UNDERSTANDING ESSAY RATING AS A SOCIALLY MEDIATED ACTIVITY: THE CASE OF A HIGH-STAKES ENGLISH TEST IN CHINA

Thesis (Ph.D, Education) -- Queen's University, 2016-09-22 22:05:24.246

The quality of the physical environment and its association with activities and well-being among older people in residential care facilities

The physical environment can influence older people’s health and well-being, and is often mentioned as being an important factor for person-centred care. Due to high levels of frail health, many older people spend a majority of their time within care facilities and depend on the physical environment for support in their daily life. However, the quality of the physical environment is rarely evaluated, and knowledge is sparse in terms of how well the environment meets the needs of older people. This is partly due to the lack of valid and reliable instruments that could provide important information on environmental quality. Aim: The aim of this thesis was to study the quality of the physical environment in Swedish care facilities for older people, and how it relates to residents’ activities and well-being. Methods: The thesis comprises four papers where both qualitative and quantitative methods were used. Study I involved the translation and adaptation of the Sheffield Care Environment Assessment Matrix (SCEAM) into a Swedish version (S-SCEAM). Several methods were used including forward and backward translation, test of validity via expert consultation and reliability tests. In Study II, S-SCEAM was used to assess the quality of the environment, and descriptive data were collected from 20 purposively sampled residential care facilities (RCFs). Study III was a comparative case study conducted at two RCFs using observations, interviews and S-SCEAM to examine how the physical environment relates to older people’s activities and interactions. In study IV, multilevel modeling was used to determine the association between the quality of the physical environment and the psychological and social well-being of older people living in RCFs. The data in the thesis were analysed using qualitative content analysis, and descriptive, bivariate and multilevel statistics. Results: A specific result was the production of the Swedish version of SCEAM. The instrument contains 210 items structured into eight domains reflecting the needs of older people. When using S-SCEAM, the results showed a substantial variation in the quality of the physical environment between and within RCFs. In general, private apartments and dining areas had high quality, whereas overall building layout and outdoor areas had lower quality. Also, older people’s safety was supported in the majority of facilities, whereas cognitive support and privacy had lower quality. Further, the results showed that environmental quality in terms of cognitive support was associated with residents’ social well-being. Specific environmental features, such as building design and space size, were also noted, through observation, as influencing residents’ activities, and several barriers were found that seemed to restrict residents’ full use of the environment. Conclusions: This thesis contributes to the growing evidence-based design field. The S-SCEAM can be used in future research on the association between the environment and people’s health and well-being. The instrument could also serve as a guide in the planning and design process of new RCFs.

Autonomous formation flying: unified control and collision avoidance methods for close manoeuvring spacecraft

