Journal papers
- Camacho, J., Sorochan Armstrong, M. Population Power Curves in ASCA with Permutation Testing. Journal of Chemometrics, 2024, : -.
- Saccenti, E., Timmerman, M.E., Camacho, J. A simulation study of the effects of additive, multiplicative, correlated and uncorrelated error on Principal Components Analysis. Journal of Chemometrics, 2024, : -.
- Camacho, J., Wasielewska, K., Bro, R., Kotz, D. Interpretable Feature Learning in Multivariate Big Data Analysis for Network Monitoring.. IEEE Transactions on Network and Service Management. , 2024, 21 (3): 2926-2943.
- González‐Olmedo, C., et al. Metabolomics signature as a survival predictor in patients with resectable colorectal liver metastasis . Clinical and Translational Medicine, 2024, 14 (1): e1541-.
- Koleini, F., Hugelier, S., Lakeh, M.A., Abdollahi, H., Camacho, J., Gemperline, P.J. On the complementary nature of ANOVA simultaneous component analysis (ASCA+) and Tucker3 tensor decompositions on designed multi-way datasets. Journal of Chemometrics, 2023, 37 (11): e3514-.
- Camacho, J., Vitale, R., Morales-Jiménez, D., Gómez-Llorente, C. Variable-Selection ANOVA Simultaneous Component Analysis. Bioinformatics, 2023, 39 (1): btac795-.
- García-Teodoro, P., Camacho, J., Maciá-Fernández, G., Gómez-Hernández, J.A., López-Marín, V. A Novel Zero-Trust Network Access Control Scheme based on the Security Profile of Devices and Users . Computer Networks, 2022, 212: 109068-.
- Camacho, J., Díaz, C., Sánchez-Rovira, P. Permutation Tests for ASCA in Multivariate Longitudinal Intervention Studies. Journal of Chemometrics, 2022, 37 (7): e3398-.
- Díaz, C., et al. Predicting dynamic response to neoadjuvant chemotherapy in breast cancer: a novel metabolomics approach. Molecular Oncology, 2022, 16 (14): 2658-2671.
- Gómez-Hernández, J., Camacho, J., Holgado-Terriza, J., García-Teodoro, P., Maciá-Fernández, G. ARANAC: A Bring-Your-Own-Permissions Network Access Control Methodology for Android Devices. IEEE Access, 2021, 9: 101321-101334.
- Fuentes-García, N.M., Camacho, J., Maciá-Fernández, G. Present and Future of Network Security Monitoring. IEEE Access, 2021, 9: 112744-112760.
- Camacho, J., Smilde, A.K., Saccenti, E., Westerhuis, J., Bro, R. All Sparse PCA Models Are Wrong, But Some Are Useful. Part II: Limitations and Problems of Deflation . Chemometrics and Intelligent Laboratory Systems, 2021, 208: 104212-.
- Jiménez-Carvelo, A.M., Martín-Torres, S., Ortega-Gavilán, F., Camacho, J. PLS-DA vs Sparse PLS-DA in food traceability. A case study: authentication of avocado samples. Talanta, 2021, 224: 121904-.
- Gómez-Llorente, A., et al., Gómez-Llorente, C. A Multi-omics Approach Reveals New Signatures in Obese Allergic Asthmatic Children. Biomedicines , 2020, 8 (9): 359-.
- Tortorella, S., Servili, M., Toschi, T.G., Cruciani, G., Camacho, J. Subspace Discriminant Index to Expedite Exploration of Multi-Class Omics Data. Chemometrics and Intelligent Laboratory Systems, 2020, 206: 104160-.
- Camacho, J., Acar, E., Rasmunssen, M., Bro, R. Cross-product Penalized Component Analysis (X-CAN). Chemometrics and Intelligent Laboratory Systems, 2020, 203: 104038-.
- Magán-Carrión, R., Camacho, J., Maciá-Fernández, G., Ruiz-Zafra, A. MSNM-Sensor: An Effective Tool for Real-Time Monitoring and Anomaly Detection in Complex Networks and Systems. International Journal of Distributed Sensor Networks, 2020, 16 (5): -.
- Camacho, J., McDonald, C., Peterson, R., Zhou, X. Longitudinal Analysis of a Campus Wi-Fi Network. Computer Networks, 2020, 179: 107103-.
- Camacho, J., Smilde, A.K., Saccenti, E., Westerhuis, J. All Sparse PCA Models Are Wrong, But Some Are Useful. Part I: Computation of Scores, Residuals and Explained Variance. Chemometrics and Intelligent Laboratory Systems, 2020, 196: 1039072-.
