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Visual attention retargeting attempts to modify an image such that the viewer's attention is directed to specific regions. Goals include highlighting a particular object or hiding possible problems in the image. In this work, we show that we can pose the visual retargeting problem in terms of gamut mapping. In short, visual attention retargeting can be achieved by performing gamut extension in those regions that we want to highlight and gamut reduction in the other regions. ; Authors are supported by the European Research Council, Starting Grant ref. 306337, by the Spanish government FEDER Fund, grant ref. TIN2015-71537-P(MINECO/FEDER,UE), and by the Icrea Academia Award. The work of J. Vazquez-Corral was supported by the Spanish government under Grant IJCI-2014- 19516.

Comunicació presentada a: SMPTE 2017 Annual Technical Conference and Exhibition, celebrat del 23 al 26 d'octubre de 2017 a Los Angeles, Estats Units d'Amèrica. ; Gamut mapping transforms colors of the original (image or video) content to the color palette of the display device with the simultaneous goals of (a) reproducing content accurately while preserving the artistic intent of the original content's creator and (b) exploiting the full color rendering potential of the target display device. The rapid advancement in display technologies has created a pressing need to develop automatic and fast gamut mapping algorithms that can deal with imagery intended for both conventional and emerging displays. In this paper, we propose a novel framework based on retinal and color perception models from vision science that offers a functionality to perform both gamut reduction and gamut extension, while preserving hue and taking into account the analysis of the colors of the input image. We evaluate the performance of the proposed framework visually and by using a perceptually-based error metric, according to which the gamut-mapped results of our framework outperform those of the state-of-the-art methods. ; This work was supported by the European Research Council, Starting Grant ref. 306337, by the Spanish government and FEDER Fund, grant ref. TIN2015-71537-P (MINECO/FEDER,UE), and by the Icrea Academia Award. The work of Javier Vazquez-Corral was supported by the Spanish government grant IJCI-2014-19516.

This work was supported by the European Research Council, Starting Grant ref. 306337, by the Spanish government and FEDER Fund, grant ref. TIN2015-71537-P (MINECO/FEDER,UE), and by the Icrea Academia Award. The work of Javier Vazquez-Corral was supported by the Spanish government grant IJCI-2014-19516.

Gamut mapping is the problem of transforming the colors of image or video content so as to fully exploit the color palette ofthe display device where the content will be shown, while preserving the artistic intent of the original content's creator. In particular in thecinema industry, the rapid advancement in display technologies has created a pressing need to develop automatic and fast gamutmapping algorithms. In this paper we propose a novel framework that is based on vision science models, performs both gamut reductionand gamut extension, is of low computational complexity, produces results that are free from artifacts and outperforms state-of-the-artmethods according to psychophysical tests. Our experiments also highlight the limitations of existing objective metrics for the gamutmapping problem. ; Thiswork has received funding from the European Union'sHorizon 2020 research and innovation programme undergrant agreement number 761544 (project HDR4EU) andunder grant agreement number 780470 (project SAUCE),and by the Spanish government and FEDER Fund, grantref. TIN2015-71537-P (MINECO/FEDER,UE). The work of J.Vazquez-Corral was supported by the Spanish governmentunder Grant IJCI-2014-19516

Gamut mapping transforms the color gamut of an image to that of a target device. Two cases are usually considered: gamut reduction (target gamut smaller than source gamut), and gamut extension (target gamut larger than the source gamut). Less attention is devoted to the more general case, when neither gamut is fully included in the other. In this work we unify and expand two recent methods for gamut extension and reduction, so as to simultaneously perform both forms of gamut mapping in di erent regions of the same image without introducing color artifacts or halos. We demonstrate the usefulness of this approach for the traditional gamut mapping problem, and also how the proposed method can be used to adapt the color palette of an image so that it is closer to that of a given reference image. Results are compared with the state-of-the-art and validated through user tests and objective metrics. ; This work is supported by the European Research Council, Starting Grant ref. 306337, by the Spanish government FEDER Fund, grant ref. TIN2015-71537-P(MINECO/FEDER,UE), and by the Icrea Academia Award. The work of J. Vazquez-Corral was supported by the Spanish government under Grant IJCI-2014-19516

