Digital frequency relaying based on the modified least mean square method

This research presents a method for frequency estimation in power systems using an adaptive filter based on the Least Mean Square Algorithm (LMS). In order to analyze a power system, three-phase voltages were converted into a complex signal applying the alpha beta-transform and the results were used in an adaptive filtering algorithm. Although the use of the complex LMS algorithm is described in the literature, this paper deals with some practical aspects of the algorithm implementation. In order to reduce computing time, a coefficient generator was implemented. For the algorithm validation, a computing simulation of a power system was carried Out using the ATP software. Many different situations were Simulated for the performance analysis of the proposed methodology. The results were compared to a commercial relay for validation, showing the advantages of the new method. (C) 2009 Elsevier Ltd. All rights reserved.

Combined solution for fault location in three-terminal lines based on wavelet transforms

This work presents the study and development of a combined fault location scheme for three-terminal transmission lines using wavelet transforms (WTs). The methodology is based on the low- and high-frequency components of the transient signals originated from fault situations registered in the terminals of a system. By processing these signals and using the WT, it is possible to determine the time of travelling waves of voltages and/or currents from the fault point to the terminals, as well as estimate the fundamental frequency components. A new approach presents a reliable and accurate fault location scheme combining some different solutions. The main idea is to have a decision routine in order to select which method should be used in each situation presented to the algorithm. The combined algorithm was tested for different fault conditions by simulations using the ATP (Alternative Transients Program) software. The results obtained are promising and demonstrate a highly satisfactory degree of accuracy and reliability of the proposed method.

Noise reduction in biomedical speech signal processing based on time and frequency Kalman filtering combined with spectral subtraction

The goal of this paper is to study and propose a new technique for noise reduction used during the reconstruction of speech signals, particularly for biomedical applications. The proposed method is based on Kalman filtering in the time domain combined with spectral subtraction. Comparison with discrete Kalman filter in the frequency domain shows better performance of the proposed technique. The performance is evaluated by using the segmental signal-to-noise ratio and the Itakura-Saito`s distance. Results have shown that Kalman`s filter in time combined with spectral subtraction is more robust and efficient, improving the Itakura-Saito`s distance by up to four times. (C) 2007 Elsevier Ltd. All rights reserved.

Efficiency and feasibility of product disassembly: A case-based study

The productivity associated with commonly available disassembly methods today seldomly makes disassembly the preferred end-of-life solution for massive take back product streams. Systematic reuse of parts or components, or recycling of pure material fractions are often not achievable in an economically sustainable way. In this paper a case-based review of current disassembly practices is used to analyse the factors influencing disassembly feasibility. Data mining techniques were used to identify major factors influencing the profitability of disassembly operations. Case characteristics such as involvement of the product manufacturer in the end-of-life treatment and continuous ownership are some of the important dimensions. Economic models demonstrate that the efficiency of disassembly operations should be increased an order of magnitude to assure the competitiveness of ecologically preferred, disassembly oriented end-of-life scenarios for large waste of electric and electronic equipment (WEEE) streams. Technological means available to increase the productivity of the disassembly operations are summarized. Automated disassembly techniques can contribute to the robustness of the process, but do not allow to overcome the efficiency gap if not combined with appropriate product design measures. Innovative, reversible joints, collectively activated by external trigger signals, form a promising approach to low cost, mass disassembly in this context. A short overview of the state-of-the-art in the development of such self-disassembling joints is included. (c) 2008 CIRP.

Optimization of modal filters based on arrays of piezoelectric sensors

Modal filters may be obtained by a properly designed weighted sum of the output signals of an array of sensors distributed on the host structure. Although several research groups have been interested in techniques for designing and implementing modal filters based on a given array of sensors, the effect of the array topology on the effectiveness of the modal filter has received much less attention. In particular, it is known that some parameters, such as size, shape and location of a sensor, are very important in determining the observability of a vibration mode. Hence, this paper presents a methodology for the topological optimization of an array of sensors in order to maximize the effectiveness of a set of selected modal filters. This is done using a genetic algorithm optimization technique for the selection of 12 piezoceramic sensors from an array of 36 piezoceramic sensors regularly distributed on an aluminum plate, which maximize the filtering performance, over a given frequency range, of a set of modal filters, each one aiming to isolate one of the first vibration modes. The vectors of the weighting coefficients for each modal filter are evaluated using QR decomposition of the complex frequency response function matrix. Results show that the array topology is not very important for lower frequencies but it greatly affects the filter effectiveness for higher frequencies. Therefore, it is possible to improve the effectiveness and frequency range of a set of modal filters by optimizing the topology of an array of sensors. Indeed, using 12 properly located piezoceramic sensors bonded on an aluminum plate it is shown that the frequency range of a set of modal filters may be enlarged by 25-50%.

