• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.8 s.111
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• pp.760-766
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• 2006

In this paper, we present a wideband patch antenna with folded and shorted structure for 5 GHz WLAN(Wireless Local Area Network). The proposed antenna used folded and shorted structure in the rectangular patch for miniaturization and wide frequency bandwidth. The antenna was designed by using 3D simulation program, HFSS(High Frequency Structure Simulator) software of the Ansoft company and the implemented antenna was measured by using HP 8720c network analyzer and far field measurement chamber. Simulation result on the return loss shows fairly good characteristic of at least 13.41dB in whole frequency range of interests, and the 10dB bandwidth is 1,523MHz which shows wide bandwidth characteristic. And the simulated maximum gain of the proposed antenna is 6.57 dBi at 5.825GHz. Measured result for the 10dB bandwidth of the implemented folded and shorted structure antenna is 1,377 MHz. Measured maximum gain of the implemented antenna is 6.87dBi at 5.775GHz. Measured results for the implemented antenna showed applicable performances for the 5 GHz WLAN.

• Convergence Security Journal
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• v.21 no.2
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• pp.47-56
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• 2021

Network topology visualization has been studied a lot since the past and developed with many tools. The network topology has strength in understanding the overall structure of a network physically and is useful for understanding data flow between nodes logically. Although there are existing tools, not many can be utilized efficiently while using the general network node data structure and express the topology similar to the actual network structure. In this paper, we propose an efficient method to visualize topology using only connection information of network nodes. The method finds the central node by using the centrality, the influence of nodes in the network, and visualizes the topology by dynamically segmenting all nodes and placing network nodes in 3D space using the weight of the child node. It is a straightforward method, yet it effectively visualizes in the form of an actual network structure.

• Journal of Korea Multimedia Society
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• v.22 no.12
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• pp.1457-1465
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• 2019

3D convolution is to stack multiple consecutive frames to form a cube, and then apply the 3D convolution kernel in the cube. In this structure, each feature map of the convolutional layer is connected to multiple adjacent sequential frames in the previous layer, thus capturing the motion information. However, due to the changes of pedestrian posture, motion and position, the convolution at the same place is inappropriate, and when the 3D convolution kernel is convoluted in the time domain, only time domain features of three consecutive frames can be extracted, which is not a good enough to get action information. This paper proposes an action recognition method based on feature fusion of 3D convolutional neural network. Based on the VGG16 network model, sending a pre-acquired optical flow image for learning, then get the time domain features, and then the feature of the time domain is extracted from the features extracted by the 3D convolutional neural network. Finally, the behavior classification is done by the SVM classifier.

• Design & Manufacturing
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• v.16 no.3
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• pp.1-8
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• 2022

In this study, an artificial neural network(ANN) was constructed to establish the relationship between process condition prameters and the qualities of the injection-molded product in the injection molding process. Six process parmeters were set as input parameter for ANN: melt temperature, mold temperature, injection speed, packing pressure, packing time, and cooling time. As output parameters, the mass, nominal diameter, and height of the injection-molded product were set. Two learning structures were applied to the ANN. The single-task learning, in which all output parameters are learned in correlation with each other, and the multi-task learning structure in which each output parameters is individually learned according to the characteristics, were constructed. As a result of constructing an artificial neural network with two learning structures and evaluating the prediction performance, it was confirmed that the predicted value of the ANN to which the multi-task learning structure was applied had a low RMSE compared with the single-task learning structure. In addition, when comparing the quality specifications of injection molded products with the prediction values of the ANN, it was confirmed that the ANN of the multi-task learning structure satisfies the quality specifications for all of the mass, diameter, and height.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.7 s.337
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• pp.41-48
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• 2005

We design and fabricate 3-dB tandem directional coupler using the coplanar waveguide structure which is applicable to balanced amplifiers and mixers for 60 GHz wireless local area network system. The coupler comprises the multiple-sectional parallel-coupled lines to facilitate the fabrication process, and enable smaller device size and higher directivity than those of the conventional 3-dB coupler employing the edge-coupled line. In this study, we adopt the structure of two-sectional parallel-coupled lines of which each single-coupled line has a coupling coefficient of -8.34 dB and airbridge structure to monolithically materialize the uniplanar coupler structure instead of using the conventional multilayer or bonded structure. The airbridge structure also supports to minimize the parasitic components and maintain desirable device performance in V-band (50$\~$75 GHz). The measured results from the fabricated couplers show couplings of 3.S$\~$4 dB and phase differences of 87.5$^{\circ}{\pm}1^{\circ}$ in V-band range and show directivities higher than 30 dB at a frequency of 60 GHz.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.893-898
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• 2014

