Throughput analysis of primary and secondary networks in a shared IEEE 802.11 system

In this paper, we analyze the coexistence of a primary and a secondary (cognitive) network when both networks use the IEEE 802.11 based distributed coordination function for medium access control. Specifically, we consider the problem of channel capture by a secondary network that uses spectrum sensing to determine the availability of the channel, and its impact on the primary throughput. We integrate the notion of transmission slots in Bianchi's Markov model with the physical time slots, to derive the transmission probability of the secondary network as a function of its scan duration. This is used to obtain analytical expressions for the throughput achievable by the primary and secondary networks. Our analysis considers both saturated and unsaturated networks. By performing a numerical search, the secondary network parameters are selected to maximize its throughput for a given level of protection of the primary network throughput. The theoretical expressions are validated using extensive simulations carried out in the Network Simulator 2. Our results provide critical insights into the performance and robustness of different schemes for medium access by the secondary network. In particular, we find that the channel captures by the secondary network does not significantly impact the primary throughput, and that simply increasing the secondary contention window size is only marginally inferior to silent-period based methods in terms of its throughput performance.

Calibration of etched fiber bragg grating sensor arrays for measurement of molecular surface adsorption

Etched Fiber Bragg Grating (EFBG) sensors are attractive from the point of the inherently high multiplexing ability of fiber based sensors. However, the strong dependence of the sensitivity of EFBG sensors on the fiber diameter requires robust methods for calibration when used for distributed sensing in a large array format. Using experimental data and numerical modelling, we show that knowledge of the wavelength shift during the etch process is necessary for high-fidelity calibration of EFBG arrays. However as this approach requires the monitoring of every element of the sensor array during etching, we also proposed and demonstrated a calibration scheme using data from bulk refractometry measurements conducted post-fabrication without needing any information about the etching process. Although this approach is not as precise as the first one, it may be more practical as there is no requirement to monitor each element of the sensor array. We were able to calibrate the response of the sensors to within 3% with the approach using information acquired during etching and to within 5% using the post-fabrication bulk refractometry approach in spite of the sensitivities of the array element differing by more than a factor of 4. These two approaches present a tradeoff between accuracy and practicality.

Guided Ultrasonic Wave Propagation through Inaccessible Damage in a Folded Plate using Sensor-Actuator Network

Rapid diagnostics and virtual imaging of damages in complex structures like folded plate can help reduce the inspection time for guided wave based NDE and integrated SHM. Folded plate or box structure is one of the major structural components for increasing the structural strength. Damage in the folded plate, mostly in the form of surface breaking cracks in the inaccessible zone is a usual problem in aerospace structures. One side of the folded plate is attached (either riveted or bonded) to adjacent structure which is not accessible for immediate inspection. The sensor-actuator network in the form of a circular array is placed on the accessible side of the folded plate. In the present work, a circular array is employed for scanning the entire folded plate type structure for damage diagnosis and wave field visualization of entire structural panel. The method employs guided wave with relatively low frequency bandwidth of 100-300 kHz. Change in the response signal with respect to a baseline signal is used to construct a quantitative relationship with damage size parameters. Detecting damage in the folded plate by using this technique has significant potential for off-line and on-line SHM technologies. By employing this technique, surface breaking cracks on inaccessible face of the folded plate are detected without disassembly of structure in a realistic environment.

On Uniform Approximate Solutions in Bending of Symmetric Laminated Plates

A layer-wise theory with the analysis of face ply independent of lamination is used in the bending of symmetric laminates with anisotropic plies. More realistic and practical edge conditions as in Kirchhoff's theory are considered. An iterative procedure based on point-wise equilibrium equations is adapted. The necessity of a solution of an auxiliary problem in the interior plies is explained and used in the generation of proper sequence of two dimensional problems. Displacements are expanded in terms of polynomials in thickness coordinate such that continuity of transverse stresses across interfaces is assured. Solution of a fourth order system of a supplementary problem in the face ply is necessary to ensure the continuity of in-plane displacements across interfaces and to rectify inadequacies of these polynomial expansions in the interior distribution of approximate solutions. Vertical deflection does not play any role in obtaining all six stress components and two in-plane displacements. In overcoming lacuna in Kirchhoff's theory, widely used first order shear deformation theory and other sixth and higher order theories based on energy principles at laminate level in smeared laminate theories and at ply level in layer-wise theories are not useful in the generation of a proper sequence of 2-D problems converging to 3-D problems. Relevance of present analysis is demonstrated through solutions in a simple text book problem of simply supported square plate under doubly sinusoidal load.

