A triplexer is presented by using bandpass filters (BPFs) which consist of two-stage of wideband resonator and additional open-circuited stubs. The resonator is firstly proposed by using a coupled-line and an inductive element loaded transmission line. This resonator produces the wide passband by a dual-mode resonance, high attenuation level at stopbands, and the steepness at the edge of the passband due to the attenuation poles. In order to understand the behavior of the resonator, the conditions for resonances and attenuation poles are especially solved and their current densities are analyzed by an electromagnetic simulation. Secondly, three types of wideband BPFs are constituted and finally a wideband triplexer is composed by using these BPFs. The basic characteristics of the proposed BPFs and the matching methodology enable to realize the triplexer whose desired passbands are around 3.1-5.1 GHz, 5.85-7.85 GHz, and 8.6-10.6 GHz with high isolation performance at the other passbands. The proposed triplexer is predominance in the flexible bandwidth or wide operating frequency range. All the BPFs and the triplexer are implemented on a planar printed circuit board assuming the use of the microstrip line structure.

The reputation-based majority-voting approach is a promising solution for detecting malicious workers in a cloud system. However, this approach has a drawback in that it can detect malicious workers only when the number of colluders make up no more than half of all workers. In this paper, we simulate the behavior of a reputation-based method and mathematically analyze its accuracy. Through the analysis, we observe that, regardless of the number of colluders and their collusion probability, if the reputation value of a group is significantly different from those of other groups, it is a completely honest group. Based on the analysis result, we propose a new method for distinguishing honest workers from colluders even when the colluders make up the majority group. The proposed method constructs groups based on their reputations. A group with the significantly highest or lowest reputation value is considered a completely honest group. Otherwise, honest workers are mixed together with colluders in a group. The proposed method accurately identifies honest workers even in a mixed group by comparing each voting result one by one. The results of a security analysis and an experiment show that our method can identify honest workers much more accurately than a traditional reputation-based approach with little additional computational overhead.

We consider the problem of deciding whether a query can be rewritten by a nondeterministic view. It is known that rewriting is decidable if views are given by single-valued non-copying devices such as compositions of single-valued extended linear top-down tree transducers with regular look-ahead, and queries are given by deterministic MSO tree transducers. In this paper, we extend the result to the case that views are given by nondeterministic devices that are not always single-valued. We define two variants of rewriting: universal preservation and existential preservation, and discuss the decidability of them.

In this paper a new method for noise removal from single-trial event-related potentials recorded with a multi-channel electroencephalogram is addressed. An observed signal is separated into multiple signals with a multi-channel Wiener filter whose coefficients are estimated based on parameter estimation of a probabilistic generative model that locally models the amplitude of each separated signal in the time-frequency domain. Effectiveness of using prior information about covariance matrices to estimate model parameters and frequency dependent covariance matrices were shown through an experiment with a simulated event-related potential data set.

The most famous silhouette puzzle is the tangram, which originated in China more than two centuries ago. From around the same time, there is a similar Japanese puzzle called Sei Shonagon Chie no Ita. Both are derived by cutting a square of material with straight incisions into seven pieces of varying shapes, and each can be decomposed into sixteen non-overlapping identical right isosceles triangles. It is known that the pieces of the tangram can form thirteen distinct convex polygons. We first show that the Sei Shonagon Chie no Ita can form sixteen. Therefore, in a sense, the Sei Shonagon Chie no Ita is more expressive than the tangram. We also propose more expressive patterns built from the same 16 identical right isosceles triangles that can form nineteen convex polygons. There exist exactly four sets of seven pieces that can form nineteen convex polygons. We show no set of seven pieces can form at least 20 convex polygons, and demonstrate that eleven pieces made from sixteen identical isosceles right triangles are necessary and sufficient to form 20 convex polygons. Moreover, no set of six pieces can form nineteen convex polygons.

