• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.2
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• pp.369-377
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• 2008

Though the Hough transform(HT) is a well-known method for detecting analytical shape represented by a number of free parameters, the basic property of the HT, the one-to-many mapping from an image spare to a Hough space, causes the innate problem, the sensitivity to noise. This basic problem also deteriorates the quality of detected lines and makes the detected line deviated from the real one or generates some bogus, multiple lines where only one real line exists. The size of Hough space also affects the quality of detected lines. In this paper, we analyzed the line distortions in the traditional Hough transform and showed that the distortions are relieved in the edge strength Hough transform(ESHT), which is a modified HT. However the usage of expanded edge and edge strength in ESHT can cause some new line distortions which do not exist in the HT. These new ones can be solved by a proper setting of decreasing and broadening parameter values and the optimal values can be determined only by some pre-determined values. We also illustrated several examples to show the distortion-decreasing property of ESHT.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.581-584
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• 2009

Recently, the cameras which used for observation are installed in children protection area and local crime prevention area in order to protect life and property and by its work being recognized and are installed more. Normal cameras have cost problem to observe multiple area and detail, because they can observe only one place. PTZ camera can observe multiple area by moving focus by schedule or remote control, but it can't automatically move the focus of it to the place where event occurred, because it can't recognize the place. In this study, we can monitor multiple area effectively, by installing a wireless sensor node equipped with temperature, lighting, gas and human detection sensor to each area, to monitor many place low-price and actively and to move the focus of PTZ camera to preset position, and send recorded video to the user, when the various sensor data received from wireless sensors in observation area are to be determined abnormal by analyzing. In addition, at night we can record a scene using infrared, but to reduce power consumption of lighting system which are installed to improve resolution, it supplies power to the lighting system when event occurred. So we were able to implement low power green monitoring system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1711-1717
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• 2020

X-ray of up to 9MeV are used for container inspection. X-ray intensity must be maintained stably regardless of changes in time. If dose is not constant, it may affect the image quality, and as a result, may affect the inspection of abnormal cargo. Therefore, to acquire high-quality images, continuous dose monitoring is required. In this study, the ion-chamber based device was developed for monitoring the dose change in high-energy x-ray. And to estimate the performance of signal-processing device change according to the environmental change, the output changing due to the change of temperature and humidity was observed. In addition, verification of the device was performed by measuring the output change. As a result of the measurement, there was no significant difference in performance due to changes in temperature and humidity, and the change in output according to the change in exposure was linear. Therefore, it was found that the developed device is suitable for the dose monitoring of high-energy x-ray.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.1
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• pp.41-49
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• 2023

A convolutional neural network (CNN) is a representative algorithm for implementing artificial neural networks. CNNs have improved on the issues of rapid increase in calculation amount and low object classification rates, which are associated with a conventional multi-layered fully-connected neural network (FNN). However, because of the rapid development of IT devices, the maximum resolution of images captured by current smartphone and tablet cameras has reached 108 million pixels (MP). Specifically, a traditional CNN algorithm requires a significant cost and time to learn and process simple, high-resolution images. Therefore, this study proposes an improved CNN algorithm for implementing an object classification learning model for simple, high-resolution images. The proposed method alters the adjacency matrix value of the pooling layer's max pooling operation for the CNN algorithm to reduce the high-resolution image learning model's creation time. This study implemented a learning model capable of processing 4, 8, and 12 MP high-resolution images for each altered matrix value. The performance evaluation result showed that the creation time of the learning model implemented with the proposed algorithm decreased by 36.26% for 12 MP images. Compared to the conventional model, the proposed learning model's object recognition accuracy and loss rate were less than 1%, which is within the acceptable error range. Practical verification is necessary through future studies by implementing a learning model with more varied image types and a larger amount of image data than those used in this study.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.454-464
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• 2023

This paper proposes a low-power 8-bit asynchronous SAR ADC with a sampling rate of 1 MS/s for sensor node applications. The ADC uses bootstrapped switches to improve linearity and applies a VCM-based CDAC switching technique to reduce the power consumption and area of the DAC. Conventional synchronous SAR ADCs that operate in synchronization with an external clock suffer from high power consumption due to the use of a clock faster than the sampling rate, which can be overcome by using an asynchronous SAR ADC structure that handles internal comparisons in an asynchronous manner. In addition, the SAR logic is designed using dynamic logic circuits to reduce the large digital power consumption that occurs in low resolution ADC designs. The proposed ADC was simulated in a 180-nm CMOS process, and at a 1.8 V supply voltage and a sampling rate of 1 MS/s, it consumed 46.06 𝜇W of power, achieved an SNDR of 49.76 dB and an ENOB of 7.9738 bits, and obtained a FoM of 183.2 fJ/conv-step. The simulated DNL and INL are +0.186/-0.157 LSB and +0.111/-0.169 LSB.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.6
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• pp.185-190
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• 2023

