The use of process simulation methods in support of organisational learning in availability contracting

Traditional business models in the aerospace industry are based on a conventional supplier to customer relationship based on the design, manufacture and subsequent delivery of the physical product. Service provision, from the manufacturer's perspective, is typically limited to the supply of procedural documentation and the provision of spare parts to the end user as the product passes through the latter stages of its intended lifecycle. Challenging economic and political conditions have resulted in end users re-structuring their core business activities, particularly in the defence sector. This has resulted in the need for original equipment manufacturers (OEMs) to integrate and manage support service activities in partnership with the customer to deliver platform availability. This improves the probability of commercial sustainability for the OEM through shared operational risks while reducing the cost of platform ownership for the customer. The need for OEMs to evolve their design, manufacture and supply strategies by focusing on customer requirements has revealed a need for reconstruction of traditional internal behaviours and design methodologies. Application of organisational learning is now a well recognised principle for innovative companies to achieve long term growth and sustained technical development, and hence, greater market command. It focuses on the process by which the organisation's knowledge and value base changes, leading to improved problem solving ability and capacity for action. From the perspective of availability contracting, knowledge and the processes by which it is generated, used and retained, become primary assets within the learning organisation. This paper will introduce the application of digital methods to asset management by demonstrating how the process of learning can benefit from a digital approach, how product and process design can be integrated within a virtual framework and finally how the approach can be applied in a service context.

LC- HRMS based metabolomics in food safety and doping control – DeTECH21

Issues surrounding the misuse of prohibited and licensed substances in animals destined for food production and performance sport competition continue to be an enormous challenge to regulatory authorities charged with enforcing their control. Efficient analytical strategies are implemented to screen and confirm the presence of a wide range of exogenous substances in various biological matrices. However, such methods rely on the direct measurement of drugs and/or their metabolites in a targeted mode, allowing the detection of restricted number of compounds. As a consequence, emerging practices, in particular the use of natural hormones, designer drugs and low-dose cocktails, remain difficult to handle from a control point of view. A new SME-led FP7 funded project, DeTECH21, aims to overcome current limitations by applying an untargeted metabolomics approach based on liquid chromatography coupled to high resolution mass spectrometry and bioinformatic data analysis to identify bovine and equine animals which have been exposed to exogenous substances and assist in the identification of administered compounds. Markerbased strategies, dealing with the comprehensive analysis of metabolites present in a biological sample (urine/plasma/tissue), offer a reliable solution in the areas of food safety and animal sport doping control by effective, high-throughput and sensitive detection of exogenously administered agents. Therefore, the development of the first commercially available forensic test service based on metabolomics profiling will meet 21st century demands in animal forensics.

Machine learning for transient discovery in Pan-STARRS1 difference imaging

Efficient identification and follow-up of astronomical transients is hindered by the need for humans to manually select promising candidates from data streams that contain many false positives. These artefacts arise in the difference images that are produced by most major ground-based time-domain surveys with large format CCD cameras. This dependence on humans to reject bogus detections is unsustainable for next generation all-sky surveys and significant effort is now being invested to solve the problem computationally. In this paper, we explore a simple machine learning approach to real-bogus classification by constructing a training set from the image data of similar to 32 000 real astrophysical transients and bogus detections from the Pan-STARRS1 Medium Deep Survey. We derive our feature representation from the pixel intensity values of a 20 x 20 pixel stamp around the centre of the candidates. This differs from previous work in that it works directly on the pixels rather than catalogued domain knowledge for feature design or selection. Three machine learning algorithms are trained (artificial neural networks, support vector machines and random forests) and their performances are tested on a held-out subset of 25 per cent of the training data. We find the best results from the random forest classifier and demonstrate that by accepting a false positive rate of 1 per cent, the classifier initially suggests a missed detection rate of around 10 per cent. However, we also find that a combination of bright star variability, nuclear transients and uncertainty in human labelling means that our best estimate of the missed detection rate is approximately 6 per cent.

An Efficient LS-SVM-Based Method for Fuzzy System Construction

This paper proposes an efficient learning mechanism to build fuzzy rule-based systems through the construction of sparse least-squares support vector machines (LS-SVMs). In addition to the significantly reduced computational complexity in model training, the resultant LS-SVM-based fuzzy system is sparser while offers satisfactory generalization capability over unseen data. It is well known that the LS-SVMs have their computational advantage over conventional SVMs in the model training process; however, the model sparseness is lost, which is the main drawback of LS-SVMs. This is an open problem for the LS-SVMs. To tackle the nonsparseness issue, a new regression alternative to the Lagrangian solution for the LS-SVM is first presented. A novel efficient learning mechanism is then proposed in this paper to extract a sparse set of support vectors for generating fuzzy IF-THEN rules. This novel mechanism works in a stepwise subset selection manner, including a forward expansion phase and a backward exclusion phase in each selection step. The implementation of the algorithm is computationally very efficient due to the introduction of a few key techniques to avoid the matrix inverse operations to accelerate the training process. The computational efficiency is also confirmed by detailed computational complexity analysis. As a result, the proposed approach is not only able to achieve the sparseness of the resultant LS-SVM-based fuzzy systems but significantly reduces the amount of computational effort in model training as well. Three experimental examples are presented to demonstrate the effectiveness and efficiency of the proposed learning mechanism and the sparseness of the obtained LS-SVM-based fuzzy systems, in comparison with other SVM-based learning techniques.

