Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications. (C) 2005 Elsevier B. V. All rights reserved.

Occupational chronic solvent encephalopathy in Finland 1995 - 2007 : incidence and diagnostic methods

The occurrence of occupational chronic solvent encephalopathy (CSE) seems to decrease, but still every year reveals new cases. To prevent CSE and early retirement of solvent-exposed workers, actions should focus on early CSE detection and diagnosis. Identifying the work tasks and solvent exposure associated with high risk for CSE is crucial. Clinical and exposure data of all the 128 cases diagnosed with CSE as an occupational disease in Finland during 1995-2007 was collected from the patient records at the Finnish Institute of Occupational Health (FIOH) in Helsinki. The data on the number of exposed workers in Finland were gathered from the Finnish Job-exposure Matrix (FINJEM) and the number of employed from the national workforce survey. We analyzed the work tasks and solvent exposure of CSE patients and the findings in brain magnetic resonance imaging (MRI), quantitative electroencephalography (QEEG), and event-related potentials (ERP). The annual number of new cases diminished from 18 to 3, and the incidence of CSE decreased from 8.6 to 1.2 / million employed per year. The highest incidence of CSE was in workers with their main exposure to aromatic hydrocarbons; during 1995-2006 the incidence decreased from 1.2 to 0.3 / 1 000 exposed workers per year. The work tasks with the highest incidence of CSE were floor layers and lacquerers, wooden surface finishers, and industrial, metal, or car painters. Among 71 CSE patients, brain MRI revealed atrophy or white matter hyperintensities or both in 38% of the cases. Atrophy which was associated with duration of exposure was most frequently located in the cerebellum and in the frontal or parietal brain areas. QEEG in a group of 47 patients revealed increased power of the theta band in the frontal brain area. In a group of 86 patients, the P300 amplitude of auditory ERP was decreased, but at individual level, all the amplitude values were classified as normal. In 11 CSE patients and 13 age-matched controls, ERP elicited by a multimodal paradigm including an auditory, a visual detection, and a recognition memory task under single and dual-task conditions corroborated the decrease of auditory P300 amplitude in CSE patients in single-task condition. In dual-task conditions, the auditory P300 component was, more often in patients than in controls, unrecognizable. Due to the paucity and non-specificity of the findings, brain MRI serves mainly for differential diagnostics in CSE. QEEG and auditory P300 are insensitive at individual level and not useful in the clinical diagnostics of CSE. A multimodal ERP paradigm may, however, provide a more sensitive method to diagnose slight cognitive disturbances such as CSE.

New Concepts for PVC Detection

A new scheme is proposed for the detection of premature ventricular beats, which is a vital function in rhythm monitoring of cardiac patients. A transformation based on the first difference of the digitized electrocardiogram (ECG) signal is developed for the detection and delineation of QRS complexes. The method for classifying the abnormal complexes from the normal ones is based on the concepts of minimum phase and signal length. The parameters of a linear discriminant function obtained from a training feature vector set are used to classify the complexes. Results of application of the scheme to ECG of two arrhythmia patients are presented.

Microbial identification by detection of ligation probes on DNA microarray

Microbes in natural and artificial environments as well as in the human body are a key part of the functional properties of these complex systems. The presence or absence of certain microbial taxa is a correlate of functional status like risk of disease or course of metabolic processes of a microbial community. As microbes are highly diverse and mostly notcultivable, molecular markers like gene sequences are a potential basis for detection and identification of key types. The goal of this thesis was to study molecular methods for identification of microbial DNA in order to develop a tool for analysis of environmental and clinical DNA samples. Particular emphasis was placed on specificity of detection which is a major challenge when analyzing complex microbial communities. The approach taken in this study was the application and optimization of enzymatic ligation of DNA probes coupled with microarray read-out for high-throughput microbial profiling. The results show that fungal phylotypes and human papillomavirus genotypes could be accurately identified from pools of PCR amplicons generated from purified sample DNA. Approximately 1 ng/μl of sample DNA was needed for representative PCR amplification as measured by comparisons between clone sequencing and microarray. A minimum of 0,25 amol/μl of PCR amplicons was detectable from amongst 5 ng/μl of background DNA, suggesting that the detection limit of the test comprising of ligation reaction followed by microarray read-out was approximately 0,04%. Detection from sample DNA directly was shown to be feasible with probes forming a circular molecule upon ligation followed by PCR amplification of the probe. In this approach, the minimum detectable relative amount of target genome was found to be 1% of all genomes in the sample as estimated from 454 deep sequencing results. Signal-to-noise of contact printed microarrays could be improved by using an internal microarray hybridization control oligonucleotide probe together with a computational algorithm. The algorithm was based on identification of a bias in the microarray data and correction of the bias as shown by simulated and real data. The results further suggest semiquantitative detection to be possible by ligation detection, allowing estimation of target abundance in a sample. However, in practise, comprehensive sequence information of full length rRNA genes is needed to support probe design with complex samples. This study shows that DNA microarray has the potential for an accurate microbial diagnostic platform to take advantage of increasing sequence data and to replace traditional, less efficient methods that still dominate routine testing in laboratories. The data suggests that ligation reaction based microarray assay can be optimized to a degree that allows good signal-tonoise and semiquantitative detection.

