Rapid scanning of spectrograms for efficient identification of bioacoustic events in big data

Acoustic sensing is a promising approach to scaling faunal biodiversity monitoring. Scaling the analysis of audio collected by acoustic sensors is a big data problem. Standard approaches for dealing with big acoustic data include automated recognition and crowd based analysis. Automatic methods are fast at processing but hard to rigorously design, whilst manual methods are accurate but slow at processing. In particular, manual methods of acoustic data analysis are constrained by a 1:1 time relationship between the data and its analysts. This constraint is the inherent need to listen to the audio data. This paper demonstrates how the efficiency of crowd sourced sound analysis can be increased by an order of magnitude through the visual inspection of audio visualized as spectrograms. Experimental data suggests that an analysis speedup of 12× is obtainable for suitable types of acoustic analysis, given that only spectrograms are shown.

HMM relative entropy rate concepts for vision-based aircraft manoeuvre detection

Machine vision is emerging as a viable sensing approach for mid-air collision avoidance (particularly for small to medium aircraft such as unmanned aerial vehicles). In this paper, using relative entropy rate concepts, we propose and investigate a new change detection approach that uses hidden Markov model filters to sequentially detect aircraft manoeuvres from morphologically processed image sequences. Experiments using simulated and airborne image sequences illustrate the performance of our proposed algorithm in comparison to other sequential change detection approaches applied to this application.

Role of electromechanical wave propagation in power systems

In a large interconnected power system, disturbances initiated by a fault or other events cause acceleration in the generator rotors with respect to their synchronous reference frame. This acceleration of rotors can be described by two different dynamic phenomena, as shown in existing literature. One of the phenomena is simultaneous acceleration and the other is electromechanical wave propagation, which is characterized by travelling waves in terms of a wave equation. This paper demonstrates that depending on the structure of the system, the exhibited dynamic response will be dominated by one phenomenon or the other or a mixture of both. Two system structures of choice are examined, with each structure exemplifying each phenomenon present to different degrees in their dynamic responses. Prediction of dominance of either dynamic phenomenon in a particular system can be determined by taking into account the relative sizes of the values of its reduced admittance matrix.

A flexible protection scheme for an islanded Multi-Microgrid

Multi-Microgrids (MMGs) have been proposed to connect distributed generators (DG), microgrids (MG), and medium-voltage (MV) loads with the distribution system. A flexible protection scheme that enables an islanded MMG to continue operation during fault conditions is yet to be developed. In this paper, a protection scheme for an islanded MMG that utilises MG controllers and communication links is proposed. The MMG model used includes two MGs connected to the distribution system. Each MG consists of diesel, wind, and photovoltaic (PV) microsources. The effectiveness of the proposed protection scheme is evaluated by simulation.

An improved protection strategy for microgrids

Microgrids (MG) enable the integration of low capacity renewable energy resources with distribution systems. A recently proposed protection scheme for MGs utilising undervoltage, High Impedance Fault (HIF) detection, directional protection modules, and communication links significantly reduces the fault clearing time compared to previous schemes. In this paper, the effect of replacing undervoltage protection with differential protection in a scheme that also contains HIF and directional protection modules is studied. The MG model used in this study includes a diesel, wind, and two photovoltaic (PV) microsources. The alternative protection schemes are evaluated by simulation. It is found that the protection scheme consisting of differential, HIF detection, and directional protection modules is more effective compared to the alternative in protecting the MG from some fault conditions such as the phase-A-to-ground, phase-B-to-C, and phase-B-to-C-to-ground.

A novel real time pricing scheme for demand response in residential distribution systems

Price based technique is one way to handle increase in peak demand and deal with voltage violations in residential distribution systems. This paper proposes an improved real time pricing scheme for residential customers with demand response option. Smart meters and in-home display units are used to broadcast the price and appropriate load adjustment signals. Customers are given an opportunity to respond to the signals and adjust the loads. This scheme helps distribution companies to deal with overloading problems and voltage issues in a more efficient way. Also, variations in wholesale electricity prices are passed on to electricity customers to take collective measure to reduce network peak demand. It is ensured that both customers and utility are benefitted by this scheme.

