‘Learning This Way Is Like Piecing a Puzzle Together’: Bringing My Autoethnography as a Self-Directed Learner of French to a Conclusion

This is the fourth and final part of an autoethnography about how I tried to enrich my vocabulary and improve my listening skills through French language songs. I made a learning plan and followed the same Study Use Review Evaluate (SURE) learning cycle as my students in a self-directed English course at a university in Japan, over a period of six weeks. Throughout the project and in the course of writing it up, I made comparisons and identified connections between my learning and that of my students. In this installment, I first compare the difficulty levels of the vocabulary in the three songs I studied by finding the lexical frequency profile of each. Next, in revisiting my trouble with understanding spoken French while in France, I discuss how cultural awareness, in addition to linguistic knowledge, is necessary for intercultural communication. After that, I briefly explore empathy as a factor in advising students, and particularly how learning in the same way as them (as in this project) can assist a teacher/advisor in better understanding and helping their students/advisees. Finally, I discuss the writing process as a method of inquiry. I feel that writing this autoethnography has transformed me into a better learner, teacher/advisor, writer, and researcher, and in this way, I hope to help others benefit from this method too.

Automatic Recognition of the Lighting Whistler waves from the Wave Data of SCM Boarded on ZH-1 satellite

<p>Lightning whistlers, found frequently in electromagnetic satellite observation, are the important tool to study electromagnetic environment of the earth space. With the increasing data from electromagnetic satellites, a considerable amount of time and human efforts are needed to detect lightning whistlers from these tremendous data. In recent years, algorithms for lightning whistlers automatic detection have been conducted. However, these methods can only work in the time-frequency profile (image) of the electromagnetic satellites data with two major limitations: vast storage memory for the time-frequency profile (image) and expensive computation for employing the methods to detect automatically the whistler from the time-frequency profile. These limitations hinder the methods work efficiently on ZH-1 satellite. To overcome the limitations and realize the real-time whistler detection automatically on board satellite, we propose a novel algorithm for detecting lightning whistler from the original observed data without transforming it to the time-frequency profile (image).</p><p>The motivation is that the frequency of lightning whistler is in the audio frequency range. It encourages us to utilize the speech recognition techniques to recognize the whistler in the original data \of SCM VLF Boarded on ZH-1. Firstly, we averagely move a 0.16 seconds window on the original data to obtain the patch data as the audio clip. Secondly, we extract the Mel-frequency cepstral coefficients (MFCCs) of the patch data as a type of cepstral representation of the audio clip. Thirdly, the MFCCs are input to the Long Short-Term Memory (LSTM) recurrent neutral networks to classification. To evaluate the proposed method, we construct the dataset composed of 10000 segments of SCM wave data observed from ZH-1 satellite(5000 segments which involving whistler and 5000 segments without any whistler). The proposed method can achieve 84% accuracy, 87% in recall, 85.6% in F1score.Furthermore, it can save more than 126.7MB and 0.82 seconds compared to the method employing the YOLOv3 neutral network for detecting whistler on each time-frequency profile.</p><p> </p><p>Key words: ZH-1 satellite, SCM,lightning whistler, MFCC, LSTM</p>

Russian Iambic Tetrameter: The Evolution of Its Rhythmic Structure

To characterize the rhythm of stresses in a line of Russian iambic tetrameter, a frequency profile is often used, i. e., a diagram of the occurrence of real stresses on all feet (ictuses) of the verse line. This article discusses in detail one of the mechanisms that enables the speech factor to influence the formation of the stress profile. It is shown that in Russian iambic tetrameter of the nineteenth and twentieth centuries, the high frequency of stresses of the second ictus is explained by the fact that the beginning of the line more often than not coincides with the beginning of a sentence or clause, and the Russian syntagma is more frequently stressed in the middle. And vice versa, wherever the frequency of enjambments increases, the second ictus is less frequently stressed, because the beginning of the syntagma moves to the middle of the line. Considering the above, the author attempts to characterize the peculiarity of the rhythmic structure of Russian iambic tetrameter in synchronic and diachronic aspects and reveal some major large-scale trends such as the growth of the rhythmic diversity of poetic texts.

Sequence and word frequency

It is well-established that the linear ordering of words in a sentence is influenced by a variety of factors that are typically labelled as grammatical, discourse or cognitive constraints. The aim of the present study is to determine whether frequency effects are visible in the sequencing of words in a sentence. In other words, do “more frequently used units tend to be placed before less frequently used units” (Fenk-Oczlon 2001: 443)? Using a corpus of newspaper articles, we examine the frequency of words in different positions in sentences. That is, using data from thousands of sentences, we investigate the median value for the frequency or rank of words in first position in a sentence, compared with second position, and so on. We find that there is a frequency effect in English: the first element in a sentence has the highest frequency and last element in a sentence has the lowest frequency, with the middle of sentences having a more or less flat frequency profile. We also find that the overall shape of the frequency profile for sentences is rather consistent even when sentence length is taken into account.