Αντικείμενο αυτής της διπλωματικής εργασίας είναι η εύρεση της θέσης ενός κινούμενου ρομπότ. Για το σκοπό αυτό, χρησιμοποιείται ένα στερεοσκοπικό σύστημα όμοιων καμερών (web-cameras) υπό γωνία μεταξύ τους. Κάθε μια εκ των 2 καμερών λαμβάνει μια ακολουθία φωτογραφιών σε κοινό χρόνο. Η εύρεση της θέσης γίνεται με τη μέθοδο της τριγωνοποίησης (triangulation), η οποία δίνει τις συντεταγμένες του κινούμενου αντικειμένου μέσω ομοίων τριγώνων που σχηματίζονται από τα 2 επίπεδα των φωτογραφιών (image planes), την ευθεία που ενώνει τα κέντρα των 2 καμερών καθώς και από το ίδιο το κινούμενο αντικείμενο. Ωστόσο, η γεωμετρική αυτή μέθοδος εφαρμόζεται σε φωτογραφίες που έχουν ληφθεί με παράλληλες κάμερες. Για τον λόγο αυτό, εφαρμόζεται η μέθοδος της διόρθωσης εικόνας (image rectification) η οποία μετασχηματίζει τις εικόνες έτσι ώστε να είναι σα να έχουν ληφθεί από παράλληλες κάμερες. Στη συνέχεια εντοπίζεται το κινούμενο αντικείμενο με μορφολογική επεξεργασία εικόνας, υπολογίζεται το κέντρο βάρους του και γίνεται η τριγωνοποίηση γεωμετρικά. Στην προαναφερθείσα διαδικασία, θεωρούνται γνωστά τα εσωτερικά στοιχεία των καμερών και η μεταξύ τους απόσταση. Επιπλέον, θεωρείται ότι όλος ο όγκος του ρομπότ αναπαρίσταται απο ένα σημείο P με συντεταγμένες (X,Y,Z) ως προς σύστημα συντεταγμένων με αρχή το κέντρο προβολής της αριστερής κάμερας. / The objective of this thesis is the position estimation of a moving robot. For this purpose, a stereoscopic system of two identical, non-parallel cameras has been used (web-cameras). Each of the two cameras takes a photo synchronized sequence. The position of the robot has been estimated with the method of triangulation, which computes the coordinates of the moving object via similar triangles formed by the two image planes, the straight line joining the centres of the cameras and by the moving object. However, triangulation is applicable to images acquired by parallel cameras. For this reason, the images have been rectified. Image rectification is a transformation process that is used to project two-or-more images onto a common image. Then, the moving object is detected with morphological image processing techniques, its centroid is calculated and finally triangulation has been applied. The intrinsic parameters of the cameras and the distance between them are known. Furthermore, we consider that the entire volume of the robot is represented by a point P with coordinates (X, Y, Z) with respect to the left camera coordinate system.

The thesis research examined localized socio-environmental perceptions related to amplified fresh water requirements for hydraulic fracturing and subsequent flowback disposal activities. These requirements are associated with increasing shale gas development in the Duvernay formation, located within the Kaybob region of West-central Alberta, Canada. Fresh water refers to surface and groundwater with a total dissolved solids concentration of less than 4,000 ppm. Through recourse to a mixed methods approach, combined with triangulation as a method of further validation, the research demonstrates that there exists a public sensitivity related to fresh water use in the Kaybob region. This sensitivity arises from increasing development activities in the Duvernay shale gas formation. The thesis presents conclusions and recommendations whereby industry may address stakeholder concerns, and provides advice for future research.

The methods presented in this study are aimed at the identification of subpopulations (clones) of genetically similar cells within tissue samples through measurement of loci-specific Fluorescence in-situ hybridization (FISH) spot signals for each nucleus and analyzing cell spatial distributions by way of Voronoi tessellation and Delaunay triangulation to robustly define cell neighbourhoods. The motivation for the system is to examine lung cancer patient for subpopulations of Non-Small Cell Lung Cancer (NSCLC) cells with biologically meaningful gene copy-number profiles: patterns of genetic alterations statistically associated with resistance to cis-platinum/vinorelbine doublet chemotherapy treatment. Current technologies for gene-copy number profiling rely on large amount of cellular material, which is not always available and suffers from limited sensitivity to only the most dominant clone in often heterogeneous samples. Thus, through the use of FISH, the detection of gene copy-numbers is possible in unprocessed tissues, allowing identification of specific tumour clones with biologically relevant patterns of genetic aberrations. The tissue-wide characterization of multiplexed loci-specific FISH signals, described herein, is achieved through a fully automated, multicolour fluorescence imaging microscope and object segmentation algorithms to identify cell nuclei and FISH spots within. Related tumour clones are identified through analysis of robustly defined cell neighbourhoods and cell-to-cell connections for regions of cells with homogenous and highly interconnected FISH spot signal characteristics. This study presents experiments which demonstrate the system’s ability to accurately quantify FISH spot signals in various tumour tissues and in up to 5 colours simultaneously or more through multiple rounds of FISH staining. Furthermore, the system’s FISH-based cell classification performance is evaluated at a sensitivity of 84% and specificity 81% and clonal identification algorithm results are determined to be comparable to clone delineation by a human-observer. Additionally, guidelines and procedures to perform anticipated, routine analysis experiments are established.

