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167 results on '"Sanchez-Medina, Javier"'

1. Sentiment analysis and random forest to classify LLM versus human source applied to Scientific Texts

Author

Sanchez-Medina, Javier J.

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Computers and Society, Computer Science - Machine Learning, 68
Abstract

After the launch of ChatGPT v.4 there has been a global vivid discussion on the ability of this artificial intelligence powered platform and some other similar ones for the automatic production of all kinds of texts, including scientific and technical texts. This has triggered a reflection in many institutions on whether education and academic procedures should be adapted to the fact that in future many texts we read will not be written by humans (students, scholars, etc.), at least, not entirely. In this work it is proposed a new methodology to classify texts coming from an automatic text production engine or a human, based on Sentiment Analysis as a source for feature engineering independent variables and then train with them a Random Forest classification algorithm. Using four different sentiment lexicons, a number of new features where produced, and then fed to a machine learning random forest methodology, to train such a model. Results seem very convincing that this may be a promising research line to detect fraud, in such environments where human are supposed to be the source of texts., Comment: 12 Pages, 3 tables, 6 figures

Published
2024

2. From Data to Actions in Intelligent Transportation Systems: a Prescription of Functional Requirements for Model Actionability

Author

Lana, Ibai, Sanchez-Medina, Javier J., Vlahogianni, Eleni I., and Del Ser, Javier

Subjects
Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Computer Science - Neural and Evolutionary Computing
Abstract

Advances in Data Science permeate every field of Transportation Science and Engineering, resulting in developments in the transportation sector that {are} data-driven. Nowadays, Intelligent Transportation Systems (ITS) could be arguably approached as a ``story'' intensively producing and consuming large amounts of data. A~diversity of sensing devices densely spread over the infrastructure, vehicles or the travelers' personal devices act as sources of data flows that are eventually fed {into} software running on automatic devices, actuators or control systems producing, in~turn, complex information flows {among} users, traffic managers, data analysts, traffic modeling scientists, etc. These~information flows provide enormous opportunities to improve model development and decision-making. This work aims to describe how data, coming from diverse ITS sources, can be used to learn and adapt data-driven models for efficiently operating ITS assets, systems and processes; in~other words, for data-based models to fully become \emph{actionable}. Grounded in this described data modeling pipeline for ITS, we~define the characteristics, engineering requisites and challenges intrinsic to its three compounding stages, namely, data fusion, adaptive learning and model evaluation. We~deliberately generalize model learning to be adaptive, since, in~the core of our paper is the firm conviction that most learners will have to adapt to the ever-changing phenomenon scenario underlying the majority of ITS applications. Finally, we~provide a prospect of current research lines within Data Science that can bring notable advances to data-based ITS modeling, which will eventually bridge the gap towards the practicality and actionability of such models., Comment: 40 pages, 3 figures

Published
2020

3. Unsupervised Learning in Reservoir Computing for EEG-based Emotion Recognition

Author

Fourati, Rahma, Ammar, Boudour, Sanchez-Medina, Javier, and Alimi, Adel M.

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Neural and Evolutionary Computing
Abstract

In real-world applications such as emotion recognition from recorded brain activity, data are captured from electrodes over time. These signals constitute a multidimensional time series. In this paper, Echo State Network (ESN), a recurrent neural network with a great success in time series prediction and classification, is optimized with different neural plasticity rules for classification of emotions based on electroencephalogram (EEG) time series. Actually, the neural plasticity rules are a kind of unsupervised learning adapted for the reservoir, i.e. the hidden layer of ESN. More specifically, an investigation of Oja's rule, BCM rule and gaussian intrinsic plasticity rule was carried out in the context of EEG-based emotion recognition. The study, also, includes a comparison of the offline and online training of the ESN. When testing on the well-known affective benchmark "DEAP dataset" which contains EEG signals from 32 subjects, we find that pretraining ESN with gaussian intrinsic plasticity enhanced the classification accuracy and outperformed the results achieved with an ESN pretrained with synaptic plasticity. Four classification problems were conducted in which the system complexity is increased and the discrimination is more challenging, i.e. inter-subject emotion discrimination. Our proposed method achieves higher performance over the state of the art methods.

Published
2018

4. On Smart Mobility and Data Stream Mining

Author

Sanchez-Medina, Javier J., Guerra-Montenegro, Juan Antonio, Sanchez-Medina, Agustin J., Alonso-González, Itzíar G., Sánchez-Rodríguez, David, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Moreno-Díaz, Roberto, editor, Pichler, Franz, editor, and Quesada-Arencibia, Alexis, editor

Published
2022
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5. Traffic Predictive Analysis Through Data Stream Mining

Author

Guerra-Montenegro, Juan, Sánchez-Medina, Javier, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Moreno-Díaz, Roberto, editor, Pichler, Franz, editor, and Quesada-Arencibia, Alexis, editor

Published
2020
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6. What Can Smart Mobility Offer to Tourism Economy?

