This master thesis has been done in the field of Advanced Driver Assistance Systems and presents a method to assist cross traffic at road junctions. An accurate tracking of crossing objects is necessary in order to assist traffic at road junctions. At Continental, the stable tracking of crossing objects is available, but the system still gives false alarms for non-colliding objects (e.g. Target Braking at crossroads). Hence the main focus of this thesis is on the reduction of false alarms for non colliding objects. Radar based Maneuver Detection function has been developed for Crossing Emergency Brake Assist system, which uses radar measurement parameters to detect the maneuvering of target objects in order to differentiate between collision and non-collision cases. Different crossing scenarios have been created in a Matlab environment and the algorithm is tested. Secondly, the algorithm is tested by using the measurement data from real recordings and evaluation is made. The proposed algorithm has reliably detected the non-collided objects (in normal cases) and helped in reducing the false alarm rate significantly.

The YellowCar at the professorship of computer engineering of TU Chemnitz is a demonstration vehicle. The car is equipped with multiple networked Electronic Control Unit (ECU)s. There are regular software and hardware updates. Before introduction of any new update, it is essential to test the behavior of the car. This can be done through simulation. Since the majority of the ECU in YellowCar are AUTOSAR based, several AUTOSAR simulation tools can be used to do so. However non-AUTOSAR ECU applications can still not be simulated in these tools. Moreover simulating with such tools need the whole application to be implemented and also very expensive. Simulink is one of the most powerful tools for the purpose of Model-in-the-Loop (MIL) testing which is a popular strategy in the embedded world. The scope of this Master thesis is analyzing the YellowCar and its architecture to develop a dynamic Simulink architectural model that can be modified and extended to facilitate future updates. The outcome of this thesis is an implementation of a model for the YellowCar which allows both AUTOSAR and non-AUTOSAR ECUs to be simulated as one system. Also the model supports extension by easy addition of new modules like ECU or sensor through a graphical user interface.

MATLAB is an array language, initially popular for rapid prototyping, but is now being in-creasingly used to develop production code for numerical and scientific applications. Typical MATLAB programs have abundant data parallelism. These programs also have control flow dominated scalar regions that have an impact on the program’s execution time. Today’s com-puter systems have tremendous computing power in the form of traditional CPU cores and also throughput-oriented accelerators such as graphics processing units (GPUs). Thus, an approach that maps the control flow dominated regions of a MATLAB program to the CPU and the data parallel regions to the GPU can significantly improve program performance. In this work, we present the design and implementation of MEGHA, a compiler that auto-matically compiles MATLAB programs to enable synergistic execution on heterogeneous pro-cessors. Our solution is fully automated and does not require programmer input for identifying data parallel regions. Our compiler identifies data parallel regions of the program and com-poses them into kernels. The kernel composition step eliminates a number of intermediate arrays which are otherwise required and also reduces the size of the scheduling and mapping problem the compiler needs to solve subsequently. The problem of combining statements into kernels is formulated as a constrained graph clustering problem. Heuristics are presented to map identified kernels to either the CPU or GPU so that kernel execution on the CPU and the GPU happens synergistically, and the amount of data transfer needed is minimized. A heuristic technique to ensure that memory accesses on the CPU exploit locality and those on the GPU are coalesced is also presented. In order to ensure that data transfers required for dependences across basic blocks are performed, we propose a data flow analysis step and an edge-splitting strategy. Thus our compiler automatically handles kernel composition, mapping of kernels to CPU and GPU, scheduling and insertion of required data transfers. Additionally, we address the problem of identifying what variables can coexist in GPU memory simultaneously under the GPU memory constraints. We formulate this problem as that of identifying maximal cliques in an interference graph. We approximate the interference graph using an interval graph and develop an efficient algorithm to solve the problem. Furthermore, we present two program transformations that optimize memory accesses on the GPU using the software managed scratchpad memory available in GPUs. We have prototyped the proposed compiler using the Octave system. Our experiments using this implementation show a geometric mean speedup of 12X on the GeForce 8800 GTS and 29.2X on the Tesla S1070 over baseline MATLAB execution for data parallel benchmarks. Experiments also reveal that our method provides up to 10X speedup over hand written GPUmat versions of the benchmarks. Our method also provides a speedup of 5.3X on the GeForce 8800 GTS and 13.8X on the Tesla S1070 compared to compiled MATLAB code running on the CPU.

