pinecone/core-2020-05-10-deduplication huggingface dataset:
Complex modelling of open system design for sustainable architecture

This paper argues a model of complex system design for sustainable architecture within a framework of entropy evolution. The spectrum of sustainable architecture consists of the efficient use of energy and material resource in life-cycle of buildings, the active involvement of the occupants in micro-climate control within buildings, and the natural environmental context. The interactions of the parameters compose a complex system of sustainable architectural design, of which the conventional linear and fragmented design technologies are insufficient to indicate holistic and ongoing environmental performance. The complexity theory of dissipative structure states a microscopic formulation of open system evolution, which provides a system design framework for the evolution of building environmental performance towards an optimization of sustainability in architecture
Modelling Dengue Epidemics with Autoregressive Switching Markov Models (AR-HMM)

This work presents the Autorregresive switching-Markov Model (AR-HMM) as a technique that allows modelling time series which are controlled by some unobserved process and finite time lags. Our objetive is to bring to light the potential of this method to give valuable information about how an efficient control strategy can be performed. As a case of study, we apply the method to the dengue fever epidemics (DF) in 2001 in Havana. For this time series, a first experiment with real data is performed in order to obtain the characterization of differents stages of the epidemics
Easing the smart home: Translating human hierarchies to intelligent environments

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-02478-8_137Proceedings of 10th International Work-Conference on Artificial Neural Networks, IWANN 2009, Salamanca, Spain.Ubiquitous computing research have extended traditional environments in the so–called Intelligent Environments. All of them use their capabilities for pursuing their inhabitants’s satisfaction, but the ways of getting it are most of the times unclear and frequently unshared among different users. This last problem becomes patent in shared environments
in which users with different preferences live together. This article presents a solution translating human hierarchies to the Ubicomp domain, in a continuing effort for leveraging the control capabilities of the inhabitants in their on–growing capable environments. This mechanism, as a natural ubicomp extension of the coordination mechanism used daily by humans, has been implemented over a real environment: a iving room equipped with ambient intelligence capabilities, and installed in two more: an intelligent classroom and an intelligent secure room.This work was partially funded by the Spanish Ministry of Science and Technology through the HADA project(TIN2007-64718) and by the chair UAM–Indra of Ambient Intelligenc
Ambulatory mobility characterization using body inertial system: an applicatio to fall detection

The aim of this paper is to study the use of a prototype of wearable device for long term monitoring of gait and balance using inertial sensors. First, it is focused on the design of the device that can be used all day during the patient daily life activities, because it is small, usable and non invasive. Secondly, we present the system calibration to ensure the quality of the sensors data. Afterwodrs, we focus in the experimental methodology for data harvest from extensive types of falls. Finally a statistical analysis allows us to determine the discriminant information to detect falls.Peer ReviewedPostprint (author’s final draft
PNEPs, NEPs for context free parsing: Application to natural language processing

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-02478-8_59Proceedings of 10th International Work-Conference on Artificial Neural Networks, IWANN 2009, Salamanca, Spain.This work tests the suitability of NEPs to parse languages. We propose PNEP, a simple extension to NEP, and a procedure to translate a grammar into a PNEP that recognizes the same language. These parsers based on NEPs do not impose any additional constrain
to the structure of the grammar, which can contain all kinds of recursive, lambda or ambiguous rules. This flexibility makes this procedure specially suited for Natural Languge Processing (NLP). In a first proof with a simplified English grammar, we got a performance (a linear time complexity) similar to that of the most popular syntactic parsers in the NLP area (Early and its derivatives). All the possible derivations for ambiguous grammars were generatedThis work was partially supported by MEC, project TIN2008-02081/TIN and by DGUI CAM/UAM, project CCG08-UAM/TIC-4425
Evolutionary genetic algorithms in a constraint satisfaction problem: Puzzle Eternity II

Proceeding of: International Work-Conference on Artificial Neural Networks, IWANN 2009, Salamanca, Spain, June 10-12, 2009This paper evaluates a genetic algorithm and a multiobjective evolutionary algorithm in a constraint satisfaction problem (CSP). The problem that has been chosen is the Eternity II puzzle (E2), an edge-matching puzzle. The objective is to analyze the results and the convergence of both algorithms in a problem that is not purely multiobjective but that can be split into multiple related objectives. For the genetic algorithm two different fitness functions will be used, the first one as the score of the puzzle and the second one as a combination of the multiobjective algorithm objectives.This work was supported in part by the Carlos III University of Madrid under
grant PIF UC3M01-0809 and by the Ministry of Science and Innovation under project TRA2007-67374-C02-02
Multiobjective Algorithms Hybridization to Optimize Broadcasting Parameters in Mobile Ad-Hoc Networks

