A5048454804- Genomics and Phylogenetic Studies
- Algorithms and Data Compression
- Vehicle Routing Optimization Methods
- Metaheuristic Optimization Algorithms Research
- RNA and protein synthesis mechanisms
- Distributed and Parallel Computing Systems
- Optimization and Search Problems
- Genome Rearrangement Algorithms
- Online Learning and Analytics
- Advanced Graph Theory Research
- Artificial Immune Systems Applications
- Scheduling and Optimization Algorithms
- Machine Learning and Algorithms
- Complexity and Algorithms in Graphs
- Underground infrastructure and sustainability
- Influenza Virus Research Studies
- AI-based Problem Solving and Planning
- Educational Assessment and Pedagogy
- Cloud Computing and Resource Management
- Genomic variations and chromosomal abnormalities
- Occupational Health and Safety Research
- Wikis in Education and Collaboration
- Advanced Optical Network Technologies
- Explainable Artificial Intelligence (XAI)
- Intelligent Tutoring Systems and Adaptive Learning
University of Concepción
2018-2024
Universidad Politécnica de Cartagena
2023
Buenos Aires Institute of Technology
2023
University of Buenos Aires
2023
Consejo Nacional de Investigaciones Científicas y Técnicas
2023
Universidad Santo Tomás
2014-2017
University of the Basque Country
2014-2017
Deep Learning (DL), a groundbreaking branch of Machine (ML), has emerged as driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted complex non-linear artificial neural systems, excel at extracting high-level features from data. demonstrated human-level performance real-world tasks, including clinical diagnostics, unlocked solutions to previously intractable problems virtual agent design, robotics, genomics, neuroimaging, computer vision, industrial...
Abstract One of the problems with exact techniques for solving combinatorial optimization is that they tend to run into growing problem instance size. Nevertheless, might still be very usefully employed, even in context large instances, as a sub-ordinate method within so-called hybrid metaheuristics. “Construct, Merge, Solve and Adapt” ( Cmsa ) metaheuristic technique allows application methods large-scale instances through intelligent reduction. However, does not make use an explicit...
This work deals with the so-called minimum capacitated dominating set (CAPMDS) problem, which is an NP-Hard combinatorial optimization problem in graphs. In this paper we describe application of a recently introduced hybrid algorithm known as Construct, Merge, Solve & Adapt (CMSA) to problem. Moreover, evaluate performance standalone ILP solver. The results show that both CMSA and solver outperform current state-of-the-art algorithms from literature. contrast solver, does not degrade for...
The primary aim of this study is to introduce a didactic programme that incorporates gamification in geometry classes for high school students. purpose boost students’ motivation towards learning. In the present educational scenario, role information and communication technologies (ICT) paramount. Gamification has potential enhance learning process by integrating game elements into non-game environments. This approach deemed necessary as emotional factors teaching may not lead meaningful...
Limited payload capacity on small unmanned aerial vehicles (UAVs) results in restricted flight time. In order to increase the operational range of UAVs, recent research has focused use mobile ground charging stations. The cooperative route planning for both and (GVs) is strongly coupled due fuel constraints UAV, terrain GV speed differential two vehicles. This problem is, general, an NP-hard combinatorial optimization problem. Existing polynomial-time solution approaches make a trade-off...
An artificial bioindicator system is developed in order to solve a network intrusion detection problem. The system, inspired by an ecological approach biological immune systems, evolves population of agents that learn survive their environment. adaptation process allows the transformation agent into capable reacting anomalies. Two characteristics stand out our proposal. On one hand, it able discover new, previously unseen attacks, and on other contrary most existing systems for detection,...
Finding dominating sets in graphs is very important the context of numerous real-world applications, especially area wireless sensor networks. This because network lifetime networks can be prolonged by assigning sensors to disjoint node sets. The nodes these are then used a sleep-wake cycling mechanism sequential way; that is, at any moment time, only from exactly one switched on while others off. paper presents population-based iterated greedy algorithm for solving weighted version maximum...
The minimum capacitated dominating set problem is an NP-hard variant of the well-known in undirected graphs. This finds applications context clustering and routing wireless networks. Two algorithms are presented this work. first one extended version construct, merge, solve adapt, while main contribution a hybrid between biased random key genetic algorithm exact approach which we labeled Barrakuda. Both evaluated on large benchmark instances from literature. In addition, they tested new, more...
MicroMeasure es un programa cientÃfico de análisis imágenes, cuya aplicación está destinada a estudios citológicos, citogenéticos y citotaxonómicos. Este diseñado especÃficamente para la medición lineal los cromosomas utilizando fundamentalmente el centrómero cada cromosoma como punto crucial dos brazos uno ellos. Los datos se calculan automáticamente, dando resultado una hoja cálculo Excel. A partir esta tabla Excel, pueden hacer multiplicidad cálculos, dependiendo las...
The minimum common string partition problem is an NP-hard combinatorial optimization with applications in computational biology. In this work we propose the first integer linear programming model for solving problem. Moreover, on basis of develop a deterministic 2-phase heuristic which applicable to larger instances. results show that provenly optimal solutions can be obtained instances small and medium size from literature by proposed CPLEX. Furthermore, new best-known are all considered...
Despite the fact that outside is becoming frontier of indoor workplaces, a large amount real-world work like road construction has to be done by outdoor human activities in open areas. Given promise smart workplace various aspects including productivity and safety, we decided employ technologies for collaborative project both improve efficiency reduce worker injuries. Nevertheless, our trials on implementation have encountered few problems ranging from theoretical confusion among different...
The detection of anomalies in unknown environments is a problem that has been approached from different perspectives with variable results. Artificial Immune Systems (AIS) present particularly advantageous characteristics for the such anomalies. This research based on an existing detector model, named Bioindicators System (ABS) which identifies and solves its main weaknesses. An ABS anomaly classifier model presented, incorporating elements AIS. In this way, new (R-ABS) developed includes...