Feature Extraction in Densely Sensed Environments: Extensions to Multiple Broadcast Domains

The vision of the Internet of Things (IoT) includes large and dense deployment of interconnected smart sensing and monitoring devices. This vast deployment necessitates collection and processing of large volume of measurement data. However, collecting all the measured data from individual devices on such a scale may be impractical and time consuming. Moreover, processing these measurements requires complex algorithms to extract useful information. Thus, it becomes imperative to devise distributed information processing mechanisms that identify application-specific features in a timely manner and with a low overhead. In this article, we present a feature extraction mechanism for dense networks that takes advantage of dominance-based medium access control (MAC) protocols to (i) efficiently obtain global extrema of the sensed quantities, (ii) extract local extrema, and (iii) detect the boundaries of events, by using simple transforms that nodes employ on their local data. We extend our results for a large dense network with multiple broadcast domains (MBD). We discuss and compare two approaches for addressing the challenges with MBD and we show through extensive evaluations that our proposed distributed MBD approach is fast and efficient at retrieving the most valuable measurements, independent of the number sensor nodes in the network.

An integrated system for human action recognition from video using hidden Markov model

In this paper, we present an integrated system for real-time automatic detection of human actions from video. The proposed approach uses the boundary of humans as the main feature for recognizing actions. Background subtraction is performed using Gaussian mixture model. Then, features are extracted from silhouettes and Vector Quantization is used to map features into symbols (bag of words approach). Finally, actions are detected using the Hidden Markov Model. The proposed system was validated using a newly collected real- world dataset. The obtained results show that the system is capable of achieving robust human detection, in both indoor and outdoor environments. Moreover, promising classification results were achieved when detecting two basic human actions: walking and sitting.

Feature Nets: behavioural modelling of software product lines

Software product lines (SPL) are diverse systems that are developed using a dual engineering process: (a)family engineering defines the commonality and variability among all members of the SPL, and (b) application engineering derives specific products based on the common foundation combined with a variable selection of features. The number of derivable products in an SPL can thus be exponential in the number of features. This inherent complexity poses two main challenges when it comes to modelling: Firstly, the formalism used for modelling SPLs needs to be modular and scalable. Secondly, it should ensure that all products behave correctly by providing the ability to analyse and verify complex models efficiently. In this paper we propose to integrate an established modelling formalism (Petri nets) with the domain of software product line engineering. To this end we extend Petri nets to Feature Nets. While Petri nets provide a framework for formally modelling and verifying single software systems, Feature Nets offer the same sort of benefits for software product lines. We show how SPLs can be modelled in an incremental, modular fashion using Feature Nets, provide a Feature Nets variant that supports modelling dynamic SPLs, and propose an analysis method for SPL modelled as Feature Nets. By facilitating the construction of a single model that includes the various behaviours exhibited by the products in an SPL, we make a significant step towards efficient and practical quality assurance methods for software product lines.

Refactoring feature modules : disciplined generation of reusable modules

Magdeburg, Univ., Fak. für Informatik, Diss., 2011

Towards flexible feature composition : static and dynamic binding in software product lines

Magdeburg, Univ., Fak. für Informatik, Diss., 2011

Product-line specification and verification with feature-oriented contracts

Magdeburg, Univ., Fak. für Informatik, Diss., 2015

Prototype based clustering in high-dimensional feature spaces

...In dieser Arbeit untersuche ich den ”Fluch der Dimensionen” mittels dem Begriff der Distanzkonzentration. Ich zeige, dass dieser Effekt im Datenmodell mittels der paarweisen Kovarianzkoeffizienten der Randverteilungen beschrieben werden kann. Zusätzlich vergleiche ich 10 prototypbasierte Clusteralgorithmen mittels 800.000 Clusterergebnissen von künstlich erzeugten Datensätzen. Ich erforsche, wie und warum Clusteralgorithmen von der Anzahl der Merkmale beeinflusst werden. Mit den Clusterergebnissen untersuche ich außerdem, wie gut 5 der populärsten Clusterqualitätsmaße die tatsächliche Clusterqualität schätzen.

Conserved non-genic sequences - an unexpected feature of mammalian genomes.

