A blind watermarking method using maximum wavelet coefficient quantization

This paper proposes a blind watermarking algorithm based on maximum wavelet coefficient quantization for copyright protection. The wavelet coefficients are grouped into different block size and blocks are randomly selected from different subbands. We add different energies to the maximum wavelet coefficient under the constraint that the maximum wavelet coefficient is always maximum in a block. The watermark is embedded the local maximum coefficient which can effectively resist attacks. Also, using the block-based watermarking, we can extract the watermark without using the original image or watermark. Experimental results show that the proposed method is quite robust under either non-geometry or geometry attacks.     

Slippage control in soft finger grasping and manipulation

Handling objects with robotic soft fingers without considering the odds of slippage are not realistic. Grasping and manipulation algorithms have to be tested under such conditions for evaluating their robustness. In this paper, a dynamic analysis of rigid object manipulation with slippage control is studied using a two-link finger with soft hemispherical tip. Dependency on contact forces applied by a soft finger while grasping a rigid object is examined experimentally. A power-law model combined with a linear viscous damper is used to model the elastic behavior and damping effect of the soft tip, respectively. In order to obtain precise dynamic equations governing the system, two second-order differential equations with variable coefficients have been designed to describe the different possible states of the contact forces accordingly. A controller is designed based on the rigid fingertip model using the concept of feedback linearization for each phase of the system dynamics. Numerical simulations are used to evaluate the performance of the controller. The results reveal that the designed controller shows acceptable performance for both soft and rigid finger manipulation in reducing and canceling slippage. Furthermore, simulations indicate that the applied force in the soft finger manipulation is considerably less than the rigid “one.”.     

Stereoscopic image generation with depth image based rendering

In this paper, we proposed stereoscopic image generation methods of adjusting the depth value of edge pixels and improved hole filling procedures. For the conventional system, the smooth of depth map can reduce the incidence of image holes, but cause geometric distortions of the image depth. To solve the problems, the depth map is first expanded to refine the accuracy of image depth and the quality of images. Next, we derive a hardware-oriented method for 3D warping. Finally, appropriate blocks are searched to enhance the performance of image by improving hole-filling procedures. The experimental results demonstrate the proposed methods have great performance and practicability.     

GPU accelerated tensor contractions in the plaquette renormalization scheme

We use the graphical processing unit (GPU) to accelerate the tensor contractions, which is the most time consuming operations in the variational method based on the plaquette renormalized states. Using a frustrated Heisenberg J₁–J₂ model on a square lattice as an example, we implement the algorithm based on the compute unified device architecture (CUDA). For a single plaquette contraction with the bond dimensions C = 3 of each rank of the tensor, results are obtained 25 times faster on GPU than on a current CPU core. This makes it possible to simulate systems with the size 8 × 8 and larger, which are extremely time consuming on a single CPU. This technology successfully relieves the computing time dependence with C, while in the CPU serial computation, the total required time scales both with C and the system size.     

On constructing an optimal consensus clustering from multiple clusterings

Computing a suitable measure of consensus among several clusterings on the same data is an important problem that arises in several areas such as computational biology and data mining. In this paper, we formalize a set-theoretic model for computing such a similarity measure. Roughly speaking, in this model we have k>1 partitions (clusters) of the same data set each containing the same number of sets and the goal is to align the sets in each partition to minimize a similarity measure. For k=2, a polynomial-time solution was proposed by Gusfield (Information Processing Letters 82 (2002) 159-164). In this paper, we show that the problem is MAX-SNP-hard for k=3 even if each partition in each cluster contains no more than 2 elements and provide a -approximation algorithm for the problem for any k.     

