Performance evaluation for DRED discrete-time queueing network analytical model

Due to the rapid development in computer networks, congestion becomes a critical issue. Congestion usually occurs when the connection demands on network resources, i.e. buffer spaces, exceed the available ones. We propose in this paper a new discrete-time queueing network analytical model based on dynamic random early drop (DRED) algorithm to control the congestion in early stages. We apply our analytical model on two-queue nodes queueing network. Furthermore, we compare between the proposed analytical model and three known active queue management (AQM) algorithms, including DRED, random early detection (RED) and adaptive RED, in order to figure out which of them offers better quality of service (QoS). We also experimentally compare the queue nodes of the proposed analytical model and the three AQM methods in terms of different performance measures, including, average queue length, average queueing delay, throughput, packet loss probability, etc., aiming to determine the queue node that offers better performance.     

Christopher Strachey: Recollections of His Influence

My early research was inspired by the mathematical semantics of Scott and Strachey. Two such topics, recounted in this paper, were the fixed-point analysis of pointer loops and the expressibility of a style of functional programming introduced by Barron and Strachey.     

A network model of barrier synchronization algorithms

We consider two algorithms for the barrier synchronization ofN processes: the Dissemination algorithm⁽²⁾ and Brooks algorithm.^(1,2) Both algorithms comprise a number of binary communications amongst the processes, organized into a sequence of stages. It is shown that Brooks' algorithm⁽¹⁾ requires between LogN(log₂ N) and 2 LogN stages, the lower bound being guaranteed only in the case thatN is a power of 2 (cubic) and the upper bound seemingly needed for most otherN. On the other hand, it is shown⁽²⁾ that the Dissemination algorithm requires only LogN stages regardless ofN, making it apparently superior to the Brooks algorithm. We introduce a network model of local barrier algorithms. Using it we obtain a rigorous correctness proof for local barrier algorithms, and show that the number of stages in the Brooks algorithm is bounded above by LogN+1. The Brooks algorithms is therefore essentially equivalent in time complexity to the Dissemination algorithm. We then address the question of which values ofN admit exactly LogN Brooks stages. We find a sufficient condition, and conjecture that it is also necessary.     

New method for selectivity enhancement of SiC field effect gas sensors for quantification of NO x

A silicon carbide based enhancement type metal insulator field effect transistor with porous gate metallization has been investigated as a total NO _x sensor operated in a temperature cycling mode. This operating mode is quite new for gas sensors based on the field effect but promising results have been reported earlier. Based on static investigations we have developed a suitable T-cycle optimized for NO _x detection and quantification in a mixture of typical exhaust gases (CO, C₂H₄, and NH₃). Significant features describing the shape of the sensor response have been extracted and evaluated with multivariate statistics (e.g. linear discriminant analysis) allowing quantification of NO _x . Additional cleaning-cycles every 30?min improve the stability of the sensor further. With this kind of advanced signal processing the influence of sensor drift and cross sensitivity to ambient gases can be reduced effectively. Measurements have proven that different concentrations of NO _x can be detected even in a changing mixture of other typical exhaust gases under dry and humid conditions. In addition to that, unknown concentrations of NO _x can be detected based on a small set of training data. It can be concluded that the performance of GasFETs for NO _x determination can be enhanced considerably with temperature cycling and appropriate signal processing.     

Sex Differences and Individual Differences in Cognitive Performance and Their Relationship to Endogenous Gonadal Hormones and Gonadotropins.

Sexually dimorphic cognitive performance in men (n=42) and women (n=42) was related to testosterone, estradiol, progesterone, luteinizing hormone, follicle-stimulating hormone, and sex hormone binding globulin, measured in 10-ml blood samples collected between 0900 and 1030 and, among women, during the follicular phase of the menstrual cycle. Significant sex differences favored men on spatial tasks (Mental Rotation and Judgment of Line Orientation) and on an inhibition task and favored women on a verbal task (category fluency). However, there were no significant relationships between any of the hormones and cognitive performance, suggesting that there are few, if any, consistent, substantial relationships between endogenous, nonfluctuating levels of gonadal hormones or gonadotropins and these cognitive abilities in men or women. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Predicting change for individual psychotherapy clients on the basis of their nearest neighbors.

This study extended client-focused research by using the nearest neighbor (NN) approach, a client-specific sampling and prediction strategy derived from research on alpine avalanches. Psychotherapy clients (N = 203) seen in routine practice settings in the United Kingdom completed a battery of intake measures and then completed symptom intensity ratings before each session. Forecasts of each client's rate of change and session-by-session variability were computed on the basis of that client's NNs (n = 10-50 in different comparisons). Alternative forecasts used linear or log-linear slopes and were compared with an alternative prediction strategy. Results showed that the NN approach was superior to the alternative model in predicting rate of change, though the advantage was less clear for predicting variability. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

National and international university departmental Web site interlinking

Although many link patterns have been identified at the university level, departmental interlinking has been relatively ignored. Universities are multidisciplinary by nature and various disciplines may employ the Web differently, thus patterns identified at the university level may hide subject differences. Departments are typically subject-oriented, and departmental interlinking may therefore illustrate interesting disciplinary linking patterns, perhaps relating to informal scholarly communication. The aim of this paper is to identify whether and how link patterns differ along country and disciplinary lines between similar disciplines and similar countries. Physics, Chemistry and Biology departments in Australia, Canada and the UK have been chosen. In order to get a holistic picture of departments' Web use profiles and link patterns, five different perspectives are identified and compared for each set of departments. Differences in link patterns are identified along both national and disciplinary lines, and are found to reflect offline phenomena. Along national lines, a likely explanation for the difference is that countries with better research performances make more general use of the Web; and, with respect to international peer interlinking, countries that share more scholarly communication tend to interlink more with each other. Along disciplinary lines, it seems that departments from disciplines which are more willing to distribute their research outputs tend to make more general use of the Web, and also interlink more with their national and international peers.     

GigaMatrix: an ultra high-throughput tool for accessing biodiversity

Recombinant approaches for tapping into the biodiversity present in nature for the discovery of novel enzymes and biosynthetic pathways can result in large gene libraries. Likewise, laboratory evolution techniques can result in large but potentially valuable libraries. Thorough screening of these libraries requires ultra high-throughput methods. The GigaMatrix^™ screening platform addresses this opportunity using reusable high-density plates with 100,000 to 1,000,000 through-hole wells in a microplate footprint. In addition to throughputs of over 10⁷ wells per day, the platform offers a significant reduction in reagent use and waste, has fully integrated automated “cherry picking,” and uses no complicated dispensing equipment. Wells containing putative hits from targeted fluorescent liquid phase assays are revealed by a fluorescent imaging system. Vision-guided robotics are utilized to recover hits by accessing individual 200 μm and smaller wells with a disposable sterile needle. The GigaMatrix platform has proven to be an effective and efficient tool for screening gene libraries for both discovery and evolution applications.