Application of XRF and correspondence analysis to provenance studies of coastal and inland archaeological pottery from the Mngeni river area, South Africa

XRF spectrometry was applied to provenance studies of Iron Age pottery specimens that originated from the Mngeni river area in South Africa. Ten transition metals (Sc to Zn) mere determined in 107 potsherds, excavated from four different sites. The data were subjected to a computerized mathematical technique (correspondence analysis), which was used to group the samples according to the similarity of their elemental distributions. The groupings were interpreted in terms of social or cultural interaction between the sites. (C) 1997 by John Wiley & Sons, Ltd.

Application of a theoretical framework to foster a cardiac-diabetes self-management programme

AIM: This paper analyses and illustrates the application of Bandura's self-efficacy construct to an innovative self-management programme for patients with both type 2 diabetes and coronary heart disease. BACKGROUND: Using theory as a framework for any health intervention provides a solid and valid foundation for aspects of planning and delivering such an intervention; however, it is reported that many health behaviour intervention programmes are not based upon theory and are consequently limited in their applicability to different populations. The cardiac-diabetes self-management programme has been specifically developed for patients with dual conditions with the strategies for delivering the programme based upon Bandura's self-efficacy theory. This patient group is at greater risk of negative health outcomes than that with a single chronic condition and therefore requires appropriate intervention programmes with solid theoretical foundations that can address the complexity of care required. SOURCES OF EVIDENCE: The cardiac-diabetes self-management programme has been developed incorporating theory, evidence and practical strategies. DISCUSSION: This paper provides explicit knowledge of the theoretical basis and components of a cardiac-diabetes self-management programme. Such detail enhances the ability to replicate or adopt the intervention in similar or differing populations and/or cultural contexts as it provides in-depth understanding of each element within the intervention. CONCLUSION: Knowledge of the concepts alone is not sufficient to deliver a successful health programme. Supporting patients to master skills of self-care is essential in order for patients to successfully manage two complex, chronic illnesses. IMPLICATIONS FOR NURSING PRACTICE OR HEALTH POLICY: Valuable information has been provided to close the theory-practice gap for more consistent health outcomes, engaging with patients for promoting holistic care within organizational and cultural contexts.

Challenges facing the application of sustainability to housing in Saudi Arabia

Modern Saudi housing supply is neither sustainable nor efficient in meeting the conservative Islamic culture of the community and the local environmental conditions. This thesis develops a model for successful development of sustainable housing in Saudi Arabia by incorporating multi stakeholder inputs on key barriers, critical success factors and best practice case studies. The model will help create public awareness and education tools for both private and public sectors on sustainable housing. It provides a framework that includes cultural and environmental needs of the conservative Saudi neighbourhood. It may assist the Saudi government to regulate new building codes and regulations.

Development and application of Palygorskite porous ceramsite in a biological aerated filter (BAF)

Novel filter Palygorskite porous ceramsite (PC) was prepared using Palygorskite clay, poreforming material sawdust, and sodium silicate with a mass ratio of 10:2:1 after sintering at 700°C for 180 min. PC was characterized with X-ray diffraction, X-ray fluorescence, scanning electron microscopy, elemental, and porosimetry. PC had a total porosity of 67% and specific surface area of 61 m2/g. In order to assess the usefulness of PC as a medium for biological aerated filters (BAF), PC and (commercially available ceramsite) CAC were used to treat wastewater city in two laboratory-scale upflow BAFs. The results showed that the reactor containing PC was more efficient than the reactor containing CAC in terms of total organic carbon (TOC), ammonia nitrogen (NH3-N), and the removal of total nitrogen (TN) and phosphorus (P). This system was found to be more efficient at water temperatures ranging from 20 to 26°C, an air–water (A/W) ratio of 3:1, dissolved oxygen concentration >4.00 mg/L, and hydraulic retention time (HRT) ranging from 0.5 to 7 h. The interconnected porous structure produced for PC was suitable for microbial growth, and primarily protozoan and metazoan organisms were found in the biofilm. Microorganism growth also showed that, under the same submerged culture conditions, the biological mass in PC was significantly higher than in CAC (34.1 and 2.2 mg TN/g, respectively). In this way, PC media can be considered suitable for the use as a medium in novel biological aerated filters for the simultaneous removal of nitrogen and phosphorus.

The application of social network analysis in the construction industry of Hong Kong

The Hong Kong construction industry is currently facing ageing problem and labour shortage. There are opportunities for employing ethnic minority construction workers to join this hazardous industry. These ethnic minority workers are prone to accidents due to communication barriers. Safety communication is playing an important role for avoiding the accidents on construction sites. However, the ethnic minority workers are not very fluent in the local language and facing safety communication problems while working with local workers. Social network analysis (SNA), being an effective tool to identify the safety communication flow on the construction site, is used to attain the measures of safety communication like centrality, density and betweenness within the ethnic minorities and local workers, and to generate sociograms that visually represent communication pattern within the effective and ineffective safety networks. The aim of this paper is to present the application of SNA for improving the safety communication of ethnic minorities in the construction industry of Hong Kong. The paper provides the theoretical background of SNA approaches for the data collection and analysis using the software UCINET and NetDraw, to determine the predominant safety communication network structure and pattern of ethnic minorities on site.

