Aplicación de la Shear Wave Elastography en la patología músculo esquelética

La Elastografía, unida a la técnica con ultrasonidos, es un nueva modalidad de técnica de imagen, con la que se reflejan en tiempo real los parámetros relacionados con la organización estructural de los tejidos (elasticidad) respecto de los tejidos adyacentes. De esta manera, aporta una información que junto a las propiedades morfológicas que proporciona la ecografía convencional y el modo- Doppler puede resultar útil en la práctica clínica. Aunque la Shear Wave Elastography (SWE) , fue inicialmente introducida en otro tipo de localizaciones anatómicas, como próstata, mama o hígado, ha crecido la evidencia en los últimos años, de que puede convertirse en una herramienta muy útil para la evaluación de las propiedades elásticas en el aparato locomotor y para el diagnóstico de diversas patologías dentro de él. A día de hoy, los resultados que se observan en los múltiples estudios realizados en el sistema músculo esquelético, plantean la posibilidad de que esta técnica constituya el futuro tercer pilar de la imagen en la ecografía. En este trabajo se pretende realizar una revisión de lo que es la Elastografía y específicamente de la modalidad, Shear Wave Elastograhy (SWE), y defender su validez en su aplicación al diagnóstico sistema musculo esquelético y en el seguimiento de la regeneración de lesiones traumáticas.Grado en Medicin

Using Association Rules to Learn Users' Assistance Requirements

Interface agents are computer programs that learn users' preferences to provide them personalized assistance with their computer-based tasks. In order to personalize the interaction with users, interface agents must learn how to best interact with each user and how to provide them assistance of the right sort at the right time. Particularly, an interface agent has to discover when the user needs a suggestion to solve a problem, when he requires only a warning about it, when he wants the agent to execute an action and when he wants the agent to do just nothing. In this work we propose a learning algorithm, named WATSON, to tackle this problem. The WATSON algorithm enables an interface agent to adapt its behavior and its interaction with a user to the user's assistance requirements. Our algorithm uses association rules (AR) to discover associations among problem situations and a user's assistance requirements in a given application domain.Sociedad Argentina de Informática e Investigación Operativ

Integrity: A Vital Tool for the 21st Century Church Leaders in Nigeria

The increasing level of moral decadence such as rape, fraud, covetousness, sexual misconduct, character assassination, cultic activities, bloodshed, idolatry, syncretism among some church leaders in the 21st century has caused lots of reproach to the sacred order and arose varieties of questioning to the sanctity of the call of some church leaders in the present age. More worrisome also is the fact that while some church leaders in the 21st century spend more effort in theological formation, little or no attention is given to moral discipline. What should be the attitude of church leaders in matters of morality at home, society and church? Shouldn’t the church leaders be honest and consistent in all things? Pauline discourse on the qualification of church leaders in 1 Timothy 3:1-7 is used as a guide. The paper employs phenomenological and historical-critical method. The essence of the paper is to remind church leaders in the 21st-century church that a high level of moral responsibility is demanded of them if they must thrive and be a voice in the present age

Object-Agent Oriented Programming

Object-oriented programming has been used for building intelligent agents, with the limitation it cannot represent complex mental attitudes. With logic programming it is possible to represent and infer relationships among mental attitudes such as intentions, goals and beliefs, with limitations in the usage of capabilities of action. This paper presents two alternatives for integrating object- oriented with logic programming, which enable agent programming. Java and Smalltalk have been used for providing one typed and another non-typed integration with Prolog.Sociedad Argentina de Informática e Investigación Operativ

Collaborative Learning Team Formation Considering Team Roles: An Evolutionary Approach based on Adaptive Crossover, Mutation and Simulated Annealing

