• Journal of the Institute of Electronics Engineers of Korea SC
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• v.38 no.3
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• pp.31-39
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• 2001

In this paper, we proposed a new pixel circuit of the CMOS image sensor for high dynamic range operation, which is based on a multiple sampling scheme and a conditional reset circuit. To expand the pixel dynamic range, the output is multiple-sampled in the integration time. In each sampling, the pixel output is compared with a reference voltage, and the result of comparison may activate the conditional reset circuit. The times of conditional reset, N, during the integration will contribute to the increase of the dynamic range by the times of N. The test chip was fabricated with 0.65-${\mu}m$ CMOS technology (2-P, 2-M).

• Smart Structures and Systems
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• v.17 no.4
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• pp.647-667
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• 2016

In this paper, dynamic displacement is estimated with high accuracy by blending high-sampling rate acceleration data with low-sampling rate displacement measurement using a two-stage Kalman estimator. In Stage 1, the two-stage Kalman estimator first approximates dynamic displacement. Then, the estimator in Stage 2 estimates a bias with high accuracy and refines the displacement estimate from Stage 1. In the previous Kalman filter based displacement techniques, the estimation accuracy can deteriorate due to (1) the discontinuities produced when the estimate is adjusted by displacement measurement and (2) slow convergence at the beginning of estimation. To resolve these drawbacks, the previous techniques adopt smoothing techniques, which involve additional future measurements in the estimation. However, the smoothing techniques require more computational time and resources and hamper real-time estimation. The proposed technique addresses the drawbacks of the previous techniques without smoothing. The performance of the proposed technique is verified under various dynamic loading, sampling rate and noise level conditions via a series of numerical simulations and experiments. Its performance is also compared with those of the existing Kalman filter based techniques.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.5
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• pp.25-31
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• 2009

The recently developed sampling theory, "compressed sensing" is gathering huge interest in MR reconstruction area because of its feasibility of high spatio-temporal resolution of dynamic MRI which has been limited in conventional methods based on Nyquist sampling theory. Since dynamic MRI usually has high redundant information along temporal direction, this can be very sparsely represented in most of cases. Therefore, compressed sensing that exploits the sparsity of unknown images can be effectively applied in most of dynamic MRI. This review article briefly introduces currently proposed compressed sensing based dynamic MR imaging algorithms and other methods exploiting sparsity. By comparing them with conventional methods, you may have insight how the compressed sensing based methods can impact nearly every area of clinical dynamic MRI.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.4940-4957
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• 2019

Compared with the localization methods in the static sensor networks, node localization in dynamic sensor networks is more complicated due to the mobility of the nodes. Dynamic Sampling Localization Algorithm Based on Virtual Anchor (DSLA) is proposed in this paper to localize the unknown nodes in dynamic sensor networks. Firstly, DSLA algorithm predicts the speed and movement direction of nodes to determine a sector sampling area. Secondly, a method of calculating the sampling quantity with the size of the sampling area dynamically changing is proposed in this paper. Lastly, the virtual anchor node, i.e., the unknown node that got the preliminary possible area (PLA), assists the other unknown nodes to reduce their PLAs. The last PLA is regarded as a filtering condition to filter out the conflicting sample points quickly. In this way, the filtered sample is close to its real coordinates. The simulation results show that the DSLA algorithm can greatly improve the positioning performance when ensuring the execution time is shorter and the localization coverage rate is higher. The localization error of the DSLA algorithm can be dropped to about 20%.

• Journal of the Semiconductor & Display Technology
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• v.14 no.3
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• pp.37-43
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• 2015

In this paper, a new background subtraction algorithm for video based fence monitoring surveillance systems is proposed. We adopt the sampling based background subtraction technique and focus on the two main issues: handling highly dynamic environment and handling the flickering nature of pulse based IR (infrared) lamp. Natural scenes from fence monitoring system are usually composed of several dynamic entities such as swaying trees, moving water, waves and rain. To deal with such dynamic backgrounds, we utilize the confidence factor for each background value of the input image. For the flickering IR lamp, the original sampling based technique is extended to handle double background models. Experimental results revealed that our method works well in real fence monitoring surveillance systems.