- Camacho, J., García-Giménez, J., Fuentes-García, N.M., Maciá-Fernández, G. Multivariate Big Data Analysis for Intrusion Detection: 5 steps from the haystack to the needle. Computers & Security, 2019, 87: 101603-.
- Fuentes-García, N.M., González-Martinez, J.M., Maciá-Fernández, G., Camacho, J. PARAMO: Enhanced Data Pre-processing in Batch Multivariate Statistical Process Control. Journal of Chemometrics, 2019, 33 (12): e3188-.
- Camacho, J., Therón, R., García-Giménez, J., Maciá-Fernández, G., García-Teodoro, P. Group-Wise Principal Component Analysis for Exploratory Intrusion Detection. IEEE Access, 2019, 7: 113081-.
- Tenorio-Jiménez, C., et al., Gómez-Llorente, C. Lactobacillus reuteri V3401 Reduces Inflammatory Biomarkers and Modifies the Gastrointestinal Microbiome in Adults with Metabolic Syndrome: The PROSIR Study. Nutrients, 2019, 11: 1761-.
- Camacho, J., Maciá-Fernández, G., Fuentes-García, N.M., Saccenti, E. Semi-supervised Multivariate Statistical Network Monitoring for Learning Security Threats. IEEE Transactions on Information Forensics and Security, 2019, 14 (8): 2179-2189.
- González-Martinez, J.M., Camacho, J., Ferrer, A.J. MVBatch: A matlab toolbox for batch process modeling and monitoring. Chemometrics and Intelligent Laboratory Systems, 2018, 183: 122-133.
- Saccenti, E., Smilde, A.K., Camacho, J. Group-wise ANOVA simultaneous component analysis for designed omics experiments. Metabolomics, 2018, 14 (6): 73-.
- Suárez-Tangil, S., Dash, S.K., García-Teodoro, P., Camacho, J., Cavallaro, L. Anomaly-based Exploratory Analysis and Detection of Exploits in Android Mediaserver. IET Information Security, 2018, 12 (5): 404-413.
- Fuentes-García, N.M., Maciá-Fernández, G., Camacho, J. Evaluation of diagnosis methods in PCA-based Multivariate Statistical Process Control. Chemometrics and Intelligent Laboratory Systems, 2018, 172: 194-210.
- Maciá-Fernández, G., Camacho, J., Magán-Carrión, R., García-Teodoro, P., Therón, R. Ugr'16: a new dataset for the evaluation of cyclostationarity-based network IDSs. Computer & Security, 2018, 73: 411-424.
- Camacho, J., Saccenti, E. Group-wise Partial Least Squares Regression. Journal of Chemometrics, 2018, 32: 1-11.
- Magán-Carrión, R., Camacho, J., García-Teodoro, P., Flushing, E., Caro, G. A Dynamical Relay Node placement Solution for MANETs. Computer Communications, 2017, 114 (1): 36-50.
- Camacho, J. On the Generation of Random Multivariate Data. Chemometrics and Intelligent Laboratory Systems, 2017, 160: 40-51.
- Camacho, J., Rodríguez-Gómez, R., Saccenti, E. Group-wise Principal Component Analysis for Exploratory Data Analysis. Journal of Computational and Graphical Statistics , 2017, 26 (3): 501-512.
- Magán-Carrión, R., Rodríguez-Gómez, R., Camacho, J., García-Teodoro, P. Optimal Relay Placement in Multi-Hop Wireless Networks. Ad hoc Networks, 2016, 46: 23-36.
- Camacho, J., Magán-Carrión, R., García-Teodoro, P., Treinen, J.J. Networkmetrics: Multivariate Big Data Analysis in the Context of the Internet. Journal of Chemometrics, 2016, 30 (9): 487-.
- Camacho, J., Pérez-Villegas, A., García-Teodoro, P., Maciá-Fernández, G. PCA-based Multivariate Statistical Network Monitoring for Anomaly Detection . Computers & Security, 2016, 59: 118-137.
- Saccenti, E., Camacho, J. Determining the number of components in principal components analysis: A comparison of statistical, crossvalidation and approximated methods. Chemometrics and Intelligent Laboratory Systems, 2015, 149: 99-116.
- Saccenti, E., Camacho, J. On the use of the observation-wise k-fold operation in PCA cross-validation. Journal of Chemometrics, 2015, 29 (8): 467-478.
- Magán-Carrión, R., Camacho, J., García-Teodoro, P. Multivariate Statistical Approach for Anomaly Detection and Lost Data Recovery in Wireless Sensor Networks. International Journal of Distributed Sensor Networks, 2015, 2015: 1-20.
