Search results for "TASK"
showing 10 items of 1658 documents
Analysis of spectral line shapes in low-temperature plasma by means of inverse ill-posed problem solution
2017
Promocijas darbs ir veltīts zemtemperatūras plazmas diagnostikas metodes attīstīšanai, augstfrekvences bezelektrodu lampām (ABL). Darbā tika izstrādāta jauna metode spektroskopisko datu apstrādei un reālo spektrāllīniju kontūru noteikšanai, risinot nekorekto apgriezto uzdevumu, kas balstās uz Tihonova regularizācijas algoritmu. Metode tika testēta aprēķinot patiesās profilu formas izmantojot eksperimentāli iegūtas Hg līnijās, emitētas no specialas formas mikro ABL. Tika pierādīts, ka aparatūras funkcijas neņemšana vērā zemtemperatūras plazmas gadījumā var ieviest lielu neprecizitāti, nosakot profilu formu un platumu un, sekojoši, ABL temperatūru. Tika analizēta arī atkarība no bufergāzes ve…
A Controllable Text Simplification System for the Italian Language
2021
Text simplification is a non-trivial task that aims at reducing the linguistic complexity of written texts. Researchers have studied the problem by proposing new methodologies for addressing the English language, but other languages, like the Italian one, are almost unexplored. In this paper, we give a contribution to the enhancement of the Automated Text Simplification research by presenting a deep learning-based system, inspired by a state of the art system for the English language, capable of simplifying Italian texts. The system has been trained and tested by leveraging the Italian version of Newsela; it has shown promising results by achieving a SARI value of 30.17.
Student Partners in Task Design in a computer medium to promote Foundation students' learning of mathematics
2018
International audience; A team consisting of three mathematics education teacher-researchers, four former Foundation students (called Student Partners, SPs), and two analytic assistants worked together to produce mathematical tasks in a computer medium for the mathematical learning of current Foundation students (FSs). We have explored the collaboration between the SPs and researchers, the processes and outcomes of task design, and the contribution of the collaboration to tutorial teaching of FSs. We seek insight into the learning of all concerned of mathematics, mathematics teaching, task design and personal-professional development. The project is ongoing. Here we introduce the project an…
"Master-Slave" Biological Network Alignment
2010
Performing global alignment between protein-protein interaction (PPI) networks of different organisms is important to infer knowledge about conservation across species. Known methods that perform this task operate symmetrically, that is to say, they do not assign a distinct role to the input PPI networks. However, in most cases, the input networks are indeed distinguishable on the basis of how well the corresponding organism is biologically well-characterized. For well-characterized organisms the associated PPI network supposedly encode in a sound manner all the information about their proteins and associated interactions, which is far from being the case for not well characterized ones. He…
Canonical Retina-to-Cortex Vision Model Ready for Automatic Differentiation
2020
Canonical vision models of the retina-to-V1 cortex pathway consist of cascades of several Linear+Nonlinear layers. In this setting, parameter tuning is the key to obtain a sensible behavior when putting all these multiple layers to work together. Conventional tuning of these neural models very much depends on the explicit computation of the derivatives of the response with regard to the parameters. And, in general, this is not an easy task. Automatic differentiation is a tool developed by the deep learning community to solve similar problems without the need of explicit computation of the analytic derivatives. Therefore, implementations of canonical visual neuroscience models that are ready…
An inductive inference approach to classification
1992
In this paper, we introduce a formal framework for investigating the relationship of inductive inference and the task of classification. We give the first results on the relationship between functions that can be identified in the limit and functions that can be acquired from unclassified objects only. Moreover, we present results on the complexity of classification functions and the preconditions necessary in order to allow the computation of such functions.
ENFORCEMENT OF INTER-TASK DEPENDENCIES IN WORKFLOWS, CHARACTERIZATION AND PARADIGM
1998
Workflow techniques have gained a lot of attention as a means to support advanced business applications such as cooperative information systems and process re-engineering but also as a means to integrate legacy systems. Inter-task dependencies, described separately from the other parts of the workflow, have been recognized as a valuable method in describing certain restrictions on the executions of workflows. In this paper, we study the issue of pre-analysing and enforcing inter-task dependencies. The protocol and the theory behind it are presented, along with examples and discussions on ways to improve the performance. The idea is to present the meaning of a dependency through an automato…
On enhancing the object migration automaton using the Pursuit paradigm
2017
Abstract One of the most difficult problems that is all-pervasive in computing is that of partitioning. It has applications in the partitioning of databases into relations, the realization of the relations themselves into sub-relations based on the partitioning of the attributes, the assignment of processes to processors, graph partitioning, and the task assignment problem, etc. The problem is known to be NP-hard. The benchmark solution for this for the Equi-Partitioning Problem (EPP) has involved the classic field of Learning Automata (LA), and the corresponding algorithm, the Object Migrating Automata (OMA) has been used in all of these application domains. While the OMA is a fixed struct…
User Grouping and Power Allocation in NOMA Systems: A Reinforcement Learning-Based Solution
2020
In this paper, we present a pioneering solution to the problem of user grouping and power allocation in Non-Orthogonal Multiple Access (NOMA) systems. There are two fundamentally salient and difficult issues associated with NOMA systems. The first involves the task of grouping users together into the pre-specified time slots. The subsequent second phase augments this with the solution of determining how much power should be allocated to the respective users. We resolve this with the first reported Reinforcement Learning (RL)-based solution, which attempts to solve the partitioning phase of this issue. In particular, we invoke the Object Migration Automata (OMA) and one of its variants to re…
Electronic properties of graphene: A learning path for undergraduate students
2016
The purpose of this work is to present a learning path aimed at deepening student understanding of the fundamental concepts underlying the electronic properties of new materials, graphene in particular. To achieve this task, we propose a five-week long workshop where students may be introduced to fundamental concepts of advanced physics, rarely used in learning paths, such as the symmetry properties of the crystal lattice, the group theory , the features of the free electron wave functions and energy levels, the relativistic Dirac equation. Particular emphasis is given to the manner of introducing these concepts, since an essential knowledge of solid state physics, quantum physics and relat…