José M. Molina

University Carlos III de Madrid | UC3M · Department of Computer Science and Engineering

This study proposes a swarm-based Unmanned Aerial Vehicle (UAV) system designed for surveillance tasks, specifically for detecting and tracking ground vehicles. The proposal is to assess how a system consisting of multiple cooperating UAVs can enhance performance by utilizing fast detection algorithms. Within the study, the differences in one-stage...

In the field of the intralogistics industry, we present DMZoomNet, a novel architecture that combines deep learning-based detectors with distance information to enhance object detection performance. Evaluation of our approach is conducted using the LOCO dataset, one of the few open source datasets available specifically designed for intralogistics...

Intelligent Transportation Systems are expected to automate how parking slots are booked by trucks. The intrinsic dynamic nature of this problem, the need of explanations and the inclusion of private data justify an agent-based solution. Agents solving this problem act with a Believe Desire Intentions reasoning, and are implemented with JASON. Priv...

Due to Industry 4.0, machines can be connected to their manufacturing processes with the ability to react faster and smarter to changing conditions in a factory. Previously, Internet of Things (IoT) devices could only collect and send data to the cloud for analysis. However, the increasing computing capacity of today”s devices allows them to perfor...

En este artículo se presentan las características que han de adoptar los intermediarios que actúen en el marco de un sistema abierto de agentes inteligentes dedicado al comercio electrónico en general. En lo que respecta al negocio turístico, los intermediarios han desarrollado históricamente una labor que ha de adaptarse a estas nuevas circunstanc...

Tuning the navigation systems is a complex engineering task due to the sensitivity of their parameters, specific requirements to be met, as well as the maneuvering context that the system is designed to address. This problem is still a challenge for navigation system engineers who spend a lot of time to tests and simulations to achieve tuning. Tuni...

Unmanned Aerial Vehicles (UAVs) are a highly innovative technology that is subject to strict regulations due to their potentially hazardous characteristics and a lack of legislative framework for their safe operation. To overcome these challenges, the Unmanned Air System Traffic Management (UTM) initiatives aim to establish validation and monitorin...

In this paper, we propose a trust model to be used in a hypothetical mixed environment where humans and unmanned vehicles cooperate. We address the inclusion of emotions inside a trust model in a coherent way to investigate the practical approaches to current psychological theories. The most innovative contribution of this work is the elucidation o...

The Middle Member of the Llopis Fm in the Sierra de Bedmar-Jódar Unit of the Prebetic Zone of Jaén (southern Spain) was deposited on a shallow-marine platform of the Southern Iberian Continental Margin during the earliest Aptian. Detailed field logging of nine stratigraphic sections and facies mapping have allowed seven lithofacies associations (L1...

Currently it is hard to develop UAV in civil environments, being simulation the best option to develop complex UAV missions with AI. To carry out useful AI training in simulation for real-world use, it is best to do it over a similar environment as the one a real UAV will work, with realistic objects in the scene of interest (buildings, vehicles, s...

This paper presents a context information extraction process over Automatic Identification System (AIS) real world ship data, building a system with the capability to extract representative points of a trajectory cluster. With the trajectory cluster, the study proposes the use of trajectory segmentation algorithms to extract representative points o...

One of the problems facing online marketing in omni-channel environments is efficient budget allocation to each channel. The complexity of this problem is greater in omni-channel environments due to the greater number of channels and the need to analyze data sources containing user interaction information. To solve this problem, different attributi...

The task of reconstructing high-resolution images given low-resolution images is called image super-resolution (SR). Within the wide variety of RS applications, it has a strong impact on the advancement of unmanned aerial vehicle (UAV) technologies. The camera is one of the most commonly used sensors in current UAVs, allowing complex information to...

In the future, UAVs should be a part of the IoT ecosystems. Integration of sensors onboard allows to enrich information stored in the cloud and, at the same time, to improve the capacities of UAVs. Developing new sensors and the integration in UAV architecture could improve control functions. Design of future UAV systems requires from advanced tool...

Some of the limitations of state-space models are given by the difficulty of modeling certain systems, the filters convergence time, or the impossibility of modeling dependencies in the long term. Having agile and alternative methodologies that allow the modeling of complex problems but still provide solutions to the classic challenges of estimatio...

