The Yonder project : literacy and social competency development in primary school students through co-creation of live performance

Since 2007 Kite Arts Education Program (KITE), based at Queensland Performing Arts Centre (QPAC), has been engaged in delivering a series of theatre-based experiences for children in low socio-economic primary schools in Queensland. The artist in residence (AIR) project titled Yonder includes performances developed by the children with the support and leadership of teacher artists from KITE for their community and parents/carers,supported by a peak community cultural institution. In 2009,Queensland Performing Arts Centre partnered with Queensland University of Technology (QUT) Creative Industries Faculty (Drama) to conduct a three-year evaluation of the Yonder project to understand the operational dynamics, artistic outputs and the educational benefits of the project. This paper outlines the research findings for children engaged in the Yonder project in the interrelated areas of literacy development and social competencies. Findings are drawn from six iterations of the project in suburban locations on the edge of Brisbane city and in regional Queensland.

Identifying key enablers to improve business performance in Taiwanese electronic manufacturing companies

Purpose – Integrated supplier management (ISM), new product development (NPD) and knowledge sharing (KS) practices are three primary business activities utilised to enhance manufacturers' business performance (BP). The purpose of this paper is to empirically investigate the relationships between these three business activities (i.e. ISM, NPD, KS) and BP in a Taiwanese electronics manufacturing context. Design/methodology/approach – A questionnaire survey is first administered to a sample of electronic manufacturing companies operating in Taiwan to elicit the opinions of technical and managerial professionals regarding business activities and BP within their companies. A total of 170 respondents from 83 companies respond to the survey. Factor, correlation and path analysis are undertaken on this quantitative data set to derive the key factors which leverage business outcomes in these companies. Following empirical analysis, six semi-structured interviews are undertaken with manufacturing executives to provide qualitative insights into the underlying reasons why certain business activity factors are the strongest predictors of BP. Findings – The investigation shows that the ISM, NPD and KS constructs all play an important role in the success of company operations and creating business outcomes. Specifically, the key factors within these constructs which influenced BP are: supplier evaluation and selection; design simplification and modular design; information technology infrastructure and systems and open communication. Accordingly, sufficient financial and human resources should be allocated to these important activities to derive accelerated rates of improved BP. These findings are supported by the qualitative interviews with manufacturing executives. Originality/value – The paper depicts the pathways to improved manufacturing BP, through targeting efforts into the above-mentioned factors within the ISM, NPD and KS constructs. Based on the empirical path model, and the specific insights derived from the explanatory interviews with manufacturing executives, the paper also provides a number of practical implications for manufacturing companies seeking to enhance their BP through improved operational activities.

Achieving superior innovation-based performance outcomes in SMEs through innovation resource–capability complementarity

Firms are increasingly identifying new avenues to enhance their market position. One such effort involves the firms' ability to continuously learn. Learning has the capacity to enable firms to develop and implement more efficient and effective innovation-focused strategies, resulting in the ability to develop and deliver more products in a timelier manner. This study tests the relationship between innovation resource–capability complementarity and innovation-based performance. This study further elaborates that while innovation resource–capability complementarity drives innovation-based performance; their relationship will be enhanced via the firms' possession of superior learning capability. The findings show a significant effect of innovation resource–capability complementarity on innovation-based performance. The results also show that firms that possess superior learning capability are willing to question their operational processes and routines and make adjustments following the feedback obtained from customers and channels; thereby enhancing their abilities to develop more new products and increase their speed in delivering products to the customers.

Socio-emotional and operational demands on service employees

Enacting appropriate behaviors often requires service employees to suppress genuine emotions and/or express other emotions, genuine or contrived. Managing emotions to act in a socially appropriate manner constitutes a form of labor: emotional labor. If labor demands exceed the resources of the employee, burnout arises, with negative consequences for overall psychological well-being and job performance. Similarly, task related activities engender role stress, which can also lead to burnout. Both task related role demands and socio-emotional demands are likely to be omnipresent in interpersonal interactions in service settings. Accordingly, this study sets out to investigate the simultaneous impact of these job demands on burnout in front line service professionals. Based on survey data collected from allied health service workers, the study findings strongly suggest that both socio-emotional demands and task related role demands are significant determinants of workplace stress and that their simultaneous effects on employee burnout can be large.

Sewer performance reporting : factors that influence blockages

Managing sewer blockages represents a significant operational challenge for water utilities. In Australia, company-level blockage rates are used to compare the effectiveness of the management strategies of different utilities. Anecdotal evidence suggests this may not be a fair basis for comparison because blockages are influenced by a range of factors beyond management control and that vary from company to company. This issue was investigated as part of a broader research effort on sewer blockage management undertaken in conjunction with the Water Services Association of Australia (WSAA) and its members. A Web-based survey was used to collate expert opinion on factors that influence blockage rate. The identified factors were then investigated in an exploratory analysis of blockage-related data provided by two participating utilities, supported by literature reviews. The results indicate that blockage rate is influenced by a range of factors, including asset attributes, climatic conditions, water consumption, and soil type. Since these factors vary from utility to utility, this research supports the assertion that company-level blockage rate is not in itself an appropriate metric for comparing management effectiveness.

