Portfolio selection using artificial intelligence

The application of artificial intelligence in finance is relatively new area of research. This project employed artificial neural networks (ANNs) that use both fundamental and technical inputs to predict future prices of widely held Australian stocks and use these predicted prices for stock portfolio selection over a long investment horizon. The research involved the creation and testing of a large number of possible network configurations and draws conclusions about ANN architectures and their overall suitability for the purpose of stock portfolio selection.

Laser-radar data fusion with Gaussian Process Implicit Surfaces

This work considers the problem of building high-fidelity 3D representations of the environment from sensor data acquired by mobile robots. Multi-sensor data fusion allows for more complete and accurate representations, and for more reliable perception, especially when different sensing modalities are used. In this paper, we propose a thorough experimental analysis of the performance of 3D surface reconstruction from laser and mm-wave radar data using Gaussian Process Implicit Surfaces (GPIS), in a realistic field robotics scenario. We first analyse the performance of GPIS using raw laser data alone and raw radar data alone, respectively, with different choices of covariance matrices and different resolutions of the input data. We then evaluate and compare the performance of two different GPIS fusion approaches. The first, state-of-the-art approach directly fuses raw data from laser and radar. The alternative approach proposed in this paper first computes an initial estimate of the surface from each single source of data, and then fuses these two estimates. We show that this method outperforms the state of the art, especially in situations where the sensors react differently to the targets they perceive.

Visual metrics for the evaluation of sensor data quality in outdoor perception

This paper proposes an experimental study of quality metrics that can be applied to visual and infrared images acquired from cameras onboard an unmanned ground vehicle (UGV). The relevance of existing metrics in this context is discussed and a novel metric is introduced. Selected metrics are evaluated on data collected by a UGV in clear and challenging environmental conditions, represented in this paper by the presence of airborne dust or smoke.

The role of the ethnic enclave in facilitating immigrant business performance and social integration

Chinese immigrant entrepreneurs, known the world over for their successful business practices (Kee, 1994), tend to start businesses within their ethnic enclave. But in a move away from multiculturalism, host countries increasingly fear that immigration and asylum pose a threat to social integration resulting in a lack of social cohesion and a plethora of government programs (Cheong, Edwards, Goulbourne & Solomos, 2007). For many immigrant entrepreneurs, the EE is an integral part of their social and cultural context and the location where ethnic resources reside (Logan, Alba & Stults, 2003). Immigrant entrepreneurs can harness the networks for labor and customers through various ties in their EE (Portes and Zhou, 1996). Yang, Ho and Chang (2010) illustrate in their paper that the Chinese immigrant entrepreneurs (IE) were able to utilize ethnic network resources as their social capital in order to reduce transaction costs and thus enhance business performance. Tilly (1990) explains that immigrants’ reliance on such networks for business or other information minimizes the socioeconomic hardships they would experience in host countries (Raijman & Tienda, 2000). Acquiring jobs in ethnic businesses and establishing businesses within an EE may facilitate migrants’ social integration into the host country (Tian & Shan, 1999). Although an EE has distinct economic advantages for immigrant entrepreneurs, Sequeira and Rasheed (2006: 367) argue that ‘Exclusive reliance on strong ties within the immigrant enclave has a negative effect on growth outside the enclave community.’ Similarly, Drori, Honig and Ginsberg (2010: 20) also propose that ‘The greater the reliance of transnational entrepreneurs on ethnic (versus societal) embedded resources and network structure, the narrower their possibilities of expanding the scope of their business.’ This research asks, ‘What is the role of the ethnic enclave in facilitating immigrant business growth and social integration? This project has the following important aims: A1 To better understand the role of IE, in particular Chinese IE in the Australian economy A2 To investigate the role of the EE in facilitating or inhibiting immigrant business performance A3 To understand how locating their firm inside or outside of the EE will affect the IE’s embeddedness in co-ethnic and nonco-ethnic networks and social integration A4 To understand how an IE’s social network affects business performance and social integration

