Implementation of throughput enhancing client-AP association scheme On a WLAN controller

In a typical enterprise WLAN, a station has a choice of multiple access points to associate with. The default association policy is based on metrics such as Re-ceived Signal Strength(RSS), and “link quality” to choose a particular access point among many. Such an approach can lead to unequal load sharing and diminished system performance. We consider the RAT (Rate And Throughput) policy [1] which leads to better system performance. The RAT policy has been implemented on home-grown centralized WLAN controller, ADWISER [2] and we demonstrate that the RAT policy indeed provides a better system performance.

Using intra-flock association patterns to understand why birds participate in mixed-species foraging flocks in terrestrial habitats

Bird species are hypothesized to join mixed-species flocks (flocks hereon) either for direct foraging or anti-predation-related benefits. In this study, conducted in a tropical evergreen forest in the Western Ghats of India, we used intra-flock association patterns to generate a community-wide assessment of flocking benefits for different species. We assumed that individuals needed to be physically proximate to particular heterospecific individuals within flocks to obtain any direct foraging benefit (flushed prey, kleptoparasitism, copying foraging locations). Alternatively, for anti-predation benefits, physical proximity to particular heterospecifics is not required, i.e. just being in the flock vicinity can suffice. Therefore, we used choice of locations within flocks to infer whether individual species are obtaining direct foraging or anti-predation benefits. A small subset of the bird community (5/29 species), composed of all members of the sallying guild, showed non-random physical proximity to heterospecifics within flocks. All preferred associates were from non-sallying guilds, suggesting that the sallying species were likely obtaining direct foraging benefits either in the form of flushed or kleptoparasitized prey. The majority of the species (24/29) chose locations randomly with respect to heterospecifics within flocks and, thus, were likely obtaining antipredation benefits. In summary, our study indicates that direct foraging benefits are important for only a small proportion of species in flocks and that predation is likely to be the main driver of flocking for most participants. Our findings apart, our study provides methodological advances that might be useful in understanding asymmetric interactions in social groups of single and multiple species.

SPATIO-TEMPORAL DYNAMICS ALONG THE TERRAIN GRADIENT OF DIVERSE LANDSCAPE

Land use (LU) land cover (LC) information at a temporal scale illustrates the physical coverage of the Earth's terrestrial surface according to its use and provides the intricate information for effective planning and management activities. LULC changes are stated as local and location specific, collectively they act as drivers of global environmental changes. Understanding and predicting the impact of LULC change processes requires long term historical restorations and projecting into the future of land cover changes at regional to global scales. The present study aims at quantifying spatio temporal landscape dynamics along the gradient of varying terrains presented in the landscape by multi-data approach (MDA). MDA incorporates multi temporal satellite imagery with demographic data and other additional relevant data sets. The gradient covers three different types of topographic features, planes; hilly terrain and coastal region to account the significant role of elevation in land cover change. The seasonality is another aspect to be considered in the vegetation dominated landscapes; variations are accounted using multi seasonal data. Spatial patterns of the various patches are identified and analysed using landscape metrics to understand the forest fragmentation. The prediction of likely changes in 2020 through scenario analysis has been done to account for the changes, considering the present growth rates and due to the proposed developmental projects. This work summarizes recent estimates on changes in cropland, agricultural intensification, deforestation, pasture expansion, and urbanization as the causal factors for LULC change.

Temporal variability of forest communities: empirical estimates of population change in 4000 tree species

Long-term surveys of entire communities of species are needed to measure fluctuations in natural populations and elucidate the mechanisms driving population dynamics and community assembly. We analysed changes in abundance of over 4000 tree species in 12 forests across the world over periods of 6-28years. Abundance fluctuations in all forests are large and consistent with population dynamics models in which temporal environmental variance plays a central role. At some sites we identify clear environmental drivers, such as fire and drought, that could underlie these patterns, but at other sites there is a need for further research to identify drivers. In addition, cross-site comparisons showed that abundance fluctuations were smaller at species-rich sites, consistent with the idea that stable environmental conditions promote higher diversity. Much community ecology theory emphasises demographic variance and niche stabilisation; we encourage the development of theory in which temporal environmental variance plays a central role.

Multi-Temporal Satellite Image Analysis Using Gene Expression Programming

This paper discusses an approach for river mapping and flood evaluation to aid multi-temporal time series analysis of satellite images utilizing pixel spectral information for image classification and region-based segmentation to extract water covered region. Analysis of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images is applied in two stages: before flood and during flood. For these images the extraction of water region utilizes spectral information for image classification and spatial information for image segmentation. Multi-temporal MODIS images from ``normal'' (non-flood) and flood time-periods are processed in two steps. In the first step, image classifiers such as artificial neural networks and gene expression programming to separate the image pixels into water and non-water groups based on their spectral features. The classified image is then segmented using spatial features of the water pixels to remove the misclassified water region. From the results obtained, we evaluate the performance of the method and conclude that the use of image classification and region-based segmentation is an accurate and reliable for the extraction of water-covered region.

