Fast acoustic tomography of costal, tidally-driven temperature and current fields

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Ocean Engineering, 1998.Includes bibliographical references (leaves 160-169).by Pierre Elisseeff.Ph.D

Explanation Trees for Causal Bayesian Networks

Bayesian networks can be used to extract explanations about the observed state of a subset of variables. In this paper, we ex- plicate the desiderata of an explanation and confront them with the concept of expla- nation proposed by existing methods. The necessity of taking into account causal ap- proaches when a causal graph is available is discussed. We then introduce causal expla- nation trees, based on the construction of ex- planation trees using the measure of causal information flow (Ay and Polani, 2006). This approach is compared to several other meth- ods on known networks

Kernel Dependency Estimation

We consider the learning problem of finding a dependency between a general class of objects and another, possibly different, general class of objects. The objects can be for example: vectors, images, strings, trees or graphs. Such a task is made possible by employing similarity measures in both input and output spaces using kernel functions, thus embedding the objects into vector spaces. Output kernels also make it possible to encode prior information and/or invariances in the loss function in an elegant way. We experimentally validate our approach on several tasks: mapping strings to strings, pattern recognition, and reconstruction from partial images

Transdermal photopolymerization of hydrogels for tissue engineering

Thesis (Ph.D.)--Harvard--Massachusetts Institute of Technology Division of Health Sciences and Technology, 1999.Includes bibliographical references.by Jennifer Hartt Elisseeff.Ph.D

Maintaining dimensions and mechanical properties of ionically crosslinked alginate hydrogel scaffolds in vitro

Ionically crosslinked alginate hydrogels are attractive scaffolds because of their biocompatibility and mild gelation reaction that allows for gentle cell incorporation. However, the instability of ionically crosslinked hydrogels in an aqueous environment is a challenge that limits their application. This report presents a novel method to control the dimensions and mechanical properties of ionically crosslinked hydrogels via control of the ionic concentration of the medium. Homogeneous calcium-alginate gels were incubated in physiological saline baths adjusted to specific calcium ion concentrations. Swelling and shrinking occurred at low and high ionic concentrations of the medium, respectively, while an “optimal” intermediate calcium ion concentration of the medium was found to maintain original size and shape of the hydrogel. This optimal calcium ion concentration was found to be a function of crosslinking density and polymer concentration of the hydrogel and chemical composition of the alginate. The effects of optimal and high calcium ion concentrations of the medium on swelling behavior, calcium content, dry weight, and mechanical properties of the immersed hydrogels were investigated. It was found that the resulting hydrogel composition and mechanical properties depended on not only the calcium concentration of the medium, but also the crosslinking density and polymer concentration of the gel. In an 8-week experiment, controlled dimensions and mechanical properties of alginate gels in an aqueous environment were demonstrated. This new technique significantly enhances the potential of alginate hydrogels for tissue engineering and other biomedical applications. © 2007 Wiley Periodicals, Inc. J Biomed Mater Res, 2008Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/58038/1/31375_ftp.pd

Risque garanti pour les modèles de discrimination multi-classes

Colloque avec actes et comité de lecture.Nous étudions les performances en généralisation des systèmes de discrimination à catégories multiples. Nous établissons deux bornes sur ces performances, en fonction de deux mesures de capacité de la famille de fonctions calculées : la fonction de croissance et les nombres de couverture. Ces bornes sont évaluées sur un modèle de combinaison de classifieurs estimant les probabilités a posteriori des classes. Ceci permet de comparer l'adéquation des deux mesures de capacité

Machine Learning approaches to protein ranking: discriminative, semi-supervised, scalable algorithms

A key tool in protein function discovery is the ability to rank databases of proteins given a query amino acid sequence. The most successful method so far is a web-based tool called PSI-BLAST which uses heuristic alignment of a profile built using the large unlabeled database. It has been shown that such use of global information via an unlabeled data improves over a local measure derived from a basic pairwise alignment such as performed by PSI-BLAST's predecessor, BLAST. In this article we look at ways of leveraging techniques from the field of machine learning for the problem of ranking. We show how clustering and semi-supervised learning techniques, which aim to capture global structure in data, can significantly improve over PSI-BLAST

Measurements, Medications, and Symptoms Logging Using a Virtual Assistant

This disclosure describes virtual assistant based techniques that, with user permission, log medications, symptoms, and measures of health. The techniques offer an easy mechanism for users to document their symptoms, vital signs, health data, etc. For example, a user simply speaks out their symptoms to their virtual assistant to create a log. Vital signs are automatically logged by the virtual assistant (with user permission) using, e.g., sensors and mobile/wearable devices. The techniques enable users to develop a personal health journal that frictionlessly logs activity, sleep, nutrition, heart rate, etc. When enabled, the virtual assistant reminds users of medications to be taken and also prevents accidental doubling of dosages. The automatically generated and curated personal health journal enables users to focus on a healthier lifestyle, provides valuable clues to pathologies, enables querying of health history, helps understand trends, and helps caregivers and doctors better deliver healthcare. The techniques are implemented with specific user permissions and in compliance with regulations related to health information