Road traffic signs provide instructions, warning information, to regulate driver behavior. In addition, these signs provide a reliable guarantee for safe and convenient driving. The Traffic Sign Detection and Recognition (TSDR) system is one of the primary applications for Advanced Driver Assistance Systems (ADAS). TSDR has obtained a great deal of attention over the recent years. But, it is still a challenging field of image processing. In this thesis, we first created our own dataset for North American Traffic Signs, which is still being updated. We then decided to choose Histogram Orientation Gradients (HOG) and Support Vector Machines (SVMs) to build our system after comparing them with some other techniques. For better results, we tested different HOG parameters to find the best combination. After this, we developed a TSDR system using HOG, SVM and our new color information extraction algorithm. To reduce time-consumption, we used the Maximally Stable Extremal Region (MSER) to replace the HOG and SVM detection stage. In addition, we developed a new approach based on Global Positioning System (GPS) information other than image processing. At last, we tested these three systems; the results show that all of them can recognize traffic signs with a good accuracy rate. The MSER based system is faster than the one using only HOG and SVM; and, the GPS based system is even faster than the MSER based system.

Boston University. University Professors Program Senior theses. / PLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at open-help@bu.edu. Thank you. / 2031-01-02

In this paper we intend to reveal media image of former president of Iraq, Saddam Hussein as it has been constructed for six months before the war in 2003 has started. Research material came from Newsweek International news magazine. Text was decyphered using semiotic methods set in the theoretical framework based on Marxism and some of its followers. We found the representation of a "dictator" an ideological narrative serving needs of dominant ideology.

Introduction: There are no validated strategies in the teaching of ultrasound as a diagnostic tool in undergraduate medicine students. Given the role that ultrasound plays in the diagnostic capacity of any clinician is currently undeniable, a teaching method is proposed based on the demonstration of the association between the histopathology of a large vessel vasculitis and the characteristic ultrasound finding, known as the «halo sign». Methods: The teaching strategy was imparted by means of a 10-minute video presentation. Twenty-one final-year students from a single medical school participated in a concordance study and a validation test, identifying images corresponding to the halo sign in 120 different cases. The overall sensitivity, specificity and likelihood ratio of the students were also determined. Results: The overall concordance test had a kappa coefficient of 0.749 (SD: 0.11). The kappa concordance was 0.76 with dynamic images, and 0.84 with cross-sectional slices. The overall sensitivity was 89.7%, and the positive predictive value was 92.3%. The likelihood ratio achieved was 7.28. Conclusions: It has been shown that the application of this pedagogical method is useful in teaching the identification of an ultrasound sign to medical students. This study also suggests conditions that could be useful to improve between-observer agreement in both teaching scenarios and multiple observer scientific studies. / Revisión por pares

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Low-resource languages, including sign languages, are a challenge for machine translation research. Given the lack of parallel corpora, current researchers must be content with a small parallel corpus in a narrow domain for training a system. For this thesis, we obtained a small parallel corpus of English text and American Sign Language gloss from The Church of Jesus Christ of Latter-day Saints. We cleaned the corpus by loading it into an open-source translation memory tool, where we removed computer markup language and split the large chunks of text into sentences and phrases, creating a total of 14,247 sentence pairs. We randomly partitioned the corpus into three sections: 70% for a training set, 10% for a development set, and 20% for a test set. After downloading and installing the open-source Moses toolkit, we went through several iterations of training, translating, and evaluating the system. The final evaluation on unseen data yielded a state-of-the-art score for a low-resource language.

