The situation of the "Urban Leftover" caused by the errection of linear building types -the so called "Zeile"- after World War II is obvious in over 100 locations in the former West Berlin, Germany. The radical modern urban concepts of erasing the historic structure of the city -in which context the Zeile was erected were never completly realized. This mixed structure of the traditional Block and Zeile caused the open corner condition and have become an unused urban leftover today. This thesis project studies the phenomenon of the open corner and tries to offer an answer to this urban question. / Master of Architecture

M.S.

Thesis (M.S.)--Boston University / It is the purpose of this study to examine, describe, and compare the functions of two corner-group workers a female social worker working with a girls' corner-group and a male social worker working with a boys' corner-group. This topic is related to the research goals of the Special Youth Program, the agency from which the data have been drawn and within whose frame-work the research design has been fashioned.

Pen-based interfaces utilize sketch recognition so users can create and interact with complex, graphical systems via drawn input. In order for people to freely draw within these systems, users' drawing styles should not be constrained. The low-level techniques involved with sketch recognition must then be perfected, because poor low-level accuracy can impair a user's interaction experience. Corner finding, also known as stroke segmentation, is one of the first steps to free-form sketch recognition. Corner finding breaks a drawn stroke into a set of primitive symbols such as lines, arcs, and circles, so that the original stoke data can be transformed into a more machine-friendly format. By working with sketched primitives, drawn objects can then be described in a visual language, noting what primitive shapes have been drawn and the shapes? geometric relationships to each other. We present three new corner finding techniques that improve segmentation accuracy. Our first technique, MergeCF, is a multi-primitive segmenter that splits drawn strokes into primitive lines and arcs. MergeCF eliminates extraneous primitives by merging them with their neighboring segments. Our second technique, ShortStraw, works with polyline-only data. Polyline segments are important since many domains use simple polyline symbols formed with squares, triangles, and arrows. Our ShortStraw algorithm is simple to implement, yet more powerful than previous polyline work in the corner finding literature. Lastly, we demonstrate how a combination technique can be used to pull the best corner finding results from multiple segmentation algorithms. This combination segmenter utilizes the best corners found from other segmentation techniques, eliminating many false negatives (missed primitive segmentations) from the final, low-level results. We will present the implementation and results from our new segmentation techniques, showing how they perform better than related work in the corner finding field. We will also discuss limitations of each technique, how we have sought to overcome those limitations, and where we believe the sketch recognition subfield of corner finding is headed.

Localised optimal initial perturbations are studied to gain an understanding of the global stability properties of streamwise corner-flow. A self-similar and a modified base-flow are considered. The latter mimics a characteristic deviation from the self-similar solution, commonly observed in experiment. Poweriterations in terms of subsequent direct and adjoint linearised Navier-Stokes solution sweeps are employed to converge optimal solutions for two optimisation times. The optimal response manifests as a wave packet that initially gains energy through the Orr mechanism and continues growing exponentially thereafter. The study at hand represents the first global stability analysis of streamwise corner-flow and confirms key observations made in theoretical and/or experimental work on the subject. Namely, the presence of an inviscid instability mechanism in the near-corner region and a destabilising effect of the characteristic mean-flow deformation found in experiment. / <p>QC 20130604</p>

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The mechanism of three important aldol reactions and a biomimetic transamination is investigated using a combination of experimental kinetic isotope effects (KIEs), standard theoretical calculations and dynamics trajectory simulations. This powerful mechanistic probe is found to be invaluable in understanding intricate details of the mechanism of these reactions. The successful application of variational transition state theory including multidimensional tunneling to theoretically predict isotope effects, described in this dissertation, represents a significant advance in our research methodology. The role of dynamic effects in aldol reactions is examined in great detail. The study of the proline catalyzed aldol reaction has revealed an intriguing new dynamic effect - quasiclassical corner cutting - where reactive trajectories cut the corner between reactant and product valleys and avoid the saddle point. This phenomenon affects the KIEs observed in this reaction in a way that is not predictable by transition state theory. The study of the Roush allylboration of aldehydes presents an example where recrossing affects experimental observations. The comparative study of the allylboration of two electronically different aldehydes, which are predicted to have different amounts of recrossing, suggests a complex interplay of tunneling and recrossing affecting the observed KIEs. The Mukaiyama aldol reaction has been investigated and the results unequivocally rule out the key carbon-carbon bond forming step as rate-limiting. This raises several interesting mechanistic scenarios - an electron transfer mechanism with two different rate-limiting steps for the two components, emerges as the most probable possibility. Finally, labeling studies of the base catalyzed 1,3- proton transfer reaction of fluorinated imines point to a stepwise process involving an azomethine ylide intermediate. It is found that dynamic effects play a role in determining the product ratio in this reaction.

As the popularity of the digital Web-cam¡Athese devices are more and more cheaper and powerful. We can apply computer vision techniques with camera and projector to build a more convenient presentation system. In presentation, sometimes due to the position of projector, the images appear the perspective distortion (keystone distortion). The user should manually adjust the position of projector or use the keystone corrections of the projector. But when the distortion is not trapezium, the built-in keystone corrections are not suitable in this situation. We present a computer-vision based method that uses a Web-cam to calibrate the keystone distortion. The Web-cam takes the images that the projector projected on the wall. If the Web-cam observes keystone distortions of the projected images, we use a geometric transform that pre-warps the images in the projector frame, such that these images appears rectangle with known aspect ratio after being projected on the wall. Besides, we implement the virtual buttons that allow users to interact with the computer. The virtual buttons means that when the camera detect the laser point is on the virtual buttons, computer triggers the event as the virtual button being pushed. This paper uses point-matching pairs to obtain the homography between camera image frame and source image frame. The homography, that is the fundamental of calibrating perspective distortions also help us to search the position of the laser point.

