Application of analytical solutions to simulate some mine inflow problems in underground coal mining

The paper considers the interaction of ground water flow characteristics, aquifer parameters and mining geometry in order to estimate mine water inflows. The ground water flow conditions include both steady and unsteady state flow in an infinite and finite aquifers to an imaginary pumping out well. Both linear and non-linear flow equations are discussed. The application of non-linear equations has indicated that with the use of appropriate terms in these equations both laminar as well as turbulent inflows can be simulated. Water inflow to underground dewatering tunnels are also discussed in terms of both laminar and turbulent flow. Mine water inflow to a mine discharging to multiple dewatering outlet is also included. The application of various techniques outlined enables a more realistic estimate of water inflow to be made which can be conductive to planning mine dewatering systems with reference to economics and safety.     

An appraisal of mathematical models to predict water inflows into underground coal workings

The paper describes various analytical and numerical models which have been used to predict the quantities of water flowing into underground mines. Analytical models of flow into wells are discussed briefly and their limitations when applied to mine water flow are listed. Numerical models designed specifically for underground mines are examined in detail under the three categories of water resource models, mine water models and methane and water models. The extent to which the available numerical models are applicable to British longwall coal mining operations is considered and the need for further work is identified.     

NEST: novel eMBMS scheduling technique

In order to meet the growing demand for mobile multimedia broadcast services 3GPP includes evolved multimedia broadcast and multicast (eMBMS) services in LTE systems. The high data rates, low latency and QoS provisioning makes LTE systems more suitable for mobile broadcast and multicast services than legacy wireless networks. However, the 3GPP standards has not specified any scheduling strategy for this broadcast and multicast services. In this paper, we propose a novel eMBMS scheduling technique (NEST) which focuses on reducing the average waiting time (latency) of the broadcast services offered by LTE system. This paper has twofold contributions. We proffer NEST considering two types of impatience that is user equipment (UE) departure and UE request repetition. Our proposed scheduling strategy estimates the effects originating from the departure of the mobile UEs and UE request repetition case. It intelligently combines the advantages of both flat scheduling and on-demand scheduling in such a way that the overall latency of the system is reduced. We design a suitable modeling framework to analyze the performance of the system. Simulation experiments on typical LTE systems support the performance analysis and demonstrates 10 % gains while comparing with existing eMBMS scheduling available in present LTE systems.     

Molecular beam epitaxy growth of high-quality HgCdTe LWIR layers on polished and repolished CdZnTe substrates

We report here molecular beam epitaxy (MBE) mercury cadmium telluride (HgCdTe) layers grown on polished and repolished substrates that showed state-of-the-art optical, structural, and electrical characteristics. Many polishing machines currently available do not take into account the soft semiconductor materials, CdZnTe (CZT) being one. Therefore, a polishing jig was custom designed and engineered to take in account certain physical parameters (pressure, substrate rotational frequency, drip rate of solution onto the polishing pad, and polishing pad rotational velocity). The control over these parameters increased the quality, uniformity, and the reproducibility of each polish. EPIR also investigated several bromine containing solutions used for polishing CZT. The concentration of bromine, as well as the mechanical parameters, was varied in order to determine the optimal conditions for polishing CZT.     

Supervised learning and frequency domain averaging-based adaptive channel estimation scheme for filterbank multicarrier with offset quadrature amplitude modulation

Filterbank multicarrier with offset quadrature amplitude modulation (FBMC-OQAM) is an attractive alternative to the orthogonal frequency division multiplexing (OFDM) modulation technique. In comparison with OFDM, the FBMC-OQAM signal has better spectral confinement and higher spectral efficiency and tolerance to synchronization errors, primarily due to per-subcarrier filtering using a frequency-time localized prototype filter. However, the filtering process introduces intrinsic interference among the symbols and complicates channel estimation (CE). An efficient way to improve the CE in FBMC-OQAM is using a technique known as windowed frequency domain averaging (FDA); however, it requires a priori knowledge of the window length parameter which is set based on the channel's frequency selectivity (FS). As the channel's FS is not fixed and not a priori known, we propose a k-nearest neighbor-based machine learning algorithm to classify the FS and decide on the FDA's window length. A comparative theoretical analysis of the mean-squared error (MSE) is performed to prove the proposed CE scheme's effectiveness, validated through extensive simulations. The adaptive CE scheme is shown to yield a reduction in CE-MSE and improved bit error rates compared with the popular preamble-based CE schemes for FBMC-OQAM, without a priori knowledge of channel's frequency selectivity.     

