Applying the fuzzy analytical hierarchy process in digital marketing

The fuzzy analytical network process (FANP) is introduced as a potential multi-criteria-decision-making (MCDM) method to improve digital marketing management endeavors. Today’s information overload makes digital marketing optimization, which is needed to continuously improve one’s business, increasingly difficult. The proposed FANP framework is a method for enhancing the interaction between customers and marketers (i.e., involved stakeholders) and thus for reducing the challenges of big data. The presented implementation takes realities’ fuzziness into account to manage the constant interaction and continuous development of communication between marketers and customers on the Web. Using this FANP framework, the marketers are able to increasingly meet the varying requirements of their customers. To improve the understanding of the implementation, advanced visualization methods (e.g., wireframes) are used.

A Dynamic Route Planning Prototype for Cognitive Cities

A software prototype for dynamic route planning in the travel industry for cognitive cities is presented in this paper. In contrast to existing tools, the prototype enhances the travel experience (i.e., sightseeing) by allowing additional flexibility to the user. The theoretical background of the paper strengthens the understanding of the introduced concepts (e.g., cognitive cities, fuzzy logic, graph databases) to comprehend the presented prototype. The prototype applies an instantiation and enhancement of the graph database Neo4j . For didactical reasons and to strengthen the understanding of this prototype a scenario, applied to route planning in the city of Bern (Switzerland) is shown in the paper.

Obtaining contradiction measure on intuitionistic fuzzy sets from fuzzy connectives

In a previous paper, we proposed an axiomatic model for measuring self-contradiction in the framework of Atanassov fuzzy sets. This way, contradiction measures that are semicontinuous and completely semicontinuous, from both below and above, were defined. Although some examples were given, the problem of finding families of functions satisfying the different axioms remained open. The purpose of this paper is to construct some families of contradiction measures firstly using continuous t-norms and t-conorms, and secondly by means of strong negations. In both cases, we study the properties that they satisfy. These families are then classified according the different kinds of measures presented in the above paper.

Aproximaciones del conjunto eficiente en decisión multicriterio

El conjunto eficiente en la Teoría de la Decisión Multicriterio juega un papel fundamental en los procesos de solución ya que es en este conjunto donde el decisor debe hacer su elección más preferida. Sin embargo, la generación de tal conjunto puede ser difícil, especialmente en problemas continuos y/o no lineales. El primer capítulo de esta memoria, es introductorio a la Decisión Multicriterio y en él se exponen aquellos conceptos y herramientas que se van a utilizar en desarrollos posteriores. El segundo capítulo estudia los problemas de Toma de Decisiones en ambiente de certidumbre. La herramienta básica y punto de partida es la función de valor vectorial que refleja imprecisión sobre las preferencias del decisor. Se propone una caracterización del conjunto de valor eficiente y diferentes aproximaciones con sus propiedades de encaje y convergencia. Varios algoritmos interactivos de solución complementan los desarrollos teóricos. El tercer capítulo está dedicado al caso de ambiente de incertidumbre. Tiene un desarrollo parcialmente paralelo al anterior y utiliza la función de utilidad vectorial como herramienta de modelización de preferencias del decisor. A partir de la consideración de las distribuciones simples se introduce la eficiencia en utilidad, su caracterización y aproximaciones, que posteriormente se extienden a los casos de distribuciones discretas y continuas. En el cuarto capítulo se estudia el problema en ambiente difuso, aunque de manera introductoria. Concluimos sugiriendo distintos problemas abiertos.---ABSTRACT---The efficient set of a Multicriteria Decicion-Making Problem plays a fundamental role in the solution process since the Decisión Maker's preferred choice should be in this set. However, the computation of that set may be difficult, specially in continuous and/or nonlinear problems. Chapter one introduces Multicriteria Decision-Making. We review basic concepts and tools for later developments. Chapter two studies Decision-Making problems under certainty. The basic tool is the vector valué function, which represents imprecisión in the DM's preferences. We propose a characterization of the valué efficient set and different approximations with nesting and convergence properties. Several interactive algorithms complement the theoretical results. We devote Chapter three to problems under uncertainty. The development is parallel to the former and uses vector utility functions to model the DM's preferences. We introduce utility efficiency for simple distributions, its characterization and some approximations, which we partially extend to discrete and continuous classes of distributions. Chapter four studies the problem under fuzziness, at an exploratory level. We conclude with several open problems.