A robust methodology for developing an operational systems view of mine water interactions

The Minerals Council of Australia’s (MCA) Water Accounting Framework (WAF) is an industry lead initiative to enable cross company communication and comparisons of water management performance. The WAF consists of two models, the Input-Output Model that represents water interactions between an operation and its surrounding environment and the Operational Model that represents water interactions within an operation. Recently, MCA member companies have agreed to use the Input-Output Model to report on their external water interactions in Australian operations, with some adopting it globally. The next step will be to adopt the Operational Model. This will expand the functionality of the WAF from corporate reporting to allowing widespread identification of inefficiencies and to connect internal and external interactions. Implementing the WAF, particularly the Operational Model, is non-trivial. It can be particularly difficult for operations that are unfamiliar with the WAF definitions and methodology, lack information pertaining to flow volumes or contain unusual configurations. Therefore, there is a need to help industry with its implementation. This work presents a step-by-step guide to producing the Operational Model. It begins by describing a methodology for implementing the Operational Model by describing the identification of pertinent objects (stores, tasks and treatments), quantification of flows, aggregation of objects and production of reports. It then discusses how the Operational Model can represent a series of challenging scenarios and how it can be connected with Input-Output Model to improve water management.

Effects of mass of charge on loop heat pipe operational characteristics

Experimental results on a loop heat pipe, using R134a as the working fluid, indicates that the liquid inventory in the compensation chamber can significantly influence the operating characteristics. The large liquid inventory in the compensation chamber, under terrestrial conditions, can result in loss of thermal coupling between the compensation chamber and the evaporator core. This causes the operating temperature to increase monotonically. This phenomenon, which has been experimentally observed, is reported in this paper. A theoretical model to predict the steady-state performance of a loop heat pipe with a weak thermal link between the compensation chamber and the core, as observed in the experiment, is also presented. The predicted and the experimentally determined temperatures correlate well.

Nonideal negative resistors and capacitors using an operational amplifier

Negative impedance converters (NIC's) may be used to realize negative driving-point impedances. The effect of the nonideal characteristics of the operational amplifier such as finite frequencydependent gain and output impedance on the performance of the negative impedances is analyzed. Detailed equivalent circuits showing the additional positive or negative inductive impedances due to the nonideal characteristics are given for negative resistance and negative capacitance realizations, and their relative performances are compared. The experimental results confirm the validity of the equivalent circuits. The effect of the slew rate of the operational amplifier on the maximum signal-handling capability (SHC) of the negative impedances at high frequencies is studied. Practical design considerations for achieving wider bandwidth as well as improved SHC are discussed.

Characteristics of nonideal operational amplifiers

The departures of the operational amplifiers (OA's) from the ideal performance and their effect on VCV's in the inverting and noninverting mode are discussed. It is found that for the same ideal gain, the bandwidths for the inverting and noninverting modes are different, the former being less. Complete equivalent circuits describing the frequency dependance of the input and output impedances for both modes are given. In particular, the output impedance is shown to be inductive for the frequencies of interest, and this is also confirmed by experimental results.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications. (C) 2005 Elsevier B. V. All rights reserved.

An improved-performance liquid-feed solid-polymer-electrolyte direct methanol fuel cell operating at near-ambient conditions

Results on the performance of a 25 cm(2) liquid-feed solid-polymer-electrolyte direct methanol fuel cell (SPE-DMFC), operating under near-ambient conditions, are reported. The SPE-DMFC can yield a maximum power density of c. 200 mW cm(-2) at 90 C while operating with 1 M aqueous methanol and oxygen under ambient pressure. While operating the SPE-DMFC under similar conditions with air, a maximum power density of ca. 100 mW cm(-2) is achieved. Analysis of the electrode reaction kinetics parameters on the methanol electrode suggests that the reaction mechanism for methanol oxidation remains invariant with temperature. Durability data on the SPE-DMFC at an operational current density of 100 mA cm(-2) have also been obtained.

