Random neural networks with synchronized interactions

Large-scale distributed systems, such as natural neuronal and artificial systems, have many local interconnections, but they often also have the ability to propagate information very fast over relatively large distances. Mechanisms that enable such behavior include very long physical signaling paths and possibly saccades of synchronous behavior that may propagate across a network. This letter studies the modeling of such behaviors in neuronal networks and develops a related learning algorithm. This is done in the context of the random neural network (RNN), a probabilistic model with a well-developed mathematical theory, which was inspired by the apparently stochastic spiking behavior of certain natural neuronal systems. Thus, we develop an extension of the RNN to the case when synchronous interactions can occur, leading to synchronous firing by large ensembles of cells. We also present an O(N3) gradient descent learning algorithm for an N-cell recurrent network having both conventional excitatory-inhibitory interactions and synchronous interactions. Finally, the model and its learning algorithm are applied to a resource allocation problem that is NP-hard and requires fast approximate decisions.     

Printing highly efficient organic solar cells

The technological attraction in organic solar cells is their compatibility to printing processes. However, up to today, nearly no literature on "printed" organic solar cells have been published and the major body of the research work was done by spin coating or blading techniques. Transferring the spin-coating or doctor blading process currently used for the fabrication of bulk heterojunction solar cell to a printing process holds morphological challenges that have not been observed or reported up to today. We highlight these challenges and we show that inkjet printing of organic bulk heterojunction solar cells requires completely novel approaches and skill sets compared to the current state of the art. By adjusting the chemical properties of the poly(3-hexylthiophene) polymer donor and by using our recently developed inkjet solvent mixture, we have gained control over the nanomorphology of poly(3-hexylthiophene):fullerene blends during the printing process and report a new record power conversion efficiency of 3.5% for inkjet printed poly(3-hexylthiophene):fullerene based solar cells.     

Blind Position Location via Geometric Loci Construction

A new position location technique is proposed, using received signal strength measurements, which can be implemented using inexpensive off-the-shelf equipment. The proposed technique is based on geometric loci construction, and overcomes the need for onsite calibration measurements or propagation prediction tools and topographical/architectural plans of the covered area. The proposed algorithm exhibits similar simulated performance compared to a recently proposed positioning technique, but without the need of model calibration. In addition, measurements results are also presented, demonstrating the performance of the algorithm.     

An EWMA signed ranks control chart with reliable run length performances

During the design phase of a control chart, the determination of its exact run length properties plays a vital role for its optimal operation. Markov chain or integral equation methods have been extensively applied in the design phase of conventional control charts. However, for distribution-free schemes, due to the discrete nature of the statistics being used (such as the sign or the Wilcoxon signed rank statistics, for instance), it is impossible to accurately compute their run length properties. In this work, a modified distribution-free phase II exponentially weighted moving average (EWMA)-type chart based on the Wilcoxon signed rank statistic is considered and its exact run length properties are discussed. A continuous transformation of the Wilcoxon signed rank statistic, combined with the classical Markov chain method, is used for the determination of the average run length in the in- and out-of control cases. Moreover, its exact performance is derived without any knowledge of the distribution of sample observations. Finally, an illustrative example is provided showing the practical implementation of our proposed chart.     

Three-level designs: Evaluation and comparison for screening purposes

Since their introduction by Box and Hunter, resolution criteria have been widely used when comparing regular fractional factorials designs. In this article, we investigate how a generalized resolution criterion can be used to assess some recently developed three-level screening designs, such as definitive screening designs (DSDs) and screening designs from weighing matrices. The aim of this paper is to capture the projection properties of those three-level screening designs, complementing the work of Deng and Tang, who used generalized resolution and minimum aberration criteria for ranking different two-level designs, particularly Plackett-Burman and other nonregular factorial designs. An advantage of generalized resolution, extended here to work on three-level designs, is that it offers a useful criterion for ranking three-level screening designs, whereas the Deng and Tang resolution is used mainly for the assessment of two-level designs. In addition, we applied a projection estimation capacity (PEC) criterion to select three-level screening designs with desirable properties. Practical examples and the best projections of the designs are presented in tables.     

Sensor integration and data fusion

The problem of sensor integration and data fusion is addressed. We consider the problem of combining information from diversified sources in a coherent fashion. We assume that information from various sensors may be available in different forms at the fusion. For example, data from infrared (IR) sensors may be combined with range radar (RR) data and further combined with visual images. In each case, data and information from different sensors are presented in a different format which may not be directly compatible for all sensors. Part of the available information may be in the form of attributes and part in the form of dynamical measurements. A generalized evidence processing theory and an architecture for sensor integration and data fusion that accommodates diversified sources of information are presented. Data (or, more generically, information) fusion may take place at different levels, such as the level of dynamics, the level of attributes, and the level of evidence. The common and different aspects of fusion at the different levels are investigated and several practical examples of real world data fusion problems are discussed.     

Image reconstruction based on human and monkey cone mosaics

The image reconstruction capacity of the actual foveal cone sampling mosaics of an adult monkey and human is investigated through computer simulations. A retinocortical mapping model in which positions are known and disorder is compensated (DC) has been implemented using classical Whittaker-Kotelnikov-Shannon (WKS) reconstruction theory and a two-dimensional hexagonal tessellation technique that maps the cone lattice onto a perfectly hexagonal grid. The DC model has been compared with a retinocortical mapping model in which cone positions are also known but position disorder is uncompensated (DU) in the reconstruction process. A control model has also been implemented using WKS reconstruction based on sampled data obtained with simulated perfectly hexagonal lattices whose Nyquist limits are equivalent to those of the human and monkey lattices. Quantitative comparisons of these models are based on the RMS error per pixel between the original and reconstructed images. Results of these simulations demonstrate a pronounced superiority of the DC over the DU model. The results of these simulations, which use “biologically correct” sampling lattices, document a potential image reconstruction advantage when foveal cone positions are known.     

Simulation of an industrial computer system—A case study

The purpose of this work was to explain long term variations in computer system performance by developing and using a simple discrete event simulation model. The system studied was an IBM 370/165 (with OS/MVT) used by a major U.S. corporation over the 3 yr period of 1972 through 1974. The model was calibrated and validated against data from the actual system and was successfully used to develop relationships between work load, hardware configuration, and performance. These results were used to establish the cause of major degradations in service levels that had been experienced on the actual system and provide insight into functional dependencies otherwise unobtainable. The study demonstrated that a reasonable match between the behavior of a complex computer system in the real and simulated worlds can be obtained by using straightforward simulation techniques and readily available performance data.     

Frequency-Dependent Attenuation Effects in Pulsed Doppler Ultrasound: Experimental Results

The quantitative capability of pulsed Doppler ultrasound in clinical practice is limited by the effects of frequency-dependent attenuation of ultrasound in tissue, as well as several other spectral-broadening mechanisms which distort the Doppler spectrum of an ultrasonic echo. In this communication, we present results of in vitro experiments which demonstrate the magnitude of the errors expected in clinical measurements of blood flow parameters when frequency-dependent attenuation Of ultrasound in biological tissue is ignored. It is shown that errors as large as 15 percent may occur in Doppler measurements of blood flow velocity through 7 cm of intervening tissue. A comparison is also made between experimental results and a theoretical model which includes the effects of scattering and attenuation.