Gain Adapted Optimum Mixture Estimation Scheme for Single Channel Speech Separation

This paper presents the proof of an Optimum mixture estimator for the single channel speech separation problem, which is a technique for separating two speech signals from a single recording of their mixture. The presented work is an attempt to solve a fundamental limitation in the current single channel speech separation techniques, in which it is assumed that the data used in the training as well as test phases of the separation model have the same energy levels. To overcome this limitation, a gain adapted Optimum mixture estimator is derived, which estimates the mixture of speech signals under the different signal-to-signal ratios (SSRs). Specifically, the speakers’ gains are incorporated as unknown parameters into the separation model, and then the estimator is derived in terms of the source distributions and SSR. It is demonstrated that the use of the Optimum mixture estimator results in the lower estimation error than the non-linear mapping (log and inverse-log operations)-based Mixture-Maximization (MixMax) or Quadratic estimators. The experimental results based on the real speech data also depict that the proposed estimator improves the mixture estimation performance significantly when compared with MixMax or Quadratic estimators with the gain adaptation.     

An Experimental Evaluation of Link Outage Due to Beam Wander in a Turbulent FSO Link

Wireless Personal Communications - Wireless communication using free space optics (FSO) is becoming attractive for data transmission purposes. However, the system performance gets affected by...     

Efficient methods for modelling substrate coupling in mixed-signalintegrated circuits

A key problem in the design of large mixed-signal circuits is the noise caused by the coupling of digital signals into the substrate. This paper describes methods that allow circuit designers to model efficiently such substrate noise in large mixed-signal SPICE designs. In the light of these techniques a new methodology is presented for efficiently modelling the substrate noise caused by current injection and its coupling to analogue signals; this is then extended to provide a real-time modelling capability. The practicality and the numerical efficiency of the methods are demonstrated on several prototype example circuits     

Emulating DC constant power load: a robust sliding mode control approach

This article presents emulation of a programmable power electronic, constant power load (CPL) using a dc/dc step-up (boost) converter. The converter is controlled by a robust sliding mode controller (SMC). A novel switching surface is proposed to ensure a required power sunk by the converter. The proposed dc CPL is simple in design, has fast dynamic response and high accuracy, and offers an inexpensive alternative to study converters for cascaded dc distribution power system applications. Furthermore, the proposed CPL is sufficiently robust against the input voltage variations. A laboratory prototype of the proposed dc CPL has been developed and validated with SMC realised through OPAL-RT platform. The capability of the proposed dc CPL is confirmed via experimentations in varied scenarios.     

3-D discrete shearlet transform and video processing

In this paper, we introduce a digital implementation of the 3-D shearlet transform and illustrate its application to problems of video denoising and enhancement. The shearlet representation is a multiscale pyramid of well-localized waveforms defined at various locations and orientations, which was introduced to overcome the limitations of traditional multiscale systems in dealing with multidimensional data. While the shearlet approach shares the general philosophy of curvelets and surfacelets, it is based on a very different mathematical framework, which is derived from the theory of affine systems and uses shearing matrices rather than rotations. This allows a natural transition from the continuous setting to the digital setting and a more flexible mathematical structure. The 3-D digital shearlet transform algorithm presented in this paper consists in a cascade of a multiscale decomposition and a directional filtering stage. The filters employed in this decomposition are implemented as finite-length filters, and this ensures that the transform is local and numerically efficient. To illustrate its performance, the 3-D discrete shearlet transform is applied to problems of video denoising and enhancement, and compared against other state-of-the-art multiscale techniques, including curvelets and surfacelets.