Recognition of Polycyclic Aromatic Hydrocarbons and Their Derivatives by the 1,3-Dinaphthalimide Conjugate of Calix4]arene: Emission, Absorption, Crystal Structures, and Computational Studies

Polycyclic aromatic hydrocarbons (PAHs) are environmental pollutants as well as well-known carcinogens. Therefore, it is important to develop an effective receptor for the detection and quantification of such molecules in solution. In view of this, a 1,3-dinaphthalimide derivative of calix4]arene (L) has been synthesized and characterized, and the structure has been established by single crystal XRD. In the crystal lattice, intermolecular arm-to-arm pi center dot center dot center dot pi overlap dominates and thus L becomes a promising receptor for providing interactions with the aromatic species in solution, which can be monitored by following the changes that occur in its fluorescence and absorption spectra. On the basis of the solution studies carried out with about 17 derivatives of the aromatic guest molecular systems, it may be concluded that the changes that occur in the fluorescence intensity seem to be proportional to the number of aromatic rings present and thus proportional to the extent of pi center dot center dot center dot pi interaction present between the naphthalimide moieties and the aromatic portion of the guest molecule. Though the nonaromatic portion of the guest species affects the fluorescence quenching, the trend is still based on the number of rings present in these. Four guest aldehydes are bound to L with K-ass of 2000-6000 M-1 and their minimum detection limit is in the range of 8-35 mu M. The crystal structure of a naphthaldehyde complex, L.2b, exhibits intermolecular arm-to-arm as well as arm-to-naphthaldehyde pi center dot center dot center dot pi interactions. Molecular dynamics studies of L carried out in the presence of aromatic aldehydes under vacuum as well as in acetonitrile resulted in exhibiting interactions observed in the solid state and hence the changes observed in the fluorescence and absorption spectra are attributable for such interactions. Complex formation has also been delineated through ESI MS studies. Thus L is a promising receptor that can recognize PAHs by providing spectral changes proportional to the aromatic conjugation of the guest and the extent of aromatic pi center dot center dot center dot pi interactions present between L and the guest.

Non-resonant RF and microwave response: A novel technique for the characterization of superconducting materials

When examined using continuous wave electron paramagnetic resonance and nuclear magnetic resonance spectrometers, the high T-c superconductors give rise to intense, low field, 'non-resonant' absorption signals in the superconducting state. This phenomenon can be used as a highly sensitive, contactless technique for the detection and characterization of superconductivity even in samples containing only minute amounts of the superconducting phase. Further, it can also be applied to the determination of material parameters of interest such as J(c) and H-c2 in addition to being a powerful way of distinguishing between weak-link superconductivity and bulk superconductivity. The details of these aspects are discussed

Three- and Seven-Point Optimally Weighted Recursive Median Filters for Gas Turbine Diagnostics

Measured health signals incorporate significant details about any malfunction in a gas turbine. The attenuation of noise and removal of outliers from these health signals while preserving important features is an important problem in gas turbine diagnostics. The measured health signals are a time series of sensor measurements such as the low rotor speed, high rotor speed, fuel flow, and exhaust gas temperature in a gas turbine. In this article, a comparative study is done by varying the window length of acausal and unsymmetrical weighted recursive median filters and numerical results for error minimization are obtained. It is found that optimal filters exist, which can be used for engines where data are available slowly (three-point filter) and rapidly (seven-point filter). These smoothing filters are proposed as preprocessors of measurement delta signals before subjecting them to fault detection and isolation algorithms.