Purpose The purpose of this paper is to evaluate the innovation perception, in its different aspects, of the Spanish people. To this end, several ordered logit models have been developed to determine the extent to which socio-demographic characteristics and other aspects of innovation affect the perception of innovation. Design/methodology/approac...

The process of parametric equalization of musical pieces seeks to highlight their qualities by cutting and/or stimulating certain frequencies. In this work, we present a neural model capable of equalizing a song according to the musical genre that is being played at a given moment. It is normal that (1) the equalization should adapt throughout the...

In this paper, the bounded variation property of fuzzy models with smooth compositions have been studied, and they have been compared with the standard fuzzy composition (e.g., min--max). Moreover, the contribution of the bounded variation of the smooth fuzzy model for the noise removal and edge preservation of the digital images has been investiga...

The unprecedented growth in the amount and variety of data we can store about the behaviour of customers has been parallel to the popularization and development of machine learning algorithms. This confluence of factors has created the opportunity of understanding customer behaviour and preferences in ways that were undreamt of in the past. In this...

New applications are continuously appearing with drones as protagonists, but all of them share an essential critical maneuver—landing. New application requirements have led the study of novel landing strategies, in which vision systems have played and continue to play a key role. Generally, the new applications use the control and navigation system...

Microgrids should be continuously monitored in order to maintain suitable voltages over time. Microgrids are mainly monitored remotely, and their measurement data transmitted through lossy communication networks are vulnerable to cyberattacks and packet loss. The current study leverages the idea of data fusion to address this problem. Hence, this p...

The paper presents an analysis over eleven trajectory segmentation techniques applied to the study and experimentation of ship classification problems based only on kinematic information. Using the experimental framework introduced in previous works, it cleans, smooths and extracts trajectories from real-world Automatic Identification System (AIS)...

Ship type identification in a maritime context can be critical to the authorities to control the activities being carried out. Although Automatic Identification Systems (AIS) has been mandatory for certain vessels if a vessel does not have them voluntarily or not, it can lead to a whole set of problems, so the use of tracking alternatives such as r...

Geographic Information Systems (GIS) allow analysis based on geo-referenced data. Currently only simple geo-referenced information is available, such as road networks or types of terrain, but there are other geo-referenced data that would be very useful to facilitate decision-making. These data are not collected as they are very hard to generate ma...

With the continuous development and cost reduction of positioning and tracking technologies, a large amount of trajectories are being exploited in multiple domains for knowledge extraction. A trajectory is formed by a large number of measurements, where many of them are unnecessary to describe the actual trajectory of the vehicle, or even harmful d...

Deep learning is providing very positive results in areas related to conversational interfaces, such as speech recognition, but its potential benefit for dialog management has still not been fully studied. In this paper, we perform an assessment of different configurations for deep-learned dialog management with three dialog corpora from different...

This paper analyses the perception of Artificial Intelligence (AI) of individuals in Spain and the factors associated with it. It uses data from 6,308 individuals from a 2018 Spanish survey. A binary logit regression model is formulated and estimated for the attitude towards robots and AI and its possible determinants. As main results a gender gap...

According to the World Health Organization, between and , the proportion of the world's population over will double, from to . In absolute numbers, this age group will increase from million to billion in the course of half a century. It is a reality that most of them prefer to live alone, so it is necessary to look for mechanisms and tools that wil...

Integration of symbolic and sub-symbolic approaches is rapidly emerging as an Artificial Intelligence(AI) paradigm. This paper presents a proof-of-concept approach towards an unsupervised learning method, based on Restricted Boltzmann Machines (RBMs), for extracting semantic associations among prominent entities in data. Validation of the approach...

A high‐resolution δ13Ccarb record from Cau (Spain) is proposed as a new global reference for stratigraphic correlation of the Aptian The ultrahigh‐resolution record of the onset of OAE 1a documents a long‐term negative excursion in C‐isotope values, punctuated by several marked negative spikes Evidence for the importance of OM burial as a feedbac...

Certain difficulties in path forecasting and filtering problems are based in the initial hypothesis of estimation and filtering techniques. Common hypotheses include that the system can be modeled as linear, Markovian, Gaussian, or all at one time. Although, in many cases, there are strategies to tackle problems with approaches that show very good...

