Spectral properties of the tandem Jackson network, seen as a quasi-birth-and-death process

Quasi-birth-and-death (QBD) processes with infinite “phase spaces” can exhibit unusual and interesting behavior. One of the simplest examples of such a process is the two-node tandem Jackson network, with the “phase” giving the state of the first queue and the “level” giving the state of the second queue. In this paper, we undertake an extensive analysis of the properties of this QBD. In particular, we investigate the spectral properties of Neuts’s R-matrix and show that the decay rate of the stationary distribution of the “level” process is not always equal to the convergence norm of R. In fact, we show that we can obtain any decay rate from a certain range by controlling only the transition structure at level zero, which is independent of R. We also consider the sequence of tandem queues that is constructed by restricting the waiting room of the first queue to some finite capacity, and then allowing this capacity to increase to infinity. We show that the decay rates for the finite truncations converge to a value, which is not necessarily the decay rate in the infinite waiting room case. Finally, we show that the probability that the process hits level n before level 0 given that it starts in level 1 decays at a rate which is not necessarily the same as the decay rate for the stationary distribution.

On the applicability of the Aris' equivalent sphere in multicomponent reacting systems

The validity of the concept of equivalent sphere introduced by Aris in 1957 to multicomponent reacting systems is investigated in this paper. A network of C6 hydrocarbon reforming reaction and a fixed bed reactor are taken as the model reaction network and the reactor configuration, respectively.

Development and evaluation of neural network freeway incident detection models using field data

This paper discusses a multi-layer feedforward (MLF) neural network incident detection model that was developed and evaluated using field data. In contrast to published neural network incident detection models which relied on simulated or limited field data for model development and testing, the model described in this paper was trained and tested on a real-world data set of 100 incidents. The model uses speed, flow and occupancy data measured at dual stations, averaged across all lanes and only from time interval t. The off-line performance of the model is reported under both incident and non-incident conditions. The incident detection performance of the model is reported based on a validation-test data set of 40 incidents that were independent of the 60 incidents used for training. The false alarm rates of the model are evaluated based on non-incident data that were collected from a freeway section which was video-taped for a period of 33 days. A comparative evaluation between the neural network model and the incident detection model in operation on Melbourne's freeways is also presented. The results of the comparative performance evaluation clearly demonstrate the substantial improvement in incident detection performance obtained by the neural network model. The paper also presents additional results that demonstrate how improvements in model performance can be achieved using variable decision thresholds. Finally, the model's fault-tolerance under conditions of corrupt or missing data is investigated and the impact of loop detector failure/malfunction on the performance of the trained model is evaluated and discussed. The results presented in this paper provide a comprehensive evaluation of the developed model and confirm that neural network models can provide fast and reliable incident detection on freeways. (C) 1997 Elsevier Science Ltd. All rights reserved.

Capillary network models for transport in packed beds: Considerations of pore aspect ratio

The conventional analysis for the estimation of the tortuosity factor for transport in porous media is modified here to account for the effect of pore aspect ratio. Structural models of the porous medium are also constructed for calculating the aspect ratio as a function of porosity. Comparison of the model predictions with the extensive data of Currie (1960) for the effective diffusivity of hydrogen in packed beds shows good agreement with a network model of randomly oriented intersecting pores for porosities upto about 50 percent, which is the region of practical interest. The predictions based on this network model are also found to be in better agreement with the data of Currie than earlier expressions developed for unconsolidated and grainy media.

Prediction of MHC class II-binding peptides using an evolutionary algorithm and artificial neural network

Motivation: Prediction methods for identifying binding peptides could minimize the number of peptides required to be synthesized and assayed, and thereby facilitate the identification of potential T-cell epitopes. We developed a bioinformatic method for the prediction of peptide binding to MHC class II molecules. Results: Experimental binding data and expert knowledge of anchor positions and binding motifs were combined with an evolutionary algorithm (EA) and an artificial neural network (ANN): binding data extraction --> peptide alignment --> ANN training and classification. This method, termed PERUN, was implemented for the prediction of peptides that bind to HLA-DR4(B1*0401). The respective positive predictive values of PERUN predictions of high-, moderate-, low- and zero-affinity binder-a were assessed as 0.8, 0.7, 0.5 and 0.8 by cross-validation, and 1.0, 0.8, 0.3 and 0.7 by experimental binding. This illustrates the synergy between experimentation and computer modeling, and its application to the identification of potential immunotheraaeutic peptides.

