Applied Mechanics and Materials Vols. 110-116

Abstract: In this paper, a novel scheme is propose to solve the problems in chaos control via a nonnegative multi–modal nonlinear optimization, which finds the unstable periodic orbits and best parameters of chaos system such that the objective function is minimized. The novel scheme embeds with a differential evolution algorithm consisting of techniques in three aspects: uniform design to the initial population, deflection and stretching to the objective functions, and the region zooming self–adaptively, which result in a much more effective searching mechanism with fine equilibrium between exploitation and exploration. To exhibit the new scheme’s performance, the experiments done to Hénon, Chen and Lü system are given, and the simulations done show that the method has better adaptability, dependability and robustness.

Abstract: Specific hardware solutions are always faster than programmable architectures. But dedicated architectures have the inherent disadvantage of inflexibility. Changes in the algorithm or extensions of the application are handled easily by programmable architectures. The approach discussed here involves a hardware-software co-design to optimize on performance and programmability. The architecture houses two SHARC processors to aid in parallelizing the image processing algorithms, and a reconfigurable FPGA which may be configured on the fly to execute any of the real-time algorithms as desired. The functional memory would consist of pre-designs (FPGA based) of certain objects, each of which could be used to configure an FPGA to perform a particular function.

Abstract: We apply statistical mechanics of the Q-Ising model to a typical problem in information processing technology which is called as inverse halftoning. Here, we reconstruct an original image by making use of multiple dithered images so as to maximize the posterior marginal probability. Then, in order to clarify the validity of the present method, we estimate upper bound of the performance using the Monte Carlo simulation both for a 256-level standard image and a set of gray-level images generated by an assumed true prior. The simulation for the gray-level images finds that the lower bound of the root mean square becomes smaller with the increase in the number of dithered images and that image reconstruction is perfectly carried out, if Q kinds of dithered images are utilized, where Q is the number of the gray-levels. These properties are qualitatively confirmed by the analytical estimate using the infinite-range model. Further, we find that the performance for a 256-level image is improved by utilizing prior information on gray-level images, even if we use a small number of dithered images.

Abstract: Knowledge of the permeability distribution is critical to a successful reservoir model. Nuclear Magnetic Resonance (NMR) measurements can be used for permeability prediction because the T₂ relaxation time is proportional to pore size. Due to the conventional estimators have difficult and complex problems in simulating the relationship between permeability and NMR measurements, an intelligent technique using artificial neural network and genetic algorithm to estimate permeability from NMR measurements is developed. Neural network is used as a nonlinear regression method to develop transformation between the permeability and NMR measurements. Genetic algorithm is used for selecting the best parameters and initial value for the neural network, which solved two major problems of the network: local minima and parameter selection depend on experience. Information gain principle is introduced to select the neural network's input parameters automatically from data. The technique is demonstrated with an application to the well data in Northeast China. The results show that the refined technique make more accurate and reliable reservoir permeability estimation compared with conventional methods. This intelligent technique can be utilized a powerful tool for estimate permeability from NMR logs in oil and gas industry.

Abstract: Elmore delay has been widely used as an analytical estimate of the interconnect delays in the performance-driven synthesis and layout of VLSI routing topologies. In this paper, Closed-form solutions for the 50% delay, rise time and overshoots of the step response of distributed Single Wall Carbon Nanotube (SWCNT), which consists RC and RLC parts, are presented for the first time. The proposed approach retains both efficiency and simplicity of the equivalent Elmore model with significantly improved accuracy, through surface fitting (3D) instead of curve fitting (2D).

Abstract: Adder is one of the important arithmetic units in computers. In this paper, we investigate the implementation of quaternary half adder based on multiple-valued (MV) logic gates using single electron transistor (SET) and metal-oxide-semiconductor (MOS) transistor. We use hybrid SETMOS universal literal gate which has been proposed by Mahapatra and Ionesco. We apply two 4-radix inputs to the proposed quaternary half adder and obtain sum and carry outputs. The logic operation of the proposed quaternary half adder is verified by using HSPICE simulator. Moreover we compare the performance of our proposed quaternary half adder with the performance of a quaternary half adder based on MOS technology.

Abstract: The backbone network throughput has climbed up to 40Gbps, it demands a high-speed pattern matching algorithm. In this paper, we apply Half byte matching and SRAM-based Expansion into the traditional TCAM lookup algorithm, to meet accuracy requirements. Theoretical analysis and experimental results show that, the HBS-TCAM algorithms can significantly improve the service identification accuracy, thus enhancing the performance of TCAM lookup system.

Abstract: Digital correlator play an important role for Photon Correlation Spectorscopy. In this paper, the theory of Photon Correlation Spectorscopy (PCS) and the internal structure of digital correlator are described, and by increasing the number of channels to improve the precision. The digital correlator with 256 channels is implemented by FPGA, effectively raising the real-time and precision.

Abstract: The paper analyzes HDR technologies and its applications in post process effects, refers to a new method to combine the post process effects and rendering them into the 3D scene at the same time, the method combine the post process effects in chain. And we implement this method through experiment. In contrast to the traditional method, experimental results show that the new method can build a more complex and realistic post process effect in 3D scene.

Abstract: This paper proposes a two-step process which uses the knowledge gathered in sheet-metal manufacturing practice as the basis to find proper layouts of strip in progressive dies. In the first step, manufacturing knowledge is used to formulate various rules to cluster the punches into five categories for reducing the searching space of feasible layouts. Evaluation functions are then applied to find the better ones from the feasible layouts. This two-step process provides a new approach to solving the problem of “explosive combinations” in strip layout design