Description:
Millions of people around the world suffer from or prone to health problems caused by high concentration of fluoride in drinking water sources. One of the environmentally friendly and cost-effective ways for removing fluoride is the use of bone char. In this review, the structural properties and binding affinity of fluoride ions from different water sources was critically discussed. The effect of experimental conditions on enhancing the adsorption capacity of fluoride ions using bone char samples was addressed. It appears that surface properties, and conditions of the bone char production such as temperature and residence time play an important role in designing the optimal fluoride removal process. The optimum temperature for fluoride removal seems to be in the range of 500–700 °C and a residence time of 2 h. Applying various equilibrium adsorption isotherms for understanding fluoride adsorption mechanism was presented. The effect of bone char modification with different elements were discussed and recommendations for a further increase in the removal efficiency was proposed. Cost of bone char production and large-scale treatment systems were also discussed based on information available from scientific and commercial sources. Challenges with existing domestic defluoridation designs were highlighted and suggestions for new conceptual designs were provided.
Description:
Millions of people around the world suffer from or prone to health problems caused by high concentration of fluoride in drinking water sources. One of the environmentally friendly and cost-effective ways for removing fluoride is the use of bone char. In this review, the structural properties and binding affinity of fluoride ions from different water sources was critically discussed. The effect of experimental conditions on enhancing the adsorption capacity of fluoride ions using bone char samples was addressed. It appears that surface properties, and conditions of the bone char production such as temperature and residence time play an important role in designing the optimal fluoride removal process. The optimum temperature for fluoride removal seems to be in the range of 500–700 °C and a residence time of 2 h. Applying various equilibrium adsorption isotherms for understanding fluoride adsorption mechanism was presented. The effect of bone char modification with different elements were discussed and recommendations for a further increase in the removal efficiency was proposed. Cost of bone char production and large-scale treatment systems were also discussed based on information available from scientific and commercial sources. Challenges with existing domestic defluoridation designs were highlighted and suggestions for new conceptual designs were provided.
Description:
Cloud computing delivers IT solutions as a utility to users. A common economic objective for both cloud consumers and providers is to minimise their total deployment and operational costs while achieving satisfactory system performance to meet Service Level Agreements (SLAs). Therefore, the trade-off between cost and system performance is needed to be managed to achieve the best cost effectiveness. The PhD project presented in this paper provides an efficient and accurate method to evaluate the trade-off between cost and system performance by proposing a performance testing tool for Cloud systems. This tool can accommodate different Cloud system architectures and adopt different workload and cost models of Cloud systems during the trade-off evaluation process.
Description:
Following a study of back injuries in the Queensland Coal Industry, there arose several questions that needed further research. One of these was the cost of accident and injuries, and the impact of this cost would have on an organisation. The project's research involved a comprehensive study of literature pertaining to the cost of accidents and injuries. This included both insured and uninsured costs. The following four classifications of accidents were researched; first aid treatments; first aid doctor treatments; lost time injury cases; and equipment accident damage cases. A coal mine was selected for the pilot study and, data was collected on the four classifications over a complete year. This means a year that has no out standing accident cases or liablilities. The research was then considered to determine its support for the acceptance or rejection of the hypothesis whic postulates that the current methods used to analyse the cost of accidents or injuries in the coal mining industry are inadequate. As a result of the above condsiderations, a number of key points are put forward in support of the acceptance of the hypothesis. The research established costs both insured and uninsured for the four classifications under review. Then a calculation of a weighted ratio of uninsured costs was made. The paper concludes by making certain recommendations and supporting the need for further research into accident costing within the coal mining fraternity.
