The new three-phase 5-level current-source inverter (CSI) proposed in this paper was developed by connecting three separate single-phase 5-level CSIs in series, and its operational principle was analyzed. There are two major problems existing in current-source multilevel inverters, one is the complex PWM control method (2-logic to 3-logic conversion), and the other is the problem of current-unbalance between different levels. A simple current-balance control method via DC current feedback is applied in each single-phase 5-level CSI cell to implement the current-balance control between different levels. And to reduce the output current harmonics, POD PWM control technique was used. Simulation and experimental results showed that this new three-phase 5-level CSI topology operates correctly.

Passive system theory was applied to propose a new passive control method with nonlinear observer of the Permanent Magnet Synchronous Motor chaotic system. Through constructing a Lyapunov function, the subsystem of the Permanent Magnet Synchronous Motor chaotic system could be proved to be globally stable at the equilibrium point. Then a controller with smooth state feedback is designed so that the Permanent Magnet Synchronous Motor chaotic system can be equivalent to a passive system. To get the state variables of the controller, the nonlinear observer is also studied. It is found that the outputs of the nonlinear observer can approximate the state variables of the Permanent Magnet Synchronous Motor chaotic system if the system’s nonlinear function is a globally Lipschitz function. Simulation results showed that the equivalent passive system of Permanent Magnet Synchronous Motor chaotic system could be globally asymptotically stabilized by smooth state feedback in the observed parameter convergence condition area.

A new multi-step adaptive predictive control algorithm for a class of bilinear systems is presented. The structure of the bilinear system is converted into a simple linear model by using nonlinear support vector machine (SVM) dynamic approximation with analytical control law derived. The method does not need on-line parameters estimation because the system’s internal model has been transformed into an off-line global model. Compared with other traditional methods, this control law reduces on-line parameter estimating burden. In addition, its overall linear behavior treating method allows an analytical control law available and avoids on-line nonlinear optimization. Simulation results are presented in the article to illustrate the efficiency of the method.

Particle swarm optimization (PSO), like other evolutionary algorithms is a population-based stochastic algorithm inspired from the metaphor of social interaction in birds, insects, wasps, etc. It has been used for finding promising solutions in complex search space through the interaction of particles in a swarm. It is a well recognized fact that the performance of evolutionary algorithms to a great extent depends on the choice of appropriate strategy/operating parameters like population size, crossover rate, mutation rate, crossover operator, etc. Generally, these parameters are selected through hit and trial process, which is very unsystematic and requires rigorous experimentation. This paper proposes a systematic based on Taguchi method reasoning scheme for rapidly identifying the strategy parameters for the PSO algorithm. The Taguchi method is a robust design approach using fractional factorial design to study a large number of parameters with small number of experiments. Computer simulations have been performed on two benchmark functions—Rosenbrock function and Griewank function—to validate the approach.

Strategic alliance has suffered much instabilities since its first implementation. Scholars have carried out many embedded, precise and comprehensive researches from both theory and empiricism. Here we try to find certain stable solutions by employing game theory, in an attempt to construct theoretical bases for strategic alliance, which people called “one of the most important organizational innovation in the end of the 20th century” (Shi, 2001), to exploit its advantages in the process of globalization. Finally, this article puts forward some advices for its success.

There is increasing interest in using hyperspectral data for quantitative characterization of vegetation in spatial and temporal scopes. Many spectral indices are being developed to improve vegetation sensitivity by minimizing the background influence. The chlorophyll absorption continuum index (CACI) is such a measure to calculate the spectral continuum on which the analyses are based on the area of the troughs spanned by the spectral continuum. However, different values of CACI were obtained in this method because different positions of continuums were determined by different users. Furthermore, the sensitivity of CACI to agronomic parameters such as green leaf chlorophyll density (GLCD) has been reduced because the fixed positions of continuums are determined when the red edge shifted with the change in GLCD. A modified chlorophyll absorption continuum index (MCACI) is presented in this article. The red edge inflection point (REIP) replaces the maximum reflectance point (MRP) in near-infrared (NIR) shoulder on the CACI continuum. This MCACI has been proved to increase the sensitivity and predictive power of GLCD.

