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World of technology
A motivating introduction to using essential non-fiction reading skills, children will love to find out about the technologies we use in our lives.
Book
Telling Tales: Responding to Challenges in Literacy Competencies Using e-Reader-Based Programs
Current worldwide debates on quality standards in education are interwoven with debates on the use of technology. While technology is profoundly changing the way we live, communicate and learn, relatively little seems to be known about its potential to influence literacies. The limited research that exists in this area, although sometimes encouraging, seems to focus on large-scale investment in laptop programs that have little relevance or hope in being tried or tested in evolving countries where literacy rates are most indicative of the urgent need for practical and affordable solutions. This paper reports on a 4-month study, part of a longitudinal study that looks at the power of e-readers to support change in the literacy habits and ultimately the learning cultures of a group of English as a foreign language (EFL) teachers-in-training in Chile. Literacy and how to develop it, is a prime concern in Chile. With the need for worldwide citizens to have increased and diverse competencies in meaning making and in negotiating complex information, many Chileans still lack basic reading skills. The future looks even bleaker as successive groups of teachers, who themselves have serious literacy challenges, are entering the system with little hope of affecting change. The aim of the study was to determine if access to low-cost mobile readers and a social-learning based, technology-supported, guided reading program, could reverse this picture for the participants. The study is based on social-cultural theory in which learner agency, access to funds of knowledge and social interaction are imperative ingredients for developing engaged, life-long readers. Participatory Action Research (PAR) is used to conduct the inquiry. Working within a qualitative research paradigm, ethnographic tools are employed to uncover how the use of technology influences both the literacy practices and identities of the teachers-in-training, from their perspectives. Numerical data from pre- and post-test results are also analyzed and used to support the findings that patterns of literacy development changed. The evolving changes in the way many of these learners come to view their literacy practices supported by technology, combined with their identity construction over the period of the guided program online, have important implications for other learners, educators and policy makers. The findings suggest a new model of literacy education is needed in such challenging contexts, and particularly here in Chile, that involves accessible technology as an important part of the solution to providing democratic possibilities for all learners to develop the reading habits and competencies they require to be active 21st century global citizens.
Conference Proceeding
Robots
\"Kingfisher Readers are developed with literacy experts to span five levels, from Level 1 (beginning to read) to level 5 (reading fluently). Robots introduces children who can read alone with some help to these incredible inventions. It includes facts about different types of robots, such as automatons, humanoids, androids, drones, factory robots and domestic robots. Children will read about robots that have gone to space, robots that can play sports and robots that look a lot like people. See www.kingfisherreaders.com for series information\"-- Provided by publisher.
Book
Lateral Flow Immunoassay Reader Technologies for Quantitative Point-of-Care Testing
Due to the recent pandemic caused by coronavirus disease 2019 (COVID-19), the lateral flow immunoassay used for its rapid antigen test is more popular than ever before. However, the history of the lateral flow immunoassay is about 60 years old, and its original purpose of use, such as a COVID-19 rapid antigen test or a pregnancy test, was the qualitative detection of a target analyte. Recently, the demand for quantitative analysis of lateral flow immunoassays is increasing in various fields. Lateral flow immunoassays for quantitative detection using various materials and sensor technologies are being introduced, and readers for analyzing them are being developed. Quantitative analysis readers are highly anticipated for their future development in line with technological advancements such as optical, magnetic field, photothermal, and electrochemical sensors and trends such as weight reduction, miniaturization, and cost reduction of systems. In addition, the sensing, processing, and communication functions of portable personal devices such as smartphones can be used as tools for the quantitative analysis of lateral flow immunoassays. As a result, lateral flow immunoassays can efficiently achieve the goal of rapid diagnosis by point-of-care testing. Readers used for the quantification of lateral flow immunoassays were classified according to the adopted sensor technology, and the research trends in each were reviewed in this paper. The development of a quantitative analysis system was often carried out in the assay aspect, so not only the readers but also the assay development cases were reviewed if necessary. In addition, systems for quantitative analysis of COVID-19, which have recently been gaining importance, were introduced as a separate section.
