NETGRAF: a computer graphics aid to the operation and interpretation of NETSIM, a traffic simulation model. Part 1: overview and experimental results. Final report.

Transportation Department, Office of University Research, Washington, D.C.

NETGRAF: a computer graphics aid to the operation and interpretation of NETSIM, a traffic simulation model. Part 3: programmer's guide.

Transportation Department, Office of University Research, Washington, D.C.

Studying fluid systems with the McIlroy fluid network analyzer.

Mode of access: Internet.

Privacy in the Smart City: Implications of Sensor Network Design, Law, and Policy for Locational Privacy

Thesis (Master's)--University of Washington, 2016-06

A Novel Framework for Real-time Traffic Flow Parameter Estimation from Aerial Videos

Thesis (Master's)--University of Washington, 2016-06

Is quantitative interpretation likely to increase sensitivity of dobutamine stress echocardiography? A study of false-negative results

Background: False-negative interpretations of do-butamine stress echocardiography (DSE) may be associated with reduced wall stress. using measurements of contraction, we sought whether these segments were actually ischemic but unrecognized or showed normal contraction. Methods. We studied 48 patients (29 men; mean age 60 +/- 10 years) with normal regional function on the basis of standard qualitative interpretation of DSE. At coronary angiography within. 6 months of DSE, 32 were identified as having true-negative and 16 as having false-negative results of DSE. Three apical views were used to measure regional function with color Doppler tissue, integrated backscatter, and strain rate imaging. Cyclic variation of integrated backscatter was measured in 16 segments, and strain rate and peak systolic strain was calculated in 6 walls at rest and peak stress. Results. Segments with false-negative results of DSE were divided into 2 groups with and without low wall stress according to previously published cut-off values. Age, sex, left ventricular mass, left ventricular geometric pattern, and peak workload were not significantly different between patients with true and false-negative results of DSE. Importantly, no significant differences in cyclic variation and strain parameters at rest and peak stress were found among segments with true-and false-negative results of DSE with and without low wall stress. Stenosis severity had no influence on cyclic variation and strain parameters at peak stress. Conclusions: False-negative results of DSE reflect lack of ischemia rather than underinterpretation of regional left ventricular function. Quantitative markers are unlikely to increase the sensitivity of DSE.

A probabilistic switch model of information flow in social networks: Application for virtual circuits to organizational design

Network building and exchange of information by people within networks is crucial to the innovation process. Contrary to older models, in social networks the flow of information is noncontinuous and nonlinear. There are critical barriers to information flow that operate in a problematic manner. New models and new analytic tools are needed for these systems. This paper introduces the concept of virtual circuits and draws on recent concepts of network modelling and design to introduce a probabilistic switch theory that can be described using matrices. It can be used to model multistep information flow between people within organisational networks, to provide formal definitions of efficient and balanced networks and to describe distortion of information as it passes along human communication channels. The concept of multi-dimensional information space arises naturally from the use of matrices. The theory and the use of serial diagonal matrices have applications to organisational design and to the modelling of other systems. It is hypothesised that opinion leaders or creative individuals are more likely to emerge at information-rich nodes in networks. A mathematical definition of such nodes is developed and it does not invariably correspond with centrality as defined by early work on networks.

On sensor network segmentation for urban water distribution monitoring

Identifying water wastage in forms of leaks in a water distribution network of any city becomes essential as droughts are presenting serious threats to few major cities. In this paper, we propose a deployment of sensor network for monitoring water flow in any water distribution network. We cover the issues related with designing such a dedicated sensor network by considering types of sensors required, sensors' functionality, data collection, and providing computation serving as leak detection mechanism. The main focus of this paper is on appropriate network segmentation that provides the base for hierarchical approach to pipes' failure detection. We show a method for sensors allocation to the network in order to facilitate effective pipes monitoring. In general, the identified computational problem belongs to hard problems. The paper shows a heuristic method to build effective hierarchy of the network segmentation.