An (≤n,≤ω)-one-time secure broadcast encryption scheme (BES) allows a sender to choose any subset of receivers so that only the designated users can decrypt a ciphertext. In this paper, we first show an efficient construction of an (≤n,≤ω)-one-time secure BES with general ciphertext sizes. Specifically, we propose a generic construction of an (≤n,≤ω)-one-time secure BES from key predistribution systems (KPSs) when its ciphertext size is equal to integer multiple of the plaintext size, and our construction includes all known constructions. However, there are many possible combinations of the KPSs to realize the BES in our construction methodology, and therefore, we show that which combination is the best one in the sense that secret-key size can be minimized. Our (optimized) construction provides a flexible parameter setup (i.e. we can adjust the secret-key sizes) by setting arbitrary ciphertext sizes based on restrictions on channels such as channel capacity and channel bandwidth.

To study the similarity between queries and retrieved masses, we design an interactive CBIR (Content-based Image Retrieval) CADx (Computer-aided Diagnosis) system using relevance feedback for the characterization of breast masses in ultrasound (US) images based on radiologists' visual similarity assessment. The CADx system retrieves masses that are similar to query masses from a reference library based on six computer-extracted features that describe the texture, width-to-height, and posterior shadowing of the mass. The k-NN retrieval with Euclidean distance similarity measure and the Rocchio relevance feedback algorithm (RRF) are used. To train the RRF parameters, the similarities of 1891 image pairs from 62 (31 malignant and 31 benign) masses are rated by 3 MQSA (Mammography Quality Standards Act) radiologists using a 9-point scale (9=most similar). The best RRF parameters are chosen based on 3 observer experiments. For testing, 100 independent query masses (49 malignant and 51 benign) and 121 reference masses on 230 (79 malignant and 151 benign) images were collected. Three radiologists rated the similarity between the query masses and the computer-retrieved masses. Average similarity ratings without and with RRF were 5.39 and 5.64 for the training set and 5.78 and 6.02 for the test set, respectively. Average AUC values without and with RRF were, respectively, 0.86±0.03 and 0.87±0.03 for the training set and 0.91±0.03 and 0.90±0.03 for the test set. On average, masses retrieved using the CBIR system were moderately similar to the query masses based on radiologists' similarity assessments. RRF improved the similarity of the retrieved masses.

A novel scheme to implement a filter bank multicarrier/offset quadrature amplitude modulation (FBMC/OQAM) transmission system is proposed. This is achieved by replacing the existing polyphase filter banks based on FFT/IFFT with fast filter bank (FFB) in order to utilize its good properties such as cascaded structure and high frequency selectivity with a comparable complexity as FFT/IFFT. Although this topic is not addressed in the literature, the impulse response of the prototype filter for each stage within FFB can still be obtained by using an optimization technique, which is used to minimize the distortion caused by intersymbol and interchannel interferences (ISI and ICI) of the proposed FBMC/OQAM transmission system, subject to allowable ripples in the passband and stopband. As a result, the relationship between two-path prototype filters in each subfilter should be modified with a general form accordingly. Simulations show that the number of multiplications required by the proposed scheme is smaller than that needed by the polyphase filter banks solution based on FFT/IFFT. Furthermore, the suitability of the design of prototype filters and the validation can be also supported by the results.

In this paper, by jointly considering power allocation and network selection, we address the energy efficiency maximization problem in dynamic and heterogeneous wireless networks, where user equipments are typically equipped with multi-homing capability. In order to effectively deal with the dynamics of heterogeneous wireless networks, a stochastic optimization problem is formulated that optimizes the long-term energy efficiency under the constraints of system stability, peak power consumption and average transmission rate. By adopting the parametric approach and Lyapunov optimization, we derive an equivalent optimization problem out of the original problem and then investigate its optimal resource allocation. Then, to reduce the computational complexity, a suboptimal resource allocation algorithm is proposed based on relaxed optimization, which adapts to time-varying channels and stochastic traffic without requiring relevant a priori knowledge. The simulation results demonstrate the theoretical analysis and validate the adaptiveness of our proposed algorithm.