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Today, there is an increasing demand for authentication services to provide authentication to users on the internet. One example of an authentication protocol is OpenID Connect. It is used by for example Google to provide single sign-on functionality to millions of users. Since this demand is growing and more companies are implementing the protocol, there is also a need to ensure that the protocol is implemented in such a way that ensures protection from adversaries attacking the services in different ways. This paper makes an effort at providing guidelines to those aiming at implementing the protocol. It looks into several attacks that can be performed. It is found that how one chooses to implement the protocol can greatly affect security and the protocol's susceptibility to attacks. The attacks that are studied are Cross Site Request Forgery (CSRF) attacks, Mix-Up attacks, Passive web attacks, and Distributed Denial of Service attacks. It is found, among other things, that implementers of the protocol should incorporate state variables to protect against CSRF attacks and services must utilize a secure HTTPS connection to protect e.g. sensitive data. A recommendation is made for how a federation with Relying Parties and OpenID Providers can be set up to further improve security.

For a sign-changing function a(x) E C^αloc(Rn) with bounded Ω+ = {x E R^n |a(x) > O}, we study non-negative entire solutions u(x) ≥ 0 of the semilinear elliptic equation -Δu = a(x)u^q + b(x)u^p in R^n with n ≥ 3.0 < q < 1, p > q, and λ > 0. We consider two types of coefficient b(x) E C^αloc(R^n), either b(x) ≤ 0 in (R^n) or b(x) ≡ 1. In each case, we give sufficient conditions on a(x) for which all solutions must have compact support. In case Ω+ has several connected components, we also give conditions under which there exist "dead core'' solutions which vanish identically in one or more of these components. In the "logistic" case b(x) ≤ 0, we prove that there can be only one solution with given dead core components. In the case b(x) ≡ 1, the question of existence is more delicate, and we introduce a parametrized family of equations by replacing a(x) by ay = ya^+(x) - a^- (x). We show that there exists a maximal interval y E (0, f] for which there exists a stable (locally minimizing) solution. Under some hypotheses on a^- near infinity, we prove that there are two solutions for each y E (0, f). Some care must be taken to ensure the compactness of Palais-Smale sequences, and we present an example which illustrates how the Palais-Smale condition could fail for certain a(x). The analysis is based on a combination of comparison arguments, a priori estimates, and variational methods. / Thesis / Doctor of Philosophy (PhD)

Relative to other roadway segments, intersections occupy a small portion of the overall infrastructure; however, they represent the location for nearly 41 % of the annual automotive crashes in the United States. Thus, intersections are an inherently dangerous roadway element and a prime location for vehicle conflicts. Traditional safety treatments are effective at addressing certain types of intersection safety deficiencies; however, cumulative traffic data suggests these treatments do not address a large portion of the crashes that occur each year. Intersection Collision Avoidance Systems (ICAS) represent a new breed of countermeasures that focus on the types of crashes that have not been reduced with the application of traditional methods. Incursion systems, a subset of ICAS, are designed to specifically undertake crashes that are a result of the violation of a traffic control device. Intersection Collision Avoidance Systems to address Violations (ICAS-V) monitor traffic as it approaches the intersection through a network of in-vehicle sensors, infrastructure- mounted sensors, and communication equipment. A threat-assessment algorithm performs computations to predict the driver's intended intersection maneuver, based on these sensor inputs. If the system predicts a violation, it delivers a timely warning to the driver with the aim of compelling the driver to stop. This warning helps the driver to avoid a potential crash with adjacent traffic. The following dissertation describes an investigation of intersection approach behavior aimed at developing a threat assessment algorithm for stop-sign intersections. Data were collected at live intersections to gather infrastructure-based naturalistic vehicle approach trajectories. This data were compiled and analyzed with the goal of understanding how drivers approach intersections under various speeds and environmental conditions. Six stop-controlled intersection approaches across five intersections in the New River Valley, Virginia area were selected as the test sites. Data were collected from each site for at least two months, resulting in over sixteen total months of data. A series of statistical analysis techniques were applied to construct a set of threat assessment algorithms for stop-controlled intersections. These analyses identified characteristics of intersection approaches that suggested driver intent at the stop sign. Models were constructed to predict driver stopping intent based on measured vehicle kinematics. These models were thoroughly tested using simulation and evaluated with signal detection theory. The overall output of this work is a set of algorithms that may be integrated into an ICAS-V for on-road testing. / Ph. D.