Learning Situation Models in a Smart Home

This paper addresses the problem of learning situation models for providing context-aware services. Context for modeling human behavior in a smart environment is represented by a situation model describing environment, users, and their activities. A framework for acquiring and evolving different layers of a situation model in a smart environment is proposed. Different learning methods are presented as part of this framework: role detection per entity, unsupervised extraction of situations from multimodal data, supervised learning of situation representations, and evolution of a predefined situation model with feedback. The situation model serves as frame and support for the different methods, permitting to stay in an intuitive declarative framework. The proposed methods have been integrated into a whole system for smart home environment. The implementation is detailed, and two evaluations are conducted in the smart home environment. The obtained results validate the proposed approach.     

A multimode 0.3-200-kb/s transceiver for the 433/868/915-MHz bands in 0.25-/spl mu/m CMOS

A fully integrated transceiver suitable for low-data-rate wireless telemetry and sensor networks operating in the license-free ISM frequency bands at 433, 868, or 915 MHz implemented in 0.25-/spl mu/m CMOS is presented. G/FSK, ASK, and OOK modulation formats are supported at data rates from 0.3 to 200 kb/s. The transceiver's analog building blocks include a low-noise amplifier, mixer, channel filter, received signal-strength indication, frequency synthesizer, voltage-controlled oscillator, and power amplifier. FSK demodulation is implemented using a novel digital complex-frequency correlator that operates over a wide modulation-index range and approximates matched filter detection performance. Automatic gain control, automatic frequency control, and symbol timing recovery loops are included on chip. Operating in the 915-MHz band in FSK mode at 9.6 kb/s, the receiver consumes 19.7 mA from a 3-V supply and achieves a sensitivity of -112.8dBm at 0.1% BER. The transmitter consumes 28.5 mA for an output power of 10 dBm and delivers up to 14 dBm.     

Effect of temperature on raw whole milk density and its potential impact on milk payment in the dairy industry

The objective of this study was to determine the effect of temperature on whole milk density measured at four different temperatures: 5, 10, 15, and 20 °C. A total of ninety-three individual milk samples were collected from morning milking of thirty-two Holstein Friesian dairy cows, of national average genetic merit, once every two weeks over a period of 4 weeks and were assessed by Fourier transform infrared spectroscopy for milk composition analysis. Density of the milk was evaluated using two different analytical methods: a portable density meter DMA35 and a standard desktop model DMA4500M (Anton Paar GmbH, UK). Milk density was analysed with a linear mixed model with the fixed effects of sampling period, temperature and analysis method; triple interaction of sampling period x analysis method x temperature; and the random effect of cow to account for repeated measures. The effect of temperature on milk density (ρ) was also evaluated including temperature (t) as covariate with linear and quadratic effects within each analytic method. The regression equation describing the curvature and density–temperature relationship for the DMA35 instrument was ρ = 1.0338−0.00017T−0.0000122T² (R² = 0.64), while it was ρ = 1.0334 + 0.000057T−0.00001T² (R² = 0.61) for DMA4500 instrument. The mean density determined with DMA4500 at 5 °C was 1.0334 g cm⁻³, with corresponding figures of 1.0330, 1.0320 and 1.0305 g cm⁻³ at 10, 15 and 20 °C, respectively. The milk density values obtained in this study at specific temperatures will help to address any bias in weight–volume calculations and thus may also improve the financial and operational control for the dairy processors in Ireland and internationally.     

Thermal stability of soy protein isolate and hydrolysate ingredients

The objective of this study was to characterize the effects of pH, protein concentration and calcium supplementation on thermal stability, at 140 °C, of soy protein isolate (SPI) and soy protein hydrolysate (SPH) ingredients. Increasing pH between 6.4 and 7.5 led to significantly (p < 0.05) higher mean heat coagulation times (HCTs) at 140 °C, for all soy protein ingredients at 1.8, and 3.6% (w/v) protein. Increasing protein concentration from 1.8 to 7.2% (w/v) led to shorter HCTs for protein dispersions. Calcium supplementation up to 850 mg/L, except in the case of supplementation of SPI 1 with calcium citrate (CaCit), decreased HCT for soy protein ingredient dispersions, at pH 6.4 – 7.5. No significant differences (p < 0.05) were found in mean HCT for dispersions supplemented with calcium chloride (CaCl₂) and those supplemented with CaCit at 450, 650 and 850 mg/L Ca²⁺, in the pH range 6.4–7.5.     

