Quantum computer simulators play an important role when we evaluate quantum algorithms. Quantum computation can be regarded as parallel computation in some sense, and thus, it is suitable to implement a simulator on hardware that can process a lot of operations in parallel. In this paper, we propose a hardware quantum computer simulator. The proposed simulator is based on the register reordering method that shifts and swaps registers containing probability amplitudes so that the probability amplitudes of target basis states can be quickly selected. This reduces the number of large multiplexers and improves clock frequency. We implement the simulator on an FPGA. Experiments show that the proposed simulator has scalability in terms of the number of quantum bits, and can simulate quantum algorithms faster than software simulators.

Traffic is a key aspect of everyday life. Its study, as it happens with other complex phenomena, has found in simulation a basic tool. However, the use of simulations faces important limitations. Building them requires considering different aspects of traffic (e.g. urbanism, car features, and individual drivers) with their specific theories, that must be integrated to provide a coherent model. There is also a variety of simulation platforms with different requirements. Many of these problems demand multi-disciplinary teams, where the different backgrounds can hinder the communication and validation of simulations. The Model-Driven Engineering (MDE) of simulations has been proposed in other fields to address these issues. Such approaches develop graphical Modelling Languages (MLs) that researchers use to model their problems, and then semi-automatically generate simulations from those models. Working in this way promotes communication, platform independence, incremental development, and reutilisation. This paper presents the first steps for a MDE framework for traffic simulations. It introduces a tailored extensible ML for domain experts. The ML is focused on human actions, so it adopts an Agent-Based Modelling perspective. Regarding traffic aspects, it includes concepts commonly found in related literature following the Driver-Vehicle-Environment model. The language is also suitable to accommodate additional theories using its extension mechanisms. The approach is supported by an infrastructure developed using Eclipse MDE projects: the ML is specified with Ecore, and a model editor and a code generator tools are provided. A case study illustrates how to develop a simulation based on a driver's behaviour theory for a specific target platform using these elements.

Workflow nets (WF-nets for short) are a mathematical model of real world workflows. A WF-net is often updated in accordance with the change of real world. This may cause places that are redundant from the viewpoint of the behavior. Such places are called implicit. We first proposed a necessary and sufficient condition to find implicit places. Then we proved that removing of implicit places is a reduction operation which forms branching bisimilarity. We also constructed an algorithm for the reduction. Next, we applied the proposed reduction operation to WF-net refactoring. Then we showed the usefulness of the proposed refactoring with two examples.

This paper proposes a method based on modulation transfer function (MTF) to restore the power envelope of noisy reverberant speech by using a Kalman filter with linear prediction (LP). Its advantage is that it can simultaneously suppress the effects of noise and reverberation by restoring the smeared MTF without measuring room impulse responses. This scheme has two processes: power envelope subtraction and power envelope inverse filtering. In the subtraction process, the statistical properties of observation noise and driving noise for power envelope are investigated for the criteria of the Kalman filter which requires noise to be white and Gaussian. Furthermore, LP coefficients drastically affect the Kalman filter performance, and a method is developed for deriving LP coefficients from noisy reverberant speech. In the dereverberation process, an inverse filtering method is applied to remove the effects of reverberation. Objective experiments were conducted under various noisy reverberant conditions to evaluate how well the proposed Kalman filtering method based on MTF improves the signal-to-error ratio (SER) and correlation between restored power envelopes compared with conventional methods. Results showed that the proposed Kalman filtering method based on MTF can improve SER and correlation more than conventional methods.

A new design method for a high-order series-coupled microring filter using Chebyshev filter condition was proposed and its application to the design of a wavelength-selective switch (WSS) was discussed. In the proposed method, the propagation loss in a microring resonator, coupling loss at a coupler, and a free spectral ranges (FSR) in a microring resonator are considered for the first time. It was found that for high-order series coupled microring resonators, the WSS designed using Chebyshev condition has more boxlike filter responses and high extinction ratio, compared with that designed using Butterworth condition, in the case where the round-trip loss in a microring is relatively large. In addition, the fourth-order series-coupled microring WSS with boxlike responses was successfully designed, considering Vernier effect for a larger FSR and shift in resonant wavelength.

