2006.04a
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Recent advances in the internet infrastructure have resulted in a large number of huge Web sites and portals worldwide. These Web sites are being visited by various types of users in many different ways. Among all the web page access sequences from different users, some of them occur so frequently that may need an attention from those who are interested. We call them frequent access patterns and access sequences that can be frequent the candidate patterns. Since these candidate patterns play an important role in the incremental Web mining, it is important to efficiently generate, add, delete, and search for them. This thesis presents a novel tree structure that can efficiently store the candidate patterns and a related set of algorithms for generating the tree structure adding new patterns, deleting unnecessary patterns, and searching for the needed ones. The proposed tree structure has a kind of the 3 dimensional link structure and its nodes are layered.
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Using enhanced ordering scheme of graylevel in an image, we can apply it to lossless image compression in this paper. The proposed method is ordering scheme to replace an original grayscale image with a particular ordered image without additional information. From the simulation, it is verified that the proposed method reduces the bit rates than plain ordering scheme. And it can be applied in various fields of lossless compression, water marking and edge detection.
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This paper presents JPEG quantization table design using RD optimization and neural network. Using R-D optimization, quantization table with good performance can be obtained. However, it is time-consuming and difficult to adopt to embedded systems. In this paper, a new quantization table design method is proposed using R-D optimization and neural network. Neural network learns the quantization table obtained from R-D optimization and produces a quantization table for the Images. The proposed system is applied to Yale face data. From the simulation results, it has been shown that the proposed codec has better performance than JPEG.
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This paper presents a novel scene change detection method using intra prediction mode and edge direction in H.264/AVC. When scene change occurs, there are less temporal correlation between frames, most of macro-blocks encoded in intra mode. Using this property, the method calculates the percentage of intra mode blocks in each predictive frame in order to get candidates of scene change frame. To further find scene change, we obtain edge histogram of each candidates by using eight prediction direction of intra prediction mode in H.264/AVC. We detect scene change frames with $\iota^1$-norm of edge histograms. The experimental results show that the method is efficient and robust.
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This paper presents a new global intensity compensation method for extracting moving object in a visual surveillance system by compensating time variant intensity changes of background region. The method that compensates a little changes of intensity due to time variant illumination change and automatic gain control of camera is called global intensity compensation. The proposed method expresses global intensity change with a mapping table to describe complex form of intensity change while the previous method models this global intensity change with a simple function as a straight line. The proposed method builds the mapping table by calculating the cross histogram between two images and then by selecting an initial point for generating the mapping table by using Hough transform applied to the cross histogram image. Then starting from the initial point, the mapping table is generated according to the proposed algorithm based on the assumption that reflects the characteristic of global intensity change. Experimental results show that the proposed method makes the compensation error much smaller than the previous GIC method
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The statistics for the neighbor differences between the particular pixels and their neighbors are introduced. They are incorporated into the filter to remove additive Gaussian noise contaminating images. The derived denoising method corresponds to the maximum likelihood estimator for the heavy-tailed Gaussian distribution. The error norm corresponding to our estimator from the robust statistics is equivalent to Huber's minimax norm. Our estimator is also optimal in the respect of maximizing the efficacy under the above noise environment.
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Due to development of Internet network environments and data compression techniques, the size and amount of multimedia data has greatly increased. They are compressed before transmission or storage. Dealing with these compressed data such as video retrieval or indexing requires the decoding procedure most of the time. In video retrieval and indexing a color histogram is one of the most frequently used tools. We propose a novel scheme for extracting color histograms from images transformed into the compressed domain using
$8{times}8$ DCT(Discrete Cosine Transform). In this scheme an averaged version of original image is obtained by filtering DCT coefficients with a filter we destined. -
In this paper, a nonlinear echo cancellation approach, based on a Gauss-Seidel pseudo affine projection algorithm and Volterra filtering, is proposed to compensate for echo path nonlinearity in the telephone network. Simulation results demonstrate that the proposed approach yields reduction of computational complexity and improved convergence speed than the conventional nonlinear echo cancellation methods (NLMS, ECLMS, FAP, RLS).
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In this paper, we propose a new method of automatic white balance which is one of the image signal processing techniques. Our method is conceptually based on gray world assumption. However, while previous methods generate linear results as multiplying pixel values by a gain, our method generates non-linear results using the feature of B-Spline curves. The two merits of deriving non-linear results are preventing AWB failure from transforming strong color of high level into wrong color and well preserving original contrast of an input image.
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An adaptive IIR filter in ANC(Active Noise Control) systems is more effective than an adaptive FIR filter when acoustic feedback exists, in which cause an order of an adaptive FIR filter must be very large if some of poles of the ideal control filter are near the unit circle. But the IIR filters may have stability problems especially when the adaptive algorithm for adaptive filters is not yet converged. In this paper, a stabilized multi-channel recursive LMS (MCRLMS) algorithm for an adaptive multi-channel IIR filter is presented. RLMS algorithms usually diverge before the algorithm is not yet converged. So, in the beginning of the ANC system, the stability of the RLMS algorithms could be Improved by pulling the poles of the IIR filter to the center of the unit circle, and returning the poles to their original positions after the filter converges. Computer simulations and experiments for dipole ducts using a TMS320C32 digital signal processor have performed to show the effectiveness of a proposed algorithm.
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We studied the prototypal developments of Plastic Cortex Stimulator (PCS) for stroke patients. The PC sends the stimulation parameters (amplitude, pulse width, cycle, etc.) to the transmitter ZigBee module through serial port. The receiver ZigBee module generates stimulation waveform. The generated output can be controlled by the PC program. Further study can be expanded to portable handset such as PDA using ZigBee. The wireless control of PCS with the handset can help the tele-rehabilitation.
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In this study, two algorithms for detecting respiratory rate from Portable ECG device were presented. The first algorithms counts the number of ECG samples between R-R peaks, which varies according to respiratory states of patients, such as, exhalation and inhalation. The second algorithms detects the rate by measuring the size of R wave, which also varies according to the respiratory status of patient. These two algorithms were programmed to the laboratory developed ECG device and their usefulness was verified in laboratory environment.
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It is important to estimate the hand skin temperature because it reveals not only physiological properties of a certain diseases but also it can estimate even human mental-stress conditions. In this study, we try to estimate the temporal skin temperature distribution of human hand by applying stress-cold test to possibly apply to estimate a subject's blood circulation condition in his or her hand in terms of normal or abnormal state.
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Up to the present, finger replantation patients have complained about various symptoms because of blood circulatory failure. Objective evaluation methods for the level of the blood circulatory failures in fingers were needed other than patient's subjective symptoms and complaints. Photoplethysmogram(PPG) measured from fingers is very useful for evaluation of vascular aging and sclerosis level since the PPG signal represents characteristics of peripheral vascular. Several researchers have reported that second derivative of the finger PPG waveform was useful to evaluate vascular compliance and developed various analysis methods for vascular compliance. However, vascular compliance study for finger replantation patient was never evaluated by using second derivative of PPG. Therefore, we aimed to objectively compare and to assess normal and replanted finger vascular compliance using the second derivative of PPG waveform in this study. The evaluated factors of second derivative of PPG are 'a', 'b', 'c', 'd', 'e' and b/a represents vascular compliance. Study found out that when vascular compliance is decreased, b/a is increased, the absolute value of b/a is decreased. For 43 finger replantation patients, the average vascular compliance of replanted finger is lower than the normal finger statistically(p=0.001). we suggested an objective evaluation of finger vascular compliance for finger replantation patients and effect of surgical operation.