Multi-level neural modelling : an application of object-oriented software engineering

Neu-Model, an ongoing project aimed at developing a neural simulation environment that is extremely computationally powerful and flexible, is described. It is shown that the use of good Software Engineering techniques in Neu-Model’s design and implementation is resulting in a high performance system that is powerful and flexible enough to allow rigorous exploration of brain function at a variety of conceptual levels.

Application of TS-Fuzzy Controller for Active Power and DC Capacitor Voltage Control in DFIG-Based Wind Energy Conversion Systems

This chapter focuses on the implementation of the TS (Tagaki-Sugino) fuzzy controller for the Doubly Fed Induction Generator (DFIG) based wind generator. The conventional PI control loops for mantaining desired active power and DC capacitor voltage is compared with the TS fuzzy controllers. DFIG system is represented by a third-order model where electromagnetic transients of the stator are neglected. The effectiveness of the TS-fuzzy controller on the rotor speed oscillations and the DC capacitor voltage variations of the DFIG damping controller on converter ratings is also investigated. The results from the time domain simulations are presented to elucidate the effectiveness of the TS-fuzzy controller over the conventional PI controller in the DFIG system. The proposed TS-fuzzy con-troller can improve the fault ride through capability of DFIG compared to the conventional PI controller.

Assessment and application of clustering techniques to atmospheric particle number size distribution for the purpose of source apportionment

Long-term measurements of particle number size distribution (PNSD) produce a very large number of observations and their analysis requires an efficient approach in order to produce results in the least possible time and with maximum accuracy. Clustering techniques are a family of sophisticated methods which have been recently employed to analyse PNSD data, however, very little information is available comparing the performance of different clustering techniques on PNSD data. This study aims to apply several clustering techniques (i.e. K-means, PAM, CLARA and SOM) to PNSD data, in order to identify and apply the optimum technique to PNSD data measured at 25 sites across Brisbane, Australia. A new method, based on the Generalised Additive Model (GAM) with a basis of penalised B-splines, was proposed to parameterise the PNSD data and the temporal weight of each cluster was also estimated using the GAM. In addition, each cluster was associated with its possible source based on the results of this parameterisation, together with the characteristics of each cluster. The performances of four clustering techniques were compared using the Dunn index and Silhouette width validation values and the K-means technique was found to have the highest performance, with five clusters being the optimum. Therefore, five clusters were found within the data using the K-means technique. The diurnal occurrence of each cluster was used together with other air quality parameters, temporal trends and the physical properties of each cluster, in order to attribute each cluster to its source and origin. The five clusters were attributed to three major sources and origins, including regional background particles, photochemically induced nucleated particles and vehicle generated particles. Overall, clustering was found to be an effective technique for attributing each particle size spectra to its source and the GAM was suitable to parameterise the PNSD data. These two techniques can help researchers immensely in analysing PNSD data for characterisation and source apportionment purposes.

Understanding carers' intention for their child to walk to school : further application of the theory of reasoned action

One quarter of Australian children are overweight or obese (ABS, 2010), putting them at increased risk of physical and psychological health problems (Reilly et al., 2003). Overweight and obesity in childhood tends to persist into adulthood and is associated with premature death and morbidity (Reilly & Kelly, 2011). Increases in Australian children’s weight have coincided with declines in active transportation, such as walking, to school (Salmon et al., 2005). Investigating the factors which influence walking to school is therefore important, particularly since walking to school is a low cost and effective means of reducing excess weight (Rosenberg et al., 2006) that can be easily integrated into daily routine (Brophy et al., 2011). While research in this area has expanded (e.g., Brophy et al., 2011; Giles-Corti et al., 2010), it is largely atheoretical (exceptions Napier et al., 2011). This is an important gap from a social marketing perspective given the use of theory lies at the foundation of the framework (NSMC, 2006) and a continued lack of theory use is observed (Luca & Suggs, 2013). The aim of this paper is to empirically examine a widely adopted theory, the deconstructed Theory of Reasoned Action (TRA) (Fishbein & Azjen, 1975), to understand the relative importance of attitude and subjective norms in determining intentions to increase walk to school behaviour.

Understanding caregivers’ intentions for their child to walk to school : further application of the theory of planned behaviour

Increases in childhood obesity have coincided with declines in active transportation to school. This research builds on largely atheoretical extant literature examining factors that influence walk to school behavior through application of the Theory of Planned Behavior (TPB). Understanding caregivers’ decision for their child to walk to/from school is key to developing interventions to promote this cost-effective and accessible health behavior. The results from an online survey of 512 caregivers provide support for the TPB, highlighting the important role of subjective norms. This suggests marketers should nurture caregivers’ perception that important others approve of walking to school.

