REAL TIME FUZZY CONTROLLER FOR QUADROTOR STABILITY CONTROL

In this report, we develop an intelligent adaptive neuro-fuzzy controller by using adaptive neuro fuzzy inference system (ANFIS) techniques. We begin by starting with a standard proportional-derivative (PD) controller and use the PD controller data to train the ANFIS system to develop a fuzzy controller. We then propose and validate a method to implement this control strategy on commercial off-the-shelf (COTS) hardware. An analysis is made into the choice of filters for attitude estimation. These choices are limited by the complexity of the filter and the computing ability and memory constraints of the micro-controller. Simplified Kalman filters are found to be good at estimation of attitude given the above constraints. Using model based design techniques, the models are implemented on an embedded system. This enables the deployment of fuzzy controllers on enthusiast-grade controllers. We evaluate the feasibility of the proposed control strategy in a model-in-the-loop simulation. We then propose a rapid prototyping strategy, allowing us to deploy these control algorithms on a system consisting of a combination of an ARM-based microcontroller and two Arduino-based controllers. We then use a combination of the code generation capabilities within MATLAB/Simulink in combination with multiple open-source projects in order to deploy code to an ARM CortexM4 based controller board. We also evaluate this strategy on an ARM-A8 based board, and a much less powerful Arduino based flight controller. We conclude by proving the feasibility of fuzzy controllers on Commercial-off the shelf (COTS) hardware, we also point out the limitations in the current hardware and make suggestions for hardware that we think would be better suited for memory heavy controllers.

Preface to Models@run.time 2016

The complexity of adapting software during runtime has spawned interest in how models can be used to validate, monitor and adapt runtime behaviour. The use of models during runtime extends the use of modeling techniques beyond the design and implementation phases. The goal of this workshop is to look at issues related to developing appropriate modeldriven approaches to managing and monitoring the execution of systems and, also, to allow the system to reason about itself. We aim to continue the discussion of research ideas and proposals from researchers who work in relevant areas such as MDE, software architectures, reflection, and autonomic and self-adaptive systems, and provide a 'state-of-the-art' research assessment expressed in terms of challenges and achievements.

Characterization of the volatile profile of Brazilian Merlot wines through comprehensive two dimensional gas chromatography time-of-flight mass spectrometric detection.

Wine aroma is an important characteristic and may be related to certain specific parameters, such as raw material and production process. The complexity of Merlot wine aroma was considered suitable for comprehensive two-dimensional gas chromatography (GCGC), as this technique offers superior performance when compared to one-dimensional gas chromatography (1D-GC). The profile of volatile compounds of Merlot wine was, for the first time, qualitatively analyzed by HS-SPME-GCxGC with a time-of-flight mass spectrometric detector (TOFMS), resulting in 179 compounds tentatively identified by comparison of experimental GCxGC retention indices and mass spectra with literature 1D-GC data and 155 compounds tentatively identified only by mass spectra comparison. A set of GCGC experimental retention indices was also, for the first time, presented for a specific inverse set of columns. Esters were present in higher number (94), followed by alcohols (80), ketones (29), acids (29), aldehydes (23), terpenes (23), lactones (16), furans (14), sulfur compounds (9), phenols (7), pyrroles (5), C13-norisoprenoids (3), and pyrans (2). GCxGC/TOFMS parameters were improved and optimal conditions were: a polar (polyethylene glycol)/medium polar (50% phenyl 50% dimethyl arylene siloxane) column set, oven temperature offset of 10ºC, 7 s as modulation period and 1.4 s of hot pulse duration. Co-elutions came up to 138 compounds in 1D and some of them were resolved in 2D. Among the coeluted compounds, thirty-three volatiles co-eluted in both 1D and 2D and their tentative identification was possible only due to spectral deconvolution. Some compounds that might have important contribution to aroma notes were included in these superimposed peaks. Structurally organized distribution of compounds in the 2D space was observed for esters, aldehydes and ketones, alcohols, thiols, lactones, acids and also inside subgroups, as occurred with esters and alcohols. The Fischer Ratio was useful for establishing the analytes responsible for the main differences between Merlot and non-Merlot wines. Differentiation among Merlot wines and wines of other grape varieties were mainly perceived through the following components: ethyl dodecanoate, 1-hexanol, ethyl nonanoate, ethyl hexanoate, ethyl decanoate, dehydro-2-methyl-3(2H)thiophenone, 3-methyl butanoic acid, ethyl tetradecanoate, methyl octanoate, 1,4 butanediol, and 6-methyloctan-1-ol.

