Werden zwei Aufgaben in einem Doppelaufgaben-Paradigma gleichzeitig bearbeitet, dann treten oft sogenannte Doppelaufgabenkosten auf (längere Reaktionszeiten und/oder höhere Fehlerzahlen). Diese Doppelaufgabenkosten werden durch einen zentralen “Flaschenhals” erklärt, der die gleichzeitige Verarbeitung der beiden Aufgaben an der zentralen Verarbeitungsstufe der Reaktionsauswahl verhindert. Das Ziel der vorliegenden Arbeit war es, einige mögliche Faktoren der Verarbeitungsreihenfolge an diesem Flaschenhals zu untersuchen. Die Studie zeigt, dass die Ankunftszeit am Flaschenhals ein wichtiger Faktor bei der Festlegung der Verarbeitungsreihenfolge ist. Zusätzlich ist der Einfluss der Ankunftszeit auf die Verarbeitungsreihenfolge unabhängig davon, welche der beiden Aufgaben manipuliert wurde um den Einfluss dieser Aufgabe zu untersuchen (visuelle oder auditorische Aufgabe). Ein zweiter Faktor der manipuliert wurde, ist die Instruktion an die Probanden. Die Ergebnisse zeigen, dass unter bestimmten Instruktionsbedingungen kognitive Kontrollprozesse aktiviert zu werden scheinen. Als dritten Faktor wurden Aufgabenanforderungen untersucht, indem eine Aufgabe mit zeitlicher Reihenfolge-Entscheidung mit einer Doppelaufgabe mit zufälliger Aufgabenreihenfolge, d.h.: Bestimmung der zeitlichen Reihenfolge mit der zusätzlichen Anforderung einer Reaktionswahl-Aufgabe, verglichen wurde. Die Ergebnisse dieser Experimente deuten darauf hin, dass die Entscheidung über die zeitliche Reihenfolge der beiden Aufgaben zwischen der Wahrnehmungsstufe und der Reaktionswahlstufe getroffen wird. / The simultaneous performance of two tasks in a dual-task paradigm is often accompanied by dual-task costs (longer reaction times and/or higher error rates). These dual-task costs have been explained by the existence of a central bottleneck which prohibits the simultaneous processing of the two tasks at the central response-selection stage of information processing. The aim of the present work was to investigate several of the possible factors which determine the task processing order at this central bottleneck. The study shows that the arrival time of the two tasks at the bottleneck plays an important role in the determination of task order. Additionally, the influence of the arrival time on processing order is independent of the component task which is manipulated to test the influence of that task (i.e., visual & auditory task). A second factor that was manipulated is the instruction given to the participants. The results show that cognitive control processes are activated under certain instruction conditions. As a third factor, task requirements were investigated by comparing a temporal order judgement task with a dual task with random task order (i.e., temporal order judgement with the additional requirement to do a choice-RT task). The results suggest that the decision about the temporal order of the two tasks is located between the perception stage and the response-selection stage of processing.

[pt] Este trabalho apresenta os resultados da investigação da utilização da Técnica de Sondagem em Frequência na estimação de dispersividade Espaço-Temporal do Canal Rádio Móvel. Modifcações na técnica clássica de varredura em frequência foram implementadas: um conjunto de antenas denominado array foi construído e calibrado e um algoritmo de pós-processamento do sinal medido foi testado. Foi realizada uma campanha de medidas em três ambientes diferentes para averiguar a aplicabilidade do conjunto. Foram obtidos bons resultados, demonstrando a efciência da metodologia de medidas aplicada. / [en] This work presents the results of an investigation of the use of the Frequency Sounding technique in Mobile Radio Channel`s Space-Time Dispersion characterization. Hence, some changes in the classical Frequency Sounding Technique were employed: a set of antennas was built and calibrated and an algorithm for signal pos processing was tested. A measurement campaign was carried out on three different environments to test the applicability of the set as a whole. Very good results showed the efficiency of the measurements methodology applied.