- Camacho, J., Pérez-Villegas, A., Rodríguez-Gómez, R., Jiménez-Mañas, E. Multivariate Exploratory Data Analysis (MEDA) Toolbox. Chemometrics and Intelligent Laboratory Systems, 2015, 143: 49-57.
- Camacho, J., Laurí, D., Lennox, B., Escabias, M., Valderrama, M. Evaluation of smoothing techniques in the run to run optimization of fed-batch processes with u-PLS. Journal of Chemometrics, 2015, 29 (6): 338-348.
- Camacho, J. Visualizing Big data with Compressed Score Plots: Approach and Research Challenges. Chemometrics and Intelligent Laboratory Systems, 2014, 135: 110-125. ScienceDirect TOP25 Hottest Articles.
- Camacho, J., Ferrer, A.J. Cross-validation in PCA models with the element-wise k-fold (ekf) algorithm: Practical Aspects.. Chemometrics and Intelligent Laboratory Systems, 2014, 131: 37-50.
- Laurí, D., Lennox, B., Camacho, J. Model predictive control for batch processes: Ensuring validity of predictions. Journal of Process Control, 2014, 24 (1): 239-249.
- González-Martinez, J.M., Camacho, J., Ferrer, A.J. Bilinear Modelling of Batch Processes. Part III: Parameter Stability. Journal of Chemometrics, 2014, 28 (1): 10-27.
- Camacho, J., Padilla, P., García-Teodoro, P., Díaz-Verdejo, J. A Generalizable Dynamic Flow Pairing Method for Traffic Classification. Computer Networks, 2013, 57 (14): 2718-2732.
- Padilla, P., Camacho, J., Maciá-Fernández, G., Díaz-Verdejo, J., García-Teodoro, P., Gómez-Calero, C. On the Influence of the Propagation Channel in the Performance of Energy-Efficient Geographic Routing Algorithms for Wireless Sensor Networks (WSN). Wireless Personal Communications, 2013, 70 (1): 15-38.
- Camacho, J., Ferrer, A.J. Cross-validation in PCA models with the element-wise k-fold (ekf) algorithm: theoretical aspects. Journal of Chemometrics, 2012, 26 (7): 361-373.
- Camacho, J. Observation-based missing data methods for exploratory data analysis to unveil the connection between observations and variables in latent subspace models. Journal of Chemometrics, 2011, 25 (11): 592-600.
- Camacho, J., Padilla, P., Díaz-Verdejo, J., Smith, K., Lovett, D. Least-squares approximation of a space distribution for a given covariance and latent sub-space. Chemometrics and Intelligent Laboratory Systems, 2011, 105 (2): 171-180.
- Camacho, J. Missing-data theory in the context of exploratory data analysis. Chemometrics and Intelligent Laboratory Systems, 2010, 103 (1): 8-18. ScienceDirect TOP25 Hottest Articles.
- Camacho, J., Picó, J., Ferrer, A.J. Data understanding with PCA: Structural and Variance Information plots. Chemometrics and Intelligent Laboratory Systems, 2010, 100 (1): 48-56. ScienceDirect TOP25 Hottest Articles.
- Camacho, J., Picó, J., Ferrer, A.J. On-line monitoring of batch processes based on PCA: Does the modelling structure matter?. Analytica Chimica Acta, 2009, 642 (1-2): 59-68.
- Camacho, J., Picó, J., Ferrer, A.J. Multi-Phase Analysis Framework for Handling Batch Process Data. Journal of Chemometrics, 2008, 22 (11-12): 632-643.
- Camacho, J., Picó, J., Ferrer, A.J. Bilinear Modelling of Batch Processes. Part II: A comparison of PLS soft-sensors. Journal of Chemometrics, 2008, 22 (10): 533-547.
- Camacho, J., Picó, J., Ferrer, A.J. Bilinear Modelling of Batch Processes. Part I: Theoretical Discussion. Journal of Chemometrics, 2008, 22 (5): 299-308.
- Camacho, J., Picó, J., Ferrer, A.J. Self-tuning run to run optimization of fed-batch processes using unfold-PLS. AIChE Journal, 2007, 53 (7): 1789-1804.
- Camacho, J., Picó, J. Online Monitoring of Batch Processes using Multi-Phase Principal Component Analysis. Journal of Process Control, 2006, 10 (16): 1021-1035. ScienceDirect TOP25 Hottest Articles.
- Camacho, J., Picó, J. Multi-phase principal component analysis for batch processes modelling. Chemometrics and Intelligent Laboratory Systems, 2006, 81 (2): 127-136. ScienceDirect TOP25 Hottest Articles.
