To characterize and predict the dynamics of the nonlinear polarization rotation in SOAs, an experimental method based on the frequency response technique and a model based on the density matrix and effective index formalisms are presented. Both determine the angular displacement, at the Poincare Sphere, that produces the evolution of the polarization of the output signal.

Ridge optical waveguides (OWGs) of fluorinated polyimides were deposited on a quartz crystal microbalance (QCM), and a hybrid sensor employing the OWG spectroscopy and the QCM technique was prepared. A polyvinyl alcohol (PVA) film with CoCl2 was deposited on the OWG, and humidity sensing characteristics were investigated. White light was entered into the waveguide and the output light spectra was observed. The output light intensity markedly changed because of the chromism of CoCl2 by humidity sorption. During the output light measurement, the QCM frequency was monitored simultaneously. The humidity dependences of the QCM frequency and output light were also investigated in a range from 10% to 70%. Furthermore, the response to hydrofluoroether (HFE) was observed, and the change in the output light was hardly observed because CoCl2 does not exhibit chromism in HFE sorption.

This letter proposes a spread spectrum audio watermarking robust against playback speed modification (PSM) attack which introduces both time-scale modification and pitch shifting. Two important improvements are exploited to achieve this robustness. The first one is selecting an embedding region according to the stable characteristic of the audio energy. The second one is stretching the pseudo-random noise sequence to match the length of the embedding region before embedding and detection. Experimental results show that our method is highly robust to common audio signal processing attacks and synchronization attacks including PSM, cropping, trimming and jittering.

This paper presents a method of generating sets of orthogonal and zero-correlation zone (ZCZ) periodic real-valued sequences of period 2n, n ≥ 1. The sequences admit a fast correlation algorithm and the sets of sequences achieve the upper bound on family size. A periodic orthogonal sequence has the periodic autocorrelation function with zero sidelobes, and a set with orthogonal sequences whose mutual periodic crosscorrelation function at zero shift is zero. Similarly, a ZCZ set is the set of the sequences with zero-correlation zone. In this paper, we derive the real-valued periodic orthogonal sequences of period 2n from a real-valued Huffman sequence of length 2ν+1, ν being a positive integer and ν ≥ n, whose aperiodic autocorrelation function has zero sidelobes except possibly at the left and right shift-ends. The orthogonal and ZCZ sets of real-valued periodic orthogonal sequences are useful in various systems, such as synchronous code division multiple access (CDMA) systems, quasi-synchronous CDMA systems and digital watermarkings.

In this paper, we consider the signal processing algorithm on each subcarrier for the downlink of Multi-User Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MU-MIMO OFDM) system. A novel transmit scheme is proposed for the cancellation of Inter-User Interference (IUI) at the Base Station (BS). The improved performance of each user is obtained by optimizing the transmit scheme on each subcarrier, where the Particle Swarm Optimization (PSO) algorithm is employed to solve the constrained nonlinear optimization problem. Compared with the conventional Zero Forcing Dirty Paper Coding (ZF-DPC) having only single receive antenna at each Mobile Station (MS), the proposed scheme also applies the principle of DPC to cancel the IUI, but the MS users can be equipped with multiple receive antennas producing their increased receive SNR's. With the Channel State Information (CSI) being known at the BS and the MS, the eigenvalues for all the user channels are calculated first and then the user with the maximum eigenvalue is selected as the 1-st user. The remaining users are ordered and sequentially processed, where the transmit weights are generated from the previously selected users by the Particle Swarm Optimization (PSO) algorithm which ensures the transmit gain for each user as large as possible. The computational complexity analysis, BER performance and achievable sum-rate analysis of system verify the effectiveness of the proposed scheme.

Wireless sensor networks are comprised of several sensor nodes that communicate via wireless technology. Locating the sensor nodes is a fundamental problem in developing applications for wireless sensor networks. In this paper, we introduce a distributed localization scheme, called the Rectangle Overlapping Approach (ROA), using a mobile beacon with GPS and a directional antenna. The node locations are computed by performing simple operations that rely on the rotation angle and position of the mobile beacon. Simulation results show that the proposed scheme is very efficient and that the node positions can be determined accurately when the beacon follows a random waypoint movement model.

