• Journal of IKEEE
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• v.25 no.4
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• pp.591-597
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• 2021

This paper proposes an EMC-aware PCB design method to reduce electromagnetic emission, where trace length and teturn path of critical signal are shortened by changing chip location and trace layout on the PCB, while additional filters or decoupling capacitors are not required. In the proposed method, signal velocity is calculated for various signals on the PCB. Critical signal with the fastest signal velocity is determined and its return path is shortened as much as possible by placing chip location and trace routing first. Return path of critical signal should be carefully designed not to have discontinuity. Power plane and ground plane should be carefully designed not to be divided, since these planes are the reference of return path. The proposed method was applied to automotive directional Bluetooth speaker which failed to pass CISPR 32 and CISPR 25 EMC tests. Its PCB was redesigned based on the proposed method and it easily passed the EMC tests. The proposed method is useful to EMC-sensitive electronic equipments.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.1
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• pp.46-54
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• 2022

A magnetohydrodynamic (MHD) seawater propulsion thruster has been proposed to reduce propeller noise, propeller pitting, and vessel vibration originated from the propeller cavitation. The MHD thruster was also focused to overcome the limitation of propulsion velocity for the special purpose of marine ships. The research trends and key technologies in the worldwide leading countries are reviewed for the development of MHD propulsion thrusters in Korea. A small performance test device was developed firstly with a conventional solenoid magnet of ≤0.6 Tesla and a helical-type cylindrical duct(inner diameter of 5 cm) of thruster. The artificial seawater was fabricated by a salt solution including a conductivity of 5~6 S/m. The measured flow velocity of artificial seawater in the test device was 0.03~0.42 m/s (0.06~0.84 Knot) with a magnetic field strength of 0.6 Tesla and the applied currents of 10~80 A including the change of anode materials. It was found that the flow direction of seawater was reversed by the directional change of applied current in the solenoid magnet.

• The Journal of the Acoustical Society of Korea
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• v.41 no.2
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• pp.174-183
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• 2022

Acoustic radiation from a submerged elastic shell with an internal fluid surrounded by the bubble layer is studied with the modal theory. An omni-directional point source located on the center of the internal fluid is used as acoustic noise source. The unknown coefficients of modal solutions are solved using the interface conditions between media. To preserve the stability of the modal solution over wide frequency ranges, the scaled technique of modal solution is used. The bubble layer is modeled with four kinds of bubble distribution; uni-modal distribution, uniform distribution, normal distribution, and power-law distribution, based on the effective medium theory of Commander and Prosperetti. For each bubble distribution, the insertion losses are mainly calculated for the frequency. In addition, the numerical simulations are performed depending in the bubble void fraction, the material property of elastic shell, and the gap between the bubble layer and the elastic shell.

• Science of Emotion and Sensibility
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• v.25 no.1
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• pp.3-20
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• 2022

Recently, prior to the commercialization of urban air mobility (UAM), the importance of R&D for air transportation-related industries in urban areas has significantly increased. To create a UAM environment, research is being conducted on personal air vehicles (PAVs). They are key means of air transportation, but research on the physical factors influencing their passengers is relatively insufficient. In particular, because the PAV is expected to be used as a living space for the passengers, research on the effects of the physical elements generated in the PAV on the human body is essential to design an interior space that supports the in-vehicle activities of the passengers. Therefore, the purpose of this study is to derive the constraint factors that affect the human body due to the air navigation characteristics of the PAV and to understand the impact of these constraint factors on the bodies of the passengers performing in-vehicle activities. The results of this study indicate that when the PAV was operated at less than 4,000 ft, which is the operating standard, the constraint factors were noise, vibration, and motion sickness caused by low-frequency motion. These constraint factors affect in-vehicle activity; thus, the in-vehicle activities that can be performed in a PAV were derived using autonomous cars, airplanes, and PAV concept cases. Furthermore, considering the impact of the constraint factors and their levels on the human body, recommended constraint factor criteria to support in-vehicle activities were established. To reduce the level of impact of the constraint factors on the human body and to support in-vehicle activity, the seat's shape and built-in functions of the seat (vibration reduction function, temperature control, LED lighting, etc.) and external noise reduction using a directional speaker for each individual seat were recommended. Moreover, it was suggested that interior materials for noise and vibration reduction should be used in the design of the interior space. The contributions of this study are the determination of the constraint factors affecting the in-vehicle PAV activity and the confirmation of the level of impact of the factors on the human body; in the future, these findings can be used as basic data for suitable PAV interior design.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.10
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• pp.1050-1060
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• 2009