- Camacho, J., Morillas, S., Latorre, P. Efficient impulsive noise suppression based on statistical confidence limits.. Journal of Imaging Science and Technology, 2006, 50 (5): 427-436.
- Camacho, J., Picó, J. Monitorización de procesos por lotes mediante pca multifase. Revista Iberoamericana de Automática e Informática Industrial , 2006, 3 (3): 78-91.
Conference papers
- Camacho, J. Invited Keynote: ASCA solutions for complex experimental and observational data. Chemometrics in Analytical Chemistry (CAC 20024), San José (Argentina), 2024.
- Sorochan Armstrong, M., Camacho, J., Replicate mode analysis for nested experimental designs in ANOVA – PARAFAC (PARAFASCA) models. Chemometrics in Analytical Chemistry (CAC 20024), San José (Argentina), 2024.
- Sorochan Armstrong, M. Camacho J., An alignment-agnostic method of analyzing separations data with Fast Fourier Transform - ANOVA Simultaneous Component Analysis. 8th International Chemometrics Research Meeting, Soesterberg (Netherlands), 2024.
- Sorochan Armstrong, M., An ASCA-like factorization for heterogeneous data. 8th International Chemometrics Research Meeting, Soesterberg (Netherlands), 2024.
- Sorochan Armstrong, M. Sandau C., Workflow democratization for comprehensive two-dimensional gas chromatography – high-resolution time-of-flight mass spectrometry data. 15th Multidimensional Chromatography Workshop, Los Angeles (United States), 2024.
- Giskeødegård, G.F., Madssen, T.S., Camacho, J., Jarmund, A.H., Smilde, A., Westerhuis, J., Statistical validation of multivariate effects in longitudinal study designs. Metabolomics. Metabolomics, Osaka (Japan), 2024.
- Díaz, C., Camacho, J., González-Olmedo, C., Sánchez, P., Fernández-Godino, R., Metabolomics using variable selection ANOVA simultaneous component analysis (VASCA) and partial least squares-discriminant analysis (PLS-DA) to predict relapse and survival in metastatic colorectal cancer. Metabolomics. Metabolomics, Osaka (Japan), 2024.
- Camacho, J., Fakhruzi, I., Dey, P.S., García, L., Multivariate Exploratory Data Analysis of Mobility Patterns using Distributed Acoustic Sensing. 9th International Conference in Spectral Imaging–IASIM, Bilbao (Spain), 2024.
- García, J., Camacho, J., Dey, P.S., Fakhruzi, I., Benítez, C., Barrancos, J., D’Auria, L., García, L., Exploratory Data Analysis of Seismic Data using Distributed Acoustic Sensing and Principal Component Analysis. 9th International Conference in Spectral Imaging–IASIM, Bilbao (Spain), 2024.
- Adán-López, R., Fernández-Martínez, D., Rodríguez-Gómez, R.A., Camacho, J. Coupled Design and Analysis of Experiments in Network Management. 37th IEEE/IFIP Network Operations and Management Symposium (NOMS 2024) , Seoul (Korea), 2024.
- Camacho, J. ANOVA Simultaneous Component Analysis for the Efficient Exploration of Massive Network Traffic Data. 37th IEEE/IFIP Network Operations and Management Symposium (NOMS 2024) , Seoul (Korea), 2024.
- Sorochan Armstrong, M., Camacho, J., Zamora, R. Interpolative inverse non-uniform fast Fourier transform for recovery of bilinear structures in parallel, irregularly-sampled time domain signals . Scandinavian Symposium on Chemometrics, Gothenburg (Sweden), 2023.
- Sorochan Armstrong, M., Lázaro-González, A., Mellado, M., Camacho, J., Zamora, R. Uncertainty estimation in ANOVA-Simultaneous Component Analysis – PARAFAC (PARAFASCA) for visualisation of complex interactions in factorial mistletoe metabolomics data. Scandinavian Symposium on Chemometrics, Gothenburg (Sweden), 2023.
- Polushkina, O., Ferrer, P., Fernandez-Gonzalez S., Pérez-Cruz M., Gómez-Roig M.D., Camacho, J., Gómez-Llorente, C. Application of VASCA in Longitudinal Data. XI Colloquium Chemometricum Mediterraneum, Padova (Italy), 2023.
- Camacho, J., Saccenti, E., Smilde, A. Comparison of VASCA, GASCA and its combined version G-VASCA.. XI Colloquium Chemometricum Mediterraneum, Padova (Italy), 2023.
- Camacho, J. NetMob 2013 Data Analysis with ASCA. Netmob 2023, Madrid (Spain), 2023.
