Definición de un modelo de representación del conocimiento para procesos de estimación de presupuestos

La estimación de precios es un proceso crítico para la elaboración de presupuestos en compañías que tienen que competir para obtener pedidos ofreciendo precios competitivos. En concreto, las compañías de mecanizado de piezas, dicho proceso es complejo, pues se pueden plantear un gran número de variantes. En este caso un experto en la fabricación está generalmente al cargo de esta tarea. Sin embargo, estos expertos tienen a cargo otras tareas, también importantes para la compañía, que deben atender. Es habitual la utilización de sistemas software que automaticen la estimación de costes, y los sistemas basados en conocimiento son una de las principales alternativas por dos razones fundamentales. Por un lado, la aplicación de este conocimiento constituye un área abierta de investigación que debe ser explotada. Por otro lado, la investigación acerca de los sistemas basados en conocimiento plantea la necesidad de nuevos modelos y metodologías que integren la representación del conocimiento con la web para la creación de nuevos sistemas expertos basados en web. Para responder a los dos aspectos que se han identificado, la presente tesis plantea un modelo de representación del conocimiento para capturar la experiencia de un experto orientado a la estimación de presupuestos. Este modelo de representación cubre además el conocimiento que puede obtenerse de otras aplicaciones, permite la utilización de modelos de estimación detallados que complementen al conocimiento del experto e integra la representación con tecnologías web. La siguiente aportación de esta tesis doctoral es un motor de solución basado en el modelo propuesto capaz de automatizar los procesos representados, en un entorno web. Se trata de un motor de solución genérico que no es exclusivo para la implementación del proceso de representación de la fábrica en la que se ha llevado a cabo la validación. Finalmente se ha aportado una herramienta de modelado que permite la representación del conocimiento de un experto al tiempo que facilita el proceso de validación por medio de la funcionalidad de traza. Además de los objetivos e hipótesis inicialmente planteados, la presente tesis aporta la definición formal del modelo de representación del conocimiento. Con ello se da la posibilidad de compartir la representación de distintos procesos entre expertos de diferentes lugares basándose en una definición común. La metodología seguida para la elaboración de esta tesis, ha consistido en: 1. Estudio del estado del arte. Se han analizado las distintas técnicas y herramientas empleadas en la estimación de precios dentro de las compañías de fabricación versátil, poniendo especial atención en las que se basan en conocimiento. En este sentido se ha encontrado que se emplean más conocimientos teóricos que conocimientos procedentes de la experiencia para la creación de estos sistemas. 2. Análisis del problema. En esta fase se ha realizado el planteamiento de las hipótesis de investigación, basadas en la necesidad de un modelo de representación capaz de representar el conocimiento sobre el proceso de estimación de presupuestos, el acceso al conocimiento que pueda contener otro sistema y el intercambio de información con agentes externos cuando sea necesario obtener información adicional. Adicionalmente es necesario un motor capaz de automatizar el proceso y que éste sea capaz de obtener resultados similares a los de un experto. 3. Planteamiento de la solución. En esta fase se ha planteado el modelo de representación que se propone como solución a los problemas identificados. 4. Validación. En esta fase se ha creado una herramienta de modelado basada en el modelo propuesto, así como un motor capaz de interpretar y ejecutar los procesos representados. A partir de ambas herramientas, se ha desarrollo de un sistema basado en conocimiento y comprobación de las hip´otesis de investigación. Para ello se ha modelado un proceso real en una fábrica de piezas mecanizadas. 5. Análisis de los resultados obtenidos. Tras la validación se obtuvieron un conjunto de resultados, tanto a nivel de representación como a nivel de ejecución de proceso que fueron analizados para determinar la validez del modelo y las herramientas propuestas. 