
Emilio Corchado- University of Salamanca
Emilio Corchado
- University of Salamanca
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Publications (416)
As it is well known, mobile phones have become a basic gadget for any individual that usually stores sensitive information. This mainly motivates the increase in the number of attacks aimed at jeopardizing smartphones, being an extreme concern above all on Android OS, which is the most popular platform in the market. Consequently, a strong effort h...
The ten papers featured in this special issue are an extended selection of contributions presented at the 14th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2021), held in Bilbao, Spain, from September 22–24, 2021. The event was organized by the BISITE group and the University of Deusto. CISIS 202...
In smart agriculture, the accurate prediction of evapotranspiration plays a crucial role in optimizing water usage and maximizing crop yield. However, the increasing adoption of IoT sensor technologies has resulted in the accumulation of large amounts of data, which are frequently contaminated by noise and pose a significant challenge to extract re...
The seven papers included in this special issue represent a selection of extended contributions presented at the 15th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2020, held in Burgos, Spain, September 2020, and organized by University of Burgos and BISITE and GICAP Research Groups.
SOCO 2020...
Detecting intrusions in large networks is a highly demanding task. In order to reduce the computation demand of analysing every single packet travelling along one of such networks, some years ago flows were proposed as a way of summarizing traffic information. Very few research works have addressed intrusion detection in flows from a visualizations...
The number of attacks aimed at compromising smartphones in general, and Android devices in particular, is acknowledged as one of the main security concerns of these devices. Accordingly, a great effort has been devoted in recent years to deal with such incidents. However, scant attention has been paid to study the application of different visualiza...
This research focuses on analyzing the robustness of different regression paradigms under regressand noise, which has not been examined in depth in the specialized literature. Furthermore, their synergy with fourteen noise preprocessing techniques adapted from the field of classification, known as noise filters, is studied. In order to do this, sev...
Collection of datasets used in the paper: Martin, J., Sáez, J. A., & Corchado, E. (2021). On the suitability of stacking-based ensembles in smart agriculture for evapotranspiration prediction. Applied Soft Computing, 108, 107509. https://doi.org/10.1016/j.asoc.2021.107509 - These datasets include 20 datasets of daily climatic data from 77 meteorolo...
Noise negatively affects the complexity and performance of models built in classification problems. The most common approach to mitigate its consequences is the usage of preprocessing techniques, known as noise filters, which are designed to remove noisy samples from the training data. Nevertheless, they are specifically oriented to deal with error...
The eleven papers included in this special issue represent a selection of extended contributions presented at the 14th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2019 held in León, Spain, September 4th-6th, 2019, and organized by University of León and BISITE research group.
The International Conference on Hybrid Artifi...
Smart agriculture aims at generating high harvest yields with an efficient resource management, such as the estimation of crop irrigation. One of the factors on which a productive crop irrigation depends on is evapotranspiration, defined as the water loss process from the soil. This is mainly measured by empirical equations, even though they are co...
The nine papers included in this special issue represent a selection of extended contributions presented at the 13th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2018, held in Oviedo, Spain, 20–22 June 2018, and organized by the BISITE group and the University of Oviedo.
The International Conference on Hybrid Artificial I...
The nine papers included in this special issue represent a selection of extended contributions presented at the 14th International Conference on Hybrid Artificial Intelligent Systems (HAIS), HAIS 2019, held in León, Spain, 4–6 June 2019, and organized by the BISITE group and the University of León.
The International Conference on HAIS has become a...
The present research work focuses on Intrusion Detection (ID), identifying “anomalous” patterns that may be related to an attack to a system or a network. In order to detect such anomalies, this present paper proposes the visualization of network flows for ID by applying a novel neural method called Beta Hebbian Learning (BHL). Four real-life traff...
This book constitutes the refereed proceedings of the 16th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2021, held in Bilbao, Spain, in September 2021.
The 44 full and 11 short papers presented in this book were carefully reviewed and selected from 81 submissions. The papers are grouped into these topics: data mining, kno...
The detection of anomalies (affecting hardware or software) is an open challenge for cyber-physical systems in general and robots in particular. Physical anomalies related to the hardware components of such systems have been widely researched. However, scant attention has been devoted so far to study the anomalies affecting the software components....
In the past 50 years nurse scheduling has received considerable attention in the research community. There are two cases regarding the nurse scheduling problem (NSP): the static and dynamic. Dynamic NSP, is often called nurse rerostering problem (NRRP), which presents reconstruction or modification of the predetermined roster for the current schedu...
