• Journal of Positioning, Navigation, and Timing
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• 제9권4호
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• pp.337-345
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• 2020

In this paper, an efficient signal tracking method to simultaneously track both GPS L1 C/A and Galileo E1B CBOC(6,1,1/11) using a low cost GPU is proposed. In the existing method that each GNSS signal is processed within 1 ms, more than 2 ms processing time is required in GPU to process 4 ms CBOC signal. It means that real time operation is possible if only Galileo E1B CBOC signal is concerned. But when both GPS C/A and Galileo CBOC is required, it cannot process GPS C/A signal in real time. To process 1 ms GPS C/A and 4 ms Galileo CBOC signal in real time, 4 ms Galileo CBOC signal is divided into 4 by 1 ms signal block in the proposed method. Specially, a buffer that simultaneously manages 1 ms and 4 ms signals is designed. In addition, a module that accumulates the 1 ms correlation value of the Galileo CBOC by 4 ms and passes it to the PLL and DLL is implemented. The operation and performance are evaluated with real measurements in the GPU based SDR. The experimental results show that tracking of more than 16 satellites of GPS C/A and Galileo E1B is possible using the proposed method.

• 전자공학회논문지A
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• 제28A권1호
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• pp.46-51
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• 1991

The new signal process circuit using ISFETs as two input devices of a MOS differential amplifier stage for application to a ISFET biosensor was developed and its operational characteristics simulated. For a single chip integration of ISFETs, developed signal process circuit and metal reference electrode, serial studies including process development and chip layout was carried out.

• Asian Pacific Journal of Cancer Prevention
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• 제15권22호
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• pp.9791-9795
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• 2014

To study the gene expression change and possible signal pathway during androgen-dependent prostate cancer (ADPC) becoming androgen-independent prostate cancer (AIPC), an LNCaP cell model of AIPC was established using flutamide in combination with androgen-free environment inducement, and differential expression genes were screened by microarray. Then the biological process, molecular function and KEGG pathway of differential expression genes are analyzed by Molecule Annotation System (MAS). By comparison of 12,207 expression genes, 347 expression genes were acquired, of which 156 were up-ragulated and 191 down-regulated. After analyzing the biological process and molecule function of differential expression genes, these genes are found to play crucial roles in cell proliferation, differntiation, cell cycle control, protein metabolism and modification and other biological process, serve as signal molecules, enzymes, peptide hormones, cytokines, cytoskeletal proteins and adhesion molecules. The analysis of KEGG show that the relevant genes of AIPC transformation participate in glutathione metabolism, cell cycle, P53 signal pathway, cytochrome P450 metabolism, Hedgehog signal pathway, MAPK signal pathway, adipocytokines signal pathway, PPAR signal pathway, TGF-${\beta}$ signal pathway and JAK-STAT signal pathway. In conclusion, during the process of ADPC becoming AIPC, it is not only one specific gene or pathway, but multiple genes and pathways that change. The findings above lay the foundation for study of AIPC mechanism and development of AIPC targeting drugs.

• 제어로봇시스템학회논문지
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• 제4권4호
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• pp.506-516
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• 1998

In this paper, an algorithm is proposed to detect the malfunction of plasma-etching characteristics using EPD signal trajectories. EPD signal trajectories offer many information on plasma-etching process state, so they must be considered as the most important data sets to predict the wafer states in plasma-etching process. A recent work has shown that EPD signal trajectories were successfully incorporated into process modeling through critical parameter extraction, but this method consumes much effort and time. So Principal component analysis(PCA) can be applied. PCA is the linear transformation algorithm which converts correlated high-dimensional data sets to uncorrelated low-dimensional data sets. Based on this reason neural network model can improve its performance and convergence speed when it uses the features which are extracted from raw EPD signals by PCA. Wafer-state variables, Critical Dimension(CD) and uniformity can be estimated by simulation using neural network model into which EPD signals are incorporated. After CD and uniformity values are predicted, proposed algorithm determines whether malfunction values are produced or not. If malfunction values arise, the etching process is stopped immediately. As a result, through simulation, we can keep the abnormal state of etching process from propagating into the next run. All the procedures of this algorithm can be performed on-line, i.e. wafer to wafer.