The idea of spacecraft formations, flying in tight configurations with maximum baselines of a few hundred meters in low-Earth orbits, has generated widespread interest over the last several years. Nevertheless, controlling the movement of spacecraft in formation poses difficulties, such as in-orbit high-computing demand and collision avoidance capabilities, which escalate as the number of units in the formation is increased and complicated nonlinear effects are imposed to the dynamics, together with uncertainty which may arise from the lack of knowledge of system parameters. These requirements have led to the need of reliable linear and nonlinear controllers in terms of relative and absolute dynamics. The objective of this thesis is, therefore, to introduce new control methods to allow spacecraft in formation, with circular/elliptical reference orbits, to efficiently execute safe autonomous manoeuvres. These controllers distinguish from the bulk of literature in that they merge guidance laws never applied before to spacecraft formation flying and collision avoidance capacities into a single control strategy. For this purpose, three control schemes are presented: linear optimal regulation, linear optimal estimation and adaptive nonlinear control. In general terms, the proposed control approaches command the dynamical performance of one or several followers with respect to a leader to asymptotically track a time-varying nominal trajectory (TVNT), while the threat of collision between the followers is reduced by repelling accelerations obtained from the collision avoidance scheme during the periods of closest proximity. Linear optimal regulation is achieved through a Riccati-based tracking controller. Within this control strategy, the controller provides guidance and tracking toward a desired TVNT, optimizing fuel consumption by Riccati procedure using a non-infinite cost function defined in terms of the desired TVNT, while repelling accelerations generated from the CAS will ensure evasive actions between the elements of the formation. The relative dynamics model, suitable for circular and eccentric low-Earth reference orbits, is based on the Tschauner and Hempel equations, and includes a control input and a nonlinear term corresponding to the CAS repelling accelerations. Linear optimal estimation is built on the forward-in-time separation principle. This controller encompasses two stages: regulation and estimation. The first stage requires the design of a full state feedback controller using the state vector reconstructed by means of the estimator. The second stage requires the design of an additional dynamical system, the estimator, to obtain the states which cannot be measured in order to approximately reconstruct the full state vector. Then, the separation principle states that an observer built for a known input can also be used to estimate the state of the system and to generate the control input. This allows the design of the observer and the feedback independently, by exploiting the advantages of linear quadratic regulator theory, in order to estimate the states of a dynamical system with model and sensor uncertainty. The relative dynamics is described with the linear system used in the previous controller, with a control input and nonlinearities entering via the repelling accelerations from the CAS during collision avoidance events. Moreover, sensor uncertainty is added to the control process by considering carrier-phase differential GPS (CDGPS) velocity measurement error. An adaptive control law capable of delivering superior closed-loop performance when compared to the certainty-equivalence (CE) adaptive controllers is finally presented. A novel noncertainty-equivalence controller based on the Immersion and Invariance paradigm for close-manoeuvring spacecraft formation flying in both circular and elliptical low-Earth reference orbits is introduced. The proposed control scheme achieves stabilization by immersing the plant dynamics into a target dynamical system (or manifold) that captures the desired dynamical behaviour. They key feature of this methodology is the addition of a new term to the classical certainty-equivalence control approach that, in conjunction with the parameter update law, is designed to achieve adaptive stabilization. This parameter has the ultimate task of shaping the manifold into which the adaptive system is immersed. The performance of the controller is proven stable via a Lyapunov-based analysis and Barbalat’s lemma. In order to evaluate the design of the controllers, test cases based on the physical and orbital features of the Prototype Research Instruments and Space Mission Technology Advancement (PRISMA) are implemented, extending the number of elements in the formation into scenarios with reconfigurations and on-orbit position switching in elliptical low-Earth reference orbits. An extensive analysis and comparison of the performance of the controllers in terms of total Δv and fuel consumption, with and without the effects of the CAS, is presented. These results show that the three proposed controllers allow the followers to asymptotically track the desired nominal trajectory and, additionally, those simulations including CAS show an effective decrease of collision risk during the performance of the manoeuvre.

Normative reference values for the 20-meter shuttlerun test in a population-based sample of schoolchildren in Bogota, Colombia: The FUPRECOL Study

Our aim was to determine the normative reference values of cardiorespiratory fitness (CRF) and to establish the proportion of subjects with low CRF suggestive of future cardio-metabolic risk.

Dynamical modeling of biogas production supported by an experimental anaerobic digestion process

This paper presents the development of a combined experimental and numerical approach to study the anaerobic digestion of both the wastes produced in a biorefinery using yeast for biodiesel production and the wastes generated in the preceding microbial biomass production. The experimental results show that it is possible to valorise through anaerobic digestion all the tested residues. In the implementation of the numerical model for anaerobic digestion, a procedure for the identification of its parameters needs to be developed. A hybrid search Genetic Algorithm was used, followed by a direct search method. In order to test the procedure for estimation of parameters, first noise-free data was considered and a critical analysis of the results obtain so far was undertaken. As a demonstration of its application, the procedure was applied to experimental data.