Master of Science / Department of Geology / Saugata Datta / The incidence of high arsenic (As) and other oxyanions (e.g. Mn) has been examined in a ~410km[superscript]2 areas within the Bengal Delta between North and South Matlab, Bangladesh. The aim of this study was to examine the role of sediment geochemistry, coupled with microbial community studies and their relations with different colors and grain sizes of sediments, in determining evolved groundwater hydrochemistry within the aquifers in Matlab. Groundwaters are Ca–Mg–HCO[subscript]3- types in shallow aquifers, Mg-HCO[subscript]3- in the intermediate depths and Na-K-Cl rich in the deeper aquifers. Dissolved As concentration is high (~781μg/l) associated with shallow grey and dark grey sediments, whereas light grey sediments at intermediate depths contain lower As (<10 μg/l). Dissolved Fe[superscript]T on other hand in both sediment types (light grey and grey) shows good correlation with dissolved SO[subscript]4[superscript]2-. In plots of [delta]δ[superscript]18O vs [delta]δD, intermediate and deeper depth aquifer waters plot on the arrays for LMWL and GMWL, which indicates the principal recharge mechanism is likely to be from local precipitation within the shallow aquifers. Only the high As groundwaters deflect from the LMWL, indicating that recharge might be a mixture of precipitation and surficial discharges / infiltrations for these waters. Bulk extraction of sediments showed that grey and dark grey sediments from shallow depths have higher As concentrations (~31 mg/kg) and light grey sediments have comparatively less (~11mg/kg). Sequential extractions for sediment fractionations showed that most of the As was bound to amorphous and poorly crystalline hydrous oxides of Fe and Al phases. Synchrotron-aided bulk-XANES studies conducted on sediments revealed As and S speciation in the core samples at different depths indicating the occurrences of hotspots of As distributed randomly in light grey and grey sediments. As[superscript]3+ is the dominant species in Matlab sediments. More than 101 bacterial families were identified among the eight sediment samples from the South Matlab core and out of them fewer than six families comprised more than ~80% of total bacterial families. Our results indicate significant relationships between bacterial community structure, grain size fractionation, dissolved As concentration and sediment C, Mn, and Fe concentrations for these samples. Groundwater abstracted from these light grey sediments, in contrast to reduced greyish to dark greyish sediments, contain significantly lower amounts of dissolved As and can be a source of safe water for the future. Our work demonstrates that intermediate depth light grey sediments have geochemical and microbial features conducive with safe drinking water for the future.

Quantity and intricacy of features implemented in vehicle have expanded rapidly over a past few years. Currently vision of autonomous vehicle is no longer a dream or SF movie, but instead a coming reality. In order to reach the better quality and high safety, advanced verification techniques are required. Simulink Design Verifier is a model checking tool based on formal verification, which can be effectively used to solve problems concerning error detection and testing at earlier stages of project. The transformation of requirements written in traditional form into Simulink Design Verifier objectives can be time consuming as well as requiring knowledge of system model and the verification tools. In order to reduce time consumption and to guide a user through the system model and the verification tool, the semi-automated framework has been developed. An implementation of restricted English grammar patterns into Simulink objects supports description of patterns to engineers and reduces time consumption. The developed framework is flexible and intuitive hence can be a solution for other branches of industry, but further tests and verification would be required. This thesis highlights the whole process of transformation system requirements written in natural language into Simulink Design Verifier objectives. The Fuel Level Display System model currently used by almost all Scania’s vehicles is analysed. Limitations and errors encountered during development process like a flexibility of Simulink Design Verifier to capture requirements and the patterns behaviour or ambiguity of system requirements are analysed and described in this thesis.

International Telemetering Conference Proceedings / October 18-21, 2004 / Town & Country Resort, San Diego, California / The embedded system related hardware technology has experienced rapid development, and it provided the software technology with a huge space for growth. Therefore using software approaches to perform GPS receiver functions in a powerful and generic hardware platform is becoming more feasible. In this paper, the software GPS receiver technology and the design basics of the software receiver are discussed. Further in the Matlab simulation environment, the implementation of a software receiver for replacing the processing functions of ASIC in traditional GPS receivers, i.e. RF front end and multi-channel correlator, is presented. Some simulation results and implementation details are included.

This thesis reports on algorithmic design and software development completed for the Medipix All Resolution System (MARS) multi-energy CT scanner. Two areas of research are presented - the speed and usability improvements made to the post-reconstruction material decomposition software; and the development of two algorithms designed for the implementation of a novel voxel system into the MARS image reconstruction chain. The MARS MD software package is the primary material analysis tool used by members of the MARS group. The photon-processing ability of the MARS scanner is what makes material decomposition possible. MARS MD loads reconstructed images created after a scan and creates a new set of images, one for every individual material within the object. The software is capable of discriminating at least six different materials, plus air, within the object. A significant speed improvement to this program was attained by moving the code base from GNU Octave to MATLAB and applying well known optimisation routines, while the creation of a graphical user interface made the software more accessible and easy to use. The changes made to MARS MD represented a significant contribution to the productivity of the entire MARS group. A drawback of the MARS image reconstruction chain is the time required to generate images of a scanned object. Compared to commercially available CT systems, the MARS system takes several orders of magnitude longer to do essentially the same job. With up to eight energy bins worth of data to consider during reconstruction, compared to a single energy bin in most com- mercial scanners, it is not surprising that there is a shortfall. A major performance limitation of the reconstruction process lies in the calculation of the small distances travelled by every detected photon within individual portions of the reconstruction volume. This thesis investigates a novel volume geometry that was developed by Prof. Phil Butler and Dr. Peter Renaud, and is designed to partially mitigate this time constraint. By treating the volume as a cylinder instead of a traditional cubic structure, the number of individual path length calculations can be drastically reduced. Two sets of algorithms are prototyped, coded in MATLAB, C++ and CUDA, and finally compared in terms of speed and visual accuracy.

