Learning and adaptation in physical heterogeneous teams of robots

In this paper we present a novel approach to assigning roles to robots in a team of physical heterogeneous robots. Its members compete for these roles and get rewards for them. The rewards are used to determine each agent’s preferences and which agents are better adapted to the environment. These aspects are included in the decision making process. Agent interactions are modelled using the concept of an ecosystem in which each robot is a species, resulting in emergent behaviour of the whole set of agents. One of the most important features of this approach is its high adaptability. Unlike some other learning techniques, this approach does not need to start a whole exploitation process when the environment changes. All this is exemplified by means of experiments run on a simulator. In addition, the algorithm developed was applied as applied to several teams of robots in order to analyse the impact of heterogeneity in these systems

Monitoring drug therapy.

Drug development has improved over recent decades, with refinements in analytical techniques, population pharmacokinetic-pharmacodynamic (PK-PD) modelling and simulation, and new biomarkers of efficacy and tolerability. Yet this progress has not yielded improvements in individualization of treatment and monitoring, owing to various obstacles: monitoring is complex and demanding, many monitoring procedures have been instituted without critical assessment of the underlying evidence and rationale, controlled clinical trials are sparse, monitoring procedures are poorly validated and both drug manufacturers and regulatory authorities take insufficient account of the importance of monitoring. Drug concentration and effect data should be increasingly collected, analyzed, aggregated and disseminated in forms suitable for prescribers, along with efficient monitoring tools and evidence-based recommendations regarding their best use. PK-PD observations should be collected for both novel and established critical drugs and applied to observational data, in order to establish whether monitoring would be suitable. Methods for aggregating PK-PD data in systematic reviews should be devised. Observational and intervention studies to evaluate monitoring procedures are needed. Miniaturized monitoring tests for delivery at the point of care should be developed and harnessed to closed-loop regulated drug delivery systems. Intelligent devices would enable unprecedented precision in the application of critical treatments, i.e. those with life-saving efficacy, narrow therapeutic margins and high interpatient variability. Pharmaceutical companies, regulatory agencies and academic clinical pharmacologists share the responsibility of leading such developments, in order to ensure that patients obtain the greatest benefit and suffer the least harm from their medicines.

Mult-class differentiation of cannabis seedlings in a forensic context

This article presents an experimental study about the classification ability of several classifiers for multi-classclassification of cannabis seedlings. As the cultivation of drug type cannabis is forbidden in Switzerland lawenforcement authorities regularly ask forensic laboratories to determinate the chemotype of a seized cannabisplant and then to conclude if the plantation is legal or not. This classification is mainly performed when theplant is mature as required by the EU official protocol and then the classification of cannabis seedlings is a timeconsuming and costly procedure. A previous study made by the authors has investigated this problematic [1]and showed that it is possible to differentiate between drug type (illegal) and fibre type (legal) cannabis at anearly stage of growth using gas chromatography interfaced with mass spectrometry (GC-MS) based on therelative proportions of eight major leaf compounds. The aims of the present work are on one hand to continueformer work and to optimize the methodology for the discrimination of drug- and fibre type cannabisdeveloped in the previous study and on the other hand to investigate the possibility to predict illegal cannabisvarieties. Seven classifiers for differentiating between cannabis seedlings are evaluated in this paper, namelyLinear Discriminant Analysis (LDA), Partial Least Squares Discriminant Analysis (PLS-DA), Nearest NeighbourClassification (NNC), Learning Vector Quantization (LVQ), Radial Basis Function Support Vector Machines(RBF SVMs), Random Forest (RF) and Artificial Neural Networks (ANN). The performance of each method wasassessed using the same analytical dataset that consists of 861 samples split into drug- and fibre type cannabiswith drug type cannabis being made up of 12 varieties (i.e. 12 classes). The results show that linear classifiersare not able to manage the distribution of classes in which some overlap areas exist for both classificationproblems. Unlike linear classifiers, NNC and RBF SVMs best differentiate cannabis samples both for 2-class and12-class classifications with average classification results up to 99% and 98%, respectively. Furthermore, RBFSVMs correctly classified into drug type cannabis the independent validation set, which consists of cannabisplants coming from police seizures. In forensic case work this study shows that the discrimination betweencannabis samples at an early stage of growth is possible with fairly high classification performance fordiscriminating between cannabis chemotypes or between drug type cannabis varieties.

