Speed Neuro-fuzzy Estimator Applied To Sensorless Induction Motor Control

This work proposes the development of an Adaptive Neuro-fuzzy Inference System (ANFIS) estimator applied to speed control in a three-phase induction motor sensorless drive. Usually, ANFIS is used to replace the traditional PI controller in induction motor drives. The evaluation of the estimation capability of the ANFIS in a sensorless drive is one of the contributions of this work. The ANFIS speed estimator is validated in a magnetizing flux oriented control scheme, consisting in one more contribution. As an open-loop estimator, it is applied to moderate performance drives and it is not the proposal of this work to solve the low and zero speed estimation problems. Simulations to evaluate the performance of the estimator considering the vector drive system were done from the Matlab/Simulink(R) software. To determine the benefits of the proposed model, a practical system was implemented using a voltage source inverter (VSI) to drive the motor and the vector control including the ANFIS estimator, which is carried out by the Real Time Toolbox from Matlab/Simulink(R) software and a data acquisition card from National Instruments.

Maximal exercise test is a useful method for physical capacity and oxygen consumption determination in streptozotocin-diabetic rats

Abstract Background The aim of the present study was to investigate the relationship between speed during maximum exercise test (ET) and oxygen consumption (VO2) in control and STZ-diabetic rats, in order to provide a useful method to determine exercise capacity and prescription in researches involving STZ-diabetic rats. Methods Male Wistar rats were divided into two groups: control (CG, n = 10) and diabetic (DG, n = 8). The animals were submitted to ET on treadmill with simultaneous gas analysis through open respirometry system. ET and VO2 were assessed 60 days after diabetes induction (STZ, 50 mg/Kg). Results VO2 maximum was reduced in STZ-diabetic rats (72.5 ± 1 mL/Kg/min-1) compared to CG rats (81.1 ± 1 mL/Kg/min-1). There were positive correlations between ET speed and VO2 (r = 0.87 for CG and r = 0.8 for DG), as well as between ET speed and VO2 reserve (r = 0.77 for CG and r = 0.7 for DG). Positive correlations were also obtained between measured VO2 and VO2 predicted values (r = 0.81 for CG and r = 0.75 for DG) by linear regression equations to CG (VO2 = 1.54 * ET speed + 52.34) and DG (VO2 = 1.16 * ET speed + 51.99). Moreover, we observed that 60% of ET speed corresponded to 72 and 75% of VO2 reserve for CG and DG, respectively. The maximum ET speed was also correlated with VO2 maximum for both groups (CG: r = 0.7 and DG: r = 0.7). Conclusion These results suggest that: a) VO2 and VO2 reserve can be estimated using linear regression equations obtained from correlations with ET speed for each studied group; b) exercise training can be prescribed based on ET in control and diabetic-STZ rats; c) physical capacity can be determined by ET. Therefore, ET, which involves a relatively simple methodology and low cost, can be used as an indicator of cardio-respiratory capacity in future studies that investigate the physiological effect of acute or chronic exercise in control and STZ-diabetic male rats.

Reverse Engineering tools: development and experimentation of innovative methods for physical and geometrical data integration and post-processing

In recent years, the use of Reverse Engineering systems has got a considerable interest for a wide number of applications. Therefore, many research activities are focused on accuracy and precision of the acquired data and post processing phase improvements. In this context, this PhD Thesis deals with the definition of two novel methods for data post processing and data fusion between physical and geometrical information. In particular a technique has been defined for error definition in 3D points’ coordinates acquired by an optical triangulation laser scanner, with the aim to identify adequate correction arrays to apply under different acquisition parameters and operative conditions. Systematic error in data acquired is thus compensated, in order to increase accuracy value. Moreover, the definition of a 3D thermogram is examined. Object geometrical information and its thermal properties, coming from a thermographic inspection, are combined in order to have a temperature value for each recognizable point. Data acquired by an optical triangulation laser scanner are also used to normalize temperature values and make thermal data independent from thermal-camera point of view.

Application Platforms for the Internet of Things: Theory, Architecture, Protocols, Data Formats, and Privacy

The Internet of Things (IoT) is the next industrial revolution: we will interact naturally with real and virtual devices as a key part of our daily life. This technology shift is expected to be greater than the Web and Mobile combined. As extremely different technologies are needed to build connected devices, the Internet of Things field is a junction between electronics, telecommunications and software engineering. Internet of Things application development happens in silos, often using proprietary and closed communication protocols. There is the common belief that only if we can solve the interoperability problem we can have a real Internet of Things. After a deep analysis of the IoT protocols, we identified a set of primitives for IoT applications. We argue that each IoT protocol can be expressed in term of those primitives, thus solving the interoperability problem at the application protocol level. Moreover, the primitives are network and transport independent and make no assumption in that regard. This dissertation presents our implementation of an IoT platform: the Ponte project. Privacy issues follows the rise of the Internet of Things: it is clear that the IoT must ensure resilience to attacks, data authentication, access control and client privacy. We argue that it is not possible to solve the privacy issue without solving the interoperability problem: enforcing privacy rules implies the need to limit and filter the data delivery process. However, filtering data require knowledge of how the format and the semantics of the data: after an analysis of the possible data formats and representations for the IoT, we identify JSON-LD and the Semantic Web as the best solution for IoT applications. Then, this dissertation present our approach to increase the throughput of filtering semantic data by a factor of ten.

