Modelling regular and estimable inverse demand systems : a distance function approach

To be useful for policy simulation in the current climate of rapid structural change, inverse demand systems must remain regular over substanstial variations in quantities. The distance function is a convenient vehicle for generating such systems. It also allows convenient imposition of prior ideas about the structure of preferences required for realistic policy work. While the distance function directly yields Hicksian inverse demand functions via the Shepard-Hanoch lemma, they are usually explicit in the unobservable level of utility (u), but lack a closed-form representation in terms of the observable variables. Note however that the unobservability of u need not hinder estimation. A simple one-dimensional numerical inversion allows the estimation of the distance function via the parameters of the implied Marshallian inverse demand functions. This paper develops the formal theory for using distance functions in this context, and reports on initial trials on the operational feasibility of the method.

Input usage, output mix and industry deregulation: an analysis of the Australian dairy manufacturing industry

In this paper we estimate a Translog output distance function for a balanced panel of state level data for the Australian dairy processing sector. We estimate a fixed effects specification employing Bayesian methods, with and without the imposition of monotonicity and curvature restrictions. Our results indicate that Tasmania and Victoria are the most technically efficient states with New South Wales being the least efficient. The imposition of theoretical restrictions marginally affects the results especially with respect to estimates of technical change and industry deregulation. Importantly, our bias estimates show changes in both input use and output mix that result from deregulation. Specifically, we find that deregulation has positively biased the production of butter, cheese and powders.

A grid-based index method for time warping distance

Recently DTW (dynamic time warping) has been recognized as the most robust distance function to measure the similarity between two time series, and this fact has spawned a flurry of research on this topic. Most indexing methods proposed for DTW are based on the R-tree structure. Because of high dimensionality and loose lower bounds for time warping distance, the pruning power of these tree structures are quite weak, resulting in inefficient search. In this paper, we propose a dimensionality reduction method motivated by observations about the inherent character of each time series. A very compact index file is constructed. By scanning the index file, we can get a very small candidate set, so that the number of page access is dramatically reduced. We demonstrate the effectiveness of our approach on real and synthetic datasets.

Learning sparse latent representation and distance metric for image retrieval

The performance of image retrieval depends critically on the semantic representation and the distance function used to estimate the similarity of two images. A good representation should integrate multiple visual and textual (e.g., tag) features and offer a step closer to the true semantics of interest (e.g., concepts). As the distance function operates on the representation, they are interdependent, and thus should be addressed at the same time. We propose a probabilistic solution to learn both the representation from multiple feature types and modalities and the distance metric from data. The learning is regularised so that the learned representation and information-theoretic metric will (i) preserve the regularities of the visual/textual spaces, (ii) enhance structured sparsity, (iii) encourage small intra-concept distances, and (iv) keep inter-concept images separated. We demonstrate the capacity of our method on the NUS-WIDE data. For the well-studied 13 animal subset, our method outperforms state-of-the-art rivals. On the subset of single-concept images, we gain 79:5% improvement over the standard nearest neighbours approach on the MAP score, and 45.7% on the NDCG.

Energy productivity and total-factor productivity in the Australian construction industry

There is urgent need to consider energy consumption when measuring total-factor productivity in the construction industry. This paper adopts the Malmquist index method to investigate the factors affecting the energy productivity of the Australian construction industry and compares them with those decomposed from the total-factor productivity. An input-oriented distance function and a contemporaneous benchmark technology are employed to develop the data envelopment analysis models. The Malmquist productivity index is decomposed into the technological change, pure technical efficiency change and activity effect to gain comprehensive insights into changes of construction productivity in the Australian states and territories over the past two decades. Research results show that both energy productivity and total-factor productivity improved in Australia, particularly related to technological development. The pure technical efficiency and activity indices changed slightly over time or across regions. This study demonstrates that there exists a linkage between energy productivity and total-factor productivity through their technological and technical efficiency changes. The Australian construction industry could enhance these two productivities by introducing advanced technologies and implementing them efficiently.

Geometry and combinatorics of the cutting angle method

Lower approximation of Lipschitz functions plays an important role in deterministic global optimization. This article examines in detail the lower piecewise linear approximation which arises in the cutting angle method. All its local minima can be explicitly enumerated, and a special data structure was designed to process them very efficiently, improving previous results by several orders of magnitude. Further, some geometrical properties of the lower approximation have been studied, and regions on which this function is linear have been identified explicitly. Connection to a special distance function and Voronoi diagrams was established. An application of these results is a black-box multivariate random number generator, based on acceptance-rejection approach.

M-Dimension : multi-characteristics based routing protocol in human associated delay-tolerant networks with improved performance over one dimensional classic models

Human associated delay-tolerant network (HDTN) is a new delay-tolerant network where mobile devices are associated with humans. It can be viewed from both their geographic and social dimensions. The combination of these different dimensions can enable us to more accurately comprehend a delay-tolerant network and consequently use this multi-dimensional information to improve overall network efficiency. Alongside the geographic dimension of the network which is concerned with geographic topology of routing, social dimensions such as social hierarchy can be used to guide the routing message to improve not only the routing efficiency for individual nodes, but also efficiency for the entire network.

We propose a multi-dimensional routing protocol (M-Dimension) for the human associated delay-tolerant network which uses the local information derived from multiple dimensions to identify a mobile node more accurately. Each dimension has a weight factor and is organized by the Distance Function to select an intermediary and applies multi-cast routing. We compare M-Dimension to existing benchmark routing protocols using the MIT Reality Dataset, a well-known benchmark dataset based on a human associated mobile network trace file. The results of our simulations show that M-Dimension has a significant increase in the average success ratio and is very competitive when End-to-End Delay of packet delivery is used in comparison to other multi-cast DTN routing protocols.

