DSS research and practice in perspective

The aim of this paper is to assess the state-of-the-art in the Decision Support Systems (DSS) field from both a research and a practice perspective. Three main dimensions of DSS research and practice are addressed: 1) supporting human decision-making processes, 2) integrating DSS into the organizational context, and 3) identifying new application domains. The related analysis and discussion provides a better understanding of past developments in the DSS field and insights into future evolution patterns.     

Direct sequential evaluation of optimal orthonormal eigenvectors of the discrete Fourier transform matrix by constrained optimization

The recent emergence of the discrete fractional Fourier transform has spurred research activity aiming at generating Hermite–Gaussian-like (HGL) orthonormal eigenvectors of the discrete Fourier transform (DFT) matrix F. By exploiting the unitarity of matrix F – resulting in the orthogonality of its eigenspaces pertaining to the distinct eigenvalues – the problem decouples into finding orthonormal eigenvectors for each eigenspace separately. A Direct Sequential Evaluation by constrained Optimization Algorithm (DSEOA) is contributed for the generation of optimal orthonormal eigenvectors for each eigenspace separately. This technique is direct in the sense that it does not require the generation of initial orthonormal eigenvectors as a prerequisite for obtaining the final optimal ones. The resulting eigenvectors are optimal in the sense of being as close as possible to samples of the Hermite–Gaussian functions. The technique is found to be numerically robust because total pivoting is allowed in performing the QR matrix decomposition step. The DSEOA is proved to be theoretically equivalent to each of the Gram–Schmidt algorithm (GSA) and the sequential orthogonal Procrustes algorithm (SOPA). However the three techniques are algorithmically quite distinct. An extensive comparative simulation study shows that the DSEOA is by far the most numerically robust technique among all sequential algorithms thus paying off for its relatively long computation time.     

Corrosion-resistant lightweight metallic bipolar plates for PEM fuel cells

Corrosion resistant treated metal bipolar plates with higher rigidity and electrical conductivity than graphite were developed and tested for PEM fuel cell applications. Six replicas of single cells were used three of which were made of graphite composites bipolar plates and the other three of the treated metallic plates. A Membrane Electrode Assembly (MEA) with 5.55 cm² active electrode areas, 0.3 mg cm^–2 Pt loading and Nafion membrane 115 was fitted to each cell and operated under identical conditions. The experimental testing was conducted at room temperature (20 °C). The average value of the data obtained for the three graphite cells was plotted. Similarly, the average value of the data obtained for the three treated metal cells was plotted on the same graph for comparison. Generally, the treated metal bipolar plate provided at least 12% saving in hydrogen consumption in comparison to graphite. This is attributed to the lower bulk and surface contact resistance of the metal used in this study in relation to graphite. The results of lifetime testing, conducted at room temperature under variable loading showed no indication of power degradation due to metal corrosion for at least 1500 hours.     

Processing of an East Mediterranean phosphate ore sample by an integrated attrition scrubbing/classification scheme (part one)

ABSTRACT

In this study, an Egyptian siliceous/calcareous sedimentary phosphorite was subjected to beneficiation by unsophisticated economic means. The mineralogical and chemical examination showed that the ore sample is a typical example for the East Mediterranean phosphorites with 21.80% P₂O₅, 10.93% acid insoluble and 16.61% loss on ignition. The primary crushed sample was classified into three size fractions without any milling and they were separately subjected to an integrated attrition scrubbing study. Screening and classification on the 2.30 mm and 0.071 mm sieves were sequentially introduced with the attrition process. The effect of solid%, attrition speed and time were studied and optimized for each size fraction. Results showed that three products were produced and could be categorized according to their P₂O₅ content into the coarse tailing (+2.30 mm), the attrition concentrate (?2.30 + 0.071 mm) and the phosphate fines (?0.071 mm). The P₂O₅ contents of these products reached 12.24%, 28.72% and 18.77%, with P₂O₅ distribution reached 6.74%, 51.75% and 41.51%, respectively. A global P₂O₅ of 28.72% was obtained with a recovery of about 52%. A tentative flow-sheet for the whole process was postulated.     