- Camacho, J. Simulation Power Curves in ASCA. Topics in Chemometrics, Rostock (Germany), 2023. Presentation
- Camacho, J., Wasielewska, K., Espinosa, P., Fuentes-García, M. Quality In / Quality Out: Data quality more relevant than model choice in anomaly detection with the UGR’16. . IEEE/IFIP Network Operation and Service Management (NOMS), Miami (USA), 2023.
- Khabeer A. A., Vitale R, Morales-Jimenez D. and Gómez-Llorente C. Camacho J. Variable-Selection ANOVA Simultaneous Component Analysis. Metabolomics, Valencia (Spain), 2022.
- Wasielewska, K., Soukup, D., Cejka, T., Camacho, J. Dataset Quality Assessment in Autonomous Networks with Permutation Testing. The 10th Prague Embedded Systems Workshop, Prague (Czeck Rep.), 2022.
- Camacho, J. Networkmetrics for Network Monitoring and Security- Invited Keynote. The 10th Prague Embedded Systems Workshop, Prague (Czeck Rep.), 2022. Presentation
- Camacho, J., Polushkina, O.A., Gómez-Llorente, C., Díaz, C., Sánchez-Rovira, P. Improved statistical inference in omics analysis with Variable-selection Anova Simultaneous Component Analysis (VASCA). X Bioinformatics and Genomics Symposium, Valencia (Spain), 2022.
- Wasielewska, K., Cejka, T., Soukup, D., Camacho, J. Evaluation of Detection Limit in Network Dataset Quality Assessment with Permutation Testing. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML-PKDD 2022, 4th Workshop on Machine Learning for Cybersecurity (MLCS), Grenoble (France), 2022.
- Camacho, J., Díaz, C., Sánchez-Rovira, P. Analyzing omics data from clinical interventions with ASCA. SEIO 2022, Granada (Spain), 2022.
- Villar-Argaiz, M., et al. The heat is on: Rising trend in water temperature of high mountain lakes with variable depth and geomorphometric features. International Mountain Conference, Innsbruck (Austria), 2022.
- Villar-Argaiz, M., et al. Citizen Science in Sierra Nevada: a necessary step forward in mountain water research and conservation. International Mountain Conference, Innsbruck (Austria), 2022.
- Camacho, J., Wasielewska, K. Dataset Quality Assessment in Autonomous Networks with Permutation Testing. Seventh IEEE/IFIP International Workshop on Analytics for Network and Service Management, Bucarest (Hungary), 2022.
- Cuberos, F., Herrera, I., Wasielewska, K., Camacho, J. Network Tomography and Partial Least Squares for Traffic Matrix Estimation. Poster. 17th International Conference on Network and Service Management (CNSM 2021), Izmir (Turkey), 2021. Presentation
- Mañas-Martinez, E., Cabrera, E., Wasielewska, K., Kotz, D., Camacho, J. Mining Social Interactions in Connection Traces of a Campus Wi-Fi Network. Poster. ACM SIGCOMM'21, Online (), 2021. Poster | Abstract
- Peters, T., Pierson, T., Sen, S., Camacho, J., Kotz, D. Recurring Verification of Interaction Authenticity Within Wireless Networks. 14th ACM Conference on Security and Privacy in Wireless and Mobile Networks (WiSec 2021), Abu Dabhi (UAE), 2021.
- Gómez-Hernández, J., García-Teodoro, P., Holgado-Terriza, J., Maciá-Fernández, G., Camacho, J., Noguera-Comino, J. Monitoring Android Communications for Security. Poster. IEEE INFOCOM, Online (), 2021.
- Gómez-Hernández, J., García-Teodoro, P., Holgado-Terriza, J., Maciá-Fernández, G., Camacho, J. A Monitoring Multidimensional Feature Android Application to Secure Mobile Environments. 6th International Workshop on Traffic Measurements for Cybersecurity (WTMC 2021), Online (), 2021.
- Camacho, J. Machine Learning for Intrusion Detection in CyberDefense. South Tech Week, Granada (Spain), 2020.
- Camacho, J., Bro, R., Kotz, D. MBDA in Action. Network Traffic Measurement and Analysis Conference (TMA), Berlin (Germany), 2020. Presentation
- Fuentes-García, N.M., González-Martinez, J.M., Maciá-Fernández, G., Camacho, J. PARAMO: Enhanced Data Pre-processing in Batch Multivariate Statistical Process Control. Scandinavian Symposium on Chemometrics (SSC16), Oslo (Norway), 2019.
