Employment of Real-Time/FPGA Architectures for Test and Control of Automotive Engines

Nowadays the production of increasingly complex and electrified vehicles requires the implementation of new control and monitoring systems. This reason, together with the tendency of moving rapidly from the test bench to the vehicle, leads to a landscape that requires the development of embedded hardware and software to face the application effectively and efficiently. The development of application-based software on real-time/FPGA hardware could be a good answer for these challenges: FPGA grants parallel low-level and high-speed calculation/timing, while the Real-Time processor can handle high-level calculation layers, logging and communication functions with determinism. Thanks to the software flexibility and small dimensions, these architectures can find a perfect collocation as engine RCP (Rapid Control Prototyping) units and as smart data logger/analyser, both for test bench and on vehicle application. Efforts have been done for building a base architecture with common functionalities capable of easily hosting application-specific control code. Several case studies originating in this scenario will be shown; dedicated solutions for protype applications have been developed exploiting a real-time/FPGA architecture as ECU (Engine Control Unit) and custom RCP functionalities, such as water injection and testing hydraulic brake control.

Deep Learning Architectures for time of arrival detection in Acoustic Emissions Monitoring

Acoustic Emission (AE) monitoring can be used to detect the presence of damage as well as determine its location in Structural Health Monitoring (SHM) applications. Information on the time difference of the signal generated by the damage event arriving at different sensors is essential in performing localization. This makes the time of arrival (ToA) an important piece of information to retrieve from the AE signal. Generally, this is determined using statistical methods such as the Akaike Information Criterion (AIC) which is particularly prone to errors in the presence of noise. And given that the structures of interest are surrounded with harsh environments, a way to accurately estimate the arrival time in such noisy scenarios is of particular interest. In this work, two new methods are presented to estimate the arrival times of AE signals which are based on Machine Learning. Inspired by great results in the field, two models are presented which are Deep Learning models - a subset of machine learning. They are based on Convolutional Neural Network (CNN) and Capsule Neural Network (CapsNet). The primary advantage of such models is that they do not require the user to pre-define selected features but only require raw data to be given and the models establish non-linear relationships between the inputs and outputs. The performance of the models is evaluated using AE signals generated by a custom ray-tracing algorithm by propagating them on an aluminium plate and compared to AIC. It was found that the relative error in estimation on the test set was < 5% for the models compared to around 45% of AIC. The testing process was further continued by preparing an experimental setup and acquiring real AE signals to test on. Similar performances were observed where the two models not only outperform AIC by more than a magnitude in their average errors but also they were shown to be a lot more robust as compared to AIC which fails in the presence of noise.

PCM-based in-memory computing: architectures, circuits and applications

Analog In-memory Computing (AIMC) has been proposed in the context of Beyond Von Neumann architectures as a valid strategy to reduce internal data transfers energy consumption and latency, and to improve compute efficiency. The aim of AIMC is to perform computations within the memory unit, typically leveraging the physical features of memory devices. Among resistive Non-volatile Memories (NVMs), Phase-change Memory (PCM) has become a promising technology due to its intrinsic capability to store multilevel data. Hence, PCM technology is currently investigated to enhance the possibilities and the applications of AIMC. This thesis aims at exploring the potential of new PCM-based architectures as in-memory computational accelerators. In a first step, a preliminar experimental characterization of PCM devices has been carried out in an AIMC perspective. PCM cells non-idealities, such as time-drift, noise, and non-linearity have been studied to develop a dedicated multilevel programming algorithm. Measurement-based simulations have been then employed to evaluate the feasibility of PCM-based operations in the fields of Deep Neural Networks (DNNs) and Structural Health Monitoring (SHM). Moreover, a first testchip has been designed and tested to evaluate the hardware implementation of Multiply-and-Accumulate (MAC) operations employing PCM cells. This prototype experimentally demonstrates the possibility to reach a 95% MAC accuracy with a circuit-level compensation of cells time drift and non-linearity. Finally, empirical circuit behavior models have been included in simulations to assess the use of this technology in specific DNN applications, and to enhance the potentiality of this innovative computation approach.

