Development and commissioning of decision support tools for sewerage management.

Managing sewerage systems is a highly complex task due to the dynamic nature of the facilities. Their performance strongly depends on the know-how applied by the operators. In order to define optimal operational settings, two decision support tools based on mathematical models have been developed. Moreover, easy-to-use interfaces have been created as well, aiding operators who presumably do not have the necessary skills to use modelling software. The two developed programs simulate the behaviour of both wastewater treatment plants (WWTP) and sewer network systems, respectively. They have essentially the same structure, including raw data management and statistical analysis, a simulation layer using the application programming interface of the applied software and a layer responsible for the representation of the obtained results. Four user modes are provided in the two software including the simulation of historical data using the applied and novel operational settings, as well as modes concerning prediction of possible operation periods and updates. Concerning the WWTP software, it was successfully installed in Nantes (France) in June 2004. Moreover, the one managing sewer networks has been deployed in Saint-Malo (France) in January 2005. This paper presents the structure of the developed software and the first results obtained during the commissioning phase.     

The road to maturity: navigating between craft and science

C. Ebert presents his views on the state of software engineering as a field, its roots and inherent conflicts, its relationship to other engineering disciplines, where it is headed, and what we can do to influence that direction. T. Matsubara, T. Webb, M. Pezze, and O.W. Bertelsen offer a spectrum of further insights     

Effect of hygiene measures, water sanitation and oral rehydration therapy on diarrhea in children less than five years old in the south of Ivory Coast

BACKGROUND: Gastric sucrose permeability is a noninvasive marker that reliably increases in association with gastrointestinal injury due to use of nonsteroidal antiinflammatory drugs. Despite the effect of Helicobacter pylori infection on the gastric mucosa, in a previous study we were unable to demonstrate that H. pylori infection was associated with abnormal gastric sucrose permeability. Our goal in this study was to explore further whether H. pylori infection changed gastric permeability; therefore, we evaluated the effect of treatment of H. pylori infection on gastric permeability to sucrose and the relation of sucrose permeability to density of polymorphonuclear leukocytes. MATERIALS AND METHODS: Five hundred milliliters of a solution containing 100 gm of sucrose was ingested by the subject at bedtime. Overnight urine was collected and assayed for sucrose by high-performance liquid chromatography. Sucrose permeability was assessed both before and approximately 4 weeks after anti-H. pylori therapy. RESULTS: Seventeen asymptomatic H. pylori-infected volunteers participated; 8 were cured. Sucrose permeability was in the range commonly found in normal controls both before and after anti-H. pylori therapy (mean excretion, 76.3 mg; range, 13-171 mg). Gastric sucrose permeability correlated with the density of polymorphonulcear cell infiltration of the mucosa. Cure of the H. pylori infection was associated with a small but significant decrease in sucrose permeability (98.8 +/- 18 mg to 51.7 +/- 9.8 mg (p = .01). Sucrose permeability was greater in those with a high density of mucosal polymorphonuclear cells compared to those with lower scores (119.5 +/- 4 vs 71.4 +/- 13 for those with scores > or = 5 compared to scores < or = 4; p = .023). Failed therapy resulted in an increase in the mucosal density of polymorphonuclear infiltration and sucrose permeability (56.4 +/- 13 mg-99.7 +/- 19 mg pretreatment vs posttreatment, respectively; p = .031). CONCLUSION: H. pylori gastritis causes a small but measurable increase in gastric permeability to sucrose that may reflect epithelial transmigration of neutrophils.     

Positive temperature dependence of the electron impact ionizationcoefficient in In0.53Ga0.47As/InP HBTs

Impact ionization is a major limiting factor to the maximum operating voltage of InGaAs-based, high-speed transistors. In this work, data on the positive temperature dependence of the electron impact ionization coefficient α_n in In_0.53Ga_0.47As at medium-low electric fields are reported for the first time. The increase of α_n with temperature is opposite to the behavior normally observed in most semiconductors. This anomalous behavior implies the onset of a positive feedback between power dissipation and avalanche generation which may adversely affect the power handling capability of In_0.53Ga _0.47As-based devices, and which should be taken into account in device thermal modeling. In the experimental procedure, based on the measurement of the multiplication factor M-1 in npn In_0.53Ga _0.47As/InP Heterojunction Bipolar Transistors (HBT), particular care has been taken in order to rule out possible spurious, temperature-dependent contributions to the measured multiplication current     

Application of neural networks and machine learning in networkdesign

Communication network design is becoming increasingly complex, involving making networks more usable, affordable, and reliable. To help with this, we have proposed an expert network designer (END) for configuring, modeling, simulating, and evaluating large structured computer networks, employing artificial intelligence, knowledge representation, and network simulation tools. We present a neural network/knowledge acquisition machine-learning approach to improve the END's efficiency in solving the network design problem and to extend its scope to acquire new networking technologies, learn new network design techniques, and update the specifications of existing technologies     

Evaluating the impact of CASE: an empirical comparison of retrospective and cross-sectional survey approaches

The purpose of this paper is to evaluate two methods of assessing the productivity and quality impact of Computer Aided Software Engineering (CASE) and Fourth Generation Language (4GL) technologies: (1) by the retrospective method; and (2) the cross-sectional method. Both methods involve the use of questionnaire surveys. Developers' perceptions depend on the context in which they are expressed and this includes expectations about the effectiveness of a given software product. Consequently, it is generally not reliable to base inferences about the relative merits of CASE and 4GLs on a cross-sectional comparison of two separate samples of users. The retrospective method that requires each respondent to directly compare different products is shown to be more reliable. However, there may be scope to employ cross-sectional comparisons of the findings from different samples where both sets of respondents use the same reference point for their judgements, and where numerical rather than verbal rating scales are used to measure perceptions.     

Cultural adaptation and information design: two contrasting views

Approaches to using visual language in a cultural context can be placed on a continuum, with global (universal) on one end and culture-focused on the other. Each approach reveals contrasting assumptions about three central design issues: perception, aesthetics and pragmatics. The global approach is characterized by attempts to invent an objective, universal visual language or to define such a language through perceptual principles and empirical research. The culture-focused perspective is founded on the principle that visual communication is intimately bound to experience and hence can function only within a given cultural context, to which designers must be sensitive. While the modernist, universal approach has been losing ground to the postmodern, culture-focused approach, the two complement each other in a variety of ways and, depending on the rhetorical situation, offer pragmatic benefits and drawbacks     

Performance evaluation of rule grouping on a real-time expertsystem architecture

Uses a Markov process to model a real-time expert system architecture characterized by message passing and event-driven scheduling. The model is applied to the performance evaluation of rule grouping for real-time expert systems running on this architecture. An optimizing algorithm based on Kernighan-Lin heuristic graph partitioning for the real-time architecture is developed and a demonstration system based on the model and algorithm has been developed and tested on a portion of the advanced GPS receiver (AGR) and manned manoeuvring unit (MMU) knowledge bases