A Binary Classifier for Test Case Feasibility Applied to Automatically Generated Tests of Event-Driven Software

Modern software application testing, such as the testing of software driven by graphical user interfaces (GUIs) or leveraging event-driven architectures in general, requires paying careful attention to context. Model-based testing (MBT) approaches first acquire a model of an application, then use the model to construct test cases covering relevant contexts. A major shortcoming of state-of-the-art automated model-based testing is that many test cases proposed by the model are not actually executable. These \textit{infeasible} test cases threaten the integrity of the entire model-based suite, and any coverage of contexts the suite aims to provide. In this research, I develop and evaluate a novel approach for classifying the feasibility of test cases. I identify a set of pertinent features for the classifier, and develop novel methods for extracting these features from the outputs of MBT tools. I use a supervised logistic regression approach to obtain a model of test case feasibility from a randomly selected training suite of test cases. I evaluate this approach with a set of experiments. The outcomes of this investigation are as follows: I confirm that infeasibility is prevalent in MBT, even for test suites designed to cover a relatively small number of unique contexts. I confirm that the frequency of infeasibility varies widely across applications. I develop and train a binary classifier for feasibility with average overall error, false positive, and false negative rates under 5\%. I find that unique event IDs are key features of the feasibility classifier, while model-specific event types are not. I construct three types of features from the event IDs associated with test cases, and evaluate the relative effectiveness of each within the classifier. To support this study, I also develop a number of tools and infrastructure components for scalable execution of automated jobs, which use state-of-the-art container and continuous integration technologies to enable parallel test execution and the persistence of all experimental artifacts.

Outcomes of a general hospital-based Home Parenteral Nutrition (HPN) program: report of our experience from a 26-year period

Background: Home parenteral nutrition (HPN) was introduced in Spain in the late 1980s. Our hospital was a pioneering medical centre in this field. Aim: Analyze outcomes of our HPN program. Methods: Retrospective study of patients receiving HPN between 1986-2012. Study variables are expressed as frequency, mean ± SD (range), median [interquartile range]. Parametrics, non-parametrics test and survival analysis (p < 0.05) were applied. Results: 91 patients (55 females and 36 males, mean age: 50.6 ± 5 yrs.) who received HPN for an accrual period of 55,470 days (median: 211 days [range: 63-573]) were included. The most prevalent underlying condition was cancer (49.5%), with the commonest HPN indication being short bowel syndrome (41.1%). The most frequently used catheter type was the tunneled catheter (70.7%). The complication rate was 3.58/1,000 HPN days (2.68, infection; 0.07, occlusion; 0.07 thrombosis; and 0.59, metabolic complications). Complications were consistently associated with both the underlying condition and HPN length. Infections were most frequent within the first 1,000 days of HPN. Liver disease incidence was related to HPN duration. HPN could be discontinued in 42.3% of patients. Ten-year survival rate was 42%, and varied across the underlying conditions. Conclusions: In the present series, the commonest reason for HPN was cancer. Our complication rate is in keeping with that reported in the literature. The overall survival rate was 42%, and varied across the underlying conditions.

Understanding Notional Machines through Traditional Teaching with Conceptual Contraposition and Program Memory Tracing

A correct understanding about how computers run code is mandatory in order to effectively learn to program. Lectures have historically been used in programming courses to teach how computers execute code, and students are assessed through traditional evaluation methods, such as exams. Constructivism learning theory objects to students’ passiveness during lessons, and traditional quantitative methods for evaluating a complex cognitive process such as understanding. Constructivism proposes complimentary techniques, such as conceptual contraposition and colloquies. We enriched lectures of a “Programming II” (CS2) course combining conceptual contraposition with program memory tracing, then we evaluated students’ understanding of programming concepts through colloquies. Results revealed that these techniques applied to the lecture are insufficient to help students develop satisfactory mental models of the C++ notional machine, and colloquies behaved as the most comprehensive traditional evaluations conducted in the course.

