High birefringence photonic bandgap fiber with elliptical air holes

In this paper, we proposed a high birefringence photonic bandgap fiber (PBGF) with elliptical air holes in cladding and circular air hole in core. The forbidden gaps of the honeycomb structure are calculated when the circular air holes are deformed to the elliptical shape. And the birefringence of the PBGFs is investigated by using a full-vector finite element method (FEM) and the numerical results are presented.     

OPAH a model for optimal design of multipurpose small hydropower plants

The investment in small hydropower plants requires the analysis of hydrological, technical, operational, budgetary, economical and financial aspects. The analysis of each possible configuration demands the joint action of several technicians, consuming substantial time and money. During initial design of the project, simplified procedures are usually adopted which may compromise the quality of the base configuration.In this paper we will present a global overview of the OPAH model, which was developed to surpass these limitations. This global model performs the optimization of project configuration. This model uses non-linear programming optimization to analyze the multipurpose operation of the hydropower plant. It uses a numeric simulation model of unsteady flow under pressure to analyze the hydraulic circuit. It uses an economical and financial simulation model that takes in to account the project risk associated to hydrologic and market variability, the financial capacity of the investor and the fiscal aspects.     

Improved resolution of the multiple inverse method by eliminating erroneous solutions

The multiple inverse method is a numerical technique designed to separate stresses from heterogeneous fault–slip data. The method is one of the resampling methods based on the pattern recognition. Plotting solutions determined from k-fault subset into the parameter space, we have clusters representing significant stresses for the dataset. This paper presents a technique to improve the resolution of stress for the method. The regularity/singularity test of the subsets taken from the fault–slip data is the key for this purpose. The resolution and accuracy of the method are improved by eliminating erroneous stresses or artifacts that were yielded by the method. The performances of the method are demonstrated with a variety of artificial datasets.     

Implementation of RNS-Based Distributed Arithmetic Discrete Wavelet Transform Architectures Using Field-Programmable Logic

Currently there are design barriers inhibiting the implementation of high-precision digital signal processing (DSP) objects with field programmable logic (FPL) devices. This paper explores overcoming these barriers by fusing together the popular distributed arithmetic (DA) method with the residue number system (RNS) for use in FPL-centric designs. The new design paradigm is studied in the context of a high-performance filter bank and a discrete wavelet transform (DWT). The proposed design paradigm is facilitated by a new RNS accumulator structure based on a carry save adder (CSA). The reported methodology also introduces a polyphase filter structure that results in a reduced look-up table (LUT) budget. The 2C-DA and RNS-DA are compared, in the context of a FPL implementation strategy, using a discrete wavelet transform (DWT) filter bank as a common design theme. The results show that the RNS-DA, compared to a traditional 2C-DA design, enjoys a performance advantage that increases with precision (wordlength).     

A study on flowshop scheduling problem combining Taguchi experimental design and genetic algorithm

As genetic algorithm parameters vary depending on different problem types when applying genetic algorithm to reach global optimum, appropriate design value selection has significant impact on the efficiency of genetic algorithm. However, most users adjust parameters manually based on the reference values of previous literature. Such trial-and-error method is time-consuming, ineffective, and often it could not locate the optimal combination. Therefore, in flowshop scheduling problems, this research anticipates to complete optimal parameter combination design in genetic algorithm using Taguchi experimental design. According to the research results, different ways of producing initial solution have significant influence on this research topic. Consequently, confirmation experiment is conducted using the optimal parameter combination obtained from the research results. It is found that the predicted value of signal-to-noise ratio (S/N ratio) and its actual value exists deviation of 0.238%, indicating repetitiveness and robustness of the obtained parameter combination. Hence, this research method can effectively reduce time spent on parameter design using genetic algorithm and increase efficiency of algorithm.     

