Many kinds of data can be represented as a network or graph. It is crucial to infer the latent structure underlying such a network and to predict unobserved links in the network. Mixed Membership Stochastic Blockmodel (MMSB) is a promising model for network data. Latent variables and unknown parameters in MMSB have been estimated through Bayesian inference with the entire network; however, it is important to estimate them online for evolving networks. In this paper, we first develop online inference methods for MMSB through sequential Monte Carlo methods, also known as particle filters. We then extend them for time-evolving networks, taking into account the temporal dependency of the network structure. We demonstrate through experiments that the time-dependent particle filter outperformed several baselines in terms of prediction performance in an online condition.

Tracking capsule endoscope location is one of the promising applications offered by implant body area networks (BANs). When tracking the capsule endoscope location, i.e., continuously localize it, it is effective to take the weighted sum of its past locations to its present location, in other words, to low-pass filter its past locations. Furthermore, creating an exact mathematical model of location transition will improve tracking performance. Therefore, in this paper, we investigate two tracking methods with received signal strength indicator (RSSI)-based localization in order to solve the capsule endoscope location tracking problem. One of the two tracking methods is finite impulse response (FIR) filter-based tracking, which tracks the capsule endoscope location by averaging its past locations. The other one is particle filter-based tracking in order to deal with a nonlinear transition model on the capsule endoscope. However, the particle filter requires that the particle weight is calculated according to its condition (namely, its likelihood value), while the transition model on capsule endoscope location has some model parameters which cannot be estimated from the received wireless signal. Therefore, for the purpose of applying the particle filter to capsule endoscope tracking, this paper makes some modifications in the resampling step of the particle filter algorithm. Our computer simulation results demonstrate that the two tracking methods can improve the performance as compared with the conventional maximum likelihood (ML) localization. Furthermore, we confirm that the particle filter-based tracking outperforms the conventional FIR filter-based tracking by taking the realistic capsule endoscope transition model into consideration.

The percentage of pedestrian deaths in traffic accidents is on the rise in Japan. In recent years, there have been calls for measures to be introduced to protect vulnerable road users such as pedestrians and cyclists. In this study, a method to detect and track pedestrians using an in-vehicle camera is presented. We improve the technology of detecting pedestrians by using the highly accurate images obtained with a monocular camera. In the detection step, we employ ECoHOG as the feature descriptor; it accumulates the integrated gradient intensities. In the tracking step, we apply an effective motion model using optical flow and the proposed feature descriptor ECoHOG in a tracking-by-detection framework. These techniques were verified using images captured on real roads.

As one of organic electroluminescent (EL) materials, we developed a method of fabricating an ink using low molecular- weight materials with a long emission lifetime for application to the inkjet method. Although the emission lifetime is usually long for low molecular-weight materials, their high manufacturing cost due to the necessity of vapor deposition is a disadvantage. We utilized the low molecular-weight material, tris-(8-hydroxyquinoline) aluminum (Alq3), and investigated its dispersibility in a solvent in which it has low solubility. In addition, we ascertained whether the material could maintain its photoluminescence characteristic under the irradiation of ultraviolet rays by investigating the emission of photoluminescence. Alq3 was crystallized into nanosize crystals, whose surface was then coated with a primary amine by the gas evaporation method. The fabricated ink contained crystals with an average size of 250nm and high dispersibility in tetradecane, in which Alq3 is insoluble. Thus, we made it possible to carry out an inkjet method with low molecular weight EL materials.

