We analyze the suitability of existing pre-trained transformer-based language models(PLMs)for abstractive text summarization on German technical healthcare texts.The study focuses on the multilingual capabilities of t...We analyze the suitability of existing pre-trained transformer-based language models(PLMs)for abstractive text summarization on German technical healthcare texts.The study focuses on the multilingual capabilities of these models and their ability to perform the task of abstractive text summarization in the healthcare field.The research hypothesis was that large language models could perform high-quality abstractive text summarization on German technical healthcare texts,even if the model is not specifically trained in that language.Through experiments,the research questions explore the performance of transformer language models in dealing with complex syntax constructs,the difference in performance between models trained in English and German,and the impact of translating the source text to English before conducting the summarization.We conducted an evaluation of four PLMs(GPT-3,a translation-based approach also utilizing GPT-3,a German language Model,and a domain-specific bio-medical model approach).The evaluation considered the informativeness using 3 types of metrics based on Recall-Oriented Understudy for Gisting Evaluation(ROUGE)and the quality of results which is manually evaluated considering 5 aspects.The results show that text summarization models could be used in the German healthcare domain and that domain-independent language models achieved the best results.The study proves that text summarization models can simplify the search for pre-existing German knowledge in various domains.展开更多
Accessible communication based on sign language recognition(SLR)is the key to emergency medical assistance for the hearing-impaired community.Balancing the capture of both local and global information in SLR for emerg...Accessible communication based on sign language recognition(SLR)is the key to emergency medical assistance for the hearing-impaired community.Balancing the capture of both local and global information in SLR for emergency medicine poses a significant challenge.To address this,we propose a novel approach based on the inter-learning of visual features between global and local information.Specifically,our method enhances the perception capabilities of the visual feature extractor by strategically leveraging the strengths of convolutional neural network(CNN),which are adept at capturing local features,and visual transformers which perform well at perceiving global features.Furthermore,to mitigate the issue of overfitting caused by the limited availability of sign language data for emergency medical applications,we introduce an enhanced short temporal module for data augmentation through additional subsequences.Experimental results on three publicly available sign language datasets demonstrate the efficacy of the proposed approach.展开更多
Since the specifications of most of the existing context-sensitive graph grammars tend to be either too intricate or not intuitive, a novel context-sensitive graph grammar formalism, called context-attributed graph gr...Since the specifications of most of the existing context-sensitive graph grammars tend to be either too intricate or not intuitive, a novel context-sensitive graph grammar formalism, called context-attributed graph grammar（CAGG）, is proposed. In order to resolve the embedding problem, context information of a graph production in the CAGG is represented in the form of context attributes of the nodes involved. Moreover, several properties of a set of confluent CAGG productions are characterized, and then an algorithm based on them is developed to decide whether or not a set of productions is confluent, which provides the foundation for the design of efficient parsing algorithms. It can also be shown through the comparison of CAGG with several typical context-sensitive graph grammars that CAGG is more succinct and, at the same time, more intuitive than the others, making it more suitably and effortlessly applicable to the specification of visual languages.展开更多
In order to ensure the safety,quality and efficiency of computer numerical control(CNC)machine tool processing,a real-time monitoring and visible solution for CNC machine tools based on hyper text markup language(HTML...In order to ensure the safety,quality and efficiency of computer numerical control(CNC)machine tool processing,a real-time monitoring and visible solution for CNC machine tools based on hyper text markup language(HTML)5 is proposed.The characteristics of the real-time monitoring technology of CNC machine tools under the traditional Client/Server(C/S)structure are compared and analyzed,and the technical drawbacks are proposed.Web real-time communication technology and browser drawing technology are deeply studied.A real-time monitoring and visible system for CNC machine tool data is developed based on Metro platform,combining WebSocket real-time communication technology and Canvas drawing technology.The system architecture is given,and the functions and implementation methods of the system are described in detail.The practical application results show that the WebSocket real-time communication technology can effectively reduce the bandwidth and network delay and save server resources.The numerical control machine data monitoring system can intuitively reflect the machine data,and the visible effect is good.It realizes timely monitoring of equipment alarms and prompts maintenance and management personnel.展开更多