Journal Article
International evaluation of an AI system for breast cancer screening
Screening mammography aims to identify breast cancer at earlier stages of the disease, when treatment can be more successful
1
. Despite the existence of screening programmes worldwide, the interpretation of mammograms is affected by high rates of false positives and false negatives
2
. Here we present an artificial intelligence (AI) system that is capable of surpassing human experts in breast cancer prediction. To assess its performance in the clinical setting, we curated a large representative dataset from the UK and a large enriched dataset from the USA. We show an absolute reduction of 5.7% and 1.2% (USA and UK) in false positives and 9.4% and 2.7% in false negatives. We provide evidence of the ability of the system to generalize from the UK to the USA. In an independent study of six radiologists, the AI system outperformed all of the human readers: the area under the receiver operating characteristic curve (AUC-ROC) for the AI system was greater than the AUC-ROC for the average radiologist by an absolute margin of 11.5%. We ran a simulation in which the AI system participated in the double-reading process that is used in the UK, and found that the AI system maintained non-inferior performance and reduced the workload of the second reader by 88%. This robust assessment of the AI system paves the way for clinical trials to improve the accuracy and efficiency of breast cancer screening.
An artificial intelligence (AI) system performs as well as or better than radiologists at detecting breast cancer from mammograms, and using a combination of AI and human inputs could help to improve screening efficiency.
Journal Article
Leaf it to Dot
Dad joins Dot and Hal outdoors while they work to earn their Rangeroo scavenger hunt badges and to not let technology distract them from nature.
Book
Overseas reception of English translations of Journey to the West: Temporal dynamics, cross-platform sentiment patterns, and topic modeling
The overseas reception of classical literature through online platforms presents a critical lens for understanding cross-cultural dynamics in the digital age. This study investigates the overseas reception of English translations of Journey to the West by analyzing a corpus of 1,795 reviews from Amazon and Goodreads to examine temporal dynamics, cross-platform sentiment patterns, and topic modeling. The analysis covers four celebrated translators: Arthur Waley, Anthony C. Yu, Julia Lovell, and W.J.F. Jenner. Methodologically, we developed a hybrid sentiment lexicon by integrating a domain sentiment lexicon with AFINN, NRC, and VADER through weighted fusion, addressing the limited adaptability of general sentiment lexicons in translated literature analysis. LDA modeling was further applied to enable data-driven theme extraction. Key findings reveal a consistent year-on-year increase in review counts across all translations. Notably, despite an overall positive sentiment, significant cross-platform divergences emerge, reflecting the distinct evaluative mechanisms of digital platforms. Thematic analysis identifies three central reader concerns: translation quality, plot acceptance, and character portrayal, with plot acceptance exhibiting markedly higher negativity. Furthermore, translator-level analysis reveals performance variations across these themes. This study demonstrates how digital platforms reconfigure the valuation of literary translation, and pioneers a methodological framework for capturing the dynamic interplay between reader perception, media infrastructure, and textual mobility, offering new pathways for digital humanities research in translation studies.
Journal Article
What cat is that? : all about cats
\"The Cat in the Hat learns all about cats--wild and domestic--in this feline-focused Cat in the Hat's Learning Library book!\"-- Provided by publisher.
Book
Coverage-Conflict-Aware RFID Reader Placement with Range Adjustment for Complete Tag Coverage in IIoT
Radio Frequency Identification (RFID) is a core enabler of the Industrial Internet of Things (IIoT), yet dense deployments suffer from tag collisions and reader interference that degrade reliability and inflate infrastructure cost. This study proposes a deterministic Reader Deployment Algorithm with Adjustable Reader range (RDA2R) to achieve full tag coverage with minimal interference and reader usage. The method divides the monitored field into grid units, evaluates tag coverage weights, activates high-weight readers with interference checks, and adaptively adjusts interrogation ranges. Simulation results under random and congregation tag distributions show that RDA2R requires about 46-47% fewer readers than ARLDL and 32-33% fewer than MR2D, while improving average tag coverage per reader by over 30%. These results demonstrate that RDA2R provides a scalable, interference-aware, and cost-efficient deployment strategy for RFID-enabled IIoT environments.
Journal Article