Recently, the interior permanent synchronous motor (IPMSM) has been applied to an integrated starter and generator (ISG) for hybrid electric vehicles. In the design of such a motor, thermal analysis is necessary to maximize the power density because the loss is proportional to the power of a motor. Therefore, a cooling device as a heat sink is required internally. Generally, a cooling system designed with a water jacket structure is widely used for electric motors because it has advantages of simple structure and cooling effectiveness. An effective approach to analyze an electric machine with a water jacket is a thermal equivalent network. This network is composed of thermal resistance, a heat source, and thermal capacitance that consider the conduction, convection, and radiation. In particular, modeling of the cooling channel in a network is challenging owing to the flow of the coolant. In this paper, temperature prediction using a thermal equivalent network is performed in an ISG that has a water cooled system. Then, an experiment is conducted to verify the thermal equivalent network.

• ETRI Journal
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• v.46 no.4
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• pp.571-580
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• 2024

A compact triple-band porous electromagnetic bandgap structure-loaded coplanar-waveguide-fed wearable antenna is introduced for applications of wireless body area networks. The porous structure is aimed to create a stopband or bandgap in the electromagnetic spectrum and increase breathability. The holes in the bottom electromagnetic bandgap surface increase the inductance, which in turn increases the bandwidth. The final design resonates at three bands with impedance bandwidths of 264 MHz, 100 MHz, and 153 MHz and maximum gains of 2.18 dBi, 6.75 dBi, and 9.50 dBi at 2.45 GHz, 3.5 GHz, and 5.5 GHz, respectively. In addition, measurements indicate that the proposed design can be deformed up to certain curvature and withstand human tissue loading. Moreover, the specific absorption rate remains within safe levels for humans. Therefore, the proposed antenna can suitably operate in the industrial, scientific, and medical, Bluetooth, Wi-Fi, and WiMAX bands for potential application to wireless body area networks.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.2
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• pp.239-245
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• 2020

Recently, BIM (Building Information Modeling) are widely being utilized in Construction industry. However, most structures that have been constructed in the past do not have BIM. For structures without BIM, the use of SfM (Structure from Motion) techniques in the 2D image obtained from the camera allows the generation of 3D model point cloud data and BIM to be established. However, since these generated point cloud data do not contain semantic information, it is necessary to manually classify what elements of the structure. Therefore, in this study, deep learning was applied to automate the process of classifying structural components. In the establishment of deep learning network, Inception-ResNet-v2 of CNN (Convolutional Neural Network) structure was used, and the components of bridge structure were learned through transfer learning. As a result of classifying components using the data collected to verify the developed system, the components of the bridge were classified with an accuracy of 96.13 %.

• ETRI Journal
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• v.36 no.4
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• pp.643-653
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• 2014

To reduce interconnect delay and power consumption while improving chip performance, a three-dimensional integrated circuit (3D IC) has been developed with die-stacking and through-silicon via (TSV) techniques. The power supply problem is one of the essential challenges in 3D IC design because IR-drop caused by insufficient supply voltage in a 3D chip reduces the chip performance. In particular, power bumps and TSVs are placed to minimize IR-drop in a 3D power delivery network. In this paper, we propose a design methodology for 3D power delivery networks to minimize the number of power bumps and TSVs with optimum mesh structure and distribute voltage variation more uniformly by shifting the locations of power bumps and TSVs while satisfying IR-drop constraint. Simulation results show that our method can reduce the voltage variation by 29.7% on average while reducing the number of power bumps and TSVs by 76.2% and 15.4%, respectively.

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.32-35
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• 1996

This paper analyzes characteristics of PMLSM using 3 dimensional equivalent magnetic circuit network method (3-D EMC). PMLSM of which the effective electric-airgap is not only very large, but also the width is finite width lateral edges has much leakage flux. Therefore, 2-D analysis method cannot consider it so carefully that 3-D analysis method must required. 3-D EMC which will be used for analysis of PMLSM performs modeling of it including solt and teeth structure, uses the magnetic motive force of stator winding and permanent magnet as source. and calculates magnetic flux density and force considering nonlinear characteristics of materials. we verified analysis validity by comparing simulation results with expermental results.