The Steamboat Route Between China and Thailand In The First Part of The 20th Century

The deal with the Steamboat information, advertisement of route, those examples are based on the ‘Thai Chinese newspaper’ distributed in the First part of the 20th century in the National Library of Thailand. The purpose is to find out the details of Steamboat Company which moved between China and Thailand, and those Companies’ commercial activities in Thailand during that time.東アジアの歴史と動

The Treatment of The Siam Diplomatic Envoy arrived at Guangzhou in The Qing Dynasty

In the first year of the Shunzhi Emperor of the Qing Dynasty, Emperor Shunzhi took the palce of Emperor Chongzheng of Ming Dynasty became the new Owner of China. Along with the biggest feudal Dynasty became much more powerful, the ship from abroad also came a lot. Siam, as a tributary state of China during the period of Kangxi, Yongzheng, Qianlong, Jiaqing, Daoguang and Xianfeng Emperor, sent tributes to China via Guangzhou at that time. This paper talks about the tributary rules, trade disciplines and the treatment of Siam\u27s diplomatic corps, and analyzes the communication between the Qing Empire and the diplomatic corps of Siam

The Chinese Commodity Advertisement of Thailand in the First Part of the 20th Century

Until 1900, there are 608 thousands of Chinese people living in Thailand. During the late Qing Dynasty and early Republican Periods, there were many kinds of Chinese newspapers had published in Thailand. These newspapers were be born by Chinese intellectual. They accepted Liberal Democratic from oversea,and undisguised advocacy of revolution. The Chinese newspaper printed the information about Chinese society in business, economics and school. This paper researches on the form and content of the Chinese commodity advertisement to learn about the condition of the Chinese business activities during the period．文部科学省グローバルCOEプログラム 関西大学文化交渉学教育研究拠点東アジアの歴史と動

The Trapping and Characterization of a Single Hydrogen Molecule in a Continuously Tunable Nanocavity

Using inelastic electron tunneling spectroscopy with the scanning tunneling microscope (STM-IETS) and density functional theory calculations (DFT), we investigated properties of a single H2 molecule trapped in nanocavities with controlled shape and separation between the STM tip and the Au (110) surface. The STM tip not only serves for the purpose of characterization, but also is directly involved in modification of chemical environment of molecule. The bond length of H2 expands in the atop cavity, with a tendency of dissociation when the gap closes, whereas it remains unchanged in the trough cavity. The availability of two substantially different cavities in the same setup allows understanding of H2 adsorption on noble metal surfaces and sets a path for manipulating a single chemical bond by design.Comment: 11 pages, 4 figure

17-20世紀におけるタイ国華人の研究 [論文要旨及び審査の要旨]

関西大

17-20世紀におけるタイ国華人の研究

関西大

Chinese Education Under the Thailand Compulsory Education Regulations During the First Half of the 20th Century

There is a long history of Chinese immigration to Thailand, especially from the Chaozhou area. It can be sait that Chaozhou people are living examples of the saying “Where there is sea there are Chinese immigrants”. There was a continuing influx of the Chaozhou people, moving from China’s Fujian province to Thailand. This situation was particularly evident during the 17th to 20th centuries. After the revolution of 1911, Chinese intellectuals and businessmen in Thailand, aware of the “fundamentality of education” began to build schools in order to teach Chinese children living in Thailand the Chinese language. However these schools faced many difficulties. This paper will examine the school advertisements, educational reviews and articles published in the Shinbao and Thai-Chinese newspapers during the 1920’s to 1930’s. The purpose is to reveal the conditions of Chinese education during this period.東アジアの歴史と動

Iteratively Learning Representations for Unseen Entities with Inter-Rule Correlations

Recent work on knowledge graph completion (KGC) focused on learning embeddings of entities and relations in knowledge graphs. These embedding methods require that all test entities are observed at training time, resulting in a time-consuming retraining process for out-of-knowledge-graph (OOKG) entities. To address this issue, current inductive knowledge embedding methods employ graph neural networks (GNNs) to represent unseen entities by aggregating information of known neighbors. They face three important challenges: (i) data sparsity, (ii) the presence of complex patterns in knowledge graphs (e.g., inter-rule correlations), and (iii) the presence of interactions among rule mining, rule inference, and embedding. In this paper, we propose a virtual neighbor network with inter-rule correlations (VNC) that consists of three stages: (i) rule mining, (ii) rule inference, and (iii) embedding. In the rule mining process, to identify complex patterns in knowledge graphs, both logic rules and inter-rule correlations are extracted from knowledge graphs based on operations over relation embeddings. To reduce data sparsity, virtual neighbors for OOKG entities are predicted and assigned soft labels by optimizing a rule-constrained problem. We also devise an iterative framework to capture the underlying relations between rule learning and embedding learning. In our experiments, results on both link prediction and triple classification tasks show that the proposed VNC framework achieves state-of-the-art performance on four widely-used knowledge graphs. Further analysis reveals that VNC is robust to the proportion of unseen entities and effectively mitigates data sparsity.Comment: Accepted at CIKM 202

Instruction Distillation Makes Large Language Models Efficient Zero-shot Rankers

Recent studies have demonstrated the great potential of Large Language Models (LLMs) serving as zero-shot relevance rankers. The typical approach involves making comparisons between pairs or lists of documents. Although effective, these listwise and pairwise methods are not efficient and also heavily rely on intricate prompt engineering. To tackle this problem, we introduce a novel instruction distillation method. The key idea is to distill the pairwise ranking ability of open-sourced LLMs to a simpler but more efficient pointwise ranking. Specifically, given the same LLM, we first rank documents using the effective pairwise approach with complex instructions, and then distill the teacher predictions to the pointwise approach with simpler instructions. Evaluation results on the BEIR, TREC, and ReDial datasets demonstrate that instruction distillation can improve efficiency by 10 to 100x and also enhance the ranking performance of LLMs. Furthermore, our approach surpasses the performance of existing supervised methods like monoT5 and is on par with the state-of-the-art zero-shot methods. The code to reproduce our results is available at www.github.com/sunnweiwei/RankGPT