Extending the expressiveness of fuzzy logic languages

En el trabajo que aquí presentamos se incluye la base teórica (sintaxis y semántica) y una implementación de un framework para codificar el razonamiento de la representación difusa o borrosa del mundo (tal y como nosotros, seres humanos, entendemos éste). El interés en la realización de éste trabajo parte de dos fuentes: eliminar la complejidad existente cuando se realiza una implementación con un lenguaje de programación de los llamados de propósito general y proporcionar una herramienta lo suficientemente inteligente para dar respuestas de forma constructiva a consultas difusas o borrosas. El framework, RFuzzy, permite codificar reglas y consultas en una sintaxis muy cercana al lenguaje natural usado por los seres humanos para expresar sus pensamientos, pero es bastante más que eso. Permite representar conceptos muy interesantes, como fuzzificaciones (funciones usadas para convertir conceptos no difusos en difusos), valores por defecto (que se usan para devolver resultados un poco menos válidos que los que devolveríamos si tuviésemos la información necesaria para calcular los más válidos), similaridad entre atributos (característica que utilizamos para buscar aquellos individuos en la base de datos con una característica similar a la buscada), sinónimos o antónimos y, además, nos permite extender el numero de conectivas y modificadores (incluyendo modificadores de negación) que podemos usar en las reglas y consultas. La personalización de la definición de conceptos difusos (muy útil para lidiar con el carácter subjetivo de los conceptos borrosos, donde nos encontramos con que cualificar a alguien de “alto” depende de la altura de la persona que cualifica) es otra de las facilidades incluida. Además, RFuzzy implementa la semántica multi-adjunta. El interés en esta reside en que introduce la posibilidad de obtener la credibilidad de una regla a partir de un conjunto de datos y una regla dada y no solo el grado de satisfacción de una regla a partir de el universo modelado en nuestro programa. De esa forma podemos obtener automáticamente la credibilidad de una regla para una determinada situación. Aún cuando la contribución teórica de la tesis es interesante en si misma, especialmente la inclusión del modificador de negacion, sus multiples usos practicos lo son también. Entre los diferentes usos que se han dado al framework destacamos el reconocimiento de emociones, el control de robots, el control granular en computacion paralela/distribuída y las busquedas difusas o borrosas en bases de datos. ABSTRACT In this work we provide a theoretical basis (syntax and semantics) and a practical implementation of a framework for encoding the reasoning and the fuzzy representation of the world (as human beings understand it). The interest for this work comes from two sources: removing the existing complexity when doing it with a general purpose programming language (one developed without focusing in providing special constructions for representing fuzzy information) and providing a tool intelligent enough to answer, in a constructive way, expressive queries over conventional data. The framework, RFuzzy, allows to encode rules and queries in a syntax very close to the natural language used by human beings to express their thoughts, but it is more than that. It allows to encode very interesting concepts, as fuzzifications (functions to easily fuzzify crisp concepts), default values (used for providing results less adequate but still valid when the information needed to provide results is missing), similarity between attributes (used to search for individuals with a characteristic similar to the one we are looking for), synonyms or antonyms and it allows to extend the number of connectives and modifiers (even negation) we can use in the rules. The personalization of the definition of fuzzy concepts (very useful for dealing with the subjective character of fuzziness, in which a concept like tall depends on the height of the person performing the query) is another of the facilities included. Besides, RFuzzy implements the multi-adjoint semantics. The interest in them is that in addition to obtaining the grade of satisfaction of a consequent from a rule, its credibility and the grade of satisfaction of the antecedents we can determine from a set of data how much credibility we must assign to a rule to model the behaviour of the set of data. So, we can determine automatically the credibility of a rule for a particular situation. Although the theoretical contribution is interesting by itself, specially the inclusion of the negation modifier, the practical usage of it is equally important. Between the different uses given to the framework we highlight emotion recognition, robocup control, granularity control in parallel/distributed computing and flexible searches in databases.