Recently, fuzzy set theory has been widely employed in building portfolio selection models where uncertainty plays a role. In these models, future security returns are generally taken for fuzzy variables and mathematical models are then built to maximize the investment profit according to a given risk level or to minimize a risk level based on a fixed profit level. Based on existing works, this paper proposes a portfolio selection model based on fuzzy birandom variables. Two original contributions are provided by the study: First, the concept of technical analysis is combined with fuzzy set theory to use the security returns as fuzzy birandom variables. Second, the fuzzy birandom Value-at-Risk (VaR) is used to build our model, which is called the fuzzy birandom VaR-based portfolio selection model (FBVaR-PSM). The VaR can directly reflect the largest loss of a selected case at a given confidence level and it is more sensitive than other models and more acceptable for general investors than conventional risk measurements. To solve the FBVaR-PSM, in some special cases when the security returns are taken for trapezoidal, triangular or Gaussian fuzzy birandom variables, several crisp equivalent models of the FBVaR-PSM are derived, which can be handled by any linear programming solver. In general, the fuzzy birandom simulation-based particle swarm optimization algorithm (FBS-PSO) is designed to find the approximate optimal solution. To illustrate the proposed model and the behavior of the FBS-PSO, two numerical examples are introduced based on investors' different risk attitudes. Finally, we analyze the experimental results and provide a discussion of some existing approaches.

This paper presents a new phase unwrapping algorithm, based on an extended particle filter (EPF) for SAR interferometry. This technique is not limited by the nonlinearity of the model, and is able to accurately unwrap noisy interferograms by applying EPF to simultaneously perform noise suppression and phase unwrapping. Results obtained from synthetic and real data validate the effectiveness of the proposed method.

The optimum generalized partial response (GPR) target for barium ferrite (BaFe) tape systems was studied. The shift in perpendicular magnetic recording technology in HDDs to systems employing single-pole-type (SPT) recording heads and media with a soft under layer (SUL) has been accompanied by a change in the read channel design, whereas current magnetic tape recording systems utilize a combination of a ring-type recording head with a single magnetic layer structured medium. Therefore, the read channel performance of current oriented BaFe particulate tape systems needs to be studied to best exploit the potential of this medium. Toward this end, DC-free, DC-full, and DC-suppressed targets were compared. The results show that assuming a GPRML detector with 16 or more states, a traditional DC-free target exhibits the best bit error rate performance for both longitudinally and perpendicularly oriented BaFe media, suggesting that the current read channel designed for longitudinally oriented media can also be utilized for BaFe particulate tape systems.

Video coding plays an important role in human life especially in communications. H.264/AVC is a prominent video coding standard that has been used in a variety of applications due to its high efficiency comes from several new coding techniques. However, the extremely high encoding complexity hinders itself from real-time applications. This paper presents a new encoding algorithm that makes use of particle swarm optimization (PSO) to train discriminant functions for classification based fast mode decision. Experimental results show that the proposed algorithm can successfully reduce encoding time at the expense of negligible quality degradation and bitrate increases.

MIMO transmission technologies have become an essential component of cellular systems such as Long Term Evolution (LTE) and LTE-Advanced. Recently, evaluating the communication performance of mobile users in cellular MIMO systems has become an urgent requirement. In this paper, we propose dynamic MIMO channel modeling for the urban environment. Our proposal is based on Geometry-based Stochastic Channel Modeling (GSCM). The cluster parameters such as the local scatterer locations around the measurement course are estimated by applying the particle filtering to measured data. We carried out radio propagation measurements in an urban environment at 3.35GHz band, and generated the dynamic channel from the measured data. The experiments showed that both the spreads and auto-correlation of Time of Arrival (ToA), Angle of Arrival (AoA) and Angle of Departure (AoD) were reconstructed within the acceptable error range in our dynamic channel model.

This paper presents a proposed NMOS-centered 6T SRAM cell layout that reduces a neutron-induced multiple-cell-upset (MCU) SER on a same wordline. We implemented an 1-Mb SRAM macro in a 65-nm CMOS process and irradiated neutrons as a neutron-accelerated test to evaluate the MCU SER. The proposed 6T SRAM macro improves the horizontal MCU SER by 67–98% compared with a general macro that has PMOS-centered 6T SRAM cells.