Expertise sportive et entraînement perceptivo-cognitif de l’athlète

Pour être performant au plus haut niveau, les athlètes doivent posséder une capacité perceptivo-cognitive supérieure à la moyenne. Cette faculté, reflétée sur le terrain par la vision et l’intelligence de jeu des sportifs, permet d’extraire l’information clé de la scène visuelle. La science du sport a depuis longtemps observé l’expertise perceptivo-cognitive au sein de l’environnement sportif propre aux athlètes. Récemment, des études ont rapporté que l’expertise pouvait également se refléter hors de ce contexte, lors d’activités du quotidien par exemple. De plus, les récentes théories entourant la capacité plastique du cerveau ont amené les chercheurs à développer des outils pour entraîner les capacités perceptivo-cognitives des athlètes afin de les rendre plus performants sur le terrain. Ces méthodes sont la plupart du temps contextuelles à la discipline visée. Cependant, un nouvel outil d’entraînement perceptivo-cognitif, nommé 3-Dimensional Multiple Object Tracking (3D-MOT) et dénué de contexte sportif, a récemment vu le jour et a fait l’objet de nos recherches. Un de nos objectifs visait à mettre en évidence l’expertise perceptivo-cognitive spécifique et non-spécifique chez des athlètes lors d’une même étude. Nous avons évalué la perception du mouvement biologique chez des joueurs de soccer et des non-athlètes dans une salle de réalité virtuelle. Les sportifs étaient systématiquement plus performants en termes d’efficacité et de temps de réaction que les novices pour discriminer la direction du mouvement biologique lors d’un exercice spécifique de soccer (tir) mais également lors d’une action issue du quotidien (marche). Ces résultats signifient que les athlètes possèdent une meilleure capacité à percevoir les mouvements biologiques humains effectués par les autres. La pratique du soccer semble donc conférer un avantage fondamental qui va au-delà des fonctions spécifiques à la pratique d’un sport. Ces découvertes sont à mettre en parallèle avec la performance exceptionnelle des athlètes dans le traitement de scènes visuelles dynamiques et également dénuées de contexte sportif. Des joueurs de soccer ont surpassé des novices dans le test de 3D-MOT qui consiste à suivre des cibles en mouvement et stimule les capacités perceptivo-cognitives. Leur vitesse de suivi visuel ainsi que leur faculté d’apprentissage étaient supérieures. Ces résultats confirmaient des données obtenues précédemment chez des sportifs. Le 3D-MOT est un test de poursuite attentionnelle qui stimule le traitement actif de l’information visuelle dynamique. En particulier, l’attention sélective, dynamique et soutenue ainsi que la mémoire de travail. Cet outil peut être utilisé pour entraîner les fonctions perceptivo-cognitives des athlètes. Des joueurs de soccer entraînés au 3D-MOT durant 30 sessions ont montré une amélioration de la prise de décision dans les passes de 15% sur le terrain comparés à des joueurs de groupes contrôles. Ces données démontrent pour la première fois un transfert perceptivo-cognitif du laboratoire au terrain suivant un entraînement perceptivo-cognitif non-contextuel au sport de l’athlète ciblé. Nos recherches aident à comprendre l’expertise des athlètes par l’approche spécifique et non-spécifique et présentent également les outils d’entraînements perceptivo-cognitifs, en particulier le 3D-MOT, pour améliorer la performance dans le sport de haut-niveau.

Exploring coordination-driven self-assembly with autonomous chemical robots

The work presented herein focused on the automation of coordination-driven self assembly, exploring methods that allow syntheses to be followed more closely while forming new ligands, as part of the fundamental study of the digitization of chemical synthesis and discovery. Whilst the control and understanding of the principle of pre-organization and self-sorting under non-equilibrium conditions remains a key goal, a clear gap has been identified in the absence of approaches that can permit fast screening and real-time observation of the reaction process under different conditions. A firm emphasis was thus placed on the realization of an autonomous chemical robot, which can not only monitor and manipulate coordination chemistry in real-time, but can also allow the exploration of a large chemical parameter space defined by the ligand building blocks and the metal to coordinate. The self-assembly of imine ligands with copper and nickel cations has been studied in a multi-step approach using a self-built flow system capable of automatically controlling the liquid-handling and collecting data in real-time using a benchtop MS and NMR spectrometer. This study led to the identification of a transient Cu(I) species in situ which allows for the formation of dimeric and trimeric carbonato bridged Cu(II) assemblies. Furthermore, new Ni(II) complexes and more remarkably also a new binuclear Cu(I) complex, which usually requires long and laborious inert conditions, could be isolated. The study was then expanded to the autonomous optimization of the ligand synthesis by enabling feedback control on the chemical system via benchtop NMR. The synthesis of new polydentate ligands has emerged as a result of the study aiming to enhance the complexity of the chemical system to accelerate the discovery of new complexes. This type of ligand consists of 1-pyridinyl-4-imino-1,2,3-triazole units, which can coordinate with different metal salts. The studies to test for the CuAAC synthesis via microwave lead to the discovery of four new Cu complexes, one of them being a coordination polymer obtained from a solvent dependent crystallization technique. With the goal of easier integration into an automated system, copper tubing has been exploited as the chemical reactor for the synthesis of this ligand, as it efficiently enhances the rate of the triazole formation and consequently promotes the formation of the full ligand in high yields within two hours. Lastly, the digitization of coordination-driven self-assembly has been realized for the first time using an in-house autonomous chemical robot, herein named the ‘Finder’. The chemical parameter space to explore was defined by the selection of six variables, which consist of the ligand precursors necessary to form complex ligands (aldehydes, alkineamines and azides), of the metal salt solutions and of other reaction parameters – duration, temperature and reagent volumes. The platform was assembled using rounded bottom flasks, flow syringe pumps, copper tubing, as an active reactor, and in-line analytics – a pH meter probe, a UV-vis flow cell and a benchtop MS. The control over the system was then obtained with an algorithm capable of autonomously focusing the experiments on the most reactive region (by avoiding areas of low interest) of the chemical parameter space to explore. This study led to interesting observations, such as metal exchange phenomena, and also to the autonomous discovery of self assembled structures in solution and solid state – such as 1-pyridinyl-4-imino-1,2,3-triazole based Fe complexes and two helicates based on the same ligand coordination motif.

