Andrés Iglesias's research while affiliated with Universidad de Cantabria and other places
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Publications (260)
Ant Colony Optimization (ACO) encompasses a family of metaheuristics inspired by the foraging behaviour of ants. Since the introduction of the first ACO algorithm, called Ant System (AS), several ACO variants have been proposed in the literature. Owing to their superior performance over other alternatives, the most popular ACO algorithms are Rank-b...
Malaysian campuses house rich species biodiversity that has the potential to become a tourist attraction. However, no Malaysian campuses capitalise on this opportunity to encourage ecotourism and increase the environmental awareness among students. In this context, this research aims to create a systematic framework for mobile application developme...
VR Prototype video capture of Linear Accelerator Education and Training Prototype
Learning to operate medical equipment is one of the essential skills for providing efficient treatment to patients. One of the current problems faced by many medical institutions is the lack or shortage of specialized infrastructure for medical practitioners to conduct hands-on training. Medical equipment is mostly used for patients, limiting train...
Learning to operate medical equipment is one of the essential skills for providing efficient treatment to patients. One of the current problems faced by many medical institutions is the lack or shortage of specialized infrastructure for medical practitioners to conduct hands-on training. Medical equipment is mostly used for patients, limiting train...
The visual impact assessment of large facilities can be improved thanks to Visual Impact Maps (VIMs). A VIM can be a valuable predictor (numerical and graphical) of visual effects. VIMs are conceived to help with the analysis of the Landscape professional. Even before the design stage, VIMs provide important data that complement the set of starting...
This work addresses the IFS-based image reconstruction problem for binary images. Given a binary image as the input, the goal is to obtain all the parameters of an iterated function system whose attractor approximates the input image accurately; the quality of this approximation is measured according to a similarity function between the original an...
Simulation with position-based dynamics is very popular due to its high efficiency. However, it has the weaknesses of lacking details when too few vertices are involved in simulation and inefficiency when too many vertices are used for simulation. To tackle this problem, in this paper, we propose a new method of reconstructing dynamic 3D models wit...
By extending the work published at ICCS 2021 Zhu et al. (2021), in this paper we propose a new method for using multiple explicit PDE surface patches to reconstruct complex 3D shapes from point clouds. Our proposed method includes segmenting a given point cloud into several subsets, parameterizing the points, and fitting one PDE patch to the parame...
The results of evolutionary algorithms depend on population diversity that normally decreases by increasing the selection pressure from generation to generation. Usually, this can lead the evolution process to get stuck in local optima. This study is focused on mechanisms to avoid this undesired phenomenon by introducing parallel self-adapted diffe...
Partial differential equation (PDE) based surfaces own a lot of advantages, compared to other types of 3D representation. For instance, fewer variables are required to represent the same 3D shape; the position, tangent, and even curvature continuity between PDE surface patches can be naturally maintained when certain conditions are satisfied, and t...
Polygon, subdivision, and NURBS are three mainstream modeling techniques widely applied in commercial software packages. They require heavy manual operations, and involve a lot of design variables leading to big data, high storage costs and slow network transmissions. In this paper, we integrate the strengths of boundary-based surface creation and...
In this paper, we present a new modelling method to create 3D models. First, characteristic cross section curves are generated and approximated by generalized elliptic curves. Then, a vector-valued sixth-order partial differential equation is proposed, and its closed form solution is derived to create PDE surface patches from cross section curves w...
Nowadays, it is no secret that modern machine learning methods are amongst the more computationally-intensive learning methods. The rise in the applications of computationally-intensive deep learning, automated machine learning methods, and even metaheuristics for optimization, have increased the consumption of electrical energy dramatically. Conse...
Fractal image reconstruction through iterated function systems (IFS) is an interesting and challenging topic of research. Several methods have been described in the literature to tackle this issue. However, existing methods have focused exclusively on binary or gray level images. To the best of authors’ knowledge, no method has addressed the proble...
3D point clouds parameterization is a very important research topic in the fields of computer graphics and computer vision, which has many applications such as texturing, remeshing and morphing, etc. Different from mesh parameterization, point clouds parameterization is a more challenging task in general as there is normally no connectivity informa...