Chromatographic methods for determination of nimesulide and for stability studies

Simple and rapid HPLC, GC, and TLC procedures have been developed for detection and determination of nimesulide, a non-pharmacopeial drug, in preformulation and dosage form. Use of these techniques has enabled separation of impurities and the precursor in the bulk material and in formulations. Isocratic reversed-phase HPLC was performed on a C-18 column with methanol-water-acetic acid, 67:32:1 (v/v), as mobile phase and UV detection at 230 nm. Calibration curves were linear over the concentration range 100-1000 mug mL(-1) with a good correlation coefficient (0.9993) and a coefficient of variation of 1.5%. Gas chromatography was performed on an OV-17 packed column with temperature programming and flame-ionization detection. The lower limit of determination by HPLC and GC was 4 ppm. Thin-layer chromatography of nimesulide was performed on silica gel G with toluene-ethyl acetate, 8:2, as mobile phase. Stability testing of the drug was performed under different temperature, humidity, and UV-radiation conditions.

AlignHUSH: Alignment of HMMs using structure and hydrophobicity information

Background: Sensitive remote homology detection and accurate alignments especially in the midnight zone of sequence similarity are needed for better function annotation and structural modeling of proteins. An algorithm, AlignHUSH for HMM-HMM alignment has been developed which is capable of recognizing distantly related domain families The method uses structural information, in the form of predicted secondary structure probabilities, and hydrophobicity of amino acids to align HMMs of two sets of aligned sequences. The effect of using adjoining column(s) information has also been investigated and is found to increase the sensitivity of HMM-HMM alignments and remote homology detection. Results: We have assessed the performance of AlignHUSH using known evolutionary relationships available in SCOP. AlignHUSH performs better than the best HMM-HMM alignment methods and is observed to be even more sensitive at higher error rates. Accuracy of the alignments obtained using AlignHUSH has been assessed using the structure-based alignments available in BaliBASE. The alignment length and the alignment quality are found to be appropriate for homology modeling and function annotation. The alignment accuracy is found to be comparable to existing methods for profile-profile alignments. Conclusions: A new method to align HMMs has been developed and is shown to have better sensitivity at error rates of 10% and above when compared to other available programs. The proposed method could effectively aid obtaining clues to functions of proteins of yet unknown function. A web-server incorporating the AlignHUSH method is available at http://crick.mbu.iisc.ernet.in/similar to alignhush/

Intruder detection over sensor placement in a hexagonal lattice

The problem of intrusion detection and location identification in the presence of clutter is considered for a hexagonal sensor-node geometry. It is noted that in any practical application,for a given fixed intruder or clutter location, only a small number of neighboring sensor nodes will register a significant reading. Thus sensing may be regarded as a local phenomenon and performance is strongly dependent on the local geometry of the sensor nodes. We focus on the case when the sensor nodes form a hexagonal lattice. The optimality of the hexagonal lattice with respect to density of packing and covering and largeness of the kissing number suggest that this is the best possible arrangement from a sensor network viewpoint. The results presented here are clearly relevant when the particular sensing application permits a deterministic placement of sensors. The results also serve as a performance benchmark for the case of a random deployment of sensors. A novel feature of our analysis of the hexagonal sensor grid is a signal-space viewpoint which sheds light on achievable performance.Under this viewpoint, the problem of intruder detection is reduced to one of determining in a distributed manner, the optimal decision boundary that separates the signal spaces SI and SC associated to intruder and clutter respectively. Given the difficulty of implementing the optimal detector, we present a low-complexity distributive algorithm under which the surfaces SI and SC are separated by a wellchosen hyperplane. The algorithm is designed to be efficient in terms of communication cost by minimizing the expected number of bits transmitted by a sensor.

10 Years of Click Chemistry: Synthesis and Applications of Ferrocene-Derived Triazoles

Click chemistry has played a significant role as a rapid and versatile strategy for conjugating two molecular fragments under very mild reaction conditions. Introduction of ferrocene-derived triazole systems using click chemistry has attracted enormous interest in various fields due to its potential applications in electrochemical techniques for detection and sensing. The present discussion focuses on the synthesis of ferrocene-triazole and the importance of using a CuAAC reaction for such conjugation. Applications of ferrocene-based click reactions in conjugate chemistry, asymmetric catalysis, medicinal chemistry, host-guest interactions, and materials chemistry have been highlighted.

