Construction of a 5G Wireless Semantic Web-Assisted English Digital Learning Resource Query System

Based on the 5G wireless semantic network, this paper realizes the construction of the English digital learning resources query system, providing the query and management functions for English digital learning resources, and realizes the integration of functions and resources on the digital learning system and mobile learning system. The platform is put into practical application, and data analysis is conducted to conclude how this system is used and whether it is conducive to improving students’ interest in learning English and their English proficiency. We propose a quality algorithm for 5G wireless networks, which not only captures the characteristics of 5G wireless networks such as local broadcast and node movement but also combines quality predicates as guards with broadcast reception actions, which are used to portray that a node can continue to execute subsequent processes only when the node reception actions satisfy certain conditions, which works together with the node default value mechanism to reduce the impact caused by unreliable links. The query content is interpreted and supplemented at the semantic level by using synonym expansion, and the knowledge base is used to filter the synonym expansion and further expand the synonym expansion query based on knowledge structure, to tap the implicit knowledge points related to the query, and to fuse the two extensions to realize the knowledge-based query expansion. We use 5G wireless semantic web-related technologies to build an English digital learning resource query system with complete functions and good experience across terminals. Through the questionnaire survey and data analysis of the users of this system, it is found that the system is well used and effectively enhances students’ interest in learning English and improves learning efficiency. By applying the experimental comparison method, it is known that this system has improved students’ English proficiency to a certain extent.

An AI-Based Query System for Historical Weather Radar Reflectivity Retrieval Using a Convolutional Auto-encoder

The weather patterns in Taiwan have been more changeable in recent years. Taking rainfall as an example, natural disasters that lead to major damage are often caused by heavy rainfall in a short period of time. Therefore, how to effectively predict changes in weather patterns has become an important issue for the development of disaster prevention technology. In this paper, an AI-based query system using a convolutional auto-encoder is developed for historical weather radar reflectivity retrieval that is expected to forecast heavy rainfall soon. When the weather radar receives a current radar reflectivity, meteorologists can employ the query system to quickly search for the historical radar reflectivity with the weather characteristics similar to the one to be queried. The experimental results reveal that under the given MSE threshold of 58,000, the average pass rate achieves 83.9% for the ranked top 10 similar results from 33,461 historical records via 4,319 query tests in total. Without considering the model loading time of 60 seconds, the execution time of each query requires 6 seconds for only listing query results or 8 seconds for including saving resulting maps in pseudo-colour.

A BIM-driven framework for integrating rules and regulations in the decommissioning of nuclear power plants

Purpose The relatively low capital cost and contributions to mitigating global warming have favoured the continuous construction and operation of nuclear power plants (NPPs) across the world. One critical phase in the operation of nuclear plants for ensuring the safety and security of radioactive products and by-products is decommissioning. With the advent of digital twinning in the building information modelling (BIM) methodology, efficiency and safety can be improved from context-focus access to regulations pertaining to demolition of structures and the cleaning-up of radioactivity inherent in nuclear stations. The purpose of this study, therefore, is to propose a BIM-driven framework to achieve a more regulation-aware and safer decommissioning of nuclear power plants. Design/methodology/approach The framework considers task requirements, and landscape and environmental factors in modelling demolition scenarios that characterise decommissioning processes. The framework integrates decommissioning rules/regulations in a BIM linked non-structured query system to model items and decommissioning tasks, which are implemented based on context-focussed retrieval of decommissioning rules and regulations. The concept’s efficacy is demonstrated using example cases of digitalised NPPs. Findings This approach contributes to enhancing improvements in nuclear plant decommissioning with potential for appropriate activity sequencing, risk reduction and ensuring safety. Originality/value A BIM-driven framework hinged on querying non-structured databases to provide context-focussed access to nuclear rules and regulations and to aiding decommissioning is new.

The use of an Online Student Query System using an ITIL approach at CPUT, Department of Information Technology

Student’s queries play a significant role in improving the service delivery for IT students at CPUT Department of Information Technology. It is imperative to know how to handle student requests efficiently. Currently student’s lodge their complaints, selecting from a list of topics their query gets captured, the student query might not get addressed on time or in a certain time frame to support ITIL-based continual service improvement. This study will look at implementing the key service-level processes of ITIL and discuss how to integrate it successfully.

Match Algorithms for Scientific Names in FlorItaly, the Portal to the Flora of Italy

Scientific names are not part of everyday language in any modern country, and their input as strings in a query system can be easily associated with typographical errors. While globally unique identifiers univocally address a taxon name, they can hardly be used for querying a database manually. Thus, matching algorithms are often used to overcome misspelled names in query systems in several data repositories worldwide. In order to improve users’ experience in the use of FlorItaly, the Portal to the Flora of Italy, a near match algorithm to resolve misspelled scientific names has been integrated in the query systems. In addition, a novel tool in FlorItaly, capable of rapidly aligning any list of names to the nomenclatural backbone provided by the national checklists, has been developed. This manuscript aims at describing the potential of these new tools.