• Current Optics and Photonics
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• v.5 no.4
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• pp.421-430
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• 2021

The multifocal multiphoton microscopy (MMM) enables high-speed imaging by the concurrent scanning and detection of multiple foci generated by lenslet array or diffractive optical element. The MMM system mainly suffers from crosstalk generated by scattered emission photons that form ghost images among adjacent channels. The ghost image which is a duplicate of the image acquired in sub-images significantly degrades overall image quality. To eliminate the ghost image, the photon reassignment method was established using maximum likelihood estimation. However, this post-processing method generally takes a longer time than image acquisition. In this regard, we propose a novel strategy for rapid noise reduction in the MMM system based upon Monte-Carlo (MC) simulation. Ballistic signal, scattering signal, and scattering noise of each channel are quantified in terms of photon distribution launched in tissue model based on MC simulation. From the analysis of photon distribution, we successfully eliminated the ghost images in the MMM sub-images. If the priori MC simulation under a certain optical condition is established at once, our simple, but robust post-processing technique will continuously provide the noise-reduced images, while significantly reducing the computational cost.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.1
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• pp.102-107
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• 2019

This paper proposes a method to improve the mass spectral detection performance of the residual gas analyzer. By improving the mode estimation method for setting the threshold value and improving the additive noise elimination method, it is possible to detect mass spectrums having low peak values of the threshold level difficult to distinguish from noise. Ion signal blocks for each mass index with noise removed by the improved method are effective for eliminating invalid ion signals based on the linear and quadratic fittings. The mass spectrum can be obtained from the quadratic fitted curves for the reconstructed ion signal block using only the valid ion signals. In addition, the resolution of the mass spectrum can be improved by correcting the error caused by the shift of the spectral peak position. To verify the performance of the proposed method, computer simulations were performed using real ion signals obtained from the residual gas analysis system under development. The simulation results show that the proposed method is valid.

• Journal of Radiation Protection and Research
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• v.46 no.4
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• pp.160-169
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• 2021

Background: Dual-energy X-ray images (DEI) can distinguish or improve materials of interest in a two-dimensional radiographic image, by combining two images obtained from separate low and high energies. The concepts of DEI performance describing the performance of double-exposure DEI systems in the Fourier domain been previously introduced, however, the performance of double-exposure DEI itself in terms of various parameters, has not been reported. Materials and Methods: To investigate the DEI performance, signal-difference-to-noise ratio, modulation transfer function, noise power spectrum, and noise equivalent quanta were used. Low- and high-energy were 60 and 130 kVp with 0.01-0.09 mGy, respectively. The energy-separation filter material and its thicknesses were tin (Sn) and 0.0-1.0 mm, respectively. Noise-reduction (NR) filtering used the Gaussian-filter NR, median-filter NR, and anti-correlated NR. Results and Discussion: DEI performance was affected by Sn-filter thickness, weighting factor, and dose allocation. All NR filtering successfully reduced noise, when compared with the dual-energy (DE) images without any NR filtering. Conclusion: The results indicated the significance of investigating, and evaluating suitable DEI performance, for DE images in chest radiography applications. Additionally, all the NR filtering methods were effective at reducing noise in the resultant DE images.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.1
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• pp.48-56
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• 2023

This paper implements many-to-many communication between users and develops a multi-functional smart helmet for worker protection and environmental safety in the shipbuilding and shipping industry. First, the communication situation is recorded in the field to perform signal processing for noise that interferes with communication. Then, it deals with the contents of developing smart helmets, data acquisition, algorithms, and simulations. The simulation results analyzed by applying the adaptive algorithm are shown, and their usefulness is confirmed. In conclusion, looking at the optimization process for the convergence factor of the Least Mean Square and Filtered-x Least Mean Square Adaptation Algorithm was possible. It is thought that it has laid the foundation for implementing many-to-many communication, the function of smart helmets that reduces or removes various noises at the shipyard in the future.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.1
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• pp.83-91
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• 2014

The passive UHF RFID tags for item-level tagging are now explosively used in the supply chain and retail applications as they have several advantages, the two most relevant are cost and a longer read range. However, the signal interference problem between RFID tags and smart devices in real world is expected according to the smart-phone and tablet market growth together. The performance of RFID tags can be significantly less. The popular examples are the read-success rates and read range reduction. Especially, KT Corp. recently emphasized the serious signal interference at 900 MHz of LTE and old RFID frequencies through their public demonstration. By popular demands, this paper suggests the interference tolerance measurement method between the passive UHF RFID tag and the transmitted signal from a smart device. In addition, we selected three passive UHF RFID tags(Inlay) available on the market and quantitatively evaluated read range reduction results by interference signals using the PCR(Performance Change Rates) index. As a result, the LTE system is about three times as effective as the WCDMA system in terms of interference effects, and the read range performance of two RFID tags about 60 % drop.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.11
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• pp.1307-1314
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• 2012

