Computing New Optimized Routes for GPS Navigators Using Evolutionary Algorithms

GPS navigators are now present in most vehicles and smartphones. The usual goal of these navigators is to take the user in less time or distance to a destination. However, the global use of navigators in a given city could lead to traffic jams as they have a highly biased preference for some streets. From a general point of view, spreading the traffic throughout the city could be a way of preventing jams and making a better use of public resources. We propose a way of calculating alternative routes to be assigned by these devices in order to foster a better use of the streets. Our experimentation involves maps from OpenStreetMap, real road traffic, and the microsimulator SUMO. We contribute to reducing travel times, greenhouse gas emissions, and fuel consumption. To analyze the sociological aspect of any innovation, we analyze the penetration (acceptance) rate which shows that our proposal is competitive even when just 10% of the drivers are using it.Spanish MINECO project TIN2014-57341-R (http://moveon.lcc.uma.es). FPU grant (FPU13/00954) from the Spanish Ministry of Education, Culture and Sports. University of Malaga. International Campus of Excellence Andalucia TECH

Intelligent agents, markets and competition

Strategisch onderzoek naar de ontwikkelingen op de markt voor intelligent agents. Intelligent Agents kunnen enorme invloed krijgen in de business-to-consumer Internethandel. Veel hangt daarbij af van hoe aanbieders hun producten aanbieden op het Internet. In de reisbranche zijn de mogelijkheden voor productori�ntatie en -aankoop op de websites van reisaanbieders nog beperkt. Op boekensites is meer informatie voorhanden. Hier hebben agents slechts een beperkte functie, omdat onderscheid tussen boekaanbieders enkel op prijs is te maken.

Doctor of Philosophy

dissertationTraffic congestion occurs because the available capacity cannot serve the desired demand on a portion of the roadway at a particular time. Major sources of congestion include recurring bottlenecks, incidents, work zones, inclement weather, poor signal timing, and day-to-day fluctuations in normal traffic demand. This dissertation addresses a series of critical and challenging issues in evaluating the benefits of Advanced Traveler Information Strategies under different uncertainty modeling approaches are integrated in this dissertation, namely: mathematical programming, dynamic simulation and analytical approximation. The proposed models aim to 1) represent static-state network user equilibrium conditions, knowledge quality and accessibility of traveler information systems under both stochastic capacity and stochastic demand distributions; 2) characterize day-to-day learning behavior with different information groups under stochastic capacity and 3) quantify travel time variability from stochastic capacity distribution functions on critical bottlenecks. First, a nonlinear optimization-based conceptual framework is proposed for incorporating stochastic capacity, stochastic demand, travel time performance functions and varying degrees of traveler knowledge in an advanced traveler information provision environment. This method categorizes commuters into two classes: (1) those with access to perfect traffic information every day, and (2) those with knowledge of the expected traffic conditions across different days. Using a gap function framework, two mathematical programming models are further formulated to describe the route choice behavior of the perfect information and expected travel time user classes under stochastic day-dependent travel time. This dissertation also presents adaptive day-to-day traveler learning and route choice behavioral models under the travel time variability. To account for different levels of information availability and cognitive limitations of individual travelers, a set of "bounded rationality" rules are adapted to describe route choice rules for a traffic system with inherent process noise and different information provision strategies. In addition, this dissertation investigates a fundamental problem of quantifying travel time variability from its root sources: stochastic capacity and demand variations that follow commonly used log-normal distributions. The proposed models provide theoretically rigorous and practically usefully tools to understand the causes of travel time unreliability and evaluate the system-wide benefit of reducing demand and capacity variability

Development of track-driven agriculture robot with terrain classification functionality / Khairul Azmi Mahadhir

Over the past years, many robots have been devised to facilitate agricultural activities (that are labor-intensive in nature) so that they can carry out tasks such as crop care or selective harvesting with minimum human supervision. It is commonly observed that rapid change in terrain conditions can jeopardize the performance and efficiency of a robot when performing agricultural activity. For instance, a terrain covered with gravel produces high vibration to robot when traversing on the surface. In this work, an agricultural robot is embedded with machine learning algorithm based on Support Vector Machine (SVM). The aim is to evaluate the effectiveness of the Support Vector Machine in recognizing different terrain conditions in an agriculture field. A test bed equipped with a tracked-driven robot and three types o f terrain i.e. sand, gravel and vegetation has been developed. A small and low power MEMS accelerometer is integrated into the robot for measuring the vertical acceleration. In this experiment, the vibration signals resulted from the interaction between the robot and the different type of terrain were collected. An extensive experimental study was conducted to evaluate the effectiveness of SVM. The results in terms of accuracy of two machine learning techniques based on terrain classification are analyzed and compared. The results show that the robot that is equipped with an SVM can recognize different terrain conditions effectively. Such capability enables the robot to traverse across changing terrain conditions without being trapped in the field. Hence, this research work contributes to develop a self-adaptive agricultural robot in coping with different terrain conditions with minimum human supervision

High resolution DNA copy number analysis of constitutional chromosomal aberrations in human genomic disorders