Extension of TSVM to multi-class and hierarchical text classification problems With general losses

Transductive SVM (TSVM) is a well known semi-supervised large margin learning method for binary text classification. In this paper we extend this method to multi-class and hierarchical classification problems. We point out that the determination of labels of unlabeled examples with fixed classifier weights is a linear programming problem. We devise an efficient technique for solving it. The method is applicable to general loss functions. We demonstrate the value of the new method using large margin loss on a number of multi-class and hierarchical classification datasets. For maxent loss we show empirically that our method is better than expectation regularization/constraint and posterior regularization methods, and competitive with the version of entropy regularization method which uses label constraints.

On the feasibility of network alignment for three-source three-destination Multiple Unicast networks with delays

A transform approach to network coding was in-troduced by Bavirisetti et al. (arXiv:1103.3882v3 [cs.IT]) as a tool to view wireline networks with delays as k-instantaneous networks (for some large k). When the local encoding kernels (LEKs) of the network are varied with every time block of length k >1, the network is said to use block time varying LEKs. In this work, we propose a Precoding Based Network Alignment (PBNA) scheme based on transform approach and block time varying LEKs for three-source three-destination multiple unicast network with delays (3-S3-D MUN-D). In a recent work, Menget al. (arXiv:1202.3405v1 [cs.IT]) reduced the infinite set of sufficient conditions for feasibility of PBNA in a three-source three-destination instantaneous multiple unicast network as given by Das et al. (arXiv:1008.0235v1 [cs.IT]) to a finite set and also showed that the conditions are necessary. We show that the conditions of Meng et al. are also necessary and sufficient conditions for feasibility of PBNA based on transform approach and block time varying LEKs for 3-S3-D MUN-D.

Polymer template-assisted microemulsion synthesis of large surface area, porous Li2MnO3 and its characterization as a positive electrode material of Li-ion cells

Lithium-rich manganese oxide (Li2MnO3) is prepared by reverse microemulsion method employing Pluronic acid (P123) as a soft template and studied as a positive electrode material. The as-prepared sample possesses good crystalline structure with a broadly distributed mesoporosity but low surface area. As expected, cyclic voltammetry and charge-discharge data indicate poor electrochemical activity. However, the sample gains surface area with narrowly distributed mesoporosity and also electrochemical activity after treating in 4 M H2SO4. A discharge capacity of about 160 mAh g(-1) is obtained. When the acid-treated sample is heated at 300 A degrees C, the resulting porous sample with a large surface area and dual porosity provides a discharge capacity of 240 mAh g(-1). The rate capability study suggests that the sample provides about 150 mAh g(-1) at a specific discharge current of 1.25 A g(-1). Although the cycling stability is poor, the high rate capability is attributed to porous nature of the material.

Performance analysis of beacon-less IEEE 802.15.4 multi-hop networks

We develop an approximate analytical technique for evaluating the performance of multi-hop networks based on beacon-less CSMA/CA as standardised in IEEE 802.15.4, a popular standard for wireless sensor networks. The network comprises sensor nodes, which generate measurement packets, and relay nodes which only forward packets. We consider a detailed stochastic process at each node, and analyse this process taking into account the interaction with neighbouring nodes via certain unknown variables (e.g., channel sensing rates, collision probabilities, etc.). By coupling these analyses of the various nodes, we obtain fixed point equations that can be solved numerically to obtain the unknown variables, thereby yielding approximations of time average performance measures, such as packet discard probabilities and average queueing delays. Different analyses arise for networks with no hidden nodes and networks with hidden nodes. We apply this approach to the performance analysis of tree networks rooted at a data sink. Finally, we provide a validation of our analysis technique against simulations.