Comunicació presentada a la AIC 2015 Tokyo Midterm Meeting, celebrada a Tòquio (Japó) del 19 a 22 de maig de 2015. ; Gamut mapping transforms the color of an input image within the range of a target device. A huge amount of research has been devoted to two subproblems that arise from this general one: gamut reduction and gamut extension. Gamut reduction algorithms convert the input image to a new gamut that fits inside the one of the image , i.e. the gamuts' intersection is equal to the target gamut, while gamut extension algorithms convert the input image to a gamut that embodies the original image gamut, i.e. the gamuts' intersection is equal to the source gamut. In contrast to the two aforementioned cases, very little attention has been paid to the most general problem, where the intersection of source and target gamut is not equal to one of the two gamuts. In this paper we address this most general problem of gamut mapping between any two gamuts presenting any possible intersection. To deal with this problem we unify the gamut extension and gamut reduction algorithms presented in Zamir –et al- (Zamir 2014), which are based in the perceptually inspired variational framework of Bertalmío –et al- (Bertalmío 2007) that presents three competing terms; an attachment to the original data, a term for not-modifying the perchannel image mean (i.e. not modifying the white point), and a contrast enhancement term. In particular, in this paper we show how by defining a smooth transition on the contrast enhancement parameter over the chromaticity diagram we can simultaneously reduce the input gamut in some chromatic areas while increasing it in some other without introducing neither color artifacts nor halos. ; This work was supported by the European Research Council, Starting Grant ref.306337, by the Spanish Government, grant red.TIN2012-38112, and by the Icrea Academia Award.

Comunicació presentada a: SMPTE 2016 Annual Technical Conference and Exhibition, celebrada a Los Angeles, Estats Units d'Amèrica, del 25 al 27 d'octubre de 2016. ; While wide color gamut (WCG) capabilities are a key element of emerging display and projection technologies, at present most image content is recorded using standards such as DCI-P3 for cinema or BT.709 for TV that have a reduced color gamut. Therefore, there is a need for gamut extension methods that process regular content and allow to appreciate the full color potential of new displays, improving user experience. We present a gamut extension algorithm that is based on visual perception models and explicitly takes into account low chromatic colors such as skin tones. It produces results that look natural, are free of artifacts of any kind, and outperform the state of the art. The method is fast, allowing for operation interaction if needed. ; This work was supported by the European Research Council, Starting Grant ref. 306337, by the Spanish government and FEDER Fund, grant ref. TIN2015-71537-P (MINECO/FEDER,UE), and by the Icrea Academia Award.

This paper examines the convergence of genetic algorithms using a
cluster-analytic-type procedure. The procedure is illustrated with
a hybrid genetic algorithm applied to the quadratic assignment
problem. Results provide valuable insight into how population
members are selected as the number of generations increases and how
genetic algorithms approach stagnation after many generations.

In information societies, operations, decisions and choices previously left to humans are increasingly delegated to algorithms, which may advise, if not decide, about how data should be interpreted and what actions should be taken as a result. More and more often, algorithms mediate social processes, business transactions, governmental decisions, and how we perceive, understand, and interact among ourselves and with the environment. Gaps between the design and operation of algorithms and our understanding of their ethical implications can have severe consequences affecting individuals as well as groups and whole societies. This paper makes three contributions to clarify the ethical importance of algorithmic mediation. It provides a prescriptive map to organise the debate. It reviews the current discussion of ethical aspects of algorithms. And it assesses the available literature in order to identify areas requiring further work to develop the ethics of algorithms.

