investigacion

investigacion

investigacion

Revistas especializadas y libros

2019

·       Valle, C., Ñanculef, R., Allende, H., Moraga, C. LocalBoost: A Parallelizable Approach to Boosting Classifiers (2019) Neural Processing Letters, 50 (1), pp. 19-41.

·       Araya, I.A., Valle, C., Allende, H. A Multi-Scale Model based on the Long Short-Term Memory for day ahead hourly wind speed forecasting (2019) Pattern Recognition Letters.

·       Solis, M.A., Olivares, M., Allende, H. A switched control strategy for swing-up and state regulation for the rotary inverted pendulum (2019) Studies in Informatics and Control, 28 (1), pp. 45-54.

·       Gómez-Álvarez, M.C., Jaramillo, C.M.Z., Astudillo, H. SETMAT (Software engineering teaching method and theory): A theory of software engineering teaching (2019) RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao, 2019 (19), pp. 721-734.

·       Hitpass, B., Astudillo, H. Editorial: Industry 4.0 challenges for business process management and electronic-commerce (2019) Journal of Theoretical and Applied Electronic Commerce Research, 14 (1), pp. I-III.

·       Soto, R., Crawford, B., Lanza-Gutierrez, J.M., Olivares, R., Camacho, P., Astorga, G., de la Fuente-Mella, H., Paredes, F., Castro, C. Solving the manufacturing cell design problem through an autonomous water cycle algorithm (2019) Applied Sciences (Switzerland), 9 (22), art. no. 4736.

·       Crawford, B., Soto, R., Olivares, R., Riquelme, L., Astorga, G., Johnson, F., Cortés, E., Castro, C., Paredes, F. A self-adaptive biogeography-based algorithm to solve the set covering problem (2019) RAIRO - Operations Research, 53 (3), pp. 1033-1059.

·       Soto, R., Crawford, B., Gonzalez, F., Vega, E., Castro, C., Paredes, F. Solving the Manufacturing Cell Design Problem Using Human Behavior-Based Algorithm Supported by Autonomous Search (2019) IEEE Access, 7, art. no. 8827495, pp. 132228-132239.

·       Soto, R., Crawford, B., Toledo, A.A., De la Fuente-Mella, H., Castro, C., Paredes, F., Olivares, R. Solving the manufacturing cell design problem through binary cat swarm optimization with dynamic mixture ratios (2019) Computational Intelligence and Neuroscience, 2019, art. no. 4787856.

·       Crawford, B., Soto, R., Olivares, R., Embry, G., Flores, D., Palma, W., Castro, C., Paredes, F., Rubio, J.-M. A binary monkey search algorithm variation for solving the set covering problem (2019) Natural Computing.

·       Lopez, C., De Souza, C., Gaytan, S., Gutierrez, F.J. CSCW research @Latin America (2019) Interactions, 26 (5), pp. 6-7.

·       Fierro, S.L., Montenegro, G., López, C. Towards a conceptual framework to measure the impact of computational thinking on college students’ mathematics learning [Hacia un marco conceptual para medir el impacto del pensamiento computacional en el aprendizaje de matemáticas en estudiantes universitarios] (2019) RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao, 2019 (19), pp. 619-631.

·       Guellil, I., Azouaou, F., Mendoza, M. Arabic sentiment analysis: studies, resources, and tools (2019) Social Network Analysis and Mining, 9 (1), art. no. 56.

·       Mendoza, M., Poblete, B., Valderrama, I. Nowcasting earthquake damages with Twitter (2019) EPJ Data Science, 8 (1), art. no. 3.

·       Torres, N., Mendoza, M. Clustering approaches for top-k recommender systems (2019) International Journal on Artificial Intelligence Tools, 28 (5).

·       Mendoza, M., Velastín, S.A. Preface of Special section—CIARP 2017 awards (2019) Pattern Recognition Letters, 123, p. 96.

·       Mendoza, M., Torres, N. Evaluating content novelty in recommender systems (2019) Journal of Intelligent Information Systems.

·       Zamora, J., Allende-Cid, H., Mendoza, M. Distributed Clustering of Text Collections (2019) IEEE Access, 7, art. no. 8882328, pp. 155671-155685.

·       Montero, E., Riff, M.-C. Effective collaborative strategies to setup tuners (2019) Soft Computing.

·       Menchaca-Mendez, A., Montero, E., Antonio, L.M., Zapotecas-Martinez, S., Coello Coello, C.A.C., Riff, M.-C. A Co-Evolutionary Scheme for Multi-Objective Evolutionary Algorithms Based on ϵ-Dominance (2019) IEEE Access, 7, art. no. 8637162, pp. 18267-18283.

·       Arce, P., Antognini, J., Kristjanpoller, W., Salinas, L. Fast and Adaptive Cointegration Based Model for Forecasting High Frequency Financial Time Series (2019) Computational Economics, 54 (1), pp. 99-112.