Thermal analysis of polymer ignition

Gas phase criteria for the onset of flaming combustion of solids in fires are used to locate a critical temperature T_cr in a nonisothermal analysis (TA) experiment that corresponds to the surface temperature of the solid at ignition in a fire test, T_ign. This critical TA temperature occurs at low conversion of solid to gaseous fuel so it is independent of the heating rate in the test or the thermal decomposition reaction model. However, T_cr depends on the thermal properties of the polymer and the conditions of the fire test in which the gas phase criteria were measured. Nonisothermal analysis data in nitrogen and air were obtained for 20 polymers by thermogravimetric analysis and microscale combustion calorimetry. The critical temperatures T_crs obtained from TA experiments compared favorably with analytic results for a simple polymer ignition model and finite element simulations and were in qualitative agreement with ignition temperatures measured in standardized fire tests.     

Image Manifolds which are Isometric to Euclidean Space

Recently, the Isomap procedure [10] was proposed as a new way to recover a low-dimensional parametrization of data lying on a low-dimensional submanifold in high-dimensional space. The method assumes that the submanifold, viewed as a Riemannian submanifold of the ambient high-dimensional space, is isometric to a convex subset of Euclidean space. This naturally raises the question: what datasets can reasonably be modeled by this condition? In this paper, we consider a special kind of image data: families of images generated by articulation of one or several objects in a scene—for example, images of a black disk on a white background with center placed at a range of locations. The collection of all images in such an articulation family, as the parameters of the articulation vary, makes up an articulation manifold, a submanifold of L ². We study the properties of such articulation manifolds, in particular, their lack of differentiability when the images have edges. Under these conditions, we show that there exists a natural renormalization of geodesic distance which yields a well-defined metric. We exhibit a list of articulation models where the corresponding manifold equipped with this new metric is indeed isometric to a convex subset of Euclidean space. Examples include translations of a symmetric object, rotations of a closed set, articulations of a horizon, and expressions of a cartoon face. The theoretical predictions from our study are borne out by empirical experiments with published Isomap code. We also note that in the case where several components of the image articulate independently, isometry may fail; for example, with several disks in an image avoiding contact, the underlying Riemannian manifold is locally isometric to an open, connected, but not convex subset of Euclidean space. Such a situation matches the assumptions of our recently-proposed Hessian Eigenmaps procedure, but not the original Isomap procedure.     

Synthesis and characterization of perfectly alternating polycarbonate‐polydimethylsiloxane multiblock copolymers possessing controlled block lengths

An array of perfectly alternating polycarbonate‐polydimethylsiloxane (PC‐PDMS) multiblock copolymers possessing systematic variations in block molecular weights were successfully produced by coupling preformed PC and PDMS telechelic oligomers using hydrosilylation. Based on gel permeation chromatography results, the multiblock copolymers were essentially void of the oligomeric precursors. Despite the relatively large difference in solubility parameter between PC and PDMS, the multiblock copolymers exhibited significant partial miscibility between the two phases. As expected, the degree of partial miscibility was dependent on the molecular weight of the blocks with the extent of partial miscibility increasing with decreasing block molecular weights. Morphological characterization using small angle X‐ray scattering showed that, at a given PC block molecular weight, the uniformity of the two phase morphology increased with increasing PDMS block molecular weight, which is consistent with a decrease in the extent of phase mixing with increasing PDMS block molecular weight. POLYM. ENG. SCI., 54:1648–1663, 2014. © 2013 Society of Plastics Engineers