6. Documentación. A lo largo de todo el proceso de elaboración de la tesis se ha generado la documentación que constituye la presente tesis doctoral. Las conclusiones tras la elaboración, validación y análisis de los resultados obtenidos, han mostrado que el modelo propuesto puede representar el conocimiento de un experto en el dominio de la fabricación de piezas mecanizadas. Además la validación realizada muestra como el modelo se integra con la Web permitiendo, gracias a la implementación de una herramienta de modelado y un motor de soluciones, la creación de sistemas basados en Web que afronten en concreto el problema del cálculo de precios, admitiendo problemas de otros dominios en futuros trabajos de investigación. ________________________________________________In order to satisfy the requirements for the european doctorate mention, the summary of this phd thesis has been written in English. This summary includes methodology, main contribution and conclusions. The chapter 9 “Conclusions” has also been written in English. Price estimation is a critical process for the preparation of quotations in companies that have to compete with other companies by offering competitive prices in order to have demand of orders. For machining parts companies, the estimation process is very complex, as a big number of variants may appear. An expert in manufacturing is usually in charge of this process. However, the lack of qualifying experts in such factories implies extra work for the experts and they already have other critical tasks to which they must attend. The use of conventional software systems is usual as they automate the costs’ estimation, and the knowledge based systems are one of the main alternatives for two reasons. On the one hand, this knowledge’s application constitutes an open area of research that must be exploited. On the other hand, the research on systems based on knowledge raises the need of new models and methodologies that incorporate the knowledge’s representation with the web for the creation of new expert systems based on the web. In order to give an answer to the former two aspects that have been identified, this thesis presents a knowledge representation model for representing an expert’s experience orientated to the quotation process. This representation model also covers the knowledge that can be obtained from other applications, allows the use of detailed estimation models that complement the expert’s knowledge and incorporates the representation by using web technologies. The next contribution of this thesis is a solution engine based on the proposed model which is able to automate the represented processes in a web environment. The purpose of the engine is not restricted to the concrete domain of this thesis (it is generic), and it can be used for other domains in future research works. Finally a modeling tool based on the proposed model is presented. Such a tool allows the knowledge representation of an expert and at the same time it provides the validation by means of trace functionality. Besides the objectives and hypotheses initially proposed, a formal definition of the model is presented. It makes possible the knowledge sharing between different experts in different places using a shared language. The steps taken to conduct the research are the following: 1. State of the art review. In this phase, several price estimation techniques and tools within versatile manufacturing companies has been reviewed, paying special attention to the knowledge based techniques and tools. It has been found that the creation of these systems use more theoretic knowledge than knowledge provided by experience. 2. Problem analysis. In this phase research hypotheses have been put forward. Such hypotheses are based on the need of a knowledge representation model which is able to represent knowledge about the quotation process, the knowledge stored in external applications, and the information exchange with external agents when it is necessary to obtain additional information. Additionally a solution engine is required in order to automate the represented process and so that it is capable of obtaining similar results to those from an expert. 3. Problem Solution. In this phase the knowledge representation model has been defined in order to solve the problems previously identified. 4. Validation. In this phase a knowledge representation tool has been developed based on the proposed knowledge representation model. Also a solution engine has been developed in order to interpret and execute the processes modelled by means of the knowledge representation tool. Using the representation tool and the solution engine, a knowledge based system has been developed in order to validate the proposed hypotheses. The knowledge based system has been implemented in the context of a machining parts company. 5. Analysis of the results obtained. In this phase the results of the validation phase were evaluated in order to determine the validity of the proposed model and tools. 6. Documentation. During the overall research work the present thesis has been documented in order to generate the present document. After the elaboration, validation and analysis of the results, we have concluded that the proposed model can represent the knowledge of an expert in the domain of the quotation process for machining parts. Furthermore, the validation results show that the proposed model integrates the representation with the Web technologies. It allows, by means of the modelling tool and the solution engine, developing web based expert systems for the specific problem of the quotation process and, in future research works, for other domains

