Unsupervised feature selection for outlier detection in categorical data using mutual information

Outlier detection in high dimensional categorical data has been a problem of much interest due to the extensive use of qualitative features for describing the data across various application areas. Though there exist various established methods for dealing with the dimensionality aspect through feature selection on numerical data, the categorical domain is actively being explored. As outlier detection is generally considered as an unsupervised learning problem due to lack of knowledge about the nature of various types of outliers, the related feature selection task also needs to be handled in a similar manner. This motivates the need to develop an unsupervised feature selection algorithm for efficient detection of outliers in categorical data. Addressing this aspect, we propose a novel feature selection algorithm based on the mutual information measure and the entropy computation. The redundancy among the features is characterized using the mutual information measure for identifying a suitable feature subset with less redundancy. The performance of the proposed algorithm in comparison with the information gain based feature selection shows its effectiveness for outlier detection. The efficacy of the proposed algorithm is demonstrated on various high-dimensional benchmark data sets employing two existing outlier detection methods.

Characterization and microhardness of Co-W coatings electrodeposited at different pH using gluconate bath: a comparative study

Electrodeposition of Co-W alloy coatings has been carried out with DC and PC using gluconate bath at different pH. These coatings are characterized for their structure, morphology and chemical composition by X-ray diffraction, field emission scanning electron microscopy, differential scanning calorimetry and X-ray photoelectron spectroscopy (XPS). Alloy coatings plated at pH8 are crystalline, whereas coatings electrodeposited at pH5 are nanocrystalline in nature. XPS studies have demonstrated that as-deposited alloy plated at pH8 with DC contain only Co2+ and W6+ species, whereas that alloy plated at pH5 has significant amount of Co-0 and W-0 along with Co2+ and W6+ species. Again, Co2+ and W6+ are main species in all as-deposited PC plated alloys in both pH. Co-0 concentration increases upon successive sputtering of all alloy coatings. In contrast, mainly W6+ species is detected in the following layers of all alloys plated with PC. Alloys plated at pH5 show higher microhardness compared to their pH8 counterparts.

Employing denaturation for rapid electrochemical detection of myoglobin using TiO2 nanotubes

An alternative antibody-free strategy for the rapid electrochemical detection of cardiac myoglobin has been demonstrated here using hydrothermally synthesized TiO2 nanotubes (Ti-NT). The denaturant induced unfolding of myoglobin led to easy access of the deeply buried electroactive heme center and thus the efficient reversible electron transfer from protein to electrode surface. The sensing performance of the Ti-NT modified electrodes were compared vis a vis commercially available titania and GCEs. The tubular morphology of the Ti-NT led to facile transfer of electrons to the electrode surface, which eventually provided a linear current response (obtained from cyclic voltammetry) over a wide range of Mb concentration. The sensitivity of the Ti-NT based sensor was remarkable and was equal to 18 mu A mg(-1) ml (detection limit = 50 nM). This coupled with the rapid analysis time of a few tens of minutes (compared to a few days for ELISA) demonstrates its potential usefulness for the early detection of acute myocardial infarction (AMI).

Detection limit of etched fiber bragg grating sensors

While Fiber Bragg Grating (FBG) sensors have been extensively used for temperature and strain sensing, clad etched FBGs (EFBGs) have only recently been explored for refractive index sensing. Prior literature in EFBG based refractive index sensing predominantly deals with bulk refractometry only, where the Bragg wavelength shift of the sensor as a function of the bulk refractive index of the sample can be analytically modeled, unlike the situation for adsorption of molecular thin films on the sensor surface. We used a finite element model to calculate the Bragg wavelength change as a function of thickness and refractive index of the adsorbing molecular layer and compared the model with the real-time, in-situ measurement of electrostatic layer-by-layer (LbL) assembly of weak polyelectrolytes on the silica surface of EFBGs. We then used this model to calculate the layer thickness of LbL films and found them to be in agreement with literature. Further, we used this model to arrive at a realistic estimate of the limit of detection of EFBG sensors based on nominal measurement noise levels in current FBG interrogation systems and found that sufficiently thinned EFBGs can provide a competitive platform for real-time measurement of molecular interactions while simultaneously leveraging the high multiplexing capabilities of fiber optics.

Resonance raman detection and estimation in the aqueous phase using water dispersible cyclodextrin: reduced-graphene oxide sheets

Resonance Raman spectroscopy is a powerful analytical tool for detecting and identifying analytes, but the associated strong fluorescence background severely limits the use of the technique. Here, we show that by attaching beta-cyclodextrin (beta-CD) cavities to reduced graphene-oxide (rGO) sheets we obtain a water dispersible material (beta-CD: rGO) that combines the hydrophobicity associated with rGO with that of the cyclodextrin cavities and provides a versatile platform for resonance Raman detection. Planar aromatic and dye molecules that adsorb on the rGO domains and nonplanar molecules included within the tethered beta-CD cavities have their fluorescence effectively quenched. We show that it is possible using the water dispersible beta-CD: rGO sheets to record the resonance Raman spectra of adsorbed and included organic chromophores directly in aqueous media without having to extract or deposit on a substrate. This is significant, as it allows us to identify and estimate organic analytes present in water by resonance Raman spectroscopy.

