Towards an Improved Phasor Measurement Unit Data Communications Framework

This paper discusses a proposed new communications framework for phasor measurement units (PMU) optimized for use on wide area networks. Traditional PMU telecoms have been optimized for use in environments where bandwidth is restricted. The new method takes the reliability of the telecommunications medium into account and provides guaranteed delivery of data whilst optimizing for realtime delivery of the most current data. Other important aspects, such as security, are also considered.

Wavelets for the Analysis and Compression of Power System Disturbances

Wavelets introduce new classes of basis functions for time-frequency signal analysis and have properties particularly suited to the transient components and discontinuities evident in power system disturbances. Wavelet analysis involves representing signals in terms of simpler, fixed building blocks at different scales and positions. This paper examines the analysis and subsequent compression properties of the discrete wavelet and wavelet packet transforms and evaluates both transforms using an actual power system disturbance from a digital fault recorder. The paper presents comparative compression results using the wavelet and discrete cosine transforms and examines the application of wavelet compression in power monitoring to mitigate against data communications overheads.

Power allocation strategies across N orthogonal channels for single-relay networks at both source and relay

We consider a wireless relay network with one source, one relay and one destination, where communications between nodes are preformed over N orthogonal channels. This, for example, is the case when orthogonal frequency division multiplexing is employed for data communications. Since the power available at the source and relay is limited, we study optimal power allocation strategies at the source and relay in order to maximize the overall source-destination capacity. Depending on the availability of the channel state information at both the source and relay or only at the relay, power allocation is performed at both the source and relay or only at the relay. Considering different setups for the problem, various optimization problems are formulated and solved. Some properties of the optimal solution are also proved.

Two-Stage Transmitter Precoding Based on Data-Driven Code Hopping and Partial Zero Forcing Beamforming for MC-DCMA Communications

This paper proposes a hybrid transmission technique based on adaptive code-to-user allocation and linear precoding for the downlink of phase shift keying (PSK) based multi-carrier code division multiple access (MC-CDMA) systems. The proposed scheme is based on the separation of the instantaneous multiple access interference (MAI) into constructive and destructive components taking into account the dependency on both the channel variation and the instantaneous symbol values of the active users. The first stage of the proposed technique is to adaptively distribute the available spreading sequences to the users on a symbol-by-symbol basis in the form of codehopping with the objective to steer the users' instantaneous crosscorrelations to yield a favourable constructive to destructive MAI ratio. The second stage is to employ a partial transmitter based zero forcing (ZF) scheme specifically designed for the exploitation of constructive MAI. The partial ZF processing decorrelates destructive interferers, while users that interfere constructively remain correlated. This results in a signal to interference-plus-noise ratio (SINR) enhancement without the need for additional power-per-user investment. It will be shown in the results section that significant bit error rate (BER) performance benefits can be achieved with this technique.

Millimeter-Wave Soldier-to-Soldier Communications for Covert Battlefield Operations

Mobile ad hoc networking of dismounted combat personnel is expected to play an important role in the future of network-centric operations. High-speed, short-range, soldier-to-soldier wireless communications will be required to relay information on situational awareness, tactical instructions, and covert surveillance related data during special operations reconnaissance and other missions. This article presents some of the work commissioned by the U. K. Ministry of Defence to assess the feasibility of using 60 GHz millimeter-wave smart antenna technology to provide covert communications capable of meeting these stringent networking needs. Recent advances in RF front-end technology, alongside physical layer transmission schemes that could be employed in millimeter-wave soldier-mounted radio, are discussed. The introduction of covert communications between soldiers will require the development of a bespoke directive medium access layer. A number of adjustments to the IEEE 802.11 distribution coordination function that will enable directional communications are suggested. The successful implementation of future smart antenna technologies and direction of arrival-based protocols will be highly dependent on thorough knowledge of transmission channel characteristics prior to deployment. A novel approach to simulating dynamic soldier-to-soldier signal propagation using state-of-the-art animation-based technology developed for computer game design is described, and important channel metrics such as root mean square angle and delay spread for a team of four networked infantry soldiers over a range of indoor and outdoor environments is reported.

Correlation Rotation Linear Precoding for MIMO Broadcast Communications

A simple linear precoding technique is proposed for multiple input multiple output (MIMO) broadcast systems using phase shift keying (PSK) modulation. The proposed technique is based on the fact that, on an instantaneous basis, the interference between spatial links in a MIMO system can be constructive and can contribute to the power of the useful signal to improve the performance of signal detection. In MIMO downlinks this co-channel interference (CCI) can be predicted and characterised prior to transmission. Contrary to common practice where knowledge of the interference is used to eliminate it, the main idea proposed here is to use this knowledge to influence the interference and benefit from it, thus gaining advantage from energy already existing in the communication system that is left unexploited otherwise. The proposed precoding aims at adaptively rotating, rather than zeroing, the correlation between the MIMO substreams depending on the transmitted data, so that the signal of interfering transmissions is aligned to the signal of interest at each receive antenna. By doing so, the CCI is always kept constructive and the received signal to interference-plus-noise ratio (SINR) delivered to the mobile units (MUs) is enhanced without the need to invest additional signal power per transmitted symbol at the MIMO base station (BS). It is shown by means of theoretical analysis and simulations that the proposed MIMO precoding technique offers significant performance and throughput gains compared to its conventional counterparts.