Distinguishing between task and contextual performance for nurses : development of a job performance scale

Aim. This paper is a report of a development and validation of a new job performance scale based on an established job performance model. Background. Previous measures of nursing quality are atheoretical and fail to incorporate the complete range of behaviours performed. Thus, an up-to-date measure of job performance is required for assessing nursing quality. Methods. Test construction involved systematic generation of test items using focus groups, a literature review, and an expert review of test items. A pilot study was conducted to determine the multidimensional nature of the taxonomy and its psychometric properties. All data were collected in 2005. Findings. The final version of the nursing performance taxonomy included 41 behaviours across eight dimensions of job performance. Results from preliminary psychometric investigations suggest that the nursing performance scale has good internal consistency, good convergent validity and good criterion validity. Conclusion. The findings give preliminary support for a new job performance scale as a reliable and valid tool for assessing nursing quality. However, further research using a larger sample and nurses from a broader geographical region is required to cross-validate the measure. This scale may be used to guide hospital managers regarding the quality of nursing care within units and to guide future research in the area.

Organizational factors impacting on patient satisfaction : a cross sectional examination of service climate and linkages to nurses' effort and performance

Background Patient satisfaction is influenced by the setting in which patients are treated and the employees providing care. However, to date, limited research has explained how health care organizations or nurses influence patient satisfaction. Objectives The purpose of this study was to test the model that service climate would increase the effort and performance of nursing groups and, in turn, increase patient satisfaction. Method This study incorporated data from 156 nurses, 28 supervisors, and 171 patients. A cross-sectional design was utilized to examine the relationship between service climate, nurse effort, nurse performance and patient satisfaction. Structural equation modeling was conducted to test the proposed relationships. Results Service climate was associated with the effort that nurses directed towards technical care and extra-role behaviors. In turn, the effort that nurses exerted predicted their performance, as rated by their supervisors. Finally, task performance was a significant predictor of patient satisfaction. Conclusions This study suggests that both hospital management and nurses play a role in promoting patient satisfaction. By focusing on creating a climate for service, health care managers can improve nursing performance and patient satisfaction with care.

Eldercare demands, mental health, and work performance : the moderating role of satisfaction with eldercare tasks

Due to demographic changes, a growing number of employees provide in-home care to an elderly family member. Previous research suggested a negative relationship between employees' eldercare demands and their work performance. However, the empirical nature of this relationship and its boundary conditions and mediating mechanisms have been neglected. The goal of this multisource study was to examine a mediated-moderation model of eldercare demands, mental health, and work performance. Drawing on the theory of conservation of resources (Hobfoll, 1989), it was expected that employees' satisfaction with eldercare tasks would buffer the negative relationship between eldercare demands and work performance, and that mental health would mediate this moderating effect. Data were collected from 165 employees providing in-home eldercare, as well as from one colleague and one family member of each employee. Results of mediated-moderation analyses supported the hypothesized model. The findings suggest that interventions that aim to increase employees' satisfaction with eldercare tasks may help protect employees from the negative effects of high eldercare demands on mental health and, subsequently, on work performance.

The impacts of FOREX fluctuations on construction business performance : an organisational capabilities perspective

Construction projects are a high risk business activity. When undertaking projects in an international context, it is further complicated by the risk of fluctuations in the foreign exchange rates (FOREX). Construction business performance is affected by these fluctuations. They affect progress and cause delays, which in turn create problems for subcontractors, namely cost overruns, disputes, arbitration, total abandonment and litigation. FOREX fluctuations also cause the price of raw materials to increase, leading the cost overruns. Managing FOREX risk is critical and past research have focused on the need for adequate insurance, careful planning and management, and foreign exchange futures hedging to overcome issues that have been caused by the FOREX risk. Analysis of FOREX risk in international construction business usually focused only on issues at the project level. There is currently lack of understanding of Organisational Capabilities (OC) to manage the impacts of FOREX risk, which when examined, are seen in isolation. This paper attempts to bridge the gap by discussing the impacts of FOREX fluctuations on the international construction business. The focus is on the OC perspective and the need to develop OC framework to mitigate the risk in sustaining construction business performance.

