A method of fraud & intrusion detection for e-payment systems in mobile

The need for paying with mobile devices has urged the development of payment systems for mobile electronic commerce. In this paper we have considered two important abuses in electronic payments systems for detection. The fraud, which is an intentional deception accomplished to secure an unfair gain, and an intrusion which are any set of actions that attempt to compromise the integrity, confidentiality or availability of a resource. Most of the available fraud and intrusion detection systems for e-payments are specific to the systems where they have been incorporated. This paper proposes a generic model called as Activity-Event-Symptoms(AES) model for detecting fraud and intrusion attacks which appears during payment process in the mobile commerce environment. The AES model is designed to identify the symptoms of fraud and intrusions by observing various events/transactions occurs during mobile commerce activity. The symptoms identification is followed by computing the suspicion factors for event attributes, and the certainty factor for a fraud and intrusion is generated using these suspicion factors. We have tested the proposed system by conducting various case studies, on the in-house established mobile commerce environment over wired and wire-less networks test bed.

Nonlinear ensemble prediction of chaotic daily rainfall

The significance of treating rainfall as a chaotic system instead of a stochastic system for a better understanding of the underlying dynamics has been taken up by various studies recently. However, an important limitation of all these approaches is the dependence on a single method for identifying the chaotic nature and the parameters involved. Many of these approaches aim at only analyzing the chaotic nature and not its prediction. In the present study, an attempt is made to identify chaos using various techniques and prediction is also done by generating ensembles in order to quantify the uncertainty involved. Daily rainfall data of three regions with contrasting characteristics (mainly in the spatial area covered), Malaprabha, Mahanadi and All-India for the period 1955-2000 are used for the study. Auto-correlation and mutual information methods are used to determine the delay time for the phase space reconstruction. Optimum embedding dimension is determined using correlation dimension, false nearest neighbour algorithm and also nonlinear prediction methods. The low embedding dimensions obtained from these methods indicate the existence of low dimensional chaos in the three rainfall series. Correlation dimension method is done on th phase randomized and first derivative of the data series to check whether the saturation of the dimension is due to the inherent linear correlation structure or due to low dimensional dynamics. Positive Lyapunov exponents obtained prove the exponential divergence of the trajectories and hence the unpredictability. Surrogate data test is also done to further confirm the nonlinear structure of the rainfall series. A range of plausible parameters is used for generating an ensemble of predictions of rainfall for each year separately for the period 1996-2000 using the data till the preceding year. For analyzing the sensitiveness to initial conditions, predictions are done from two different months in a year viz., from the beginning of January and June. The reasonably good predictions obtained indicate the efficiency of the nonlinear prediction method for predicting the rainfall series. Also, the rank probability skill score and the rank histograms show that the ensembles generated are reliable with a good spread and skill. A comparison of results of the three regions indicates that although they are chaotic in nature, the spatial averaging over a large area can increase the dimension and improve the predictability, thus destroying the chaotic nature. (C) 2010 Elsevier Ltd. All rights reserved.

Action regulation across the adult lifespan (ARAL): A metatheory of work and aging

The goals of this article are to integrate action regulation theory (ART) with the lifespan developmental perspective and to outline tenets of a new metatheory of work and aging. The action regulation across the adult lifespan (ARAL) theory explains how workers influence, and are influenced by, their environment across different time spans. First, the basic concepts of ART are described, including the sequential and hierarchical structure of actions, complete tasks and actions, foci of action regulation, and the action-regulating mental model. Second, principles of the lifespan developmental perspective are delineated, including development as a lifelong and multidirectional process, the joint occurrence of gains and losses, intraindividual plasticity, historical embeddedness, and contextualism. Third, propositions of ARAL theory are derived by analyzing workers’ action regulation from a lifespan developmental perspective (i.e., effects of aging on action regulation), and by analyzing aging and development in the work context from an ART perspective (i.e., effects of action regulation on age-related changes in cognition and personality). Fourth, we develop further propositions to integrate ART with lifespan theories of motivation and socioemotional experience. Finally, we discuss implications for future research and practice based on ARAL theory.

