Cues in the environment: A design principle for ambient intelligence

The aim of this paper is to propose design principles for ambient intelligence (AmI) environments. The question we are investigating is how these environments can be designed to support a group to be able to carry out common goal-oriented activities. The approach we are taking in answering this question is informed by the concept of collective intelligence (CI). We are applying the concept of CI to AmI as we have found it works well in biological and social systems. Examples from nature demonstrate the power of CI stimulated by implicit cues in the environment. We use these examples to derive design principles for AmI environments. By applying these design principles to a concrete scenario, we are able to propose ways to help decrease environmental pollution within urban areas.

GPRA and the asthma locus on chromosome 7p14-p15

The basis of this work was the identification of a genomic region on chromosome 7p14-p15 that strongly associated with asthma and high serum total immunoglobulin E in a Finnish founder population from Kainuu. Using a hierarchical genotyping approach the linkage region was narrowed down until an evolutionary collectively inherited 133-kb haplotype block was discovered. The results were confirmed in two independent data sets: Asthma families from Quebec and allergy families from North-Karelia. In all the three cohorts studied, single nucleotide polymorphisms tagging seven common gene variants (haplotypes) were identified. Over half of the asthma patients carried three evolutionary closely related susceptibility haplotypes as opposed to approximately one third of the healthy controls. The risk effects of the gene variants varied from 1.4 to 2.5. In the disease-associated region, there was one protein-coding gene named GPRA (G Protein-coupled Receptor for Asthma susceptibility also known as NPSR1) which displayed extensive alternative splicing. Only the two isoforms with distinct intracellular tail sequences, GPRA-A and -B, encoded a full-length G protein-coupled receptor with seven transmembrane regions. Using various techniques, we showed that GPRA is expressed in multiple mucosal surfaces including epithelial cells throughout the respiratory tract. GPRA-A has additional expression in respiratory smooth muscle cells. However, in bronchial biopsies with unknown haplotypes, GPRA-B was upregulated in airways of all patient samples in contrast to the lack of expression in controls. Further support for GPRA as a common mediator of inflammation was obtained from a mouse model of ovalbumin-induced inflammation, where metacholine-induced airway hyperresponsiveness correlated with elevated GPRA mRNA levels in the lung and increased GPRA immunostaining in pulmonary macrophages. A novel GPRA agonist, Neuropeptide S (NPS), stimulated phagocytosis of Esterichia coli bacteria in a mouse macrophage cell line indicating a role for GPRA in the removal of inhaled allergens. The suggested GPRA functions prompted us to study, whether GPRA haplotypes associate with respiratory distress syndrome (RDS) and bronchopulmonary dysplasia (BPD) in infants sharing clinical symptoms with asthma. According to the results, near-term RDS and asthma may also share the same susceptibility and protective GPRA haplotypes. As in asthma, GPRA-B isoform expression was induced in bronchial smooth muscle cells in RDS and BPD suggesting a role for GPRA in bronchial hyperresponsiveness. In conclusion, the results of the present study suggest that the dysregulation of the GPRA/NPS pathway may not only be limited to the individuals carrying the risk variants of the gene but is also involved in the regulation of immune functions of asthma.

