This paper studies a supply chain model in which a single supplier sells a single product to a single retailer who faces the newsvendor problem. The retailer is loss averse. The results show that the optimal production quantity with decentralized decision making with a wholesale price contract is less than that with centralized decision making. The supply chain can achieve channel coordination with buy back and target rebate contracts. With buy back contracts, the supply chain system profits can be allocated arbitrarily between the supplier and retailer. A new kind of contract, the incremental buy back contract, gives similar results as with the buy back contract. The advantages and drawbacks of these three types of contracts are analyzed with numerical examples.

In this paper we address the problem of audio-visual speech recognition in the framework of the multi-stream hidden Markov model. Stream weight training based on minimum classification error criterion is discussed for use in large vocabulary continuous speech recognition (LVCSR). We present the lattice re-scoring and Viterbi approaches for calculating the loss function of continuous speech. The experimental results show that in the case of clean audio, the system performance can be improved by 36.1% in relative word error rate reduction when using state-based stream weights trained by a Viterbi approach, compared to an audio only speech recognition system. Further experimental results demonstrate that our audio-visual LVCSR system provides significant enhancement of robustness in noisy environments.

Many efficient algorithms of Montgomery-form elliptic curve cryptology have been investigated recently. At present, there are no reported studies of the isomorphic class of the Montgomery-form elliptic curve over a finite field. This paper investigates the isomorphism of Montgomery-form elliptic curves via the isomorphism of Weierstrass-form elliptic curves and gives a table of (nearly) all the forms of Montgomery-form elliptic curves suitable for cryptographic usage. Then, an algorithm for generating a secure elliptic curve with Montgomery-form is presented. The most important advantages of the new algorithm are that it avoids the transformation from an elliptic curve's Weierstrass-form to its Montgomery-form, and that it decreases the probability of collision. So, the proposed algorithem is quicker, simpler, and more efficient than the old ones.

Locating multi-view faces in images with a complex background remains a challenging problem. In this paper, an integrated method for real-time multi-view face detection and pose estimation is presented. A simple-to-complex and coarse-to-fine view-based detector architecture has been designed to detect multi-view faces and estimate their poses efficiently. Both the pose estimators and the view-based face/nonface detectors are trained by a cost-sensitive AdaBoost algorithm to improve the generalization ability. Experimental results show that the proposed multi-view face detector, which can be constructed easily, gives more robust face detection and pose estimation and has a faster real-time detection speed compared with other conventional methods.

The Mel-frequency cepstral coefficient (MFCC) is the most widely used feature in speech and speaker recognition. However, MFCC is very sensitive to noise interference, which tends to drastically degrade the performance of recognition systems because of the mismatches between training and testing. In this paper, the logarithmic transformation in the standard MFCC analysis is replaced by a combined function to improve the noisy sensitivity. The proposed feature extraction process is also combined with speech enhancement methods, such as spectral subtraction and median-filter to further suppress the noise. Experiments show that the proposed robust MFCC-based feature significantly reduces the recognition error rate over a wide signal-to-noise ratio range.

To analyze and simulate non-stationary time series with finite length, the statistical characteristics and auto-regressive (AR) models of non-stationary time series with finite length are discussed and studied. A new AR model called the time varying parameter AR model is proposed for solution of non-stationary time series with finite length. The auto-covariances of time series simulated by means of several AR models are analyzed. The result shows that the new AR model can be used to simulate and generate a new time series with the auto-covariance same as the original time series. The size curves of cocoon filaments regarded as non-stationary time series with finite length are experimentally simulated. The simulation results are significantly better than those obtained so far, and illustrate the availability of the time varying parameter AR model. The results are useful for analyzing and simulating non-stationary time series with finite length.

This paper proposes a novel algorithm for extracting key frames to represent video shots. Regarding whether, or how well, a key frame represents a shot, different interpretations have been suggested. We develop our algorithm on the assumption that more important content may demand more attention and may last relatively more frames. Unsupervised clustering is used to divide the frames into clusters within a shot, and then a key frame is selected from each candidate cluster. To make the algorithm independent of video sequences, we employ a statistical model to calculate the clustering threshold. The proposed algorithm can capture the important yet salient content as the key frame. Its robustness and adaptability are validated by experiments with various kinds of video sequences.

This work describes an improved feature extractor algorithm to extract the peripheral features of point x(ti,fj) using a nonlinear algorithm to compute the nonlinear time spectrum (NL-TS) pattern. The algorithm observes n×n neighborhoods of the point in all directions, and then incorporates the peripheral features using the Mel frequency cepstrum components (MFCCs)-based feature extractor of the Tsinghua electronic engineering speech processing (THEESP) for Mandarin automatic speech recognition (MASR) system as replacements of the dynamic features with different feature combinations. In this algorithm, the orthogonal bases are extracted directly from the speech data using discrite cosime transformation (DCT) with 3×3 blocks on an NL-TS pattern as the peripheral features. The new primal bases are then selected and simplified in the form of the Δdp-t operator in the time direction and the Δdp-f operator in the frequency direction. The algorithm has 23.29% improvements of the relative error rate in comparison with the standard MFCC feature-set and the dynamic features in tests using THEESP with the duration distribution-based hidden Markov model (DDBHMM) based on MASR system.

