AdaptiveVLE: an integrated framework for personalised online education using MPS JetBrains domain-specific modelling environment

This paper contains the design and development of an Adaptive Virtual Learning Environment (AdaptiveVLE) framework to assist educators of all disciplines with creating adaptive VLEs tailored to their needs and to contribute towards the creation of a more generic framework for adaptive systems. Fully online education is a major trend in education technology of our times. However, it has been criticised for its lack of personalisation and therefore not adequately addressing individual students’ needs. Adaptivity and intelligence are elements that could substantially improve the student experience and enhance the learning taking place. There are several attempts in academia and in industry to provide adaptive VLEs and therefore personalise educational provision. All these attempts require a multiple-domain (multi-disciplinary) approach from education professionals, software developers, data scientists to cover all aspects of the system. An integrated environment that can be used by all the multiple-domain users mentioned above and will allow for quick experimentation of different approaches is currently missing. Specifically, a transparent approach that will enable the educator to configure the data collected and the way it is processed without any knowledge of software development and/or data science algorithms implementation details is required. In our proposed work, we developed a new language/framework using MPS JetBrains Domain-Specific Language (DSL) development environment to address this problem. Our work consists of the following stages: data collection configuration by the educator, implementation of the adaptive VLE, data processing, adaptation of the learning path. These stages correspond to the adaptivity stages of all adaptive systems such as monitoring, processing and adaptation. The extension of our framework to include other application areas such as business analytics, health analytics, etc. so that it becomes a generic framework for adaptive systems as well as more usability testing for all applications will be part of our future work

Classification Algorithms Framework (CAF) to enable Intelligent Systems using JetBrains MPS domain-specific languages environment

This paper describes the design and development of a Classification Algorithms Framework (CAF) using the JetBrains MPS domain-specific languages (DSLs) development environment. It is increasingly recognized that the systems of the future will contain some form of adaptivity therefore making them intelligent systems as opposed to the static systems of the past. These intelligent systems can be extremely complex and difficult to maintain. Descriptions at higher-level of abstraction (system-level) have long been identified by industry and academia to reduce complexity. This research presents a Framework of Classification Algorithms at system-level that enables quick experimentation with several different algorithms from Naive Bayes to Logistic Regression. It has been developed as a tool to address the requirements of British Telecom’s (BT’s) data-science team. The tool has been presented at BT and JetBrains MPS and feedback has been collected and evaluated. Beyond the reduction in complexity through the system-level description, the most prominent advantage of this research is its potential applicability to many application contexts. It has been designed to be applicable for intelligent applications in several domains from business analytics, eLearning to eHealth, etc. Its wide applicability will contribute to enabling the larger vision of Artificial Intelligence (AI) adoption in context

Proc Natl Acad Sci U S A.

During translation, usually only one in approximately 400 misincorporations affects the function of a nascent protein, because only chemically similar near-cognate amino acids are misincorporated in place of the cognate one. The deleterious misincorporation of a chemically dissimilar noncognate amino acid during the selection process is precluded by the presence of a tRNA at the ribosomal E-site. However, the selection of first aminoacyl-tRNA, directly after initiation, occurs without an occupied E-site, i.e., when only the P-site is filled with the initiator tRNA and thus should be highly error-prone. Here, we show how bacterial ribosomes have solved this accuracy problem: In the absence of a Shine-Dalgarno (SD) sequence, the first decoding step at the A-site after initiation is extremely error-prone, even resulting in the significant incorporation of noncognate amino acids. In contrast, when a SD sequence is present, the incorporation of noncognate amino acids is not observed. This is precisely the effect that the presence of a cognate tRNA at the E-site has during the elongation phase. These findings suggest that during the initiation phase, the SD interaction functionally compensates for the lack of codon-anticodon interaction at the E-site by reducing the misincorporation of near-cognate amino acids and prevents noncognate misincorporation

Genetic (co-)variation of methane emissions, efficiency, and production traits in Danish Holstein cattle along and across lactations

publishedVersio

AdaptiveSystems: an integrated framework for adaptive systems design and development using MPS JetBrains domain-specific modelling environment

