Automatic Generation of Cognitive Theories using Genetic Programming

Cognitive neuroscience is the branch of neuroscience that studies the neural mechanisms underpinning cognition and develops theories explaining them. Within cognitive neuroscience, computational neuroscience focuses on modeling behavior, using theories expressed as computer programs. Up to now, computational theories have been formulated by neuroscientists. In this paper, we present a new approach to theory development in neuroscience: the automatic generation and testing of cognitive theories using genetic programming. Our approach evolves from experimental data cognitive theories that explain “the mental program” that subjects use to solve a specific task. As an example, we have focused on a typical neuroscience experiment, the delayed-match-to-sample (DMTS) task. The main goal of our approach is to develop a tool that neuroscientists can use to develop better cognitive theories

Evaluation of a personalized digital library based on cognitive styles: Adaptivity vs. adaptability

Personalization can be addressed by adaptability and adaptivity, which have different advantages and disadvantages. This study investigates how digital library users react to these two techniques. More specifically, we develop a personalized digital library to suit the needs of different cognitive styles based on the findings of our previous work (Frias-Martinez, et al., in press). The personalized digital library includes two versions: adaptive version and adaptable version. The results showed that users not only performed better in the adaptive version, but also they perceived more positively to the adaptive version. In addition, cognitive styles have great effects on users’ responses to adaptability and adaptivity. These results provide guidance for designers to select suitable techniques to develop personalized digital libraries

Survey of data mining approaches to user modeling for adaptive hypermedia

The ability of an adaptive hypermedia system to create tailored environments depends mainly on the amount and accuracy of information stored in each user model. Some of the difficulties that user modeling faces are the amount of data available to create user models, the adequacy of the data, the noise within that data, and the necessity of capturing the imprecise nature of human behavior. Data mining and machine learning techniques have the ability to handle large amounts of data and to process uncertainty. These characteristics make these techniques suitable for automatic generation of user models that simulate human decision making. This paper surveys different data mining techniques that can be used to efficiently and accurately capture user behavior. The paper also presents guidelines that show which techniques may be used more efficiently according to the task implemented by the applicatio

The role of human factors in stereotyping behavior and perception of digital library users: A robust clustering approach

To deliver effective personalization for digital library users, it is necessary to identify which human factors are most relevant in determining the behavior and perception of these users. This paper examines three key human factors: cognitive styles, levels of expertise and gender differences, and utilizes three individual clustering techniques: k-means, hierarchical clustering and fuzzy clustering to understand user behavior and perception. Moreover, robust clustering, capable of correcting the bias of individual clustering techniques, is used to obtain a deeper understanding. The robust clustering approach produced results that highlighted the relevance of cognitive style for user behavior, i.e., cognitive style dominates and justifies each of the robust clusters created. We also found that perception was mainly determined by the level of expertise of a user. We conclude that robust clustering is an effective technique to analyze user behavior and perception

Modeling human behavior in user-adaptive systems: recent advances using soft computing techniques

Adaptive Hypermedia systems are becoming more important in our everyday activities and users are expecting more intelligent services from them. The key element of a generic adaptive hypermedia system is the user model. Traditional machine learning techniques used to create user models are usually too rigid to capture the inherent uncertainty of human behavior. In this context, soft computing techniques can be used to handle and process human uncertainty and to simulate human decision-making. This paper examines how soft computing techniques, including fuzzy logic, neural networks, genetic algorithms, fuzzy clustering and neuro-fuzzy systems, have been used, alone or in combination with other machine learning techniques, for user modeling from 1999 to 2004. For each technique, its main applications, limitations and future directions for user modeling are presented. The paper also presents guidelines that show which soft computing techniques should be used according to the task implemented by the application

The Atmospheric Monitoring System of the JEM-EUSO Space Mission

An Atmospheric Monitoring System (AMS) is a mandatory and key device of a space-based mission which aims to detect Ultra-High Energy Cosmic Rays (UHECR) and Extremely-High Energy Cosmic Rays (EHECR) from Space. JEM-EUSO has a dedicated atmospheric monitoring system that plays a fundamental role in our understanding of the atmospheric conditions in the Field of View (FoV) of the telescope. Our AMS consists of a very challenging space infrared camera and a LIDAR device, that are being fully designed with space qualification to fulfil the scientific requirements of this space mission. The AMS will provide information of the cloud cover in the FoV of JEM-EUSO, as well as measurements of the cloud top altitudes with an accuracy of 500 m and the optical depth profile of the atmosphere transmittance in the direction of each air shower with an accuracy of 0.15 degree and a resolution of 500 m. This will ensure that the energy of the primary UHECR and the depth of maximum development of the EAS ( Extensive Air Shower) are measured with an accuracy better than 30\% primary energy and 120 $g/cm^2$ depth of maximum development for EAS occurring either in clear sky or with the EAS depth of maximum development above optically thick cloud layers. Moreover a very novel radiometric retrieval technique considering the LIDAR shots as calibration points, that seems to be the most promising retrieval algorithm is under development to infer the Cloud Top Height (CTH) of all kind of clouds, thick and thin clouds in the FoV of the JEM-EUSO space telescope

Piezoelectric actuators for bone mechanical stimulation: exploring the concept.

Arthroplasty is liable to cause intense changes on strain levels and distribution in the boné surrounding the implant, namely stress shielding. Several solutions have been proposed for this, namely design variations and development of controlled-stiffness implants. A new approach to this problem, with potential application to other orthopaedic problems and other medical fields, would be the development of smart implants integrating systems for bone mechanical stimulation. Ideally, the implant should presente sensing capability and the ability to maintain physiological levels of strain at the implant interface. Piezoelectric materials’ huge potential as a mean to produce direct mechanical stimulation lies on the possibility of producing stimuli at a high range of frequencies and in multiple combinations. The present in vitro and preliminary in vivo studies were a first step towards the validation of the concept

Bone mechanical stimulation with piezoelectric materials

This chapter summarized explores in vivo use of a piezoelectric polymer for bone mechanical stimulatio

Sobre la poesía de Camilo Pessanha

Camilo Pessanha nació en 1867, en Coimbra (Portugal), y murió en Macao (1926). Licenciado en derecho (1891), fue profesor de filosofía del liceo de Macao, a donde llegó en 1894, y también registrador de propiedad y magistrado. Se interesó por la estética y la literatura oriental, y reunió una significativa colección de arte chino. Desde 1885 publicó en periódicos y revistas su poesía, que en parte sería recogida en el volumen Clepsydra (Lisboa, 1920)