Hybrid Bayesian Classifier for Improved Classification Accuracy

The widely used Bayesian classifier is based on the assumption of equal prior probabilities for all the classes. However, inclusion of equal prior probabilities may not guarantee high classification accuracy for the individual classes. Here, we propose a novel technique-Hybrid Bayesian Classifier (HBC)-where the class prior probabilities are determined by unmixing a supplemental low spatial-high spectral resolution multispectral (MS) data that are assigned to every pixel in a high spatial-low spectral resolution MS data in Bayesian classification. This is demonstrated with two separate experiments-first, class abundances are estimated per pixel by unmixing Moderate Resolution Imaging Spectroradiometer data to be used as prior probabilities, while posterior probabilities are determined from the training data obtained from ground. These have been used for classifying the Indian Remote Sensing Satellite LISS-III MS data through Bayesian classifier. In the second experiment, abundances obtained by unmixing Landsat Enhanced Thematic Mapper Plus are used as priors, and posterior probabilities are determined from the ground data to classify IKONOS MS images through Bayesian classifier. The results indicated that HBC systematically exploited the information from two image sources, improving the overall accuracy of LISS-III MS classification by 6% and IKONOS MS classification by 9%. Inclusion of prior probabilities increased the average producer's and user's accuracies by 5.5% and 6.5% in case of LISS-III MS with six classes and 12.5% and 5.4% in IKONOS MS for five classes considered.

Comparison of 10 Multi-Sensor Image Fusion Paradigms for IKONOS Images

Fusion of multi-sensor imaging data enables a synergetic interpretation of complementary information obtained by sensors of different spectral ranges. Multi-sensor data of diverse spectral, spatial and temporal resolutions require advanced numerical techniques for analysis and interpretation. This paper reviews ten advanced pixel based image fusion techniques – Component substitution (COS), Local mean and variance matching, Modified IHS (Intensity Hue Saturation), Fast Fourier Transformed-enhanced IHS, Laplacian Pyramid, Local regression, Smoothing filter (SF), Sparkle, SVHC and Synthetic Variable Ratio. The above techniques were tested on IKONOS data (Panchromatic band at 1 m spatial resolution and Multispectral 4 bands at 4 m spatial resolution). Evaluation of the fused results through various accuracy measures, revealed that SF and COS methods produce images closest to corresponding multi-sensor would observe at the highest resolution level (1 m).

Wireless sensor networks forhuman intruder detection

In this paper we report on the outcomes of a research and demonstration project on human intrusion detection in a large secure space using an ad hoc wireless sensor network. This project has been a unique experience in collaborative research, involving ten investigators (with expertise in areas such as sensors, circuits, computer systems,communication and networking, signal processing and security) to execute a large funded project that spanned three to four years. In this paper we report on the specific engineering solution that was developed: the various architectural choices and the associated specific designs. In addition to developing a demonstrable system, the various problems that arose have given rise to a large amount of basic research in areas such as geographical packet routing, distributed statistical detection, sensors and associated circuits, a low power adaptive micro-radio, and power optimising embedded systems software. We provide an overview of the research results obtained.

Fast Robust Pattern Classification Algorithms for Real Time Neuro-Motor Prosthetic Applications

In this paper, we give a brief review of pattern classification algorithms based on discriminant analysis. We then apply these algorithms to classify movement direction based on multivariate local field potentials recorded from a microelectrode array in the primary motor cortex of a monkey performing a reaching task. We obtain prediction accuracies between 55% and 90% using different methods which are significantly above the chance level of 12.5%.

Minimal unsatisfiable sets: Classification and bounds

Proving the unsatisfiability of propositional Boolean formulas has applications in a wide range of fields. Minimal Unsatisfiable Sets (MUS) are signatures of the property of unsatisfiability in formulas and our understanding of these signatures can be very helpful in answering various algorithmic and structural questions relating to unsatisfiability. In this paper, we explore some combinatorial properties of MUS and use them to devise a classification scheme for MUS. We also derive bounds on the sizes of MUS in Horn, 2-SAT and 3-SAT formulas.