In this paper, a hybrid evolutionary algorithm is proposed to solve a collaborative learning team formation problem in higher education contexts. This problem involves a grouping criterion evaluated satisfactorily in a great variety of higher education courses as well as training programs. This criterion is based on the team roles of students, and implies forming well-balanced teams respecting the team roles of their members. The hybrid evolutionary algorithm uses adaptive crossover, mutation and simulated annealing processes, in order to improve the performance of the evolutionary search. These processes adapt their behavior regarding the state of the evolutionary search. The performance of the hybrid evolutionary algorithm is exhaustively evaluated on data sets with very different complexity levels, and after that, is compared with those of the algorithms previously reported in the literature to solve the addressed problem. The results obtained from the performance comparison indicate that the hybrid evolutionary algorithm significantly outperforms the algorithms previously reported, in both effectiveness and efficiency.Fil: Yannibelli, Virginia Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Instituto de Sistemas Tandil; ArgentinaFil: Amandi, Analia Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Instituto de Sistemas Tandil; Argentin

Learning browsing patterns for context-aware recommendation

The success of personal information agents depends on their capacity to both identify relevant information for users and proactively recommend context-relevant information. In this paper, we propose an approach to enable proactive context-aware recommendation based on the knowledge of both user interests and browsing patterns. The pro- posed approach analyzes the browsing behavior of users to derive a semantically enhanced context that points out the information which is likely to be relevant for a user according to its current activities.IFIP International Conference on Artificial Intelligence in Theory and Practice - Agents 1Red de Universidades con Carreras en Informática (RedUNCI

Agents that learn how to generate arguments from other agents

Learning how to argue is a key ability for a negotiator agent. In this paper, we propose an approach that allows agents to learn how to build arguments by observing how other agents argue in a negotiation context. Particularly, our approach enables the agent to infer the rulesfor argument generation that other agents apply to build their arguments. To carry out this goal, the agent stores the arguments uttered by other agents and the facts of the negotiation context where each argument is uttered. Then, an algorithm for fuzzy generalized association rules is applied to discover the desired rules. This kind of algorithm allows us (a) to obtain general rules that can be applied to dierent negotiation contexts; and (b) to deal with the uncertainty about the knowledge of what facts of the context are taken into account by the agents. The experimental results showed that it is possible to infer argument generation rules from a reduced number of observed arguments.Fil: Amandi, Analia Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; ArgentinaFil: Monteserin, Ariel José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentin

A Reinforcement Learning Approach to Improve the Argument Selection Effectiveness in Argumentation-based Negotiation

Argument selection is considered the essence of the strategy in argumentation-based negotiation. An agent, which is arguing during a negotiation, must decide what arguments are the best to persuade the opponent. In fact, in each negotiation step, the agent must select an argument from a set of candidate arguments by applying some selection policy. Following this policy, the agent observes some factors of the negotiation context, for instance: trust in the opponent and expected utility of the negotiated agreement, among others. Usually, argument selection policies are dened statically. However, as the negotiation context varies from a negotiation to another, dening a static selection policy it is not useful. Therefore, the agent should modify its selection policy in order to adapt it to the dierent negotiation contexts as the agent´s experience increases. In this paper, we present a reinforcement learning approach that allows the agent to improve the argument selection eciency by updating the argument selection policy. To carry out this goal, the argument selection mechanism is represented as a reinforcement learning model. We tested this approach in a multiagent system, in a stationary as well as in a dynamic environment, and obtained promising results in both.Fil: Amandi, Analia Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; ArgentinaFil: Monteserin, Ariel José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentin

Agents That Learn What Argument to Select In Argumentation-Based Negotiations

Argument selection is considered the essence of the strategy in argumentation-based negotiation. An agent, which is arguing during a negotiation, has to decide what arguments are the best to persuade the opponent. In fact, in each negotiation step, the agent must select an argument from a set of candidate arguments by applying some selection criterion. For this task, the agent observes some factors of the negotiation context, for instance trust in the opponent, expected utility, among others. Usually, argument selection mechanisms are defined statically. However, as the negotiation context varies from a negotiation to another, defining a static selection mechanism it is not useful. For this reason, we present in this paper a novel approach to personalize argument selection mechanisms in the context of argumentation-based negotiation. The selection mechanism defines a set of preferences that determine how preferable it is to utter an argument in a given context. Our approach maintains a hierarchy of preferences in order to learn new preferences and update the existing ones as the agent experience increases. We tested this approach in a simulated multiagent system and obtained promising results.Fil: Monteserin, Ariel José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; ArgentinaFil: Amandi, Analia Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentin