• Title/Summary/Keyword: complex signals

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A machine learning informed prediction of severe accident progressions in nuclear power plants

  • JinHo Song;SungJoong Kim
    • Nuclear Engineering and Technology
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    • v.56 no.6
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    • pp.2266-2273
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    • 2024
  • A machine learning platform is proposed for the diagnosis of a severe accident progression in a nuclear power plant. To predict the key parameters for accident management including lost signals, a long short term memory (LSTM) network is proposed, where multiple accident scenarios are used for training. Training and test data were produced by MELCOR simulation of the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident at unit 3. Feature variables were selected among plant parameters, where the importance ranking was determined by a recursive feature elimination technique using RandomForestRegressor. To answer the question of whether a reduced order ML model could predict the complex transient response, we performed a systematic sensitivity study for the choices of target variables, the combination of training and test data, the number of feature variables, and the number of neurons to evaluate the performance of the proposed ML platform. The number of sensitivity cases was chosen to guarantee a 95 % tolerance limit with a 95 % confidence level based on Wilks' formula to quantify the uncertainty of predictions. The results of investigations indicate that the proposed ML platform consistently predicts the target variable. The median and mean predictions were close to the true value.

Effects of Prenatal and Restraint Stress on Astrocytes of Amygdala Complex of Rat: I. Effects on the Astrocytic Cell Body (출생 전 스트레스와 감금 스트레스가 흰쥐 편도복합체 별아교세포에 미치는 영향: I. 별아교세포의 세포체에 미치는 영향)

  • Lee, Ji-Yong;Choi, Byoung-Young;Kim, Dong-Heui;Jung, Won-Sug;Cho, Byung-Pil;Yang, Young-Chul
    • Applied Microscopy
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    • v.38 no.3
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    • pp.213-219
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    • 2008
  • The plasticity of nervous system is generated not only due to changes in neurons but also due to changes in neuroglial cells. Astrocyte is important for maintaining the normal brain function and controlling the neuronal functions. The amygdala receives an array of important sensory information of danger signals. This information is further transduced and integrated to produce the highly adaptive emotion, fear. In this study, morphometric changes in the cell bodies of astrocytes in the amygdala, induced by prenatal stress and restraint stress were examined. For this purpose. rats were classified into 4 groups; control group (CON), only restraint-stressed (starting on P90 for 3 days) group (CONR), prenatally-stressed group (PNS), and prenatally and restraint (on P90 for 3 days) stressed group (PNSR). Astrocytes were verified with anti-GFAP immunohistochemistry, counter stained with methylene blue/azure II and were examined using the Neurolucida. Results showed that astrocytes in the amygdala of PNS rats had significantly larger cell bodies than did CON rats and this was enhanced further by restraint stress. Thus this data showed that hypertrophy of the astrocytic cell bodies of amygdala complex is induced by prenatal and restraint stress.

Human Walking Detection and Background Noise Classification by Deep Neural Networks for Doppler Radars (사람 걸음 탐지 및 배경잡음 분류 처리를 위한 도플러 레이다용 딥뉴럴네트워크)

  • Kwon, Jihoon;Ha, Seoung-Jae;Kwak, Nojun
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.29 no.7
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    • pp.550-559
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    • 2018
  • The effectiveness of deep neural networks (DNNs) for detection and classification of micro-Doppler signals generated by human walking and background noise sources is investigated. Previous research included a complex process for extracting meaningful features that directly affect classifier performance, and this feature extraction is based on experiences and statistical analysis. However, because a DNN gradually reconstructs and generates features through a process of passing layers in a network, the preprocess for feature extraction is not required. Therefore, binary classifiers and multiclass classifiers were designed and analyzed in which multilayer perceptrons (MLPs) and DNNs were applied, and the effectiveness of DNNs for recognizing micro-Doppler signals was demonstrated. Experimental results showed that, in the case of MLPs, the classification accuracies of the binary classifier and the multiclass classifier were 90.3% and 86.1%, respectively, for the test dataset. In the case of DNNs, the classification accuracies of the binary classifier and the multiclass classifier were 97.3% and 96.1%, respectively, for the test dataset.

Improvement of the Accuracy of Wrist Noninvasive Blood Pressure Measurement Using Multiple Bio-signals (다중 생체 신호를 통한 손목 혈압 측정의 정확도 향상)

  • Jung, Woon-Mo;Sim, Myeong-Heon;Jung, Sang-O;Kim, Min-Yong;Yoon, Chan-Sol;Jung, In-Chol;Yoon, Hyung-Ro
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.60 no.8
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    • pp.1606-1616
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    • 2011
  • The blood pressure measuring equipment, which is being supplied and used most widely by being recognized convenience and accuracy now generally, is oscillometric blood pressure monitor. However, a change in blood pressure is basically influenced by diverse elements such as each individual's physiological status and physical condition. Thus, the measurement of blood pressure, which used single element called oscillation in blood pressure of being conveyed to cuff, is not considered on physiological elements such as cardiovascular system status and blood vessel stiffness index, and on external elements, thereby being quite in error. Accordingly, this study detected diverse bio-signals and body informations in each individual as the measurement subject such as ECG, PPG, and Korotkoff Sound in order to enhance convenience and accuracy of measuring blood pressure in the complex measurement equipment, thereby having extracted regression method for compensation in error of oscillometric blood pressure measurement on the wrist, and having improved accuracy of measuring blood pressure. To verify a method of improving accuracy, the blood pressure value in each of SBP, DBP, MAP was acquired through 4-stage experimental procedure targeting totally 51 subjects. Prior to experiment, the subjects were divided into two groups such as the experimental group for extracting regression method and the control group for verifying regression method. Its error was analyzed by comparing the reference blood pressure value, which was obtained through the auscultatory method, and the oscillometric blood pressure value on the wrist. To reduce the detected error, the blood pressure compensation regression method was calculated through multiple linear regression analysis on elements of blood pressure, individual body information, PTT, HR, K-Sound PSD change. Verification was carried out on improving significance and accuracy by applying the regression method to the data of control group. In the experimental results, as a result of confirming error on the reference blood pressure value in SBP, DBP, and MAP, which were acquired through applying regression method, the results of $-0.47{\pm}7.45$ mmHg, $-0.23{\pm}7.13$ mmHg, $0.06{\pm}6.39$ mmHg could be obtained. This is not only the numerical value of satisfying the sphygmomanometer reference of AAMI, but also shows the lower result than the numerical value in SBP : $-2.5{\pm}12.2$ mmHg, DBP : $-7.5{\pm}8.4$ mmHg, which is the mean error in the experimental results of Brram's research for verifying accuracy of Omron RX-M, which shows relatively high accuracy among wrist sphygmomanometers. Thus, the blood pressure compensation could be confirmed to be made within significant level.

The Development of Neural Network Model to Improve the Reliability of the Demand/Effort Model for Evaluating Highway Safety (도로위험도를 평가하는 요구/노력모형의 신뢰도 향상을 위한 신경망 모형 개발)

  • Jeong, Bong-Jo;Gang, Jae-Su;Jang, Myeong-Sun
    • Journal of Korean Society of Transportation
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    • v.27 no.2
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    • pp.95-105
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    • 2009
  • Traffic accidents on highways are likely to happen when there is an imbalance in the complex relationships among key elements such as road geometries, driver related factors, and mechanical performances. The Demand-Effort Model (DEM), which evaluates highway safety, can be explained by the imbalance, which occurs when the level of demand of the driver's attention to the road environment exceeds that of the response from the driver. This study suggests a new model that improves the reliability of the current DEM through the reinterpretation on the physiological signals with the help of the Neural Network Model (NNM). The data were collected from 149 subjects, who drove a test vehicle on the Yongdong, Honam, and Seohaean Expressways in Korea. Three important results could be drawn from the recursive tests as follows; (1) Only 5 out of 10 parameters on the physiological signals which are currently used were proven to be meaningful through the Normality Test, Cluster Analysis, and Mann-Whitney Analysis. (2) The revised DEM, which internally uses the NNM, showed more reliable results than existing DEM. Group 1, which is based on the new DEM showed 80.0% of accuracy in measuring the level of driver's efforts, however, that of Group 2 based on the current DEM was 74.3%. (3) Field tests on the Honam Expressway showed lower 'type II error' with the new DEM (40.5%) than the old DEM (58.8%). The DEM is designed as a quick and easy way to determine highway safety prior to the minute road safety audit (RSA) by a professional audit team. Then a new DEM, which is based on the NNM, needs to be considered since it showed higher reliability and lower error.