• 한국통신학회:학술대회논문집
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• 한국통신학회 2004년도 하계종합학술발표회논문초록집
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• pp.235-235
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• 2004

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2001년도 춘계학술대회 논문집(한국공작기계학회)
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• pp.192-196
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• 2001

This work describes the modeling of cutting process for feedback control based on signal processing in end-milling. Here, cutting force is used to design control model by a variety of schemes which are moving average, ensemble average, peak value, root mean square and analog low-pass filtering. It is expected that each model offers its own peculiar advantage in following cutting force control.

• IEIE Transactions on Smart Processing and Computing
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• 제3권6호
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• pp.372-381
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• 2014

This study examined a radar signal active cancelation technique, which is a theoretical way of achieving stealth by employing a baseband process that involves sampling the incoming hostile radar signal, analyzing its characteristics, and generating countermeasure signals to cancel out the linear-FM signal of the hostile radar signal reflected from the airborne target. To successfully perform an active cancelation, the effects of errors in the countermeasure signal were first analyzed. To generate the countermeasure signal that requires very fast and accurate processing, the down-sampling technique with the suboptimal maximum likelihood estimation (sMLE) scheme was proposed to improve the speed of the estimation process while preserving the estimation accuracy. The simulation results showed that the proposed down-sampling technique using a 2048 FFT size yields substantial power reduction despite its small FFT size and exhibits similar performance to the sMLE scheme using the 32768 FFT size.

• 소성∙가공
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• 제18권2호
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• pp.144-149
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• 2009

Recently, the monitoring technology of machining process is very important to improve productivity and quality in manufacturing filed. Such monitoring technology has been performed to measurement using vibration signal, acoustic emission signal and tool dynamometer. However, micro machining is limited small-scale parts machining because micro tool is very small and weakness to generate signal in micro machining process. Therefore, this study has efficient sensing technology for real monitoring system in micro machine that is proposed to supplement a disadvantage of single-sensor by multi sensor. From experimental result, it was evaluated tool wear and cutting situation according to repetitive slot cutting condition and changing cutting condition, and it was performed monitoring spindle rpm and condition according to compare acceleration signal with current signal.

• 대한의용생체공학회:의공학회지
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• 제13권1호
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• pp.1-8
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• 1992

In the field of prosthesis arm control, the pattern classification of the EMG signal is a required basis process and also the estimation of force from collected EMG data is another necessary duty. But unfortunately, what we've got is not real force but an EMG signal which contains the information of force. This is the reason why we estimate the force from the EMG data. In this paper, when we handle the EMG signal to estimate the force, spatial prewhitening process is applied from which the spatial correlation between the channels are removed. And after the orthogonal transformation which is used in the force estimation process, the transformed signal Is inputed into the probabilistic model for pattern classification. To verify the different results of the multiple channels, SNR(signal to noise ratio) function is introduced.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 추계학술대회 논문집
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• pp.315-318
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• 1997

In terms of productivity, the speed of machining process has been increasing in most of engineering part. But the tapping process does not reach at enough level compared with other machining processes because of its complicate cutting mechanism. In the high speed tapping process, the one of important elements is tool monitoring system to prevent tool breakage. This paper describes tool monitoring system by acoustic emission(AE) in the tapping process. We used 2 types of AE sensors in this test. The one is commercial sensor which is used in other machining monitoring system like polishing and the other is a self-fabricated sensor for this test. In this test we purpose to find out the frequency of AE signal in tapping process and verify the possibility of applying AE sensor in in-process tapping monitoring system. Also grasp of characteristic of tapping process by AE signal is handled.