To reduce the effects of clutters with subsurface inhomogenities in ground-penetrating radar(GPR) images, an eigenimage based signal-processing technique is presented. If the conventional eigenimage filtering technique is applied to B-scan images of a GPR survey, relatively homogeneous clutters such as antenna ringing, direct coupling between transmitting and receiving antennas, and soil-surface reflection, can be removed sufficiently. However, since random clutters of subsurface inhomogenities still remain in the images, target signals are distorted and obscured by the clutters. According to a comparison of the eigenimage filtering results, there is different coherency between subsurface clutters and target signals. To reinforce the pixels with high coherency and reduce the pixels with low coherency, the pixel-by-pixel geometric-mean process after the eigenimage filtering is proposed here. For the validity of the proposed approach, GPR survey for detection of a metal target in a randomly inhomogeneous soil is numerically simulated by using a random media generation technique and the finite-difference time-domain(FDTD) method. And the proposed signal processing is applied to the B-scan data of the GPR survey. We show that the proposed approach provides sufficient enhancement of target signals as well as remarkable reduction of subsurface inhomogeneous clutters in comparison with the conventional eigenimage filtering.

• Asian Journal of Atmospheric Environment
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• v.8 no.3
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• pp.162-174
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• 2014

An abnormal decrease in ozonesonde sensor signal occurred during air-pollution study campaigns in November 2011 and March 2012 in Mexico City Metropolitan Area (MCMA). Sharp drops in sensor signal around 5 km above sea level and above were observed in November 2011, and a reduction of signal over a broad range of altitude was observed in the convective boundary layer in March 2012. Circumstantial evidence indicated that $SO_2$ gas interfered with the electrochemical concentration cell (ECC) ozone sensors in the ozonesonde and that this interference was the cause of the reduced sensor signal output. The sharp drops in November 2011 were attributed to the $SO_2$ plume from Popocat$\acute{e}$petl volcano southeast of MCMA. Experiments on the response of the ECC sensor to representative atmospheric trace gases showed that only $SO_2$ could cause the observed abrupt drops in sensor signal. The vertical profile of the plume reproduced by a Lagrangian particle diffusion simulation supported this finding. A near-ground reduction in the sensor signal in March 2012 was attributed to an $SO_2$ plume from the Tula industrial complex north-west of MCMA. Before and at the time of ozonesonde launch, intermittent high $SO_2$ concentrations were recorded at ground-level monitoring stations north of MCMA. The difference between the $O_3$ concentration measured by the ozonesonde and that recorded by a UV-based $O_3$ monitor was consistent with the $SO_2$ concentration recorded by a UV-based monitor on the ground. The vertical profiles of the plumes estimated by Lagrangian particle diffusion simulation agreed fairly well with the observed profile. Statistical analysis of the wind field in MCMA revealed that the effect Popocat$\acute{e}$petl was most likely to have occurred from June to October, whereas the effect of the industries north of MCMA, including the Tula complex, was predicted to occur throughout the year.

• The Journal of the Acoustical Society of Korea
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• v.41 no.5
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• pp.492-499
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• 2022

This study experimentally investigates the effect of dimensionality reduction of vibration signal on fault diagnosis of a marine engine. By using the principal component analysis, a vibration signal having the dimension of 513 is converted into a low-dimensional signal having the dimension of 1 to 15, and the variation in fault diagnosis accuracy according to the dimensionality change is observed. The vibration signal measured from a full-scale marine generator diesel engine is used, and the contribution of the dimension-reduced signal is quantitatively evaluated using two kinds of variable importance analysis algorithms which are the integrated gradients and the feature permutation methods. As a result of experimental data analysis, the accuracy of the fault diagnosis is shown to improve as the number of dimensions used increases, and when the dimension approaches 10, near-perfect fault classification accuracy is achieved. This shows that the dimension of the vibration signal can be considerably reduced without degrading fault diagnosis accuracy. In the variable importance analysis, the dimension-reduced principal components show higher contribution than the conventional statistical features, which supports the effectiveness of the dimension-reduced signals on fault diagnosis.

• The Journal of the Acoustical Society of Korea
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• v.16 no.4
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• pp.101-105
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• 1997

The active noise control method that was developed for long duct has some problems to be applied for short duct. To overcome this problem, we apply the SISO(Single Input Single Output) algorithm for the active noise control of short duct using zero acoustic impedance boundary. The SISO algorithm can input noise signal and error signal with one microphone simultaneously. The real-time controller was implemented using TMS320E25 DSP(Digital Signal Processing) chip and it's performance was evaluated by experiment. As a result, we obtain total 4.7dBA noise reduction for 0.80m short duct.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.10a
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• pp.357-363
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• 2009

This paper deals with the Filtered-x Least Mean Square algorithm for a active vibration control in vehicle vibration reduction. Before applying the proposed FxLMS algorithm to automobile, the performance of the FxLMS algorithm is simulated using sensor data of a vehicle. The FxLMS algorithm requires that reference signal be a representation of disturbance signal and the plant model be incorporated into the computation path. To this end, The system identification is carried out to obtain the plant model based on the measurement results. A tachometer signal is used as reference signal. The FxLMS control algorithm is first tested using simulation and applied to a vehicle. Experimental results show that the proposed control algorithm can reduce vibration level in a short period of time.