Application of organo-beidellites for the adsorption of atrazine

The surfaces of natural beidellite were modified with cationic surfactant octadecyl trimethylammonium bromide at different concentrations. The organo-beidellite adsorbent materials were then used for the removal of atrazine with the goal of investigating the mechanism for the adsorption of organic triazine herbicide from contaminated water. Changes on the surfaces and structure of beidellite were characterised by X-ray diffraction (XRD), thermogravimetric analysis (TGA), Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM) and BET surface analysis. Kinetics of the adsorption studies were also carried out which show that the adsorption capacity of the organoclays increases with increasing surfactant concentration up until 1.0 CEC surfactant loading, after which the adsorption capacity greatly decreases. TG analysis reveals that although the 2.0 CEC sample has the greatest percentage of surfactant by mass, most of it is present on external sites. The 0.5 CEC sample has the highest proportion of surfactant exchanged into the internal active sites and the 1.0 CEC sample accounts for the highest adsorption capacity. The goodness of fit of the pseudo-second order kinetic confirms that chemical adsorption, rather than physical adsorption, controls the adsorption rate of atrazine.

Application of anomaly technique in wind turbine bearing fault detection

Bearing faults are the most common cause of wind turbine failures. Unavailability and maintenance cost of wind turbines are becoming critically important, with their fast growing in electric networks. Early fault detection can reduce outage time and costs. This paper proposes Anomaly Detection (AD) machine learning algorithms for fault diagnosis of wind turbine bearings. The application of this method on a real data set was conducted and is presented in this paper. For validation and comparison purposes, a set of baseline results are produced using the popular one-class SVM methods to examine the ability of the proposed technique in detecting incipient faults.

Application of a Bayesian Network complex system model to a successful community electricity demand reduction program

Utilities worldwide are focused on supplying peak electricity demand reliably and cost effectively, requiring a thorough understanding of all the factors influencing residential electricity use at peak times. An electricity demand reduction project based on comprehensive residential consumer engagement was established within an Australian community in 2008, and by 2011, peak demand had decreased to below pre-intervention levels. This paper applied field data discovered through qualitative in-depth interviews of 22 residential households at the community to a Bayesian Network complex system model to examine whether the system model could explain successful peak demand reduction in the case study location. The knowledge and understanding acquired through insights into the major influential factors and the potential impact of changes to these factors on peak demand would underpin demand reduction intervention strategies for a wider target group.

An application of fuzzy DL-Based semantic perception to soil container classification

Semantic perception and object labeling are key requirements for robots interacting with objects on a higher level. Symbolic annotation of objects allows the usage of planning algorithms for object interaction, for instance in a typical fetchand-carry scenario. In current research, perception is usually based on 3D scene reconstruction and geometric model matching, where trained features are matched with a 3D sample point cloud. In this work we propose a semantic perception method which is based on spatio-semantic features. These features are defined in a natural, symbolic way, such as geometry and spatial relation. In contrast to point-based model matching methods, a spatial ontology is used where objects are rather described how they "look like", similar to how a human would described unknown objects to another person. A fuzzy based reasoning approach matches perceivable features with a spatial ontology of the objects. The approach provides a method which is able to deal with senor noise and occlusions. Another advantage is that no training phase is needed in order to learn object features. The use-case of the proposed method is the detection of soil sample containers in an outdoor environment which have to be collected by a mobile robot. The approach is verified using real world experiments.

Effective emergency messaging during natural disasters: An application of message compliance theories

Study/Objective This research examines the types of emergency messages used in Australia during the response and early recovery phases of a natural disaster. The aim of the research is to develop theory-driven emergency messages that increase individual behavioural compliance during a disaster. Background There is growing evidence of non-compliant behaviour in Australia, such as refusing to evacuate and travelling through hazardous areas. This can result in personal injury, loss of life, and damage to (or loss of) property. Moreover, non-compliance can place emergency services personnel in life-threatening situations when trying to save non-compliant individuals. Drawing on message compliance research in psychology and sociology, a taxonomy of message types was developed to ascertain how emergency messaging can be improved to produce compliant behaviour. Method A review of message compliance literature was conducted to develop the taxonomy of message types previously found to achieve compliance. Seven categories were identified: direct-rational, manipulation, negative phrasing, positive phrasing, exchange appeals, normative appeals, and appeals to self. A content analysis was then conducted to assess the emergency messages evident in the Australian emergency management context. The existing messages were aligned with the literature to identify opportunities to improve emergency messaging. Results & Conclusion The results suggest there is an opportunity to improve the effectiveness of emergency messaging to increase compliance during the response and early recovery phases of a natural disaster. While some message types cannot legally or ethically be used in emergency communication (e.g. manipulative messaging), there is an opportunity to create more persuasive messages (e.g. appeals to self) that personalise the individual’s perception of risk, triggering them to comply with the message.