This paper explores a simple discriminative preordering model for statistical machine translation. Our model traverses binary constituent trees, and classifies whether children of each node should be reordered. The model itself is not extremely novel, but herein we introduce a new procedure to determine oracle labels so as to maximize Kendall's τ. Experiments in Japanese-to-English translation revealed that our simple method is comparable with, or superior to, state-of-the-art methods in translation accuracy.
The purpose of this study was to evaluate the dark adaptation time in canine
electroretinography (ERG) using a contact lens electrode with a built-in LED. Twelve eyes
of six normal laboratory beagle dogs were used and exposed to steady room light at 500 lux
for 30 min for light adaption. ERG was recorded at different time points during dark
adaptation in sedated and light-adapted beagles. The stimulus intensity was 0.0096
cd/m2/sec. The b-wave amplitude increased significantly until 25 min of dark
adaptation, whereas no significant changes in amplitudes were observed after 30 min. Dark
adaptation for more than 25 min would be necessary for accurate ERG in canine ERG using a
contact lens electrode with a built-in LED.
Writing an ad text that attracts people and persuades them to click or act is essential for the success of search engine advertising. Therefore, ad creators must consider various aspects of advertising appeals (A 3 ) such as the price, product features, and quality. However, products and services exhibit unique effective A 3 for different industries. In this work, we focus on exploring the effective A 3 for different industries with the aim of assisting the ad creation process. To this end, we created a dataset of advertising appeals and used an existing model that detects various aspects for ad texts. Our experiments demonstrated that different industries have their own effective A 3 and that the identification of the A 3 contributes to the estimation of advertising performance.
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