Does chemometrics enhance the performance of electroanalysis?

This review explores the question whether chemometrics methods enhance the performance of electroanalytical methods. Electroanalysis has long benefited from the well-established techniques such as potentiometric titrations, polarography and voltammetry, and the more novel ones such as electronic tongues and noses, which have enlarged the scope of applications. The electroanalytical methods have been improved with the application of chemometrics for simultaneous quantitative prediction of analytes or qualitative resolution of complex overlapping responses. Typical methods include partial least squares (PLS), artificial neural networks (ANNs), and multiple curve resolution methods (MCR-ALS, N-PLS and PARAFAC). This review aims to provide the practising analyst with a broad guide to electroanalytical applications supported by chemometrics. In this context, after a general consideration of the use of a number of electroanalytical techniques with the aid of chemometrics methods, several overviews follow with each one focusing on an important field of application such as food, pharmaceuticals, pesticides and the environment. The growth of chemometrics in conjunction with electronic tongue and nose sensors is highlighted, and this is followed by an overview of the use of chemometrics for the resolution of complicated profiles for qualitative identification of analytes, especially with the use of the MCR-ALS methodology. Finally, the performance of electroanalytical methods is compared with that of some spectrophotometric procedures on the basis of figures-of-merit. This showed that electroanalytical methods can perform as well as the spectrophotometric ones. PLS-1 appears to be the method of practical choice if the %relative prediction error of not, vert, similar±10% is acceptable.

Fingerprinting of complex mixtures with the use of high performance liquid chromatography, inductively coupled plasma atomic emission spectroscopy and chemometrics

The molecular and metal profile fingerprints were obtained from a complex substance, Atractylis chinensis DC—a traditional Chinese medicine (TCM), with the use of the high performance liquid chromatography (HPLC) and inductively coupled plasma atomic emission spectroscopy (ICP-AES) techniques. This substance was used in this work as an example of a complex biological material, which has found application as a TCM. Such TCM samples are traditionally processed by the Bran, Cut, Fried and Swill methods, and were collected from five provinces in China. The data matrices obtained from the two types of analysis produced two principal component biplots, which showed that the HPLC fingerprint data were discriminated on the basis of the methods for processing the raw TCM, while the metal analysis grouped according to the geographical origin. When the two data matrices were combined into a one two-way matrix, the resulting biplot showed a clear separation on the basis of the HPLC fingerprints. Importantly, within each different grouping the objects separated according to their geographical origin, and they ranked approximately in the same order in each group. This result suggested that by using such an approach, it is possible to derive improved characterisation of the complex TCM materials on the basis of the two kinds of analytical data. In addition, two supervised pattern recognition methods, K-nearest neighbors (KNNs) method, and linear discriminant analysis (LDA), were successfully applied to the individual data matrices—thus, supporting the PCA approach.

A model to predict hypovigilance during a monotonous task

The driving task requires sustained attention during prolonged periods, and can be performed in highly predictable or repetitive environments. Such conditions could create drowsiness or hypovigilance and impair the ability to react to critical events. Identifying vigilance decrement in monotonous conditions has been a major subject of research, but no research to date has attempted to predict this vigilance decrement. This pilot study aims to show that vigilance decrements due to monotonous tasks can be predicted through mathematical modelling. A short vigilance task sensitive to short periods of lapses of vigilance called Sustained Attention to Response Task is used to assess participants’ performance. This task models the driver’s ability to cope with unpredicted events by performing the expected action. A Hidden Markov Model (HMM) is proposed to predict participants’ hypovigilance. Driver’s vigilance evolution is modelled as a hidden state and is correlated to an observable variable: the participant’s reactions time. This experiment shows that the monotony of the task can lead to an important vigilance decline in less than five minutes. This impairment can be predicted four minutes in advance with an 86% accuracy using HMMs. This experiment showed that mathematical models such as HMM can efficiently predict hypovigilance through surrogate measures. The presented model could result in the development of an in-vehicle device that detects driver hypovigilance in advance and warn the driver accordingly, thus offering the potential to enhance road safety and prevent road crashes.

Internal audit quality, audit committee independence, growth opportunities and firm performance

This study explores whether the relation between internal audit quality and firm performance is associated with firm characteristics of information asymmetry and uncertainty (growth opportunities) and certain governance controls (audit committee effectiveness). The results from this preliminary study of 60 Malaysian companies show that the association between internal audit quality and firm performance is stronger for firms with high growth opportunities and that this positive association is weakened by increasing audit committee independence. These findings demonstrate the internal auditors conflicting roles and question the governance recommendations that require all members of the audit committee to be non-executive directors.

Sampling perceptions; testing reality : an evidence-based approach to measurably improve information literacy and student research skills

Do commencing students possess the level of information literacy (IL) knowledge and skills they need to succeed at university? What impact does embedding IL within the engineering and design curriculum have? This paper reports on the self-perception versus the reality of IL knowledge and skills, across a large cohort of first year built environment and engineering students. Acting on the findings of this evaluation, the authors (a team of academic librarians) developed an intensive IL skills program which was integrated into a faculty wide unit. Perceptions, knowledge and skills were re-evaluated at the end of the semester to determine if embedded IL education made a difference. Findings reveal that both the perception and reality of IL skills were significantly and measurably improved.