The APSEL4D Monolithic Active Pixel Sensor and its Usage in a Single Electron Interference Experiment

We have realized a Data Acquisition chain for the use and characterization of APSEL4D, a 32 x 128 Monolithic Active Pixel Sensor, developed as a prototype for frontier experiments in high energy particle physics. In particular a transition board was realized for the conversion between the chip and the FPGA voltage levels and for the signal quality enhancing. A Xilinx Spartan-3 FPGA was used for real time data processing, for the chip control and the communication with a Personal Computer through a 2.0 USB port. For this purpose a firmware code, developed in VHDL language, was written. Finally a Graphical User Interface for the online system monitoring, hit display and chip control, based on windows and widgets, was realized developing a C++ code and using Qt and Qwt dedicated libraries. APSEL4D and the full acquisition chain were characterized for the first time with the electron beam of the transmission electron microscope and with 55Fe and 90Sr radioactive sources. In addition, a beam test was performed at the T9 station of the CERN PS, where hadrons of momentum of 12 GeV/c are available. The very high time resolution of APSEL4D (up to 2.5 Mfps, but used at 6 kfps) was fundamental in realizing a single electron Young experiment using nanometric double slits obtained by a FIB technique. On high statistical samples, it was possible to observe the interference and diffractions of single isolated electrons traveling inside a transmission electron microscope. For the first time, the information on the distribution of the arrival time of the single electrons has been extracted.

Power Converters and Electric Drives for Smart Grid Applications

The present dissertation aims to explore, theoretically and experimentally, the problems and the potential advantages of different types of power converters for “Smart Grid” applications, with particular emphasis on multi-level architectures, which are attracting a rising interest even for industrial requests. The models of the main multilevel architectures (Diode-Clamped and Cascaded) are shown. The best suited modulation strategies to function as a network interface are identified. In particular, the close correlation between PWM (Pulse Width Modulation) approach and SVM (Space Vector Modulation) approach is highlighted. An innovative multilevel topology called MMC (Modular Multilevel Converter) is investigated, and the single-phase, three-phase and "back to back" configurations are analyzed. Specific control techniques that can manage, in an appropriate way, the charge level of the numerous capacitors and handle the power flow in a flexible way are defined and experimentally validated. Another converter that is attracting interest in “Power Conditioning Systems” field is the “Matrix Converter”. Even in this architecture, the output voltage is multilevel. It offers an high quality input current, a bidirectional power flow and has the possibility to control the input power factor (i.e. possibility to participate to active and reactive power regulations). The implemented control system, that allows fast data acquisition for diagnostic purposes, is described and experimentally verified.

Development of a microgrid with renewable energy sources and electrochemical storage system integration

Beside the traditional paradigm of "centralized" power generation, a new concept of "distributed" generation is emerging, in which the same user becomes pro-sumer. During this transition, the Energy Storage Systems (ESS) can provide multiple services and features, which are necessary for a higher quality of the electrical system and for the optimization of non-programmable Renewable Energy Source (RES) power plants. A ESS prototype was designed, developed and integrated into a renewable energy production system in order to create a smart microgrid and consequently manage in an efficient and intelligent way the energy flow as a function of the power demand. The produced energy can be introduced into the grid, supplied to the load directly or stored in batteries. The microgrid is composed by a 7 kW wind turbine (WT) and a 17 kW photovoltaic (PV) plant are part of. The load is given by electrical utilities of a cheese factory. The ESS is composed by the following two subsystems, a Battery Energy Storage System (BESS) and a Power Control System (PCS). With the aim of sizing the ESS, a Remote Grid Analyzer (RGA) was designed, realized and connected to the wind turbine, photovoltaic plant and the switchboard. Afterwards, different electrochemical storage technologies were studied, and taking into account the load requirements present in the cheese factory, the most suitable solution was identified in the high temperatures salt Na-NiCl2 battery technology. The data acquisition from all electrical utilities provided a detailed load analysis, indicating the optimal storage size equal to a 30 kW battery system. Moreover a container was designed and realized to locate the BESS and PCS, meeting all the requirements and safety conditions. Furthermore, a smart control system was implemented in order to handle the different applications of the ESS, such as peak shaving or load levelling.

