Use of a Neural Network to Predict Strength and Optimum Compositions of Natural Alumina-Silica-Based Geopolymers

In order to predict compressive strength of geopolymers prepared from alumina-silica natural products, based on the effect of Al 2 O 3 /SiO 2, Na 2 O/Al 2 O 3, Na 2 O/H 2 O, and Na/[Na+K], more than 50 pieces of data were gathered from the literature. The data was utilized to train and test a multilayer artificial neural network (ANN). Therefore a multilayer feedforward network was designed with chemical compositions of alumina silicate and alkali activators as inputs and compressive strength as output. In this study, a feedforward network with various numbers of hidden layers and neurons were tested to select the optimum network architecture. The developed three-layer neural network simulator model used the feedforward back propagation architecture, demonstrated its ability in training the given input/output patterns. The cross-validation data was used to show the validity and high prediction accuracy of the network. This leads to the optimum chemical composition and the best paste can be made from activated alumina-silica natural products using alkaline hydroxide, and alkaline silicate. The research results are in agreement with mechanism of geopolymerization.


Read More: http://ascelibrary.org/doi/abs/10.1061/(ASCE)MT.1943-5533.0000829

Portfolio of Compositions investigating ensemble improvisation, distributed and real-time scoring, and multi-nodal input and output

This output is a collection of compositions which explore issues of ensemble improvisation, ensemble management and orchestration, real-time and distributed scoring, multi-nodal inputs and outputs, and animated and graphic notation. Compositions include: Activities I; tutti, duet, trio, solo, quartet; Lewitt Notations I; Webwork I; and Sometimes I feel the space between people (voices) in terms of tempos. These compositions are presented in computer animated scores which are synchronized through the network and subject to real-time modification and control. They can be performed by ensembles distributed over large physical spaces connected by the network. The scores for these compositions include software which displays the animations to the performers, software to structure and disseminate score events, and triggering software that allows the control of a performance to be distributed. Scores can also include live electronics which are coordinated with graphic events.

Reduced-complexity iterative equalization for severe time-dispersive MIMO channels

In this paper, a reduced-complexity soft-interference-cancellation minimum mean-square-error.(SIC-MMSE) iterative equalization method for severe time-dispersive multiple-input-multiple-output (MIMO) channels is proposed. To mitigate the severe time dispersiveness of the channel, a single carrier with cyclic prefix is employed, and the equalization is per-formed in the frequency domain. This simplifies the challenging problem of equalization in MIMO channels due to both the intersymbol interference (ISI) and the coantenna interference (CAI). The proposed iterative algorithm works in two stages. The first stage estimates the transmitted frequency-domain symbols using a low-complexity SIC-MMSE equalizer. The second stage converts the estimated frequency-domain symbols in the time domain and finds their means and variances to incorporate in the SIC-MMSE equalizer in the next iteration. Simulation results show the bit-/symbol-error-rate performance of the SIC-MMSE equalizer, with and without coding, for various modulation schemes.

Multiple Input Governor Control for a Diesel Generating Set

The paper presents a multiple input single output fuzzy logic governor algorithm that can be used to improve the transient response of a diesel generating set, when supplying an islanded load. The proposed governor uses the traditional speed input in addition to voltage and power factor to modify the fuelling requirements during various load disturbances. The use of fuzzy logic control allows the use of PID type structures that can provide variable gain strategies to account for non-linearities in the system. Fuzzy logic also provides a means of processing other input information by linguistic reasoning and a logical control output to aid the governor action during transient disturbance. The test results were obtained using a 50 kVA naturally aspirated diesel generator testing facility. Both real and reactive load tests were conducted. The complex load test results demonstrate that, by using additional inputs to the governor algorithm, enhanced generator transient speed recovery response can be obtained.

Iterative Multiuser Detection and Decoding for DS-CDMA System With Space-Time Linear Dispersion

This paper considers a Q-ary orthogonal direct-sequence code-division multiple-access (DS-CDMA) system with high-rate space-time linear dispersion codes (LDCs) in time-varying Rayleigh fading multiple-input-multiple-output (MIMO) channels. We propose a joint multiuser detection, LDC decoding, Q-ary demodulation, and channel-decoding algorithm and apply the turbo processing principle to improve system performance in an iterative fashion. The proposed iterative scheme demonstrates faster convergence and superior performance compared with the V-BLAST-based DS-CDMA system and is shown to approach the single-user performance bound. We also show that the CDMA system is able to exploit the time diversity offered by the LDCS in rapid-fading channels.

A fast multi-output RBF neural network construction method

This paper investigates the center selection of multi-output radial basis function (RBF) networks, and a multi-output fast recursive algorithm (MFRA) is proposed. This method can not only reveal the significance of each candidate center based on the reduction in the trace of the error covariance matrix, but also can estimate the network weights simultaneously using a back substitution approach. The main contribution is that the center selection procedure and the weight estimation are performed within a well-defined regression context, leading to a significantly reduced computational complexity. The efficiency of the algorithm is confirmed by a computational complexity analysis, and simulation results demonstrate its effectiveness. (C) 2010 Elsevier B.V. All rights reserved.