This study presents the application of self-organizing maps to air-quality data in order to analyze episodes of high pollution in Madrid (Spain’s capital city). The goal of this work is to explore the dataset and then compare several scenarios with similar atmospheric conditions (periods of high Nitrogen dioxide concentration): some of them when no...
This book contains accepted papers presented at CISIS 2020 held in the beautiful and historic city of Burgos (Spain), in September 2020.
The aim of the CISIS 2020 conference is to offer a meeting opportunity for academic and industry-related researchers belonging to the various, vast communities of computational intelligence, information security,...
This book contains accepted papers presented at SOCO 2020 conference held in the beautiful and historic city of Burgos (Spain), in September 2020.
Soft computing represents a collection or set of computational techniques in machine learning, computer science and some engineering disciplines, which investigate, simulate, and analyze very complex iss...
This book contains accepted papers presented at ICEUTE 2020 held in the beautiful and historic city of Burgos (Spain), in September 2020.
The 11th International Conference on EUropean Transnational Education (ICEUTE 2020) has been a meeting point for people working on transnational education within Europe. It has provided a stimulating and fruitful...
In recent years, the digital transformation has been advancing in industrial companies, supported by the Key Enabling Technologies (Big Data, IoT, etc.) of Industry 4.0. As a consequence, companies have large volumes of data and information that must be analyzed to give them competitive advantages. This is of the utmost importance in fields such as...
This research presents a novel topology preserving map (TPM) called Weighted Voting Supervision -Beta-Scale Invariant Map (WeVoS-Beta-SIM), based on the application of the Weighted Voting Supervision (WeVoS) meta-algorithm to a novel family of learning rules called Beta-Scale Invariant Map (Beta- SIM). The aim of the novel TPM presented is to impro...
The present research work focuses on overcoming cybersecurity problems in the Smart Grid. Smart Grids must have feasible data capture and communications infrastructure to be able to manage the huge amounts of data coming from sensors. To ensure the proper operation of next-generation electricity grids, the captured data must be reliable and protect...
The eight papers included in this special issue represent a selection of extended contributions presented at the 12th International Conference on Hybrid Artificial Intelligent Systems (HAIS 2017) held in Logroño (La Rioja), Spain on 21–23 June 2017 and organized by the BISITE group and the University of La Rioja.
The International Conference on Hyb...
Material flow management refers to the analysis and specific optimization of the inventory‐production system. Material flow can be characterized as the organized flow of material in a production process with the required sequence determined by a technological procedure. The Milk run system assures the transportation of materials at the right time a...
Student performance and its evaluation remain a serious challenge for education systems. Frequently, the recording and processing of students’ scores in a specific curriculum have several flaws for various reasons. In this context, the absence of data from some of the student scores undermines the efficiency of any future analysis carried out in or...
Nowadays, batteries play an important role in a lot of different applications like energy storage, electro-mobility, consumer electronic and so on. All the battery types have a common factor that is their complexity, independently of its nature. Usually, the batteries have an electrochemical nature. Several different test are accomplished to check...
Although great effort has been devoted to successfully detect Android malware, it still is a problem to be addressed. Its complexity increases due to the high number of features that can be obtained from Android apps in order to improve detection. Present paper proposes wrapper feature selection by applying a genetic algorithm and a Multilayer Perc...
This book constitutes the refereed proceedings of the 15th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2020, held in Gijón, Spain, in November 2020.
The 65 regular papers presented in this book were carefully reviewed and selected from 106 submissions. The papers are grouped into these topics: advanced data processing an...
In supervised learning, some data characteristics (e.g. presence of errors, overlapping degree, etc.) may negatively influence classifier performance. Many methods are designed to overcome the undesirable effects of the aforementioned issues. When comparing one of those techniques with existing ones, a proper selection of datasets must be made, bas...
The typical inaccuracy of data gathering and preparation procedures makes erroneous and unnecessary information to be a common issue in real-world applications. In this context, feature selection methods are used in order to reduce the harmful impact of such information in data analysis by removing irrelevant features from datasets. This research p...
This study presents the application of neural models to a real-life problem in order to study the energy and water consumptions of an automotive multinational company for resources saving and environment protection. The aim is to visually and naturally analyse different consumptions data for a whole year, month by month, from factories and location...
The clustering of a new unsupervised problem usually requires of knowing both if the samples may be separable in different groups and the number of these groups. This information, which has a great impact in the results obtained, is generally unknown beforehand. A wide explored research line in the literature proposes to use some metrics, known as...