Biometric authentication of users through iris by using key binding and similarity preserving hash functions = Autenticación biométrica de usuarios a través del iris mediante la ocultación de claves y funciones resumen que preservan la similitud

El extraordinario auge de las nuevas tecnologías de la información, el desarrollo de la Internet de las Cosas, el comercio electrónico, las redes sociales, la telefonía móvil y la computación y almacenamiento en la nube, han proporcionado grandes beneficios en todos los ámbitos de la sociedad. Junto a éstos, se presentan nuevos retos para la protección y privacidad de la información y su contenido, como la suplantación de personalidad y la pérdida de la confidencialidad e integridad de los documentos o las comunicaciones electrónicas. Este hecho puede verse agravado por la falta de una frontera clara que delimite el mundo personal del mundo laboral en cuanto al acceso de la información. En todos estos campos de la actividad personal y laboral, la Criptografía ha jugado un papel fundamental aportando las herramientas necesarias para garantizar la confidencialidad, integridad y disponibilidad tanto de la privacidad de los datos personales como de la información. Por otro lado, la Biometría ha propuesto y ofrecido diferentes técnicas con el fin de garantizar la autentificación de individuos a través del uso de determinadas características personales como las huellas dáctilares, el iris, la geometría de la mano, la voz, la forma de caminar, etc. Cada una de estas dos ciencias, Criptografía y Biometría, aportan soluciones a campos específicos de la protección de datos y autentificación de usuarios, que se verían enormemente potenciados si determinadas características de ambas ciencias se unieran con vistas a objetivos comunes. Por ello es imperativo intensificar la investigación en estos ámbitos combinando los algoritmos y primitivas matemáticas de la Criptografía con la Biometría para dar respuesta a la demanda creciente de nuevas soluciones más técnicas, seguras y fáciles de usar que potencien de modo simultáneo la protección de datos y la identificacíón de usuarios. En esta combinación el concepto de biometría cancelable ha supuesto una piedra angular en el proceso de autentificación e identificación de usuarios al proporcionar propiedades de revocación y cancelación a los ragos biométricos. La contribución de esta tesis se basa en el principal aspecto de la Biometría, es decir, la autentificación segura y eficiente de usuarios a través de sus rasgos biométricos, utilizando tres aproximaciones distintas: 1. Diseño de un esquema criptobiométrico borroso que implemente los principios de la biometría cancelable para identificar usuarios lidiando con los problemas acaecidos de la variabilidad intra e inter-usuarios. 2. Diseño de una nueva función hash que preserva la similitud (SPHF por sus siglas en inglés). Actualmente estas funciones se usan en el campo del análisis forense digital con el objetivo de buscar similitudes en el contenido de archivos distintos pero similares de modo que se pueda precisar hasta qué punto estos archivos pudieran ser considerados iguales. La función definida en este trabajo de investigación, además de mejorar los resultados de las principales funciones desarrolladas hasta el momento, intenta extender su uso a la comparación entre patrones de iris. 3. Desarrollando un nuevo mecanismo de comparación de patrones de iris que considera tales patrones como si fueran señales para compararlos posteriormente utilizando la transformada de Walsh-Hadarmard. Los resultados obtenidos son excelentes teniendo en cuenta los requerimientos de seguridad y privacidad mencionados anteriormente. Cada uno de los tres esquemas diseñados han sido implementados para poder realizar experimentos y probar su eficacia operativa en escenarios que simulan situaciones reales: El esquema criptobiométrico borroso y la función SPHF han sido implementados en lenguaje Java mientras que el proceso basado en la transformada de Walsh-Hadamard en Matlab. En los experimentos se ha utilizado una base de datos de imágenes de iris (CASIA) para simular una población de usuarios del sistema. En el caso particular de la función de SPHF, además se han realizado experimentos para comprobar su utilidad en el campo de análisis forense comparando archivos e imágenes con contenido similar y distinto. En este sentido, para cada uno de los esquemas se han calculado los ratios de falso negativo y falso positivo. ABSTRACT The extraordinary increase of new information technologies, the development of Internet of Things, the electronic commerce, the social networks, mobile or smart telephony and cloud computing and storage, have provided great benefits in all areas of society. Besides this fact, there are new challenges for the protection and privacy of information and its content, such as the loss of confidentiality and integrity of electronic documents and communications. This is exarcebated by the lack of a clear boundary between the personal world and the business world as their differences are becoming narrower. In both worlds, i.e the personal and the business one, Cryptography has played a key role by providing the necessary tools to ensure the confidentiality, integrity and availability both of the privacy of the personal data and information. On the other hand, Biometrics has offered and proposed different techniques with the aim to assure the authentication of individuals through their biometric traits, such as fingerprints, iris, hand geometry, voice, gait, etc. Each of these sciences, Cryptography and Biometrics, provides tools to specific problems of the data protection and user authentication, which would be widely strengthen if determined characteristics of both sciences would be combined in order to achieve common objectives. Therefore, it is imperative to intensify the research in this area by combining the basics mathematical algorithms and primitives of Cryptography with Biometrics to meet the growing demand for more secure and usability techniques which would improve the data protection and the user authentication. In this combination, the use of cancelable biometrics makes a cornerstone in the user authentication and identification process since it provides revocable or cancelation properties to the biometric traits. The contributions in this thesis involve the main aspect of Biometrics, i.e. the secure and efficient authentication of users through their biometric templates, considered from three different approaches. The first one is designing a fuzzy crypto-biometric scheme using the cancelable biometric principles to take advantage of the fuzziness of the biometric templates at the same time that it deals with the intra- and inter-user variability among users without compromising the biometric templates extracted from the legitimate users. The second one is designing a new Similarity Preserving Hash Function (SPHF), currently widely used in the Digital Forensics field to find similarities among different files to calculate their similarity level. The function designed in this research work, besides the fact of improving the results of the two main functions of this field currently in place, it tries to expand its use to the iris template comparison. Finally, the last approach of this thesis is developing a new mechanism of handling the iris templates, considering them as signals, to use the Walsh-Hadamard transform (complemented with three other algorithms) to compare them. The results obtained are excellent taking into account the security and privacy requirements mentioned previously. Every one of the three schemes designed have been implemented to test their operational efficacy in situations that simulate real scenarios: The fuzzy crypto-biometric scheme and the SPHF have been implemented in Java language, while the process based on the Walsh-Hadamard transform in Matlab. The experiments have been performed using a database of iris templates (CASIA-IrisV2) to simulate a user population. The case of the new SPHF designed is special since previous to be applied i to the Biometrics field, it has been also tested to determine its applicability in the Digital Forensic field comparing similar and dissimilar files and images. The ratios of efficiency and effectiveness regarding user authentication, i.e. False Non Match and False Match Rate, for the schemes designed have been calculated with different parameters and cases to analyse their behaviour.

