AI chatbot for educational service improvement in the post-pandemic era : a case study prototype for supporting digital reading list

This paper describes the development of an educational artificial intelligence (AI) chatbot prototype to support teachers in developing digital reading lists for their students. The chatbot aims to teach users how to use an educational system – Talis Aspire – effectively by giving them quick answers to questions, offering demonstrations and instructions on how to complete essential tasks on Talis Aspire, advising them how to solve problems and providing solutions for common issues. We have presented the prototype, together with the approach we used to design and develop it by considering the concepts of ‘Recontextualisation’ and ‘Quality Function Deployment’. We argue that the use of chatbot technology can not only help tutors develop online education and teaching materials but may also improve the quality of educational services during and after the COVID-19 pandemic. A number of recommendations and further work suggested by domain experts have also been highlighted in this paper in order to improve our prototype further

Big Data Analytics in Smart Grids for Renewable Energy Networks: Systematic Review of Information and Communication Technology Tools

El desarrollo industrial y económico de los países industrializados, a partir del siglo XIX, ha ido de la mano del desarrollo de la electricidad, del motor de combustión interna, de los ordenadores, de Internet, de la utilización de datos y del uso intensivo del conocimiento centrado en la ciencia y la tecnología. La mayoría de las fuentes de energía convencionales han demostrado ser finitas y agotables. A su vez, las diferentes actividades de producción de bienes y servicios que utilizan combustibles fósiles y energía convencional, han aumentado significativamente la contaminación del medio ambiente, y con ello, han contribuido al calentamiento global. El objetivo de este trabajo fue realizar una aproximación teórica a las tecnologías de análisis de datos e inteligencia de negocio aplicadas a las redes de sistemas eléctricos inteligentes con energías renovables. Para este trabajo se realizó una revisión bibliométrica y bibliográfica sobre Big Data Analytics, herramientas TIC de la industria 4.0 y Business intelligence en diferentes bases de datos disponibles en el dominio público. Los resultados del análisis indican la importancia del uso de la analítica de datos y la inteligencia de negocio en la gestión de las empresas energéticas. El trabajo concluye señalando cómo se está aplicando la inteligencia de negocio y la analítica de datos en ejemplos concretos de empresas energéticas y su creciente importancia en la toma de decisiones estratégicas y operativasThe industrial and economic development of the industrialized countries, from the nineteenth century, has gone hand in hand with the development of electricity, the internal combustion engine, computers, the Internet, data use and the intensive use of knowledge focused on science and the technology. Most conventional energy sources have proven to be finite and exhaustible. In turn, the different production activities of goods and services using fossil fuels and conventional energy, have significantly increased the pollution of the environment, and with it, contributed to global warming. The objective of this work was to carry out a theoretical approach to data analytics and business intelligence technologies applied to smart electrical-system networks with renewable energies. For this paper, a bibliometric and bibliographic review about Big Data Analytics, ICT tools of industry 4.0 and Business intelligence was carried out in different databases available in the public domain. The results of the analysis indicate the importance of the use of data analytics and business intelligence in the management of energy companies. The paper concludes by pointing out how business intelligence and data analytics are being applied in specific examples of energy companies and their growing importance in strategic and operational decision makinghttps://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000192503https://scholar.google.com/citations?user=9HLAZYUAAAAJ&hl=eshttps://scienti.minciencias.gov.co/gruplac/jsp/visualiza/visualizagr.jsp?nro=00000000005961https://orcid.org/0000-0003-1166-198

Conceptualización de territorios inteligentes: Una aproximación desde el enfoque sociotécnico.

El concepto de territorios inteligentes ha ido emergiendo en la literatura por la necesidad de extender las premisas de las ciudades inteligentes a entornos rurales o de enfoque regional. Este trabajo hace una conceptualización de territorios inteligentes desde un enfoque sociotécnico,a partir de la revisión de literatura del concepto de ciudad inteligente, donde se identifican tanto componentes tecnológicos (conectividad, analítica, instrumentación y aplicaciones) como contextuales (institucionalización, especialización inteligente e innovación), como parte esencialpara el desarrollo de estas iniciativas. Se expone una arquitectura genérica con los componentes expuestos y se definen algunas estrategias para la dinamización de territorios inteligentes a partir de los componentes propuestos

Translational recoding as a feedback controller : systems approaches reveal polyamine-specific effects on the antizyme ribosomal frameshift

Peer reviewedPublisher PD

Education in the digital age : learning experience in virtual and mixed realities

In recent years Virtual Reality has been revitalized, having gained and lost popularity between the 1960s and 1990s, and is now widely used for entertainment purposes. However, Virtual Reality, along with Mixed Reality and Augmented Reality, has broader application possibilities, thanks to significant advances in technology and accessibility. In the current study, we examined the effectiveness of these new technologies for use in education. We found that learning in both virtual and mixed environments resulted in similar levels of performance to traditional learning. However, participants reported higher levels of engagement in both Virtual Reality and Mixed Reality conditions compared to the traditional learning condition, and higher levels of positive emotions in the Virtual Reality condition. No simulator sickness was found from using either headset, and both headsets scored similarly for system usability and user acceptance of the technology. Virtual Reality, however, did produce a higher sense of presence than Mixed Reality. Overall, the findings suggest that some benefits can be gained from using Virtual and Mixed Realities for education