Hierarchical active inference for cognitive architectures

This thesis explores the methods based on the free energy principle and active inference for modelling cognition. Active inference is an emerging framework for designing intelligent agents where psychological processes are cast in terms of Bayesian inference. Here, I appeal to it to test the design of a set of cognitive architectures, via simulation. These architectures are defined in terms of generative models where an agent executes a task under the assumption that all cognitive processes aspire to the same objective: the minimization of variational free energy. Chapter 1 introduces the free energy principle and its assumptions about self-organizing systems. Chapter 2 describes how from the mechanics of self-organization can emerge a minimal form of cognition able to achieve autopoiesis. In chapter 3 I present the method of how I formalize generative models for action and perception. The architectures proposed allow providing a more biologically plausible account of more complex cognitive processing that entails deep temporal features. I then present three simulation studies that aim to show different aspects of cognition, their associated behavior and the underlying neural dynamics. In chapter 4, the first study proposes an architecture that represents the visuomotor system for the encoding of actions during action observation, understanding and imitation. In chapter 5, the generative model is extended and is lesioned to simulate brain damage and neuropsychological patterns observed in apraxic patients. In chapter 6, the third study proposes an architecture for cognitive control and the modulation of attention for action selection. At last, I argue how active inference can provide a formal account of information processing in the brain and how the adaptive capabilities of the simulated agents are a mere consequence of the architecture of the generative models. Cognitive processing, then, becomes an emergent property of the minimization of variational free energy.

The engagement of yugoslav technical cooperation experts in post-colonial Algeria (1962-1990). A global microhistory of east-south relations

The venture of socialist Eastern Europe in assisting the development efforts of the post-colonial countries opened up official migratory channels to the Global South for a specific labour group engaged under international technical cooperation programmes. By taking post-colonial Algeria as a space of East-South interactions and intense inter-socialist competition, the thesis studies labour mobility from socialist Yugoslavia of a heterogeneous group labelled “technical cooperation experts” in the period from 1962 to 1990. While CMEA members dispatched to the country personnel in great numbers, after 1965, Yugoslavia failed to do so. Tracing them beyond the institutional level, the thesis aims at detecting and exposing factors which inhibited the attempts to increase the presence of Yugoslav technical experts in Algeria. It argues that instead of building an alternative, solidarity-based aid model, Yugoslav technical cooperation with the developing countries was reduced to mediation in the employment of highly-skilled labour abroad. The cooperation scheme, which differed from one of its Eastern European counterparts, manifested in the employment and legal status as well as everyday life and work experiences of Yugoslav citizens. Relying on the methodological approach of global microhistory, which strongly favours the micro-historical analysis of primary sources in studying global processes, the thesis provides a more comprehensive and nuanced understanding of Yugoslav globalization endeavours. By shifting the focus to the experiences of ordinary people who were under the strong influence of globalization forces of the Cold War era, the thesis adds a “human” dimension to the history of East-South relations.

QoS-aware architectures, technologies, and middleware for the cloud continuum

The recent trend of moving Cloud Computing capabilities to the Edge of the network is reshaping how applications and their middleware supports are designed, deployed, and operated. This new model envisions a continuum of virtual resources between the traditional cloud and the network edge, which is potentially more suitable to meet the heterogeneous Quality of Service (QoS) requirements of diverse application domains and next-generation applications. Several classes of advanced Internet of Things (IoT) applications, e.g., in the industrial manufacturing domain, are expected to serve a wide range of applications with heterogeneous QoS requirements and call for QoS management systems to guarantee/control performance indicators, even in the presence of real-world factors such as limited bandwidth and concurrent virtual resource utilization. The present dissertation proposes a comprehensive QoS-aware architecture that addresses the challenges of integrating cloud infrastructure with edge nodes in IoT applications. The architecture provides end-to-end QoS support by incorporating several components for managing physical and virtual resources. The proposed architecture features: i) a multilevel middleware for resolving the convergence between Operational Technology (OT) and Information Technology (IT), ii) an end-to-end QoS management approach compliant with the Time-Sensitive Networking (TSN) standard, iii) new approaches for virtualized network environments, such as running TSN-based applications under Ultra-low Latency (ULL) constraints in virtual and 5G environments, and iv) an accelerated and deterministic container overlay network architecture. Additionally, the QoS-aware architecture includes two novel middlewares: i) a middleware that transparently integrates multiple acceleration technologies in heterogeneous Edge contexts and ii) a QoS-aware middleware for Serverless platforms that leverages coordination of various QoS mechanisms and virtualized Function-as-a-Service (FaaS) invocation stack to manage end-to-end QoS metrics. Finally, all architecture components were tested and evaluated by leveraging realistic testbeds, demonstrating the efficacy of the proposed solutions.