Establishing sustainable and reliable smart grids

This paper addresses challenges part of the shift of paradigm taking place in the way we produce, transmit and use power related to what is known as smart grids. The aim of this paper is to explore present initiatives to establish smart grids as a sustainable and reliable power supply system. We argue that smart grids are not isolated to abstract conceptual models alone. We suggest that establishing sustainable and reliable smart grids depend on series of contributions including modeling and simulation projects, technological infrastructure pilots, systemic methods and training, and not least how these and other elements must interact to add reality to the conceptual models. We present and discuss three initiatives that illuminate smart grids from three very different positions. First, the new power grid simulator project in the electrical engineering PhD program at Queensland University of Technology (QUT). Second, the new smart grids infrastructure pilot run by the Norwegian Centers of Expertise Smart Energy Markets (NCE SMART). And third, the new systemic Master program on next generation energy technology at østfold University College (Hiø). These initiatives represent future threads in a mesh embedding smart grids in models, technology, infrastructure, education, skills and people.

It's just an old apron : aprons, artefacts and art - representations of personal and private 'her-stories', as public histories

This paper examines art and artefact in the representation and recollection of deeply personal WWII women’s experiences as POW’s under the Japanese. This kind of treatment of internees in the Tjideng Women and Children’s internment camp (and others) in Batavia under the Japanese in WWII, stands in stark and brutal contrast to the idyllic life lived by many families up to that time in what was then known as the Dutch East Indies (Indonesia). The deprivation and brutality of the Japanese incarceration of these women and children evoked responses - not military, but certainly militant, if muted. Representations of those responses – as both art and artefact - may be found in the most unlikely places and unexpected forms - and are still being unearthed to this day. However close we might personally be to these artists and artisans, can we, as observers from a distance, ever truly comprehend through spoken or written words alone, the day-today realities of those extraordinary times?

Adapting Lyubashevsky's signature schemes to the ring signature setting

Basing signature schemes on strong lattice problems has been a long standing open issue. Today, two families of lattice-based signature schemes are known: the ones based on the hash-and-sign construction of Gentry et al.; and Lyubashevsky’s schemes, which are based on the Fiat-Shamir framework. In this paper we show for the first time how to adapt the schemes of Lyubashevsky to the ring signature setting. In particular we transform the scheme of ASIACRYPT 2009 into a ring signature scheme that provides strong properties of security under the random oracle model. Anonymity is ensured in the sense that signatures of different users are within negligible statistical distance even under full key exposure. In fact, the scheme satisfies a notion which is stronger than the classical full key exposure setting as even if the keypair of the signing user is adversarially chosen, the statistical distance between signatures of different users remains negligible. Considering unforgeability, the best lattice-based ring signature schemes provide either unforgeability against arbitrary chosen subring attacks or insider corruption in log-sized rings. In this paper we present two variants of our scheme. In the basic one, unforgeability is ensured in those two settings. Increasing signature and key sizes by a factor k (typically 80 − 100), we provide a variant in which unforgeability is ensured against insider corruption attacks for arbitrary rings. The technique used is pretty general and can be adapted to other existing schemes.

A Human identification technique using images of the iris and wavelet transform

A new approach for recognizing the iris of the human eye is presented. Zero-crossings of the wavelet transform at various resolution levels are calculated over concentric circles on the iris, and the resulting one-dimensional (1-D) signals are compared with model features using different dissimilarity functions.

