Discriminant Analysis Based Prognostics of Avionic Systems

In this paper, a novel discriminant analysis based predictive model for preventing false alarms leading to unnecessary replacement of an avionic system component is presented. The model is validated by prediction of false alarms (also known as false positives, type I, or alpha errors) in the left generator shaft of a Sikorsky helicopter UH-60, using the Goodrich health and usage management system (HUMS). The paper presents one of the first approaches based on applying discriminant analysis for prognostics of avionic systems, specifically in the context of identifying false positives within the next 1 or 2 h. In practice, predictions for the next 2 h are sufficient as typical helicopter flight schedules and durations are such that up to 2 h advance notice is most useful. This is an important contribution because drive train components of helicopters are normally very robust with very rare failures; therefore, the cost of unnecessary preventive maintenance based on false alarms is very high.     

Midwavelength Infrared Avalanche Photodiode Using InAs–GaSb Strain Layer Superlattice

InAs-GaSb strain layer superlattice p⁺-n^--n avalanche photodiodes (APDs) are fabricated using a newly introduced electron-beam aided zinc sulfide deposition. Temperature-dependent measurements were performed on 300 times 300 mum² mesa etched APDs. The effect of passivation was also studied on the diode characteristics and APD performances. Temperature-dependent gain strongly correlates with avalanche mechanism.     

Ultra-Thin Si<Subscript>1−<Emphasis Type="Italic">x</Emphasis></Subscript>Ge<Subscript><Emphasis Type="Italic">x</Emphasis></Subscript> Dislocation Blocking Layers for Ge/Strained Si CMOS Devices

We demonstrate ultra-thin (<150 nm) Si_1−x Ge _x dislocation blocking layers on Si substrates used for the fabrication of tensile-strained Si N channel metal oxide semiconductor (NMOS) and Ge P channel metal oxide semiconductor (PMOS) devices. These layers were grown using ultra high vacuum chemical vapor deposition (UHVCVD). The Ge mole fraction was varied in rapid, but distinct steps during the epitaxial layer growth. This results in several Si_1−x Ge _x interfaces in the epitaxially grown material with significant strain fields at these interfaces. The strain fields enable a dislocation blocking mechanism at the Si_1−x Ge _x interfaces on which we were able to deposit very smooth, atomically flat, tensile-strained Si and relaxed Ge layers for the fabrication of high mobility N and P channel metal oxide semiconductor (MOS) devices, respectively. Both N and P channel metal oxide semiconductor field effect transister (MOSFETs) were successfully fabricated using high-k dielectric and metal gates on these layers, demonstrating that this technique of using ultra-thin dislocation blocking layers might be ideal for incorporating high mobility channel materials in a conventional CMOS process.     

Crystallization behaviour and mechanical properties of rapidly solidified Al<Subscript>87.5</Subscript>Ni<Subscript>7</Subscript>Mm<Subscript>5</Subscript>Fe<Subscript>0.5</Subscript> amorphous alloy

The crystallization behaviour and the mechanical properties of rapidly solidified Al_87.5Ni₇Mm₅Fe_0.5 alloy ribbons have been examined in both as-melt-spun and heat-treated condition using differential scanning calorimetry, X-ray diffractometry (XRD), transmission electron microscopy (TEM), tensile testing and Vicker’s microhardness machine. XRD and TEM studies revealed that the as-melt-spun ribbons are fully amorphous. The amorphous ribbon undergoes three-stage crystallization process upon heating. Primary crystallization resulted in the formation of fine nanocrystalline fcc-Al particles embedded in the amorphous matrix. The second and third crystallization stages correspond to the precipitation of Al₁₁(La,Ce)₃ and Al₃Ni phases, respectively. Microhardness and tensile strength of the ribbons were examined with the variation of temperature and subsequently correlated with the evolved structure. Initially, the microhardness of the ribbon increases with temperature followed by a sharp drop in hardness owing to the decomposition of amorphous matrix that leads to formation of intermetallic compounds     

A Case‐Based Reasoning system for complex medical diagnosis

A Case‐Based Reasoning (CBR) system for medical diagnosis mimics the way doctors make a diagnosis. Given a new case, its accuracy in practice depends on successful retrieval of similar cases. CBR systems have had some success in dealing with simple diseases because of the robustness of their case base. However, their diagnostic accuracy suffers when dealing with complex diseases particularly those that involve multiple domains in medicine. An example of such a condition is Premenstrual syndrome (PMS) as it falls under both gynaecology and psychiatry. To address this issue, the paper proposes a CBR‐based expert system that uses the K‐nearest neighbour (KNN) algorithm to search k similar cases based on the Euclidean distance measure. The novelty of the system is in the design of a flexible auto‐set tolerance (T), which serves as a threshold to extract cases for which similarities are greater than the assigned value of T. A prototype software tool with a menu‐driven Graphical User Interface (GUI) has been developed for case input, analysis of results, and case adaptation within the system. Finally, the performance of the tool has been checked on a set of real‐world PMS cases.     

