Controller system design using the coefficient diagram method

Coefficient diagram method is a controller design technique for linear time-invariant systems. This design procedure occurs into two different domains: an algebraic and a graphical. The former is closely paired to a conventional pole placement method and the latter consists on a diagram whose reading from the plotted curves leads to insights regarding closed-loop control system time response, stability and robustness. The controller structure has two degrees of freedom and the design process leads to both low overshoot closed-loop time response and good robustness performance regarding mismatches between the real system and the design model. This article presents an overview on this design method. In order to make more transparent the presented theoretical concepts, examples in Matlab®code are provided. The included code illustrates both the algebraic and the graphical nature of the coefficient diagram design method. © 2016, King Fahd University of Petroleum & Minerals.

QUALIDADE FISIOLÓGICA DE SEMENTES DE Tabernaemontana fuchsiaefolia A. DC EM FUNÇÃO DO TESTE DE ENVELHECIMENTO ACELERADO1

Tabernaemontana fuchsiaefolia A. DC é uma espécie da família Apocynaceae, nativa do Brasil, com característica invasora, possuindo potencial para uso em recuperação de áreas degradadas. O trabalho teve o objetivo de avaliar a influência dos métodos de envelhecimento acelerado sobre a qualidade fisiológica e germinação de sementes, utilizando-se o método tradicional e em solução de NaCl, empregando-se a metodologia de gerbox, formando minicâmaras de envelhecimento, em três temperaturas (41, 43 e 45°C) e cinco tempos de envelhecimento (0, 24, 48, 72 e 96 horas). As sementes, após o envelhecimento, foram colocadas para germinar em rolos de papel germitest, em quatro repetições de 25 sementes, em câmaras BOD a temperatura de 30°C, com fotoperíodo de 8 horas. O efeito da temperatura foi comparado pelo teste de Tukey em nível de 5% de probabilidade e o efeito do tempo de envelhecimento, pela análise de regressão. Após 35 dias, foram avaliados percentual, índice de velocidade, tempo médio e frequência da germinação, bem como comprimento de raiz e parte aérea, massa seca de plântulas e percentual de plântulas normais. Observou-se que o método alternativo de envelhecimento com solução de NaCl teve pouca influência na qualidade das sementes, não sendo indicado para testes de vigor para a espécie. O método tradicional, na temperatura de 45°C em período de envelhecimento de 96 horas, promoveu queda na germinação e pode ser utilizado para testar o vigor de sementes de leiteira.

Método para reconhecimento de vogais e extração de parâmetros acústicos para analises forenses

Forensic speaker comparison exams have complex characteristics, demanding a long time for manual analysis. A method for automatic recognition of vowels, providing feature extraction for acoustic analysis is proposed, aiming to contribute as a support tool in these exams. The proposal is based in formant measurements by LPC (Linear Predictive Coding), selectively by fundamental frequency detection, zero crossing rate, bandwidth and continuity, with the clustering being done by the k-means method. Experiments using samples from three different databases have shown promising results, in which the regions corresponding to five of the Brasilian Portuguese vowels were successfully located, providing visualization of a speaker’s vocal tract behavior, as well as the detection of segments corresponding to target vowels.

Nuclear alterations in nasal mucosa epithelial cells of students exposed to formaldehyde

Introduction: Formaldehyde is a compound with a wide range and is commonly used in anatomy and pathology laboratories. At room temperature is quickly volatilized to a pungent and suffocating gas and its inhalation has been correlated to nuclear alterations in different tissues. We aimed to investigate whether exposure to this compound was correlated with the appearance of cytotoxic and genotoxic features in the nasal epithelial cells of students enrolled in a human anatomy course. Material and Methods: This prospective study collected periodically nasal cells from mucosa of 17 volunteers from two different undergraduate programs with different workloads of practical lessons in an anatomy laboratory, 30 and 90 hours per semester. Cells were staining according to Feulgen method and nuclear morphology was analyzed to detect possible damage. Dunn's post hoc test was used in the statistical analysis. Pearson's correlation was performed for gender, age and questionnaire responses. Results: Epithelial cells showed indicators of cytotoxicity and mutagenicity. Students with a more extensive workload in anatomy laboratory displayed a more severe profile with an increase in karyorrhexis (p < 0.05) over time. The micronucleus analysis showed difference between first and second collection (p < 0.01), although it was not maintained over the time. Students with a less extensive workload display no differences in most of cytological features. Despite karyorrhexis was present in a greater number of cells, for this group no significant difference was observed between any range. The same was observed to karyolysis and micronucleus (p > 0.05). Conclusion: Individuals exposed for short periods of time to formaldehyde are subject to the toxic action of this gas. Karyorrhexis was the most frequently observed cytotoxic feature and micronucleus showed an increase between the first time point. The patterns observed between the student's groups suggest a negative effect due to exposure time.

