Migrating to a sustainable energy system : distributed generation and storage, fuel cells and hypercars

This paper examines a number of issues in sustainable energy generation and distribution, and explores avenues that are available for integration of our society’s energy supplies. In particular, the paper presents a way in which transport vehicle energy supplies could be integrated with distributed generation schemes to achieve synergistic and beneficial outcomes. The worldwide energy system contains fundamental problems that result directly from the use of unsustainable fuels and a lack of energy system integration. There is a need to adopt an integrated, sustainable energy system for our society. The adoption of distributed generation could result in beneficial restructuring of the energy trade, and a change in the role of energy providers. Inherent benefits in distributed generation schemes would directly combat barriers to installation of renewable generation facilities, which might prove distributed renewable energy sources to be more feasible. The presence of fuel cells, batteries, power electronic inverters and intelligent controls in vehicles of the future provides many opportunities for the integration of vehicle energy supplies into a distributed generation scheme. In such a system, vehicles could play a major role in power generation and storage.

Numerical analysis for the time distributed-order and Riesz space fractional diffusions on bounded domains

Subdiffusion equations with distributed-order fractional derivatives describe some important physical phenomena. In this paper, we consider the time distributed-order and Riesz space fractional diffusions on bounded domains with Dirichlet boundary conditions. Here, the time derivative is defined as the distributed-order fractional derivative in the Caputo sense, and the space derivative is defined as the Riesz fractional derivative. First, we discretize the integral term in the time distributed-order and Riesz space fractional diffusions using numerical approximation. Then the given equation can be written as a multi-term time–space fractional diffusion. Secondly, we propose an implicit difference method for the multi-term time–space fractional diffusion. Thirdly, using mathematical induction, we prove the implicit difference method is unconditionally stable and convergent. Also, the solvability for our method is discussed. Finally, two numerical examples are given to show that the numerical results are in good agreement with our theoretical analysis.

Temperature variation between neighboring days and mortality: a distributed lag non-linear analysis

Objectives To investigate whether a sudden temperature change between neighboring days has significant impact on mortality. Methods A Poisson generalized linear regression model combined with a distributed lag non-linear models was used to estimate the association of temperature change between neighboring days with mortality in a subtropical Chinese city during 2008–2012. Temperature change was calculated as the current day’s temperature minus the previous day’s temperature. Results A significant effect of temperature change between neighboring days on mortality was observed. Temperature increase was significantly associated with elevated mortality from non-accidental and cardiovascular diseases, while temperature decrease had a protective effect on non-accidental mortality and cardiovascular mortality. Males and people aged 65 years or older appeared to be more vulnerable to the impact of temperature change. Conclusions Temperature increase between neighboring days has a significant adverse impact on mortality. Further health mitigation strategies as a response to climate change should take into account temperature variation between neighboring days.

More than just food: Field visits to an emergency relief centre

Emergency relief centres provide financial, housing, food and other types of support to families and individuals who experience financial hardship. These centres are non-profit, often government supported organizations that rely on the help of their volunteers and social workers. This paper reports on our preliminary findings from field visits to one such centre called Communify, in the inner west of Brisbane, Australia. Communify runs an emergency food relief facility for people who find themselves in a crisis or temporarily unable to afford groceries. Over a period of five months, we did several field visits to the centre and carried out 21 short in-situ interviews, with a mix of Communify clients and volunteers. Our results shed light on people’s experiences of financial hardship and their interactions with the emergency relief centre. In particular, issues related to their perceived values and stigmas associated with their experiences are highlighted in our findings. We identify opportunities for design that can empower people struggling with financial hardship.

Ionized Gas towards Galactic Centre-Constraints from Low-Frequency Recombination Lines

Observations of the H272α recombination line towards the galactic centre show features near VLSR= 0, -50 and + 36 kms-1 . We have combined the parameters of these features with the available -166 measurements to obtain the properties of the ionized gas present along the line of sight and also in the -3 kpc arm-. For the line-of-sight ionized gas we get an electron density around 7 cm-3 and a pathlength through it 10-60 pc. The emission measure and the electron temperature are in the range 500-2900 pc cm-6 and 2000-6000 - respectively. The ionized gas in the 3 kpc arm has an electron density of 30 cm-3 and extends over 9 pc along the line of sight if we assume an electron temperature of 104 K. Using the available upper limit to the intensity of the H351α recombination line, we show that the distributed ionized gas responsible for the dispersion of pulsar signals should have a temperature > 4500 - and a minimum filling factor of 20 per cent. We also show that recombination lines from the -warm ionized- gas proposed by McKee & Ostriker (1977) should be detectable in the frequency range 100-150 MHz towards the galactic centre with the sensitivity available at present.

Distributed Robotic Vision as a service

The vision sense of standalone robots is limited by line of sight and onboard camera capabilities, but processing video from remote cameras puts a high computational burden on robots. This paper describes the Distributed Robotic Vision Service, DRVS, which implements an on-demand distributed visual object detection service. Robots specify visual information requirements in terms of regions of interest and object detection algorithms. DRVS dynamically distributes the object detection computation to remote vision systems with processing capabilities, and the robots receive high-level object detection information. DRVS relieves robots of managing sensor discovery and reduces data transmission compared to image sharing models of distributed vision. Navigating a sensorless robot from remote vision systems is demonstrated in simulation as a proof of concept.