·       Fernández, C., Salinas, L., Torres, C.E. A meta extreme learning machine method for forecasting financial time series (2019) Applied Intelligence, 49 (2), pp. 532-554.

·       Sazo, A.H.J., Ibarra S., P., Sanhueza R., A., Casas, F.J.A., Torres, C.E., Emelianenko, M., Golovaty, D. Evolution of two-dimensional grain boundary networks implemented in GPU (2019) Computational Materials Science, 160, pp. 315-333.

·       Villanueva, M., Araya, M., Torres, C.E., Amigo, P. HDMClouds: A hierarchical decomposition of molecular clouds based on Gaussian mixtures (2019) Monthly Notices of the Royal Astronomical Society, 482 (3), pp. 2878-2892.

·       Sazo, A.H.J., Torres, C.E., Emelianenko, M., Golovaty, D. A vertex model of recrystallization with stored energy implemented in GPU (2019) Materials Research Express, 6 (5), art. no. 055506.

2018

1. López, E., Valle, C., Allende, H., Gil, E., Madsen, H. Wind power forecasting based on Echo State Networks and Long Short-Term Memory (2018) Energies, 11 (3), art. no. 526

2. Valle, C., Ñanculef, R., Allende, H., Moraga, C. LocalBoost: A Parallelizable Approach to Boosting Classifiers (2018) Neural Processing Letters

3. Arroyuelo, D., Oyarzún, M., González, S., Sepulveda, V. Hybrid compression of inverted lists for reordered document collections (2018) Information Processing and Management, 54 (6), pp. 1308-1324.

4. Torres, R., Salas, R., Bencomo, N., Astudillo, H. An architecture based on computing with words to support runtime reconfiguration decisions of service-based systems (2018) International Journal of Computational Intelligence Systems, 11 (1), pp. 272-281.

5. Crawford, B., Soto, R., Astorga, G., Castro, C., Paredes, F., Misra, S., Rubio, J.-M. Solving the software project scheduling problem using intelligent water drops (2018) Tehnicki Vjesnik, 25 (2), pp. 350-357.

6. García, J., Crawford, B., Soto, R., Castro, C., Paredes, F. A k-means binarization framework applied to multidimensional knapsack problem (2018) Applied Intelligence, 48 (2), pp. 357-380.

7. Crawford, B., Soto, R., San Martín, M.A., De La Fuente-Mella, H., Castro, C., Paredes, F. Automatic High-Frequency Trading: An Application to Emerging Chilean Stock Market (2018) Scientific Programming, 2018, art. no. 8721246,

8. Soto, R., Crawford, B., Olivares, R., Taramasco, C., Figueroa, I., Gómez, Á., Castro, C., Paredes, F. Adaptive black hole algorithm for solving the set covering problem (2018) Mathematical Problems in Engineering, 2018, art. no. 2183214

9. Araya, M., Mendoza, M., Solar, M., Mardones, D., Bayo, A. Unsupervised learning of structure in spectroscopic cubes (2018) Astronomy and Computing, 24, pp. 25-35.

10. Montero, E., Riff, M.-C., Rojas-Morales, N. Tuners review: How crucial are set-up values to find effective parameter values? (2018) Engineering Applications of Artificial Intelligence, 76, pp. 108-118.

11. Hidalgo, N., Rosas, E., Vasquez, C., Wladdimiro, D. Measuring stream processing systems adaptability under dynamic workloads (2018) Future Generation Computer Systems, 88, pp. 413-423.

12. Baixeries, J., Codocedo, V., Kaytoue, M., Napoli, A. Characterizing approximate-matching dependencies in formal concept analysis with pattern structures (2018) Discrete Applied Mathematics, 249, pp. 18-27.

13. Farias, H., Nuñez, C., Solar, M. TensorFit a tool to analyse spectral cubes in a tensor mode (2018) Astronomy and Computing, 25, pp. 195-202.

14. Solar, M., Bayo, A., Lorente, N., Pichara, K. Astronomical data analysis software and systems (2018) Astronomy and Computing, 25, pp. 203-204.

15. Araya, M., Osorio, M., Díaz, M., Ponce, C., Villanueva, M., Valenzuela, C., Solar, M. JOVIAL: Notebook-based astronomical data analysis in the cloud (2018) Astronomy and Computing, 25, pp. 110-117.

16. Salinas, Á., Torres, C.E., Ayala, O. Well-balanced open boundary condition in a lattice Boltzmann model for shallow water with arbitrary bathymetry (2018) Computer Physics Communications, 230, pp. 89-98.

17. Bakan, A., Ruscheweyh, S., Salinas, L. On geometric properties of the generating function for the Ramanujan sequence (2018) Ramanujan Journal, 46 (1), pp. 173-188.

