Market-oriented new product development of health promoting foods for the ageing population

Major factors influencing food development and food marketing strategies in global market places at present can be attributable to the changing age structure of the population. The significant shifts in global age structure will inevitably lead to the number of people aged 60 reaching an all-time high of one billion by the year 2020. The rapidly growing population of ageing people globally represents a large, neglected and very much under-developed category within the Food Industry. The primary focus of this study was the integration of knowledge creation techniques at early NPD stages, for the development of market-oriented new health promoting foods for the ageing population. The methodology of this study was centered on an exploratory sequential mixed methods strategy. Stage one of the study involved in-depth semi-structured interviews with 16 Stakeholders to facilitate the need identification stage of the NPD process. The main outputs identified were the need for: the fortification of foods for a preventative nutrition approach, the development of foods that targeted age-related conditions such as cognitive, heart, gut and bone health, the integration of ageing compensatory packaging adaptations and the creation of marketing messages with an active lifestyle message. Stage two consisted of a market-oriented computer assisted NPD technique, a user centered design interaction (UCD) to integrate consumers as co-creators throughout the idea generation stage of the NPD process. The most important product attributes identified in this stage included: products targeted at brain and cognitive health, liquid based beverages, easy to use packaging with environmentally friendly elements, simplistic marketing with a clear focus on health not age and realistic health claims constructed with consumer friendly terminology. Finally, Stage three used an abbreviated means-end chain (MEC) analysis to complete the concept development stage of the NPD process. This stage identified commercial information that could be used by food firms for the development of positioning and communication strategies. Equally, the information generated could be of high strategic importance to governments, policy makers, health professionals and medical professionals. The values and goals listed in this stage included: better overall health, active lifestyle, optimum nutrition and wellbeing feelings. Overall, this research illustrated that knowledge creation techniques can assist firms in the development of market-oriented health promoting foods for the ageing population.

Maude Object-Oriented Action Tool

MAIDL, André Murbach; CARVILHE, Claudio; MUSICANTE, Martin A. Maude Object-Oriented Action Tool. Electronic Notes in Theoretical Computer Science. [S.l:s.n], 2008.

Computational statistics, electronic publishing, and access to research data

Abstract not available

Maude Object-Oriented Action Tool

MAIDL, André Murbach; CARVILHE, Claudio; MUSICANTE, Martin A. Maude Object-Oriented Action Tool. Electronic Notes in Theoretical Computer Science. [S.l:s.n], 2008.

Evolution feature oriented model driven product line engineering approach for synergistic and dynamic service evolution in clouds: A04BPEL3.0 proposal.

Model Driven based approach for Service Evolution in Clouds will mainly focus on the reusable evolution patterns' advantage to solve evolution problems. During the process, evolution pattern will be driven by MDA models to pattern aspects. Weaving the aspects into service based process by using Aspect-Oriented extended BPEL engine at runtime will be the dynamic feature of the evolution.

Evolution of mylonitic microfabrics (EMM), a computer application for educational purposes

`Evolution of mylonitic microfabrics' (EMM) is an interactive Filemaker Pro 3.0 application that documents a series of see-through deformation experiments on polycrystalline norcamphor. The application comprises computer animations, graphics and text explanations designed to give students and researchers insight into the interaction and dynamic nature of small-scale, mylonitic processes like intracrystalline glide, dynamic recrystallization and strain localization (microshearing). EMM shows how mylonitic steady state is achieved at different strain rates and temperatures. First, rotational mechanisms like glide-induced vorticity, subgrain rotation recrystallization and rigid-body rotation bring grains' crystal lattices into orientations that are favorable for intracrystalline glide. In a second stage, selective elimination of grains whose lattices are poorly oriented for glide involves grain boundary migration. This strengthens the texture. Temperature and strain rate affect both the relative activity of different strain accommodation mechanisms and the rate of microfabric change. Steady-state microfabrics are characterized by stable texture, grain size and shape-preferred orientations of grains and domains. This involves the cyclical generation and elimination of dynamically recrystallized grains and microshear zones.

Support vector machines to detect physiological patterns for EEG and EMG-based human-computer interaction:a review

Support Vector Machines (SVMs) are widely used classifiers for detecting physiological patterns in Human-Computer Interaction (HCI). Their success is due to their versatility, robustness and large availability of free dedicated toolboxes. Frequently in the literature, insufficient details about the SVM implementation and/or parameters selection are reported, making it impossible to reproduce study analysis and results. In order to perform an optimized classification and report a proper description of the results, it is necessary to have a comprehensive critical overview of the application of SVM. The aim of this paper is to provide a review of the usage of SVM in the determination of brain and muscle patterns for HCI, by focusing on electroencephalography (EEG) and electromyography (EMG) techniques. In particular, an overview of the basic principles of SVM theory is outlined, together with a description of several relevant literature implementations. Furthermore, details concerning reviewed papers are listed in tables, and statistics of SVM use in the literature are presented. Suitability of SVM for HCI is discussed and critical comparisons with other classifiers are reported.

