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Task-based language learning in a real-world digital environment : the European digital kitchen
How can you use the latest digital technology to create an environment in which people can learn European languages while performing a meaningful real-world task and experiencing the cultural aspect of learning to cook European dishes? This book explains how to do this from A to Z, covering how a real-world, immersive digital environment for language learning was designed and built, as well as showing the learning experiences of users in five European countries. The project makes language learning motivational and fun by tapping into people's interest in both cooking and technology - you can learn a language while cooking and interacting with a speaking digital kitchen. The kitchens provide spoken instructions in the foreign language on how to prepare European cuisine. Digital sensors are inserted in or attached to all the kitchen equipment and ingredients, so the digital kitchen detects what learners are doing and gives them feedback. Learners are also able to communicate with the kitchens and can ask for help via photos and videos if they don't understand any foreign language words. Written by experts in computing and linguistics, the book explains the principles and procedures involved, enabling others to design and implement a real-world digital learning environment in the same way. It includes numerous photographs of the system in use and evidence of how and what 250 users actually learnt.
Book
SmartDetectAI: An AI‐Powered Web App for Real‐Time Colorimetric Detection of Heavy Metals in Water
AI‐powered monitoring platforms can significantly enhance the accessibility and responsiveness of water quality assessment in decentralized and resource‐limited settings. Conventional methods for detecting heavy metal ions, such as atomic absorption spectroscopy (AAS), offer high accuracy but require expensive instrumentation, trained personnel, and laboratory infrastructure, limiting their use in field applications. Here, SmartDetectAI, a low‐cost, portable, AI‐powered web application designed for rapid, on‐site colorimetric detection of heavy metal ions in water is presented. The system integrates silver nanoparticles (AgNPs) prepared from plant extract with a custom‐built imaging chamber and a web‐based application (web app) for automated and remote analysis. Supported by a computer vision model (YOLOv8n) for region detection and a machine learning algorithm (XGBoost) for concentration estimation, SmartDetectAI enables automated, real‐time quantification of mercury‐ and cadmium‐based species, which are the predominant aqueous forms under near‐neutral pH conditions. Users capture sensor images with a smart device and receive result outputs through an intuitive graphical interface hosted on a Flask‐based server. Field validation using pond water samples spiked with 1 and 10 μM Cd2+ shows strong agreement with standard AAS measurements, achieving an average predictive accuracy of ≈84%. SmartDetectAI integrates silver nanoparticle‐based colorimetric sensing with an AI‐powered web app for rapid, on‐site detection of toxic heavy metals in water. By combining aggregation‐driven optical changes with machine learning analysis of red ‐ green ‐ blue values, the platform achieves portable, low‐cost, and accurate monitoring of Hg‐ and Cd‐based species, validated against atomic absorption spectroscopy in real water samples.
Journal Article
Status of Sustainability Management Education in African MBA Programmes: A Web-based Research Approach
Emerging evidence suggests that business schools in Africa are lagging behind in promoting sustainability education. Grand challenges that point to a limited focus on transformative sustainability education such as environmental pollution, conflicts, inequalities and unemployment still persist in African economies, with the profit motive remaining central to businesses’ operating philosophy. Informed by the clarion call for business schools to be key drivers of sustainability education, this study reviews the African master of business administration (MBA) curricula with the objective of assessing the status of sustainability management education. The content of the MBA curricula of 42 African business schools accredited with the Association of African Business Schools was analysed using a web-based research approach. The findings indicate that the concept of sustainability has not been sufficiently embedded into the African MBA curricula. The values and mission statements of the majority of business schools were found not to be aligned with the principles of sustainability education. It was also found that shareholder value oriented modules constitute the core curriculum of the majority of MBA programmes reviewed. An incremental elective approach was found to be the most dominant strategy used by African business schools to incorporate sustainability education in the MBA curricula. An integrative approach of embedding sustainability education focusing on re-orientation of the business schools’ values, mission, curriculum, systems, operations and governance is recommended. The increased use of experiential learning is also recommended as an effective teaching pedagogy for equipping MBA students with practical aspects of sustainability education.
Journal Article
Interactive Web-Based Visual Analysis on Network Traffic Data
Network traffic data analysis is important for securing our computing environment and data. However, analyzing network traffic data requires tremendous effort because of the complexity of continuously changing network traffic patterns. To assist the user in better understanding and analyzing the network traffic data, an interactive web-based visualization system is designed using multiple coordinated views, supporting a rich set of user interactions. For advancing the capability of analyzing network traffic data, feature extraction is considered along with uncertainty quantification to help the user make precise analyses. The system allows the user to perform a continuous visual analysis by requesting incrementally new subsets of data with updated visual representation. Case studies have been performed to determine the effectiveness of the system. The results from the case studies support that the system is well designed to understand network traffic data by identifying abnormal network traffic patterns.