Industrial Demilitarized Zone and Zero Trust cybersecurity models for Industrial Control Systems

Today more than ever, with the recent war in Ukraine and the increasing number of attacks that affect systems of nations and companies every day, the world realizes that cybersecurity can no longer be considered just as a “cost”. It must become a pillar for our infrastructures that involve the security of our nations and the safety of people. Critical infrastructure, like energy, financial services, and healthcare, have become targets of many cyberattacks from several criminal groups, with an increasing number of resources and competencies, putting at risk the security and safety of companies and entire nations. This thesis aims to investigate the state-of-the-art regarding the best practice for securing Industrial control systems. We study the differences between two security frameworks. The first is Industrial Demilitarized Zone (I-DMZ), a perimeter-based security solution. The second one is the Zero Trust Architecture (ZTA) which removes the concept of perimeter to offer an entirely new approach to cybersecurity based on the slogan ‘Never Trust, always verify’. Starting from this premise, the Zero Trust model embeds strict Authentication, Authorization, and monitoring controls for any access to any resource. We have defined two architectures according to the State-of-the-art and the cybersecurity experts’ guidelines to compare I-DMZ, and Zero Trust approaches to ICS security. The goal is to demonstrate how a Zero Trust approach dramatically reduces the possibility of an attacker penetrating the network or moving laterally to compromise the entire infrastructure. A third architecture has been defined based on Cloud and fog/edge computing technology. It shows how Cloud solutions can improve the security and reliability of infrastructure and production processes that can benefit from a range of new functionalities, that the Cloud could offer as-a-Service.We have implemented and tested our Zero Trust solution and its ability to block intrusion or attempted attacks.

Convolutional Neural Network Architectures for Template Matching

The Neural Networks customized and tested in this thesis (WaldoNet, FlowNet and PatchNet) are a first exploration and approach to the Template Matching task. The possibilities of extension are therefore many and some are proposed below. During my thesis, I have analyzed the functioning of the classical algorithms and adapted with deep learning algorithms. The features extracted from both the template and the query images resemble the keypoints of the SIFT algorithm. Then, instead of similarity function or keypoints matching, WaldoNet and PatchNet use the convolutional layer to compare the features, while FlowNet uses the correlational layer. In addition, I have identified the major challenges of the Template Matching task (affine/non-affine transformations, intensity changes...) and solved them with a careful design of the dataset.

The Consequences Of Refractory Epilepsy And Its Treatment.

Seizures in some 30% to 40% of patients with epilepsy fail to respond to antiepileptic drugs or other treatments. While much has been made of the risks of new drug therapies, not enough attention has been given to the risks of uncontrolled and progressive epilepsy. This critical review summarizes known risks associated with refractory epilepsy, provides practical clinical recommendations, and indicates areas for future research. Eight international epilepsy experts from Europe, the United States, and South America met on May 4, 2013, to present, review, and discuss relevant concepts, data, and literature on the consequences of refractory epilepsy. While patients with refractory epilepsy represent the minority of the population with epilepsy, they require the overwhelming majority of time, effort, and focus from treating physicians. They also represent the greatest economic and psychosocial burdens. Diagnostic procedures and medical/surgical treatments are not without risks. Overlooked, however, is that these risks are usually smaller than the risks of long-term, uncontrolled seizures. Refractory epilepsy may be progressive, carrying risks of structural damage to the brain and nervous system, comorbidities (osteoporosis, fractures), and increased mortality (from suicide, accidents, sudden unexpected death in epilepsy, pneumonia, vascular disease), as well as psychological (depression, anxiety), educational, social (stigma, driving), and vocational consequences. Adding to this burden is neuropsychiatric impairment caused by underlying epileptogenic processes (essential comorbidities), which appears to be independent of the effects of ongoing seizures themselves. Tolerating persistent seizures or chronic medicinal adverse effects has risks and consequences that often outweigh risks of seemingly more aggressive treatments. Future research should focus not only on controlling seizures but also on preventing these consequences.