Landslide susceptibility map is one of the study fields portraying the spatial distribution of future slope failure susceptibility. This paper deals with past methods for producing landslide susceptibility map and divides these methods into 3 types. The logistic linear regression approach is further elaborated on by crosstabs method, which is used to analyze the relationship between the categorical or binary response variable and one or more continuous or categorical or binary explanatory variables derived from samples. It is an objective assignment of coefficients serving as weights of various factors under considerations while expert opinions make great difference in heuristic approaches. Different from deterministic approach, it is very applicable to regional scale. In this study, double logistic regression is applied in the study area. The entire study area is first analyzed. The logistic regression equation showed that elevation, proximity to road, river and residential area are main factors triggering landslide occurrence in this area. The prediction accuracy of the first landslide susceptibility map was showed to be 80%. Along the road and residential area, almost all areas are in high landslide susceptibility zone. Some non-landslide areas are incorrectly divided into high and medium landslide susceptibility zone. In order to improve the status, a second logistic regression was done in high landslide susceptibility zone using landslide cells and non-landslide sample cells in this area. In the second logistic regression analysis, only engineering and geological conditions are important in these areas and are entered in the new logistic regression equation indicating that only areas with unstable engineering and geological conditions are prone to landslide during large scale engineering activity. Taking these two logistic regression results into account yields a new landslide susceptibility map. Double logistic regression analysis improved the non-landslide prediction accuracy. During calculation of parameters for logistic regression, landslide density is used to transform nominal variable to numeric variable and this avoids the creation of an excessively high number of dummy variables.

Accuracy of a simulation strongly depends on the grid quality. Here, quality means orthogonality at the boundaries and quasi-orthogonality within the critical regions, smoothness, bounded aspect ratios and solution adaptive behaviour. It is not recommended to refine the parts of the domain where the solution shows little variation. It is desired to concentrate grid points and cells in the part of the domain where the solution shows strong gradients or variations. We present a simple, effective and computationally efficient approach for quadrilateral mesh adaptation. Several numerical examples are presented for supporting our claim.

The Hill cipher algorithm is one of the symmetric key algorithms that have several advantages in data encryption. However, a main drawback of this algorithm is that it encrypts identical plaintext blocks to identical ciphertext blocks and cannot encrypt images that contain large areas of a single color. Thus, it does not hide all features of the image which reveals patterns in the plaintext. Moreover, it can be easily broken with a known plaintext attack revealing weak security. This paper presents a variant of the Hill cipher that overcomes these disadvantages. The proposed technique adjusts the encryption key to form a different key for each block encryption. Visually and computationally, experimental results demonstrate that the proposed variant yields higher security and significantly superior encryption quality compared to the original one.

Boundary recovery is one of the main obstacles in applying the Delaunay criterion to mesh generation. A standard resolution is to add Steiner points directly at the intersection positions between missing boundaries and triangulations. We redesign the algorithm with the aid of some new concepts, data structures and operations, which make its implementation routine. Furthermore, all possible intersection cases and their solutions are presented, some of which are seldom discussed in the literature. Finally, numerical results are presented to evaluate the performance of the new algorithm.

Extension of a B-spline curve or surface is a useful function in a CAD system. This paper presents an algorithm for extending cubic B-spline curves or surfaces to one or more target points. To keep the extension curve segment GC²-continuous with the original one, a family of cubic polynomial interpolation curves can be constructed. One curve is chosen as the solution from a sub-class of such a family by setting one GC² parameter to be zero and determining the second GC² parameter by minimizing the strain energy. To simplify the final curve representation, the extension segment is reparameterized to achieve C²-continuity with the given B-spline curve, and then knot removal from the curve is done. As a result, a sub-optimized solution subject to the given constraints and criteria is obtained. Additionally, new control points of the extension B-spline segment can be determined by solving lower triangular linear equations. Some computing examples for comparing our method and other methods are given.

