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Susana Muñoz-Hernández
Departamento de Lenguajes y Sistemas Informáticos e Ingeniería de Software (DLSIIS), Campus de Montegancedo, Universidad Politécnica de Madrid, 28660 Madrid, Spain

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Journal article
Published: 30 August 2021 in Sustainability
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This study explains the rationale of a methodology developed by the Universidad Politécnica of Madrid (UPM) group TechPeopleCare as applied to the e-Health Inclusion through ICT Training project partly funded by the European Institute of Technology EIT-Health in 2019. An initial sample of 168 participants with different lifestyles and migrant backgrounds, with high female participation, were recruited in three different countries by three different organisations following strict ethical protocols that limit the data that can be shared. The learning materials were aimed at people lacking the operational and formal skills to use digital media, for example, using a mouse, a keyboard, and navigating the Internet. This learning would enable these cohorts to become beneficiaries of e-Health interventions, such as making a doctor’s appointment, accessing a health record, finding the location of a health centre or the nearest open pharmacy. By the end of the training programme, we found that the motivation to learn was high. The possibility of reviewing learning content at the individual’s pace and without the need of an instructor was appreciated, especially by younger cohorts with migrant backgrounds. A majority reported being satisfied with their learning of the health systems, unique to each country, and willing to learn more regardless of the training method. However, allowing for individual and independent learning “by doing” appears more accessible to suit different lifestyles and more sustainable than traditional computer classes. Since social and digital inequality are intertwined, sustainable and innovative learning programmes in developing countries within communities specifically addressing the acquisition of operational and formal skills are a pre-condition to move forward and bridge the gap of being on the wrong side of the digital divide.

ACS Style

Susana Muñoz-Hernández; Clara Benac-Earle; Angel Herranz Nieva; Mayte Gonzalez-McGuinness. Sustainable Methodology for Operational and Formal Digital Skills Acquisition: A Case Study of e-Health Inclusion. Sustainability 2021, 13, 9698 .

AMA Style

Susana Muñoz-Hernández, Clara Benac-Earle, Angel Herranz Nieva, Mayte Gonzalez-McGuinness. Sustainable Methodology for Operational and Formal Digital Skills Acquisition: A Case Study of e-Health Inclusion. Sustainability. 2021; 13 (17):9698.

Chicago/Turabian Style

Susana Muñoz-Hernández; Clara Benac-Earle; Angel Herranz Nieva; Mayte Gonzalez-McGuinness. 2021. "Sustainable Methodology for Operational and Formal Digital Skills Acquisition: A Case Study of e-Health Inclusion." Sustainability 13, no. 17: 9698.

Conference paper
Published: 16 April 2021 in Applied Computational Intelligence and Mathematical Methods
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This proposal provides a user-friendly way of personalizing fuzzy search criteria in an expressive searching platform. The interest is in, for example, if we have a fuzzy criterion “expensive” for searching expensive restaurants defined in the system, by personalization, any user can access the criterion and personalize it with his/her preferences and values that satisfies his/her needs. In this way, every user retrieves different results while querying over a single fuzzy search criterion. The system executes this personalized fuzzy searching criterion if the logged-in user has previously personalized that criterion definition. Moreover, our framework is user-friendly enough to perform expressive searches over modern and conventional database formats without knowing the low-level syntax of the criteria of the framework. Furthermore, we present the architecture of this novel framework, with its design and implementation details. We provide a clarifying case study on our system by providing an experiment. We have analyzed the results obtained from the experiment to show our system’s behavior and performance after incorporating the functionality of the personalization of fuzzy search criteria.

ACS Style

Mohammad Halim Deedar; Susana Muñoz-Hernández. Personalizing Fuzzy Search Criteria for Improving User-Based Flexible Search. Applied Computational Intelligence and Mathematical Methods 2021, 186 -199.

AMA Style

Mohammad Halim Deedar, Susana Muñoz-Hernández. Personalizing Fuzzy Search Criteria for Improving User-Based Flexible Search. Applied Computational Intelligence and Mathematical Methods. 2021; ():186-199.

