Resource allocation in multiuser cooperative OFDM system using forced cost based decisions

A sub optimal resource allocation algorithm for Orthogonal Frequency Division Multiplexing (OFDM) based cooperative scheme is proposed. The system consists of multiple relays. Subcarrier space is divided into blocks and relays participating in cooperation are allocated specific blocks to be used with a user. To ensure unique subcarrier assignment system is constrained such that same block cannot be used by more than one user. Users are given fair block assignments while no restriction for maximum number of blocks a relay can employ is given. Forced cost based decisions [1] are used for block allocation. Simulation results show that this scheme outperforms a non cooperating scheme with sequential allocation with respect to power usage.

Dying for the bonds of marriage : forced marriages as a weapon of genocide

‘Forced marriages’ involve a woman or girl being abducted and declared the ‘wife’ of her captor without her consent or her family’s consent. The practice generally occurs during wartime and the ‘wife’ is normally subjected to rape, forced impregnation and sexual slavery. Moreover, she is coerced into an intimate relationship with a man who is often the perpetrator of crimes against her and her community. While forced marriages have recently been recognised as a crime against humanity, this Article contends that this does not constitute full recognition of the destructive nature of forced marriages. Instead, this Article mirrors and extends the Akayesu decision that rape can be used as a tool of genocide and maintains that forced marriages can also be a form of genocide.

Utilizing Wide-Area Signals for off-center SVCs to damp interarea oscillations

Wide-Area Measurement Systems (WAMS) provide the opportunity of utilizing remote signals from different locations for the enhancement of power system stability. This paper focuses on the implementation of remote measurements as supplementary signals for off-center Static Var Compensators (SVCs) to damp inter-area oscillations. Combination of participation factor and residue method is used for the selection of most effective stabilizing signal. Speed difference of two generators from separate areas is identified as the best stabilizing signal and used as a supplementary signal for lead-lag controller of SVCs. Time delays of remote measurements and control signals is considered. Wide-Area Damping Controller (WADC) is deployed in Matlab Simulink framework and is tested under different operating conditions. Simulation results reveal that the proposed WADC improve the dynamic characteristic of the system significantly.

Differential entrainment of neuroelectric delta oscillations in developmental dyslexia

Oscillatory entrainment to the speech signal is important for language processing, but has not yet been studied in developmental disorders of language. Developmental dyslexia, a difficulty in acquiring efficient reading skills linked to difficulties with phonology (the sound structure of language), has been associated with behavioural entrainment deficits. It has been proposed that the phonological ‘deficit’ that characterises dyslexia across languages is related to impaired auditory entrainment to speech at lower frequencies via neuroelectric oscillations (<10 Hz, ‘temporal sampling theory’). Impaired entrainment to temporal modulations at lower frequencies would affect the recovery of the prosodic and syllabic structure of speech. Here we investigated event-related oscillatory EEG activity and contingent negative variation (CNV) to auditory rhythmic tone streams delivered at frequencies within the delta band (2 Hz, 1.5 Hz), relevant to sampling stressed syllables in speech. Given prior behavioural entrainment findings at these rates, we predicted functionally atypical entrainment of delta oscillations in dyslexia. Participants performed a rhythmic expectancy task, detecting occasional white noise targets interspersed with tones occurring regularly at rates of 2 Hz or 1.5 Hz. Both groups showed significant entrainment of delta oscillations to the rhythmic stimulus stream, however the strength of inter-trial delta phase coherence (ITC, ‘phase locking’) and the CNV were both significantly weaker in dyslexics, suggestive of weaker entrainment and less preparatory brain activity. Both ITC strength and CNV amplitude were significantly related to individual differences in language processing and reading. Additionally, the instantaneous phase of prestimulus delta oscillation predicted behavioural responding (response time) for control participants only.

On the periodicity of traffic oscillations and capacity drop : the role of driver characteristics

This paper shows that traffic hysteresis, a manifestation of driver characteristics, has a profound impact on the development of traffic oscillations and the bottleneck discharge rate. Findings suggest that aggressive driver behavior (with small response times and jammed spacing) leads to spontaneous formations of stop-and-go disturbances. Furthermore, the aggressive behavior, coupled with a late response to adopt less aggressive behavior, generates large hysteresis that leads to oscillations’ transformation from localized to substantial disturbances and growth. The larger the magnitude of hysteresis is, the larger the growth is. Our finding also suggests that the bottleneck discharge rate can diminish by 8-23% when driver adopts a less aggressive reaction to a disturbance (characterized by a larger response time). This finding is particularly notable since lane-changes have been believed to be the major cause of a reduction in bottleneck discharge rate.

Pulse-coupled neural network performance for real-time identification of vegetation during forced landing

Safety concerns in the operation of autonomous aerial systems require safe-landing protocols be followed during situations where the a mission should be aborted due to mechanical or other failure. On-board cameras provide information that can be used in the determination of potential landing sites, which are continually updated and ranked to prevent injury and minimize damage. Pulse Coupled Neural Networks have been used for the detection of features in images that assist in the classification of vegetation and can be used to minimize damage to the aerial vehicle. However, a significant drawback in the use of PCNNs is that they are computationally expensive and have been more suited to off-line applications on conventional computing architectures. As heterogeneous computing architectures are becoming more common, an OpenCL implementation of a PCNN feature generator is presented and its performance is compared across OpenCL kernels designed for CPU, GPU and FPGA platforms. This comparison examines the compute times required for network convergence under a variety of images obtained during unmanned aerial vehicle trials to determine the plausibility for real-time feature detection.