Approximation of Spatio-Temporal Random Processes Using Tensor Decomposition

A new representation of spatio-temporal random processes is proposed in this work. In practical applications, such processes are used to model velocity fields, temperature distributions, response of vibrating systems, to name a few. Finding an efficient representation for any random process leads to encapsulation of information which makes it more convenient for a practical implementations, for instance, in a computational mechanics problem. For a single-parameter process such as spatial or temporal process, the eigenvalue decomposition of the covariance matrix leads to the well-known Karhunen-Loeve (KL) decomposition. However, for multiparameter processes such as a spatio-temporal process, the covariance function itself can be defined in multiple ways. Here the process is assumed to be measured at a finite set of spatial locations and a finite number of time instants. Then the spatial covariance matrix at different time instants are considered to define the covariance of the process. This set of square, symmetric, positive semi-definite matrices is then represented as a third-order tensor. A suitable decomposition of this tensor can identify the dominant components of the process, and these components are then used to define a closed-form representation of the process. The procedure is analogous to the KL decomposition for a single-parameter process, however, the decompositions and interpretations vary significantly. The tensor decompositions are successfully applied on (i) a heat conduction problem, (ii) a vibration problem, and (iii) a covariance function taken from the literature that was fitted to model a measured wind velocity data. It is observed that the proposed representation provides an efficient approximation to some processes. Furthermore, a comparison with KL decomposition showed that the proposed method is computationally cheaper than the KL, both in terms of computer memory and execution time.

Non-polio enterovirus association with persistent diarrhea in children as revealed by a follow-up study of an Indian cohort during the first two years of life

Background: We recently reported significant association of non-polio enteroviruses (NPEVs) with acute diarrhea in children. Persistent diarrhea (PD) remains a major cause of morbidity and mortality in infants below two years of age in developing countries. Understanding age-dependent frequency and duration of NPEV infections is important to determine their association with persistent diarrhea and disease burden. Objectives: A cohort of 140 infants was followed for 6 months to 2 years of age to determine the frequency, duration, and association with PD of NPEV infections in comparison with rotavirus and other agents. Study design: Stool samples were collected every 14 days, and diarrheal episodes and their duration were recorded. Enteroviruses were characterized by RT-PCR and VP1 gene sequence analysis, rotavirus by electropherotyping, and other agents by PCR. Results: Of 4545 samples, negative for oral polio vaccine strains, 3907 (85.96%) and 638 (14.04%) were NPEV-negative and NPEV-positive, respectively, representing 403 (8.87%) infection episodes. About 68% of NPEV infections occurred during the first year with every child having at least one episode lasting between four days and four months. Approximately 38% and 22% of total diarrheal episodes were positive for NPEV and RV, respectively. While about 18% of NPEV infection episodes were associated with diarrhea, 6% being persistent, 13% of total diarrheal episodes were persistent involving infections by monotype NPEV strains or sequential infections by multiple strains and other agents. Conclusions: This is the first report revealing NPEVs as the single most frequently and persistently detected viral pathogen in every PD episode. (C) 2014 Elsevier B.V. All rights reserved.

Estimation of voice-onset time in continuous speech using temporal measures

This paper proposes an automatic acoustic-phonetic method for estimating voice-onset time of stops. This method requires neither transcription of the utterance nor training of a classifier. It makes use of the plosion index for the automatic detection of burst onsets of stops. Having detected the burst onset, the onset of the voicing following the burst is detected using the epochal information and a temporal measure named the maximum weighted inner product. For validation, several experiments are carried out on the entire TIMIT database and two of the CMU Arctic corpora. The performance of the proposed method compares well with three state-of-the-art techniques. (C) 2014 Acoustical Society of America

VIRTUAL VIEW SYNTHESIS BY NON-LOCAL MEANS FILTERING USING TEMPORAL DATA

A novel algorithm for Virtual View Synthesis based on Non-Local Means Filtering is presented in this paper. Apart from using the video frames from the nearby cameras and the corresponding per-pixel depth map, this algorithm also makes use of the previously synthesized frame. Simple and efficient, the algorithm can synthesize video at any given virtual viewpoint at a faster rate. In the process, the quality of the synthesized frame is not compromised. Experimental results prove the above mentioned claim. The subjective and objective quality of the synthesized frames are comparable to the existing algorithms.

Wind speed prediction using spatio-temporal covariance

High wind poses a number of hazards in different areas such as structural safety, aviation, and wind energy-where low wind speed is also a concern, pollutant transport, to name a few. Therefore, usage of a good prediction tool for wind speed is necessary in these areas. Like many other natural processes, behavior of wind is also associated with considerable uncertainties stemming from different sources. Therefore, to develop a reliable prediction tool for wind speed, these uncertainties should be taken into account. In this work, we propose a probabilistic framework for prediction of wind speed from measured spatio-temporal data. The framework is based on decompositions of spatio-temporal covariance and simulation using these decompositions. A novel simulation method based on a tensor decomposition is used here in this context. The proposed framework is composed of a set of four modules, and the modules have flexibility to accommodate further modifications. This framework is applied on measured data on wind speed in Ireland. Both short-and long-term predictions are addressed.

