Malay Kingship in Kedah : Religion, Trade, and Society

The book probes and examines traditional sources of royal power and control, as well as indigenous socio-political systems in the Malay world. It is focused on the north-western Malaysian Sultanate of Kedah which is acknowledged as the oldest unbroken independent kingship line in the ‘Malay and Islamic world’ with 1,000 years of history. Little scholarly attention has been paid to its pre-modern history, society, religion, system of government and unique geographic situation, potentially controlling both land and sea lines of communication into the remainder of Southeast Asia. It will thus provide the first comprehensive treatment in English, or other languages, on Kedah’s pre-modern and nineteenth century historiography and can provide a foundation for comparative studies of the various Malay states which is presently lacking. The proposed book also sheds much needed light on a range of important topics in Malay history including: Kedah and the northern Melaka Straits history, colonial expansion and rivalry, Southeast Asian history and politics, interregional migration and the influence of the sea peoples or orang laut, traditional Malay socio-political and economic life, Islamic influences and the course of Thai-Malay relations. The book attempts to offer a new understanding, not only of Kedah, but of the political and cultural development of the entire Malay world and of its relationships with the broader forces in both its continental and maritime settings. It argues that Kedah does not seem to follow, and in fact, often seems to contradict what has been commonly been accepted as the “typical model” of the traditional Malay state. Thus it concludes that the ruling dynasty has historically exploited a wide range of unique environmental conditions, local traditions, global spiritual trends and economic forces to preserve and strengthen its political position. The scope and theme of book The Kedah Sultanate is the oldest unbroken independent kingship lines in the “Malay world” with 1,000 years of history, and arguably one of the oldest in the Islamic world. In this study I examine key geopolitical and spiritual attributes of Malay kingship that have traditionally cemented the ruler, the peoples, and the environment. Brief description of the primary audience for the book: There is little written in English or Malay on Kedah’s pre twentieth century history. The available sources only look at certain aspects of Kedah’s history, are outdated or are confined to a specific period often outside the scope of the book. It is therefore anticipated that the readership and market for the book includes: • Scholars of Southeast Asian history, Islam, kingship, trade. • Academics & Historians (including: Asian, Thai history, Islamic, Maritime, Persian, South Asian, Southeast Asian and Colonial) • Libraries • Students, particularly those in Malaysia (especially the states of Kedah, Perlis and Penang), Thailand and Singapore. • Universities • Scholars and students in Political Science & International Relations

State cycles, initialization and the Trivium stream cipher

Trivium is a keystream generator for a binary additive synchronous stream cipher. It was selected in the final portfolio for the Profile 2 category of the eSTREAM project. The keystream generator is constructed using bit- based shift registers. In this paper we present an alternate representation of Trivium using word-based shift registers, with a word size of three bits. This representation is useful for determining cycles of internal state values. Under this representation it is clear that the state space can be partitioned into subspaces and that over some of these subspaces the state update function is effectively linear. The role of the initialization process is critical in ensuring the states used for generating keystream are updated nonlinearly at some point, as the state update function alone does not provide this.

Maintenance optimisation of a multi-state series-parallel system considering economic dependence and state-dependent inspection intervals

This paper presents a maintenance optimisation method for a multi-state series-parallel system considering economic dependence and state-dependent inspection intervals. The objective function considered in the paper is the average revenue per unit time calculated based on the semi-regenerative theory and the universal generating function (UGF). A new algorithm using the stochastic ordering is also developed in this paper to reduce the search space of maintenance strategies and to enhance the efficiency of optimisation algorithms. A numerical simulation is presented in the study to evaluate the efficiency of the proposed maintenance strategy and optimisation algorithms. The simulation result reveals that maintenance strategies with opportunistic maintenance and state-dependent inspection intervals are more cost-effective when the influence of economic dependence and inspection cost is significant. The study further demonstrates that the optimisation algorithm proposed in this paper has higher computational efficiency than the commonly employed heuristic algorithms.

Evaluation of implementation of a healthy food and drink supply strategy throughout the whole school environment in Queensland state schools, Australia

BACKGROUND/OBJECTIVES: This paper reports on the evaluation of the Smart Choices healthy food and drink supply strategy for Queensland schools (Smart Choices) implementation across the whole school environment in state government primary and secondary schools in Queensland, Australia. SUBJECTS/METHODS: Three concurrent surveys using different methods for each group of stakeholders that targeted all 1275 school Principals, all 1258 Parent and Citizens’ Associations (P&Cs) and a random sample of 526 tuckshop convenors throughout Queensland. Nine hundred and seventy-three Principals, 598 P&Cs and 513 tuckshop convenors participated with response rates of 78%, 48% and 98%, respectively. RESULTS: Nearly all Principals (97%), P&Cs (99%) and tuckshop convenors (97%) reported that their school tuckshop had implemented Smart Choices. The majority of Principals and P&Cs reported implementation, respectively, in: school breakfast programs (98 and 92%); vending machine stock (94 and 83%); vending machine advertising (85 and 84%); school events (87 and 88%); school sporting events (81 and 80%); sponsorship and advertising (93 and 84%); fundraising events (80 and 84%); and sporting clubs (73 and 75%). Implementation in curriculum activities, classroom rewards and class parties was reported, respectively, by 97%, 86% and 75% of Principals. Respondents also reported very high levels of understanding of Smart Choices and engagement of the school community. CONCLUSIONS: The results demonstrated that food supply interventions to promote nutrition across all domains of the school environment can be implemented successfully.