Assessment of driving-related performance in chronic whiplash using an advanced driving simulator

Driving is often nominated as problematic by individuals with chronic whiplash associated disorders (WAD), yet driving-related performance has not been evaluated objectively. The purpose of this study was to test driving-related performance in persons with chronic WAD against healthy controls of similar age, gender and driving experience to determine if driving-related performance in the WAD group was sufficiently impaired to recommend fitness to drive assessment. Driving-related performance was assessed using an advanced driving simulator during three driving scenarios; freeway, residential and a central business district (CBD). Total driving duration was approximately 15 min. Five driving tasks which could cause a collision (critical events) were included in the scenarios. In addition, the effect of divided attention (identify red dots projected onto side or rear view mirrors) was assessed three times in each scenario. Driving performance was measured using the simulator performance index (SPI) which is calculated from 12 measures. z-Scores for all SPI measures were calculated for each WAD subject based on mean values of the control subjects. The z-scores were then averaged for the WAD group. A z-score of ≤−2 indicated a driving failing grade in the simulator. The number of collisions over the five critical events was compared between the WAD and control groups as was reaction time and missed response ratio in identifying the red dots. Seventeen WAD and 26 control subjects commenced the driving assessment. Demographic data were comparable between the groups. All subjects completed the freeway scenario but four withdrew during the residential and eight during the CBD scenario because of motion sickness. All scenarios were completed by 14 WAD and 17 control subjects. Mean z-scores for the SPI over the three scenarios was statistically lower in the WAD group (−0.3 ± 0.3; P < 0.05) but the score was not below the cut-off point for safe driving. There were no differences in the reaction time and missed response ratio in divided attention tasks between the groups (All P > 0.05). Assessment of driving in an advanced driving simulator for approximately 15 min revealed that driving-related performance in chronic WAD was not sufficiently impaired to recommend the need for fitness to drive assessment.

Hunting and gathering : new imperatives in mapping and collecting student learning data to assure quality outcomes

Assurance of learning (AOL) is a quality enhancement and quality assurance process used in higher education. It involves a process of determining programme learning outcomes and standards, and systematically gathering evidence to measure students' performance on these. The systematic assessment of whole-of-programme outcomes provides a basis for curriculum development and management, continuous improvement, and accreditation. To better understand how AOL processes operate, a national study of university practices across one discipline area, business and management, was undertaken. To solicit data on AOL practice, interviews were undertaken with a sample of business school representatives (n = 25). Two key processes emerged: (1) mapping of graduate attributes and (2) collection of assurance data. External drivers such as professional accreditation and government legislation were the primary reasons for undertaking AOL outcomes but intrinsic motivators in relation to continuous improvement were also evident. The facilitation of academic commitment was achieved through an embedded approach to AOL by the majority of universities in the study. A sustainable and inclusive process of AOL was seen to support wider stakeholder engagement in the development of higher education learning outcomes.

The unfinished revolution : what is missing from the E&P industry’s move to “big data”

One cannot help but be impressed by the inroads that digital oilfield technologies have made into the exploration and production (E&P) industry in the past decade. Today’s production systems can be monitored by “smart” sensors that allow engineers to observe almost any aspect of performance in real time. Our understanding of how reservoirs are behaving has improved considerably since the dawn of this revolution, and the industry has been able to move away from point answers to more holistic “big picture” integrated solutions. Indeed, the industry has already reaped the rewards of many of these kinds of investments. Many billions of dollars of value have been delivered by this heightened awareness of what is going on within our assets and the world around them (Van Den Berg et al. 2010).