Relationship between blood pressure and psychological features of experience and behaviour among teachers

Purpose: Relationships between psychic features and psychophysical parameters, such as blood pressure, have a high relevance in research on coping with stress. We want to investigate the correlation between blood pressure and this psychic features. Methods: We investigated 79 teachers from high schools and secondary schools in and around Leipzig, Germany. Using the systolic blood pressure as an indicator, we built three groups: hypotonics, normotonics, and hypertonics. We assessed several health psychologically dependent variables and looked for differences between these groups (Chi-Square-Test). Results: Hypotonics experienced more stress and less planning and goal behaviour. Furthermore, they more often use physical exercises in order to increase their social well-being. Hypertonics, on the other hand, were driven by fear of loss of control and show a higher sense of feeling threatened. Conclusions: We could find for each group different relationships that are highly relevant to health. This results shows how psychological features and physiological regulation mechanisms are linked.

Sviluppo di un framework per l'automazione dei test al banco e la prototipazione di algoritmi di controllo di motori a combustione interna

Negli ultimi anni, i limiti sempre più stringenti sulle emissioni inquinanti dei gas di scarico, hanno portato ad un notevole aumento della complessità dei motori a combustione interna. Questa complicazione determina un aumento esponenziale del numero di test da effettuare nella sala prova. I metodi tipici di gestione dei test non possono più essere utilizzati, ma è essenziale creare un sistema che ottimizzi le prove. Per ridurre drasticamente il tempo di esecuzione, è necessario implementare un'architettura in grado di facilitare lo scambio di dati tra i sistemi presenti nella sala prova, e, in aggiunta, definire le strategie di automazione dei test. L'approccio a taluni metodi si presenta ancora complicato in molti gruppi di sviluppo di strategie di controllo motore, anche se, una volta sviluppati, portano e a grandi benefici durante la fase di test. Il lavoro illustra i metodi implementati per la gestione di queste strategie. Prima si descrive l'approccio utilizzato nella calibrazione di anticipo di accensione per mantenere livelli accettabili di detonazione durante il processo di calibrazione. Successivamente è mostrato il sistema di automazione dei test che consente il pieno controllo del punto di funzionamento del motore, la gestione dell'acquisizione e la verifica della stabilità delle condizioni ottenute. L'ultima parte mostra sistemi di prototipazione rapida per la gestione di componenti innovatici del motore.

Additive Manufacturing by LPBF and WAAM of metals: correlation between production process, microstructure and mechanical properties

In the most recent years, Additive Manufacturing (AM) has drawn the attention of both academic research and industry, as it might deeply change and improve several industrial sectors. From the material point of view, AM results in a peculiar microstructure that strictly depends on the conditions of the additive process and directly affects mechanical properties. The present PhD research project aimed at investigating the process-microstructure-properties relationship of additively manufactured metal components. Two technologies belonging to the AM family were considered: Laser-based Powder Bed Fusion (LPBF) and Wire-and-Arc Additive Manufacturing (WAAM). The experimental activity was carried out on different metals of industrial interest: a CoCrMo biomedical alloy and an AlSi7Mg0.6 alloy processed by LPBF, an AlMg4.5Mn alloy and an AISI 304L austenitic stainless steel processed by WAAM. In case of LPBF, great attention was paid to the influence that feedstock material and process parameters exert on hardness, morphological and microstructural features of the produced samples. The analyses, targeted at minimizing microstructural defects, lead to process optimization. For heat-treatable LPBF alloys, innovative post-process heat treatments, tailored on the peculiar hierarchical microstructure induced by LPBF, were developed and deeply investigated. Main mechanical properties of as-built and heat-treated alloys were assessed and they were well-correlated to the specific LPBF microstructure. Results showed that, if properly optimized, samples exhibit a good trade-off between strength and ductility yet in the as-built condition. However, tailored heat treatments succeeded in improving the overall performance of the LPBF alloys. Characterization of WAAM alloys, instead, evidenced the microstructural and mechanical anisotropy typical of AM metals. Experiments revealed also an outstanding anisotropy in the elastic modulus of the austenitic stainless-steel that, along with other mechanical properties, was explained on the basis of microstructural analyses.

