Secondary social science teacher training in Papua New Guinea and secondary social studies teacher training in New Zealand : a comparative study : a thesis presented in partial fulfilment of the requirements for the degree of Masters in Education at Massey University

This thesis is presented in a form of a report on a comparative documentary survey of secondary social science teacher training in Papua New Guinea and secondary social studies teacher training in New Zealand. But because of the complexity of the field, the study has encompassed a number of related areas. The thesis is organized into five chapters. Chapter one introduces the nature of study. Chapter two presents the descriptive information on education and the secondary social science teacher training in Papua New Guinea. Chapter three follows a similar pattern to chapter one but focuses on New Zealand and on secondary social studies teacher training at Auckland in particular. Taken together, these chapters investigate such issues as, firstly, who goes to school and for how long. Secondly, they investigate the background information of the staff and students of the teachers college. Thirdly, these chapters examine the college curricula, how and why they are organized in that manner. In general, these two chapters set the scene and provide the background information as the basis for discussion in chapter four. In chapter four there is an analysis and comparison of education and social science teacher training in Papua New Guinea, and education and social studies teacher training in New Zealand. In doing so, the chapter reveals some of the significant weaknesses of secondary social science teacher training in Papua New Guinea. The final chapter is devoted to making general conclusions and some suggestions for further studies for Papua New Guinea on the basis of the weaknesses identified in chapter four

Local and Global Explanations of Agent Behavior: Integrating Strategy Summaries with Saliency Maps

With advances in reinforcement learning (RL), agents are now being developed in high-stakes application domains such as healthcare and transportation. Explaining the behavior of these agents is challenging, as the environments in which they act have large state spaces, and their decision-making can be affected by delayed rewards, making it difficult to analyze their behavior. To address this problem, several approaches have been developed. Some approaches attempt to convey the $\textit{global}$ behavior of the agent, describing the actions it takes in different states. Other approaches devised $\textit{local}$ explanations which provide information regarding the agent's decision-making in a particular state. In this paper, we combine global and local explanation methods, and evaluate their joint and separate contributions, providing (to the best of our knowledge) the first user study of combined local and global explanations for RL agents. Specifically, we augment strategy summaries that extract important trajectories of states from simulations of the agent with saliency maps which show what information the agent attends to. Our results show that the choice of what states to include in the summary (global information) strongly affects people's understanding of agents: participants shown summaries that included important states significantly outperformed participants who were presented with agent behavior in a randomly set of chosen world-states. We find mixed results with respect to augmenting demonstrations with saliency maps (local information), as the addition of saliency maps did not significantly improve performance in most cases. However, we do find some evidence that saliency maps can help users better understand what information the agent relies on in its decision making, suggesting avenues for future work that can further improve explanations of RL agents

Wissensbasierte Informationspräsentation : zwei Beiträge zum Fachgespräch Graphik und KI. - 1. Ein planbasierter Ansatz zur Synthese illustrierter Dokumente. - 2. Wissensbasierte Perspektivenwahl für die automatische Erzeugung von 3D-Objektdarstellungen

Teil 1: Obwohl die Erzeugung multimodaler Dokumente in der KI-Forschung zunehmendes Interesse findet, werden in den meisten Systemen Text- und Graphik weitgehend unabhängig voneinander aufgebaut und stehen daher beziehungslos nebeneinander. In dieser Arbeit wird von der Überlegung ausgegangen, daß nicht nur die Erzeugung von Texten, sondern auch die Erzeugung multimodaler Dokumente als kommunikative Handlung zur Erreichung von Zielen aufgefaßt werden kann. Für die Realisierung eines Systems, das selbstständig illustrierte Dokumente erstellt, bietet sich daher ein planbasierter Ansatz an. Es wird zunächst gezeigt, daß die in der Textlinguistik gebräuchliche Unterscheidung zwischen Haupt- und Nebenhandlungen auch für Text-Bild-Kombinationen geeignet ist. Von dieser Unterscheidung ausgehend werden Strategien formuliert, die sich sowohl auf die Erzeugung von Text als auch auf den Aufbau von Bildern beziehen. Die gemeinsame Planung von Text und Bild wird als grundlegende Voraussetzung angesehen, die beiden Modi in einem Dokument aufeinander abzustimmen. Teil 2: Aus welcher Perspektive ein Objekt gezeigt werden soll, ist eine der elementaren Fragen, die sich bei der automatischen Erzeugung von 3D-Darstellungen stellt, die aber in den wenigen Systemen, die graphische Objektdarstellungen selbstständig planen, bisher vernachlässigt wurde. Ziel der vorliegenden Arbeit ist es, aufzuzeigen, wie sich Wissen über Objekte und Darstellungstechniken verwenden läßt, um die Menge der möglichen Perspektiven, aus denen ein Objekt gesehen und gezeigt werden kann, sinnvoll einzuschränken. Als Grundlage zur Perspektivenwahl schlagen wir ein Bezugssystem vor, das eine Einteilung der Perspektiven in 26 Klassen nahelegt und das darüberhinaus Vorteile bietet, wenn gewählte Perspektiven natürlichsprachlich zu beschreiben sind. Anschließend führen wir einige für die Perspektivenwahl relevante Kriterien an. Diese Kriterien werden dann zur Formulierung von Regeln herangezogen, die wir dazu verwenden, um in einer konkreten Präsentationssituation eine geeignete Perspektive zu bestimmen