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Cleft palate is a congenital deformity condition with separation of the two sides of the lip resulting in nose deformity. Evaluation of surgical corrections and outcome assessments for nose deformity due to the cleft lip depends mainly on doctor's subjective judgment. An objective method for evaluation of the condition and surgical outcome of nose deformity due to the cleft palate is needed. This study aimed at objective assessment of a cleft palate nose deformity condition by analyzing the following parameters obtained from photographic images of a cleft palate patients: (1) angle difference between two nostril axes. (2) center of the nostril and distance between two centers. (3) overlapped area of two nostrils, and (4) the overlapped area ratio of the two nostrils. A regression equation of doctor's grades was obtained using the eight parameters. Three plastic surgeons gave us the grades for the each photographic image by 10 increments with maximum grade of 100. The average reproducibility of the grades given by the three plastic surgeons and the three laymen using the developed program was
$10.8{\pm}4.6%$ and$7.4{\pm}1.8%$ , respectively. Kappa values representing the degree of consensus of the plastic surgeons and the three laymen were 0.43 and 0.83. respectively. Correlation coefficient of the grades evaluated by the surgeons and obtained by the neural network was 0.798. In conclusion. the developed neural network model provided us better reproducibility and much better consensus than doctor's subjective evaluation in addition to objectiveness and easy application. -
In this paper, we propose a method to minimize the baseline wandering that make hard to detect R wave in ECG. This method uses a different signal between ECG and ascending slope tracing waves to minimize the baseline wandering. When the slope of ECG signal maintains the value or falls, the ascending slope tracing wave fellows ECG signal directly, and this wave holds that value of ECG signal when the slope begins to rises in a certain time(=hold time). After this hold time, this wave traces ECG signal again. To evaluate this minimizing method for baseline wandering, the experiments are carried out with 5 ECG data in the database of MIT/BIH. R waves in the proposed different signal are detected by using descending slope trace waves and compared with the annotation file. The results show that the proposed method Is sure to minimize the baseline wandering in ECG.
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This paper proposes a portable ECG monitoring system, which integrates uptodate PDA and RF communication technology. The aim of the study is to acquire the subject's biomedical signal without any constraint. It has two types of transmission mode, which are total signal transmission mode and HR(heart rate)/SC(step count) transmission mode. In audition, wireless communication technology uses Zigbee Wireless PAN and can work in low-power mode, which is one of the advantages of ZiBbee communication technology. The developed system is composed of a transmitter and a receiver. The transmitter has three-axial acceleration sensor. ECG amplifier and Zigbee communication controller. In total signal transmission mode, it can send data 50 packets per second whose transmission speed corresponds to 300 ECG samples and 60 acceleration samples. In HR/SG transmission mode, it can calculate heart rate from EEG data with 216 samples per second and step count from acceleration data and send a packet every cardiac cycle. The receiver forwards the received data to PDA, where the data can be stored and displayed. Therefore, the developed device enables to continuous monitoring for Activities of Daily Living(ADL). Also, this method will reduce medical costs in the aged society.
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To get the robust and reliable input command, we designed shaping function for target tracking system with commander's handle. Input signals of the commander's handle are generated by human operator. It is response of the human to reduce the error between target and gun. But, tracking error while operator aim a moving target manually gives poor system performance. Input noise, particularly, affects hit accuracy as the system performance. We proposed the design method of input command shaping to reduce the Input noise and to improve the operation ability and convenience. We performed the experiments with combat vehicle, example of Target Tracking System, to show the proposed method is efficient and practical.
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In this paper, we investigate the wireless TCP protocol for throughput improvement in wireless Broadband. If the burst error duration of a wireless link is significantly long, retransmissions of lost packets by Snoop TCP are fulfilled mainly not by the receipt of duplicate acknowledgement (DUPACKs) but by local timer expiration. With the proposed scheme, Snoop TCP recovers packet losses fast by shortening the interval of local retransmissions based on the channel status. From the simulation results, we can show that the proposed scheme can improve TCP throughput considerably.
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This paper presents an efficient frequency offset (FO) estimation algorithm for the orthogonal frequency division multiplexing (OFDM) based wireless local area networks (WLANS). The packet preamble imformation is utilized on the high rate WLAN standards adopted by the IEEE 802.11a. We present FO estimation schemes using diversity. In the simulation results, we prove that the presented schemes can improve the estimation performance compared with the convolutional scheme.
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As OFDM-based systems exhibits robustness over wireless channel, it is possible to consider them the next generation of the wireless communications including the mobile communications. However, there is a critical point that OFDM-based systems can receive the distorted signal due to the frequency-offset. Therefore, it is necessary to accurately estimate the frequency-offset for OFDM-based systems to be adopted as the next wireless communication systems. In this paper, the efficient frequency-offset estimation scheme based on MUSIC is presented in 802,1la WLAN systems. As shown in the simulation result, this scheme can improve and optimize the estimation performance.
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DVB-H (Digital Video Broadcasting for Handhold) is a new standard, currently being developed, which defines mobile enhancements for the DVB-T (DVB-Terrestrial) standard. For the reception of service via mobile handhold devices, seamless mobility and power saving are essential requirements of DVB-H. For seamless handover, the receiver should monitor neighboring cells and it increases the power consumption. And so, power efficient handover scheme to support both mobility and power saving is required. In this paper, we propose cell searching scheme to reduce power consumption by reducing the number of frequency scanning during the handover. Through the numerical evaluation, we analyzethe performance of handover schemes.
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본고에서는 T-DMB에서 사용하는 데이터 서비스에 필요한 프로토콜 중, 세션계층의 프로토콜을 분석하여 UML로 모델링하였다. 세션계층에 속한 프로토콜로는 MOT 프로토콜과 데이터 그룹 프로토콜이 있다. 이 프로토콜들은 데이터 서비스를 위한 프로토콜로 방송웹사이트나 슬라이드 쇼 등을 전송하는데 이용된다. MOT 프로토콜은 부가 정보를 포함하는 객체 정보를 부호화 하는 과정이고, 데이터 그룹 프로토콜은 MOT 부호화된 객체를 분할하는 과정이다. 이러한 분석은 MOT 데이터 서비스를 위한 송수신기 설계 및 구현에 활용될 수 있다.
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본 논문에서는 현재 무료로 본 방송이 진행 중인 T-DMB 제한 수신을 위한 시스템 분석에 대해 기술하였다. T-DMB 방송사업자들은 별도의 수신료를 징수하지 않고 광고 수입에 의존하게 되는데, 막대한 제작 비용이 소모되는 데이터 서비스를 위한 콘텐츠들을 무료로 서비스하게 된다면 수익 구조상 데이터 서비스에 매우 소극적이 될 것이다. 이런 이유로 일부 데이터 서비스들에 대한 유료화 필요성이 대두되면서 제한 수신 시스템의 도입이 추진되고 있다. 현재 제한 수신 시스템을 T-DMB에 적용하기 위한 방법으로 서브 채널 제한 수신, 데이터 그룹 제한 수신, MOT 제한 수신 등의 세 가지 모드가 있다. 분석 결과, T-DMB에 제한 수신 시스템을 적용할 시에, 많은 가입자 수에 따른 대역폭 부족의 문제, AV와 함께 전송되는 BIFS만 따로 스크램블링 할 수 없다는 문제, 복수의 제한 수신 사업자들의 헤드 엔드 장비간 공통 인터페이스 작성, 다양한 수신 단말기들이 공통 인터페이스 작성 둥의 문제점들에 대해서 기술하였다.
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In this paper, the technology of the conformance test for Broadcast Web Site Service (BWS) which is one of the data services of the T-DMB (Terrestrial Digital Multimedia Broadcasting) is proposed. First, the standard of the BWS Service is introduced and then the method of the conformance test of BWS bitstream and BWS receiver module is provided. A BWS bitstream analyzer is implemented for use in verifying the transmitted BWS bitstreams. To provide a means for the receiver manufactures to verify their own BWS receiver modules, a receiver test suite is developed including BWS test bitstreams and a BWS reference receiver module. The BWS bitstream analyzer includes the analysis function for the conformance test of MOT protocol, HTML, PNG, MNG, JPEG, and Ecma Script. Also, it was actually used for verifying the BWS test bitstreams. In the course of developing a HWS receiver module, 4he BWS receiver module under test can be verified by comparing the results of the BWS reference receiver module with those of the receiver module under test. when the same BWS test bitstreams are fed into the two receiver modules.
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Mouse is widely used in multimedia education. However, using mouse is not easy for user to get exact three dimentional (3D) user input and to manipulate delicately as the user can not know the surface information of virtual objects, which are typical drawbacks of using mouse in multimedia education, especially in 3D multimedia contents authoring. In this paper, haptic device is introduced to the 3D multimedia education. The haptic device provides 3D user's input information as well as haptic information of virtual objects such as surface textures, collisions and etc. which thus allow to enhance the task efficiency in multimedia education. Simple experiment results are presented to show the positive results of using the haptic device in multimedia education.
