Developing a multi-dimensional scale for ethical decision making: the managerial ethical profile (MEP)

This article describes the development and validation of a multi-dimensional scale for measuring managers’ perceptions of the range of factors that routinely guide their decision-making processes. An instrument for identifying managerial ethical profiles (MEP) is developed by measuring the perceived role of different ethical principles in the decision-making of managers. Evidence as to the validity of the multidimensionality of the ethical scale is provided, based on the comparative assessment of different models for managerial ethical decision-making. Confirmatory Factor Analysis (CFA) supported a eight-factor model including two factors for each of the main four schools of moral philosophy. Future research needs and the value of this measure to business ethics are discussed.

The reliability and validity of the Severity of Dependence Scale for detecting cannabis dependence in psychosis.

Aims: To determine the reliability and validity of the Severity of Dependence Scale (SDS) for detecting cannabis dependence in a large sample of in-patients with a schizophrenia spectrum disorder. Design: Cross-sectional study. Participants: Participants were 153 in-patients with a schizophrenia spectrum disorder in Brisbane, Australia. Measurements: Participants were administered the SDS for cannabis dependence in the past 12 months. The presence of Diagnostic and Statistical Manual Version-IV (DSM-IV) cannabis dependence in the previous 12 months was assessed using the Comprehensive International Diagnostic Interview (CIDI). Findings: The SDS had high levels of internal consistency and strong construct and concurrent validity. Individuals with a score of ≥2 on the SDS were nearly 30 times more likely to have DSM-IV cannabis dependence. The SDS was the strongest predictor of DSM-IV cannabis dependence after controlling for other predictor variables. Conclusions: The SDS is a brief, valid and reliable screen for cannabis dependence among people with psychosis

Validation of the Edinburgh Postnatal Depression Scale for men, and comparison of item endorsement with their partners

BACKGROUND: The Edinburgh Postnatal Depression Scale (EPDS) has been validated and used extensively in screening for depression in new mothers, both in English speaking and non-English speaking communities. While some studies have reported the use of the EPDS with fathers, none have validated it for this group, and thus the appropriate cut-off score for screening for depression or anxiety caseness for this population is not known. METHODS: Couples were recruited antenatally and interviewed at six weeks postpartum. EPDS scores and distress caseness (depression or anxiety disorders) for 208 fathers and 230 mothers were determined using the Diagnostic Interview Schedule. RESULTS: Analyses of the EPDS for fathers using distress caseness (depression or anxiety disorders) as the criterion shows that a cut-off of 5/6 has optimum receiver operating characteristics. Furthermore acceptable reliability (split-half and internal consistency) and validity (concurrent) coefficients were obtained. For mothers the optimum cut-off screening value to detect distress caseness was 7/8. Item analysis revealed that fathers endorsed seven of the ten items at lower rates to mothers, with the most significant being that referring to crying. CONCLUSIONS: The EPDS is a reliable and valid measure of mood in fathers. Screening for depression or anxiety disorders in fathers requires a two point lower cut-off than screening for depression or anxiety in mothers, and we recommend this cut-off to be 5/6

Fast searching algorithm for candidate satellite-node set in NLMG

The Node-based Local Mesh Generation (NLMG) algorithm, which is free of mesh inconsistency, is one of core algorithms in the Node-based Local Finite Element Method (NLFEM) to achieve the seamless link between mesh generation and stiffness matrix calculation, and the seamless link helps to improve the parallel efficiency of FEM. Furthermore, the key to ensure the efficiency and reliability of NLMG is to determine the candidate satellite-node set of a central node quickly and accurately. This paper develops a Fast Local Search Method based on Uniform Bucket (FLSMUB) and a Fast Local Search Method based on Multilayer Bucket (FLSMMB), and applies them successfully to the decisive problems, i.e. presenting the candidate satellite-node set of any central node in NLMG algorithm. Using FLSMUB or FLSMMB, the NLMG algorithm becomes a practical tool to reduce the parallel computation cost of FEM. Parallel numerical experiments validate that either FLSMUB or FLSMMB is fast, reliable and efficient for their suitable problems and that they are especially effective for computing the large-scale parallel problems.