Challenges And Opportunities In Analytic-Predictive Environments Of Big Data And Natural Language Processing For Social Network Rating Systems

Social Media is playing a key role in today's society. Many of the events that are taking place in diverse human activities could be explained by the study of these data. Big Data is a relatively new parading in Computer Science that is gaining increasing interest by the scientific community. Big Data Predictive Analytics is a Big Data discipline that is mostly used to analyze what is in the huge amounts of data and then perform predictions based on such analysis using advanced mathematics and computing techniques. The study of Social Media Data involves disciplines like Natural Language Processing, by the integration of this area to academic studies, useful findings have been achieved. Social Network Rating Systems are online platforms that allow users to know about goods and services, the way in how users review and rate their experience is a field of evolving research. This paper presents a deep investigation in the state of the art of these areas to discover and analyze the current status of the research that has been developed so far by academics of diverse background

Automatic learning framework for pharmaceutical record matching

Pharmaceutical manufacturers need to analyse a vast number of products in their daily activities. Many times, the same product can be registered several times by different systems using different attributes, and these companies require accurate and quality information regarding their products since these products are drugs. The central hypothesis of this research work is that machine learning can be applied to this domain to efficiently merge different data sources and match the records related to the same product. No human is able to do this in a reasonable way because the number of records to be matched is extremely high. This article presents a framework for pharmaceutical record matching based on machine learning techniques in a big data environment. The proposed framework aims to explode the well-known rules for the matching of records from different databases for training machine learning models. Then the trained models are evaluated by predicting matches with records that do not follow these known rules. Finally, the production environment is simulated by generating a huge amount of combinations of records and predicting the matches. The obtained results show that, despite the good results obtained with the training datasets, in the production environment, the average accuracy of the best model is around 85%. That shows that matches which do not follow the known rules can be predicted and, considering that there is not a human way to process this amount of data, the results are promising.This work was supported by the Research Program of the Ministry of Economy and competitiveness, Government of Spain, through the DeepEMR Project, under Grant TIN2017-87548-C2-1-

Automatic detection of relationships between banking operations using machine learning

In their daily business, bank branches should register their operations with several systems in order to share information with other branches and to have a central repository of records. In this way, information can be analysed and processed according to different requisites: fraud detection, accounting or legal requirements. Within this context, there is increasing use of big data and artificial intelligence techniques to improve customer experience. Our research focuses on detecting matches between bank operation records by means of applied intelligence techniques in a big data environment and business intelligence analytics. The business analytics function allows relationships to be established and comparisons to be made between variables from the bank's daily business. Finally, the results obtained show that the framework is able to detect relationships between banking operation records, starting from not homogeneous information and taking into account the large volume of data involved in the process. (C) 2019 Elsevier Inc. All rights reserved.This work was supported by the Research Program of the Ministry of Economy and Competitiveness - Government of Spain, (DeepEMR project TIN2017-87548-C2-1-R)

Sub-Sync: automatic synchronization of subtitles in the broadcasting of true live programs in spanish

Individuals With Sensory Impairment (Hearing Or Visual) Encounter Serious Communication Barriers Within Society And The World Around Them. These Barriers Hinder The Communication Process And Make Access To Information An Obstacle They Must Overcome On A Daily Basis. In This Context, One Of The Most Common Complaints Made By The Television (Tv) Users With Sensory Impairment Is The Lack Of Synchronism Between Audio And Subtitles In Some Types Of Programs. In Addition, Synchronization Remains One Of The Most Significant Factors In Audience Perception Of Quality In Live-Originated Tv Subtitles For The Deaf And Hard Of Hearing. This Paper Introduces The Sub-Sync Framework Intended For Use In Automatic Synchronization Of Audio-Visual Contents And Subtitles, Taking Advantage Of Current Well-Known Techniques Used In Symbol Sequences Alignment. In This Particular Case, These Symbol Sequences Are The Subtitles Produced By The Broadcaster Subtitling System And The Word Flow Generated By An Automatic Speech Recognizing The Procedure. The Goal Of Sub-Sync Is To Address The Lack Of Synchronism That Occurs In The Subtitles When Produced During The Broadcast Of Live Tv Programs Or Other Programs That Have Some Improvised Parts. Furthermore, It Also Aims To Resolve The Problematic Interphase Of Synchronized And Unsynchronized Parts Of Mixed Type Programs. In Addition, The Framework Is Able To Synchronize The Subtitles Even When They Do Not Correspond Literally To The Original Audio And/Or The Audio Cannot Be Completely Transcribed By An Automatic Process. Sub-Sync Has Been Successfully Tested In Different Live Broadcasts, Including Mixed Programs, In Which The Synchronized Parts (Recorded, Scripted) Are Interspersed With Desynchronized (Improvised) Ones

Framework for the Classification of Emotions in People With Visual Disabilities Through Brain Signals

Nowadays, the recognition of emotions in people with sensory disabilities still represents a challenge due to the difficulty of generalizing and modeling the set of brain signals. In recent years, the technology that has been used to study a person’s behavior and emotions based on brain signals is the brain–computer interface (BCI). Although previous works have already proposed the classification of emotions in people with sensory disabilities using machine learning techniques, a model of recognition of emotions in people with visual disabilities has not yet been evaluated. Consequently, in this work, the authors present a twofold framework focused on people with visual disabilities. Firstly, auditory stimuli have been used, and a component of acquisition and extraction of brain signals has been defined. Secondly, analysis techniques for the modeling of emotions have been developed, and machine learning models for the classification of emotions have been defined. Based on the results, the algorithm with the best performance in the validation is random forest (RF), with an accuracy of 85 and 88% in the classification for negative and positive emotions, respectively. According to the results, the framework is able to classify positive and negative emotions, but the experimentation performed also shows that the framework performance depends on the number of features in the dataset and the quality of the Electroencephalogram (EEG) signals is a determining factor.This work was supported by the National Council of Science and Technology of Mexico (CONACyT), through grant number 709656