18. Maldonado, D., Gajardo, A., De Menibus, B.H., Moreira, A. Nontrivial turmites are turing-universal (2018) Journal of Cellular Automata, 13 (5-6), pp. 373-392.

2017

1. Allende, H., Valle, C., Ensemble methods for time series forecasting, Studies in Fuzziness and Soft Computing , 349, pp. 217-232

2. Crawford, B., Soto, R., Astorga, G., Castro, C., Paredes, F., Putting continuous metaheuristics to work in binary search spaces, Complexity 2017,8404231

3. García, J., Crawford, B., Soto, R., Castro, C., Paredes, F., A k-means binarization framework applied to multidimensional knapsack problem, Applied Intelligence , pp. 1-24

4. Rohan, P.-Y., Lobos, C., Nazari, M.A., Perrier, P., Payan, Y., Finite element models of the human tongue: a mixed-element mesh approach, Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization , 5(6), pp. 390-400

5. Rojas-Morales, N., Riff, M.-C., Montero, E., A survey and classification of Opposition-Based Metaheuristics, Computers and Industrial Engineering , 110, pp. 424-435

6. Rojas-Morales, N., Riff, M.-C., Improving harmony search algorithms by using tonal variation: the case of Sudoku and MKP, Connection Science , pp. 1-27

7. Rojas-Moraleda, R., Xiong, W., Halama, N., Salinas, L., Heermann, D.W., Valous, N.A., Robust detection and segmentation of cell nuclei in biomedical images based on a computational topology framework, Medical Image Analysis , 38, pp. 90-103

8. Rojas-Moraleda, R., Valous, N.A., Gowen, A., Salinas, L., O’Donnell, C., A frame-based ANN for classification of hyperspectral images: assessment of mechanical damage in mushrooms, Neural Computing and Applications , 28, pp. 969-981

9. Bakan, A., Ruscheweyh, S., Salinas, L., On geometric properties of the generating function for the Ramanujan sequence, Ramanujan Journal , pp. 1-16

10. Arce, P., Antognini, J., Kristjanpoller, W., Salinas, L., Fast and Adaptive Cointegration Based Model for Forecasting High Frequency Financial Time Series, Computational Economics , pp. 1-14

11. Vandenbussche, P.-Y., Umbrich, J., Matteis, L., Hogan, A., Buil-Aranda, C., SPARQLES: Monitoring public SPARQL endpoints, Semantic Web , 8(6), pp. 1049-1065

12. Brusilovsky, P., Oh, J.S., López, C., Parra, D., Jeng, W, Linking information and people in a social system for academic conferences, New Review of Hypermedia and Multimedia , 23(2), pp. 81-111

 

2016

1. Allende-Cid, H., Valle, C., Moraga, C., Allende, H., Salas, R., Improving the weighted distribution estimation for AdaBoost using a novel concurrent approach, Studies in Computational Intelligence , 616, pp. 223-232

2. Solis, M.A., Olivares, M., Allende, H., Stabilizing dynamic state feedback controller synthesis: A reinforcement learning approach, Studies in Informatics and Control , 25(2), pp. 245-254

3. Allende-Cid, H., Monge, R., Allende, H., Soft computing applied to distributed regression with context-heterogeneity, Journal of Multiple-Valued Logic and Soft Computing , 26(3-5), pp. 389-416

4. Allende-Cid, H., Salas, R., Veloz, A., Moraga, C., Allende, H. , SONFIS: Structure Identification and Modeling with a Self-Organizing Neuro-Fuzzy Inference System, International Journal of Computational Intelligence Systems , 9(3), pp. 416-432

5. Veloz, A., Salas, R., Allende-Cid, H., Allende, H., Moraga, C., Identification of Lags in Nonlinear Autoregressive Time Series Using a Flexible Fuzzy Model, Neural Processing Letters 43(3), pp. 641-666

6. Mardones, T., Allende, H., Moraga, C., Leveraging similarities and structure for dense representations combination in image retrieval, Journal of Visual Communication and Image Representation , 38, pp. 641-657

7. Zamora, J., Mendoza, M., Allende, H., Hashing-based clustering in high dimensional data, Expert Systems with Applications , 62, pp. 202-211

8. Arroyuelo, D., Davoodi, P., Satti, S.R., Succinct Dynamic Cardinal Trees, Algorithmica 74(2), pp. 742-777

9. Génova, G., Astudillo, H., Fraga, A., The Scientometric Bubble Considered Harmful, Science and Engineering Ethics , 22(1), pp. 227-235

10. Hidalgo, N., Arantes, L., Sens, P., Bonnaire, X., ECHO: Efficient Complex Query over DHT Overlays, Journal of Parallel and Distributed Computing , 88, pp. 31-45

11. Soto, R., Crawford, B., Palma, W., Galleguillos, K., Castro, C., Monfroy, E., Johnson, F., Paredes, F., Using autonomous search for solving constraint satisfaction problems via new modern approaches, Swarm and Evolutionary Computation, 30, pp. 64-77

Diverse: An R package to measure diversity in complex systems. R Journal, 8(2):60-78.