Home and group-based implementation of the "Growing Up Happily in the Family" program in at-risk psychosocial contexts

"Growing Up Happily in the Family" is a program to prevent child maltreatment targeted at parents of children aged 0-5 years old in at-risk psychosocial contexts. The program is delivered via either a group-based or a home-visit format. The objective of this study was to evaluate the impact of various implementation components in the home and group versions on changes in parental attitudes about child development and education. At-risk and non at-risk parents participated in the group-based (196 participants in 26 groups) and home-visit (95 participants) versions of the program delivered through local social services. We analyzed program adherence, adaptations, participant responsiveness, quality of delivery, and implementation barriers as predictors of changes in parental attitudes. The results showed that greater program adherence, better quality of delivery and participant responsiveness, and positive climate predicted changes in parental attitudes in both formats. Therefore, it is important to take into account the quality of the implementation process when testing the effectiveness of early group-based and home-visit interventions in at-risk families.

Evidence in promoting positive parenting through the Program-Guide to Develop Emotional Competences

This study aims at providing evidence of the effectiveness of the Program-Guide to Develop Emotional Competences in promoting positive parenting. Contextual, institutional, methodological and professional issues were taken into account to develop a social innovation experience to support parenting as a preventive measure to family conflicts. The study describes both the contents of the Program-Guide and the methodological and evaluation issues that trained professionals need to consider when delivering the Program-Guide to families in natural contexts. Information was gathered and analyzed from 259 parents with children of ages 1-18 who participated in 26 parent training groups. A pre- and post-test design showed that after finishing the sessions parents perceived themselves more competent as parents according to the five dimensions of parenting competences considered: (1) emotional self-regulation abilities; (2) self-esteem and assertiveness; (3) communication strategies; (4) strategies to solve conflicts and to negotiate; and (5) strategies to establish coherent norms, limits and consequences to promote positive discipline. The study presents a discussion on these results from evidence-based parenting programs, as well as some strengths and limitations of the study, together with some suggestions for further research.

Investigation into the Influence of Build Parameters on Failure of 3D Printed Parts

Additive manufacturing, including fused deposition modeling (FDM), is transforming the built world and engineering education. Deep understanding of parts created through FDM technology has lagged behind its adoption in home, work, and academic environments. Properties of parts created from bulk materials through traditional manufacturing are understood well enough to accurately predict their behavior through analytical models. Unfortunately, Additive Manufacturing (AM) process parameters create anisotropy on a scale that fundamentally affects the part properties. Understanding AM process parameters (implemented by program algorithms called slicers) is necessary to predict part behavior. Investigating algorithms controlling print parameters (slicers) revealed stark differences between the generation of part layers. In this work, tensile testing experiments, including a full factorial design, determined that three key factors, width, thickness, infill density, and their interactions, significantly affect the tensile properties of 3D printed test samples.

