Testing the role of sensory systems in the migratory heading of a songbird

The identification of the sensory cues and mechanisms by which migratory birds are able to reach the same breeding and wintering grounds year after year has eluded biologists despite more than 50 years of intensive study. While a number of environmental cues have been proposed to play a role in the navigation of birds, arguments still persist about which cues are essential for the experience based navigation shown by adult migrants. To date, few studies have tested the sensory basis of navigational cues used during actual migration in the wild: mainly laboratory based studies or homing during the non-migratory season have been used to investigate this behaviour. Here we tested the role of olfactory and magnetic cues in the migration of the catbird (Dumetella carolinensis) by radio tracking the migration of birds with sensory manipulations during their actual migratory flights. Our data suggest that adult birds treated with zinc sulphate to produce anosmia were unable to show the same orientation as control adults, and instead reverted to a direction similar to that shown by juveniles making their first migration. The magnetic manipulation had no effect on the orientation of either adults or juveniles. These results allow us to propose that the olfactory sense may play a role in experience based migration in adult catbirds. While the olfactory sense has been shown to play a role in the homing of pigeons and other birds, this is the first time it has been implicated in migratory orientation.

Online Tracking of Thévenin Equivalent Parameters Using PMU Measurements

This paper presents a new method for tracking Thévenin equivalent parameters for a power system at a node using local Phasor Measurement Unit (PMU) measurements. Three consecutive phasor measurements for voltage and current, recorded at one location, are used. The phase drifts caused by the measurement slip frequency are first determined and phase angles of the measured phasors are corrected so that the corrected phasors are synchronized to the same reference. The synchronized phasors are then used to determine the equivalent Thévenin parameters of the system.

Tracking Human Position and Lower Body Parts Using Kalman and Particle Filters Constrained by Human Biomechanics

In this paper, a novel framework for visual tracking of human body parts is introduced. The approach presented demonstrates the feasibility of recovering human poses with data from a single uncalibrated camera by using a limb-tracking system based on a 2-D articulated model and a double-tracking strategy. Its key contribution is that the 2-D model is only constrained by biomechanical knowledge about human bipedal motion, instead of relying on constraints that are linked to a specific activity or camera view. These characteristics make our approach suitable for real visual surveillance applications. Experiments on a set of indoor and outdoor sequences demonstrate the effectiveness of our method on tracking human lower body parts. Moreover, a detail comparison with current tracking methods is presented.

Migratory navigation in birds: new opportunities in an era of fast-developing tracking technology

Birds have remained the dominant model for studying the mechanisms of animal navigation for decades, with much of what has been discovered coming from laboratory studies or model systems. The miniaturisation of tracking technology in recent years now promises opportunities for studying navigation during migration itself (migratory navigation) on an unprecedented scale. Even if migration tracking studies are principally being designed for other purposes, we argue that attention to salient environmental variables during the design or analysis of a study may enable a host of navigational questions to be addressed, greatly enriching the field. We explore candidate variables in the form of a series of contrasts (e. g. land vs ocean or night vs day migration), which may vary naturally between migratory species, populations or even within the life span of a migrating individual. We discuss how these contrasts might help address questions of sensory mechanisms, spatiotemporal representational strategies and adaptive variation in navigational ability. We suggest that this comparative approach may help enrich our knowledge about the natural history of migratory navigation in birds.

Analysis of Dependence Tracking Algorithms for Task Dataflow Execution

Processor architectures has taken a turn towards many-core processors, which integrate multiple processing cores on a single chip to increase overall performance, and there are no signs that this trend will stop in the near future. Many-core processors are harder to program than multi-core and single-core processors due to the need of writing parallel or concurrent programs with high degrees of parallelism. Moreover, many-cores have to operate in a mode of strong scaling because of memory bandwidth constraints. In strong scaling increasingly finer-grain parallelism must be extracted in order to keep all processing cores busy.

Task dataflow programming models have a high potential to simplify parallel program- ming because they alleviate the programmer from identifying precisely all inter-task de- pendences when writing programs. Instead, the task dataflow runtime system detects and enforces inter-task dependences during execution based on the description of memory each task accesses. The runtime constructs a task dataflow graph that captures all tasks and their dependences. Tasks are scheduled to execute in parallel taking into account dependences specified in the task graph.

Several papers report important overheads for task dataflow systems, which severely limits the scalability and usability of such systems. In this paper we study efficient schemes to manage task graphs and analyze their scalability. We assume a programming model that supports input, output and in/out annotations on task arguments, as well as commutative in/out and reductions. We analyze the structure of task graphs and identify versions and generations as key concepts for efficient management of task graphs. Then, we present three schemes to manage task graphs building on graph representations, hypergraphs and lists. We also consider a fourth edge-less scheme that synchronizes tasks using integers. Analysis using micro-benchmarks shows that the graph representation is not always scalable and that the edge-less scheme introduces least overhead in nearly all situations.