Recent attempts to directly combine CMOS pixel readout chips with modern gas detectors open the possibility to fully take advantage of gas detectors. Those conventional readout LSIs designed for hybrid semiconductor detectors show some issues when applied to gas detectors. Several new proposed readout LSIs can improve the time and the charge measurement precision. However, the widely used basic charge sensitive amplifier (CSA) has an almost fixed dynamic range. There is a trade-off between the charge measurement resolution and the detectable input charge range. This paper presents a method to apply the folding integration technique to a basic CSA. As a result, the detectable input charge dynamic range is expanded while maintaining all the key merits of a basic CSA. Although folding integration technique has already been successfully applied in CMOS image sensors, the working conditions and the signal characteristics are quite different for pixel readout LSIs for gas particle detectors. The related issues of the folding CSA for pixel readout LSIs, including the charge error due to finite gain of the preamplifier, the calibration method of charge error, and the dynamic range expanding efficiency, are addressed and analyzed. As a design example, this paper also demonstrates the application of the folding integration technique to a Qpix readout chip. This improves the charge measurement resolution and expands the detectable input dynamic range while maintaining all the key features. Calculations with SPICE simulations show that the dynamic range can be improved by 12 dB while the charge measurement resolution is improved by 10 times. The charge error during the folding operation can be corrected to less than 0.5%, which is sufficient for large input charge measurement.

In this letter, we present an efficient method for high quality surface reconstruction from simulation data of smoothed particles hydrodynamics (SPH). For computational efficiency, instead of computing scalar field in overall particle sets, we only construct scalar field around fluid surfaces. Furthermore, an adaptive scalar field model is proposed, which adaptively adjusts the smoothing length of ellipsoidal kernel by a constraint-correction rule. Then the isosurfaces are extracted from the scalar field data. The proposed method can not only effectively preserve fluid details, such as splashes, droplets and surface wave phenomena, but also save computational costs. The experimental results show that our method can reconstruct the realistic fluid surfaces with different particle sets.

This paper describes the analysis and design of low-noise analog circuits for a new architecture readout LSI, Qpix. In contrast to conventional readout LSIs using TOT method, Qpix measures deposited charge directly as well as time information. A preamplifier with a two-stage op amp and current-copy output buffers is proposed to realize these functions. This preamplifier is configured to implement a charge sensitive amplifier (CSA) and a trans-impedance amplifier (TIA). Design issues related to CSA are analyzed, which includes gain requirement of the op amp, stability and compensation of the two-stage cascode op amp, noise performance estimation, requirement for the resolution of the ADC and time response. The offset calibration method in the TIA to improve the charge detecting sensitivity is also presented. Also, some design principles for these analog circuits are presented. In order to verify the theoretical analysis, a 400-pixel high speed readout LSI: Qpix v.1 has been designed and fabricated in 180 nm CMOS process. Calculations and SPICE simulations show that the total output noise is about 0.31 mV (rms) at the output of the CSA and the offset voltage is less than 4 mV at the output of the TIA. These are attractive performances for experimental particle detector using Qpix v.1 chip as its readout LSI.

We investigated oxidation time dependence of graphene oxide employing modified Hummer method by dynamic light scattering. Oxidation reaction proceeded rapidly within about 24 hours, and was saturated. It is suggested that graphene oxides were not able to freely fragment. This implies that the oxidation reactions occur at the limited sites.

We propose a practical local and global path-planning algorithm for an autonomous vehicle or a car-like robot in an unknown semi-structured (or unstructured) environment, where obstacles are detected online by the vehicle's sensors. The algorithm utilizes a probabilistic method based on particle filters to estimate the dynamic obstacles' locations, a support vector machine to provide the critical points and Bezier curves to smooth the generated path. The generated path safely travels through various static and moving obstacles and satisfies the vehicle's movement constraints. The algorithm is implemented and verified on simulation software. Simulation results demonstrate the effectiveness of the proposed method in complicated scenarios that posit the existence of multi moving objects.

Streak cameras are now widely used for measurements of ultra short phenomena, such as those in semi conductor luminescence and plasma gaseous discharge. To further improve the temporal resolution and carry out higher-dimensional measurements, it is necessary to understand the electron beam behavior in detail. Thus, numerical simulations play an important role in the analysis of the streak camera. The authors have been working on the development of a numerical simulation code that uses the finite difference method (FDM) for electric field analysis, the Runge-Kutta (R-K) method for charged particle motion determination, and the particle-in-cell (PIC) method for charge density calculation. However, the use of the PIC method leads to inaccuracy in the charge density calculation in cases of high-density electron beams. To improve the accuracy of the conventional analysis of the streak camera, we perform the boundary element (BE) analysis of the streak camera.

