We propose the spectrum allocation and resource scheduling algorithms in cognitive point to multipoint (PMP) networks with rapid changes of spectrum opportunities and present a media access control (MAC) protocol based on these algorithms. The objective of spectrum allocation is to make efficient use of the spectrum while maintaining the transceiver synchronization on frequency and time in the network. The objective of resource scheduling is to guarantee the quality of service (QoS) requirements of different kinds of connections and to minimize the total energy consumption in the network as well. By sensing only a small set of possible channels in each slot based on the state transition probability of each channel, our spectrum allocation algorithm achieves high spectrum efficiency in the network. The resource scheduling problem is divided into three sub problems and we derive optimal solutions to these problems by greedy algorithm and convex optimization. The simulation results show that our algorithm can make efficient use of the spectrum and the network resources at a cost of low computational complexity.

Peer-to-peer (P2P) technology provides a cost-effective and scalable way to distribute video data. However, high heterogeneity of the P2P network, which rises not only from heterogeneous link capacity between peers but also from dynamic variation of available bandwidth, brings forward great challenge to video streaming. To attack this problem, an adaptive scheme based on rate-distortion optimization (RDO) is proposed in this paper. While low complexity RDO based frame dropping is exploited to shape bitrate into available bandwidth in peers, the streamed bitstream is dynamically switched among multiple available versions in an RDO way by the streaming server. Simulation results show that the proposed scheme based on RDO achieves great gain in overall perceived quality over simple heuristic schemes.

The new H.264 video coding standard achieves significantly higher compression performance than MPEG-2. As the MPEG-2 is popular in digital TV, DVD, etc., bandwidth or memory space can be saved by transcoding those streams into H.264 in these applications. Unfortunately, the huge complexity keeps transcoding from being widely used in practical applications. This paper proposes an efficient transcoding architecture with a smart downscaling decoder and a fast mode decision algorithm. Using the proposed architecture, huge buffering memory space is saved and the transcoding complexity is reduced. Performance of the proposed fast mode decision algorithm is validated by experiments.

This paper describes a Least Squares (LS) channel estimation scheme for MIMO OFDM systems based on time-domain training sequence. We first compute the minimum mean square error (MSE) of the LS channel estimation, and then derive the optimal criteria of the training sequence with respect to the minimum MSE. It is shown that optimal time-domain training sequence should satisfy two criteria. First, the autocorrelation of the sequence transmitted from the same antenna is an impulse function in a region longer than the channel maximum delay. Second, the cross-correlation between sequences transmitted from different antennas is zero in this region. Simulation results show that the estimator using optimal time-domain training sequences has better performance than that using optimal frequency training sequence at low signal-to-noise ratio (SNR). To reduce the training overhead, a suboptimal training sequence is also proposed. Comparing with optimal training sequence, it has low computation complexity and high transmission efficiency at the expense of little performance degradation.

Swept volume solid modeling has been applied to many areas such as NC machining simulation and verification, robot workspace analysis, collision detection, and CAD. But self-intersections continue to be a challenging problem in the boundary representation of swept volume solids. A novel algorithm is presented in this paper to trim self-intersection regions in swept volume solids modeling. This trimming algorithm consists of two major steps: (1) roughly detecting self-intersection regions by checking intersections or overlapping of the envelop profiles; (2) splitting the whole envelop surfaces of the swept volume solid into separate non-self-intersecting patches to trim global self-intersections, and to trim local self-intersections, dividing local self-intersecting regions into patches and replacing self-intersecting patches with non-self-intersecting ones. Examples show that our algorithm is efficient and robust.

In this paper we propose a method to model flowers of solid shape. Based on (Ijiri et al., 2005)’s method, we separate individual flower modeling and inflorescence modeling procedures into structure and geometry modeling. We incorporate interactive editing gestures to allow the user to edit structure parameters freely onto structure diagram. Furthermore, we use free-hand sketching techniques to allow users to create and edit 3D geometrical elements freely and easily. The final step is to automatically merge all independent 3D geometrical elements into a single waterproof mesh. Our experiments show that this solid modeling approach is promising. Using our approach, novice users can create vivid flower models easily and freely. The generated flower model is waterproof. It can have applications in visualization, animation, gaming, and toys and decorations if printed out on 3D rapid prototyping devices.

