacketing method, which is one of the retrofitting method of RC members, can enhance strength and stiffness of original RC column with enlarged section and provide uniformly distributed lateral load capacity throughout the structure. The experimental studies have been conducted by many researchers to analyze seismic performance of seismic strengthened RC column. However, structures which have plan and vertical irregularities shows torsional behavior, and therefore it causes large deformation on RC column when subjected to seismic load. Thus, test results from concentric cyclic loading can be overestimated comparing to eccentric cyclic test results, In this paper, two kinds of eccentric loading pattern was suggested to analyze structural performance of RC columns, which are strengthened by concrete jacketing method with new details in jacketed section. Based on the results, it is concluded that specimens strengthened with new concrete jacketing method increased 830% of maximum load, 150% of maximum displacement and changed the failure modes of non-strengthened RC columns.

• Journal of the Korean Society of Clothing and Textiles
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• v.46 no.3
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• pp.481-493
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• 2022

This study investigated process conditions for 3D printing through manufacturing thermoplastic polyurethane (TPU) samples under different infill conditions. Samples were prepared using a fused deposition modeling 3D printer and TPU filament. 12 infill patterns were set (2D: grid, lines, zigzag; 3D: triangles, cubic, cubic subdivision, octet, quarter cubic; 3DF: concentric, cross 3D, cross, honeycomb), with 3 infill densities (20%, 50%, 80%). Morphology, actual time/weight and compressive properties were analyzed. In morphology: it was found that, as infill density increased, the increase rate of the number of units rose for 2D and fell for 3DF. Printing time varied with the number of nozzle movements. In the 3DF case, the number of nozzle movements increased rapidly with infill density. Sample weight increased similarly. However, where the increase rate of the number of units was low, sample weight was also low. In compressive properties: compressive stress increased with infill density and stress was high for the patterns with layers of the same shape.

• Convergence Security Journal
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• v.23 no.1
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• pp.55-61
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• 2023

QR Code is a two-dimensional code in the form of a matrix that contains data in a square-shaped black-and-white grid pattern, and has recently been used in various fields. In particular, in order to prevent the spread of COVID-19, the usage increased rapidly by identifying the movement path in the form of a QR code that anyone can easily and conveniently use. As such, Qshing attacks and damages using QR codes are increasing in proportion to the usage of QR codes. Therefore, in this paper, a system was implemented to block movement to harmful sites and installation of malicious codes when scanning QR codes.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.2
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• pp.236-242
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• 1986

The dependence of the current-voltage characteristics of hydrogenated amorphous silicon pin solar cells on the illumimination light intensity has been investigated. The open circuit voltage increases linearly with increasing the logarithm of light intensity up to AM 1, and nearly saturates above AM 1, indicating the open circuit voltage approaching the built-in potential of the pin solar cell above AM 1. The short circuit current density increase with light intensity in proportion to I**0.85 before and I**0.97 after light exposure. Since the series resistance devreses and shunt resistance increases with light intensily, the fill factor increases with light illumination. To increase the fill factor at high illumination in large area solar cells, t6he grid pattern on the ITO substrates should be made. Long light exposure on the solar cells gives rise to the increase of bulk resistance and defect states, resulting in the decrease of the fil factor and short circuit current density. The potential drop in the bulk of the a-Si:H pin solar cells at short circuit condition increases with decreasing temperature, and increases after long light exposure.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.41-41
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• 2021

최근 전 세계적으로 급증하는 기후변화의 영향으로 이상기후로 인한 자연재해들의 강도 및 발생 빈도의 증가가 다양한 연구를 통하여 확인되고 있으며, 이를 대비 및 대응하기 위한 방안수립 연구가 세계의 가장 중요한 주제로 부상되고 있다. 우리나라의 경우에는 기후변화에 따른 심각성 문제가 대두되고 있지만 국가적 대응기반조성 및 수자원정책 의사결정에 직접적으로 활용될 수 있는 일관성 있고 통합적인 기후 정보가 부족한 실정이다. 미래 기상 변동성을 나타내는 기후모델은 전 지구적 대규모 기상장(large scale climate pattern)을 비교적 정확하게 묘사하는 것으로 알려져 있으나 모형에 내재해 있는 시·공간적 편의(spatial-temporal bias) 및 불확실성으로 인하여 통계학적 상세화가 필수적으로 요구된다. 이러한 편향성은 일반적으로 지상 관측 자료를 격자에 보간하여 보정하는 방법이 적용되고 있지만, 관측자료의 불연속성 및 관측소의 불균등성으로 인하여 공간적 신뢰성이 낮다. 이에, 본 연구에서는 Bayesian 기반의 Kriging을 통한 공간적 편의보정 및 QDM(quantile delta mapping)을 연계한 새로운 격자 기반의 통계적 상세화 모형 Bayesian Kriging-QDM을 개발하였다. 본 연구를 통하여 산정된 결과는 과거자료에 근거하여 이루어지는 기존의 보수적인 수자원 관리 체계의 위험성을 저감 시킬 수 있는 의사결정에 직접적으로 활용될 수 있는 기초 자료로 이용 가능할 것으로 판단된다.

• Clean Technology
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• v.25 no.4
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• pp.324-330
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• 2019

The selective catalytic reduction system is a highly effective technique for the denitrification of the flue gases emitted from the industrial facilities. The distribution of mixing ratio between ammonia and nitrogen oxide at the inlet of the catalyst layers is important to the efficiency of the de-NOx process. In this study, computational analysis tools have been applied to improve the uniformity of NH₃/NO molar ratio by controlling the flow rate of the ammonia injection nozzles according to the distribution pattern of the nitrogen oxide in the inlet flue gas. The root mean square of NH₃/NO molar ratio was chosen as the optimization parameter while the design of experiment was used as the base of the optimization algorithm. As the inlet conditions, four (4) types of flow pattern were simulated; i.e. uniform, parabolic, upper-skewed, and random. The flow rate of the eight nozzles installed in the ammonia injection grid was adjusted to the inlet conditions. In order to solve the two-dimensional, steady, incompressible, and viscous flow fields, the commercial software ANSYS-FLUENT was used with the k-𝜖 turbulence model. The results showed that the improvement of the uniformity ranged between 9.58% and 80.0% according to the inlet flow pattern of the flue gas.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.1
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• pp.62-68
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• 2012

Steady-State Visually Evoked Potentials (SSVEP) are natural response signal associated with the visual stimuli with specific frequency. By using SSVEP, occipital lobe region is electrically activated as frequency form equivalent to stimuli frequency with bandwidth from 3.5Hz to 75Hz. In this paper, we propose an experimental paradigm for analyzing EEGs based on the properties of SSVEP. At first, an experiment is performed to extract frequency feature of EEGs that is measured from the image-based visual stimuli associated with specific objective with affordance and object-related affordance is measured by using mirror neuron system based on the frequency feature. And then, linear discriminant analysis (LDA) method is applied to perform the online classification of the objective pattern associated with the EEG-based affordance data. By using the SSVEP measurement experiment, we propose a Brain-Computer Interface (BCI) system for recognizing user's inherent intentions. The existing SSVEP application system, such as speller, is able to classify the EEG pattern based on grid image patterns and their variations. However, our proposed SSVEP-based BCI system performs object pattern classification based on the matters with a variety of shapes in input images and has higher generality than existing system.