Extractive transnational corporations, intrastate conflict and peacemaking : frameworks and best practice

This thesis explores the role of mining and oil transnational corporations in corporate peacemaking. That is, helping to bring together warring parties in intrastate conflict to enable them to conduct peace negotiations and then, supporting these negotiations. Key concerns, and new theory, frameworks and best-practice in corporate peacemaking are proposed.

An agent-based hybrid framework for database mining

While knowledge discovery in databases (KDD) is defined as an iterative sequence of the following steps: data pre-processing, data mining, and post data mining, a significant amount of research in data mining has been done, resulting in a variety of algorithms and techniques for each step. However, a single data-mining technique has not been proven appropriate for every domain and data set. Instead, several techniques may need to be integrated into hybrid systems and used cooperatively during a particular data-mining operation. That is, hybrid solutions are crucial for the success of data mining. This paper presents a hybrid framework for identifying patterns from databases or multi-databases. The framework integrates these techniques for mining tasks from an agent point of view. Based on the experiments conducted, putting different KDD techniques together into the agent-based architecture enables them to be used cooperatively when needed. The proposed framework provides a highly flexible and robust data-mining platform and the resulting systems demonstrate emergent behaviors although it does not improve the performance of individual KDD techniques.

The right to convert exploration licences to mining leases in Australia: a proposed national uniform model

In this article, the authors raise an important proposal for reform to Australia's mining legislation: a nationally-consistent model providing exploration licence holders with a legislative right to be granted a mining lease. This proposed national model will be designed to reflect the present Western Australian system - Western Australia being the only jurisdiction to provide exploration licence holders with the express right to be granted a mining lease on application. The authors believe that the Western Australian system should provide the basis for a national legislative model, given that it is designed to balance appropriately the interests of companies wanting a right to mine to recoup the costs involved in exploring for minerals, and the interests of the public in ensuring that exploration and mining is conducted
reasonably.

Transnational feminism, globalisation, human rights and education

The article demonstrates how neo-liberal ideologies and market forces of
globalisation have produced new discourses in education, which have created new sites of political action and require a radical rethinking about feminist theorizing concerning gender equity in education. The article, in analysing the transformation of the social relations of gender and social stratification, draws from feminist, poststructuralist and postcolonial theories. The author concludes that there is need for redefining
feminist paradigms in global pedagogies. Such a new paradigm in feminist pedagogy, based on discourses of power, human rights and social justice should provide a foundation for improving the equity for girls and women in education and society globally.

Analyzing security protocols using association rule mining

Current studies to analyzing security protocols using formal methods require users to predefine authentication goals. Besides, they are unable to discover potential correlations between secure messages. This research attempts to analyze security protocols using data mining. This is done by extending the idea of association rule mining and converting the verification of protocols into computing the frequency and confidence of inconsistent secure messages. It provides a novel and efficient way to analyze security protocols and find out potential correlations between secure messages. The conducted experiments demonstrate our approaches.

An incremental FP-growth web content mining and its application in preference identification

This paper presents a real application of Web-content mining using an incremental FP-Growth approach. We firstly restructure the semi-structured data retrieved from the web pages of Chinese car market to fit into the local database, and then employ an incremental algorithm to discover the association rules for the identification of car preference. To find more general regularities, a method of attribute-oriented induction is also utilized to find customer’s consumption preferences. Experimental results show some interesting consumption preference patterns that may be beneficial for the government in making policy to encourage and guide car consumption.

Agents and stream data mining: a new perspective

Many organizations struggle with the massive amount of data they collect. Today, data does more than serve as the ingredients for churning out statistical reports. They help support efficient operations in many organizations, and to some extent, data provide the competitive intelligence organizations need to survive in today's economy. Data mining can't always deliver timely and relevant results because data are constantly changing. However, stream-data processing might be more effective, judging by the Matrix project.

