Efficient Regular Expression Pattern Matching for Network Intrusion Detection Systems using Modified Word-based Automata

Network Intrusion Detection Systems (NIDS) intercept the traffic at an organization's network periphery to thwart intrusion attempts. Signature-based NIDS compares the intercepted packets against its database of known vulnerabilities and malware signatures to detect such cyber attacks. These signatures are represented using Regular Expressions (REs) and strings. Regular Expressions, because of their higher expressive power, are preferred over simple strings to write these signatures. We present Cascaded Automata Architecture to perform memory efficient Regular Expression pattern matching using existing string matching solutions. The proposed architecture performs two stage Regular Expression pattern matching. We replace the substring and character class components of the Regular Expression with new symbols. We address the challenges involved in this approach. We augment the Word-based Automata, obtained from the re-written Regular Expressions, with counter-based states and length bound transitions to perform Regular Expression pattern matching. We evaluated our architecture on Regular Expressions taken from Snort rulesets. We were able to reduce the number of automata states between 50% to 85%. Additionally, we could reduce the number of transitions by a factor of 3 leading to further reduction in the memory requirements.

A possible connection between antidiabetic and antilipemic properties of psoralea corylifolia seeds and the trace elements present: a LIBS based study

Psoralea corylifolia (PC), a medicinal plant, is used in traditional medicine to treat diabetes. Purpose of the research was to examine the antidiabetic and antilipemic potential of PC and to determine the relationship between its antidiabetic potential and the trace elements present. Wistar rats (150-200 g) with fasting blood glucose (FBG) of 80-110 mg dl(-1)(sub-diabetic) and 150-200 mg dl(-1)(mild diabetic) were selected for the short term antidiabetic studies and severely diabetic rats (FBG > 300 mg dl(-1)) were chosen for the long term antidiabetic and hypolipemic studies of PC seed extract. Laser induced breakdown spectroscopy (LIBS) was used to detect trace elements in the PC extract and the intensity ratios of trace elements were estimated. The dose of 250 mg kg(-1) of PC extract was found to be the most effective in lowering blood glucose level (BGL) of normal, sub, mild and severely diabetic rats during FBG and glucose tolerance test (GTT) studies. Lipid profile studies on severely diabetic rats showed substantial reduction in total cholesterol, triglycerides, very low density lipoprotein, and low density lipoprotein and an increase in the total protein, body weight, high density lipoprotein, and hemoglobin after 28 days of treatment. Significant reduction in urine sugar and protein levels was also observed. LIBS analysis of the PC extract revealed the presence of Mg, Si, Na, K, Ca, Zn and Cl. The study validates the traditional use of PC in the treatment of diabetes and confirms its antilipemic potential. The antidiabetic activity of PC extract may partly be due to the presence of appreciable amounts of insulin potentiating elements like Mg, Ca, and K.

Synergistic effect of reactor chemistry and compressive stress on dislocation bending during GaN growth

The synergistic effect of compressive growth stresses and reactor chemistry, silane presence, on dislocation bending at the very early stages of GaN growth has been studied using in-situ stress measurements and cross-sectional transmission electron microscopy. A single 100 nm Si-doped GaN layer is found to be more effective than a 1 mu m linearly graded AlGaN buffer layer in reducing dislocation density and preventing the subsequent layer from transitioning to a tensile stress. 1 mu m crack-free GaN layers with a dislocation density of 7 x 10(8)/cm(2), with 0.13 nm surface roughness and no enhancement in n-type background are demonstrated over 2 inch substrates using this simple transition scheme. (C) 2013 AIP Publishing LLC.

Generation of extended light-sheets for single and multi-photon fluorescence microscopy

We theoretically propose and computationally demonstrate the generation of extended light-sheet for fluorescence microscopy. This is made possible by the introduction of a specially designed double-window spatial filter that allows the light to pass through the periphery and center of a cylindrical lens. When illuminated with a plane wave, the proposed filter results in an extended depth-of-focus along with side-lobes which are due to other interferences in the transverse focal plane. Computational studies show a maximum extension of light-sheet by 3.38 times for single photon excitation and 3.68 times for multiphoton excitation as compared to state-of-art single plane illumination microscopy system. This technique may facilitate the study of large biological specimens (such as Zebrafish embryo and tissue) with high spatial resolution and reduced photobleaching. (C) 2013 AIP Publishing LLC.

