A Neural Network Approach for Signal Detection in Digital Communications

In this paper, we propose a new approach for signal detection in wireless digital communications based on the neural network with transient chaos and time-varying gain (NNTCTG), and give a concrete model of the signal detector after appropriate transformations and mappings. It is well known that the problem of the maximum likelihood signal detection can be described as a complex optimization problem that has so many local optima that conventional Hopfield-type neural networks fail to solve. By refraining from the serious local optima problem of Hopfield-type neural networks, the NNTCTG makes use of the time-varying parameters of the recurrent neural network to control the evolving behavior of the network so that the network undergoes the transition from chaotic behavior to gradient convergence. It has richer and more flexible dynamics rather than conventional neural networks only with point attractors, so that it can be expected to have much ability to search for globally optimal or near-optimal solutions. After going through a transiently inverse-bifurcation process, the NNTCTG can approach the global optimum or the neighborhood of global optimum of our problem. Simulation experiments have been performed to show the effectiveness and validation of the proposed neural network based method for the signal detection in digital communications.     

锗γ能谱测量中的符合相加修正

本文介绍了锗γ能谱测量中符合相加修正的原理和方法,给出了修正公式。分别计算了不同几何条件下两个锗探测器对一些放射性核素的符合相加修正因子,估计了符合相加修正因子对活度测量结果的误差贡献。     

Sequential tripping strategy for a transmission network back-upprotection expert system

This paper describes a sequential tripping strategy used in a wide area back-up protection expert system (BPES) to combat situations in which protection relays have maloperated or information is missing. The BPES is an innovative back-up protection scheme designed to prevent the occurrence of widespread blackouts. The BPES evaluates the certainty that transmission lines are likely to be affected by the fault and uses a sequential tripping strategy to isolate the fault if a firm decision is not available due to maloperated relays and/or missing information. The mode of analysis and the sequential tripping strategy ensures that the BPES will clear a fault at minimum risk to the network. An example is included to demonstrate how the certainty factor based sequential tripping strategy is employed by the BPES to clear a fault which occurred on the South Western part of the UK National Grid System     

Effects of solid retention time on the performance of submerged anoxic/oxic membrane bioreactor.

In this study, four similar bench-scale submerged Anoxic/Oxic Membrane Bioreactors (MBR) were used simultaneously to investigate the effects of solids retention time (SRT) on organic and nitrogen removal in MBR for treating domestic wastewater. COD removal efficiencies in all reactors were consistently above 94% under steady state conditions. Complete conversion of NH(4+)-N to NO(3-)-N was readily achieved over a feed NH(4+)-N concentration range of 30 to 50 mg/L. It was also observed that SRT did not significantly affect the nitrification in the MBR systems investigated. The average denitrification efficiencies for the 3, 5, 10 and 20 days SRT operations were 43.9, 32.6, 47.5 and 66.5%, respectively. In general, the average effluent nitrogen concentrations, which were mainly nitrate, were about 22.2, 27.6, 21.7 and 13.9 mg/L for the 3, 5, 10 and 20 days SRT systems, respectively. The rate of membrane fouling at 3 days SRT operation was more rapid than that observed at 5 days SRT. No fouling was noted in the 10 days and 20 days SRT systems during the entire period of study.     

Photoreactivation of Escherichia coli following medium-pressure ultraviolet disinfection and its control using chloramination.

Ultraviolet (UV) disinfection is becoming increasingly popular as an alternative disinfection technology to chlorination in recent years. In this study, we investigated the photoreactivation of Escherichia coli following medium-pressure (MP) UV disinfection of synthetic water by a bench-scale collimated beam apparatus. The UV doses ranged from 1.6 -19.7 mWs/cm2 and photoreactivation was investigated for 6 hours under fluorescent light. In addition, chloramination was applied after UV disinfection to investigate its ability to control photoreactivation. It was found that photoreactivation occurred for all UV doses tested and the increase in bacteria numbers ranged from 0.04 to 1.35 log10. However, the degree of photoreactivation decreased with increased UV doses. Chloramination experiments revealed that the addition of 0.5 mg/l of monochloramine resulted in suppression of photoreactivation for 1 hour only. An increased monochloramine dose of 1 mg/l was found to prevent photoreactivation for the entire duration of the experiment. The results of this study have shown that photoreactivation occurs even after MP UV disinfection, although it is of a lesser extent at higher UV doses. This study has also established that secondary chloramination can effectively suppress and eliminate photoreactivation with a chloramine dose of 1 mg/l.     

Expert system application for the loading capability assessment oftransmission lines

This paper describes the application of an expert system for the evaluation of the short-term thermal rating and temperature rise of overhead conductors. The expert system has been developed using a database and Leonardo expert system shell which is gaining popularity among commercial tools for developing expert system applications. The expert system has been found to compare well when evaluated against site tests. A practical application is given to demonstrate the usefulness of the expert system developed     

Assessment of underground cable ratings based on distributed temperature sensing

Numerous power utilities have installed advanced distributed temperature sensing (DTS) systems to measure the temperature of underground cables. This paper presents a general procedure for real-time assessment of underground cable ratings based on DTS. After the identification and location of hot spots on a cable, the cable installation data, load, and DTS-recorded temperature over a period of time are used to estimate soil thermal parameters and assess cable ratings under normal and overloading conditions. In order to accurately estimate soil thermal parameters, a combined technique of the finite-element method and gradient-based optimization is used. The technique was validated in the laboratory and applied to a rating assessment of a 230-kV/500-MVA cable circuit. The assessed continuous and emergency ratings are helpful in improving the operation of this circuit.     

Exploratory analysis of brain connectivity with ICA.

Covariance-based methods of exploration of functional connectivity of the brain from functional magnetic resonance imaging (fMRI) experiments, such as principal component analysis (PCA) and structural equation modeling (SEM), require a priori knowledge such as an anatomical model to infer functional connectivity. In this research, a hybrid method, combining independent component analysis (ICA) and SEM, which is capable of deriving functional connectivity in an exploratory manner without the need of a prior model is introduced. The spatial ICA (SICA) derives independent neural systems or sources involved in task-related brain activation, while an automated method based on the SEM finds the structure of the connectivity among the elements in independent neural systems. Unlike second-order approaches used in earlier studies, the task-related neural systems derived from the ICA provide brain connectivity in the complete statistical sense. The use and efficacy of this approach is illustrated on two fMRI datasets obtained from a visual task and a language reading task.     

A neural network control system with parallel adaptive enhancementsapplicable to nonlinear servomechanisms

In this paper, we present a technique for using an additional parallel neural network to provide adaptive enhancements to a basic fixed neural network-based nonlinear control system. This proposed parallel adaptive neural network control system is applicable to nonlinear dynamical systems of the type commonly encountered in many practical position control servomechanisms. Properties of the controller are discussed, and it is shown that if Gaussian radial basis function networks are used for the additional parallel neural network, uniformly stable adaptation is assured and the approximation error converges to zero asymptotically. In the paper, the effectiveness of the proposed parallel adaptive neural network control system is demonstrated in real-time implementation experiments for position control in a servomechanism with asymmetrical loading and changes in the load     

Enhancement of oxide break-up by implantation of fluorine inpoly-Si emitter contacted p+-n shallow junctionformation

In this study, it is demonstrated that the incorporation of fluorine can enhance poly-Si/Si interfacial oxide break-up in the poly-Si emitter contacted p⁺-n shallow junction formation. The annealing temperature for breaking up the poly-Si/Si interfacial oxide has been found to be as low as 900°C. As a result, the junction depth of the BF₂-implanted device is much larger than that of the boron-implanted device