• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.10a
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• pp.338-345
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• 2013

Induction motors play an increasing importance in industrial manufacturing. Therefore, the state monitoring systems also have been considering as the key in dealing with their negative effect by absorbing faulty symptoms in motors. There are numerous proposed systems in literature, in which, several kinds of signals are utilized as the input. To solve the multiple faults problem of induction motors, like the proposed system, the vibration signals is good candidate. In this study, a new signal processing scheme was utilized, which transforms the time domain vibration signal into the spatial domain as an image. Then the spatial features of converted image then have been extracted by applying the dominant neighbourhood structure (DNS) algorithm. In addition, these feature vectors were evaluated to obtain the fruitful dimensions, which support to discriminate between states of motors. Because of reliability, the conventional one-against-all (OAA) multi-class support vector machines (MCSVM) have been utilized in the proposed system as classifier module. Even though examined in severity levels of signal-to-noise ratio (SNR), up to 15dB, the proposed system still reliable in term of two criteria: true positive (TF) and false positive (FP). Furthermore, it also offers better performance than five state-of-the-art systems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.11
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• pp.2022-2030
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• 2008

System such as FA and breakup TC is applied by real time and need to manage. This paper studies data processing skill that can divide TC and data of much quantity with collection by real time. Modularize to several system, and use of computer communication network that interlink computers that can achieve control function of each systems to network is spreading. Develop that can take advantage of Ideonet communication method and transmit signal of channel because do multiplex all. Do data that have semi-conductor equipment or many input of LCD equipment and output node multiplex, and several units real time Ideonet communication that control is available use that all input of point of contact and output module develop.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.5
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• pp.179-186
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• 2021

For stereo matching based on deep learning, the design of network structure is crucial to the calculation of matching cost, and the time-consuming problem of convolutional neural network in image processing also needs to be solved urgently. In this paper, a method of stereo matching using sparse loss volume in parallax dimension is proposed. A sparse 3D loss volume is constructed by using a wide step length translation of the right view feature map, which reduces the video memory and computing resources required by the 3D convolution module by several times. In order to improve the accuracy of the algorithm, the nonlinear up-sampling of the matching loss in the parallax dimension is carried out by using the method of multi-category output, and the training model is combined with two kinds of loss functions. Compared with the benchmark algorithm, the proposed algorithm not only improves the accuracy but also shortens the running time by about 30%.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.2
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• pp.27-33
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• 2014

This paper proposes a gradation image processing method for the development of a Road Sign Recognition Platform (RReP), which aims to facilitate the rapid and accurate management and surveying of approximately 160,000 road signs installed along the highways, national roadways, and local roads in the cities, districts (gun), and provinces (do) of Korea. RReP is based on GPS(Global Positioning System), IMU(Inertial Measurement Unit), INS(Inertial Navigation System), DMI(Distance Measurement Instrument), and lasers, and uses an imagery information collection/classification module to allow the automatic recognition of signs, the collection of shapes, pole locations, and sign-type data, and the creation of road sign registers, by extracting basic data related to the shape and sign content, and automated database design. Image division and merging, which were applied in this study, produce superior results compared with local binarization method in terms of speed. At the results, larger texts area were found in images, the accuracy of text recognition was improved when images had been gradated. Multi-threshold values of natural scene images are used to improve the extraction rate of texts and figures based on pattern recognition.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.04b
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• pp.1619-1622
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• 2002

최근에 생산되는 디지털 VLSI칩들은 그 집적도가 계속 높아지고 있으며, 이러한 칩들을 장착한 보드의 경우도 그 복잡성이 점차 높아지고 있다. 이에 따라 칩 및 보드에 대한 철저한 테스트 과정이 요구된다. 지금까지 보드 테스트 방법으로 널리 쓰였던 ICT(In-Circuit Test)는 칩의 고집적화에 따른 핀 간격의 조밀화와 SMT(Surface Mount Technology), BGA(Ball Grid Array), MCM(Multi Chip Module) 등의 새로운 패키징 방식의 등장에 따라 테스트 방법으로의 한계성을 드러내고 있다. 이에 대한 대안으로 등장한 IEEE Std 1149.1 은 ICT의 한계성을 극복할 수 있는 기술일 뿐 아니라 여러 가지 장점을 가지고 있으며 그 활용 분야도 다양하다. 본 논문에서는 IEEE Std 1149.1에 따라 설계된 보드 상에서 발생 가능한 고장들에 대한 고장 모델을 제시한다. 또한 각 고장 모델들의 양상과 진단 기법을 제시한다. 이를 통해 IEEE Std 1149.1에 따라 설계된 보드 상에서 발생한 고장들을 검출할 수 있으며, 고장의 종류 및 성격, 그리고 고장의 발생 위치 등의 정보를 얻을 수 있다. IEEE Std 1149.1에 따른 보드 설계가 보드의 신뢰성 보장에 긴요함을 인식하는 계기가 되기를 기대하며 제시된 고장 모델 및 진단 기법이 기술적으로 중요한 참고자료가 되기를 기대한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.852-854
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• 2010