Taylor series expansion based multidimensional image reconstruction for confocal and 4pi microscopy

We propose and experimentally demonstrate a three-dimensional (3D) image reconstruction methodology based on Taylor series approximation (TSA) in a Bayesian image reconstruction formulation. TSA incorporates the requirement of analyticity in the image domain, and acts as a finite impulse response filter. This technique is validated on images obtained from widefield, confocal laser scanning fluorescence microscopy and two-photon excited 4pi (2PE-4pi) fluorescence microscopy. Studies on simulated 3D objects, mitochondria-tagged yeast cells (labeled with Mitotracker Orange) and mitochondrial networks (tagged with Green fluorescent protein) show a signal-to-background improvement of 40% and resolution enhancement from 360 to 240 nm. This technique can easily be extended to other imaging modalities (single plane illumination microscopy (SPIM), individual molecule localization SPIM, stimulated emission depletion microscopy and its variants).

Optimization of HfO2 films for high transconductance back gated graphene transistors

Hafnium dioxide (HfO2) films, deposited using electron beam evaporation, are optimized for high performance back-gated graphene transistors. Bilayer graphene is identified on HfO2/Si substrate using optical microscope and subsequently confirmed with Raman spectroscopy. Back-gated graphene transistor, with 32 nm thick HfO2 gate dielectric, has been fabricated with very high transconductance value of 60 mu S. From the hysteresis of the current-voltage characteristics, we estimate the trap density in HfO2 to be in the mid 10(11)/cm(2) range, comparable to SiO2.

The effect of cell size and channel density on neuronal information encoding and energy efficiency

Identifying the determinants of neuronal energy consumption and their relationship to information coding is critical to understanding neuronal function and evolution. Three of the main determinants are cell size, ion channel density, and stimulus statistics. Here we investigate their impact on neuronal energy consumption and information coding by comparing single-compartment spiking neuron models of different sizes with different densities of stochastic voltage-gated Na+ and K+ channels and different statistics of synaptic inputs. The largest compartments have the highest information rates but the lowest energy efficiency for a given voltage-gated ion channel density, and the highest signaling efficiency (bits spike(-1)) for a given firing rate. For a given cell size, our models revealed that the ion channel density that maximizes energy efficiency is lower than that maximizing information rate. Low rates of small synaptic inputs improve energy efficiency but the highest information rates occur with higher rates and larger inputs. These relationships produce a Law of Diminishing Returns that penalizes costly excess information coding capacity, promoting the reduction of cell size, channel density, and input stimuli to the minimum possible, suggesting that the trade-off between energy and information has influenced all aspects of neuronal anatomy and physiology.

Aluminium coated carbon nanotube film for wavelength-selective surface

We report selective optical reflectance in an aluminium (Al) coated flexible carbon nanotube (CNT) thin film over a wide range of wavelengths (500-2500 nm). Selective-wavelength surface is achieved by coating CNT surfaces with Al thin film that presented a maximum optical reflectivity of similar to 65% in the infrared region. However, CNT film alone showed a reflectance of 15-20% over a larger range of wavelengths without any structural modification, which has not been realized so far. Moreover, a tailorable reflectance in CNT is shown to be achieved by tuning various parameters, namely, the porosity of the material, angle of an incident light, and refractive index of the materials. Owing to higher infrared reflectivity and thermal diffusivity, Al coated CNT presents a potential for a high efficiency solar collector. (C) 2013 AIP Publishing LLC.

Observation of trap-assisted space charge limited conductivity in short channel MoS2 transistor

We present temperature dependent I-V measurements of short channel MoS2 field effect devices at high source-drain bias. We find that, although the I-V characteristics are ohmic at low bias, the conduction becomes space charge limited at high V-DS, and existence of an exponential distribution of trap states was observed. The temperature independent critical drain-source voltage (V-c) was also determined. The density of trap states was quantitatively calculated from V-c. The possible origin of exponential trap distribution in these devices is also discussed. (C) 2013 AIP Publishing LLC.

Engineered spin-valve type magnetoresistance in Fe3O4-CoFe2O4 core-shell nanoparticles

Naturally occurring spin-valve-type magnetoresistance (SVMR), recently observed in Sr2FeMoO6 samples, suggests the possibility of decoupling the maximal resistance from the coercivity of the sample. Here we present the evidence that SVMR can be engineered in specifically designed and fabricated core-shell nanoparticle systems, realized here in terms of soft magnetic Fe3O4 as the core and hard magnetic insulator CoFe2O4 as the shell materials. We show that this provides a magnetically switchable tunnel barrier that controls the magnetoresistance of the system, instead of the magnetic properties of the magnetic grain material, Fe3O4, and thus establishing the feasibility of engineered SVMR structures. (C) 2013 AIP Publishing LLC.