Computational Method to Determine Reflected Ultrasonic Signals From Arbitrary-Geometry Targets

A computational method based on the impulse response and on the discrete representation computational concept is proposed for the determination of the echo responses from arbitrary-geometry targets. It is supposed that each point of the transducer aperture can be considered as a source radiating hemispherical waves to the reflector. The local interaction with each of the hemispherical waves at the reflector surface can be modeled as a plane wave impinging on a planar surface, using the respective reflection coefficient. The method is valid for all field regions and can be performed for any excitation waveform radiated from an arbitrary acoustic aperture. The effects of target geometry, position, and material on both the amplitude and the shape of the echo response are studied. The model is compared with experimental results obtained using broadband transducers together with plane and cylindrical concave rectangular reflectors (aluminum, brass, and acrylic), as well as a circular cavity placed on a plane surface, in a water medium. The method can predict the measured echoes accurately. This paper shows an improved approach of the method, considering the reflection coefficient for all incident hemispherical waves arriving at each point of the target surface.

INVESTIGATION OF ACOUSTIC SIGNALS AS A TOOL FOR CHARACTERIZING SPOUTED BED DYNAMICS

The feasibility of characterizing the dynamics of a spouted bed based on acoustic emission (AE) signals is evaluated. Acoustic emission signals were measured in a semi-cylindrical Plexiglas column of diameter 150 mm and height 1000 mm with a conical base of internal angle 60 degrees and 25 mm inlet orifice diameter. Data were obtained for U/U(ms), from 0.3 to 2.0, static bed height from 250 to 500 mm, and glass beads of diameter 1.2 and 2.4 mm. AE signals reflected the effects of particle size and U/U(ms), but in general were insensitive to bed depth, even when there were drastic changes in spouting flow patterns. The results indicate that the AE signals were insensitive to the spouted bed hydrodynamics for the conditions studied. Overall, it appears that the AE analysis is unlikely to be a suitable technique for discriminating spouted bed flow regimes, at least for the range of frequencies and operating conditions investigated.

Finger and A-B ridge count, and fluctuating asymmetry in psychosis: A catchment area case-control study

Dermatoglyphic measures are of interest to schizophrenia research because they serve as persistent markers of deviant development in foetal life. Several studies have reported alterations in A–B ridge counts, total finger ridge counts and measures related to asymmetry in schizophrenia. The aim of this study was to assess these measures in an Australian catchment area, case-control study. Individuals with psychosisŽns246.were drawn from a catchment-area prevalence study, and well controlsŽns229. were recruited from the same area. Finger and palm prints were taken usingan inkless technique and all dermatoglyphic measures were assessed by a trained rater blind to case status. The dermatoglyphic measures Žfinger ridge count, A–B ridge count, and their derived asymmetry measures. were divided into quartiles based on the distribution of these variables in controls. The main analysis Žlogistic regression controlled for age and sex.examined all psychotic disorders, with planned subgroup analyses comparing controls with Ž1. nonaffective psychosis Žschizophrenia, delusional disorder, schizophreniform psychosis, atypical psychosis.andŽ2. affective psychosis Ždepression with psychosis, bipolar disorder, schizoaffective psychosis.. There were no statistically significant alterations in the odds of havinga psychotic disorder for any of the dermatoglyphic measures. The results did not change when we examined affective and nonaffective psychosis separately. The dermatoglyphic features that distinguish schizophreniar psychosis in other studies were not identified in this Australian study. Regional variations in these findings may provide clues to differential ethnicrgenetic and environmental factors that are associated with schizophrenia. The Stanley Foundation supported this project.

