To date, comparing and visualizing genome sequences remain challenging due to the large genome size. Existing approaches take advantage of the stable property of oligonucleotides and exhibit the main characteristics of the whole genome, yet they commonly fail to show progression patterns of the genome adjustably. This paper presents a novel visual encoding technique, which not only supports the binning process (phylogenetic analysis), but also allows the sequential analysis of the genome. The key idea is to regard the combination of each k-nucleotide and its reverse complement as a visual word, and to represent a long genome sequence with a list of local statistical feature vectors derived from the local frequency of the visual words. Experimental results on a variety of examples demonstrate that the presented approach has the ability to quickly and intuitively visualize DNA sequences, and to help the user identify regions of differences among multiple datasets.

This paper is concerned with the routing protocol design for large-scale wireless sensor and actor networks (WSANs). The actor-sensor-actor communication (ASAC) strategy is first proposed to guarantee the reliability of persistent actor-actor communication. To keep network connectivity and prolong network lifetime, we propose a dynamic gradient-based routing protocol (DGR) to balance the energy consumption of the network. With the different communication ranges of sensors and actors, the DGR protocol uses a data load expansion strategy to significantly prolong the network lifetime. The balance coefficient and the routing re-establishment threshold are also introduced to make the tradeoff between network lifetime and routing efficiency. Simulation results show the effectiveness of the proposed DGR protocol for unbalanced and persistent data transmission.

We propose two novel power control policies for a two-way amplify-and-forward (AF) relaying system, in which each node (two sources and one relay) is assumed to operate under both minimum and peak power constraints. Through the exploitation of instantaneous channel gains, the first policy can maximize the sum rate of the system. However, the instantaneous channel gains may be unavailable in a rapid time-varying system, where the first policy is inoperable. Consequently, a robust power control policy which requires only mean channel gains is proposed to maximize the upper bound of the average sum rate, and the properties of this policy are investigated. Simulation results show that, by comparison with the policy in which all the nodes use their peak transmit power, the proposed power control policies can provide considerable system performance improvement. Furthermore, the performance difference between the two proposed policies is negligible when the relay is close to one source.

By mapping a fixed polarity Reed-Muller (RM) expression into an onset table and studying the properties of the onset table, an algorithm is proposed to obtain a compact multi-level single-output mixed-polarity RM function by searching for and extracting the common variables using the onset table. Furthermore, by employing the multiplexer model, the algorithm is extended to optimize multi-level multi-output mixed-polarity RM forms. The proposed algorithm is implemented in C language and tested using some MCNC benchmarks. Experimental results show that the proposed algorithm can obtain a more compact RM form than that under fixed polarity. Compared with published results, the proposed algorithm makes a significant speed improvement, with a small increase in the number of literals.

The performance of the support vector regression (SVR) model is sensitive to the kernel type and its parameters. The determination of an appropriate kernel type and the associated parameters for SVR is a challenging research topic in the field of support vector learning. In this study, we present a novel method for simultaneous optimization of the SVR kernel function and its parameters, formulated as a mixed integer optimization problem and solved using the recently proposed heuristic ‘extremal optimization (EO)’. We present the problem formulation for the optimization of the SVR kernel and parameters, the EO-SVR algorithm, and experimental tests with five benchmark regression problems. The results of comparison with other traditional approaches show that the proposed EO-SVR method provides better generalization performance by successfully identifying the optimal SVR kernel function and its parameters.

It is difficult to analyze the harmonic distortion of a self-oscillating power amplifier (SOPA), because the SOPA is a hard nonlinear system without an external clock. The single or multiple sinusoidal inputs describing function (DF) method is commonly used to linearize a nonlinear element, but this method considers only the components at the same frequencies as the input signals (i.e., fundamental components) at the nonlinear element’s output. In this paper, besides the fundamental components, the third harmonic components are also calculated at the output of a comparator with three sinusoidal inputs, to create a linearized model of the comparator, and thus of the SOPA. The third harmonic distortion of the SOPA is calculated. The models of the zeroth and the first order SOPA are verified by behavioral simulation using MATLAB.