Briefing paper on eTextbooks and third party eLearning products and their implications for Australian university libraries

The briefing paper was commissioned by the Council of Australian University Librarians (CAUL) to examine the current picture and evolving role of electronic textbooks (eTextbooks) and third party eLearning products in the academic arena. The study reviews industry trends, identifies the major players and considers the different stakeholder perspectives of eTextbook adoption. Within the context of learning and teaching in the digital age, specific areas of research, policy and practice are highlighted to consider the implications that eTextbooks might have for universities in general and for university libraries in particular. An environmental scan focused on the analysis of current developments and the anticipated future directions of digital learning resources in Australia, as well as in other major English speaking countries such as the United Kingdom and the United States. This research guided the development of key interview questions aimed at examining, at a deeper level, diverse stakeholder perspectives about the roles university libraries can play in the adoption of digital learning content.

The exemplification of governance principles within state asset management laws and policies : the case of Indonesia

This chapter reviews aspects of the challenge of reviewing and reforming Indonesian practice within state asset management law and policy specifically related to public housing, public buildings, parklands, and vacant land. A critical issue in beginning this review is how Indonesia currently conceptualizes the notion of asset governance and how this meaning is embodied in recent changes in law and policy and importantly in options for future change. This chapter discusses the potential complexities uniquely Indonesian characteristics such as decentralisation and regional autonomy regime, political history, and bureaucratic culture.

Dynamic equivalent state estimation for multi-area power systems with synchronized phasor measurement units

This paper proposes a new approach for state estimation of angles and frequencies of equivalent areas in large power systems with synchronized phasor measurement units. Defining coherent generators and their correspondent areas, generators are aggregated and system reduction is performed in each area of inter-connected power systems. The structure of the reduced system is obtained based on the characteristics of the reduced linear model and measurement data to form the non-linear model of the reduced system. Then a Kalman estimator is designed for the reduced system to provide an equivalent dynamic system state estimation using the synchronized phasor measurement data. The method is simulated on two test systems to evaluate the feasibility of the proposed method.

Non-invasive identification of proteoglycans and chondrocyte differentiation state by Raman microspectroscopy

Proteoglycans (PGs) are crucial extracellular matrix (ECM) components that are present in all tissues and organs. Pathological remodeling of these macromolecules can lead to severe diseases such as osteoarthritis or rheumatoid arthritis. To date, PG-associated ECM alterations are routinely diagnosed by invasive analytical methods. Here, we employed Raman microspectroscopy, a laser-based, marker-free and non-destructive technique that allows the generation of spectra with peaks originating from molecular vibrations within a sample, to identify specific Raman bands that can be assigned to PGs within human and porcine cartilage samples and chondrocytes. Based on the non-invasively acquired Raman spectra, we further revealed that a prolonged in vitro culture leads to phenotypic alterations of chondrocytes, resulting in a decreased PG synthesis rate and loss of lipid contents. Our results are the first to demonstrate the applicability of Raman microspectroscopy as an analytical and potential diagnostic tool for non-invasive cell and tissue state monitoring of cartilage in biomedical research. ((c) 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim).

Blogging the 2009 Queensland State Election

The internet has become important in political communication in Australia. Using Habermas' ideal types, it is argued that political blogs can be viewed as public spheres that might provide scope for the expansion of deliberative democratic discussion. This hypothesis is explored through analysis of the group political blog Pineapple Party Time. It is evident that the bloggers and those who commented on their posts were highly knowledgeable about and interested in politics. Form an examination of these posts and the comments on them, Pineapple Party Time did act as a public sphere to some degree, and did provide for the deliberative discussion essential for a democracy, but it was largely restricted to Crikey readers. For a deliberative public sphere and democratic discussion to function to any extent, the public sphere must be open to all citizens, who need to have the access and knowledge to engage in deliberative discussion.