Mobile phone technologies and advanced data analysis towards the enhancement of diabetes self-management

Advances in the area of mobile and wireless communication for healthcare (m-Health) along with the improvements in information science allow the design and development of new patient-centric models for the provision of personalised healthcare services, increase of patient independence and improvement of patient's self-control and self-management capabilities. This paper comprises a brief overview of the m-Health applications towards the self-management of individuals with diabetes mellitus and the enhancement of their quality of life. Furthermore, the design and development of a mobile phone application for Type 1 Diabetes Mellitus (T1DM) self-management is presented. The technical evaluation of the application, which permits the management of blood glucose measurements, blood pressure measurements, insulin dosage, food/drink intake and physical activity, has shown that the use of the mobile phone technologies along with data analysis methods might improve the self-management of T1DM.

Development of a model-based transient calibration process for diesel engine electronic control module tables – Part 2: modelling and optimization

This is the second part of a study investigating a model-based transient calibration process for diesel engines. The first part addressed the data requirements and data processing required for empirical transient emission and torque models. The current work focuses on modelling and optimization. The unexpected result of this investigation is that when trained on transient data, simple regression models perform better than more powerful methods such as neural networks or localized regression. This result has been attributed to extrapolation over data that have estimated rather than measured transient air-handling parameters. The challenges of detecting and preventing extrapolation using statistical methods that work well with steady-state data have been explained. The concept of constraining the distribution of statistical leverage relative to the distribution of the starting solution to prevent extrapolation during the optimization process has been proposed and demonstrated. Separate from the issue of extrapolation is preventing the search from being quasi-static. Second-order linear dynamic constraint models have been proposed to prevent the search from returning solutions that are feasible if each point were run at steady state, but which are unrealistic in a transient sense. Dynamic constraint models translate commanded parameters to actually achieved parameters that then feed into the transient emission and torque models. Combined model inaccuracies have been used to adjust the optimized solutions. To frame the optimization problem within reasonable dimensionality, the coefficients of commanded surfaces that approximate engine tables are adjusted during search iterations, each of which involves simulating the entire transient cycle. The resulting strategy, different from the corresponding manual calibration strategy and resulting in lower emissions and efficiency, is intended to improve rather than replace the manual calibration process.

Intravaginal practices, bacterial vaginosis, and HIV infection in women: individual participant data meta-analysis

Background Identifying modifiable factors that increase women's vulnerability to HIV is a critical step in developing effective female-initiated prevention interventions. The primary objective of this study was to pool individual participant data from prospective longitudinal studies to investigate the association between intravaginal practices and acquisition of HIV infection among women in sub-Saharan Africa. Secondary objectives were to investigate associations between intravaginal practices and disrupted vaginal flora; and between disrupted vaginal flora and HIV acquisition. Methods and Findings We conducted a meta-analysis of individual participant data from 13 prospective cohort studies involving 14,874 women, of whom 791 acquired HIV infection during 21,218 woman years of follow-up. Data were pooled using random-effects meta-analysis. The level of between-study heterogeneity was low in all analyses (I2 values 0.0%–16.1%). Intravaginal use of cloth or paper (pooled adjusted hazard ratio [aHR] 1.47, 95% confidence interval [CI] 1.18–1.83), insertion of products to dry or tighten the vagina (aHR 1.31, 95% CI 1.00–1.71), and intravaginal cleaning with soap (aHR 1.24, 95% CI 1.01–1.53) remained associated with HIV acquisition after controlling for age, marital status, and number of sex partners in the past 3 months. Intravaginal cleaning with soap was also associated with the development of intermediate vaginal flora and bacterial vaginosis in women with normal vaginal flora at baseline (pooled adjusted odds ratio [OR] 1.24, 95% CI 1.04–1.47). Use of cloth or paper was not associated with the development of disrupted vaginal flora. Intermediate vaginal flora and bacterial vaginosis were each associated with HIV acquisition in multivariable models when measured at baseline (aHR 1.54 and 1.69, p<0.001) or at the visit before the estimated date of HIV infection (aHR 1.41 and 1.53, p<0.001), respectively. Conclusions This study provides evidence to suggest that some intravaginal practices increase the risk of HIV acquisition but a direct causal pathway linking intravaginal cleaning with soap, disruption of vaginal flora, and HIV acquisition has not yet been demonstrated. More consistency in the definition and measurement of specific intravaginal practices is warranted so that the effects of specific intravaginal practices and products can be further elucidated.