Knowledge-based best of breed approach for automated detection of clinical events based on German free text digital hospital discharge letters

OBJECTIVES: The secondary use of medical data contained in electronic medical records, such as hospital discharge letters, is a valuable resource for the improvement of clinical care (e.g. in terms of medication safety) or for research purposes. However, the automated processing and analysis of medical free text still poses a huge challenge to available natural language processing (NLP) systems. The aim of this study was to implement a knowledge-based best of breed approach, combining a terminology server with integrated ontology, a NLP pipeline and a rules engine. METHODS: We tested the performance of this approach in a use case. The clinical event of interest was the particular drug-disease interaction "proton-pump inhibitor [PPI] use and osteoporosis". Cases were to be identified based on free text digital discharge letters as source of information. Automated detection was validated against a gold standard. RESULTS: Precision of recognition of osteoporosis was 94.19%, and recall was 97.45%. PPIs were detected with 100% precision and 97.97% recall. The F-score for the detection of the given drug-disease-interaction was 96,13%. CONCLUSION: We could show that our approach of combining a NLP pipeline, a terminology server, and a rules engine for the purpose of automated detection of clinical events such as drug-disease interactions from free text digital hospital discharge letters was effective. There is huge potential for the implementation in clinical and research contexts, as this approach enables analyses of very high numbers of medical free text documents within a short time period

Deciding when to react to incremental user input in human-robot interaction

Abstract -  GCG implementation was believed will help companies and countries which were in a cricis condition rising towards to a better conditions, competitive and restore the investor confidences. Therefore, the improvement of GCG implementation in Indonesia, especially for Publicly Listed Companies became main priority because it was one of the companies’ key to successful growth as well as giving long term benefits for the companies to win the bussiness competition. Many efforts were made to improve awareness of all parties about the importance of GCG implementation in Indonesia, as well as IDX which always try to improve GCG implementation of Listed Companies.This research was done to find out the impact of GCG implementation to the market performance of the companies which listed in IDX. GCG implementation will be proxied by the value of Corporate Governance Perception Index (CGPI). While company’s market performance will be proxied by PBV ratio. Besides, this research also try to find out the impact of fundamental factors, such as ROE, ROA, DER, growth and firm size to PBV. It was done to know what should be done by IDX to improve GCG implementation of the Listed Companies. This research uses multiple regression model in SPSS to test the correlation of GCG implementation, fundamental factors and company’s market performance. The samples are companies which listed in IDX from 2010-2013, have complete financial datas, and have CGPI value which released by The Indonesia Institute of Corporate Governance (IICG) from 2010-2013. The result shows that only ROE and DER variables which have significant impact to PBV at the level of significance (α) 10%. While CGPI, ROA, growth and firm size variables do not have significant impact to PBV. Those  results show that the benefit of GCG implementation to create added value to the stakeholders is still can be reflected well yet in Indonesia because of the variation of the GCG implementation that caused by the lack of strict legal rules regarding to the GCG implementation and also lack of awareness about the need of GCG implementation. Hence, IDX as one of the regulator in Indonesian Capital Market is expected to have a strict rule regarding to GCG implementation of Listed Companies and able to improve the awareness of Listed Companies, investors, and all parties in Indonesian Capital Market about the importance of GCG implementation through educational programs, seminars, and the other forms of coaching as well as incentive and reward programs. The budget to implement those plans could use budget of routine activities as well as budget specialized for workshop or seminar activities in IDX. Keywords: Good Corporate Governance (GCG), Corporate Governance Perception Index (CGPI), ROE, DER, Multiple Regression , Bursa Efek Indonesia (IDX)