Search results for "intelligence"
showing 10 items of 6959 documents
Development of pre-academic skills and motivation in kindergarten : a subgroup analysis between classroom quality profiles
2017
AbstractThe present study extends research on classroom quality profiles by examining the differences between profiles with respect to children’s development in pre-academic skills and motivation across the kindergarten year. Teacher–child interactions were observed in 49 Finnish kindergarten classrooms using the CLASS Pre-K instrument. Based on prior identification of latent profiles of classroom quality, subgroup analyses on children’s data were carried out on three profiles representing high Emotional Support and Classroom Organisation and intermediate Instructional Support (Profile 1), higher-intermediate Emotional Support and Classroom Organisation and lower-intermediate Instructional …
What Conclusions does Rapid Image Classification by Eye Movements Provide for Machine Vision?
2008
Human ability to rapidly classify images of natural objects has been a matter of study for more than a decade. Recently eye movements have been exploited as a behavioural response, which has lead to alternative hypotheses of natural image processing. In this research, twelve volunteers made a movement towards a briefly displayed digital image if it was an animal, and a movement away otherwise. In both cases, the average response time was more than 400 milliseconds.
An Integrative Approach for Product Development and Customer Satisfaction Measurement
1999
As soon as the automotive industry in the western world countries recognizes that the outstanding performance of Japanese manufacturers is the result of a customer-oriented understanding of quality, the QFD approach became a famous instrument to achieve the product quality demanded by customers. Nevertheless this concept has its limits. In this article we suggest the extension of the QFD approach on the base of customer values and benefits.
Optimal configuration for size-based burst assembly algorithms at the edge node for video traffic transmissions over OBS networks
2008
Optical burst switching (OBS) has been proposed to be a technology for implementing the next generation optical Internet. In this architecture, burst assembly algorithms have an important influence in the pattern traffic that characteristic this sort of optical networks. On the other hand, traffic coming from new applications (such as video on demand, Voice over IP, online gaming or Grid computing) that have real time and bandwidth constraints, has been experimented a rapid increment. Consequently, we consider important to evaluate the performance of traffic from real time applications over OBS networks. In this paper, we evaluate the effects of implementing a size-based burst assembly sche…
Classification of diabetes-related retinal diseases using a deep learning approach in optical coherence tomography
2019
Background and objectives: Spectral Domain Optical Coherence Tomography (SD-OCT) is a volumetric imaging technique that allows measuring patterns between layers such as small amounts of fluid. Since 2012, automatic medical image analysis performance has steadily increased through the use of deep learning models that automatically learn relevant features for specific tasks, instead of designing visual features manually. Nevertheless, providing insights and interpretation of the predictions made by the model is still a challenge. This paper describes a deep learning model able to detect medically interpretable information in relevant images from a volume to classify diabetes-related retinal d…
LocalRec 2018 workshop report the second ACM SIGSPATIAL workshop on recommendations for location-based services and social networks * Seattle, Washin…
2019
Driven by technological advances in hardware (positioning systems, environmental sensors), software (standards, tools, network services), and aided by various open movements (open, linked, government data) and the ever-growing mentality of sharing for the greater good (crowdsourcing, crowdfunding, collaborative and volunteered geographic information), the amount of available geo-referenced data has seen dramatic explosion over the past few years. Human activities generate data and traces that are now often transparently annotated with location and contextual information. At the same time, it has become easier than ever to collect and combine rich and diverse information about locations. Exp…
On solving single elevator-like problems using a learning automata-based paradigm
2020
This paper concentrates on a host of problems with characteristics similar to those that are related to moving elevators within a building. These are referred to as Elevator-like problems (ELPs), and their common phenomena will be expanded on in the body of the paper. We shall resolve ELPs using a subfield of AI, namely the field of learning automata (LA). Rather than working with the well-established mathematical formulations of the field, our intention is to use these tools to tackle ELPs, and in particular, those that deal with single “elevators” moving between “floors”. ELPs have not been tackled before using AI. In a simplified domain, the ELP involves the problem of optimizing the sch…
Agent assisted interactive algorithm for computationally demanding multiobjective optimization problems
2015
Abstract We generalize the applicability of interactive methods for solving computationally demanding, that is, time-consuming, multiobjective optimization problems. For this purpose we propose a new agent assisted interactive algorithm. It employs a computationally inexpensive surrogate problem and four different agents that intelligently update the surrogate based on the preferences specified by a decision maker. In this way, we decrease the waiting times imposed on the decision maker during the interactive solution process and at the same time decrease the amount of preference information expected from the decision maker. The agent assisted algorithm is not specific to any interactive me…
ELM Regularized Method for Classification Problems
2016
Extreme Learning Machine (ELM) is a recently proposed algorithm, efficient and fast for learning the parameters of single layer neural structures. One of the main problems of this algorithm is to choose the optimal architecture for a given problem solution. To solve this limitation several solutions have been proposed in the literature, including the regularization of the structure. However, to the best of our knowledge, there are no works where such adjustment is applied to classification problems in the presence of a non-linearity in the output; all published works tackle modelling or regression problems. Our proposal has been applied to a series of standard databases for the evaluation o…
Optimal imaging of multi-channel EEG features based on a novel clustering technique for driver fatigue detection
2020
Abstract Fatigue may cause a decrease in mental and physical performance capacity, which is a serious safety risk for the drivers in the transportation system. Recently, various studies have demonstrated the deviations of electroencephalogram (EEG) indicators from normal vigilant state during fatigue in time and frequency domains. However, when considering spatial information, these feature descriptors are not satisfying the demand for reliable detection due to the well-known challenge of signal mixing. In this paper, we propose a novel approach based on clustering on brain networks (CBNs) to alleviate the problem to improve the performance of driver fatigue detection. The clustering algori…