Aprendizagem baseada em projetos na consolidação de conceitos de programação de linguagens SCRIPT

Relatório da prática de ensino supervisionada, Mestrado em Ensino de Informática, Universidade de Lisboa, 2014

Business Process Modelling based on formal temporal theory with an application to hospital patient flows

Existing Workflow Management Systems (WFMSs) follow a pragmatic approach. They often use a proprietary modelling language with an intuitive graphical layout. However the underlying semantics lack a formal foundation. As a consequence, analysis issues, such as proving correctness i.e. soundness and completeness, and reliable execution are not supported at design level. This project will be using an applied ontology approach by formally defining key terms such as process, sub-process, action/task based on formal temporal theory. Current business process modelling (BPM) standards such as Business Process Modelling Notation (BPMN) and Unified Modelling Language (UML) Activity Diagram (AD) model their constructs with no logical basis. This investigation will contribute to the research and industry by providing a framework that will provide grounding for BPM to reason and represent a correct business process (BP). This is missing in the current BPM domain, and may result in reduction of the design costs and avert the burden of redundant terms used by the current standards. A graphical tool will be introduced which will implement the formal ontology defined in the framework. This new tool can be used both as a modelling tool and at the same time will serve the purpose of validating the model. This research will also fill the existing gap by providing a unified graphical representation to represent a BP in a logically consistent manner for the mainstream modelling standards in the fields of business and IT. A case study will be conducted to analyse a catalogue of existing ‘patient pathways’ i.e. processes, of King’s College Hospital NHS Trust including current performance statistics. Following the application of the framework, a mapping will be conducted, and new performance statistics will be collected. A cost/benefits analysis report will be produced comparing the results of the two approaches.

A general framework for Business Process Modelling (BPM) based on Formal Temporal Theory with an application to Hospital Patient flows

Existing Workflow Management Systems (WFMSs) follow a pragmatic approach. They often use a proprietary modelling language with an intuitive graphical layout. However the underlying semantics lack a formal foundation. As a consequence, analysis issues, such as proving correctness i.e. soundness and completeness, and reliable execution are not supported at design level. This project will be using an applied ontology approach by formally defining key terms such as process, sub-process, action/task based on formal temporal theory. Current business process modelling (BPM) standards such as Business Process Modelling Notation (BPMN) and Unified Modelling Language (UML) Activity Diagram (AD) model their constructs with no logical basis. This investigation will contribute to the research and industry by providing a framework that will provide grounding for BPM to reason and represent a correct business process (BP). This is missing in the current BPM domain, and may result in reduction of the design costs and avert the burden of redundant terms used by the current standards. A graphical tool will be introduced which will implement the formal ontology defined in the framework. This new tool can be used both as a modelling tool and at the same time will serve the purpose of validating the model. This research will also fill the existing gap by providing a unified graphical representation to represent a BP in a logically consistent manner for the mainstream modelling standards in the fields of business and IT. A case study will be conducted to analyse a catalogue of existing ‘patient pathways’ i.e. processes, of King’s College Hospital NHS Trust including current performance statistics. Following the application of the framework, a mapping will be conducted, and new performance statistics will be collected. A cost/benefits analysis report will be produced comparing the results of the two approaches.

Controlo fotogramétrico da condição de estruturas quebra-mar

Dissertação de natureza Científica para obtenção do grau de Mestre em Engenharia Civil

A mobile robot platform for open learning based on serious games and remote laboratories

Within the pedagogical community, Serious Games have arisen as a viable alternative to traditional course-based learning materials. Until now, they have been based strictly on software solutions. Meanwhile, research into Remote Laboratories has shown that they are a viable, low-cost solution for experimentation in an engineering context, providing uninterrupted access, low-maintenance requirements, and a heightened sense of reality when compared to simulations. This paper will propose a solution where both approaches are combined to deliver a Remote Laboratory-based Serious Game for use in engineering and school education. The platform for this system is the WebLab-Deusto Framework, already well-tested within the remote laboratory context, and based on open standards. The laboratory allows users to control a mobile robot in a labyrinth environment and take part in an interactive game where they must locate and correctly answer several questions, the subject of which can be adapted to educators' needs. It also integrates the Google Blockly graphical programming language, allowing students to learn basic programming and logic principles without needing to understand complex syntax.

