A single microphone capillary-based system for measuring the complex input impedance of musical wind instruments

Capillary-based systems for measuring the input impedance of musical wind instruments were first developed in the mid-20th century and remain in widespread use today. In this paper, the basic principles and assumptions underpinning the design of such systems are examined. Inexpensive modifications to a capillary-based impedance measurement set-up made possible due to advances in computing and data acquisition technology are discussed. The modified set-up is able to measure both impedance magnitude and impedance phase even though it only contains one microphone. In addition, a method of calibration is described that results in a significant improvement in accuracy when measuring high impedance objects on the modified capillary-based system. The method involves carrying out calibration measurements on two different objects whose impedances are well-known theoretically. The benefits of performing two calibration measurements (as opposed to the one calibration measurement that has been traditionally used) are demonstrated experimentally through input impedance measurements on two test objects and a Boosey and Hawkes oboe. © S. Hirzel Verlag · EAA.

Changing climate, changing process: implications for salt transportation and weathering within building sandstones in the UK

Salt weathering is a crucial process that brings about a change in stone, from the scale of landscapes to stone outcrops and natural building stone facades. It is acknowledged that salt weathering is controlled by fluctuations in temperature and moisture, where repeated oscillations in these parameters can cause re-crystallisation, hydration/de-hydration of salts, bringing about stone surface loss in the form of, for example, granular disaggregation, scaling, and multiple flaking. However, this ‘traditional’ view of how salt weathering proceeds may need to be re-evaluated in the light of current and future climatic trends. Indeed, there is considerable scope for the investigation of consequences of climate change on geomorphological processes in general. Building on contemporary research on the ‘deep wetting’ of natural building stones, it is proposed that (as stone may be wetter for longer), ion diffusion may become a more prominent mechanism for the mixing of molecular constituents, and a shift in focus from physical damage to chemical change is suggested. Data from ion diffusion cell experiments are presented for three different sandstone types, demonstrating that salts may diffuse through porous stone relatively rapidly (in comparison to, for example, dense concrete). Pore water from stones undergoing diffusion experiments was extracted and analysed. Factors controlling ion diffusion
relating to ‘time of wetness’ within stones are discussed, (continued saturation, connectivity of pores, mineralogy, behaviour of salts, sedimentary structure), and potential changes in system dynamics as a result of climate change are addressed. System inputs may change in terms of increased moisture input, translating into a greater depth of wetting front. Salts are likely to be ‘stored’ differently in stones, with salt being in solution for longer periods (during prolonged winter wetness). This has myriad implications in terms of the movement of ions by diffusion and the potential for chemical change in the stone (especially in more mobile constituents), leading to a weakening of the stone matrix/grain boundary cementing. The ‘output’ may be mobilisation and precipitation of elements leading to, for example, uneven cementing in the stone. This reduced strength of the stone, or compromised ability of the stone to absorb stress, is likely to make crystallisation a more efficacious mechanism of decay when it does occur. Thus, a delay in the onset of crystallisation while stonework is wet does not preclude exaggerated or accelerated material loss when it finally happens.

Low-Power Process-Variation Tolerant Arithmetic Units Using Input-Based Elastic Clocking

In this paper we propose a design methodology for low-power high-performance, process-variation tolerant architecture for arithmetic units. The novelty of our approach lies in the fact that possible delay failures due to process variations and/or voltage scaling are predicted in advance and addressed by employing an elastic clocking technique. The prediction mechanism exploits the dependence of delay of arithmetic units upon input data patterns and identifies specific inputs that activate the critical path. Under iso-yield conditions, the proposed design operates at a lower scaled down Vdd without any performance degradation, while it ensures a superlative yield under a design style employing nominal supply and transistor threshold voltage. Simulation results show power savings of upto 29%, energy per computation savings of upto 25.5% and yield enhancement of upto 11.1% compared to the conventional adders and multipliers implemented in the 70nm BPTM technology. We incorporated the proposed modules in the execution unit of a five stage DLX pipeline to measure performance using SPEC2000 benchmarks [9]. Maximum area and throughput penalty obtained were 10% and 3% respectively.

MSC-clustering and forward stepwise regression for virtual metrology in highly correlated input spaces

Increasingly semiconductor manufacturers are exploring opportunities for virtual metrology (VM) enabled process monitoring and control as a means of reducing non-value added metrology and achieving ever more demanding wafer fabrication tolerances. However, developing robust, reliable and interpretable VM models can be very challenging due to the highly correlated input space often associated with the underpinning data sets. A particularly pertinent example is etch rate prediction of plasma etch processes from multichannel optical emission spectroscopy data. This paper proposes a novel input-clustering based forward stepwise regression methodology for VM model building in such highly correlated input spaces. Max Separation Clustering (MSC) is employed as a pre-processing step to identify a reduced srt of well-conditioned, representative variables that can then be used as inputs to state-of-the-art model building techniques such as Forward Selection Regression (FSR), Ridge regression, LASSO and Forward Selection Ridge Regression (FCRR). The methodology is validated on a benchmark semiconductor plasma etch dataset and the results obtained are compared with those achieved when the state-of-art approaches are applied directly to the data without the MSC pre-processing step. Significant performance improvements are observed when MSC is combined with FSR (13%) and FSRR (8.5%), but not with Ridge Regression (-1%) or LASSO (-32%). The optimal VM results are obtained using the MSC-FSR and MSC-FSRR generated models. © 2012 IEEE.