Methodology for automatic fault detection in photovoltaic arrays from artificial neural networks

This article presents a methodology for automatic fault detection in photovoltaic arrays. Due to the great importance in the construction of increasingly robust photovoltaic plants, automatic fault detection has become a necessary tool to extend the useful life of these plants, avoid system shutdowns and reduce serious safety problems. In the present study, nine possible faults are detected, caused by malfunction in the bypass and blocking diodes. The solution consists of training two models based on artificial neural networks, the first model is a binary classifier that detects whether or not a fault occurs, the second is a multiclass classifier that detects the fault type. The obtained models were trained from simulation data, in an architecture of 9 photovoltaic panels interconnected in three rows by three columns matrix (extendable to larger systems). The evaluation shows that the prediction system has a total accuracy of 92.95%. Finally, this methodology is intended to be implemented in Colombia, in zones with difficult access and not interconnected to the electricity grid, seeking to reduce corrective maintenance

Optimal sensor arrangements in Angle of Arrival (AoA) and range based localization with linear sensor arrays

This paper investigates the linear separation requirements for Angle-of-Arrival (AoA) and range sensors, in order to achieve the optimal performance in estimating the position of a target from multiple and typically noisy sensor measurements. We analyse the sensor-target geometry in terms of the Cramer–Rao inequality and the corresponding Fisher information matrix, in order to characterize localization performance with respect to the linear spatial distribution of sensors. Here in this paper, we consider both fixed and adjustable linear sensor arrays

Towards hierarchical blackboard mapping on a whiskered robot

The paradigm case for robotic mapping assumes large quantities of sensory information which allow the use of relatively weak priors. In contrast, the present study considers the mapping problem for a mobile robot, CrunchBot, where only sparse, local tactile information from whisker sensors is available. To compensate for such weak likelihood information, we make use of low-level signal processing and strong hierarchical object priors. Hierarchical models were popular in classical blackboard systems but are here applied in a Bayesian setting as a mapping algorithm. The hierarchical models require reports of whisker distance to contact and of surface orientation at contact, and we demonstrate that this information can be retrieved by classifiers from strain data collected by CrunchBot's physical whiskers. We then provide a demonstration in simulation of how this information can be used to build maps (but not yet full SLAM) in an zero-odometry-noise environment containing walls and table-like hierarchical objects. © 2012 Elsevier B.V. All rights reserved

Identifying the science and technology dimensions of emerging public policy issues through horizon scanning

Public policy requires public support, which in turn implies a need to enable the public not just to understand policy but also to be engaged in its development. Where complex science and technology issues are involved in policy making, this takes time, so it is important to identify emerging issues of this type and prepare engagement plans. In our horizon scanning exercise, we used a modified Delphi technique [1]. A wide group of people with interests in the science and policy interface (drawn from policy makers, policy adviser, practitioners, the private sector and academics) elicited a long list of emergent policy issues in which science and technology would feature strongly and which would also necessitate public engagement as policies are developed. This was then refined to a short list of top priorities for policy makers. Thirty issues were identified within broad areas of business and technology; energy and environment; government, politics and education; health, healthcare, population and aging; information, communication, infrastructure and transport; and public safety and national security.Public policy requires public support, which in turn implies a need to enable the public not just to understand policy but also to be engaged in its development. Where complex science and technology issues are involved in policy making, this takes time, so it is important to identify emerging issues of this type and prepare engagement plans. In our horizon scanning exercise, we used a modified Delphi technique [1]. A wide group of people with interests in the science and policy interface (drawn from policy makers, policy adviser, practitioners, the private sector and academics) elicited a long list of emergent policy issues in which science and technology would feature strongly and which would also necessitate public engagement as policies are developed. This was then refined to a short list of top priorities for policy makers. Thirty issues were identified within broad areas of business and technology; energy and environment; government, politics and education; health, healthcare, population and aging; information, communication, infrastructure and transport; and public safety and national security

A single amino acid change of translation termination factor eRF1 switches between bipotent and omnipotent stop-codon specificity†

In eukaryotes a single class-1 translation termination factor eRF1 decodes the three stop codons: UAA, UAG and UGA. Some ciliates, like Euplotes, have a variant code, and here eRF1s exhibit UAR-only specificity, whereas UGA is reassigned as a sense codon. Since eukaryote eRF1 stop-codon recognition is associated with its N-terminal domain, structural features should exist in the N domain of ciliate eRF1s that restrict their stop-codon specificity. Using an in vitro reconstituted eukaryotic translation system we demonstrate here that a chimeric eRF1 composed of the N domain of Euplotes aediculatus eRF1 fused to the MC domains of human eRF1 exhibits UAR-only specificity. Functional analysis of eRF1 chimeras constructed by swapping Euplotes N domain sequences with the cognate regions from human eRF1 as well as site-directed mutagenesis of human eRF1 highlighted the crucial role of the alanine residue in position 70 of E. aediculatus eRF1 in restricting UGA decoding. Switching the UAR-only specificity of E. aediculatus eRF1 to omnipotent mode is due to a single point mutation. Furthermore, we examined the influence of eRF3 on the ability of chimeric and mutant eRF1s to induce peptide release in response to different stop codons