This paper proposes a novel image integral equation of the first type (IIE-1) for a TE plane wave scattering from periodic rough surfaces with perfect conductivity by means of the method of image Green's function. Since such an IIE-1 is valid for any incident wavenumbers including the critical wavenumbers, the analytical properties of the scattered wavefield can be generally and rigorously discussed. This paper firstly points out that the branch point singularity of the bare propagator inevitably appears on the incident wavenumber characteristics of the scattered wavefield and its related quantities just at the critical wavenumbers. By applying a quadrature method, the IIE-1 becomes a matrix equation to be numerically solved. For a periodic rough surface, several properties of the scattering are shown in figures as functions of the incident wavenumbers. It is then confirmed that the branch point singularity clearly appears in the numerical solution. Moreover, it is shown that the proposed IIE-1 gives a numerical solution satisfying sufficiently the optical theorem even for the critical wavenumbers.

Nowadays, with the development of online social networks (OSN), a mass of online social information has been generated in OSN, which has triggered research on social recommendation. Collaborative filtering, as one of the most popular techniques in social recommendation, faces several challenges, such as data sparsity, cold-start users and prediction quality. The motivation of our work is to deal with the above challenges by effectively combining collaborative filtering technology with social information. The trust relationship has been identified as a useful means of using social information to improve the quality of recommendation. In this paper, we propose a trust-based recommendation approach which uses GlobalTrust (GT) to represent the trust value among users as neighboring nodes. A matrix factorization based on singular value decomposition is used to get a trust network built on the GT value. The recommendation results are obtained through a modified random walk algorithm called GlobalTrustWalker. Through experiments on a real-world sparser dataset, we demonstrate that the proposed approach can better utilize users' social trust information and improve the recommendation accuracy on cold-start users.

In this paper, a method for designing of Incremental Granular Model (IGM) based on integration of Linear Regression (LR) and Linguistic Model (LM) with the aid of fuzzy granulation is proposed. Here, IGM is designed by the use of information granulation realized via Context-based Interval Type-2 Fuzzy C-Means (CIT2FCM) clustering. This clustering approach are used not only to estimate the cluster centers by preserving the homogeneity between the clustered patterns from linguistic contexts produced in the output space, but also deal with the uncertainty associated with fuzzification factor. Furthermore, IGM is developed by construction of a LR as a global model, refine it through the local fuzzy if-then rules that capture more localized nonlinearities of the system by LM. The experimental results on two examples reveal that the proposed method shows a good performance in comparison with the previous works.

We propose a new swept-frequency measurement method for the electromagnetic characterization of materials. The material is a multilayer cylinder that pierces a rectangular waveguide through two holes in the narrow waveguide walls. The complex permittivity and permeability of the material are calculated from measured S-parameters as an inverse problem. To this aim, the paper develops a complete electromagnetic formulation of the problem, where the effects of material insertion holes are taken into consideration. The formulation is validated through the measurement of ferrite and water samples in the S-band.

We propose an algorithm for the scattering analyses of gratings with various local defects based on the difference-field boundary-element method (DFBEM). In the algorithm, the defect in the grating is partitioned, and the DFBEM is sequentially applied for each defect section. We validate the proposed algorithm by demonstrating its flexibility for various defect topologies for a locally deformed grating.

Incoming GPS signals through windows can be often observed indoors. However, conventional indoor positioning systems do not use Global Positioning System (GPS) generally because the signals may come in NLOS (Non Line of Sight). In this paper, we propose a positioning method by fingerprinting based on the incoming GPS signals.

Since digital hearing aids are sensitive to time delay and power consumption, the computational complexity of noise reduction must be reduced as much as possible. Therefore, some complicated algorithms based on the analysis of the time-frequency domain are very difficult to implement in digital hearing aids. This paper presents a new approach that yields an improved noise reduction algorithm with greatly reduce computational complexity for multi-channel digital hearing aids. First, the sub-band sound pressure level (SPL) is calculated in real time. Then, based on the calculated sub-band SPL, the noise in the sub-band is estimated and the possibility of speech is computed. Finally, a posteriori and a priori signal-to-noise ratios are estimated and the gain function is acquired to reduce the noise adaptively. By replacing the FFT and IFFT transforms by the known SPL, the proposed algorithm greatly reduces the computation loads. Experiments on a prototype digital hearing aid show that the time delay is decreased to nearly half that of the traditional adaptive Wiener filtering and spectral subtraction algorithms, but the SNR improvement and PESQ score are rather satisfied. Compared with modulation frequency-based noise reduction algorithm, which is used in many commercial digital hearing aids, the proposed algorithm achieves not only more than 5dB SNR improvement but also less time delay and power consumption.