An interactive planning and scheduling framework for optimising pits-to-crushers operations

In this paper, an interactive planning and scheduling framework are proposed for optimising operations from pits to crushers in ore mining industry. Series of theoretical and practical operations research techniques are investigated to improve the overall efficiency of mining systems due to the facts that mining managers need to tackle optimisation problems within different horizons and with different levels of detail. Under this framework, mine design planning,mine production sequencing and mine transportation scheduling models are integrated and interacted within a whole optimisation system. The proposed integrated framework could be used by mining industry for reducing equipment costs, improving the production efficiency and maximising the net present value.

Demand response for residential appliances via Customer Reward Scheme

This paper proposes a reward based demand response algorithm for residential customers to shave network peaks. Customer survey information is used to calculate various criteria indices reflecting their priority and flexibility. Criteria indices and sensitivity based house ranking is used for appropriate load selection in the feeder for demand response. Customer Rewards (CR) are paid based on load shift and voltage improvement due to load adjustment. The proposed algorithm can be deployed in residential distribution networks using a two-level hierarchical control scheme. Realistic residential load model consisting of non-controllable and controllable appliances is considered in this study. The effectiveness of the proposed demand response scheme on the annual load growth of the feeder is also investigated. Simulation results show that reduced peak demand, improved network voltage performance, and customer satisfaction can be achieved.

Decision fusion from parts and samples for robust iris recognition

Fusion techniques can be used in biometrics to achieve higher accuracy. When biometric systems are in operation and the threat level changes, controlling the trade-off between detection error rates can reduce the impact of an attack. In a fused system, varying a single threshold does not allow this to be achieved, but systematic adjustment of a set of parameters does. In this paper, fused decisions from a multi-part, multi-sample sequential architecture are investigated for that purpose in an iris recognition system. A specific implementation of the multi-part architecture is proposed and the effect of the number of parts and samples in the resultant detection error rate is analysed. The effectiveness of the proposed architecture is then evaluated under two specific cases of obfuscation attack: miosis and mydriasis. Results show that robustness to such obfuscation attacks is achieved, since lower error rates than in the case of the non-fused base system are obtained.

A comparative study of the semi-elastic and fully-elastic MapReduce models

MapReduce is a computation model for processing large data sets in parallel on large clusters of machines, in a reliable, fault-tolerant manner. A MapReduce computation is broken down into a number of map tasks and reduce tasks, which are performed by so called mappers and reducers, respectively. The placement of the mappers and reducers on the machines directly affects the performance and cost of the MapReduce computation in cloud computing. From the computational point of view, the mappers/reducers placement problem is a generation of the classical bin packing problem, which is NP-complete. Thus, in this paper we propose a new heuristic algorithm for the mappers/reducers placement problem in cloud computing and evaluate it by comparing with other several heuristics on solution quality and computation time by solving a set of test problems with various characteristics. The computational results show that our heuristic algorithm is much more efficient than the other heuristics and it can obtain a better solution in a reasonable time. Furthermore, we verify the effectiveness of our heuristic algorithm by comparing the mapper/reducer placement for a benchmark problem generated by our heuristic algorithm with a conventional mapper/reducer placement which puts a fixed number of mapper/reducer on each machine. The comparison results show that the computation using our mapper/reducer placement is much cheaper than the computation using the conventional placement while still satisfying the computation deadline.

Performance-driven live migration of multiple virtual machines in datacenters

Live migration of multiple Virtual Machines (VMs) has become an indispensible management activity in datacenters for application performance, load balancing, server consolidation. While state-of-the-art live VM migration strategies focus on the improvement of the migration performance of a single VM, little attention has been given to the case of multiple VMs migration. Moreover, existing works on live VM migration ignore the inter-VM dependencies, and underlying network topology and its bandwidth. Different sequences of migration and different allocations of bandwidth result in different total migration times and total migration downtimes. This paper concentrates on developing a multiple VMs migration scheduling algorithm such that the performance of migration is maximized. We evaluate our proposed algorithm through simulation. The simulation results show that our proposed algorithm can migrate multiple VMs on any datacenter with minimum total migration time and total migration downtime.