Synthetic portfolio for event studies: Estimating the effects of volatility call auctions

We propose a method denoted as synthetic portfolio for event studies in market microstructure that is particularly interesting to use with high frequency data and thinly traded markets. The method is based on Synthetic Control Method and provides a robust data driven method to build a counterfactual for evaluating the effects of the volatility call auctions. We find that SMC could be used if the loss function is defined as the difference between the returns of the asset and the returns of a synthetic portfolio. We apply SCM to test the performance of the volatility call auction as a circuit breaker in the context of an event study. We find that for Colombian Stock Market securities, the asynchronicity of intraday data reduces the analysis to a selected group of stocks, however it is possible to build a tracking portfolio. The realized volatility increases after the auction, indicating that the mechanism is not enhancing the price discovery process.

Machine learning "as a service" for high energy physics (MLaaS4HEP): evolution of a framework for ML-based physics analyses

The scientific success of the LHC experiments at CERN highly depends on the availability of computing resources which efficiently store, process, and analyse the amount of data collected every year. This is ensured by the Worldwide LHC Computing Grid infrastructure that connect computing centres distributed all over the world with high performance network. LHC has an ambitious experimental program for the coming years, which includes large investments and improvements both for the hardware of the detectors and for the software and computing systems, in order to deal with the huge increase in the event rate expected from the High Luminosity LHC (HL-LHC) phase and consequently with the huge amount of data that will be produced. Since few years the role of Artificial Intelligence has become relevant in the High Energy Physics (HEP) world. Machine Learning (ML) and Deep Learning algorithms have been successfully used in many areas of HEP, like online and offline reconstruction programs, detector simulation, object reconstruction, identification, Monte Carlo generation, and surely they will be crucial in the HL-LHC phase. This thesis aims at contributing to a CMS R&D project, regarding a ML "as a Service" solution for HEP needs (MLaaS4HEP). It consists in a data-service able to perform an entire ML pipeline (in terms of reading data, processing data, training ML models, serving predictions) in a completely model-agnostic fashion, directly using ROOT files of arbitrary size from local or distributed data sources. This framework has been updated adding new features in the data preprocessing phase, allowing more flexibility to the user. Since the MLaaS4HEP framework is experiment agnostic, the ATLAS Higgs Boson ML challenge has been chosen as physics use case, with the aim to test MLaaS4HEP and the contribution done with this work.

Analytic Network Process (ANP) a supporto della scelta della strategia produttiva: sviluppo e test di un approccio decisionale

Di fronte alla concorrenza globale, la sopravvivenza di un'azienda manifatturiera dipende sempre più da come essa può progettare, gestire e strutturare al meglio il proprio sistema di produzione per far fronte alla diversità dei prodotti, per migliorare l'affidabilità di consegna e anche per ridurre i costi. In questo contesto, le aziende manifatturiere utilizzano spesso sistemi di produzione diversi, in base a ciò che richiede il mercato. Molto in generale, i sistemi produttivi possono essere classificati in due categorie principali: make-to-stock (MTS) e make-to-order (MTO), in base alla politica di risposta alla domanda del mercato. Nel nuovo contesto competitivo le aziende si sono trovate a dover produrre costantemente prodotti specifici e di alta qualità con costi unitari bassi e livelli di servizio elevati (ossia, tempi di consegna brevi). È chiaro, dunque, che una delle principali decisioni strategiche da prendere da parte delle aziende sia quella relativa alla ripartizione dei prodotti in MTS/MTO, ovvero quale prodotto o famiglia di prodotti può essere fabbricato per essere stoccato a magazzino (MTS), quale può essere prodotto su ordinazione (MTO) e quale dovrebbe essere fabbricato in base alla politica di produzione ibrida MTS/MTO. Gli ultimi anni hanno mostrato una serie di cambiamenti nella politica di produzione delle aziende, che si stanno gradualmente spostando sempre più verso la modalità̀ di produzione ibrida MTS/MTO. In particolare, questo elaborato si concentrerà sul delayed product differentiation (DPD), una particolare strategia produttiva ibrida, e ne verrà proposto un modello decisionale basato sul funzionamento dell’Analytic Network Process (ANP) implementato attraverso il software Superdecisions.

SmartForge: An event-driven architecture for simulator-based process optimization

In the metal industry, and more specifically in the forging one, scrap material is a crucial issue and reducing it would be an important goal to reach. Not only would this help the companies to be more environmentally friendly and more sustainable, but it also would reduce the use of energy and lower costs. At the same time, the techniques for Industry 4.0 and the advancements in Artificial Intelligence (AI), especially in the field of Deep Reinforcement Learning (DRL), may have an important role in helping to achieve this objective. This document presents the thesis work, a contribution to the SmartForge project, that was performed during a semester abroad at Karlstad University (Sweden). This project aims at solving the aforementioned problem with a business case of the company Bharat Forge Kilsta, located in Karlskoga (Sweden). The thesis work includes the design and later development of an event-driven architecture with microservices, to support the processing of data coming from sensors set up in the company's industrial plant, and eventually the implementation of an algorithm with DRL techniques to control the electrical power to use in it.

