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This study investigates the contrasting views on life and death as presented by Hui Shi’s concept of “birth and death” and Zhuangzi’s teachings on the same topic. By analyzing the meaning of the conjunction suiran(雖然) in Zhuangzi's texts, traditionally interpreted as indicating contradiction, this paper proposes a reinterpretation that suggests suiran can be understood as a connective term that bridges Hui Shi and Zhuangzi’s philosophies.

This paper introduces Mirza Ghalib and explicates his three Urdu ghazals, translated into Korean with the assistance of Google Translate and an Urdu native student, by referring to Aijaz Ahmad’s literal translations, notes, and general explanations. Often, it is believed that an outsider with little knowledge of the source language cannot successfully translate the original text due to lexical, historical, and cultural limitations. Even if one manages to do so, such translations are often viewed with suspicion of containing errors. However, I have already addressed this issue in my previous paper, where I examined Ezra Pound’s translation of Li Bai’s poems from Ernest Fenollosa’s cribs and argued that a translation is another original, reflecting a translator’s creative imaginations and original expressions generated through a dialogue with the original author. In this respect I am to challenge the skeptics by translating Ghalib’s three ghazals into Korean, just as Adrienne Rich did: I too maintained the translation principles provided by Ahmad in the 1960s, who encouraged her to create ‘poetry’ instead of ‘academic translations’ by using his literal translations as base texts. Since Ghalib is unfamiliar to most Koreans, I begin this paper by providing brief biographical information about him and my own view on the uniqueness of Ghalib’s Urdu Ghazal. Then, with the acknowledgment of my limitations, I offer my Korean translations of three ghazals, followed by my explications. In doing so, I try to contextualize Ghalib in the history of British colonization. While I do not intend to argue for any direct British influence on Ghalib, I make a suggestion that his ghazals may offer new, interesting layers of interpretation when hyper-connected to British Romantic poets.

This paper examines the evolution of narrative structures in storytelling, focusing on the interplay between character-driven narratives and media-specific formats. Using The Man Who Laughs a traditional feature-length film and Mask Girl a modern OTT series as case studies, the analysis highlights how differences in character arcs influence and shape narrative structures that align with the unique demands of their respective media. The study begins by exploring the character of Gwynplaine in The Man Who Laughs, whose singular and linear arc reflects the traditional three-act structure of classic cinema. The film's concise format prioritizes thematic clarity and emotional intensity, adhering to the requirements of the theatrical medium. In contrast, Mask Girl utilizes a non-linear, episodic structure characteristic of OTT platforms, leveraging its extended runtime and multiple character perspectives to explore contemporary themes such as identity, societal beauty standards, and the psychological implications of social media. By comparing these two works, the paper underscores how narrative techniques adapt to audience behavior and technological advancements. The cinematic medium emphasizes brevity and symbolic storytelling, while the digital OTT format allows for layered narratives and prolonged character development. The study also discusses the cultural and thematic relevance of these works, highlighting their critique of societal norms and their reflections on the human condition. This research contributes to understanding how storytelling evolves across media platforms and offers insights for creators and scholars into crafting narratives that resonate with diverse audiences in an ever-changing media landscape. By bridging traditional and modern techniques, this paper demonstrates the dynamic relationship between character, structure, and medium in contemporary storytelling.

The aim of this study is to answer the question of why simultaneous interpreting, successfully introduced in the 1945 Nuremberg Trials, was not utilized in the Tokyo Trials that took place the following year. At Nuremberg, simultaneous interpreting had dramatically accelerated the trials and allowed justice to be achieved in four languages. It was an innovation that gave rise to the profession of conference interpreting, and established research on interpreting as an independent academic discipline. The Tokyo Trials, however, employed only consecutive interpreting. The primary reason was the shortage of bilinguals fluent in English and Japanese. Additionally, the Tokyo tribunal neglected the fact that linguistic justice was a prerequisite for legal justice. A more fundamental reason was the tribunal’s mistrust in Japanese interpreters. The US-led tribunal, forced to depend on Japanese interpreters in a courtroom where their compatriots were being tried, assigned Japanese-Americans (Kibei) as monitors and US military officials as language arbiters to keep close watch on them. Unlike their counterparts in Nuremberg, the interpreters in the Tokyo Trials were reluctant to publicly disclose their involvement. The Tokyo Trials thus failed to become a turning point in the history of interpreting and Interpreting Studies in Japan.

