Granular computing as a tool of human data interaction - a cognitive cities use case

The article proposes granular computing as a theoretical, formal and methodological basis for the newly emerging research field of human–data interaction (HDI). We argue that the ability to represent and reason with information granules is a prerequisite for data legibility. As such, it allows for extending the research agenda of HDI to encompass the topic of collective intelligence amplification, which is seen as an opportunity of today’s increasingly pervasive computing environments. As an example of collective intelligence amplification in HDI, we introduce a collaborative urban planning use case in a cognitive city environment and show how an iterative process of user input and human-oriented automated data processing can support collective decision making. As a basis for automated human-oriented data processing, we use the spatial granular calculus of granular geometry.

An Exploratory Study of Data Quality Management Practices in the ERP Software Systems Context

Quality data are not only relevant for successful Data Warehousing or Business Intelligence applications; they are also a precondition for efficient and effective use of Enterprise Resource Planning (ERP) systems. ERP professionals in all kinds of businesses are concerned with data quality issues, as a survey, conducted by the Institute of Information Systems at the University of Bern, has shown. This paper demonstrates, by using results of this survey, why data quality problems in modern ERP systems can occur and suggests how ERP researchers and practitioners can handle issues around the quality of data in an ERP software Environment.

Assessment of Hydrogen as suistinable clean energy

The progressive depletion of fossil fuels and their high contribution to the energy supply in this modern society forces that will be soon replaced by renewable fuels. But the dispersion and alternation of renewable energy production also undertake to reduce their costs to use as energy storage and hydrogen carrier. It is necessary to develop technologies for hydrogen production from all renewable energy storage technologies and the development of energy production from hydrogen fuel cells and cogeneration and tri generation systems. In order to propel this technological development discussed where the hydrogen plays a key role as energy storage and renewable energy, the National Centre of Hydrogen and Fuel Cell Technology Experimentation in Spain equipped with installations that enable scientific and technological design, develop, verify, certify, approve, test, measure and, more importantly, the facility ensures continuous operation for 24 hours a day, 365 days year. At the same time, the system is scalable so as to allow continuous adaptation of new technologies are developed and incorporated into the assembly to verify integration at the same time it checks the validity of their development. The transformation sector can be said to be the heart of the system, because without neglecting the other sectors, this should prove the validity of hydrogen as a carrier - energy storage are important efforts that have to do to demonstrate the suitability of fuel cells or internal combustion systems to realize the energy stored in hydrogen at prices competitive with conventional systems. The multiple roles to meet the fuel cells under different conditions of operation require to cover their operating conditions, many different sizes and applications. The fourth area focuses on integration is an essential complement within the installation. We must integrate not only the electricity produced, but also hydrogen is used and the heat generated in the process of using hydrogen energy. The energy management in its three forms: hydrogen chemical, electrical and thermal integration requires complicated and require a logic and artificial intelligence extremes to ensure maximum energy efficiency at the same time optimum utilization is achieved. Verification of the development and approval in the entire production system and, ultimately, as a demonstrator set to facilitate the simultaneous evolution of production technology, storage and distribution of hydrogen fuel cells has been assessed.

Solving complex problems with a bioinspired model

Membrane systems are parallel and bioinspired systems which simulate membranes behavior when processing information. As a part of unconventional computing, P-systems are proven to be effective in solvingcomplexproblems. A software technique is presented here that obtain good results when dealing with such problems. The rules application phase is studied and updated accordingly to obtain the desired results. Certain rules are candidate to be eliminated which can make the model improving in terms of time.

Image sub-segmentation by PFCM and Artificial Neural Networks to detect pore space in 2D and 3D CT soil images

The image by Computed Tomography is a non-invasive alternative for observing soil structures, mainly pore space. The pore space correspond in soil data to empty or free space in the sense that no material is present there but only fluids, the fluid transport depend of pore spaces in soil, for this reason is important identify the regions that correspond to pore zones. In this paper we present a methodology in order to detect pore space and solid soil based on the synergy of the image processing, pattern recognition and artificial intelligence. The mathematical morphology is an image processing technique used for the purpose of image enhancement. In order to find pixels groups with a similar gray level intensity, or more or less homogeneous groups, a novel image sub-segmentation based on a Possibilistic Fuzzy c-Means (PFCM) clustering algorithm was used. The Artificial Neural Networks (ANNs) are very efficient for demanding large scale and generic pattern recognition applications for this reason finally a classifier based on artificial neural network is applied in order to classify soil images in two classes, pore space and solid soil respectively.