Proceeding of: 10th InternationalWork-Conference
on Artificial Neural Networks, IWANN 2009
Salamanca, Spain, June 10-12, 2009The aim os this paper is to study the hybridization of two multi-objective algorithms in the context of a real problem, the MANETs problem. The algorithms studied are Particle Swarm Optimization (MOPSO) and a new multiobjective algorithm based in the combination of NSGA-II with Evolution Strategies (ESN). This work analyzes the improvement produced by hybridization over the Pareto’s fronts compared with the non-hybridized algorithms. The purpose of this work is to validate how hybridization of two evolutionary algorithms of different families may help to solve certain problems together in the context of MANETs problem. The hybridization used for this work consists on a sequential execution of the two algorithms and using the final population of the first algorithm as initial population of the second one.This article has been financed by the Spanish founded research MEC projects OPLINK::UC3M, Ref:TIN2005-08818- C04-02 and MSTAR::UC3M, Ref:TIN2008-06491-C04-03.Publicad
Adaptive interfaces for people with special needs

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-02481-8_117Proceedings of 10th International Work-Conference on Artificial Neural Networks, IWANN 2009 Workshops, Salamanca, Spain, June 10-12, 2009This paper covers those aspects of modern interfaces which expand and enhance the way in which people interact with computers, like multi-touch table systems, presence-detection led displays and interactive virtualized real-life environments. It elaborates on how disabled or conditioned people take great advantage of natural interaction as interfaces adapt to their needs; interfaces which can be focused towards memory, cognitive or physical deficiencies. Applications size-up to serve specific users with customized tools and options, and are aware while taking into account the state and situation of the individual.This work has been partly funded by HADA project number TIN2007 – 64718
Case-based reasoning decision making in ambient assisted living

Series : Lecture Notes in Computer Science, vol. 5518Quality on the welfare services in caring, and the trend to minimize the economical
and social-political costs that come with such practice, due to the population aging, are
paramount nowadays, i.e., health care reform has become the leading policy issue in all
latitudes. Indeed, the major thrust of all this research is the perception that escalating costs
make the current structure and financing of health care unsustainable. The issue of
sustainability is, therefore, the main subject of this paper. As a result, and in order to
accomplish this goal, we decided to look to the problem from an user perspective, i.e., the
system not only will provide different services, but will be also able to trace the ones more
frequently used and to learn about the context in which they happen. As a result, we will have a
system that will act and learn according to the preferences and habits of its users, and,
simultaneously, will adapt to the environment with the objective of reducing the cost of its
practices
Biomedical text mining applied to document retrieval and semantic indexing

In Biomedical research, the ability to retrieve the adequate information from the ever growing literature is an extremely important asset. This work provides an enhanced and general purpose approach to the process of document retrieval that enables the filtering of PubMed query results. The system is based on semantic indexing providing, for each set of retrieved documents, a network that links documents and relevant terms obtained by the annotation of biological entities (e.g. genes or proteins). This network provides distinct user perspectives and allows navigation over documents with similar terms and is also used to assess document relevance. A network learning procedure, based on previous work from e-mail spam filtering, is proposed, receiving as input a training set of manually classified documents
Tabu search for the founder sequence reconstruction problem: a preliminary study

The problem of inferring ancestral genetic information in terms of a set of founders of a given population arises in various biological contexts. In optimization terms, this problem can be formulated as a\ud
combinatorial string problem. The main problem of existing techniques, both exact and heuristic, is that their time complexity scales exponentially, which makes them impractical for solving large-scale instances. We developed a new constructive heuristic and a tabu search method with\ud
the explicit aim of providing solutions in a reduced amount of computation time. Experimental results show that when the number of founders grows, our algorithms have advantages over the ones proposed in the\ud
literature.Peer ReviewedPostprint (published version
A software tool for the simulation and optimization of dynamic metabolic models

In Systems Biology, there is a growing need for simulation and optimization tools for the prediction of the phenotypical behavior of microorganisms. In this paper, an open-source software platform is proposed to provide support for research in Metabolic Engineering, by implementing tools that enable the simulation and optimization of dynamic metabolic models using ordinary differential equations. Its main functionalities are related with (i) phenotype simulation of both wild type and mutant strains under given environmental conditions and (ii) strain optimization tackling tasks such as gene knockout selection or the definition of the optimal level of enzyme expression, given appropriate objective functions. The central carbon metabolism of E. coli was used as a case study, to illustrate the main features of the software
Large scale dynamic model reconstruction for the central carbon metabolism of escherichia coli