The influence of Johnson–Cook material constants on finite element simulation of machining of AISI 316L steel

In literature, five different sets of work material constants used in the Johnson–Cook's (J–C) constitutive equation are implemented in a numerical model to describe the behaviour of AISI 316L steel. The aim of this research is to study the effects of five different sets of material constants of the J–C constitutive equation in finite-element modelling of orthogonal cutting of AISI 316L on the experimental and predicted cutting forces, chip morphology, temperature distributions and residual stresses. Several experimental equipments were used to estimate the experimental results, such as piezoelectric dynamometer for cutting forces measurements, thermal imaging system for temperature measurements and X-ray diffraction technique for residual stresses determination on the machined surfaces; while an elastic–viscoplastic FEM formulation was implemented to predict the local and global variables involved in this research. It has been observed that all the considered process output and, in particular the residual stresses are very sensitive to the J–C's material constants.     

Tackling group-to-tree matching in large scale group communications

As a mechanism to efficiently support group communications, multicasting, faces a serious state scalability problem when there are large numbers of groups in the network. Recently, a novel solution called Aggregated Multicast has been proposed, in which multiple groups can share one delivery tree. A key problem in Aggregated Multicast is group-to-tree matching (i.e., assigning groups to proper trees). In this paper, we formally define this problem, and formulate two versions of the problem: static and dynamic. We analyze the static version and prove that it is NP-complete. To tackle this hard problem, we propose three algorithms: one optimal (using Linear Integer Programming, or ILP), one near-optimal (using Greedy method), and one Pseudo-Dynamic algorithm. For the dynamic version, we present a generic dynamic on-line algorithm. Simulation study has been conducted to evaluate the performance of the algorithms. Our results show that: (1) for the static problem, the Greedy algorithm is a feasible solution and its performance is very close to the optimal ILP solution, while the Pseudo-Dynamic algorithm is a good heuristic for many cases where Greedy does not work well; (2) for the dynamic problem, the generic dynamic on-line algorithm is a very practical solution with promising performance and reasonable computation requirement.     

Electrochemical characteristics of heme proteins in hydroxyethylcellulose film

A stable film made from hydroxyethylcellulose (HEC) on pyrolytic graphite (PG) electrode was employed for incorporating hemoglobin (Hb), myoglobin (Mb) and horseradish peroxidase (HRP), and the electrochemical characteristics of the proteins were studied correspondingly. Experimental results revealed that HEC film could greatly accelerate electron transfer between the proteins and electrode, and the proteins showed a thin layer electrochemical behavior in the film. Moreover, all the proteins in the film exhibited good catalytic activity towards the reduction of hydrogen peroxide (H₂O₂) in the low H₂O₂ concentration range. In the high concentration range, H₂O₂ would exhibit toxicity effect on the proteins. The electrochemical properties and electrocatalytic abilities of the three heme proteins in HEC film have been compared, and the optimal conditions for H₂O₂ biosensor fabrication have been obtained.     

Electrical properties of dysprosium phthalocyanine films

Forty-four nanometers thick films of alkyl-substituted dysprosium phthalocyanine molecules were prepared on carefully cleaned indium tin oxide (ITO) substrates by the spin casting method. UV–vis absorption spectra and dc conduction characteristics were obtained in order to investigate the structure–conduction property relationship. The conduction is Ohmic at low applied voltages but the space charge limited mechanism is prevalent at relatively high voltages. The conductivities of both as-deposited and heat treated films are found to show directionally anisotropic behaviour. The columnar conductivity was found to be significantly large in the liquid crystalline state.     

Applications of data analysis techniques for oil production prediction

This paper describes two data analysis techniques adopted in a Decision Support System (DSS) that aids users in predicting oil production of an infill well. The system generates predictions in the form of a possible range of cumulative production and length of production life of an infill well. The system also shows the worst and best case scenarios based on different production curves so that the expert can examine the plots of predicted production rates for each existing well and decide which model gives the best fit. The production curve of each individual well was mathematically modeled so that production values beyond the historical data can be produced. Decline curve estimation and neural network approaches were adopted for data analysis in the system. The system was tested with data from two groups of wells from two different fields in Saskatchewan, Canada. Observations on the suitable duration that the historical data set should cover and a comparison among different curve estimation and neural network models are presented.