In this thesis, we study the array theory and the array synthesis methods to design a sector antenna composed of a broadside collinear array and a corner reflector that is suitable for base stations. The antenna produces a sector beam in the horizontal plane to reduce the co-channel interference. In the elevation plane the antenna produces a narrower beam in order to achieve a higher gain. A uniform array is known to produce a high side lobe level which will cause serious interference. Therefore, Dolph-Tchebyscheff linear array method and Taylor line source method are utilized for the antenna design. We also design the structure of corner reflector which is combined with an array to form the sector antenna. We also study the switched-beam system, design and fabricate a 4¡Ñ1 microstrip patch antenna array to simulate the operation of the system and measure its performance.

Image features play important roles in a wide range of computer vision applications, such as image registration, 3D reconstruction, object detection and video understanding. These image features include edges, contours, corners, regions, lines, curves, interest points, etc. However, the research is fragmented in these areas, especially when it comes to line and curve detection. In this thesis, we aim to discover, integrate, evaluate and summarize past research as well as our contributions in the area of image features. This thesis provides a comprehensive framework of concept, evaluation, implementation, and applications for image features. Firstly, this thesis proposes a novel concept of interest curves. Interest curves is a concept derived and extended from interest points. Interest curves are significant lines and arcs in an image that are repeatable under various image transformations. Interest curves bring clear guidelines and structures for future curve and line detection algorithms and related applications. Secondly, this thesis presents an evaluation framework for detecting and describing interest curves. The evaluation framework provides a new paradigm for comparing the performance of state-of-the-art line and curve detectors under image perturbations and transformations. Thirdly, this thesis proposes an interest curve detector (Distinctive Curves, DICU), which unifies the detection of edges, corners, lines and curves. DICU represents our state-of-the-art contribution in the areas concerning the detection of edges, corners, curves and lines. Our research efforts cover the most important attributes required by these features with respect to robustness and efficiency. Interest curves preserve richer geometric information than interest points. This advantage gives new ways of solving computer vision problems. We propose a simple description method for curve matching applications. We have found that our proposed interest curve descriptor outperforms all state-of-the-art interest point descriptors (SIFT, SURF, BRISK, ORB, FREAK). Furthermore, in our research we design a novel object detection algorithm that only utilizes DICU geometries without using local feature appearance. We organize image objects as curve chains and to detect an object, we search this curve chain in the target image using dynamic programming. The curve chain matching is scale and rotation-invariant as well as robust to image deformations. These properties have given us the possibility of resolving the rotation-variance problem in object detection applications. In our face detection experiments, the curve chain matching method proves to be scale and rotation-invariant and very computational efficient. / Bilddetaljer har en viktig roll i ett stort antal applikationer för datorseende, t.ex., bildregistrering, 3D-rekonstruktion, objektdetektering och videoförståelse. Dessa bilddetaljer inkluderar kanter, konturer, hörn, regioner, linjer, kurvor, intressepunkter, etc. Forskningen inom dessa områden är splittrad, särskilt för detektering av linjer och kurvor. I denna avhandling, strävar vi efter att hitta, integrera, utvärdera och sammanfatta tidigare forskning tillsammans med vår egen forskning inom området för bildegenskaper. Denna avhandling presenterar ett ramverk för begrepp, utvärdering, utförande och applikationer för bilddetaljer. För det första föreslår denna avhandling ett nytt koncept för intressekurvor. Intressekurvor är ett begrepp som härrör från intressepunkter och det är viktiga linjer och bågar i bilden som är repeterbara oberoende av olika bildtransformationer. Intressekurvor ger en tydlig vägledning och struktur för framtida algoritmer och relaterade tillämpningar för kurv- och linjedetektering. För det andra, presenterar denna avhandling en utvärderingsram för detektorer och beskrivningar av intressekurvor. Utvärderingsramverket utgör en ny paradigm för att jämföra resultatet för de bästa möjliga teknikerna för linje- och kurvdetektorer vid bildstörningar och bildtransformationer. För det tredje presenterar denna avhandling en detektor för intressekurvor (Distinctive curves, DICU), som förenar detektering av kanter, hörn, linjer och kurvor. DICU representerar vårt främsta bidrag inom området detektering av kanter, hörn, kurvor och linjer. Våra forskningsinsatser täcker de viktigaste attribut som krävs av dessa funktioner med avseende på robusthet och effektivitet. Intressekurvor innehåller en rikare geometrisk information än intressepunkter. Denna fördel öppnar för nya sätt att lösa problem för datorseende. Vi föreslår en enkel beskrivningsmetod för kurvmatchningsapplikationer och den föreslagna deskriptorn för intressekurvor överträffar de bästa tillgängliga deskriptorerna för intressepunkter (SIFT, SURF, BRISK, ORB, och FREAK). Dessutom utformar vi en ny objektdetekteringsalgoritm som bara använder geometri för DICU utan att använda det lokala utseendet. Vi organiserar bildobjekt som kurvkedjor och för att upptäcka ett objekt behöver vi endast söka efter denna kurvkedja i målbilden med hjälp av dynamisk programmering. Kurvkedjematchningen är oberoende av skala och rotationer samt robust vid bilddeformationer. Dessa egenskaper ger möjlighet att lösa problemet med rotationsberoende inom objektdetektering. Vårt ansiktsigenkänningsexperiment visar att kurvkedjematchning är oberoende av skala och rotationer och att den är mycket beräkningseffektiv. / INTRO – INteractive RObotics research network