Space-Constrained Massive MIMO: Hitting the Wall of Favorable Propagation

The recent development of the massive multiple-input multiple-output (MIMO) paradigm, has been extensively based on the pursuit of favorable propagation: in the asymptotic limit, the channel vectors become nearly orthogonal and interuser interference tends to zero [1]. In this context, previous studies
have considered fixed inter-antenna distance, which implies an increasing array aperture as the number of elements increases. Here, we focus on a practical, space-constrained topology, where an increase in the number of antenna elements in a fixed total space imposes an inversely proportional decrease in the inter-antenna distance. Our analysis shows that, contrary to existing studies, inter-user interference does not vanish in the massive MIMO regime, thereby creating a saturation effect on the achievable rate.

A Coordination and Ligand Replacement Based Three-Input Colorimetric Logic Gate Sensing Platform for Melamine, Mercury Ions, and Cysteine

Discrimination of different species in various target scopes within a single sensing platform can provide many advantages such as simplicity, rapidness, and cost effectiveness. Here we design a three-input colorimetric logic gate based on the aggregation and anti-aggregation of gold nanoparticles (Au NPs) for the sensing of melamine, cysteine, and Hg2+. The concept takes advantages of the highly specific coordination and ligand replacement reactions between melamine, cysteine, Hg2+, and Au NPs. Different outputs are obtained with the combinational inputs in the logic gates, which can serve as a reference to discriminate different analytes within a single sensing platform. Furthermore, besides the intrinsic sensitivity and selectivity of Au NPs to melamine-like compounds, the “INH” gates of melamine/cysteine and melamine/Hg2+ in this logic system can be employed for sensitive and selective detections of cysteine and Hg2+, respectively.

Lanthanide luminescent logic gate mimics in soft matter: [H(+)] and [F(-)] dual-input device in a polymer gel with potential for selective component release

The non-covalent incorporation of responsive luminescent lanthanide, Ln(iii), complexes with orthogonal outputs from Eu(iii) and Tb(iii) in a gel matrix allows for in situ logic operation with colorimetric outputs. Herein, we report an exemplar system with two inputs ([H(+)] and [F(-)]) within a p(HEMA-co-MMA) polymer organogel acting as a dual-responsive device and identify future potential for such systems.

Statistical Eigenmode Transmission for the MU-MIMO Downlink in Rician Fading

In this paper, we study the achievable ergodic sum-rate of multiuser multiple-input multiple-output downlink systems in Rician fading channels. We first derive a lower bound on the average signal-to-leakage-and-noise ratio by using the Mullen’s inequality, and then use it to analyze the effect of channel mean information on the achievable ergodic sum-rate. A novel statistical-eigenmode space-division multiple-access (SESDMA) downlink transmission scheme is then proposed. For this scheme, we derive an exact analytical closed-form expression for the achievable ergodic rate and present tractable tight upper and lower bounds. Based on our analysis, we gain valuable insights into the system parameters, such as the number of transmit antennas, the signal-to-noise ratio (SNR) and Rician K-factor on the system sum-rate. Results show that the sum-rate converges to a saturation value in the high SNR regime and tends to a lower limit for the low Rician K-factor case. In addition, we compare the achievable ergodic sum-rate between SE-SDMA and zeroforcing beamforming with perfect channel state information at the base station. Our results reveal that the rate gap tends to zero in the high Rician K-factor regime. Finally, numerical results are presented to validate our analysis.

Achievable sum-rate of multiuser massive MIMO downlink in ricean fading channels

We investigate the achievable ergodic sum-rate of multi-user multiple-input multiple-output systems in Ricean fading channels. We first derive a lower bound on the average signal-to-leakage-and-noise ratio by utilizing the Mullen's inequality, which is then used to analyze the effect of channel mean information on the achievable sum-rate. With these results, a novel statistical-eigenmode space-division multipleaccess downlink transmission scheme is proposed. For this scheme, we derive an exact closed-form expression for the achievable ergodic sum-rate. Our results show that the achievable ergodic sum-rate converges to a saturation value in the high signal-to-noise ratio (SNR) region and reaches to a lower limit value in the lower Ricean K-factor range. In addition, we present tractable upper and lower bounds, which are shown to be tight for any SNR and Ricean K-factor value. Finally, the theoretical analysis is validated via numerical simulations.

Massive MIMO in sparse channels

Massive multi-user multiple-input multiple-output (MU-MIMO) systems are cellular networks where the base stations (BSs) are equipped with hundreds of antennas, N, and communicate with tens of mobile stations (MSs), K, such that, N ≫ K ≫ 1. Contrary to most prior works, in this paper, we consider the uplink of a single-cell massive MIMO system operating in sparse channels with limited scattering. This case is of particular importance in most propagation scenarios, where the prevalent Rayleigh fading assumption becomes idealistic. We derive analytical approximations for the achievable rates of maximum-ratio combining (MRC) and zero-forcing (ZF) receivers. Furthermore, we study the asymptotic behavior of the achievable rates for both MRC and ZF receivers, when N and K go to infinity under the condition that N/K → c ≥ 1. Our results indicate that the achievable rate of MRC receivers reaches an asymptotic saturation limit, whereas the achievable rate of ZF receivers grows logarithmically with the number of MSs.