A hybrid decomposition method for molecular dynamics simulations was presented, using simultaneously spatial decomposition and force decomposition to fit the architecture of a cluster of symmetric multi-processor (SMP) nodes. The method distributes particles between nodes based on the spatial decomposition strategy to reduce inter-node communication costs. The method also partitions particle pairs within each node using the force decomposition strategy to improve the load balance for each node. Simulation results for a nucleation process with 4 000 000 particles show that the hybrid method achieves better parallel performance than either spatial or force decomposition alone, especially when applied to a large scale particle system with non-uniform spatial density.

A modified diffusion flux model (DFM) was developed to analyze turbulent multi-dimensional gas-particle two-phase flows. In the model, the solid particles move in a modified acceleration field, g″, which includes the effects of various forces on the particles as if all the forces have the same effect on the particles as the gravity. The accelerations due to various forces are then taken into account in the calculation of the diffusion velocities of the solid particles in the gas-particle two-phase flow. The DFM was used to numerically simulate the gas-solid two-phase flow behind a vertical backward-facing step. The numerical simulation compared well with experimental data and numerical results using both the k-?-Ap and k-?-kp two-fluid models available in the literature. The comparison shows that the modified diffusion flux model correctly simulates the turbulent gas-particle two-phase flow.

The classical problem of a round metal tube collapsing in concertina mode when subjected to axial compressive loading has been reexamined both theoretically and experimentally. The model including an eccentricity factor proposed by Wierzbicki et al. and modified by Singace et al. has been taken one step further to obtain the real load-displacement history and to investigate eccentricity effects. The influence of the eccentricity parameter m on the mean crushing load was discussed according to the present analysis. Experiments were carried out to verify the eccentricity effects. The results show that experimental and theoretical load-displacement curves match perfectly, especially in terms of half wavelength. Unlike previous researchs, the results suggest that m is not a fixed value and may affect energy absorption.

This paper proposes an artificial neural network maximum power point tracker (MPPT) for solar electric vehicles. The MPPT is based on a highly efficient boost converter with insulated gate bipolar transistor (IGBT) power switch. The reference voltage for MPPT is obtained by artificial neural network (ANN) with gradient descent momentum algorithm. The tracking algorithm changes the duty-cycle of the converter so that the PV-module voltage equals the voltage corresponding to the MPPT at any given insolation, temperature, and load conditions. For fast response, the system is implemented using digital signal processor (DSP). The overall system stability is improved by including a proportional-integral-derivative (PID) controller, which is also used to match the reference and battery voltage levels. The controller, based on the information supplied by the ANN, generates the boost converter duty-cycle. The energy obtained is used to charge the lithium ion battery stack for the solar vehicle. The experimental and simulation results show that the proposed scheme is highly efficient.

Project boundary setting and leakage treatment are two important issues to be considered when a clean development mechanism (CDM) project is being designed. There are still many uncertainties concerning these two issues. This paper reviews the concepts of project boundary setting and leakage in CDM projects, cites the types and sources of leakage, discusses the principles for determining leakage, and gives some proposed methods for dealing with leakage. A case study, using several steps to solve the boundary and leakage problems, shows how the analyzed principles and treatments can be implemented in a real project. Based on the result of the case study, the methods discussed are shown to be appropriate for settling leakage issues.

A microstructure oil-damping shock absorber was designed for the protection of electronic-packaging components in vibration-impact environments. The nonlinearity of the oil viscosity, the oil flow characteristics, and the coupling between the oil and the physical structure were included in a mathematical model of the oil-damping shock absorber to attenuate vibrations. The results of multi-parameter-coupled dynamic tests show that the mathematical model accurately simulates the actual physical system of the oil-damping shock absorber. The model could be used for engineering designs of vibration-impact isolation of electronic-packaging components.

Neither the finite element method nor the discontinuous deformation analysis method can solve problems very well in rock mechanics and engineering due to their extreme complexities. A coupling method combining both of them should have wider applicability. Such a model coupling the discontinuous deformation analysis method and the finite element method is proposed in this paper. In the model, so-called line blocks are introduced to deal with the interaction via the common interfacial boundary of the discontinuous deformation analysis domain with the finite element domain. The interfacial conditions during the incremental iteration process are satisfied by means of the line blocks. The requirement of gradual small displacements in each incremental step of this coupling method is met through a displacement control procedure. The model is simple in concept and is easy in numerical implementation. A numerical example is given. The displacement obtained by the coupling method agrees well with those obtained by the finite element method, which shows the rationality of this model and the validity of the implementation scheme.

