A neural network that outputs reconstructed images based on projection data containing scattered X-rays is presented, and the proposed scheme exhibits better accuracy than conventional computed tomography (CT), in which the scatter information is removed. In medical X-ray CT, it is a common practice to remove scattered X-rays using a collimator placed in front of the detector. In this study, the scattered X-rays were assumed to have useful information, and a method was devised to utilize this information effectively using a neural network. Therefore, we generated 70,000 projection data by Monte Carlo simulations using a cube comprising 216 (6 × 6 × 6) smaller cubes having random density parameters as the target object. For each projection simulation, the densities of the smaller cubes were reset to different values, and detectors were deployed around the target object to capture the scattered X-rays from all directions. Then, a neural network was trained using these projection data to output the densities of the smaller cubes. We confirmed through numerical evaluations that the neural-network approach that utilized scattered X-rays reconstructed images with higher accuracy than did the conventional method, in which the scattered X-rays were removed. The results of this study suggest that utilizing the scattered X-ray information can help significantly reduce patient dosing during imaging.

In X-ray computed tomography, scattered X-rays are generally removed by using a post-patient collimator located in front of the detector. In this paper, we show that the scattered X-rays have the potential to improve the estimation accuracy of the attenuation coefficient in computed tomography. In order to clarify the problem, we simplified the geometry of the computed tomography into a thin cylinder composed of a homogeneous material so that only one attenuation coefficient needs to be estimated. We then conducted a Monte Carlo numerical experiment on improving the estimation accuracy of attenuation coefficient by measuring the scattered X-rays with several dedicated toroidal detectors around the cylinder in addition to the primary X-rays. We further present a theoretical analysis to explain the experimental results. We employed a model that uses a T-junction (i.e., T-junction model) to divide the photon transport into primary and scattered components. This division is processed with respect to the attenuation coefficient. Using several T-junction models connected in series, we modeled the case of several scatter detectors. The estimation accuracy was evaluated according to the variance of the efficient estimator, i.e., the Cramer-Rao lower bound. We confirmed that the variance decreases as the number of scatter detectors increases, which implies that using scattered X-rays can reduce the irradiation dose for patients.

In this paper, we investigate the channel characteristics of underwater optical wireless communications (UOWC) based on Monte Carlo simulation method. The impulse response and channel time dispersion of the link are discussed. Also we consider the channel parameters comprehensively like the water type, attenuation length, divergence angle, beam width, field-of-view (FOV), receiver aperture and position. Simulation results suggest that in clear water, the channel can effectively be considered as non inter-symbol interference (ISI) when working over distance of up to 40m. Therefore, in practice the receiver does not need to perform computationally complex signal processing operations. However, in harbor water, the channel time dispersion will enlarge with larger FOV or divergence angle, and reduce the data transmission efficiency. When the attenuation length is smaller than diffused length, larger receivers offer lower intensity than smaller ones. In contrast, the intensity enhances with larger receiver at the small FOV, however, they trend to similar regardless of the apertures at large FOV. Furthermore, we study the effect of misalignment of the transmitter and receiver on the received intensity. The results give us some insight in terms of what constitutes an accurate UOWC channel.

In recent data centers, large-scale storage systems storing big data comprise thousands of large-capacity drives. Our goal is to establish a method for building highly reliable storage systems using more than a thousand low-cost large-capacity drives. Some large-scale storage systems protect data by erasure coding to prevent data loss. As the redundancy level of erasure coding is increased, the probability of data loss will decrease, but the increase in normal data write operation and additional storage for coding will be incurred. We therefore need to achieve high reliability at the lowest possible redundancy level. There are two concerns regarding reliability in large-scale storage systems: (i) as the number of drives increases, systems are more subject to multiple drive failures and (ii) distributing stripes among many drives can speed up the rebuild time but increase the risk of data loss due to multiple drive failures. If data loss occurs by multiple drive failure, it affects many users using a storage system. These concerns were not addressed in prior quantitative reliability studies based on realistic settings. In this work, we analyze the reliability of large-scale storage systems with distributed stripes, focusing on an effective rebuild method which we call Dynamic Refuging. Dynamic Refuging rebuilds failed blocks from those with the lowest redundancy and strategically selects blocks to read for repairing lost data. We modeled the dynamic change of amount of storage at each redundancy level caused by multiple drive failures, and performed reliability analysis with Monte Carlo simulation using realistic drive failure characteristics. We showed a failure impact model and a method for localizing the failure. When stripes with redundancy level 3 were sufficiently distributed and rebuilt by Dynamic Refuging, the proposed technique turned out to scale well, and the probability of data loss decreased by two orders of magnitude for systems with a thousand drives compared to normal RAID. The appropriate setting of a stripe distribution level could localize the failure.