The original intention of visual question answering(VQA)models is to infer the answer based on the relevant information of the question text in the visual image,but many VQA models often yield answers that are biased ...The original intention of visual question answering(VQA)models is to infer the answer based on the relevant information of the question text in the visual image,but many VQA models often yield answers that are biased by some prior knowledge,especially the language priors.This paper proposes a mitigation model called language priors mitigation-VQA(LPM-VQA)for the language priors problem in VQA model,which divides language priors into positive and negative language priors.Different network branches are used to capture and process the different priors to achieve the purpose of mitigating language priors.A dynamically-changing language prior feedback objective function is designed with the intermediate results of some modules in the VQA model.The weight of the loss value for each answer is dynamically set according to the strength of its language priors to balance its proportion in the total VQA loss to further mitigate the language priors.This model does not depend on the baseline VQA architectures and can be configured like a plug-in to improve the performance of the model over most existing VQA models.The experimental results show that the proposed model is general and effective,achieving state-of-the-art accuracy in the VQA-CP v2 dataset.展开更多
二语写作是二语习得研究领域的重要组成部分。运用CiteSpace软件对近十年发表在Journal of Second Language Writing的231篇实证研究论文进行可视化分析,研究发现:二语写作研究整体呈波动性上升趋势,研究规模较为稳定,研究关注度逐渐提...二语写作是二语习得研究领域的重要组成部分。运用CiteSpace软件对近十年发表在Journal of Second Language Writing的231篇实证研究论文进行可视化分析,研究发现:二语写作研究整体呈波动性上升趋势,研究规模较为稳定,研究关注度逐渐提升;二语写作研究领域暂未形成明显的核心作者和机构的合作网络;研究主题主要聚焦二语写作教学方法的多元化、二语写作反馈的多焦点、二语写作评估与测试的科学化,以及学习者个体差异的多维影响等方面。基于此,提出未来该领域发展需加强学者、机构之间的相互合作;关注个体学习者写作过程的认知特征与情感因素,尤其重视青少年二语学习过程的研究;扩大二语写作纵向研究规模,推动研究的深入发展。展开更多
Dynamic sign language recognition holds significant importance, particularly with the application of deep learning to address its complexity. However, existing methods face several challenges. Firstly, recognizing dyn...Dynamic sign language recognition holds significant importance, particularly with the application of deep learning to address its complexity. However, existing methods face several challenges. Firstly, recognizing dynamic sign language requires identifying keyframes that best represent the signs, and missing these keyframes reduces accuracy. Secondly, some methods do not focus enough on hand regions, which are small within the overall frame, leading to information loss. To address these challenges, we propose a novel Video Transformer Attention-based Network (VTAN) for dynamic sign language recognition. Our approach prioritizes informative frames and hand regions effectively. To tackle the first issue, we designed a keyframe extraction module enhanced by a convolutional autoencoder, which focuses on selecting information-rich frames and eliminating redundant ones from the video sequences. For the second issue, we developed a soft attention-based transformer module that emphasizes extracting features from hand regions, ensuring that the network pays more attention to hand information within sequences. This dual-focus approach improves effective dynamic sign language recognition by addressing the key challenges of identifying critical frames and emphasizing hand regions. Experimental results on two public benchmark datasets demonstrate the effectiveness of our network, outperforming most of the typical methods in sign language recognition tasks.展开更多
Visual Query Language on Spatial Information (SIVQL) is one kind of visual query language based on the extension of Query by Example (QBE). It is a visual operation based on graphics or media object, such as point, li...Visual Query Language on Spatial Information (SIVQL) is one kind of visual query language based on the extension of Query by Example (QBE). It is a visual operation based on graphics or media object, such as point, line and area elements. In this paper, the relation calculation and query function of SIVQL have been studied and discussed by using set theory and relation algebra. The theory foundation of SIVQL has been investigated by the mathematical method. Finally, its application examples are also given with the specific information system.展开更多