The Research Space: using career paths to predict the evolution of the research output of individuals, institutions, and nations. Scientometrics, 109(3):1695-1709, Springer.

Reducing Hardware Hit by Queries in Web Search Engines. Information Processing & Management, 52(6):1031-1052, Elsevier.

Indexing Data Cubes for Content-based Searches in Radio Astronomy. Astronomy and Computing, 14:23-34, Elsevier

16. Fernandez, E.B., Monge, R., Hashizume, K., Building a security reference architecture for cloud systems, Requirements Engineering , 21(2), pp. 225-249

17. Frandi, E., Ñanculef, R., Lodi, S., Sartori, C., Suykens, J.A.K., Fast and scalable Lasso via stochastic Frank–Wolfe methods with a convergence guarantee, Machine Learning , 104(2-3), pp. 195-221

18. Cares, J.P., Riff, M.-C., Neveu, B., GeneRa: A problem generator for radiotherapy treatment scheduling problems, Annals of Mathematics and Artificial Intelligence , 76(1-2), pp. 191-214

19. Riff, M.-C., Cares, J.P., Neveu, B., RASON: A new approach to the scheduling radiotherapy problem that considers the current waiting times, Expert Systems with Applications , 64, pp. 287-295

20. Pezoa, R., Salinas, L., Torres, C.,, Maureira-Fredes, C., Arce, P. , Segmentation of HER2 protein overexpression in immunohistochemically stained breast cancer images using Support Vector Machines, Journal of Physics: Conference Series , 762(1),012050

21. Solar, M., Michelon, P., Avarias, J., Garces, M. , A scheduling model for astronomy, Astronomy and Computing , 15, pp. 90-104

22. Loyola, C., Sepúlveda, M., Solar, M., Lopez, P., Parada, V., Automatic design of algorithms for the traveling salesman problem, Cogent Engineering , 3(1),1255165

23. Yegorov, I., Torres, C.E., Emelianenko, M., A Boltzmann-type kinetic model for misorientation distribution functions in two-dimensional fiber-texture polycrystalline grain growth, Acta Materialia, 109, pp. 230-247

 

2015

Allende-Cid, H., Allende, H., Monge, R., Moraga, C., Discrete neighborhood representations and modified stacked generalization methods for distributed regression, Journal of Universal Computer Science , 21(6), pp. 842-855

Allende-Cid, H., Allende, H., Monge, R., Moraga, C., Regression from distributed data sources using discrete neighborhood representations and modified stalked generalization models, Studies in Computational Intelligence , 570, pp. 249-258

Arroyuelo, D., Claude, F., Maneth, S.Sirén, J., Välimäki, N., Fast in-memory XPath search using compressed indexes, Software - Practice and Experience , 45(3), pp. 399-434

Crawford, B., Soto, R., Berríos, N., Castro, C., Norero, E., A Binary Cat Swarm Optimization Algorithm for the Non-Unicost Set Covering Problem, Mathematical Problems in Engineering , 578541

Soto, R., Crawford, B., Palma, W., Castro, C., Paredes, F., Top-k based adaptive enumeration in constraint programming, Mathematical Problems in Engineering, 580785

Soto, R., Crawford, B., Palma, W., Galleguillos, K., Castro, C., Monfroy, E., Johnson, F., Paredes, F., Boosting autonomous search for CSPs via skylines, Information Sciences , 308, pp. 38-48

Lobos, C., González, E., Mixed-element Octree: A meshing technique toward fast and real-time simulations in biomedical applications, International Journal for Numerical Methods in Biomedical Engineering , 31(12),e02725

Pérez-Cáceres, L., Riff, M.C., Solving scheduling tournament problems using a new version of CLONALG, Connection Science , 27(1), pp. 5-21

Bakan, A., Ruscheweyh, S., Salinas, L., Universal convexity and universal starlikeness of polylogarithms, Proceedings of the American Mathematical Society , 143(2), pp. 717-729

Araya, M., Solar, M., Antognini, J., A brief survey on the Virtual Observatory, New Astronomy 39, pp. 46-54

Torres, C.E., Emelianenko, M., Golovaty, D., Kinderlehrer, D., Ta'Asan, S., Numerical analysis of the vertex models for simulating grain boundary networks, SIAM Journal of Applied Mathematics, 75(2), pp. 762-786

 

 

2014

1. J. Zamora, M. Mendoza, H. Allende, “Query Intent Detection Based on Query Log Mining”, Journal of Web Engineering; Vol. 13(1-2), pp. 24-52; Mar. 2014

