Output probability from a general combinational network

In this paper, we present the method which calculates the probability of the output of a general combinational network being 1, when the probabilities is given for each input being 1. Also we present the method which derives the output probability expression in terms of a given set of input probabilities.The method is based on a basic probability axiom and Binary Decision Diagrams. A Boolean function for a combinational network is transformed into a Binary Decision Diagram and the output probability expression is derived from it. Therefore a derivation of the output probability for a combinational network can be straightforward. Some examples are showed that the method using Binary Decision Diagrams is simple and efficient. We can see a variation of the output probability for a combinational network according to the given set of input probabilities.     

Two-level optimal output feedback stabilizer design

Design of two-level system stabilizers is considered using an optimal reduced-order model whose state variables are torque angles and speeds. The reduced-order model retains their physical meaning and is used to design a two-level linear feedback controller that takes into account the realities and constraints of the electrical power systems. The two-level control strategy is used, and a global control signal is generated from the output variables to minimize the effect of interaction. The effectiveness of this controller is evaluated, and an example, the multimachine system, is given to illustrate the advantages of the proposed method. The responses of the system with the two-level scheme and optimal reduced order scheme are included for comparative analyses     

Effect of the Liquid-Phase Characteristic on the Microstructures and Dielectric Properties of Donor- (Niobium) and Acceptor- (Magnesium) Doped Barium Titanate

Changes in the microstructure and dielectric properties with the variation of the donor/acceptor ratio in BaTiO₃ ceramics were investigated. In donor-rich specimens, a liquid that appeared during sintering did not penetrate into grain boundaries. However, in the acceptor-rich specimens, the grains were separated by a liquid film during sintering. The much higher mobility of the liquid film than that of the grain boundaries was suggested to cause extensive grain growth in acceptor-rich BaTiO₃. The macroscopic homogenization of dopants because of grain growth in acceptor-rich specimens resulted in changes in the dielectric properties.     

Effects of potential and heat treatment on phase transition of alumina dielectric layer

The characteristics and growth behaviors of alumina dielectric layer formed by anodic oxidation were investigated. The aluminum oxide layer anodized at 400 V was predominantly amorphous alumina, but at the applied potentials more than 500 V, amorphous and crystalline γ-alumina were existed in anodic oxide layer and the ratio of γ-alumina increased with the increasing applied potential. During the heat treatment at 600^°C or higher temperature, amorphous alumina layer was transformed into the crystalline γ-alumina. The phase transition of anodic amorphous alumina into crystalline depends on anodic applied potentials and heat-treatment temperatures.     

Scaling laws and internal structure for characterizing electrospun poly[(R)-3-hydroxybutyrate] fibers

Using chloroform/dimethylformamide (CF/DMF) co-solvent, electrospinning of poly[(R)-3-hydroxybutyrate] (PHB) solutions was carried out at ambient temperature. The effects of the applied voltage (V), flow-rate (Q), and solution viscoelastic properties on the Taylor cone, electrified jet, and fiber morphology were investigated. In addition, the electric field developed by the needle-plate electrode configuration was calculated using a finite element analysis to reveal the tip-to-collector (H) effect. Among the processing parameters (V, Q and H), it was found that Q played a key role in determining the jet diameter (d_j) and electrospun fiber diameter (d_f), and scaling laws existed between them, i.e., d_j-Q^0.61 and d_f-Q^0.33. The diameter reduction ratios of D_o/d_j (D_o is the needle diameter) and d_j/d_f were measured as 50-120 and 5-10, respectively; it suggested that major jet stretching took place in the straight electrified jet region, and further chain orientation could be gained by the subsequent process of jet whipping. By changing PHB concentrations from 5 to 15 wt%, the solution viscosity (η_o) was increased from 100 to 4900 cP, whereas the surface tension and solution conductivity remained unchanged; it provided a good model solution to exclusively reveal the η_o effect on the electrospinning process. Our results showed that the η_o-dependence of d_j and d_f also followed simple scaling laws: d_j-η_o^0.06, and d_f-η_o^0.39, with a prefactor depending on the processing variables, mainly the flow-rate. Regardless of the PHB concentrations used, the obtained PHB fibers showed a similar crystallinity fraction of ca. 0.63 and possession of major α-crystals together with a small amount of β-crystals with zigzag chain conformation.     