Time Series Classification for Online Tamil Handwritten Character Recognition – A Kernel Based Approach

In this paper, we consider the problem of time series classification. Using piecewise linear interpolation various novel kernels are obtained which can be used with Support vector machines for designing classifiers capable of deciding the class of a given time series. The approach is general and is applicable in many scenarios. We apply the method to the task of Online Tamil handwritten character recognition with promising results.

External-cavity semiconductor laser sensor

The spectral characteristics of a diode laser are significantly affected due to interference caused between the laser diode output and the optical feedback in the external-cavity. This optical feedback effect is of practical use for linewidth reduction, tuning or for sensing applications. A sensor based on this effect is attractive due to its simplicity, low cost and compactness. This optical sensor has been used so far, in different configuration such as for sensing displacement induced by different parameters. In this paper we report a compact optical sensor consisting of a semiconductor laser coupled to an external cavity. Theoretical analysis of the self- mixing interference for optical sensing applications is given for moderate optical feedback case. A comparison is made with our experimental observations. Experimental results are in good agreement with the simulated power modulation based on self-mixing interference theory. Displacements as small as 10-4 nm have been measured using this sensor. The developed sensor showed a fringe sensitivity of one fringe per 400nm displacement for reflector distance of around 10cms. The sensor has also been tested for magnetic field and temperature induced displacement measurements.

A novel interrogation system for fiber Bragg grating sensor array

Interrogation techniques for fiber Bragg grating sensor arrays need particular attention in the case of structural health monitoring applications involving dynamic strain measurement. Typically the performance of the sensing system is dependent on both the sensor type and the interrogation method employed. A novel interrogation system is proposed here that consists of different interrogation units for each sensor in the array, each unit comprising of a circulator, chirped grating and a Mach-Zehnder interferometer. We present an analysis that consists of tracking the spectral changes as the light passes through various elements in the interrogation system. This is expected to help in the optimization of sensor and interrogation elements leading to improved performance of the health monitoring system.

Cd concentration sensor based on fiber grating technology

Fiber Bragg grating (FBG) and Long Period Grating (LPG) chemical sensors are one of the most exciting developments in the field of optical fiber sensors. In this paper we have proposed a simple and effective chemical sensor based on FBG and LPG techniques for detecting the traces of cadmium (Cd) in drinking water at ppm level. The sensitiveness of these two has been compared. Also, these results have been compared with the results obtained by sophisticated spectroscopic atomic absorption and emission spectrometer instruments. For proper designing of FBG to act as a concentration sensor, the cladding region of the grating has been etched using HF solution. We have characterized the FBG concentration sensor sensitivities for different solutions of Cd concentrations varying from 0.01 ppm to 0.04 ppm and observed reflected spectrum in FBG and transmitted spectrum in LPG using Optical Spectrum Analyzer. Proper reagents have been used in the solutions for detection of the Cd species. The overall shift in wavelength is 10 nm in case of LPG and the shift of Bragg wavelength is 0.07 nm in case of FBG for 0.01-0.04 ppm concentrations. (C) 2011 Elsevier B.V. All rights reserved.

Delay Optimal Event Detection on Ad Hoc Wireless Sensor Networks

We consider a small extent sensor network for event detection, in which nodes periodically take samples and then contend over a random access network to transmit their measurement packets to the fusion center. We consider two procedures at the fusion center for processing the measurements. The Bayesian setting, is assumed, that is, the fusion center has a prior distribution on the change time. In the first procedure, the decision algorithm at the fusion center is network-oblivious and makes a decision only when a complete vector of measurements taken at a sampling instant is available. In the second procedure, the decision algorithm at the fusion center is network-aware and processes measurements as they arrive, but in a time-causal order. In this case, the decision statistic depends on the network delays, whereas in the network-oblivious case, the decision statistic does not. This yields a Bayesian change-detection problem with a trade-off between the random network delay and the decision delay that is, a higher sampling rate reduces the decision delay but increases the random access delay. Under periodic sampling, in the network-oblivious case, the structure of the optimal stopping rule is the same as that without the network, and the optimal change detection delay decouples into the network delay and the optimal decision delay without the network. In the network-aware case, the optimal stopping problem is analyzed as a partially observable Markov decision process, in which the states of the queues and delays in the network need to be maintained. A sufficient decision statistic is the network state and the posterior probability of change having occurred, given the measurements received and the state of the network. The optimal regimes are studied using simulation.

