9 resultados para 671200 Computer Hardware and Electronic Equipment
em Universidad de Alicante
Resumo:
Paper submitted to the 7th International Symposium on Feedstock Recycling of Polymeric Materials (7th ISFR 2013), New Delhi, India, 23-26 October 2013.
Resumo:
Computer science studies possess a strong multidisciplinary aptitude since most graduates do their professional work outside of a computing environment, in close collaboration with professionals from many different areas. However, the training offered in computer science studies lacks that multidisciplinary factor, focusing more on purely technical aspects. In this paper we present a novel experience where computer studies and educational psychology find a common ground and realistic working through laboratory practices. Specifically, the work enables students of computer science education the development of diagnosis support systems, with artificial intelligence techniques, which could then be used for future educational psychologists. The applications developed by computer science students are the creation of a model for the diagnosis of pervasive developmental disorders (PDD), sometimes also commonly called the autism spectrum disorders (ASD). The complexity of this diagnosis, not only by the exclusive characteristics of every person who suffers from it, but also by the large numbers of variables involved in it, requires very strong and close interdisciplinary participation. This work demonstrates that it is possible to intervene in a curricular perspective, in the university, to promote the development of interpersonal skills. What can be shown, in this way, is a methodology for interdisciplinary practices design and a guide for monitoring and evaluation. The results are very encouraging since we obtained significant differences in academic achievement between students who attended a course using the new methodology and those who did not use it.
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The constant increase in the production of electronic devices implies the need for an appropriate management of a growing number of waste electrical and electronic equipment. Thermal treatments represent an interesting alternative to recycle this kind of waste, but particular attention has to be paid to the potential emissions of toxic by-products. In this study, the emissions from thermal degradation of printed circuit boards (with and without metals) have been studied using a laboratory scale reactor, under oxidizing and inert atmosphere at 600 and 850 °C. Apart from carbon oxides, HBr was the main decomposition product, followed by high amounts of methane, ethylene, propylene, phenol and benzene. The maximum formation of PAHs was found in pyrolysis at 850 °C, naphthalene being the most abundant. High levels of 2-, 4-, 2,4-, 2,6- and 2,4,6-bromophenols were found, especially at 600 °C. Emissions of PCDD/Fs and dioxin-like PCBs were quite low and much lower than that of PBDD/Fs, due to the higher bromine content of the samples. Combustion at 600 °C was the run with the highest PBDD/F formation: the total content of eleven 2,3,7,8-substituted congeners (tetra- through heptaBDD/Fs) was 7240 and 3250 ng WHO2005-TEQ/kg sample, corresponding to the sample with and without metals, respectively.
Resumo:
The permanent expansion of the market of electrical and electronic equipment (EEE) and the shorter innovation cycles, lead to a faster replacement of these appliances, making EEE a fast-growing source of waste (WEEE). As stated in Directive 2012/19/EU1 on waste electrical and electronic equipment, the content of hazardous components in EEE is a major concern during the waste management phase, and recycling of WEEE is not currently undertaken to a sufficient extent, resulting in a loss of valuable resources.
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Resumen del póster presentado en Symposium on Renewable Energy and Products from Biomass and Waste, CIUDEN (Cubillos de Sil, León, Spain), 12-13 May 2015
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The robotics is one of the most active areas. We also need to join a large number of disciplines to create robots. With these premises, one problem is the management of information from multiple heterogeneous sources. Each component, hardware or software, produces data with different nature: temporal frequencies, processing needs, size, type, etc. Nowadays, technologies and software engineering paradigms such as service-oriented architectures are applied to solve this problem in other areas. This paper proposes the use of these technologies to implement a robotic control system based on services. This type of system will allow integration and collaborative work of different elements that make up a robotic system.