[the Perception Of Behavior Related To Mindfulness And The Brazilian Version Of The Freiburg Mindfulness Inventory].

Mindfulness is a practice and a form of consciousness which has been the basis for innovative interventions in care and health promotion. This study presents mindfulness, describes and discusses the process of cultural adaptation of The Freiburg Mindfulness Inventory (FMI) to Brazilian Portuguese. From the original version of this pioneering instrument for assessing mindfulness two translations and two back-translations were made. These were evaluated by a committee of 14 experts (Buddhists, linguists, health professionals), who helped to create two versions for the first pre-test, based on which suggestions were made by a sample of 41 people of the population through interviews. Considering the difficulties in understanding the concepts that are unfamiliar to the Brazilian culture, a new version was prepared with additional explanations, which underwent a further evaluation of the experts and a second pre-test with 72 people. This process aimed at addressing the limitations and challenges of evaluating mindfulness in a country of western culture through a self-report instrument based on Buddhist psychology. With appropriate levels of clarity and equivalence with the original instrument, the Freiburg Mindfulness Inventory adapted for Brazil is presented.

Diagnosis, Treatment, And Follow-up Of Medullary Thyroid Carcinoma: Recommendations By The Thyroid Department Of The Brazilian Society Of Endocrinology And Metabolism.

Medullary thyroid carcinoma (MTC) originates in the thyroid parafollicular cells and represents 3-4% of the malignant neoplasms that affect this gland. Approximately 25% of these cases are hereditary due to activating mutations in the REarranged during Transfection (RET) proto-oncogene. The course of MTC is indolent, and survival rates depend on the tumor stage at diagnosis. The present article describes clinical evidence-based guidelines for the diagnosis, treatment, and follow-up of MTC. The aim of the consensus described herein, which was elaborated by Brazilian experts and sponsored by the Thyroid Department of the Brazilian Society of Endocrinology and Metabolism, was to discuss the diagnosis, treatment, and follow-up of individuals with MTC in accordance with the latest evidence reported in the literature. After clinical questions were elaborated, the available literature was initially surveyed for evidence in the MedLine-PubMed database, followed by the Embase and Scientific Electronic Library Online/Latin American and Caribbean Health Science Literature (SciELO/Lilacs) databases. The strength of evidence was assessed according to the Oxford classification of evidence levels, which is based on study design, and the best evidence available for each question was selected. Eleven questions corresponded to MTC diagnosis, 8 corresponded to its surgical treatment, and 13 corresponded to follow-up, for a total of 32 recommendations. The present article discusses the clinical and molecular diagnosis, initial surgical treatment, and postoperative management of MTC, as well as the therapeutic options for metastatic disease. MTC should be suspected in individuals who present with thyroid nodules and family histories of MTC, associations with pheochromocytoma and hyperparathyroidism, and/or typical phenotypic characteristics such as ganglioneuromatosis and Marfanoid habitus. Fine-needle nodule aspiration, serum calcitonin measurements, and anatomical-pathological examinations are useful for diagnostic confirmation. Surgery represents the only curative therapeutic strategy. The therapeutic options for metastatic disease remain limited and are restricted to disease control. Judicious postoperative assessments that focus on the identification of residual or recurrent disease are of paramount importance when defining the follow-up and later therapeutic management strategies.