Faster and parameter-free discord search in quasi-periodic time series

Time series discord has proven to be a useful concept for time-series anomaly identification. To search for discords, various algorithms have been developed. Most of these algorithms rely on pre-building an index (such as a trie) for subsequences. Users of these algorithms are typically required to choose optimal values for word-length and/or alphabet-size parameters of the index, which are not intuitive. In this paper, we propose an algorithm to directly search for the top-K discords, without the requirement of building an index or tuning external parameters. The algorithm exploits quasi-periodicity present in many time series. For quasi-periodic time series, the algorithm gains significant speedup by reducing the number of calls to the distance function.

Bone density and neuromuscular function in older competitive athletes depend on running distance

UNLABELLED: Individuals who are involved in explosive sport types, such as 100-m sprints and long jump, have greater bone density, leg muscle size, jumping height and grip strength than individuals involved in long-distance running. INTRODUCTION: The purpose of this study is to examine the relationship between different types of physical activity with bone, lean mass and neuromuscular performance in older individuals. METHODS: We examined short- (n = 50), middle- (n = 19) and long-distance (n = 109) athletes at the 15th European Masters Championships in Poznań, Poland. Dual X-ray absorptiometry was used to measure areal bone mineral density (aBMD) and lean tissue mass. Maximal countermovement jump, multiple one-leg hopping and maximal grip force tests were performed. RESULTS: Short-distance athletes showed significantly higher aBMD at the legs, hip, lumbar spine and trunk compared to long-distance athletes (p ≤ 0.0012). Countermovement jump performance, hop force, grip force, leg lean mass and arm lean mass were greater in short-distance athletes (p ≤ 0.027). A similar pattern was seen in middle-distance athletes who typically showed higher aBMD and better neuromuscular performance than long-distance athletes, but lower in magnitude than short-distance athletes. In all athletes, aBMD was the same or higher than the expected age-adjusted population mean at the lumbar spine, hip and whole body. This effect was greater in the short- and middle-distance athletes. CONCLUSIONS: The stepwise relation between short-, middle- and long-distance athletes on bone suggests that the higher-impact loading protocols in short-distance disciplines are more effective in promoting aBMD. The regional effect on bone, with the differences between the groups being most marked at load-bearing regions (legs, hip, spine and trunk) rather than non-load-bearing regions, is further evidence in support of the idea that bone adaptation to exercise is dependent upon the local loading environment, rather than as part of a systemic effect.

The use of home experimentation kits for distance students in first-year undergraduate electronics

Laboratory and practical classes are an important part of the education of students in electronics and electrical engineering. "Hands-on" experience is critical for any engineer working in these fields in particular. For many years, delivering engineering practicals to distance-education students has been a tremendous challenge for universities. For a number of years now, students enrolled in the common first-year electronics course by distance mode at Deakin University have received a home experimentation kit. Using the kit and a laboratory manual, students are required to complete a number of experiments based on components included in the kit. The kit supports a full range of practical activities for digital electronics, and a more limited range of activities for analog electronics. With the kit, off campus students are supplied software for simulating AC electronic circuits, such as amplifiers and rectifiers. In this report we examine the past use of this kit and software,
review anecdotal student experiences with the package, and propose changes to it and to other curriculum resources, aiming to enhance the use of the kit by distance students. Key curriculum resources planned are a web-based 'companion' for the components in and the use of the kit, and two additions to the kit itself: a battery powered function generator, and a PC-based oscilloscope.

State and input simultaneous estimation for a class of nonlinear systems

This paper addresses the problem of estimating simultaneously the state and input of a class of nonlinear systems. Here, the systems nonlinear part comprises a Lipschitz nonlinear function with respect to the state and input, and a state-dependent unknown function including additive disturbance as well as uncertain/nonlinear/time-varying terms. Upon satisfying some conditions, the observer design problem can be solved via a Riccati inequality or a LMI-based technique with asymptotic estimation guaranteed. A numerical example is included for illustration.

Simultaneous state and input estimation with application to a two-link robotic system

This paper addresses the problem of estimating simultaneously the state and input of a nonlinear system with application to a two link robotic manipulator - the Pendubot. The system nonlinearity comprises a Lipschitz function with respect to the state, and a nonlinear term which is a function of both the state and input. It is shown that under some conditions, an observer can be designed to estimate simultaneously the system’s state and input. Simulation and experimental results, obtained around the inverted equilibrium position, are presented to demonstrate the validity of the approach.

Design of reduced-order state/unknown input observers: a descriptor system approach

This paper addresses the problem of estimating simultaneously a linear function of both the state and unknown input of linear system with unknown inputs. By adopting the descriptor system approach, the problem can be conveniently solved. Observers proposed in this paper are of low-order and do not include the derivatives of the outputs. New conditions for the existence of reduced-order observers are derived. A design procedure for the determination of the observer parameters can also be easily derived based on the derived existence conditions

The impact of information and communications technology on teaching and design of flexible, online and distance education courses at Deakin University

This paper describes the use of an online learning environment which has been established for postgraduate students studying at Master’s level in Professional Education and Training Deakin University. A detailed evaluation of the use of computer conferences in an Open and Distance Education specialism was undertaken during 2000 as part of a CUTSD funded project, Learner Centred Evaluation of Computer Facilitated Learning Projects in Higher Education. As the Open and Distance Education specialism is being revised and new units are written, the information gathered in this evaluation is being integrated into the pedagogical planning and the technological decisions being made about the design of the new master’s program.
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