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Page 1. Diego Andina DucTruongPham Editors for Engineering an Page 2. Computational Intelligence Page 3. Computational Intelligence for Engineering and Manufacturing Edited by Diego Andina Technical University of Madrid ...
The control of the security in a limited area, like a house, is a complex task. This paper proposc a stand-alone intelligent system based on image recogiiit~on. The system detects moving peisoiis and successive update steps are applied in... more
The control of the security in a limited area, like a house, is a complex task. This paper proposc a stand-alone intelligent system based on image recogiiit~on. The system detects moving peisoiis and successive update steps are applied in order to track them pviding important information about the position and their activity in term oi'traiectories perlbrined. Finally, a verification subsystem. based on the Intrusioti Detection System (IDS) used in coinputer networks technology attempts to identify unauthorized proximity based on ntrrinality patterns. 1. IN'I'RC)DUCTION Automatic human detection and body part lucalization arc important and challenging prohleins in compufer vision (1).(2). The solution to those prohleins cilii be einploycd in a wide nnge of applications such as safe robot navigation, visual surveillance, huinan-computer intcrl'ace, and figure animation. Our application doinnin is Domotics, i.e. the integral automation of huildings and housing. We can dcline it as: "A scr of eleincnts that, when installed, interconnected and cotitrolled autoinatically in a building. save the users wonying about routine weiyday actions, providing improvement in their coinfoii. in encrgy consumption. in security and iii conmimicarion as well". The context for human detectivn is the general ob,ject detection problem. Our approach is IO lirst seginetit Ibregruund ob.jects fium the hackground and then classify cach segmented ohject as human or non-human. Classifying only seginentcd ohjeots rather than searching them in the whole image significantly reduces computational complexity. Due to thr application domain of our system, we do not care about the classification of moving objccts as persons. So, we deal every inoving ab,icct as a threat for the security of the house. The tinal Intrusion I3etection subsystem based vti the shape ond trnjectories followed by tlic object should discriminate if this object is compromising the user defined security areas. The orgatiization ol the paper is 21s fAlows. First we review the work done for the European I'ro,ject Eureka EU- 136 I, which makes use of segmentation of forcginund ohjccls to pre-proccss vidcoconference scenes. The dctected ohjects are tracked using a mhiist regression scheme that will dcscribe their trqjectories using affitirr motion inodel parameters. Both the shape and tra.jectorics are used as the input for an Intrusion Detection System ((lF.), which is hascd on previous research done for detecting attacks 011 computer networks (3). The IDS attempts to idcntify unauthorized proximity to the high sccurity areas louking for statistical and rule-bnsed onnmaltes. Thcse high security areas are detined previously by the user of the system with an interact i ve i 11 terfacc.
One of the mayor limitations associated to Neural Networks (NNs) learning algorithms is the number of input-output pattern pairs needed to obtain the desired classilication pcrlbmancc. In many practical cases, the number... more
One of the mayor limitations associated to Neural Networks (NNs) learning algorithms is the number of input-output pattern pairs needed to obtain the desired classilication pcrlbmancc. In many practical cases, the number 01' pairs used to design the NN is much lower than necessary. Either bccause of the excessivc price of data acquisition or, simply, for availability reasons. An Importance
In the first half of this book, Chapters 1 to 5, we have presented the foundations of information risk management (Chapter 1), the profiles required by an IT security team (Chapter 2), the basic aspects that guide the team-individual... more
In the first half of this book, Chapters 1 to 5, we have presented the foundations of information risk management (Chapter 1), the profiles required by an IT security team (Chapter 2), the basic aspects that guide the team-individual contract (Chapter 3), a list of security principles to follow and activities to perform by the team (Chapter 4) and some
A new sub-segmentation method has been proposed in 2009 which, in digital images, help us to identify the typical pixels, as well as the less representative pixels or atypical of each segmented region. This method is based on the... more
A new sub-segmentation method has been proposed in 2009 which, in digital images, help us to identify the typical pixels, as well as the less representative pixels or atypical of each segmented region. This method is based on the Possibilistic Fuzzy c-Means (PFCM) clustering algorithm, as it integrates absolute and relative memberships. Now, the segmentation problem is related to isolate each one of the objects present in an image. However, and considering only one segmented object or region represented by gray levels as its only feature, the totality of pixels is divided in two basic groups, the group of pixels representing the object, and the others that do not represent it. In the former group, there is a sub-group of pixels near the most representative element of the object, the prototype, and identified here as the typical pixels, and a sub-group corresponding to the less representative pixels of the object, which are the atypical pixels, and generally located at the borders of the pixels representing the object. Besides, the sub-group of atypical pixels presents greater tones (brighter or towards the white color) or smaller tones (darker or towards black color). So, the sub-segmentation method offers the capability to identify the sub-region of atypical pixels, although without performing a differentiation between the brighter and the darker ones. Hence, the proposal of this work contributes to the problem of image segmentation with the improvement on the detection of the atypical sub-regions, and clearly recognizing between both kind of atypical pixels, because in many cases only the brighter or the darker atypical pixels are the ones that represent the object of interest in an image, depending on the problem to be solved. In this study, two real cases are used to show the contribution of this proposal; the first case serves to demonstrate the pores detection in soil images represented by the darker atypical pixels, and the second one to demonstrate the detection of microcalcifications in mammograms, represented in this case by the brighter atypical pixels.