Extracting S-matrix poles for resonances from numerical scattering data: Type-II Pade reconstruction

We present a FORTRAN 77 code for evaluation of resonance pole positions and residues of a numerical scattering matrix element in the complex energy (CE) as well as in the complex angular momentum (CAM) planes. Analytical continuation of the S-matrix element is performed by constructing a type-II Pade approximant from given physical values (Bessis et al. (1994) [421: Vrinceanu et al. (2000) [24]; Sokolovski and Msezane (2004) [23]). The algorithm involves iterative 'preconditioning' of the numerical data by extracting its rapidly oscillating potential phase component. The code has the capability of adding non-analytical noise to the numerical data in order to select 'true' physical poles, investigate their stability and evaluate the accuracy of the reconstruction. It has an option of employing multiple-precision (MPFUN) package (Bailey (1993) [451) developed by D.H. Bailey wherever double precision calculations fail due to a large number of input partial waves (energies) involved. The code has been successfully tested on several models, as well as the F + H-2 -> HE + H, F + HD : HE + D, Cl + HCI CIH + Cl and H + D-2 -> HD + D reactions. Some detailed examples are given in the text.

Incremental learning from stream data

Recent years have witnessed an incredibly increasing interest in the topic of incremental learning. Unlike conventional machine learning situations, data flow targeted by incremental learning becomes available continuously over time. Accordingly, it is desirable to be able to abandon the traditional assumption of the availability of representative training data during the training period to develop decision boundaries. Under scenarios of continuous data flow, the challenge is how to transform the vast amount of stream raw data into information and knowledge representation, and accumulate experience over time to support future decision-making process. In this paper, we propose a general adaptive incremental learning framework named ADAIN that is capable of learning from continuous raw data, accumulating experience over time, and using such knowledge to improve future learning and prediction performance. Detailed system level architecture and design strategies are presented in this paper. Simulation results over several real-world data sets are used to validate the effectiveness of this method.

A Capabilities-Aware Framework for Using Computational Accelerators in Data-Intensive Computing

Multicore computational accelerators such as GPUs are now commodity components for highperformance computing at scale. While such accelerators have been studied in some detail as stand-alone computational engines, their integration in large-scale distributed systems raises new challenges and trade-offs. In this paper, we present an exploration of resource management alternatives for building asymmetric accelerator-based distributed systems. We present these alternatives in the context of a capabilities-aware framework for data-intensive computing, which uses an enhanced implementation of the MapReduce programming model for accelerator-based clusters, compared to the state of the art. The framework can transparently utilize heterogeneous accelerators for deriving high performance with low programming effort. Our work is the first to compare heterogeneous types of accelerators, GPUs and a Cell processors, in the same environment and the first to explore the trade-offs between compute-efficient and control-efficient accelerators on data-intensive systems. Our investigation shows that our framework scales well with the number of different compute nodes. Furthermore, it runs simultaneously on two different types of accelerators, successfully adapts to the resource capabilities, and performs 26.9% better on average than a static execution approach.

Job characteristics and burnout among aging professionals in information and communications technology

The aim of this Study was to examine the relationship between job characteristics and burnout, i.e., exhaustion, cynicism and lack of professional efficacy, in a sample of 115 (49- to 61-yr.-old) information and communications technology professionals. Questionnaire survey data were collected at two time points. In 1995 (Time 1), higher quantitative overload and lower job control were associated with higher exhaustion. Job control was negatively associated with lack of professional efficacy. In 2001 (Time 2), quantitative overload and information overload were positively associated with exhaustion, but with job control negatively. Use of new information Was negatively associated with cynicism. In addition, job control and use of new information were negatively associated with lack of professional efficacy. job characteristics at Time 1 were not significantly associated with burnout at Time 2 when job characteristics at Time 2 were controlled.

Robust Multimodal Person Identification With Limited Training Data

This paper presents a novel method of audio-visual feature-level fusion for person identification where both the speech and facial modalities may be corrupted, and there is a lack of prior knowledge about the corruption. Furthermore, we assume there are limited amount of training data for each modality (e.g., a short training speech segment and a single training facial image for each person). A new multimodal feature representation and a modified cosine similarity are introduced to combine and compare bimodal features with limited training data, as well as vastly differing data rates and feature sizes. Optimal feature selection and multicondition training are used to reduce the mismatch between training and testing, thereby making the system robust to unknown bimodal corruption. Experiments have been carried out on a bimodal dataset created from the SPIDRE speaker recognition database and AR face recognition database with variable noise corruption of speech and occlusion in the face images. The system's speaker identification performance on the SPIDRE database, and facial identification performance on the AR database, is comparable with the literature. Combining both modalities using the new method of multimodal fusion leads to significantly improved accuracy over the unimodal systems, even when both modalities have been corrupted. The new method also shows improved identification accuracy compared with the bimodal systems based on multicondition model training or missing-feature decoding alone.