Microbial aspects of acid generation and bioremediation with relevance to indian mining

The role of Acidithiobacillus group of bacteria in acid generation and heavy metal dissolution was studied with relevance to some Indian mines. Microorganisms implicated in acid generation such as Acidithiobacillus Acidithicibacillus thiooxidans and Leptospirillum ferrooxidans were isolated from abandoned mines, waste rocks and tailing dumps. Arsenite oxidizing Thiomonas and Bacillus group of bacteria were isolated and their ability to oxidize As (111) to As (V) established. Mine isolated Sulfate reducing bacteria were used to remove dissolved copper, zinc, iron and arsenic from solutions.

A cloud-based intelligent computing system for contextual exploration on personal sleep-tracking data using association rule mining

With the development of wearable and mobile computing technology, more and more people start using sleep-tracking tools to collect personal sleep data on a daily basis aiming at understanding and improving their sleep. While sleep quality is influenced by many factors in a person’s lifestyle context, such as exercise, diet and steps walked, existing tools simply visualize sleep data per se on a dashboard rather than analyse those data in combination with contextual factors. Hence many people find it difficult to make sense of their sleep data. In this paper, we present a cloud-based intelligent computing system named SleepExplorer that incorporates sleep domain knowledge and association rule mining for automated analysis on personal sleep data in light of contextual factors. Experiments show that the same contextual factors can play a distinct role in sleep of different people, and SleepExplorer could help users discover factors that are most relevant to their personal sleep.

A self-adaptive migration model genetic algorithm for data mining applications

Data mining involves nontrivial process of extracting knowledge or patterns from large databases. Genetic Algorithms are efficient and robust searching and optimization methods that are used in data mining. In this paper we propose a Self-Adaptive Migration Model GA (SAMGA), where parameters of population size, the number of points of crossover and mutation rate for each population are adaptively fixed. Further, the migration of individuals between populations is decided dynamically. This paper gives a mathematical schema analysis of the method stating and showing that the algorithm exploits previously discovered knowledge for a more focused and concentrated search of heuristically high yielding regions while simultaneously performing a highly explorative search on the other regions of the search space. The effective performance of the algorithm is then shown using standard testbed functions and a set of actual classification datamining problems. Michigan style of classifier was used to build the classifier and the system was tested with machine learning databases of Pima Indian Diabetes database, Wisconsin Breast Cancer database and few others. The performance of our algorithm is better than others.

Quality certification and company performance: The newly developed country experience

This study investigates the impacts of ISO 9001:2008 certification on companies in Malaysia. Data were collected from CEOs and Managers through a questionnaire survey. A multivariate analysis and SPSS macro were used as statistical techniques to assess the effects of ISO 9001 certification. Results of the study indicate that ISO 9001 certified companies were having significantly greater benefits and financial performance compared to non-certified companies. However, no significant direct relationship between ISO 9001 certification and company's financial performance was found. A further investigation revealed that financial performance is actually directly related to quality and local and international business performance, which are significantly influenced by ISO 9001 certification. Therefore quality and business performances are involved in the mediational process between the financial performance of companies and ISO 9001 certification. The novelty of this research lies in the establishment of, for the first time, high level statistical relationship between ISO 9001 certification, its mediating factors and financial performance of companies.

Water management capacity building to support rapidly developing mining economies

Many developing countries are experiencing rapid expansion in mining with associated water impacts. In most cases mining expansion is outpacing the building of national capacity to ensure that sustainable water management practices are implemented. Since 2011, Australia's International Mining for Development Centre (IM4DC) has funded capacity building in such countries including a program of water projects. Five projects in particular (principally covering experiences from Peru, Colombia, Ghana, Zambia, Indonesia, Philippines and Mongolia) have provided insight into water capacity building priorities and opportunities. This paper reviews the challenges faced by water stakeholders, and proposes the associated capacity needs. The paper uses the evidence derived from the IM4DC projects to develop a set of specific capacity-building recommendations. Recommendations include: the incorporation of mine water management in engineering and environmental undergraduate courses; secondments of staff to suitable partner organisations; training to allow site staff to effectively monitor water including community impacts; leadership training to support a water stewardship culture; training of officials to support implementation of catchment management approaches; and the empowerment of communities to recognise and negotiate solutions to mine-related risks. New initiatives to fund the transfer of multi-disciplinary knowledge from nations with well-developed water management practices are called for.