A Comparison of Criterion Functions for a Neural Network Applied to Binary Detection Diego ANDINA, Jose L. SANZ-GONZALEZ and Jose.A. JIMENEZ-PAJARES Departamento de Senates, Sistemas y Radiocomunicaciones, ETSI de Telecomunicacion,... more
A Comparison of Criterion Functions for a Neural Network Applied to Binary Detection Diego ANDINA, Jose L. SANZ-GONZALEZ and Jose.A. JIMENEZ-PAJARES Departamento de Senates, Sistemas y Radiocomunicaciones, ETSI de Telecomunicacion, Universidad ...
Technology transfer is a key functio n or process of the global innovation systems. There is a wide variety of activities through which academics transfer their new knowledge. Some of these activities are more formal than others. Many... more
Technology transfer is a key functio n or process of the global innovation systems. There is a wide variety of activities through which academics transfer their new knowledge. Some of these activities are more formal than others. Many prior studies have concentrated on more formal activities based on intellectual property rights as the main outcomes of universities such as patenting, licensing and the formation of spin-offs. After a systematic literature review, we outline an analytical framework that uses global chains as the mechanism for bridging global and national innovation systems. The merit of global chains is that they emphasize inter-firm and intra-organization interactions and networks along the production process of a given product. These are often neglected by innovation systems. But these interactions allow us to understand better the role of informal university technology transfer along global value chain and its risks. https://library.iated.org/view/MARTINRUBIO2016RIS
ABSTRACT The sensitivity of mass fractal dimension (Dm), a spectral dimension (d), and the ratio of the two, (-d- Dm), that relates to the scaling property of dynamical processes in soil such as diffusion, to different threshold criteria... more
ABSTRACT The sensitivity of mass fractal dimension (Dm), a spectral dimension (d), and the ratio of the two, (-d- Dm), that relates to the scaling property of dynamical processes in soil such as diffusion, to different threshold criteria was estimated. In order to do so, intact soil samples were collected from four horizons of a Brazilian soil and 3D images, of 45.1 mm resolution (256x256x256 voxels), were obtained. Four different threshold criteria were used to transform CT grey-scale imagery in binary imagery (pore/solid), based on the frequency of CT units. To compare the effect of threshold and soil horizons on the two parameters studied and its ratio, an analysis of variance was performed in a split-plot design. In this study each image is the "main plot unit" where we have performance four determinations of the parameters. Therefore, it was considered the three locations as blocks, each horizon as main plot effect and each threshold as subplot effect. GenStat® version 12.1 was used to performance these analysis. The significance level of all the statistical analysis was at 5%. Fractal-like scaling was observed overall length scales, however the effect of thresholding on the estimate for Dm depended on the range of length scales used. The log-log plots, from which Dm is estimated, show that thresholding influenced mainly the scaling at the smallest length scales (of size length from 1 to 16 voxels). This demonstrates that different thresholding schemes mainly influence the features close to the resolution limit of the image. Dm and d showed a relation with the apparent porosity (i.e. the value calculated for different threshold criteria) in the image for the 12 samples studied. Plotting the apparent soil porosity against Dm or dwe found that both increased with respect to porosity, being logarithmic for Dm and linear for d. The ratio (d- Dm) can characterize each of the horizons considered in this study when the mass dimension was estimated not using only the smallest length scales, which is highly sensitive to the threshold criteria.