Positional cloning and pathway analysis of the asthma susceptibility gene, NPSR1

In the present study, we identified a novel asthma susceptibility gene, NPSR1 (neuropeptide S receptor 1) on chromosome 7p14.3 by the positional cloning strategy. An earlier significant linkage mapping result among Finnish Kainuu asthma families was confirmed in two independent cohorts: in asthma families from Quebec, Canada and in allergy families from North Karelia, Finland. The linkage region was narrowed down to a 133-kb segment by a hierarchial genotyping method. The observed 77-kb haplotype block showed 7 haplotypes and a similar risk and nonrisk pattern in all three populations studied. All seven haplotypes occur in all three populations at frequences > 2%. Significant elevated relative risks were detected for elevated total IgE (immunoglobulin E) or asthma. Risk effects of the gene variants varied from 1.4 to 2.5. NPSR1 belongs to the G protein-coupled receptor (GPCR) family with a topology of seven transmembrane domains. NPSR1 has 9 exons, with the two main transcripts, A and B, encoding proteins of 371 and 377 amino acids, respectively. We detected a low but ubiquitous expression level of NPSR1-B in various tissues and endogenous cell lines while NPSR1-A has a more restricted expression pattern. Both isoforms were expressed in the lung epithelium. We observed aberrant expression levels of NPSR1-B in smooth muscle in asthmatic bronchi as compared to healthy. In an experimental mouse model, the induced lung inflammation resulted in elevated Npsr1 levels. Furthermore, we demonstrated that the activation of NPSR1 with its endogenous agonist, neuropeptide S (NPS), resulted in a significant inhibition of the growth of NPSR1-A overexpressing stable cell lines (NPSR1-A cells). To determine which target genes were regulated by the NPS-NPSR1 pathway, NPSR1-A cells were stimulated with NPS, and differentially expressed genes were identified using the Affymetrix HGU133Plus2 GeneChip. A total of 104 genes were found significantly up-regulated and 42 down-regulated 6 h after NPS administration. The up-regulated genes included many neuronal genes and some putative susceptibility genes for respiratory disorders. By Gene Ontology enrichment analysis, the biological process terms, cell proliferation, morphogenesis and immune response were among the most altered. The expression of four up-regulated genes, matrix metallopeptidase 10 (MMP10), INHBA (activin A), interleukin 8 (IL8) and EPH receptor A2 (EPHA2), were verified and confirmed by quantitative reverse-transcriptase-PCR. In conclusion, we identified a novel asthma susceptibility gene, NPSR1, on chromosome 7p14.3. NPS-NPSR1 represents a novel pathway that regulates cell proliferation and immune responses, and thus may have functional relevance in the pathogenesis of asthma.

Estimation of cutting volume with three inventory methods for harvest planning in Canadian boreal forests.

Two methods of pre-harvest inventory were designed and tested on three cutting sites containing a total of 197 500 m3 of wood. These sites were located on flat-ground boreal forests located in northwestern Quebec. Both methods studied involved scaling of trees harvested to clear the road path one year (or more) prior to harvest of adjacent cut-blocks. The first method (ROAD) considers the total road right-of-way volume divided by the total road area cleared. The resulting volume per hectare is then multiplied by the total cut-block area scheduled for harvest during the following year to obtain the total estimated cutting volume. The second method (STRATIFIED) also involves scaling of trees cleared from the road. However, in STRATIFIED, log scaling data are stratified by forest stand location. A volume per hectare is calculated for each stretch of road that crosses a single forest stand. This volume per hectare is then multiplied by the remaining area of the same forest stand scheduled for harvest one year later. The sum of all resulting estimated volumes per stand gives the total estimated cutting-volume for all cut-blocks adjacent to the studied road. A third method (MNR) was also used to estimate cut-volumes of the sites studied. This method represents the actual existing technique for estimating cutting volume in the province of Quebec. It involves summing the cut volume for all forest stands. The cut volume is estimated by multiplying the area of each stand by its estimated volume per hectare obtained from standard stock tables provided by the governement. The resulting total estimated volume per cut-block for all three methods was then compared with the actual measured cut-block volume (MEASURED). This analysis revealed a significant difference between MEASURED and MNR methods with the MNR volume estimate being 30 % higher than MEASURED. However, no significant difference from MEASURED was observed for volume estimates for the ROAD and STRATIFIED methods which respectively had estimated cutting volumes 19 % and 5 % lower than MEASURED. Thus the ROAD and STRATIFIED methods are good ways to estimate cut-block volumes after road right-of-way harvest for conditions similar to those examined in this study.

Interaction of guar gum with hydrophobic solids

The interaction of guar gum with the hydrophobic solids namely talc, mica and graphite has been investigated through adsorption, electrokinetic and flotation experiments. The adsorption densities of guar gum onto the above hydrophobic minerals show that they are more or less independent of pH. The adsorption isotherms of guar gum onto talc, mica and graphite indicate that the adsorption densities increase with increase in guar gum concentration and all the isotherms follow the as L1 type according to Giles classification. The magnitude of the adsorption density of guar gum onto the above minerals may be arranged in the following sequence: talc > graphite > mica The effect of particle size on the adsorption density of guar gum onto these minerals has indicated that higher adsorption takes place in the coarser size fraction, consequent to an increase in the surface face-to-edge ratio. In the case of the talc and mica samples pretreated with EDTA and the leached graphite sample, a decrease in the adsorption density of guar gum is observed, due to a reduction in the metallic adsorption sites. The adsorption densities of guar gum increase with decrease in sample weight for all the three minerals. Electrokinetic measurements have indicated that the isoelectric points (iep) of these minerals lie between pH 2-3, Addition of guar gum decreases the negative electrophoretic mobility values in proportion to the guar gum concentration without any observable shift in the iep values, resembling the influence of an indifferent electrolyte. The flotation recovery is diminished in the presence of guar gum for all the three minerals, The magnitude of depression follows the same sequence as observed in the adsorption studies. The floatability of EDTA treated talc and mica samples as well as the leached graphite sample is enhanced, complementing the adsorption data, Possible mechanisms of interaction between the hydrophobic minerals and guar gum are discussed.

