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The preschool years are an important time in the development of understanding the property of weight. This experiment investigates whether social learning, specifically imitation, will promote preschoolers’ use of this property. Children were randomly assigned to one of three groups. Those in the experimental group saw an adult sort four objects based on their weights. Children were then presented with the objects. Whether children sorted these objects based on their weights was scored, as was their sorting of a novel set of objects (to assess generalization) and their imitation of the hefting gestures used by the adult. Comparisons to control groups indicated that 4-year-olds, but not 3-year-olds, benefitted from the modeling and sorted by weight. These results suggest that social learning is an effective way to promote children’s use of this invisible property.

可信度是網路服務首要解決的問題，我們從數位憑證，認證、授權、委任授權等安全層面去研究代理者可信度，並提出一套完整可信度規則分類機制當作信任度判斷的依據。在此篇論文中，我們論證如何將規則概念應用在代理者的溝通協定、服務流程控制上。我們並同時整合語意網規則和本體論的技術，以達到可信的網路服務環境。 / Trust is one of the most important issues for Web Services. We studied the agent trust problem based on security technologies, such as digital certificates, authentication, authorization, and delegation, etc. Furthermore, we propose a complete trust rule taxonomy mechanism to assistant us on the evaluation of agent trustworthiness. In this thesis, we justify the feasibility of using rule concepts on the agent communication protocol and service process control. We also demonstrated how to integrate the semantic web rules and ontologies to have a trusted web services environment.

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A number of industrially relevant separation processes involve carboxylic acids. Carboxylic acids are also amongst the various oxygenated products found in aqueous waste streams or as by-products of industrial operations in Sasol’s Fischer Tropsch processes. Other by-products include alcohols and ketones. Accurate vapour-liquid-equilibrium (VLE) data are required for the efficient and optimal modeling and simulation of these processes. In addition, removing and separating these components will help to prevent their pollution and the associated impact on the environment. / Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2009.

If there is any fixed star in our constitutional and criminal procedure constellation, it is that torture is illegal and torture-introduced evidence is inadmissible. The purposes of this research are to (1) assess the exclusionary rule in the United Kingdom and United States; (2) explore the theoretical constitutional foundation of the rule; and (3) establish the Chinese exclusionary rule. Currently, there is no exclusionary rule explicitly in the Chinese Code of Criminal Procedure. If the wrongful conviction of the innocent is a pressing issue in China today, police torture is the flashpoint. Police torture in China is the prevalent evil not the isolated anecdote. This thesis combines diagnosis and prescription – the problem of police torture in China and the solution of the exclusionary rule. The ultimate goal of the research is to find a suitable exclusionary rule for China to solve the serious problem of police torture and wrongdoing. At the level of theory, my exclusionary rule framework is grounded in the separation of powers. Previous research about the separation of powers doctrine has focused almost entirely on constitutional law and political theory. They completely ignored the special role that the doctrine plays in the criminal justice system, a role consisting of the exercise of a reviewing function to ensure executive compliance with the criminal law. Separation of powers is a core component of the constitution’s system of checks and balances, a system in which each branch of the government is endowed with a constitutional control over the others. Without any judicial supervision or due process, the potential for arbitrary enforcement is high. The alternatives to the exclusionary rule are mainly illusory and of no practical avail. Past history also demonstrates that the very idea of protecting the defendant’s right is completely empty unless it is linked to an efficient mechanism. China grants the police too much power and has too little judicial supervision over police investigations. It creates imbalance in the existing Chinese criminal justice system. It is such an imbalance and the lack of separation of powers in the criminal justice system that poses a significant and growing threat for the protection of defendants’ rights.

