With the advent of Network-Centric Warfare (NCW) concepts, Command and Control (C2) Systems need efficient methods for communicating between heterogeneous systems. To extract or exchange various levels of information within the networks requires interoperability between human and machine as well as between machine and machine. This dissertation explores the Information Exchange Framework (IEF) concept of distributed data fusion sensor networks in Network-centric environments. It is used to synthesize integrative battlefield pictures by combining the Battle Management Language (BML) and System Entity Structure (SES) ontology framework for C2 systems. The SES is an ontology framework that can facilitate information exchange in a network environment. From the perspective of the SES framework, BML serves to express pragmatic frames, since it can specify the information desired by a consumer in an unambiguous way. This thesis formulates information exchange in the SES ontology via BML and defines novel pruning and transformation processes of the SES to extract and fuse data into higher level representations. This supports the interoperability between human users and other sensor systems. The efficacy of such data fusion and exchange is illustrated with several battlefield scenario examples.A second intercommunication issue between sensor systems is how to ensure efficient and effective message passing. This is studied by using Cursor-on-Target (CoT), an effort to standardize a battlefield data exchange format. CoT regulates only a few essential data types as standard and has a simple and efficient structure to hold a wide range of message formats used in dissimilar military enterprises. This thesis adopts the common message type into radar sensor networks to manage the target tracking problem in distributed sensor networks.To demonstrate the effectiveness of the proposed Information Exchange Framework for data fusion systems, we illustrate the approach in an air defense operation scenario using DEVS modeling and simulation. The examples depict basic air defense operation procedure. The demonstration shows that the information requested by a commander is delivered in the right way at the right time so that it can support agile decision making against threats.

Prediction of flow and combustion in IC engines remains a challenging task. Traditional Reynolds Averaged Navier Stokes (RANS) methods and emerging Large Eddy Simulation (LES) techniques are being used as reliable mathematical tools for such predictions. However, RANS models have to be further refined to make them more predictive by eliminating or reducing the requirement for application based fine tuning. LES holds a great potential for more accurate predictions in engine related unsteady combustion and associated cycle-tocycle variations. Accordingly, in the present work, new advanced CFD based flow models were developed and validated for RANS and LES modelling of turbulent premixed combustion in SI engines. In the research undertaken for RANS modelling, theoretical and experimental based modifications have been investigated, such that the Bray-Moss-Libby (BML) model can be applied to wall-bounded combustion modelling, eliminating its inherent wall flame acceleration problem. Estimation of integral length scale of turbulence has been made dynamic providing allowances for spatial inhomogeneity of turbulence. A new dynamic formulation has been proposed to evaluate the mean flame wrinkling scale based on the Kolmogorov Pertovsky Piskunow (KPP) analysis and fractal geometry. In addition, a novel empirical correlation to quantify the quenching rates in the influenced zone of the quenching region near solid boundaries has been derived based on experimentally estimated flame image data. Moreover, to model the spark ignition and early stage of flame kernel formation, an improved version of the Discrete Particle Ignition Kernel (DPIK) model was developed, accounting for local bulk flow convection effects. These models were first verified against published benchmark test cases. Subsequently, full cycle combustion in a Ricardo E6 engine for different operating conditions was simulated. An experimental programme was conducted to obtain engine data and operating conditions of the Ricardo E6 engine and the formulated model was validated using the obtained experimental data. Results show that, the present improvements have been successful in eliminating the wall flame acceleration problem, while accurately predicting the in-cylinder pressure rise and flame propagation characteristics throughout the combustion period. In the LES work carried out in this research, the KIVA-4 RANS code was modified to incorporate the LES capability. Various turbulence models were implemented and validated in engine applications. The flame surface density approach was implemented to model the combustion process. A new ignition and flame kernel formation model was also developed to simulate the early stage of flame propagation in the context of LES. A dynamic procedure was formulated, where all model coefficients were locally evaluated using the resolved and test filtered flow properties during the fully turbulent phase of combustion. A test filtering technique was adopted to use in wall bounded systems. The developed methodology was then applied to simulate the combustion and associated unsteady effects in Ricardo E6 spark ignition engine at different operating conditions. Results show that, present LES model has been able to resolve the evolution of a large number of in-cylinder flow structures, which are more influential for engine performance. Predicted heat release rates, flame propagation characteristics, in-cylinder pressure rise and their cyclic variations are also in good agreement with measurements.

Based on a study of the engagement process between humans, I have developed models for four types of connection events involving gesture and speech: directed gaze, mutual facial gaze, adjacency pairs and backchannels. I have developed and validated a reusable Robot Operating System (ROS) module that supports engagement between a human and a humanoid robot by generating appropriate connection events. The module implements policies for adding gaze and pointing gestures to referring phrases (including deictic and anaphoric references), performing end-of-turn gazes, responding to human-initiated connection events and maintaining engagement. The module also provides an abstract interface for receiving information from a collaboration manager using the Behavior Markup Language (BML) and exchanges information with a previously developed engagement recognition module. This thesis also describes a Behavior Markup Language (BML) realizer that has been developed for use in robotic applications. Instead of the existing fixed-timing algorithms used with virtual agents, this realizer uses an event-driven architecture, based on Petri nets, to ensure each behavior is synchronized in the presence of unpredictable variability in robot motor systems. The implementation is robot independent, open-source and uses the Robot Operating System (ROS).

L'étude expérimentale porte sur l'influence de la haute-pression jusqu'à 0.9 MPa pour la combustion d'une flamme de prémélange méthane-air, pauvre, turbulente stabilisée sur un brûleur de type Bunsen. La vitesse débitante et la richesse sont fixées à 2.1 m/s et 0.6. Le champ de vitesses et les échelles de la turbulence sont déterminés à l'aide de l'anémométrie Laser Doppler. Les mesures de diffusion Rayleigh renseignent sur la fluctuation du scalaire. De l'imagerie de Mie deux dimensions sont obtenus la courbure, l'angle d'orientation, les longueurs de plissement et enfin, la densité de surface de flamme et l'intensité de combustion qui sont comparées avec les valeurs données par le modèle BML. Lorsque la pression augmente les échelles de Taylor et de Kolmogorov diminuent avec la viscosité cinématique, l'échelle intégrale et la vitesse fluctuante restent constantes, les structures du front de flamme deviennent plus petites et plus pointues, augmentant la densité de surface de flamme.

The goal of this master's thesis is a creation of dataset capturing selected users' activities, network analysis of this dataset, design and implementation of method to detect selected users' activities and discussion of achieved results. 4 devices have been chosen for the creation of this dataset.