We developed a novel movement-imagery-based brain-computer interface (BCI) for untrained subjects without employing machine learning techniques. The development of BCI consisted of several steps. First, spline Laplacian analysis was performed. Next, time-frequency analysis was applied to determine the optimal frequency range and latencies of the electroencephalograms (EEGs). Finally, trials were classified as right or left based on β-band event-related synchronization using the cumulative distribution function of pretrigger EEG noise. To test the performance of the BCI, EEGs during the execution and imagination of right/left wrist-bending movements were measured from 63 locations over the entire scalp using eight healthy subjects. The highest classification accuracies were 84.4% and 77.8% for real movements and their imageries, respectively. The accuracy is significantly higher than that of previously reported machine-learning-based BCIs in the movement imagery task (paired t-test, p < 0.05). It has also been demonstrated that the highest accuracy was achieved even though subjects had never participated in movement imageries.

Multi-operand adders, which calculates the summation of more than two operands, usually consist of compressor trees which reduce the number of operands to two without any carry propagation, and a carry-propagate adder for the two operands in ASIC implementation. The former part is usually realized using full adders or (3;2) counters like Wallace-trees in ASIC, while adder trees or dedicated hardware are used in FPGA. In this paper, an approach to realize compression trees on FPGAs is proposed. In case of FPGA with m-input LUT, any counters with up to m inputs can be realized with one LUT per an output. Our approach utilizes generalized parallel counters (GPCs) with up to m inputs and synthesizes high-performance compressor trees by setting some intermediate height limits in the compression process like Dadda's multipliers. Experimental results show that the number of GPCs are reduced by up to 22% compared to the existing heuristic. Its effectivity on reduction of delay is also shown against existing approaches on Altera's Stratix III.

Network testbeds have been used for network measurement and experiments. In such testbeds, resources, such as CPU, memory, and I/O interfaces, are shared and virtualized to maximize node utility for many users. A few studies have investigated the impact of virtualization on precise network measurement and understood Internet traffic characteristics on virtualized testbeds. Although scheduling latency and heavy loads are reportedly affected in precise network measurement, no clear conditions or criteria have been established. Moreover, empirical-statistical criteria and methods that pick out anomalous cases for precise network experiments are required on userland because virtualization technology used in the provided testbeds is hardly replaceable. In this paper, we show that ‘oversize packet spacing’, which can be caused by CPU scheduling latency, is a major cause of throughput instability on a virtualized network testbed even when no significant changes occur in well-known network metrics. These are unusual anomalies on virtualized network environment. Empirical-statistical analysis results accord with results at previous work. If network throughput is decreased by the anomalies, we should carefully review measurement results. Our empirical approach enables anomalous cases to be identified. We present CPU availability as an important criterion for estimating the anomalies.

Inter-satellite link (ISL) is an important part of the next generation global navigation satellite system (GNSS). In this paper, key technologies of GNSS ISL ranging and time synchronization are researched. Considering that Ka frequency band is used for ISL, a fixed topology is designed and a new time division duplex (TDD) mode is proposed after analyzing the characteristics of GNSS constellations. A novel method called Non-coherent Dual One-way Measuring (NC-DOWM) is applied to this TDD mode. In addition, relevant mathematical formulas, error models and error compensation are discussed in detail. It is found that the proposed NC-DOWM method for GNSS ISL ranging and time synchronization outperforms the current method for GPS in terms of channel utilization efficiency and measuring precision. Furthermore, the presented method has excellent anti-interference capability and engineering feasibility, which can provide a strong technical support for the ISL of the next generation GNSS.