Chicago/Turabian Style

Mohammad Halim Deedar; Susana Muñoz-Hernández. 2021. "Personalizing Fuzzy Search Criteria for Improving User-Based Flexible Search." Applied Computational Intelligence and Mathematical Methods , no. : 186-199.

Journal article
Published: 21 August 2020 in Canadian Journal of Electrical and Computer Engineering
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We present a parametric framework (UFleSe) with a user-friendly interface having a search engine that enables regular users (without the need of neither technical nor theoretical knowledge) to define their fuzzy concepts, rules, similarity relations, synonyms, antonyms, and personalizing their definitions for different users, and to link them with the crisp database fields for performing flexible, expressive queries in a language close to natural language. It works over multiple modern and conventional data formats, such as JSON, SQL, Prolog, CSV, XLS, and XLSX. We present the syntax involved in the construction of our various flexible searching criteria and their personalizations. Furthermore, we present the architecture of this novel system that combines fuzzy, crisp data, and similarity relations in its queries to return constructive answers ordered by a degree of searching criteria satisfaction (truth-value between 0 and 1). Finally, we include a comparative analysis of different fuzzy querying systems here, and we provide various experiments, to show the system behavior, performance, efficiency, and scalability as well.

ACS Style

Mohammad Halim Deedar; Susana Munoz-Hernandez. UFleSe: User-Friendly Parametric Framework for Expressive Flexible Searches. Canadian Journal of Electrical and Computer Engineering 2020, 43, 235 -250.

AMA Style

Mohammad Halim Deedar, Susana Munoz-Hernandez. UFleSe: User-Friendly Parametric Framework for Expressive Flexible Searches. Canadian Journal of Electrical and Computer Engineering. 2020; 43 (4):235-250.

Chicago/Turabian Style

Mohammad Halim Deedar; Susana Munoz-Hernandez. 2020. "UFleSe: User-Friendly Parametric Framework for Expressive Flexible Searches." Canadian Journal of Electrical and Computer Engineering 43, no. 4: 235-250.

Conference paper
Published: 01 April 2020 in Computer Vision – ECCV 2020
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In this article we describe a methodology, and its evaluation, for achieving technical competence through digital literacy training using self-learning training material. The key component is self-learning in the sense that the targeted population learns digital operational skills without the need of a teacher. This is achieved through the adaptation of the training material to the trained group. As training groups are diverse, e.g., including both populations in developing and developed countries, and varying in age aspects, gender, languages, literacy levels and technological literacy levels, materials and the speed which training takes place has to be adapted to take into account these differences. The methodology involves use of training videos, and use a dual screen approach where training material is shown on one screen and training takes place on a second screen (computer). The approach has been evaluated in both developing countries and developed countries, with training groups of different capabilities and backgrounds (in Kenya, El Salvador, Spain, France and The Netherlands), with promising results.

ACS Style

Susana Muñoz Hernández; Clara Benac Earle; Lars-Åke Fredlund. A Methodology for Addressing the Second-Level Digital Divide. Computer Vision – ECCV 2020 2020, 12067, 331 -337.

AMA Style

Susana Muñoz Hernández, Clara Benac Earle, Lars-Åke Fredlund. A Methodology for Addressing the Second-Level Digital Divide. Computer Vision – ECCV 2020. 2020; 12067 ():331-337.

Chicago/Turabian Style

Susana Muñoz Hernández; Clara Benac Earle; Lars-Åke Fredlund. 2020. "A Methodology for Addressing the Second-Level Digital Divide." Computer Vision – ECCV 2020 12067, no. : 331-337.

Conference paper
Published: 25 September 2019 in Lecture Notes in Electrical Engineering
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Although all databases frameworks let us make conventional (crisp) searches, there are only a few of them that take into account some flexible, fuzzy, expressive criteria. The few of them that provide some of these searching characteristics are restricted to a particular database format, as FleSe that is devoted to search in a flexible way over Prolog databases. We have extended FleSe framework by an extraordinary feature that allows users to query various conventional and modern databases such as Prolog, CSV, XLS, XLSX, MySQL, and MongoDB or JSON in a fuzzy way. We have developed an adaptable and configurable platform for it so that any user can personalize at run-time. The fuzzy searching criteria can be created and added in a very user-friendly way, so that any user can upload his/her conventional (crisp) database, define the fuzzy search criteria that he/she is interested in and search at the database flexibly and expressively using concepts as similarity, fuzziness, qualification, and negation.

