A birth-process approach to Moranda's geometric software-reliability model

To alleviate some of the objections to the basic Jelinski Moranda (JM) model for software failures, Moranda proposed a geometric de-eutrophication model. This model assumes that the times between failures are statistically-independent exponential random variables with given failure rates. In this model the failure rates decrease geometrically with the detection of a fault. Using an intuitive approach, Musa, Iannino, Okumoto , see also Farr , derived expressions for the mean and the intensity functions of the process N (t) which counts the number of faults detected in the time interval [O, t] for the Moranda geometric de-eutrophication model. N (t) is studied as a pure birth stochastic process; its probability generating function is derived, as well as its mean, intensity and reliability functions. The expressions for the mean and intensity functions derived by MIO are only approximations and can be quite different from the true functions for certain choices of the failure rates. The exact expressions for the mean function and the intensity function of N (t) are used to find the optimum release time of software based on a cost structure for Moranda's geometric de-eutrophication model.     

Equilibrium analysis of cellular neural networks

Cellular neural networks (CNNs) are dynamical systems, described by a large set of coupled nonlinear differential equations. The equilibrium-point analysis is an important step for understanding the global dynamics and for providing design rules. We yield a set of sufficient conditions (and a simple algorithm for checking them) ensuring the existence of at least one stable equilibrium point. Such conditions give rise to simple constraints, that extend the class of CNNs, for which the existence of a stable equilibrium point is rigorously proved. In addition, they are suitable for design and easy to check, because they are directly expressed in term of the template elements.     

基于交会图和多元统计法的神经网络技术在火山岩识别中的应用

针对火山岩储层的特殊性(复杂性、离散性和随机性),应用BP神经网络技术对火山岩测井解释中岩性识别问题进行了研究。该方法的技术关键是样本集和初始权重的建立,以及模型的优选。本文提出了一种基于交会图和多元统计法的学习样本生成方法,即根据取心岩样的地球化学和岩石学研究,用交会图技术建立样本集,采用聚类分析和距离判别法确定初始权重。将研究方法应用在松辽盆地杏山地区火山岩岩性识别问题中,取得了很好的效果,岩性解释符合率高于90%。文中通过四种岩性识别处理模式的对比研究,表明赋权重处理模式为最优处理模型。在神经网络模型预测过程中,需充分利用已有的地质经验和测井曲线信息建立典型可靠的样本文件,同时考虑神经网络方法中各种因素的影响,优选模型和计算参数才能使预测结果符合实际情况。     

Randomized scheduling algorithms for high-aggregate bandwidth switches

The aggregate bandwidth of a switch is its port count multiplied by its operating line rate. We consider switches with high-aggregate bandwidths; for example, a 30-port switch operating at 40 Gb/s or a 1000-port switch operating at 1 Gb/s. Designing high-performance schedulers for such switches with input queues is a challenging problem for the following reasons: (1) high performance requires finding good matchings; (2) good matchings take time to find; and (3) in high-aggregate bandwidth switches there is either too little time (due to high line rates) or there is too much work to do (due to a high port count). We exploit the following features of the switching problem to devise simple-to-implement, high-performance schedulers for high-aggregate bandwidth switches: (1) the state of the switch (carried in the lengths of its queues) changes slowly with time, implying that heavy matchings will likely stay heavy over a period of time and (2) observing arriving packets will convey useful information about the state of the switch. The above features are exploited using hardware parallelism and randomization to yield three scheduling algorithms - APSARA, LAURA, and SERENA. These algorithms are shown to achieve 100% throughput and simulations show that their delay performance is quite close to that of the maximum weight matching, even when the traffic is correlated. We also consider the stability property of these algorithms under generic admissible traffic using the fluid-model technique. The main contribution of this paper is a suite of simple to implement, high-performance scheduling algorithms for input-queued switches. We exploit a novel operation, called MERGE, which combines the edges of two matchings to produce a heavier match, and study of the properties of this operation via simulations and theory. The stability proof of the randomized algorithms we present involves a derandomization procedure and uses methods which may have wider applicability.     

Oxidative degradation of polyamide reverse osmosis membranes: Studies of molecular model compounds and selected membranes

Selected aromatic amides were used to model the chemical reactivity of aromatic polyamides found in thin‐film composite reverse osmosis (RO) membranes. Chlorination and possible amide bond cleavage of aromatic amides upon exposure to aqueous chlorine, which can lead to membrane failure, were investigated. Correlations are made of the available chlorine concentration, pH, and exposure time with chemical changes in the model compounds. From the observed reactivity trends, insights are obtained into the mechanism of RO membrane performance loss upon chlorine exposure. Two chemical pathways for degradation are shown, one at constant pH and another that is pH‐history dependent. An alternative strategy is presented for the design of chlorine‐resistant RO membranes, and an initial performance study of RO membranes incorporating this strategy is reported. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 90: 1173–1184, 2003     

Results from the ORPHEUS dark matter detector

The ORPHEUS dark matter detector consists of 450 g superconducting tin granules with diameters of 28 and 36 μm. The detector has been operating in the shallow site of the underground laboratory in Bern (70 m.w.e). First preliminary results on WIMP detection sensitivity will be presented.     

Effect of film thickness on hydrogen content in a-Si : H

The hydrogen content, its depth distribution, and its bonding configuration have been studied in hydrogenated amorphous silicon prepared by plasma-enhanced chemical vapor deposition with hydrogen-diluted silane. Nuclear reaction analysis and infrared spectroscopy were used to determine the total amount of hydrogen and its bonded component, respectively. It has been established that the total concentration of hydrogen does not depend on the film thickness, and has a uniform depth profile. The concentration of bonded hydrogen changes with the film thickness within the measurement accuracy. The data obtained suggest the presence of molecular (non-bonded) hydrogen, uniformly distributed in concentration across the film thickness.