Learning systems have been focused on creating models capable of obtaining the best results in error metrics. Recently, the focus has shifted to improvement in the interpretation and explanation of the results. The need for interpretation is greater when these models are used to support decision making. In some areas, this becomes an indispensable...

Deep learning is providing very positive results in areas related to conversational interfaces, such as speech recognition, but its potential benefit for dialog management has still not been fully studied. In this paper, we perform an assessment of different configurations for deep-learned dialog management with three dialog corpora from different...

Some of the limitations of state-space models are given by the difficulty of modelling certain systems, the filters convergence time or the impossibility of modelling dependencies in the long term. Having agile and alternative methodologies that allow the modelling of complex problems but still provide solutions to the classic challenges of estimat...

An analysis over trajectory segmentation techniques is carried out by the study of the different algorithms and the experimentation over a ship classification problem, which use a data preparation and classification system used in previous works. With the data preparation, the system handles real-world Automatic Identification System (AIS) data, cl...

Music equalization is the process of trimming or raising specific frequencies (or a range of frequencies, called “frequency bands”) to increase the quality of a song. This paper presents an architecture that obtains a smart song equalization for a song based on a prediction of its musical genre. This prediction is based on a neural model designed i...

Learning systems have been very focused on creating models that are capable of obtaining the best results in error metrics. Recently, the focus has shifted to improvement in order to interpret and explain their results. The need for interpretation is greater when these models are used to support decision making. In some areas this becomes an indisp...

This study is aimed at the early detection of cardiovascular diseases using predictions learning with a high percentage of successes using the lowest possible number of attributes. Results are comparable to other techniques. Applying the learning system through the reduction of attributes, a tree was obtained with the same classification result of...

This research explores the capacity of Information Fusion and Data Mining to extract knowledge about associations among agricultural products and achieve better predictions for future consumption in local markets in the Andean region of Ecuador. This commercial activity is performed using Alternative Marketing Circuits (CIALCO), seeking to establis...

Local governments dispose of powerful tools like development funds that can be distributed among its different constituents to compensate economic disequilibrium originated by a complex array of factors. But it is always one of the hardest decisions to assign handouts to people who could think its own expectations are not being taken properly into...

Conversational systems have become an element of everyday life for billions of users who use speech‐based interfaces to services, engage with personal digital assistants on smartphones, social media chatbots, or smart speakers. One of the most complex tasks in the development of these systems is to design the dialogue model, the logic that provided...

Within the design and development of a smartphone, an important phase arises regarding time, which is related to the tuning of the ISP (image signal processor) of the camera. The ISP is an element that allows the adjustment of the images captured by a sensor in order to achieve the best image quality. The ISP implements different image improvement...

This paper proposes a data preparation process for managing real-world kinematic data and detecting fishing vessels. The solution is a binary classification that classifies ship trajectories into either fishing or non-fishing ships. The data used are characterized by the typical problems found in classic data mining applications using real-world da...

Evaluation of UAV systems is mostly based on simulation tools that are manually configured to define the trajectory (ground truth trajectory) for comparing with the system output. In this work, the authors present an original method to evaluate the performance of UAV platform in real situations without considering simulations. The proposed evaluati...

In this paper we describe a proposal that employs Soft Computing techniques for developing intelligent dialog systems that can improve over time. To do this, our proposal merges statistical dialog management methodologies, intentional and emotional information in order to make dialog managers more efficient and adaptive. The prediction of the user...

In service industries such as telecommunications, hotels, insurance, banking, retail, or medical services, companies are increasingly paying more attention to human-computer communication systems that are in direct contact with customers, and focused on achieving the desired profit and market share goals. For this reason, chatbots are increasingly...

In this paper, we present a statistical model for spoken dialog segmentation that decides the current phase of the dialog by means of an automatic classification process. We have applied our proposal to three practical conversational systems acting in different domains. The results of the evaluation show that is possible to attain high accuracy rat...

The unprecedented growth in the amount and variety of data we can store about the behaviour of customers has been parallel to the popularization and development of machine learning algorithms. This confluence of factors has created the opportunity of understanding customer behaviour and preferences in ways that were undreamt of in the past. In this...