Recently, tracking radar requires the development of millimeter wave tracking radar to acquire target information with high resolution in various environments. The development of millimeter wave tracking radar requires the development of transmission and receiving components that can be applied to the millimeter wave tracking radar, as well as verification of the applicability of the tracking radar. In order to verify the applicability of the developed transmitting and receiving components, it is necessary to develop a signal acquisition device that can control the transmitting and receiving components using the operating concept of a tracking radar and check the status of the received signal. In this paper, we implemented a signal acquisition device that can confirm the applicability of components developed for millimeter wave tracking radar. The signal acquisition device was designed to process in real time the OOOMHz center frequency and OOMHz bandwidth signals input from 4 channels to verify the received signal. In addition, component control applying the tracking radar operation concept was designed to be controlled by communication such as RS422, RS232, and SPI and generation of control signals for the transmission and receiving time. Lastly, the implemented signal acquisition device was verified through a signal acquisition device performance test.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.3
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• pp.210-216
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• 2016

Malfunctioning of telecom systems can have serious implications on the safe navigation and operation of vessels and off-shore plants. Most safety-related accidents incur significant monetary damages and pollution due to complicated arrangements of the working environments and facilities. Therefore, an automated monitoring system that can collect data from configured telecom equipment connected to a network based on IP is required to ensure safe navigation and operation of such crucial institutions. This paper reports a list of such system requirements, system functions, and user-centered requirements based on the NORSOK T-100 (a standard of telecom management system). These findings were made through research with the newly designed and developed telecom management system (TMS). The TMS was tested by a testbed configured with CCTV, PA/GA, and other network equipment.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.07a
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• pp.100-102
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• 2015

In recent years, using a smart phone that can access the Internet becomes routine in society through development of information and communication technology. On land, as especially actual accidents and research results show risk that using the smart phone while driving at the same time, and there are traffic laws and regulations that restriction of using of smart phone. But the regulations on the use of smart phones at sea is incomplete state. On this paper. We invested present status of use and reality of smart phone at sea and analyzed the subjective risk for judging to apply to regulation. And we analyzed risk quantitatively by using the simulation experiment; it Suggested a direction of guideline for use of smart phone at sea.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2006.06a
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• pp.179-179
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• 2006

산업기술의 고도화에 따른 IT 산업의 급속한 발전으로 각종 전자, 정보통신기기에 대해 더욱 소형화 고성능화를 요구하고 있다. 이와 같은 경향에 따라 더욱 향상된 기능을 가지고 각종 소자 부품의 개발과 동시에 유독 물질 발생이 없는 청정생산기술 개발에 대한 요구가 끊임없이 제기 되어 왔다. 이러한 요구에 부응하여 기술들이 개발되고 있으며 그 중의 하나로 잉크젯 프린팅 기술이 연구되고 있다. 특히 Dod(Drop on Demand) 방식의 잉크젯은 가정용 프린터로 개발되어 널리 보급된 기술이지만, 이 기술을 PCB 제조기술에 전용하면 친환경 생산공정으로 부품 성장밀도를 증대 시킬 수 있다. 기존의 PCB 제조기술은 전극과 신호 패턴을 형성시키기 위하여 노광공정과 에칭공정을 반복적으로 사용하고 있는데, 노광공정에서 쓰이는 마스크와 유틸리티 설비 유지 비용의 문제가 대두되고 있다. 노즐로부터 분사된 잉크 액적들의 집합으로 기판위에 점/선/면의 인쇄이미지를 구현하게 된다. 그러므로 인쇄 해상도는 잉크액적 및 인쇄 방법, 기판과의 상호작용에 크게 의존하게 된다. 잉크 액적과 기판의 상호작용에 영향을 미치는 요소로는 잉크의 물리화학적 물성(밀도, 점도, 표면장력), 잉크 액적의 충돌 조건(액적 지름, 부피, 속도), 그리고 기판의 특성(친수/소수성, Porous/Nonporous, 표면조도 등)을 들 수 있겠다. 우선적으로 노즐을 통과해서 분사되는 액적의 크기에 따라 기판위에 형성되는 라인의 두께 및 폭이 결정된다. 떨어진 액적이 기판위에서 퍼지는 것을 UV 조사를 통한 가경화 과정을 통해서 최종적으로 라인의 투께 및 폭을 조절하려고 한다. 따라서 선폭 $75{\mu}m$의 일정한 미세 배선을 형성시키기 위해 액적 크기 조절과 탄착 resist 액적 표면의 UV 가경화 조건으로 구현하려고 한다. 또한 DPI(Dot Per Inch) 조절을 통한 인쇄로 탄착 resist의 두께 확보 후 에칭시 박리되는 현상을 억제 시키려 한다.

• The Journal of the Acoustical Society of Korea
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• v.38 no.1
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• pp.106-113
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• 2019

In this paper, we propose an algorithm to classify the received active pulse when the active sonar system is operated as a non-cooperative mode. The proposed algorithm uses CNN (Convolutional Neural Networks) which shows good performance in various fields. As an input of CNN, time frequency analysis data which performs STFT (Short Time Fourier Transform) of the received signal is used. The CNN used in this paper consists of two convolution and pulling layers. We designed a database based neural network and a pulse feature based neural network according to the output layer design. To verify the performance of the algorithm, the data of 3110 CW (Continuous Wave) pulses and LFM (Linear Frequency Modulated) pulses received from the actual ocean were processed to construct training data and test data. As a result of simulation, the database based neural network showed 99.9 % accuracy and the feature based neural network showed about 96 % accuracy when allowing 2 pixel error.