Data mining at enterprise level operates on huge amount of data such as government transactions, banks, insurance companies and so on. Inevitably, these businesses produce complex data that might be distributed in nature. When mining is made on such data with a single-step, it produces business intelligence as a particular aspect. However, this is not sufficient in enterprise where different aspects and standpoints are to be considered before taking business decisions. It is required that the enterprises perform mining based on multiple features, data sources and methods. This is known as combined mining. The combined mining can produce patterns that reflect all aspects of the enterprise. Thus the derived intelligence can be used to take business decisions that lead to profits. This kind of knowledge is known as actionable knowledge. / Data mining is a process of obtaining trends or patterns in historical data. Such trends form business intelligence that in turn leads to taking well informed decisions. However, data mining with a single technique does not yield actionable knowledge. This is because enterprises have huge databases and heterogeneous in nature. They also have complex data and mining such data needs multi-step mining instead of single step mining. When multiple approaches are involved, they provide business intelligence in all aspects. That kind of information can lead to actionable knowledge. Recently data mining has got tremendous usage in the real world. The drawback of existing approaches is that insufficient business intelligence in case of huge enterprises. This paper presents the combination of existing works and algorithms. We work on multiple data sources, multiple methods and multiple features. The combined patterns thus obtained from complex business data provide actionable knowledge. A prototype application has been built to test the efficiency of the proposed framework which combines multiple data sources, multiple methods and multiple features in mining process. The empirical results revealed that the proposed approach is effective and can be used in the real world.

The increased demand for interoperability among Emergency Responders (ERs) and timely accessibility to a large amount of reliable, accurate, context and location aware, and privacy-preserved data (e.g., environmental data, health records, building plan, etc.), mandates the emergence of dedicated Public Safety Broadband Networks (PSBNs). However, realizing PSBNs and addressing such requirements encounters substantial challenges. For example, several security and privacy vulnerabilities have been detected in the Long Term Evolution (LTE) which is the leading enabler of PSBNs. Nonetheless, the more significant challenge lies under the corresponding data requirements. This is because data is unstructured, its volume is enormous, and it includes inaccurate, irrelevant, and context-free data. Moreover, the data sources are heterogeneous and may not be reachable in an emergency. Furthermore, the data contains personally identifiable information for which privacy and access authorization should be respected. In this thesis, we investigate and address the aforementioned challenges. Here, we propose an efficient and secure algorithm to mitigate the main security and privacy vulnerability of LTE. In addition, to provide context and location aware data availability during an emergency, we propose a secure data storage structure and privacy-preserving search scheme. Furthermore, we propose a location-aware data access model to filter irrelevant data with regards to an incident and prevent unauthorized data access. To envision our access model, we propose a location-aware fine grained access authorization scheme. Our security analysis shows that our search scheme is secure against a chosen keyword attack and the proposed authorization scheme is formally proven secure against a selective chosen ciphertext attack. Concerning performance efficiency, our search scheme requires minimal data search and retrieval delay and the proposed authorization scheme imposes constant communication and decryption computation overheads. Finally, we propose a context-aware framework, which fully complies with emergency response requirements, based on the concept of trust to filter-out inaccurate and irrelevant data. The integration of our contributions promises highly reliable, accurate, context and location aware, and privacy-preserved data availability and timely data accessibility.

A learning analytics dashboard (LAD) is an application that illustrates the activity and progress of a user in a self-regulated, online learning environment. This tool mines source data to provide meaningful information that supports decision making and positively impacts learning behaviour. Research on this topic explores how learning activities and pedagogical goals are impacted by integrating LADs into learning and/or teaching environments. Currently, the majority of the research is centred around predicting student academic performance and identifying students that are at risk of failing. The popularity of integrating technology into educational practices has led to the adoption of LADs into learning management systems (LMS) or massive open online courses (MOOCs). The objective of this paper is to develop a concept for a standalone prototype LAD, for an Introductory Statistics course (STA 1000), to be potentially integrated into the University of Cape Town's (UCT) LMS, Vula. The dashboard aims to create and incorporate meaningful visualisations, that have the potential to primarily assist students as well as educators. Visualised information in the LAD aims to positively impact students to enhance and drive effective learning, which could consequentially aid educators. Additionally, the dashboard will aim to provide actionable feedback, derived from predictive modelling and course analytics, that positively impacts learning behaviour and identifies factors that the student could most effectively use to leverage their chances of passing and improve academic performance. Predictive analytics aim to identify academic factors, that a student has control over, such as course assessments and engagement variables, at certain time points in the academic semester and provide a useful course of action at those time points. Other than variables measured throughout the course, the predictive modelling takes certain prior academic information into consideration.