In recent years there has been growing interest in ad-hoc and wireless sensor networks (WSNs) for a variety of indoor applications. Localization information in these networks is an enabling technology and in some applications it is the main sought after parameter. The cooperative localization performance of WSNs is ultimately constrained by the behavior of the utilized ranging technology in dense cluttered indoor environments. Recently, ultra-wideband (UWB) Time-of-Arrival (TOA) based ranging has exhibited potential due to its large bandwidth and high time resolution. However, the performance of its ranging and cooperative localization capabilities in dense indoor multipath environments needs to be further investigated. Of main concern is the high probability of non-line of sight (NLOS) and Direct Path (DP) blockage between sensor nodes, which biases the TOA estimation and degrades the localization performance. In this dissertation, we first present the results of measurement and modeling of UWB TOA-based ranging in different indoor multipath environments. We provide detailed characterization of the spatial behavior of ranging, where we focus on the statistics of the ranging error in the presence and absence of the DP and evaluate the pathloss behavior in the former case which is important for indoor geolocation coverage characterization. Parameters of the ranging error probability distributions and pathloss models are provided for different environments: traditional office, modern office, residential and manufacturing floor; and different ranging scenarios: indoor-to-indoor (ITI), outdoor-to-indoor (OTI) and roof-to-indoor (RTI). Based on the developed empirical models of UWB TOA-based OTI and ITI ranging, we derive and analyze cooperative localization bounds for WSNs in the different indoor multipath environments. First, we highlight the need for cooperative localization in indoor applications. Then we provide comprehensive analysis of the factors affecting localization accuracy such as network and ranging model parameters. Finally we introduce a novel distributed cooperative localization algorithm for indoor WSNs. The Cooperative LOcalization with Quality of estimation (CLOQ) algorithm integrates and disseminates the quality of the TOA ranging and position information in order to improve the localization performance for the entire WSN. The algorithm has the ability to reduce the effects of the cluttered indoor environments by identifying and mitigating the associated ranging errors. In addition the information regarding the integrity of the position estimate is further incorporated in the iterative distributed localization process which further reduces error escalation in the network. The simulation results of CLOQ algorithm are then compared against the derived G-CRLB, which shows substantial improvements in the localization performance.

National security needs dictate the development of new radar systems capable of identifying and tracking exoatmospheric threats to aid our defense. These new radar systems feature reduced noise floors, electronic beam steering, and ultra-wide bandwidths, all of which facilitate threat discrimination. However, in order to identify missile attributes such as RF reflectivity, distance, and velocity, many existing processing algorithms rely upon narrow bandwidth assumptions that break down with increased signal bandwidth. We present a fresh investigation into these algorithms for removing bandwidth limitations and propose novel state-space and direct-data factoring formulations such as * the multidimensional extension to the Eigensystem Realization Algorithm, * employing state-space models in place of interpolation to obtain a form which admits a separation and isolation of solution components, * and side-stepping the joint diagonalization of state transition matrices, which commonly plagues methods like multidimensional ESPRIT. We then benchmark our approaches and relate the outcomes to the Cramer-Rao bound for the case of one and two adjacent reflectors to validate their conceptual design and identify those techniques that compare favorably to or improve upon existing practices.

In a narrative the narrator tells the story, and the focalizer is a character through whose eyes the story is seen. The narrator is thus the one who speaks, whilst the focalizer is silent. The identification of these two narratological features is made with the help of verbal cues such as personal pronouns for instance. Determining the narrator and the focalizer can sometimes be challenging due to ambiguous cues in the analyzed text, as well as narratological aspects which at times can be difficult to distinguish from each other. Determining the narrator and the focalizer in graphic narratives (comics) with no narrative voice, or which completely lack words, must be done with the help of pictorial cues instead. In this thesis, Shaun Tan’s wordless graphic narrative The Arrival is used in order to show how the narrator and the focalizer can be determined by combining pictorial cues with the reader’s general knowledge of storytelling as well as his or her experiences from real life scenarios. To analyze narratological features in The Arrival, I employ terminology from comics studies, literary and film narratology. My analysis shows that determining the narrator and the focalizer in narratives lacking explicit narrative voice is possible by using only pictorial cues.