![Figure 3. The standard model of the mind as proposed by Laird et al. [30].](publication/356808328/figure/fig2/AS:1098595310800908@1638936941698/The-standard-model-of-the-mind-as-proposed-by-Laird-et-al-30_Q320.jpg)
![Power-based training zones according to Coggan [37].](publication/356808328/figure/tbl1/AS:1098595310800940@1638936941847/Power-based-training-zones-according-to-Coggan-37_Q320.jpg)
The rapid development of computer science and telecommunications has brought new ways and practices to sport training. The artificial sport trainer, founded on computational intelligence algorithms, has gained momentum in the last years. However, artificial sport trainer usually suffers from a lack of automatisation in realization and control phase...
3D printing, regarded as the most popular additive manufacturing technology, is finding many applications in various industrial sectors. Along with the increasing number of its industrial applications, reducing its material consumption and increasing the strength of 3D printed objects have become an important topic. In this paper, we introduce unid...
Image processing techniques are becoming standard technology in many medical specialities, such as dermatology, where they are a key tool for the early detection and diagnosis of melanoma and other skin cancers and tumors. A previous paper by the authors presented at SOCO 2020 conference introduced a new method for image segmentation of skin images...
Computational Intelligence methods for automatic generation of sport training plans in individual sport disciplines have achieved a mature phase. In order to confirm their added value, they have been deployed into practice. As a result, several methods have been developed for generating well formulated training plans on computers automatically that...
Cross-section curves play an important role in many fields. Analytically representing cross-section curves can greatly reduce design variables and related storage costs and facilitate other applications. In this paper, we propose composite generalized elliptic curves to approximate open and closed cross-section curves, present their mathematical ex...
Partial differential equation (PDE) based geometric modelling has a number of advantages such as fewer design variables, avoidance of stitching adjacent patches together to achieve required continuities, and physics-based nature. Although a lot of papers have investigated PDE-based shape creation, shape manipulation, surface blending and volume ble...
Since diverse and complex emotions need to be expressed by different facial deformation and appearances, facial animation has become a serious and on-going challenge for computer animation industry. Face reconstruction techniques based on 3D morphable face model and deep learning provide one effective solution to reuse existing databases and create...
Swarm intelligence is a branch of artificial intelligence focused on the collective behavior of decentralized and self-organized systems composed of relatively simple agents interacting locally with one another and with the environment. It takes its inspiration from the surprising collective behavior of colonies of several social insects (ants, fir...
Decision-making is one of the most important cognitive processes in psychology, with outstanding implications in a number of fields including systems neuroscience, cognitive neuroscience, brain and cognitive sciences, logic, computation, artificial intelligence, machine learning, and many others. Basically, it consists of the process of identificat...
The authors got the motivation for writing the paper based on an issue, with which developers of the newly developed nature-inspired algorithms are usually confronted today: How to select the test benchmark such that it highlights the quality of the developed algorithm most fairly? In line with this, the CEC Competitions on Real-Parameter Single-Ob...
As the COVID-19 pandemic unfolds, manually enhanced ad-hoc solutions have helped the physical space designers and decision makers to cope with the dynamic nature of space planning. Due to the unpredictable nature by which the pandemic is unfolding, the standard operating procedures also change, and the protocols for physical interaction require con...
This work is an extension of a previous paper (presented at the Cyberworlds 2019 conference) introducing a new method for fractal compression of bitmap binary images. That work is now extended and enhanced through three new valuable features: (1) the bat algorithm is replaced by an improved version based on optimal forage strategy (OFS) and random...
The Van der Waals (VdW) equation is an equation of state that generalizes the ideal gas law by taking into account molecular size and molecular interaction forces. This equation is widely used to analyze the interplay and transitions between the liquid and gas phases. To this purpose, two characteristic curves, called binodal and spinodal curves, a...
The results of evolutionary algorithms depends on population diversity that normally decreases by increasing the selection pressure from generation to generation. Usually, this can lead evolution process to get stuck in local optima. The study is focused on mechanisms to avoid this undesired phenomenon by introducing parallel differential evolution...