How transnational environmental advocacy networks socialize international financial institutions: a case study of the international finance corporation

Environmental organizations, characterized here as transnational advocacy networks, use various strategies to "green" international financial institutions (IFIs). This article goes beyond analyzing network strategies to examine how transnational advocacy networks reconstitute the identity of IFIs. This, it is argued, results from processes of socialization: social influence, persuasion and coercion by lobbying. A case study of the International Finance Corporation (IFC), as a member of the World Bank Group, is used to analyze how an IFI internalized sustainable development norms. The IFC finances private enterprise in developing countries by providing venture capital for private projects. Transnational advocacy networks socialized the IFC through influencing its projects, policies and institutions via direct and indirect interactions to the point where the organization now sees itself as a sustainable development financier. This article applies constructivist insights to the greening process in order to demonstrate how socialization can reshape an IFI's identity.

Mining frequent patterns for AMP-activated protein kinase regulation on skeletal muscle

Background
AMP-activated protein kinase (AMPK) has emerged as a significant signaling intermediary that regulates metabolisms in response to energy demand and supply. An investigation into the degree of activation and deactivation of AMPK subunits under exercise can provide valuable data for understanding AMPK. In particular, the effect of AMPK on muscle cellular energy status makes this protein a promising pharmacological target for disease treatment. As more AMPK regulation data are accumulated, data mining techniques can play an important role in identifying frequent patterns in the data. Association rule mining, which is commonly used in market basket analysis, can be applied to AMPK regulation.

Results
This paper proposes a framework that can identify the potential correlation, either between the state of isoforms of α, β and γ subunits of AMPK, or between stimulus factors and the state of isoforms. Our approach is to apply item constraints in the closed interpretation to the itemset generation so that a threshold is specified in terms of the amount of results, rather than a fixed threshold value for all itemsets of all sizes. The derived rules from experiments are roughly analyzed. It is found that most of the extracted association rules have biological meaning and some of them were previously unknown. They indicate direction for further research.

Conclusion
Our findings indicate that AMPK has a great impact on most metabolic actions that are related to energy demand and supply. Those actions are adjusted via its subunit isoforms under specific physical training. Thus, there are strong co-relationships between AMPK subunit isoforms and exercises. Furthermore, the subunit isoforms are correlated with each other in some cases. The methods developed here could be used when predicting these essential relationships and enable an understanding of the functions and metabolic pathways regarding AMPK.

Mining frequent itemsets for protein kinase regulation

Protein kinases, a family of enzymes, have been viewed as an important signaling intermediary by living organisms for regulating critical biological processes such as memory, hormone response and cell growth. The
unbalanced kinases are known to cause cancer and other diseases. With the increasing efforts to collect, store and disseminate information about the entire kinase family, it not only leads to valuable data set to understand cell regulation but also poses a big challenge to extract valuable knowledge about metabolic pathway from the data. Data mining techniques that have been widely used to find frequent patterns in large datasets can be extended and adapted to kinase data as well. This paper proposes a framework for mining frequent itemsets from the collected kinase dataset. An experiment using AMPK regulation data demonstrates that our approaches are useful and efficient in analyzing kinase regulation data.

Mining small databases by collecting knowledge

Current data mining techniques may not be helpful for mining some companies/organizations such as nuclear power plants and earthquake bureaus, which have only small databases. Apparently, these companies/organizations also expect to apply data mining techniques to extract useful patterns in their databases so as to make their decisions. However, data in these databases such as the accident database of a nuclear power plant and the earthquake database in an earthquake bureau, may not be large enough to form any patterns. To meet the applications, we present a new mining model in this paper, which is based on the collecting knowledge from such as Web, journals, and newspapers.

Collecting quality data for database mining

Data collecting is necessary to some organizations such as nuclear power plants and earthquake bureaus, which have very small databases. Traditional data collecting is to obtain necessary data from internal and external data-sources and join all data together to create a homogeneous huge database. Because collected data may be untrusty, it can disguise really useful patterns in data. In this paper, breaking away traditional data collecting mode that deals with internal and external data equally, we argue that the first step for utilizing external data is to identify quality data in data-sources for given mining tasks. Pre- and post-analysis techniques are thus advocated for generating quality data.