Towards the recognition of the emotions of people with visual disabilities through brain-computer interfaces

This article belongs to the Section Intelligent Sensors.A brain&-computer interface is an alternative for communication between people and computers, through the acquisition and analysis of brain signals. Research related to this field has focused on serving people with different types of motor, visual or auditory disabilities. On the other hand, affective computing studies and extracts information about the emotional state of a person in certain situations, an important aspect for the interaction between people and the computer. In particular, this manuscript considers people with visual disabilities and their need for personalized systems that prioritize their disability and the degree that affects them. In this article, a review of the state of the techniques is presented, where the importance of the study of the emotions of people with visual disabilities, and the possibility of representing those emotions through a brain&-computer interface and affective computing, are discussed. Finally, the authors propose a framework to study and evaluate the possibility of representing and interpreting the emotions of people with visual disabilities for improving their experience with the use of technology and their integration into today's society.This work was supported by the Consejo Nacional de Ciencia y Tecnología CONACyT, through the number 709656 and by the Research Program of the Ministry of Economy and Competitiveness—Government of Spain, (DeepEMR project TIN2017-87548-C2-1-R)

CESARSC: Framework for creating Cultural Entertainment Systems with Augmented Reality in Smart Cities

The areas of application for augmented reality technology are heterogeneous but the content creation tools available are usually single-user desktop applications. Moreover, there is no online development tool that enables the creation of such digital content. This paper presents a framework for the creation of Cultural Entertainment Systems and Augmented Reality, employing cloud-based technologies and the interaction of heterogeneous mobile technology in real time in the field of mobile tourism. The proposed system allows players to carry out a series of games and challenges that will improve their tourism experience. The system has been evaluated in a real scenario, obtaining promising results.The areas of application for augmented reality technology are heterogeneous but the content creation tools available are usually single-user desktop applications. Moreover, there is no online development tool that enables the creation of such digital content. This paper presents a framework for the creation of Cultural Entertainment Systems and Augmented Reality, employing cloud-based technologies and the interaction of heterogeneous mobile technology in real time in the field of mobile tourism. The proposed system allows players to carry out a series of games and challenges that will improve their tourism experience. The system has been evaluated in a real scenario, obtaining promising results.This work is supported by the Spanish Ministry of Economy and Competitiveness under the INNPACTO project CL-SMARTVIEW (IPT-2012-1043-410000)

PB-ADVISOR: A private banking multi-investment porfolio.

Private banking is a business area in which the investor requires tailor-made advice. Because of the current market situation, investors are requiring answers to difficult questions and looking for assurance from wealth managers. Private bankers need to have deep knowledge about an innumerable list of products and their characteristics as well as the suitability of each product for the client’s characteristics to be able to offer an optimal portfolio according to client expectations. Client and portfolio diversity calls for new recommendation and advice systems focused on their specific characteristics. This paper presents PB-ADVISOR, a system aimed at recommending investment portfolios based on fuzzy and semantic technologies to private bankers. The proposed system provides private bankers with a powerful tool to support their decision process and help deal with complex investment portfolios. The system has been evaluated in a real scenario obtaining promising results

SINVLIO: using semantics and fuzzy logic to provide individual investment portfolio recommendations

Portfolio selection addresses the problem of how to diversify investments in the most efficient and profitable way possible. Portfolio selection is a field of study that has been broached from several perspectives, including, among others, recommender systems. This paper presents SINVLIO (Semantic INVestment portfoLIO), a tool based on semantic technologies and fuzzy logic techniques that recommends investments grounded in both psychological aspects of the investor and traditional financial parameters of the investments. The results are very encouraging and reveal that SINVLIO makes good recommendations, according to the high degree of agreement between SINVLIO and expert recommendationsThis work is supported by the Spanish Ministry of Industry, Tourism, and Commerce under the projects SONAR2 (TSI-020100-2008-665) and the Spanish Ministry of Science and Innovation under the project “FINANCIAL LINKED OPEN DATA REASONING AND MANAGEMENT FOR WEB SCIENCE” (TIN2011-27405).Publicad