Artificial-Intelligence-Based Optimization of the Management of Snow Removal Assets and Resources Final Report, October 2002

Geographic information systems (GIS) and artificial intelligence (AI) techniques were used to develop an intelligent snow removal asset management system (SRAMS). The system has been evaluated through a case study examining snow removal from the roads in Black Hawk County, Iowa, for which the Iowa Department of Transportation (Iowa DOT) is responsible. The SRAMS is comprised of an expert system that contains the logical rules and expertise of the Iowa DOT’s snow removal experts in Black Hawk County, and a geographic information system to access and manage road data. The system is implemented on a mid-range PC by integrating MapObjects 2.1 (a GIS package), Visual Rule Studio 2.2 (an AI shell), and Visual Basic 6.0 (a programming tool). The system could efficiently be used to generate prioritized snowplowing routes in visual format, to optimize the allocation of assets for plowing, and to track materials (e.g., salt and sand). A test of the system reveals an improvement in snowplowing time by 1.9 percent for moderate snowfall and 9.7 percent for snowstorm conditions over the current manual system.

Organisational adaptation of multi-agent systems in a peer-to-peer scenario

Organisations in Multi-Agent Systems (MAS) have proven to be successful in regulating agent societies. Nevertheless, changes in agents' behaviour or in the dynamics of the environment may lead to a poor fulfilment of the system's purposes, and so the entire organisation needs to be adapted. In this paper we focus on endowing the organisation with adaptation capabilities, instead of expecting agents to be capable of adapting the organisation by themselves. We regard this organisational adaptation as an assisting service provided by what we call the Assistance Layer. Our generic Two Level Assisted MAS Architecture (2-LAMA) incorporates such a layer. We empirically evaluate this approach by means of an agent-based simulator we have developed for the P2P sharing network domain. This simulator implements 2-LAMA architecture and supports the comparison between different adaptation methods, as well as, with the standard BitTorrent protocol. In particular, we present two alternatives to perform norm adaptation and one method to adapt agents'relationships. The results show improved performance and demonstrate that the cost of introducing an additional layer in charge of the system's adaptation is lower than its benefits.

Building the future: the Brazilian university library in 2010

Information technology will affect academic activities as well as the nature of the high education sector. This sector besides the need to assimilate these technologies will need to attend the requisites of market globalization and, as consequence, all theses changes will be reflected in the university library. Prospectives impacts will affect the structure (emphasis in user services, outsourcing of several services), in the financing aspect (growing of consortia in order to reduce costs), in services (electronic reference, support to long distance education programs, intelligent agents) and in the clientele (attending the great demand por high education which implies a diversity of people).

Usabilitat dels sistemes operatius en smartphones (Android vs iOS)

Aquest treball es portarà a terme realitzant una avaluació heurística dels sistmes operatius seleccionats i de les seves aplicacions, un test d'usabilitat i un anàlisi de l'organització de les funcions mitjançant un card sorting on-line.

Multi-Purpose ESS/ITS Data Collection Sites, SPR72-00-0003-042, 2014

This document presents the results of a state-of-practice survey of transportation agencies that are installing intelligent transportation sensors (ITS) and other devices along with their environmental sensing stations (ESS) also referred to as roadway weather information system (RWIS) assets.

Percepciones de estudiantes sobre el Aprendizaje móvil; la nueva generación de la educación a distancia

Durante años, muchas instituciones y universidades han comenzado a experimentar con los dispositivos móviles en el aprendizaje a través de diferentes proyectos como parte de su metodología de aprendizaje. La experiencia adquirida con el empleo de estrategias y enfoques en la educación a distancia puede facilitar la conceptualización del aprendizaje móvil, así como el desarrollo de aplicaciones para este nuevo medio de aprendizaje. Los dispositivos móviles abren además nuevos caminos para el aprendizaje y una nueva generación para la educación a distancia, y los investigadores conocen estos nuevos caminos para el aprendizaje y oportunidades de llegar a un público más amplio. Este trabajo, muestra los resultados de un grupo de discusión que se llevó a cabo entre 20 estudiantes de licenciatura con el fin de explorar las percepciones, y en general todo aquello que afecta a la interpretación subjetiva de los individuos y su interacción con un fenómeno social como el aprendizaje móvil.