SLAM is one of the most important components in robot navigation. A SLAM algorithm based on image sequences captured by a single digital camera is proposed in this paper. By this algorithm, SIFT feature points are selected and matched between image pairs sequentially. After three images have been captured, the environment’s 3D map and the camera’s positions are initialized based on matched feature points and intrinsic parameters of the camera. A robust method is applied to estimate the position and orientation of the camera in the forthcoming images. Finally, a robust adaptive bundle adjustment algorithm is adopted to optimize the environment’s 3D map and the camera’s positions simultaneously. Results of quantitative and qualitative experiments show that our algorithm can reconstruct the environment and localize the camera accurately and efficiently.

We present an algorithm which can realize 3D stereo vision simultaneous localization and mapping (SLAM) for mobile robot in unknown outdoor environments, which means the 6-DOF motion and a sparse but persistent map of natural landmarks be constructed online only with a stereo camera. In mobile robotics research, we extend FastSLAM 2.0 like stereo vision SLAM with “pure vision” domain to outdoor environments. Unlike popular stochastic motion model used in conventional monocular vision SLAM, we utilize the ideas of structure from motion (SFM) for initial motion estimation, which is more suitable for the robot moving in large-scale outdoor, and textured environments. SIFT features are used as natural landmarks, and its 3D positions are constructed directly through triangulation. Considering the computational complexity and memory consumption, Bkd-tree and Best-Bin-First (BBF) search strategy are utilized for SIFT feature descriptor matching. Results show high accuracy of our algorithm, even in the circumstance of large translation and large rotation movements.

We present a semi-custom design methodology based on transistor tuning to optimize the design performance. Compared with other transistor tuning approaches, our tuning process takes the cross-talk effect into account and prominently reduces the complexity for circuit simulation and analysis by decomposing the circuit network utilizing graph theory. Furthermore, the incremental placement and routing for the corresponding transistor tuning in conventional approaches is not required in our methodology, which might induce timing graph variation and additional iterations for design convergence. This methodology combines the flexible automated circuit tuning and physical design tools to provide more opportunities for design optimization throughout the design cycle.

To make audio watermarking accomplish both copyright protection and content authentication with localization, a novel multipurpose audio watermarking scheme is proposed in this paper. The zero-watermarking idea is introduced into the design of robust watermarking algorithm to ensure the transparency and to avoid the interference between the robust watermark and the semi-fragile watermark. The property of natural audio that the VQ indices of DWT-DCT coefficients among neighboring frames tend to be very similar is utilized to extract essential feature from the host audio, which is then used for watermark extraction. And, the chaotic mapping based semi-fragile watermark is embedded in the detail wavelet coefficients based on the instantaneous mixing model of the independent component analysis (ICA) system. Both the robust and semi-fragile watermarks can be extracted blindly and the semi-fragile watermarking algorithm can localize the tampering accurately. Simulation results demonstrate the effectiveness of our algorithm in terms of transparency, security, robustness and tampering localization ability.

Single instruction multiple data (SIMD) instructions are often implemented in modern media processors. Although SIMD instructions are useful in multimedia applications, most compilers do not have good support for SIMD instructions. This paper focuses on SIMD instructions generation for media processors. We present an efficient code optimization approach that is integrated into a retargetable C compiler. SIMD instructions are generated by finding and combining the same operations in programs. Experimental results for the UltraSPARC VIS instruction set show that a speedup factor up to 2.639 is obtained.

To find the optimal routing is always an important topic in wireless sensor networks (WSNs). Considering a WSN where the nodes have limited energy, we propose a novel Energy*Delay model based on ant algorithms (“E&D ANTS” for short) to minimize the time delay in transferring a fixed number of data packets in an energy-constrained manner in one round. Our goal is not only to maximize the lifetime of the network but also to provide real-time data transmission services. However, because of the tradeoff of energy and delay in wireless network systems, the reinforcement learning (RL) algorithm is introduced to train the model. In this survey, the paradigm of E&D ANTS is explicated and compared to other ant-based routing algorithms like AntNet and AntChain about the issues of routing information, routing overhead and adaptation. Simulation results show that our method performs about seven times better than AntNet and also outperforms AntChain by more than 150% in terms of energy cost and delay per round.

In this paper, a nonlinear dynamic MIMO model of a 6-DOF underactuated quad rotor rotorcraft is derived based on Newton-Euler formalism. The derivation comprises determining equations of motion of the quad rotor in three dimensions and seeking to approximate the actuation forces through modeling of the aerodynamic coefficients and electric motor dynamics. The derived model is dynamically unstable, so a sequential nonlinear control strategy is implemented for the quad rotor. The control strategy includes exact feedback linearization technique, using the geometric methods of nonlinear control. The performance of the nonlinear control algorithm is evaluated using simulation and the results show the effectiveness of the proposed control strategy for the quad rotor rotorcraft near quasi-stationary flight.

