Biblioteca Aritmética de operaciones en Tiempo Real para Números en Coma Flotante

Lenguaje de alto nivel utilizado: JavaEl estándar IEEE754 es ampliamente utilizado en representación numérica de números reales y es actualmente seguida por los fabricantes en muchas de las implementaciones de CPU. Este estándar determina una serie de formatos para la representación de números en coma flotante, sus casos especiales y situaciones de error. Muchos lenguajes especifican que formatos y aritmética de la IEEE implementan, por ejemplo, en los lenguajes C/C++ y Java, el tipo float representa números en simple precisión y el tipo double representa números en doble precisión) y definen los operadores aritméticos básicos (suma, resta, producto y división) para operar con estos números. Sin embargo, estos lenguajes de alto nivel no permiten operar a nivel de bit con los números en punto flotante, por lo tanto, no se permite obtener el valor de un bit concreto ni aplicar operadores como el desplazamiento de bits. Esta biblioteca contiene la implementación en alto nivel de la colección de funciones aritméticas que operan con números codificados en el estándar. Su propósito es el de disponer de una base funcional que permita realizar experimentos de análisis de coste y precisión en el uso de los distintas variantes del formato. Asímismo, la biblioteca contiene la implementación de las operaciones básicas con restricciones temporales, es decir, con capacidad de prefijar el momento y precisión del resultado

Time-Precision Flexible Adder

Paper submitted to 10th IEEE International Conference on Electronics, Circuits and Systems (ICECS), Sharjah, Emiratos Árabes, 2003.A new conception of flexible calculation that allows us to adjust a sum depending on the available time computation is presented. More specifically, the objective is to obtain a calculation model that makes the processing time/precision more flexible. The addition method is based on carry-select scheme adder and the proposed design uses precalculated data stored in look-up tables, which provide, above all, quality results and systematization in the implementation of low level primitives that set parameters for the processing time. We report an evaluation of the architecture in area, delay and computation error, as well as a suitable implementation in FPGA to validate the design.This work is being backed by grant DPI2002-04434-C04-01 from the Ministerio de Ciencia y Tecnología of the Spanish Government

Exact Numerical Processing

Paper submitted to Euromicro Symposium on Digital Systems Design (DSD), Belek-Antalya, Turkey, 2003.A model of an exact arithmetic processing is presented. We describe a representation format that gives us a greater expressive capability and covers a wider numerical set. The rational numbers are represented by means of fractional notation and explicit codification of its periodic part. We also give a brief description of exact arithmetic operations on the proposed format. This model constitutes a good alternative for the symbolic arithmetic, in special when numerical exact values are required. As an example, we show an application of the exact numerical processing to calculate the perpendicular vector to another one for aerospace purposes.This work is being backed by grant DPI2002-04434-C04-01 from the Ministerio de Ciencia y Tecnología of the Spanish Government

Application of Texture Descriptors to Facial Emotion Recognition in Infants

The recognition of facial emotions is an important issue in computer vision and artificial intelligence due to its important academic and commercial potential. If we focus on the health sector, the ability to detect and control patients’ emotions, mainly pain, is a fundamental objective within any medical service. Nowadays, the evaluation of pain in patients depends mainly on the continuous monitoring of the medical staff when the patient is unable to express verbally his/her experience of pain, as is the case of patients under sedation or babies. Therefore, it is necessary to provide alternative methods for its evaluation and detection. Facial expressions can be considered as a valid indicator of a person’s degree of pain. Consequently, this paper presents a monitoring system for babies that uses an automatic pain detection system by means of image analysis. This system could be accessed through wearable or mobile devices. To do this, this paper makes use of three different texture descriptors for pain detection: Local Binary Patterns, Local Ternary Patterns, and Radon Barcodes. These descriptors are used together with Support Vector Machines (SVM) for their classification. The experimental results show that the proposed features give a very promising classification accuracy of around 95% for the Infant COPE database, which proves the validity of the proposed method.This work has been partially supported by the Spanish Research Agency (AEI) and the European Regional Development Fund (FEDER) under project CloudDriver4Industry TIN2017-89266-R, and by the Conselleria de Educación, Investigación, Cultura y Deporte, of the Community of Valencia, Spain, within the program of support for research under project AICO/2017/134

Flexible processing architecture for maintaining QoS in embedded systems applications

Comunicación presentada en las V Jornadas de Computación Empotrada, Valladolid, 17-19 Septiembre 2014The growing available capacity on a single chip is leading to increasingly sophisticated applications in the field of embedded systems. In addition, the cloud computing paradigm, allows the extension of the capabilities of these systems using remote resources. Among the wide range of applications that can arise in this context, are those in which it is critical to meet certain quality of service (QoS) requirements, such as limited latency. In these cases, real-time operating systems (RTOS) provide a valid solution to guarantee predictability and response time using the resources of the embedded system. However, in applications where the elements to process can grow and decrease in a variable way, the load can exceed the capabilities of the embedded system, which is an important limitation. In this paper, a new architecture is proposed, aiming to take the most of remotely available resources only when the load temporarily exceeds the capabilities of the embedded system. The access to the remote resources is done by using cloud platforms maintaining an acceptable level of QoS for the application