In this paper, a X-Band T/R-module for SAR(Synthetic Aperture Radar) systems based on active phased array antennas is designed and fabricated. The T/R modules have a and width of more than 800 MHz centered at X-Band and support dual, switched polarizations. The output power of the module is 7 watts over a wide bandwidth. The noise figure is as low as 3.9 dB. Phase and amplitude are controlled by a 6-bit phase shifter and a 6-bit digital attenuator, respectively. Further the fabricated T/R module has est and calibration port with directional coupler and power divider. Highly integrated T/R module is achieved by using LTCC(Low Temperature Co-fired Ceramic) multiple layer substrate. RMS gain error is less than 0.8 dB max. in Rx mode, and RMS phase error is less than $4^{\circ}$ max. in Rx/Tx phase under all operating frequency band, or the T/R module meet the required electrical performance m test. This structure an be applied to active phase array SAR Antennas.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.12
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• pp.2151-2156
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• 2006

Beamforming for underwater acoustic communication (UAC) is affected by the broadband feature of UAC signal, which has relatively low currier frequency as compared to the signal bandwidth. The narrow-band assumption does not hold good in UAC. In this paper, we discuss a broadband FIR beamformer for UAC using the baseband equivalent way signal model. We consider the broadband FIR beamformer for QPSK UAC with carrier frequency 25kHz and symbol rate 5kHz. Array geometry is a uniform linear way with 8 omni-directional elements and sensor spacing is the half of the carrier wavelength. The simulation results show that the broadband n beamformer achieves nearly optimum signal to interference and noise ratio (SINR) and outperforms the conventional narrowband beamformer by SINR 0.5dB when two-tap FIR filter is employed at each sensor and the inter-tap delay is a quarter of the symbol interval. The broadband FIR beamformer performance is more degraded as the FIR filter length is increased above a certain value. If the inter-tap delay is not greater than half of the symbol period, SINR performance does not depend on the inter-tap delay. More training period is required when the inter-tap delay is same as the symbol period.

• Journal of the Korean association of regional geographers
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• v.2 no.2
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• pp.183-196
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• 1996

The purpose of this paper is to explore the possibility of automatic extraction of line feature from Satellite image. The first part reviews the relationship between spatial filtering and cartographic interpretation. The second part describes the principal operations of high frequency filters and their properties, the third part presents the result of filtering application to the SPOT Panchromatic image of the Chinju city. Some experimental results are given here indicating the high feasibility of the filtering technique. The results of the paper is summarized as follows: Firstly the good all-purposes filter dose not exist. Certain laplacian filter and Frei-chen filter were very sensitive to the noise and could not detect line features in our case. Secondly, summary filters and some other filters do an excellent job of identifying edges around urban objects. With the filtered image added to the original image, the interpretation is more easy. Thirdly, Compass gradient masks may be used to perform two-dimensional, discrete differentiation directional edge enhancement, however, in our case, the line featuring was not satisfactory. In general, the wide masks detect the broad edges and narrow masks are used to detect the sharper discontinuities. But, in our case, the difference between the $3{\times}3$ and $7{\times}7$ kernel filters are not remarkable. It may be due to the good spatial resolution of Spot scene. The filtering effect depends on local circumstance. Band or kernel size selection must be also considered. For the skillful geographical interpretation, we need to take account the more subtle qualitative information.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.6
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• pp.70-77
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• 2008

This paper proposes a new text candidate region detection method that uses genetic algorithm based on information of the segmented regions. In image segmentation, a classification of the pixels at each color channel and a reclassification of the region-unit for reducing inhomogeneous clusters are performed. EWFCM(Entropy-based Weighted C-Means) algorithm to classify the pixels at each color channel is an improved FCM algorithm added with spatial information, and therefore it removes the meaningless regions like noise. A region-based reclassification based on a similarity between each segmented region of the most inhomogeneous cluster and the other clusters reduces the inhomogeneous clusters more efficiently than pixel- and cluster-based reclassifications. And detecting text candidate regions is performed by genetic algorithm based on energy and variance of the directional edge components, the number, and a size of the segmented regions. The region information-based detection method can singles out semantic text candidate regions more accurately than pixel-based detection method and the detection results will be more useful in recognizing the text regions hereafter. Experiments showed the results of the segmentation and the detection. And it confirmed that the proposed method was superior to the existing methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.9
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• pp.2109-2116
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• 2014