This paper presents a new 8T (8-transistor) SRAM cell layout mitigating multiple-bit upset (MBU) in a divided wordline structure. Because bitlines along unselected columns are not activated, the divided wordline structure eliminates a half-select problem and achieves low-power operation, which is often preferred for low-power/low-voltage applications. However, the conventional 8T SRAM with the divided wordline structure engenders MBUs because all bits in the same word are physically adjoining. Consequently, it is difficult to apply an error correction coding (ECC) technique to it. In this paper, we propose a new 8T cell layout pattern that separates internal latches in SRAM cells using both an n-well and a p-substrate. We saw that a SEU cross section of nMOS is 3.5–4.5 times higher than that of pMOS (SEU: single event upset; a cross section signifies a sensitive area to soft error effects). By using a soft-error simulator, iRoC TFIT, we confirmed that the proposed 8T cell has better neutron-induced MBU tolerance. The simulator includes soft-error measurement data in a commercial 65-nm process. The MBU in the proposed 8T SRAM is improved by 90.70% and the MBU soft error rate (SER) is decreased to 3.46 FIT at 0.9 V when ECC is implemented (FIT: failure in time). Additionally, we conducted Synopsys 3-D TCAD simulation, which indicates that the linear energy transfer (LET) threshold in SEU is also improved by 66% in the proposed 8T SRAM by a common-mode effect.

This paper presents measurement results of bit error rate (BER) and soft error rate (SER) improvement on 150-nm FD-SOI 7T/14T (7-transistor/ 14-transistor) SRAM test chips. The reliability of the 7T/14T SRAM can be dynamically changed by a control signal depending on an operating condition and application. The 14T dependable mode allocates one bit in a 14T cell and improves the BER in a read operation and SER in a retention state, simultaneously. We investigate its error rate mitigating mechanisms using Synopsys TCAD simulator. In our measurements, the minimum operating voltage was improved by 100 mV, the alpha-induced SER was suppressed by 80.0%, and the neutron-induced SER was decreased by 34.4% in the 14T dependable mode over the 7T normal mode.

We have developed a process for the fabrication of high-quality Nb/AlOx/Nb tunnel junctions with small area and high current densities for the heterodyne mixers at millimeter and submillimeter wavelengths. Their dc I-V curves are numerically studied, including the broadening of quasiparticle density of states resulting from the existence of an imaginary part of the gap energy of Nb. We have found both experimentally and numerically that the subgap current is strongly dependent on bias voltage at temperatures below 4.2 K unlike the prediction of the BCS tunneling theory. It is shown that calculated dc I-V curves taking into account the complex number of the gap energy agree well with those of Nb/AlOx/Nb junctions measured at temperatures from 0.4 to 4.2 K. We have successfully built receivers at millimeter and submillimeter wavelengths with the noise temperature as low as 4 times the quantum photon noise, employing those high-quality Nb/AlOx/Nb junctions. Those low-noise receivers are to be installed in the ALMA (Atacama Large Millimeter/Submillimeter Array) telescope and they are going into series production now.

Magnetic particle imaging (MPI), in which the nonlinear interaction between internally administered magnetic nanoparticles (MNPs) and electromagnetic waves irradiated from outside of the body is utilized, has attracted attention for its potential to achieve early diagnosis of diseases such as cancer. In MPI, the local magnetic field distribution is scanned, and the magnetization signal from MNPs within a selected region is detected. However, the signal sensitivity and image resolution are degraded by interference from magnetization signals generated by MNPs outside of the selected region, mainly because of imperfections (limited gradients) in the local magnetic field distribution. Here, we propose new methods based on correlation information between the observed signal and the system function–defined as the interaction between the magnetic field distribution and the magnetizing properties of MNPs. We performed numerical analyses and found that, although the images were somewhat blurred, image artifacts could be significantly reduced and accurate images could be reconstructed without the inverse-matrix operation used in conventional image reconstruction methods.