Image reconstruction enables high resolution imaging at large penetration depths in fluorescence microscopy

Imaging thick specimen at a large penetration depth is a challenge in biophysics and material science. Refractive index mismatch results in spherical aberration that is responsible for streaking artifacts, while Poissonian nature of photon emission and scattering introduces noise in the acquired three-dimensional image. To overcome these unwanted artifacts, we introduced a two-fold approach: first, point-spread function modeling with correction for spherical aberration and second, employing maximum-likelihood reconstruction technique to eliminate noise. Experimental results on fluorescent nano-beads and fluorescently coated yeast cells (encaged in Agarose gel) shows substantial minimization of artifacts. The noise is substantially suppressed, whereas the side-lobes (generated by streaking effect) drops by 48.6% as compared to raw data at a depth of 150 mu m. Proposed imaging technique can be integrated to sophisticated fluorescence imaging techniques for rendering high resolution beyond 150 mu m mark. (C) 2013 AIP Publishing LLC.

Predictability of nonstationary time series using wavelet and EMD based ARMA models

Research has been undertaken to ascertain the predictability of non-stationary time series using wavelet and Empirical Mode Decomposition (EMD) based time series models. Methods have been developed in the past to decompose a time series into components. Forecasting of these components combined with random component could yield predictions. Using this ideology, wavelet and EMD analyses have been incorporated separately which decomposes a time series into independent orthogonal components with both time and frequency localizations. The component series are fit with specific auto-regressive models to obtain forecasts which are later combined to obtain the actual predictions. Four non-stationary streamflow sites (USGS data resources) of monthly total volumes and two non-stationary gridded rainfall sites (IMD) of monthly total rainfall are considered for the study. The predictability is checked for six and twelve months ahead forecasts across both the methodologies. Based on performance measures, it is observed that wavelet based method has better prediction capabilities over EMD based method despite some of the limitations of time series methods and the manner in which decomposition takes place. Finally, the study concludes that the wavelet based time series algorithm can be used to model events such as droughts with reasonable accuracy. Also, some modifications that can be made in the model have been discussed that could extend the scope of applicability to other areas in the field of hydrology. (C) 2013 Elesvier B.V. All rights reserved.

Investigation on non-exchange spring behaviour and exchange spring behaviour: A first order reversal curve analysis

The First Order Reversal Curve (FORC) method has been utilised to understand the magnetization reversal and the extent of the irreversible magnetization of the soft CoFe2O4-hard SrFe12O19 nanocomposite in the nonexchange spring and the exchange spring regime. The single peak switching behaviour in the FORC distribution of the exchange spring composite confirms the coherent reversal of the soft and hard phases. The onset of the nucleation field and the magnetization reversal by domain wall movement are also evident from the FORC measurements. (C) 2013 AIP Publishing LLC.

An early in-situ stress signature of the AlN-Si pre-growth interface for successful integration of nitrides with (111) Si

The integration of Metal Organic Chemical Vapor Deposition (MOCVD) grown group III-A nitride device stacks on Si (111) substrates is critically dependent on the quality of the first AlN buffer layer grown. A Si surface that is both oxide-free and smooth is a primary requirement for nucleating such layers. A single parameter, the AlN layer growth stress, is shown to be an early (within 50 nm), clear (<0.5 GPa versus > 1GPa), and fail-safe indicator of the pre-growth surface, and the AlN quality required for successful epitaxy. Grain coalescence model for stress generation is used to correlate growth stress, the AlN-Si interface, and crystal quality. (C) 2013 AIP Publishing LLC.

Excellent Performance of Few-Layer Borocarbonitrides as Anode Materials in Lithium-Ion Batteries

Borocarbonitrides (BxCyNz) with a graphene-like structure exhibit a remarkable high lithium cyclability and current rate capability. The electrochemical performance of the BxCyNz materials, synthesized by using a simple solid-state synthesis route based on urea, was strongly dependent on the composition and surface area. Among the three compositions studied, the carbon-rich compound B0.15C0.73N0.12 with the highest surface area showed an exceptional stability (over 100cycles) and rate capability over widely varying current density values (0.05-1Ag(-1)). B0.15C0.73N0.12 has a very high specific capacity of 710mAhg(-1) at 0.05Ag(-1). With the inclusion of a suitable additive in the electrolyte, the specific capacity improved drastically, recording an impressive value of nearly 900mAhg(-1) at 0.05Ag(-1). It is believed that the solid-electrolyte interphase (SEI) layer at the interface of BxCyNz and electrolyte also plays a crucial role in the performance of the BxCyNz .