2. R. Ñanculef, E. Frandi, C. Sartori, H. Allende, “A novel Frank-Wolfe algorithm. Analysis and applications to large-scale SVM training”, Information Sciences; Vol. 285, pp. 66-99; 2014

3. G. Ulloa, H. Allende-Cid, H. Allende, “Robust Sieve Bootstrap Prediction Intervals for Contaminated Time Series”, International Journal of Pattern Recognition and Artificial Intelligence; Vol. 28(7), art. 1460012(14); 2014

4. D. Arroyuelo, C. Bonacic, V. Gil-Costa, M. Marín, G. Navarro, “Distributed text search using sufflix arrays”, Parallel Computing; Vol 40, pp. 471-495; 2014

5. R. Torres, R. Salas, H. Astudillo, “Time-Based Hesitant Fuzzy Information Aggregation Approach for Decision-Making Problems”, International Journal of Intelligent Systems; Vol. 29, pp. 579-595; 2014

6. R. Torres, H. Astudillo, “A Market-Based Approach to the Dynamic Reconfiguration Problem of Service-Based Systems”, International Journal of Innovative Computing; Vol. 10 N° 1, pp. 115-132; February 2014

7. R. Mora, H. Astudillo, S. Bravo, “Looking ahead: A vision-based software for predicting pedestrian movement”, Ingeniería e Investigación; Vol. 34 (1), pp. 79-82; Apr. 2014

8. J. Atkinson, A. González, M. Muñoz, H. Astudillo, “Web metadata extraction and semantic indexing for learning objects extraction”, Applied Intelligence; Vol. 41(2), pp. 649-664; Sept. 2014

9. R. Soto, B. Crawford, S. Misra, E. Monfroy, W. Palma, C. Castro, F. Paredes, “Constraint Programming for Optimal Design of Arquitectures for Water Distribution Tanks and Reservoirs: A Case Study”, Tehnicki Vjesnik-Technical Gazette; Vol. 21(1), pp. 99- 105; 2014

10. P.Y. Rohan, C. Lobos, M. Ali Nazari, P. Perrier, Y. Payan, “Finite element modelling of nearly incompressible materials and volumetric locking: A case study”, Computers Methods in Biomechanics and Biomedical Engineering; Vol. 17 N° S1, pp. 192-193; 2014

11. F. Bravo, M. Mendoza, B. Poblete, “Meta-level sentiment models for big social data analysis”, Knowledge-Based Systems; Vol. 69, pp. 86-99; 2014

12. R. Ñanculef, I. Flaounas, N. Cristianini, “Efficient classification of multi-labeled text streams by clashing”, Expert Systems with Applications; Vol. 41, pp. 5431-5450; 2014

13. I. Araya, M.C. Riff, “A beam search approach to the container loading problem”, Computers & Operations Research; Vol. 43, pp. 100-107; 2014

14. E. Montero, M.C. Riff, B. Neveu, “A beginner’s guide to tuning methods”, Applied Soft Computing; Vol. 17, pp. 39-51; 2014

15. I. Araya, M.C. Riff, “A filtering method for algorithm configuration based on consistency techniques”, Knowledge-Based Systems; Vol. 60, pp. 73-81; 2014

16. G. Hernández, R. Plaza, L. Salinas, “Heuristic quadratic approximation for the universality theorem”, Cluster Computing – Journal of Networks Software Tools and Applications, Vol. 17 (2), pp. 281-289; June 2014

17. M. Solar, F. Daniels, R. López, L. Meijueiro, “A Model to Guide the Open Government Data Implementation in Public Agencies”, Journal of Universal Computer Science; Vol. 20(11), pp. 1564-1582; 2014

18. M. Solar, F. Daniels, R. Lopez, “Automatic Generation of Roadmaps for Open Data”, Chapter Ebook Electronic Government and Electronic Participation, M.F.W.H.A. Janssen et al. (Eds.), IOS Press; Vol. 21, pp. 95-105, 2014

19. A. Zamyatnin, O.L. Voronina, “Fragmentomics of Hemoglobin”, Journal of Peptide Science; Vol. 20 S1, p. S294; Sept. 2014

20. A. Zamyatnin, A.S. Borchikov, “Mathematical principles of protein fragmentomics”, Journal of Peptide Science; Vol. 20 S1, pp. S293-S294; Sept. 2014

 

2013

1. F. Ramírez, H. Allende, “Detection of Flaws in Aluminium Castings: A Comparative Study between Generative and Discriminant Approaches”, Insight: Non-Destructive Testing and Condition Monitoring; Vol. 55(7), pp. 366-371; July 2013

2. X. Bonnaire, “Fixed Interval Nodes Estimation: An Accurate and Low Cost Algorithm to Estimate the Number of Nodes in Distributed Hash Tables”, Information Sciences; Vol. 218, pp. 165-181; 2013