Vibrational spectroscopic studies of laboratory scale polymer melt processing : application to a thermoplastic polyurethane nanocomposite

A laboratory scale twin screw extruder has been interfaced with a near infrared (NIR) spectrometer via a fibre optic link so that NIR spectra can be collected continuously during the small scale experimental melt state processing of polymeric materials. This system can be used to investigate melt state processes such as reactive extrusion, in real time, in order to explore the kinetics and mechanism of the reaction. A further advantage of the system is that it has the capability to measure apparent viscosity simultaneously which gives important additional information about molecular weight changes and polymer degradation during processing. The system was used to study the melt processing of a nanocomposite consisting of a thermoplastic polyurethane and an organically modified layered silicate.

Wear mechanisms and scale effects in two-body abrasion

The ‘particle size effect’ and its manifestation in abrasion still attracts considerable debate as to its origins and the ranking of its likely causes. Experiments have been conducted to study the important contribution that the formation of wear debris can have on the progression of wear. The experiments consist of unlubricated (dry) pin-on-disk tests with silicon carbide coated paper of varying particle size, with different pin material, diameter and loads. It has been observed that the influence of debris formation on wear rate is more pronounced for fine abrasives and soft-wearing materials. Consequently, it is proposed that the particle size effect can be explained in terms of geometrical scaling and the evolution of third-body effects with diminishing particle diameter.

Numerical methods for fractional partial differential equations with Riesz space fractional derivatives

In this paper, we consider the numerical solution of a fractional partial differential equation with Riesz space fractional derivatives (FPDE-RSFD) on a finite domain. Two types of FPDE-RSFD are considered: the Riesz fractional diffusion equation (RFDE) and the Riesz fractional advection–dispersion equation (RFADE). The RFDE is obtained from the standard diffusion equation by replacing the second-order space derivative with the Riesz fractional derivative of order αset membership, variant(1,2]. The RFADE is obtained from the standard advection–dispersion equation by replacing the first-order and second-order space derivatives with the Riesz fractional derivatives of order βset membership, variant(0,1) and of order αset membership, variant(1,2], respectively. Firstly, analytic solutions of both the RFDE and RFADE are derived. Secondly, three numerical methods are provided to deal with the Riesz space fractional derivatives, namely, the L1/L2-approximation method, the standard/shifted Grünwald method, and the matrix transform method (MTM). Thirdly, the RFDE and RFADE are transformed into a system of ordinary differential equations, which is then solved by the method of lines. Finally, numerical results are given, which demonstrate the effectiveness and convergence of the three numerical methods.

Enhancing digital road map with lane details extracted from large-scale stereo aerial imagery using object-oriented image analysis

Precise, up-to-date and increasingly detailed road maps are crucial for various advanced road applications, such as lane-level vehicle navigation, and advanced driver assistant systems. With the very high resolution (VHR) imagery from digital airborne sources, it will greatly facilitate the data acquisition, data collection and updates if the road details can be automatically extracted from the aerial images. In this paper, we proposed an effective approach to detect road lane information from aerial images with employment of the object-oriented image analysis method. Our proposed algorithm starts with constructing the DSM and true orthophotos from the stereo images. The road lane details are detected using an object-oriented rule based image classification approach. Due to the affection of other objects with similar spectral and geometrical attributes, the extracted road lanes are filtered with the road surface obtained by a progressive two-class decision classifier. The generated road network is evaluated using the datasets provided by Queensland department of Main Roads. The evaluation shows completeness values that range between 76% and 98% and correctness values that range between 82% and 97%.

