Economic Comparison of NdFeB and Hard Ferrites in Automotive Applications

With the increasing use of electric motors in automobiles—in some cases as many as 100 electric motors per vehicle—alternatives to ferrite magnetic materials are under consideration. If more powerful magnetic materials could be implemented, size reductions in these motors could result in curb weight reductions that lead to improved fuel economy. NdFeB magnets are attractive as potential replacement materials, due to their higher flux density and thus smaller required size; however, high material costs have limited their implementation. To investigate the economic competitiveness of alternative magnetic materials, technical cost models (TCMs) were developed and used to examine the manufacturing economics related to the production of both NdFeB and ferrite magnets. Results from the TCMs are used to identify the cost drivers and opportunities for cost reductions. Subsequent investigations will include effects on vehicle fuel efficiency, and the environmental impact of magnet manufacture and disposal.     

Key management approaches to offer data confidentiality for secure multicast

Multicasting is an efficient way to deliver data to a large group of users in applications such as Internet stock quotes, audio and music delivery, file and video distribution, etc. Many of these applications require the security feature of data confidentiality, which is not readily offered by the "open" nature of multicast. In order to offer such confidentiality, the encryption and decryption keys must be constantly changed upon a membership change. In this article, after discussing some performance criteria to offer secure multicast, we present a number of the proposed key management schemes for data confidentiality. We categorize these schemes into four groups: key tree-based approaches, contributory key agreement schemes supported by the Diffie-Hellman algorithm, computational number theoretic approaches, and secure multicast framework approaches. Through examples, we describe the operation of the schemes and compare their performances.     

Semiautomatic implementation of protocols using an Estelle-Ccompiler

The basic ideas underlying an Estelle-C compiler, which accepts an Estelle protocol specification and produces a protocol implementation in C, are presented. The implementation of the ISO (International Organization for Standardization) class-2 transparent protocol, using the semiautomatic approach, is discussed. A manual implementation of the protocol is performed and compared to the semiautomatic implementation. The semiautomatic approach to protocol implementation offers several advantages over the conventional manual one, including correctness and modularity in protocol implementation code, conformance to the specification, and reduction in implementation time. Finally, ongoing development of a new Estelle-C compiler is presented     

Orbital volume measurement in the management of pure blowout fractures of the orbital floor

With the recent advent of accurate orbital volume assessment by computed tomography, a retrospective analysis was made of 31 patients with 'pure' blowout fracture of the orbital floor, managed either surgically or conservatively, to determine whether orbital volume measurement could provide an additional parameter of use in the management of such fractures. There was a significant difference in orbital volume discrepancy between patients managed surgically or conservatively suggesting that this investigation may be of use in decision making on surgical intervention in patients with orbital blowout fractures.     

Error Concealment Based on Semantic Prioritization with Hardware‐Based Face Tracking

With video compression standards such as MPEG‐4, a transmission error happens in a video‐packet basis, rather than in a macroblock basis. In this context, we propose a semantic error prioritization method that determines the size of a video packet based on the importance of its contents. A video packet length is made to be short for an important area such as a facial area in order to reduce the possibility of error accumulation. To facilitate the semantic error prioritization, an efficient hardware algorithm for face tracking is proposed. The increase of hardware complexity is minimal because a motion estimation engine is efficiently re‐used for face tracking. Experimental results demonstrate that the facial area is well protected with the proposed scheme.     

Birefringence in benzocyclobutene strip optical waveguides

We report the fabrication of benzocyclobutene strip optical waveguides and the measurement of their birefringence properties. To take into account the stress-induced birefringence in the waveguide, we generalize the formulas reported previously for the analysis of strip waveguides. Our experimental results are shown to agree closely with the theoretical calculation. The condition for achieving zero modal birefringence by control of the aspect ratio of the strip of the waveguide is highlighted. The dependence of the birefringence in the waveguides on the temperature is also measured and discussed.     

Reliability evaluation and optimisation of imperfect inspections for a component with multi-defects

In this paper, a model is developed to evaluate the reliability and optimise the inspection schedule for a multi-defect component. The model uses a non-homogeneous Poisson process (NHPP) method in conjunction with a delay time approach. The inspections are designed to detect any defects in the component, however it can be imperfect. The defect is a definable state before a functional failure happens to the component. Occurrences of defects are assumed to follow an NHPP and a defect will be minimally repaired if it is identified during an inspection. It is shown that the failures occurring in an interval of inspection will also follow an NHPP. The situation of imperfect inspections and non-constant inspection intervals are considered. An algorithm is presented to optimise the intervals of inspections in order to maximise the reliability of the component, and the properties of the algorithm are shown. A numerical example with parametric study is given to show the performance of the model and the algorithm.     

Managing Clinical Use of High-Alert Drugs: A Supervised Learning Approach to Pharmacokinetic Data Analysis

Drug-related problems, particularly those that result from sub- or overtherapeutic doses of high-alert medications, have become a growing concern in clinical medicine. In this paper, we use a model-tree-based regression technique (namely, M5) and support vector machine (SVM) for regression to develop learning-based systems for predicting the adequacy of a vancomycin regimen. We empirically evaluate each system's accuracy in predicting patients' peak and trough concentrations in different clinical scenarios characterized by renal functions and regimen types. Our data consist of 1099 clinical cases that were collected from a major tertiary medical center in southern Taiwan. We also examine the use of bagging for enhancing the prediction power of the respective systems and include in our evaluation a salient one-compartment model for performance benchmark purposes. Overall, our evaluation results suggest that both M5 and SVM are significantly more accurate than the benchmark one-compartment model in predicting patients' peak and trough concentrations across all investigated clinical scenarios. M5 appears to benefit considerably from bagging, which has a positive but seemingly smaller effect on SVM. Taken together, our findings indicate supervised learning techniques that are capable of effectively supporting clinicians' use of vancomycin or similar high-alert drugs in their patient care and management.