Nestmate recognition in the stingless bee Frieseomelitta varia (Hymenoptera, Apidae, Meliponini): sources of chemical signals

Social insects use cuticular lipids for nestmate recognition. These lipids are chiefly hydrocarbons that can be endogenously produced or acquired from the environment. Although these compounds are already described as coming from different sources for different groups of social insects, nothing is known about the source of cuticular hydrocarbons in stingless bees. We used behavioural recognition tests and cuticle chemical investigation to elucidate the role of endogenous and environmentally based cues for nestmate recognition in the stingless bee Frieseomelitta varia. We found that although newly emerged workers present specific cuticle patterns according to their nest origin, these compounds are not used for nestmate recognition, since newly emerged workers are broadly accepted in different colonies. The cerumen used in nest construction played an important role in recognition behaviour. Twenty minutes of contact with foreign cerumen was sufficient to increase the rejection rates of nestmates and separate the groups of workers according to their chemical profile. On the other hand, tests of feeding on a common diet showed no effect on chemical cuticle pattern or recognition behaviour. (C) 2010 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

The use of electrospray ionization tandem mass spectrometry on the structural characterization of novel asymmetric metallo-organic supermolecules, based on pentafluorophenylporphyrins and ruthenium complexes

The novel asymmetric metallo-organic triads cis- and trans-[B(4-py)BPFPH(2){Ru(3)O(Ac)(6)(py)(2)}(Ru(bpy)(2)Cl}](PF(6))(2) (5a,b) for which cis- and trans-B(4-py)BPFPH(2)=5,10-bis(pentafluorophenyl)-15,20-bis(4-pyridyl)porphyrin and 5,15-bis(pentafluorophenyl)-10,20-bis(4-pyridyl)porphyrin, respectively; Ac = acetate; py = pyridine and bpy = 2,2`-bipyridine, as well as their corresponding monosubstituted dyads cis- and trans-[B(4-py)BPFPH(2){Ru(3)O(Ac)(6)(py)(2)}]PF(6) (4a,b) have been structurally characterized via electrospray ionization mass spectrometry (ESI-MS and ESI-MS/MS). The ESI-MS of dyads 4a,b display two characteristic Ru-multicomponent clusters of isotopologue ions corresponding to singly charged ions 4a,b(+) of m/z 1629 and doubly charged ions [4a,b+H](2+) of m/z 815 and the triads 5a,b are detected by ESI-MS as the intact doubly charged cluster of isotopologue ions of m/z 1039 [5a,b](2+). The ESI-MS/MS of 4a,b(+), [4a,b+H](2+) and [5a,b](2+) reveal characteristic dissociation pathways, which confirm the structural assignments providing additional information on the intrinsic binding strengths of the gaseous ions. Although the gas-phase behavior of each pair of isomers was rather similar, the less symmetric dyads 4a,b are distinguished via the (1)H NMR spectral profile of the pyrrolic signals. Exploratory photophysical assays have shown that both modifying motifs alter the porphyrinic core emission profile, opening the possibility to use these asymmetric systems as photophysical devices. (C) 2008 Elsevier Ltd. All rights reserved.

EEG-based Brain-Computer Interfaces: An Overview of Basic Concepts and Clinical Applications in Neurorehabilitation

Some patients are no longer able to communicate effectively or even interact with the outside world in ways that most of us take for granted. In the most severe cases, tetraplegic or post-stroke patients are literally `locked in` their bodies, unable to exert any motor control after, for example, a spinal cord injury or a brainstem stroke, requiring alternative methods of communication and control. But we suggest that, in the near future, their brains may offer them a way out. Non-invasive electroencephalogram (EEG)-based brain-computer interfaces (BCD can be characterized by the technique used to measure brain activity and by the way that different brain signals are translated into commands that control an effector (e.g., controlling a computer cursor for word processing and accessing the internet). This review focuses on the basic concepts of EEG-based BC!, the main advances in communication, motor control restoration and the down-regulation of cortical activity, and the mirror neuron system (MNS) in the context of BCI. The latter appears to be relevant for clinical applications in the coming years, particularly for severely limited patients. Hypothetically, MNS could provide a robust way to map neural activity to behavior, representing the high-level information about goals and intentions of these patients. Non-invasive EEG-based BCIs allow brain-derived communication in patients with amyotrophic lateral sclerosis and motor control restoration in patients after spinal cord injury and stroke. Epilepsy and attention deficit and hyperactive disorder patients were able to down-regulate their cortical activity. Given the rapid progression of EEG-based BCI research over the last few years and the swift ascent of computer processing speeds and signal analysis techniques, we suggest that emerging ideas (e.g., MNS in the context of BC!) related to clinical neuro-rehabilitation of severely limited patients will generate viable clinical applications in the near future.