This research proposes the analysis and subsequent characterisation of Android malware families by means of low dimensional visualisations using dimensional reduction techniques. The well-known Malgenome data set, coming from the Android Malware Genome Project, has been thoroughly analysed through the following six dimensionality reduction techniqu...
This study presents the application of dimensionality reduction and clustering techniques to episodes of high pollution in Madrid City (Spain). The goal of this work is to compare two scenarios with similar atmospheric conditions (periods of high NO2 concentration): one of them when no actions were taken and the other one when traffic restrictions...
The Heat Pump with geothermal exchanger is one of the best methods to heat up a building. The heat exchanger is one of the most representative elements when a heat pump is employed as building heating system. In the present study, a novel intelligent system was designed to predict the performance of on this kind of heating equipment. The novel appr...
Medical data mining problems are usually characterized by examples of some of the classes appearing more frequently. Such a learning difficulty is known as imbalanced classification problems. This contribution analyzes the application of algorithms for tackling multi-class imbalanced classification in the field of vertebral column diseases classifi...
This book includes papers presented at SOCO 2018, CISIS 2018 and ICEUTE 2018, all held in the beautiful and historic city of San Sebastian (Spain), in June 2018.
Soft computing represents a collection or set of computational techniques in machine learning, computer science and some engineering disciplines, which investigate, simulate, and analyze...
Ozone is one of the pollutants with most negative effects on human health and in general on the biosphere. Many data-acquisition networks collect data about ozone values in both urban and background areas. Usually, these data are incomplete or corrupt and the imputation of the missing values is a priority in order to obtain complete datasets, solvi...
This volume of Advances in Intelligent and Soft Computing contains accepted papers presented at SOCO 2017, CISIS 2017 and ICEUTE 2017, all conferences held in the beautiful and historic city of León (Spain), in September 2017.
Soft computing represents a collection or set of computational techniques in machine learning, computer science and some en...
This volume constitutes the refereed proceedings of the 13th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2018, held in Oviedo, Spain, in June 2018.
The 62 full papers published in this volume were carefully reviewed and selected from 104 submissions. They are organized in the following topical sections: Neurocomputing, f...
The thirteen papers included in this special issue represent a selection of extended contributions presented at the 10th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2015 held in Bilbao, Spain, March 22nd–24th 2015, and organized by the BISITE and the DeustoTech research groups.
The International Conference on Hybrid Arti...
This study presents the application of clustering techniques to a real-life problem of studying the air quality of the Castilla y León region in Spain. The goal of this work is to analyze the level of air pollution in eight points of this Spanish region between years 2008 and 2015. The analyzed data were provided by eight acquisition stations from...
Due to the ever increasing amount and severity of attacks aimed at compromising smartphones in general, and Android devices in particular, much effort have been devoted in recent years to deal with such incidents. However, accurate detection of bad-intentioned Android apps still is an open challenge. As a follow-up step in an ongoing research, pres...
In this paper, an experience to approach the competence about ethical aspects of the profession is presented. Following an existing methodology, several cases are presented to the students in order to determine if people involved have had a professional or ethical behaviour. Codes of professional ethics or conduct have been also discussed with the...
Due to the ever increasing amount and severity of attacks aimed at compromising smartphones in general, and Android devices in particular, much effort have been devoted in recent years to deal with such incidents. However, scant attention has been devoted to study the interplay between visualization techniques and Android malware detection. As an i...
In this research, a novel family of learning rules called Beta Hebbian Learning (BHL) is thoroughly investigated to extract information from high-dimensional datasets by projecting the data onto low-dimensional (typically two dimensional) subspaces, improving the existing exploratory methods by providing a clear representation of data's internal st...
In this study we present a novel version of the Scale Invariant Map (SIM) called Beta-SIM, developed to facilitate the clustering and visualization of the internal structure of complex datasets effectively and efficiently. It is based on the application of a family of learning rules derived from the Probability Density Function (PDF) of the residua...
This paper employs well-known techniques as Support Vector Machines and Neural Networks in order to classify images of boar sperm cells. Acrosome integrity gives information about if a sperm cell is able to fertilize an oocyte. If the acrosome is intact, the fertilization is possible. Otherwise, if a sperm cell has already reacted and has lost its...
This volume constitutes the refereed proceedings of the 12th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2017, held in La Rioja, Spain, in June 2017.