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This Paper suggests efficient design method which is used by Bit_Inerleaver in the IEEE 802.15,3.a. Bit_Interleaver is consist of Symbol_Interleaver and Tone_Interleaver Each Interleaver is designed by using memory. In other to resolve burst error, Block Interleaver is using different leading and writing address for mixing the data. However This method has a different reading and writing memory address to realize Block Interleaver so this schematic is some complex. This Paper suggests efficient and simple Bit_Interleaver Method which classify the memory of Bit_Interleavr to reduce complexity of shcemeatic.
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An informed watermarking algorithm is proposed in this work that aids in concealing packet loss errors in video communications. This watermark-based error concealment(WEC) method embeds a low resolution version of the video frame inside itself as watermark data. At the receiver, the extracted watermark is used as a reference for error concealment. The proposed DCT-based algorithm has features of informed watermarking in order to minimize the distortion of the host frame. At the encoder, a predictive feedback loop Is employed which helps to adjusts the strength of the scale factor Furthermore, some of the modified coefficients of the DCT signal are virtually free from distortion by employing bit- sign adaptivity. The performance of the detector is Qualitatively analyzed for error concealment applications where full-frame DCT embedding proved to be more advantageous.
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A handover for DVB-H(Digital Video Broadcasting for Handheld) is the action of switching a receiver from receiving one signal to receiving another, when moving between the border of their coverage areas. This paper proposes new approaches for improving loss-free handover performance in the DVB-H networks. The proposed handover schemes are targeted to two different DVB-H receivers: One is for the receivers equipped with GPS devices. The other is for ones without GPS support. The first handover approach modifies the cell description table(CDT) proposed in the literature[1]. The second proposes a novel handover region estimation technique based on a new handover map table(HMT). This new handover approach estimates a predefined hand over region described in the HMT using measured RSSIs signal patterns. The estimation success rate is simulated and the benefits of the proposed method are discussed considering time and power consumption.
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기존의 Support Vector Data Description (SVDD) 방법은 학습 데이터의 개수가 증가함에 따라 학습 시간이 지수 함수적으로 증가하므로, 대량의 데이터를 학습하는 데에는 한계가 있었다. 본 논문에서는 학습 속도를 빠르게 하기 위해 K-means clustering 알고리즘을 이용하는 SVDD 알고리즘을 제안하고자 한다. 제안된 알고리즘은 기존의 decomposition 방법과 유사하게 K-means clustering 알고리즘을 이용하여 학습 데이터 영역을 sub-grouping한 후 각각의 sub-group들을 개별적으로 학습함으로써 계산량 감소 효과를 얻는다. 이러한 sub-grouping 과정은 hypersphere를 이용하여 학습 데이터를 둘러싸는 SVDD의 학습 특성을 훼손시키지 않으면서 중심점으로 모여진 작은 영역의 학습 데이터를 학습하도록 함으로써, 기존의 SVDD와 비교하여 학습 정확도의 차이 없이 빠른 학습을 가능하게 한다. 다양한 데이터들을 이용한 모의실험을 통하여 그 효과를 검증하도록 한다.
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In many control system applications, the system designed must not only satisfy the damping and accuracy specifications, but the control must also yield performance that is robust to external disturbance and parameter variations. We have shown that feedback in conventional control systems has the inherent ability of reducing the effects of external disturbance and parameter variations. Unfortunately, robustness with the conventional feedback configuration is achieved only with a high loop gain, which is normally detrimental to stability. The design of intelligent, autonomous machines to perform tasks that are dull, repetitive, hazardous, or that require skill, strength, or dexterity beyond the capability of humans is the ultimate goal of robotics research. This paper prove the robust control using Analog Adaptive Resonance Theorv(ART2) Algorithm about case study.
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A new ex-situ model to diagnose a plasma processing equipment was presented. The model was constructed by combining wavelet, scanning electron microscope, ex-situ measurement of etching profile, and neural network. The diagnosis technique was applied to a tungsten etching process, conducted in a
$SF_6$ helicon plasma. The wavelet was used to characterize detailed variations of plasma-etched surface. The diagnosis model was constructed with the vertical wavelet component. For comparison, a conventional model was built by using the estimated profile data. Compared to the conventional model, the wavelet-based model, demonstrated a much improved diagnosis. -
Auto-Cross Correlated time series (ACTS) model was constructed by using the backpropagation neural network. The performance of ACTS model was evaluated with sensor information collected from a large volume, industrial plasma-enhanced chemical vapor deposition system. A total of 18 sensor information were collected. The effect of inclusion of past and future information were examined. For all but three sensor information with a large data variance demonstrated a prediction error less than 3%. By integrating ACTS model into equipment software, process quality can be more stringently monitored while improving device throughput.
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Auto-Correlated time series (ATS) model was constructed by using the backpropagation neural network. The performance of ATS model was evaluated with sensor information collected from a large volume, industrial plasma-enhanced chemical vapor deposition system. A total of 18 sensor information were collected. The effect of inclusion of past and future information were examined. For all but three sensor information with a large data variance demonstrated a prediction error less than 4%. By integrating ATS model into equipment software, process quality can be more stringently monitored while improving device throughput.
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As internet streaming data increase, transport protocol such as TCP, TGP-Friendly is important to study control transmission rate and share of Internet bandwidth. In this paper, we propose a TCP-Friendly protocol using Neural Network for media delivery over wired Internet which has various traffic size(PTFRC). PTFRC can effectively send streaming data when occur congestion and predict one-step ahead round trip time and packet loss rate. A multi-layer perceptron structure is used as the prediction model, and the Levenberg-Marquardt algorithm is used as a traning algorithm. The performance of the PTFRC was evaluated by the share of Bandwidth and packet loss rate with various protocols.
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A prediction model of charge concentration of silicon nitride (SiN) thin films was constructed by using neural network and genetic algorithm. SIN films were deposited by plasma enhanced chemical vapor deposition and the deposition process was characterized by means of
$2^{6-1}$ fractional factorial experiment. Effect of five training factors on the model prediction performance was optimized by using genetic algorithm. This was examined as a function of the learring rate. The root mean squared error of optimized model was 0.975, which is much smaller than statistical regression model by about 45%. The constructed model can facilitate a Qualitative analysis of parameter effects on the charge concentration. -
DEAS is an direct searching and optimization method that based on the binary code space. It can be classified as an direct hill climbing searching. However, because of binary code space based searching, the searching in low resolution has random property. As the resolution of code increases during the search, its property of searching changes like that of hill climbing search. This paper propose a method for improving the performance of minimum seeking ability of DEAS with history information. The cost evaluation is increased. However the minimum searching ability of DEAS is improved along the same starting resolution.
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This paper is to propose the palm print recognition system using wavelet transform. The palm print is frequently used as the material for the biometric recognition system such as the finger print, iris, face, etc. Since the palm print has lots of properties which include principle line, wrinkles, ridge and so forth, the ways of the implementation of the system are various. In this paper, at first, the palm print image is acquired and then some level of wavelet transform is performed. The coefficients become to be some blocks size of M by N after divided into the horizontal, vertical, diagonal components each level. The mean values, which are calculated with values of each block, are used as the feature vector. To compare between the stored template and the acquired vectors, we adopt the PNN (Probability Neural Network) method.
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In this work, we suggest another method to localize DFT in spatial domain. This enables DFT algorithm to be used for local pattern matching. Once calculated, it costs same load to calculate localized DFT regardless of the size or the position of local region In spatial domain. We applied this method to face detection problem and got the results which prove the utility of our method.
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In this paper, We have designed a face recognition system based on the embedded Linux. This paper has an aim in embedded system to recognize the face more exactly. At first, the contrast of the face image is adjusted with lightening compensation method, the skin and lip color is founded based on YCbCr values from the compensated image. To take advantage of the method based on feature and appearance, these methods are applied to the eyes which has the most highly recognition rate of all the part of the human face. For eyes detecting, which is the most important component of the face recognition, we calculate the horizontal gradient of the face image and the maximum value. This part of the face is resized for fitting the eye image. The image, which is resized for fit to the eye image stored to be compared, is extracted to be the feature vectors using the continuous wavelet transform and these vectors are decided to be whether the same person or not with PNN, to miminize the error rate, the accuracy is analyzed due to the rotation or movement of the face. Also last part of this paper we represent many cases to prove the algorithm contains the feature vector extraction and accuracy of the comparison method.