Mammalian genomes contain highly conserved sequences that are not functionally transcribed. These sequences are single copy and comprise approximately 1-2% of the human genome. Evolutionary analysis strongly supports their functional conservation, although their potentially diverse, functional attributes remain unknown. It is likely that genomic variation in conserved non-genic sequences is associated with phenotypic variability and human disorders. So how might their function and contribution to human disorders be examined?

The feature of papers and citation analysis of eleven journals in tropical medicine indexed by Science Citation Index Expanded

To determine the features of papers, authors, and citation of eleven journals in tropical medicine indexed by Science Citation Index Expanded, the database of the Institute for Scientific Information, we analyzed original articles, editorials, reviews, corrections, letters, biographies, and news published in these journals. The results show that these journals covered 107 countries or regions on six continents. The average number of reference was 23.05, with 87.89% of the references from periodicals. The Price Index was 31.43% and the self-citing rate was 7.02%. The references in the first 20 journals ranked by the amount of citation accounted for 36.71% of the total citations. Brazil, United States, India, and England are more advanced in tropical medicine research. The conclusion is that these journals covered most research done in these countries or regions. Most researches were done by cooperation of the researchers, but many of the publications used outdated articles and should include newer information.

Quantization of energy and writhe in self-repelling knots

Probably the most natural energy functional to be considered for knotted strings is that given by electrostatic repulsion. In the absence of counter-charges, a charged, knotted string evolving along the energy gradient of electrostatic repulsion would progressively tighten its knotted domain into a point on a perfectly circular string. However, in the presence of charge screening self-repelling knotted strings can be stabilized. It is known that energy functionals in which repulsive forces between repelling charges grow inversely proportionally to the third or higher power of their relative distance stabilize self-repelling knots. Especially interesting is the case of the third power since the repulsive energy becomes scale invariant and does not change upon Mobius transformations (reflections in spheres) of knotted trajectories. We observe here that knots minimizing their repulsive Mobius energy show quantization of the energy and writhe (measure of chirality) within several tested families of knots.

Particularités de la prise en charge des infections chez le patient neutropénique [Special feature in the handling of infectious in neutropenic patients]

Les progrès continus des connaissances réalisés dans le domaine de l'oncohématologie depuis quelques décennies ont permis une amélioration considérable du pronostic de la plupart des formes de cancer. Toutefois, la morbidité et la mortalité attribuables aux infections apparaissent actuellement comme les principaux facteurs limitant l'agressivité des traitements de la maladie cancéreuse, et un meilleur contrôle de ces dernières est devenu l'un des éléments essentiels de la prise en charge de ce type de patients. Une recherche clinique intense a permis d'en identifier les grands principes qui sont exposés dans cet article. Un algorithme thérapeutique susceptible de guider le clinicien face au développement d'un état fébrile, toujours suspect d'infection chez le patient cancéreux neutropénique, est ensuite proposé.

A genetic algorithm to ensemble feature selection

We are going to implement the "GA-SEFS" by Tsymbal and analyse experimentally its performance depending on the classifier algorithms used in the fitness function (NB, MNge, SMO). We are also going to study the effect of adding to the fitness function a measure to control complexity of the base classifiers.

A survey on transfer-based approaches to MT using feature structures

Aquest treball és una revisió d'alguns sistemes de Traducció Automàtica que segueixen l'estratègia de Transfer i fan servir estructures de trets com a eina de representació. El treball s'integra dins el projecte MLAP-9315, projecte que investiga la reutilització de les especificacions lingüístiques del projecte EUROTRA per estàndards industrials.

Morphometric shape analysis using learning vector quantization neural networks - an example distinguishing two microtine vole species

Closely related species may be very difficult to distinguish morphologically, yet sometimes morphology is the only reasonable possibility for taxonomic classification. Here we present learning-vector-quantization artificial neural networks as a powerful tool to classify specimens on the basis of geometric morphometric shape measurements. As an example, we trained a neural network to distinguish between field and root voles from Procrustes transformed landmark coordinates on the dorsal side of the skull, which is so similar in these two species that the human eye cannot make this distinction. Properly trained neural networks misclassified only 3% of specimens. Therefore, we conclude that the capacity of learning vector quantization neural networks to analyse spatial coordinates is a powerful tool among the range of pattern recognition procedures that is available to employ the information content of geometric morphometrics.