With the advent of the next-generation Air Traffic Control(ATC)system,there is growing interest in using Artificial Intelligence(AI)techniques to enhance Situation Awareness(SA)for ATC Controllers(ATCOs),i.e.,Intellig...With the advent of the next-generation Air Traffic Control(ATC)system,there is growing interest in using Artificial Intelligence(AI)techniques to enhance Situation Awareness(SA)for ATC Controllers(ATCOs),i.e.,Intelligent SA(ISA).However,the existing AI-based SA approaches often rely on unimodal data and lack a comprehensive description and benchmark of the ISA tasks utilizing multi-modal data for real-time ATC environments.To address this gap,by analyzing the situation awareness procedure of the ATCOs,the ISA task is refined to the processing of the two primary elements,i.e.,spoken instructions and flight trajectories.Subsequently,the ISA is further formulated into Controlling Intent Understanding(CIU)and Flight Trajectory Prediction(FTP)tasks.For the CIU task,an innovative automatic speech recognition and understanding framework is designed to extract the controlling intent from unstructured and continuous ATC communications.For the FTP task,the single-and multi-horizon FTP approaches are investigated to support the high-precision prediction of the situation evolution.A total of 32 unimodal/multi-modal advanced methods with extensive evaluation metrics are introduced to conduct the benchmarks on the real-world multi-modal ATC situation dataset.Experimental results demonstrate the effectiveness of AI-based techniques in enhancing ISA for the ATC environment.展开更多
Calvin Wee first set foot in China at the age of 14—not for a diplomatic forum or a youth initiative,but on a week-long school trip to Guangzhou.Yet even then,the experience left a lasting impression.“We visited a l...Calvin Wee first set foot in China at the age of 14—not for a diplomatic forum or a youth initiative,but on a week-long school trip to Guangzhou.Yet even then,the experience left a lasting impression.“We visited a local school and sat in on several classes,”he recalled.“The math lessons stood out—the students’intensity and focus were striking.In Singapore,we study hard,but this was on another level.”That early glimpse into China’s education system stayed with him,and years later,it resurfaced as he began to engage more deeply with the Chinese language and culture.A pocket-sized wuxia xiaoshuo(martial arts novel),picked up on a whim in a Guangzhou bookstore,opened the door to martial arts fiction—and sparked a lasting interest in Chinese literature and,eventually,China Studies.展开更多
Iince rising to fame in 1987 on the television drama Sunshine After Rain,Singaporean artist Edmund Chen has starred in many films and TV series.He has also been active in theatre,hosting programs,and-more recently-pub...Iince rising to fame in 1987 on the television drama Sunshine After Rain,Singaporean artist Edmund Chen has starred in many films and TV series.He has also been active in theatre,hosting programs,and-more recently-publishing.Chen has authored 15 picture books and two art activity books for children,earning recognition as Southeast Asia’s Best Emerging Children’s Author.Today,he remains a prominent figure in public,not just as an actor but also as a writer and illustrator.展开更多
Extracting data from visually rich documents and charts using traditional methods that rely on OCR-based parsing poses multiple challenges,including layout complexity in unstructured formats,limitations in recognizing...Extracting data from visually rich documents and charts using traditional methods that rely on OCR-based parsing poses multiple challenges,including layout complexity in unstructured formats,limitations in recognizing visual elements,and the correlation between different parts of the documents,as well as domain-specific semantics.Simply extracting text is not sufficient;advanced reasoning capabilities are proving to be essential to analyze content and answer questions accurately.This paper aims to evaluate the ability of the Large Language Models(LLMs)to correctly answer questions about various types of charts,comparing their performance when using images as input versus directly parsing PDF files.To retrieve the images from the PDF,ColPali,a model leveraging state-of-the-art visual languagemodels,is used to identify the relevant page containing the appropriate chart for each question.Google’s Gemini multimodal models were used to answer a set of questions through two approaches:1)processing images derived from PDF documents and 2)directly utilizing the content of the same PDFs.Our findings underscore the limitations of traditional OCR-based approaches in visual document understanding(VrDU)and demonstrate the advantages of multimodal methods in both data extraction and reasoning tasks.Through structured benchmarking of chart question answering(CQA)across input formats,our work contributes to the advancement of chart understanding(CU)and the broader field of multimodal document analysis.Using two diverse and information-rich sources:the World Health Statistics 2024 report by theWorld Health Organisation and the Global Banking Annual Review 2024 by McKinsey&Company,we examine the performance ofmultimodal LLMs across different input modalities,comparing their effectiveness in processing charts as images versus parsing directly from PDF content.These documents were selected due to their multimodal nature,combining dense textual analysis with varied visual representations,thus presenting realistic challenges for vision-language models.This comparison is aimed at assessing how advanced models perform with different input formats and to determine if an image-based approach enhances chart comprehension in terms of accurate data extraction and reasoning capabilities.展开更多