3. X. Bonnaire, P. Sens, “Design Principles of Large-Scale Distributed System”, Chapter in Distributed Systems: Design and Algorithms, Wiley Online Library; pp. 33-57; Feb. 13, 2013

4. B. Crawford, R. Soto, E. Monfroy, W. Palma, C. Castro, F. Paredes, “Parameter Tuning of a Choice-function Based Hyperheuristic using Particle Swarm Optimization”, Expert Systems with Applications; Vol. 40, pp. 1690-1695; 2013

5. E. Monfroy, C. Castro, B. Crawford, R. Soto, F. Paredes, C. Figueroa, “A reactive and hybrid constraint solver”, Journal of Experimental & Theoretical Artificial Intelligence; Vol. 25(1), pp. 1-72; Mar. 1, 2013

6. R. Soto, B. Crawford, S. Misra, W. Palma, E. Monfroy, C. Castro, F. Paredes, “Choice functions for automomous search in constraint Programming: GA vs. PSO”, Tehnicki Vjesnik-Technical Gazette; Vol. 20(4), pp. 621-627; Aug. 2013

7. B. Crawford, R. Soto, E. Monfroy, C. Castro, W. Palma, F. Paredes, “A Hybrid Soft Computing approach for Subset Problems”, Mathematical Problems in Engineering; Vol. 2013, art. 7160069(12); 2013

8. B. Crawford, C. Castro, E. Monfroy, R. Soto, W. Palma, F. Paredes, “A Hyperheuristic Approach for Guiding Enumeration in Constraint Solving”, Advances in Intelligent Systems and Computing; Vol. 175, pp. 171-188; 2013

9. E. Dimnet, E. Haza-Rozier, G. Vincesias, R. León, G. Hernández, “Experimental and numerical study of a shock-absorbing structure”, Acta Mechanica; Vol. 224 (12), pp. 3037-3055; Dec 2013

10. C. Castillo, M. Mendoza, B. Poblete, “Predicting information credibility in time-sensitive social media”, Internet Research; Vol. 23(5), pp. 1-29; 2013

11. E. Frandi, R. Ñanculef, M.G. Grazia, S. Lodi, C. Sartori, “Training Support Vector Machines using Frank-Wolfe Optimization Methods”, International Journal of Pattern Recognition and Artificial Intelligence; Vol. 27(3), Art. 1360003; May 2013

12. M.C. Riff, E. Montero, B. Neveu, “Reducing Calibration Effort for Clonal Selection based Algorithms: A Reinforcement Learning Approach”, Knowledge-Based Systems; Vol. 41, pp. 54-67; Nov. 7-9, 2013

13. J. Simmonds, S. Ben-David, M. Chechik, “Monitoring and Recovery for Web Service Applications”, Computing; Vol. 95, pp. 223-267; 2013

14. J. Hurtado, M.C. Bastarrica, S. Ochoa, J. Simmonds, “MDE Software Process Lines in Small Companies”, Journal of Systems and Software; Vol. 86, pp. 1153-1171; 2013

15. M. Solar, J. Sabattin, V. Parada, “A Maturity Model for Assessing the Use of ICT in School Education”, Educational Technology & Society; Vol. 16(1), pp. 206-218; 2013

16. C.E. Torres, H. Parishani, O. Ayala, L.F. Rossi, L.-P. Wang, “Analysis and Parallel Implementation of a Forced N-body Problem”, Journal of Computational Physics; Vol. 245, pp. 235-258; 2013

2012

1. R. Ñanculef, C. Valle, H. Allende, C. Moraga, “Training Regression Ensembles by Sequential Target Correction and Resampling”, Information Science; Vol. 195, pp. 154-174; 2012

2. C. Fernández, C. Droop, H. Allende, “An Improved Genetic Algorithm for Robust Design in Multivariate Systems”, Quality and Quantity; Vol. 46 (2), pp. 665-678; 2012

3. E. Canessa, C. Valle, F. Saravia, H. Allende, “Behavior Analysis of Neural Network Ensemble Algorithm on a Virtual Machine Cluster”, Neural Computing & Applications; Vol. 21 Issue 3, pp. 535-542; 2012

4. E. Canessa, S. Vera, H. Allende, “A New Method for Estimating Missing Values for a Genetic Algorithm used in Robust Design”, Engineering Optimization; Vol. 44(7), pp. 787-800; 2012

5. I. Araya, B. Neveu, G. Trombettoni, “An Interval Extension Based on Occurrence Grouping”, Computing; Vol. 94, pp. 173-188; 2012

6. C. López, V. Codocedo, H. Astudillo, L.M. Cysneiros, “Bridging the Gap between Software Architecture Rationale Formalisms and Actual Architecture Documents: An Ontology-driven Approach”, Science of Computer Programming; Vol. 77(1), pp. 66-80; 2012.

