reading system
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Gut ◽  
2022 ◽  
pp. gutjnl-2021-325575
Author(s):  
Tim Raine ◽  
Holly Pavey ◽  
Wendi Qian ◽  
Gordon W Moran ◽  
Sreedhar Subramanian ◽  
...  

2022 ◽  
Vol 2022 ◽  
pp. 1-11
Author(s):  
Shumei Huang

In this paper, wireless sensor network technology is applied to an English-assisted reading system to highly simulate and restore the context and improve the performance of all aspects of the English-assisted reading system to optimize the English-assisted reading system. The product designed in this paper is based on wireless sensor network technology with Linux as the core operating system and supports POSIX (Portable Operating System Interface Standard) standard application development interface; QT is used as the component and framework of the system to support many applications. Based on player open-source multimedia audio and video technology, optimized and tailored for the hardware platform, it well supports multimedia learning and entertainment functions; this paper also adopts open-source database technology based on SQL (Structured Quevy Language) and Berkeley DB, using them as a platform for data storage and access, supporting a million-level thesaurus and high-speed, example sentence search. In this paper, we describe the user’s personalized needs by creating interest models for the user, recommending the text content, and reading order that can help with understanding through the interest models and reading articles and expanding the recommended text range by making expansions to the reading content through references and related articles to further help the user understand the text. Based on the above work, this paper implements an assisted reading system; finally, a multihop self-organizing network system is formed through a wireless sensor network to make the rigid and boring English reading easy and interesting.


2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yuanyao Lu ◽  
Qi Xiao ◽  
Haiyang Jiang

In recent years, deep learning has already been applied to English lip-reading. However, Chinese lip-reading starts late and lacks relevant dataset, and the recognition accuracy is not ideal. Therefore, this paper proposes a new hybrid neural network model to establish a Chinese lip-reading system. In this paper, we integrate the attention mechanism into both CNN and RNN. Specifically, we add the convolutional block attention module (CBAM) to the ResNet50 neural network, which enhances its ability to capture the small differences among the mouth patterns of similarly pronounced words in Chinese, improving the performance of feature extraction in the convolution process. We also add the time attention mechanism to the GRU neural network, which helps to extract the features among consecutive lip motion images. Considering the effects of the moments before and after on the current moment in the lip-reading process, we assign more weights to the key frames, which makes the features more representative. We further validate our model through experiments on our self-built dataset. Our experiments show that using convolutional block attention module (CBAM) in the Chinese lip-reading model can accurately recognize Chinese numbers 0–9 and some frequently used Chinese words. Compared with other lip-reading systems, our system has better performance and higher recognition accuracy.


2021 ◽  
Author(s):  
Hongyu Sun ◽  
Song Wang ◽  
Dong Han ◽  
Die Zhang
Keyword(s):  

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Jingen Jiang ◽  
Yongchun Xia

This paper designs and implements an intelligent online reading platform based on wireless sensor network. The platform adopts SSM framework based on Spring architecture as the cornerstone and is oriented to ordinary users and teachers and students. Ordinary users can carry out normal online reading on the platform, and teachers and students can carry out auxiliary reading teaching on the platform. The online reading platform is an interactive reading platform system integrating online reading, EPub resource generation and management, and user reading data statistics. The whole platform is composed of registration and login module, online reading module, EPub e-book generation module, and reading data report module. Spring, Spring MVC, and Mybatis framework are used to achieve hierarchical solution and improve development efficiency. For the problems that may occur in the process of EPub generation, an intelligent EPub generation mechanism is designed and implemented to achieve intelligent error correction and improve the stability of EPub generation. Platform design and implementation of a reading data report generation system can be in the background of the report generation and download. In addition, the random extraction problem in platform business is also analyzed, the problem model is established, and the database random extraction scheme commonly used in the industry is studied. The application of wireless sensor for reading aid is less and mostly stays in theory. Based on the traditional intelligent clustering system, the system is designed to improve the system scalability and provide a feasible literature assisted reading scheme while ensuring the accuracy and efficiency of the system.


2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Mila Glavaški ◽  
Lazar Velicki

Abstract Background Biomedical knowledge is dispersed in scientific literature and is growing constantly. Curation is the extraction of knowledge from unstructured data into a computable form and could be done manually or automatically. Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiac disease, with genotype–phenotype associations still incompletely understood. We compared human- and machine-curated HCM molecular mechanisms’ models and examined the performance of different machine approaches for that task. Results We created six models representing HCM molecular mechanisms using different approaches and made them publicly available, analyzed them as networks, and tried to explain the models’ differences by the analysis of factors that affect the quality of machine-curated models (query constraints and reading systems’ performance). A result of this work is also the Interactive HCM map, the only publicly available knowledge resource dedicated to HCM. Sizes and topological parameters of the networks differed notably, and a low consensus was found in terms of centrality measures between networks. Consensus about the most important nodes was achieved only with respect to one element (calcium). Models with a reduced level of noise were generated and cooperatively working elements were detected. REACH and TRIPS reading systems showed much higher accuracy than Sparser, but at the cost of extraction performance. TRIPS proved to be the best single reading system for text segments about HCM, in terms of the compromise between accuracy and extraction performance. Conclusions Different approaches in curation can produce models of the same disease with diverse characteristics, and they give rise to utterly different conclusions in subsequent analysis. The final purpose of the model should direct the choice of curation techniques. Manual curation represents the gold standard for information extraction in biomedical research and is most suitable when only high-quality elements for models are required. Automated curation provides more substance, but high level of noise is expected. Different curation strategies can reduce the level of human input needed. Biomedical knowledge would benefit overwhelmingly, especially as to its rapid growth, if computers were to be able to assist in analysis on a larger scale.


2021 ◽  
Author(s):  
S.H. Wong ◽  
◽  
S.L. Yang ◽  
C.M. Tsui

Laboratory instruments are commonly equipped with communication interfaces (e.g., GPIB, USB or LAN port) for data acquisition or control through a computer. However, such interface might not be available on handheld equipment, e.g., multi-meters, where readings have to be taken manually by operators during calibration. To improve efficiency and reduce possible human errors, SCL has developed an automatic meter reading system for seven segment displays using deep learning techniques.


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