High responsivity silicon MOS phototransistors

We describe a metal-oxide silicon (MOS) phototransistor that relies on a novel lateral doping scheme that creates a p-i-n junction configuration for light detection. This is essentially a hybrid device with the horizontal structure of a p-i-n diode and the vertical structure of a MOS field-effect transistor. The lateral p-i-n diode detects light whereas the gate can be used to change the current flowing through the device; making it appear as a MOSFET. This feature makes it easy to integrate it with other conventional MOSFETs on a CMOS process flow. The device shows high optical responsivities that persist to wavelengths in the near-ultraviolet region. The fabrication of the device as well as its electrical and optical characteristics is described.     

Novel e-nose for the discrimination of volatile organic biomarkers with an array of carbon nanotubes (CNT) conductive polymer nanocomposites (CPC) sensors

We report the original design of a new type of electronic nose (e-nose) consisting of only five sensors made of hierarchically structured conductive polymer nanocomposites (CPC). Each sensor benefits from both the exceptional electrical properties of carbon nanotubes (CNT) used to build the conductive architecture and the spray layer by layer (sLbL) assembly technique, which provides the transducers with a highly specific 3D surface structure. Excellent sensitivity and selectivity were obtained by optimizing the amount of CNT with five different polymer matrices: poly(caprolactone) (PCL), poly(lactic acid) (PLA), poly(carbonate) (PC), poly(methyl methacrylate) (PMMA) and a biobased polyester (BPR). The ability of the resulting e-nose to detect nine organic solvent vapours (isopropanol, tetrahydrofuran, dichloromethane, n-heptane, cyclohexane, methanol, ethanol, water and toluene), as well as biomarkers for lung cancer detection in breath analysis, has been demonstrated. Principal component analysis (PCA) proved to be an excellent pattern recognition tool to separate vapour clusters.     

Motor noise generation and prediction for high spinning speed hard disk drive

The acoustic level of a hard disk drive is an important specification. This is especially so for enterprise HDD which is required to operate under a high spinning speed. In order to reduce the acoustics level of a HDD, an in depth understanding behind the mechanisms whereby the noise is being generated in a HDD should be established. This paper will study the acoustics characteristics of a high speed permanent magnet brushless DC motor (PM BLDC) and investigate the physics underlying the generation of noise associated with a motor. An analysis procedure of the PM BLDC motor noise generating mechanisms is proposed. Through finite element analysis and experimental verification, the results indicate that the major noise source for the high speed PM BLDC motor is due to the presence of electromagnetic (EM) torque ripples. Furthermore, it has been observed that the noise radiated by a HDD can be amplified when its structural dynamics are close to the frequency components of the noise source. Finally, a methodology which discusses the steps involved in the prediction of motor radiated noise will be presented.     

Approximate TOPSIS for vessel selection under uncertain environment

The selection of appropriate vessels to carry out shipping activities is crucial for many maritime stakeholders including charterers, shipowners, brokers, surveyors and safety engineers. The task is essentially a process of multiple criteria decision making (MCDM) under uncertainty requiring analysts to derive rational decisions from ambiguous and incomplete data contained in different quantitative and qualitative forms. Fuzzy Techniques for Order Preference by Similarity to an Ideal Solution (TOPSIS) have been well documented in the literature and commonly used in the process of group decision-making under fuzzy environment. While showing the attractiveness in dealing with ambiguous estimates, they have been criticised to be incapable of modelling incompleteness encountered in decision analysis. This paper therefore uses the concept of degrees of belief to develop a novel approximate interval TOPSIS approach for overcoming some of the drawbacks of classical fuzzy TOPSIS methods and facilitating the development of reliable vessel selection models under uncertain environment.     

Shrinkage and model selection with correlated variables via weighted fusion

In this paper, we propose the weighted fusion, a new penalized regression and variable selection method for data with correlated variables. The weighted fusion can potentially incorporate information redundancy among correlated variables for estimation and variable selection. Weighted fusion is also useful when the number of predictors p is larger than the number of observations n. It allows the selection of more than n variables in a motivated way. Real data and simulation examples show that weighted fusion can improve variable selection and prediction accuracy.     

Reliability and validity of an ergonomics-related Job Factors Questionnaire

Musculoskeletal disorders are an important cause of work disability and absenteeism. Specific job factors or tasks may increase the likelihood of developing work-related musculoskeletal disorders. The purpose of the present study was to translate and adapt a Job Factors Questionnaire for the Brazilian–Portuguese language and evaluate its psychometric properties. A cross-cultural adaptation was performed according to an internationally recommended methodology involving translation, synthesis, back-translation, revision by an expert committee, and pre-testing. The psychometric properties were evaluated by administering the questionnaire to 148 employees at two companies involved in the assembly and fabrication of metal products. The reliability of the questionnaire was assessed by measuring the temporal stability through a test–retest design. Construct validity was assessed using the known-groups technique and by comparing workers responses with findings from the Nordic Questionnaire. Reliability was determined to be satisfactory based on Intraclass Correlation Coefficients ranging from 0.54 to 0.73. Construct validity analysis demonstrated a significant difference (p ≤ 0.02) between production and office workers on answers to 10 questionnaire items, and a significant difference (p ≤ 0.01) on the scores of the adapted questionnaire between subjects that indicated presence or absence of musculoskeletal symptoms. The results indicated that the adapted version of the questionnaire had psychometric properties that were acceptable for use in occupational studies involving workers that speak Brazilian–Portuguese.

Relevance to industry

The present study provides results of a cross-cultural adaptation process and a psychometric properties analysis of an instrument that verifies workers' perception of job factors that may lead to work-related pain and discomfort.     

一种优化的射频IC接收电路

简要介绍射频IC系统的结构,并针对现有射频IC系统接收电路的不足,通过调整混频器增益、混频管之间距离和工作频率等方法,实现对接收电路的优化。通过仿真,证明了优化的有效性。     

A computer-enabled solution procedure for food wholesalers’ distribution decision in cities with a circular transportation infrastructure

This paper addresses the food distribution decision from a wholesaler's perspective, as the wholesalers are often faced with thorny issues such as when, where, how to deliver products at the lowest costs to best satisfy the retailers’ changing needs. This research relies on a distribution problem encountered at Northern Grocery Company in Beijing as an example to develop a two-stage solution procedure and subsequent computer-enabled programs for identifying efficient vehicle routing alternatives. The solution process, which integrates heuristic search algorithms and an integer programming model, can be applied to a wide range of distribution problems with specified route durations and a circular transportation network structure as exemplified by City of Beijing.     

Multiple-objective scheduling and real-time dispatching for the semiconductor manufacturing system

Implementing efficient scheduling and dispatching policies is a critical means to gain competitiveness for modern semiconductor manufacturing systems. In contemporary global market, a successful semiconductor manufacturer has to excel in multiple performance indices, consequently qualified scheduling approaches should provide efficient and holistic management of wafer products, information and manufacturing resources and make adaptive decisions based on real-time processing status to reach an overall optimized system performance. To cope with this challenge, a timed extended object-oriented Petri nets (EOPNs) based multiple-objective scheduling and real-time dispatching approach is proposed in this paper. Four performance objectives pursued by semiconductor manufacturers are integrated into a priority-ranking algorithm that serves as the initial scheduling guidance, and then all wafer lots will be dynamically dispatched by the hybrid real-time dispatching control system. A set of simulation experiments validate the proposed multiple-objective scheduling and real-time dispatching algorithm may achieve satisfactory performances.