The computer and microelectronics technologies are developing very quickly nowadays. In the mean time, the modern integrated avionics systems are burgeoning unceasingly. The modern integrated modular architecture more and more requires the low-latency and reliable communication databus with the high bandwidth. The traditional avionics databus technology, such as ARINC429, can not provide enough high speed and size for data communication, and it is a problem to achieve transmission mission successfully between the advanced avionic devices with the sufficient bandwidth. AFDX(Avionics Full Duplex Switched Ethernet) is a good solution for this problem, which is the high-speed full duplex switched avionic databus, on the basis of the Ethernet technology. AFDX can not only avoid Ethernet conflicts and collisions, but also increase transmission rate with a lower weigh of the databus. AFDX is now adopted by A380,B787 aircraft successfully. The avionics data must be delivered punctualy and reliablely, so it is very essential to validate the real-time performance of AFDX during the design process. The simulation is a good method to acquire the network performance, but it only happends in some given set of scenarios, and it is impossible to consider every case. So a sophisticatd network performance method for the worst-case scenario with the pessimistic upper bound requires to be deduced. The avionic design engineers have launched many researches in the AFDX simulation and methods study. That is the goal that this thesis is aimming for. The development of this project can been planned in the following two steps. In the first step, a communication platform plans to be implemented to simulate the AFDX network in two versions – the RTAI realtime framework and Linux user space framework. Ultimately, these frameworks need to be integrated into net-ASS, which is an integrated simulation and assessment platform in the cranfield’s lab.The second step deduces an effective method to evaluate network performance, including three bounds(delay,backlog and output flow), based on the NC. It is called Network Calculus. It is an internet theory keeping the network system in determistic way. It is also used in communication queue management. This mathematics method is planed to be verified with simulation results from the AFDX simuation communication platform, in order to assure its validity and applicability. All in all, the project aims to assess the performance of different network topologies in different avionic architectures, through the simulation and the mathematical assessment. The technologies used in this thesis benefit to find problems and faults in the beginning stage of the avionics architecture design in the industrial project, especially, in terms of guarantee the lossless service in avionics databus.

Waterflood optimization via rate control is receiving increased interest because of rapid developments in the smart well completions and I-field technology. The use of inflow control valves (ICV) allows us to optimize the production/injection rates of various segments along the wellbore, thereby maximizing sweep efficiency and delaying water breakthrough. It is well recognized that field scale rate optimization problems are difficult because they often involve highly complex reservoir models, production and facilities related constraints and a large number of unknowns. Some aspects of the optimization problem have been studied before using mainly optimal control theory. However, the applications to-date have been limited to rather small problems because of the computation time and the complexities associated with the formulation and solution of adjoint equations. Field-scale rate optimization for maximizing waterflood sweep efficiency under realistic field conditions has still remained largely unexplored. We propose a practical and efficient approach for computing optimal injection and production rates and thereby manage the waterflood front to maximize sweep efficiency and delay the arrival time to minimize water cycling. Our work relies on equalizing the arrival times of the waterfront at all producers within selected sub-regions of a water flood project. The arrival time optimization has favorable quasi-linear properties and the optimization proceeds smoothly even if our initial conditions are far from the solution. We account for geologic uncertainty using two optimization schemes. The first one is to formulate the objective function in a stochastic form which relies on a combination of expected value and standard deviation combined with a risk attitude coefficient. The second one is to minimize the worst case scenario using a min-max problem formulation. The optimization is performed under operational and facility constraints using a sequential quadratic programming approach. A major advantage of our approach is the analytical computation of the gradient and Hessian of the objective which makes it computationally efficient and suitable for large field cases. Multiple examples are presented to support the robustness and efficiency of the proposed optimization scheme. These include several 2D synthetic examples for validation purposes and 3D field applications.