Operational experience on a grid connected 100 kWe biomass gasification power plant in Karnataka, India

The paper reports the operational experience from a 100 kWe gasification power plant connected to the grid in Karnataka. Biomass Energy for Rural India (BERI) is a program that implemented gasification based power generation with an installed capacity of 0.88 MWe distributed over three locations to meet the electrical energy needs in the district of Tumkur. The operation of one 100 kWe power plant was found unsatisfactory and not meeting the designed performance. The Indian Institute of Science, Bangalore, the technology developer, took the initiative to ensure the system operation, capacity building and prove the designed performance. The power plant connected to the grid consists of the IISc gasification system which includes reactor, cooling, cleaning system, fuel drier and water treatment system to meet the producer gas quality for an engine. The producer gas is used as a fuel in Cummins India Limited, GTA 855 G model, turbo charged engine and the power output is connected to the grid. The system has operated for over 1000 continuous hours, with only about 70 h of grid outages. The total biomass consumption for 1035 h of operation was 111 t at an average of 107 kg/h. Total energy generated was 80.6 MWh reducing over loot of CO(2) emissions. The overall specific fuel consumption was about 1.36 kg/kWh, amounting to an overall efficiency from biomass to electricity of about 18%. The present operations indicate that a maintenance schedule for the plant can be at the end of 1000 h. The results for another 1000 h of operation by the local team are also presented. (C) 2011 International Energy Initiative. Published by Elsevier Inc. All rights reserved.

Arithmetic coding based lossless compression schemes for power system steady state operational data

Introduction of processor based instruments in power systems is resulting in the rapid growth of the measured data volume. The present practice in most of the utilities is to store only some of the important data in a retrievable fashion for a limited period. Subsequently even this data is either deleted or stored in some back up devices. The investigations presented here explore the application of lossless data compression techniques for the purpose of archiving all the operational data - so that they can be put to more effective use. Four arithmetic coding methods suitably modified for handling power system steady state operational data are proposed here. The performance of the proposed methods are evaluated using actual data pertaining to the Southern Regional Grid of India. (C) 2012 Elsevier Ltd. All rights reserved.

Assessing impact of material transition and thermal comfort models on embodied and operational energy in vernacular dwellings (India)

Vernacular dwellings are well-suited climate-responsive designs that adopt local materials and skills to support comfortable indoor environments in response to local climatic conditions. These naturally-ventilated passive dwellings have enabled civilizations to sustain even in extreme climatic conditions. The design and physiological resilience of the inhabitants have coevolved to be attuned to local climatic and environmental conditions. Such adaptations have perplexed modern theories in human thermal-comfort that have evolved in the era of electricity and air-conditioned buildings. Vernacular local building elements like rubble walls and mud roofs are given way to burnt brick walls and reinforced cement concrete tin roofs. Over 60% of Indian population is rural, and implications of such transitions on thermal comfort and energy in buildings are crucial to understand. Types of energy use associated with a buildings life cycle include its embodied energy, operational and maintenance energy, demolition and disposal energy. Embodied Energy (EE) represents total energy consumption for construction of building, i.e., embodied energy of building materials, material transportation energy and building construction energy. Embodied energy of building materials forms major contribution to embodied energy in buildings. Operational energy (OE) in buildings mainly contributed by space conditioning and lighting requirements, depends on the climatic conditions of the region and comfort requirements of the building occupants. Less energy intensive natural materials are used for traditional buildings and the EE of traditional buildings is low. Transition in use of materials causes significant impact on embodied energy of vernacular dwellings. Use of manufactured, energy intensive materials like brick, cement, steel, glass etc. contributes to high embodied energy in these dwellings. This paper studies the increase in EE of the dwelling attributed to change in wall materials. Climatic location significantly influences operational energy in dwellings. Buildings located in regions experiencing extreme climatic conditions would require more operational energy to satisfy the heating and cooling energy demands throughout the year. Traditional buildings adopt passive techniques or non-mechanical methods for space conditioning to overcome the vagaries of extreme climatic variations and hence less operational energy. This study assesses operational energy in traditional dwelling with regard to change in wall material and climatic location. OE in the dwellings has been assessed for hot-dry, warm humid and moderate climatic zones. Choice of thermal comfort models is yet another factor which greatly influences operational energy assessment in buildings. The paper adopts two popular thermal-comfort models, viz., ASHRAE comfort standards and TSI by Sharma and Ali to investigate thermal comfort aspects and impact of these comfort models on OE assessment in traditional dwellings. A naturally ventilated vernacular dwelling in Sugganahalli, a village close to Bangalore (India), set in warm - humid climate is considered for present investigations on impact of transition in building materials, change in climatic location and choice of thermal comfort models on energy in buildings. The study includes a rigorous real time monitoring of the thermal performance of the dwelling. Dynamic simulation models validated by measured data have also been adopted to determine the impact of the transition from vernacular to modern material-configurations. Results of the study and appraisal for appropriate thermal comfort standards for computing operational energy has been presented and discussed in this paper. (c) 2014 K.I. Praseeda. Published by Elsevier Ltd.