Support Vector Machines in Analysis of Top Quark Production

Multivariate data analysis techniques have the potential to improve physics analyses in many ways. The common classification problem of signal/background discrimination is one example. The Support Vector Machine learning algorithm is a relatively new way to solve pattern recognition problems and has several advantages over methods such as neural networks. The SVM approach is described and compared to a conventional analysis for the case of identifying top quark signal events in the dilepton decay channel amidst a large number of background events.Comment: 8 pages, 8 figures, to be published in the proceedings of the "Advanced Statistical Techniques in Particle Physics" conference in Durham, UK (March, 2002

A Note on Interactions of (Non-Commutative) Instantons Via AdS/CFT

We consider the interaction between instantons and anti-instantons in four-dimensional N=4 super-Yang-Mills theory at large N and large 't Hooft coupling as described by D-instantons via AdS/CFT duality. We give an estimate of the strength of the interaction in various regimes. We discuss also the case of Non-Commutative super Yang-Mills theory where the interaction between instantons and anti-instantons can be used as a way to probe the locality properties of the theory in the supergravity picture, without explicit reference to the definition of local operators.Comment: harvmac, 13 p

Therapie bei Progression und Rezidiv des Ovarialkarzinoms

Secondary surgery after failure of primary treatment is a promising and reasonable option only for patients with a relapse-free interval of at least 6-12 months who should have ideally achieved a tumor-free status after primary therapy. As after primary surgery, size of residual tumor is the most significant predictor of survival after secondary surgery. Even in the case of multiple tumor sites, complete removal of the tumor can be achieved in nearly 30% of the patients. Treatment results are much better in specialized oncology centers with optimal interdisciplinary cooperation compared with smaller institutions. Chemotherapy can be used both for consolidation after successful secondary surgery and for palliation in patients with inoperable recurrent disease. Since paclitaxel has been integrated into first-line chemotherapy, there is no defined standard for second-line chemotherapy. Several cytotoxic agents have shown moderate activity in this setting, including treosulfan, epirubicin, and newer agents such as topotecan, gemcitabine, vinorelbine, and PEG(polyethylene glycol)-liposomal doxorubicin. Thus, the German Arbeitsgemeinschaft Gynakologische Onkologie (AGO) has initiated several randomized studies in patients with recurrent ovarian cancer in order to define new standards for second-line chemotherapy

Analyzing First-Person Stories Based on Socializing, Eating and Sedentary Patterns

First-person stories can be analyzed by means of egocentric pictures acquired throughout the whole active day with wearable cameras. This manuscript presents an egocentric dataset with more than 45,000 pictures from four people in different environments such as working or studying. All the images were manually labeled to identify three patterns of interest regarding people's lifestyle: socializing, eating and sedentary. Additionally, two different approaches are proposed to classify egocentric images into one of the 12 target categories defined to characterize these three patterns. The approaches are based on machine learning and deep learning techniques, including traditional classifiers and state-of-art convolutional neural networks. The experimental results obtained when applying these methods to the egocentric dataset demonstrated their adequacy for the problem at hand.Comment: Accepted at First International Workshop on Social Signal Processing and Beyond, 19th International Conference on Image Analysis and Processing (ICIAP), September 201

Aharonov-Bohm Effect and Disclinations in an Elastic Medium

In this work we investigate quasiparticles in the background of defects in solids using the geometric theory of defects. We use the parallel transport matrix to study the Aharonov-Bohm effect in this background. For quasiparticles moving in this effective medium we demonstrate an effect similar to the gravitational Aharonov- Bohm effect. We analyze this effect in an elastic medium with one and $N$ defects.Comment: 6 pages, Revtex

Using topic information to improve non-exact keyword-based search for mobile applications

Considering the wide offer of mobile applications available nowadays, effective search engines are imperative for an user to find applications that provide a specific desired functionality. Retrieval approaches that leverage topic similarity between queries and applications have shown promising results in previous studies. However, the search engines used by most app stores are based on keyword-matching and boosting. In this paper, we explore means to include topic information in such approaches, in order to improve their ability to retrieve relevant applications for non-exact queries, without impairing their computational performance. More specifically, we create topic models specialized on application descriptions and explore how the most relevant terms for each topic covered by an application can be used to complement the information provided by its description. Our experiments show that, although these topic keywords are not able to provide all the information of the topic model, they provide a sufficiently informative summary of the top- ics covered by the descriptions, leading to improved performance.info:eu-repo/semantics/publishedVersio

Anomalous Neutrino Reactions at HERA

We study the sensitivity of HERA to new physics using the helicity suppressed reaction $e_R p \rightarrow \nu X$, where the final neutrino can be a standard model one or a heavy neutrino. The approach is model independent and is based on an effective lagrangian parametrization. It is shown that HERA will put significant bounds on the scale of new physics, though, in general, these are more modest than previously thought. If deviations from the standard model are observed in the above processes, future colliders such as the SSC and LHC will be able to directly probe the physics responsible for these discrepancies}Comment: 11 Pages + 2 figures is TOPDRAWER (included at the end or available by mail). Report UCRHEP-T113 (requires the macropackage PHYZZX). A line in the TeX file requesting an input file has been removed, it caused problem

Finding rare objects and building pure samples: Probabilistic quasar classification from low resolution Gaia spectra

We develop and demonstrate a probabilistic method for classifying rare objects in surveys with the particular goal of building very pure samples. It works by modifying the output probabilities from a classifier so as to accommodate our expectation (priors) concerning the relative frequencies of different classes of objects. We demonstrate our method using the Discrete Source Classifier, a supervised classifier currently based on Support Vector Machines, which we are developing in preparation for the Gaia data analysis. DSC classifies objects using their very low resolution optical spectra. We look in detail at the problem of quasar classification, because identification of a pure quasar sample is necessary to define the Gaia astrometric reference frame. By varying a posterior probability threshold in DSC we can trade off sample completeness and contamination. We show, using our simulated data, that it is possible to achieve a pure sample of quasars (upper limit on contamination of 1 in 40,000) with a completeness of 65% at magnitudes of G=18.5, and 50% at G=20.0, even when quasars have a frequency of only 1 in every 2000 objects. The star sample completeness is simultaneously 99% with a contamination of 0.7%. Including parallax and proper motion in the classifier barely changes the results. We further show that not accounting for class priors in the target population leads to serious misclassifications and poor predictions for sample completeness and contamination. (Truncated)Comment: MNRAS accepte

How Big Can Anomalous W Couplings Be?

Conventional wisdom has it that anomalous gauge-boson self-couplings can be at most a percent or so in size. We test this wisdom by computing these couplings at one loop in a generic renormalizable model of new physics. (For technical reasons we consider the CP-violating couplings here, but our results apply more generally.) By surveying the parameter space we find that the largest couplings (several percent) are obtained when the new particles are at the weak scale. For heavy new physics we compare our findings with expectations based on an effective-lagrangian analysis. We find general patterns of induced couplings which robustly reflect the nature of the underlying physics. We build representative models for which the new physics could be first detected in the anomalous gauge couplings.Comment: 40 pages, 11 figures, (dvi file and figures combined into a uuencoded compressed file), (We correct an error in eq. 39 and its associated figure (9). No changes at all to the text.), McGill-93/40, UQAM-PHE-93/03, NEIPH-93-00