The major objective of metabolic engineering is the construction of industrially relevant microbial strains with desired properties. From an engineering perspective, dynamic mathematical modeling to quantitatively assess intracellular metabolism and predict the complex behavior of living cells is one of the most successful tools to achieve that goal. In this work, we present an expansion of the original E. coli dynamic model [1], which links the acetate metabolism and tricarboxylic acid cycle (TCA) with the phosphotransferase systems, the pentose-phosphate pathway and the glycolysis system based on mechanistic enzymatic rate equations. The kinetic information is collected from available database and literature, and is used as an initial guess for the global fitting. The results of the numeric simulations were in good agreement with the experimental results. Thus, the results are sufficiently good to prompt us to seek further experimental data for comparison with the simulations
Verification of the Effectiveness of the Online Tuning System for Unknown Person in the Awaking Behavior Detection System

We have developed an awaking behavior detection system using a neural network (abbreviated as NN). However, the detection ability of unknown people is not sufficient with compared to that of learned people. In this research, to improve the detection ability of unknown people, we apply an online tuning system using a continuous learning of the NN for the detection system. In the online tuning system, only a few additional data of a new objective person are used for the continuous learning, where the weights of the NN converged in the initial learning are used as the initial weights for the continuous learning. In this paper, to verify an ability of the online tuning system, we compare detection ability of the converged initial learning with that of the converged online tuning.Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living
10th International Work-Conference on Artificial Neural Networks, IWANN 2009 Workshops, Salamanca, Spain, June 10-12, 2009. Proceedings, Part I
A process model for group decision making with quality evaluation

Série : Lecture Notes in Computer Science, vol. 5518In this work it is addressed the problem of information evaluation
and decision making process in Group Decision Support Systems (GDSS). A
Multi-valued Extended Logic Programming language is used for imperfect
information representation and reasoning. A model embodying the quality
evaluation of the information, along the several stages of the decision making
process, is presented. This way we give the decision makers a measure of the
value of the information that supports the decision itself. This model is
presented in the context of a GDSS for VirtualECare, a system aimed at
sustaining online healthcare services. Reasoning with incomplete and uncertain
knowledge has to be dealt with in this kind of environment, due to the particular
nature of the healthcare services, where the awful consequences of bad
decisions, or lack of timely ones, demand for a responsible answer
Integrated feature and parameter optimization for an evolving spiking neural network

This study extends the recently proposed Evolving Spiking Neural Network (ESNN) architecture by combining it with an optimization algorithm, namely the Versatile Quantum-inspired Evolutionary Algorithm (vQEA). Following the wrapper approach, the method is used to identify relevant feature subsets and simultaneously evolve an optimal ESNN parameter setting. Applied to carefully designed benchmark data, containing irrelevant and redundant features of varying information quality, the ESNN-based feature selection procedure lead to excellent classification results and an accurate detection of relevant information in the dataset. Redundant and irrelevant features were rejected successively and in the order of the degree of information they contained
Personalised modelling for multiple time-series data prediction

The behaviour of multiple stock markets can be described within the framework of complex dynamic systems (CDS). Using a global model with the Kalman Filter we are able to extract the dynamic interaction network (DIN) of these markets. The model was shown to successfully capture interactions between stock markets in the long term. In this study we investigate the effectiveness of two different personalised modelling approaches to multiple stock market prediction. Preliminary results from this study show that the personalised modelling approach when applied to the rate of change of the stock market index is better able to capture recurring trends that tend to occur with stock market data
Exploratory fMRI analysis without spatial normalization

We present an exploratory method for simultaneous parcellation of multisubject fMRI data into functionally coherent areas. The method is based on a solely functional representation of the fMRI data and a hierarchical probabilistic model that accounts for both inter-subject and intra-subject forms of variability in fMRI response. We employ a Variational Bayes approximation to fit the model to the data. The resulting algorithm finds a functional parcellation of the individual brains along with a set of population-level clusters, establishing correspondence between these two levels. The model eliminates the need for spatial normalization while still enabling us to fuse data from several subjects. We demonstrate the application of our method on a visual fMRI study.Author Manuscript received 2010 March 11. 21st International Conference, IPMI 2009, Williamsburg, VA, USA, July 5-10, 2009. ProceedingsMcGovern Institute for Brain Research at MIT. Neurotechnology ProgramNational Science Foundation (U.S.) (CAREER Grant 0642971)National Institutes of Health (U.S.) (NIBIB NAMIC U54-EB005149)National Institutes of Health (U.S.) (NCRR NAC P41-RR13218
Spatial clustering of molecular dynamics trajectories in protein unfolding simulations

