Mobile service oriented architectures for NN-queries

The ever-increasing number of mobile device users has also raised the users’ expectation of mobile services accordingly. This phenomenon has given pressures to the mobile service providers to improve their services in order to stay competitive in the market. The service oriented approach is seen to be a promising scheme for mobile services. This paper presents mobile service oriented architectures for Nearest-Neighbor (NN) queries that are classified into five categories, namely (i) intermittent query mobile services, (ii) continuous query mobile services, (iii) context-aware mobile services, (iv) continuous moving object query mobile services, and (v) data broadcast mobile services. These services incorporate query, location and context-aware services, ontological context model, and broadcast. The proposed architectures are concerned with mobile services for clients on the move requesting services based on their current location, which is arguably the most important feature in a wireless environment. Furthermore, we also discuss the Quality-of-Service (QoS) requirement for mobile services in which request latency time is one of the most important parameters to consider. Some analytical models for query latency measurement are presented and the results are compared with the simulation experiments.     

Characterizing the cross-sectional geometry of thin,non-cylindrical,twisted fibres (spider silk)

Quantitative tensile property evaluation of fibres requires accurate cross-sectional area measurement at a location close to the point of failure. Laser diffraction was evaluated as a non-destructive technique for characterizing the cross-sectional geometry of translucent, non-cylindrical, and/or twisted fibres with thicknesses in the range 2–5 m. Forcibly silked major ampullate fibres from Nephila clavipes spiders were used as specimens. Scanning electron microscopy was used to calibrate the extent to which laser diffraction over- or under-estimates fibre diameter. For the purpose of area measurement, elliptical or oval cross-sections can be treated as though they were circular. We demonstrate mathematically that the area can be obtained to within a few per cent of the true value, if (a) the circle is assigned an equivalent diameter equal to the average of at least four measurements of apparent diameter, (b) the apparent diameter measurements are taken at equal intervals of fibre rotation through a 180° range, and (c) the axial ratio of the cross-section is less than 1.5. The extent to which a non-cylindrical fibre is twisted can be deduced from the periodicity of bright and dark regions that alternate along the length of the fibre in reflected light. Values of cross-sectional ellipticity and area measured from a twisted fibre were smaller than the corresponding values obtained from a twist-free fibre. The apparent diameter of twist-free major ampullate fibre was found to be highly variable-by as much as ±20% relative to the mean within a 0.6 mm length. Therefore, local measurements of area, rather than a value derived from fibre denier, should be used in tensile property evaluation of this material.     

Energy and Trust Management Framework for MANET using Clustering Algorithm

In General, Mobile Ad-Hoc Network (MANET) has limited energy resources, and it cannot recharge itself. This research goal focuses on building a power management scheme that saves energy in the MANET. Due to power instability, there is a chance that cluster heads fail and function incorrectly in cluster-based routing. As a result, instability occurs with the cluster heads while collecting data and communicating with others effectively. This work focuses on detecting the unstable cluster heads, which are replaced by other nodes implementing the envisaged self-configurable cluster mechanism. A self-configurable cluster mechanism with a k-means protocol approach is proposed to designate cluster heads effectively. The proposed k-means procedure is based on periodic irregular cluster head rotations or altering the number of clusters. We also propose a trust management mechanism in this research to detect and avoid MANET vulnerabilities. Because of the continuously changing topology and limited resources (power, bandwidth, computing), the trust management algorithm should only use local data. Consequently, compared to traditional protocols, the proposed approach with the k-means procedure and its experimental results show lower power usage and provide an optimal system for trust management.

     

Improved authentication and computation of medical data transmission in the secure IoT using hyperelliptic curve cryptography

The Journal of Supercomputing - Data transmission is a great challenge in any network environment. However, medical data collected from IoT devices need to be transmitted at high speed to ensure...     

Serum from diabetic BB/W rats enhances calcium currents in primary sensory neurons

We examined the hypothesis that exposure of nondiabetic rat dorsal root ganglion (DRG) neurons to sera from diabetic BB/W rats would produce an increase in calcium currents associated with impaired regulation of the inhibitory G protein-calcium channel complex. Acutely dissociated rat DRGs were incubated for 18-24 h in medium supplemented with sera (10% vol/vol) from either diabetic rats with neuropathy or age-matched, nondiabetic controls. Exposure of DRG neurons to sera from diabetic BB/W rats resulted in a surface membrane immunofluorescence pattern when treated with an anti-rat light-chain antibody that was not observed in neurons exposed to control sera. Calcium current density (IDCa) was assessed with the use of the whole cell variation of the patch-clamp technique. IDCa in neurons exposed to diabetic sera was significantly increased compared with neurons exposed to control sera. Guanine nucleotide-binding (G) protein regulation of calcium channel function was examined with the use of a two-pulse "facilitation" or IDCa enhancement protocol in the presence of activators [guanosine 5'-O-(3-thiotriphosphate) (GTP gamma S)] or antagonists [guanosine 5'-O-(2-thiodiphosphate) (GDP beta S) and pertussis toxin (PTX)] of G protein function. Facilitation was significantly decreased in neurons exposed to diabetic sera. Intracellular diffusion of neurons with GDP beta s blocked facilitation, whereas dialysis with GTP gamma s increased facilitation to a similar magnitude in neurons exposed to either diabetic or control sera. Treatment with PTX resulted in a significant increase in IDCa and approximately 50% decrease in facilitation in neurons treated with control sera but no significant changes in neurons exposed to diabetic sera. We conclude that serum from diabetic BB/W rats with neuropathy contains an autoimmune immunoglobulin that impairs regulation of the inhibitory G protein-calcium channel complex, resulting in enhanced calcium influx. Regulation of the inhibitory G protein-calcium channel complex involves PTX-sensitive and -insensitive G proteins.     

