Polarization-insensitive electroabsorption by use of quantum well interdiffusion

A paraboliclike quantum well structure can be used to produce polarization-insensitive waveguide type modulators. We propose the use of interdiffusion of AlGaAs/GaAs quantum wells to achieve the parabolic well shape. Criteria to achieve the paraboliclike quantum wells by interdiffusion are discussed. The theoretical results indicate that interdiffused quantum wells can produce equal eigenstate spacing, polarization insensitive Stark shifts, and modulation similar to an ideal parabolic quantum well. Three procedures are also proposed to develop polarization-insensitive on and off states in paraboliclike interdiffused quantum wells. The modulation depth is compatible with that of the measured parabolic quantum wells. For diffused quantum wells one can take advantage of using an as-grown rectangular quantum well with postgrowth thermal processing. These features demonstrate that an interdiffused quantum well structure can be used to produce a polarization-insensitive electroabsorptive modulator.     

Efficiently extendible mappings for balanced data distribution

In data storage applications, a large collection of consecutively numbered data “buckets” are often mapped to a relatively small collection of consecutively numbered storage “bins.” For example, in parallel database applications, buckets correspond to hash buckets of data and bins correspond to database nodes. In disk array applications, buckets correspond to logical tracks and bins correspond to physical disks in an array. Measures of the “goodness” of a mapping method include:

1. Thetime (number of operations) needed to compute the mapping.
2. Thestorage needed to store a representation of the mapping.
3. Thebalance of the mapping, i.e., the extent to which all bins receive the same number of buckets.
4. The cost ofrelocation, that is, the number of buckets that must be relocated to a new bin if a new mapping is needed due to an expansion of the number of bins or the number of buckets.

One contribution of this paper is to give a new mapping method, theInterval-Round-Robin (IRR) method. The IRR method has optimal balance and relocation cost, and its time complexity and storage requirements compare favorably with known methods. Specifically, ifm is the number of times that the number of bins and/or buckets has increased, then the time complexity isO(logm) and the storage isO(m ²). Another contribution of the paper is to identify the concept of ahistory-independent mapping, meaning informally that the mapping does not “remember” the past history of expansions to the number of buckets and bins, but only the current number of buckets and bins. Thus, such mappings require very little information to be stored. Assuming that balance and relocation are optimal, we prove that history-independent mappings are possible if the number of buckets is fixed (so only the number of bins can increase), but not possible if the number of bins and buckets can both increase.     

Elicitator: An expert elicitation tool for regression in ecology

Expert elicitation is the process of retrieving and quantifying expert knowledge in a particular domain. Such information is of particular value when the empirical data is expensive, limited or unreliable. This paper describes a new software tool, called Elicitator, which assists in quantifying expert knowledge in a form suitable for use as a prior model in Bayesian regression. Potential environmental domains for applying this elicitation tool include habitat modelling, assessing detectability or eradication, ecological condition assessments, risk analysis and quantifying inputs to complex models of ecological processes. The tool has been developed to be user-friendly, extensible and facilitate consistent and repeatable elicitation of expert knowledge across these various domains. We demonstrate its application to elicitation for logistic regression in a geographically based ecological context. The underlying statistical methodology is also novel, utilizing an indirect elicitation approach to target expert knowledge on a case-by-case basis. For several elicitation sites (or cases), experts are asked simply to quantify their estimated ecological response (e.g. probability of presence), and its range of plausible values, after inspecting (habitat) covariates via GIS.     

P(VDF-TrFE) copolymer acoustic emission sensors

Acoustic emission (AE) sensors have been fabricated using polarized polyvinylidene fluoride/trifluoroethylene (P(VDF-TrFE)) piezoelectric copolymer films. The acoustic and electromechanical properties of the copolymers have been determined using the ultrasonic immersion technique and the resonance technique, respectively. The P(VDF-TrFE) AE sensors have been calibrated according to the ASTM standard and evaluated for potential application in the detection of AE in glass fiber reinforced polypropylene (GFPP). A ceramic AE sensor also has been fabricated using lead zirconate titanate (PZT) 7A piezoelectric ceramic and its sensitivity and performance are reported as well. The copolymer sensors do not show resonance peaks of the ceramic sensor and have adequate sensitivity. They can reproduce AE signals accurately without giving artifacts and have potential use in commercial AE systems.     