- Camacho, J., Acar, E., Rasmunssen, M., Bro, R. X-CAN: Cross-Penalized Component Analysis. Scandinavian Symposium on Chemometrics (SSC16), Oslo (Norway), 2019. Presentation
- Camacho, J., Smilde, A.K., Saccenti, E., Westerhuis, J.A. All sparse PCA models are wrong, but some are useful. Scandinavian Symposium on Chemometrics (SSC16), Oslo (Norway), 2019. Presentation
- Camacho, J. Multivariate Statistical Control in the Big Data Context. II Arctic Analysis, (Iceland), 2018.
- González-Martinez, J.M., Fuentes-García, N.M., Camacho, J., Maciá-Fernández, G. Parameter stability and its effects on bilinear modelling of batch processes. Mini Arctic Workshop, Valencia (Spain), 2017.
- Camacho, J., Saccenti, E., González-Martinez, J.M. Cross validation in Sparse PLS. Mini Arctic Workshop, Valencia (Spain), 2017.
- Arteaga, F., Camacho, J., Ferrer, A.J. Orthogonal Procrustes Problem to generate multivariate datasets by simultaneously controlling the covariances structure and the rows distribution. Mini Arctic Workshop, Valencia (Spain), 2017.
- Tortorella, S., Camacho, J. GPCA for improved multivariate analysis interpretation in lipidomics. Wenvomics, Barcelona (Spain), 2017.
- Therón, R., Magán-Carrión, R., Camacho, J., Maciá-Fernández, G. Network-wide intrusion detection supported by multivariate analysis and interactive visualization. VizSec, Phoenix (USA), 2017.
- Fuentes-García, N.M., Maciá-Fernández, G., Camacho, J. A Univariate Approach for Diagnosis in PCA-MSPC. Scandinavian Symposium on Chemometrics (SSC15), Naantali (Finland), 2017.
- Camacho, J., Saccenti, E., Therón, R. Group-wise Principal Component Analysis. Scandinavian Symposium on Chemometrics (SSC15), Naantali (Finland), 2017. Presentation
- Camacho, J., García-Teodoro, P., Maciá-Fernández, G. Traffic Monitoring and Diagnosis with Multivariate Statistical Network Monitoring: A Case Study. IEEE Security & Privacy International Workshop on Traffic Measurements for Cybersecurity (WTMC 2017), San Jose, California (USA), 2017. Presentation
- Camacho, J., Therón, R., Magán-Carrión, R. Exploratory Analysis on Big Data using the MEDA ToolboxPresent and Future. Mini Arctic Workshop, Groningen (Netherlands), 2016. Presentation
- Maciá-Fernández, G., Camacho, J., García-Teodoro, P., Rodríguez-Gómez, R. Hierarchical PCA-Based Multivariate Statistical Network Monitoring for Anomaly Detection. 8th IEEE International Workshop on Information Forensics and Security (WIFS), Abu Dhabi (UAE), 2016.
- Iturbe, M., Camacho, J., Garitano, I., Zurutuza, U., Uribeetxeberria, R. On the Feasibility of Distinguishing Between Process Disturbances and Intrusions in Process Control Systems using Multivariate Statistical Process Control. The 3rd International Workshop on Reliability and Security Aspects for Critical Infrastructure, Tolouse (France), 2016.
- Therón, R., Camacho, J. Visual Steering in Multivariate Exploratory Data Analysis. 16th Chemometrics in Analytical Chemistry, Barcelona (Spain), 2016.
- Fuentes-García, N.M., Camacho, J., Maciá-Fernández, G. Fault Diagnosis : Contribution plots Vs oMEDA. 16th Chemometrics in Analytical Chemistry, Barcelona (Spain), 2016.
- Magán-Carrión, R., Camacho, J., García-Teodoro, P., Flushing, E., Caro, G. DRNS: Dynamical Relay Node Placement Solution. PAAMS, Sevilla (Spain), 2016.
- Camacho, J. Multivariate Big Data Analysis and its Application on Internet. Invited Keynote: 16th Chemometrics in Analytical Chemistry, Barcelona (Spain), 2016. Presentation
- Camacho, J., Maciá-Fernández, G., García-Teodoro, P., Therón, R. Exploratory Analysis in Big Data based on PCA and PLS. Invited Keynote: 14th Scandinavian Symposium on Chemometrics, Sardinia (Italy), 2015. Presentation
- Camacho, J., Maciá-Fernández, G., Díaz-Verdejo, J., García-Teodoro, P. Tackling the Big Data 4 Vs for Anomaly Detection. INFOCOM'2014 Workshop on Security and Privacy in Big Data, Toronto (Canada), 2014.
