SORIA MORILLO , Luis Miguel

En este documento se muestra una arquitectura software para la gestión y desarrollo de aplicaciones susceptibles de ser disparadas por contexto en dispositivos móviles, entendiendo por contexto toda la información externa al dispositivo que representa el estado en el que se encuentra el usuario en un momento determinado. Dicha arquitectura...

A methodology to quantify the dependence be tween features using the Ameva discretization algorithm and the advantages of qualitative models is presented in this paper. This approach will be applied over medical data sets. A com parison among Ameva and other related works has been done. The results, as will be depth explained in this paper,...

Stress is a recognized as a predominant disease with growing costs of treatment. The approach presented here is aimed to detect stress using a light weighted, mobile, cheap and easy to use system. The result sho ws that stress can be de tected even in case a person's natural bio vital data is out of the main range. The system enables storage of...

Intemet of Things has achieved a great expectation in the last few years, largely due to possibilities in the field of the interaction between user and environment. This interaction between users to get involved in their environments, managing at all times each ítem that surrounds them. Specially, because of complex services delivered by...

Human activity recognition systems are currently implemented by hundreds of applications and, in recent years, several technology manufacturers have introduced new wearable devices for this purpose. Battery consumption constitutes a critical point in these systems since most are provided with a rechargeable battery. In this paper, by using...

Currently, the lifestyle of elderly people is regularly monitored in order to establish guidelines for rehabilitation processes or ensure the welfare of this segment of the population. In this sense, activity recognition is essential to detect an objective set of behaviors throughout the day. This paper describes an accurate, comfortable and...

This article aims to develop a minimally intrusive system of care and monitoring. Furthermore, the goal is to get a cheap, comfortable and, especially, efficient system which controls the physical activity car ried out by the user. For this purpose an innovative approach to physical activity recognition is presented, based on the use of...

An innovative approach to physical activity recognition based on the use of discrete variables obtained from accelerometer sensors is presented. The system first performs a discretization process for each variable, which allows efficient recognition of activities performed by users using as little energy as possible. To this end, an...

This paper aims to develop a cheap, comfortable and, spe cially, efficient system which controls the physical activity carried out by the user. For this purpose an extended approach to physical activ ity recognition is presented, based on the use of discrete variables which employ data from accelerometer sensors. To this end, an innovative se...

A lot of significant data describing the behavior or/and actions of systems can be collected in several domains. These data define some aspects, called features, that can be clustered in several classes. A qualitative or quantitative value for each feature is stored from measurements or observations. In this paper, the problem of finding...

This paper presents a Deep Learning approach for traffic sign recognition systems. Several classification experiments are conducted over publicly available traffic sign datasets from Germany and Belgium using a Deep Neural Network which comprises Convolutional layers and Spatial Transformer Networks. Such trials are built to measure the impact...

Traffic sign detection systems constitute a key component in trending real-world applications, such as autonomous driving, and driver safety and assistance. This paper analyses the state-of-the-art of several object-detection systems (Faster R-CNN, R-FCN, SSD, and YOLO V2) combined with various feature extractors (Resnet V1 50, Resnet V1 101,...

In this paper, a preliminary methodology which quantifies the dependence between features in a data set by using the Ameva discretization algo rithm and the advantages of a qualitative model is developed. Thus, different matrices of inter dependence are built providing a grade of depen dence between two features. This methodology is applied to...

Our work provides developers of context-based application for mobile devices a framework for developing comprehensive and adaptable solutions that can interacts each other through a set of functionalities and interaction methods for building secure applications easily. On the other hand, our work provides a platform to reduce the energy...

In this paper, a methodology which quantifies the dependence beteen features in a data set is developed. This methodology uses the Ameva discretization algorithm. In particular, it uses the Ameva coefficient to quantify the dependece. Furthermore, a new coefficient called entropy has been proposed for cases where it is not possible to apply the...

During the last decade, technology has created a new field in software development, known as pervasive computing, thank lo the improvement and extension of integrated sensors. These sensors have been successfully integrated in the daily-life of the common user, using devices like mobile phones. Those new hardware improvements gave the common...

Nowadays, the recognition of physical activity (PA) is a well-known problem with many solutions. Sev eral kind of algorithms, using MEMS sensors, al low determine the most likely activity. Indeed, these applications work well when physical activity is performed for long periods of time and steadily. However, indoors, these systems are not...

Background: In this paper a new approach is applied to the area of marketing research. The aim of this paper is to recognize how brain activity responds during the visualization of short video advertisements using discrete classification techniques. By means of low cost electroencephalography devices (EEG), the activation level of some brain...

The arrival of ubiquitous computing and the increasing use of mobile devices can geta lot of information about the user. This information is used by some applications to adapt its functionality to the user itself and the surrounding environment. In this way the applications need to become more autonomous and less each time user interaction....

This article aims to develop a minimally intrusive system of care and monitoring. Furthermore, the goal is to get a cheap, comfortable and, especially, efficient system which controls the physical activity carried out by the user. All this, is based on the data of accelerometry analysis which are obtained by a mobile phone. Besides this, we...

In this paper a new neuroscience technique is applied into Marketing, which is becoming commonly known as the field of Neuromarketing. The aim of this paper is to recognize how brain responds during the visualization of short advertising movies. Using low cost electroencephalography (EEG), brain regions used during the presentation have been...

The recent boom of GPS (Global Positioning System) as a universal method of location has meant that most people in developed countries have already used this technology sometime in their lives. However, this system suffers from an ever-increasing problem: energy expenditure. GPS receivers have been integrated into increasingly smaller devices...