Simulation and development of a mock circulation loop with variable compliance

Heart disease is attributed as the highest cause of death in the world. Although this could be alleviated by heart transplantation, there is a chronic shortage of donor hearts and so mechanical solutions are being considered. Currently, many Ventricular Assist Devices (VADs) are being developed worldwide in an effort to increase life expectancy and quality of life for end stage heart failure patients. Current pre-clinical testing methods for VADs involve laboratory testing using Mock Circulation Loops (MCLs), and in vivo testing in animal models. The research and development of highly accurate MCLs is vital to the continuous improvement of VAD performance. The first objective of this study was to develop and validate a mathematical model of a MCL. This model could then be used in the design and construction of a variable compliance chamber to improve the performance of an existing MCL as well as form the basis for a new miniaturised MCL. An extensive review of literature was carried out on MCLs and mathematical modelling of their function. A mathematical model of a MCL was then created in the MATLAB/SIMULINK environment. This model included variable features such as resistance, fluid inertia and volumes (resulting from the pipe lengths and diameters); compliance of Windkessel chambers, atria and ventricles; density of both fluid and compressed air applied to the system; gravitational effects on vertical columns of fluid; and accurately modelled actuators controlling the ventricle contraction. This model was then validated using the physical properties and pressure and flow traces produced from a previously developed MCL. A variable compliance chamber was designed to reproduce parameters determined by the mathematical model. The function of the variability was achieved by controlling the transmural pressure across a diaphragm to alter the compliance of the system. An initial prototype was tested in a previously developed MCL, and a variable level of arterial compliance was successfully produced; however, the complete range of compliance values required for accurate physiological representation was not able to be produced with this initial design. The mathematical model was then used to design a smaller physical mock circulation loop, with the tubing sizes adjusted to produce accurate pressure and flow traces whilst having an appropriate frequency response characteristic. The development of the mathematical model greatly assisted the general design of an in vitro cardiovascular device test rig, while the variable compliance chamber allowed simple and real-time manipulation of MCL compliance to allow accurate transition between a variety of physiological conditions. The newly developed MCL produced an accurate design of a mechanical representation of the human circulatory system for in vitro cardiovascular device testing and education purposes. The continued improvement of VAD test rigs is essential if VAD design is to improve, and hence improve quality of life and life expectancy for heart failure patients.

Examining the use of bid information in predicting the contractor’s performance

Purpose – The purpose of this paper is to examine the use of bid information, including both price and non-price factors in predicting the bidder’s performance. Design/methodology/approach – The practice of the industry was first reviewed. Data on bid evaluation and performance records of the successful bids were then obtained from the Hong Kong Housing Department, the largest housing provider in Hong Kong. This was followed by the development of a radial basis function (RBF) neural network based performance prediction model. Findings – It is found that public clients are more conscientious and include non-price factors in their bid evaluation equations. With the input variables used the information is available at the time of the bid and the output variable is the project performance score recorded during work in progress achieved by the successful bidder. It was found that past project performance score is the most sensitive input variable in predicting future performance. Research limitations/implications – The paper shows the inadequacy of using price alone for bid award criterion. The need for a systemic performance evaluation is also highlighted, as this information is highly instrumental for subsequent bid evaluations. The caveat for this study is that the prediction model was developed based on data obtained from one single source. Originality/value – The value of the paper is in the use of an RBF neural network as the prediction tool because it can model non-linear function. This capability avoids tedious ‘‘trial and error’’ in deciding the number of hidden layers to be used in the network model. Keywords Hong Kong, Construction industry, Neural nets, Modelling, Bid offer spreads Paper type Research paper

Measuring quality : how does this improve construction performance?

The paper charts the history and development of the Hong Kong Housing Department (HKHD) Performance Assessment Scoring System (PASS) from 1990 to the present day and examines its effect on facilitating change to the quality of construction work of building contractors engaged in the production of public sector housing projects Hong Kong. The paper builds partly on empirical research carried out by the author as part of a doctoral thesis from 2000 to 2005, on experiential knowledge and also on some relevant case studies. The outcomes from this earlier research and validation of PASS based on results derived from the system since the research was originally undertaken are of benefit to practitioners and academics working and studying in the areas of performance assessment and organisational culture and change. The conclusions presented in the paper further underpin the connection established in previous research between strong organisational culture and project and corporate success. Organisational culture was measured using a survey instrument originally developed by Denison and Neale (1994), adapted for the environment of the study, and corporate success was measured by the PASS system mentioned above. The major results of the original study indicate that there is significant linkage between strong organisational cultures and business success and the detailed findings were that, (1) strong organisational culture was positively associated a high level of company effectiveness, (2) a high level of company effectiveness was positively associated with the cultural traits of ‘consistency’, ‘adaptability’ and ‘mission’, and (3) a high level of company effectiveness was positively associated with the combined cultural traits represented by the dimensions of ‘external focus’ and ‘stable culture’. Several opportunities to take forward this research have been identified, including extending the study to other countries and also longitudinally re-evaluating some of the original case studies to ascertain how organisational cultures have changed or further developed in relation to the changing construction climate in Hong Kong.