Description:
Masters in Applied Science in Occupational Health and Safety
Description:
Following a study of back injuries in the Queensland Coal Industry, there arose several questions that needed further research. One of these was the cost of accident and injuries, and the impact of this cost would have on an organisation. The project's research involved a comprehensive study of literature pertaining to the cost of accidents and injuries. This included both insured and uninsured costs. The following four classifications of accidents were researched; first aid treatments; first aid doctor treatments; lost time injury cases; and equipment accident damage cases. A coal mine was selected for the pilot study and, data was collected on the four classifications over a complete year. This means a year that has no out standing accident cases or liablilities. The research was then considered to determine its support for the acceptance or rejection of the hypothesis whic postulates that the current methods used to analyse the cost of accidents or injuries in the coal mining industry are inadequate. As a result of the above condsiderations, a number of key points are put forward in support of the acceptance of the hypothesis. The research established costs both insured and uninsured for the four classifications under review. Then a calculation of a weighted ratio of uninsured costs was made. The paper concludes by making certain recommendations and supporting the need for further research into accident costing within the coal mining fraternity.
Description:
Masters in Applied Science in Occupational Health and Safety
Description:
ISO55000 is the International Organisation for Standardization (ISO) standard for asset management published in 2014. It stipulates that effective control and governance of assets by organizations is essential to realize value through managing risk and opportunity, in order to achieve the desired balance of cost, risk and performance. It is a challenge to industries on how to address this. This paper is on the issues and challenges of balancing cost, performance and risk in heavy haul rail asset management. Illustrative example from heavy haul network is used for this and on how to address some of the important challenges faced by heavy haul sector for managing life of rail assets.
Description:
Heterogeneous wireless sensor networks (WSNs) consist of resource-starving nodes that face a challenging task of handling various issues such as data redundancy, data fusion, congestion control, and energy efficiency. In these networks, data fusion algorithms process the raw data generated by a sensor node in an energy-efficient manner to reduce redundancy, improve accuracy, and enhance the network lifetime. In literature, these issues are addressed individually, and most of the proposed solutions are either application-specific or too complex that make their implementation unrealistic, specifically, in a resource-constrained environment. In this paper, we propose a novel node-level data fusion algorithm for heterogeneous WSNs to detect noisy data and replace them with highly refined data. To minimize the amount of transmitted data, a hybrid data aggregation algorithm is proposed that performs in-network processing while preserving the reliability of gathered data. This combination of data fusion and data aggregation algorithms effectively handle the aforementioned issues by ensuring an efficient utilization of the available resources. Apart from fusion and aggregation, a biased traffic distribution algorithm is introduced that considerably increases the overall lifetime of heterogeneous WSNs. The proposed algorithm performs the tedious task of traffic distribution according to the network's statistics, ie, the residual energy of neighboring nodes and their importance from a network's connectivity perspective. All our proposed algorithms were tested on a real-time dataset obtained through our deployed heterogeneous WSN in an orange orchard and also on publicly available benchmark datasets. Experimental results verify that our proposed algorithms outperform the existing approaches in terms of various performance metrics such as throughput, lifetime, data accuracy, computational time, and delay.
Description:
Heterogeneous wireless sensor networks (WSNs) consist of resource-starving nodes that face a challenging task of handling various issues such as data redundancy, data fusion, congestion control, and energy efficiency. In these networks, data fusion algorithms process the raw data generated by a sensor node in an energy-efficient manner to reduce redundancy, improve accuracy, and enhance the network lifetime. In literature, these issues are addressed individually, and most of the proposed solutions are either application-specific or too complex that make their implementation unrealistic, specifically, in a resource-constrained environment. In this paper, we propose a novel node-level data fusion algorithm for heterogeneous WSNs to detect noisy data and replace them with highly refined data. To minimize the amount of transmitted data, a hybrid data aggregation algorithm is proposed that performs in-network processing while preserving the reliability of gathered data. This combination of data fusion and data aggregation algorithms effectively handle the aforementioned issues by ensuring an efficient utilization of the available resources. Apart from fusion and aggregation, a biased traffic distribution algorithm is introduced that considerably increases the overall lifetime of heterogeneous WSNs. The proposed algorithm performs the tedious task of traffic distribution according to the network's statistics, ie, the residual energy of neighboring nodes and their importance from a network's connectivity perspective. All our proposed algorithms were tested on a real-time dataset obtained through our deployed heterogeneous WSN in an orange orchard and also on publicly available benchmark datasets. Experimental results verify that our proposed algorithms outperform the existing approaches in terms of various performance metrics such as throughput, lifetime, data accuracy, computational time, and delay.