Autonomous forced landing system for light general aviation aircraft in unknown environments

This paper presents a system which enhances the capabilities of a light general aviation aircraft to land autonomously in case of an unscheduled event such as engine failure. The proposed system will not only increase the level of autonomy for the general aviation aircraft industry but also increase the level of dependability. Safe autonomous landing in case of an engine failure with a certain level of reliability is the primary focus of our work as both safety and reliability are attributes of dependability. The system is designed for a light general aviation aircraft but can be extended for dependable unmanned aircraft systems. The underlying system components are computationally efficient and provides continuous situation assessment in case of an emergency landing. The proposed system is undergoing an evaluation phase using an experimental platform (Cessna 172R) in real world scenarios.

Pulse-coupled neural network performance for real-time identification of vegetation during forced landing

Safety concerns in the operation of autonomous aerial systems require safe-landing protocols be followed during situations where the mission should be aborted due to mechanical or other failure. This article presents a pulse-coupled neural network (PCNN) to assist in the vegetation classification in a vision-based landing site detection system for an unmanned aircraft. We propose a heterogeneous computing architecture and an OpenCL implementation of a PCNN feature generator. Its performance is compared across OpenCL kernels designed for CPU, GPU, and FPGA platforms. This comparison examines the compute times required for network convergence under a variety of images to determine the plausibility for real-time feature detection.

High-frequency electrostatic surface oscillations in a dust-contaminated plasma

High-frequency electrostatic surface waves at the interface of a dusty plasma and a dielectric wall are investigated. The effects of ionization, recombination, and dust-charge variation are taken into account in a self-consistent manner, so that the system considered is closed. It is shown that a coupling of the surface waves and the dust-charge relaxation mode leads to anomalous damping and frequency downshift of the waves.

Thermal effect of plasmon oscillations on the tunnel current in gold nanoisland thin film at low laser intensity

The effect of plasmon oscillations on the DC tunnel current in a gold nanoisland thin film (GNITF) is investigated using low intensity P~1W/cm2 continuous wave lasers. While DC voltages (1–150 V) were applied to the GNITF, it was irradiated with lasers at different wavelengths (k¼473, 532, and 633 nm). Because of plasmon oscillations, the tunnel current increased. It is found that the tunnel current enhancement is mainly due to the thermal effect of plasmon oscillations rather than other plasmonic effects. The results are highly relevant to applications of plasmonic effects in opto-electronic devices.

Automatic UAV forced landing site detection using machine learning

The commercialization of aerial image processing is highly dependent on the platforms such as UAVs (Unmanned Aerial Vehicles). However, the lack of an automated UAV forced landing site detection system has been identified as one of the main impediments to allow UAV flight over populated areas in civilian airspace. This article proposes a UAV forced landing site detection system that is based on machine learning approaches including the Gaussian Mixture Model and the Support Vector Machine. A range of learning parameters are analysed including the number of Guassian mixtures, support vector kernels including linear, radial basis function Kernel (RBF) and polynormial kernel (poly), and the order of RBF kernel and polynormial kernel. Moreover, a modified footprint operator is employed during feature extraction to better describe the geometric characteristics of the local area surrounding a pixel. The performance of the presented system is compared to a baseline UAV forced landing site detection system which uses edge features and an Artificial Neural Network (ANN) region type classifier. Experiments conducted on aerial image datasets captured over typical urban environments reveal improved landing site detection can be achieved with an SVM classifier with an RBF kernel using a combination of colour and texture features. Compared to the baseline system, the proposed system provides significant improvement in term of the chance to detect a safe landing area, and the performance is more stable than the baseline in the presence of changes to the UAV altitude.

Wide-area damping control for inter-area oscillations using inverse filtering technique

In this study, a non-linear excitation controller using inverse filtering is proposed to damp inter-area oscillations. The proposed controller is based on determining generator flux value for the next sampling time which is obtained by maximising reduction rate of kinetic energy of the system after the fault. The desired flux for the next time interval is obtained using wide-area measurements and the equivalent area rotor angles and velocities are predicted using a non-linear Kalman filter. A supplementary control input for the excitation system, using inverse filtering approach, to track the desired flux is implemented. The inverse filtering approach ensures that the non-linearity introduced because of saturation is well compensated. The efficacy of the proposed controller with and without communication time delay is evaluated on different IEEE benchmark systems including Kundur's two area, Western System Coordinating Council three-area and 16-machine, 68-bus test systems.

Time-temperature histories of spherical food products during bulk forced-air precooling

A general mathematical model for forced air precooling of spherical food products in bulk is developed. The food products are arranged inline to form a rectangular parallelepiped. Chilled air is blown along the height of the package. The governing equations for the transient two-dimensional conduction with internal heat generation in the product, simultaneous heat and mass transfer at the product-air interface and one-dimensional transient energy and species conservation equations for the moist air are solved numerically using finite difference methods. Results are presented in the form of time-temperature histories. Experiments are conducted with model foods in a laboratory scale air precooling tunnel. The agreement between the theoretical and experimental results is found to be good. In general, a single product analysis fails to predict the precooling characteristics of bulk loads of food products. In the range of values investigated, the respiration heat is found to have a negligible effect.