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This paper discusses the method of vision based sensor fusion system for biped robot walking. Most researches on biped walking robot have mostly focused on walking algorithm itself. However, developing vision systems for biped walking robot is an important and urgent issue since biped walking robots are ultimately developed not only for researches but to be utilized in real life. In the research, systems for environment recognition and tole-operation have been developed for task assignment and execution of biped robot as well as for human robot interaction (HRI) system. For carrying out certain tasks, an object tracking system using modified optical flow algorithm and obstacle recognition system using enhanced template matching and hierarchical support vector machine algorithm by wireless vision camera are implemented with sensor fusion system using other sensors installed in a biped walking robot. Also systems for robot manipulating and communication with user have been developed for robot.
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For pattern matching, an object image should be segmented and analyzed for the first time. Thresholding is a fundamental approach to segmentation that utilizes a significant degree of pixel popularity or intensity. Otsu's thresholding is one of the most veil-known methods proposed in the literature. However, the method has a disadvantage of repeatedly searching the optimal thresholds for the entire region. To overcome this problem, a number of methods have been proposed. In this paper, we propose a simple and fast thresholding method of finding multi-level threshold values by extending the Otsu's method. Our experimental results for the benchmak images show a possibility that the proposed method could be used efficiently for pattern matching.
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The performances of neural network systems mainly depend on the kind and the number of input patterns for its training. Hence, the kind of input patterns as well as its number is very important for the character recognition system using back-propagation network. The more input patters are used, the better the system recognizes various characters. However, training is not always successful as the number of input patters increases. Moreover, there exists a limit to consider many input patterns of the recognition system for cursive script characters. In this paper we present a new character recognition system using the back-propagation neural networks. By using an additional neural network, an input pattern generation method is provided for increasing the recognition ratio and a successful training. We firstly introduce the structure of the proposed system. Then, the character recognition system is investigated through some experiments.
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To improve equipment throughput and device yield, a malfunction in plasma equipment should be accurately diagnosed. A recognition model for plasma diagnosis was constructed by applying neural network to scanning electron microscope (SEM) image of plasma-etched patterns. The experimental data were collected from a plasma etching of tungsten thin films. Faults in plasma were generated by simulating a variation in process parameters. Feature vectors were obtained by applying direct and wavelet techniques to SEM Images. The wavelet techniques generated three feature vectors composed of detailed components. The diagnosis models constructed were evaluated in terms of the recognition accuracy. The direct technique yielded much smaller recognition accuracy with respect to the wavelet technique. The improvement was about 82%. This demonstrates that the direct method is more effective in constructing a neural network model of SEM profile information.
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To improve device yield and throughput, faults in plasma processing equipment should be quickly and accurately diagnosed. Despite many useful information of ex-situ sensor measurements, their applications to recognize plasma faultshave not been investigated. In this study, a new technique to identify fault causes by recognizing X-ray photoelectron spectroscopy (XPS) using neural network and continuous wavelet transformation (CWT). The presented technique was evaluated with the plasma etch data. A totalof 17 experiments were conducted for model construction. Model performance was investigated from the perspectives of training error, testing error, and recognition accuracy with respect to various thresholds. CWT-based BPNN models demonstrated a higher prediction accuracy of about 26%. Their advantages over pure XPS-based models were conspicuous in all three measures at small networks.
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A new diagnosis model was constructed by combining atomic force microscopy (AFM), wavelet, and neural network. Plasma faults were characterized by filtering AFM-measured etch surface roughness with wavelet. The presented technique was evaluated with the data collected during the etching of silicon oxynitride thin film. A total of 17 etch experiments were conducted. Applying wavelet to AFM, surface roughness was detailed into vertical, horizon%at, and diagonal components. For each component, neural network recognition models were constructed and evaluated. Comparisons revealed that the vertical component-based model yielded about 30% improvement in the recognition accuracy over others. The presented technique was evaluated with the data collected during the etching of silicon oxynitride thin film. A total of 17 etch experiments were conducted
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한국을 비롯한 동양 금석학 정보 인식의 중요한 매체인 탁본을 디지털 영상데이터로 변환하여 영상 특성을 분석하고 수학적 모델을 구현한다. 이를 위해 역사적으로 유명한 대표적 탁본을 포함한 50여개의 탁본영상 샘플을 작위로 선택하였고, 샘플영상 속에 내재되어 있는 영역특성을 중심으로 통계분석을 시도하였다. 탁본 원영상은 흑백의 두 영역으로 분할되는 완벽한 이진영상인데 반하여, 관측영상은 탁본뜨기 수작업과정을 거치면서 영역간 색도의 혼재와 얼룩무늬와 문양이 전체 영상에 분포한다. 본래의 두 영역은 정보영역과 바탕영역으로 구분되나 이들 얼룩무늬들은 또 다른 영역들로 치부되어 주로 바탕영역에 산발적으로 분포되어 영상인식을 저해하는 요인으로 작용한다. 관측영상 속에 내재되어 있는 영역 본래의 특성과 본뜨기 수작업 과정에서 새로 생성되는 영역들 사이의 기하학적 차이를 통계적으로 분류 처리함으로 관측 탁본영상의 영역 특성의 추이를 추론할 수 있다. 분석 결과, 탁본영상은 영역간 극단적인 확률적 차이를 보였으며, 이 양극성은 곧 탁본 원영상의 속성이 수작업과 관측이라는 훼손 과정을 거치면서도 보존됨을 의미한다. 이를 근거로 영역 특성과 훼손 과정을 수학적으로 모델링하였고 정보영역 추출의 일차적 개연성을 제시하였다.
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The Data Matrix of two-dimensional bar codes is a new technology capable of holding relatively large amounts of data compared to the conventional one-dimensional bar code which is just a key that can access detailed information to the host computer database. A secret key is used to prevent a watermark from malicious attacks. We encoded copyright information into a Data Matrix bar code for encoding process and it was spread a pseudo random pattern using owner key. We embedded a randomized watermark into the image using watermark's embedding position, pattern generated with a secret key. The experimental results have shown that the proposed scheme has good quality and is very robust to various attacks, such as JPEG compression and noise. Also the performance of the proposed scheme is verified by comparing the copyright information with the information which is extracted from a bar code scantier.
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We designed an intelligent intrusion detection scheme that works based on target system's operational states and doesn't depend on humans' analysis. As a prior work, we presents a scheme to describe computer system's operational states. For this, Hidden Markov Model is used. As input to modeling, huge amount of system audit trail including data on events occurred in target system connected to network and target system's resource usage monitoring data is used. We can predict system's future state based on current events' sequence using developed model and determine whether it would be in daniel or not.
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Our goal of study is to develop an automatic carkeeping book using ZigBee Protocol. Car owner gets information of car by PDA or Mobile phone through ZigBee wireless communication network, Running distance, tuning information of car, refueling information and repair information are automatically downloaded from Gas-Station or Tuning-shop. Finally, carkeeping book is automatically recorded without typing.
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An automatic remote water measurement system was developed. This system sends automatic remote measured and collected water meters data automatically from the transmitter with CDMA modem through SK-Telecom network The water meter data are received through LAH TCP/IP and displayed as test file on IE(Internet Explorer) window. The existing water meters of mechanical type have so many problems to measure data. The person must visit the location of each water meters and write down the data records manually. In this system the RF module has attached each water meter Client/Server programs are developed by network socket programming.
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A super-regenerative receiver is designed and tested at 433 MHz ISM band, The designed receiver has the data rate of up to 200 kbps and a power consumption of 10 mW. We carried out the system performance test for the TX power of 0.1 mW and 1 m distance. The result of the bit-error rate test shows one bit error among the 4000 bits.
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The peer-to-peer (P2P) systems have Brown significantly over last few years due to their hish potential of sharing various resources. Super-peer based P2P systems have been found very effective by dividing the peers into two layers, SP (Super-Peer) and OP (Ordinary-Peer). In this paper, we present ISP2P (Intelligent Super-peer based P2P system), which allows us to choose the best SP. Through analyzing capacity and similarity between SP and OP, we can help OPs to select the most appropriate SP respectively. Proposed system can improve the performance of the average response time by superior SP, reduce the bandwidth cost by small path length due to content similarity and solve frequent SP replacement problem by considering similarity of user behavior.
