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Building a Bidirectional Visible Light Communication Link: Challenges and Contributions
Visible Light Communication is a new information transmission method that involves sending data through light emitting diodes and photo-diodes via the visible light spectrum. It has strong applications in improving security for IoT (Internet of Things) devices. This paper describes a hardware-first approach to building a visible light communication (VLC) link. A VLC link was designed by choosing the simplest possible circuit and software and then incrementally improving it as challenges such as ambient lighting noise and data rate limitations were encountered. This link was used with two main communication protocols: On-off keying (OOK), and Frequency-Shift Keying. The paper describes a design for a fast, robust system using both protocols that also allows for an adjustable data rate. Because many issues were encountered along the way, the paper presents several possible sources of noise and data rate limitations and how to remove this noise and limitations. Finally, the paper also describes extensions to the design to make it bidirectional, more robust, and faster.Electrical and Computer Engineerin
2kenize: Tying Subword Sequences for Chinese Script Conversion
Simplified Chinese to Traditional Chinese character conversion is a common
preprocessing step in Chinese NLP. Despite this, current approaches have poor
performance because they do not take into account that a simplified Chinese
character can correspond to multiple traditional characters. Here, we propose a
model that can disambiguate between mappings and convert between the two
scripts. The model is based on subword segmentation, two language models, as
well as a method for mapping between subword sequences. We further construct
benchmark datasets for topic classification and script conversion. Our proposed
method outperforms previous Chinese Character conversion approaches by 6 points
in accuracy. These results are further confirmed in a downstream application,
where 2kenize is used to convert pretraining dataset for topic classification.
An error analysis reveals that our method's particular strengths are in dealing
with code-mixing and named entities.Comment: Accepted to ACL 202
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