On Reasonable Space and Time Cost Models for the λ-Calculus

Slot and van Emde Boas Invariance Thesis states that a time (respectively, space) cost model is reasonable for a computational model C if there are mutual simulations between Turing machines and C such that the overhead is polynomial in time (respectively, linear in space). The rationale is that under the Invariance Thesis, complexity classes such as LOGSPACE, P, PSPACE, become robust, i.e. machine independent. In this dissertation, we want to find out if it possible to define a reasonable space cost model for the lambda-calculus, the paradigmatic model for functional programming languages. We start by considering an unusual evaluation mechanism for the lambda-calculus, based on Girard's Geometry of Interaction, that was conjectured to be the key ingredient to obtain a space reasonable cost model. By a fine complexity analysis of this schema, based on new variants of non-idempotent intersection types, we disprove this conjecture. Then, we change the target of our analysis. We consider a variant over Krivine's abstract machine, a standard evaluation mechanism for the call-by-name lambda-calculus, optimized for space complexity, and implemented without any pointer. A fine analysis of the execution of (a refined version of) the encoding of Turing machines into the lambda-calculus allows us to conclude that the space consumed by this machine is indeed a reasonable space cost model. In particular, for the first time we are able to measure also sub-linear space complexities. Moreover, we transfer this result to the call-by-value case. Finally, we provide also an intersection type system that characterizes compositionally this new reasonable space measure. This is done through a minimal, yet non trivial, modification of the original de Carvalho type system.

Interpretable Convolutional Neural Networks for Decoding and Analyzing Neural Time Series Data

Machine learning is widely adopted to decode multi-variate neural time series, including electroencephalographic (EEG) and single-cell recordings. Recent solutions based on deep learning (DL) outperformed traditional decoders by automatically extracting relevant discriminative features from raw or minimally pre-processed signals. Convolutional Neural Networks (CNNs) have been successfully applied to EEG and are the most common DL-based EEG decoders in the state-of-the-art (SOA). However, the current research is affected by some limitations. SOA CNNs for EEG decoding usually exploit deep and heavy structures with the risk of overfitting small datasets, and architectures are often defined empirically. Furthermore, CNNs are mainly validated by designing within-subject decoders. Crucially, the automatically learned features mainly remain unexplored; conversely, interpreting these features may be of great value to use decoders also as analysis tools, highlighting neural signatures underlying the different decoded brain or behavioral states in a data-driven way. Lastly, SOA DL-based algorithms used to decode single-cell recordings rely on more complex, slower to train and less interpretable networks than CNNs, and the use of CNNs with these signals has not been investigated. This PhD research addresses the previous limitations, with reference to P300 and motor decoding from EEG, and motor decoding from single-neuron activity. CNNs were designed light, compact, and interpretable. Moreover, multiple training strategies were adopted, including transfer learning, which could reduce training times promoting the application of CNNs in practice. Furthermore, CNN-based EEG analyses were proposed to study neural features in the spatial, temporal and frequency domains, and proved to better highlight and enhance relevant neural features related to P300 and motor states than canonical EEG analyses. Remarkably, these analyses could be used, in perspective, to design novel EEG biomarkers for neurological or neurodevelopmental disorders. Lastly, CNNs were developed to decode single-neuron activity, providing a better compromise between performance and model complexity.

Characterization of ENSO changes under idealised radiative forcing in an intermediate complexity general circulation model

Intermediate-complexity general circulation models are a fundamental tool to investigate the role of internal and external variability within the general circulation of the atmosphere and ocean. The model used in this thesis is an intermediate complexity atmospheric general circulation model (SPEEDY) coupled to a state-of-the-art modelling framework for the ocean (NEMO). We assess to which extent the model allows a realistic simulation of the most prominent natural mode of variability at interannual time scales: El-Niño Southern Oscillation (ENSO). To a good approximation, the model represents the ENSO-induced Sea Surface Temperature (SST) pattern in the equatorial Pacific, despite a cold tongue-like bias. The model underestimates (overestimates) the typical ENSO spatial variability during the winter (summer) seasons. The mid-latitude response to ENSO reveals that the typical poleward stationary Rossby wave train is reasonably well represented. The spectral decomposition of ENSO features a spectrum that lacks periodicity at high frequencies and is overly periodic at interannual timescales. We then implemented an idealised transient mean state change in the SPEEDY model. A warmer climate is simulated by an alteration of the parametrized radiative fluxes that corresponds to doubled carbon dioxide absorptivity. Results indicate that the globally averaged surface air temperature increases of 0.76 K. Regionally, the induced signal on the SST field features a significant warming over the central-western Pacific and an El-Niño-like warming in the subtropics. In general, the model features a weakening of the tropical Walker circulation and a poleward expansion of the local Hadley cell. This response is also detected in a poleward rearrangement of the tropical convective rainfall pattern. The model setting that has been here implemented provides a valid theoretical support for future studies on climate sensitivity and forced modes of variability under mean state changes.