京都大学 / 新制・課程博士 / 博士(人間健康科学) / 甲第24539号 / 人健博第110号 / 新制||人健||8(附属図書館) / 京都大学大学院医学研究科人間健康科学系専攻 / (主査)教授 木下 彩栄, 教授 中尾 恵, 教授 中山 健夫 / 学位規則第4条第1項該当 / Doctor of Human Health Sciences / Kyoto University / DFAM

環保投資往往造成廠商成本負擔之增加，若缺乏政府管制或經濟誘因，廠商極有可能降低環保方面的投資，導致自然環境的污染及社會外部成本之發生，故透過公共環保政策之適度介入，似乎是不得不存在之必要手段。而本文所欲探討的環保補貼政策，即是存有多元見解及爭議之一種經濟誘因工具。 本文先介紹環保補貼之範圍、定義與各國適用之情形，並採用文獻回顧之方式，整理各學者對政府獎勵企業污染防治措施之爭議，以瞭解環保補貼對環境保護或全球整體經濟的影響。 肯定環保補貼對經濟發展及環境保護有正面的效果之後，接著討論環保補貼與SCM協定中「禁止性補貼」、「可控訴補貼」及「不可控訴補貼」類型間之關係，並探討當「不可控訴補貼」類型所依據之SCM協定相關規定停止適用後目前之定位，同時提出環保補貼於SCM協定下合法規避他國控訴之方式。 本文最後檢驗與分析我國之環保補貼於SCM協定下之適法性，並對我國環保補貼政策未來之發展與方向提出建議。 / The use of subsidies as environmental policy instruments has increased in recent years since firms usually aren’t willing to pay for the expense of pollution prevention and control. Environmental subsidies involving financial support by the government, as an economical incentive approach, are deemed to be important and effective by many researchers. However, it still remains controversial because some researchers argue that government intervention would always result in resources distortion and economic inefficiency. Therefore, this thesis focuses on subsidies with a positive impact on the environment and aims to discuss their utility and compatibility with relevant WTO covered agreements, especially the Agreement on Subsidies and Countervailing Measure (the SCM Agreement). The thesis first introduces the definition, scope and practice of environmental subsidies, and, by using literature review, presents several studies on the environmental and economic impact of environmental subsidies. The thesis then discusses the relevant regulations under the SCM Agreement framework and finds that environmental subsidies may be categorized as more than one type, ie non-actionable subsidy, of subsidies under the SCM Agreement. Furthermore, the thesis also analyzes how environmental subsidies can be designed in a way that complies with the SCM Agreement, thus avoiding the risk of being challenged under the WTO by other WTO Members. Finally, the thesis examines various types of environmental subsidies provided by Taiwanese government to understand whether they are consistent with the regulations of the SCM Agreement. Suggestions based on this research are put forward at the end of the thesis.

The purpose is to exemplify how the didactic model of organizing purposes can be used by teachers to support the development of chemistry education aimed at increasing students ́ action competence in waste management issues. We conducted didactic modeling with the exemplification phase as the research approach. To exemplify how the organizing purposes model provided support in didactic design and analysis, we created a teaching sequence of two lessons and implemented it in a class. The goal was to create progression between activities that would lead to students developing competence in action. Data collection was carried out through video recordings during these two teaching sessions, which were then transcribed and analyzed. During the analysis, we used the conceptual framework of organizing purposes: proximal purposes, overarching purposes, goals-in-view, and continuity. The exemplification shows that the model supported us in selecting activities to create a thoughtful progression. It also supported us in considering how to connect what students did with our overarching goal.

With national cuts on solar PV subsidies and the current “oversupply” of panels, the global solar market is clearly threatened by a contraction. Yet, the need for more solar power is apparent, particularly for the world’s poor and vulnerable population. Instead of securing modern energy access for these people, trade interests have triggered a counterproductive solar trade war. This contemporary legal study addresses these issues by examining existent and potential instruments for stimulating a North-to-South solar capital flow. The research finds that recent reforms of the CDM will do little difference from previous deficiencies, as local investment barriers are not reflected in the monetary support of the clean development mechanism. Competing technologies are successfully keeping solar out of the game while baseline requirements are undermining the poor. Inspired by national renewable energy law and policy, international alternatives could address these shortcomings. While feed-in tariffs have been commonly advocated, the REC model seems far more appropriate in an international context. Its ability to be traded separately from the electricity makes it a perfect candidate as a substitute for the CDM. Entrusted with certain features it could address the geographical unbalance and provide with greater investor certainty. But the scheme(s) are under current WTO regulations required to be non-discriminatory, making it highly questionable to believe that developed countries would ever fund such incentive. It is not likely that solar capital exporters want Chinese solar PV manufacturers, who are already receiving significant production subsidies, to receive the same benefits as other producers. However, if countries adversely effected by subsidies where allowed to offset the injury by discriminating Chinese producers in international REC schemes, the Author believes that it would be easier to sell such a concept and implement it, for the benefits of climate change mitigation and adaptation as well as the world’s vulnerable and poor nations. However, this would require extensive reforms under WTO which the Author calls for.

Certain individual and institutional factors such as knowledge about stigma and discrimination, fear of infection, social judgement, legal and policy environment act as actionable drivers and facilitators of HIV-related stigma and discrimination. These factors may hinder the utilisation and quality of care provided to people living with HIV. Purpose: The purpose of the study was to establish the actionable drivers and facilitators that determine the different forms of HIV-related stigma and discrimination among healthcare professionals at a district hospital in Malawi. Methods: The study used a descriptive correlational study. Data was collected through self-administered questionnaire. Data were analysed using SPPS and STATA 12. Fisher's Exact Test was used to conclude the association and binary logistic regression was used to model the degree of the statistical relationships. Results: The results showed statistically significant relationship between knowledge of stigma and discrimination, social judgement and awareness of workplace policy and HIV-related stigma and discrimination. Recommendations: Interventions aimed at increasing knowledge about HIV-related stigma, reducing social judgement, reinforcing HIV-related workplace policies are needed to reduce HIV-related stigma and discrimination in healthcare settings. / Health Studies / M. Ph. (Health Studies)