A novel interrogation system for fiber Bragg grating sensor array

Interrogation techniques for fiber Bragg grating sensor arrays need particular attention in the case of structural health monitoring applications involving dynamic strain measurement. Typically the performance of the sensing system is dependent on both the sensor type and the interrogation method employed. A novel interrogation system is proposed here that consists of different interrogation units for each sensor in the array, each unit comprising of a circulator, chirped grating and a Mach-Zehnder interferometer. We present an analysis that consists of tracking the spectral changes as the light passes through various elements in the interrogation system. This is expected to help in the optimization of sensor and interrogation elements leading to improved performance of the health monitoring system.

Trellis coded modulation scheme for the fading relay channel

A decode and forward protocol based Trellis Coded Modulation (TCM) scheme for the half-duplex relay channel, in a Rayleigh fading environment, is presented. The proposed scheme can achieve any spectral efficiency greater than or equal to one bit per channel use (bpcu). A near-ML decoder for the suggested TCM scheme is proposed. It is shown that the high Signal to Noise Ratio (SNR) performance of this near-ML decoder approaches the performance of the optimal ML decoder. Based on the derived Pair-wise Error Probability (PEP) bounds, design criteria to maximize the diversity and coding gains are obtained. Simulation results show a large gain in SNR for the proposed TCM scheme over uncoded communication as well as the direct transmission without the relay.

Wireless network-coded accumulate-compute and forward two-way relaying

The design of modulation schemes for the physical layer network-coded two way wireless relaying scenario is considered. It was observed by Koike-Akino et al. for the two way relaying scenario, that adaptively changing the network coding map used at the relay according to the channel conditions greatly reduces the impact of multiple access interference which occurs at the relay during the MA Phase and all these network coding maps should satisfy a requirement called exclusive law. We extend this approach to an Accumulate-Compute and Forward protocol which employs two phases: Multiple Access (MA) phase consisting of two channel uses with independent messages in each channel use, and Broadcast (BC) phase having one channel use. Assuming that the two users transmit points from the same 4-PSK constellation, every such network coding map that satisfies the exclusive law can be represented by a Latin Square with side 16, and conversely, this relationship can be used to get the network coding maps satisfying the exclusive law. Two methods of obtaining this network coding map to be used at the relay are discussed. Using the structural properties of the Latin Squares for a given set of parameters, the problem of finding all the required maps is reduced to finding a small set of maps. Having obtained all the Latin Squares, the set of all possible channel realizations is quantized, depending on which one of the Latin Squares obtained optimizes the performance. The quantization thus obtained, is shown to be the same as the one obtained in [7] for the 2-stage bidirectional relaying.

LANDSCAPE DYNAMICS MODELING THROUGH INTEGRATED MARKOV, FUZZY-AHP AND CELLULAR AUTOMATA

Multi temporal land use information were derived using two decades remote sensing data and simulated for 2012 and 2020 with Cellular Automata (CA) considering scenarios, change probabilities (through Markov chain) and Multi Criteria Evaluation (MCE). Agents and constraints were considered for modeling the urbanization process. Agents were nornmlized through fiizzyfication and priority weights were assigned through Analytical Hierarchical Process (AHP) pairwise comparison for each factor (in MCE) to derive behavior-oriented rules of transition for each land use class. Simulation shows a good agreement with the classified data. Fuzzy and AHP helped in analyzing the effects of agents of growth clearly and CA-Markov proved as a powerful tool in modelling and helped in capturing and visualizing the spatiotemporal patterns of urbanization. This provided rapid land evaluation framework with the essential insights of the urban trajectory for effective sustainable city planning.