7. G. Concha, H. Astudillo, M. Porrúa, C. Pimenta, “E-Government Procurement Observatory, Maturity Model and Early Measurements”, Government Information Quarterly; Vol. 29, pp. S43-S50; 2012

8. B. Crawford, C. Castro, E. Monfroy, R. Soto, W. Palma, F. Paredes, “A Hyperheuristic Approach for Guiding Enumeration in Constraint Solving”, Chapter in EVOLVE, A bridge between Probability, Set Oriented Numerics and Evolutionary Computation, ed. O. Schütze et al., Mexico City, Mexico; Vol. 175, pp. 171–188; 2012

9. P. Garrido, C. Castro, “A Flexible and Adaptive Hyper-heuristic Approach for (Dynamic) Capacitated Vehicle Routing Problems”, Fundamenta Informaticae; Vol. 119(1), pp. 29-60; 2012

10. B. Crawford, C. Castro, E. Monfroy, R. Soto, W. Palma, F. Paredes, “Dynamic Selection of Enumeration Strategies for Solving Constraint Satisfaction Problems”, Romanian Journal of Information Science and Technology; Vol. 15(2), pp. 106-128; 2012

11. T. Arredondo, D. Candel, M. Leiva, L. Dombrovskaia, L. Agulló, M. Seeger, “Inference System using Softcomputing and Mixed Data Applied in Metabolic Pathway Datamining”, International Journal of Data Mining and Bioinformatics; Vol. 6 Nº 1, pp. 61-85; 2012

12. P. Rodríguez, M. Nussbaum, L. Dombrovskaia, “ICT for Education: A Conceptual Framework for the Sustainable Adoption of Technology-enhanced Learning Environments in Schools”, Technology, Pedagogy and Education; Vol. 21 N° 3, pp. 291-315; October 2012

13. P. Rodríguez, M. Nussbaum, L. Dombrovskaia, “Evolutionary Development: A Model for the Design, Implementation and Evaluation of ICT for Education Programmes”, Journal of Computer Assisted Learning; Vol. 28, pp. 81-98; 2012

14. M. Solar, J. Rojas, M. Mendoza, R. Monge, V. Parada, “A Multiagent-Based Approach to the Grid-Scheduling Problem”, Special issue of best papers presented at CLEI 2011, Quito, Ecuador; CLEI Electronic Journal; Vol. 15 N° 2, paper 5(16); August 2012

15. M. Mendoza, “A New Term-weighting Scheme for Naïve Bayes Text Categorization”, International Journal of Web Information Systems; Vol. 8 N° 1, pp. 55-72; 2012

16. C. Valenzuela, B. Crawford, R. Soto, E. Monfroy, F. Paredes, “A 2-level Metaheuristic for the Set Covering Problem”, International Journal of Computers Communictions & Control; Vol. 7 (2), pp. 377-387; Jun. 2012

17. R. Soto, H. Kjellerstrand, O. Durán, B. Crawford, E. Monfroy, F. Paredes, “Cell formation in group technology using constraint programming and Boolean satisfiability”, Expert Systems with Applications; Vol. 39(13), pp. 11423-11427; Oct. 1, 2012

18. R. Soto, B. Crawford, E. Monfroy, F. Paredes, “Syntax Extensions for a Constrained-Object Language via Dynamic Parser Cooperation”, Studies in Informatics and Control; Vol. 21(1) SI, pp. 41-48; Mar. 2012

19. A. Gajardo, J. Kari, A. Moreira, “On Time-symmetry in Cellular Automata”, Journal of Computer and System Sciences; Vol. 78 (4), pp. 1115-1126; 2012

20. E. Goles, A. Moreira, “Number-Conserving Cellular Automata and Communication Complexity: A Numerical Exploration Beyond Elementary CAs”, Journal of Cellular Automata; Vol. 7 (2), pp. 151-165; 2012

21. L. Altamirano, M.C. Riff, I. Araya, L. Trilling, “Anesthesiology Nurse Scheduling using Particle Swarm Optimization”, International Journal of Computational Intelligence Systems; Vol. 5 N° 1, pp. 111-125; Feb. 2012

22. M.C. Riff, “Emergent Computing: An Introduction to Selected Articles. Preface”, Fundamenta Informaticae; Vol. 119 (1), pp.i-ii; 2012

23. L.P. Cáceres, M.C. Riff, “AISTTP: An Artificial Inmune Algorithm to Solve Travelling Tournament Problems”, International Journal of Computational Intelligence and Applications, Imperial College Press; Vol. 11(1), Art. 1250008(15); 2012

24. R. Fournier, S. Ruscheweyh, L. Salinas, “On a Discrete Norm for Polynomials”, Journal of Mathematical Analysis and Applications; Vol. 396, pp. 425-433; 2012

25. G. Hernández, R. León, L. Salinas, E. Dimnet, “A Fragmentation Model with Neighborhood Interaction”, Applied Mathematical Modelling; Vol. 36(4), pp. 1694-1702; Apr. 2012

