Computing the level of trust between two indirectly connected users in an online social network (OSN) is a problem that has received considerable attention of researchers in recent years. Most algorithms focus on finding the most accurate prediction of trust; however, little work has been done to make them fast enough to be applied on today's very large OSNs. To address this need we propose a method for fast trust computation that is suitable for very large social networks. Our method uses min-max trust propagation strategies along with the landmark based method. Path strength of every node is pre-computed to and from a small set of reference users or landmarks. Using these pre-computed values, we estimate the strength of trust paths from the source user to in-neighbors of the target user. The final trust estimate is obtained by aggregating information from most reliable in-neighbors of the target user. We also describe how the landmark based method can be used for fast trust computation according to other trust propagation models. Experiments on a variety of real social network datasets verify the efficiency and accuracy of our method.

Electromagnetic power transmission through two cyl-inder-penetrated circular apertures in parallel conducting planes is studied. The Weber transform and superposition principle are used to represent the scattered field. A set of simultaneous equations for the modal coefficients are constituted based on the mode-matching and boundary conditions. The whole integration path is slightly deformed into a new one below the positive real axis not to pass through the pole singularities encountered on the original path so that it is easily calculated by direct numerical quadrature. Computation shows the behaviors of power transmission in terms of aperture geometry and wavelength. The presented scheme is very amenable to numerical evaluations and useful for various electromagnetic scattering and antenna radiation analysis involved with singularity problems.

In this paper, online sparse Volterra system identification is proposed. For that purpose, the conventional adaptive projection-based algorithm with weighted l1 balls (APWL1) is revisited for nonlinear system identification, whereby the linear-in-parameters nature of Volterra systems is utilized. Compared with sparsity-aware recursive least squares (RLS) based algorithms, requiring higher computational complexity and showing faster convergence and lower steady-state error due to their long memory in time-invariant cases, the proposed approach yields better tracking capability in time-varying cases due to short-term data dependence in updating the weight. Also, when N is the number of sparse Volterra kernels and q is the number of input vectors involved to update the weight, the proposed algorithm requires O(qN) multiplication complexity and O(Nlog 2N) sorting-operation complexity. Furthermore, sparsity-aware least mean-squares and affine projection based algorithms are also tested.

This paper deals with the problem of underdetermined blind source separation (BSS) where the number of sources is unknown. We propose a BSS approach that simultaneously estimates the number of sources, separates the sources based on the sparseness of speech, estimates the direction of arrival of each source, and performs permutation alignment. We confirmed experimentally that reasonably good separation was obtained with the present method without specifying the number of sources.

Serial RapidIO (SRIO) is a high-performance interconnection standard for embedded systems. Cyclic Redundancy Check (CRC) provides protection for packet transmissions and impacts the device performances. In this paper, two CRC calculation strategies, based on adjustable slicing parallelization and simplified calculators, are proposed. In the first scheme, the temporary CRC result of the previous cycle (CPre) is considered as a dependent input for the new cycle and is combined with a specific segment of packet data before slicing parallelization. In the second scheme, which can reach a higher maximum working frequency, CPre is considered as an independent input and is separated from the calculation of packet data for further parallelization. Performance comparisons based on ASIC and FPGA implementations are demonstrated to show their effectiveness. Compared with the reference designs, more than 34.8% and 13.9% of average power can be improved by the two proposed schemes at 156.25MHz in 130nm technology, respectively.

In this paper, we propose a use of the group sparsity in adaptive learning of second-order Volterra filters for the nonlinear acoustic echo cancellation problem. The group sparsity indicates sparsity across the groups, i.e., a vector is separated into some groups, and most of groups only contain approximately zero-valued entries. First, we provide a theoretical evidence that the second-order Volterra systems tend to have the group sparsity under natural assumptions. Next, we propose an algorithm by applying the adaptive proximal forward-backward splitting method to a carefully designed cost function to exploit the group sparsity effectively. The designed cost function is the sum of the weighted group l1 norm which promotes the group sparsity and a weighted sum of squared distances to data-fidelity sets used in adaptive filtering algorithms. Finally, Numerical examples show that the proposed method outperforms a sparsity-aware algorithm in both the system-mismatch and the echo return loss enhancement.