ACS Style

Mohammad Halim Deedar; Susana Muñoz Hernández. Extending a Flexible Searching Tool for Multiple Database Formats. Lecture Notes in Electrical Engineering 2019, 25 -35.

AMA Style

Mohammad Halim Deedar, Susana Muñoz Hernández. Extending a Flexible Searching Tool for Multiple Database Formats. Lecture Notes in Electrical Engineering. 2019; ():25-35.

Chicago/Turabian Style

Mohammad Halim Deedar; Susana Muñoz Hernández. 2019. "Extending a Flexible Searching Tool for Multiple Database Formats." Lecture Notes in Electrical Engineering , no. : 25-35.

Conference paper
Published: 24 August 2019 in Applied Computational Intelligence and Mathematical Methods
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We present a framework that allows any user (without the need of neither technical no theoretical knowledge) to define fuzzy criteria based on the non-fuzzy information stored in databases in an easy way. The interests for developing such a framework is to provide a human-oriented (fuzzy and non-fuzzy) search engine with a user-friendly interface to perform expressive and flexible searches over databases. We achieved this task by providing an intelligent interface for the users to define fuzzy criteria without having any knowledge about its low-level syntax or implementation details. Our framework allows users to pose different queries (combining crisp and fuzzy search criteria) over various conventional and modern data formats such as JSON, SQL, Prolog, CSV, XLS and XLSX. We believe our approach adds to the advancement for more intelligent and human-oriented fuzzy search engines.

ACS Style

Mohammad Halim Deedar; Susana Muñoz-Hernández. User-Friendly Interface for Introducing Fuzzy Criteria into Expressive Searches. Applied Computational Intelligence and Mathematical Methods 2019, 982 -997.

AMA Style

Mohammad Halim Deedar, Susana Muñoz-Hernández. User-Friendly Interface for Introducing Fuzzy Criteria into Expressive Searches. Applied Computational Intelligence and Mathematical Methods. 2019; ():982-997.

Chicago/Turabian Style

Mohammad Halim Deedar; Susana Muñoz-Hernández. 2019. "User-Friendly Interface for Introducing Fuzzy Criteria into Expressive Searches." Applied Computational Intelligence and Mathematical Methods , no. : 982-997.

Conference paper
Published: 27 May 2019 in Computer Vision – ECCV 2020
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A bi-valued logic is not enough to make an intelligent search engine to give us the result for the queries like “I am looking for a cheap restaurant, Mediterranean food or similar type”. With the integration of Fuzzy Logic and Logic Programming, we were able to model and pose flexible queries over databases. Therefore, we present a framework that allows users to pose their expressive queries based on defining similar relation criteria over various modern and conventional data formats such as JSON, SQL, CSV, XLS, and XLSX. The interest is in, for example, obtaining “drama movie” when asking for “romantic movie” (only if the similarity relation between drama and romantic movie is explicitly defined in the configuration file). The uses of similarity relation between values allow us to obtain more answers apart from the identical one. The searches that use two or more criteria are much more expressive and accurate. This framework provides the facility to define, modify and remove similarity relations from a user-friendly interface (without the need to be concern about the low-level syntax of the similarity criteria).

ACS Style

Mohammad Halim Deedar; Susana Muñoz-Hernández. Allowing Users to Create Similarity Relations for Their Flexible Searches over Databases. Computer Vision – ECCV 2020 2019, 526 -541.

AMA Style

Mohammad Halim Deedar, Susana Muñoz-Hernández. Allowing Users to Create Similarity Relations for Their Flexible Searches over Databases. Computer Vision – ECCV 2020. 2019; ():526-541.

Chicago/Turabian Style

Mohammad Halim Deedar; Susana Muñoz-Hernández. 2019. "Allowing Users to Create Similarity Relations for Their Flexible Searches over Databases." Computer Vision – ECCV 2020 , no. : 526-541.