Machine translation offers the challenge of automatically translating a text from one natural language into another. Statistical methods - originating from the field of information theory - have shown to be a major breakthrough in the field of machine translation. Prior to this paradigm, many systems had been developed following a rule-based approach. This denotes a system based on a linguistic description of the languages involved and of how translation occurs in the mind of the (human) translator. Statistical models on the contrary use empirical means and may work with very little linguistic hypothesis on language and translation as performed by humans. This had implications for rule-based translation systems, in terms of software architecture and the nature of the rules, which were manually input and lack any statistical feature. In the view of such diverging paradigms, we can imagine trying to combine both in a hybrid system. In the present work, we start by examining the state-of-the-art of both rule-based and statistical systems. We restrict the rule-based approach to transfer-based systems. We compare rule-based and statistical paradigms in terms of global translation quality and give a qualitative analysis of their respective specific errors. We also introduce initial black-box hybrid models that confirm there is an expected gain in combining the two approaches. Motivated by the qualitative analysis, we focus our study and experiments on lexical phrasal rules. We propose a setup allowing to extract such resources from corpora. Going one step further in the integration of rule-based and statistical approaches, we then examine how to combine the extracted rules with decoding modules that will allow for a corpus-based handling of ambiguity. This then leads to the final delivery of this work: a rule-based system for which we can learn non-deterministic rules from corpora, and whose decoder can be optimised on a tuning set in the same domain.

This paper studies determinants of FDI in Turkey using panel data analyses. The results of the study show that political stability, education level, rule of law, and trade cost have significant impact on FDI inflow in Turkey while similarity in economy size of home and host country (Turkey) has not. The effect of the trade cost and rule of law was surprising but it gave a clue to new research area. It was concluded that next studies of FDI determinants in Turkey must be conducted at firms' level to better understand the behaviour of foreign direct investments in the country.

Student Number : 0500919V - MA research report - School of Social Sciences - Faculty of Humanities / Governance reform in Africa has attracted both local and international attention. African initiatives, such as NEPAD and African Union, have endorsed good governance as a precondition for Africa’s emancipation from poverty while the international community has appreciated the need for well-governed proactive states in Africa in place of minimalist view that donors promoted with structural adjustment programmes. Donors’ proactive view of states led to governance reform as a criterion for receiving aid. Thus, limiting corruption by creating anti-corruption agencies became one of the requirements for donors’ support. Though not concentrating on anti-corruption agencies exclusively, this research report captures the complexity of donor conditions in reforming governance in Kenya through anti-corruption initiatives. It concludes that conditions are inevitable in an aid dependent country but cannot be sustained by external actors if they work without local support. The central argument of this paper is that there is need for promotion of a convergence of approach in reforming governance. The donor community and indigenous Africans need to view and promote governance reform from a developmental perspective in order to make foreign aid count in meeting Africa’s objectives. The policies donors espouse will bear out on African development if electorates buttress them and these policies need to be consistence with the welfare of the populace especially economically marginalized groups of population as Millennium Development Goals seek to encourage.

Adverse Drug Reactions (ADRs) are a major cause of morbidity and mortality worldwide. Clinical trials, which are extremely costly, human labor intensive and specific to controlled human subjects, are ineffective to uncover all ADRs related to a drug. There is thus a growing need of computing-supported methods facilitating the automated detection of drugs-related ADRs from large reports data sets; especially ADRs that left undiscovered during clinical trials but later arise due to drug-drug interactions or prolonged usage. For this purpose, big data sets available through drug-surveillance programs and social media provide a wealth of longevity information and thus a huge opportunity. In this research, we thus design a system using machine learning techniques to discover severe unknown ADRs triggered by a combination of drugs, also known as drug-drug-interaction. Our proposed Multi-drug Adverse Reaction Analytics System (MARAS) adopts and adapts an association rule mining-based methodology by incorporating contextual information to detect, highlight and visualize interesting drug combinations that are strongly associated with a set of ADRs. MARAS extracts non-spurious associations that are true representations of the combination of drugs taken and reported by patients. We demonstrate the utility of MARAS via case studies from the medical literature, and the usability of the MARAS system via a user study using real world medical data extracted from the FDA Adverse Event Reporting System (FAERS).