Approaching near-capacity on a multi-antenna channel using successive decoding and interference cancellation receivers

In this paper, we address the problem of designing multirate codes for a multiple-input and multiple-output (MIMO) system by restricting the receiver to be a successive decoding and interference cancellation type, when each of the antennas is encoded independently. Furthermore, it is assumed that the receiver knows the instantaneous fading channel states but the transmitter does not have access to them. It is well known that, in theory, minimum-mean-square error (MMSE) based successive decoding of multiple access (in multi-user communications) and MIMO channels achieves the total channel capacity. However, for this scheme to perform optimally, the optimal rates of each antenna (per-antenna rates) must be known at the transmitter. We show that the optimal per-antenna rates at the transmitter can be estimated using only the statistical characteristics of the MIMO channel in time-varying Rayleigh MIMO channel environments. Based on the results, multirate codes are designed using punctured turbo codes for a horizontal coded MIMO system. Simulation results show performances within about one to two dBs of MIMO channel capacity.

Dynamic Linear Precoding for the Exploitation of Known Interference in MIMO Broadcast Systems

This paper introduces a novel channel inversion (CI) precoding scheme for the downlink of phase shift keying (PSK)-based multiple input multiple output (MIMO) systems. In contrast to common practice where knowledge of the interference is used to eliminate it, the main idea proposed here is to use this knowledge to glean benefit from the interference. It will be shown that the system performance can be enhanced by exploiting some of the existent inter-channel interference (ICI). This is achieved by applying partial channel inversion such that the constructive part of ICI is preserved and exploited while the destructive part is eliminated by means of CI precoding. By doing so, the effective signal to interference-plus-noise ratio (SINR) delivered to the mobile unit (MU) receivers is enhanced without the need to invest additional transmitted signal power at the MIMO base station (BS). It is shown that the trade-off to this benefit is a minor increase in the complexity of the BS processing. The presented theoretical analysis and simulations demonstrate that due to the SINR enhancement, significant performance and throughput gains are offered by the proposed MIMO precoding technique compared to its conventional counterparts.

AND Logic Gates Based on Small Molecules with Chemical Inputs and Luminescence Output

AND logic gate behaviour can be recognized in chemical-responsive luminescence phenomena concerning small molecules. Though initial developments concerned separate and distinguishable chemical species as inputs, consideration of other types of input sets allows substantial expansion of the sub-field. Dissection of these molecular devices into modules, where possible, enables analysis of their logic behaviour according to supramolecular photochemical mechanisms.

Designing computer architecture research workloads

MinneSPEC proposes reduced input sets that microprocessor designers can use to model representative short-running workloads. A four-step methodology verifies the program behavior similarity of these input sets to reference sets.

Software-defined sphere decoding for FPGA-based MIMO detection

Sphere Decoding (SD) is a highly effective detection technique for Multiple-Input Multiple-Output (MIMO) wireless communications receivers, offering quasi-optimal accuracy with relatively low computational complexity as compared to the ideal ML detector. Despite this, the computational demands of even low-complexity SD variants, such as Fixed Complexity SD (FSD), remains such that implementation on modern software-defined network equipment is a highly challenging process, and indeed real-time solutions for MIMO systems such as 4 4 16-QAM 802.11n are unreported. This paper overcomes this barrier. By exploiting large-scale networks of fine-grained softwareprogrammable processors on Field Programmable Gate Array (FPGA), a series of unique SD implementations are presented, culminating in the only single-chip, real-time quasi-optimal SD for 44 16-QAM 802.11n MIMO. Furthermore, it demonstrates that the high performance software-defined architectures which enable these implementations exhibit cost comparable to dedicated circuit architectures.

A Kernel Interleaved Scheduling Method for Streaming Applications on Soft-core Vector Processors

Massively parallel networks of highly efficient, high performance Single Instruction Multiple Data (SIMD) processors have been shown to enable FPGA-based implementation of real-time signal processing applications with performance and
cost comparable to dedicated hardware architectures. This is achieved by exploiting simple datapath units with deep processing pipelines. However, these architectures are highly susceptible to pipeline bubbles resulting from data and control hazards; the only way to mitigate against these is manual interleaving of
application tasks on each datapath, since no suitable automated interleaving approach exists. In this paper we describe a new automated integrated mapping/scheduling approach to map algorithm tasks to processors and a new low-complexity list scheduling technique to generate the interleaved schedules. When applied to a spatial Fixed-Complexity Sphere Decoding (FSD) detector
for next-generation Multiple-Input Multiple-Output (MIMO) systems, the resulting schedules achieve real-time performance for IEEE 802.11n systems on a network of 16-way SIMD processors on FPGA, enable better performance/complexity balance than current approaches and produce results comparable to handcrafted implementations.

Amplitude-modulation characteristics of power-combining Class-E amplifier with finite choke

Power back-off performances of a new variant power-combining Class-E amplifier under different amplitude-modulation schemes such as continuous wave (CW), envelope elimination and restoration (EER), envelope tracking (ET) and outphasing are for the first time investigated in this study. Finite DC-feed inductances rather than massive RF chokes as used in the classic single-ended Class-E power amplifier (PA) resulted from the approximate yet effective frequency-domain circuit analysis provide the wherewithal to increase modulation bandwidth up to 80% higher than the classic single-ended Class-E PA. This increased modulation bandwidth is required for the linearity improvement in the EER/ET transmitters. The modified output load network of the power-combining Class-E amplifier adopting three-harmonic terminations technique relaxes the design specifications for the additional filtering block typically required at the output stage of the transmitter chain. Qualitative agreements between simulation and measurement results for all four schemes were achieved where the ET technique was proven superior to the other schemes. When the PA is used within the ET scheme, an increase of average drain efficiency of as high as 40% with respect to the CW excitation was obtained for a multi-carrier input signal with 12 dB peak-to-average power ratio. © 2011 The Institution of Engineering and Technology.