Molecular dynamics simulations is a valuable tool to study protein unfolding in silico. Analyzing the relative spatial position of the residues during the simulation may indicate which residues are essential in determining the protein structure. We present a method, inspired by a popular data mining technique called Frequent Itemset Mining, that clusters sets of amino acid residues with a synchronized trajectory during the unfolding process. The proposed approach has several advantages over traditional hierarchical clustering.The authors acknowledge the support of the "Fundacao para a Ciencia e Tecnologia,Portugal, and the program FEDER, through grant PTDC/BIA-PRO/72838/2006 (to PJA and RMMB) and the Fellowships SFRH/BPD/42003/2007(to PGF) and SFRH/BD/16888/2004 (to CGS). We thank the Center for Computational Physics, Departamento de Fisica, Universidade de Coimbra, for the computer resources provided for the MD simulations
A proposal of awareness services for the construction of quality community knowledge supported by the knowledge management system knowcat

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-02556-3_42Procceedings of Symposium on Human Interface 2009, Held as Part of HCI International 2009, San Diego, CA, USA, July 19-24, 2009, Part IIt is well known that members of work groups need awareness about one another, about shared elements, and about the group process. We present a generic framework of awareness services for groupware systems. The proposed approach has been tested through the implementation of a prototype composed by several awareness services for the Knowledge Management system called KnowCat. KnowCat is a groupware that supports the collaborative construction of quality community knowledge. We carried out a research study with a group of students enrolled in a graduate course at Universidad Autónoma de Madrid (Spain) to test our approach. The study outcomes corroborated that providing to the KnowCat users the most useful information about how the classmates have interacted with the system through the awareness services, can help them to know how they should solve their own work in the system and to be aware that they are working in a collaborative way.This research was partly funded by the Spanish National Plan of
R+D, project number,TIN2008-02081/TIN; and by the AECI (Spanish Agency for the
International Cooperation) project number A/017436/08
Modeling of user interest based on its interaction with a collaborative knowledge management system

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-02580-8_36Proceedings of 13th International Conference, HCI International 2009, San Diego, CA, USA, July 19-24, 2009, Part IIISKC is a prototype system for knowledge management in the Web by means of semantic information without supervision and tries to select the knowledge contained in the system by paying attention to its use. This paper explains user activity analysis in order to find out their interest for knowledge elements in the system, and the application of this interest for users classification and knowledge identification for their interest, inside and outside SKC. As a result a model for user interest based on interaction is obtained.This research has been partially financed by the Spanish Ministry
of Science and Technology, through TIN2007-64718 and TIN2008-02081/TIN
projects, and by the Spanish Agency for the International Cooperation (AECI)
through A/7954/07 project
Human computer interaction with a PIM application: Merging activity, location and social setting into context

This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2009 Springer VerlagPersonal Information Managers exploit the ubiquitous paradigm in mobile computing technology to integrate services and programs for business and leisure. Recognizing that every situation is constituted by information and events, this context will vary depending on the situation users are in, and the tasks they are about to commit. The value of context as a source of information is highly recognized and for individual dimensions context has been both conceptually described and prototypes implemented. The novelty in this paper is a new implementation of context by integrating three dimensions of context: social information, activity information and geographical position. Based on an application developed for Microsoft Window Mobile these three dimensions of context are explored and implemented in an application for mobile telephone users. Experiment conducted show the viability of tailoring contextual information in three dimensions to provide user with timely and relevant information
Healthcare Game Design: Behavioral Modeling of Serious Gaming Design for Children with Chronic Diseases

This article introduces the design principles of serious games for chronic patients based on behavioral models. First, key features of the targeted chronic condition (Diabetes) are explained. Then, the role of psychological behavioral models in the management of chronic conditions is covered. After a short review of the existing health focused games, two recent health games that are developed based on behavioral models are overviewed in more detail. Furthermore, design principles and usability issues regarding the creation of these health games are discussed. Finally, the authors conclude that designing healthcare games based on behavioral models can increase the usability of the game in order to improve the effectiveness of the game’s desired healthcare outcomes
A Novel Visualization Tool for Evaluating Medication Side-Effects in Multi-drug Regimens

The evaluation and management of medication side-effects is a common and complex task for physicians. Information visualization has the potential to increase the efficiency and reduce the cognitive load involved in this process. We describe the design and development of Rxplore, a novel tool for assessing medication side-effects. Rxplore supports simultaneous lookup of multiple medications and an intuitive visual representation of query results. In a pilot study of Rxplore’s usability and utility, physicians rated the system highly for efficiency, intuitiveness, and clinical value