Based on input-output approach, the robust stability and stabilization problems for uncertain singular systems with time-varying delays are investigated. The parameter uncertainties are assumed to be norm-bounded and the time-varying delays include both discrete delay and distributed delay. By introducing a new input-output model, the time-delay system is embedded in a family of systems with a forward system without time delay and a dynamical feedback uncertainty. A sufficient and necessary condition, which guarantees the system regular, impulse-free and stable for all admissible uncertainties, is obtained. Based on the strict linear matrix inequality, the desired robust state feedback controller is also obtained. Finally, a numerical example is provided to demonstrate the application of the proposed method.

Control design is important for proton exchange membrane fuel cell (PEMFC) generator. This work researched the anode system of a 60-kW PEMFC generator. Both anode pressure and humidity must be maintained at ideal levels during steady operation. In view of characteristics and requirements of the system, a hybrid intelligent PID controller is designed specifically based on dynamic simulation. A single neuron PI controller is used for anode humidity by adjusting the water injection to the hydrogen cell. Another incremental PID controller, based on the diagonal recurrent neural network (DRNN) dynamic identification, is used to control anode pressure to be more stable and exact by adjusting the hydrogen flow rate. This control strategy can avoid the coupling problem of the PEMFC and achieve a more adaptive ability. Simulation results showed that the control strategy can maintain both anode humidity and pressure at ideal levels regardless of variable load, nonlinear dynamic and coupling characteristics of the system. This work will give some guides for further control design and applications of the total PEMFC generator.

Dynamic equivalence of the wind farm is a fundamental problem in the simulation of a power system connected with wind farms because it is unpractical to model every generator in a wind farm in detail. In this paper, an Equivalence Method based on the Output Characteristics (EMOC) is proposed, with which the wind farm composed of Squirrel-Cage Induction Generators (SCIGs) can be equivalent to one generator. By considering the diversity of wind generators and special operating characteristics of a wind farm, the equivalent generator based on EMOC responds accurately in various faults. No matter whether the wind farm is integrated in grid or just programmed, EMOC can be used to acquire an accurate equivalent generator. Simulation of the dynamic equivalence of an SCIG wind farm validated the method.

This paper presents a novel mega-Hz-level super high frequency zero-voltage soft-switching converter for induction heating power supplies. The prominent advantage of this topology is that it can absorb both inductive and capacitive parasitic components in the converter. The switch devices operate in a zero-voltage soft-switching mode. Consequently, the high voltage and high current spikes caused by parasitic inductors or capacitors oscillation do not occur in this circuit, and the high power loss caused by high frequency switching can be greatly reduced. A large value inductor is adopted between the input capacitor and the switches, thus, this novel converter shares the benefits of both voltage-type and current-type circuits simultaneously, and there are no needs of dead time between two switches. The working principles in different modes are introduced. Results of simulation and experiments operated at around 1 MHz frequency verify the validity of parasitic components absorption and show that this converter is competent for super high frequency applications.

A novel elevator door driven by tubular permanent magnet linear synchronous motor (TPMLSM) is presented. This TPMLSM applies axial magnet array topology of the secondary rod, air-cored armature windings and slotless structure of the forcer to improve the stability of the thrust. The influence of two major dimensions, the pitch and radius of the permanent magnet (PM), on magnetic field was studied and the best values were given by the finite element analysis (FEA). The magnetic field, back EMF and thrust of the motor were analyzed and the PM size was optimized to reduce the harmonic components of the magnetic field and improve the performance of the motor. Predicted results are validated by the experiment. It is shown that the performance of the motor and the novel elevator door system is satisfying.

Electromagnetic relay is a widely used apparatus which usually works in a magnetic disturbance environment. To evaluate its electromagnetic compatibility (EMC) in a static magnetic field, dynamic characteristics of a clapper relay in a uniform static magnetic field situation based on the finite element method (FEM) is studied. Influences of the magnetic field on dynamic parameters (delay time, pick-up time, end pressure, and final velocity) as well as a situation in which the relay cannot function normally are analyzed. Simulation reveals that the external magnetic field which weakens the relay’s air-gap field has a greater influence on the relay’s dynamic parameters than the one strengthening the field. The validity of the simulation is verified by measured results of coil current and armature displacement.