Convergence Condition of Explicit Finite Element Method for Heat Transfer Problem

The convergence condition of the explicit difference method for the heat transfer problem is aiready obtained. On the other hand, if the problem is formulated by using the weighted residual method for spatial axis, we have no tool to estimate the critical timestep width. In this paper, the estimation method is theoretically presented, and its propriety is examined through a number of numerical experiments

Relations between Sleep Time and SNS Texts

Sleeping habits are one of the major issues in today’s healthcare. In this paper, we consider the problem of analyzing sleeping habits of people using social networking service (SNS) texts. As the first step toward predicting user’s sleeping time using SNS texts, we assume that the time span between the user’s last post in one day and the first post the next day can be used as a pseudo-indicator for the user’s sleeping time if the user posts the text sufficiently frequently. We call such tweet time spans “pseudo-sleeping time” if the first tweet of the next day include “Good morning” or similar words. We try to predict such pseudo-sleeping time using the text (tweet) of the preceding tweet (i.e., the last tweet of the day). Preliminary experiments show that the tweet text contains some useful information to predict the user’s pseudo-sleeping time

Emotional Similarity Word Embedding Model for Sentiment Analysis

We propose a method for constructing a dictionary of emotional expressions, which is an indispensable language resource for sentiment analysis in the Japanese. Furthermore, we propose a method for constructing a language model that reproduces emotional similarity between words, which to date has yet not been considered in conventional dictionaries and language models. In the proposed method, we pre-trained sentiment labels for the distributed representations of words. An intermediate feature vector was obtained from the pre-trained model. By learning an additional semantic label on this feature vector, we can construct an emotional semantic language model that embeds both emotion and semantics. To confirm the effectiveness of the proposed method, we conducted a simple experiment to retrieve similar emotional words using the constructed model. The results of this experiment showed that the proposed method can retrieve similar emotional words with higher accuracy than the conventional word-embedding model

Effect of Soft Abdomen on Quadrupedal Gait Control

The 11th International Symposium on Adaptive Motion of Animals and Machines. Kobe University, Japan. 2023-06-06/09. Adaptive Motion of Animals and Machines Organizing Committee.Poster Session P5

Solid-phase total synthesis and structural confirmation of antimicrobial longicatenamide A

Longicatenamides A–D are cyclic hexapeptides isolated from the combined culture of Streptomyces sp. KUSC_F05 and Tsukamurella pulmonis TP-B0596. Because these peptides are not detected in the monoculture broth of the actinomycete, they are key tools for understanding chemical communication in the microbial world. Herein, we report the solid-phase total synthesis and structural confirmation of longicatenamide A. First, commercially unavailable building blocks were chemically synthesized with stereocontrol. Second, the peptide chain was elongated via Fmoc-based solid-phase peptide synthesis. Third, the peptide chain was cyclized in the solution phase, followed by simultaneous cleavage of all protecting groups to afford longicatenamide A. Chromatographic analysis corroborated the chemical structure of longicatenamide A. Furthermore, the antimicrobial activity of synthesized longicatenamide A was confirmed. The developed solid-phase synthesis is expected to facilitate the rapid synthesis of diverse synthetic analogues

Classification of Smartphone Application Reviews Using Small Corpus Based on Bidirectional LSTM Transformer

This paper provides the classification of the review texts on a smartphone application posted on social media. We propose a high performance binary classification method (positive/negative) of review texts, which uses the bidirectional long short-term memory (biLSTM) self-attentional Transformer and is based on the distributed representations created by unsupervised learning of a manually labelled small review corpus, dictionary, and an unlabeled large review corpus. The proposed method obtained higher accuracy as compared to the existing methods, such as StarSpace or the Bidirectional Encoder Representations from Transformer (BERT)