Learning digital test and diagnostics via Internet

An environment targeted to e-learning is presented for teaching design and test of electronic systems. The environment consists of a set of Java applets, and of web based access to the hardware equipments, which can be used in the classroom, for learning at home, in laboratory research and training, or for carrying out testing of students during exams. The tools support university courses on digital electronics, computer hardware, testing and design for testability to learn by hands-on exercises how to design digital systems, how to make them testable, how to build self-testing systems, how to generate test patterns, how to analyze the quality of tests, and how to localize faults in hardware. The tasks chosen for hands-on training represent simultaneously research problems, which allow to fostering in students critical thinking, problem solving skills and creativity

The future of laboratory medicine - A 2014 perspective.

Predicting the future is a difficult task. Not surprisingly, there are many examples and assumptions that have proved to be wrong. This review surveys the many predictions, beginning in 1887, about the future of laboratory medicine and its sub-specialties such as clinical chemistry and molecular pathology. It provides a commentary on the accuracy of the predictions and offers opinions on emerging technologies, economic factors and social developments that may play a role in shaping the future of laboratory medicine

Case studies of personalized learning

Deliverable 4.1, Literature review of personalised learning and the Cloud, started with an evaluation and synthesis of the definitions of personalized learning, followed by an analysis of how this is implemented in a method (e-learning vs. i-learning, m-learning and u-learning), learning approach and the appropriate didactic process, based on adapted didactic theories. From this research a list of criteria was created needed to implement personalised learning onto the learner of the future. This list of criteria is the basis for the analysis of all case studies investigated. – as well to the learning process as the learning place. In total 60 case studies (all 59 case studies mentioned in D6.4 Education on the Cloud 2015 + one extra) were analysed. The case studies were compared with the list of criteria, and a score was calculated. As a result, the best examples could be retained. On average most case studies were good on: taking different learning methods into account, interactivity and accessibility and usability of learning materials for everyone. All had a real formal education content, thus aiming at the core-curriculum, valuing previous knowledge, competences, life and work skills, also informal. Also the availability of an instructor / tutor or other network of peers, experts and teachers to guide and support the learning is common. On the other hand, most case studies lack diagnostics tests as well at the start (diagnostic entry test), during the personalized learning trajectory and at the end (assessment at the end). Also most do not include non-formal and informal learning aspects. And the ownership of personalized learning is not in the hands of the learner. Five of the 60 case studies can as a result be considered as very good examples of real personalized learning

Immunochromatographic diagnostic test analysis using Google Glass.

We demonstrate a Google Glass-based rapid diagnostic test (RDT) reader platform capable of qualitative and quantitative measurements of various lateral flow immunochromatographic assays and similar biomedical diagnostics tests. Using a custom-written Glass application and without any external hardware attachments, one or more RDTs labeled with Quick Response (QR) code identifiers are simultaneously imaged using the built-in camera of the Google Glass that is based on a hands-free and voice-controlled interface and digitally transmitted to a server for digital processing. The acquired JPEG images are automatically processed to locate all the RDTs and, for each RDT, to produce a quantitative diagnostic result, which is returned to the Google Glass (i.e., the user) and also stored on a central server along with the RDT image, QR code, and other related information (e.g., demographic data). The same server also provides a dynamic spatiotemporal map and real-time statistics for uploaded RDT results accessible through Internet browsers. We tested this Google Glass-based diagnostic platform using qualitative (i.e., yes/no) human immunodeficiency virus (HIV) and quantitative prostate-specific antigen (PSA) tests. For the quantitative RDTs, we measured activated tests at various concentrations ranging from 0 to 200 ng/mL for free and total PSA. This wearable RDT reader platform running on Google Glass combines a hands-free sensing and image capture interface with powerful servers running our custom image processing codes, and it can be quite useful for real-time spatiotemporal tracking of various diseases and personal medical conditions, providing a valuable tool for epidemiology and mobile health

Drivers and Impacts of R&D Adoption on Transport and Logistics Services

Actually, technologies and applications in industries are changing via business restructuring, new business models, new knowledge and supply chains. So R&D is not focused primarily on manufacturing industry as it used to be, but on different kinds of industries as logistics and transport (TLS). Nevertheless, the characteristics of the TLS industry determine the introduction of specific R&D solutions accordingly to sectors operations. The objective of this paper is to describe the R&D opportunities in the TLS industry and how managers use them to make their businesses more innovative and efficient. Using the Structure-Conduct-Performance (SCP) model the paper identifies the links between R&D adoption and innovation dynamics. Relating the findings, on the driver’s side there are three points that are worth mentioning: increasing market competition, the relationships of firms interacting with each other and the availability and quality of complementary assets such as employee skills and IT know-how. On the impacts’ side, firms advanced in terms of implementing R&D solutions are more likely to implement organizational changes. Finally, a set of recommendations on how to further improve the continuous innovation in the TLS industry is presented

An evaluation of the economic impact of broadband in Lincolnshire: updated final report

The Lincolnshire Broadband Initiative, ‘onlincolnshire’, was launched in 2003 to bring a range of broadband supply and demand stimulation activities to businesses across the county. The initiative has used £15 million of European funding, together with matched funding from Lincolnshire County Council, to support a series of significant Information and Communication Technology (ICT) interventions to provide support and financial assistance to eligible Lincolnshire businesses. The ‘onlincolnshire’ initiative has four long term strategic objectives. By 2010: • Lincolnshire will be the foremost rural County in the UK, with regards to ICT usage and skills and will have a commercial environment that embraces ICT; • The main employment sites and premises will have attracted increased and more diverse investment; • ICT will have made a major contribution to business competitiveness, expansion and diversification of the economy – measured through an increase in ICT related employment and a range of ICT based activities; • To have engaged individuals and employers in improving ICT skills to increase local competitiveness, raise the standards, participation and achievement in ICT throughout the County

Analyzing E-Learning Adoption via Recursive Partitioning

The paper analyzes factors that influence the adoption of e-learning and gives an example of how to forecast technology adoption based on a post-hoc predictive segmentation using a classification and regression tree (CART). We find strong evidence for the existence of technological interdependencies and organizational learning effects. Furthermore, we find different paths to elearning adoption. The results of the analysis suggest a growing "digital divide" among firms. We use cross-sectional data from a European survey about e-business in June 2002, covering almost 6,000 enterprises in 15 industry sectors and 4 countries. Comparing the predictive quality of CART, we find that CART outperforms a traditional logistic regression. The results are more parsimonious, i. e. CARTs use less explanatory variables, better interpretable since different paths of adoption are detected, and from a statistical standpoint, because interactions between the covariates are taken into account.Technology Adoption, Path Dependence, Interaction between Different Technologies, Regression Trees, Predictive Segmentation, Logistic Regression, E-Learning, E-Business