This study examines the reading passages in Vietnamese upper secondary English textbooks across three curriculum revisions (2006, 2012, and 2018). A corpus analysis was conducted to quantitatively analyze lexical, cohesion, syntactic, and readability features with Coh-Metrix. The 2006 edition exhibited a clear progression in complexity, with significant differences in word count, sentence length, lexical diversity and readability across grade levels. The 2012 and 2018 editions, while generally more complex, showed less consistent patterns of increasing difficulty. While these revisions suggest an overall trend towards more challenging texts, the lack of consistent patterns in other features highlights the need for a deeper understanding of how textbook features interact to influence reading difficulty. Future research should explore the qualitative aspects of textbook content to provide insights into how specific lexical choices and syntactic structures impact comprehension.

This study explores derivatives formed by the quasi-suffix “-狗”, a prominent feature of modern Chinese Internet language. The character “-狗” (meaning “dog”), originally used only in compound words as a free morpheme with its independent lexical meaning, first appeared as a quasi-suffix in 2011. The term “单身狗” was the first widely popular derivative. Since then, numerous derivatives featuring the “-狗” quasi-suffix have emerged, spreading from online contexts into everyday language. While “-狗” in compound words typically refers to the animal “dog”, in the structure “root + -狗”, it takes on a figurative meaning. It no longer refers literally to a dog but has evolved to describe people who share particular characteristics, conditions, hobbies; tendencies, or occupations. The causes of the creation and spread of the “-狗” derivative include internal and external factors grammaticalization (metapher, metonymy, analogy), language economy, social-cultural change, the Internet use, and the action of memes. Accordingly, the rapid pace of change in the Internet culture has given rise to numerous neologisms, many of which fade quickly. However, derivatives with the “-狗” quasi-suffix have shown remarkable productivity and enduring vitality, contributing significantly to the expansion of contemporary Chinese vocabulary. Based on these findings, further research should focus on the ongoing development of the Internet language and the role of quasi-affixes in shaping new vocabulary.

This study suggests a teaching method of w verbs of ancient Greek. Recently, when Greek verbs are taught in the classroom, the focus is usually on the endings of Greek verbs. As a result, students are often misinformed by considering the outward agreement of verbs despite their different tenses. For example, it is taught that the future tense forms are formed by inserting the future tense-aspect suffix s into the present conjugation, or that the imperfect tense forms are conjugated in the basis on the present stem. However, these explanations are primarily misleading about Greek verb systems which are conjugated according to verb stems. Therefore, I suggested to the six stems of Greek verbs([1] pres. act. ・mid-pass.・pass. and impf. act.・mid-pass.・pass. stem-[2] fut. act.・mid-pass.・pass. stem-[3] aor. ac t.・mid-pass. stem-[4] pf. act. and pl-pf. act. stem-[5] pf. mid.-pass.・pass. and pl-pf. mid.-pass.・pass. stem-[6] aor. pass. and fut. pass. stem) rather than the endings in teaching Greek to students because it is more effective to teach students Greek verbal system in the basis of six stems of verbs.

This study aims to identify an AI classification model that is optimal for the classification of linguistic data. For this purpose, three commonly used classification models (XGBoost classifier, Random Forest Classifier, and SVM classifier) are compared in terms of their performance. Specifically, the three models are trained to classify the input data into essays and dialogues based on the syntactic complexity-related characteristics that distinguish between essays and dialogues. To determine if a model performing well on balanced data also performs well on imbalanced data, the three models’ performances are measured under two conditions: when the training dataset is balanced and when it is imbalanced. The performances of the trained models on the first test dataset are evaluated using accuracy, F1-score, normalized confusion matrix, and the area under the receiver operating characteristic curve. The performances on the second test dataset are assessed in terms of accuracy, confusion matrix, precision, and recall. The results demonstrate that the Random Forest Classifier has the best performance among the three models regardless of the balance of training data.