Representation of 3D surfaces by two-variable Fourier descriptors

A method for generating two-variable 3D FDs directly from a striped lighting system is developed. An iterative algorithm is proposed to compute the two-variable 3D FDs for both axisymmetric and nonaxisymmetric objects and a formula for convergence test is derived. Experiments conducted for a set of 3D objects show that the iterative algorithm converges very quickly and the two-variable 3D FD representations are attained accurately     

Surface properties and interfacial adhesion studies of aramid fibres modified by gas plasmas

The surface of aramid (Kevlar 49) fibre was modified by NH₃, O₂ or H₂O plasmas in order to improve the adhesion to epoxy resin. Electron spectroscopy for chemical analysis (ESCA) and static secondary ion mass spectroscopy (SSIMS) were used to identify the chemical compositions and functional groups of the plasma-treated fibre surface, respectively. The surface topography and mechanical properties of plasma-treated fibres were also investigated. After plasma treatments, the interfacial shear strength (IFSS) of aramid-fibre/epoxy-resin composites, as measured by the microbond pull-out technique, was markedly improved (43–83% improvement) and the fibre strength was only little affected (less than 10% loss). Significant improvement in the IFSS principally resulted from forming the covalent bonds between the newly reactive functionalities at the modified fibre surfaces and the epoxides of the resin.     

Improved Light Extraction Efficiency in AlGaInP Light-Emitting Diodes by Applying a Periodic Texture on the Surface

In this letter, AlGaInP-GaP-based light-emitting diodes (LEDs) were fabricated with an Si substrate and an SiO₂-ITO-Ag omni-directional reflector using a metal-to-metal bonding technique. To enhance light extraction efficiency, a periodic texture was applied to the (Al_0.5Ga_0.5)_0.5In_0.5P surface layer of AlGaInP-Si LEDs by photolithography and a wet etching process. The exterior of the etched texture consists of a series of bowl-shaped recesses. With a 350-mA current injection, the typical output power of the AlGaInP-Si LEDs with and without the textured surface (LED-I and LED-II, respectively) were measured at approximately 118 and 81 mW, respectively, when the LED chips were bonded on the TO 46 without resin encapsulation. The enhancement of output power in LED-I can be attributed to a multitude of bowl-shaped notches on the surface, which resulted in a reduction of the reabsorption probability of the photons due to the fact that the photon path length in LED-I is shorter than in LED-II before the photons escape into the free space.     

Phosphor-Free GaN-Based Transverse Junction White-Light Light-Emitting Diodes With Regrown n-Type Regions

In this study, we demonstrate a GaN-based phosphor-free white-light light-emitting diode (LED), which is composed of GaN-based dual-wavelength (blue and yellow-green) multiple-quantum-wells (MQWs) and a transverse p-n junction. The device was realized by the regrowth of n-type GaN layers on the sidewall of p-type GaN and undoped MQWs. The problems related to the bias-dependent shape of the electroluminescence spectra that occur in traditional phosphor-free white-light LEDs (with vertical p-n junctions) are greatly minimized. The current-voltage performance of our device is comparable to that of the commercially available phosphor white-light LEDs. In addition, the dynamic measurement results indicate that we can attain a much higher modulation bandwidth (22 versus 3 MHz) with this device than with the currently available commercial ones.     

A Distributed Localization Scheme for Wireless Sensor Networks with Improved Grid-Scan and Vector-Based Refinement

Localization is a fundamental and essential issue for wireless sensor networks (WSNs). Existing localization algorithms can be categorized as either range-based or range-free schemes. Range-based schemes are not suitable for WSNs because of their irregularity of radio propagation and their cost of additional devices. In contrast, range-free schemes do not need to use received signal strength to estimate distances and only need simple and cheap hardware, and are thus more suitable for WSNs. However, existing range-free schemes are too costly and not accurate enough or are not scalable. To improve previous work, we present a fully distributed range-free localization scheme for WSNs. We assume that only a few sensor nodes, called anchors, know their locations, and the remaining (normal) nodes need to estimate their own locations by gathering nearby neighboring information. We propose an improved grid-scan algorithm to find the estimated locations of the normal nodes. Furthermore, we derive a vector-based refinement scheme to improve the accuracy of the estimated locations. Analysis, simulation, and experiment results show that our scheme outperforms the other range-free schemes even when the communication radius is irregular.     

