Studi epidemiologici osservazionali europei: le coorti dalla nascita

Objective: in recent years there has been a growing interest in birth cohorts. The aim of this review is to know and understand the state of the art of European cohorts to date, with a focus on those that started data collection at birth. In particular, the aim is to provide an overview of current research topics and designs, and provide input for those creating collaborations and laying out guidelines aimed at unifying cohort methodologies to enable data merging and maximize knowledge acquisition. Methods: we searched PubMed and Embase for articles referring to longitudinal, prospective European birth cohorts, and searched online cohort inventories. Results: we found references to 111 birth cohorts, 45 of which began enrolment at birth. These cohorts began between 1921 and 2015 and represented 19 countries, with varying sample sizes (236 to 21,000 children). As of 5 January 2020, 5 were still recruiting. The main areas addressed were allergic diseases (14 cohorts) and environmental exposure (12 cohorts) and most cohorts were publicly funded. Conclusion: given the large costs of running cohorts and the importance of long follow-up periods in identifying the risk factors for disorders thought to have a perinatal/early life etiology, current cohorts must be designed to answer research questions considering several aspects, from genetic ones to psychological, social, and environmental ones. Furthermore, universally recognized methodological aspects are needed to permit the comparison and merging of cohort data.

Decision Support Approach for Assessing of Rail Transport

As part of the certification process for a new rail transport system, one of the essential steps is to examine, from a safety point of view, that the system (and its technical and human environment) satisfies the regulatory requirements of safety and in particular that it can in no case be a source of risk for travelers. This intellectual process by which a certification expert assesses a situation, predicts an event, or makes a decision is often difficult to model in the form of reliable and definitive algorithms. This difficulty can be partially overcome by using artificial intelligence (AI) techniques. In order to improve the usual approaches to analysis and evaluation of safety studies used in the context of certification, this chapter presents several methods and tools based on AI techniques and in particular on knowledge acquisition methods, supervised machine learning (SML), case-based reasoning (CBR), and knowledge-based systems (KBS).

Developing Undergraduate Students’ Teaching Competences

Introduction:The goal of this paper is to show how the undergraduate students are able to differentiate among learning-centered, learner-centered, feedback-centered and community-centered knowledge acquisitions. We wanted them to recognize which method is used by the teacher and how each method influences the primary school pupils’ knowledge acquisition.Methods:We chose the video analyzing technique to make the students recognize different learning organizational methods.Results:The results of the study suggest that the observation helped the undergraduate students understand the aims, tasks and techniques of teaching and organizing classroom work. They realized that this type of analysis helps them develop their own teaching strategies.Discussion:Drawing on the results it is not possible to be a “good teacher” without obtaining and continuously maintaining a high level of professional knowledge, whose important element might be the Complex Instruction method and the recognition of the knowledge acquisition methods in the classroom.Limitations:This study was limited to only undergraduate students who attended the study voluntarily. The sampling was confined to 46 participants.Conclusion:The students are able to spot the teacher’s activities that support pupils’ learning. They recognized the positive impact of generating debate among the pupils on the development of their skills.

Entwicklung eines selbstlernenden Assistenzsystems zur automatischen Akquisition von konstruktionsrelevantem Fertigungswissen

Companies within different industries have to face several key challenges, among whichthe demand for shortening the time-to-market whilst decreasing costs and the strong indiviuality and dynamic of globalized markets are highlighted. In order to overcome those challenges companies not only have to optimize their products but also the underlying product development and manufacturing processes. The objective from engineering design point of view is the exchange of design-relevant manufacturing knowlegde between both disciplines as early as possible. Especially for newly emerging manufacturing technologies common knowledge acquisition methods to assist such knowledge exchange processes fail. This thesis proposes an approach for a self-learning engineering assistance system (referred to as Slassy) for the automatic acquisition of design-relevant manufacturing knowledge. Such knowledge is represented in terms of so-called metamodels. In the context of this thesis a metamodel is cap...

Sources of knowledge used by Spanish coaches: A study according to competition level, gender and professional experience

This research analyzed sources of knowledge used by Spanish coaches according to competition level, gender, and professional experience. It provides valuable insight regarding the influence of demographic factors on the knowledge acquisition of coaches in a sub-group of the population (Spanish coaches) for which little is known. Participants were 675 coaches of different team and individual sports. Data were collected through the use of a standardized validated questionnaire. Results indicated that coaches in Spain subscribe to informal knowledge acquisition methods more than formal and non-formal ones. The sources of knowledge most used were an exchange of knowledge with other professionals, observation of other coaches, and previous athletic experience. The sources of knowledge least used were reading books or magazines, and conducting research. Additionally, it was found that coach demographics were associated with differences in the priority given to specific sources of knowledge. Consequently, commonly utilized formal knowledge translation approaches may need to be reconsidered.

Comparison of Knowledge Acquisition Methods for Dynamic Scheduling of Wafer Test Processes with Unpredictable Testing Errors

The scheduling of semiconductor wafer testing processes may be seen as a resource constraint project scheduling problem (RCPSP), but it includes uncertainties caused by wafer error, human factors, etc. Because uncertainties are not simply quantitative, estimating the range of the parameters is not useful. Considering such uncertainties, finding a good situationdependent dispatching rule is more suitable than solving an RCPSP under uncertainties. In this paper we apply machine learning approaches to acquiring situation-dependent dispatching rule. We compare obtained rules and examine their effectiveness and usefulness in problems with unpredictable wafer testing errors.

New Method of Knowledge Acquisition of Aid Decision-Making for Missile-Launching

Acquiring causal knowledge of abnormity is essential to Missile-Launching reliably. There are lots of Knowledge Acquisition methods. But it is absence for usage and maintenance support process. So it is necessary to start the research on new knowledge acquisition technology of aid Decision-Making for Missile-Launching. Based on the Usage and Maintenance-Support Process, this thesis acquires knowledge with the ESD and CESD (Converse Event Sequence Diagram) method. First, this thesis gives the concept of CESD. Then, in order to adapt the CESD model of the complex systems more effectively, this paper expands the CESD framework and provides a software frame of computer aided ESD study. Finally, the operation of pulse power supply system is analyzed on the basis of the improved ESD and CESD. This sample shows the applicability of ESD and CESD methodology in knowledge acquisition technology of aid Decision-Making for Missile-Launching.

Model of the Enterprise Value Management System

This paper is to explore how to apply the research achievement to the development of the real estate knowledge management system. It will give the design principle and the frame of the real estate knowledge management prototype system based on the knowledge acquisition methods based agent cooperation search model and genetic algorithm based knowledge discovery method, and the design plans of its major modules. The prototype system's objective is to verify the feasibility of the design plan of the real estate knowledge management system to develop in the future.