A Prediction Model to Diabetes using Artificial Metaplasticity

Diabetes is the most common disease nowadays in all populations and in all age groups. Different techniques of artificial intelligence has been applied to diabetes problem. This research proposed the artificial metaplasticity on multilayer perceptron (AMMLP) as prediction model for prediction of diabetes. The Pima Indians diabetes was used to test the proposed model AMMLP. The results obtained by AMMLP were compared with other algorithms, recently proposed by other researchers, that were applied to the same database. The best result obtained so far with the AMMLP algorithm is 89.93%

Inner-Hair Cells Parameterized-Hardware Implementation for Personalized Auditory Nerve Stimulation

In this paper the hardware implementation of an inner hair cell model is presented. Main features of the design are the use of Meddis’ transduction structure and the methodology for Design with Reusability. Which allows future migration to new hardware and design refinements for speech processing and custom-made hearing aids

Artificial cognitive control system based on the shared circuits model of sociocognitive capacities. A first approach

sharedcircuitmodels is presented in this work. The sharedcircuitsmodelapproach of sociocognitivecapacities recently proposed by Hurley in The sharedcircuitsmodel (SCM): how control, mirroring, and simulation can enable imitation, deliberation, and mindreading. Behavioral and Brain Sciences 31(1) (2008) 1–22 is enriched and improved in this work. A five-layer computational architecture for designing artificialcognitivecontrolsystems is proposed on the basis of a modified sharedcircuitsmodel for emulating sociocognitive experiences such as imitation, deliberation, and mindreading. In order to show the enormous potential of this approach, a simplified implementation is applied to a case study. An artificialcognitivecontrolsystem is applied for controlling force in a manufacturing process that demonstrates the suitability of the suggested approach

Hydrologic models for emergency decision support using Bayesian networks

In the presence of a river flood, operators in charge of control must take decisions based on imperfect and incomplete sources of information (e.g., data provided by a limited number sensors) and partial knowledge about the structure and behavior of the river basin. This is a case of reasoning about a complex dynamic system with uncertainty and real-time constraints where bayesian networks can be used to provide an effective support. In this paper we describe a solution with spatio-temporal bayesian networks to be used in a context of emergencies produced by river floods. In the paper we describe first a set of types of causal relations for hydrologic processes with spatial and temporal references to represent the dynamics of the river basin. Then we describe how this was included in a computer system called SAIDA to provide assistance to operators in charge of control in a river basin. Finally the paper shows experimental results about the performance of the model.

Performance of artificial neural networks and genetical evolved artificial neural networks unfolding techniques

With the Bonner spheres spectrometer neutron spectrum is obtained through an unfolding procedure. Monte Carlo methods, Regularization, Parametrization, Least-squares, and Maximum Entropy are some of the techniques utilized for unfolding. In the last decade methods based on Artificial Intelligence Technology have been used. Approaches based on Genetic Algorithms and Artificial Neural Networks have been developed in order to overcome the drawbacks of previous techniques. Nevertheless the advantages of Artificial Neural Networks still it has some drawbacks mainly in the design process of the network, vg the optimum selection of the architectural and learning ANN parameters. In recent years the use of hybrid technologies, combining Artificial Neural Networks and Genetic Algorithms, has been utilized to. In this work, several ANN topologies were trained and tested using Artificial Neural Networks and Genetically Evolved Artificial Neural Networks in the aim to unfold neutron spectra using the count rates of a Bonner sphere spectrometer. Here, a comparative study of both procedures has been carried out.

User-independent accelerometer-based gesture recognition for mobile devices

Many mobile devices embed nowadays inertial sensors. This enables new forms of human-computer interaction through the use of gestures (movements performed with the mobile device) as a way of communication. This paper presents an accelerometer-based gesture recognition system for mobile devices which is able to recognize a collection of 10 different hand gestures. The system was conceived to be light and to operate in a user -independent manner in real time. The recognition system was implemented in a smart phone and evaluated through a collection of user tests, which showed a recognition accuracy similar to other state-of-the art techniques and a lower computational complexity. The system was also used to build a human -robot interface that enables controlling a wheeled robot with the gestures made with the mobile phone.

Improving web learning through model optimization using bootstrap for a tour-guide robot

We perform a review of Web Mining techniques and we describe a Bootstrap Statistics methodology applied to pattern model classifier optimization and verification for Supervised Learning for Tour-Guide Robot knowledge repository management. It is virtually impossible to test thoroughly Web Page Classifiers and many other Internet Applications with pure empirical data, due to the need for human intervention to generate training sets and test sets. We propose using the computer-based Bootstrap paradigm to design a test environment where they are checked with better reliability.