About one to three percent of the human population is aflicted by mild to severe mental retardation, often in association with congenital abnormalities (MR/CA). These abnormalities in normal human morphogenesis may express themselves as subtle dysmorphic signs not causing any harm or present as severe disabling and life-threatening malformations such as congenital heart defects. It is well established that constitutional chromosomal aberrations are an important cause for MR/CA. The screening for such chromosomal rearrangements is done by widely used routine analysis of banded metaphase chromosomes (karyotyping). Given the limited resolution of such analyses (5-10 Mb), it was anticipated that a significant number of submicroscopic deletions or duplications (DNA copy number variations, CNV) were overlooked in patients with idiopathic mental retardation with or without congenital anomalies. This thesis represents one of the _rst exhaustive studies of this patient group using a new and more sensitive method for detection of CNVs. This technique, termed array comparative genomic hybridization (array CGH), allows the genome wide screening for submicroscopic aberrations in one single experiment. Array CGH uses reporter DNA molecules more or less evenly spread throughout the entire genome which are spotted or synthesized in an array on a glass slide. Each reporter is used to interrogate the DNA copy number of a specific genomic region through the competitive hybridization of differentially fluorescent labeled patient and control DNA. Together with the tedious optimalization of the technique, also a web based open source (MySQL) database platform was developed for the analysis and visualization of large amount of array CGH data (medgen.ugent.be/arrayCGHbase) (paper 6). A total of 140 carefully clinically selected patients with mental retardation and/or congenital abnormalities were analyzed for hidden chromosomal aberrations in a collaborative effort with the Center for Medical Genetics Leuven (KUL). This initial study together with a review of other published investigations, allowed for the first time to establish a reliable figure of the number of submicroscopic CNVs in this patient population. When excluding patients with subtelomeric imbalances which could be identified through FISH or MLPA analyses, array CGH still allowed to detect CNVs in an additional ~8% of patients (paper 2). A major challenge resulting from this new flow of information is the search and description of new microdeletion/microduplication syndromes. Although most CNVs seemed to be scattered across the entire genome we were able to describe a new microdeletion syndrome characterized by osteopoikilosis, mental retardation and short stature. This observation was facilitated through the identification of LEMD3 as the causal gene for osteopoikilosis, Buschke-Ollendorff syndrome (BOS) and melorheostosis in the 12q14.3 deleted interval and subsequent, the finding of two additional patients with a 12q14.3 microdeletion (paper 3). The present work also illustrates the possible contribution of array CGH in the delineation of the critical region for recurrent deletion syndromes. In this study we identified a small interstitial deletion on chromosome 18q12.3 in a patient with clinical features of the del(18)(q12.1q21.1) syndrome. We were able to delineate the critical region for this syndrome to an interval of 1.8 Mb, enabling hereby the determination of the crucial genes for this microdeletion syndrome (paper 4). This thesis also further illustrates the power of combined flow cytometry and array CGH for rapid identification of translocation breakpoints. Using this approach we were able to identify OPHN1 as the causal gene for the observed mental retardation and overgrowth in a girl with an apparent balanced t(X;9) translocation (paper 5). In conclusion, the presented work clearly illustrates several important applications of array CGH in the field of clinical cytogenetics. The use of this new performant methodology will greatly improve the diagnostic yield in patients with unexplained mental retardation, provide more insights into genotype-phenotype correlations and ultimately lead to the identification of the causal genes. Functional studies of these gene products will enhance our understanding of the genetic regulation in normal human morphogenesis, embryogenesis and brain functioning. Finally, it is my believe that implementation of array CGH will represent a major and perhaps last wave of innovation in cytogenetics, as the latter may become largely redundant. Ultimately and perhaps earlier than we can anticipate, sequencing of the whole genome of a patient may eventually emerge as the method of choice

Modelling water quality for water distribution systems

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Maintaining water quality in distribution systems has become a prominent issue in the study of water networks. This thesis concentrates on disinfectant and particle counts as two important indicators of water quality. The models discussed in this work are based on data collected by the author. The experimental set-up and procedure are described and observations of particle counts, particle counter size distributions, monochloramine as disinfectant, temperature, heterotrophic plate counts and epifluorescence microscopy counts are reported. A model of the response of particle counts to an increase in flow is developed. This model is obtained from specification derived from the data and assumptions, and is validated by its interpretability and its fit to data. A local shear-off density and an initial biofilm shedding profile were introduced and thus a linear model for this part of the water quality dynamics could be obtained. A procedure for the identification of the parameters of the local shear-off function and for the determination of the biofilm shedding profile is presented. This profile can be used to provide information about the status of the distribution system in terms of shear-off from the biofilm on the pipe walls. Monochloramine decay dynamics are investigated. The chlorine meter data is preprocessed with the help of titration data to correct meter drift. The data is then used in calibrating two different possible chlorine models: a model with a single decay coefficient and a model with bulk decay coefficient and wall demand (as used in Epanet). Important difficulties in identifying these parameters that come about because of the structure of the models are highlighted. Identified decay coefficients are compared and tested for flow, inlet chlorine and temperature dependence. The merits and limits of the approach to modelling taken in this work and a possible generalisation are discussed. The water industry perspective and an outlook are provided