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This whitepaper is a research about the sensor network technology which enhance the performance of the blood management system. The problem of measuring and monitoring the real time temperature of a every point in a limited environment let us to develop a system which is able to monitor the temperature of a remote area using multi-hop networking technology. This whitepaper propose the error correction technologies, which were used to eliminate problems that might occur during real tests of the system.
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In this paper we present a new-generation sensor network processor which is not optimized in circuit level, but in system architecture level. The new design build on a conventional processor architecture, improving the design by focusing on application oriented specification, ISA, and micro-architectural optimization that reduce overall design size and advance energy-per-instruction. The design employs harvard architecture, 8-bit data paths, and an compact 19 bit wide RISC ISA. The design also features a unique interrupt handler which offloads periodical monitoring jobs from the main part of CPU. Our most efficient design is capable of running at 300 KHz (0.3 MIPS) while consuming only about few pJ/instruction.
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In this paper, authors realize water AMR(Automatic Meter Reading) network using low power ZigBee protocol included routing ability for improving wireless communitation error detection and network range. ZigBee wireless standard is an important standard of the field related Ubiquitous industry and recently has application to Home-Network. It's special features are to spend low power and to include routing ability each terminator. Because of these features, authors realize water AMR system on Embedded system using ZigBee protocol for applying to transfer data between a water meter and RF module equipped with a water meter in each house.
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Because sensor networks use wireless communication, they are vulnerable to attacks which are more difficult launch in the wired domain. Many wired networks benefit from their inherent physical security properties. It is unlikely that an adversary will dig up the Internet backbone and splice into the line. However, wireless communications are difficult to protect; they are by nature a broadcast medium. In a broadcast medium, adversaries can easily eavesdrop on, intercept, inject, and alter transmitted data. In addition, adversaries are not restricted to using sensor network hardware. We have analyzed the IEEE 802.15.4, ZigBee specification which includes a number of security provisions and options. In this paper, we highlight places where USN security considerations and home network attack scenarios.
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Kang, Jeong-Hoon;Yoo, Jun-Jae;Yoon, Myung-Hyun;Lee, Myung-Soo;Lim, Ho-Jung;Lee, Min-Goo;Jang, Dong-Seop 174
Sensor network supports data delivery from Physical world to cyber space. Sensors get physical events then wireless network transfers sensor data to service server. We use sensor network technology to light control system for intelligent building. In ubiquitous computing environment. wireless sensor network is basic tool for intelligent service. In this paper, we propose intelligent building light control system based on wireless sensor network. It is implemented using previous light control product, can be adopted to present building light system. -
Kang, Jeong-Hoon;Yoo, Jun-Jae;Yoon, Myung-Hun;Lee, Myung-Soo;Lim, Ho-Jung;Lee, Min-Goo;Hwang, Sung-Il 177
This paper presents an analysis architecture of embedded operating systems for wireless sensor network. Wireless multi-hop sensor networks use battery-operated computing and sensing device. We expect sensor networks to be deployed in an ad hoc fashion, with very high energy constraints. These characteristics of multi-hop wireless sensor networks and applications motivate an operating system that is different from traditional embedded operating system. These days new wireless sensor network embedded operating system come out with some advances compared with previous ones. The analysis is focusing on understanding differences of dominant wireless sensor network OS, such as TinyOS 2.0 with TinyOS 1.x. -
This paper presents a SISO nonlinear controller for the power system consisting of a synchronous generator connected to an infinite bus. The proposed controller is based on input-output feedback linearization, with a modified version of the terminal voltage equation used as the output. The resulting closed-loop has no internal dynamics, and thus stability is guaranteed. The controller performance is seen to be effective through simulations.
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To secure abyssal resources, submarine environment should be firstly explored. On that occasion, the withdrawal of the instrument is of importance and the submarine ultrasonic wave should be stably identified regardless submarine environment and passive factor. In the existing control methods, the control informations, received from an observation instrument, are identified used by hardware and repeatedly compared with standard information. Hereupon, a marine observation instrument remote control system using the combination of FSK and ASK that was improved its controllability and movability was presented in this paper. Likewise, the logicality of control algorithm and remote control system were ascertained by experiments.
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This paper analyzes effect of the spinning vehicle on the GPS signal. In rapid spinning vehicles such as missiles and space rockets, carrier phase and frequency depend on the roll rate of the vehicle. It induces phase and frequency modulation caused by the roll rate. The modulated phase and frequency increase dynamic stress error of the tracking loop. Even though higher order tracking loop can remove dynamic stress error, the dynamic stress error can not be remove in this case. In order to analyze the effect of the spinning vehicle on the GPS signal, the experiments are carried out. The experiment results show the modulation of the carrier frequency and phase caused by the roll rate of the spinning vehicle.
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Backlash between meshing gear teeth causes impact, tracking error and undesired vibrations. It is usually minimized by precision gear, spring-loaded anti-backlash gears and precise mechanical adjustment. Although these techniques can help to reduce the backlash gap, its cost is relatively high and performance is limited. And the classic controller is insufficient to control the dynamic system with nonlinearity. For these reason, a fuzzy controller is proposed to compensate the backlash effect at a robot system. The input variables are position error and change in error. The output variable can be defined by input voltage of motor. The performance of a fuzzy controller is verified by comparing with a PID controller. The results show that the undesired vibration is suppressed. And then diminishing the position error is observed.
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In this paper, an interface unit is designed to efficiently monitor transmission data in Controller Area Network(CAN)-based control systems. The CAN uses a serial multi master communication protocol that efficiently supports distributed real-time control with a very high level of data integrity, and communication speeds of up to 1Mbps. The interface unit is composed of a DSP controller which collects data on the CAN bus and transfers data to a personal computer via serial communication to save and display of interesting signals. The experimental system consists of three DSP controllers which represent electronic control units of a vehicle, an interface unit for analysing the data on the bus, and a graphic monitoring program coded on the Windows platform. The validity and the effectiveness of the proposed simple type of CAN interface unit are shown through the experimental results.
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In this paper, three types of power control strategies for controlling a Fuel Cell Hybrid Electric Vehicle(FCHEV) are studied in view of fuel economy. The FCHEV has become one of alternatives for future vehicles since it does emit water only without any exhaust gas while it has a high well-to-wheel efficiency together with an energy saving due to regenerative braking. However, it has also several disadvantages such as the complexity of vehicle system, the increased weight and the extra battery cost. Among various power control strategies, a static power control strategy, a power assist control strategy and a fuzzy logic-based power control strategy are simulated and compared to show the effectiveness of each method.
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This paper describes a new LOS(Line-of-Sight) estimator for BTT missiles. The dynamic models of LOS rate and a seeker are derived. Based on these dynamic models, we design a nonlinear estimator, which takes into account roll motion of BTT missiles and sensor noises. Simulation results show that the LOS rate estimates of the proposed estimator are more accurate than those of the conventional estimator.
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This paper presents realization and evaluation of digital image stabilization for roil motion. The proposed image stabilizer has been implemented on the DSP based hardware and DSP/BIOS software. The proposed image stabilizer is tested in the field. The results show good performance with the sufficient bandwidth. The proposed image stabilizer is combined with mechanical stabilizer and tested to evaluate whether that is feasible for 3-axis stabilization of tank sight system. The results also show food performance.
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Choi, Jung-Sik;Ko, Jae-Sub;Lee, Jung-Ho;Kim, Jong-Kwan;Park, Ki-Tae;Park, Byung-Sang;Chung, Dong-Hwa 207
A number of techniques have been developed for estimation of speed or position in motor drives. The accuracy of these techniques is affected by the variation of motor parameters such as the stator resistance, stator inductance or torque constant. This paper is proposed a neural network based estimator for torque and ststor resistance in IPMSM Drives. The neural weights are initially chosen randomly and a model reference algorithm adjusts those weights to give the optimum estimations. The neural network estimator is able to track the varying parameters quite accurately at different speeds with consistent performance. The neural network parameter estimator has been applied to slot and flux linkage torque ripple minimization of the IPMSM. The validity of the proposed parameter estimator is confirmed by the operating characteristics controlled by neural networks control. -
Lee, Jung-Ho;Choi, Jung-Sik;Ko, Jae-Sub;Kim, Jong-Kwan;Park, Ki-Tae;Park, Byung-Sang;Chung, Dong-Hwa 210
This paper presents Hybrid PI(HBPI) controller of IPMSM drive using fuzzy adaptive mechanism control. In general, PI controller in computer numerically controlled machine process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness, fixed gain PI controller, HBPI controller proposes a new method based self tuning PI controller. HBPI controller is developed to minimize overshoot and settling time following sudden parameter changes such as speed, load torque, inertia, rotor resistance and self inductance. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance. -
A static frequency converter(SFC) in a pumped storage power plant is important equipment for converting electric motor kinetic energy into electric Bower. A SFC monitoring system consists of high voltage thyristor firing equipment, fault detection module, data gathering module, real time data processing equipment and man machine Interface system. This paper describes SFC system overview, developed SFC monitoring system configuration including system characteristics. and successful application result to San-Cheong pumped storage power plant.
