Characterization of polylactic acid films for food packaging as affected by dielectric barrier discharge atmospheric plasma

Dielectric barrier discharge (DBD) air plasma is a novel technique for in-package decontamination of food, but it has not been yet applied to the packaging material. Characterization of commercial polylactic acid (PLA) films was done after in-package DBD plasma treatment at different voltages and treatment times to evaluate its suitability as food packaging material. DBD plasma increased the roughness of PLA film mainly at the site in contact with high voltage electrode at both the voltage levels of 70 and 80 kV. DBD plasma treatments did not induce any change in the glass transition temperature, but significant increase in the initial degradation temperature and maximum degradation temperature was observed. DBD plasma treatment did not adversely affect the oxygen and water vapor permeability of PLA. A very limited overall migration was observed in different food simulants and was much below the regulatory limits. Industrial relevance: In-package DBD plasma is a novel and innovative approach for the decontamination of foods with potential industrial application. This paper assesses the suitability of PLA as food packaging material for cold plasma treatment. It characterizes the effect of DBD plasma on the packaging material when used for in-package decontamination of food. The work described in this research offers a promising alternative to classical methods used in fruit and vegetable industries where in-package DBD plasma can serve as an effective decontamination process and avoids any post-process recontamination or hazards from the package itself.

An approach to the application of shift-and-add algorithms on engineering and industrial processes

Different kinds of algorithms can be chosen so as to compute elementary functions. Among all of them, it is worthwhile mentioning the shift-and-add algorithms due to the fact that they have been specifically designed to be very simple and to save computer resources. In fact, almost the only operations usually involved with these methods are additions and shifts, which can be easily and efficiently performed by a digital processor. Shift-and-add algorithms allow fairly good precision with low cost iterations. The most famous algorithm belonging to this type is CORDIC. CORDIC has the capability of approximating a wide variety of functions with only the help of a slight change in their iterations. In this paper, we will analyze the requirements of some engineering and industrial problems in terms of type of operands and functions to approximate. Then, we will propose the application of shift-and-add algorithms based on CORDIC to these problems. We will make a comparison between the different methods applied in terms of the precision of the results and the number of iterations required.

Robotic control systems based on bioinspired multi-agent systems: application of the principles of neuroscience to robotics

Robotics is a field that presents a large number of problems because it depends on a large number of disciplines, devices, technologies and tasks. Its expansion from perfectly controlled industrial environments toward open and dynamic environment presents a many new challenges, such as robots household robots or professional robots. To facilitate the rapid development of robotic systems, low cost, reusability of code, its medium and long term maintainability and robustness are required novel approaches to provide generic models and software systems who develop paradigms capable of solving these problems. For this purpose, in this paper we propose a model based on multi-agent systems inspired by the human nervous system able to transfer the control characteristics of the biological system and able to take advantage of the best properties of distributed software systems.

GPGPU implementation of growing neural gas: application to 3D scene reconstruction

Self-organising neural models have the ability to provide a good representation of the input space. In particular the Growing Neural Gas (GNG) is a suitable model because of its flexibility, rapid adaptation and excellent quality of representation. However, this type of learning is time-consuming, especially for high-dimensional input data. Since real applications often work under time constraints, it is necessary to adapt the learning process in order to complete it in a predefined time. This paper proposes a Graphics Processing Unit (GPU) parallel implementation of the GNG with Compute Unified Device Architecture (CUDA). In contrast to existing algorithms, the proposed GPU implementation allows the acceleration of the learning process keeping a good quality of representation. Comparative experiments using iterative, parallel and hybrid implementations are carried out to demonstrate the effectiveness of CUDA implementation. The results show that GNG learning with the proposed implementation achieves a speed-up of 6× compared with the single-threaded CPU implementation. GPU implementation has also been applied to a real application with time constraints: acceleration of 3D scene reconstruction for egomotion, in order to validate the proposal.

Adiestrando a la juventud obrera: la política de formación técnica-industrial de la dictadura primorriverista

El objetivo de este trabajo es analizar cómo la dictadura de Primo de Rivera llevó a cabo la reforma de la enseñanza industrial del joven obrero a través del Estatuto de Enseñanza Industrial de 1924 y del Estatuto de Formación Profesional de 1928, dentro de la órbita ideológica del “modernismo reaccionario”. La dictadura primorriverista se encontraba en una época influida por las consecuencias de la Gran Guerra y empezaba a percibir la formación profesional técnica-industrial como un mecanismo de adoctrinamiento de la juventud obrera, a partir del cual se podía construir una identidad nacional y profesional, a la vez que modernizar la industria nacional. Por ello, la dictadura de Primo de Rivera decidió centralizar todos los canales de formación industrial del joven obrero a través de un nuevo plan de estudios técnico e industrial dentro de las escuelas industriales y de trabajo. Así intentaba controlar al movimiento obrero, formar una clase media de técnicos industriales, satisfacer las necesidades económicas del país, al mismo tiempo que mantener la jerarquización socio-política tradicional. Pero la aplicación de este proyecto educativo durante la Segunda República no cumplió con las expectativas ideológicas y políticas de la dictadura de Primo de Rivera.

3D-based reconstruction using growing neural gas landmark: application to rapid prototyping in shoe last manufacturing

Customizing shoe manufacturing is one of the great challenges in the footwear industry. It is a production model change where design adopts not only the main role, but also the main bottleneck. It is therefore necessary to accelerate this process by improving the accuracy of current methods. Rapid prototyping techniques are based on the reuse of manufactured footwear lasts so that they can be modified with CAD systems leading rapidly to new shoe models. In this work, we present a shoe last fast reconstruction method that fits current design and manufacturing processes. The method is based on the scanning of shoe last obtaining sections and establishing a fixed number of landmarks onto those sections to reconstruct the shoe last 3D surface. Automated landmark extraction is accomplished through the use of the self-organizing network, the growing neural gas (GNG), which is able to topographically map the low dimensionality of the network to the high dimensionality of the contour manifold without requiring a priori knowledge of the input space structure. Moreover, our GNG landmark method is tolerant to noise and eliminates outliers. Our method accelerates up to 12 times the surface reconstruction and filtering processes used by the current shoe last design software. The proposed method offers higher accuracy compared with methods with similar efficiency as voxel grid.