IMAGE DENOISING USING OPTIMALLY WEIGHTED BILATERAL FILTERS: A SURE AND FAST APPROACH

The bilateral filter is known to be quite effective in denoising images corrupted with small dosages of additive Gaussian noise. The denoising performance of the filter, however, is known to degrade quickly with the increase in noise level. Several adaptations of the filter have been proposed in the literature to address this shortcoming, but often at a substantial computational overhead. In this paper, we report a simple pre-processing step that can substantially improve the denoising performance of the bilateral filter, at almost no additional cost. The modified filter is designed to be robust at large noise levels, and often tends to perform poorly below a certain noise threshold. To get the best of the original and the modified filter, we propose to combine them in a weighted fashion, where the weights are chosen to minimize (a surrogate of) the oracle mean-squared-error (MSE). The optimally-weighted filter is thus guaranteed to perform better than either of the component filters in terms of the MSE, at all noise levels. We also provide a fast algorithm for the weighted filtering. Visual and quantitative denoising results on standard test images are reported which demonstrate that the improvement over the original filter is significant both visually and in terms of PSNR. Moreover, the denoising performance of the optimally-weighted bilateral filter is competitive with the computation-intensive non-local means filter.

IMAGE DENOISING IN MULTIPLICATIVE NOISE

We address the problem of denoising images corrupted by multiplicative noise. The noise is assumed to follow a Gamma distribution. Compared with additive noise distortion, the effect of multiplicative noise on the visual quality of images is quite severe. We consider the mean-square error (MSE) cost function and derive an expression for an unbiased estimate of the MSE. The resulting multiplicative noise unbiased risk estimator is referred to as MURE. The denoising operation is performed in the wavelet domain by considering the image-domain MURE. The parameters of the denoising function (typically, a shrinkage of wavelet coefficients) are optimized for by minimizing MURE. We show that MURE is accurate and close to the oracle MSE. This makes MURE-based image denoising reliable and on par with oracle-MSE-based estimates. Analogous to the other popular risk estimation approaches developed for additive, Poisson, and chi-squared noise degradations, the proposed approach does not assume any prior on the underlying noise-free image. We report denoising results for various noise levels and show that the quality of denoising obtained is on par with the oracle result and better than that obtained using some state-of-the-art denoisers.

FAST AND ACCURATE BILATERAL FILTERING USING GAUSS-POLYNOMIAL DECOMPOSITION

The bilateral filter is a versatile non-linear filter that has found diverse applications in image processing, computer vision, computer graphics, and computational photography. A common form of the filter is the Gaussian bilateral filter in which both the spatial and range kernels are Gaussian. A direct implementation of this filter requires O(sigma(2)) operations per pixel, where sigma is the standard deviation of the spatial Gaussian. In this paper, we propose an accurate approximation algorithm that can cut down the computational complexity to O(1) per pixel for any arbitrary sigma (constant-time implementation). This is based on the observation that the range kernel operates via the translations of a fixed Gaussian over the range space, and that these translated Gaussians can be accurately approximated using the so-called Gauss-polynomials. The overall algorithm emerging from this approximation involves a series of spatial Gaussian filtering, which can be efficiently implemented (in parallel) using separability and recursion. We present some preliminary results to demonstrate that the proposed algorithm compares favorably with some of the existing fast algorithms in terms of speed and accuracy.

CROWD FLOW SEGMENTATION IN COMPRESSED DOMAIN USING CRF

Crowd flow segmentation is an important step in many video surveillance tasks. In this work, we propose an algorithm for segmenting flows in H.264 compressed videos in a completely unsupervised manner. Our algorithm works on motion vectors which can be obtained by partially decoding the compressed video without extracting any additional features. Our approach is based on modelling the motion vector field as a Conditional Random Field (CRF) and obtaining oriented motion segments by finding the optimal labelling which minimises the global energy of CRF. These oriented motion segments are recursively merged based on gradient across their boundaries to obtain the final flow segments. This work in compressed domain can be easily extended to pixel domain by substituting motion vectors with motion based features like optical flow. The proposed algorithm is experimentally evaluated on a standard crowd flow dataset and its superior performance in both accuracy and computational time are demonstrated through quantitative results.

SALIENT OBJECT DETECTION VIA OBJECTNESS MEASURE

Salient object detection has become an important task in many image processing applications. The existing approaches exploit background prior and contrast prior to attain state of the art results. In this paper, instead of using background cues, we estimate the foreground regions in an image using objectness proposals and utilize it to obtain smooth and accurate saliency maps. We propose a novel saliency measure called `foreground connectivity' which determines how tightly a pixel or a region is connected to the estimated foreground. We use the values assigned by this measure as foreground weights and integrate these in an optimization framework to obtain the final saliency maps. We extensively evaluate the proposed approach on two benchmark databases and demonstrate that the results obtained are better than the existing state of the art approaches.