Virtual Calibration of CO2 and Pollutant Emissions of a High-Performance PHEV using Model-in-the-Loop Methodology

The study analyses the calibration process of a newly developed high-performance plug-in hybrid electric passenger car powertrain. The complexity of modern powertrains and the more and more restrictive regulations regarding pollutant emissions are the primary challenges for the calibration of a vehicle’s powertrain. In addition, the managers of OEM need to know as earlier as possible if the vehicle under development will meet the target technical features (emission included). This leads to the necessity for advanced calibration methodologies, in order to keep the development of the powertrain robust, time and cost effective. The suggested solution is the virtual calibration, that allows the tuning of control functions of a powertrain before having it built. The aim of this study is to calibrate virtually the hybrid control unit functions in order to optimize the pollutant emissions and the fuel consumption. Starting from the model of the conventional vehicle, the powertrain is then hybridized and integrated with emissions and aftertreatments models. After its validation, the hybrid control unit strategies are optimized using the Model-in-the-Loop testing methodology. The calibration activities will proceed thanks to the implementation of a Hardware-in-the-Loop environment, that will allow to test and calibrate the Engine and Transmission control units effectively, besides in a time and cost saving manner.

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.

Structural health monitoring of storage tanks

In this thesis, Ph.D candidate presents a compact sensor node (SN) designed for long-term and real-time acoustic emission (AE) monitoring of above ground storage tanks (ASTs). Each SN exploits up to three inexpensive low-frequency sensors based on piezoelectric diaphragms for effective leakage detection, and it is capable by means of built-in Digital Signal Processing functionalities to process the acquired time waveforms extracting the AE features usually required by testing protocols. Alternatively, capability to plug three high frequency AE sensors to a SN for corrosion simulated phenomena detection is envisaged and demonstrated. Another innovative aspect that the Ph.D candidate presents in this work is an alternative mathematical model of corrosion location on the bottom of the AST. This approach implies considering the three-dimensional localization model versus the two-dimensional commonly used according to the literature. This approach is aimed at significant optimization in the number of sensors in relation to the standard approach for solving localization problems as well as to allow filtering the false AE events related to the condensate droplets from AST ceiling. The technological implementation of this concept required the solution of a number of technical problems, such as the precise time of arrival (ToA) signal estimation, vertical localization of the AE source and multilaration solution that were discussed in detail in this work. To validate the developed prototype, several experimental campaigns were organized that included the simulation of target phenomena both in laboratory conditions and on a real water storage tank. The presented test results demonstrate the successful application of the developed AE system both for simulated leaks and for corrosion processes on the tank bottom. Mathematical and technological algorithms for localization and characterization of AE signals implemented during the development of the prototype are also confirmed by the test results.

Design and testing of innovative, artificial intelligence-based techniques to model and control the combustion process and to reduce the Co2 emissions in modern, high-performance, gasoline direct injection engines

This work deals with the development of calibration procedures and control systems to improve the performance and efficiency of modern spark ignition turbocharged engines. The algorithms developed are used to optimize and manage the spark advance and the air-to-fuel ratio to control the knock and the exhaust gas temperature at the turbine inlet. The described work falls within the activity that the research group started in the previous years with the industrial partner Ferrari S.p.a. . The first chapter deals with the development of a control-oriented engine simulator based on a neural network approach, with which the main combustion indexes can be simulated. The second chapter deals with the development of a procedure to calibrate offline the spark advance and the air-to-fuel ratio to run the engine under knock-limited conditions and with the maximum admissible exhaust gas temperature at the turbine inlet. This procedure is then converted into a model-based control system and validated with a Software in the Loop approach using the engine simulator developed in the first chapter. Finally, it is implemented in a rapid control prototyping hardware to manage the combustion in steady-state and transient operating conditions at the test bench. The third chapter deals with the study of an innovative and cheap sensor for the in-cylinder pressure measurement, which is a piezoelectric washer that can be installed between the spark plug and the engine head. The signal generated by this kind of sensor is studied, developing a specific algorithm to adjust the value of the knock index in real-time. Finally, with the engine simulator developed in the first chapter, it is demonstrated that the innovative sensor can be coupled with the control system described in the second chapter and that the performance obtained could be the same reachable with the standard in-cylinder pressure sensors.