Book chapter
Published: 01 January 2012 in Hybrid Evolutionary Algorithms
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Any realistic approach to automatic program parallelization must take into account practical issues related to the resource usage of parallel executions, such as the overheads associated with parallel tasks creation, migration of tasks to remote processors, and communication. The aim of granularity control techniques is avoiding such overheads undermining the benefits of parallel executions. For example, sufficient conditions have been proposed to ensure that the parallel execution of some given tasks will not take longer than their corresponding sequential execution. However, when the goal is to optimize the average execution time of several runs, such conditions can be very conservative, causing a loss in parallelization opportunities. To solve this problem, we have proposed novel conditions based on fuzzy logic and performed an experimental assessment with real programs. The results show that such conditions select the optimal type of execution in most cases and behave much better than the conservative conditions.

ACS Style

T. Trigo De La Vega; P. Lopez-Garcia; S. Muñoz-Hernández. A Fuzzy Approach to Resource Aware Automatic Parallelization. Hybrid Evolutionary Algorithms 2012, 229 -245.

AMA Style

T. Trigo De La Vega, P. Lopez-Garcia, S. Muñoz-Hernández. A Fuzzy Approach to Resource Aware Automatic Parallelization. Hybrid Evolutionary Algorithms. 2012; ():229-245.

Chicago/Turabian Style

T. Trigo De La Vega; P. Lopez-Garcia; S. Muñoz-Hernández. 2012. "A Fuzzy Approach to Resource Aware Automatic Parallelization." Hybrid Evolutionary Algorithms , no. : 229-245.

Journal article
Published: 15 May 2011 in Information Sciences
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We present the RFuzzy framework, a Prolog-based tool for representing and reasoning with fuzzy information. The advantages of our framework in comparison to previous tools along this line of research are its easy, user-friendly syntax, and its expressivity through the availability of default values and types. In this approach we describe the formal syntax, the operational semantics and the declarative semantics of RFuzzy (based on a lattice). A least model semantics, a least fixpoint semantics and an operational semantics are introduced and their equivalence is proven. We provide a real implementation that is free and available. (It can be downloaded from http://babel.ls.fi.upm.es/software/rfuzzy/.) Besides implementation details, we also discuss some actual applications using RFuzzy.

ACS Style

Susana Munoz-Hernandez; Víctor Pablos-Ceruelo; Hannes Strass. RFuzzy: Syntax, semantics and implementation details of a simple and expressive fuzzy tool over Prolog. Information Sciences 2011, 181, 1951 -1970.

AMA Style

Susana Munoz-Hernandez, Víctor Pablos-Ceruelo, Hannes Strass. RFuzzy: Syntax, semantics and implementation details of a simple and expressive fuzzy tool over Prolog. Information Sciences. 2011; 181 (10):1951-1970.

Chicago/Turabian Style

Susana Munoz-Hernandez; Víctor Pablos-Ceruelo; Hannes Strass. 2011. "RFuzzy: Syntax, semantics and implementation details of a simple and expressive fuzzy tool over Prolog." Information Sciences 181, no. 10: 1951-1970.

Journal article
Published: 03 August 2009 in Electronic Notes in Theoretical Computer Science
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Negation has traditionally been a difficult issue in Logic Programming. Most of Prolog programmers have been restricted to use just a weak negation technique, like negation as failure.Many alternative semantics were proposed for achieving constructive negation in the last 20 years, but no implementation was provided so far because of its exponential complexity and the difficulty for developing it. First effective implementations of constructive negation into standard Prolog compilers are available just recently, around 2003, provided by our previous works.In this paper we present an extension of our implementations by introducing types in programs, thus improving usability as well as efficiency in some cases of our implementations of constructive negation. This can make constructive negation an interesting approach for its use in data bases querying, web search, filtered search, ontologies querying, coding rules, business rules, etc.Thanks to the use of types, our constructive negation can provide concrete values as results, instead of constraints (as in our previous works). We provide details about the semantics and the implementation in our approaches of classical, finite constructive, and intensional negation. The paper also includes some practical examples additionally allowing for providing measurements of computational behavior

ACS Style

Susana Munoz-Hernandez; Juan Jose Moreno-Navarro. Extending Constructive Logic Negation with Types. Electronic Notes in Theoretical Computer Science 2009, 246, 183 -198.