An Artificial Neural Network Classifier Design Based-on Variable Kernel and Non-Parametric Density Estimation

This paper proposes a probabilistic variant of the SOM-kMER (Self Organising Map-kernel-based Maximum Entropy learning Rule) model for data classification. The classifier, known as pSOM-kMER (probabilistic SOM-kMER), is able to operate in a probabilistic environment and to implement the principles of statistical decision theory in undertaking classification problems. A distinctive feature of pSOM-kMER is its ability in revealing the underlying structure of data. In addition, the Receptive Field (RF) regions generated can be used for variable kernel and non-parametric density estimation. Empirical evaluation using benchmark datasets shows that pSOM-kMER is able to achieve good performance as compared with those from a number of machine learning systems. The applicability of the proposed model as a useful data classifier is also demonstrated with a real-world medical data classification problem.     

Environmental effects on the coevolution of pursuit and evasion strategies

The game of tag is frequently used in the study of pursuit and evasion strategies that are discovered through competitive coevolution. The aim of coevolution is to create an arms race where opposing populations cyclically evolve in incremental improvements, driving the system towards better strategies. A coevolutionary simulation of the game of tag involving two populations of agents; pursuers and evaders, is developed to investigate the effects of a boundary and two obstacles. The evolution of strategies through Chemical Genetic Programming optimizes the mapping of genotypic strings to phenotypic trees. Four experiments were conducted, distinguished by speed differentials and environmental conditions. Designing experiments to evaluate the efficacy of emergent strategies often reveal necessary steps needed for coevolutionary progress. The experiments that excluded obstacles and boundaries provided design pointers to ensure coevolutionary progress as well as a deeper understanding of strategies that emerged when obstacles and boundaries were added. In the latter, we found that an awareness of the environment and the pursuer was not critical in an evader’s strategy to survive, instead heading to the edge of the boundary or behind an obstacle in a bid to ‘throw-off or hide from the pursuer’ or simply turn in circles was often sufficient, thereby revealing possible suboptimal strategies that were environment specific. We also observed that a condition for coevolutionary progress was that the problem complexity must be surmountable by at least one population; that is, some pursuer must be able to tag an opponent. Due to the use of amino-acid building blocks in our Chemical Genetic Program, our simulations were able to achieve significant complexity in a short period of time.

A real-time food safety management system for receiving operations in distribution centers

Food safety plan is being promoted in the food industry by the Hong Kong Government as a preliminary quality control tool. However, it appears to be a challenging task for Distribution Centers (DC) that handles food inventory since most of them are lack of knowledge and know how technology to manage information in a real time base. This paper proposes a Radio Frequency Identification based Food Operations Assignment System (RFID-FOAS) to help DC facilitates the food safety control activities in receiving areas by generating a proper safety plan. The system has adopted the Radio Frequency Identification (RFID) technology and the Case-Based Reasoning (CBR) technique to facilitate the inventory data-capturing process and assist in formulating decisions, respectively. The developed system aims to help reduce the difficulties in safety plan development using a knowledge-based expert system. The significance and contribution of RFID-FOAS in the context of managing the inventory quality in DC for safety plan development is demonstrated through the adoption of the system in a Hong Kong-based logistics company. The generated results show that the decision-making process of the safety plan development is facilitated. Moreover, the real-time data capturing nature of RFID technology has further improved the efficiency and timeframe requested for the actions. With the support of RFID-FOAS, the data capture system and the decision-making time is minimized. As a result, inventory quality and customer satisfaction level are significantly improved.     

Epitaxial growth of CeO2/yttria-stabilized ZrO2 double layer films on biaxially textured Ni tape via electrostatic spray assisted vapour deposition

Epitaxial growth of CeO₂ and yttria-stabilized ZrO₂ (YSZ) double layer films has been successfully carried out on biaxially textured nickel substrates at a temperature between 400 and 600 °C using electrostatic spray assisted vapour deposition method. The structure of the double layer was characterized by X-ray diffraction and scanning electron microscopy. The results show that highly oriented CeO₂/YSZ double buffer films were formed epitaxially onto biaxially textured Ni substrates. The orientation relationships between YSZ layer and Ni substrate are 001_YSZ//001_Ni and 110_YSZ//100_Ni, while the orientation relationships between CeO₂ and YSZ are 001_CeO2//001_YSZ and 100_CeO2//100_YSZ.     

外延SCNN电光薄膜生长及研究

用激光脉冲沉积(PLD)法在MgO(001)衬底上成功地生长、制备出了外延铌酸锶钡钠(SCNN)电光薄膜.对生长制备出的SCNN电光薄膜用X射线衍射对其微观结构进行了测量研究;X射线衍射结果显示生长在MgO(001)衬底上的SCNN电光薄膜是外延膜;对生长在MgO(001)衬底上的外延SCNN电光薄膜在200～900nm光谱范围的透射光谱进行了测量研究,通过对薄膜透射光谱的振荡曲线分析计算得到了SCNN电光薄膜的光学常数,结果发现外延SCNN电光薄膜的折射率符合单电子模型.