The nucleus of Saccharomyces bayanus

The extra-vacuolar nucleus is visible in a small percentage of living cells from 72–96 hour wort cultures. The vacuoles show a luminous boundary under dark ground illumination. The details observed in living nuclei could be stained with haematoxylin after fixation in iodine-formaldehyde-acetic acid mixture. The Feulgen-negative nature of the vacuole and the limitation of the Feulgen-positive material to the area bounded by the nuclear membrane would imply that the ‘centrosome’ described by Lindegren and Rafalko (1950) is the real nucleus. The nucleus ofS. bayanus conforms in its structure to those of higher organisms.

Transcriptional switching in Escherichia coli during stress and starvation by modulation of Sigma 70 activity

During active growth of Escherichia coli, majority of the transcriptional activity is carried out by the housekeeping sigma factor (Sigma 70), whose association with core RNAP is generally favoured because of its higher intracellular level and higher affinity to core RNAP. In order to facilitate transcription by alternative sigma factors during nutrient starvation, the bacterial cell uses multiple strategies by which the transcriptional ability of Sigma 70 is diminished in a reversible manner. The facilitators of shifting the balance in favour of alternative sigma factors happen to be as diverse as a small molecule (p)ppGpp (represents ppGpp or pppGpp), proteins (DksA, Rsd) and a species of RNA (6S RNA). Although 6S RNA and (p)ppGpp were known in literature for a long time, their role in transcriptional switching has been understood only in recent years. With themelucidation of function of DksA, a new dimension has been added to the phenomenon of stringent response. As the final outcome of actions of (p)ppGpp, DksA, 6S RNA and Rsd is similar, there is a need to analyse hese mechanisms in a collective manner. We review the recent trends in understanding the regulation of Sigma 70 by (p)ppGpp, DksA, Rsd and 6S RNA and present a case for evolving a unified model of RNAP redistribution during starvation by modulation of Sigma 70 activity in E. coli.

Droplet Epitaxy of InN Quantum Dots on Si(111) by RF Plasma-Assisted Molecular Beam Epitaxy

InN quantum dots (QDs) were fabricated on Si(111) substrate by droplet epitaxy using an RF plasma-assisted MBE system. Variation of the growth parameters, such as growth temperature and deposition time, allowed us to control the characteristic size and density of the QDs. As the growth temperature was increased from 100 C to 300 degrees C, an enlargement of QD size and a drop in dot density were observed, which was led by the limitation of surface diffusion of adatoms with the limited thermal energy. Atomic force microscopy (AFM) and scanning electron microscopy (SEM) were used to assess the QDs size and density. The chemical bonding configurations of InN QDs were examined by X-ray photo-electron spectroscopy (XPS). Fourier transform infrared (FTIR) spectrum of the deposited InN QDs shows the presence of In-N bond. Temperature-dependent photoluminescence (PL) measurements showed that the emission peak energies of the InN QDs are sensitive to temperature and show a strong peak emission at 0.79 eV.

A LSQR-type method provides a computationally efficient automated optimal choice of regularization parameter in diffuse optical tomography

Purpose: Developing a computationally efficient automated method for the optimal choice of regularization parameter in diffuse optical tomography. Methods: The least-squares QR (LSQR)-type method that uses Lanczos bidiagonalization is known to be computationally efficient in performing the reconstruction procedure in diffuse optical tomography. The same is effectively deployed via an optimization procedure that uses the simplex method to find the optimal regularization parameter. The proposed LSQR-type method is compared with the traditional methods such as L-curve, generalized cross-validation (GCV), and recently proposed minimal residual method (MRM)-based choice of regularization parameter using numerical and experimental phantom data. Results: The results indicate that the proposed LSQR-type and MRM-based methods performance in terms of reconstructed image quality is similar and superior compared to L-curve and GCV-based methods. The proposed method computational complexity is at least five times lower compared to MRM-based method, making it an optimal technique. Conclusions: The LSQR-type method was able to overcome the inherent limitation of computationally expensive nature of MRM-based automated way finding the optimal regularization parameter in diffuse optical tomographic imaging, making this method more suitable to be deployed in real-time. (C) 2013 American Association of Physicists in Medicine. http://dx.doi.org/10.1118/1.4792459]