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Ko, Jae-Sub;Choi, Jung-Sik;Lee, Jung-Ho;Kim, Jong-Kwan;Park, Ki-Tae;Park, Byung-Sang;Chung, Dong-Hwa 216
The paper is proposed high performance control of induction motor drive with adaptive fuzzy logic controller(AFLC). Also, this paper is proposed speed control of induction motor using AFLC and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The proposed control algorithm is applied to induction motor drive system controlled AFLC and ANN controller. And this paper is proposed the results to verify the effectiveness of the AFLC and ANN controller. -
The recently developed autopilot controller can make the input-output (I/O) dynamic characteristics of the nonlinear missile dynamics linear and independent of flight conditions. However, significant fin actuator dynamics can degenerate the I/O dynamic performance of the overall system. In this paper, we propose a singular perturbation-like method to compensate the effect of significant fin actuator dynamics in nonlinear missile control. The proposed compensation method does not require the time derivatives of fin angles but can maintain the linear I/O dynamic characteristics provided by the recently developed autopilot controller.
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Since most real experimental situations are different from those of the simulations, it is required to modify control rules through experiments owing to uncertainties and unmodeled dynamics of the plant. This paper presents a convenient monitoring system which can display system responses exactly and test the performances of the control system. We design a PID controller using DSP board and propose a monitoring system based on PC and C++ Builder program. With the proposed monitoring system we can easily control the velocity of a DC motor system.
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This note investigates the convergence condition of ADILC (iterative learning control with advanced output data) for nonminimum phase systems. ADILC has simple learning structure including both minimum phase and nonminimum phase systems. However, for nonminimum phase systems, the overall time horizon must be considered in input update law. This makes the dimension of convergence condition matrix large. In this paper, a new sufficient condition is proposed to satisfy the convergence condition. Also, it has been shown that this sufficient condition can be satisfied although it is not full impulse response.
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While trains perform a complete precision stopping control at stop point, it is essential to keep better commuters comfort in prompt. Because a train's brake force tends to increase a brake effort in a low speed and a low brake effort, a brake force in motor cars must be increased to keep better passenger comfort, to control the special braking qua1ities and to prevent the impact of the automatic coupler rather than trailer's, Rail cars must have a special braking process for the train stopping control. In the train stop mode, the train stopping control is designed to start at 20km/h. It starts by Dynamic brake blending, and then finally stops by only the friction. If these process are not exactly activated, the train may fail a complete precision stop. In this report, it studied the electric and friction brake processing during the precious stopping control. To achieve exact test results, the speed reference has to be reduced the calculated difference. In the precision stopping control. the ways of the keeping brake force in motor car was analyzed and some solutions of controling air pressure was brought up by means of direct test in main line, This study was based on line 5 in Seoul Metropolitan subway.
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Arc Fault Current is an electric discharge which is occurred in two opposite electrode. In this paper, arc current control algorithm is designed for the interruption of arc fault current which is occurred in the low voltage network. This arc is one of the main causes of electric fire. General arc current sensor has troubles for detecting arc currents, thus we would like to propose the arc current detection method without current sensor. In this paper, arc discharge currents within power lines are being detected through the arc current control algorithm.
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Because of its long measurement range and ultra-precise resolution. the heterodyne laser interferometer systems are very common in various industry area such as semiconductor manufacturing. However the periodical nonlinearity property caused from frequency mixing is an obstacle to improve the high measurement accuracy in nanometer scale. In this paper to minimize the effect of nonlinearity, we propose an adaptive nonlinearity compensation algorithm. We first compute compensation parameters using least square (LS) with the capacitance displacement sensor as a reference input. We then update the parameters with recursive LS (RLS) while the values are optimized to modify the elliptical phase into circular one. Through comparison with some experimental results of laser system, we demonstrate the effectiveness of our proposed algorithm.
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Nowadays the core control systems are made by multiple redundancy strategy. There are analog excitation systems which have been operating during more than twenty years. This project is aim to retrofit nuclear power plants, also improves the reliance, safety, faculty of nuclear generator excitation system.
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The inspection method, which is used to inspect the electronic system for the control system of the fossil-powered thermal power plant, has the technical restrictions based on its primary application area, whereas the reliability is requested more and more by the plant operators to minimize the shutdown of a plant. This paper reviews the inspection methods currently used by the thermal power plant and how to adopt the condition based maintenance to increase the availability of power plant.
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A closed-loop sensorless stroke control system for a linear compressor has been designed. The motor parameters are identified as a function of the piston position and the motor current. They are stored in ROM table and used later for the accurate estimation of piston position. Also it was attempted to approximate the identified motor parameters to the 2nd-order surface functions. Some experimental results are given in order to show the feasibility of the proposed control schemes for linear compressors.
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This paper is concerned with non-fragile guaranteed cost state feedback controller design algorithm for descriptor systems with time-varying delay and static state feedback controller with multiplicative uncertainty. The considered uncertainties are norm-bounded and time delay is time-varying. Under the condition of controller gain variations, conditions for the existence of controller satisfying asymptotic stability and non-fragility and controller design method are derived via LMI approach. Moreover, the measure of non-fragility and the upper bound to minimize guaranteed cost function are given.
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In this study, a systematic and effective tuning method of the actuator control parameters of the control loading system for aircraft based on control theory is presented. Firstly, to raise the time response of the system, the proportional gain and the integral gain of the velocity control loop is maximized within the range where vibration and noise does not occur. And then the position control loop is composed by getting the transfer function of the control loading system including the velocity control loop. With the root locus of the composed position control loop, the proportional gain of the position control loop that keeps stable transient state and leads good time response of the system is predicted, and the simulations are performed by using the predicted gain. Lastly, the actuator control parameters of actual control loading system are set to the previously obtained gain values. And the experiments to actuate the control loading system are executed. It shows that the tuning method of the actuator control parameter proposed in this study is applied to actual control loading system very well by comparing the results of the experiments with those of the simulations.
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The recent improvement in the performance of digital processor, the application of control technology, which used in the HVDC(High Voltage Direct Current) system with the digital processors, has increased. Having this research development as the basis, this paper presents an achievement of progression by tuning the parameter of PI controller based on Genetic Algorithms(GAs) and by controlling with PI controller with a developed simulator by applying the Matrix operating function, voltage source switching element, modified nodal analysis which can include transformer and the backward Euler which does not create the problem of numerical oscillation. As a result, I expect this development in the simulator HVDC System to bring more application in the field of control technology research with an expanded practicality.
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This paper proposed a platform which includes both Network processor and DSP for flexible IED. The Network processor is one of the Intel's IXP4XX Product Line family and the DSP is one of the TI's C6000 family. An embedded Linux is ported in Network processor so that a DSP program can be downloaded to Network processor through ethernet and then downloaded to DSP. Using this method, various algorithms according to IED can be applied to the Network processor board. Maximum ten ADCs can be connected because there is a CPLD between DSP and ADC. That is, the network processor board which can measure maximum 40 channels is implemented. In DSP program, thread and double buffering methods are used not to miss voltage samples. The Network processor board is verified using a method that eight channel voltage signals converted to digital are transmitted to server through both DSP and IXP425.