Three-port DC-DC Converter for Stand-Alone Photovoltaic Systems

System efficiency and cost effectiveness are of critical importance for photovoltaic (PV) systems. This paper addresses the two issues by developing a novel three-port DC-DC converter for stand-alone PV systems, based on an improved Flyback-Forward topology. It provides a compact single-unit solution with a combined feature of optimized maximum power point tracking (MPPT), high step-up ratio, galvanic isolation and multiple operating modes for domestic and aerospace applications. A theoretical analysis is conducted to analyze the operating modes followed by simulation and experimental work. The paper is focused on a comprehensive modulation strategy utilizing both PWM and phase-shifted control that satisfies the requirement of PV power systems to achieve MPPT and output voltage regulation. A 250 W converter was designed and prototyped to provide experimental verification in term of system integration and high conversion efficiency.

Robust visual tracking using structurally random projection and weighted least squares

Sparse representation based visual tracking approaches have attracted increasing interests in the community in recent years. The main idea is to linearly represent each target candidate using a set of target and trivial templates while imposing a sparsity constraint onto the representation coefficients. After we obtain the coefficients using L1-norm minimization methods, the candidate with the lowest error, when it is reconstructed using only the target templates and the associated coefficients, is considered as the tracking result. In spite of promising system performance widely reported, it is unclear if the performance of these trackers can be maximised. In addition, computational complexity caused by the dimensionality of the feature space limits these algorithms in real-time applications. In this paper, we propose a real-time visual tracking method based on structurally random projection and weighted least squares techniques. In particular, to enhance the discriminative capability of the tracker, we introduce background templates to the linear representation framework. To handle appearance variations over time, we relax the sparsity constraint using a weighed least squares (WLS) method to obtain the representation coefficients. To further reduce the computational complexity, structurally random projection is used to reduce the dimensionality of the feature space while preserving the pairwise distances between the data points in the feature space. Experimental results show that the proposed approach outperforms several state-of-the-art tracking methods.

Tracking smart grid hackers

The next-generation smart grid will rely highly on telecommunications infrastructure for data transfer between various systems. Anywhere we have data transfer in a system is a potential security threat. When we consider the possibility of smart grid data being at the heart of our critical systems infrastructure it is imperative that we do all we can to ensure the confidentiality, availability and integrity of the data. A discussion on security itself is outside the scope of this paper, but if we assume the network to be as secure as possible we must consider what we can do to detect when that security fails, or when the attacks comes from the inside of the network. One way to do this is to setup a hacker-trap, or honeypot. A honeypot is a device or service on a network which appears legitimate, but is in-fact a trap setup to catch breech attempts. This paper identifies the different types of honeypot and describes where each may be used. The authors have setup a test honeypot system which has been live for some time. The test system has been setup to emulate a device on a utility network. The system has had many hits, which are described in detail by the authors. Finally, the authors discuss how larger-scale systems in utilities may benefit from honeypot placement.

A biologically inspired appearance model for robust visual tracking

In this work, we propose a biologically inspired appearance model for robust visual tracking. Motivated in part by the success of the hierarchical organization of the primary visual cortex (area V1), we establish an architecture consisting of five layers: whitening, rectification, normalization, coding and polling. The first three layers stem from the models developed for object recognition. In this paper, our attention focuses on the coding and pooling layers. In particular, we use a discriminative sparse coding method in the coding layer along with spatial pyramid representation in the pooling layer, which makes it easier to distinguish the target to be tracked from its background in the presence of appearance variations. An extensive experimental study shows that the proposed method has higher tracking accuracy than several state-of-the-art trackers.

A framework for experimental determination of localised vertical pedestrian forces on full-scale structures using wireless attitude and heading reference systems

A major weakness among loading models for pedestrians walking on flexible structures proposed in recent years is the various uncorroborated assumptions made in their development. This applies to spatio-temporal characteristics of pedestrian loading and the nature of multi-object interactions. To alleviate this problem, a framework for the determination of localised pedestrian forces on full-scale structures is presented using a wireless attitude and heading reference systems (AHRS). An AHRS comprises a triad of tri-axial accelerometers, gyroscopes and magnetometers managed by a dedicated data processing unit, allowing motion in three-dimensional space to be reconstructed. A pedestrian loading model based on a single point inertial measurement from an AHRS is derived and shown to perform well against benchmark data collected on an instrumented treadmill. Unlike other models, the current model does not take any predefined form nor does it require any extrapolations as to the timing and amplitude of pedestrian loading. In order to assess correctly the influence of the moving pedestrian on behaviour of a structure, an algorithm for tracking the point of application of pedestrian force is developed based on data from a single AHRS attached to a foot. A set of controlled walking tests with a single pedestrian is conducted on a real footbridge for validation purposes. A remarkably good match between the measured and simulated bridge response is found, indeed confirming applicability of the proposed framework.