Factor graph based joint detection/decoding for LDPC coded large-MIMO systems

In this paper, we employ message passing algorithms over graphical models to jointly detect and decode symbols transmitted over large multiple-input multiple-output (MIMO) channels with low density parity check (LDPC) coded bits. We adopt a factor graph based technique to integrate the detection and decoding operations. A Gaussian approximation of spatial interference is used for detection. This serves as a low complexity joint detection/decoding approach for large dimensional MIMO systems coded with LDPC codes of large block lengths. This joint processing achieves significantly better performance than the individual detection and decoding scheme.

Low-pass filters and differential tympanal tuning in a paleotropical bushcricket with an unusually low frequency call

Low-frequency sounds are advantageous for long-range acoustic signal transmission, but for small animals they constitute a challenge for signal detection and localization. The efficient detection of sound in insects is enhanced by mechanical resonance either in the tracheal or tympanal system before subsequent neuronal amplification. Making small structures resonant at low sound frequencies poses challenges for insects and has not been adequately studied. Similarly, detecting the direction of long-wavelength sound using interaural signal amplitude and/or phase differences is difficult for small animals. Pseudophylline bushcrickets predominantly call at high, often ultrasonic frequencies, but a few paleotropical species use lower frequencies. We investigated the mechanical frequency tuning of the tympana of one such species, Onomarchus uninotatus, a large bushcricket that produces a narrow bandwidth call at an unusually low carrier frequency of 3.2. kHz. Onomarchus uninotatus, like most bushcrickets, has two large tympanal membranes on each fore-tibia. We found that both these membranes vibrate like hinged flaps anchored at the dorsal wall and do not show higher modes of vibration in the frequency range investigated (1.5-20. kHz). The anterior tympanal membrane acts as a low-pass filter, attenuating sounds at frequencies above 3.5. kHz, in contrast to the high-pass filter characteristic of other bushcricket tympana. Responses to higher frequencies are partitioned to the posterior tympanal membrane, which shows maximal sensitivity at several broad frequency ranges, peaking at 3.1, 7.4 and 14.4. kHz. This partitioning between the two tympanal membranes constitutes an unusual feature of peripheral auditory processing in insects. The complex tracheal shape of O. uninotatus also deviates from the known tube or horn shapes associated with simple band-pass or high-pass amplification of tracheal input to the tympana. Interestingly, while the anterior tympanal membrane shows directional sensitivity at conspecific call frequencies, the posterior tympanal membrane is not directional at conspecific frequencies and instead shows directionality at higher frequencies.

FeatureMatch: A General ANNF Estimation Technique and its Applications

In this paper, we propose FeatureMatch, a generalised approximate nearest-neighbour field (ANNF) computation framework, between a source and target image. The proposed algorithm can estimate ANNF maps between any image pairs, not necessarily related. This generalisation is achieved through appropriate spatial-range transforms. To compute ANNF maps, global colour adaptation is applied as a range transform on the source image. Image patches from the pair of images are approximated using low-dimensional features, which are used along with KD-tree to estimate the ANNF map. This ANNF map is further improved based on image coherency and spatial transforms. The proposed generalisation, enables us to handle a wider range of vision applications, which have not been tackled using the ANNF framework. We illustrate two such applications namely: 1) optic disk detection and 2) super resolution. The first application deals with medical imaging, where we locate optic disks in retinal images using a healthy optic disk image as common target image. The second application deals with super resolution of synthetic images using a common source image as dictionary. We make use of ANNF mappings in both these applications and show experimentally that our proposed approaches are faster and accurate, compared with the state-of-the-art techniques.

Exclusive Detection of Sub-Nanomolar Levels of Palladium(II) in Water: An Excellent Probe for Multiple Applications

A new colorimetric probe has been developed for the detection and estimation of Pd-II at sub-nanomolar concentrations. The probe consisted of rhodamine (signaling unit), which was linked with a bis-picolyl moiety (binding site) through a phenyl ring. Pd-II induced opening of the spirolactam ring of the probe with the generation of a prominent pink color. The excellent selectivity of the probe towards Pd-II over Pd-0 or Rh-II ensured its potential utility for the detection of residual palladium contamination in pharma-ceutical drugs and in Pd-catalyzed reactions. The probe showed a ``turn-on'' (bright yellow) fluorescence upon the addition of Pd-II, which made it suitable for the detection of Pd contaminants in mammalian cells.