ABSTRACT
KLN (Koniocortex Like Network) is a novel Bioinspired Artificial Neural Network that models relevant biological properties of neurons as Synaptic Directionality, Long Term Potenciation, Long Term Depression, Metaplasticity and Intrinsic... more
KLN (Koniocortex Like Network) is a novel Bioinspired Artificial Neural Network that models relevant biological properties of neurons as Synaptic Directionality, Long Term Potenciation, Long Term Depression, Metaplasticity and Intrinsic plasticity, together with natural normalization of sensory inputs and Winner-Take-All competitive learning. As a result, KLN performs a Deeper Learning on DataSets showing several high order properties of biological brains as: associative memory, scalability and even continuous learning. KLN learning is originally unsupervised and its architecture is inspired in the koniocortex, the first cortical layer receiving sensory inputs where map reorganization and feature extraction have been identified, as is the case of the visual cortex. This new model has shown big potential on synthetic inputs and research is now on application performance in complex problems involving real data in comparison with state-of-art supervised and unsupervised techniques. In this paper we apply KLN to explore its capabilities on one of the biggest problem of nowadays society and medical community, as it is the early detection of cardiovascular disease. The world’s number one killer, with 17,9 million deaths every year. Results of KLN on the classification of Cardiac arrhythmias from the well-known MIT-BIH cardiac arrhythmias database are reported.
Mauelshagen et al. reveal that the intellectual capital required for effective environmental policy making is particular diverse and encourage the development of models than can understand the profile of individuals and teams when dealing... more
Mauelshagen et al. reveal that the intellectual capital required for effective environmental policy making is particular diverse and encourage the development of models than can understand the profile of individuals and teams when dealing with collaboration, knowledge transfer and innovation. Furthermore, stakeholders frequently kill novel ideas when those ideas do not fit with the organization?s identity, i.e. organizational actors' enduring sense of who the organization is and what it stands for. The challenges of radical innovation requires architectures that embrace and augment, "hot" cognitive processes and the underlying mechanisms of interactions and innovation is still limited. The objective of our work is to understand the cognitive style of our students when finding solutions as agents of changes, as could be climate change following Kirton Adaptation-Innovation Theory (KAI).
Abstract Smart and optimal manufacturing in Industry 4.0 aims to realize distributed networking manufacturing connecting the whole supply chain: suppliers, factories, distribution, and customers. Automatic sensing information via modern... more
Abstract Smart and optimal manufacturing in Industry 4.0 aims to realize distributed networking manufacturing connecting the whole supply chain: suppliers, factories, distribution, and customers. Automatic sensing information via modern control technology makes possible to respond proactively to the demand change. System of systems engineering exploits mechanisms and expert knowledge that enables the decision-makers to understand the interaction of different systems according to different objectives (cost, quality, and lead time). The intelligence of smart manufacturing is possible when the systems of systems are properly designed. Attributes like collaborations, tensions, traceability, and cybersecurity should be considered to generate intelligent platforms. A key aspect is the design of control strategy.
The Metaplasticity is an inherent property of the Biological neuron connections that consists in the capacity of modifying the learning mechanism using the information present in the network itself during the training. This concept can be... more
The Metaplasticity is an inherent property of the Biological neuron connections that consists in the capacity of modifying the learning mechanism using the information present in the network itself during the training. This concept can be applied to Artificial Learning Algorithms using a technique called Artificial Metaplasticity. The idea is to improve the results in Machine Learning taking as the base the hypothesis studied by Metaplasticity in Biological Learning. This paper presents and discuss the results of applying an Artificial Metaplasticity implementation based on the information present at the output of the network in Multilayer Perceptrons at artificial neuron learning level. The objective of this study is a state-of-the-art research: the diagnosis of breast cancer data from the Wisconsin Breast Cancer Database.
This paper deals with the consideration of Business Intelligence for planning new products and supply chain system, from a SoSE perspective. The problem of understanding, designing, engineering and governing the technologies behind these... more
This paper deals with the consideration of Business Intelligence for planning new products and supply chain system, from a SoSE perspective. The problem of understanding, designing, engineering and governing the technologies behind these new products requires new concepts. The emergence of these modern technologies causes a myriad of interconnected systems, which are working together to satisfy the necessities of modern life. System of System Engineering (SoSE) can contribute to the science community to fulfill this requirement.
ABSTRACT The objective of this chapter is to present a mathematical model that will allow the development and evaluation of integral plans for adaptation of communities to the climate change, in vulnerable areas of Europe and Latin... more
ABSTRACT The objective of this chapter is to present a mathematical model that will allow the development and evaluation of integral plans for adaptation of communities to the climate change, in vulnerable areas of Europe and Latin America and to help to select the most suitable alternative, evaluate the costs and design strategies of application, formation and diffusion of knowledge, and the education of the society. The results will lay the basis of economic and social sustainable development, by means of a suitable planning and territorial arrangements, including not only the rational and sustainable use of the Earth, but also other natural resources.
