Mean anisotropy of homogeneous Gaussian random fields and anisotropic norms of linear translation-invariant operators on multidimensional integer lattices

Sensitivity of output of a linear operator to its input can be quantified in various ways. In Control Theory, the input is usually interpreted as disturbance and the output is to be minimized in some sense. In stochastic worst-case design settings, the disturbance is considered random with imprecisely known probability distribution. The prior set of probability measures can be chosen so as to quantify how far the disturbance deviates from the white-noise hypothesis of Linear Quadratic Gaussian control. Such deviation can be measured by the minimal Kullback-Leibler informational divergence from the Gaussian distributions with zero mean and scalar covariance matrices. The resulting anisotropy functional is defined for finite power random vectors. Originally, anisotropy was introduced for directionally generic random vectors as the relative entropy of the normalized vector with respect to the uniform distribution on the unit sphere. The associated a-anisotropic norm of a matrix is then its maximum root mean square or average energy gain with respect to finite power or directionally generic inputs whose anisotropy is bounded above by a >= 0. We give a systematic comparison of the anisotropy functionals and the associated norms. These are considered for unboundedly growing fragments of homogeneous Gaussian random fields on multidimensional integer lattice to yield mean anisotropy. Correspondingly, the anisotropic norms of finite matrices are extended to bounded linear translation invariant operators over such fields

Low-energy finite field arithmetic primitives for implementing security in wireless sensor networks

In this paper we propose the use of identity based encryption (IBE) for ensuring a secure wireless sensor network. In this context we have implemented the arithmetic operations required for the most computationally expensive part of IBE, which is the Tate pairing, in 90 nm CMOS and obtained area, timing and energy figures for the designs. Initial results indicate that a hardware implementation of IBE would meet the strict energy constraint of a wireless sensor network nod

Breathing feedback system with wearable textile sensors

Breathing exercises form an essential part of the treatment for respiratory illnesses such as cystic fibrosis. Ideally these exercises should be performed on a daily basis. This paper presents an interactive system using a wearable textile sensor to monitor breathing patterns. A graphical user interface provides visual real-time feedback to patients. The aim of the system is to encourage the correct performance of prescribed breathing exercises by monitoring the rate and the depth of breathing. The system is straightforward to use, low-cost and can be installed easily within a clinical setting or in the home. Monitoring the user with a wearable sensor gives real-time feedback to the user as they perform the exercise, allowing them to perform the exercises independently. There is also potential for remote monitoring where the user’s overall performance over time can be assessed by a clinician

Integrating multiple sensor modalities for environmental monitoring of marine locations

In this paper we present preliminary work on integrating visual sensing with the more traditional sensing modalities for marine locations. We have deployed visual sensing at one of the Smart Coast WSN sites in Ireland and have built a software platform for gathering and synchronizing all sensed data. We describe how the analysis of a range of different sensor modalities can reinforce readings from a given noisy, unreliable sensor

Animal models of Zika virus infection, pathogenesis, and immunity

Zika virus (ZIKV) is an emerging mosquito-transmitted flavivirus that now causes epidemics affecting millions of people on multiple continents. The virus has received global attention because of some of its unusual epidemiological and clinical features, including persistent infection in the male reproductive tract and sexual transmission, an ability to cross the placenta during pregnancy and infect the developing fetus to cause congenital malformations, and its association with Guillain-Barré syndrome in adults. This past year has witnessed an intensive effort by the global scientific community to understand the biology of ZIKV and to develop pathogenesis models for the rapid testing of possible countermeasures. Here, we review the recent advances in and utility and limitations of newly developed mouse and nonhuman primate models of ZIKV infection and pathogenesis

Image processing for smarter browsing of ocean color data products: investigating algal blooms

Remote sensing technology continues to play a significant role in the understanding of our environment and the investigation of the Earth. Ocean color is the water hue due to the presence of tiny plants containing the pigment chlorophyll, sediments, and colored dissolved organic material and so can provide valuable information on coastal ecosystems. We propose to make the browsing of Ocean Color data more efficient for users by using image processing techniques to extract useful information which can be accessible through browser searching. Image processing is applied to chlorophyll and sea surface temperature images. The automatic image processing of the visual level 1 and level 2 data allow us to investigate the occurrence of algal blooms. Images with colors in a certain range (red, orange etc.) are used to address possible algal blooms and allow us to examine the seasonal variation of algal blooms in Europe (around Ireland and in the Baltic Sea). Yearly seasonal variation of algal blooms in Europe based on image processing for smarting browsing of Ocean Color are presented