Supervised and weakly supervised counting-by-segmentation: the fluorescent microscopy use case

This thesis focuses on automating the time-consuming task of manually counting activated neurons in fluorescent microscopy images, which is used to study the mechanisms underlying torpor. The traditional method of manual annotation can introduce bias and delay the outcome of experiments, so the author investigates a deep-learning-based procedure to automatize this task. The author explores two of the main convolutional-neural-network (CNNs) state-of-the-art architectures: UNet and ResUnet family model, and uses a counting-by-segmentation strategy to provide a justification of the objects considered during the counting process. The author also explores a weakly-supervised learning strategy that exploits only dot annotations. The author quantifies the advantages in terms of data reduction and counting performance boost obtainable with a transfer-learning approach and, specifically, a fine-tuning procedure. The author released the dataset used for the supervised use case and all the pre-training models, and designed a web application to share both the counting process pipeline developed in this work and the models pre-trained on the dataset analyzed in this work.

Promuovere l'autovalutazione e il miglioramento delle strategie di apprendimento degli studenti internazionali cinesi: una ricerca empirica presso l'Università di Bologna

Nel quadro di alcuni filoni di ricerca inerenti alla promozione delle strategie cognitive, metacognitive e motivazionali degli studenti per una migliore efficacia del loro apprendimento (anche a livello universitario), il contributo presenta l’impianto e gli esiti di una ricerca empirica volta a indagare le percezioni degli studenti internazionali cinesi sulla loro esperienza universitaria in Italia, con un focus sulle eventuali difficoltà nell’adozione di un approccio autonomo e strategico all’apprendimento, e a sperimentare un intervento formativo messo a punto per sostenerli nel miglioramento del loro approccio all’apprendimento attraverso l’uso di procedure sistematiche di autoriflessione, self-recording e autovalutazione supportate dalla ricercatrice. Il disegno della ricerca è un quasi-esperimento a due gruppi con pre-test e post-test. Il campione è costituito da 60 studenti di diversi Dipartimenti dell’Università di Bologna che hanno partecipato volontariamente alla ricerca, di cui 30 hanno preso parte all’intervento. Gli strumenti utilizzati per la misurazione in ingresso e in uscita sono il Questionario sui Processi di Apprendimento e alcune scale del Questionario sulle Strategie di Apprendimento. Agli studenti del gruppo sperimentale è stato somministrato anche un questionario finale di valutazione del percorso formativo. Sono state inoltre effettuate alcune interviste a distanza di tempo come fase di follow up. Gli studenti in entrambi i gruppi affrontano sfide relative all’ambientamento nel contesto universitario italiano, con particolare riferimento a difficoltà linguistiche e di integrazione sociale. I principali fattori influenti sull’efficacia dello studio includono le barriere linguistiche, la gestione del tempo, la consapevolezza e l’uso delle strategie di studio. Nonostante emerga un miglioramento del gruppo sperimentale tra pre e post test, le differenze tra i due gruppi non sono risultate statisticamente significative. Tuttavia, i feedback forniti dagli studenti nel questionario di soddisfazione per il percorso formativo e nelle interviste post-intervento evidenziano percezioni positive sull’utilità del percorso, con benefici relativi al loro approccio allo studio.

Neural Network Based UAV Fault Tolerant Control with Aerodynamic Disturbance Estimation and Compensation

In this thesis, the problem of controlling a quadrotor UAV is considered. It is done by presenting an original control system, designed as a combination of Neural Networks and Disturbance Observer, using a composite learning approach for a system of the second order, which is a novel methodology in literature. After a brief introduction about the quadrotors, the concepts needed to understand the controller are presented, such as the main notions of advanced control, the basic structure and design of a Neural Network, the modeling of a quadrotor and its dynamics. The full simulator, developed on the MATLAB Simulink environment, used throughout the whole thesis, is also shown. For the guidance and control purposes, a Sliding Mode Controller, used as a reference, it is firstly introduced, and its theory and implementation on the simulator are illustrated. Finally the original controller is introduced, through its novel formulation, and implementation on the model. The effectiveness and robustness of the two controllers are then proven by extensive simulations in all different conditions of external disturbance and faults.

The Learning Tourism Destination: The potential of a learning organisation approach for improving the sustainability of tourism destinations

Globalisation, increasing complexity, and the need to address triple-bottom line sustainability has seen the proliferation of Learning Organisations (LO) who, by definition, have the capacity to anticipate environmental changes and economic opportunities and adapt accordingly. Such organisations use system dynamics modelling (SDM) for both strategic planning and the promotion of organisational learning. Although SDM has been applied in the context of tourism destination management for predictive reasons, the current literature does not analyse or recognise how this could be used as a foundation for an LO. This study introduces the concept of the Learning Tourism Destinations (LTD) and discusses, on the basis of a review of 6 case studies, the potential of SDM as a tool for the implementation and enhancement of collective learning processes. The results reveal that SDM is capable of promoting communication between stakeholders and stimulating organisational learning. It is suggested that the LTD approach be further utilised and explored.

The Building Partnerships Program: An Approach to Community-based Learning for Medical Students in Australia

The Building Partnerships Program at the University of Queensland, Australia seeks to address the dual challenge of preparing doctors who are responsive to the community while providing a meaningful context for social sciences learning. Through partnerships with a diverse range of community agencies, the program offers students opportunities to gain non-clinical perspectives on health and illness through structured learning activities including: family visits; community agency visits and attachments; and interview training. Students learn first-hand about psychosocial influences on health and how people manage health problems on a day-to-day basis. They also gain insights into the work of community agencies and how they as future doctors might work in partnership with them to enhance patient care. We outline the main components of the program, identify challenges and successes from student and community agency perspectives, and consider areas that invite further development.

