Design and analysis of an integrated antiresonant reflecting optical waveguide refractive-index sensor

An integrated optical waveguide refractometer, believed to be novel, is presented. The sensor is based on an antiresonant reflecting optical waveguide and uses the strong attenuation dependence on the refractive index of antiresonant cladding layers as the sensing principle. The theory and the operation of the sensor are discussed in terms of one- and two-dimensional geometry. The theoretical predictions and numerical analysis show that a versatile sensor can be realized. The design trade-offs are discussed, and the sensitivity and measurement range are presented.     

The Impact of an Agile Methodology on the Well Being of Development Teams

This paper describes an empirical study, which addresses the aspect of well being amongst members of the software development teams. The question of interest is whether an agile methodology has any distinct effect on the well being of the software developers. Both quantitative and qualitative methods were utilised, including the participative observation, focus group interviews, close-ended questionnaires and simple statistical tests such as Spearman Correlation and Mann–Whitney test. Initial results showed that an agile methodology (XP) has a positive effect on the level of enthusiasm of the software developers in the most dynamic project. To understand why XP can increase enthusiasm, results are interpreted with references to cognitive, affective and managerial properties of the practices studied. This result needs further investigation on the individual effects of each practice on the wellbeing and attitudes of Software Engineering (SE) teams.     

Genetic homogeneity of autoimmune polyglandular disease type I

Autoimmune polyglandular disease type I (APECED) is an autosomal recessive autoimmune disease (MIM 240300) characterized by hypoparathyroidism, primary adrenocortical failure, and chronic mucocutaneous candidiasis. The disease is highly prevalent in two isolated populations, the Finnish population and the Iranian Jewish one. Sporadic cases have been identified in many other countries, including almost all European countries. The APECED locus has previously been assigned to chromosome 21q22.3 by linkage analyses in 14 Finnish families. Locus heterogeneity is a highly relevant question in this disease affecting multiple tissues and with great phenotypic diversity. To solve this matter, we performed linkage and haplotype analyses on APECED families rising from different populations. Six microsatellite markers on the critical chromosomal region of 2.6 cM on 21q22.3 were analyzed. Pairwise linkage analyses revealed significant LOD scores for all these markers, maximum LOD score being 10.23. The obtained haplotype data and the geographic distribution of the great-grandparents of the Finnish APECED patients suggest the presence of one major, relatively old mutation responsible for approximately 90% of the Finnish cases. Similar evidence for one founder mutation was also found in analyses of Iranian Jewish APECED haplotypes. These haplotypes, however, differed totally from the Finnish ones. The linkage analyses in 21 non-Finnish APECED families originating from several European countries provided independent evidence for linkage to the same chromosomal region on 21q22.3 and revealed no evidence for locus heterogeneity. The haplotype analyses of APECED chromosomes suggest that in different populations APECED is due to a spectrum of mutations in a still unknown gene on chromosome 21.     

Dynamic transitions from smooth to rough to twinning in dislocation motion

The motion of dislocations in response to stress dictates the mechanical behaviour of materials. However, it is not yet possible to directly observe dislocation motion experimentally at the atomic level. Here, we present the first observations of the long-hypothesized kink-pair mechanism in action using atomistic simulations of dislocation motion in iron. In a striking deviation from the classical picture, dislocation motion at high strain rates becomes rough, resulting in spontaneous self-pinning and production of large quantities of debris. Then, at still higher strain rates, the dislocation stops abruptly and emits a twin plate that immediately takes over as the dominant mode of plastic deformation. These observations challenge the applicability of the Peierls threshold concept to the three-dimensional motion of screw dislocations at high strain rates, and suggest a new interpretation of plastic strength and microstructure of shocked metals.     