On this paper the authors study a set of maritime trajectory classifiers that classify the type of the ship or the kind of movement that is doing. All with the objective of deciding the viability of using the variables set introduced to the algorithm and the classification result as context information useful for a maritime vigilance system that co...

As life expectancy increases, it has become more necessary to find ways to support healthy ageing. A number of active ageing initiatives are being developed nowadays to foster healthy habits in the population. This paper presents our contribution to these initiatives in the form of a multimodal conversational coach that acts as a coach for physical...

Programs for aesthetic improvements of the images have been one of the applications more widely in the last years so much from the commercial point of view like the private one. The improvement of images has been made through the application of different filters that transform the original image into another whose aesthetics have been improved. In...

In this article, we study the structural properties that smooth compositions bring to predictive control of TS fuzzy models and examine how they affect the uncertainties, parameter variations of the system and environmental noises to die out. We have employed the smoothness structure of compositions to convert the MPC cost function of TS fuzzy mode...

The importance of the maritime vehicles makes necessary the implementation of systems capable of ensure the safety and security. This paper presents an analysis on Automatic Identification System (AIS) data processed with Interacting Multiple Model (IMM) filter in order to help trajectory data analysis for predictive tasks. The main objective is bu...

Nowadays, modern societies are facing the important problem of ageing of their population. On many occasions, older people must leave their homes to be cared for by their relatives or to enter specialised centres for the elderly. On the other hand, something similar happens with disabled people who need the support of other people for their daily a...

In this paper, we present a methodology for the development of embodied conversational agents for social virtual worlds. The agents provide multimodal communication with their users in which speech interaction is included. Our proposal combines different techniques related to Artificial Intelligence, Natural Language Processing, Affective Computing...

Recent developments in sensor technology, wearable computing , Internet of Things (IoT), and wireless communication have given rise to research in ubiquitous healthcare and remote monitoring of human's health and activities. Health monitoring systems involve processing and analysis of data retrieved from smartphones, smart watches, smart bracelets,...

In the last two decades, data and information fusion has experienced significant development due mainly to advances in sensor technology. The sensors provide a continuous flow of data about the environment in which they are deployed, which is received and processed to build a dynamic estimation of the situation. With current technology, it is relat...

In this paper, a monitoring system of agricultural production is modeled as a Data Fusion System (data from local fairs and meteorological data). The proposal considers the particular information of sales in agricultural markets for knowledge extraction about the associations among them. This association knowledge is employed to improve predictions...

This paper develops a smooth model identification and self-learning strategy for dynamic systems taking into account possible parameter variations and uncertainties. We have tried to solve the problem such that the model follows the changes and variations in the system on a continuous and smooth surface. Running the model to adaptively gain the opt...

With the advances in Language Technologies and Natural Language Processing, conversational interfaces have begun to play an increasingly important role in the design of human-machine interaction systems in a number of devices and intelligent environments. In this paper, we present a statistical model for spoken dialog segmentation and labeling base...

In this paper we propose the practical application of multimodal conversational interfaces to develop advanced mobile learning applications. Our proposal integrates features of Android APIs on a modular architecture that emphasizes interaction management and context-awareness to build user-adapted, robust and maintainable (mobile learning) m-learni...

In this paper, we propose and compare alternative ways to merge plans formed of sequences of actions with unknown similarities between the goals and actions. Plans are formed of actions and are executed by several operator agents, which cooperate through recommendations. The operator agents apply the plan actions to passive elements (which we call...

This work formalizes a multi-objective evolutionary approach for the segmentation issue according to Piecewise Linear Representation. It consists in the approximation of a given digital curve by a set of linear models minimizing the representation error and the number of such models. This solution allows the final user to decide from the best array...

This research explores information fusion and data mining techniques and proposes a methodology to improve predictions based on strong associations among agricultural products, which allows prediction for future consumption in local markets in the Andean region of Ecuador using spatial prediction techniques. This commercial activity is performed us...

This research explores the capacity of Machine Learning techniques to detect anomalies and how incorporate this capacity to thinger.io platform. Thinger.io is a IoT opensource platform that allows to create an IoT environment using any hardware available on market. In this paper, several ML techniques are proposed to detect anomalies in the platfor...