A generalized dynamic programming based algorithm and a local search heuristic are used to solve the Two Runway Departure Scheduling Problem that arises at an airport. The objective of this work is to assign the departing aircraft to one of the runways and find a departing time for each aircraft so that the overall delay is minimized subject to the timing, safety, and the ordering constraints. A reduction in the overall delay of the departing aircraft at an airport can improve the airport surface operations and aircraft scheduling. The generalized dynamic programming algorithm is an exact algorithm, and it finds the optimal solution for the two runway scheduling problem. The performance of the generalized dynamic programming algorithm is assessed by comparing its running time with a published dynamic programming algorithm for the two runway scheduling problem. The results from the generalized dynamic programming algorithm show that this algorithm runs much faster than the dynamic programming algorithm. The local search heuristic with k − exchange neighborhoods has a short running time in the order of seconds, and it finds an approximate solution. The performance of this heuristic is assessed based on the quality of the solution found by the heuristic and its running time. The results show that the solution found by the heuristic for a 25 aircraft problem has an average savings of approximately 15 percent in delays with respect to a first come-first served solution. Also, the solutions produced by a 3-opt heuristic for a 25 aircraft scheduling problem has an average quality of 8 percent with respect to the optimal solution found by the generalized dynamic programming algorithm. The heuristic can be used for both real-time and fast-time simulations of airport surface operations, and it can also provide an upper limit for an exact algorithm. Aircraft arrival scheduling problems may also be addressed using the generalized dynamic programming algorithm and the local search heuristic with slight modification to the constraints.

In this thesis a new approach is proposed for non-uniform linear arrays (NLA) which employs conventional subspace methods to improve the direction of arrival (DOA) estimation performance. Uniform linear arrays (ULA) are composed of evenly spaced sensor elements located on a straight line. ULA&#039 / s covariance matrix have a Vandermonde matrix structure, which is required by fast subspace DOA estimation algorithms. NLA differ from ULA only by some missing sensor elements. These missing elements cause some gaps in covariance matrix and Vandermonde structure is lost. Therefore fast subspace DOA algorithms can not be applied in this case. Linear programming methods and array interpolation methods can be used to solve this problem. However linear programming is computationally expensive and array interpolation is angular sector dependent and requires the same number of sensor in the virtual array. In this thesis, a covariance matrix augmentation method is developed by using the array interpolation technique and initial DOA estimates. An initial DOA estimate is obtained by Toeplitz completion of the covariance matrix. This initial DOA estimates eliminates the sector dependency and reduces the least square mapping error of array interpolation. A Wiener formulation is developed which allows more sensors in the virtual array than the real array. In addition, it leads to better estimates at low SNR. The new covariance matrix is used in the root-MUSIC algorithm to obtain a better DOA estimate. Several computer simulations are done and it is shown that the proposed approach improves the DOA estimation accuracy significantly compared to the same number of sensor ULA. This approach also increases the number of sources that can be identifed.

In this thesis, a Neural Network (NN) based beamforming algorithm is proposed for real time target tracking problem. The algorithm is performed for two applications, linear and cylindrical arrays. The linear array application is implemented with equispaced omnidirectional sources. The influence of the number of antenna elements and the angular seperation between the incoming signals on the performance of the beamformer in the linear array beamformer is studied, and it is observed that the algorithm improves its performance by increasing both two parameters in linear array beamformer. The cylindrical array application is implemented with twelve microstrip patch antenna (MPA) elements. The angular range of interest is divided into twelve sectors. Since three MPA elements are used to form the beam in each sector, the input size of the neural network (NN) is reduced in cylindrical array. According to the reduced size of NN, the training time of the beamformer is decreased. The reduced size of the NN has no degradation in forming the beams to the desired directions. The angular separation between the targets is an important parameter in cylindrical array beamformer.