The 60 full papers published in this volume were carefully reviewed and selected from 130 submissions. They are organized in the following topical sections: data mining, k...
At present time, although many theoretical formulations have been successfully proposed, there is a lack of ICT-based tools to support practical deployment of knowledge management (KM) in real settings. To bridge this gap, a hybrid artificial intelligence system is proposed in present study, aimed at gaining deeper knowledge about KM practices in f...
A comprehensive analysis of clustering techniques is presented in this paper through their application to data on meteorological conditions. Six partitional and hierarchical clustering techniques (k-means, k-medoids, SOM k-means, Agglomerative Hierarchical Clustering, and Clustering based on Gaussian Mixture Models) with different distance criteria...
Latest research on Soft Computing Models in Industrial and Environmental Applications, Computational Intelligence in Security for Information Systems and European Transnational Education
Scientific outcome of the International Joint Conference SOCO’16-CISIS’16-ICEUTE’16 held in San Sebastián, Spain, October 19th-21st, 2016
Presents new applicatio...
In this research a parallel version of two existing algorithms that implement Maximum Likelihood Scale Invariant Map (MLHL-SIM) and Scale Invariant Map (SIM) is proposed. By using OpenMP to distribute the independent iterations of for-loops among the available threads, a significant reduction in the computation time for all the experiments is achie...
In recent years, mobile devices such as smartphones, tablets and wearables have become the new paradigm of user–computer interaction. The increasing use and adoption of such devices is also leading to an increased number of potential security risks. The spread of mobile malware, particularly on popular and open platforms such as Android, has become...
Much effort has been devoted to research on intrusion detection (ID) in recent years because intrusion strategies and technologies are constantly and quickly evolving. As an innovative solution based on visualization, MObile VIsualisation Connectionist Agent-Based IDS was previously proposed, conceived as a hybrid-intelligent ID System. It was desi...
Currently, the electrical mobility and the intermittent power generation facilities problem are two of the main purposes of batteries. Batteries, in general terms, have a complex behavior. Due to the usual electrochemical nature of batteries, several tests are made to check their performance, and it is very useful to know a priori how they are work...
Nowadays the student performance and its evaluation is a challenge in general terms. Frequently, the students’ scores of a specific curriculum have several fails due to different reasons. In this context, the lack of data of any of student scores adversely affects any future analysis to be done for achieving conclusions. When this occurs, a data im...
Control of dental millingprocesses is a task which can significantly reduce production costs due to possible savings in time. Appropriate setup of production parameters can be done in a course of optimisation aiming at minimising selected objective function, e.g. time. Nonetheless, the main obstacle here is lack of explicitly defined objective func...
This volume constitutes the refereed proceedings of the 11th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2016, held in Seville, Spain, in April 2016.
The 63 full papers published in this volume were carefully reviewed and selected from 150 submissions. They are organized in topical sections on data mining and knowledge d...
The nine contributions selected in this special issue represent a collection of extended papers presented at the sixth International Conference on Computational Intelligence in Security for Information Systems (CISIS 2013).
CISIS aims to offer a meeting opportunity for academic and industry-related researchers belonging to the various, vast communi...
The Secure Shell Protocol (SSH) is a well-known standard protocol, mainly used for remotely accessing shell accounts on Unix-like
operating systems to perform administrative tasks. As a result, the SSH service has been an appealing target for attackers,
aiming to guess root passwords performing dictionary attacks or to directly exploit the service...
The heat pump with geothermal exchanger is one of the best methods to heat up a building. The heat exchanger is an element with high probability of failure due to the fact that it is an outside construction and also due to its size. In the present study, a novel intelligent system was designed to detect faults on this type of heating equipment. The...
Present study proposes the application of different soft-computing and statistical techniques to the characterization of atmospheric conditions in Spain. The main goal is to visualize and analyze the air quality in a certain region of Spain (Madrid) to better understand its circumstances and evolution. To do so, real-life data from three data acqui...
With the aim of calculating the extinction angle of the current of a single-phase half wave controlled rectifier with resistive and inductive load, present work shows a method to obtain a regression model based on intelligent methods. This type of circuit is a typical non-linear case of study that requires a hard work to solve it by hand. To create...
All fields of science have advanced and still advance significantly. One of the facts that contributes positively is the synergy between areas. In this case, the present research shows the Electromyogram (EMG) modeling of patients undergoing to anesthesia during surgery. With the aim of predicting the patient EMG signal, a model that allows to know...