Operating swarm robots has the virtues of improved performance, fault tolerance, distributed sensing, and so on. The problem is, high overall system costs are the main barrier in managing a system of foraging swarm robots. Moreover, its control algorithm should be scalable and reliable as the foraging (search) spaces become wider. This paper analyzes a nature-inspired cooperative method to reduce the operating costs of the foraging swarm robots through simulation experiments. The aim of this research is to improve efficiency of mechanisms for reducing the cost by developing a new algorithm for the synergistic cooperation of the group. In this paper, we set the evaluation index of energy efficiency considering that the mission success rate as well as energy saving is important. The value is calculated as the number of successful operations against the total consumption of energy in order to also guarantee optimized for the work processing power than the one simple goal of energy savings. The method employs a behavioral model of a honey bee swarm to improve the energy efficiency in collecting crops or minerals. Experiments demonstrate the effectiveness of the approach. The experiment is set a number of strategies to combine the techniques to the proposed and conventional methods. Considering variables such as the area of search space and the size of a swarm, the efficiency comparison test is performed. As the result, the proposed method showed the enhanced energy efficiency of the average 76.9% as compared to the conventional simple model that means reduction of the recharging cost more than 40%.

Synthetic aperture radar (SAR) imagery is significantly deteriorated by the random phase noises which are generated by the frequency jitter of the transmit signal and atmospheric turbulence. In this paper, we recast the SAR imaging problem via the phase-corrupted data as for a special case of quadratic compressed sensing (QCS). Although the quadratic measurement model has potential to mitigate the effects of the phase noises, it also leads to a nonconvex and quartic optimization problem. In order to overcome these challenges and increase reconstruction robustness to the phase noises, we proposed a QCS-based SAR imaging algorithm by greedy local search to exploit the spatial sparsity of scatterers. Our proposed imaging algorithm can not only avoid the process of precise random phase noise estimation but also acquire a sparse representation of the SAR target with high accuracy from the phase-corrupted data. Experiments are conducted by the synthetic scene and the moving and stationary target recognition Sandia laboratories implementation of cylinders (MSTAR SLICY) target. Simulation results are provided to demonstrate the effectiveness and robustness of our proposed SAR imaging algorithm.

This paper considers an optimal stabilization problem of quantitative discrete event systems (DESs) under the influence of disturbances. We model a DES by a deterministic weighted automaton. The control cost is concerned with the sum of the weights along the generated trajectories reaching the target state. The region of weak attraction is the set of states of the system such that all trajectories starting from them can be controlled to reach a specified set of target states and stay there indefinitely. An optimal stabilizing controller is a controller that drives the states in this region to the set of target states with minimum control cost and keeps them there. We consider two control objectives: to minimize the worst-case control cost (1) subject to all enabled trajectories and (2) subject to the enabled trajectories starting by controllable events. Moreover, we consider the disturbances which are uncontrollable events that rarely occur in the real system but may degrade the control performance when they occur. We propose a linearithmic time algorithm for the synthesis of an optimal stabilizing controller which is robust to disturbances.

This paper proposes two linearity enhancement techniques for open-loop amplifiers. One technique is nonlinearity cancellation. An amplifier with reversed nonlinearity is proposed to cascade with a conventional common source amplifier. The product of these two nonlinear gains demonstrates much higher linearity. It achieves a SFDR of 71 dB when differential output range is 600 mV. Compared with the conventional common source amplifier, about 24 dB improvement is achieved. Another proposed technique is gain adapting. An input amplitude detector utilizing second order nonlinearity is combined with a source-degenerated amplifier. It can adjust the gain automatically according to the input amplitude, and compensate the gain compression when the input amplitude becomes larger. A SFDR of 69 dB is realized when the differential output range is 600 mV. An improvement of 23 dB is achieved after gain is adapted. Furthermore, mismatch calibration for the two proposed linearity enhancement techniques is investigated. Finally, comparison between two proposed amplifiers is introduced. The amplifier with nonlinearity cancellation has advantage in large signal range while the amplifier utilizing gain adapting is more competitive on accurate calibration, fast response and low noise.