Learning Association Rules and Tracking the Changing Concepts on Webpages: An Effective Pornographic Websites Filtering Approach

We applied the decision tree algorithm to learn association rules between webpage’s category (pornographic or normal) and the critical features. Based on these rules, we proposed an efficient method of filtering pornographic webpages with the following major advantages: 1) a weighted window-based technique was proposed to estimate for the condition of concept drift for the keywords found recently in pornographic webpages; 2) checking only contexts of webpages without scanning pictures; 3) an incremental learning mechanism was designed to incrementally update the pornographic keyword database.     

Strengths and weaknesses of finite element modeling deep hole drilling as compared with beam and column equations

Deep hole drilling has been studied mainly experimentally in the past. Recently, some theories using beam or column equations have been proposed, which involved complicated mathematical efforts. This work analyzed deep hole drilling by a finite element model (FEM). Results of modal analysis on the established FEM were compared with results from Euler beam equations. Further analysis showed that the FEM could also predict straightness deviation as did the column equation. In addition, FEM could analyze the effects of variable support distance which neither beam nor column equation could. Other analysis results are also presented. The results in this study showed the strength and weakness of the FEM.     

Integrating multivariate engineering process control and multivariate statistical process control

Multivariate engineering process control (MEPC) and multivariate statistical process control (MSPC) are two strategies for quality improvement that have developed independently. MEPC aims to minimize variability by adjusting process variables to keep the process output on target. On the other hand, MSPC aims to reduce variability by monitoring and eliminating assignable causes of variation. In this paper, the use of MEPC alone is compared to using the MEPC coupled with MSPC. We use simulations to evaluate the average run lengths (ARL) and the averages of the performance measure. The simulation results show that the use of both MEPC and MSPC can always outperform the use of either alone. To detect small sustained shifts of the mean vector, combing MEPC with a multivariate generally weighted moving average (MGWMA) chart (MEPC/MGWMA) is more sensitive than the MEPC/multivariate exponentially weighted moving average (MEWMA) chart and MEPC/Hotelling’s χ² chart. An example of the application, based on the proposed method, is also given.     

Generally weighted moving average control chart for monitoring process variability

Most applications of the EWMA control chart for monitoring processes depend on detecting shifts in the process mean. The problem of detecting an increase in process variability, which can also strongly affect the quality of products, is perhaps more important. When a process moves from the pilot phase to the production phase, the mean may not shift but the variation will probably increase because new sources of variation are introduced, including new people and materials. A simulation is performed to evaluate the ARL to false alarm and to monitor the change in the process variability of the EWMA control chart and the GWMA control chart. An extensive comparison reveals that the GWMA control chart is more sensitive than the EWMA control chart in monitoring the variance of a process. The results of this study can be applied to monitor the process variability in automated industries.     

Forecasting the volatility of a combined multi‐country stock index using GWMA algorithms

Globalization has increased the volatility of international financial transactions, particularly those related to international stock markets. An increase in the volatility of one country's stock market spreads throughout the globe, affecting other countries' stock markets. In particular, the Dow Jones Industrial Average plays an extremely important role in the international stock market. This paper uses the generally weighted moving average method and data from the Dow Jones Industrial Average, the National Association of Securities Dealers Automated Quotations, Japan's Nikkei 225, the Korea Composite Stock Price Index, and the Hong Kong Hang Seng Index to predict the performance of the Taiwan Capitalization Weighted Stock Index. This paper attempts to find the smallest prediction error using the optimal combination of generally weighted moving average model parameters and combinations of various international stock market data and compares the results to that found using the exponentially weighted moving average model to explore differences between the two types of forecasting models.