Design of an adaptive self-organizing fuzzy neural network controller for uncertain nonlinear chaotic systems

Though the control performances of the fuzzy neural network controller are acceptable in many previous published papers, the applications are only parameter learning in which the parameters of fuzzy rules are adjusted but the number of fuzzy rules should be determined by some trials. In this paper, a Takagi–Sugeno-Kang (TSK)-type self-organizing fuzzy neural network (TSK-SOFNN) is studied. The learning algorithm of the proposed TSK-SOFNN not only automatically generates and prunes the fuzzy rules of TSK-SOFNN but also adjusts the parameters of existing fuzzy rules in TSK-SOFNN. Then, an adaptive self-organizing fuzzy neural network controller (ASOFNNC) system composed of a neural controller and a smooth compensator is proposed. The neural controller using the TSK-SOFNN is designed to approximate an ideal controller, and the smooth compensator is designed to dispel the approximation error between the ideal controller and the neural controller. Moreover, a proportional-integral (PI) type parameter tuning mechanism is derived based on the Lyapunov stability theory, thus not only the system stability can be achieved but also the convergence of tracking error can be speeded up. Finally, the proposed ASOFNNC system is applied to a chaotic system. The simulation results verify the system stabilization, favorable tracking performance, and no chattering phenomena can be achieved using the proposed ASOFNNC system.     

Electrochemical oxidation of manganese(II) at a platinum electrode

Electrochemical oxidation of Mn²⁺ in sulphuric acid to form MnO₂ was studied using stationary and rotating platinum/platinum ring-disc electrodes. It appears that nucleation of MnO₂ is governed by an equilibrium involving a Mn(III) intermediate. Growth of MnO₂ involves the reduction of MnO₂ surfaces by Mn²⁺ ions in the solution to form MnOOH intermediates. The subsequent electrochemical oxidation of MnOOH releases a hydrogen ion and results in the formation of MnO₂. The rate constant of MnOOH oxidation to MnO₂ was estimated to be 40 s^–1. With a sufficient supply of Mn²⁺ ions, a layer of MnOOH is built up and the in-solid diffusion of hydrogen ions becomes the ratedetermining-step. With a low Mn²⁺ concentration, diffusion of Mn²⁺ ions from bulk electrolyte to the MnO₂/electrolyte interface is a factor controlling the growth of MnO₂. The activation energy and the pre-exponential term of the diffusion coefficient of Mn²⁺ in 0.5m sulphuric acid were determined to be 44.8 kJ mol^–1 and 100 cm² s^–1, respectively.     

Development of Virtual Simulation System for Remote Collaborative Surface Machining

1 Introduction Many parts of aerospace ,automobile and mold industries are high precision and complex-shaped. There-fore ,it needs multi-axis machining. Multi-axis machining has advantages of i mproving efficiency and surfaceprecision,reducing production expense and shortening ti me to market . Although there are many advantages inmulti-axis machining,there are many steps on process planningfor complexsurface .And every step needs engi-neers to make appropriate decisions by their professional…     

GaAsSb/InAlAs PA DHBTs Grown by Production MBE

The epi material growth of GaAsSb based DHBTs with InAlAs emitters are investigated using a 4 × 100mm multi-wafer production Riber 49 MBE reactor fully equipped with real-time in-situ sensors including an absorption band edge spectroscope and an optical-based flux monitor. The state-of-the-art hole mobilities are obtained from 100nm thick carbon-doped GaAsSb. A Sb composition variation of less than ± 0.1 atomic percent across a 4 × 100mm platen configuration has been achieved. The large area InAlAs/GaAsSb/InP DHBT device demonstrates excellent DC characteristics,such as BVCEO＞6V and a DC current gain of 45 at 1kA/cm2 for an emitter size of 50μm × 50μm. The devices have a 40nm thick GaAsSb base with p-doping of 4. 5 × 1019cm-3 . Devices with an emitter size of 4μm × 30μm have a current gain variation less than 2% across the fully processed 100mm wafer. ft and fmax are over 50GHz,with a power efficiency of 50% ,which are comparable to standard power GaAs HBT results. These results demonstrate the potential application of GaAsSb/InP DHBT for power amplifiers and the feasibility of multi-wafer MBE for mass production of GaAsSb-based HBTs.