Industrial land price and its impact on urban growth : a Chinese case study

China is experiencing rapid progress in industrialization, with its own rationale toward industrial land development based on a deliberate change from an extensive to intensive form of urban land use. One result has been concerted attempts by local government to attract foreign investment by a low industrial land price strategy, which has resulted in a disproportionally large amount of industrial land within the total urban land use structure at the expense of the urban sprawl of many cities. This paper first examines “Comparable Benchmark Price as Residential land use” (CBPR) as the theoretical basis of the low industrial land price phenomenon. Empirical findings are presented from a case study based on data from Jinyun County, China. These data are analyzed to reveal the rationale of industrial land price from 2000 to 2010 concerning the CBPR model. We then explore the causes of low industrial land prices in the form of a “Centipede Game Model”, involving two neighborhood regions as “major players” to make a set of moves (or strategies). When one of the players unilaterally reduces the land price to attract investment with the aim to maximize profits arising from the revenues generated from foreign investment and land premiums, a two-player price war begins in the form of a dynamic game, the effect of which is to produce a downward spiral of prices. In this context, the paradox of maximizing profits for each of the two players are not accomplished due to the inter-regional competition of attracted investment leading to a lose-lose situation for both sides’ in competing for land premium revenues. A short-term solution to the problem is offered involving the establishment of inter-regional cooperative partnerships. For the longer term, however, a comprehensive reform of the local financial system, more adroit regional planning and an improved means of evaluating government performance is needed to ensure the government's role in securing pubic goods is not abandoned in favor of one solely concerned with revenue generation.

High frequency high power converters for industrial applications

The main contribution of this project was to investigate power electronics technology in designing and developing high frequency high power converters for industrial applications. Therefore, the research was conducted at two levels; first at system level which mainly encapsulated the circuit topology and control scheme and second at application level which involves with real-world applications. Pursuing these objectives, varied topologies have been developed and proposed within this research. The main aim was to resolving solid-state switches limited power rating and operating speed while increasing the system flexibility considering the application characteristics. The developed new power converter configurations were applied to pulsed power and high power ultrasound applications for experimental validation.

Robots for environmental monitoring : significant advancements and applications

Robotic systems are increasingly being utilised as fundamental data-gathering tools by scientists, allowing new perspectives and a greater understanding of the planet and its environmental processes. Today's robots are already exploring our deep oceans, tracking harmful algal blooms and pollution spread, monitoring climate variables, and even studying remote volcanoes. This article collates and discusses the significant advancements and applications of marine, terrestrial, and airborne robotic systems developed for environmental monitoring during the last two decades. Emerging research trends for achieving large-scale environmental monitoring are also reviewed, including cooperative robotic teams, robot and wireless sensor network (WSN) interaction, adaptive sampling and model-aided path planning. These trends offer efficient and precise measurement of environmental processes at unprecedented scales that will push the frontiers of robotic and natural sciences.

Experiments with cooperative control of underwater robots

In this paper we describe cooperative control algorithms for robots and sensor nodes in an underwater environment. Cooperative navigation is defined as the ability of a coupled system of autonomous robots to pool their resources to achieve long-distance navigation and a larger controllability space. Other types of useful cooperation in underwater environments include: exchange of information such as data download and retasking; cooperative localization and tracking; and physical connection (docking) for tasks such as deployment of underwater sensor networks, collection of nodes and rescue of damaged robots. We present experimental results obtained with an underwater system that consists of two very different robots and a number of sensor network modules. We present the hardware and software architecture of this underwater system. We then describe various interactions between the robots and sensor nodes and between the two robots, including cooperative navigation. Finally, we describe our experiments with this underwater system and present data.

Purification of particles of subterranean clover red leaf virus using an industrial-grade cellulase

Particles of two isolates of subterranean clover red leaf virus were purified by a method in which infected plant tissue was digested with an industrial-grade cellulase, Celluclast® 2.0 L type X. The yields of virus particles using this enzyme were comparable with those obtained using either of two laboratory-grade cellulases, Cellulase type 1 (Sigma) and Driselase®. However, the specific infectivity or aphid transmissibility of the particles purified using Celluclast® was 10-100 times greater than those of preparations obtained using laboratory-grade cellulases or no enzyme. The main advantage of using Celluclast® is that at present in Australia its cost is only ca. 1% of laboratory-grade cellulases.

Brain-inspired sensor fusion for navigating robots

Current state of the art robot mapping and navigation systems produce impressive performance under a narrow range of robot platform, sensor and environmental conditions, in contrast to animals such as rats that produce “good enough” maps that enable them to function under an incredible range of situations. In this paper we present a rat-inspired featureless sensor-fusion system that assesses the usefulness of multiple sensor modalities based on their utility and coherence for place recognition, without knowledge as to the type of sensor. We demonstrate the system on a Pioneer robot in indoor and outdoor environments with abrupt lighting changes. Through dynamic weighting of the sensors, the system is able to perform correct place recognition and mapping where the static sensor weighting approach fails.