Journal Article
DBtRend: A Web-Server of tRNA Expression Profiles from Small RNA Sequencing Data in Humans
Transfer RNA (tRNA), a key component of the translation machinery, plays critical roles in stress conditions and various diseases. While knowledge regarding the importance of tRNA function is increasing, its biological roles are still not well understood. There is currently no comprehensive database or web server providing the expression landscape of tRNAs across a variety of human tissues and diseases. Here, we constructed a user-friendly and interactive database, DBtRend, which provides a profile of mature tRNA expression across various biological conditions by reanalyzing the small RNA or microRNA sequencing data from the Cancer Genome Atlas (TCGA) and NCBI’s Gene Expression Omnibus (GEO) in humans. Users can explore not only the expression values of mature individual tRNAs in the human genome, but also those of isodecoders and isoacceptors based on our specific pipelines. DBtRend provides the expressed patterns of tRNAs, the differentially expressed tRNAs in different biological conditions, and the information of samples or patients, tissue types, and molecular subtype of cancers. The database is expected to help researchers interested in functional discoveries of tRNAs.
Journal Article
Rapid clinical diagnostic variant investigation of genomic patient sequencing data with iobio web tools
Computational analysis of genome or exome sequences may improve inherited disease diagnosis, but is costly and time-consuming.
We describe the use of
, a web-based tool suite for intuitive, real-time genome diagnostic analyses.
We used
to identify the disease-causing variant in a patient with early infantile epileptic encephalopathy with prior nondiagnostic genetic testing.
tools can be used by clinicians to rapidly identify disease-causing variants from genomic patient sequencing data.
Journal Article
ArrayQue: The comprehensive transcriptome data analysis tool
We have developed microarray analysis pipeline software for covering the entire process of transcriptome data analysis. This software, part of the Korea Toxicogenomics Integrated System (KOTIS), is freely distributed to users who upload their microarray data to the KOTIS database, which is operated under the server system of the National Institute of Toxicological Research (NITR). The uploaded microarray data can be downloaded by users through a web search interface within KOTIS and are used as input data of the analysis software. The software, which consists of four major analysis modules and one meta-analysis module, is connected to a gene-related annotation database through the web. Major analysis modules consist of (1) data import and preprocessing, (2) differentially expressed gene finding, (3) clustering analysis, and (4) classification analysis. A gene-related annotation database provides the biological meanings of the analysis results. A highly standardized analysis flow, from data import to differentially expressed gene finding, can be easily implemented using the interface series of a run wizard. The KOTIS system and analysis software are accessible at
http://kotis.nitr.go.kr
.
Journal Article
Building energy information systems: user case studies
Measured energy performance data are essential to national efforts to improve building efficiency, as evidenced in recent benchmarking mandates, and in a growing body of work that indicates the value of permanent monitoring and energy information feedback. This paper presents case studies of energy information systems (EIS) at four enterprises and university campuses, focusing on the attained energy savings, and successes and challenges in technology use and integration. EIS are broadly defined as performance monitoring software, data acquisition hardware, and communication systems to store, analyze, and display building energy information. Case investigations showed that the most common energy savings and instances of waste concerned scheduling errors, measurement and verification, and inefficient operations. Data quality is critical to effective EIS use, and is most challenging at the subsystem or component level, and with non-electric energy sources. Sophisticated prediction algorithms may not be well understood but can be applied quite effectively, and sites with custom benchmark models or metrics are more likely to perform analyses external to the EIS. Finally, resources and staffing were identified as a universal challenge, indicating a need to identify additional models of EIS use that extend beyond exclusive in-house use, to analysis services.
Journal Article
Local safety and security planning in Finland
Local community safety and security planning is considered an effective tool to increase the security of citizens. When the Ministry of the Interior launched a new internal safety programme in 2004, it also decided to provide support to the regional authorities to prepare these plans. For this reason, VTT Technical Research Centre of Finland was asked to develop a common method and tool to identify and assess local threats. The developed method classifies threats in seven safety and security areas. In some of these, such as general vulnerability, criminality and major accidents, the method finds out which issues threaten people in their everyday lives. Some areas, such as disturbances and social exclusion, are regarded as consequences of other trouble, and the aim is to find the root causes of them. The method was established as a web-based software tool called ARTU.
Conference Proceeding
Access to Microdata on the Internet: Web-Based Analysis and Data Subset Extraction Tools
The Internet is increasingly being recognized as an invaluable component of education. At the college and university level, online databases and statistical tools for Web-based analysis and data subset extraction have become important instructional resources. These Internet resources enable students to formulate specific research hypotheses, identify relevant variables, and analyze large existing databases. This article describes three of these resources: the Federal Electronic Research and Review Extraction Tool (FERRET) of the U.S. Bureau of the Census, the Survey Documentation and Analysis (SDA) unit at the University of California, Berkley, and the Inter-University Consortium for Political and Social Research (ICPSR), which is housed at the University of Michigan.
Journal Article