Automated or semi-automated annotation is a practical solution for large-scale corpus construction. However, the special characteristics of Thai language, such as lack of word-boundary and sentence-boundary markers, trigger several issues in automatic corpus annotation. This paper presents a multi-stage annotation framework, containing two stages of chunking and three stages of tagging. The two chunking stages are pattern matching-based named entity (NE) extraction and dictionary-based word segmentation while the three succeeding tagging stages are dictionary-, pattern- and statist09812490981249ical-based tagging. Applying heuristics of ambiguity priority, NE extraction is performed first on an original text using a set of patterns, in the order of pattern ambiguity. Next, the remaining text is segmented into words with a dictionary. The obtained chunks are then tagged with types of named entities or parts-of-speech (PoS) using dictionaries, patterns and statistics. Focusing on the reduction of human intervention in corpus construction, our experimental results show that the dictionary-based tagging process can assign unique tags to 64.92% of the words, with the remaining of 24.14% unknown words and 10.94% ambiguously tagged words. Later, the pattern-based tagging can reduce unknown words to only 13.34% while the statistical-based tagging can solve the ambiguously tagged words to only 3.01%.

A joint superimposed sequence design, known as SuperImposed sequence for PAPR Reduction, or SIPR, using per-tone affine precoding technique is proposed to jointly estimate MIMO-OFDM channels and reduce the peak-to-average power ratio (PAPR) for MIMO-OFDM systems. The proposed technique optimizes the trade-off between BER, MSE of the channel estimate, and PAPR reduction performance. Moreover, it does not require side information to be transmitted for the removal of the sequence at the receiver, and the transmit redundancy can be as small as 1 symbol/subcarrier. The superimposed sequence is designed by solving a convex quadratically constrained quadratic programming problem and has a computational complexity comparable to previous technique using linear programming. It is shown that SIPR can be regarded as a generalization of the popular tone reservation (TR) technique, and thus, is able to outperform TR in terms PAPR reduction performance, with less transmit overhead. Simulation results and transmit redundancy analysis of SIPR and TR are shown to illustrate the efficacy of the proposed scheme.

The extensive study and design of Body Area Networks (BANs) and development of related applications have been an object of interest during the last few years. Indeed, the majority of applications have been developed to operate at frequencies up to X band. However nowadays, a new growing attention is being focused on moving the study of BANs to higher frequencies such as those in V andW bands. The characterization of the on-body propagation channel is therefore essential for the design of reliable mm-wave BAN systems. However the classical methods (FDTD, MoM, FEM) commonly used at lower frequencies are not computationally efficient at mm-wave due to the large amount of mesh elements needed to discretize an electrically large geometry such as the human body. To overcome this issue, a ray tracing technique, generally used for characterizing indoor propagation, has been used to analyze a specific channel: chest-to-belt link. The reliability of this high frequency method has been investigated in this paper considering three different test cases. Moreover, a comparison of simulations and measurements, both performed on a body centric scenario at 94GHz, is also presented as well.

Near range microwave imaging systems have broad application prospects in the field of concealed weapon detection, biomedical imaging, nondestructive testing, etc. In this paper, the technique of optimized sparse antenna array is applied to near range microwave imaging, which can greatly reduce the complexity of imaging systems. In detail, the paper establishes three-dimensional sparse array imaging geometry and corresponding echo model, where the imaging geometry is formed by arranging optimized sparse antenna array in elevation, scanning in azimuth and transmitting broadband signals in range direction; and by analyzing the characteristics of near range imaging, that is, the maximum interval of transmitting and receiving elements is limited by the range from imaging system to targets, we propose the idea of piecewise sparse line array; secondly, by analyzing the convolution principle, we develop a method of arranging piecewise sparse array which can generate the same distribution of equivalent phase centers as filled antenna array; then, the paper deduces corresponding imaging algorithm; finally, the imaging geometry and corresponding algorithm proposed in this paper are investigated and verified via numerical simulations and near range imaging experiments.