Lead ion sensor with electrodes modified by imidazole-functionalized polyaniline

Glassy carbon electrodes (GCE) and carbon paste electrodes (CPE) were modified with imidazole functionalized polyaniline with the aim to develop a sensor for lead (II) in both acidic and basic aqueous solution. The electrodes were characterized by cyclic voltammetry and differential pulse adsorptive stripping voltammetry. The limit of detections obtained with glassy carbon electrode and carbon paste electrode are 20 ng mL(-1) and 2 ng mL(-1) of lead ion, respectively. An interference study was carried out with Cd(II), As(III), Hg(II) and Co(II) ions. Cd(II) ions interfere significantly (peak overlap) and As(III) has a depressing effect on the lead signal. The influence of pH was investigated indicating that bare and modified GCE and CPE show optimum response at pH 4.0 +/- 0.05.

Surface Modified CaTiO3 Loaded in Polyaniline by Sodium Dodecyl Benzene Sulphonic Acid for Humidity Sensor

Polyaniline-CaTiO3 nanocomposites with their various weight percentages were prepared by chemical oxidative in situ polymerization technique. The prepared composites were characterized by Fourier transform infrared spectroscopy, scanning electronic microscope, and X-ray diffraction. The temperature-dependent dc conductivity of polyaniline-CaTiO3 nanocomposite was studied within the range of 40-200 degrees C and found that 50 wt% shows high conductivity compared to other composites. Humidity sensor properties of polyaniline-CaTiO3 nanocomposite show better sensing properties and exhibit good linearity in sensing response curve, which discuss the implications of distortions and nonstoichiometry on their physical properties. Among all composites, 50 wt% of polyaniline-CaTiO3 nanocomposites show high sensitivity up to similar to 90% and their response-recovery times are 500 and 453 s, respectively.

Green synthesis of biopolymer-silver nanoparticle nanocomposite: An optical sensor for ammonia detection

Biopolymer used for the production of nanoparticles (NPs) has attracted increasing attention. In the presence article we use aqueous solution of polysaccharide Cyamopsis tetragonaloba commonly known as guar gum (GG), from plants. GG acts as reductive preparation of silver nanoparticles which are found to be <10. nm in size. The uniformity of the NPs size was measured by the SEM and TEM, while a face centered cubic structure of crystalline silver nanoparticles was characterized using powder X-ray diffraction technique. Aqueous ammonia sensing study of polymer/silver nanoparticles nanocomposite (GG/AgNPs NC) was performed by optical method based on surface plasmon resonance (SPR). The performances of optical sensor were investigated which provide the excellent result. The response time of 2-3. s and the detection limit of ammonia solution, 1. ppm were found at room temperature. Thus, in future this room temperature optical ammonia sensor can be used for clinical and medical diagnosis for detecting low ammonia level in biological fluids, such as plasma, sweat, saliva, cerebrospinal liquid or biological samples in general for various biomedical applications in human. © 2012 Elsevier B.V.

Zinc Oxide Modified Au Electrode as Sensor for an Efficient Detection of Hydrazine

ZnO nanoparticles (ZnO NPs) prepared by microwave heating technique are used to modify a gold electrode (ZnO/Au) for the hydrazine detection study. The synthesized product is well characterized by various techniques. Detailed electrochemical investigation of the oxidation of hydrazine on the ZnO/Au electrode in 0.02 M phosphate buffer solution (PBS) of pH 7.4 was carried out. A very low detection limit of 66 nM (S/N=4) and a wide linearity in current for a concentration range from 66.0X10-3 to 415 mu M was achieved by amperometry. The electrode was found to be stable for over a month when preserved in PBS.