A multi-band/multi-mode single-pole nine-throw (SP9T) switch for GSM/UMTS (global system for mobile communications/universal mobile telecommunication system) systems is demonstrated. The switch consists of a GaAs 0.5 μm pseudomorphic high-electron mobility transistor (pHEMT) radio frequency (RF) switches module and Si complementary metal–oxide–semiconductor (COMS) digital module with an encoder and a DC boost circuit. High isolation and high linearity are achieved by a series-shunt switch structure and the DC boost circuit, respectively. The switch shows a measured insertion loss of 0.4 dB at 0.8 GHz for GSM transmit arms, 0.7 dB at 0.9 GHz and 0.9 dB at 1.8 GHz for GSM receive arms, and 0.6 dB at 1.8 GHz for UMTS arms. The switch introduces 2nd and 3rd harmonic suppression levels less than ?64 dBc at 37 dBm input power. Isolations between transmit and receive terminals are more than 48 dB when one transmit arm is activated. The size of the RF switches module is 1.5 mm×1.1 mm, and the size of the digital module is 1.3 mm×0.63 mm with gold bonding wires connecting these two modules.

We present a novel method to implement the radix-2 fast Fourier transform (FFT) algorithm on field programmable gate arrays (FPGA). The FFT architecture exploits parallelism by having more pipelined units in the stages, and more parallel units within a stage. It has the noticeable advantages of high speed and more efficient resource utilization by employing four ganged butterfly engines (GBEs), and can be well matched to the placement of the resources on the FPGA. We adopt the decimation-in-frequency (DIF) radix-2 FFT algorithm and implement the FFT processor on a state-of-the-art FPGA. Experimental results show that the processor can compute 1024-point complex radix-2 FFT in about 11 μs with a clock frequency of 200 MHz.

When interharmonics exist in power system signals, large errors emerge in traditional time domain reactive power measurement. In this paper, we present a novel time domain integral method with good effect of restraining interharmonics, synchronization error, and white noise, as well as the principle of the selection of the sampling periods when employing this approach. The current signal and phase-shifted voltage signal are reconstructed after the harmonic components of signals are extracted, so that the interharmonics are filtered. The influence of the synchronization error on the measurement is reduced through removing the weight coefficients of the reactive components. In the simulation, we apply several cosine windows to the proposed method and analyze signals containing both harmonics and interharmonics. The results show that, in the presence of interharmonics, synchronization error, and white noise (with a fundamental signal-to-noise ratio of 40 dB) all together, the relative errors are within the magnitude of 10^?4, which perfectly satisfies the practical requirement.

Transients in load and consequently in stack current have a significant impact on the performance and durability of fuel cells. The delays in auxiliary equipments in fuel cell systems (such as pumps and heaters) and back pressures degrade system performance and lead to problems in controlling tuning parameters including temperature, pressure, and flow rate. To overcome this problem, fast and delay-free systems are necessary for predicting control signals. In this paper, we propose a neural network model to control the stack terminal voltage as a proper constant and improve system performance. This is done through an input air pressure control signal. The proposed artificial neural network was constructed based on a back propagation network. A fuel cell nonlinear model, with and without feed forward control, was investigated and compared under random current variations. Simulation results showed that applying neural network feed forward control can successfully improve system performance in tracking output voltage. Also, less energy consumption and simpler control systems are the other advantages of the proposed control algorithm.

The acoustic emission (AE) method could be used to detect and locate partial discharges (PD) in cast-resin dry-type transformers. However, due to the high sound attenuation in the filled epoxy, the signal is prone to interference from external noises and thus, in practice, there is little possibility of detecting PD. In this study, two techniques were developed to alleviate the shortcomings of the AE method. First, a waveguide is installed on the high-voltage (HV) windings, so that the acoustic signals of PD will propagate to the AE sensors that are installed on both terminals of the waveguide. The location of the winding that has PD can then be detected from the difference in arrival time of the acoustic signals. Test results indicate that the waveguide technique is able to enhance the safety of a measurement system and offers the advantages of easy installation and higher flexibility. Second, a specially designed AE sensor pair is used to distinguish whether acoustic signals are generated by PD inside the HV winding or by the corona outside the transformers. Using these two techniques of waveguide and AE sensor pair not only greatly improves sensitivity but also increases the reliability of the measurement system. Practical test results show that the new techniques can be used to locate precisely the PD in HV windings.