Fabrication of IMT-2000 Linear Power Amplifier using Current Control Adaptation Method in Signal Cancelling Loop (신호 제거 궤환부의 전류 제어 적응형 알고리즘을 이용한 IMT-2000용 선형화 증폭기 제작)

  • 오인열;이창희;정기혁;조진용;라극한
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.40 no.1
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    • pp.24-36
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    • 2003
  • The digital mobile communication will be developed till getting multimedia service in anyone, any where, any time. Theses requiring items are going to be come true via IMT-2000 system. Transmitting signal bandwidth of IMT-2000 system is 3 times as large as IS-95 system. That is mean peak to average of signal is higher than IS-95A system. So we have to design it carefully not to effect in adjacent channel. HPA(High Power Amplifier) located in the end point of system is operated in 1-㏈ compression point(Pl㏈), then it generates 3rd and 5th inter modulation signals. Theses signals affect at adjacent channel and RF signal is distorted by compressed signal which is operated near by Pl㏈ point. Then the most important design factor is how we make HPA having high linearity. Feedback, Pre-distorter and Feed-forward methods are presented to solve theses problems. Feed-forward of these methods is having excellent improving capacity, but composed with complex structure. Generally, Linearity and Efficiency in power amplifier operate in the contrary, then it is difficult for us to find optimal operating point. In this paper we applied algorithm which searches optimal point of linear characteristics, which is key in Power Amplifier, using minimum current point of error amplifier in 1st loop. And we made 2nd loop compose with new structure. We confirmed fabricated LPA is operated by having high linearity and minimum current condition with ACPR of -26 ㏈m max. @ 30㎑ BW in 3.515㎒ and ACLR of 48 ㏈c max@${\pm}$㎒ from 1W to 40W.

Design of 3-bit Arbitrary Logic Circuit based on Single Layer Magnetic-Tunnel-Junction Elements (단층 입력 구조의 Magnetic-Tunnel-Junction 소자를 이용한 임의의 3비트 논리회로 구현을 위한 자기논리 회로 설계)

  • Lee, Hyun-Joo;Kim, So-Jeong;Lee, Seung-Yeon;Lee, Seung-Jun;Shin, Hyung-Soon
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.45 no.12
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    • pp.1-7
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    • 2008
  • Magnetic Tunneling Junction (MTJ) has been used as a nonvolatile universal storage element mainly in memory technology. However, according to several recent studies, magneto-logic using MTJ elements show much potential in substitution for the transistor-based logic device. Magneto-logic based on MTJ can maintain the data during the power-off mode, since an MTJ element can store the result data in itself. Moreover, just by changing input signals, the full logic functions can be realized. Because of its programmability, it can embody the reconfigurable magneto-logic circuit in the rigid physical architecture. In this paper, we propose a novel 3-bit arbitrary magneto-logic circuit beyond the simple combinational logic or the short sequential one. We design the 3-bit magneto-logic which has the most complexity using MTJ elements and verify its functionality. The simulation results are presented with the HSPICE macro-model of MTJ that we have developed in our previous work. This novel magneto-logic based on MTJ can realize the most complex logic function. What is more, 3-bit arbitrary logic operations can be implemented by changing gate signals of the current drivel circuit.

