Search results for "learning"
showing 10 items of 6669 documents
Todavía unas palabras sobre las venas cefálica y basílica
1993
Ever since 1879, when Josef Hyrtl first formulated his thesis that the names of the cephalic and basilic veins, as applied to the arm veins, were of Arab origin, a discussion began between philologists and historians of medicine as the former defended the Greek source of such denominations whilst the latter shared the view of the Viennese anatomist. The author, after making a critical review of the -relevant works published hitherto, unearthes a text drawn from a Persian manuscript dating back to the 15th century that, in his view, confirms the rigthness of the Viennese anatomist's thesis.
Some Effects of Individual Learning on the Evolution of Sensors
2001
In this paper, we present an abstract model of sensor evolution, where sensor development is only determined by artificial evolution and the adaptation of agent reactions is accomplished by individual learning. With the environment cast into a MDP framework, sensors can be conceived as a map from environmental states to agent observations and Reinforcement Learning algorithms can be utilised. On the basis of a simple gridworld scenario, we present some results of the interaction between individual learning and evolution of sensors.
Forecasting basketball players' performance using sparse functional data*
2019
Statistics and analytic methods are becoming increasingly important in basketball. In particular, predicting players’ performance using past observations is a considerable challenge. The purpose of this study is to forecast the future behavior of basketball players. The available data are sparse functional data, which are very common in sports. So far, however, no forecasting method designed for sparse functional data has been used in sports. A methodology based on two methods to handle sparse and irregular data, together with the analogous method and functional archetypoid analysis is proposed. Results in comparison with traditional methods show that our approach is competitive and additio…
On incorporating the paradigms of discretization and Bayesian estimation to create a new family of pursuit learning automata
2013
Published version of an article in the journal: Applied Intelligence. Also available from the publisher at: http://dx.doi.org/10.1007/s10489-013-0424-x There are currently two fundamental paradigms that have been used to enhance the convergence speed of Learning Automata (LA). The first involves the concept of utilizing the estimates of the reward probabilities, while the second involves discretizing the probability space in which the LA operates. This paper demonstrates how both of these can be simultaneously utilized, and in particular, by using the family of Bayesian estimates that have been proven to have distinct advantages over their maximum likelihood counterparts. The success of LA-…
Social Emotional Competence, Learning Outcomes, Emotional and Behavioral Difficulties of Preschool Children: Parent and Teacher Evaluations
2022
This paper addresses the role of social emotional competence in the emotional and behavioral problems and learning outcomes of preschool children based on their parents’ and teachers’ evaluations. In this study, we compared the perceptions of teachers and parents when evaluating the same child using the multi-informant assessment. First, the associations and differences between both the informant evaluations were investigated. Second, the correlation of the social emotional competence and emotional, and behavioral difficulties among preschool children was analyzed, separately addressing their parents’ and teachers’ evaluations. Third, the role of the preschool children’s social emotional co…
Poor School Academic Performance and Benign Epilepsy with Centro-Temporal Spikes
2023
Background: Poor academic performance of students with epilepsy seems to be a multifactorial problem related to difficulties in reading, writing, math, and logic skills. Poor school and academic performances refer to learning problems in a specific academic area due to learning disorders and learning difficulties not excluding the ability to learn in a different manner during school and academic life. Sometimes, school, academic difficulties, and Rolandic epilepsy can coexist together, and there may be comorbidities. Consequently, the risk of impaired academic performance in people with epilepsy is high. Methods: This review analyzed the relationship between Benign Epilepsy with Centro-Temp…
Previous Training in the Water Maze
1999
It has been shown that acquisition rates in the water maze vary across strains of mice, although the differential effects of previous experience in this spatial task have been scarcely evaluated. The aim of the present study was to evaluate the effects of training in the water maze at an early age (2 months) in two strains of mice (NMRI and C57BL) using a longitudinal study. Mice with or without previous training were tested when they were 6 months, and retested when 10 months old. The results showed that trained NMRI mice performed better than all the other groups, both at test and retest, indicating that previous training had more beneficial effects in NMRI than in C57BL mice. These resul…
How to learn a conceptual space
2005
the experiments proposed in the article by steels & belpaeme (s&b) can be considered as a starting point toward a general methodology for the automatic learning of conceptual spaces.
A Collaborative Filtering Approach for Drug Repurposing
2022
A recommendation system is proposed based on the construction of Knowledge Graphs, where physical interaction between proteins and associations between drugs and targets are taken into account. The system suggests new targets for a given drug depending on how proteins are linked each other in the graph. The framework adopted for the implementation of the proposed approach is Apache Spark, useful for loading, managing and manipulating data by means of appropriate Resilient Distributed Datasets (RDD). Moreover, the Alternating Least Square (ALS) machine learning algorithm, a Matrix Factorization algorithm for distributed and parallel computing, is applied. Preliminary obtained results seem to…
The Datafication of Hate: Expectations and Challenges in Automated Hate Speech Monitoring.
2020
Laaksonen, S-M.; Haapoja, J.; Kinnunen, T., Nelimarkka, M. & Pöyhtäri, R. (2020, accepted). . Frontiers in Big Data: Data Mining and Management / Critical Data and Algorithm Studies. doi:10.3389/fdata.2020.00003 Hate speech has been identified as a pressing problem in society and several automated approaches have been designed to detect and prevent it. This paper reports and reflects upon an action research setting consisting of multi-organizational collaboration conducted during Finnish municipal elections in 2017, wherein a technical infrastructure was designed to automatically monitor candidates' social media updates for hate speech. The setting allowed us to engage in a 2-fold investiga…