Analysis of small signal stability margins using genetic optimization

Power system small signal stability analysis aims to explore different small signal stability conditions and controls, namely: (1) exploring the power system security domains and boundaries in the space of power system parameters of interest, including load flow feasibility, saddle node and Hopf bifurcation ones; (2) finding the maximum and minimum damping conditions; and (3) determining control actions to provide and increase small signal stability. These problems are presented in this paper as different modifications of a general optimization to a minimum/maximum, depending on the initial guesses of variables and numerical methods used. In the considered problems, all the extreme points are of interest. Additionally, there are difficulties with finding the derivatives of the objective functions with respect to parameters. Numerical computations of derivatives in traditional optimization procedures are time consuming. In this paper, we propose a new black-box genetic optimization technique for comprehensive small signal stability analysis, which can effectively cope with highly nonlinear objective functions with multiple minima and maxima, and derivatives that can not be expressed analytically. The optimization result can then be used to provide such important information such as system optimal control decision making, assessment of the maximum network's transmission capacity, etc. (C) 1998 Elsevier Science S.A. All rights reserved.

Generalized optimal lattice covering of finite-dimensional Euclidean space

A generalization of the classical problem of optimal lattice covering of R-n is considered. Solutions to this generalized problem are found in two specific classes of lattices. The global optimal solution of the generalization is found for R-2. (C) 1998 Elsevier Science Inc. All rights reserved.

Thermal and mechanical properties of radiation crosslinked poly(tetrafluoroethylene-co-perfluoromethyl vinyl ether)

The gamma-radiolysis of poly(tetrafluoroethylene-co-perfluoromethyl vinyl ether) (TFE/PMVE) was investigated using chemical and mechanical analyses. The polymer was found to form an insoluble network with a dose of gelation of 15.8 kGy. Tensile and glass transition temperature measurements indicated the predominance of crosslinking, with optimal elastomeric properties reached in the dose range of 120 to 200 kGy. Photoacoustic FTIR spectroscopy CPAS) showed the formation of new carboxylic acid end groups on irradiation. These new end groups were shown to decrease the thermal oxidative stability of the crosslinked network as determined by thermal gravimetric analysis. Electron spin resonance (ESR) studies of the polymer at 77 K indicated the presence of radical precursors. A G-value of 1.1 was determined for radical production at 77 K. Comparison of radical concentrations for a copolymer with a different mole ratio of PMVE, indicated that the PMVE units contribute to scission reactions. (C) 1998 Elsevier Science Ltd. All rights reserved.

The nurse lecturer role in clinical practice conceptualized: helping clinical teachers provide optimal student learning

Despite the fairly wide reporting in the literature of the ma ny roles of clinical supervision by the nursing teacher, little attention has been given to conceptualizing the relative priorities these roles take during the process of supervising nursing students in clinical practice. The purpose of this paper is to consider the manifestations and implications of conflicting roles when nurse lecturers undertake clinical supervision. Previously published research will provide working examples of issues in a conceptual framework for clinical teaching.

Modeling the fluid-flow-induced stress and collapse in a dendritic network

An analytical approach to the stress development in the coherent dendritic network during solidification is proposed. Under the assumption that stresses are developed in the network as a result of the friction resisting shrinkage-induced interdendritic fluid flow, the model predicts the stresses in the solid. The calculations reflect the expected effects of postponed dendrite coherency, slower solidification conditions, and variations of eutectic volume fraction and shrinkage. Comparing the calculated stresses to the measured shear strength of equiaxed mushy zones shows that it is possible for the stresses to exceed the strength, thereby resulting in reorientation or collapse of the dendritic network.

The influence of supra-optimal root-zone temperatures on growth and stomatal conductance in Capsicum annuum L.

Pepper (Capsicum annuum L.) plants were grown aeroponically in a Singapore greenhouse under natural diurnally fluctuating ambient shoot temperatures, but at two different root-zone temperatures (RZTs): a constant 20 +/- 2 degrees C RZT and a diurnally fluctuating ambient (A) (25-40 degrees C) RZT, Plants grown at 20-RZT had more leaves, greater leaf area and dry weight than A-RZT plants. Reciprocal transfer experiments were conducted between RZTs to investigate the effect on plant growth, stomatal conductance (g(s)) and water relations. Transfer of plants from A-RZT to 20-RZT increased plant dry weight, leaf area, number of leaves, shoot water potential (Psi(shoot)), and g(s); while transfer of plants from 20-RZT to A-RZT decreased these parameters. Root hydraulic conductivity was measured in the latter transfer and decreased by 80% after 23 d at A-RZT. Transfer of plants from 20-RZT to A-RZT had no effect on xylem ABA concentration or xylem nitrate concentration, but reduced xylem sap pH by 0.2 units. At both RZTs, g(s) measured in the youngest fully expanded leaves increased with plant development. In plants with the same number of leaves, A-RZT plants had a higher g(s) than 20-RZT plants, but only under high atmospheric vapour pressure deficit. The roles of chemical signals and hydraulic factors in controlling g(s) of aeroponically grown Capsicum plants at different RZTs are discussed.