Study of dynamic behaviour of recession curves

Since Brutsaert and Neiber (1977), recession curves are widely used to analyse subsurface systems of river basins by expressing -dQ/dt as a function of Q, which typically take a power law form: -dQ/dt=kQ, where Q is the discharge at a basin outlet at time t. Traditionally recession flows are modelled by single reservoir models that assume a unique relationship between -dQ/dt and Q for a basin. However, recent observations indicate that -dQ/dt-Q relationship of a basin varies greatly across recession events, indicating the limitation of such models. In this study, the dynamic relationship between -dQ/dt and Q of a basin is investigated through the geomorphological recession flow model which models recession flows by considering the temporal evolution of its active drainage network (the part of the stream network of the basin draining water at time t). Two primary factors responsible for the dynamic relationship are identified: (i) degree of aquifer recharge (ii) spatial variation of rainfall. Degree of aquifer recharge, which is likely to be controlled by (effective) rainfall patterns, influences the power law coefficient, k. It is found that k has correlation with past average streamflow, which confirms the notion that dynamic -dQ/dt-Q relationship is caused by the degree of aquifer recharge. Spatial variation of rainfall is found to have control on both the exponent, , and the power law coefficient, k. It is noticed that that even with same and k, recession curves can be different, possibly due to their different (recession) peak values. This may also happen due to spatial variation of rainfall. Copyright (c) 2012 John Wiley & Sons, Ltd.

Raman Spectroscopic Study of Serum Components

Early diagnosis of disease is important, because therapeutic intervention is most successful before it spread to the subject. The best health screenings method could be the blood test because the blood contains thousands of bio-molecules coming as by-products from the diseased part of the organism and would be non-invasive approach. The major limitation of this approach is the very low concentrations of the analytes need to be detected. Raman spectroscopy has been proven as one of the cutting edge technique applied in the field of histology, cytology and clinical chemistry. The primary obstacle of Raman spectroscopy is the low signal intensities. One of the promising approaches to overcome that is surface enhanced Raman spectroscopy (SERS) which has opened novel opportunities for chemical and biomedical analytics. Albumin is one of the most abundant proteins in blood, produced by liver. The state of albumin in serum determines the health of the liver and kidney. Serum albumin helps to transport many small molecules such as fatty acids, bilirubin, calcium, drugs through the blood. In this study, SERS is being used for the quantification and to understand of binding mechanism serum albumin.

A non-resonant mass sensor to eliminate the ``missing mass'' effect during mass measurement of biological materials

Resonant sensors and crystal oscillators for mass detection need to be excited at very high natural frequencies (MHz). Use of such systems to measure mass of biological materials affects the accuracy of mass measurement due to their viscous and/or viscoelastic properties. The measurement limitation of such sensor system is the difficulty in accounting for the ``missing mass'' of the biological specimen in question. A sensor system has been developed in this work, to be operated in the stiffness controlled region at very low frequencies as compared to its fundamental natural frequency. The resulting reduction in the sensitivity due to non-resonant mode of operation of this sensor is compensated by the high resolution of the sensor. The mass of different aged drosophila melanogaster (fruit fly) is measured. The difference in its mass measurement during resonant mode of operation is also presented. That, viscosity effects do not affect the working of this non-resonant mass sensor is clearly established by direct comparison. (C) 2014 AIP Publishing LLC.

Toward a High-Resolution Monitoring of Continental Surface Water Extent and Dynamics, at Global Scale: from GIEMS (Global Inundation Extent from Multi-Satellites) to SWOT (Surface Water Ocean Topography)

Up to now, high-resolution mapping of surface water extent from satellites has only been available for a few regions, over limited time periods. The extension of the temporal and spatial coverage was difficult, due to the limitation of the remote sensing technique e.g., the interaction of the radiation with vegetation or cloud for visible observations or the temporal sampling with the synthetic aperture radar (SAR)]. The advantages and the limitations of the various satellite techniques are reviewed. The need to have a global and consistent estimate of the water surfaces over long time periods triggered the development of a multi-satellite methodology to obtain consistent surface water all over the globe, regardless of the environments. The Global Inundation Extent from Multi-satellites (GIEMS) combines the complementary strengths of satellite observations from the visible to the microwave, to produce a low-resolution monthly dataset () of surface water extent and dynamics. Downscaling algorithms are now developed and applied to GIEMS, using high-spatial-resolution information from visible, near-infrared, and synthetic aperture radar (SAR) satellite images, or from digital elevation models. Preliminary products are available down to 500-m spatial resolution. This work bridges the gaps and prepares for the future NASA/CNES Surface Water Ocean Topography (SWOT) mission to be launched in 2020. SWOT will delineate surface water extent estimates and their water storage with an unprecedented spatial resolution and accuracy, thanks to a SAR in an interferometry mode. When available, the SWOT data will be adopted to downscale GIEMS, to produce a long time series of water surfaces at global scale, consistent with the SWOT observations.