Nonparametric distributed sequential detection via universal source coding

We consider nonparametric or universal sequential hypothesis testing when the distribution under the null hypothesis is fully known but the alternate hypothesis corresponds to some other unknown distribution. These algorithms are primarily motivated from spectrum sensing in Cognitive Radios and intruder detection in wireless sensor networks. We use easily implementable universal lossless source codes to propose simple algorithms for such a setup. The algorithms are first proposed for discrete alphabet. Their performance and asymptotic properties are studied theoretically. Later these are extended to continuous alphabets. Their performance with two well known universal source codes, Lempel-Ziv code and KT-estimator with Arithmetic Encoder are compared. These algorithms are also compared with the tests using various other nonparametric estimators. Finally a decentralized version utilizing spatial diversity is also proposed and analysed.

Efficient method of moving shadow detection and vehicle classification

Moving shadow detection and removal from the extracted foreground regions of video frames, aim to limit the risk of misconsideration of moving shadows as a part of moving objects. This operation thus enhances the rate of accuracy in detection and classification of moving objects. With a similar reasoning, the present paper proposes an efficient method for the discrimination of moving object and moving shadow regions in a video sequence, with no human intervention. Also, it requires less computational burden and works effectively under dynamic traffic road conditions on highways (with and without marking lines), street ways (with and without marking lines). Further, we have used scale-invariant feature transform-based features for the classification of moving vehicles (with and without shadow regions), which enhances the effectiveness of the proposed method. The potentiality of the method is tested with various data sets collected from different road traffic scenarios, and its superiority is compared with the existing methods. (C) 2013 Elsevier GmbH. All rights reserved.

EFFECT OF CORE-SHELL STRUCTURE OF HYDROGEL BEADS ON THE THRESHOLD CONCENTRATION OF WATER FOR SWELLING AND ITS PH SENSITIVITY

In this paper we investigate the effect of core-shell structure of Sodium Alginate based hydrogel beads and their size on certain activation threshold concentration of water for applications in swelling and pH sensing. This type of hydrogel experiences diffusive pressure due to transport of certain free charges across its interface with a solvent or electrolyte. This process is essentially a dynamic equilibrium of the electric force field, stress in the polymeric network with cage like structure and molecular diffusion including phase transformation due to pressure imbalance between the hydrogel and its surroundings. The effect of pH of the solvant on the swelling rate of these beads has been studied experimentally. A mathematical model of the swelling process has been developed by considering Nernst-Planck equation representing the migration of mobile ions and Er ions, Poisson equation representing the equilibrium of the electric field and mechanical field equation representing swelling of the gel. An attempt has been made to predict the experimentally observed phenomena using these numerical simulations. It is observed experimentally that certain minimum concentration called activation threshold concentration of the water molecules must be present in the hydrogel in order to activate the swelling process. For the required activation threshold concentration of water in the beads, the pH induced change in the rate of swelling is also investigated. This effect is analyzed for various different core-shell structures of the beads.

pH Induced switching in hydrogel coated fiber bragg grating sensor

In this paper we report a novel hydrogel functionalized optical Fiber Bragg Grating (FBG) sensor based on chemo-mechanical-optical sensing, and demonstrate its specific application in pH activated process monitoring. The sensing mechanism is based on the stress due to ion diffusion and polymer phase transition which produce strain in the FBG. This results in shift in the Bragg wavelength which is detected by an interrogator system. A simple dip coating method to coat a thin layer of hydrogel on the FBG has been established. The gel consists of sodium alginate and calcium chloride. Gel formation is observed in real-time by continuously monitoring the Bragg wavelength shift. We have demonstrated pH sensing in the range of pH of 2 to 10. Another interesting phenomenon is observed by swelling and deswelling of FBG functionalized with hydrogel by a sequence of alternate dipping between acidic and base solutions. It is observed that the Bragg wavelength undergoes reversible and repeatable pH dependent switching.

Molecular flexibility tuned emission in ``V'' shaped naphthalimides: Hg(II) detection and aggregation-induced emission enhancement (AIEE)

Four ``V'' shaped 1,8-naphthalimides (1-4) have been synthesized and their fluorescence quantum-yields correlated to their molecular flexibility. The correlation was used for detection of Hg(II) via a chemodosimetric approach. 4 was found to be an AIE active molecule with the formation of fluorescent nanoaggregates.