The application of artificial neural networks to the interpretation and classification of freshwater benthic invertebrate communities

This thesis presents a thorough and principled investigation into the application of artificial neural networks to the biological monitoring of freshwater. It contains original ideas on the classification and interpretation of benthic macroinvertebrates, and aims to demonstrate their superiority over the biotic systems currently used in the UK to report river water quality. The conceptual basis of a new biological classification system is described, and a full review and analysis of a number of river data sets is presented. The biological classification is compared to the common biotic systems using data from the Upper Trent catchment. This data contained 292 expertly classified invertebrate samples identified to mixed taxonomic levels. The neural network experimental work concentrates on the classification of the invertebrate samples into biological class, where only a subset of the sample is used to form the classification. Other experimentation is conducted into the identification of novel input samples, the classification of samples from different biotopes and the use of prior information in the neural network models. The biological classification is shown to provide an intuitive interpretation of a graphical representation, generated without reference to the class labels, of the Upper Trent data. The selection of key indicator taxa is considered using three different approaches; one novel, one from information theory and one from classical statistical methods. Good indicators of quality class based on these analyses are found to be in good agreement with those chosen by a domain expert. The change in information associated with different levels of identification and enumeration of taxa is quantified. The feasibility of using neural network classifiers and predictors to develop numeric criteria for the biological assessment of sediment contamination in the Great Lakes is also investigated.

Traffic Offered Behaviour Regarding Target QOS Parameters in Network Dimensioning

We consider a model of overall telecommunication network with virtual circuits switching, in stationary state, with Poisson input flow, repeated calls, limited number of homogeneous terminals and 8 types of losses. One of the main problems of network dimensioning/redimensioning is estimation of traffic offered in network because it reflects on finding of necessary number of circuit switching lines on the basis of the consideration of detailed users manners and target Quality of Service (QoS). In this paper we investigate the behaviour of the traffic offered in a network regarding QoS variables: “probability of blocked switching” and “probability of finding B-terminals busy”. Numerical dependencies are shown graphically. A network dimensioning task (NDT) is formulated, solvability of the NDT and the necessary conditions for analytical solution are researched as well. International Journal "Information Technologies and Knowledge" Vol.2 / 2008 174 The received results make the network dimensioning/redimensioning, based on QoS requirements easily, due to clearer understanding of important variables behaviour. The described approach is applicable directly for every (virtual) circuit switching telecommunication system e.g. GSM, PSTN, ISDN and BISDN. For packet - switching networks, at various layers, proposed approach may be used as a comparison basis and when they work in circuit switching mode (e.g. VoIP).

Dimensioning of Telecommunication Network Based on Quality of Services Demand and Detailed Behaviour of Users

The aim of this paper is to be determined the network capacity (number of necessary internal switching lines) based on detailed users’ behaviour and demanded quality of service parameters in an overall telecommunication system. We consider detailed conceptual and its corresponded analytical traffic model of telecommunication system with (virtual) circuit switching, in stationary state with generalized input flow, repeated calls, limited number of homogeneous terminals and losses due to abandoned and interrupted dialing, blocked and interrupted switching, not available intent terminal, blocked and abandoned ringing (absent called user) and abandoned conversation. We propose an analytical - numerical solution for finding the number of internal switching lines and values of the some basic traffic parameters as a function of telecommunication system state. These parameters are requisite for maintenance demand level of network quality of service (QoS). Dependencies, based on the numericalanalytical results are shown graphically. For proposed conceptual and its corresponding analytical model a network dimensioning task (NDT) is formulated, solvability of the NDT and the necessary conditions for analytical solution are researched as well. It is proposed a rule (algorithm) and computer program for calculation of the corresponded number of the internal switching lines, as well as corresponded values of traffic parameters, making the management of QoS easily.

Data Flow Analysis and the Linear Programming Model

* The research is supported partly by INTAS: 04-77-7173 project, http://www.intas.be

Probabilistic multiple model neural network based leak detection system:experimental study

This paper presents an effective decision making system for leak detection based on multiple generalized linear models and clustering techniques. The training data for the proposed decision system is obtained by setting up an experimental pipeline fully operational distribution system. The system is also equipped with data logging for three variables; namely, inlet pressure, outlet pressure, and outlet flow. The experimental setup is designed such that multi-operational conditions of the distribution system, including multi pressure and multi flow can be obtained. We then statistically tested and showed that pressure and flow variables can be used as signature of leak under the designed multi-operational conditions. It is then shown that the detection of leakages based on the training and testing of the proposed multi model decision system with pre data clustering, under multi operational conditions produces better recognition rates in comparison to the training based on the single model approach. This decision system is then equipped with the estimation of confidence limits and a method is proposed for using these confidence limits for obtaining more robust leakage recognition results.