This study examines the application of the Understanding by Design(UbD)approach to enhance students’cognitive,affective,and psychomotor learning domains,as well as their intercultural communication competence,in the ...This study examines the application of the Understanding by Design(UbD)approach to enhance students’cognitive,affective,and psychomotor learning domains,as well as their intercultural communication competence,in the Introduction to Chinese Culture course.UbD,a curriculum design framework emphasizing deep understanding over rote memorization,employs a“backward design”process to help students achieve a profound comprehension of Chinese culture and its modern implications.Through this approach,students also develop critical intercultural communication skills.The study offers helpful strategies for integrating English language teaching with Chinese cultural education,providing practical insights for curriculum development that bridges linguistic and cultural learning.展开更多
Based on the ADDIE model,we explored the integration path between Understanding Contemporary China:An English Reading and Writing Textbook and the main textbook of college English reading.Firstly,the basis of textbook...Based on the ADDIE model,we explored the integration path between Understanding Contemporary China:An English Reading and Writing Textbook and the main textbook of college English reading.Firstly,the basis of textbook integration was analyzed,followed by an explanation of the overall design scheme of textbook integration,and then a series of teaching resources were initially developed and used in teaching practice.Through testing,it was found that the integrative teaching of the two sets of textbooks under the ADDIE model achieved good teaching results,and promoted the three aspects of reading literacy,disciplinary literacy,and value leadership.展开更多
This is a research report on the interrelationship among understanding, memory and oral expression in listening comprehension training. The research investigated 150 non-English majors through a questionnaire in a hig...This is a research report on the interrelationship among understanding, memory and oral expression in listening comprehension training. The research investigated 150 non-English majors through a questionnaire in a higher vocational college. The result indicates that the interrelationship among understanding, memory and oral expression in listening classes which are determined by the listening materials and teaching method directly influences students' listening proficiency and speaking ability. It is suggested that some strategies to be used to foster students' abilities in these three areas so as to improve their listening ability.展开更多
基金supported by the National Natural Science Foundation of China(Nos.62371323,62401380,U2433217,U2333209,and U20A20161)Natural Science Foundation of Sichuan Province,China(Nos.2025ZNSFSC1476)+2 种基金Sichuan Science and Technology Program,China(Nos.2024YFG0010 and 2024ZDZX0046)the Institutional Research Fund from Sichuan University(Nos.2024SCUQJTX030)the Open Fund of Key Laboratory of Flight Techniques and Flight Safety,CAAC(Nos.GY2024-01A).
文摘With the advent of the next-generation Air Traffic Control(ATC)system,there is growing interest in using Artificial Intelligence(AI)techniques to enhance Situation Awareness(SA)for ATC Controllers(ATCOs),i.e.,Intelligent SA(ISA).However,the existing AI-based SA approaches often rely on unimodal data and lack a comprehensive description and benchmark of the ISA tasks utilizing multi-modal data for real-time ATC environments.To address this gap,by analyzing the situation awareness procedure of the ATCOs,the ISA task is refined to the processing of the two primary elements,i.e.,spoken instructions and flight trajectories.Subsequently,the ISA is further formulated into Controlling Intent Understanding(CIU)and Flight Trajectory Prediction(FTP)tasks.For the CIU task,an innovative automatic speech recognition and understanding framework is designed to extract the controlling intent from unstructured and continuous ATC communications.For the FTP task,the single-and multi-horizon FTP approaches are investigated to support the high-precision prediction of the situation evolution.A total of 32 unimodal/multi-modal advanced methods with extensive evaluation metrics are introduced to conduct the benchmarks on the real-world multi-modal ATC situation dataset.Experimental results demonstrate the effectiveness of AI-based techniques in enhancing ISA for the ATC environment.
文摘Calvin Wee first set foot in China at the age of 14—not for a diplomatic forum or a youth initiative,but on a week-long school trip to Guangzhou.Yet even then,the experience left a lasting impression.“We visited a local school and sat in on several classes,”he recalled.“The math lessons stood out—the students’intensity and focus were striking.In Singapore,we study hard,but this was on another level.”That early glimpse into China’s education system stayed with him,and years later,it resurfaced as he began to engage more deeply with the Chinese language and culture.A pocket-sized wuxia xiaoshuo(martial arts novel),picked up on a whim in a Guangzhou bookstore,opened the door to martial arts fiction—and sparked a lasting interest in Chinese literature and,eventually,China Studies.