This paper considers the problem of image segmentation for medical images, in particular, cutaneous lesions. Given a digital image of a skin lesion, our goal is to compute the border curve separating the lesion from the image background. This problem can be formulated as an optimization problem, where the border curve is computed through data fitti...
Association Rule Mining belongs to one of the more prominent methods in Data Mining, where relations are looked for among features in a transaction database. Normally, algorithms for Association Rule Mining mine a lot of association rules, from which it is hard to extract knowledge. This paper proposes a new visualization method capable of extracti...
The term Swarm Robotics collectively refers to a population of robotic devices that efficiently undertakes diverse tasks in a collaborative way by virtue of computational intelligence techniques. This paradigm has given rise to a profitable stream of contributions in recent years, all sharing a clear consensus on the performance benefits derived fr...
Preference time in a triathlon denotes the time that is planned to be achieved by an athlete in a particular competition. Usually, the preference time is calculated some days, weeks, or even months before the competition. Mostly, trainers calculate the proposed preference time according to the current form, body performances of athletes, psychologi...
Functional networks are a powerful extension of neural networks where the scalar weights are replaced by neural functions. This paper concerns the problem of parametric learning of the associative model, a functional network that represents the associativity operator. This problem can be formulated as a nonlinear continuous least-squares minimizati...
Multitasking optimization is an emerging research field which has attracted lot of attention in the scientific community. The main purpose of this paradigm is how to solve multiple optimization problems or tasks simultaneously by conducting a single search process. The main catalyst for reaching this objective is to exploit possible synergies and c...
The Van der Waals (VdW) equation of state is a popular generalization of the law of ideal gases proposed time ago. In many situations, it is convenient to compute the characteristic curves of the VdW equation of state, called binodal and spinodal curves. Typically, they are constructed through data fitting from a collection of data points represent...
The emerging research paradigm coined as multitasking optimization aims to solve multiple optimization tasks concurrently by means of a single search process. For this purpose, the exploitation of complementarities among the tasks to be solved is crucial, which is often achieved via the transfer of genetic material, thereby forging the Transfer Opt...
Multitasking optimization is an emerging research field which has attracted lot of attention in the scientific community. The main purpose of this paradigm is how to solve multiple optimization problems or tasks simultaneously by conducting a single search process. The main catalyst for reaching this objective is to exploit possible synergies and c...
This work follows up a previous paper at conference Cyberworlds 2018 for automatic border approximation of cutaneous melanoma and other skin lesions from macroscopic medical images. Given a set of feature points on the boundary of the skin lesion obtained by a dermatologist, we introduce a new method for automatic least-squares B-spline curve fitti...
Robotics have experienced a meteoric growth over the last decades, reaching a remarkable level of intelligence. Today, a myriad of real-world scenarios can beneffit from their widespread application, such as structural health monitoring, complex manufacturing, efficient logistic or disaster management aid. Related to this topic, there is a paradigm...
Flood routing is a methodology to predict the changes of the flow of water as it moves through a natural river, an artificial channel, or a reservoir. It is widely used in fields such as flood prediction, reservoir design, geographic planning, and many others. One of the most popular and widely used flood routing techniques is the Muskingum model,...
Border reconstruction is a key technology in medical image processing, where it is applied to identify and separate different tissues, organs, and tumors in diagnostic procedures. The classical approaches for this problem are based on either linear or polynomial functions to describe the border of the region of interest. However, little effort has...
Stochastic population-based nature-inspired metaheuristics have recently revealed that they are a very robust tool for planning sport training sessions in various sports, e.g. running, cycling, triathlon. Most of the existing solutions in literature are focused on planning training sessions for a particular training cycle. Until recently, no specia...
Finding communities of interrelated nodes is a learning task that often holds in problems that can be modeled as a graph. In any case, detecting an optimal partition in a graph is highly time-consuming and complex. For this reason, the implementation of search-based metaheuristics arises as an alternative for addressing these problems. This manuscr...
Border detection of melanoma and other skin lesions from images is an important step in the medical image processing pipeline. Although this task is typically carried out manually by the dermatologists, some recent papers have applied evolutionary computation techniques to automate this process. However, these works are only focused on the polynomi...