ERP stakeholders’ perceptions of data quality and utility

While data quality has been identified as a critical factor associated with enterprise resource planning (ERP) failure, the relationship between ERP stakeholders, the information they require and its relationship to ERP outcomes continues to be poorly understood. Applying stakeholder theory to the problem of ERP performance, we put forward a framework articulating the fundamental differences in the way users differentiate between ERP data quality and utility. We argue that the failure of ERPs to produce significant organisational outcomes can be attributed to conflict between stakeholder groups over whether the data contained within an ERP is of adequate ‘quality’. The framework provides guidance as how to manage data flows between stakeholders, offering insight into each of their specific data requirements. The framework provides support for the idea that stakeholder affiliation dictates the assumptions and core values held by individuals, driving their data needs and their perceptions of data quality and utility.

Performance measures for Australian laboratories reporting cervical cytology : a decade of data 1998–2008

Aim Performance measures for Australian laboratories reporting cervical cytology are a set of quantifiable measures relating to the profile and accuracy of reporting. This study reviews aggregate data collected over the ten years in which participation in the performance measures has been mandatory. Methods Laboratories submit annual data on performance measures relating to the profile of reporting, including reporting rates for technically unsatisfactory specimens, high grade or possible high grade abnormalities and abnormal reports. Cytology-histology correlation data and review findings of negative smears reported from women with histological high grade disease are also collected. Suggested acceptable standards are set for each measure. This study reviews the aggregate data submitted by all laboratories for the years 1998-2008 and examines trends in reporting and the performance of laboratories against the suggested standards. Results The performance of Australian laboratories has shown continued improvement over the study period. There has been a fall in the proportion of laboratories with data outside the acceptable standard range in all performance measures. Laboratories are reporting a greater proportion of specimens as definite or possible high grade abnormality. This is partly attributable to an increase in the proportion of abnormal results classified as high grade or possible high grade abnormality. Despite this, the positive predictive value for high grade and possible high grade abnormalities has continued to rise. Conclusion Performance measures for cervical cytology have provided a valuable addition to external quality assurance procedures in Australia. They have documented continued improvements in the aggregate performance, as well as providing benchmarking data and goals for acceptable performance for individual laboratories.

Compatibility of stormwater treatment performance data between different geographical areas

Using a case study approach, this paper presents a robust methodology for assessing the compatibility of stormwater treatment performance data between two geographical regions in relation to a treatment system. The desktop analysis compared data derived from a field study undertaken in Florida, USA, with South East Queensland (SEQ) rainfall and pollutant characteristics. The analysis was based on the hypothesis that when transposing treatment performance information from one geographical region to another, detailed assessment of specific rainfall and stormwater quality parameters is required. Accordingly, characteristics of measured rainfall events and stormwater quality in the Florida study were compared with typical characteristics for SEQ. Rainfall events monitored in the Florida study were found to be similar to events that occur in SEQ in terms of their primary characteristics of depth, duration and intensity. Similarities in total suspended solids (TSS) and total nitrogen (TN) concentration ranges for Florida and SEQ suggest that TSS and TN removal performances would not be very different if the treatment system is installed in SEQ. However, further investigations are needed to evaluate the treatment performance of total phosphorus (TP). The methodology presented also allows comparison of other water quality parameters.

Mining business process deviance : a quest for accuracy

This paper evaluates the suitability of sequence classification techniques for analyzing deviant business process executions based on event logs. Deviant process executions are those that deviate in a negative or positive way with respect to normative or desirable outcomes, such as non-compliant executions or executions that undershoot or exceed performance targets. We evaluate a range of feature types and classification methods in terms of their ability to accurately discriminate between normal and deviant executions both when deviances are infrequent (unbalanced) and when deviances are as frequent as normal executions (balanced). We also analyze the ability of the discovered rules to explain potential causes and contributing factors of observed deviances. The evaluation results show that feature types extracted using pattern mining techniques only slightly outperform those based on individual activity frequency. The results also suggest that more complex feature types ought to be explored to achieve higher levels of accuracy.