We deal with the scattering of a plane wave by the end-face of a waveguide system by the numerical method based on the sinc function and calculate the electric field on the end-face. It is shown that the results obtained analytically by the perturbation method are in relatively good agreement with the numerical results.

This letter describes a speech enhancement algorithm for stereo signals corrupted by diffuse noise. It estimates the noise signal and also a beamformed target signal based on blind target signal cancelation derived from sparsity minimization. Enhanced target speech is obtained by Wiener filtering using both the signals. Experimental results demonstrate the effectiveness of the proposed method.

In this paper, we propose a new joint transmit and receive spatial/frequency-domain filtering for single-carrier (SC) multiple-input multiple-output (MIMO) eigenmode transmission using iterative interference cancellation (IC). Iterative IC is introduced to a previously proposed joint transmit and receive spatial/frequency-domain filtering based on minimum mean square error criterion (called joint Tx/Rx MMSE filtering) to reduce the residual inter-symbol interference (ISI) after the Rx filtering. The optimal Tx/Rx filters are derived based on the MMSE criterion taking into account the iterative IC. The superiority of our proposed technique is confirmed by computer simulation.

A high frequency approximation method is proposed to obtain the scattering from rectangular dielectric cuboids. Our formulation is based on a Kirchhoff type aperture integration of the equivalent current sources over the surface of the scattering bodies. The derived formulae have been used to get the radar cross section of cuboids, and the results are compared with those by other methods, such as physical optics, geometrical theory of diffraction, the HFSS simulation and measurements. Good agreement has been observed to confirm the validity of our method.

Based upon the Kerckhoffs' principle, illegal users can get to know the embedding and detection algorithms except for a secret key. Then, it is possible to access to a host signal which may be selected from frequency components of a digital content for embedding watermark signal. Especially for a fingerprinting scheme which embeds user's information as a watermark, the selected components can be easily found by the observation of differently watermarked copies of a same content. In this scenario, it is reported that some non-linear collusion attacks will be able to remove/modify the embedded signal. In this paper, we study the security analysis of our previously proposed spread-spectrum (SS) fingerprinting scheme[1], [2] under the Kerckhoffs' principle, and reveal its drawback when an SS sequence is embedded in a color image. If non-linear collusion attacks are performed only to the components selected for embedding, the traceability is greatly degraded while the pirated copy keeps high quality after the attacks. We also propose a simple countermeasure to enhance the robustness against non-linear collusion attacks as well as possible signal processing attacks for the underlying watermarking method.

In this letter, an effective acoustic feedback cancellation algorithm is proposed based on the normalized sub-band adaptive filter (NSAF). To improve the confliction between fast convergence rate and low misalignment in the NSAF algorithm, a variable step size is designed to automatically vary according to the update state of the filter. The update state of the filter is adaptively detected via the normalized distance between the long term average and the short term average of the tap-weight vector. Simulation results demonstrate that the proposed algorithm has superior performance in terms of convergence rate and misalignment.

In this paper, an electromagnetic plane wave diffraction by finite number of loaded thick slits on infinitely long perfectly electric conductor (PEC) screen is analyzed. Here we formulate the problem by utilizing the Kobayashi Potential (KP) method, which is a kind of eigenfunction expansion method in terns of Weber-Schafheitlin discontinuous integrals. The multiple scattering contributions between the slits are analytically included in the formulation. The solution derived here may provide us with precise numerical result, so it may be considered as a reference solution to other numerical and approximate analyses.

This paper shows accuracy of using azimuth-variable path-loss fitting in white-space (WS) boundary-estimation. We perform experiments to evaluate this method, and demonstrate that the required number of sensors can be significantly reduced. We have proposed a WS boundary-estimation framework that utilizes sensors to not only obtain spectrum sensing data, but also to estimate the boundaries of the incumbent radio system (IRS) coverage. The framework utilizes the transmitter position information and pathloss fitting. The pathloss fitting describes the IRS coverage by approximating the well-known pathloss prediction formula from the received signal power data, which is measured using sensors, and sensor-transmitter separation distances. To enhance its accuracy, we have further proposed a pathloss-fitting method that employs azimuth variables to reflect the azimuth dependency of the IRS coverage, including the antenna directivity of the transmitter and propagation characteristics.