Anomalous event detection using a semi-two dimensional hidden Markov model

The rapid increase in the deployment of CCTV systems has led to a greater demand for algorithms that are able to process incoming video feeds. These algorithms are designed to extract information of interest for human operators. During the past several years, there has been a large effort to detect abnormal activities through computer vision techniques. Typically, the problem is formulated as a novelty detection task where the system is trained on normal data and is required to detect events which do not fit the learned `normal' model. Many researchers have tried various sets of features to train different learning models to detect abnormal behaviour in video footage. In this work we propose using a Semi-2D Hidden Markov Model (HMM) to model the normal activities of people. The outliers of the model with insufficient likelihood are identified as abnormal activities. Our Semi-2D HMM is designed to model both the temporal and spatial causalities of the crowd behaviour by assuming the current state of the Hidden Markov Model depends not only on the previous state in the temporal direction, but also on the previous states of the adjacent spatial locations. Two different HMMs are trained to model both the vertical and horizontal spatial causal information. Location features, flow features and optical flow textures are used as the features for the model. The proposed approach is evaluated using the publicly available UCSD datasets and we demonstrate improved performance compared to other state of the art methods.

Spatio temporal feature evaluation for action recognition

Spatio-Temporal interest points are the most popular feature representation in the field of action recognition. A variety of methods have been proposed to detect and describe local patches in video with several techniques reporting state of the art performance for action recognition. However, the reported results are obtained under different experimental settings with different datasets, making it difficult to compare the various approaches. As a result of this, we seek to comprehensively evaluate state of the art spatio- temporal features under a common evaluation framework with popular benchmark datasets (KTH, Weizmann) and more challenging datasets such as Hollywood2. The purpose of this work is to provide guidance for researchers, when selecting features for different applications with different environmental conditions. In this work we evaluate four popular descriptors (HOG, HOF, HOG/HOF, HOG3D) using a popular bag of visual features representation, and Support Vector Machines (SVM)for classification. Moreover, we provide an in-depth analysis of local feature descriptors and optimize the codebook sizes for different datasets with different descriptors. In this paper, we demonstrate that motion based features offer better performance than those that rely solely on spatial information, while features that combine both types of data are more consistent across a variety of conditions, but typically require a larger codebook for optimal performance.

Machine prognostics based on health state estimation using SVM

The ability to accurately predict the remaining useful life of machine components is critical for machine continuous operation, and can also improve productivity and enhance system safety. In condition-based maintenance (CBM), maintenance is performed based on information collected through condition monitoring and an assessment of the machine health. Effective diagnostics and prognostics are important aspects of CBM for maintenance engineers to schedule a repair and to acquire replacement components before the components actually fail. All machine components are subjected to degradation processes in real environments and they have certain failure characteristics which can be related to the operating conditions. This paper describes a technique for accurate assessment of the remnant life of machines based on health state probability estimation and involving historical knowledge embedded in the closed loop diagnostics and prognostics systems. The technique uses a Support Vector Machine (SVM) classifier as a tool for estimating health state probability of machine degradation, which can affect the accuracy of prediction. To validate the feasibility of the proposed model, real life historical data from bearings of High Pressure Liquefied Natural Gas (HP-LNG) pumps were analysed and used to obtain the optimal prediction of remaining useful life. The results obtained were very encouraging and showed that the proposed prognostic system based on health state probability estimation has the potential to be used as an estimation tool for remnant life prediction in industrial machinery.

How to design extended finite state machine test models in Java

This chapter is a tutorial that teaches you how to design extended finite state machine (EFSM) test models for a system that you want to test. EFSM models are more powerful and expressive than simple finite state machine (FSM) models, and are one of the most commonly used styles of models for model-based testing, especially for embedded systems. There are many languages and notations in use for writing EFSM models, but in this tutorial we write our EFSM models in the familiar Java programming language. To generate tests from these EFSM models we use ModelJUnit, which is an open-source tool that supports several stochastic test generation algorithms, and we also show how to write your own model-based testing tool. We show how EFSM models can be used for unit testing and system testing of embedded systems, and for offline testing as well as online testing.

Application of clustering technique to generating capacity state model for reliability evaluation

Capacity probability models of generating units are commonly used in many power system reliability studies, at hierarchical level one (HLI). Analytical modelling of a generating system with many units or generating units with many derated states in a system, can result in an extensive number of states in the capacity model. Limitations on available memory and computational time of present computer facilities can pose difficulties for assessment of such systems in many studies. A cluster procedure using the nearest centroid sorting method was used for IEEE-RTS load model. The application proved to be very effective in producing a highly similar model with substantially fewer states. This paper presents an extended application of the clustering method to include capacity probability representation. A series of sensitivity studies are illustrated using IEEE-RTS generating system and load models. The loss of load and energy expectations (LOLE, LOEE), are used as indicators to evaluate the application

A spectroscopic comparison of YBCO superconductors synthesised by solid-state and co-precipitation methods

Raman spectroscopy, X-ray diffraction (XRD), and scanning electron microscopy (SEM) have been used to compare samples of YBa2Cu3O7 (YBCO) synthesised by the solid-state method and a novel co-precipitation technique. XRD results indicate that YBCO prepared by these two methods are phase pure, however the Raman and SEM results show marked differences between these samples.