The characteristics of the air jet from the outlet of a personalized ventilation system were related to the perceived air quality and ventilation rate. The perceived air quality was expressed as percentage of dissatisfied people for a system supplying isothermal fresh air. The relationship was verified using a thermal manikin with a breathing function in a climate chamber sitting by a desk equipped with a personalized ventilation system. A trace gas was introduced into the climate chamber and fully mixed. The personal exposure effectiveness (?p) is based on concentrations of trace gas in the chamber and in the manikin nose which is affected more by the distance between the movable outlet and the occupant's breathing zone than by the personalized air flowrate and does not change much for the personalized air flowrate higher than 10 L/s when the distance is fixed. Some predicted dissatisfied values for a personalized ventilation system compared with those acquired in human subject experiments have an absolute difference of less than 3%.

An artificial neural network (ANN) is applied in the preliminary structural design of reticulated shells. Major efforts are made to enhance the generalization ability of networks through well-selected training samples. Number-theoretic methods (NTMs) are adopted to generate samples with low discrepancy, i.e., uniformly scattered in the domain, where discrepancy is a quantitative measurement of the uniformity. The discrepancy of the NTM-based sample set is 1/6-1/7 that of samples with equal spacing. In a case study, networks trained by NTM-based samples are compared with those trained by equal-spaced samples in generalizing performance. The results show that both the computational precision and stability of the former ANNs are more satisfactory than those of the latter. It is concluded that the flexibility of ANNs in generalizing can be effectively increased by use of uniformly distributed training samples rather than simply piling data. More reliable uniformity should be obtained, however, through NTMs instead of equal-spaced samples.

Power system security and reliability are more complex issues in a deregulated environment. Various criteria have been considered for power system reliability. In the day-ahead market, a successful trade schedule should be able to accept various disturbances with sufficient flexibility to be adjusted during the re-dispatch process. This paper describes the dispatch liquidity theory and some liquidity indices. The liquidity indices evaluate the effective operating reserves with the network constraints taken into consideration. A model is presented to calculate the liquidity index. An extended trade scheduling model with minimum liquidity index constraints is presented that considers the distribution requirements of the operating reserves. The liquidity indices could also be used to coordinate the security and reliability between multistage markets and for contingency selection. The algorithms were tested with real power system data. The results show that the dispatch liquidity theory is reasonable and the algorithms are effective.

A new fault location method based on six-sequence fault components was developed for parallel lines based on the fault analysis of a joint parallel transmission line. In the six-sequence fault network, the ratio of the root-mean square value of the fault current from two terminals is the function of the line impedance, the system impedance, and the fault distance away from the buses. A fault location equation is given to relate these factors. For extremely long transmission lines, the distributed capacitance is divided by the fault point and allocated to the two terminals of the transmission line in a lumped parameter to eliminate the influence of the distributed capacitance on the location accuracy. There is no limit on fault type and synchronization of the sampling data. Simulation results show that the location accuracy is high with an average error about 2%, and it is not influenced by factors such as the load current, the operating mode of the power system, or the fault resistance.

Risk models with stochastic investment return are widely held in practice, as well as in more challenging research fields. Risk theory is mainly concerned with ruin probability, and a tight bound for ruin probability is the best for practical use. This paper presents a discrete time risk model with stochastic investment return. Conditional expectation properties and martingale inequalities are used to obtain both exponential and non-exponential upper bounds for the ruin probability.

This paper analyzes a continuous time risk model with a linear model used to model the claim process. The time is discretized stochastically using the times when claims occur, using Doob's stopping time theorem and martingale inequalities to obtain expressions for the ruin probability as well as both exponential and non-exponential upper bounds for the ruin probability for an infinite time horizon. Numerical results are included to illustrate the accuracy of the non-exponential bound.

At present, there are few effective ways to analyze area logistics systems. This paper uses system dynamics to analyze the area logistics system and establishes a system dynamics model for the area logistics system based on the characteristics of the area logistics system and system dynamics. Numerical simulations with the system dynamic model were used to analyze a logistic system. Analysis of the Guangzhou economy shows that the model can reflect the actual state of the system objectively and can be used to make policy and harmonize environment.

A very promising technology to achieve a carbon free energy system is to produce hydrogen from water, rather than from fossil fuels. Iodine-sulfur (IS) thermochemical water decomposition is one promising process. The IS process can be used to efficiently produce hydrogen using the high temperature gas-cooled reactor (HTGR) as the energy source supplying gas at 1000癈. This paper describes that demonstration experiment for hydrogen production was carried out by an IS process at a laboratory scale. The results confirmed the feasibility of the closed-loop operation for recycling all the reactants besides the water, H2, and O2 . Then the membrane technology was developed to enhance the decomposition efficiency. The maximum attainable one-pass conversion rate of HI exceeds 90% by membrane technology, whereas the equilibrium rate is about 20%.