Diss. (sammanfattning) SLU : Sveriges lantbruksuniv., 2009. / Härtill 4 uppsatser.

With the recent development of smart-well technology, the reservoir community now faces the challenge of developing robust and efficient techniques for reservoir characterization by means of data inversion. Unfortunately, classical history-matching methodologies do not possess computational efficiency and robustness needed to assimilate data measured almost in real time. Therefore, the reservoir community has started to explore techniques previously applied in other disciplines. Such is the case of the representer method, a variational data assimilation technique that was first applied in physical oceanography. The representer method is an efficient technique for solving linear inverse problems when a finite number of measurements are available. To the best of our knowledge, a general representer-based methodology for nonlinear inverse problems has not been fully developed. We fill this gap by presenting a novel implementation of the representer method applied to the nonlinear inverse problem of identifying petrophysical properties in reservoir models. Given production data from wells and prior knowledge of the petrophysical properties, the goal of our formulation is to find improved parameters so that the reservoir model prediction fits the data within some error given a priori. We first define an abstract framework for parameter identification in nonlinear reservoir models. Then, we propose an iterative representer-based scheme (IRBS) to find a solution of the inverse problem. Sufficient conditions for convergence of the proposed algorithm are established. We apply the IRBS to the estimation of absolute permeability in single-phase Darcy flow through porous media. Additionally, we study an extension of the IRBS with Karhunen-Loeve (IRBS-KL) expansions to address the identification of petrophysical properties subject to linear geological constraints. The IRBS-KL approach is compared with a standard variational technique for history matching. Furthermore, we apply the IRBS-KL to the identification of porosity, absolute and relative permeabilities given production data from an oil-water reservoir. The general derivation of the IRBS-KL is provided for a reservoir whose dynamics are modeled by slightly compressible immiscible displacement of two-phase flow through porous media. Finally, we present an ad-hoc sequential implementation of the IRBS-KL and compare its performance with the ensemble Kalman filter. / text