Predicting project performance through neural networks

Successful project delivery of construction projects depends on many factors. With regard to the construction of a facility, selecting a competent contractor for the job is paramount. As such, various approaches have been advanced to facilitate tender award decisions. Essentially, this type of decision involves the prediction of a bidderÕs performance based on information available at the tender stage. A neural network based prediction model was developed and presented in this paper. Project data for the study were obtained from the Hong Kong Housing Department. Information from the tender reports was used as input variables and performance records of the successful bidder during construction were used as output variables. It was found that the networks for the prediction of performance scores for Works gave the highest hit rate. In addition, the two most sensitive input variables toward such prediction are ‘‘Difference between Estimate’’ and ‘‘Difference between the next closest bid’’. Both input variables are price related, thus suggesting the importance of tender sufficiency for the assurance of quality production.

The self-Googling phenomenon : investigating the performance of personalized information resources

This paper investigates self–Googling through the monitoring of search engine activities of users and adds to the few quantitative studies on this topic already in existence. We explore this phenomenon by answering the following questions: To what extent is the self–Googling visible in the usage of search engines; is any significant difference measurable between queries related to self–Googling and generic search queries; to what extent do self–Googling search requests match the selected personalised Web pages? To address these questions we explore the theory of narcissism in order to help define self–Googling and present the results from a 14–month online experiment using Google search engine usage data.

Theater 38.3 : Censorship and Performance

Censorship and Performance, edited by Tom Sellar, examines the politics of censorship, and continuing contests over the ‘right’ to claim theatrical and cultural stages for controversial forms of social and self representation, at the start of the twenty-first century. In bringing this collection together, Sellar has taken a broad-based approach to the concept of censorship in theatrical performance—and, indeed, to the concept of theatrical performance itself. Sellar and his contributors clearly accept that surveillance, suppression and restriction of specific forms of representation is a complex, culturally specific phenomenon. In this sense, Censorship and Performance addresses direct political control over content, as well as thornier arguments about media controversy, moral panic, and the politics of self-censorship amongst artists and arts organisations.

A fuzzy neural network approach for contractor pre-qualification

Nonlinearity, uncertainty and subjectivity are the three predominant characteristics of contractors prequalification which cause the process more of an art than a scientific evaluation. A fuzzy neural network (FNN) model, amalgamating both the fuzzy set and neural network theories, has been developed aiming to improve the objectiveness of contractor prequalification. Through the FNN theory, the fuzzy rules as used by the prequalifiers can be identified and the corresponding membership functions can be transformed. Eighty-five cases with detailed decision criteria and rules for prequalifying Hong Kong civil engineering contractors were collected. These cases were used for training (calibrating) and testing the FNN model. The performance of the FNN model was compared with the original results produced by the prequalifiers and those generated by the general feedforward neural network (GFNN, i.e. a crisp neural network) approach. Contractor’s ranking orders, the model efficiency (R2) and the mean absolute percentage error (MAPE) were examined during the testing phase. These results indicate the applicability of the neural network approach for contractor prequalification and the benefits of the FNN model over the GFNN model. The FNN is a practical approach for modelling contractor prequalification.

The on-road difficulties of older drivers and their relationship with self-reported motor vehicle crashes

OBJECTIVES: To quantify the driving difficulties of older adults using a detailed assessment of driving performance and to link this with self-reported retrospective and prospective crashes. DESIGN: Prospective cohort study. SETTING: On-road driving assessment. PARTICIPANTS: Two hundred sixty-seven community-living adults aged 70 to 88 randomly recruited through the electoral roll. MEASUREMENTS: Performance on a standardized measure of driving performance. RESULTS: Lane positioning, approach, and blind spot monitoring were the most common error types, and errors occurred most frequently in situations involving merging and maneuvering. Drivers reporting more retrospective or prospective crashes made significantly more driving errors. Driver instructor interventions during self-navigation (where the instructor had to brake or take control of the steering to avoid an accident) were significantly associated with higher retrospective and prospective crashes; every instructor intervention almost doubled prospective crash risk. CONCLUSION: These findings suggest that on-road driving assessment provides useful information on older driver difficulties, with the self-directed component providing the most valuable information.

In-vehicle technology functional requirements for older drivers

Older drivers represent the fastest growing segment of the road user population. Cognitive and physiological capabilities diminishes with ages. The design of future in-vehicle interfaces have to take into account older drivers' needs and capabilities. Older drivers have different capabilities which impact on their driving patterns and subsequently on road crash patterns. New in-vehicle technology could improve safety, comfort and maintain elderly people's mobility for longer. Existing research has focused on the ergonomic and Human Machine Interface (HMI) aspects of in-vehicle technology to assist the elderly. However there is a lack of comprehensive research on identifying the most relevant technology and associated functionalities that could improve older drivers' road safety. To identify future research priorities for older drivers, this paper presents: (i) a review of age related functional impairments, (ii) a brief description of some key characteristics of older driver crashes and (iii) a conceptualisation of the most relevant technology interventions based on traffic psychology theory and crash data.