Did the German court do Europe a favor? Bruegel Working Paper 2014/09, July 2014

The European Central Bank’s Outright Monetary Transactions (OMT) programme was a politically-pragmatic tool to diffuse the euro-area crisis. But it did not deal with the fundamental incompleteness of the European monetary union. As such, it blurred the boundary between monetary and fiscal policy. The fuzziness of this boundary helped in the short-term but pushed political and economic risks to the future. Unless a credible commitment to enforcing losses on private creditors is instituted, these conundrums will persist. The German Federal Constitutional Court has helped by insisting that such a dialogue be conducted in order to achieve a more durable political and economic solution. A study of the European Union Court of Justice’s Pringle decision (Thomas Pringle v Government of Ireland, Ireland and The Attorney General, Case C-370/12, ECJ, 27 November 2012) suggests that the ECJ will also not rubber-stamp the OMT – and, if it does, the legal victory will not resolve the fundamental dilemmas.

A Framework of Fuzzy Diagnosis

Fault diagnosis has become an important component in intelligent systems, such as intelligent control systems and intelligent eLearning systems. Reiter's diagnosis theory, described by first-order sentences, has been attracting much attention in this field. However, descriptions and observations of most real-world situations are related to fuzziness because of the incompleteness and the uncertainty of knowledge, e. g., the fault diagnosis of student behaviors in the eLearning processes. In this paper, an extension of Reiter's consistency-based diagnosis methodology, Fuzzy Diagnosis, has been proposed, which is able to deal with incomplete or fuzzy knowledge. A number of important properties of the Fuzzy diagnoses schemes have also been established. The computing of fuzzy diagnoses is mapped to solving a system of inequalities. Some special cases, abstracted from real-world situations, have been discussed. In particular, the fuzzy diagnosis problem, in which fuzzy observations are represented by clause-style fuzzy theories, has been presented and its solving method has also been given. A student fault diagnostic problem abstracted from a simplified real-world eLearning case is described to demonstrate the application of our diagnostic framework.