- Maciá-Fernández, G., Camacho, J., García-Teodoro, P. A Multiagent Self-healing System against Security Incidents in MANETs. Workshop on Active Security through Multi-Agent Systems (WASMAS), Salamanca (Spain), 2014.
- Magán-Carrión, R., Pulido, F., Camacho, J., García-Teodoro, P. Tampered Data Recovery in WSNs through Dynamic PCA and Variable Routing Strategies. ICCNS - Journal of Communications, Vol. 8, November, (), 2013, pp:738-750.
- Magán-Carrión, R., Camacho, J., García-Teodoro, P. A Security Response Approach Based on the Deployment of Mobile Agents: A Practical Vision. 11th International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS 2013), Salamanca (Spain), 2013.
- Magán-Carrión, R., Camacho, J., García-Teodoro, P. A Security Response Approach based on the Deployment of Mobile Agents. 11th International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS 2013), Salamanca (Spain), 2013.
- Camacho, J., Padilla, P., Salcedo-Campos, F.J., Díaz-Verdejo, J., García-Teodoro, P. Pair-wise Similarity Criteria for Flows Identification in P2P/non-P2P Traffic Classification. The Third International Conference on Advances in P2P Systems, Lisbon (Portugal), 2011.
- Camacho, J., Padilla, P., Díaz-Verdejo, J. Exploratory data analysis: a latent subspace approach. 5th International Chemometrics Research Meeting, Berg en Dal (Netherlands), 2011.
- Ferrer, A.J., Camacho, J., González-Martinez, J.M. Issues on Batch Multi-Variate Statistical Process Control. Eastern Analytical Symposium and Exposition, Somerset (USA), 2010.
- Camacho, J., Picó, J., Ferrer, A.J. Crossvalidation in Principal Component Analysis: searching for the best approach. 12th Conference on Chemometrics in Analytical Chemistry, Anvers (Belgium), 2010.
- Camacho, J., Bondía, J., Vehí, J., Fernández-Real, J.M. Application of missing data methods for exploratory data analysis in medical research. VII Colloquium Mediterraneum, Granada (Spain), 2010.
- Camacho, J., Díaz-Verdejo, J. Principal Component Analysis for very large data sets. VII Colloquium Mediterraneum, Granada (Spain), 2010.
- Camacho, J., Picó, J., Ferrer, A.J. Data Understanding with Principal Component Analysis. 11th Scandinavian Symposium on Chemometrics, Loen/Stryn (Norway), 2009.
- Camacho, J., Picó, J., Ferrer, A.J. Covariance Maps for Batch Process Modelling. 11th Scandinavian Symposium on Chemometrics, Loen/Stryn (Norway), 2009.
- Camacho, J., Picó, J., Ferrer, A.J. Multi-phase analysis framework: pattern recognition for batch process modelling. IFPAC, Baltimore (USA), 2009. Presentation
- Camacho, J., Picó, J., Ferrer, A.J. Run-to-run optimization of fed-batch processes with unfold-PLS. IFPAC, Baltimore (USA), 2009. Presentation
- Camacho, J., Picó, J., Ferrer, A.J. On-line monitoring of batch processes: Does the modelling structure matter?. 11th Conference on Chemometrics in Analytical Chemistry, Montpellier (France), 2008. Presentation | Abstract
- Camacho, J., Picó, J., Ferrer, A.J. Leave-n-Samples-Out Cross-validation in PCA for Missing Data Recovery and Robustness in front of Measurement Noise. 11thconference on Chemometrics in Analytical Chemistry, Montpellier (France), 2008. Poster | Abstract
- Camacho, J. New Methods Based on the Projection to Latent Structures for Monitoring, Prediction and Optimization of Batch Processes. Invited Presentation. 9th Belgian Chemometrics Symposium, Gembloux (Belgium), 2008. Presentation
- Camacho, J., Picó, J., Ferrer, A.J. New advances in the on-line monitoring of batch processes. IFPAC, Baltimore (USA), 2008. Abstract
- Camacho, J., Picó, J., Ferrer, A.J. A new algorithm for selecting the unfolding method and the number of sub-models in batch process modelling with PCA. 10th Scandinavian Symposium on Chemometrics, Laapperanta (Finland), 2007. Poster | Abstract
- Camacho, J., Picó, J., Ferrer, A.J. New Cross-Validation Methods in Principal Component Analysis. 10th Scandinavian Symposium on Chemometrics, Laapperanta (Finland), 2007. Poster | Abstract
- Camacho, J., Picó, J., Ferrer, A.J. A new look at the dynamic covariance structure of various approaches for batch process modelling. 10th Scandinavian Symposium on Chemometrics, Laapperanta (Finland), 2007. Poster | Abstract
- Camacho, J., Picó, J., Ferrer, A.J. Multi-Phase Analysis Framework for Handling Batch Process Data. 10th Scandinavian Symposium on Chemometrics, Laapperanta (Finland), 2007. Presentation | Abstract
- Camacho, J., de Molina, R.M., Martín, E., Mellado, M. Implementing a Cooperative Framework among Bio-inspired Robots based on Phonotaxis. Multi Agent Robotic Systems, International Conference on Informatics in Control, Automation and Robotics, Barcelona (Spain), 2005, pp:31-38.