Scheduling on Unrelated Machines under Tree-Like Precedence Constraints

We present polylogarithmic approximations for the R|prec|C _max and R|prec|∑ _j w _j C _j problems, when the precedence constraints are “treelike”—i.e., when the undirected graph underlying the precedences is a forest. These are the first non-trivial generalizations of the job shop scheduling problem to scheduling with precedence constraints that are not just chains. These are also the first non-trivial results for the weighted completion time objective on unrelated machines with precedence constraints of any kind. We obtain improved bounds for the weighted completion time and flow time for the case of chains with restricted assignment—this generalizes the job shop problem to these objective functions. We use the same lower bound of “congestion + dilation”, as in other job shop scheduling approaches (e.g. Shmoys, Stein and Wein, SIAM J. Comput. 23, 617–632, 1994). The first step in our algorithm for the R|prec|C _max problem with treelike precedences involves using the algorithm of Lenstra, Shmoys and Tardos to obtain a processor assignment with the congestion + dilation value within a constant factor of the optimal. We then show how to generalize the random-delays technique of Leighton, Maggs and Rao to the case of trees. For the special case of chains, we show a dependent rounding technique which leads to a bicriteria approximation algorithm for minimizing the flow time, a notoriously hard objective function. A preliminary version of this paper appeared in the Proc. International Workshop on Approximation Algorithms for Combinatorial Optimization Problems (APPROX), pages 146–157, 2005. V.S. Anil Kumar supported in part by NSF Award CNS-0626964. Part of this work was done while at the Los Alamos National Laboratory, and supported in part by the Department of Energy under Contract W-7405-ENG-36. M.V. Marathe supported in part by NSF Award CNS-0626964. Part of this work was done while at the Los Alamos National Laboratory, and supported in part by the Department of Energy under Contract W-7405-ENG-36. Part of this work by S. Parthasarathy was done while at the Department of Computer Science, University of Maryland, College Park, MD 20742, and in part while visiting the Los Alamos National Laboratory. Research supported in part by NSF Award CCR-0208005 and NSF ITR Award CNS-0426683. Research of A. Srinivasan supported in part by NSF Award CCR-0208005, NSF ITR Award CNS-0426683, and NSF Award CNS-0626636.     

On neighbor discovery in cognitive radio networks

A cognitive radio node is a radio device capable of operating over multiple channels. As a result, a network consisting of one or more cognitive radio nodes can adapt to varying channel availability in its geographical region by dynamically changing the channel (or channels) nodes are using for communication.     

Parameter-uniform hybrid numerical scheme for time-dependent convection-dominated initial-boundary-value problems

In this paper, we propose a numerical scheme which is almost second-order spatial accurate for a one-dimensional singularly perturbed parabolic convection-diffusion problem exhibiting a regular boundary layer. The proposed numerical scheme consists of classical backward-Euler method for the time discretization and a hybrid finite difference scheme for the spatial discretization. We analyze the scheme on a piecewise-uniform Shishkin mesh for the spatial discretization to establish uniform convergence with respect to the perturbation parameter. Numerical results are presented to validate the theoretical results.     

ILP-assisted de novo drug design

The accurate and early detection of epileptic seizures in continuous electroencephalographic (EEG) data has a growing role in the management of patients with epilepsy. Early detection allows for therapy to be delivered at the start of seizures and for caregivers to be notified promptly about potentially debilitating events. The challenge to detecting epileptic seizures, however, is that seizure morphologies exhibit considerable inter-patient and intra-patient variability. While recent work has looked at addressing the issue of variations across different patients (inter-patient variability) and described patient-specific methodologies for seizure detection, there are no examples of systems that can simultaneously address the challenges of inter-patient and intra-patient variations in seizure morphology. In our study, we address this complete goal and describe a multi-task learning approach that trains a classifier to perform well across many kinds of seizures rather than potentially overfitting to the most common seizure types. Our approach increases the generalizability of seizure detection systems and improves the tradeoff between latency and sensitivity versus false positive rates. When compared against the standard approach on the CHB–MIT multi-channel scalp EEG data, our proposed method improved discrimination between seizure and non-seizure EEG for almost 83 % of the patients while reducing false positives on nearly 70 % of the patients studied.     

Richardson extrapolation technique for singularly perturbed parabolic convection–diffusion problems

This paper deals with the study of a post-processing technique for one-dimensional singularly perturbed parabolic convection–diffusion problems exhibiting a regular boundary layer. For discretizing the time derivative, we use the classical backward-Euler method and for the spatial discretization the simple upwind scheme is used on a piecewise-uniform Shishkin mesh. We show that the use of Richardson extrapolation technique improves the ε-uniform accuracy of simple upwinding in the discrete supremum norm from O (N ⁻¹ ln N + Δt) to O (N ⁻² ln² N + Δt ²), where N is the number of mesh-intervals in the spatial direction and Δt is the step size in the temporal direction. The theoretical result is also verified computationally by applying the proposed technique on two test examples.