A service-oriented user interaction analysis framework supporting adaptive applications

A comprehensive user model, built by monitoring a user's current use of applications, can be an excellent starting point for building adaptive user-centred applications. The BaranC framework monitors all user interaction with a digital device (e.g. smartphone), and also collects all available context data (such as from sensors in the digital device itself, in a smart watch, or in smart appliances) in order to build a full model of user application behaviour. The model built from the collected data, called the UDI (User Digital Imprint), is further augmented by analysis services, for example, a service to produce activity profiles from smartphone sensor data. The enhanced UDI model can then be the basis for building an appropriate adaptive application that is user-centred as it is based on an individual user model. As BaranC supports continuous user monitoring, an application can be dynamically adaptive in real-time to the current context (e.g. time, location or activity). Furthermore, since BaranC is continuously augmenting the user model with more monitored data, over time the user model changes, and the adaptive application can adapt gradually over time to changing user behaviour patterns. BaranC has been implemented as a service-oriented framework where the collection of data for the UDI and all sharing of the UDI data are kept strictly under the user's control. In addition, being service-oriented allows (with the user's permission) its monitoring and analysis services to be easily used by 3rd parties in order to provide 3rd party adaptive assistant services. An example 3rd party service demonstrator, built on top of BaranC, proactively assists a user by dynamic predication, based on the current context, what apps and contacts the user is likely to need. BaranC introduces an innovative user-controlled unified service model of monitoring and use of personal digital activity data in order to provide adaptive user-centred applications. This aims to improve on the current situation where the diversity of adaptive applications results in a proliferation of applications monitoring and using personal data, resulting in a lack of clarity, a dispersal of data, and a diminution of user control.

Computer and laboratory simulation in the teaching of neonatal nursing: innovation and impact on learning

Objectives: to evaluate the cognitive learning of nursing students in neonatal clinical evaluation from a blended course with the use of computer and laboratory simulation; to compare the cognitive learning of students in a control and experimental group testing the laboratory simulation; and to assess the extracurricular blended course offered on the clinical assessment of preterm infants, according to the students. Method: a quasi-experimental study with 14 Portuguese students, containing pretest, midterm test and post-test. The technologies offered in the course were serious game e-Baby, instructional software of semiology and semiotechnique, and laboratory simulation. Data collection tools developed for this study were used for the course evaluation and characterization of the students. Nonparametric statistics were used: Mann-Whitney and Wilcoxon. Results: the use of validated digital technologies and laboratory simulation demonstrated a statistically significant difference (p = 0.001) in the learning of the participants. The course was evaluated as very satisfactory for them. The laboratory simulation alone did not represent a significant difference in the learning. Conclusions: the cognitive learning of participants increased significantly. The use of technology can be partly responsible for the course success, showing it to be an important teaching tool for innovation and motivation of learning in healthcare.

Interoperability Challenges in Internet of Things Systems: a Service-Oriented Computing Approach

Internet of Things systems are pervasive systems evolved from cyber-physical to large-scale systems. Due to the number of technologies involved, software development involves several integration challenges. Among them, the ones preventing proper integration are those related to the system heterogeneity, and thus addressing interoperability issues. From a software engineering perspective, developers mostly experience the lack of interoperability in the two phases of software development: programming and deployment. On the one hand, modern software tends to be distributed in several components, each adopting its most-appropriate technology stack, pushing programmers to code in a protocol- and data-agnostic way. On the other hand, each software component should run in the most appropriate execution environment and, as a result, system architects strive to automate the deployment in distributed infrastructures. This dissertation aims to improve the development process by introducing proper tools to handle certain aspects of the system heterogeneity. Our effort focuses on three of these aspects and, for each one of those, we propose a tool addressing the underlying challenge. The first tool aims to handle heterogeneity at the transport and application protocol level, the second to manage different data formats, while the third to obtain optimal deployment. To realize the tools, we adopted a linguistic approach, i.e.\ we provided specific linguistic abstractions that help developers to increase the expressive power of the programming language they use, writing better solutions in more straightforward ways. To validate the approach, we implemented use cases to show that the tools can be used in practice and that they help to achieve the expected level of interoperability. In conclusion, to move a step towards the realization of an integrated Internet of Things ecosystem, we target programmers and architects and propose them to use the presented tools to ease the software development process.

Data-driven and data-oriented methods for materials science and technologies

The discovery of new materials and their functions has always been a fundamental component of technological progress. Nowadays, the quest for new materials is stronger than ever: sustainability, medicine, robotics and electronics are all key assets which depend on the ability to create specifically tailored materials. However, designing materials with desired properties is a difficult task, and the complexity of the discipline makes it difficult to identify general criteria. While scientists developed a set of best practices (often based on experience and expertise), this is still a trial-and-error process. This becomes even more complex when dealing with advanced functional materials. Their properties depend on structural and morphological features, which in turn depend on fabrication procedures and environment, and subtle alterations leads to dramatically different results. Because of this, materials modeling and design is one of the most prolific research fields. Many techniques and instruments are continuously developed to enable new possibilities, both in the experimental and computational realms. Scientists strive to enforce cutting-edge technologies in order to make progress. However, the field is strongly affected by unorganized file management, proliferation of custom data formats and storage procedures, both in experimental and computational research. Results are difficult to find, interpret and re-use, and a huge amount of time is spent interpreting and re-organizing data. This also strongly limit the application of data-driven and machine learning techniques. This work introduces possible solutions to the problems described above. Specifically, it talks about developing features for specific classes of advanced materials and use them to train machine learning models and accelerate computational predictions for molecular compounds; developing method for organizing non homogeneous materials data; automate the process of using devices simulations to train machine learning models; dealing with scattered experimental data and use them to discover new patterns.

Utilização da discriminação grafica de Fisher para indicação dos dermatoglifos como referencial de potencialidade de atletas de basquetebol

Universidade Estadual de Campinas. Faculdade de Educação Física

Composição corporal e somatotipo em pessoas com síndrome de Down

Universidade Estadual de Campinas . Faculdade de Educação Física

O uso de softwares para estimulação da percepção do surdo frente aos parametros de velocidade do ritmo : proposta de utilização do Bpm Counter e do Vpm Counter no programa de atividade ritmicas adaptado as pessoas surdas

Universidade Estadual de Campinas . Faculdade de Educação Física

Educação fisica escolar : o lado oculto das ausencias as aulas

Universidade Estadual de Campinas. Faculdade de Educação Física