Majority logic is quite important for various applications such as fault tolerant systems, threshold logic, spectrum spread coding, and artificial neural networks. The circuit implementation of majority logic is difficult when the number of inputs becomes large because the number of transistors becomes huge and serious delay would occur. In this paper, we propose a new majority circuit with large fan-in. The circuit is composed of ordinary CMOS transistors and the total number of transistors is approximately only 4N, where N is the total number of inputs. We confirmed a correct operation by using HSPICE simulation. The yield of the proposed circuit was evaluated with respect to N under the variations of device parameters by using Monte Carlo simulation.

A simplified circuit has been utilized for fast computation of the current flowing in the cross-point memory array. However, the circuit has a constraint in that the selected cell is located farthest from current drivers so as to estimate the current degraded by metal wire resistance. This is because the length of the current path along the metal wire varies with the selected address in the cross-point memory array. In this paper, a new simplified circuit is proposed for calculating the current at every address in order to take account of the metal wire resistance. By employing the Monte Carlo simulation to solve the proposed simplified circuit, the current distribution across the array is obtained, so that failure rates of read disturbance and write error are estimated precisely. By comparing the conventional and the proposed simplified circuits, it was found that the conventional simplified circuit estimated optimistic failure rates for read disturbance and for write error when the wire resistance was prominent enough as a parasitic resistance.

In this paper, we study on an availability analysis for a multibase system with lateral resupply of spare items between bases. We construct a basic model that a spare item of a base is transported for operation to another base without spare upon occurrence of failure, and simultaneously, the base that supplies the spare item receives the failed item of the other base for repair. We propose an approximation method to obtain the availability of the system and show the accuracy of the solution through numerical experiments. Also, two modified models are constructed to show the efficiency of the basic model. The two models modify the assumption on the lateral resupply of spare items between bases in the basic model. We numerically illustrate that the basic model can increase the availability of the system compared with the two modified models through Monte Carlo simulation.

The composite binary offset carrier (CBOC) modulated signal contains multi-peaks in its auto-correlation function, which brings ambiguity to the signal acquisition process of a GNSS receiver. Currently, most traditional ambiguity-removing schemes for CBOC signal acquisition approximate CBOC signal as a BOC signal, which may incur performance degradation. Based on Galileo E1 CBOC signal, this paper proposes a novel adaptive ambiguity-removing acquisition scheme which doesn't adopt the approximation used in traditional schemes. According to the energy ratio of each sub-code of CBOC signal, the proposed scheme can self-adjust its local reference code to achieve unambiguous and precise signal synchronization. Monte Carlo simulation is conducted in this paper to analyze the performance of the proposed scheme and three traditional schemes. Simulation results show that the proposed scheme has higher detection probability and less mean acquisition time than the other three schemes, which verify the superiority of the proposed scheme.

This paper presents a basic investigation of the power imbalance problem with regard to maximum ratio combining (MRC) array antennas for digital TV broadcast reception. First, the relationship between the decrease in the diversity gain and reduction in the received power was investigated using two-element and four-element dipole array antennas by means of a Monte Carlo simulation. The relationship between the decrease in the diversity gain and the number of branches imposed to reduce the received power was also investigated. Then, a simple method of predicting the reduction in the diversity gain under imbalanced power conditions is given using the simulation results. The objective is to determine a criterion associated with the gain reduction that allows us to achieve the required system performance. Finally, the proposed method is confirmed by analysis using a model representing a typical portable digital broadcasting TV set held with both hands that simulates the power imbalance condition.

Clock network synthesis is one of the most important and limiting factors in VLSI designs. Hence, the clock skew variation reduction is one of the most important objectives in clock distribution methodology. Cross-link insertion is proposed in [1], however, it is based on empirical methods and does not use variation information for link insertion location choice. [17] considers the delay variation, but it is slow even for small clock trees. In this paper, we propose a fast link insertion algorithm that considers the delay variation information directly during link selection process. Experimental results show that our algorithm is very fast and achieves better skew variability reduction while utilizing considerably lesser routing resources compared with existing methods.

We herein investigate the operation stability of the single-electron-pump (SEP) refrigerator with respect to thermal and dimensional fluctuations. The SEP refrigerator was found to successfully demonstrate single-electron extraction and injection at temperatures up to 2 K. Although the dimensional fluctuation in junction capacitance will seriously affect operation, the effect of the gate capacitance fluctuation is unlikely to be severe.

This study shows a fast simulation method for turbo codes over an additive white class A noise (AWAN) channel. The reduction of the estimation time is achieved by applying importance sampling (IS) which is one of the variance reduction simulation methods. In order to adapt the AWAN channel, we propose a design method of a simulation probability density function (PDF) utilized in IS. The proposed simulation PDF is related to the Bhattacharyya bound to evaluate wider area of the signal space than the conventional method. Since the mean translation method, which is a conventional design method of the simulation PDF used in IS, is optimized for an additive white Gaussian noise channel, the evaluation time of the error performance of turbo codes over the AWAN channel can not be reduced. To evaluate BER of 10-8, the simulation time of the proposed method can be reduced to 1/104 under the condition of the same accuracy of the traditional Monte Carlo simulation method.