AMA Style

Susana Munoz-Hernandez, Juan Jose Moreno-Navarro. Extending Constructive Logic Negation with Types. Electronic Notes in Theoretical Computer Science. 2009; 246 ():183-198.

Chicago/Turabian Style

Susana Munoz-Hernandez; Juan Jose Moreno-Navarro. 2009. "Extending Constructive Logic Negation with Types." Electronic Notes in Theoretical Computer Science 246, no. : 183-198.

Conference paper
Published: 01 January 2009 in Computer Vision
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Fuzzy reasoning is a very productive research field that during the last years has provided a number of theoretical approaches and practical implementation prototypes. Nevertheless, the classical implementations, like Fril, are not adapted to the latest formal approaches, like multi-adjoint logic semantics. Some promising implementations, like Fuzzy Prolog, are so general that the regular user/programmer does not feel comfortable because either the representation of fuzzy concepts is complex or the results of the fuzzy queries are difficult to interpret. In this paper we present a modern framework, RFuzzy, that is modeling multi-adjoint logic in a practical way. It provides some extensions as default values (to represent missing information), partial default values (for a subset of data) and typed variables. RFuzzy represents the truth value of predicates using facts, rules and also can define fuzzy predicates as continuous functions. Queries are answered with direct results (instead of providing complex constraints), so it is easy to use for any person that wants to represent a problem using fuzzy reasoning in a simple way (just using the classical fuzzy representation with real numbers). The most promising characteristic of RFuzzy is that the user can obtain constructive answers to queries that restrict the truth value.

ACS Style

Susana Munoz-Hernandez; Victor Pablos Ceruelo; Hannes Strass. RFuzzy: An Expressive Simple Fuzzy Compiler. Computer Vision 2009, 270 -277.

AMA Style

Susana Munoz-Hernandez, Victor Pablos Ceruelo, Hannes Strass. RFuzzy: An Expressive Simple Fuzzy Compiler. Computer Vision. 2009; ():270-277.

Chicago/Turabian Style

Susana Munoz-Hernandez; Victor Pablos Ceruelo; Hannes Strass. 2009. "RFuzzy: An Expressive Simple Fuzzy Compiler." Computer Vision , no. : 270-277.

Book chapter
Published: 01 January 2007 in Computational Intelligence Based on Lattice Theory
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Summary. Incomplete information is a problem in many aspects of actual environments. Furthermore, in many scenarios the knowledge is not represented in a crisp way. It is common to find fuzzy concepts or problems with some level of uncertainty. There are not many practical systems which handle fuzziness and uncertainty and the few examples that we can find are used by a minority. To extend a popular system (which many programmers are using) with the ability of combining crisp and fuzzy knowledge representations seems to be an interesting issue.

ACS Style

Susana Munoz-Hernandez; Claudio Vaucheret. Fuzzy Prolog: Default Values to Represent Missing Information. Computational Intelligence Based on Lattice Theory 2007, 67, 287 -308.

AMA Style

Susana Munoz-Hernandez, Claudio Vaucheret. Fuzzy Prolog: Default Values to Represent Missing Information. Computational Intelligence Based on Lattice Theory. 2007; 67 ():287-308.

Chicago/Turabian Style

Susana Munoz-Hernandez; Claudio Vaucheret. 2007. "Fuzzy Prolog: Default Values to Represent Missing Information." Computational Intelligence Based on Lattice Theory 67, no. : 287-308.