Pressure Controlled Self-Assembly of High Quality Three-Dimensional Colloidal Photonic Crystals

A concise pressure controlled isothermal heating vertical deposition (PCIHVD) method is developed, which provides an optimal growing condition with better stability and reproducibility for fabricating photonic crystals (PCs) without the limitation of colloidal sphere materials and sizes. High quality PCs are fabricated with PCIHVD from polystyrene spheres with diameters ranging from 200 nm to 1 mu m. The deep photonic band gap and steep photonic band edge of the samples are most favorable for realizing ultrafast optical devices, photonic chips, and communications. This method makes a meaningful advance in the quality and diversity of PCs and greatly promotes their wide applications.

An optimal theory for an expansion of flow quantities to capture the flow structures

An optimal theory on how database analysis to capture the flow structures has been developed in this paper, which include the POD method as its special case. By means of the remainder minimization method in the Sobolev space, for more general optimal conditions the new theory has the potential to overcome an inherent limitation of the POD method, i.e., it cannot be used to the situations in which the optimal condition is other than the inner product global one. As an example, using the new theory, the database of a two-dimensional flow over a backward-facing step is analyzed in detail, with velocity and vorticity bases.

Coherent linking of periodic nano-ripples on a ZnO crystal surface induced by femtosecond laser pulses

We demonstrate the coherent linking of periodic nano-ripples formed on the surface of ZnO crystals induced by femtosecond laser pulses. By adjusting the distance between two laser scanning zones, the periodic nano-ripples induced by two separated laser writing processes can be coherently linked and the ZnO nanograting with much longer grooves is therefore produced. The length limitation of this kind of nanograting previously set by the laser focus size is thus overcome. The micro-Raman mapping technique is used to evaluate the quality of coherent linking, and the underlying physics is discussed. The demonstrated scheme is promising for producing large-size self-organized nanogratings induced by femtosecond laser pulses.

Control of dynamical systems with temporal logic specifications

This thesis is motivated by safety-critical applications involving autonomous air, ground, and space vehicles carrying out complex tasks in uncertain and adversarial environments. We use temporal logic as a language to formally specify complex tasks and system properties. Temporal logic specifications generalize the classical notions of stability and reachability that are studied in the control and hybrid systems communities. Given a system model and a formal task specification, the goal is to automatically synthesize a control policy for the system that ensures that the system satisfies the specification. This thesis presents novel control policy synthesis algorithms for optimal and robust control of dynamical systems with temporal logic specifications. Furthermore, it introduces algorithms that are efficient and extend to high-dimensional dynamical systems.

The first contribution of this thesis is the generalization of a classical linear temporal logic (LTL) control synthesis approach to optimal and robust control. We show how we can extend automata-based synthesis techniques for discrete abstractions of dynamical systems to create optimal and robust controllers that are guaranteed to satisfy an LTL specification. Such optimal and robust controllers can be computed at little extra computational cost compared to computing a feasible controller.

The second contribution of this thesis addresses the scalability of control synthesis with LTL specifications. A major limitation of the standard automaton-based approach for control with LTL specifications is that the automaton might be doubly-exponential in the size of the LTL specification. We introduce a fragment of LTL for which one can compute feasible control policies in time polynomial in the size of the system and specification. Additionally, we show how to compute optimal control policies for a variety of cost functions, and identify interesting cases when this can be done in polynomial time. These techniques are particularly relevant for online control, as one can guarantee that a feasible solution can be found quickly, and then iteratively improve on the quality as time permits.

The final contribution of this thesis is a set of algorithms for computing feasible trajectories for high-dimensional, nonlinear systems with LTL specifications. These algorithms avoid a potentially computationally-expensive process of computing a discrete abstraction, and instead compute directly on the system's continuous state space. The first method uses an automaton representing the specification to directly encode a series of constrained-reachability subproblems, which can be solved in a modular fashion by using standard techniques. The second method encodes an LTL formula as mixed-integer linear programming constraints on the dynamical system. We demonstrate these approaches with numerical experiments on temporal logic motion planning problems with high-dimensional (10+ states) continuous systems.