Search results for "learning"
showing 10 items of 6669 documents
Cerebellar learning of bio-mechanical functions of extra-ocular muscles: modeling by artificial neural networks
2003
A control circuit is proposed to model the command of saccadic eye movements. Its wiring is deduced from a mathematical constraint, i.e. the necessity, for motor orders processing, to compute an approximate inverse function of the bio-mechanical function of the moving plant, here the bio-mechanics of the eye. This wiring is comparable to the anatomy of the cerebellar pathways. A predicting element, necessary for inversion and thus for movement accuracy, is modeled by an artificial neural network whose structure, deduced from physical constraints expressing the mechanics of the eye, is similar to the cell connectivity of the cerebellar cortex. Its functioning is set by supervised reinforceme…
Cooling of the cerebellar interpositus nucleus abolishes somatosensory cortical learning-related activity in eyeblink conditioned rabbits.
2005
Nictitating membrane movement and multiple-unit activity in the somatosensory cortex were recorded from rabbits during paired (N = 6) and unpaired (N = 5) presentations of a tone conditioned stimulus (CS) and an airpuff unconditioned stimulus (US). A behavioural conditioned response (CR) to the CS and an accompanying neural response in the somatosensory cortex developed only in the paired group. Inactivation of the cerebellar interpositus nucleus abolished both the acquired CR and the accompanying neural response. However, the CS facilitated both behavioural and neural responses to the US during the inactivation. Thus, the absence of the CR could not be accounted for by the general inabilit…
System-theoretical analysis of the Clare Bishop Area in the cat
1980
The Clare Bishop Area (CBA) is a retinotopically organized cortical area in the cat brain connected to a great variety of visual areas in a very complex wax (Fig. 1). Experimental analysis is difficult because of the following aspects: 1. As the distance from the retina increases, the signal combinations necessary to analyse the system become more and more specific. 2. Feedback loops cannot be opened, so an unequivocal identification of CBA cell properties is impossible. 3. The nonlinear character seems to have a great influence on signal processing. To circumvent these problems, specific signal combinations leading to a separation of input subsystems have been developed (Hoffmann and v. Se…
Regional and experiential differences in surgeon preference for the treatment of cervical facet injuries: a case study survey with the AO Spine Cervi…
2021
Abstract Purpose The management of cervical facet dislocation injuries remains controversial. The main purpose of this investigation was to identify whether a surgeon’s geographic location or years in practice influences their preferred management of traumatic cervical facet dislocation injuries. Methods A survey was sent to 272 AO Spine members across all geographic regions and with a variety of practice experience. The survey included clinical case scenarios of cervical facet dislocation injuries and asked responders to select preferences among various diagnostic and management options. Results A total of 189 complete responses were received. Over 50% of responding surgeons in each region…
Computational identification of chemical compounds with potential anti-Chagas activity using a classification tree
2021
Chagas disease is endemic to 21 Latin American countries and is a great public health problem in that region. Current chemotherapy remains unsatisfactory; consequently the need to search for new drugs persists. Here we present a new approach to identify novel compounds with potential anti-chagasic action. A large dataset of 584 compounds, obtained from the Drugs for Neglected Diseases initiative, was selected to develop the computational model. Dragon software was used to calculate the molecular descriptors and WEKA software to obtain the classification tree. The best model shows accuracy greater than 93.4% for the training set; the tree was also validated using a 10-fold cross-validation p…
Effectiveness of local feature selection in ensemble learning for prediction of antimicrobial resistance
2008
In the real world concepts are often not stable but change over time. A typical example of this in the biomedical context is antibiotic resistance, where pathogen sensitivity may change over time as pathogen strains develop resistance to antibiotics that were previously effective. This problem, known as concept drift (CD), complicates the task of learning a robust model. Different ensemble learning (EL) approaches (that instead of learning a single classifier try to learn and maintain a set of classifiers over time) have been shown to perform reasonably well in the presence of concept drift. In this paper we study how much local feature selection (FS) can improve ensemble performance for da…
DESIGNING A TEACHER TRAINING PROGRAMME FOR CHARACTER EDUCATION: AN INTERNATIONAL PARTNERSHIP
2020
There is a need of innovative teacher training programmes for character education. This paper addresses three research questions: What are the challenges that a teacher training programme for character education should address? What are the learning outcomes that the programme should achieve? How should the programme be structured for supporting the achievement of those learning outcomes? Two regional authorities, three schools, three universities and a centre of teacher training from Latvia, Estonia and Spain created a strategic partnership for answering these research questions, using design-based implementation research. The results include six domains of learning outcomes and a programm…
Opinion dynamics in coalitional games with transferable utilities
2014
This paper studies opinion dynamics in a large number of homogeneous coalitional games with transferable utilities (TU), where the characteristic function is a continuous-time stochastic process. For each game, which we can see as a “small world”, the players share opinions on how to allocate revenues based on the mean-field interactions with the other small worlds. As a result of such mean-field interactions among small worlds, in each game, a central planner allocates revenues based on the extra reward that a coalition has received up to the current time and the extra reward that the same coalition has received in the other games. The paper also studies the convergence and stability of op…
Drug Activity Characterization Using One-Class Support Vector Machines with Counterexamples
2013
The problem of detecting chemical activity in drugs from its molecular description constitutes a challenging and hard learning task. The corresponding prediction problem can be tackled either as a binary classification problem (active versus inactive compounds) or as a one class problem. The first option leads usually to better prediction results when measured over small and fixed databases while the second could potentially lead to a much better characterization of the active class which could be more important in more realistic settings. In this paper, a comparison of these two options is presented when support vector models are used as predictors.
Microstructure–property relation and machine learning prediction of hole expansion capacity of high-strength steels
2021
Abstract The relationship between microstructure features and mechanical properties plays an important role in the design of materials and improvement of properties. Hole expansion capacity plays a fundamental role in defining the formability of metal sheets. Due to the complexity of the experimental procedure of testing hole expansion capacity, where many influencing factors contribute to the resulting values, the relationship between microstructure features and hole expansion capacity and the complexity of this relation is not yet fully understood. In the present study, an experimental dataset containing the phase constituents of 55 microstructures as well as corresponding properties, su…