[renal Tumors: The International Society Of Urologic Pathology (isup) 2012 Consensus Conference Recommendations].

During the last 30 years many advances have been made in kidney tumor pathology. In 1981, 9 entities were recognized in the WHO Classification. In the latest classification of 2004, 50 different types have been recognized. Additional tumor entities have been described since and a wide variety of prognostic parameters have been investigated with variable success; however, much attention has centered upon the importance of features relating to both stage and grade. The International Society of Urological Pathology (ISUP) recommends after consensus conferences the development of reporting guidelines, which have been adopted worldwide ISUP undertook to review all aspects of the pathology of adult renal malignancy through an international consensus conference to be held in 2012. As in the past, participation in this consensus conference was restricted to acknowledged experts in the field.

Adaptação de um questionário de autoconfiança relacionado a situações-problema em Odontopediatria

This work describes the adaptation of Milgrom's questionnaire on self-confidence and ways of dealing with behavior problems faced during pediatric dental treatment. The adaptation of the instrument was approved by experts and was analyzed in terms of quantity, coherence and quality of responses. The results of this study suggest that the questionnaire can contribute to dentist's education.

COMPARAÇÃO DAS PROPRIEDADES REOLÓGICAS DA MASSA DE CACAU TORRADA CONVENCIONALMENTE E POR MICROONDAS

Two kinds of roasting cocoa system: conventional batch method in electrical oven, and by microwaves, in a continuous microwave rotary applicator (2450MHz), were compared with respect to viscosity. Cocoa was roasted in whole beans and in nibs. The variable used in the microwave treatment was the power density applied to the whole beans (254,45 to 290,80 Wh/kg) and to the nibs (227,27 to 262,23 Wh/kg), with a constant holding time of 10 minutes. The variable used in the conventional roasting process was the roasting time of the beans (40 to 44 min) and the nibs (34 to 38 min), with constant temperature in the jacket of electric oven (150°C). Viscosity was measured in a Brookfield rheometer (mod RV-DVIII) at 40°C. In general, the plastic viscosity of the microwaved samples was lower than that of the conventional roasted samples. Also the nibs showed lower viscosities than the whole beans when roasted in the electric oven. The viscosity of the samples roasted in the microwave oven was lower in the whole beans than in the nibs. The product was sensorially evaluated by three experts in cocoa flavour, and it was shown that the flavour of the microwave roasted products was similar to that of the conventionally roasted products, with the advantage of a reduction in process time.

Consenso brasileiro para a abordagem clínica e tratamento do hipotireoidismo subclínico em adultos: recomendações do Departamento de Tireoide da Sociedade Brasileira de Endocrinologia e Metabologia

INTRODUCTION: Subclinical hypothyroidism (SCH), defined as elevated concentrations of thyroid stimulating hormone (TSH) despite normal levels of thyroid hormones, is highly prevalent in Brazil, especially among women and the elderly. Although an increasing number of studies have related SCH to an increased risk of coronary artery disease and mortality, there have been no randomized clinical trials verifying the benefit of levothyroxine treatment in reducing these risks, and the treatment remains controversial. OBJECTIVE: This consensus, sponsored by the Thyroid Department of the Brazilian Society of Endocrinology and Metabolism and developed by Brazilian experts with extensive clinical experience with thyroid diseases, presents these recommendations based on evidence for the clinical management of SCH patients in Brazil. MATERIALS AND METHODS: After structuring the clinical questions, the search for evidence in the literature was initially performed in the MedLine-PubMed database and later in the Embase and SciELO - Lilacs databases. The strength of evidence was evaluated according to the Oxford classification system and established based on the experimental design used, considering the best available evidence for each question and the Brazilian experience. RESULTS: The topics covered included SCH definition and diagnosis, natural history, clinical significance, treatment and pregnancy, and the consensus issued 29 recommendations for the clinical management of adult patients with SCH. CONCLUSION: Treatment with levothyroxine was recommended for all patients with persistent SCH with serum TSH values > 10 mU/L and for certain patient subgroups.