Scalable sequential alternating proximal methods for sparse structural SVMs and CRFs

Structural Support Vector Machines (SSVMs) and Conditional Random Fields (CRFs) are popular discriminative methods used for classifying structured and complex objects like parse trees, image segments and part-of-speech tags. The datasets involved are very large dimensional, and the models designed using typical training algorithms for SSVMs and CRFs are non-sparse. This non-sparse nature of models results in slow inference. Thus, there is a need to devise new algorithms for sparse SSVM and CRF classifier design. Use of elastic net and L1-regularizer has already been explored for solving primal CRF and SSVM problems, respectively, to design sparse classifiers. In this work, we focus on dual elastic net regularized SSVM and CRF. By exploiting the weakly coupled structure of these convex programming problems, we propose a new sequential alternating proximal (SAP) algorithm to solve these dual problems. This algorithm works by sequentially visiting each training set example and solving a simple subproblem restricted to a small subset of variables associated with that example. Numerical experiments on various benchmark sequence labeling datasets demonstrate that the proposed algorithm scales well. Further, the classifiers designed are sparser than those designed by solving the respective primal problems and demonstrate comparable generalization performance. Thus, the proposed SAP algorithm is a useful alternative for sparse SSVM and CRF classifier design.

PMV model is insufficient to capture subjective thermal response from Indians

A controlled laboratory experiment was carried out on forty Indian male college students for evaluating the effect of indoor thermal environment on occupants' response and thermal comfort. During experiment, indoor temperature varied from 21 degrees C to 33 degrees C, and the variables like relative humidity, airflow, air temperature and radiant temperature were recorded along with subject's physiological parameters (skin (T-sk) and oral temperature (T-c)) and subjective thermal sensation responses (TSV). From T-sk and T-c, body temperature (T-b) was evaluated. Subjective Thermal Sensation Vote (TSV) was recorded using ASHRAE 7-point scale. In PMV model, Fanger's T-sk equation was used to accommodate adaptive response. Step-wise regression analysis result showed T-b was better predictor of TSV than T-sk and T-c. Regional skin temperature response, suppressed sweating without dipping, lower sweating threshold temperature and higher cutaneous threshold for sweating were observed as thermal adaptive responses. These adaptive responses cannot be considered in PMV model. To incorporate subjective adaptive response, mean skin temperature (T-sk) is considered in dry heat loss calculation. Along with these, PMV-model and other two methodologies are adopted to calculate PMV values and results are compared. However, recent literature is limited to measure the sweat rate in Indians and consideration of constant Ersw in PMV model needs to be corrected. Using measured T-sk in PMV model (Method(1)), thermal comfort zone corresponding to 0.5 <= PMV <= 0.5 was evaluated as (22.46-25.41) degrees C with neutral temperature of 23.91 degrees C, similarly while using TSV response, wider comfort zone was estimated as (23.25-26.32) degrees C with neutral temperature at 24.83 degrees C, which was further increased to with TSV-PPDnew, relation. It was observed that PMV-model overestimated the actual thermal response. Interestingly, these subjects were found to be less sensitive to hot but more sensitive to cold. A new TSV-PPD relation (PPDnew) was obtained from the population distribution of TSV response with an asymmetric distribution of hot-cold thermal sensation response from Indians. The calculations of human thermal stress according to steady state energy balance models used on PMV model seem to be inadequate to evaluate human thermal sensation of Indians. Relevance to industry: The purpose of this paper is to estimate thermal comfort zone and optimum temperature for Indians. It also highlights that PMV model seems to be inadequate to evaluate subjective thermal perception in Indians. These results can be used in feedback control of HVAC systems in residential and industrial buildings. (C) 2014 Elsevier B.V. All rights reserved.

Dense network of O-H ... O and C-H ... O interactions in the solid state structure of n-pentyl-2-chloro-2-deoxy-alpha-D-manno-sept 3-uloside

Single crystal X-ray structural analysis of a septanoside, namely, n-pentyl-2-chloro-2-deoxy sept-3-uloside (1) provides many finer details of the molecular structure, in addition to its preferred twist-chair conformation, namely, (TC3,4)-T-5,6 conformation. Structural analysis reveals a dense network of O-H...O, C-H...O and van der Waals interactions that stabilize interdigitized, planar bi-layer structure of the crystal lattice. (C) 2014 Elsevier Ltd. All rights reserved.