Reforming technology company incentive programs for achieving knowledge-based economic development:a Brazil-Australia comparative study

This doctoral thesis aims to demonstrate the importance of incentives to technology-based firms as a strategy to promote knowledge-based economic development (KBED). To remain competitive, technology-based firms must innovate and seek new markets; therefore, this study aims to propose an incentive model to technology-based firms as a strategy to promote knowledge-based urban development, according to framework described by Yigitcanlar (2011). This is an exploratory and descriptive research with a qualitative approach. Surveys were carried out with national trade associations that represented technology-based firms both in Brazil and Australia. After analysing the surveys, structured interviews were conducted with government representatives, trade associations and businessmen who had used financial support by the federal government. When comparing both countries, the study found the importance of direct incentives through tax incentives, for it is a less bureaucratic, quicker and more direct process for firms. We suggest to include the terms incentives in the framework of knowledge-based urban development, as one of the pillars that contribute to knowledge-based economic development.

Hybrid learning scheme for data mining applications

Classification of large datasets is a challenging task in Data Mining. In the current work, we propose a novel method that compresses the data and classifies the test data directly in its compressed form. The work forms a hybrid learning approach integrating the activities of data abstraction, frequent item generation, compression, classification and use of rough sets.

Hybrid learning scheme for data mining applications

Classification of large datasets is a challenging task in Data Mining. In the current work, we propose a novel method that compresses the data and classifies the test data directly in its compressed form. The work forms a hybrid learning approach integrating the activities of data abstraction, frequent item generation, compression, classification and use of rough sets.

Data mining approaches to software fault diagnosis

Automatic identification of software faults has enormous practical significance. This requires characterizing program execution behavior and the use of appropriate data mining techniques on the chosen representation. In this paper, we use the sequence of system calls to characterize program execution. The data mining tasks addressed are learning to map system call streams to fault labels and automatic identification of fault causes. Spectrum kernels and SVM are used for the former while latent semantic analysis is used for the latter The techniques are demonstrated for the intrusion dataset containing system call traces. The results show that kernel techniques are as accurate as the best available results but are faster by orders of magnitude. We also show that latent semantic indexing is capable of revealing fault-specific features.

Shareholder/Stakeholder Value Management, Company Growth and

There has been considerable discussion in the literature about the relative merits of shareholder value management and stakeholder value management, but relatively little empirical research has been reported concerning the relationship between these types of management and financial performance. The present study puts forward a hypothesis that true shareholder value management also encompasses stakeholder value management. This combination of shareholder/stakeholder value management is hypothesised to be associated with superior financial performance and sales growth. Using a sample of chief financial officers' ratings of the contemporary management accounting techniques economic value added and the balanced scorecard to represent the two management types, the study found evidence in support of the hypothesis.

Strategic Priorities, Company Performance and Attitudes Towards Management Accounting Techniques: an Empirical Study

The study investigates whether there is an association between different combinations of emphasis on generic strategies (product differentiation and cost efficiency) and perceived usefulness of management accounting techniques. Previous research has found that cost leadership is associated with traditional accounting techniques and product differentiation with a variety of modern management accounting approaches. The present study focuses on the possible existence of a strategy that mixes these generic strategies. The empirical results suggest that (a) there is no difference in the attitudes towards the usefulness of traditional management accounting techniques between companies that adhere either to a single strategy or a mixed strategy; (b) there is no difference in the attitudes towards modern and traditional techniques between companies that adhere to a single strategy, whether this is product differentiation or cost efficiency, and c) companies that favour a mixed strategy seem to have a more positive attitude towards modern techniques than companies adhering to a single strategy