Influence of a lifestyle intervention in preschool children on physiological and psychological parameters (Ballabeina): study design of a cluster randomized controlled trial.

Childhood obesity and physical inactivity are increasing dramatically worldwide. Children of low socioeconomic status and/or children of migrant background are especially at risk. In general, the overall effectiveness of school-based programs on health-related outcomes has been disappointing. A special gap exists for younger children and in high risk groups. This paper describes the rationale, design, curriculum, and evaluation of a multicenter preschool randomized intervention study conducted in areas with a high migrant population in two out of 26 Swiss cantons. Twenty preschool classes in the German (canton St. Gallen) and another 20 in the French (canton Vaud) part of Switzerland were separately selected and randomized to an intervention and a control arm by the use of opaque envelopes. The multidisciplinary lifestyle intervention aimed to increase physical activity and sleep duration, to reinforce healthy nutrition and eating behaviour, and to reduce media use. According to the ecological model, it included children, their parents and the teachers. The regular teachers performed the majority of the intervention and were supported by a local health promoter. The intervention included physical activity lessons, adaptation of the built infrastructure; promotion of regional extracurricular physical activity; playful lessons about nutrition, media use and sleep, funny homework cards and information materials for teachers and parents. It lasted one school year. Baseline and post-intervention evaluations were performed in both arms. Primary outcome measures included BMI and aerobic fitness (20 m shuttle run test). Secondary outcomes included total (skinfolds, bioelectrical impedance) and central (waist circumference) body fat, motor abilities (obstacle course, static and dynamic balance), physical activity and sleep duration (accelerometry and questionnaires), nutritional behaviour and food intake, media use, quality of life and signs of hyperactivity (questionnaires), attention and spatial working memory ability (two validated tests). Researchers were blinded to group allocation. The purpose of this paper is to outline the design of a school-based multicenter cluster randomized, controlled trial aiming to reduce body mass index and to increase aerobic fitness in preschool children in culturally different parts of Switzerland with a high migrant population. Trial Registration: (clinicaltrials.gov) NCT00674544.

Exploring the use of effective learning strategies to increase students' reading comprehension and test taking skills /

This study examined the effects of providing students with explicit instruction in how to use a repertoire of reading comprehension strategies and test taking skills when reading and responding to three types of questions (direct, inferential, critical). Specifically, the study examined whether providing students with a "model" of how to read and respond to the text and to the comprehension questions improved their reading comprehension relative to providing them with implicit instruction on reading comprehension strategies and test taking skills. Students' reading comprehension and test taking performance scores were compared as a function of instructional condition. Students from 2 grade 8 classes participated in this study. The reading component of the Canadian Achievement Tests, Third Edition (CAT/3) was used to identify students' level of reading comprehension prior to the formal instructional sessions. Students received either explicit instruction, which involved modelling, or implicit instruction, which consisted of review and discussion of the strategies to be used. Comprehension was measured through the administration of formative tests after each instructional session. The formative tests consisted of reading comprehension questions pertaining to a specific form of text (narrative, informational, graphic). In addition, students completed 3 summative tests and a delayed comprehension test which consisted of the alternative version of the CAT/3 standardized reading assessment. These data served as a posttest measure to determine whether students had shown an improvement in their reading comprehension skills as a result of the program delivery. There were significant differences in students' Canadian Achievement Test performance scores prior to the onset of the study. Students in the implicit group attained significantly higher comprehension scores than did students in the explicit group. The results from the program sessions indicated no significant differences in reading comprehension between the implicit and explicit conditions, with the exception of the 6th session involving the reading and interpreting of graphic text. Students in the explicit group performed significantly better when reading and interpreting graphic text than those in the implicit group. No significant differences were evident between the two study conditions across the three summative tests. Upon completion of the study, the results from the Canadian Achievement Test indicated no significant differences in performance between the two study conditions. The findings from this study reveal the effectiveness of providing students with explicit strategy instruction when reading and responding to various forms of text. Modelling the appropriate reading comprehension strategies and test taking skills enabled students to apply the same thought processes to their own independent work. This form of instruction enabled students in the explicit group to improve in their abilities to comprehend and respond to text and therefore should be incorporated as an effective form of classroom teaching.