An introduction to low-level analysis methods of DNA microarray data

This article gives an overview over the methods used in the low--level analysis of gene expression data generated using DNA microarrays. This type of experiment allows to determine relative levels of nucleic acid abundance in a set of tissues or cell populations for thousands of transcripts or loci simultaneously. Careful statistical design and analysis are essential to improve the efficiency and reliability of microarray experiments throughout the data acquisition and analysis process. This includes the design of probes, the experimental design, the image analysis of microarray scanned images, the normalization of fluorescence intensities, the assessment of the quality of microarray data and incorporation of quality information in subsequent analyses, the combination of information across arrays and across sets of experiments, the discovery and recognition of patterns in expression at the single gene and multiple gene levels, and the assessment of significance of these findings, considering the fact that there is a lot of noise and thus random features in the data. For all of these components, access to a flexible and efficient statistical computing environment is an essential aspect.

The neurophysiological time pattern of illusionary visual perceptual transitions: a simultaneous EEG and fMRI study

Several divergent cortical mechanisms generating multistability in visual perception have been suggested. Here, we investigated the neurophysiologic time pattern of multistable perceptual changes by means of a simultaneous recording with electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). Volunteers responded to the subjective perception of a sudden change between stable patterns of illusionary motion (multistable transition) during a stroboscopic paradigm. We found a global deceleration of the EEG frequency prior to a transition and an occipital-accentuated acceleration after a transition, as obtained by low-resolution electromagnetic tomography analysis (LORETA) analysis. A decrease in BOLD response was found in the prefrontal cortex before, and an increase after the transitions was observed in the right anterior insula, the MT/V5 regions and the SMA. The thalamus and left superior temporal gyrus showed a pattern of decrease before and increase after transitions. No such temporal course was found in the control condition. The multimodal approach of data acquisition allows us to argue that the top-down control of illusionary visual perception depends on selective attention, and that a diminution of vigilance reduces selective attention. These are necessary conditions to allow for the occurrence of a perception discontinuity in absence of a physical change of the stimulus.

Continuous monitoring of bovine spongiform encephalopathy rapid test performance by weak positive tissue controls and quality control charts

Bovine spongiform encephalopathy (BSE) rapid tests and routine BSE-testing laboratories underlie strict regulations for approval. Due to the lack of BSE-positive control samples, however, full assay validation at the level of individual test runs and continuous monitoring of test performance on-site is difficult. Most rapid tests use synthetic prion protein peptides, but it is not known to which extend they reflect the assay performance on field samples, and whether they are sufficient to indicate on-site assay quality problems. To address this question we compared the test scores of the provided kit peptide controls to those of standardized weak BSE-positive tissue samples in individual test runs as well as continuously over time by quality control charts in two widely used BSE rapid tests. Our results reveal only a weak correlation between the weak positive tissue control and the peptide control scores. We identified kit-lot related shifts in the assay performances that were not reflected by the peptide control scores. Vice versa, not all shifts indicated by the peptide control scores indeed reflected a shift in the assay performance. In conclusion these data highlight that the use of the kit peptide controls for continuous quality control purposes may result in unjustified rejection or acceptance of test runs. However, standardized weak positive tissue controls in combination with Shewhart-CUSUM control charts appear to be reliable in continuously monitoring assay performance on-site to identify undesired deviations.

Adolescent Sexual Behavior: Examining Data from Texas and the US

Background: The US has higher rates of teen births and sexually transmitted infections (STI) than other developed countries. Texas youth are disproportionately impacted. Purpose: To review local, state, and national data on teens’ engagement in sexual risk behaviors to inform policy and practice related to teen sexual health. Methods: 2009 middle school and high school Youth Risk Behavior Survey (YRBS) data, and data from All About Youth, a middle school study conducted in a large urban school district in Texas, were analyzed to assess the prevalence of sexual initiation, including the initiation of non-coital sex, and the prevalence of sexual risk behaviors among Texas and US youth. Results: A substantial proportion of middle and high school students are having sex. Sexual initiation begins as early as 6th grade and increases steadily through 12th grade with almost two-thirds of high school seniors being sexually experienced. Many teens are not protecting themselves from unintended pregnancy or STIs – nationally, 80% and 39% of high school students did not use birth control pills or a condom respectively the last time they had sex. Many middle and high school students are engaging in oral and anal sex, two behaviors which increase the risk of contracting an STI and HIV. In Texas, an estimated 689,512 out of 1,327,815 public high school students are sexually experienced – over half (52%) of the total high school population. Texas students surpass their US peers in several sexual risk behaviors including number of lifetime sexual partners, being currently sexually active, and not using effective methods of birth control or dual protection when having sex. They are also less likely to receive HIV/AIDS education in school. Conclusion: Changes in policy and practice, including implementation of evidence-based sex education programs in middle and high schools and increased access to integrated, teen-friendly sexual and reproductive health services, are urgently needed at the state and national levels to address these issues effectively.