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In this paper, we designed a embedded system that will perform a primary role of Tangible Space implementation. This hardware includes function of image capture through camera interface, image process and sending off image information by LAN (local area network) or WLAN(wireless local area network). We define this hardware as a network based Visual Agent Platform for Tangible Space
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Nowadays, technologies such as RFID, sensor network makes our life comfortable more and more. In this paper we propose a wearable computing system for blind and deaf person who can be easily out of sight from our technology. We are making a wearable computing system that is consisted of embedded board to processing data, ultrasonic sensors to get distance data and motors that make vibration as a signal to see the screen for a deaf person. This system offers environmental informations by text and voice. For example, distance data from a obstacle to a person are calculated by data compounding module using sensed ultrasonic reflection time. This data is converted to text or voice by main processing module, and are serviced to a handicapped person. Furthermore we will extend this system using a voice recognition module and text to voice convertor module to help communication among the blind and deaf persons.
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This traveling wave tube amplifier maintenance system was developed for performance of microwave Surveillance radar traveling wave tube amplification parts, and field operation. The Maintenance system is traveling wave tube amplification part RF output waveform measurement and HVPS Voltage adjustment and a maintenance function are offer. The system was developed as an embedded system base it consisted of Linux os which applied a top-down design and visual technique. Therefore change and easy extension of a system. This paper discussed characteristic of maintenance equipment function, composition, and an employment program.
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Recently, flash memories are one of best media to support portable computer's storages in mobile computing environment. The features of non-volatility, low power consumption, and fast access time for read operations are sufficient grounds to support flash memory as major database storage components of portable computers. However, we need to improve traditional Indexing scheme such as B-Tree due to the relatively slow characteristics of flash operation as compared to RAM memory. In order to achieve this goal, we devise a new indexing scheme called F-Tree. F-Tree improves tree operation performance by compressing pointers and keys in tree nodes and rewriting the nodes without a slow erase operation in node insert/delete processes.
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In this paper, we discuss optimal design of Fuzzy Polynomial Neural Networks by means of Genetic Algorithms(GAs) using symbolic coding for non-linear data. One of the major subject of genetic algorithms is representation of chromosomes. The proposed model optimized by the means genetic algorithms which used symbolic code to represent chromosomes. The proposed gFPNN used a triangle and a Gaussian-like membership function in premise part of rules and design the consequent structure by constant and regression polynomial (linear, quadratic and modified quadratic) function between input and output variables. The performance of the proposed model is quantified through experimentation that exploits standard data already used in fuzzy modeling. These results reveal superiority of the proposed networks over the existing fuzzy and neural models.
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In this paper, we introduce a new design of fuzzy neural networks using input-output data information of target system. The proposed fuzzy neural networks is constructed by input-output data information and used the center of data distance by HCM clustering to obtain the characteristics of data. A membership function is defined by HCM clustering and is applied input-output dat included each rule to conclusion polynomial functions. We use triangular membership functions and simplified fuzzy inference, linear fuzzy inference, and modified quadratic fuzzy inference in conclusion. In the networks learning, back propagation algorithm of network is used to update the parameters of the network. The proposed model is evaluated with benchmark data.
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In this paper, a complete solution to fuzzy-model-based digital redesign problem (IDR) for sampled-data nonlinear systems is presented, The term of intelligent digital redesign (IDR) is to design a digital fuzzy controller such that the sampled-data closed-loop fuzzy system is equivalent to the continuous-time closed-loop fuzzy system using the state matching, Its solution is simply obtained by linear transformation, Under the proposed sampled-data controller, the states of the sampled-data and continuous-time fuzzy system are completely matched at every sampling points.
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In this paper, we study an approach to design a self-tuning Fuzzy-PI controller in HVDC(High Voltage Direct Current) system. In the rectifier of conversional HVDC system, turning on, turning off, triggering and protections of thyristors have lots of problems that can make the dynamic instability and cannot damp the dynamic disturbance efficiently. The above problems are solved by adapting Fuzzy-PI controller for the fire angle control of rectifier.[7] The performance of the Fuzzy-PI controller is sensitive to the variety of scaling factors. The design procedure dwells on the use of evolutionary computing(Genetic Algorithms, GAs). Then we can obtain the optimal scaling factors of the Fuzzy-PI controller by Genetic Algorithms. In order to improve Fuzzy-PI controller, we adopt FIS to tune the scaling factors of the Fuzzy-PI controller on line. A comparative study has been performed between Fuzzy-PI and self-tuning Fuzzy-PI controller, to prove the superiority of the proposed scheme.
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UV lamp systems have been used for cleaning of display pannels of TFT LCD or Plasma Display Pannel (PDP). However, the needs for high efficient cleaning and low cost made high voltage plasma cleaning techniques be developed and improved. In this paper, 3kW high voltage plasma power supply system was developed for LCD cleaning. The 3-phase input voltage is rectified and then inverter system is used to make a high frequency pulse train, which is rectified after passing through a high-power transformer. Finally, bi-directional high voltage pulse switching circuits are used to generate the high voltage plasma.
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An efficiency improving method for Uninterruptible Power Supply System(UPS) was developed by using OP-AMP based application circuits such as voltage detection device, current detection device and static switch control device. The efficiency improving algorithm was made by mixing the operating concepts of On-Line type UPS with the operating concepts of Off-Line type UPS. The UPS' inverter does not work if the UPS' output load current is not higher than the low load operating current which is about 0-30(%) of the UPS' output load capacity. The low load operating current is adjustable within the half of the UPS' output load capacity. If the UPS' output load current is rising over than the low load operating current, the UPS' inverter starts working and the inverter output power feeds to the loads of UPS. If UPS' input power breaks out while UPS' inverter does not operate because the load current is low, the inverter starts working within 4(ms) with excessive output voltage which is
${\pm}$ 8(%) of normal UPS' output voltage. Like these. UPS can continuously feeds power to it's load device and reduce power consumptions. -
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Baek, Bum-Hyun;Jee, Dong-Jun;Park, Chan-Jung;Han, Ki-Sung;Lee, Sun-Young;Kim, Kyeong-Tae;Hong, Sung-Won;Park, Hong-Seong 297
Many distributed applications is developed in various environment such as operating system, software platform. So, they exhibit different types of system behavior, status, during the course of their operation. Each such behavior may have different functional and non-functional requirements. Therefore, many distributed application need to fault-tolerance solution. Personal robot provide various service or application. Because personal robot has many application or service, it need to fault-tolerance architecture. A flexible architecture is required to provide dependability. In this paper, it is suggested a fault-tolerant architecture for module-based personal robot with module fault-tolerance, service fault-tolerance. -
Middleware offers function that user application program can transmit data independently of network device. Connection management about network connection of module is important for normal service of module base personal robot. Unpredictable network disconnection is influenced to whole robot performance in module base personal robot. For this, Middleware must be offer two important function. The first is function of error detection and reporting about abnormal network disconnection. Therefore, middleware need method for network error detection and module management to consider special quality that each network device has. The second is the function recovering that makes the regular service possible. When the module closed from connection reconnects, as this service reports connection state of the corresponding module, the personal robot resumes the existing service. In this paper proposed method of network connection management for to support fault tolerant about network error of network module based personal robot.
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In this paper, we present an implementation of the URC (Ubiquitous Robotics Companion) robot S/W platform which is based on the Qplus/Esto. We applied this platform to the NETTORO which is made by hanwool robotics for URC exhibition services and test the URC services on it. We expect this platform to be used in variable URC robots as standard S/W platform for improving the compatibility and reusing the developed components.
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We propose an attention based object recognition system, to recognize object fast and robustly. For this we calculate visual stimulus degrees and make saliency maps. Through this map we find a strongly attentive part of image by stimulus degrees, where local features are extracted to recognize objects.
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This paper aims to provide a way to improve dynamic stability of biped robots against undesirable disturbances. By using an angular velocity sensor on its shoulder, we can make a medium-sized biped robot walk stably against an impulsive disturbance. The measured signal from the sensor in used for compensating the reference angles of ankle, knee, and pelvis joints. An experiment shows that the stability of the robot is much enhanced by using a cheap sensor and simple algorithm. This kind of research helps biped robots walk more stably in real environments.
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Researches on biped robot walking have been mostly focusing on walking on even surfaces. Therefore, robot walking has been only realized on pre-specified spaces with pre-specified movements according to the previous researches. In this paper a walking system for a biped robot using fuzzy system and neural networks to overcome those constraints. The system enables biped walking to be possible in various environments and with more complicated obstacels. For the purpose, a walking robot should recognize its surrounding environment and determine its movement. In the proposed system, a robot dynamically generates its walking trajectories of each joint by using neural networks when facing new obstacle such as stairs, and it maintains its walking stability by using closed loop fuzzy control system which manipulates the waist joints.