Direct And Non-destructive Proof Of Authenticity For The 2nd Generation Of Brazilian Real Banknotes Via Easy Ambient Sonic Spray Ionization Mass Spectrometry.

Using a desorption/ionization technique, easy ambient sonic-spray ionization coupled to mass spectrometry (EASI-MS), documents related to the 2nd generation of Brazilian Real currency (R$) were screened in the positive ion mode for authenticity based on chemical profiles obtained directly from the banknote surface. Characteristic profiles were observed for authentic, seized suspect counterfeit and counterfeited homemade banknotes from inkjet and laserjet printers. The chemicals in the authentic banknotes' surface were detected via a few minor sets of ions, namely from the plasticizers bis(2-ethylhexyl)phthalate (DEHP) and dibutyl phthalate (DBP), most likely related to the official offset printing process, and other common quaternary ammonium cations, presenting a similar chemical profile to 1st-generation R$. The seized suspect counterfeit banknotes, however, displayed abundant diagnostic ions in the m/z 400-800 range due to the presence of oligomers. High-accuracy FT-ICR MS analysis enabled molecular formula assignment for each ion. The ions were separated by 44 m/z, which enabled their characterization as Surfynol® 4XX (S4XX, XX=40, 65, and 85), wherein increasing XX values indicate increasing amounts of ethoxylation on a backbone of 2,4,7,9-tetramethyl-5-decyne-4,7-diol (Surfynol® 104). Sodiated triethylene glycol monobutyl ether (TBG) of m/z 229 (C10H22O4Na) was also identified in the seized counterfeit banknotes via EASI(+) FT-ICR MS. Surfynol® and TBG are constituents of inks used for inkjet printing.

Undulatory Physical Resistance Training Program Increases Maximal Strength In Elderly Type 2 Diabetics.

To investigate the effects of a specific protocol of undulatory physical resistance training on maximal strength gains in elderly type 2 diabetics. The study included 48 subjects, aged between 60 and 85 years, of both genders. They were divided into two groups: Untrained Diabetic Elderly (n=19) with those who were not subjected to physical training and Trained Diabetic Elderly (n=29), with those who were subjected to undulatory physical resistance training. The participants were evaluated with several types of resistance training's equipment before and after training protocol, by test of one maximal repetition. The subjects were trained on undulatory resistance three times per week for a period of 16 weeks. The overload used in undulatory resistance training was equivalent to 50% of one maximal repetition and 70% of one maximal repetition, alternating weekly. Statistical analysis revealed significant differences (p<0.05) between pre-test and post-test over a period of 16 weeks. The average gains in strength were 43.20% (knee extension), 65.00% (knee flexion), 27.80% (supine sitting machine), 31.00% (rowing sitting), 43.90% (biceps pulley), and 21.10% (triceps pulley). Undulatory resistance training used with weekly different overloads was effective to provide significant gains in maximum strength in elderly type 2 diabetic individuals.

Semiologia neurológica numa população de escolares da primeira série do ensino fundamental

We evaluated children in the first grade of a elementary school using neurological examination. With no previous knowledgement of their educational performance, were invited all children attending five classes of the first grade of an elementary public school chosen randomly, in Itatiba / Sao Paulo / Brazil, whose parents assigned a Commitment Term for participation in this research. Children who missed three evaluations in different days or whose parents did not assigned the Commitment Term were excluded. The Traditional Neurological Examination (ENT) (Lefevre, 1972) was applied. It was considered for normal the measurement of the skull circumference, proposed by Diament & Rodrigues (1976), and the application of all ENT items. The data were stored in a database of the Epi6 Program (Epidemiologic Information), and analyzed by percentage calculation and by the c2 test. The significance level was 0.05. Children evaluated were 124. The ENT results were normal in 87 (70.16%) and altered in 37 (29.83%). Among the alterations, there were observed: light tremor, light muscular hypotonia, speech acquisition delay, macrocephaly, microcephaly, hyperactivity, cranial nerve syndrome, central facial paralysis. One child presented corticospinal tract impairment syndrome of the distal lower extremities.