Indiana University-Purdue University Indianapolis (IUPUI) / Close range, image based photogrammetry and LIDAR laser scanning technique are commonly utilized methodologies to snap real objects.3D models of already existing model or parts can be reconstructed by laser scanning and photogrammetry. These 3D models can be useful in applications like quality inspection, reverse engineering. With these techniques, they have their merits and limitations. Though laser scanners have higher accuracy, they require higher initial investment. Close-range photogrammetry is known for its simplicity, versatility and e ective detection of complex surfaces and 3D measurement of parts. But photogrammetry techniques can be initiated with comparatively much lower initial cost with acceptable accuracy. Currently, many industries are using photogrammetry for reverse engineering, quality inspection purposes. But, for photogrammetric object reconstruction, they are using di erent softwares. Industrial researchers are using commercial/open source codes for reconstruction and another stand-alone software for reverse engineering and mesh deviation analysis. So the problem statement here for this thesis is to integrate Photogrammetry, reverse engineering and deviation analysis to make one state-of-the-art work ow. xx The objectives of this thesis are as follows: 1. Comparative study between available source codes and identify suitable and stable code for integration; understand the photogrammetry methodology of that particular code. 2. To create a taskpane add-in using API for Integration of selected photogrammetry methodology and facilitate methodology with parameters. 3. To demonstrate the photogrammetric work ow followed by a reverse engineering case studies to showcase the potential of integration. 4. Parametric study for number of images vs accuracy 5. Comparison of Scan results, photogrammetry results with actual CAD data

No description available.

Die Skelettextraktion ist besonders in der Formanalyse ein wichtiges Werkzeug. Im Rahmen des Forschungsprojektes ’Extraktion fertigungsrelevanter Merkmale aus 3D-Daten umformtechnischer Bauteile zur featurebasierten Fertigungsprozessgestaltung’ als Kooperationsprojekt zwischen der Professur Graphische Datenverarbeitung und Visualisierung an der Technischen Universität Chemnitz und des Fraunhofer-Institut für Werkzeugmaschinen und Umformtechnik Chemnitz wurde diese zur Featureerkennung umgesetzt. Dieses Dokument gibt zunächst Einblick in grundlegende Verfahren und Problemstellungen einer solchen Extraktion. Die Ergebnisse mehrerer Forschungsschwerpunkte, die sich aus den zu untersuchenden Massivumformteilen ergaben, werden vorgestellt. Hierbei besonders interessant ist die robuste Extraktion von Kurvenskeletten bei Bauteilen mit nicht-zylindrischer Hauptform, sowie bei Bauteilen mit Nebenformelementen. Desweiteren werden Nachverarbeitung und Auswertung des Kurvenskeletts, sowie verwandte Forschungsarbeiten und -ergebnisse diskutiert.

published_or_final_version / abstract / Mechanical Engineering / Doctoral / Doctor of Philosophy

Photogrammetry and laser scanning are two primary methods used for object reconstruction / reverse engineering. But Laser scanners have much higher initial investment compared to photogrammetry method.<div>Currently, in the industry, researchers have been using 3 different softwares for reverse engineering purposes from photogrammetry/laser scanning.</div><div><br></div><div>This thesis is to showcase research work with following points:</div><div>1. Comparison between laser scanner and photogrammetry tools.</div><div>2. Application of photogrammetry in the industry.</div><div>3. Evaluation of photogrammetry tools based on quality of mesh results and comparison with baseline standard of laser-scanner results.</div><div>4. Proposed integrated methodology with photogrammetry tool for reverse engineering within single environment. </div><div>5. Validation of this integrated methodology with case studies.</div><div>6. Parametric study of tool for accuracy and comparison with actual standard models.</div><div><div><br></div></div>