A diffuse reflectance comparative study of benzil inclusion within p-tert-butylcalix[n]arenes (n=4, 6, and 8) and silicalite

Diffuse reflectance and laser-induced techniques were used to access photochemical and photophysical processes of benzil in solid supports, namely p-tert-butylcalix[n]arenes with n = 4, 6, and 8. A comparative study was performed using these results and those obtained with another electronically inert support, silicalite, which is a hydrophobic zeolite. In the latter substrate, ground-state benzil has the two carbonyl groups in an s-trans planar conformation while in the calixarenes a distribution of conformers exists, largely dominated by skew conformations where the carbonyl groups are twisted one to the other. In all substrates, room-temperature phosphorescence was obtained in air-equilibrated samples. The decay times vary greatly and the largest lifetime was obtained for benzil/p-tert-butylcalix[6]arene, showing that this host cavity well accommodates benzil, enhancing its room-temperature phosphorescence. p-tert-Butylcalix[6] and [8]arene molecules provide larger hydrophobic cavities than silicalite, and inclusion complexes are formed with these hosts and benzil as guest; p-tert-butylcalix[4]arene does not include benzil. This probe is deposited outside the calix[41 cavity, in the form of microcrystals. Triplet-triplet absorption of benzil was detected in all cases and is predominant in the silicalite channel inclusion case. Benzil ketyl radical formation occurs with inclusion in calix[6]arene and calix[8]arene. In the three cases, benzoyl radical was detected at long times (in the millisecond time scale). Product analysis and identification clearly show that the main detected degradation photoproducts in all substrates are benzoyl radical derivatives. Calix[6] and [8]arenes are able to supply hydrogen atoms that allow also another reaction, the reduction to benzoin through benzil ketyl radical formation.

COMPOSITION OF FRESHLY HARVESTED BRAZILIAN ROYAL JELLY - IDENTIFICATION OF CARBOHYDRATES FROM THE SUGAR FRACTION

Samples of Brazilian royal jelly from Africanized Apis mellifera were analysed in order to determine the gross composition: crude moisture ranged from 67.80% to 69.40%, crude protein from 15.80% to 16.70%, crude lipid from 2.90% to 3.98% and-total sugars from 11.40% to 11.50%. The sugar fraction was investigated and revealed the presence of the following compounds identified by their retention time during HPLC analysis: ribose, fructose, glucose, sucrose, mannose, trehalose, erythritol, adonitol and mannitol.

Non-invasive winding fault detection for induction machines based on stray flux magnetic sensors

Non-intrusive monitoring of health state of induction machines within industrial process and harsh environments poses a technical challenge. In the field, winding failures are a major fault accounting for over 45% of total machine failures. In the literature, many condition monitoring techniques based on different failure mechanisms and fault indicators have been developed where the machine current signature analysis (MCSA) is a very popular and effective method at this stage. However, it is extremely difficult to distinguish different types of failures and hard to obtain local information if a non-intrusive method is adopted. Typically, some sensors need to be installed inside the machines for collecting key information, which leads to disruption to the machine operation and additional costs. This paper presents a new non-invasive monitoring method based on GMRs to measure stray flux leaked from the machines. It is focused on the influence of potential winding failures on the stray magnetic flux in induction machines. Finite element analysis and experimental tests on a 1.5-kW machine are presented to validate the proposed method. With time-frequency spectrogram analysis, it is proven to be effective to detect several winding faults by referencing stray flux information. The novelty lies in the implement of GMR sensing and analysis of machine faults.

Radio frequency communication and fault detection for railway signalling

The continuous and swift progression of both wireless and wired communication technologies in today's world owes its success to the foundational systems established earlier. These systems serve as the building blocks that enable the enhancement of services to cater to evolving requirements. Studying the vulnerabilities of previously designed systems and their current usage leads to the development of new communication technologies replacing the old ones such as GSM-R in the railway field. The current industrial research has a specific focus on finding an appropriate telecommunication solution for railway communications that will replace the GSM-R standard which will be switched off in the next years. Various standardization organizations are currently exploring and designing a radiofrequency technology based standard solution to serve railway communications in the form of FRMCS (Future Railway Mobile Communication System) to substitute the current GSM-R. Bearing on this topic, the primary strategic objective of the research is to assess the feasibility to leverage on the current public network technologies such as LTE to cater to mission and safety critical communication for low density lines. The research aims to identify the constraints, define a service level agreement with telecom operators, and establish the necessary implementations to make the system as reliable as possible over an open and public network, while considering safety and cybersecurity aspects. The LTE infrastructure would be utilized to transmit the vital data for the communication of a railway system and to gather and transmit all the field measurements to the control room for maintenance purposes. Given the significance of maintenance activities in the railway sector, the ongoing research includes the implementation of a machine learning algorithm to detect railway equipment faults, reducing time and human analysis errors due to the large volume of measurements from the field.