文摘Iince rising to fame in 1987 on the television drama Sunshine After Rain,Singaporean artist Edmund Chen has starred in many films and TV series.He has also been active in theatre,hosting programs,and-more recently-publishing.Chen has authored 15 picture books and two art activity books for children,earning recognition as Southeast Asia’s Best Emerging Children’s Author.Today,he remains a prominent figure in public,not just as an actor but also as a writer and illustrator.
基金supported by a grant from the Ministry of Research,Innovation and Digitization,CNCS/CCCDI-UEFISCDI,project number COFUND-CETP-SMART-LEM-1,within PNCDI Ⅳ.
文摘Extracting data from visually rich documents and charts using traditional methods that rely on OCR-based parsing poses multiple challenges,including layout complexity in unstructured formats,limitations in recognizing visual elements,and the correlation between different parts of the documents,as well as domain-specific semantics.Simply extracting text is not sufficient;advanced reasoning capabilities are proving to be essential to analyze content and answer questions accurately.This paper aims to evaluate the ability of the Large Language Models(LLMs)to correctly answer questions about various types of charts,comparing their performance when using images as input versus directly parsing PDF files.To retrieve the images from the PDF,ColPali,a model leveraging state-of-the-art visual languagemodels,is used to identify the relevant page containing the appropriate chart for each question.Google’s Gemini multimodal models were used to answer a set of questions through two approaches:1)processing images derived from PDF documents and 2)directly utilizing the content of the same PDFs.Our findings underscore the limitations of traditional OCR-based approaches in visual document understanding(VrDU)and demonstrate the advantages of multimodal methods in both data extraction and reasoning tasks.Through structured benchmarking of chart question answering(CQA)across input formats,our work contributes to the advancement of chart understanding(CU)and the broader field of multimodal document analysis.Using two diverse and information-rich sources:the World Health Statistics 2024 report by theWorld Health Organisation and the Global Banking Annual Review 2024 by McKinsey&Company,we examine the performance ofmultimodal LLMs across different input modalities,comparing their effectiveness in processing charts as images versus parsing directly from PDF content.These documents were selected due to their multimodal nature,combining dense textual analysis with varied visual representations,thus presenting realistic challenges for vision-language models.This comparison is aimed at assessing how advanced models perform with different input formats and to determine if an image-based approach enhances chart comprehension in terms of accurate data extraction and reasoning capabilities.
基金The 2022 Guangdong Provincial Higher Education Teaching Quality and Reform Project“Research and Practice of English Teaching Integrating Ideological and Political Education into the Introduction to Chinese Culture Course Based on UbD Theory”。
文摘This study examines the application of the Understanding by Design(UbD)approach to enhance students’cognitive,affective,and psychomotor learning domains,as well as their intercultural communication competence,in the Introduction to Chinese Culture course.UbD,a curriculum design framework emphasizing deep understanding over rote memorization,employs a“backward design”process to help students achieve a profound comprehension of Chinese culture and its modern implications.Through this approach,students also develop critical intercultural communication skills.The study offers helpful strategies for integrating English language teaching with Chinese cultural education,providing practical insights for curriculum development that bridges linguistic and cultural learning.
基金funded by Project Information:2022 Guangzhou Municipal Higher Education Teaching Research and Reform Key Research Project:“Innovation and Practice of English Reading Curriculum Ideological and Political in Colleges and Universities:A Study on the Integration of Understanding Contemporary China:An English Reading and Writing Textbook and English Reading Teaching”(2023JGZDXM001).
文摘Based on the ADDIE model,we explored the integration path between Understanding Contemporary China:An English Reading and Writing Textbook and the main textbook of college English reading.Firstly,the basis of textbook integration was analyzed,followed by an explanation of the overall design scheme of textbook integration,and then a series of teaching resources were initially developed and used in teaching practice.Through testing,it was found that the integrative teaching of the two sets of textbooks under the ADDIE model achieved good teaching results,and promoted the three aspects of reading literacy,disciplinary literacy,and value leadership.
文摘This is a research report on the interrelationship among understanding, memory and oral expression in listening comprehension training. The research investigated 150 non-English majors through a questionnaire in a higher vocational college. The result indicates that the interrelationship among understanding, memory and oral expression in listening classes which are determined by the listening materials and teaching method directly influences students' listening proficiency and speaking ability. It is suggested that some strategies to be used to foster students' abilities in these three areas so as to improve their listening ability.