Blood pressure evaluation using sphygmomanometry assisted by arterial pulse waveform detection by fiber Bragg grating pulse device

We report a blood pressure evaluation methodology by recording the radial arterial pulse waveform in real time using a fiber Bragg grating pulse device (FBGPD). Here, the pressure responses of the arterial pulse in the form of beat-to-beat pulse amplitude and arterial diametrical variations are monitored. Particularly, the unique signatures of pulse pressure variations have been recorded in the arterial pulse waveform, which indicate the systolic and diastolic blood pressure while the patient is subjected to the sphygmomanometric blood pressure examination. The proposed method of blood pressure evaluation using FBGPD has been validated with the auscultatory method of detecting the acoustic pulses (Korotkoff sounds) by an electronic stethoscope. (C) 2013 Society of Photo-Optical Instrumentation Engineers (SPIE)

Spatial Wavelet Approach to Local Matrix Crack Detection in Composite Beams with Ply Level Material Uncertainty

Wavelet coefficients based on spatial wavelets are used as damage indicators to identify the damage location as well as the size of the damage in a laminated composite beam with localized matrix cracks. A finite element model of the composite beam is used in conjunction with a matrix crack based damage model to simulate the damaged composite beam structure. The modes of vibration of the beam are analyzed using the wavelet transform in order to identify the location and the extent of the damage by sensing the local perturbations at the damage locations. The location of the damage is identified by a sudden change in spatial distribution of wavelet coefficients. Monte Carlo Simulations (MCS) are used to investigate the effect of ply level uncertainty in composite material properties such as ply longitudinal stiffness, transverse stiffness, shear modulus and Poisson's ratio on damage detection parameter, wavelet coefficient. In this study, numerical simulations are done for single and multiple damage cases. It is observed that spatial wavelets can be used as a reliable damage detection tool for composite beams with localized matrix cracks which can result from low velocity impact damage.

Study on the detection efficiency of gaseous photomultipliers

Efficient photon detection in gaseous photomultipliers require maximum photoelectron yield from the photocathode surface and also detection of them. In this work we have investigated the parameters that affect the photoelectron yield from the photocathode surface and methods to improve them thus ensuring high detection efficiency of the gaseous photomultiplier. The parameters studied are the electric field at the photocathode surface, surface properties of photocathode and pressure of gas mixture inside the gaseous photomultiplier. It was observed that optimized electric field at the photocathode ensures high detection efficiency. Lower pressure of filled gas increases the photoelectron yield from the photocathode surface but reduces the focusing probability of electrons inside the electron multiplier. Also evacuation for longer duration before gas filling increases the photoelectron yield.

Identification of immuno-dominant antigens of Trypanosoma evansi for detection of chronic trypanosomosis using experimentally infected equines

Trypanosoma evansi is the most extensively distributed trypanosome responsible for disease called surra in livestock in many countries including frequent outbreaks in India. The prevalence of this disease is most commonly reported by standard parasitological detection methods (SPDM); however, antibody ELISA is being in practice by locally produced whole cell lysate (WCL) antigens in many countries. In the present investigation, we attempted to identify and purify immuno dominant, infection specific trypanosome antigens from T. evansi proteome using experimentally infected equine serum by immuno blot. Three immuno dominant clusters of proteins i.e. 62-66 kDa, 52-55 kDa and 41-43 kDa were identified based on their consistent reactivity with donkey sequential serum experimentally infected T. evansi up to 280 days post infection (dpi). The protein cluster of 62-66 kDa was purified in bulk in native form and comparatively evaluated with whole cell lysate antigen (WCL). ELISA and immuno blot showed that polypeptide of this cluster is 100% sensitive in detection of early and chronic infection. Further, this protein cluster was also found immuno reactive against hyper immune serum raised against predominantly 66 kDa exo antigen, revealed that this is a common immunodominant moieties in proteome and secretome of T. evansi.

Narrowband signal detection techniques in shallow ocean by acoustic vector sensor array

This paper presents the formulation and performance analysis of four techniques for detection of a narrowband acoustic source in a shallow range-independent ocean using an acoustic vector sensor (AVS) array. The array signal vector is not known due to the unknown location of the source. Hence all detectors are based on a generalized likelihood ratio test (GLRT) which involves estimation of the array signal vector. One non-parametric and three parametric (model-based) signal estimators are presented. It is shown that there is a strong correlation between the detector performance and the mean-square signal estimation error. Theoretical expressions for probability of false alarm and probability of detection are derived for all the detectors, and the theoretical predictions are compared with simulation results. It is shown that the detection performance of an AVS array with a certain number of sensors is equal to or slightly better than that of a conventional acoustic pressure sensor array with thrice as many sensors.