Wavelet correlation between subjects: A time-scale data driven analysis for brain mapping using fMRI

Functional magnetic resonance imaging (fMRI) based on BOLD signal has been used to indirectly measure the local neural activity induced by cognitive tasks or stimulation. Most fMRI data analysis is carried out using the general linear model (GLM), a statistical approach which predicts the changes in the observed BOLD response based on an expected hemodynamic response function (HRF). In cases when the task is cognitively complex or in cases of diseases, variations in shape and/or delay may reduce the reliability of results. A novel exploratory method using fMRI data, which attempts to discriminate between neurophysiological signals induced by the stimulation protocol from artifacts or other confounding factors, is introduced in this paper. This new method is based on the fusion between correlation analysis and the discrete wavelet transform, to identify similarities in the time course of the BOLD signal in a group of volunteers. We illustrate the usefulness of this approach by analyzing fMRI data from normal subjects presented with standardized human face pictures expressing different degrees of sadness. The results show that the proposed wavelet correlation analysis has greater statistical power than conventional GLM or time domain intersubject correlation analysis. (C) 2010 Elsevier B.V. All rights reserved.

Power quality analysis applying a hybrid methodology with wavelet transforms and neural networks

A hybrid system to automatically detect, locate and classify disturbances affecting power quality in an electrical power system is presented in this paper. The disturbances characterized are events from an actual power distribution system simulated by the ATP (Alternative Transients Program) software. The hybrid approach introduced consists of two stages. In the first stage, the wavelet transform (WT) is used to detect disturbances in the system and to locate the time of their occurrence. When such an event is flagged, the second stage is triggered and various artificial neural networks (ANNs) are applied to classify the data measured during the disturbance(s). A computational logic using WTs and ANNs together with a graphical user interface (GU) between the algorithm and its end user is then implemented. The results obtained so far are promising and suggest that this approach could lead to a useful application in an actual distribution system. (C) 2009 Elsevier Ltd. All rights reserved.

Further results on the relationship between mu-invariant measures and quasi-stationary distributions for absorbing continuous-time Markov chains

This note considers continuous-time Markov chains whose state space consists of an irreducible class, C, and an absorbing state which is accessible from C. The purpose is to provide results on mu-invariant and mu-subinvariant measures where absorption occurs with probability less than one. In particular, the well-known premise that the mu-invariant measure, m, for the transition rates be finite is replaced by the more natural premise that m be finite with respect to the absorption probabilities. The relationship between mu-invariant measures and quasi-stationary distributions is discussed. (C) 2000 Elsevier Science Ltd. All rights reserved.

Comparative analysis of time-frequency methods estimating the time-varying microstructure of sleep EEG spindles

Proceedings of the Information Technology Applications in Biomedicine, Ioannina - Epirus, Greece, October 26-28, 2006

Automatic Small Bowel Tumor Diagnosis by Using Multi-Scale Wavelet-Based Analysis in Wireless Capsule Endoscopy Images

BACKGROUND: Wireless capsule endoscopy has been introduced as an innovative, non-invasive diagnostic technique for evaluation of the gastrointestinal tract, reaching places where conventional endoscopy is unable to. However, the output of this technique is an 8 hours video, whose analysis by the expert physician is very time consuming. Thus, a computer assisted diagnosis tool to help the physicians to evaluate CE exams faster and more accurately is an important technical challenge and an excellent economical opportunity. METHOD: The set of features proposed in this paper to code textural information is based on statistical modeling of second order textural measures extracted from co-occurrence matrices. To cope with both joint and marginal non-Gaussianity of second order textural measures, higher order moments are used. These statistical moments are taken from the two-dimensional color-scale feature space, where two different scales are considered. Second and higher order moments of textural measures are computed from the co-occurrence matrices computed from images synthesized by the inverse wavelet transform of the wavelet transform containing only the selected scales for the three color channels. The dimensionality of the data is reduced by using Principal Component Analysis. RESULTS: The proposed textural features are then used as the input of a classifier based on artificial neural networks. Classification performances of 93.1% specificity and 93.9% sensitivity are achieved on real data. These promising results open the path towards a deeper study regarding the applicability of this algorithm in computer aided diagnosis systems to assist physicians in their clinical practice.

Analysis of an iterative deconvolution approach for estimating the source wavelet during waveform inversion of crosshole ground-penetrating radar data

A major issue in the application of waveform inversion methods to crosshole georadar data is the accurate estimation of the source wavelet. Here, we explore the viability and robustness of incorporating this step into a time-domain waveform inversion procedure through an iterative deconvolution approach. Our results indicate that, at least in non-dispersive electrical environments, such an approach provides remarkably accurate and robust estimates of the source wavelet even in the presence of strong heterogeneity in both the dielectric permittivity and electrical conductivity. Our results also indicate that the proposed source wavelet estimation approach is relatively insensitive to ambient noise and to the phase characteristics of the starting wavelet. Finally, there appears to be little-to-no trade-off between the wavelet estimation and the tomographic imaging procedures.