Projective filtering of time-aligned ECG beats

A method of electrocardiographic (ECG) signal processing developed by introduction of time synchronization into the method of nonlinear state-space projections is presented. It can be regarded as an extension of time averaging but contrary to usual averaging it preserves variability of ECG beats morphology. For this purpose, after the respective beats time alignment, the synchronized intervals of the signal undergo processing according to the rules of principal component analysis (PCA). PCA allows for determination of orthogonal basis functions which can be employed for approximation of the respective intervals. The operation is aimed to retain the deviations from the mean which result from the desired component changes and to reject the deviations caused by noise. The method's capabilities are investigated and some of its applications are presented.     

Call for Papers: Special Issue on Aquatic Chemical Ecology

Call for Papers

Call for Papers: Special Issue on Aquatic Chemical Ecology     

Event-driven Video Awareness Providing Physical Security

The Video Event Awareness Workbench (VEAW) analyzes surveillance video from thousands of video cameras and automatically detects complex events in near-real-time-at pace with their input video streams. For events of interest to security personnel, VEAW generates and routes alerts and related video evidence to subscribing security personnel. Complex event processing in VEAW is driven by user-authored awareness specifications comprised of inter-connected spatio-temporal stream and statistical operators that consume and produce events described in VEAW’s surveillance ontology. In this paper we introduce VEAW’s event driven architecture and describe its solutions for automating video surveillance, including the orchestration of continuous and tasked video analysis algorithms (e.g., for entity tracking and identification), fusion of events from multiple sources in an installation-specific “world” model, and proactive information gathering to deal with missing or incomplete information (this is done by tasking video analysis algorithms and security personnel to provide it). We also discuss how VEAW deals with late arriving information (due to out-of-band video analysis tasks and overhead), as well as a related resource optimization aimed at minimizing computation costs. We illustrate the benefits of VEAW by illustrating its application on the automation of real-world security policies.     

The kernel common vector method: a novel nonlinear subspace classifier for pattern recognition.

The common vector (CV) method is a linear subspace classifier method which allows one to discriminate between classes of data sets, such as those arising in image and word recognition. This method utilizes subspaces that represent classes during classification. Each subspace is modeled such that common features of all samples in the corresponding class are extracted. To accomplish this goal, the method eliminates features that are in the direction of the eigenvectors corresponding to the nonzero eigenvalues of the covariance matrix of each class. In this paper, we introduce a variation of the CV method, which will be referred to as the modified CV (MCV) method. Then, a novel approach is proposed to apply the MCV method in a nonlinearly mapped higher dimensional feature space. In this approach, all samples are mapped into a higher dimensional feature space using a kernel mapping function, and then, the MCV method is applied in the mapped space. Under certain conditions, each class gives rise to a unique CV, and the method guarantees a 100% recognition rate with respect to the training set data. Moreover, experiments with several test cases also show that the generalization performance of the proposed kernel method is comparable to the generalization performances of other linear subspace classifier methods as well as the kernel-based nonlinear subspace method. While both the MCV method and its kernel counterpart did not outperform the support vector machine (SVM) classifier in most of the reported experiments, the application of our proposed methods is simpler than that of the multiclass SVM classifier. In addition, it is not necessary to adjust any parameters in our approach.     

New length bounds for cycle bases

Based on a recent work by Abraham, Bartal and Neiman (2007), we construct a strictly fundamental cycle basis of length O(n²) for any unweighted graph, whence proving the conjecture of Deo et al. (1982).For weighted graphs, we construct cycle bases of length O(W⋅lognloglogn), where W denotes the sum of the weights of the edges. This improves the upper bound that follows from the result of Elkin et al. (2005) by a logarithmic factor and, for comparison from below, some natural classes of large girth graphs are known to exhibit minimum cycle bases of length Ω(W⋅logn).We achieve this bound for weighted graphs by not restricting ourselves to strictly fundamental cycle bases—as it is inherent to the approach of Elkin et al.—but rather also considering weakly fundamental cycle bases in our construction. This way we profit from some nice properties of Hierarchically Well-Separated Trees that were introduced by Bartal (1998).