WSNs (Wireless Sensor Networks) are becoming more widely used in various fields, and localization is a crucial and essential issue for sensor network applications. In this letter, we propose a low-complexity localization mechanism for WSNs that operate in 3D (three-dimensional) space. The basic idea is to use aerial vehicles that are deliberately equipped with anchor nodes. These anchors periodically broadcast beacon signals containing their current locations, and unknown nodes receive these signals as soon as the anchors enter their communication range. We estimate the locations of the unknown nodes based on the proposed scheme that transforms the 3D problem into 2D computations to reduce the complexity of 3D localization. Simulated results show that our approach is an effective scheme for 3D self-positioning in WSNs.

Dye-sensitized solar cells are expected to be used as future clean energy. Most of the researchers in the field of the dye-sensitized solar cells use Ruthenium complex as dye. On the other hand, we have proposed the dye-sensitized solar cells using natural dyes, such as dye of red-cabbage and curcumin. In this paper, we use new electrolyte solution for the solar cells using dye of curcumin. As a result, a conversion efficiency of about 1.3% has been obtained (light source: halogen lamp).

In multiuser cognitive radio (CR) networks, we address the problem of joint transmit beamforming (BF) and power control (PC) for secondary users (SUs) when they are allowed to transmit simultaneously with primary users (PUs). The objective is to optimize the network sum rate under the interference constraints of PUs, which is a nonconvex problem. Iterative dual subgradient (IDuSuG) algorithm is proposed by iteratively performing BF and PC to optimize the sum rate, among which minimum mean square error (MMSE) or virtual power-weighed projection (VIP2) is used to design beamformers and subgradient method is used to control the power. VIP2 algorithm is devised for the case in which the interference caused by MMSE beamformer exceeds the threshold. Moreover, channel uncertainty due to lack of cooperation is considered. A closed-form worst-case expression is derived, with which the uncertainty optimization problem is transformed into a certain one. A robust algorithm based on IDuSuG is provided by modifying updates in iterative process. Furthermore, second-order cone programming approximation (SOCPA) method is proposed as another robust algorithm. Typical network models are approximated to SOCP problems and solved by interior-point method. Finally the network sum rates for different PU and SU numbers are assessed for both certainty and uncertainty channel models by simulation.

This paper investigates a new method for fusion of scores generated by multiple classification sub-systems that help to further reduce the classification error rate in Spoken Language Recognition (SLR). In recent studies, a variety of effective classification algorithms have been developed for SLR. Hence, it has been a common practice in the National Institute of Standards and Technology (NIST) Language Recognition Evaluations (LREs) to fuse the results from several classification sub-systems to boost the performance of the SLR systems. In this work, we introduce a discriminative performance measure to optimize the performance of the fusion of 7 language classifiers developed as IIR's submission to the 2009 NIST LRE. We present an Error Corrective Fusion (ECF) method in which we iteratively learn the fusion weights to minimize error rate of the fusion system. Experiments conducted on the 2009 NIST LRE corpus demonstrate a significant improvement compared to individual sub-systems. Comparison study is also conducted to show the effectiveness of the ECF method.

The noise performance of common source and cascode topology 60 GHz LNAs is analyzed and verified. The analysis result shows that the noise performance of the cascode topology is degraded at high frequency due to the inter-stage node capacitance. The analysis result is verified by experimental results. A three-stage LNA employing two noise-matched CS stages and a cascode stage is proposed. For comparison a conventional two-stage cascode LNA is also been studied with the measurement-based model. The measured results of the proposed LNA show that an input and output matching of less than -10 dB, a maximum gain of 9.7 dB and a noise figure (NF) of 3.2 dB are obtained with a power consumption of 30 mW from a 1.2-V supply voltage. Compared to the conventional cascode LNA, an improvement of 2.3-dB for NF and 1.9-dB for power gain are realized. Both the proposed and conventional LNAs are implemented in 65 nm CMOS process.

In the framework of supervisory control of timed discrete event systems (TDESs), a supervisor decides the set of events to be enabled to occur and the set of events to be forced to occur in order for a given specification to be satisfied. In this paper, we consider decentralized supervisory control of TDESs where enforcement decisions of local supervisors are fused by the AND rule or the OR rule. We derive existence conditions of a decentralized supervisor under these decision fusion rules.