International Journal of Advanced Research in Artificial Intelligence(IJARAI), 4(12), 2015 ; The poverty rate that was recorded high in Indonesia becomes main priority the government to find a solution to poverty rate was below 10%. Initial identification the potential poverty becomes a very important thing to anticipate the amount of the poverty rate. Naive Bayes Classifier (NBC) algorithm was one of data mining algorithms that can be used to perform classifications the family poor with 11 indicators with three classifications. This study using sample data of poor families a total of 219 data. A system that built use Java programming compared to the result of Weka software with accuracy the results of classification of 93%. The results of classification data of poor families mapped by adding latitude-longitude data and a photograph of the house of the condition of poor families. Based on the results of mapping classifications using NBC can help the government in Kabupaten Bantul in examining the potential of poor people. ; http://thesai.org/Downloads/IJARAI/Volume4No12/Paper_5-Naive_Bayes_Classifier_Algorithm_Approach_for_Mapping.pdf

LGBTQ+ communities were among the first to appropriate the Internet to experiment with their identities and socialize outside of mainstream society. Recently, those platforms have implemented algorithmic systems that curate, exploit, and predict user practices and identities. Yet, the social implications that platform algorithms raise for LGBTQ+ communities remain largely unexplored. Drawing from critical platform studies, science and technology studies, as well as gender and sexuality studies, this paper maps the main issues that platform algorithms raise for LGBTQ+ users and analyzes their implications for social justice and equity. To do so, it identifies and discusses public controversies through a review and analysis of journalistic articles. Our analysis points to five important algorithmic issues that affect the lives of LGBTQ+ users in ways that require additional scrutiny from researchers, policymakers, and tech developers alike: the ability for sorting algorithms to identify, categorize, and predict the sexual orientation and/or gender identity of users; the role that recommendation algorithms play in mediating LGBTQ+ identities, kinship, and cultures; the development of automated anti-LGBTQ+ speech detection/filtering software and the collateral harm caused to LGBTQ+ users; the power struggles over the nature and types of visibility afforded to LGBTQ+ issues online; and the overall enactment of cisheteronormative biases by platform affordances.

© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. ; Network function virtualization (NFV) and software defined networking (SDN) have been proposed to increase the cost-efficiency, flexibility, and innovation in network service provisioning. This is achieved by leveraging IT virtualization techniques and combining them with programmable networks. By doing so, NFV and SDN are able to decouple the network functionality from the physical devices on which they are deployed. Service function chains (SFCs) composed out of virtual network functions (VNFs) can now be deployed on top of the virtualized infrastructure to create new value-added services. Current NFV approaches are limited to mapping the different VNF to the physical substrate subject to resource capacity constraints. They do not provide the possibility to define location requirements with a certain granularity and constraints on the colocation of VNF and virtual edges. Nevertheless, many scenarios can be envisioned in which a service provider (SP) would like to attach placement constraints for efficiency, resilience, legislative, privacy, and economic reasons. Therefore, we propose a set of affinity and anti-affinity constraints, which can be used by SP to define such placement restrictions. Furthermore, a semantic SFC validation framework is proposed that allows the virtual network function infrastructure provider (VNFInP) to check the validity of a set of constraints and provide feedback to the SPs. This allows the VNFInP to filter out any non-valid SFC requests before sending them to the mapping algorithm, significantly reducing the mapping time. ; Peer Reviewed ; Postprint (published version)

© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. ; Network function virtualization (NFV) and software defined networking (SDN) have been proposed to increase the cost-efficiency, flexibility, and innovation in network service provisioning. This is achieved by leveraging IT virtualization techniques and combining them with programmable networks. By doing so, NFV and SDN are able to decouple the network functionality from the physical devices on which they are deployed. Service function chains (SFCs) composed out of virtual network functions (VNFs) can now be deployed on top of the virtualized infrastructure to create new value-added services. Current NFV approaches are limited to mapping the different VNF to the physical substrate subject to resource capacity constraints. They do not provide the possibility to define location requirements with a certain granularity and constraints on the colocation of VNF and virtual edges. Nevertheless, many scenarios can be envisioned in which a service provider (SP) would like to attach placement constraints for efficiency, resilience, legislative, privacy, and economic reasons. Therefore, we propose a set of affinity and anti-affinity constraints, which can be used by SP to define such placement restrictions. Furthermore, a semantic SFC validation framework is proposed that allows the virtual network function infrastructure provider (VNFInP) to check the validity of a set of constraints and provide feedback to the SPs. This allows the VNFInP to filter out any non-valid SFC requests before sending them to the mapping algorithm, significantly reducing the mapping time. ; Peer Reviewed ; Postprint (published version)