A fuzzy levelised energy cost method for renewable energy technology assessment

Renewable energy project development is highly complex and success is by no means guaranteed. Decisions are often made with approximate or uncertain information yet the current methods employed by decision-makers do not necessarily accommodate this. Levelised energy costs (LEC) are one such commonly applied measure utilised within the energy industry to assess the viability of potential projects and inform policy. The research proposes a method for achieving this by enhancing the traditional discounting LEC measure with fuzzy set theory. Furthermore, the research develops the fuzzy LEC (F-LEC) methodology to incorporate the cost of financing a project from debt and equity sources. Applied to an example bioenergy project, the research demonstrates the benefit of incorporating fuzziness for project viability, optimal capital structure and key variable sensitivity analysis decision-making. The proposed method contributes by incorporating uncertain and approximate information to the widely utilised LEC measure and by being applicable to a wide range of energy project viability decisions. © 2013 Elsevier Ltd. All rights reserved.

Performance measurement with fuzzy data envelopment analysis

The intensity of global competition and ever-increasing economic uncertainties has led organizations to search for more efficient and effective ways to manage their business operations. Data envelopment analysis (DEA) has been widely used as a conceptually simple yet powerful tool for evaluating organizational productivity and performance. Fuzzy DEA (FDEA) is a promising extension of the conventional DEA proposed for dealing with imprecise and ambiguous data in performance measurement problems. This book is the first volume in the literature to present the state-of-the-art developments and applications of FDEA. It is designed for students, educators, researchers, consultants and practicing managers in business, industry, and government with a basic understanding of the DEA and fuzzy logic concepts.

The state of the art in fuzzy data envelopment analysis

Data envelopment analysis (DEA) is a methodology for measuring the relative efficiencies of a set of decision making units (DMUs) that use multiple inputs to produce multiple outputs. Crisp input and output data are fundamentally indispensable in conventional DEA. However, the observed values of the input and output data in real-world problems are sometimes imprecise or vague. Many researchers have proposed various fuzzy methods for dealing with the imprecise and ambiguous data in DEA. This chapter provides a taxonomy and review of the fuzzy DEA (FDEA) methods. We present a classification scheme with six categories, namely, the tolerance approach, the α-level based approach, the fuzzy ranking approach, the possibility approach, the fuzzy arithmetic, and the fuzzy random/type-2 fuzzy set. We discuss each classification scheme and group the FDEA papers published in the literature over the past 30 years. © 2014 Springer-Verlag Berlin Heidelberg.

Credibility theory-based available transfer capability assessment

Since the development of large scale power grid interconnections and power markets, research on available transfer capability (ATC) has attracted great attention. The challenges for accurate assessment of ATC originate from the numerous uncertainties in electricity generation, transmission, distribution and utilization sectors. Power system uncertainties can be mainly described as two types: randomness and fuzziness. However, the traditional transmission reliability margin (TRM) approach only considers randomness. Based on credibility theory, this paper firstly built models of generators, transmission lines and loads according to their features of both randomness and fuzziness. Then a random fuzzy simulation is applied, along with a novel method proposed for ATC assessment, in which both randomness and fuzziness are considered. The bootstrap method and multi-core parallel computing technique are introduced to enhance the processing speed. By implementing simulation for the IEEE-30-bus system and a real-life system located in Northwest China, the viability of the models and the proposed method is verified.

Assessing productive efficiency of banks using integrated Fuzzy-DEA and bootstrapping:a case of Mozambican banks

Performance analysis has become a vital part of the management practices in the banking industry. There are numerous applications using DEA models to estimate efficiency in banking, and most of them assume that inputs and outputs are known with absolute precision. Here, we propose new Fuzzy-DEA α-level models to assess underlying uncertainty. Further, bootstrap truncated regressions with fixed factors are used to measure the impact of each model on the efficiency scores and to identify the most relevant contextual variables on efficiency. The proposed models have been demonstrated using an application in Mozambican banks to handle the underlying uncertainty. Findings reveal that fuzziness is predominant over randomness in interpreting the results. In addition, fuzziness can be used by decision-makers to identify missing variables to help in interpreting the results. Price of labor, price of capital, and market-share were found to be the significant factors in measuring bank efficiency. Managerial implications are addressed.