Association Rule Sharing Model for Privacy Preservation and Collaborative Data Mining Efficiency

The disclosure of information and its misuse in Privacy Preserving Data Mining (PPDM) systems is a concern to the parties involved. In PPDM systems data is available amongst multiple parties collaborating to achieve cumulative mining accuracy. The vertically partitioned data available with the parties involved cannot provide accurate mining results when compared to the collaborative mining results. To overcome the privacy issue in data disclosure this paper describes a Key Distribution-Less Privacy Preserving Data Mining (KDLPPDM) system in which the publication of local association rules generated by the parties is published. The association rules are securely combined to form the combined rule set using the Commutative RSA algorithm. The combined rule sets established are used to classify or mine the data. The results discussed in this paper compare the accuracy of the rules generated using the C4. 5 based KDLPPDM system and the CS. 0 based KDLPPDM system using receiver operating characteristics curves (ROC).

Spatio-temporal correlations in aqueous systems: computational studies of static and dynamic heterogeneity by 2D-IR spectroscopy

Local heterogeneity is ubiquitous in natural aqueous systems. It can be caused locally by external biomolecular subsystems like proteins, DNA, micelles and reverse micelles, nanoscopic materials etc., but can also be intrinsic to the thermodynamic nature of the aqueous solution itself (like binary mixtures or at the gas-liquid interface). The altered dynamics of water in the presence of such diverse surfaces has attracted considerable attention in recent years. As these interfaces are quite narrow, only a few molecular layers thick, they are hard to study by conventional methods. The recent development of two dimensional infra-red (2D-IR) spectroscopy allows us to estimate length and time scales of such dynamics fairly accurately. In this work, we present a series of interesting studies employing two dimensional infra-red spectroscopy (2D-IR) to investigate (i) the heterogeneous dynamics of water inside reverse micelles of varying sizes, (ii) supercritical water near the Widom line that is known to exhibit pronounced density fluctuations and also study (iii) the collective and local polarization fluctuation of water molecules in the presence of several different proteins. The spatio-temporal correlation of confined water molecules inside reverse micelles of varying sizes is well captured through the spectral diffusion of corresponding 2D-IR spectra. In the case of supercritical water also, we observe a strong signature of dynamic heterogeneity from the elongated nature of the 2D-IR spectra. In this case the relaxation is ultrafast. We find remarkable agreement between the different tools employed to study the relaxation of density heterogeneity. For aqueous protein solutions, we find that the calculated dielectric constant of the respective systems unanimously shows a noticeable increment compared to that of neat water. However, the `effective' dielectric constant for successive layers shows significant variation, with the layer adjacent to the protein having a much lower value. Relaxation is also slowest at the surface. We find that the dielectric constant achieves the bulk value at distances more than 3 nm from the surface of the protein.

The Self-Association of Graphane Is Driven by London Dispersion and Enhanced Orbital Interactions

We investigated the nature of the cohesive energy between graphane sheets via multiple CH center dot center dot center dot HC interactions, using density functional theory (DFT) including dispersion correction (Grimmes D3 approach) computations of n]graphane sigma dimers (n = 6-73). For comparison, we also evaluated the binding between graphene sheets that display prototypical pi/pi interactions. The results were analyzed using the block-localized wave function (BLW) method, which is a variant of ab initio valence bond (VB) theory. BLW interprets the intermolecular interactions in terms of frozen interaction energy (Delta E-F) composed of electrostatic and Pauli repulsion interactions, polarization (Delta E-pol), charge-transfer interaction (Delta E-CT), and dispersion effects (Delta E-disp). The BLW analysis reveals that the cohesive energy between graphane sheets is dominated by two stabilizing effects, namely intermolecular London dispersion and two-way charge transfer energy due to the sigma CH -> sigma*(HC) interactions. The shift of the electron density around the nonpolar covalent C-H bonds involved in the intermolecular interaction decreases the C-H bond lengths uniformly by 0.001 angstrom. The Delta E-CT term, which accounts for similar to 15% of the total binding energy, results in the accumulation of electron density in the interface area between two layers. This accumulated electron density thus acts as an electronic glue for the graphane layers and constitutes an important driving force in the self-association and stability of graphane under ambient conditions. Similarly, the double faced adhesive tape style of charge transfer interactions was also observed among graphene sheets in which it accounts for similar to 18% of the total binding energy. The binding energy between graphane sheets is additive and can be expressed as a sum of CH center dot center dot center dot HC interactions, or as a function of the number of C-H bonds.