Stochastic population-based nature-inspired metaheuristics have been proven as a robust tool for mining association rules. These algorithms are very scalable, as well as very fast compared with some deterministic ones that search for solutions exhaustively. Typically, algorithms for association rule mining identify a lot of rules depending, on the...
Flood routing models are mathematical methods used to predict the changes over the time in variables such as the magnitude, speed and shape of a flood wave when water moves in a river, a stream or a reservoir. These techniques are widely used in water engineering for flood prediction and many other applications such as dam design, geographic and ur...
Novelty search ensures evaluation of solutions in stochastic population-based nature-inspired algorithms according to additional measure, where each solution is evaluated by a distance to its neighborhood beside the fitness function. Thus, the population diversity is preserved that is a prerequisite for the open-ended evolution in evolutionary robo...
Computer reconstruction of digital images is an important problem in many areas such as image processing, computer vision, medical imaging, sensor systems, robotics, and many others. A very popular approach in that regard is the use of different kernels for various morphological image processing operations such as dilation, erosion, blurring, sharp...
Detecting communities of interconnected nodes is a frequently addressed problem in situation that be modeled as a graph. A common practical example is this arising from Social Networks. Anyway, detecting an optimal partition in a network is an extremely complex and highly time-consuming task. This way, the development and application of meta-heuris...
Novelty search is a tool in evolutionary and swarm robotics for maintaining the diversity of population needed for continuous robotic operation. It enables nature-inspired algorithms to evaluate solutions on the basis of the distance to their k-nearest neighbors in the search space. Besides this, the fitness function represents an additional measur...
Automatic planning of sport training sessions with Swarm Intelligence algorithms has been proposed recently in the scientific literature that influences the sports training process in practice dramatically. These algorithms are capable of generating sophisticated training plans based on an archive of the existing sports training sessions. In recent...
Within a repowering context, this paper opens a new field of application for visibility and Visual Impact Assessment (VIA) procedures in the decision-making process typical of the design stage of Wind Farms (WF). The proposed methodology presents a test capable of reporting on the visual sustainability of different layouts. It is called Equivalent...
Finding groups from a set of interconnected nodes is a recurrent paradigm in a variety of practical problems that can be modeled as a graph, as those emerging from Social Networks. However, finding an optimal partition of a graph is a computationally complex task, calling for the development of approximative heuristics. In this regard, the work pre...
This paper presents a swarm robotics approach for dual non-cooperative search, where two robotic swarms are deployed within a map with the goal to find their own target point, placed at an unknown location of the map. We consider the self-centered mode, in which each swarm tries to solve its own goals with no consideration to any other factor exter...
Association rule mining is a method for identification of dependence rules between features in a transaction database. In the past years, researchers applied the method using features consisting of categorical attributes. Rarely, numerical attributes were used in these studies. In this paper, we present a novel approach for mining association based...
In this paper, a driving route planning system for multi-point routes is designed and developed. The routing problem has modeled as an Open-Path and Asymmetric Green Traveling Salesman Problem (OAG-TSP). The main objective of the proposed OAG-TSP is to find a route between a fixed origin and destination, visiting a group of intermediate points exac...
Swarm intelligence is based on the recently-acquired notion that sophisticated behaviors can also be obtained from the cooperation of several simple individuals with a very limited intelligence but cooperating together through low-level interactions between them and with the environment using decentralized control and self-organization. Such intera...
This paper presents an evolutionary computation scheme for automatic human motion generation in computer animation and video games. Given a set of identical physics-driven skeletons seated on the ground as an initial pose (similar for all skeletons), the method applies forces on selected bones seeking for a final stable pose with all skeletons stan...
This paper addresses the problem of automatic fitting of feature points for border detection of skin lesions. This problem is an important task in segmentation of dermoscopy images for semi-automatic early diagnosis of melanoma and other skin lesions. Given a set of feature points selected by a dermatologist, we apply a powerful nature-inspired met...
In recent years, planning sport training sessions with computational intelligence have been studied by many authors. Most of the algorithms were used for proposing basic and advanced training plans for athletes. In a nutshell, most of the solutions focused on the individual sports disciplines, such as, for example, cycling and running. To the knowl...