Long Duration Persistent Photocurrent in 3 nm Thin Doped Indium Oxide for Integrated Light Sensing and In-Sensor Neuromorphic Computation

Miniaturization and energy consumption by computational systems remain major challenges to address. Optoelectronics based synaptic and light sensing provide an exciting platform for neuromorphic processing and vision applications offering several advantages. It is highly desirable to achieve single-element image sensors that allow reception of information and execution of in-memory computing processes while maintaining memory for much longer durations without the need for frequent electrical or optical rehearsals. In this work, ultra-thin (<3 nm) doped indium oxide (In₂O₃) layers are engineered to demonstrate a monolithic two-terminal ultraviolet (UV) sensing and processing system with long optical state retention operating at 50 mV. This endows features of several conductance states within the persistent photocurrent window that are harnessed to show learning capabilities and significantly reduce the number of rehearsals. The atomically thin sheets are implemented as a focal plane array (FPA) for UV spectrum based proof-of-concept vision system capable of pattern recognition and memorization required for imaging and detection applications. This integrated light sensing and memory system is deployed to illustrate capabilities for real-time, in-sensor memorization, and recognition tasks. This study provides an important template to engineer miniaturized and low operating voltage neuromorphic platforms across the light spectrum based on application demand.     

Local Convergence of the Lavrentiev Method for the Cauchy Problem via a Carleman Inequality

The purpose is to perform a sharp analysis of the Lavrentiev method applied to the regularization of the ill-posed Cauchy problem, set in the Steklov-Poincaré variational framework. Global approximation results have been stated earlier that demonstrate that the Lavrentiev procedure yields a convergent strategy. However, no convergence rates are available unless a source condition is assumed on the exact Cauchy solution. We pursue here bounds on the approximation (bias) and the noise propagation (variance) errors away from the incomplete boundary where instabilities are located. The investigation relies on a Carleman inequality that enables enhanced local convergence rates for both bias and variance errors without any particular smoothness assumption on the exact solution. These improved results allows a new insight on the behavior of the Lavrentiev solution, look similar to those established for the Quasi-Reversibility method in [Inverse Problems 25, 035005, 2009]. There is a case for saying that this sort of ??super-convergence?? is rather inherent to the nature of the Cauchy problem and any reasonable regularization procedure would enjoy the same locally super-convergent behavior.     

The induced damage in the hepatopancreas of Orchestia species after exposure to a mixture of Cu/Zn—An ultrastructural study

The hepatopancreas of crustaceans species has been recognized as an essential target organ to assess trace elements' effects. Due to its dynamic and capability of detoxifying trace metal, this organ often indicates distinct pathological disturbances. In the present work, we intend to evaluate the bioaccumulation of trace metal in three Orchestia species (Orchestia montagui, Orchestia gammarellus, and Orchestia mediterranea) living in symmetry in the banks of Bizerte lagoon (37°13′8″N 09°55′1″E) after their exposure during 14 days to a mixture of copper and zinc, and to highlight the effect of these metals on their hepatopancreas ultrastructure using transmission electron microscopy. At the end of the experiment, results showed that the mortality and the body mass varied according to the used nominal concentrations. Significant alterations were noted in all the treatment groups. The degree of these alterations depends on the used concentration, and they are represented especially by the cells remoteness and the border lyses, the reduction of the nuclear volume, the increase in the cytoplasm density with the presence of trace metal in the nucleus as well as in the vacuole, the disorganization and the destruction of microvilli, the condensation of the majority of cellular organelles and mitochondria swelling. Through this study, Orchestia genus could be an attractive candidate for the biochemical study of trace metal toxicity in Tunisian wetlands.     

ANN-based techniques for estimating fault location on transmissionlines using Prony method

A system is proposed to locate faults on transmission lines using the traveling wave phenomenon. Prony method is used to analyze the voltage or current signal at the local bus and extract its modal information. This information represents the traveling wave generated by the fault and can be used to estimate its location. Artificial neural networks (ANNs) are used to estimate the fault location based on the modal information. Two schemes are presented: the first with a voltage input signal; and the second with a current input signal. Training and testing data are obtained by ATP-EMTP simulations. Tests were done to study the effect of fault resistance variation and fault incidence angle on both schemes. The system has the advantages of utilizing single-end measurements, using either a voltage or current signal; no pre-fault data is required     

Intracranial self-stimulation of the dorsal raphe sensitizes psychostimulant locomotion.

The authors hypothesized that repeated rewarding electrical stimulation of the dorsal raphe can produce behavioral sensitization to psychostimulants. Groups of male rats were implanted with a stimulation electrode and preexposed to brain stimulation at parameters set to equate rewarding effectiveness across rats. Control groups were implanted with an electrode but never stimulated, or not implanted at all. Twenty-four hours after the 12th self-stimulation session, all groups were challenged with amphetamine (0.5 mg/kg, ip), nicotine (0.2 mg/kg, sc), or saline, and locomotor activity was measured for 1 hr. Locomotor responses to amphetamine and to nicotine were significantly greater in rats preexposed to brain stimulation. These findings suggest at least partial overlap of underlying substrates. (PsycINFO Database Record (c) 2010 APA, all rights reserved)