Distributed Scheduling for Multi-Hop Wireless Networks

We study the performance of greedy scheduling in multihop wireless networks where the objective is aggregate utility maximization. Following standard approaches, we consider the dual of the original optimization problem. Optimal scheduling requires selecting independent sets of maximum aggregate price, but this problem is known to be NP-hard. We propose and evaluate a simple greedy heuristic. We suggest how the greedy heuristic can be implemented in a distributed manner. We evaluate an analytical bound in detail, for the special case of a line graph and also provide a loose bound on the greedy heuristic for the case of an arbitrary graph.

Worst-Case Asymmetric Distributed Source Coding

We consider the asymmetric distributed source coding problem, where the recipient interactively communicates with N correlated informants to gather their data. We are mainly interested in minimizing the worst-case number of informant bits required for successful data-gathering at recipient, but we are also concerned with minimizing the number of rounds as well as the number of recipient bits. We provide two algorithms, one that optimally minimizes the number of informant bits and other that trades-off the number of informant bits to efficiently reduce the number of rounds and number of recipient bits.

Elite Bargaining and the Evolution of Centre-Periphery Relations in Post-Soviet Russia : A Comparative Analysis

This work is concerned with presenting a modified theoretical approach to the study of centre-periphery relations in the Russian Federation. In the widely accepted scientific discourse, the Russian federal system under the Yeltsin Administration (1991-2000) was asymmetrical; largely owing to the varying amount of structural autonomy distributed among the federation s 89 constituent units. While providing an improved understanding as to which political and socio-economic structures contributed to federal asymmetry, it is felt that associated large N-studies have underemphasised the role played by actor agency in re-shaping Russian federal institutions. It is the main task of this thesis to reintroduce /re-emphasise the importance of actor agency as a major contributing element of institutional change in the Russian federal system. By focusing on the strategic agency of regional elites simultaneously within regional and federal contexts, the thesis adopts the position that political, ethnic and socio-economic structural factors alone cannot fully determine the extent to which regional leaders were successful in their pursuit of economic and political pay-offs from the institutionally weakened federal centre. Furthermore, this work hypothesises that under conditions of federal institutional uncertainty, it is the ability of regional leaders to simultaneously interpret various mutable structural conditions then translate them into plausible strategies which accounts for the regions ability to extract variable amounts of economic and political pay-offs from the Russian federal system. The thesis finds that while the hypothesis is accurate in its theoretical assumptions, several key conclusions provide paths for further inquiry posed by the initial research question. First, without reliable information or stable institutions to guide their actions, both regional and federal elites were forced into ad-hoc decision-making in order to maintain their core strategic focus: political survival. Second, instead of attributing asymmetry to either actor agency or structural factors exclusively, the empirical data shows that both agency and structures interact symbiotically in the strategic formulation process, thus accounting for the sub-optimal nature of several of the actions taken in the adopted cases. Third, as actor agency and structural factors mutate over time, so, too do the perceived payoffs from elite competition. In the case of the Russian federal system, the stronger the federal centre became, the less likely it was that regional leaders could extract the high degree of economic and political pay-offs that they clamoured for earlier in the Yeltsin period. Finally, traditional approaches to the study of federal systems which focus on institutions as measures of federalism are not fully applicable in the Russian case precisely because the institutions themselves were a secondary point of contention between competing elites. Institutional equilibriums between the regions and Moscow were struck only when highly personalised elite preferences were satisfied. Therefore the Russian federal system is the product of short-term, institutional solutions suited to elite survival strategies developed under conditions of economic, political and social uncertainty.

A Distributed Robotic Vision Service

Robotic vision is limited by line of sight and onboard camera capabilities. Robots can acquire video or images from remote cameras, but processing additional data has a computational burden. This paper applies the Distributed Robotic Vision Service, DRVS, to robot path planning using data outside line-of-sight of the robot. DRVS implements a distributed visual object detection service to distributes the computation to remote camera nodes with processing capabilities. Robots request task-specific object detection from DRVS by specifying a geographic region of interest and object type. The remote camera nodes perform the visual processing and send the high-level object information to the robot. Additionally, DRVS relieves robots of sensor discovery by dynamically distributing object detection requests to remote camera nodes. Tested over two different indoor path planning tasks DRVS showed dramatic reduction in mobile robot compute load and wireless network utilization.

