This paper relies on 1 prerequisite mathematical and architectural foundations.
Background: Visible light of short wavelength (blue light) can damage the retina cells, called blue light hazard. To protect the retina, permissible exposure limits have been determined by ICNIRP (the International Commission on Non-Ionizing Radiation Protection) and other health and safety agencies. These limits include complex physical concepts, and their evaluation requires light measuring instruments equipped with a blue light hazard function filter, which is not available at the moment in developing countries. This study aims to assess retinal blue light hazard using the correlated color temperature of Light-Emitting Diode (LED) light sources. Methods: In this study, a new method was proposed for evaluating the retinal blue light hazard using only the Correlated Color Temperature (CCL) of LED light sources for which concern on blue light hazard has currently been reinforced. In the proposed method, the radiometric quantity (blue light effective radiance) in W.m-2.sr-1 was converted to the corresponding photometric quantity (blue light effective luminance) in lm.m-2.sr-1. Then a computer code was developed for relevant calculations. Results: The estimated permissible exposure times applying the new photometry approach were highly reliable and supported by the literature. The proposed method is particularly useful because it eliminates the need to utilize any light measuring device. Conclusion: The new approach makes the concept of blue light hazard straightforward and understandable for all specialists dealing with optical radiation safety.
Addresses critical efficiency and scalability bottlenecks in modern computing systems, providing concrete empirical evidence and reproducible designs.
Background: Visible light of short wavelength (blue light) can damage the retina cells, called blue light hazard.
Methods: In this study, a new method was proposed for evaluating the retinal blue light hazard using only the Correlated Color Temperature (CCL) of LED light sources for which concern on blue light hazard has currently been reinforced.
These limits include complex physical concepts, and their evaluation requires light measuring instruments equipped with a blue light hazard function filter, which is not available at the moment in developing countries.
Trade-offs between peak accuracy and memory overhead remain under investigation across diverse hardware environments.
The dominant sequence transduction models are based on complex recurrent or convolutional neural networks that include an encoder and a decoder. We propose the Transformer, a model architecture eschewing recurrence and instead relying entirely on an attention mechanism to draw global dependencies between input and output.
We propose Low-Rank Adaptation, or LoRA, which freezes the pretrained model weights and injects trainable rank decomposition matrices into each layer of the Transformer architecture, greatly reducing the number of trainable parameters for downstream tasks.