HIV/AIDS is widely spread and ranks as the sixth biggest killer all over the world. Moreover, due to the rapid replication rate and the lack of proofreading mechanism of HIV virus, drug resistance is commonly found and is one of the reasons causing the failure of the treatment. Even though the drug resistance tests are provided to the patients and help choose more efficient drugs, such experiments may take up to two weeks to finish and are expensive. Because of the fast development of the computer, drug resistance prediction using machine learning is feasible. In order to accurately predict the HIV drug resistance, two main tasks need to be solved: how to encode the protein structure, extracting the more useful information and feeding it into the machine learning tools; and which kinds of machine learning tools to choose. In our research, we first proposed a new protein encoding algorithm, which could convert various sizes of proteins into a fixed size vector. This algorithm enables feeding the protein structure information to most state of the art machine learning algorithms. In the next step, we also proposed a new classification algorithm based on sparse representation. Following that, mean shift and quantile regression were included to help extract the feature information from the data. Our results show that encoding protein structure using our newly proposed method is very efficient, and has consistently higher accuracy regardless of type of machine learning tools. Furthermore, our new classification algorithm based on sparse representation is the first application of sparse representation performed on biological data, and the result is comparable to other state of the art classification algorithms, for example ANN, SVM and multiple regression. Following that, the mean shift and quantile regression provided us with the potentially most important drug resistant mutants, and such results might help biologists/chemists to determine which mutants are the most representative candidates for further research.

Data-dependent triangulation (DDT) based mesh-generation schemes for image representation are studied. A flexible mesh-generation framework and a highly effective mesh-generation method that employs this framework are proposed. The proposed framework is derived from frameworks proposed by Rippa and Garland and Heckbert by making a number of key modifications to facilitate the development of much more effective mesh-generation methods. As the proposed framework has several free parameters, the effects of different choices of these parameters on mesh quality (both in terms of squared error and subjectively) are studied, leading to the recommendation of a particular set of choices for these parameters. A new mesh-generation method is then introduced that employs the proposed framework with these best parameter choices. Experimental results show our proposed mesh-generation method outperforms several competing approaches, namely, the DDT-based incremental scheme proposed by Garland and Heckbert, the COMPRESS scheme proposed by Rippa, and the adaptive thinning scheme proposed by Demaret and Iske. More specifically, in terms of PSNR, our proposed method was found to outperform these three schemes by median margins of 4.1 dB, 10.76 dB, and 0.83 dB, respectively. The subjective qualities of reconstructed images were also found to be correspondingly better. In terms of computational cost, our proposed method was found to be comparable to the schemes proposed by Garland and Heckbert and Rippa. Moreover, our proposed method requires only about 5 to 10% of the time of the scheme proposed by Demaret and Iske. In terms of memory cost, our proposed method was shown to require essentially same amount of memory as the schemes proposed by Garland and Heckbert and Rippa, and orders of magnitude (33 to 800 times) less memory than the scheme proposed by Demaret and Iske. / Graduate

This thesis presents a 3D reconstruction approach to the detection of static obstacles from a single rear view parking camera. Corner features are tracked to estimate the vehicle’s motion and to perform multiview triangulation in order to reconstruct the scene. We model the camera motion as planar motion and use the knowledge of the camera pose to efficiently solve motion parameters. Based on the observed motion, we selected snapshots from which the scene is reconstructed. These snapshots guarantee a sufficient baseline between the images and result in more robust scene modeling. Multiview triangulation of a feature is performed only if the feature obeys the epipolar constraint. Triangulated features are semantically labelled according to their 3D location. Obstacle features are spatially clustered to reduce false detections. Finally, the distance to the nearest obstacle cluster is reported to the driver.