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In addition to accurate position and velocity control, force control is necessary for a successful robot operation. In this paper, we have designed a simple robot gripper using a DC motor. For its force control, a current feedback control law is presented without using additional force sensors. Experimental results prove the effectiveness of the proposed control law. A digital controller is also developed with a TMS320LF2406 processor.
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Inaccurate localization exposes a robot to many dangerous conditions. It could make a robot be moved to wrong direction or damaged by collision with surrounding obstacles. There are numerous approaches to self-localization, and there are different modalities as well (vision, laser range finders, ultrasonic sonars). Since sensor information is generally uncertain and contains noise, there are many researches to reduce the noise. But, the correctness is limited because most researches are based on statistical approach. The goal of our research is to measure more exact robot location by matching between built VRML 3D model and real vision image. To determine the position of mobile robot, landmark-localitzation technique has been applied. Landmarks are any detectable structure in the physical environment. Some use vertical lines, others use specially designed markers, In this paper, specially designed markers are used as landmarks. Given known focal length and a single image of three landmarks it is possible to compute the angular separation between the lines of sight of the landmarks. The image-processing and neural network pattern matching techniques are employed to recognize landmarks placed in a robot working environment. After self-localization, the 2D scene of the vision is overlaid with the VRML scene.
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The IEEE 802.15.4 uses a CSMA/CA algorithm on access of media. The CSMA/CA algorithm does Random Backoff before the data is transmitted to avoid collisions. The random backoff is a kind of unavoidable delays and introduces the side effect of energy consumptions. To cope with those problems we propose a new media access algorithm, the Priority Based Ordered Media Access (PBOMA) algorithm, which uses different IFSs. The PBOMA algorithm uses Sampling Rate and Beacon Interval to get a different access probability(or IFS). The access probability is higher, the IFS is shorter. Note that The transfer of urgent data uses tone signal to transmit it immediately. The proposed algorithm is expected to reduce the energy consumptions and the delay.
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CCD형 영상소자는 방사선 피폭 시 표면과 격자내부에 모두 손상을 받게 되며, 감마방사선이나 X선과 같은 고에너지의 이온화 방사선에 노출될 경우 격자 실리콘 내부에 전자-전공쌍(Electron-hole pair, EHP)이 발생된다. 이러한 EHP는 CCD의 순간 출력 광전류로 변환되어 백색 화소 형태의 영상잡음으로 가시화되며, 이 화소 수는 피폭 방사선량에 비례하여 증가하는 특성을 지니고 있다. 따라서 출력 영상정보를 분석하면 조사된 방사선의 양과 특성을 측정할 수 있다. 본 연구에서는 CCD를 이용하여 가상의 방사능 물질 누출 공간에서 방사선원의 방향과 거리정보를 고속으로 탐지하기 위한 장치와 고속 측정 알고리즘을 구현하고 실제 방사선장에서 실증시험을 수행하였다. 방사선 탐지기는 콘형 납 콜리메이터(Collimator)와 가시광 변환용 신틸레이터(CsITl) 및 차폐체로 구성된 센서부와 제어 및 방사광 신호처리를 수행하는 PC부로 구성된다. 감마방사선(
$^{60}Co$ ) 방사선장 실증시험에서 방사선원간 거리 83cm에서 측정된 거리 탐지는 5.3%의 오차로 확인되었다. 이 방사선 탐지기는 임의의 고방사선 누출사고에 대한 초기대응 작업을 수행하기 위한 무인 이동로봇용 방사선 탐지기로 활용이 가능하다. -
In this paper, the cutting qualities by laser dicing and fracture strength of a silicon die is investigated. Laser micromachining is the non-contact process using thermal ablation and evaporation mechanisms. By these mechanisms, debris is generated and stick on the surface of wafer, which is the problem to apply laser dicing to semiconductor manufacture process. Unlike mechanical sawing using diamond blade, chipping on the surface and crack on the back side of wafer isn't made by laser dicing. Die strength by laser dicing is measured via the three-point bend test and is compared with the die strength by mechanical sawing. As a results, die strength by laser dicing shows a decrease of 50% in compared with die strength by mechanical sawing.
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A short distance laser range detector was developed on digital circuit. The circuit changed the analog circuit to digital circuit as possible as. The currently available laser range circuit one uses analog circuit mainly. But this ranger design targeted mass production with digital reporting function. So digital circuits replaced the analog circuit except amplifier and remained minor circuits those are hard to replace with digital circuit. The simulation shows that it is possible to make a reasonable distance measuring circuit on a digital circuit for very low price compare to analog circuit one.
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In this page, we developed the inspection system for automobile parts using the laser vision sensor. Laser vision sensor has gotten 2 dimensions information and third dimension information of laser vision camera using the vision camera. Used JIG and ROBOT for inspection position transfer. Also, computer integration system developed that control system component pal1s and manage data measurement information. Compare sensor measurement result with CAD Data and verified measurement result effectiveness taking advantage of CAD to get information of measurement object.
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One of the important topics concerning the safety of electrical and electronic system is the reliability of the wiring system. The Time-Frequency Domain Reflectometry(TFDR) is a state-of-the-art system for detection and estimation of the fault on a wiring/cable. The purpose of this paper is to implement a Labview based TFDR Real Time system though the instruments of PCI extensions for Instrumentation(PXI). The TFDR Real Time system consists of the five parts: Reference signal design, signal generation, signal acquisition, algorithm execution, results diplay part. In the signal generation and acquisition parts we adopt the Arbitrary Waveform Generator(AWG) and Digital Storage Oscilloscope(DSO) PXI modules which offer commonality, compatibility and easy integration at low cost. And execution of the PXI modules not only is controlled by the Labview programing but also the total system process is executed by the Labview application software.
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This paper proposes a method of container position measurement using automatic landing system that is estimated by a laser range finder. In the most of container position measurement methods, CCD cameras or laser scanners have been used to get the source data. However those sensors are not only weak for disturbances, for examples, the light, fog, and rain, but also the system cost is high. When the spreader arrives the goal position, it is still swung by inertia or by wind effect. In this paper, the spreader swung data have been used to find the container position. The laser range finder is equipped in the front side of spreader. It can measure distance and relative position between spreader and container. This laser range finder can be rotated as desired by a motor. And a tilt sensor is equipped on the spreader to measure spreader sway. We estimate the relative position information between the spreader and a container using the laser range finder and tilt sensor through the geometrical analysis.
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During last years, large investments have been directed to development and research of nano-technological products like semiconductor, display panel, optic-fiber communication components, life technology, and ultra-precision components. All quantitative measurements at nanometre scale should guarantees accurate results and high quality. Laser interferometer is one of most famous nanometre scale devices to be able to measure metre-scale distance with nanometre scale resolution, but it is easily affected by various error causes like geometrical, instrumental and environmental factor. On the other side, capacitive sensor is robust to above error factors, but it is able to measure relatively shorter distance, under
$100{\mu}m$ , than laser interferometer. New error correction method for laser interferometry using capacitive sensor will be introduced in this paper. -
An interferometer is the unique measurement device that can measure the range up to a few meters with sub-nano accuracy and this characteristic makes it as the important sensing device for the emerging nano-mechatronics technologies. The interferometer, however, is very sensitive to the environments such as temperature, humidity, sound noises, vibrations and air turbulences and these factors result in a few hundred nano meter errors. There have been many efforts to reduce these environmental errors. These efforts are mainly focused in reducing the errors inside the interferometer and improving the environments physically. The purpose of this paper is to improve accuracy of the interferometer by using measurement noise models and the Kalman filter algorithm.
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Currently the indication method of the traffic signal light which is established in our country displays each "red, yellow, green" using the brightness LED signal light. In this paper, one LED circular arrangement replaces the Current indication method of the traffic signal light using two color LED. Also the blinking signal function of present time uses the MCU of AVR series and it is embodied with magnification and abridgment of the circular arrangement for recognizing easily far away. The signal light indication method which is proposed will be able to substitute the signal light of 3 colors with 1 signal light with economic profit presented the reform measure of energy efficiency improvement together.