• Journal of Sensor Science and Technology
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• v.21 no.1
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• pp.7-12
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• 2012

In this paper, we propose a 4-transistor active pixel sensor(APS) with a novel correlated double sampling(CDS) circuit for the purpose of extending dynamic range. Dual sampling techniques can overcome low-sensitivity and temporal disparity problems at low illumination. To accomplish this, two images are obtained at the same time using different sensitivities. The novel CDS circuit proposed in this paper contains MOS switches that make it possible for the capacitance of a conventional CDS circuit to function as a charge pump, so that the proposed APS exhibits an extended dynamic range as well as reduced noise. The designed circuit was fabricated by using $0.35{\mu}m$ 2-poly 4-metal standard CMOS technology and its characteristics have been evaluated.

• Bulletin of the Korean Chemical Society
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• v.33 no.3
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• pp.980-986
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• 2012

In this paper we develop a minimalist model of single molecule spectroscopy in a dynamic environment. Our model is based upon a lattice system consisting of a probe molecule embedded in an Ising-model like environment. We assume that the probe molecule interacts with the Ising spins via a dipole-dipole potential, and calculate free energy curves and lineshapes of the system. To investigate fluctuation behavior of the system we exploit the metadynamics sampling method. In particular, using the method, we calculate the free energy curve of magnetization of the lattice and that of the transition energy of the probe molecule. Furthermore, we compare efficiencies of three different sampling methods used; unbiased, umbrella, and metadynamics sampling methods. Finally, we explore the lineshape behavior of the probe molecule as the system undergoes a phase transition from a sub-critical and to a super-critical temperature. We show that the transition energy of a probe molecule is broadly distributed due to the heterogeneous, local environments.

• International Journal of Reliability and Applications
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• v.2 no.1
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• pp.27-36
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• 2001

This Paper proposes a new methodology for assessing the reliability of an accident management, which Is based on the reliability physics and the scheme to generate dynamic event tree. The methodology consists of 3 main steps: screening; uncertainty propagation; and probability estimation. Sensitivity analysis is used for screening the variables of significance. Latin Hypercube sampling technique and MAAP code are used for uncertainty propagation, and the dynamic event tree generation method is used for the estimation of non-success probability of implementing an accident management strategy. This approach is applied in assessing the non-success probability of implementing a cavity flooding strategy, which is to supply water into the reactor cavity using emergency fire systems during the sequence of station blackout at the reference plant.

• Journal of Biomedical Engineering Research
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• v.9 no.1
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• pp.87-92
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• 1988

In this paper, a new focusing method, to be called the pipelined sampled delay focusing (PSDF), is implemented. This method improves the lateral resolution in ultrasound imaging system. In PSDF, the analog belay lines are no longer necessary because sampling sum process can replace the conventional delay sum process. Also, the method offers continuous dynamic focusing on the resolution pixel basis, and eliminates the constraint that the maximum delay time is less than the sampling interval. Second order sampling is adopted in order to extend the sampling interval.

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.2
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• pp.109-118
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• 2008

We present a robust localization algorithm using particle filter for mobile robots in a dynamic environment. It is difficult to describe moving obstacles like people or other robots on the map and the environment is changed after mapping. A mobile robot cannot estimate its pose robustly with this incomplete map because sensor observations are corrupted by un-modeled obstacles. The proposed algorithms provide robustness in such a dynamic environment by suppressing the effect of corrupted sensor observations with a selective update or a sampling from non-corrupted window. A selective update method makes some particles keep track of the robot, not affected by the corrupted observation. In a sampling from non-corrupted window method, particles are always sampled from several particle sets which use only non-corrupted observation. The robustness of proposed algorithm is validated with experiments and simulations.