This paper proposes the antenna arrangement for 2×2 MIMO (Multiple-Input Multiple-Output) sensor and evaluates the detection performance based on raytracing simulation. In this arrangement, the transmitting and receiving antennas are placed closely. Two types of the arrangement are considered. In the first method, all of the transmitting and receiving antennas are located closely. In the second method, two sets of the antennas are placed separately, and each set has one transmitting and one receiving antennas. The numerical analysis of the indoor propagation based on the raytracing method is carried out. The path distribution and intrusion detection performance with the various antenna arrangements are evaluated for the human positions all over the room. The numerical analysis results show that the proposed antenna arrangements achieve the compact configuration of the sensor antenna system as well as high detection performance.

In terms of the transmission-line theory, a general synthesis of a new class of optimum Chebyshev-type ultra-wideband bandpass (UWB) filter prototype composed of multistage stepped-impedance resonators (SIRs) and two short-circuited shunt stubs positioned at input- and output- ports is presented. By the comparison of the real and theoretical transfer functions, the design/characteristic equations are obtained for the design of the proposed filter prototype rather than the traditional design tables. The explicit expressions of one-stage and two-stage filters are then derived and reported. Accordingly, bandpass filters with an arbitrary FBW (Fractional Bandwidth) and passband ripple can be easily designed by solving the design equations. As an example, a 10-degree Chebyshev distributed filter (two-stage filter) with an FBW of 110% is synthesized to meet FCC's outdoor mask. The synthesized circuit model are confirmed by a commercial circuit simulator and then optimized by an EM simulator, fabricated in microstrip line and characterized by the network analyzer. The good agreements between the measured and predicted frequency responses validate the effectiveness of newly proposed filter prototype and the corresponding synthesis technique. In addition, the designed filter exhibits good characteristics of comparatively low insertion loss, quite sharp skirt, very flat group delay and good stopband (especially in lower one) as well. It should be also highlighted that, compared with the conventional filters composed merely of parallel-coupled SIRs or shunt short-circuit-stubs, the new prototype can reduce the overall length of the filter by more than 3/4λg. Moreover, in terms of the presented design technique, the proposed filter prototype can be also used to easily realize the UWB filters with an FBW even greater than 110%.

This paper presents the shadowing analysis of a body area network (BAN) diversity antenna based on the statistical measurements of the human walking motion. First, the dynamic characteristics of the arm-swing motion were measured using human subjects, and a statistical analysis was then carried out using the measured data to extract useful information for the analysis of a BAN diversity antenna. Second, the analytical results of the shadowing effects of the BAN antenna were shown based on the statistical data of the swing motion. The difference between the typical and the realistic arm-swinging models significantly affected the bit error rate (BER) characteristic of the BAN antenna. To eliminate the shadowing caused by the movement of the arms, a BAN diversity antenna was used. Particular emphasis was placed on the evaluation of the spatial separation of the diversity antennas to attain reduction of the signal-to-noise ratio (SNR) required to achieve a specific BER performance, considering the combined outcome of shadowing and multipath fading unique to BAN antenna systems. We determined that an antenna angle separation of greater than 80° is required to reduce the shadowing effects when the diversity antenna is mounted at the left waist in a symmetrical configuration. Further, an antenna angle separation of 120° is required when the diversity antenna is mounted in an asymmetric configuration.