This paper presents the implementation and design of the advanced WI-FI systems with beam-forming antenna that radiate their power to the direction of user equipment to improve the overall throughput, contrast to the general WI-FI systems equipped with omni-antenna. The system consists of patch array antenna, DSP, FPGA, and Qualcomm's commercial chip. The beam-forming system on the FPGA utilizes the packet information from Qualcomm's commercial chip to control the phase shifters and attenuators of the patch array antenna. The PCI express interface has been used to maximize the communication speed between DSP and FPGA. The directions of arrival of users are managed using the database, and each user is distinguished by the MAC address given from the packet information. When the system wants to transmit a packet to one user, it forms beams to the direction of arrival of the corresponding user stored in the database to maximize the throughput. Directions of arrival of users are estimated using the received preamble in the packet to make its SINR as high as possible. The proposed beam-forming system was implemented using an FPGA and Qualcommm's commercial chip together. The implemented system showed considerable throughput improvement over the existing general AP system with omni-directional antenna in the multi-user communication environment.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.1-25
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• 2020

In this paper, we suggest an application system architecture which provides accurate, fast and efficient automatic gasometer reading function. The system captures gasometer image using mobile device camera, transmits the image to a cloud server on top of private LTE network, and analyzes the image to extract character information of device ID and gas usage amount by selective optical character recognition based on deep learning technology. In general, there are many types of character in an image and optical character recognition technology extracts all character information in an image. But some applications need to ignore non-of-interest types of character and only have to focus on some specific types of characters. For an example of the application, automatic gasometer reading system only need to extract device ID and gas usage amount character information from gasometer images to send bill to users. Non-of-interest character strings, such as device type, manufacturer, manufacturing date, specification and etc., are not valuable information to the application. Thus, the application have to analyze point of interest region and specific types of characters to extract valuable information only. We adopted CNN (Convolutional Neural Network) based object detection and CRNN (Convolutional Recurrent Neural Network) technology for selective optical character recognition which only analyze point of interest region for selective character information extraction. We build up 3 neural networks for the application system. The first is a convolutional neural network which detects point of interest region of gas usage amount and device ID information character strings, the second is another convolutional neural network which transforms spatial information of point of interest region to spatial sequential feature vectors, and the third is bi-directional long short term memory network which converts spatial sequential information to character strings using time-series analysis mapping from feature vectors to character strings. In this research, point of interest character strings are device ID and gas usage amount. Device ID consists of 12 arabic character strings and gas usage amount consists of 4 ~ 5 arabic character strings. All system components are implemented in Amazon Web Service Cloud with Intel Zeon E5-2686 v4 CPU and NVidia TESLA V100 GPU. The system architecture adopts master-lave processing structure for efficient and fast parallel processing coping with about 700,000 requests per day. Mobile device captures gasometer image and transmits to master process in AWS cloud. Master process runs on Intel Zeon CPU and pushes reading request from mobile device to an input queue with FIFO (First In First Out) structure. Slave process consists of 3 types of deep neural networks which conduct character recognition process and runs on NVidia GPU module. Slave process is always polling the input queue to get recognition request. If there are some requests from master process in the input queue, slave process converts the image in the input queue to device ID character string, gas usage amount character string and position information of the strings, returns the information to output queue, and switch to idle mode to poll the input queue. Master process gets final information form the output queue and delivers the information to the mobile device. We used total 27,120 gasometer images for training, validation and testing of 3 types of deep neural network. 22,985 images were used for training and validation, 4,135 images were used for testing. We randomly splitted 22,985 images with 8:2 ratio for training and validation respectively for each training epoch. 4,135 test image were categorized into 5 types (Normal, noise, reflex, scale and slant). Normal data is clean image data, noise means image with noise signal, relfex means image with light reflection in gasometer region, scale means images with small object size due to long-distance capturing and slant means images which is not horizontally flat. Final character string recognition accuracies for device ID and gas usage amount of normal data are 0.960 and 0.864 respectively.