Fixed-orientation equilateral triangle matching of point sets

Given a point set P and a class C of geometric objects, G(C)(P) is a geometric graph with vertex set P such that any two vertices p and q are adjacent if and only if there is some C is an element of C containing both p and q but no other points from P. We study G(del)(P) graphs where del is the class of downward equilateral triangles (i.e., equilateral triangles with one of their sides parallel to the x-axis and the corner opposite to this side below that side). For point sets in general position, these graphs have been shown to be equivalent to half-Theta(6) graphs and TD-Delaunay graphs. The main result in our paper is that for point sets P in general position, G(del)(P) always contains a matching of size at least vertical bar P vertical bar-1/3] and this bound is tight. We also give some structural properties of G(star)(P) graphs, where is the class which contains both upward and downward equilateral triangles. We show that for point sets in general position, the block cut point graph of G(star)(P) is simply a path. Through the equivalence of G(star)(P) graphs with Theta(6) graphs, we also derive that any Theta(6) graph can have at most 5n-11 edges, for point sets in general position. (C) 2013 Elsevier B.V. All rights reserved.

Lineage delimitation and description of nine new species of bush frogs (Anura: Raorchestes, Rhacophoridae) from the Western Ghats Escarpment

Bush frogs of the genus Raorchestes are distributed mainly in the Western Ghats Escarpment of Peninsular India. The inventory of species in this genus is incomplete and there is ambiguity in the systematic status of species recognized by morphological criteria. To address the dual problem of taxon sampling and systematic uncertainty in bush frogs, we used a large-scale spatial sampling design, explicitly incorporating the geographic and ecological heterogeneity of the Western Ghats. We then used a hierarchical multi-criteria approach by combining mitochondrial phylogeny, genetic distance, geographic range, morphology and advertisement call to delimit bush frog lineages. Our analyses revealed the existence of a large number of new lineages with varying levels of genetic divergence. Here, we provide diagnoses and descriptions for nine lineages that exhibit divergence across multiple axes. The discovery of new lineages that exhibit high divergence across wide ranges of elevation and across the major massifs highlights the large gaps in historical sampling. These discoveries underscore the significance of addressing inadequate knowledge of species distribution, namely the ``Wallacean shortfall'', in addressing the problem of taxon sampling and unknown diversity in tropical hotspots. A biogeographically informed sampling and analytical approach was critical in detecting and delineating lineages in a consistent manner across the genus. Through increased taxon sampling, we were also able to discern a number of well-supported sub-clades that were either unresolved or absent in earlier phylogenetic reconstructions and identify a number of shallow divergent lineages which require further examination for assessment of their taxonomic status.

A Comparison of Machine Learning Techniques for Modeling River Flow Time Series: The Case of Upper Cauvery River Basin

Models of river flow time series are essential in efficient management of a river basin. It helps policy makers in developing efficient water utilization strategies to maximize the utility of scarce water resource. Time series analysis has been used extensively for modeling river flow data. The use of machine learning techniques such as support-vector regression and neural network models is gaining increasing popularity. In this paper we compare the performance of these techniques by applying it to a long-term time-series data of the inflows into the Krishnaraja Sagar reservoir (KRS) from three tributaries of the river Cauvery. In this study flow data over a period of 30 years from three different observation points established in upper Cauvery river sub-basin is analyzed to estimate their contribution to KRS. Specifically, ANN model uses a multi-layer feed forward network trained with a back-propagation algorithm and support vector regression with epsilon intensive-loss function is used. Auto-regressive moving average models are also applied to the same data. The performance of different techniques is compared using performance metrics such as root mean squared error (RMSE), correlation, normalized root mean squared error (NRMSE) and Nash-Sutcliffe Efficiency (NSE).

Emergency Handling in MICS based Body Area Network

Body Area Network, a new wireless networking paradigm, promises to revolutionize the healthcare applications. A number of tiny sensor nodes are strategically placed in and around the human body to obtain physiological information. The sensor nodes are connected to a coordinator or a data collector to form a Body Area Network. The tiny devices may sense physiological parameters of emergency in nature (e.g. abnormality in heart bit rate, increase of glucose level above the threshold etc.) that needs immediate attention of a physician. Due to ultra low power requirement of wireless body area network, most of the time, the coordinator and devices are expected to be in the dormant mode, categorically when network is not operational. This leads to an open question, how to handle and meet the QoS requirement of emergency data when network is not operational? Emergency handling becomes more challenging at the MAC layer, if the channel access related information is unknown to the device with emergency message. The aforementioned scenarios are very likely scenarios in a MICS (Medical Implant Communication Service, 402-405 MHz) based healthcare systems. This paper proposes a mechanism for timely and reliable transfer of emergency data in a MICS based Body Area Network. We validate our protocol design with simulation in a C++ framework. Our simulation results show that more than 99 p ercentage of the time emergency messages are reached at the coordinator with a delay of 400ms.