An S-band GaN on Si based 1kW-class SSPA system for space wireless applications is proposed. Since high-efficiency and high-reliability amplifier is one of the most important technologies for power and communication systems in a future space base station on a planet, compact, high-power, and high-efficiency SSPA is strongly requested instead of TWTA. Thus, we adopt GaN on Si based amplifier due to its remarkable material properties. At the beginning, thermal vacuum and radiation test of GaN on Si are conducted so as to confirm the space applicability. Fabricated SSPA system consists of eight 200W HPAs and coaxial waveguide power combiner. It achieves high efficiency such as 57% of drain efficiency and 87% of combining efficiency when RF output power achieves more than 60dBm. Furthermore, long-term stable operation and good phase noise characteristics are also confirmed.

For face recognition with a single training image per person, Collaborative Representation based Classification (CRC) has significantly less complexity than Extended Sparse Representation based Classification (ESRC). However, CRC gets lower recognition rates than ESRC. In order to combine the advantages of CRC and ESRC, we propose Extended Collaborative Representation based Classification (ECRC) for face recognition with a single training image per person. ECRC constructs an auxiliary intraclass variant dictionary to represent the possible variation between the testing and training images. Experimental results show that ECRC outperforms the compared methods in terms of both high recognition rates and low computation complexity.

Sparse representation has been studied within the field of signal processing as a means of providing a compact form of signal representation. This paper introduces a sparse representation based framework named Sparse Probabilistic Linear Discriminant Analysis in speaker recognition. In this latent variable model, probabilistic linear discriminant analysis is modified to obtain an algorithm for learning overcomplete sparse representations by replacing the Gaussian prior on the factors with Laplace prior that encourages sparseness. For a given speaker signal, the dictionary obtained from this model has good representational power while supporting optimal discrimination of the classes. An expectation-maximization algorithm is derived to train the model with a variational approximation to a range of heavy-tailed distributions whose limit is the Laplace. The variational approximation is also used to compute the likelihood ratio score of all trials of speakers. This approach performed well on the core-extended conditions of the NIST 2010 Speaker Recognition Evaluation, and is competitive compared to the Gaussian Probabilistic Linear Discriminant Analysis, in terms of normalized Decision Cost Function and Equal Error Rate.

In this paper, Hermite polynomial representation is proposed as an alternative way to represent finite fields of characteristic two. We show that multiplication in Hermite polynomial representation can be achieved with subquadratic space complexity. This representation enables us to find binomial or trinomial irreducible polynomials which allows us faster modular reduction over binary fields when there is no desirable such low weight irreducible polynomial in other representations. We then show that the product of two elements in Hermite polynomial representation can be performed as Toeplitz matrix-vector product. This representation is very interesting for NIST recommended binary field GF(2571) since there is no ONB for the corresponding extension. This representation can be used to obtain more efficient finite field arithmetic.

Reverberation chambers that easily create multipath-rich environments are suggested as test environments for the performance evaluation of multiple-input multiple-output (MIMO) terminals. However, the propagation environment characteristic is difficult to control in conventional reverberation chambers. In this paper, we propose an improved double-layered reverberation chamber to control the arrival wave distribution in addition to the cross-polarization power ratio (XPR). We show the design method of the double-layered reverberation chamber and the experimental results of the propagation environment control using our constructed measurement system.

Spatial correlation is an index for evaluating performance of multi-antenna systems. Although various equations exist, the distinction remains evasive. This paper presents applicable condition of equations for spatial correlation coefficient considering propagation channels. We reveal that under Rayleigh fading environments, the spatial correlation is properly evaluated by the equation based on three-dimensional radiation patterns, however, under environments with strong direct waves, the equation based on the channel matrix should be used for the evaluation.

Microwaves have typically been used for communications and radar, but nowadays are given much attention to energy transfer applications. This paper describes microwave power transfer from a satellite to Earth that is visualized as a solar power satellite system (SPSS). After the system configuration is explained, unique engineering features are presented. Then, some contributions made by Japanese community are introduced, focusing on microwave and antenna engineering. As SPSS will handle high power levels at microwave frequency, and so components should be mass-produced to reduce the cost, then we need to shift our paradigm on the technology involved. Finally, the roadmap to a commercial SPSS is discussed.