Cognitive radio is a promising approach to ensuring the coexistence of heterogeneous wireless networks since it can perceive wireless conditions and freely switch among different network modes. When there are many network opportunities, how to decide the appropriate network selection for CR user's current service is the main problem we study in this paper. We make full use of the intelligent characteristic of CR user and propose a fuzzy learning based network selection scheme, in which the network selection choice is made based on the estimated evaluations of available networks. Multiple factors are considered when estimating these evaluations. Both the outer environment factors directly sensed by CR user (signal strength of the available network and network mode), and also the factor that cannot be determined beforehand and is learnt by our scheme (the bandwidth allocated by the optional network) are considered. From several interactions with the wireless environment, the experience of network selection behavior is accumulated which will direct our scheme to make a proper decision of the network. Two simulations verify that our scheme could not only guarantee a better bandwidth requirement of CR user compared with other three network selection methods, but also shows it to be a reasonable scheme for utilizing the available resources of these networks.

The on-chip interconnection network (OCIN) is an integrated solution for system-on-chip (SoC) designs. The buffer architecture and size, however, dominate the performance of OCINs and affect the design of routers. This work analyzes different buffer architectures and uses a data-link two-level FIFO (first-in first-out) buffer architecture to implement high-performance routers. The concepts of shared buffers and multiple accesses for buffers are developed using the two-level FIFO buffer architecture. The proposed two-level FIFO buffer architecture increases the utilities of the storage elements via the centralized buffer organization and reduces the area and power consumption of routers to achieve the same performance achieved by other buffer architectures. Depending on a cycle-accurate simulator, the proposed data-link two-level FIFO buffer can realize performance similar to that of the conventional virtual channels, while using 25% of the buffers. Consequently, the two-level FIFO buffer can achieve about 22% power reduction compared with the similar performance of the conventional virtual channels using UMC 65 nm CMOS technology.

This paper proposes a single-carrier transmission method based on an overlap frequency-domain equalizing (FDE) and a coherent averaging. FDE is a block-based equalizing technique using discrete Fourier transform. A cyclic prefix is often used to avoid inter-block interference under multipath channel conditions, which reduces transmission efficiency. An overlap FDE is a technique to avoid the cyclic prefix insertion, but the residual interferences often exist after the FDE processing according to the channel conditions. The method proposed in this paper suppresses the residual interferences by applying a coherent averaging to the FDE outputs and improve the equalization performances. Computer simulation shows the effect of the proposed technique over the multipath channels.

This paper presents a novel method for reconstructing 3D geometry of camera motion and human-face model from a video sequence. The approach combines the concepts of Powell's line minimization with gradient descent. We adapted the line minimization with bracketing used in Powell's minimization to our method. However, instead of bracketing and searching deep down a direction for the minimum point along that direction as done in their line minimization, we achieve minimization by bracketing and searching for the direction in the bracket which provides a lower energy than the previous iteration. Thus, we do not need a large memory as required by Powell's algorithm. The approach to moving in a better direction is similar to classical gradient descent except that the derivative calculation and a good starting point are not needed. The system's constraints are also used to control the bracketing direction. The reconstructed solution is further improved using the Levenberg Marquardt algorithm. No average face model or known-coordinate markers are needed. Feature points defining the human face are tracked using the active appearance model. Occluded points, even in the case of self occlusion, do not pose a problem. The reconstructed space is normalized where the origin can be arbitrarily placed. To use the obtained reconstruction, one can rescale the computed volume to a known scale and transform the coordinate system to any other desired coordinates. This is relatively easy since the 3D geometry of the facial points and the camera parameters of all frames are explicitly computed. Robustness to noise and lens distortion, and 3D accuracy are also demonstrated. All experiments were conducted with an off-the-shelf digital camera carried by a person walking without using any dolly to demonstrate the robustness and practicality of the method. Our method does not require a large memory or the use of any particular, expensive equipment.