In this thesis, a machine learning approach was used to develop a predictive model for residual methanol concentration in industrial formalin produced at the Akzo Nobel factory in Kristinehamn, Sweden. The MATLABTM computational environment supplemented with the Statistics and Machine LearningTM toolbox from the MathWorks were used to test various machine learning algorithms on the formalin production data from Akzo Nobel. As a result, the Gaussian Process Regression algorithm was found to provide the best results and was used to create the predictive model. The model was compiled to a stand-alone application with a graphical user interface using the MATLAB CompilerTM.

A research report submitted to the faculty of Engineering and the Built Environment, of the University of the Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the degree of Master of Science in Engineering Johannesburg 2014 / Clearances are an important aspect of High Voltage (HV) transmission line design, construction and maintenance. A software tool that combines clearance violation analysis and optimum loading operating conditions for power lines could save power utilities the capital cost of refurbishing transmission power lines that marginally exceed maximum power line clearance distances. This can be achieved by operating the power lines at an optimum amperage level for any given set of weather conditions. This research project proposes a low cost MATLAB® based software tool that detects clearance violations and determines operational limits on transmission power lines using prevalent weather conditions as well as the power line amperage. Various power lines around the states of Missouri and Illinois in the United States of America are analysed to test the viability and functionality of the software. In order to validate the accuracy of the program, the results obtained were compared to results from PLSCADD ®. Key Words: conductor, clearance, sag, software, temperature / MB2016

Los autovalores y autovectores son elementos muy utilizados en diversos problemas como análisis de estructuras, reconocimiento de imágenes, compresión de datos, solución de problemas electrodinámicos, entre otros. Existen muchos algoritmos para calcular y tratar con autovalores y autovectores mediante el uso de computadoras, sin embargo, cuando solo se requiere uno o unos pocos autovalores (los más significativos) y autovectores, se puede optar por Power Method o la Iteración Lanczos. Por otro lado, factores como la cantidad de información a procesar o la precisión deseada pueden significar tiempos de ejecución no aceptables para ciertas aplicaciones, surgiendo la alternativa de realizar implementaciones paralelas, siendo la arquitectura CUDA una de la mejores opciones actualmente. En la presente tesis se propone diseñar e implementar un algoritmo paralelo para la iteración Lancos en arquitectura CUDA, el cual es un método para el cálculo del mayor autovalor y su correspondiente autovector. La propuesta esta dividia en tres bloques principales. El primer bloque realiza la tridiagonalización parcial de una matriz cuadrada simétrica. El segundo bloque calcula la descomposición de Schur de la matriz tridiagonal obteniendo los autovectores y autovalores de esta. El tercer bloque calcula el mayor autovalor y su correspondiente autovector de la matriz inicial a partir de lo obtenido en etapas anteriores y determinará si es necesario seguir realizando cálculos. Los bloques trabajan iterativamente hasta encontrar resultados que se ajusten a la precisión deseada. Además de la implementación paralela en CUDA, se realizaron implementaciones en el entorno de simulación MATLAB y en lenguaje C secuencial, con el propósito de comparar y verificar una correcta y eficiente implementación paralela. Los resultados computacionales evaluados para una matriz de 4000 _ 4000 elementos reflejan un rendimiento de 13;4 y 5;8 al compararse la implementación en CUDA con MATLAB y C secuencial respectivamente. Estos rendimientos tienden a crecer mientras mayor sea el tamaño de la matriz. La organización de la tesis es: en el primer capítulo se describe la problemática del tema. En el segundo capítulo se explica la teoría correspondiente a Power Method y Lanczos, así como los algoritmos necesarios. En el capítulo tres se exponen conceptos fundamentales sobre arquitectura CUDA. El diseño del algoritmo paralelo se desarrolla en el capítulo cuatro. Finalmente, en el capítulo cinco, se muestran y analizan los resultados computacionales, seguidos de las conclusiones, recomendaciones y bibliografía. / Tesis