Τα Δίκτυα Αισθητήρων αποτελούνται από ένα μεγάλο αριθμό μικρών αυτόνομων συσκευών, που αλληλεπιδρούν με το άμεσο περιβάλλον τους μέσω αισθητήρων, επικοινωνούν μεταξύ τους ασύρματα και συνεργάζονται φέροντας εις πέρας εργασίες που δε θα μπορούσε να ολοκληρώσει μία μόνο συσκευή. Κάθε συσκευή του δικτύου διαθέτει περιορισμένη υπολογιστική δύναμη και ενεργειακούς πόρους, επομένως η όσο το δυνατόν λιγότερη κατανάλωση ενέργειας είναι βασικό πρόβλημα των δικτύων αισθητήρων για τη μεγιστοποίηση του χρόνου ζωής τους. Συνήθως τα δίκτυα αισθητήρων αναπτύσσονται σε μεγάλες περιοχές ενδιαφέροντος για την υποστήριξη σημαντικών εφαρμογών του πραγματικού κόσμου. Η πληροφορία που ανιχνεύεται από τους κόμβους αισθητήρων προωθείται προς ένας σταθερό, συνήθως, κέντρο ελέγχου, με αναμεταδόσεις των δεδομένων στους ενδιάμεσους κόμβους. Η διαδικασία αυτή έχει ως αποτέλεσμα τη μεγάλη κατανάλωση ενέργειας στις συσκευές, ιδιαίτερα σε αυτές που βρίσκονται κοντά στο κέντρο ελέγχου, αφού πρέπει να αναμεταδίδουν και τα δεδομένα που φτάνουν από το υπόλοιπο δίκτυο προς το κέντρο ελέγχου. Για την επίτευξη μιας πιο ισορροπημένης και αποδοτικής διαδικασίας συλλογής δεδομένων, τα τελευταία χρόνια έχει υιοθετηθεί μια νέα προσέγγιση, όπου το κέντρο ελέγχου είναι κινητό. Η βασική ιδέα είναι ότι το κέντρο ελέγχου διαθέτει σημαντικά και εύκολα ανανεώσιμα αποθέματα ενέργειας, επομένως μπορεί να κινείται στην περιοχή όπου έχει αναπτυχθεί το δίκτυο αισθητήρων, αναλαμβάνοντας να συλλέξει τα δεδομένα από τους κόμβους με πολύ μικρό κόστος. Ωστόσο, η μετάδοση των δεδομένων μπορεί να παρουσιάζει σημαντικές καθυστερήσεις. Στην παρούσα εργασία αναπτύχθηκαν πρωτόκολλα ελέγχου της κίνησης ενός κέντρου ελέγχου σε δίκτυο αισθητήρων με ανομοιογενή ανάπτυξη των κόμβων αισθητήρων, με στόχο την αποδοτική, ως προς την ενέργεια και τον χρόνο παράδοσης, συλλογή των δεδομένων. Συγκεκριμένα, το κέντρο ελέγχου διαιρεί νοητά το δίκτυο σε περιοχές τις οποίες και επισκέπτεται διαδοχικά, σταματώντας σε κάθε περιοχή για ένα συγκεκριμένο χρονικό διάστημα, ώστε να συλλέξει τα δεδομένα. Προτείνουμε δύο τρόπους κίνησης του κέντρου ελέγχου, ντετερμινιστικό και τυχαίο. Στην τυχαία κίνηση, η επιλογή της επόμενης περιοχής την οποία θα επισκεφτεί το κέντρο ελέγχου γίνεται με τυχαίο τρόπο, εισάγοντας όμως ένα όρο μεροληψίας, έτσι ώστε να προτιμούνται περιοχές που έχουν δεχτεί λιγότερες επισκέψεις. Επιπλέον η μέθοδός μας αποφασίζει το χρόνο παύσης σε κάθε περιοχή λαμβάνοντας υπόψιν κάποιες βασικές παραμέτρους του δικτύου, όπως τα αρχικά αποθέματα ενέργειας των κόμβων αισθητήρων και την πυκνότητα της κάθε περιοχής, έτσι ώστε να παραμένει περισσότερο χρόνο σε περιοχές με μεγαλύτερη πυκνότητα, άρα και μεγαλύτερη ποσότητα πληροφορίας. Με τον τρόπο αυτό επιτυγχάνεται η γρήγορη κάλυψη όλου του δικτύου, καθώς επίσης και η δίκαιη εξυπηρέτηση των επιμέρους περιοχών του δικτύου. Τα προτεινόμενα πρωτόκολλα αξιολογήθηκαν πειραματικά μέσω προσομοίωσης, χρησιμοποιώντας ποικίλες τιμές για βασικές παραμέτρους του δικτύου και σύγκρινοντάς τα με σχετικές υπάρχουσες ευρέως αποδεκτές μεθόδους. Τα αποτελέσματα που πήραμε δείχνουν ότι τόσο ο χρόνος παράδοσης των μηνυμάτων, όσο και η ενέργεια που καταλώθηκε διατηρούνται σε χαμηλά επίπεδα, βελτιώνοντας σημαντικά την προηγούμενη σχετική έρευνα. / Wireless Sensor Networks consist of a large number of small, autonomous devices, that are able to interact with their inveronment by sensing and collaborate to fulfill their tasks, as, usually, a single node is incapable of doing so; and they use wireless communication to enable this collaboration. Each device has limited computational and energy resources, thus a basic issue in the applicastions of wireless sensor networks is the low energy consumption and hence, the maximization of the network lifetime. The collected data is disseminated to a static control point – data sink in the network, using node to node - multi-hop data propagation. However, sensor devices consume significant amounts of energy in addition to increased implementation complexity, since a routing protocol is executed. Also, a point of failure emerges in the area near the control center where nodes relay the data from nodes that are farther away. Recently, a new approach has been developed that shifts the burden from the sensor nodes to the sink. The main idea is that the sink has significant and easily replenishable energy reserves and can move inside the area the sensor network is deployed, in order to acquire the data collected by the sensor nodes at very low energy cost. However, the need to visit all the regions of the network may result in large delivery delays. In this work we have developed protocols that control the movement of the sink in wireless sensor networks with non-uniform deployment of the sensor nodes, in order to succeed an efficient (with respect to both energy and latency) data collection. More specifically, a graph formation phase is executed by the sink during the initialization: the network area is partitioned in equal square regions, where the sink, pauses for a certain amount of time, during the network traversal, in order to collect data. We propose two network traversal methods, a deterministic and a random one. When the sink moves in a random manner, the selection of the next area to visit is done in a biased random manner depending on the frequency of visits of its neighbor areas. Thus, less frequently visited areas are favored. Moreover, our method locally determines the stop time needed to serve each region with respect to some global network resources, such as the initial energy reserves of the nodes and the density of the region, stopping for a greater time interval at regions with higher density, and hence more traffic load. In this way, we achieve accelerated coverage of the network as well as fairness in the service time of each region.Besides randomized mobility, we also propose an optimized deterministic trajectory without visit overlaps, including direct (one-hop) sensor-to-sink data transmissions only. We evaluate our methods via simulation, in diverse network settings and comparatively to related state of the art solutions. Our findings demonstrate significant latency and energy consumption improvements, compared to previous research.

