Current-mode analogue defuzzifier

A CMOS current-mode approach for implementing the defuzzification function in analogue fuzzy controllers is proposed. The circuit computes the centre of area of the output fuzzy conclusion using switched current adders and a current divider. Simulation results of the defuzzifier show how the circuit can produce a good approximation of the centre of area even if a small number of levels are used to quantise the output variable.<>     

Allergic rhinitis and asthma as probable clinical manifestations of the same process

Acetylsalicylic acid (ASA) alone (at least 30 mg per day) in post-cerebral ischaemia patients reduces the relative risk of further vascular events by 13% compared with placebo. A meta-analysis of all studies shows that the combination of ASA with dipyridamole reduces the relative risk by 16% (95% confidence interval: 5-26%) compared with ASA alone, but confirmation by a major trial appears desirable, because of discrepant results of a recent trial and 4 previous ones. Clopidogrel might reduce the risk by 7% compared with ASA alone, but this drug is expected to be expensive. Anticoagulation therapy with an international normalized ratio (INR) of 2.0-4.0 is particularly efficacious for secondary prevention in patients with atrial fibrillation, but anticoagulation therapy with an INR of 3.0-4.5 is not safe in secondary prevention of cerebral ischaemia of presumed arterial origin. Finally, not all atherosclerotic vascular diseases are identical from the therapeutic point of view; the effect of treatment depends in part on the clinical manifestation form.     

Image segmentation towards new image representation methods

Very low bit-rate video coding has recently become one of the most important areas of image communication and a large variety of applications have already been identified. Since conventional approaches are reaching a saturation point, in terms of coding efficiency, a new generation of video coding techniques, aiming at a deeper “understanding” of the image, is being studied. In this context, image analysis, particularly the identification of objects or regions in images (segmentation), is a very important step. This paper describes a segmentation algorithm based on split and merge. Images are first simplified using mathematical morphology operators, which eliminate perceptually less relevant details. The simplified image is then split according to a quad tree structure and the resulting regions are finally merged in three steps: merge, elimination of small regions and control of the number of regions.     

Structure of nylon 7 solution grown crystals

Single crystals of nylon 7 prepared by crystallization from glycerine were studied by both X-rays and electron microscopy. Electron diffraction proved that they consist of a twinned layered-structure with hydrogen bonds running parallel to their long dimension. Polyethylene decoration of such crystals showed that they are subdivided in folding domains so that both chain folding and hydrogen bonding take place along the same crystallographical planes.     

Facilitating the learning process in parallel computing by using instant messaging

Parallel Programming skills may require a long time to acquire. “Think in parallel” is a skill that requires time, effort, and experience. In this work, we propose to facilitate the students’ learning process in parallel programming by using instant messaging. Our aim was to find out whether students’ interaction through instant messaging tools is beneficial for the learning process. In order to do so, we asked several students of an HPC course of the Master’s degree in Computer Science of the University of León to develop a specific parallel application, each of them using a different application program interface: OpenMP, MPI, CUDA, or OpenCL. Even though the used APIs are different, there are common points in the design process. We encouraged students to interact with each other by using Gitter, an instant messaging tool for GitHub users. Our analysis of the communications and results demonstrate that the direct interaction of students through the Gitter tool has a positive impact on the learning process.

     

A panoramic view and swot analysis of artificial intelligence for achieving the sustainable development goals by 2030: progress and prospects

Applied Intelligence - The17 Sustainable Development Goals (SDGs) established by the United Nations Agenda 2030 constitute a global blueprint agenda and instrument for peace and prosperity...     

Hyperspectral imaging-based unsupervised adulterated red chili content transformation for classification: Identification of red chili adulterants

Neural Computing and Applications - Preserving red-chili quality is of utmost importance in which the authorities demand quality techniques to detect, classify, and prevent it from impurities. For...     

Face recognition with lattice independent component analysis and extreme learning machines

We focus on two aspects of the face recognition, feature extraction and classification. We propose a two component system, introducing Lattice Independent Component Analysis (LICA) for feature extraction and Extreme Learning Machines (ELM) for classification. In previous works we have proposed LICA for a variety of image processing tasks. The first step of LICA is to identify strong lattice independent components from the data. In the second step, the set of strong lattice independent vector are used for linear unmixing of the data, obtaining a vector of abundance coefficients. The resulting abundance values are used as features for classification, specifically for face recognition. Extreme Learning Machines are accurate and fast-learning innovative classification methods based on the random generation of the input-to-hidden-units weights followed by the resolution of the linear equations to obtain the hidden-to-output weights. The LICA-ELM system has been tested against state-of-the-art feature extraction methods and classifiers, outperforming them when performing cross-validation on four large unbalanced face databases.     

The GPU on the simulation of cellular computing models

Membrane Computing is a discipline aiming to abstract formal computing models, called membrane systems or P systems, from the structure and functioning of the living cells as well as from the cooperation of cells in tissues, organs, and other higher order structures. This framework provides polynomial time solutions to NP-complete problems by trading space for time, and whose efficient simulation poses challenges in three different aspects: an intrinsic massively parallelism of P systems, an exponential computational workspace, and a non-intensive floating point nature. In this paper, we analyze the simulation of a family of recognizer P systems with active membranes that solves the Satisfiability problem in linear time on different instances of Graphics Processing Units (GPUs). For an efficient handling of the exponential workspace created by the P systems computation, we enable different data policies to increase memory bandwidth and exploit data locality through tiling and dynamic queues. Parallelism inherent to the target P system is also managed to demonstrate that GPUs offer a valid alternative for high-performance computing at a considerably lower cost. Furthermore, scalability is demonstrated on the way to the largest problem size we were able to run, and considering the new hardware generation from Nvidia, Fermi, for a total speed-up exceeding four orders of magnitude when running our simulations on the Tesla S2050 server.     

Fuzzy ontologies-based user profiles applied to enhance e-learning activities

Nowadays, the impact of technological developments on improving human activities is becoming more evident. In e-learning, this situation is no different. There are common to use systems that assist the daily activities of students and teachers. Typically, e-learning recommender systems are focused on students; however, teachers can also benefit from these type of tools. A recommender system can propose actions and resources that facilitate teaching activities like structuring learning strategies. In any case, a complete user’s representation is required. This paper shows how a fuzzy ontology can be used to represent user profiles into a recommender engine and enhances the user’s activities into e-learning environments. A fuzzy ontology is an extension of domain ontologies for solving the problems of uncertainty in sharing and reusing knowledge on the Semantic Web. The user profile is built from learning objects published by the user himself into a learning object repository. The initial experiment confirms that the automatically obtained fuzzy ontology is a good representation of the user’s preferences. The experiment results also indicate that the presented approach is useful and warrants further research in recommending and retrieval information.