Teaching and learning production and operations management: the journey from identity crisis to a cross, disciplinary approach

Este artigo tem suas raízes em algumas questões relacionadas à "forma" e ao "conteúdo" do que nós, professores, ensinamos na área de Administração da Produção e Operações. Inicialmente, descrevo a evolução histórica desse campo no Brasil. Em seguida, discuto a crise de identidade que o campo está sofrendo. Com o objetivo de apresentar respostas para essa situação, apresento seis propostas para o desenvolvimento e consolidação do campo. Finalmente, descrevo uma iniciativa prática, envolvendo uma disciplina específica da área, ensinada para alunos de pós-graduação. Essa iniciativa enfatiza a "dimensão do conteúdo" (de uma abordagem técnico-operacional para uma abordagem estratégico-gerencial) como também a "dimensão da forma" (do foco no ensino para o foco no aprendizado). O sucesso dessa experiência em curso confirma a coerência da agenda proposta e induz futuros aperfeiçoamentos.

Thinking over b‐learning strategy: the MIPO model approach

This article describes the main research results in a new methodology, in which the stages and strategies of the technology integration process are identified and described. A set of principles and recommendations are therefore presented. The MIPO model described in this paper is a result of the effort made regarding the understanding of the main success features of good practices, in the web environment, integrated in the information systems/information technology context. The initial model has been created, based on experiences and literature review. After that, it was tested in the information and technology system units at higher school and also adapted as a result of four cycles of an actionresearch work combined with a case study research. The information, concepts and procedures presented here give support to teachers and instructors, instructional designers and planning teams – anyone who wants to develop effective b‐learning instructions.

Unlocking the technology-mediated learning process : insights and articulating actions for an institutional approach

This paper is part of the results from the project "Implementation Strategies and Development of an Open and Distance Education System for the University of the Azores" funded by the European Social Fund. http://hdl.handle.net/10400.3/2327

A sustainable approach to the reuse of student - centered learning scenarios

Proceedings of EULEARN09 - Intenational Conference and New Learning Technologies, Barcelona, Spain, 6-8 July

A semantic approach for learning objects repositories with knowledge reuse

In this paper we discuss how the inclusion of semantic functionalities in a Learning Objects Repository allows a better characterization of the learning materials enclosed and improves their retrieval through the adoption of some query expansion strategies. Thus, we started to regard the use of ontologies to automatically suggest additional concepts when users are filling some metadata fields and add new terms to the ones initially provided when users specify the keywords with interest in a query. Dealing with different domain areas and having considered impractical the development of many different ontologies, we adopted some strategies for reusing ontologies in order to have the knowledge necessary in our institutional repository. In this paper we make a review of the area of knowledge reuse and discuss our approach.

B-learning quality: dimensions, criteria and pedagogical approach

Measuring the quality of a b-learning environment is critical to determine the success of a b-learning course. Several initiatives have been recently conducted on benchmarking and quality in e-learning. Despite these efforts in defining and examining quality issues concerning online courses, a defining instrument to evaluate quality is one of the key challenges for blended learning, since it incorporates both traditional and online instruction methods. For this paper, six frameworks for quality assessment of technological enhanced learning were examined and compared regarding similarities and differences. These frameworks aim at the same global objective: the quality of e-learning environment/products. They present different perspectives but also many common issues. Some of them are more specific and related to the course and other are more global and related to institutional aspects. In this work we collected and arrange all the quality criteria identified in order to get a more complete framework and determine if it fits our b-learning environment. We also included elements related to our own b-learning research and experience, acquired during more than 10 years of experience. As a result we have create a new quality reference with a set of dimensions and criteria that should be taken into account when you are analyzing, designing, developing, implementing and evaluating a b-learning environment. Besides these perspectives on what to do when you are developing a b-learning environment we have also included pedagogical issues in order to give directions on how to do it to reach the success of the learning. The information, concepts and procedures here presented give support to teachers and instructors, which intend to validate the quality of their blended learning courses.

A Learning Algorithm and System Approach to Address Exceptional Events in Domestic Consumption Management

The integration of the Smart Grid concept into the electric grid brings to the need for an active participation of small and medium players. This active participation can be achieved using decentralized decisions, in which the end consumer can manage loads regarding the Smart Grid needs. The management of loads must handle the users’ preferences, wills and needs. However, the users’ preferences, wills and needs can suffer changes when faced with exceptional events. This paper proposes the integration of exceptional events into the SCADA House Intelligent Management (SHIM) system developed by the authors, to handle machine learning issues in the domestic consumption context. An illustrative application and learning case study is provided in this paper.

An approach to teach Calculus/Mathematical Analysis (for engineering students) using computers and active learning – its conception, development of materials and evaluation

Dissertação para obtenção do Grau de Doutor em Ciências da Educação

Learning joint representations for order and timing of perceptual-motor sequences: a dynamic neural field approach

Many of our everyday tasks require the control of the serial order and the timing of component actions. Using the dynamic neural field (DNF) framework, we address the learning of representations that support the performance of precisely time action sequences. In continuation of previous modeling work and robotics implementations, we ask specifically the question how feedback about executed actions might be used by the learning system to fine tune a joint memory representation of the ordinal and the temporal structure which has been initially acquired by observation. The perceptual memory is represented by a self-stabilized, multi-bump activity pattern of neurons encoding instances of a sensory event (e.g., color, position or pitch) which guides sequence learning. The strength of the population representation of each event is a function of elapsed time since sequence onset. We propose and test in simulations a simple learning rule that detects a mismatch between the expected and realized timing of events and adapts the activation strengths in order to compensate for the movement time needed to achieve the desired effect. The simulation results show that the effector-specific memory representation can be robustly recalled. We discuss the impact of the fast, activation-based learning that the DNF framework provides for robotics applications.