On the Selection of Non-Invasive Methods Based on Speech Analysis Oriented to Automatic Alzheimer Disease Diagnosis

The work presented here is part of a larger study to identify novel technologies and biomarkers for early Alzheimer disease (AD) detection and it focuses on evaluating the suitability of a new approach for early AD diagnosis by non-invasive methods. The purpose is to examine in a pilot study the potential of applying intelligent algorithms to speech features obtained from suspected patients in order to contribute to the improvement of diagnosis of AD and its degree of severity. In this sense, Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects). Two human issues have been analyzed for feature selection: Spontaneous Speech and Emotional Response. Not only linear features but also non-linear ones, such as Fractal Dimension, have been explored. The approach is non invasive, low cost and without any side effects. Obtained experimental results were very satisfactory and promising for early diagnosis and classification of AD patients.

Alzheimer disease diagnosis based on automatic spontaneous speech analysis

Alzheimer’s disease (AD) is the most prevalent form of progressive degenerative dementia and it has a high socio-economic impact in Western countries, therefore is one of the most active research areas today. Its diagnosis is sometimes made by excluding other dementias, and definitive confirmation must be done trough a post-mortem study of the brain tissue of the patient. The purpose of this paper is to contribute to im-provement of early diagnosis of AD and its degree of severity, from an automatic analysis performed by non-invasive intelligent methods. The methods selected in this case are Automatic Spontaneous Speech Analysis (ASSA) and Emotional Temperature (ET), that have the great advantage of being non invasive, low cost and without any side effects.

Disseny d'un sistema de control del consum d'aigua automàtic

Avui en dia s’ha convertit en una necessitat tenir cura del medi ambient i optimitzar els recursos naturals. En el camp per estalviar energia s’han fet grans progressos i disposem d’un gran ventall de dispositius que ens ajuden i ens faciliten l’optimització del consum d’energia. Però és una realitat que en l’estalvi del consum d’aigua el progrés ha estat molt menor i es limita molt a donar consells i repartir dosificadors d’aigua. Qui no ha vist carrers o jardins o cases inundades amb milers de litres d’aigua? Aquesta realitat m’ha portat a dissenyar i desenvolupar un prototip que em permeti tenir un millor control del consum d’aigua. El prototip, a trets principals, consta d’un sensor, una electrovàlvula i una placa Arduino Atmega. El sensor ens permet mesurar els litres consumits durant un cert període de temps. Passat aquest temps de mostreig es compara els litres consumits amb el consum habitual, en aquell període de temps. En cas de sobrepassar el volum programat es tancarà l’electrovàlvula de forma automàtica i rebrem un SMS al telèfon. L’activació de l’alarma es pot ajustar que sigui al igualar-se els dos valors, litres programats i litres consumits. També es pot programar el percentatge que cal sobrepassar de litres consumits per activar l’alarma, com el temps de mostreig. El fet de poder programar tots aquests valors ens permet fer un ajust ideal per a la instal·lació que es vol tenir controlada. A més, el prototip es pot utilitzar per enviar a la companyia d’aigua el valor del comptador de forma automàtica. D’aquesta forma la companyia d’aigua també optimitza recursos estalviant-se el desplaçament de personal a la instal·lació per fer la lectura corresponent. El prototip està basat amb un Arduino Atmega que ens permet el processament de les dades programades i capturades pel sensor. També s’ha incorporat una pantalla TFT Touch 2’8”, que permet visualitzar i programar els valors d’una forma molt més intuïtiva. Per enviar els SMS s’utilitza una placa d’Arduino Cel·lular Shield - SM5100B, a la qual només cal afegir una targeta SIM. A priori, el prototip té un elevat cost al fabricar una sola unitat i pot semblar poc útil. Però ens pot estalviar alguna sorpresa en les factures d’aigua si tenim una fuita i no ens n’adonem fins a veure el rebut de la companyia. Si es fabriqués a grans quantitats es podria abaratir el preu i fer-lo encara més engrescador.

El Confort a través de la domòtica

Els objectius del projecte és dissenyar un habitatge unifamiliar aïllat intel•ligent, situat al carrer Marbella, 25, de la localitat de Santa Coloma de Farners, província de Girona; i fer una simulació de com actuen els elements domòtics, amb el programa informàtic LabView

Multidimensional Adaptations for Open Learning Management Systems

Our work is focused on alleviating the workload for designers of adaptive courses on the complexity task of authoring adaptive learning designs adjusted to specific user characteristics and the user context. We propose an adaptation platform that consists in a set of intelligent agents where each agent carries out an independent adaptation task. The agents apply machine learning techniques to support the user modelling for the adaptation process