Rainfall is one of the most important events in daily life of human beings. During several decades, scientists have been trying to characterize the weather, current forecasts are based on high complex dynamic models (ensembles). In this... more
Rainfall is one of the most important events in daily life of human beings. During several decades, scientists have been trying to characterize the weather, current forecasts are based on high complex dynamic models (ensembles). In this paper is presented a local rainfall forecast system based on wavelet Time Series analysis and of Neural Networks. After several year taking data, a subjective local model has been automated by this system in different stages. This work is focused to explain the wavelet filters (MOWDT and CWT). This filtering stage obtains the pressure waves at appropriate scales and trains the neural classifier. As a result it allows detecting the upcoming of warm and cold fronts.
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ABSTRACT
... benefits of CT techniques are: reducing the physical impact to sampling, providing three-dimensional (3D) information and allowing rapid scanning to study sample dynamics in near real-time ([Rasiah and Aylmore, 1998a], [Rasiah and... more
... benefits of CT techniques are: reducing the physical impact to sampling, providing three-dimensional (3D) information and allowing rapid scanning to study sample dynamics in near real-time ([Rasiah and Aylmore, 1998a], [Rasiah and Aylmore, 1998b] and [Elliot and Heck ...
In this paper, we use the neural property known as intrinsic plasticity to develop neural network models that resemble the koniocortex, the fourth layer of sensory cortices. These models evolved from a very basic two-layered neural... more
In this paper, we use the neural property known as intrinsic plasticity to develop neural network models that resemble the koniocortex, the fourth layer of sensory cortices. These models evolved from a very basic two-layered neural network to a complex associative koniocortex network. In the initial network, intrinsic and synaptic plasticity govern the shifting of the activation function, and the modification of synaptic weights, respectively. In this first version, competition is forced, so that the most activated neuron is arbitrarily set to one and the others to zero, while in the second, competition occurs naturally due to inhibition between second layer neurons. In the third version of the network, whose architecture is similar to the koniocortex, competition also occurs naturally owing to the interplay between inhibitory interneurons and synaptic and intrinsic plasticity. A more complex associative neural network was developed based on this basic koniocortex-like neural networ...
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Research Interests:
ABSTRACT This chapter introduces a swarm intelligence-inspired approach for target allocation in large teams of autonomous robots. For this purpose, the Distributed Bees Algorithm (DBA) was proposed and developed by the authors. The... more
ABSTRACT This chapter introduces a swarm intelligence-inspired approach for target allocation in large teams of autonomous robots. For this purpose, the Distributed Bees Algorithm (DBA) was proposed and developed by the authors. The algorithm allows decentralized decision-making by the robots based on the locally available information, which is an inherent feature of animal swarms in nature. The algorithm’s performance was validated on physical robots. Moreover, a swarm simulator was developed to test the scalability of larger swarms in terms of number of robots and number of targets in the robot arena. Finally, improved target allocation in terms of deployment cost efficiency, measured as the average distance traveled by the robots, was achieved through optimization of the DBA’s control parameters by means of a genetic algorithm.
... F. Sorbello, S. Vitabile: “Two-days ahead prediction of daily maximum concentrations of SO2, O3, PM10, NO2, CO in the urban area of ... 1990 [22] E. Vega-López: “Gaceta Oficial del Distrito Federal”, Órgano de Gob-ierno del Distrito... more
... F. Sorbello, S. Vitabile: “Two-days ahead prediction of daily maximum concentrations of SO2, O3, PM10, NO2, CO in the urban area of ... 1990 [22] E. Vega-López: “Gaceta Oficial del Distrito Federal”, Órgano de Gob-ierno del Distrito Federal, 2006 [23] JM Barron-Adame, JA ...

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Atypical Data can have high value in Big Data through Machine Learning:
https://youtu.be/vYLVNAPHCnI
Emerging and novel Bioinspired Artificial Neural Networks (BIANN) provide new interdisciplinary approaches for solution of complicated and intractable problems. How can engineering, mathematics, computation, Artificial Intelligence (AI)... more
Emerging and novel Bioinspired Artificial Neural Networks (BIANN) provide new interdisciplinary approaches for solution of complicated and intractable problems. How can engineering, mathematics, computation, Artificial Intelligence (AI) and Knowledge Engineering (KE) find inspiration in the behavior and internal functioning of physical, biological nervous systems to conceive, develop and build-up new concepts, materials, mechanisms and algorithms of potential value for solution of real world applications? And how can these techniques be used to conceptualize and model the nervous system? The aim of this special issue is research on the intersection of neurosciences and artificial neural networks and computations. Novel, emerging, and high impact BIANN theories and models with applications to illustrate their potential are welcome. Please inform the guest editors and the Editor-in-Chief about your intention to submit a manuscript for possible publication in the special issue as soon as possible. Please email the following to one of the Guest Editors with a copy to the Editor-in-Chief by March 15, 2016:
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