Preprint
Published: 22 August 2005
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Incomplete information is a problem in many aspects of actual environments. Furthermore, in many sceneries the knowledge is not represented in a crisp way. It is common to find fuzzy concepts or problems with some level of uncertainty. There are not many practical systems which handle fuzziness and uncertainty and the few examples that we can find are used by a minority. To extend a popular system (which many programmers are using) with the ability of combining crisp and fuzzy knowledge representations seems to be an interesting issue. Our first work (Fuzzy Prolog) was a language that models $\mathcal{B}([0,1])$-valued Fuzzy Logic. In the Borel algebra, $\mathcal{B}([0,1])$, truth value is represented using unions of intervals of real numbers. This work was more general in truth value representation and propagation than previous works. An interpreter for this language using Constraint Logic Programming over Real numbers (CLP(${\cal R}$)) was implemented and is available in the Ciao system. Now, we enhance our former approach by using default knowledge to represent incomplete information in Logic Programming. We also provide the implementation of this new framework. This new release of Fuzzy Prolog handles incomplete information, it has a complete semantics (the previous one was incomplete as Prolog) and moreover it is able to combine crisp and fuzzy logic in Prolog programs. Therefore, new Fuzzy Prolog is more expressive to represent real world. Fuzzy Prolog inherited from Prolog its incompleteness. The incorporation of default reasoning to Fuzzy Prolog removes this problem and requires a richer semantics which we discuss.

ACS Style

Susana Munoz-Hernandez; Claudio Vaucheret. Extending Prolog with Incomplete Fuzzy Information. 2005, 1 .

AMA Style

Susana Munoz-Hernandez, Claudio Vaucheret. Extending Prolog with Incomplete Fuzzy Information. . 2005; ():1.

Chicago/Turabian Style

Susana Munoz-Hernandez; Claudio Vaucheret. 2005. "Extending Prolog with Incomplete Fuzzy Information." , no. : 1.

Conference paper
Published: 01 January 2005 in Computer Vision – ECCV 2020
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Truth values associated to fuzzy variables can be represented in an ordeal of different flavors, such as real numbers, percentiles, intervals, unions of intervals, and continuous or discrete functions on different domains. Many of the most interesting fuzzy problems deal with a discrete range of truth values. In this work we represent these ranges using Constraint Logic Programming over Finite Domains (CLP(\(\mathcal{FD}\))). This allows to produce finite enumerations of constructive answers instead of complicated, hardly self-explanatory, constraints expressions. Another advantage of representing fuzzy models through finite domains is that some of the existing techniques and algorithms of the field of distributed constraint programming can be borrowed. In this paper we exploit these considerations in order to create a new generation of collaborative fuzzy agents in a distributed environment.

ACS Style

Susana Munoz-Hernandez; Jose Manuel Gomez-Perez. Solving Collaborative Fuzzy Agents Problems with CLP( $\mathcal{FD}$ ). Computer Vision – ECCV 2020 2005, 187 -202.

AMA Style

Susana Munoz-Hernandez, Jose Manuel Gomez-Perez. Solving Collaborative Fuzzy Agents Problems with CLP( $\mathcal{FD}$ ). Computer Vision – ECCV 2020. 2005; ():187-202.

Chicago/Turabian Style

Susana Munoz-Hernandez; Jose Manuel Gomez-Perez. 2005. "Solving Collaborative Fuzzy Agents Problems with CLP( $\mathcal{FD}$ )." Computer Vision – ECCV 2020 , no. : 187-202.

Conference paper
Published: 01 January 2004 in Computer Vision
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Logic Programming has been advocated as a language for system specification, especially for those involving logical behaviours, rules and knowledge. However, modeling problems involving negation, which is quite natural in many cases, is somewhat limited if Prolog is used as the specification / implementation language. These restrictions are not related to theory viewpoint, where users can find many different models with their respective semantics; they concern practical implementation issues. The negation capabilities supported by current Prolog systems are rather constrained, and there is no a correct and complete implementation available. In this paper, we refine and propose some extensions to the classical method of constructive negation, providing the complete theoretical algorithm. Furthermore, we also discuss implementation issues providing a preliminary implementation and also an optimized one to negate predicates with a finite number of solutions.

ACS Style

Susana Munoz-Hernandez; Juan José Moreno-Navarro. Implementation Results in Classical Constructive Negation. Computer Vision 2004, 3132, 284 -298.

AMA Style

Susana Munoz-Hernandez, Juan José Moreno-Navarro. Implementation Results in Classical Constructive Negation. Computer Vision. 2004; 3132 ():284-298.

Chicago/Turabian Style

Susana Munoz-Hernandez; Juan José Moreno-Navarro. 2004. "Implementation Results in Classical Constructive Negation." Computer Vision 3132, no. : 284-298.