Robust manufacturing system design using multi objective genetic algorithms,Petri nets and Bayesian uncertainty representation

Decisions involving robust manufacturing system configuration design are often costly and involve long term allocation of resources. These decisions typically remain fixed for future planning horizons and failure to design a robust manufacturing system configuration can lead to high production and inventory costs, and lost sales costs. The designers need to find optimal design configurations by evaluating multiple decision variables (such as makespan and WIP) and considering different forms of manufacturing uncertainties (such as uncertainties in processing times and product demand). This paper presents a novel approach using multi objective genetic algorithms (GA), Petri nets and Bayesian model averaging (BMA) for robust design of manufacturing systems. The proposed approach is demonstrated on a manufacturing system configuration design problem to find optimal number of machines in different manufacturing cells for a manufacturing system producing multiple products. The objective function aims at minimizing makespan, mean WIP and number of machines, while considering uncertainties in processing times, equipment failure and repairs, and product demand. The integrated multi objective GA and Petri net based modeling framework coupled with Bayesian methods of uncertainty representation provides a single tool to design, analyze and simulate candidate models while considering distribution model and parameter uncertainties.     

High-dimensional MRI data analysis using a large-scale manifold learning approach

A novel manifold learning approach is presented to efficiently identify low-dimensional structures embedded in high-dimensional MRI data sets. These low-dimensional structures, known as manifolds, are used in this study for predicting brain tumor progression. The data sets consist of a series of high-dimensional MRI scans for four patients with tumor and progressed regions identified. We attempt to classify tumor, progressed and normal tissues in low-dimensional space. We also attempt to verify if a progression manifold exists—the bridge between tumor and normal manifolds. By identifying and mapping the bridge manifold back to MRI image space, this method has the potential to predict tumor progression. This could be greatly beneficial for patient management. Preliminary results have supported our hypothesis: normal and tumor manifolds are well separated in a low-dimensional space. Also, the progressed manifold is found to lie roughly between the normal and tumor manifolds.     

Study on coke size degradation from coke plant wharf to blast furnaces stock house

The gas permeability, which is one of the most important requirements served by coke, is dependent largely on the size distribution of the coke at the various zones in the blast furnace. This papers deals with breakage of coke when it travels from wharf to blast furnace. In this study, six different coal blend samples in the range of 23.6–25.0% volatile matter and 11.7–14.8% ash were studied in stamp charged coke making process (wet bulk density 1.15 t/m³). The coke samples were collected from battery no. 8 wharf, CK06 (conveyer belt) and auto sampler. All experiments were conducted on shatter machine and an attempt has been made to find out reasons for breakage of coke. Results indicate that the coke size degradation is function of transporting system and dropping height of coke from wharf to blast furnace. It was also found that in stamp charging condition, it is possible to improve yield of blast furnace grade coke even at higher composition balance index of coal blend (2.94–3.70).     

Researching haptics in higher education: The complexity of developing haptics virtual learning systems and evaluating its impact on students’ learning

hapTEL, an interdisciplinary project funded by two UK research councils from 2007 to 2011, involves a large interdisciplinary team (with undergraduate and post-graduate student participants) which has been developing and evaluating a virtual learning system within an HE healthcare education setting, working on three overlapping strands. Strand 1 involves the technical development and evaluation of the hapTEL workstation which simulates clinical conditions for dental training including haptics (sense of touch). Strand 2 involves examining the traditional undergraduate curriculum and how this could benefit from the use of haptics. Strand 3 is concerned with the educational evaluation of the impact of the work carried out within Strands 1 and 2. Two theoretical frameworks (Entwistle, (1987) and Webb and Cox (2004)) have been used to identify as many factors as possible which could affect the impact of Technology Enhanced Learning (TEL) on the quality of the learning achieved. These frameworks have formed a foundation for measuring the impact of TEL on curriculum change, teachers’ pedagogical practices, students’ learning and on institutional practices. A range of quantitative and qualitative methods were designed, piloted and evaluated in order to measure the impact of TEL on teaching and learning; and to have a rich and robust data set which also addresses the variables in the frameworks. The results from using these frameworks show that institutional and departmental factors should be considered when evaluating the impact of TEL in higher education and that these had a major influence on the design and curriculum integration of the hapTEL systems. We have also shown that by involving the end users from the beginning enabled not only an enhancement of the students’ learning experiences but also a modification to the traditional curriculum itself and the successful integration of TEL within a very traditional undergraduate higher education dental curriculum. The conclusions from this paper confirm earlier reviews of researching TEL that technology integration is extremely complex and the related research requires a comprehensive approach of both quantitative and qualitative methods if one is to take account of the range of variables identified by theoretical frameworks. Finally, repeating the range of empirical investigations for a second year enables researchers to validate the effectiveness of the methods used in the initial year and thereby maximise the reliability and generalisability of the research outcomes.     

A boundary element method for steady incompressible thermoviscous flow

A boundary element formulation is presented for moderate Reynolds number, steady, incompressible, thermoviscous flows. The governing integral equations are written exclusively in terms of velocities and temperatures, thus eliminating the need for the computation of any gradients. Furthermore, with the introduction of reference velocities and temperatures, volume modelling can often be confined to only a small portion of the problem domain, typically near obstacles or walls. The numerical implementation includes higher order elements, adaptive integration and multiregion capability. Both the integral formulation and implementation are discussed in detail. Several examples illustrate the high level of accuracy that is obtainable with the current method.