Defining health and economic burden of Invasive Meningococcal Disease (IMD) in Canada is critical to inform Public Health Policy around immunization programs. A comprehensive literature review was conducted to assess available studies, a lack of comprehensive Canadian data to allow evaluation of total economic burden of IMD was identified in Canada. Thus, this dissertation proposes a prospective cost collection methodology tailored to Canadian data and healthcare utilization (HCU). All patient-related HCU is considered and outlined. HCU is then categorized as direct or indirect and relevant direct and indirect healthcare costs are detailed. Intangible costs are described and methodology for capturing these costs using validated quality of life instruments is proposed. As all published economic evaluations of this disease lack prospective collection of data, this study proposes the use of a patient diary to serve as a memory aid during patient cost-collection interviews.

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The aim of this study was to investigate if a mechanical recruitment process could be a useful tool for employers to avoid discrimination. National and international law protect jobseekers from discrimination during the recruiting process. Despite this individuals frequently report that they are treated unfairly when they apply for a job. In line with this research shows that some individuals do not have the same opportunities in the labour market as the rest of the population. This study focus on discrimination based on ethnicity, age, gender or disability. Today most of the hiring decisions are based on employers professional judgement. This constitute a potential risk for discrimination since the judgement can be influenced by prejudices and stereotypes. The research shows that employers tend to measure variables which are not relevant for individuals future job performance when they make decisions in selection processes. A mechanical approach for the recruitment can broadly correct for this since it is based on standardized procedures that eliminates human judgement. The data collection of candidates strictly relate to a defined job profile which only contains criterions that are of importance for the employment. Pre-specified algorithms are later on used for combining each candidates data into an overall assessment. This regulates that the same criteria is measured for all individuals. In order to analyse the material a legal dogmatic method has been combined with a legal sociology method.

A wireless sensor network is a collection of numerous sensors distributed on an area of interest to collect and process data from the environment. One particular threat in wireless sensor networks is node compromise attacks, that is, attacks where the adversary gets physical access to a node and to the programs and keying material stored on it. Only authorized queries should be allowed in the network and the integrity and confidentiality of the data that is being collected should be protected. We propose a layered key distribution scheme together with two protocols for query authentication and confidential data aggregation. The layered key distribution is more robust to node and communication failures than a predefined tree structure. The protocols are secure under the assumption that less than n sensor nodes are compromised. n is a design parameter that allows us to trade off security for overhead. When more than n sensor nodes are compromised, our simulations show that the attacker can only introduce unauthorized queries into a limited part of the network and can only get access to a small part of the data that is aggregated in the network. Considering the data collection protocol we also contribute with strategies to reduce the energy consumption of an integrity preserving in-network aggregation scheme to a level below the energy consumption of a non-aggregation scheme. Our improvements reduce node congestion by a factor of three and the total communication load by 30%. Location privacy of the users carrying mobile devices is another aspect considered in this thesis. Considering a mobile sink that collects data from the network, we propose a strategy for data collection that requires no information about the location and movement pattern of the sink. We show that it is possible to provide data collection services, while protecting the location privacy of the sink. When mobile phones with built-in sensors are used as sensor nodes, location information about where the data has been sensed can be used to trace users and infer other personal information about them, like state of health or personal preferences. Therefore, location privacy preserving mechanisms have been proposed to provide location privacy to the users. We investigate how a location privacy preserving mechanism influences the quality of the collected data and consider strategies to reconstruct the data distribution without compromising location privacy. / WISENET