Identification Of Corynebacterium Spp. Isolated From Bovine Intramammary Infections By Matrix-assisted Laser Desorption Ionization-time Of Flight Mass Spectrometry.

Corynebacterium species (spp.) are among the most frequently isolated pathogens associated with subclinical mastitis in dairy cows. However, simple, fast, and reliable methods for the identification of species of the genus Corynebacterium are not currently available. This study aimed to evaluate the usefulness of matrix-assisted laser desorption ionization/mass spectrometry (MALDI-TOF MS) for identifying Corynebacterium spp. isolated from the mammary glands of dairy cows. Corynebacterium spp. were isolated from milk samples via microbiological culture (n=180) and were analyzed by MALDI-TOF MS and 16S rRNA gene sequencing. Using MALDI-TOF MS methodology, 161 Corynebacterium spp. isolates (89.4%) were correctly identified at the species level, whereas 12 isolates (6.7%) were identified at the genus level. Most isolates that were identified at the species level with 16 S rRNA gene sequencing were identified as Corynebacterium bovis (n=156; 86.7%) were also identified as C. bovis with MALDI-TOF MS. Five Corynebacterium spp. isolates (2.8%) were not correctly identified at the species level with MALDI-TOF MS and 2 isolates (1.1%) were considered unidentified because despite having MALDI-TOF MS scores >2, only the genus level was correctly identified. Therefore, MALDI-TOF MS could serve as an alternative method for species-level diagnoses of bovine intramammary infections caused by Corynebacterium spp.

A Metabolomic Protocol For Plant Systematics By Matrix-assisted Laser-desorption/ionization Time-of Flight Mass Spectrometry.

Matrix-assisted laser desorption/ionization time-of flight mass spectrometry (MALDI-TOF MS) has been widely used for the identification and classification of microorganisms based on their proteomic fingerprints. However, the use of MALDI-TOF MS in plant research has been very limited. In the present study, a first protocol is proposed for metabolic fingerprinting by MALDI-TOF MS using three different MALDI matrices with subsequent multivariate data analysis by in-house algorithms implemented in the R environment for the taxonomic classification of plants from different genera, families and orders. By merging the data acquired with different matrices, different ionization modes and using careful algorithms and parameter selection, we demonstrate that a close taxonomic classification can be achieved based on plant metabolic fingerprints, with 92% similarity to the taxonomic classifications found in literature. The present work therefore highlights the great potential of applying MALDI-TOF MS for the taxonomic classification of plants and, furthermore, provides a preliminary foundation for future research.

Profile Of Phenolic Compounds Of Brazilian Virgin Olive Oils By Rapid Resolution Liquid Chromatography Coupled To Electrospray Ionisation Time-of-flight Mass Spectrometry (rrlc-esi-tof-ms).

In recent years, agronomical researchers began to cultivate several olive varieties in different regions of Brazil to produce virgin olive oil (VOO). Because there has been no reported data regarding the phenolic profile of the first Brazilian VOO, the aim of this work was to determine phenolic contents of these samples using rapid-resolution liquid chromatography coupled to electrospray ionisation time-of-flight mass spectrometry. 25 VOO samples from Arbequina, Koroneiki, Arbosana, Grappolo, Manzanilla, Coratina, Frantoio and MGS Mariense varieties from three different Brazilian states and two crops were analysed. It was possible to quantify 19 phenolic compounds belonging to different classes. The results indicated that Brazilian VOOs have high total phenolic content because the values were comparable with those from high-quality VOOs produced in other countries. VOOs from Coratina, Arbosana and Grappolo presented the highest total phenolic content. These data will be useful in the development and improvement of Brazilian VOO.