Strategies for genetic model specification in the screening of genome-wide meta-analysis signals for further replication

Background Meta-analysis is increasingly being employed as a screening procedure in large-scale association studies to select promising variants for follow-up studies. However, standard methods for meta-analysis require the assumption of an underlying genetic model, which is typically unknown a priori. This drawback can introduce model misspecifications, causing power to be suboptimal, or the evaluation of multiple genetic models, which augments the number of false-positive associations, ultimately leading to waste of resources with fruitless replication studies. We used simulated meta-analyses of large genetic association studies to investigate naive strategies of genetic model specification to optimize screenings of genome-wide meta-analysis signals for further replication. Methods Different methods, meta-analytical models and strategies were compared in terms of power and type-I error. Simulations were carried out for a binary trait in a wide range of true genetic models, genome-wide thresholds, minor allele frequencies (MAFs), odds ratios and between-study heterogeneity (tau(2)). Results Among the investigated strategies, a simple Bonferroni-corrected approach that fits both multiplicative and recessive models was found to be optimal in most examined scenarios, reducing the likelihood of false discoveries and enhancing power in scenarios with small MAFs either in the presence or in absence of heterogeneity. Nonetheless, this strategy is sensitive to tau(2) whenever the susceptibility allele is common (MAF epsilon 30%), resulting in an increased number of false-positive associations compared with an analysis that considers only the multiplicative model. Conclusion Invoking a simple Bonferroni adjustment and testing for both multiplicative and recessive models is fast and an optimal strategy in large meta-analysis-based screenings. However, care must be taken when examined variants are common, where specification of a multiplicative model alone may be preferable.

Analyzing the connectivity between regions of interest: An approach based on cluster Granger causality for NRI data analysis

The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.

Can ECG changes predict the long-term outcome in patients admitted to hospital for suspected acute myocardial infarction?

7,028 patients with suspected acute myocardial infarction and discharged alive from hospital were followed in a 10-year community-based study. The long-term prognosis was relatively good if the electrocardiograms (ECGs) were normal (5-year all-cause death rate 5%), poor with uncodable ECGs showing rhythm or conduction disturbances (37%), and intermediate with new Q wave, new ST elevation, new T wave inversion or ischemic ECG (17-21%), and with new ST depression (27%). Similar patterns were found for ischemic cardiac death and reinfarction. The long-term prognosis of patients with suspected acute myocardial infarction is relatively good if the ECGs are normal and poor if ECGs are uncodable. ST depression may be a marker for a worse long-term outcome.

Direct measurement of instantaneous source speed for a HDR brachytherapy unit using an optical fiber based detector

Purpose: Several attempts to determine the transit time of a high dose rate (HDR) brachytherapy unit have been reported in the literature with controversial results. The determination of the source speed is necessary to accurately calculate the transient dose in brachytherapy treatments. In these studies, only the average speed of the source was measured as a parameter for transit dose calculation, which does not account for the realistic movement of the source, and is therefore inaccurate for numerical simulations. The purpose of this work is to report the implementation and technical design of an optical fiber based detector to directly measure the instantaneous speed profile of a (192)Ir source in a Nucletron HDR brachytherapy unit. Methods: To accomplish this task, we have developed a setup that uses the Cerenkov light induced in optical fibers as a detection signal for the radiation source moving inside the HDR catheter. As the (192)Ir source travels between two optical fibers with known distance, the threshold of the induced signals are used to extract the transit time and thus the velocity. The high resolution of the detector enables the measurement of the transit time at short separation distance of the fibers, providing the instantaneous speed. Results: Accurate and high resolution speed profiles of the 192Ir radiation source traveling from the safe to the end of the catheter and between dwell positions are presented. The maximum and minimum velocities of the source were found to be 52.0 +/- 1.0 and 17.3 +/- 1:2 cm/s. The authors demonstrate that the radiation source follows a uniformly accelerated linear motion with acceleration of vertical bar a vertical bar = 113 cm/s(2). In addition, the authors compare the average speed measured using the optical fiber detector to those obtained in the literature, showing deviation up to 265%. Conclusions: To the best of the authors` knowledge, the authors directly measured for the first time the instantaneous speed profile of a radiation source in a HDR brachytherapy unit traveling from the unit safe to the end of the catheter and between interdwell distances. The method is feasible and accurate to implement on quality assurance tests and provides a unique database for efficient computational simulations of the transient dose. (C) 2010 American Association of Physicists in Medicine. [DOI: 10.1118/1.3483780]