High-strength steels manufactured via Laser Powder Bed Fusion: effect of post-process heat treatments and surface finishing on microstructure and mechanical properties

Laser Powder Bed Fusion (LPBF) permits the manufacturing of parts with optimized geometry, enabling lightweight design of mechanical components in aerospace and automotive and the production of tools with conformal cooling channels. In order to produce parts with high strength-to-weight ratio, high-strength steels are required. To date, the most diffused high-strength steels for LPBF are hot-work tool steels, maraging and precipitation-hardening stainless steels, featuring different composition, feasibility and properties. Moreover, LPBF parts usually require a proper heat treatment and surface finishing, to develop the desired properties and reduce the high roughness resulting from LPBF. The present PhD thesis investigates the effect of different heat treatments and surface finishing on the microstructure and mechanical properties of a hot-work tool steel and a precipitation-hardening stainless steel manufactured via LPBF. The bibliographic section focuses on the main aspects of LPBF, hot-work tool steels and precipitation-hardening stainless steels. The experimental section is divided in two parts. Part A addresses the effect of different heat treatments and surface finishing on the microstructure, hardness, tensile and fatigue behaviour of a LPBF manufactured hot-work tool steel, to evaluate its feasibility for automotive and racing components. Results indicated the possibility to achieve high hardness and strength, comparable to the conventionally produced steel, but a great sensitivity of fatigue strength on defects and surface roughness resulting from LPBF. Part B investigates the effect of different heat treatments on the microstructure, hardness, tensile and notch-impact behaviour of a LPBF produced precipitation-hardening stainless steel, to assess its feasibility for tooling applications. Results indicated the possibility to achieve high hardness and strength also through a simple Direct Aging, enabling heat treatment simplification by exploiting the microstructural features resulting from LPBF.

Bright-field multiplex immunohistochemistry for tumor. Microenvironment evaluation in mucosal melanoma of the head and neck region: technical aspects, results, and correlation with clinicopathologic features and molecular landscape

Mucosal melanoma of the head and neck region (MM-H&N) is a rare disease, characterized by a poor prognosis and limited therapeutic strategies, especially regarding targeted therapy (lower rate of targetable mutations compared to cutaneous melanoma) and immunotherapy (lack of diagnostic tools able to predict the response). Meanwhile, bright-field multiplex immunohistochemistry (BF-mIHC) is emerging as a promising tool for characterizing tumor microenvironment (TME) and predicting response to immunotherapy in several tumors, including melanoma. This PhD project aims to develop a BF-mIHC protocol to evaluate the TME in MM-H&N, analyze the correlation between immune markers/immune profiles and MM-H&N features (clinicopathologic and molecular), and find new biomarkers useful for prognostic-therapeutic stratification of these patients. Specific aims are: (I) describe the clinicopathological features of MM-H&N; (II) analyze the molecular status of MM-H&N and correlate it with the clinicopathological features; (III) analyze the molecular status of multiple specimens from the same patient to verify whether molecular heterogeneity of MM-H&N could affect the results with relevant prognostic-therapeutic implications; (IV) develop a BF-mIHC protocol to study TME in MM-H&N; (V) analyze the correlation between immune markers/immune profiles and MM-H&N features (clinicopathologic and molecular) to test whether BF-mIHC could be a promising tool for prognostic-therapeutic characterization of these patients.

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.