Resumo:
Objectives: To design and validate a questionnaire to measure visual symptoms related to exposure to computers in the workplace. Study Design and Setting: Our computer vision syndrome questionnaire (CVS-Q) was based on a literature review and validated through discussion with experts and performance of a pretest, pilot test, and retest. Content validity was evaluated by occupational health, optometry, and ophthalmology experts. Rasch analysis was used in the psychometric evaluation of the questionnaire. Criterion validity was determined by calculating the sensitivity and specificity, receiver operator characteristic curve, and cutoff point. Testeretest repeatability was tested using the intraclass correlation coefficient (ICC) and concordance by Cohen’s kappa (k). Results: The CVS-Q was developed with wide consensus among experts and was well accepted by the target group. It assesses the frequency and intensity of 16 symptoms using a single rating scale (symptom severity) that fits the Rasch rating scale model well. The questionnaire has sensitivity and specificity over 70% and achieved good testeretest repeatability both for the scores obtained [ICC 5 0.802; 95% confidence interval (CI): 0.673, 0.884] and CVS classification (k 5 0.612; 95% CI: 0.384, 0.839). Conclusion: The CVS-Q has acceptable psychometric properties, making it a valid and reliable tool to control the visual health of computer workers, and can potentially be used in clinical trials and outcome research.
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The evidence suggests that emotional intelligence and personality traits are important qualities that workers need in order to successfully exercise a profession. This article assumes that the main purpose of universities is to promote employment by providing an education that facilitates the acquisition of abilities, skills, competencies and values. In this study, the emotional intelligence and personality profiles of two groups of Spanish students studying degrees in two different academic disciplines – computer engineering and teacher training – were analysed and compared. In addition, the skills forming part of the emotional intelligence and personality traits required by professionals (computer engineers and teachers) in their work were studied, and the profiles obtained for the students were compared with those identified by the professionals in each field. Results revealed significant differences between the profiles of the two groups of students, with the teacher training students scoring higher on interpersonal skills; differences were also found between professionals and students for most competencies, with professionals in both fields demanding more competencies that those evidenced by graduates. The implications of these results for the incorporation of generic social, emotional and personal competencies into the university curriculum are discussed.
Resumo:
Nowadays, new computers generation provides a high performance that enables to build computationally expensive computer vision applications applied to mobile robotics. Building a map of the environment is a common task of a robot and is an essential part to allow the robots to move through these environments. Traditionally, mobile robots used a combination of several sensors from different technologies. Lasers, sonars and contact sensors have been typically used in any mobile robotic architecture, however color cameras are an important sensor due to we want the robots to use the same information that humans to sense and move through the different environments. Color cameras are cheap and flexible but a lot of work need to be done to give robots enough visual understanding of the scenes. Computer vision algorithms are computational complex problems but nowadays robots have access to different and powerful architectures that can be used for mobile robotics purposes. The advent of low-cost RGB-D sensors like Microsoft Kinect which provide 3D colored point clouds at high frame rates made the computer vision even more relevant in the mobile robotics field. The combination of visual and 3D data allows the systems to use both computer vision and 3D processing and therefore to be aware of more details of the surrounding environment. The research described in this thesis was motivated by the need of scene mapping. Being aware of the surrounding environment is a key feature in many mobile robotics applications from simple robotic navigation to complex surveillance applications. In addition, the acquisition of a 3D model of the scenes is useful in many areas as video games scene modeling where well-known places are reconstructed and added to game systems or advertising where once you get the 3D model of one room the system can add furniture pieces using augmented reality techniques. In this thesis we perform an experimental study of the state-of-the-art registration methods to find which one fits better to our scene mapping purposes. Different methods are tested and analyzed on different scene distributions of visual and geometry appearance. In addition, this thesis proposes two methods for 3d data compression and representation of 3D maps. Our 3D representation proposal is based on the use of Growing Neural Gas (GNG) method. This Self-Organizing Maps (SOMs) has been successfully used for clustering, pattern recognition and topology representation of various kind of data. Until now, Self-Organizing Maps have been primarily computed offline and their application in 3D data has mainly focused on free noise models without considering time constraints. 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, specially 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 thesis proposes a hardware implementation leveraging the computing power of modern GPUs which takes advantage of a new paradigm coined as General-Purpose Computing on Graphics Processing Units (GPGPU). Our proposed geometrical 3D compression method seeks to reduce the 3D information using plane detection as basic structure to compress the data. This is due to our target environments are man-made and therefore there are a lot of points that belong to a plane surface. Our proposed method is able to get good compression results in those man-made scenarios. The detected and compressed planes can be also used in other applications as surface reconstruction or plane-based registration algorithms. Finally, we have also demonstrated the goodness of the GPU technologies getting a high performance implementation of a CAD/CAM common technique called Virtual Digitizing.