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×$6\times$ 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.     

Generalized Bayesian inference in a fuzzy context: From theory to a virtual reality application

A generalized Bayesian inference framework in order to embed fuzzy sets and partial probabilistic information is provided. The general framework of reference is that of coherent conditional probabilities, which allows giving a rigorous interpretation of membership function as a conditional probability, regarded as a function of the conditioning event. The inferential problem needs to be studied in situations where the prior can be partial; moreover, membership and prior can be given on different classes of events. This inferential model is applied for the virtual representation of a female avatar.     

A platform for the development of patient applications in the domain of personalized health

Personalized health (p-health) systems can contribute significantly to the sustainability of healthcare systems, though their feasibility is yet to be proven. One of the problems related to their development is the lack of well-established development tools for this domain. As the p-health paradigm is focused on patient self-management, big challenges arise around the design and implementation of patient systems. This paper presents a reference platform created for the development of these applications, and shows the advantages of its adoption in a complex project dealing with cardio-vascular diseases.     

A consensus model for group decision making problems with linguistic interval fuzzy preference relations

Sometimes, we find decision situations in which it is difficult to express some preferences by means of concrete preference degrees. In this paper, we present a consensus model for group decision making problems in which the experts use linguistic interval fuzzy preference relations to represent their preferences. This model is based on two consensus criteria, a consensus measure and a proximity measure, and on the concept of coincidence among preferences. We compute both consensus criteria in the three representation levels of a preference relation and design an automatic feedback mechanism to guide experts in the consensus reaching process.     

Synthesis of MCM-41 frameworks incorporating oxygen-sulphur derivates of molybdenum and tungsten

The first examples of mesostructured materials containing Mo- and W-oxo-sulphur species incorporated into a poorly ordered MCM-41 framework have been prepared under hydrothermal condition and alkaline medium. The incorporation of oxygen-sulphur derivates of molybdenum and tungsten not only increases significantly the pore diameter, but also improves the thermal stability of the MCM-41-related mesoporous material.     

A Monadic Semantics for Core Curry

We give a deterministic, big-step operational semantics for the essential core of the Curry language, including higher-order functions, call-by-need evaluation, non-determinism, narrowing, and residuation. The semantics is structured in modular monadic style, and is presented in the form of an executable interpreter written in Haskell. It uses monadic formulations of state, non-determinism, and resumption-based concurrency.     

Neurotrophic control of ovarian development

Substantial evidence now exists indicating that the neurotrophins, a family of growth factors required for the survival, development, and differentiation of various neuronal populations of the nervous system, are also important for the development of nonneuronal tissues. Such a function was first suggested by studies showing the presence of high-affinity neurotrophin receptors in a variety of nonneuronal tissues including those of the cardiovascular, endocrine, immune, and reproductive systems. Within the latter, the gonads appear to be a preferential site of neurotrophin action as suggested by the presence in the mammalian ovary of at least four of the five known neurotrophins and all of the neurotrophin receptors thus far identified. While the various functions that the neurotrophins may have in the ovary are still being elucidated, it is now clear that in addition to recruiting the ovarian innervation, they play a direct role in the regulation of two different maturational periods that are critical for the acquisition of female reproductive function: early follicular development and ovulation. Neurotrophins facilitate the development of newly formed follicles by promoting the initial differentiation and the subsequent growth of primordial follicles. These actions appear to be related to the ability of neurotrophins to sustain the proliferation of both mesenchymal and granulosa cells, and to induce the synthesis of follicle stimulating hormone (FSH) receptors. At the time of the first ovulation, neurotrophins contribute to the ovulatory cascade by increasing prostaglandin E(2) release, reducing gap junction communication, and inducing cell proliferation within the thecal compartment of preovulatory follicles.     

A parallel micro evolutionary algorithm for heterogeneous computing and grid scheduling

This work presents a novel parallel micro evolutionary algorithm for scheduling tasks in distributed heterogeneous computing and grid environments. The scheduling problem in heterogeneous environments is NP-hard, so a significant effort has been made in order to develop an efficient method to provide good schedules in reduced execution times. The parallel micro evolutionary algorithm is implemented using MALLBA, a general-purpose library for combinatorial optimization. Efficient numerical results are reported in the experimental analysis performed on both well-known problem instances and large instances that model medium-sized grid environments. The comparative study of traditional methods and evolutionary algorithms shows that the parallel micro evolutionary algorithm achieves a high problem solving efficacy, outperforming previous results already reported in the related literature, and also showing a good scalability behavior when facing high dimension problem instances.     

A straightforward design technique for narrowband multi‐stage low‐noise amplifiers with I/O conjugate match

Low‐noise amplifier (LNA) designers often struggle to simultaneously satisfy gain, noise, stability, and I/O matching requirements. In this article, a novel design technique, tailored for two‐stage low‐noise amplifiers, is presented. The proposed design method is completely deterministic and exploits inductive source degeneration to obtain a two‐stage LNA featuring perfect input and output match together with low noise figure (NF) and a pre‐determined gain, including stability analysis. A novel flowchart is provided together with the corresponding design chart that contains gain, matching, and stability information, therefore addressing all key figures‐of‐merit of a linear amplifier. The design chart is easily implementable in commercial Electronic Design Automation software, to aid designers in the difficult task of selecting the appropriate source degeneration inductor value. The noise performance, on the other hand, is the best possible since the matching networks are designed to provide the input of the two Field Effect Transistors with the optimum termination for noise. The design method is validated with two separate test vehicles operating respectively at Ka‐band (26.5‐31.5 GHz) and K‐band (20.0‐24.0 GHz). The realized Monolithic Microwave Integrated Circuits exhibit 18 dB gain for both versions, NF of 1.5 and 1.2 dB, respectively for the Ka‐band and K‐band version. Input and output matching are typically better than 12 and 15 dB.