This paper contains the design and development of an adaptive systems (AdaptiveSystems Domain-Specific Language - DSL) framework to assist language developers and data scientists in their attempt to apply Artificial Intelligence (AI) algorithms in several application domains. Big-data processing and AI algorithms are at the heart of autonomics research groups among industry and academia. Major advances in the field have traditionally focused on algorithmic research and increasing the performance of the developed algorithms. However, it has been recently recognized by the AI community that the applicability of these algorithms and their consideration in context is of paramount importance for their adoption. Current approaches to address AI in context lie in two areas: adaptive systems research that mainly focuses on implementing adaptivity mechanisms (technical perspective) and AI in context research that focuses on business aspects (business perspective). There is currently no approach that combines all aspects required from business considerations to appropriate level of abstraction. In this paper, we attempt to address the problem of designing adaptive systems and therefore providing AI in context by utilising DSL technology. We propose a new DSL (AdaptiveSystems) and a methodology to apply this to the creation of a DSL for specific application domains such as AdaptiveVLE (Adaptive Virtual Learning Environment) DSL. The language developer will be able to instantiate the AdaptiveSystems DSL to any application domain by using the guidelines in this paper with an integrated path from design to implementation. The domain expert will then be able to use the developed DSL (e.g. AdaptiveVLE DSL) to design and develop their application. Future work will include extension and experimentation of the applicability of this work to more application domains within British Telecom (BT) and other areas such as health care, finance, etc

Desarrollo de un curso en línea para adultos mayores enfocado en el desarrollo de la competencia de creación de contenidos digitales en tiempos de COVID-19

Ante el COVID-19, el empleo de las Tecnologías de la Información y Comunicación (TIC) aumentó considerablemente, y con ello se hicieron evidentes las brechas digitales existentes en diferentes poblaciones. El grupo de los adultos mayores es uno de los que se ve excluido de todos los beneficios y oportunidades que las TIC traen consigo, puesto que son escasos los espacios en los que puedan alfabetizarse digitalmente, y que además se consideren sus características y necesidades particulares. El presente escrito tiene como objetivo dar a conocer el proyecto desarrollado en el Programa de Alfabetización Tecnológica del Instituto Tecnológico de Sonora, México, el cual consiste en un curso en línea de alfabetización digital para adultos mayores en la competencia de creación de contenido digital. El proyecto se considera como de desarrollo y se emplea el modelo de diseño instruccional ADDIE como metodología. Los principales resultados obtenidos son que los participantes desarrollaron la competencia de creación de contenido digital; los productos desarrollados en las actividades son de utilidad en sus diversos ámbitos; y el empleo de los principios andragógicos en el diseño, desarrollo e implementación del curso permitió un mejor aprendizaje de un adulto mayor

Decay Constants of Heavy-Light Mesons

The decay constants of the heavy-light pseudoscalar mesons are studied in a high statistics run using the Wilson action at $\beta=6.0$ and $\beta=6.2$, and the clover action at $\beta=6.0$. The systematics of $O(a)$ discretisation errors are discussed. Our best estimates of the decay constants are: $f_D$ = 218(9) MeV, $f_D/f_{Ds}$ = 1.11(1) and we obtain preliminary values for $f_B$.Comment: at the Dallas Lattice Conference, October 1993. 3 pages in a single postscript file, uuencoded form. Rome Preprint 93/98

The U(1)-Higgs Model: Critical Behaviour in the Confinig-Higgs region

We study numerically the critical properties of the U(1)-Higgs lattice model, with fixed Higgs modulus, in the region of small gauge coupling where the Higgs and Confining phases merge. We find evidence of a first order transition line that ends in a second order point. By means of a rotation in parameter space we introduce thermodynamic magnitudes and critical exponents in close resemblance with simple models that show analogous critical behaviour. The measured data allow us to fit the critical exponents finding values in agreement with the mean field prediction. The location of the critical point and the slope of the first order line are accurately given.Comment: 21 text pages. 12 postscript figures available on reques