26. M. Solar, G. Valdés, H. von Brand, S. Murúa, “A Methodology to Evaluate ICT Platforms in the Implementation of e-Government”, Chapter in B. K. Joseph (Ed.): Handbook of Research on e-Government in Emerging Economies: Adoption, e-Participation, and Legal Frameworks; pp. 455-473; 2012

27. A. Zamyatnin, L. Boronina, “Food Protein Fragments are Regulatory Oligopeptides”, Biochemistry (Moscow); Vol. 77 N° 5, pp. 502-510; 2012

28. A. Zamyatnin, L. Boronina, “Food Protein Fragments are Regulatory Oligopeptides”, Journal of Paptide Science; Vol. 18 Suppl 1, p. S45; Sept. 2012

29. A. Zamyatnin, “Rapid Alkalinization Factors in Grape Vitis Vinifera”, Journal of Peptide Science; Vol. 18 Suppl 1, p. S74; Sept. 2012

30. A. Zamyatnin, A. Borchikov, “Theoretical Analysis of the Structure and Functions of Protein Fragments”, Journal of Peptide Science; Vol. 18 Suppl 1, p. S75; Sept. 2012

2011

1. R. Salas, C. Saavedra, H. Allende, C. Moraga, “Machine Fusion to Enhance the Topology Preservation of Vector Quantization Artificial Neural Networks”, Pattern Recognition Letters; Vol. 32, pp. 962-972; 2011

2. H. Allende-Cid, E. Canessa, A. Quezada, C. Droop, H. Allende, “An Improved Fuzzy Rule-Based Automated Trading Agent”, Studies in Informatics and Control; Vol. 20 (2), pp.135-142; 2011

3. E. Rosas, O. Marín, X. Bonnaire, “CORPS: Building a Community of Reputable PeerS in Distributed Hash Tables”, Computer Journal; Vol. 54 Iss. 10, pp. 1721-1735; 2011

4. N. Goles, E. Goles, S. Rica, “Dynamics and Complexity of the Schelling Segregation Model”, Physical Review E; Vol. 83(5), art. 056111; May 17, 2011

5. M. Bucki, C. Lobos, Y. Payan, N. Hitschfeld, “Jacobian-based Repair Method for Finite Element Meshes after Registration”, Engineering with Computers; Vol. 27, pp. 285-297; 2011

6. C. Hurtado, M. Mendoza, “Automatic Maintenance of Web Directories by Mining Web Browsing Data”, Journal of Web Engineering; Vol. 10 Nº 2, pp. 153-173; 2011

7. M. Mendoza, I. Ortiz, V. Rojas, “Categorización de Textos en Bases Documentales a partir de Modelos Computacionales Livianos”, Revista Signos; Vol. 44(77), pp. 251-274; 2011

8. M. Mendoza, “Minería de Datos en la Web”, Recuperación de Información. Un Enfoque Práctico y Multidisciplinar, RA-MA Editorial; Chapter 19, pp. 613-649; 2011

9. E. Goles, A. Moreira, I. Rapaport, “Communication Complexity in Number-Conserving and Monotone Cellular Automata”, Theoretical Computer Science; Vol. 412 Iss. 29, pp. 3616-3628; 2011

10. C. Soza, R. Landa, M.C. Riff, C. Coello, “Solving Timetabling Problems using a Cultural Algorithm”, Applied Soft Computing; Vol. 11(1), pp. 337-344; Jan. 2011

11. E. Montero, M.C. Riff, “On-The-Fly Calibrating Strategies for Evolutionary Algorithms”, Information Sciences; Vol. 181(3), pp. 552-566; Feb. 2011

12. G. Valdés, M. Solar, H. Astudillo, M. Iribarren, G. Concha, M. Visconti, “Conception, Development and Implementation of an e-Government Maturity Model in Public Agencies”, Government Information Quarterly; Vol. 28, pp. 176-187; 2011

13. M. Solar, E. Ducoing, “Entrenador Virtual de Fibrobroncoscopía de Bajo Costo para Enseñanza”, Revista Médica de Chile; Vol. 139, pp. 1169-1175; 2011

14. A. Zamyatnin, “Structural and Functional Diversity of Natural Antimicrobial”, Chapter Science and Technology Against Microbial Pathogens, Research, Development and Evaluation, Ed. by A. Mendez-Vilas, World Scientific Publishing Co. Ltd. (ICAR2010); pp. 28-33; July 2011

15. A. Zamyatnin, “The Second Type of Oligopeptide Regulation”, Chapter High Technologies, Basic and Applied Researches in Physiology and Medicine, A.P. Kudinov and B.V. Krylov Eds. (ISBN 978-5-7422-32-09); Vol. 2, pp. 189-191; 2011