The ring Fp + uFp + + uk-1Fp may be of interest in coding theory, which have already been used in the construction of optimal frequency-hopping sequence. In this work, cyclic codes over Fp + uFp + + uk-1Fp which is an open problem posed in [1] are considered. Namely, the structure of cyclic code over Fp + uFp + + uk-1Fp and that of their duals are derived.

Optimizating the deployment of wireless sensor networks, which is one of the key issues in wireless sensor networks research, helps improve the coverage of the networks and the system reliability. In this paper, we propose an evolutionary algorithm based on modified t-distribution for the wireless sensor by introducing a deployment optimization operator and an intelligent allocation operator. A directed perturbation operator is applied to the algorithm to guide the evolution of the node deployment and to speed up the convergence. In addition, with a new geometric sensor detection model instead of the old probability model, the computing speed is increased by 20 times. The simulation results show that when this algorithm is utilized in the actual scene, it can get the minimum number of nodes and the optimal deployment quickly and effectively.Compared with the existing mainstream swarm intelligence algorithms, this method has satisfied the need for convergence speed and better coverage, which is closer to the theoretical coverage value.

The software reliability is the ability of the software to perform its required function under stated conditions for a stated period of time. In this paper, a hybrid methodology that combines both ARIMA and fractal models is proposed to take advantage of unique strength of ARIMA and fractal in linear and nonlinear modeling. Based on the experiments performed on the software reliability data obtained from literatures, it is observed that our method is effective through comparison with other methods and a new idea for the research of the software failure mechanism is presented.

Rough set theory is an important branch of data mining and granular computing, among which neighborhood rough set is presented to deal with numerical data and hybrid data. In this paper, we propose a new concept called inconsistent neighborhood, which extracts inconsistent objects from a traditional neighborhood. Firstly, a series of interesting properties are obtained for inconsistent neighborhoods. Specially, some properties generate new solutions to compute the quantities in neighborhood rough set. Then, a fast forward attribute reduction algorithm is proposed by applying the obtained properties. Experiments undertaken on twelve UCI datasets show that the proposed algorithm can get the same attribute reduction results as the existing algorithms in neighborhood rough set domain, and it runs much faster than the existing ones. This validates that employing inconsistent neighborhoods is advantageous in the applications of neighborhood rough set. The study would provide a new insight into neighborhood rough set theory.

To detect the natural clusters for irregularly shaped data distribution is a difficult task in pattern recognition. In this study, we propose an efficient clustering algorithm for irregularly shaped clusters based on the advantages of spectral clustering and Affinity Propagation (AP) algorithm. We give a new similarity measure based on neighborhood dispersion analysis. The proposed algorithm is a simple but effective method. The experimental results on several data sets show that the algorithm can detect the natural clusters of input data sets, and the clustering results agree well with that of human judgment.

A new Gray map between codes over F2+uF2+u2F2 and codes over F2 is defined. We prove that the Gray image of a linear (1-u2)-cyclic code over F2+uF2+u2F2 of length n is a binary distance invariant linear quasi-cyclic code. We also prove that, if n is odd, then every binary code which is the Gray image of a linear cyclic code over F2+uF2+u2F2 of length n is equivalent to a quasi-cyclic code.

We report for the first time the design, process and characterization of InP-based micrometer emitter InGaAlAs/GaAsSb/InP Double HBTs (DHBTs) and their microwave performance. The layer structure not only allows the implementation of InP collector free of current blocking, but also enables small turn-on voltage and ballistic launching of electrons due to the positive conduction band discontinuity of emitter to base. The DHBT structure was grown on nominal (001) InP substrates using MBE. Solid Si and CBr4 gas were used for n-type and p-type doing respectively. Fabricated large DHBTs showed high DC gain (> 80), small turn-on voltage 0.62 V, almost zero offset voltage, and nearly ideal base and collector current characteristics (ideality factors 1.0 for both B-E and B-C junctions). Small DHBTs demonstrated VCEO > 8 V and stable operation at high current density exceeding 100 kA/cm2. Maximum fT of 57 GHz and maximum fmax of 66 GHz were achieved from 1 20 µm2 devices at similar bias condition: JC = 8.0 104 A/cm2 and VCE =3.5 V. The InGaAlAs/GaAsSb/InP DHBTs appear to be a very promising HBT solution having simultaneous excellent RF and DC performances.

Fractals are mathematical or natural objects that are made of parts similar to the whole in certain ways. In this paper a software reliability forecasting method of software failure is proposed based on predictability of fractal time series. The empirical failure data (three data sets of Musa's) are used to demonstrate the performance of the reliability prediction. Compared with other methods, our method is effective.