Convergence analysis and validation of low cost distance metrics for computational cost reduction of the Iterative Closest Point algorithm

The Iterative Closest Point algorithm (ICP) is commonly used in engineering applications to solve the rigid registration problem of partially overlapped point sets which are pre-aligned with a coarse estimate of their relative positions. This iterative algorithm is applied in many areas such as the medicine for volumetric reconstruction of tomography data, in robotics to reconstruct surfaces or scenes using range sensor information, in industrial systems for quality control of manufactured objects or even in biology to study the structure and folding of proteins. One of the algorithm’s main problems is its high computational complexity (quadratic in the number of points with the non-optimized original variant) in a context where high density point sets, acquired by high resolution scanners, are processed. Many variants have been proposed in the literature whose goal is the performance improvement either by reducing the number of points or the required iterations or even enhancing the complexity of the most expensive phase: the closest neighbor search. In spite of decreasing its complexity, some of the variants tend to have a negative impact on the final registration precision or the convergence domain thus limiting the possible application scenarios. The goal of this work is the improvement of the algorithm’s computational cost so that a wider range of computationally demanding problems from among the ones described before can be addressed. For that purpose, an experimental and mathematical convergence analysis and validation of point-to-point distance metrics has been performed taking into account those distances with lower computational cost than the Euclidean one, which is used as the de facto standard for the algorithm’s implementations in the literature. In that analysis, the functioning of the algorithm in diverse topological spaces, characterized by different metrics, has been studied to check the convergence, efficacy and cost of the method in order to determine the one which offers the best results. Given that the distance calculation represents a significant part of the whole set of computations performed by the algorithm, it is expected that any reduction of that operation affects significantly and positively the overall performance of the method. As a result, a performance improvement has been achieved by the application of those reduced cost metrics whose quality in terms of convergence and error has been analyzed and validated experimentally as comparable with respect to the Euclidean distance using a heterogeneous set of objects, scenarios and initial situations

Internet of Things: A Review of Surveys Based on Context Aware Intelligent Services

The Internet of Things (IoT) has made it possible for devices around the world to acquire information and store it, in order to be able to use it at a later stage. However, this potential opportunity is often not exploited because of the excessively big interval between the data collection and the capability to process and analyse it. In this paper, we review the current IoT technologies, approaches and models in order to discover what challenges need to be met to make more sense of data. The main goal of this paper is to review the surveys related to IoT in order to provide well integrated and context aware intelligent services for IoT. Moreover, we present a state-of-the-art of IoT from the context aware perspective that allows the integration of IoT and social networks in the emerging Social Internet of Things (SIoT) term.This work has been partially funded by the Spanish Ministry of Economy and Competitiveness (MINECO/FEDER) under the granted Project SEQUOIA-UA (Management requirements and methodology for Big Data analytics) TIN2015-63502-C3-3-R, by the University of Alicante, within the program of support for research, under project GRE14-10, and by the Conselleria de Educación, Investigación, Cultura y Deporte, Comunidad Valenciana, Spain, within the program of support for research, under project GV/2016/087. This work has also been partially funded by projects from the Spanish Ministry of Education and Competitivity TIN2015-65100-R and DIIM2.0 (PROMETEOII/2014/001)

Adjustable compression method for still JPEG images

There are a large number of image processing applications that work with different performance requirements and available resources. Recent advances in image compression focus on reducing image size and processing time, but offer no real-time solutions for providing time/quality flexibility of the resulting image, such as using them to transmit the image contents of web pages. In this paper we propose a method for encoding still images based on the JPEG standard that allows the compression/decompression time cost and image quality to be adjusted to the needs of each application and to the bandwidth conditions of the network. The real-time control is based on a collection of adjustable parameters relating both to aspects of implementation and to the hardware with which the algorithm is processed. The proposed encoding system is evaluated in terms of compression ratio, processing delay and quality of the compressed image when compared with the standard method

Computational Analysis of Distance Operators for the Iterative Closest Point Algorithm

The Iterative Closest Point (ICP) algorithm is currently one of the most popular methods for rigid registration so that it has become the standard in the Robotics and Computer Vision communities. Many applications take advantage of it to align 2D/3D surfaces due to its popularity and simplicity. Nevertheless, some of its phases present a high computational cost thus rendering impossible some of its applications. In this work, it is proposed an efficient approach for the matching phase of the Iterative Closest Point algorithm. This stage is the main bottleneck of that method so that any efficiency improvement has a great positive impact on the performance of the algorithm. The proposal consists in using low computational cost point-to-point distance metrics instead of classic Euclidean one. The candidates analysed are the Chebyshev and Manhattan distance metrics due to their simpler formulation. The experiments carried out have validated the performance, robustness and quality of the proposal. Different experimental cases and configurations have been set up including a heterogeneous set of 3D figures, several scenarios with partial data and random noise. The results prove that an average speed up of 14% can be obtained while preserving the convergence properties of the algorithm and the quality of the final results