{'fraction_non_alphanumeric': 0.020761245674740483, 'fraction_numerical': 0.0, 'mean_word_length': 5.225806451612903, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
The Identification of Ammonia Concentration by QNN

In this paper, the humidity interference on the ammonia sensors was studied and proposed. The shear horizontal surface acoustic wave (SH-SAW) devices coated with L-glutamic acid hydrochloride were applied as ammonia sensors. The responses to ammonia in the humid environment were positive frequency shifts and the perturbation was primarily from the elastic effect. In order to precisely estimate the ammonia in humid air, the quantum neural network (QNN) is used as the identifier and its identification results are reported.