A Keyword-driven approach for generating OWL DL conformance test data

The conformance of semantic technologies has to be systematically evaluated to measure and verify the real adherence of these technologies to the Semantic Web standards. Currente valuations of semantic technology conformance are not exhaustive enough and do not directly cover user requirements and use scenarios, which raises the need for a simple, extensible and parameterizable method to generate test data for such evaluations. To address this need, this paper presents a keyword-driven approach for generating ontology language conformance test data that can be used to evaluate semantic technologies, details the definition of a test suite for evaluating OWL DL conformance using this approach,and describes the use and extension of this test suite during the evaluation of some tools.

Influencia de la Ciencia Ficción en las TIC y las Telecomunicaciones

Desde el comienzo de la Historia, el ser humano ha pensado en su futuro, ya fuera por el hecho de preocuparse por su supervivencia o por razones más filosóficas, como el porvenir como especie. Pensar en el futuro es anticipación. El género de la ciencia ficción es el que más se basa en la anticipación. En muchos subgéneros de la ciencia ficción se tratan temas futuristas, viajes espaciales a otros planetas, inteligencia artificial, etc. Por otra parte, en la actualidad vivimos un período donde los cambios en las TIC (Tecnologías de la Información y Comunicación) son prácticamente diarios, aunque podría llegar a decirse que los cambios se producen hora a hora. A veces, muchos de estos avances nos parecen producto de la fantasía o la ciencia ficción, o salidos de alguna película futurista. Sin embargo, dichos avances son perfectamente posibles y explicables a través de la ciencia actual. A través de este proyecto se pretenden analizar estos avances, relacionándolos con distintas obras de ciencia ficción. Una gran cantidad de los avances tecnológicos tienen su origen en alguna obra de la ciencia ficción, ya sea literatura o cine. Otro objetivo es realizar un estudio de diferentes propuestas tecnológicas de diferentes obras de esta rama que no se hayan realizado todavía, y analizar su viabilidad, su utilidad y los posibles cambios sociológicos que produciría en el mundo en el que vivimos. El tercer objetivo es evaluar la aptitud y actitud de los ingenieros de telecomunicación en cuanto a la innovación y la proyección hacia el futuro de los estos posibles cambios tecnológicos. Abstract Since the beginning of History, humans have thought about their future, either concerned about survival or by philosophical reasons like the future as species. Thinking about the future is speculation. The science fiction genre is the one that is based on speculation. Sub-genres of science fiction covers futuristic themes like space travel to other planets, artificial intelligence, etc. Today we live in a period where changes in ICT (Information and Communication Technologies) are almost daily, although we should say that changes occur in a matter of hours. Sometimes, many of these advances seem a product of fantasy or science fiction, or coming out of a futuristic movie. However, these advances are perfectly possible and explainable by current science. Through this project the intention is to analyze these developments, relating them to various works of science fiction. A great number of this technological advancements have their origin in a work of science fiction, either literature or film. Another objective is to study different technological proposals of this genre that have not been done yet, and analyze their feasibility, usefulness and potential sociological changes that occur in the world we live in. The third objective is to evaluate the ability and attitude of telecommunication engineers in terms of innovation and future projection of these potential technological changes.

Methodological guidelines for reusing general ontologies

Currently, there is a great deal of well-founded explicit knowledge formalizing general notions, such as time concepts and the part_of relation. Yet, it is often the case that instead of reusing ontologies that implement such notions (the so-called general ontologies), engineers create procedural programs that implicitly implement this knowledge. They do not save time and code by reusing explicit knowledge, and devote effort to solve problems that other people have already adequately solved. Consequently, we have developed a methodology that helps engineers to: (a) identify the type of general ontology to be reused; (b) find out which axioms and definitions should be reused; (c) make a decision, using formal concept analysis, on what general ontology is going to be reused; and (d) adapt and integrate the selected general ontology in the domain ontology to be developed. To illustrate our approach we have employed use-cases. For each use case, we provide a set of heuristics with examples. Each of these heuristics has been tested in either OWL or Prolog. Our methodology has been applied to develop a pharmaceutical product ontology. Additionally, we have carried out a controlled experiment with graduated students doing a MCs in Artificial Intelligence. This experiment has yielded some interesting findings concerning what kind of features the future extensions of the methodology should have.