A multi-centre open-label randomised non-inferiority trial comparing watchful waiting to antibiotic treatment for acute otitis media without perforation in low-risk urban Aboriginal and Torres Strait Islander children (the WATCH trial): study protocol for a randomised controlled trial

Background Treatment guidelines recommend watchful waiting for children older than 2 years with acute otitis media (AOM) without perforation, unless they are at high risk of complications. The high prevalence of chronic suppurative otitis media (CSOM) in remote Aboriginal and Torres Strait Islander communities leads these children to be classified as high risk. Urban Aboriginal and Torres Strait Islander children are at lower risk of complications, but evidence to support the subsequent recommendation for watchful waiting in this population is lacking. Methods/Design This non-inferiority multi-centre randomised controlled trial will determine whether watchful waiting is non-inferior to immediate antibiotics for urban Aboriginal and Torres Strait Islander children with AOM without perforation. Children aged 2 − 16 years with AOM who are considered at low risk for complications will be recruited from six participating urban primary health care services across Australia. We will obtain informed consent from each participant or their guardian. The primary outcome is clinical resolution on day 7 (no pain, no fever of at least 38 °C, no bulging eardrum and no complications of AOM such as perforation or mastoiditis) as assessed by general practitioners or nurse practitioners. Participants and outcome assessors will not be blinded to treatment. With a sample size of 198 children in each arm, we have 80 % power to detect a non-inferiority margin of up to 10 % at a significance level of 5 %, assuming clinical improvement of at least 80 % in both groups. Allowing for a 20 % dropout rate, we aim to recruit 495 children. We will analyse both by intention-to-treat and per protocol. We will assess the cost- effectiveness of watchful waiting compared to immediate antibiotic prescription. We will also report on the implementation of the trial from the perspectives of parents/carers, health professionals and researchers. Discussion The trial will provide evidence for the safety and effectiveness of watchful waiting for the management of AOM in Aboriginal and Torres Strait Islander children living in urban settings who are considered to be at low risk of complications.

Interactive Distributed Source Coding in Asymmetric Communication Scenarios

We provide a new unified framework, called "multiple correlated informants - single recipient" communication, to address the variations of the traditional Distributed Source Coding (DSC) problem. Different combinations of the assumptions about the communication scenarios and the objectives of communication result in different variations of the DSC problem. For each of these variations, the complexities of communication and computation of the optimal solution is determined by the combination of the underlying assumptions. In the proposed framework, we address the asymmetric, interactive, and lossless variant of the DSC problem, with various objectives of communication and provide optimal solutions for those. Also, we consider both, the worst-case and average-case scenarios.

CUSUM Based Distributed Detection in WSNs

We are concerned with the situation in which a wireless sensor network is deployed in a region, for the purpose of detecting an event occurring at a random time and at a random location. The sensor nodes periodically sample their environment (e.g., for acoustic energy),process the observations (in our case, using a CUSUM-based algorithm) and send a local decision (which is binary in nature) to the fusion centre. The fusion centre collects these local decisions and uses a fusion rule to process the sensors’ local decisions and infer the state of nature, i.e., if an event has occurred or not. Our main contribution is in analyzing two local detection rules in combination with a simple fusion rule. The local detection algorithms are based on the nonparametric CUSUMprocedure from sequential statistics. We also propose two ways to operate the local detectors after an alarm. These alternatives when combined in various ways yield several approaches. Our contribution is to provide analytical techniques to calculate false alarm measures, by the use of which the local detector thresholds can be set. Simulation results are provided to evaluate the accuracy of our analysis. As an illustration we provide a design example. We also use simulations to compare the detection delays incurred in these algorithms.

Distributed Source Coding for Sensor Data Model and Estimation of Cluster Head Errors Using Bayesian and K-Near Neighborhood Classifiers in Deployment of Dense Wireless Sensor Networks

The lifetime calculation of large dense sensor networks with fixed energy resources and the remaining residual energy have shown that for a constant energy resource in a sensor network the fault rate at the cluster head is network size invariant when using the network layer with no MAC losses.Even after increasing the battery capacities in the nodes the total lifetime does not increase after a max limit of 8 times. As this is a serious limitation lots of research has been done at the MAC layer which allows to adapt to the specific connectivity, traffic and channel polling needs for sensor networks. There have been lots of MAC protocols which allow to control the channel polling of new radios which are available to sensor nodes to communicate. This further reduces the communication overhead by idling and sleep scheduling thus extending the lifetime of the monitoring application. We address the two issues which effects the distributed characteristics and performance of connected MAC nodes. (1) To determine the theoretical minimum rate based on joint coding for a correlated data source at the singlehop, (2a) to estimate cluster head errors using Bayesian rule for routing using persistence clustering when node densities are the same and stored using prior probability at the network layer, (2b) to estimate the upper bound of routing errors when using passive clustering were the node densities at the multi-hop MACS are unknown and not stored at the multi-hop nodes a priori. In this paper we evaluate many MAC based sensor network protocols and study the effects on sensor network lifetime. A renewable energy MAC routing protocol is designed when the probabilities of active nodes are not known a priori. From theoretical derivations we show that for a Bayesian rule with known class densities of omega1, omega2 with expected error P* is bounded by max error rate of P=2P* for single-hop. We study the effects of energy losses using cross-layer simulation of - large sensor network MACS setup, the error rate which effect finding sufficient node densities to have reliable multi-hop communications due to unknown node densities. The simulation results show that even though the lifetime is comparable the expected Bayesian posterior probability error bound is close or higher than Pges2P*.