<p>The task to this thesis has been to create an application, Katana-databas 1.0, for analysing c-code. The generated output gets stored in a data structure which content in the end of the program run gets written in a textfile which gets used by Katana. It's a tool for reverse engineering, developed by Johan Kraft at Mälardalens institute.</p><p>Katana-databas has got the following limitations. (1) It can only handle preprocessed files, meaning it doesn't contain any rows beginning with "#". (2) Only complete files can be handled. (3) No references to unknown functions or variables are allowed. (4) A further limitation is that the application can't handle any ADT's. It can only handle primitive types. (5) Finally the application is only written for pure c-code, and thus doesn't handle code written C++.</p><p>The task has been solved by creating an automatically generated lexer with Flex and Bison rules in Visual Studio. There after a limited parser has been developed which purpose is to process the lexemes which the lexer generates.</p><p>The underlying causes for the thesis is to replace Understand with Katana-databas. Katana has this far used the database in Understand, but it contains closed source code. What is seeked is open source code, which Katana-databas is based on.</p> / <p>Programmeringsuppgiften till detta arbete har bestått i att skapa en applikation, Katana-databas 1.0, för analys av C-kod. Utflödet som applikationen skapar sparas i en datastruktur vars innehåll i slutet av programkörningen skrivs ut i en textfil som används av Katana. Det är ett verktyg för reverse engineering, utvecklat av Johan Kraft på Mälardalens högskola.</p><p>Katana-databas har fått följande begränsningar. (1) Den kan bara hantera filer som är preprocessade, dvs. den innehåller inga rader som inleds med ”#”. (2) Endast kompletta filer kan hanteras. (3) Inga referenser till okända funktioner eller variabler är tillåtna. (4) En ytterligare begränsning är att applikationen inte kan hantera ADT:er. Den kan bara hantera primitiva typer. (5) Tillsist är applikationen endast skriven för ren c-kod, och klarar således inte av att hantera kod skriven i C++.</p><p>Uppgiften har lösts genom att skapa en automatgenererad lexer med Flex och Bisonrules i Visual Studio. Därefter har en limiterad parser utvecklats vars syfte är att bearbeta de lexem som lexern genererar.</p><p>Det bakomliggande syftet med arbetet är att ersätta Understand med Katana-databas. Katana har hittills använt sig av databasen i Understand, men den består av sluten källkod. Det som eftersträvas är öppen källkod, vilket Katana-databas baseras på.</p>

Thesis (Ph. D.)--University of Hong Kong, 2006. / Title proper from title frame. Also available in printed format.

published_or_final_version / Mechanical Engineering / Master / Master of Philosophy

Autonomic Computing is an approach to designing systems that are capable of self-management. Fundamental to the autonomic ideal is a software's awareness of and ability to tune parameters that affect metrics like performance and security. Traditionally, these parameters are tuned by human experts with extensive knowledge of parameter names and effects---existing software was not designed to be self-tuning. Efforts to automate the isolation and tuning of parameters have yielded encouraging results. However, the parameters are identified manually. This thesis proposes the adaptation of reverse engineering techniques for automating the recovery of software tuning parameters. Tuning parameters from several industrially relevant applications are studied for patterns of use. These patterns are used to classify the parameters into a taxonomy, and to develop a metamodel of the source code elements and relationships needed to express them. An extractor is then built to obtain instances of the relationships from source code. The relationships are represented as graphs, which are manipulated and queried for instances of tuning parameter patterns. The recovery is implemented as a tool for finding tuning parameters in applications. Experimental results show that the approach is effective at recovering documented tuning parameters, as well as other undocumented ones. The results also indicate that the tuning parameter patterns are not specific to a particular application, or application domain. / Thesis (Master, Computing) -- Queen's University, 2008-06-28 19:36:43.291

With the advent of high throughput measurement technologies, large scale gene expression data are available for analysis. Various computational methods have been introduced to analyze and predict meaningful molecular interactions from gene expression data. Such patterns can provide an understanding of the regulatory mechanisms in the cells. In the past, system identification algorithms have been extensively developed for engineering systems. These methods capture the dynamic input/output relationship of a system, provide a deterministic model of its function, and have reasonable computational requirements. In this work, two system identification methods are applied for reverse engineering of gene regulatory networks. The first method is based on an orthogonal search; it selects terms from a predefined set of gene expression profiles to best fit the expression levels of a given output gene. The second method consists of a few cascades, each of which includes a dynamic component and a static component. Multiple cascades are added in a parallel to reduce the difference of the estimated expression profiles with the actual ones. Gene regulatory networks can be constructed by defining the selected inputs as the regulators of the output. To assess the performance of the approaches, a temporal synthetic dataset is developed. Methods are then applied to this dataset as well as the Brainsim dataset, a popular simulated temporal gene expression data. Furthermore, the methods are also applied to a biological dataset in yeast Saccharomyces Cerevisiae. This dataset includes 14 cell-cycle regulated genes; their known cell cycle pathway is used as the target network structure, and the criteria sensitivity, precision, and specificity are calculated to evaluate the inferred networks through these two methods. Resulting networks are also compared with two previous studies in the literature on the same dataset. / Thesis (Master, Computing) -- Queen's University, 2010-10-18 20:47:36.458