Search results for "Machine"
showing 10 items of 2592 documents
Deep learning for knowledge tracing in learning analytics: An overview
2021
Learning Analytics (LA) is a recent research branch that refers to methods for measuring, collecting, analyzing, and reporting learners’ data, in order to better understand and optimize the processes and the environments. Knowledge Tracing (KT) deals with the modeling of the evolution, during the time, of the students’ learning process. Particularly its aim is to predict students’ outcomes in order to avoid failures and to support both students and teachers. Recently, KT has been tackled by exploiting Deep Learning (DL) models and generating a new, ongoing, research line that is known as Deep Knowledge Tracing (DKT). This was made possible by the digitalization process that has simplified t…
HR scenario game : Learning human resource management in a virtual environment
2021
This paper introduces a computer-based online scenario game that was developed to enhance the learning of human resource management (HRM) in an undergraduate course at a business school in Finland. What makes this game unique is that students played an important and active role in developing the game in collaboration with lecturers. Our findings show that the game enhances learning, interaction, and collaboration among students. We discuss how computer-based games and their development in collaboration with students can be used as a means for learning and improving working-life skills in higher education.
A Participant Experience Method for Illustrating Individuals’ Experiences in the Course of an Evolving Virtual Learning Community
2003
Early definitions of virtual learning communities often abstracted participants from their offline environments. However, often students’ virtual and physical environments are not essentially separated. Likewise, scholars should become more sensitive to and aware of their research principles and practices guiding studies in virtual settings and especially, in the intersections of on- and offline contexts. The participant experience method discussed in this paper, grants access also to the events outside the virtual learning context connecting various social settings and simultaneous events. However, the use of participant experience methods requires critical reflection during its various ph…
Representation of Autonomous Automata
2001
An autonomous automaton is a finite automaton with output in which the input alphabet has cardinality one when special reduced. We define the transition from automata to semigroups via a representation successful if given two incomparable automata (neither simulate the other), the semigroups representing the automata are distinct. We show that representation by the transition semigroup is not successful. We then consider a representation of automata by semigroups of partial transformations. We show that in general transition from automata to semigroups by this representation is not successful either. In fact, the only successful transition presented is the transiton to this semigroup of par…
Feature Ranking of Large, Robust, and Weighted Clustering Result
2017
A clustering result needs to be interpreted and evaluated for knowledge discovery. When clustered data represents a sample from a population with known sample-to-population alignment weights, both the clustering and the evaluation techniques need to take this into account. The purpose of this article is to advance the automatic knowledge discovery from a robust clustering result on the population level. For this purpose, we derive a novel ranking method by generalizing the computation of the Kruskal-Wallis H test statistic from sample to population level with two different approaches. Application of these enlargements to both the input variables used in clustering and to metadata provides a…
Image Quality Assessment Based on Intrinsic Mode Function Coefficients Modeling
2011
Reduced reference image quality assessment (RRIQA) methods aim to assess the quality of a perceived image with only a reduced cue from its original version, called ”reference image”. The powerful advantage of RR methods is their ”General-purpose”. However, most introduced RR methods are built upon a non-adaptive transform models. This can limit the scope of RR methods to a small number of distortion types. In this work, we propose a bi-dimensional empirical mode decomposition-based RRIQA method. First, we decompose both, reference and distorted images, into Intrinsic Mode Functions (IMF), then we use the Generalized Gaussian Density (GGD) to model IMF coefficients. Finally, the distortion m…
A New Image Distortion Measure Based on Natural Scene Statistics Modeling
2012
In the field of Image Quality Assessment (IQA), this paper examines a Reduced Reference (RRIQA) measure based on the bi-dimensional empirical mode decomposition. The proposed measure belongs to Natural Scene Statistics (NSS) modeling approaches. First, the reference image is decomposed into Intrinsic Mode Functions (IMF); the authors then use the Generalized Gaussian Density (GGD) to model IMF coefficients distribution. At the receiver side, the same number of IMF is computed on the distorted image, and then the quality assessment is done by fitting error between the IMF coefficients histogram of the distorted image and the GGD estimate of IMF coefficients of the reference image, using the …
Stochastical Real Time Finite State Machine LPC for Planar Manipulator Control System Model estimation
2005
This paper presents a new stochastical real-time LPC (Last Principal Component) algorithm to estimate single-input-single-output (SISO) and multiple-input-multiple-output (MIMO) varying time models from input output data clusters of non stationary black boxes. Each of data clusters is on a time window. An application to estimate the control system model of a planar manipulator is developed. In fact many mathematical models of physical systems are non stationary such as industrial manipulator model. A real time estimation algorithm via stochastical LPC algorithm and an appraiser called "finite state machine" is then described For every data cluster the finite state machine updates the parame…
PICTORIAL-C LANGUAGE FOR THE HERMIA-MACHINE
1992
The design and implementation of algorithms on multi-processors machines is hard. The paper describes the general features of the Pictorial C Language (PICL) that is oriented to image analysis. Its integration in the software environment of the HERMIA machine, and the handling of the related interconnecting network topology is also given.
MuPix and ATLASPix -- Architectures and Results
2020
High Voltage Monolithic Active Pixel Sensors (HV-MAPS) are based on a commercial High Voltage CMOS process and collect charge by drift inside a reversely biased diode. HV-MAPS represent a promising technology for future pixel tracking detectors. Two recent developments are presented. The MuPix has a continuous readout and is being developed for the Mu3e experiment whereas the ATLASPix is being developed for LHC applications with a triggered readout. Both variants have a fully monolithic design including state machines, clock circuitries and serial drivers. Several prototypes and design variants were characterised in the lab and in testbeam campaigns to measure efficiencies, noise, time reso…