We present circuit implementations for computing exponentials and logarithms suitable for rapid single-flux-quantum (RSFQ) logic. We propose hardware algorithms based on the sequential table-lookup (STL) method using the radix-2 signed-digit representation that achieve high-throughput, digit-serial calculations. The circuits are implemented by processing elements formed in systolic-array-like, regularly-aligned pipeline structures. The processing elements are composed of adders, shifters, and readouts of precomputed constants. The iterative calculations are fully overlapped, and throughputs approach the maximum throughput of serial processing. The circuit size for calculating significand parts is estimated to be approximately 5-10 times larger than that of a bit-serial floating-point adder or multiplier.

We propose an exact algorithm to determine the satisfiability of oblivious read-twice branching programs. Our algorithm runs in $2^{left(1 - Omega(rac{1}{log c}) ight)n}$ time for instances with n variables and cn nodes.

This paper presents a method for registering retinal images. Retinal image registration is crucial for the diagnoses and treatments of various eye conditions and diseases such as myopia and diabetic retinopathy. Retinal image registration is challenging because the images have non-uniform contrasts and intensity distributions, as well as having large homogeneous non-vascular regions. This paper provides a new retinal image registration method by effectively combining expectation maximization principal component analysis based mutual information (EMPCA-MI) with salient features. Experimental results show that our method is more efficient and robust than the conventional EMPCA-MI method.

It is known that, using just a deck of cards, an arbitrary number of parties with private inputs can securely compute the output of any function of their inputs. In 2009, Mizuki and Sone constructed a six-card COPY protocol, a four-card XOR protocol, and a six-card AND protocol, based on a commonly used encoding scheme in which each input bit is encoded using two cards. However, up until now, there are no known results to construct a set of COPY, XOR, and AND protocols based on a two-card-per-bit encoding scheme, which all can be implemented using only four cards. In this paper, we show that it is possible to construct four-card COPY, XOR, and AND protocols using polarizing plates as cards and a corresponding two-card-per-bit encoding scheme. Our protocols use a minimum number of cards in the setting of two-card-per-bit encoding schemes since four cards are always required to encode the inputs. Moreover, we show that it is possible to construct two-card COPY, two-card XOR, and three-card AND protocols based on a one-card-per-bit encoding scheme using a common reference polarizer which is a polarizing material accessible to all parties.

This paper proposes an appearance-based novel descriptor for estimating head orientation. Our descriptor is inspired by the Weber-based feature, which has been successfully implemented for robust texture analysis, and the gradient which performs well for shape analysis. To further enhance the orientation differences, we combine them with an analysis of the intensity deviation. The position of a pixel and its intrinsic intensity are also considered. All features are then composed as a feature vector of a pixel. The information carried by each pixel is combined using a covariance matrix to alleviate the influence caused by rotations and illumination. As the result, our descriptor is compact and works at high speed. We also apply a weighting scheme, called Block Importance Feature using Genetic Algorithm (BIF-GA), to improve the performance of our descriptor by selecting and accentuating the important blocks. Experiments on three head pose databases demonstrate that the proposed method outperforms the current state-of-the-art methods. Also, we can extend the proposed method by combining it with a head detection and tracking system to enable it to estimate human head orientation in real applications.

The purpose of this study is to make available a fall risk assessment for stroke patients during walking using an accelerometer. We assessed gait parameters, normalized root mean squared acceleration (NRMSA) and berg balance scale (BBS) values. Walking dynamics were better reflected in terms of the risk of falls during walking by NRMSA compared to the BBS.

We present a hierarchical replicated state machine (H-RSM) and its corresponding consensus protocol D-Paxos for replication across multiple data centers in the cloud. Our H-RSM is based on the idea of parallel processing and aims to improve resource utilization. We detail D-Paxos and theoretically prove that D-Paxos implements an H-RSM. With batching and logical pipelining, D-Paxos efficiently utilizes the idle time caused by high-latency message transmission in a wide-area network and available bandwidth in a local-area network. Experiments show that D-Paxos provides higher throughput and better scalability than other Paxos variants for replication across multiple data centers. To predict the optimal batch sizes when D-Paxos reaches its maximum throughput, an analytical model is developed theoretically and validated experimentally.