A new algorithm is presented that generates developable Bézier surfaces through a Bézier curve called a directrix. The algorithm is based on differential geometry theory on necessary and sufficient conditions for a surface which is developable, and on degree evaluation formula for parameter curves and linear independence for Bernstein basis. No nonlinear characteristic equations have to be solved. Moreover the vertex for a cone and the edge of regression for a tangent surface can be obtained easily. Aumann’s algorithm for developable surfaces is a special case of this paper.

At low bitrate, all block discrete cosine transform (BDCT) based video coding algorithms suffer from visible blocking and ringing artifacts in the reconstructed images because the quantization is too coarse and high frequency DCT coefficients are inclined to be quantized to zeros. Preprocessing algorithms can enhance coding efficiency and thus reduce the likelihood of blocking artifacts and ringing artifacts generated in the video coding process by applying a low-pass filter before video encoding to remove some relatively insignificant high frequent components. In this paper, we introduce a new adaptive preprocessing algorithm, which employs an improved bilateral filter to provide adaptive edge-preserving low-pass filtering which is adjusted according to the quantization parameters. Whether at low or high bit rate, the preprocessing can provide proper filtering to make the video encoder more efficient and have better reconstructed image quality. Experimental results demonstrate that our proposed preprocessing algorithm can significantly improve both subjective and objective quality.

The control method for machining non-cylinder pin hole of piston was studied systematically. A new method was presented by embedding giant magnetostrictive material (GMM) into the tool bar proper position. The model is established to characterize the relation between control current of coil and deformation of tool rod. A series of tests on deformation of giant magnetostrictive tool bar were done and the results validated the feasibility of the principle. The methods of measuring magnetostrictive coefficient of rare earth GMM were analyzed. The measuring device with the bias field and prestress was designed. A series of experiments were done to test magnetostrictive coefficient. Experimental results supplied accurate characteristic parameter for designing application device of GMM. The constitution of the developed control system made up of displacement detection and temperature detection for thermal deformation compensation was also introduced. The developed machine tool for boring the non-cylinder pin hole of piston has the micron order accuracy. This control method can be applied to other areas for machining precision or complex parts.

A perturbation method is introduced in the context of dynamical system for solving the nonlinear Korteweg-de Vries (KdV) equation. Best efficiency is obtained for few perturbative corrections. It is shown that, the question of convergence of this approach is completely guaranteed here, because a limited number of term included in the series can describe a sufficient exact solution. Comparisons with the solutions of the quintic spline, and finite difference are presented.

A quasi-filled function for nonlinear integer programming problem is given in this paper. This function contains two parameters which are easily to be chosen. Theoretical properties of the proposed quasi-filled function are investigated. Moreover, we also propose a new solution algorithm using this quasi-filled function to solve nonlinear integer programming problem in this paper. The examples with 2 to 6 variables are tested and computational results indicated the efficiency and reliability of the proposed quasi-filled function algorithm.

In Artin algebra representation theory there is an important result which states that when the order of G is invertible in Λ then gl.dim(ΛG)=gl.dim(Λ). With the development of Hopf algebra theory, this result is generalized to smash product algebra. As known, weak Hopf algebra is an important generalization of Hopf algebra. In this paper we give the more general result, that is the relation of homological dimension between an algebra A and weak smash product algebra A#H, where H is a finite dimensional weak Hopf algebra over a field k and A is an H-module algebra.

The idea of difference sequence spaces was introduced in (Kızmaz, 1981) and this concept was generalized in (Et and Çolak, 1995). In this paper we define some difference sequence spaces by a sequence of Orlicz functions and establish some inclusion relations.

In this work, we study a class of special Finsler metrics F called arctangent Finsler metric, which is a special ((,()-metric, where ( is a Riemannian metric and β is a 1-form. We obtain a sufficient and necessary condition that F is locally projectively flat if and only if ( and β satisfy two special equations. Furthermore we give the non-trivial solutions for F to be locally projectively flat. Moreover, we prove that such projectively flat Finsler metrics with constant flag curvature must be locally Minkowskian.