The Fabrication and Characterization of Single‐Component Polymeric White‐Light‐Emitting Diodes

By using Ni⁰‐mediated polymerization, we have systematically synthesized a series of fluorene‐based copolymers composed of blue‐, green‐, and red‐light‐emitting comonomers with a view to producing polymers with white‐light emission. 2,7‐Dibromo‐9,9‐dihexylfluorene, {4‐(2‐[2,5‐dibromo‐4‐{2‐(4‐diphenylamino‐phenyl)‐vinyl}‐phenyl]‐vinyl)‐phenyl}‐diphenylamine (DTPA), and 2‐{2‐(2‐[4‐{bis(4‐bromo‐phenyl)amino}‐phenyl]‐vinyl)‐6‐tert‐butyl‐pyran‐4‐ylidene}‐malononitrile (TPDCM) were used as the blue‐, green‐, and red‐light‐emitting comonomers, respectively. It was found that the emission spectra of the resulting copolymers could easily be tuned by varying their DTPA and TPDCM content. Thus with the appropriate red/green/blue (RGB) unit ratio, we were able to obtain white‐light emission from these copolymers. A white‐light‐emitting diode using the polyfluorene copolymer containing 3 % green‐emitting DTPA and 2 % red‐emitting TPDCM (PG3R2) with a structure of indium tin oxide/poly(3,4‐ethylenedioxythiophene):poly(styrene sulfonic acid)/PG3R2/Ca/Al was found to exhibit a maximum brightness of 820 cd m^–2 at 11 V with Commission Internationale de L'Eclairage (CIE) coordinates of (0.33,0.35), which are close to the standard CIE coordinates for white‐light emission (0.33,0.33).     

Pioneering e-supply chain integration in semiconductor industry: a case study

Taiwan Semiconductor Manufacturing Company (TSMC) is the largest semiconductor foundry in the world. Advanced Semiconductor Engineering Inc. (ASE) is the world’s leader in semiconductor assembly and testing. From 1998 to 2004, the two companies completed electronic integration of 11 key business processes through the Internet. The result is a seamless interface between TSMC, ASE and their joint customers. They can now obtain accurate, timely information on their product status and respond appropriately when needed. While the direct economic benefits are estimated to be around US$ 10 million through productivity increase over a total investment of about US$ 2 million, the indirect benefits of this initiative could be on the order of US $100 million if the joint customers’ benefits are considered. In collaboration with the RosettaNet organization, TSMC and ASE leveraged their pioneering experiences to define three data exchange standards which can then be widely adopted in the semiconductor industry. This case study is a demonstration of how two leading companies in their respective fields can join forces to make a difference in creating value for the entire semiconductor industry, which in turn benefits society at large. With the momentum continuing to build and the sphere of influence continuing to expand, it is anticipated that TSMC, ASE and the entire sector will upgrade their competitiveness in terms of cost, quality, responsiveness and customer orientation.     

Construction of a prediction model for the structural stability of a surface grinder using backpropagation neural network

Learning and prediction capability of the backpropagation neural network (BPNN) have been used to build the prediction model for the structural stability of a surface grinder. The Lagrange energy method is applied to derive the dynamic equation of the lumped parameter model of the surface grinder. The major factors influencing the structural stability of the system can be determined after the ratio of kinetic energy of the sub-structure and the ratio of potential energy of the sub-structure interface are obtained. An orthogonal rotatable central composite design is adopted to dispose the treatment combinations of the major factors. The BPNN model is constructed by the treatment combinations of the training patterns and verified by the treatment combinations of the test patterns. In this paper, a 3-layer BPNN model with a 10-neuron hidden layer which converged after 4,072 learning cycles is selected to predict the structural stability of a surface grinder within the planned ranges. The percentage residuals of both training patterns and test patterns are all within 3.41%, thus the prediction accuracy of the BPNN model is excellent so that the engineering demands are well satisfied.     

New multifunction filter using an inverting CCII and a voltagefollower

A new multifunction filter using minimum components is presented. This filter which possesses single input and four outputs can simultaneously generate second-order highpass, bandpass, and lowpass filtering functions at individual output terminals. The filter has the following merits; it uses only two grounded capacitors which makes it suitable for integrated circuit implementation, no matching condition is required, offering multifunction outputs and has low passive and active sensitivities. Experimental results agree very well with the theoretical result