Author

Guerra-Montenegro, Juan, Sánchez-Medina, Javier, Sánchez-Rodríguez, David, Alonso-González, Itziar, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Moreno-Díaz, Roberto, editor, Pichler, Franz, editor, and Quesada-Arencibia, Alexis, editor

Published
2020
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7. On Smart Mobility and Data Stream Mining

Author

Sanchez-Medina, Javier J., primary, Guerra-Montenegro, Juan Antonio, additional, Sanchez-Medina, Agustin J., additional, Alonso-González, Itzíar G., additional, and Sánchez-Rodríguez, David, additional

Published
2022
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10. SUMO Performance Comparative Analysis of SUMO’s Speed Using Different Programming Languages

Author

Romero Santana, Samuel, Sanchez-Medina, Javier J., Sanchez Rodriguez, David, Alonso Gonzalez, Itziar, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Moreno-Díaz, Roberto, editor, Pichler, Franz, editor, and Quesada-Arencibia, Alexis, editor

Published
2018
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11. A Simple Classification Approach to Traffic Flow State Estimation

Author

del Pino Saavedra Hernández, Aitor, Sánchez Medina, Javier J., Moraine-Matias, Luis, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Moreno-Díaz, Roberto, editor, Pichler, Franz, editor, and Quesada-Arencibia, Alexis, editor

Published
2018
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12. Optimized Echo State Network with Intrinsic Plasticity for EEG-Based Emotion Recognition

Author

Fourati, Rahma, Ammar, Boudour, Aouiti, Chaouki, Sanchez-Medina, Javier, Alimi, Adel M., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Liu, Derong, editor, Xie, Shengli, editor, Li, Yuanqing, editor, Zhao, Dongbin, editor, and El-Alfy, El-Sayed M., editor

Published
2017
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15. How to Simulate Traffic with SUMO

Author

Santana, Samuel Romero, Sanchez-Medina, Javier J., Rubio-Royo, Enrique, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Moreno-Díaz, Roberto, editor, Pichler, Franz, editor, and Quesada-Arencibia, Alexis, editor

Published
2015
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16. Platoon Driving Intelligence. A Survey

Author

Santana, Samuel Romero, Sanchez-Medina, Javier J., Rubio-Royo, Enrique, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Moreno-Díaz, Roberto, editor, Pichler, Franz, editor, and Quesada-Arencibia, Alexis, editor

Published
2015
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19. Acceleration Signal Based Linear Formation Driving Model: Algorithmic Description and Simulation Results

Author

Sánchez-Medina, Javier J., Broggi, Alberto, Galan-Moreno, Manuel J., Rubio-Royo, Enrique, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Moreno-Díaz, Roberto, editor, Pichler, Franz, editor, and Quesada-Arencibia, Alexis, editor

Published
2013
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20. Driver Pattern Study of Las Palmas de Gran Canaria

Author

Diaz-Cabrera, Moises, Sanchez-Medina, Javier J., Perez-Armas, Idaira, Medina-Machin, Elisa, Galan-Moreno, Manuel J., Rubio-Royo, Enrique, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Moreno-Díaz, Roberto, editor, Pichler, Franz, editor, and Quesada-Arencibia, Alexis, editor

Published
2012
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21. User Equilibrium Study of AETROS Travel Route Optimization System

Author

Sanchez-Medina, Javier J., Diaz-Cabrera, Moises, Galan-Moreno, Manuel J., Rubio-Royo, Enrique, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Moreno-Díaz, Roberto, editor, Pichler, Franz, editor, and Quesada-Arencibia, Alexis, editor

Published
2012
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22. Electric Scaled Vehicle as ITS Experimentation Platform

Author

Sanchez-Medina, Javier J., Diaz-Cabrera, Moises, Galan-Moreno, Manuel J., Rubio-Royo, Enrique, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Moreno-Díaz, Roberto, editor, Pichler, Franz, editor, and Quesada-Arencibia, Alexis, editor

Published
2012
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23. Traffic Signals in Traffic Circles: Simulation and Optimization Based Efficiency Study

Author

Sánchez Medina, Javier J., Galán Moreno, Manuel J., Díaz Cabrera, Moisés, Rubio Royo, Enrique, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Moreno-Díaz, Roberto, editor, Pichler, Franz, editor, and Quesada-Arencibia, Alexis, editor

Published
2009
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25. Study of Correlation Among Several Traffic Parameters Using Evolutionary Algorithms: Traffic Flow, Greenhouse Emissions and Network Occupancy