Towards an automatic road lane marks extraction based on ISODATA segmentation and shadow detection from large-scale aerial images

The automatic extraction of road features from remote sensed images has been a topic of great interest within the photogrammetric and remote sensing communities for over 3 decades. Although various techniques have been reported in the literature, it is still challenging to efficiently extract the road details with the increasing of image resolution as well as the requirement for accurate and up-to-date road data. In this paper, we will focus on the automatic detection of road lane markings, which are crucial for many applications, including lane level navigation and lane departure warning. The approach consists of four steps: i) data preprocessing, ii) image segmentation and road surface detection, iii) road lane marking extraction based on the generated road surface, and iv) testing and system evaluation. The proposed approach utilized the unsupervised ISODATA image segmentation algorithm, which segments the image into vegetation regions, and road surface based only on the Cb component of YCbCr color space. A shadow detection method based on YCbCr color space is also employed to detect and recover the shadows from the road surface casted by the vehicles and trees. Finally, the lane marking features are detected from the road surface using the histogram clustering. The experiments of applying the proposed method to the aerial imagery dataset of Gympie, Queensland demonstrate the efficiency of the approach.

Reliability driven reconfiguration of rural power distribution systems

This paper presents a reliability-based reconfiguration methodology for power distribution systems. Probabilistic reliability models of the system components are considered and Monte Carlo method is used while evaluating the reliability of the distribution system. The reconfiguration is aimed at maximizing the reliability of the power supplied to the customers. A binary particle swarm optimization (BPSO) algorithm is used as a tool to determine the optimal configuration of the sectionalizing and tie switches in the system. The proposed methodology is applied on a modified IEEE 13-bus distribution system.

Power sharing and stability enhancement of an autonomous microgrid with inertial and non-inertial DGs with DSTATCOM

This paper proposes a method of enhancing system stability with a distribution static compensator (DSTATCOM) in an autonomous microgrid with multiple distributed generators (DG). It is assumed that there are both inertial and non-inertial DGs connected to the microgrid. The inertial DG can be a synchronous machine of smaller rating while inertia less DGs (solar) are assumed as DC sources. The inertia less DGs are connected through Voltage Source Converter (VSC) to the microgrid. The VSCs are controlled by either state feedback or current feedback mode to achieve desired voltage-current or power outputs respectively. The power sharing among the DGs is achieved by drooping voltage angle. Once the reference for the output voltage magnitude and angle is calculated from the droop, state feedback controllers are used to track the reference. The angle reference for the synchronous machine is compared with the output voltage angle of the machine and the error is fed to a PI controller. The controller output is used to set the power reference of the synchronous machine. The rate of change in the angle in a synchronous machine is restricted by the machine inertia and to mimic this nature, the rate of change in the VSCs angles are restricted by a derivative feedback in the droop control. The connected distribution static compensator (DSTATCOM) provides ride through capability during power imbalance in the microgrid, especially when the stored energy of the inertial DG is not sufficient to maintain stability. The inclusion of the DSATCOM in such cases ensures the system stability. The efficacies of the controllers are established through extensive simulation studies using PSCAD.

Validation of the Australian Propensity for Angry Driving Scale (Aus-PADS)

The present study used a university sample to assess the test-retest reliability and validity of the Australian Propensity for Angry Driving Scale (Aus-PADS). The scale has stability over time, and convergent validity was established, as Aus-PADS scores correlated significantly with established anger and impulsivity measures. Discriminant validity was also established, as Aus-PADS scores did not correlate with Venturesomeness scores. The Aus-PADS has demonstrated criterion validity, as scores were correlated with behavioural measures, such as yelling at other drivers, gesturing at other drivers, and feeling angry but not doing anything. Aus-PADS scores reliably predicted the frequency of these behaviours over and above other study variables. No significant relationship between aggressive driving and crash involvement was observed. It was concluded that the Aus-PADS is a reliable and valid tool appropriate for use in Australian research, and that the potential relationship between aggressive driving and crash involvement warrants further investigation with a more representative (and diverse) driver sample.

Design and evaluation of an image analysis platform for low-power, low-bandwidth camera networks

We describe the design and evaluation of a platform for networks of cameras in low-bandwidth, low-power sensor networks. In our work to date we have investigated two different DSP hardware/software platforms for undertaking the tasks of compression and object detection and tracking. We compare the relative merits of each of the hardware and software platforms in terms of both performance and energy consumption. Finally we discuss what we believe are the ongoing research questions for image processing in WSNs.