This paper deals with the decomposition of surface data into several fractal signal based on the parameter estimation by the Mean Likelihood and Importance Sampling (IS) based on the Monte Carlo simulations. The method is applied to the feature extraction of surface data. Assuming the stochastic models for generating the surface, the likelihood function is defined by using wavelet coefficients and the parameter are estimated based on the mean likelihood by using the IS. The approximation of the wavelet coefficients is used for estimation as well as the statistics defined for the variances of wavelet coefficients, and the likelihood function is modified by the approximation. After completing the decomposition of underlying surface data into several fractal surface, the prediction method for the fractal signal is employed based on the scale expansion based on the self-similarity of fractal geometry. After discussing the effect of additive noise, the method is applied to the feature extraction of real distribution of surface data such as the cloud and earthquakes.

A random number generator composed of single electron devices is presented. Due to stochastic behavior of electron tunneling process, single electron devices have intrinsic randomness. Using its randomness, a true random number generator can be implemented. Although fluctuation of device parameters degrades the performance of the proposed circuit, we show that the adjustment of the bias voltages can compensate the fluctuation.

Electron transport in bulk Si and MOSFET inversion layers is studied using an ensemble Monte Carlo (EMC) technique coupled with the molecular dynamics (MD) method. The Coulomb interactions among point charges (electrons and negative ions) are directly taken into account in the simulation. It is demonstrated that the static screening of Coulomb interactions is correctly simulated by the EMC/MD method. Furthermore, we calculate the inversion layer mobility in Si MOSFETs, and mobility roll-off near the threshold voltage is observed by the present approach.

The validity and capability of an iterative coupling scheme between single-particle frozen-field Monte Carlo simulations and nonlinear Poisson solutions for achieving self-consistency is investigated. For this purpose, a realistic 0.1 µm lightly-doped-drain (LDD) n-MOSFET with a maximum doping level of about 2.5 1020 cm-3 is simulated. It is found that taking the drift-diffusion (DD) or the hydrodynamic (HD) model as initial simulation leads to the same Monte Carlo result for the drain current. This shows that different electron densities taken either from a DD or a HD simulation in the bulk region, which is never visited by Monte Carlo electrons, have a negligible influence on the solution of the Poisson equation. For the device investigated about ten iterations are necessary to reach the stationary state after which gathering of cumulative averages can begin. Together with the absence of stability problems at high doping levels this makes the self-consistent single-particle approach (SPARTA) a robust and efficient method for the simulation of nanoscale MOSFETs where quasi-ballistic transport is crucial for the on-current.

Monte Carlo simulation of the low field electron mobility of strained Si and SiGe active layers on Si and SiGe substrates is considered. The Ge mole fractions of both the active layer and the substrate are varied in a wide range. The linear deformation potential theory is used to calculate the shifts of the conduction band minima due to uniaxial strain along [001]. The energy shifts and the effective masses are assumed to be functions of the Ge mole fraction. It is shown that in spite of the fact that the L-valleys remain degenerate under strain conditions considered here, they play an important role at very high Ge compositions especially when SiGe as substrate is used. We found that in this case the repopulation effects of the X-valleys affect electron mobility much stronger than the alloy scattering. We also generalize the ionized impurity scattering rate to include strain effects for doped materials and show that some of the important parameters such as effective density of states, inverse screening length, and the screening function are split due to strain and must be properly modified. Finally, we perform several simulations for undoped and doped materials using Si and SiGe substrates.

This paper reports a Monte Carlo calculation of the bimolecular reaction of arsenic precipitation. As the accuracy of the numerical solution for the coupled rate equations strongly depends on the size of grid spacing, it is necessary to choose adequate number of rate equations in order to understand the behavior of the extended defects. Therefore, we developed a general kinetic Monte Carlo model for the extended defects, which explicitly takes the time evolution of the size density of the extended defects into account. The Monte Carlo calculation exhibits a quantitative agreement with the experimental data for deactivation, and successfully reproduces the rapid deactivation at the beginning phase followed by slow deactivation in the subsequent steps.

We investigate the intrinsic current fluctuations in small Si-MOSFETs via the Monte Carlo device simulation. It is demonstrated that the temporal fluctuation of the drain current in Si-MOSFETs attains a significant fraction of the averaged drain current when the device width is scaled down to the deep sub-µm regime. This is caused by the drastic decrease in the number of channel electrons. This finding holds true whenever the device width is reduced to deep sub-µm, regardless of the channel length. Most importantly, current fluctuation is associated with the quasi-equilibrium thermal noise in the heavily-doped source and drain regions, whereas its magnitude with respect to the averaged drain current is directly related to the number of channel electrons underneath the gate.

The Monte Carlo simulation is applied to fault tree analyses of the sequential failure logic. In order to make the validity of the technique clear, case studies for estimation of the statistically expected numbers of system failures during (0, t] are conducted for two types of systems using the multiple integration method as well as the Monte Carlo simulation. Results from these two methods are compared. This validates the Monte Carlo simulation in solving the sequential failure logic with respectably small deviation rates for those cases.