MCM-ERC32 는 우주 환경에서 동작하는 시스템에 사용할 목적으로 유럽에서 개발된 집약 프로세서 모듈이다. MCM (Multi Chip Module)은 크게 ERC32 single chip 과 VASI (Very Advanced Sparc Interface) 및 6MByte 의 SRAM, 32MByte 의 DRAM 으로 구성되어 있다. VASI 의 경우 각종 I/O 처리 및 timer 의 기능을 수행하며 특히 VASI RTC 의 경우 VASI cycle, slot 을 이용하여 다양한 형태의 timer 구현이 가능하다. Timer 의 경우 각종 태스크의 관리와 스케줄링에 사용되는 가장 기본적이며 매우 중요한 요소이다. 위성의 고유 시간 역시 timer 를 활용하여 설계하게 되는데 이 부분이 잘 구현 되어야 정확한 임무 수행 및 위성의 제어가 가능하다. 본 논문에서는 VASI RTC 의 구조와 기능에 대해 설명하고 이를 위성의 고유 시간 운영에 적용하는 방법에 대해 다루도록 하겠다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.5
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• pp.997-1006
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• 2019

To overcome the difficulties and inefficiencies of the existing power analysis attack, we try to extract the secret key embedded in a cryptographic device using attack model based on MLP(Multi-Layer Perceptron) method. The target of our proposed power analysis attack is the AES-128 encryption module implemented on an 8-bit processor XMEGA128. We use the divide-and-conquer method in bytes to recover the whole 16 bytes secret key. As a result, the MLP-based power analysis attack can extract the secret key with the accuracy of 89.51%. Additionally, this MLP model has the 94.51% accuracy when the pre-processing method on power traces is applied. Compared to the machine leaning-based model SVM(Support Vector Machine), we show that the MLP can be a outstanding method in power analysis attacks due to excellent ability for feature extraction.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.560-569
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• 2011

In this paper, we propose a text processing method for Hindi characters, Devanagari scripts, in the Android. The key points of the text processing are to device automata, which define the combining rules of alphabets into a set of syllables, and to implement a font rendering engine, which retrieves and displays the glyph images corresponding to specific characters. In general, an automaton depends on the type and the number of characters. For the soft-keyboard, we designed the automata with 14 consonants and 34 vowels based on Unicode. Finally, a combined syllable is converted into a glyph index using the mapping table, used as a handle to load its glyph image. According to the multi-lingual framework of Freetype font engine, Dvanagari scripts can be supported in the system level by appending the implementation of our method to the font engine as the Hindi module. The proposed method is verified through a simple message system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.3991-4010
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• 2021

The Question Similarity Measurement of Chinese Crop Diseases and Insect Pests (QSM-CCD&IP) aims to judge the user's tendency to ask questions regarding input problems. The measurement is the basis of the Agricultural Knowledge Question and Answering (Q & A) system, information retrieval, and other tasks. However, the corpus and measurement methods available in this field have some deficiencies. In addition, error propagation may occur when the word boundary features and local context information are ignored when the general method embeds sentences. Hence, these factors make the task challenging. To solve the above problems and tackle the Question Similarity Measurement task in this work, a corpus on Chinese crop diseases and insect pests(CCDIP), which contains 13 categories, was established. Then, taking the CCDIP as the research object, this study proposes a Chinese agricultural text similarity matching model, namely, the AgrCQS. This model is based on mixed information extraction. Specifically, the hybrid embedding layer can enrich character information and improve the recognition ability of the model on the word boundary. The multi-scale local information can be extracted by multi-core convolutional neural network based on multi-weight (MM-CNN). The self-attention mechanism can enhance the fusion ability of the model on global information. In this research, the performance of the AgrCQS on the CCDIP is verified, and three benchmark datasets, namely, AFQMC, LCQMC, and BQ, are used. The accuracy rates are 93.92%, 74.42%, 86.35%, and 83.05%, respectively, which are higher than that of baseline systems without using any external knowledge. Additionally, the proposed method module can be extracted separately and applied to other models, thus providing reference for related research.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.4
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• pp.707-714
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• 2016

Active driving safety systems for vehicle, such as the front collision avoidance, lane departure warning, and lane change assistance, have been popular to be adopted to the compact car. For improving performance and competitive cost, FMCW radar has been researched to adopt a phased array or a multi-beam antenna, and to integrate the front and the side radar. In this paper we propose several efficient methods to implement the signal processing module of FMCW radar system using low cost DSP. The pulse width modulation (PWM) based analog conversion, the approximation of time-eating functions, and the adoption of vector-based computation, etc, are proposed and implemented. The implemented signal processing board shows the real-time performance of 1.4ms pulse repetition interval (PRI) with 1024pt-FFT. In real road we verify the radar performance under real-time constraints of 10Hz update time.