Supermarkets and agro-industrial foods : the strategic manufacturing of consumer trust

There is increasing evidence of a weakened platform of consumer trust in mass produced food products. The resistance shown by consumers to the agro-industrial paradigm is evident in an emergent phase of reflexive consumerism, public reactions to an overly-concentrated retail sector and the rise of alternative food networks such as farmers' markets and organic box schemes. Supermarkets are responding strategically by aiming to manufacture new trust relations with consumers. This paper identifies three key strategies of trust manufacturing: (i) reputational enhancement though the institution of “behind the scenes,” business-to-business private standards; (ii) direct quality claims via private standard certification badges on food products, and ; (iii) discursive claimsmaking through symbolic representations of “authenticity” and “tradition.” Drawing upon the food governance literature and a “visual sociology” of supermarkets and supermarket produce, we highlight how trust is both commoditized and increasingly embedded into the marketing of mass-produced foods.

Provotypes: Teasing out tensions between industrial context and use context

What industrial organisations think people do and what they actually do are often two very different things. But exactly this tension can be a source of innovation: how can we give form to insights about what people do, to deliberately challenge industries' conceptions, and inspire new product and service development

Ethnography of software maintenance activities in an industrial engineering setup

New technical and procedural interventions are less likely to be adopted in industry, unless they are smoothly integrated into the existing practices of professionals. In this paper, we provide a case study of the use of ethnographic methods for studying software bug-fixing activities at an industrial engineering conglomerate. We aimed at getting an in-depth understanding of software developers' everyday practices in bug-fixing related projects and in turn inform the design of novel productivity tools. The use of ethnography has allowed us to look at the social side of software maintenance practices. In this paper, we highlight: 1) organizational issues that influence bug-fixing activities; 2) social role of bug tracking systems, and; 3) social issues specific to different phases of bug-fixing activities.

Numerical investigation of mechanical and thermal dynamic properties of the industrial transformer

Industrial transformer is one of the most critical assets in the power and heavy industry. Failures of transformers can cause enormous losses. The poor joints of the electrical circuit on transformers can cause overheating and results in stress concentration on the structure which is the major cause of catastrophic failure. Few researches have been focused on the mechanical properties of industrial transformers under overheating thermal conditions. In this paper, both mechanical and thermal properties of industrial transformers are jointly investigated using Finite Element Analysis (FEA). Dynamic response analysis is conducted on a modified transformer FEA model, and the computational results are compared with experimental results from literature to validate this simulation model. Based on the FEA model, thermal stress is calculated under different temperature conditions. These analysis results can provide insights to the understanding of the failure of transformers due to overheating, therefore are significant to assess winding fault, especially to the manufacturing and maintenance of large transformers.

Developing grounded representations for robots through the principles of sensorimotor coordination

Robots currently recognise and use objects through algorithms that are hand-coded or specifically trained. Such robots can operate in known, structured environments but cannot learn to recognise or use novel objects as they appear. This thesis demonstrates that a robot can develop meaningful object representations by learning the fundamental relationship between action and change in sensory state; the robot learns sensorimotor coordination. Methods based on Markov Decision Processes are experimentally validated on a mobile robot capable of gripping objects, and it is found that object recognition and manipulation can be learnt as an emergent property of sensorimotor coordination.

Preventing industrial scale using bauxite refinery residues

An Australian green power (AGP) company produces energy from burning biomass from the sugar industry and recycled wood waste, however alkali in biomass is released into a recirculating stream that forms a scale as it becomes more concentrated. This investigation has shown that the addition of Bayer liquor (alumina waste residue) successfully removes scale-forming species from the recirculating stream and thus has the potential to reduce the rate of scaling. Characterisation of the scale and Bayer precipitates has been performed using X-ray diffraction (XRD), infrared spectroscopy (IR) and inductively coupled plasma optical emission spectroscopy (ICP-OES).

A sparse hybrid map for vision-guided mobile robots

This paper introduces a minimalistic approach to produce a visual hybrid map of a mobile robot’s working environment. The proposed system uses omnidirectional images along with odometry information to build an initial dense posegraph map. Then a two level hybrid map is extracted from the dense graph. The hybrid map consists of global and local levels. The global level contains a sparse topological map extracted from the initial graph using a dual clustering approach. The local level contains a spherical view stored at each node of the global level. The spherical views provide both an appearance signature for the nodes, which the robot uses to localize itself in the environment, and heading information when the robot uses the map for visual navigation. In order to show the usefulness of the map, an experiment was conducted where the map was used for multiple visual navigation tasks inside an office workplace.

Long-term exploration and tours for energy constrained robots with online proprioceptive traversability estimation

This paper is concerned with how a localised and energy-constrained robot can maximise its time in the field by taking paths and tours that minimise its energy expenditure. A significant component of a robot's energy is expended on mobility and is a function of terrain traversability. We estimate traversability online from data sensed by the robot as it moves, and use this to generate maps, explore and ultimately converge on minimum energy tours of the environment. We provide results of detailed simulations and parameter studies that show the efficacy of this approach for a robot moving over terrain with unknown traversability as well as a number of a priori unknown hard obstacles.

Global reconfiguration of a team of networked mobile robots among obstacles

This paper presents a full system demonstration of dynamic sensorbased reconfiguration of a networked robot team. Robots sense obstacles in their environment locally and dynamically adapt their global geometric configuration to conform to an abstract goal shape. We present a novel two-layer planning and control algorithm for team reconfiguration that is decentralised and assumes local (neighbour-to-neighbour) communication only. The approach is designed to be resource-efficient and we show experiments using a team of nine mobile robots with modest computation, communication, and sensing. The robots use acoustic beacons for localisation and can sense obstacles in their local neighbourhood using IR sensors. Our results demonstrate globally-specified reconfiguration from local information in a real robot network, and highlight limitations of standard mesh networks in implementing decentralised algorithms.