Despite the significant advances that have been made in traffic sensor technologies, there are only a few systems that provide measurements at the trip level and fewer yet that can do so for all travel modes. On the other hand, traditional methods of collecting individual travel behavior (i.e. manual or web-based travel diaries) are resource intensive and prone to a wide range of errors. Moreover, although dedicated GPS loggers provide the ability to collect detailed travel behavior data with less effort, their use still faces several challenges including the need to distribute and retrieve the logger; the potential need to have the survey participants upload data from the logger to a server; and the need for survey participants to carry another device with them on all their trips. The widespread adoption of smart phones provides an opportunity to acquire travel behavior data from individuals without the need for participants to record trips in a travel diary or to carry dedicated recording devices with them on their travels. The collected travel data can then be used by municipalities and regions for forecasting the travel demand or for analyzing the travel behavior of individuals. In the current research, a smart phone based travel behavior surveying system is designed, developed, and pilot tested. The custom software written for this study is capable of recording the travel characteristics of individuals over the course of any period of time (e.g. days or weeks) and across all travel modes. In this system, a custom application on the smart phone records the GPS data (using the onboard GPS unit) at a prescribed frequency and then automatically transmits the data to a dedicated server. In the server, the data are stored in a dedicated database to be then processed using trip characteristics inference algorithms. The main challenge with the implemented system is the need to reduce the amount of energy consumed by the device to calculate and transmit the GPS fixes. In order to reduce the power consumption from the travel behavior data acquisition software, several techniques are proposed in the current study. Finally, in order to evaluate the performance of the developed system, first the accuracy of the position information obtained from the data acquisition software is analyzed, and then the impact of the proposed methods for reducing the battery consumption is examined. As a conclusion, the results of implemented system shows that collecting individual travel behavior data through the use of GPS enabled smart phones is technically feasible and would address most of the limitations associated with other survey techniques. According to the results, the accuracy of the GPS positions and speed collected through the implemented system is comparable to GPS loggers. Moreover, proposed battery reduction techniques are able to reduce the battery consumption rate from 13.3% per hour to 5.75% per hour (i.e. 57% reduction) when the trip maker is non-stationary and from 5.75% per hour to 1.41% per hour (i.e. 75.5% reduction) when the trip maker is stationary.

Behavioral research involves the study of the behaviors of one or more agents (often animals) in order to better understand the agents' thoughts and actions. Identifying subject movements and behaviors based upon those movements is a critical, time-consuming step in behavioral research. To successfully perform behavior analysis, three goals must be met. First, the agents of interest are observed, and their movements recorded. Second, each individual must be uniquely identified. Finally, behaviors must be identified and recognized. I explore a system that can uniquely identify and track agents, then use these tracks to automatically build behavioral models and recognize similar behaviors in the future. I address the tracking and identification problems using a combination of laser range finders, active RFID sensors, and probabilistic models for real-time tracking. The laser range component adds environmental flexibility over vision based systems, while the RFID tags help disambiguate individual agents. The probabilistic models are important to target identification during the complex interactions with other agents of similar appearance. In addition to tracking, I present work on automatic methods for generating behavioral models based on supervised learning techniques using the agents' tracked data. These models can be used to classify new tracked data and identify the behavior exhibited by the agent, which can then be used to help automate behavior analysis.

Modern civil structures as well as loads on them are still too complex to be accurately modeled or simulated. Therefore, structural failures and structural defects are NOT uncommon! More and more full-scale structural monitoring systems have been deployed in order to monitor how structures behave under various loading conditions. This research focuses on how to maximise benefits from such full-scale measurements by employing advanced digital signal processing techniques. This study is based on accelerometer and GPS data collected on three very different structures, namely, the steel tower in Tokyo, the long and slender suspension bridge in Hong Kong, and the tall office tower in Sydney, under a range of loading conditions, i.e., typhoon, earthquake, heavy traffic, and small scale wind. Systematic analysis of accelerometer and GPS data has demonstrated that the two sensors complement each other in monitoring the static, quasi-static and dynamic movements of the structures. It has also been confirmed that the Finite Element Model could under-estimate the natural frequencies of structures by more than 40% in some case. The effectiveness of using wavelet to de-noise GPS measurement has been demonstrated. The weakness and strengths of accelerometer and GPS have been identified and framework has been developed on how to integrate the two as well as how to optimize the integration. The three-dimensional spectral analysis framework has been developed which can track the temporal evolution of all the frequency components and effectively represents the result in the 3D spectrogram of frequency, time and magnitude. The dominant frequency can also be tracked on the 3D mesh to vividly illustrate the damping signature of the structure. The frequency domain coherent analysis based on this 3D analysis framework can further enhance the detection of common signals between sensors. The developed framework can significantly improve the visualized performance of the integrated system without increasing hardware costs. Indoor experiments have shown the excellent characteristics of the optical fibre Bragg gratings (FBGs) for deformation monitoring. Innovative and low-cost approach has been developed to measure the shift of FBG???s central wavelength. Furthermore, a schematic design has been completed to multiplex FBGs in order to enable distributed monitoring. In collaboration with the University of Sydney, the first Australian full-scale structural monitoring system of GPS and accelerometer has been deployed on the Latitude Tower in Sydney to support current and future research.