This dissertation was a mixed methods triangulation design combining quantitative and qualitative components. The purpose of this study was twofold. First, it examined the association between the frequency and quality of students’ online interactions with instructors and the quality of student-instructor relationship. Second, this study explored the meanings of student-instructor interactions mediated by online tools. Quantitative data were collected via an online survey from 320 undergraduate students enrolled at a public research university. Qualitative data sources were in-depth interviews with six undergraduate students and six professors, observations of student-instructor interactions on Facebook, and artifacts of student-instructor interaction via email. Hierarchical regression analysis showed that approximately one third of the variance in student-instructor connectedness was explained by the frequency of and satisfaction with face-to-face, email, Blackboard, and Facebook; the grade obtained in the class; and demographic variables. Significant predictors of connectedness were grade, frequency of face-to-face student interest-driven communication, satisfaction with the face-to-face interactions, and satisfaction with the email communication. The qualitative findings revealed that instructors held expectations of formal communication for email interactions, while students had expectations for response from instructors within one-two business days. The email practices identified for instructors included responding to student email within two days; compensating for limited face-to-face time; engaging students in communication about the class content; and dealing with student disengagement. Students adopted two main practices related to email: avoiding “emergency” emails to contact instructors, and using email to avoid face-to-face contact in some situations. For Facebook interactions, instructors expected that students initiate connections, while students expected that instructors signal their availability for connection with students. Instructors’ Facebook practices pointed out different approaches for accepting student friend requests; and performing interactions. Students’ practices on Facebook highlighted two patterns: initiating connections with instructors during the semester versus at the beginning of the semester. In addition, preserving connections beyond the boundaries of a class was a practice common to students and instructors.

The methods presented in this study are aimed at the identification of subpopulations (clones) of genetically similar cells within tissue samples through measurement of loci-specific Fluorescence in-situ hybridization (FISH) spot signals for each nucleus and analyzing cell spatial distributions by way of Voronoi tessellation and Delaunay triangulation to robustly define cell neighbourhoods. The motivation for the system is to examine lung cancer patient for subpopulations of Non-Small Cell Lung Cancer (NSCLC) cells with biologically meaningful gene copy-number profiles: patterns of genetic alterations statistically associated with resistance to cis-platinum/vinorelbine doublet chemotherapy treatment. Current technologies for gene-copy number profiling rely on large amount of cellular material, which is not always available and suffers from limited sensitivity to only the most dominant clone in often heterogeneous samples. Thus, through the use of FISH, the detection of gene copy-numbers is possible in unprocessed tissues, allowing identification of specific tumour clones with biologically relevant patterns of genetic aberrations. The tissue-wide characterization of multiplexed loci-specific FISH signals, described herein, is achieved through a fully automated, multicolour fluorescence imaging microscope and object segmentation algorithms to identify cell nuclei and FISH spots within. Related tumour clones are identified through analysis of robustly defined cell neighbourhoods and cell-to-cell connections for regions of cells with homogenous and highly interconnected FISH spot signal characteristics. This study presents experiments which demonstrate the system’s ability to accurately quantify FISH spot signals in various tumour tissues and in up to 5 colours simultaneously or more through multiple rounds of FISH staining. Furthermore, the system’s FISH-based cell classification performance is evaluated at a sensitivity of 84% and specificity 81% and clonal identification algorithm results are determined to be comparable to clone delineation by a human-observer. Additionally, guidelines and procedures to perform anticipated, routine analysis experiments are established.

Thesis (Ph. D.)--Ohio State University, 2008. / Title from first page of PDF file. Includes bibliographical references (p. 113-119).

Μια γρήγορη επίλυση του Delaunay Τριγωνισμός (DT) πρόβληματος αποτελεί ένα από τα βασικά συστατικά σε πολλές θεωριτικές και πρακτικές εφαρμογές. Οι υπάρχουσες μονάδες επεξεργασίας γραφικών (GPU), με βάση τις εφαρμογές των αλγορίθμων DT πάσχουν από δύο σοβαρά μειονεκτήματα. Το πρώτο σχετίζεται με την εξάρτηση του αλγορίθμου καθοδήγηση της GPU από την CPU για τους υπολογισμούς. Το δεύτερο πιο σοβαρό μειονέκτημα είναι η εξάρτησή τους από τη διανομή του σημειοσύνολου εισόδου. Οι περισσότεροι αλγορίθμοι για GPU έχουν καλή απόδοση μόνο με ομοιόμορφες κατανομές σημειοσύνολον. Προτείνουμε ένα καινούριο αλγόριθμο που δεν πάσχουν από τα παραπάνω προβλήματα. / A Fast solver of Delaunay Triangulation (DT) problem constitutes one of the basic ingredients in many practical and sientific applications. Existing Graphics Processing Units (GPU) based implementations of DT algorithms suffer from two serious drawbacks. The first is related to the dependency of the CPU guidance algorithm on GPU calculations. Albeit the modern GPUs have high computational throughput, if the feedback from CPU is necessary for the algorithmic evolution, the overhead caused by CPU-GPU communication can seriously degrade the performance. The second most serious drawback is their dependency on the distribution of the given point-set. Most of the GPU-based implementations can optimally run only on uniformly distributed point-sets, however, in many practical applications this is not the case.