Riffing on a Theme: Faculty Experiences With Service-Learning in a Food Security Research Network in Ontario

While service-learning is often said to be beneficial for all those involved—students, community members, higher education institutions, and faculty members—there are relatively few studies of the attraction to, and effect of, service-learning on faculty members. Existing studies have tended to use a survey design, and to be based in the United States. There is a lack of information on faculty experiences with service-learning in Ontario or Canada. This qualitative case study of faculty experiences with service-learning was framed through an Appreciative Inquiry social constructionist approach. The data were drawn from interviews with 18 faculty members who belong to a Food Security Research Network (FSRN) at a university in northern Ontario, reports submitted by the network, and personal observation of a selection of network-related events. This dissertation study revealed how involvement with service-learning created opportunities for faculty learning and growth. The focus on food security and a commitment to the sustainability of local food production was found to be an ongoing attraction to service-learning and a means to engage in and integrate research and teaching on matters of personal and professional importance to these faculty members. The dissertation concludes with a discussion of the FSRN’s model and the perceived value of a themed, transdisciplinary approach to service-learning. This study highlights promising practices for involving faculty in service-learning and, in keeping with an Appreciative Inquiry approach, depicts a view of faculty work at its best.

Conception et développement d’un environnement d’apprentissage sur les transformations d’énergies et leurs rendements

Le domaine des énergies est au cœur des préoccupations technologiques, politiques et économiques de notre société moderne. Ce domaine nécessite une compréhension minimale du concept scientifique de l’énergie. Elle est selon nous essentielle à toute formation citoyenne. Nous avons dans un premier temps, à partir de considérations théoriques et pratiques, examiné pourquoi ce domaine si important dans notre société technologique est si peu abordé dans le cursus scolaire québécois? Pourquoi se contente-t-on d’un enseignement théorique et discursif de ce concept? Pourquoi, au contraire de tout enseignement scientifique, n’a-t-on pas envisagé de situations d’apprentissages en laboratoire pour l’étude des énergies? Dans un deuxième temps, nous avons proposé une idée de solution concrète et réaliste pour répondre à l’ensemble de ces questions. Une solution qui invite les élèves à s’investir de manière constructive dans des activités de laboratoire afin de s’approprier ces concepts. Pour ce faire, nous avons conçu des variables globales énergies qui ont permis aux élèves de les mesurer et d’expérimenter facilement des transformations énergétiques. Cette recherche de développement technologique en éducation consiste donc à profiter des nouveaux développements technologiques de l’informatique et de la micro-électronique pour concevoir, réaliser et mettre à l’essai un environnement informatisé d’apprentissage en laboratoire pour les sciences et la technologie. Par ce que l’énergie est au confluent de trois domaines, cet environnement a été conçu pour supporter dans une même activité l’apprentissage des mathématiques, des sciences et de la technologie. Cette intégration recommandée par les nouveaux programmes est, selon nous, essentielle à la compréhension des concepts liés à l’énergie et à ses transformations. Par cette activité d’apprentissage multidisciplinaire, nous voulons, via une approche empirique et concrète, aborder ces problèmes de transformations énergétiques afin de donner aux élèves la capacité de perfectionner les prototypes qu’ils construisent en technologie de manière à améliorer leurs performances. Nous avons montré que cette démarche technoscientifique, assimilable à la conception d’un schème expérimental en sciences, favorise la compréhension des concepts liés aux énergies et à leurs transformations. Ce développement, ouvert à l’investigation scientifique, apporte un bénéfice didactique, non seulement, pour des enseignants en exercices et des étudiants-maîtres, mais aussi pour des élèves de 5ème année du niveau secondaire, ce que nous avons démontré dans une mise à l’essai empirique.

Aula de música : desarrollo de contenidos en una herramienta de e-learning para la asignatura de música en Educación Primaria.

Aula de música es una herramienta e-learning para el desarrollo del aprendizaje de la música para niños con edades comprendidas entre los 6 y 12 años, edades correspondientes a las de los alumnos de la etapa de la Educación Primaria. En esta herramienta destaca el uso de estándares y especificaciones como LOM, IMS, etc. que van a facilitar la tarea de reutilizar la documentación incluida para compartir conocimiento. El proceso de elaboración del contenido ha sido fundamental y en relación con el entorno de trabajo debe mencionarse que se ha primado la construcción de una GUI que sirva para aprender y que motive a los alumnos a aprender música de una forma diferente, en contraposición a realizar una diseño estético que fuera incapaz de adaptarse a las capacidades de cada tipo de usuario, para lo que se han tenido en cuenta criterios de usabilidad y accesibilidad (WAI).

Factores para la implementación eficiente de un sistema de control de gestión en las organizaciones

La implementación del MCS es una necesidad que demandan las organizaciones en la medida en que incrementan de tamaño, pero la experiencia muestra que esta metodología tiene casos de éxito como de fracaso, por lo que es importante identificar y contemplar los factores que influyen en la implementación para que el sistema sea efectivo. Este proyecto pretende analizar las variables y herramientas para la implementación de un MCS en una organización. Para este análisis se hizo una amplia revisión literaria teórica y práctica. Finalmente el resultado que se obtuvo fue definir cuáles son los factores determinantes para la implementación de un MCS efectivo en una empresa.