This paper proposes a simple method to enlarge the estimation range of conventional carrier frequency offset (CFO) estimation methods based on correlations among the identical parts of the preamble. A novel preamble is designed, which is composed of one regular OFDM training block with even numbers of identical parts and one irregular OFDM training block with odd numbers of identical parts. The initial estimates obtained over the two training blocks are next exploited to jointly estimate the CFO. By elaborately selecting the numbers of identical parts for the two training blocks, the proposed CFO estimator can estimate frequency offset over tens of the subcarrier spacing. Simulation results showed that the proposed CFO estimator satisfies the estimate range requirement for the practical OFDM systems, while achieving a very good estimate performance.

Performance evaluation shows that Hierarchical Mobile IPv6 (HMIPv6) cannot outperform standard Mobile IPv6 (MIPv6) in all scenarios. Thus, adaptive protocol selection under certain circumstances is desired. Moreover, it is necessary to balance the load among different Mobility Anchor Points (MAPs). This paper proposes an efficient three-level hierarchical architecture for mobility management in HMIPv6 networks, in which a mobile node (MN) may register with either a higher/lower MAP or its home agent according to its speed and the number of connecting correspondent nodes (CNs). An admission control algorithm and a replacement algorithm are introduced to achieve load balancing between two MAP levels and among different MAPs within the same MAP level. Admission control is based on the number of CNs but not MNs that an MAP serves. In case there is no capacity for an MN, the MAP chooses an existing MN to be replaced. The replaced MN uses the MAP selection algorithm again to choose another mobility agent. Simulation results showed that the proposed scheme achieves better performance not only in reducing the signaling overhead, but also in load balancing among different MAPs.

We formulate a “Moore’s law” for photonic integrated circuits (PICs) and their spatial integration density using two methods. One is decomposing the integrated photonics devices of diverse types into equivalent basic elements, which makes a comparison with the generic elements of electronic integrated circuits more meaningful. The other is making a complex component equivalent to a series of basic elements of the same functionality, which is used to calculate the integration density for functional components realized with different structures. The results serve as a benchmark of the evolution of PICs and we can conclude that the density of integration measured in this way roughly increases by a factor of 2 per year. The prospects for a continued increase of spatial integration density are discussed.

In this paper, we present a simple thermal model of Vertical-Cavity Surface-Emitting Laser (VCSEL) light-current (LI) characteristics based on the rate-equation. The model can be implemented in conventional SPICE-like circuit simulators, including HSPICE, and be used to simulate the key features of VCSEL. The results compare favorably with experimental data from a device reported in the literature. The simple empirical model is especially suitable for Computer Aided Design (CAD), and greatly simplifies the design of optical communication systems.

Along with the development of motion capture technique, more and more 3D motion databases become available. In this paper, a novel approach is presented for motion recognition and retrieval based on ensemble HMM (hidden Markov model) learning. Due to the high dimensionality of motion’s features, Isomap nonlinear dimension reduction is used for training data of ensemble HMM learning. For handling new motion data, Isomap is generalized based on the estimation of underlying eigenfunctions. Then each action class is learned with one HMM. Since ensemble learning can effectively enhance supervised learning, ensembles of weak HMM learners are built. Experiment results showed that the approaches are effective for motion data recognition and retrieval.

In this paper, based on the inherent characteristic of the contention relation between flows in ad hoc networks, we introduce the notion of the link’s interference set, extend the utility maximization problem representing congestion control in wireline networks to ad hoc networks, apply the penalty function approach and the subgradient method to solve this problem, and propose the congestion control algorithm Penalty function-based Optical Congestion Control (POCC) which is implemented in NS2 simulator. Specifically, each link transmits periodically the information on its congestion state to its interference set; the session at each source adjusts the transmission rate based on the optimal tradeoff between the utility value and the congestion level which the interference set of the links that this session goes though suffers from. MATLAB-based simulation results showed that POCC can approach the globally optimal solution. The NS2-based simulation results showed that POCC outperforms default TCP and ATCP to achieve efficient and fair resource allocation in ad hoc networks.