Author

Sánchez Medina, Javier, Galán Moreno, Manuel, Rubio Royo, Enrique, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Moreno Díaz, Roberto, editor, Pichler, Franz, editor, and Quesada Arencibia, Alexis, editor

Published
2007
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26. Monitoring the socio-economic impact of COVID-19 in the Maspalomas touristic area

Author

Peña-Alonso, Carolina, Sanchez-Medina, Javier, Hernández-Alemán, Anastasia, García-Romero, Leví, Sanromualdo-Collado, Abel, Santana-Santana, Sara, Pérez-Hernández, Eva, Marrero-Rodríguez, Néstor, Del Rosario Rodríguez, Eloy, Pérez-Chacón, Emma, and Hernández-Calvento, Luis

Subjects
Regional Economics, Physical and Environmental Geography, Data Science, Geographic Information Sciences, Nature and Society Relations, Human Geography
Abstract

The COVID-19 pandemic caused by the SARS-CoV-2 virus is deeply impacting social and economic systems at global scale. This situation is characterized by continuously changing scenarios. Therefore, tools are needed to contribute to the reduction of the susceptibility of the socio-economic system at different geographical scales. To this regard, the University of Las Palmas de Gran Canaria is deploying a research project focused on the socio-economic impact of COVID-19 on the tourist socio-economic activities of Maspalomas, as a benchmarking case of tourist area in the Canary Islands.

Published
2022

34. On-Board-Unit big data analytics: from data architecture to traffic forecasting

Author

Bontempi, Gianluca, Jansen, Maarten, Defrance, Matthieu, Guns, Tias, Sanchez Medina, Javier J., Buroni, Giovanni, Bontempi, Gianluca, Jansen, Maarten, Defrance, Matthieu, Guns, Tias, Sanchez Medina, Javier J., and Buroni, Giovanni

Abstract

Accurate traffic information is essential to reduce the adverse effects of road transport in cities. Today, urban planners and policy-makers demand Intelligent Transportation Systems (ITS) to conduct proactive traffic management. In this context, the thesis advances the State-Of-The-Art (SOTA) literature of road Traffic Forecasting (TF) for ITS systems. The work investigates the use of On-Board-Unit (OBU) data related to Heavy-Good Vehicles (HGV) in Belgium. The research addresses three main aspects: the setting up of a lambda architecture to collect, store, and process the OBU data; the exploratory OBU data analysis to understand the value in the context of mobility; advanced analytics to perform TF at road network scale.In the first part, we develop the core components of big data architecture to overcome the limitations of traditional solutions. The platform prototype presents promising results in terms of scalability, fault-tolerance, low latency, and debuggability thanks to the use of big data tools now mature in the field of ITS.In the second part, we strive to identify strategic areas in freight traffic. The density-based techniques applied to the OBU data provide insights into traffic dynamics in the Brussels region.In the final part, we perform advanced predictive analytics. We investigate the use of different strategies to tackle short-term traffic prediction at the urban networks. Then, we apply recent Deep Learning (DL) techniques to perform long-term traffic prediction for the urban and freeway road network. Finally, we propose an original Multi-Task Learning (MTL) model to jointly learn traffic flow and speed. Overall the analysis highlights the superiority of Machine Learning (ML) models against traditional approaches when predicting traffic conditions at the transportation network scale.The proposed thesis shows how the use of OBU data can be beneficial for ITS. In particular, it is possible to understand transport dynamics by processing such data wi, Doctorat en Sciences, info:eu-repo/semantics/nonPublished

Published
2021

45. Understanding Network Traffic States using Transfer Learning

Author

Krishnakumari, P.K., Perotti, Alan, Pinto, Viviana, Cats, O., van Lint, J.W.C., Zhang, Wei-Bin, Bayen, Alexandre, Sanchez-Medina, Javier, and Barth, Matthew

Subjects
050210 logistics & transportation, Traffic analysis, Computer science, business.industry, Feature vector, Deep learning, 05 social sciences, 02 engineering and technology, Machine learning, computer.software_genre, Convolutional neural network, 0502 economics and business, 0202 electrical engineering, electronic engineering, information engineering, Feature (machine learning), 020201 artificial intelligence & image processing, Artificial intelligence, business, Transfer of learning, computer
Abstract

Large-scale network traffic analysis is crucial for many transport applications, ranging from estimation and prediction to control and planning. One of the key issues is how to integrate spatial and temporal analyses efficiently. Deep Learning is gaining momentum as a go-to approach for artificial vision, and transfer learning approaches allow to exploit pretrained models and apply them to new domains. In this paper, we encode traffic states as images and use a pretrained deep convolutional neural network as a feature extractor. Experimental results show how the extracted feature vectors cluster naturally into meaningful network traffic states and illustrate how these network states can be used for traffic state prediction.

Published
2018

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