High Frequency Noise Reduction in ECG using a Time-Varying Variable Cutoff Frequency Lowpass Filter (시변 가변차단주파수 저역통과필터를 이용한 심전도 고주파 잡음의 제거)

  • 최안식;우응제;박승훈;윤영로
    • Journal of Biomedical Engineering Research
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    • v.25 no.2
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    • pp.137-144
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    • 2004
  • ECG signals are often contaminated with high-frequency noise such as muscle artifact, power line interference, and others. In the ECG signal processing, especially during a pre-processing stage, numerous noise removal techniques have been used to reduce these high-frequency noise without much distorting the original signal. This paper proposes a new type of digital filter with a continuously variable cutoff frequency to improve the signal quality This filter consists of a cutoff frequency controller (CFC) and variable cutoff frequency lowpass filter (VCF-LPF). From the noisy input ECG signal, CFC produces a cutoff frequency control signal using the signal slew rate. We implemented VCF-LPF based on two new filter design methods called convex combination filter (CCF) and weight interpolation fille. (WIF). These two methods allow us to change the cutoff frequency of a lowpass filter In an arbitrary fine step. VCF-LPF shows an excellent noise reduction capability for the entire time segment of ECG excluding the rising and falling edge of a very sharp QRS complex. We found VCF-LPF very useful and practical for better signal visualization and probably for better ECG interpretation. We expect this new digital filter will find its applications especially in a home health management system where the measured ECG signals are easily contaminated with high-frequency noises .

Study on Improving Maritime Distress Received & Response System (해양 조난수신 대응체계 개선방안에 관한 연구)

  • Park, Sang-Chun;Kim, Young-Sup
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2015.10a
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    • pp.87-90
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    • 2015
  • Equipments that can transmit maritime distress signals in accordance to Global Maritime Distress Safety System are the followings: A1 water(Very High Frequency, SART), A2 water(MF/HF Radio Equipment), A3 water(INMARSAT), A4 water(Emergency Position Indicating Radio Beacon). Institutions with the capacity to receive distress signals are Korea Coast Guard affiliated radio stations, patrol ships, Rescue Coordination centers, Vessel Traffic centers, Complex problems regarding repetitive distress alarms, inaccurate statistics, multiple control towers are existent. Consequently, effective measurement to resolve dispersed operating maritime distress signal system are in time of need. Moreover, current KCG Headquarter is considering to integrate five distress radio stations dispersed across nation into a single international safety communication center. The integration of radio stations are efficient in terms of information coordination between nations, however, it cannot support efficient response to real-time maritime incident. Therefore, in this study, a new system that can rapidly response to real-time maritime incident will be proposed.

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Optimum Rake Processing for Multipath Fading in Direct-Sequence Spread-Spectrum Communication Systems (주파수대역 직접확산 통신시스템에서 다중경로 페이딩 보상을 위한 최적 레이크 신호처리에 관한 연구)

  • 장원석;이재천
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.28 no.10C
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    • pp.995-1006
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    • 2003
  • It is well know that in the wireless communication systems the transmitted signals can suffer from multipath fading due to the wave propagation characteristics and the obstacles over the paths, resulting in serious reduction in the power of the received signals. However, it is possible to take advantage of the inherent diversity imposed in the multipath reception if the underlying channel can be properly estimated. One of the diversity reception methods in this case is Rake processing. In this paper we study the Rake receivers for the direct-sequence spread-spectrum communication systems utilizing PN (pseudo noise) sequences to achieve spread spectrum. A conventional Rake receiver can use the finite-duration impulse (FIR) filter followed by the PN sequence demodulator, where the FIR filter coefficients are the reverse-ordered complex conjugate values of the fading channel impulse response estimates. Here, we propose a new Rake processing method by replacing the aforementioned PN code sequence with a new set of optimum demodulator coefficients. More specifically, the concept of the new optimum Rake processing is first introduced and then the optimum demodulator coefficients are theoretically derived. The performance obtained using the new optimum Rake processing is also calculated. The analytical results are verified by computer simulation. As a result, it is shown that the new optimum Rake processing method improves the MSE performance more than 10 dB over the conventional one using the fixed PN sequence demodulator. It is also shown that the new optimum Rake processing method improves the MSE performance about 10 dB over the Adaptive Correlator that performs the combining of the multipath components and PN demodulation concurrently. And finally, the MSE performance of the optimum Rake demodulator is very close to the MSE performance of OPSK demodulator under the AWGN channel.