- Camacho, J., de Molina, R.M., Martín, E. Control Adaptativo para el Seguimiento de Robots. Workshop en Agentes Físicos (Congreso Español De Informática), Granada (Spain), 2005, pp:101-108.
- Mellado, M., Correcher, C., de Molina, R.M., Camacho, J., Benet, G. Simulation of mobile robot applications with VirtualRobot. International Industrial Simulation Conference, Berlin (Germany), 2005, pp:68-72.
Books
- Armstrong, M.S., Camacho, J. Replicate analysis for uncertainty estimation in PARAFAC and PARAFASCA analyses of factorial metabolomics data.. In A. Olivieri, G. M. Escandar, H. C. Goicoechea, A. Muñoz de la Peña's Fundamental and Applications of Multiway Data Analysis. 2024.
- Saccenti, E., Camacho, J. Multivariate exploratory data analysis using component models.. Reference Module in Food Science. Elsevier. ISBN 9780081005965. 2020.
- Camacho, J., Saccenti, E. Chemometrics Analysis of Big Data. Comprehensive Chemometrics, Chemical and Biochemical Data Anlalysis, Second Ed.. Elsevier. ISBN 9780444641656. 2020.
- Camacho, J. Exploratory Data Analysis using latent subspace models. Chemometrics in Practical Appliations. INTECH. ISBN 978-953-51-0438-4. Pages 63 - 90. 2012.
Thesis
The present Thesis is devoted to the study and application of new methods based on the projection to latent structures to batch processes. The potential economic profit and safety and ecological benefit in the improvement of the modelling, monitoring and control of these processes is widely accepted in both the academic and industrial fields.
The document has been structured in three blocks. Firstly, the related literature is revised and summarized in an introductory part. The principal projection to latent structures methods are presented using a comprehensive common nomenclature. Also, the main contributions in the literature for the modelling, monitoring and control of batch processes are discussed.
In the second block of the document, the general features of batch process data and the basis of the methods based on the projection to latent structures are studied. The study, as the rest of the Thesis, is limited to bilinear modelling approaches. This allows to observe the limitations of these modelling methods when applied to batch processes, some of which are stated here for the first time. In this block, a first theoretical analysis is carried out to investigate the dynamic covariance structures of different modelling approaches. The conclusion of this analysis is that the multi-phase modelling structure has a nice feature which makes it specially attractive for batch process modelling: the flexibility to adjust to the process nature. Multi-phase and single-phase processes, with short or long term dynamics -or even combination of both- can be effectively modelled with the multi-phase structure. The second step in this block of the document is to investigate one of the most widely used strategies to set the parameters of the projection to latent structures methods: cross-validation. New algorithms for cross-validation are proposed and extended to the batch process data case. This step is of vital importance for the development of an automatic modelling algorithm for batch data. This algorithm is presented in the last part of this second block of the Thesis. The algorithm, named Multi-phase algorithm, has been designed together with a set of tools to analyze and handle multi-phase models: the Multi-phase Framework. This framework is a modelling approach which combines the automatic recognition capabilities of the algorithms from the field of Computer Science with the well-founded data analysis from the field of Statistics.
After the study of the modelling of batch processes, several applications where this modelling is necessary are investigated in the last block of the document. The problems addressed are: the off-line and on-line monitoring, the on-line end-quality prediction, the on-line estimation of batch trajectories and the process optimization. All these problems share the common feature that batch processes are difficult to understand and to model. Nonetheless, each of the problems studied presents its particularities, which need to be addressed independently. The contributions in each of the applications go beyond the use of the new modelling approach. In both the off-line and on-line monitoring of batch processes, several improvements in the development of the monitoring system are suggested. In the on-line end-quality prediction and estimation of trajectories, a broad comparison among several modelling approaches is supplied. Finally, a new optimization algorithm, based on the combination of self-tuning extremum seeking and projection to latent structures methods, is proposed.