Efeitos da temperatura do ar, linhagem e período do dia nas freqüências de ocorrências e tempos de expressão comportamental de matrizes pesadas

Behavioral adjustments may occur fast and with less cost than the physiological adaptations. Considering the social behavior is suggestive that the frequency and the intensity of aggressive interactions, the total social cohesion and the extent of vicious attitudes may be used to evaluate welfare. This research presents an analysis of the interactions between the experimental factors such as temperature, genetic and time of the day in the behavior of female broiler breeders under controlled environment in a climatic chamber in order to enhance the different reaction of the birds facing distinct environmental conditions. The results showed significant differences between the behaviors expressed by the studied genetics presenting the need of monitoring them in real-time in order to predict their welfare in commercial housing, due to the complexity of the environmental variables that interfere in the well being process. The research also concluded that the welfare evaluation of female broiler breeders needs to consider the time of the day during the observation of the behaviors.

O jogo de futebol : investigação de sua estrutura, de seus modelos e da inteligencia de jogo, do ponto de vista da complexidade

Universidade Estadual de Campinas . Faculdade de Educação Física

Auto-organização no comportamento de crianças no jogo

Universidade Estadual de Campinas . Faculdade de Educação Física

A corporeidade do cego : novos olhares

Universidade Estadual de Campinas. Faculdade de Educação Fisica

Effect of cement type and water storage time on the push-out bond strength of a glass fiber post

This study investigated the effects of the cement type and the water storage time on the push-out bond strength of a glass fiber post. Glass fiber posts (Fibrekor, Jeneric Pentron) were luted to post spaces using a self-cured resin cement (C&B Cement [CB]), a glass ionomer cement (Ketac Cem [KC]) or a resin-modified glass ionomer cement (GC FujiCEM [FC]) according to the manufacturers’ instructions. For each luting agent, the specimens were exposed to one of the following water storage times (n=5): 1 day (T1), 7 days (T7), 90 days (T90) and 180 days (T180). Push-out tests were performed after the storage times. Control specimens were not exposed to water storage, but subjected to the push-out test 10 min after post cementation. Data (in MPa) were analyzed by Kruskal-Wallis and Dunn`s test (α=0.05). Cement type and water storage time had a significant effect (p<0.05) on the push-out bond strength. CB showed significantly higher values of retention (p<0.05) than KC and FC, irrespective of the water storage time. Water storage increased significantly the push-out bond strength in T7 and T90, regardless of the cement type (p<0.05). The results showed that fiber posts luted to post spaces with the self-cured resin cement exhibited the best bonding performance throughout the 180-day water storage period. All cements exhibited a tendency to increase the bond strength after 7 and 90 days of water storage, decreasing thereafter.

Effects of light-curing time on the cytotoxicity of a restorative composite resin on odontoblast-like cells

This in vitro study evaluated the cytotoxicity of an experimental restorative composite resin subjected to different light-curing regimens. METHODS: Forty round-shaped specimens were prepared and randomly assigned to four experimental groups (n=10), as follows: in Group 1, no light-curing; in Groups 2, 3 and 4, the composite resin specimens were light-cured for 20, 40 or 60 s, respectively. In Group 5, filter paper discs soaked in 5 µL PBS were used as negative controls. The resin specimens and paper discs were placed in wells of 24-well plates in which the odontoblast-like cells MDPC-23 (30,000 cells/cm²) were plated and incubated in a humidified incubator with 5% CO2 and 95% air at 37ºC for 72 h. The cytotoxicity was evaluated by the cell metabolism (MTT assay) and cell morphology (SEM). The data were analyzed statistically by Kruskal-Wallis and Mann-Whitney tests (p<0.05). RESULTS: In G1, cell metabolism decreased by 86.2%, indicating a severe cytotoxicity of the non-light-cured composite resin. On the other hand, cell metabolism decreased by only 13.3% and 13.5% in G2 and G3, respectively. No cytotoxic effects were observed in G4 and G5. In G1, only a few round-shaped cells with short processes on their cytoplasmic membrane were observed. In the other experimental groups as well as in control group, a number of spindle-shaped cells with long cytoplasmic processes were found. CONCLUSION: Regardless of the photoactivation time used in the present investigation, the experimental composite resin presented mild to no toxic effects to the odontoblast-like MDPC-23 cells. However, intense cytotoxic effects occurred when no light-curing was performed.