Color language has important meaning for children’s picture books.Understanding children’s preferences in terms of color language will be helpful when designers model computerized picture books in order to adapt to ...Color language has important meaning for children’s picture books.Understanding children’s preferences in terms of color language will be helpful when designers model computerized picture books in order to adapt to children’s visual senses and effectively stimulate children’s interest in reading.In this study,we aimed to further explore the general characteristics of children’s preference for colors,color depth and color matching forms in picture books.For the study,256 children between the ages of three and six were selected and divided into four groups.According to the implementation needs of the children’s color preference test,these childrenwere asked to complete a series of tasks so that their choices in the tasks could subsequently be analyzed.The tasks included making the following choices:selecting their preferred colors from nine options(red,orange,yellow,green,cyan,blue,purple,black and white);selecting their preferred color brightness fromthree different color shades;and indicating their preferences in relation to complementary colors,matching colors and pure colors.The experimental results showed that children aged between three and six mainly favor red,blue and yellow,and colors with a high degree of brightness.As children grow older,boys tend to prefer blue,and girls tend to prefer pink,with red remaining the favorite color of both genders.As for complementary colors,matching colors and solid colors,three-to six-year-old children prefer solid colors.In conclusion,it seems that color language preferences in children between the ages of three and six are very similar,which could be of use when designing children’s picture books to match their visual vocabulary and psychological cognition.展开更多
Multimodal sentiment analysis is an essential area of research in artificial intelligence that combines multiple modes,such as text and image,to accurately assess sentiment.However,conventional approaches that rely on...Multimodal sentiment analysis is an essential area of research in artificial intelligence that combines multiple modes,such as text and image,to accurately assess sentiment.However,conventional approaches that rely on unimodal pre-trained models for feature extraction from each modality often overlook the intrinsic connections of semantic information between modalities.This limitation is attributed to their training on unimodal data,and necessitates the use of complex fusion mechanisms for sentiment analysis.In this study,we present a novel approach that combines a vision-language pre-trained model with a proposed multimodal contrastive learning method.Our approach harnesses the power of transfer learning by utilizing a vision-language pre-trained model to extract both visual and textual representations in a unified framework.We employ a Transformer architecture to integrate these representations,thereby enabling the capture of rich semantic infor-mation in image-text pairs.To further enhance the representation learning of these pairs,we introduce our proposed multimodal contrastive learning method,which leads to improved performance in sentiment analysis tasks.Our approach is evaluated through extensive experiments on two publicly accessible datasets,where we demonstrate its effectiveness.We achieve a significant improvement in sentiment analysis accuracy,indicating the supe-riority of our approach over existing techniques.These results highlight the potential of multimodal sentiment analysis and underscore the importance of considering the intrinsic semantic connections between modalities for accurate sentiment assessment.展开更多
Sentence classification is the process of categorizing a sentence based on the context of the sentence.Sentence categorization requires more semantic highlights than other tasks,such as dependence parsing,which requir...Sentence classification is the process of categorizing a sentence based on the context of the sentence.Sentence categorization requires more semantic highlights than other tasks,such as dependence parsing,which requires more syntactic elements.Most existing strategies focus on the general semantics of a conversation without involving the context of the sentence,recognizing the progress and comparing impacts.An ensemble pre-trained language model was taken up here to classify the conversation sentences from the conversation corpus.The conversational sentences are classified into four categories:information,question,directive,and commission.These classification label sequences are for analyzing the conversation progress and predicting the pecking order of the conversation.Ensemble of Bidirectional Encoder for Representation of Transformer(BERT),Robustly Optimized BERT pretraining Approach(RoBERTa),Generative Pre-Trained Transformer(GPT),DistilBERT and Generalized Autoregressive Pretraining for Language Understanding(XLNet)models are trained on conversation corpus with hyperparameters.Hyperparameter tuning approach is carried out for better performance on sentence classification.This Ensemble of Pre-trained Language Models with a Hyperparameter Tuning(EPLM-HT)system is trained on an annotated conversation dataset.The proposed approach outperformed compared to the base BERT,GPT,DistilBERT and XLNet transformer models.The proposed ensemble model with the fine-tuned parameters achieved an F1_score of 0.88.展开更多
Task-based language teaching(TBLT)emphasizes the relevance of classroom tasks to real-life scenarios,while focusing on the learner’s personal life experiences as an important resource for classroom learning.This arti...Task-based language teaching(TBLT)emphasizes the relevance of classroom tasks to real-life scenarios,while focusing on the learner’s personal life experiences as an important resource for classroom learning.This article is a teaching experiment based on task-based teaching method,which requires learners to complete a picture story about their daily life.The pictures are taken in real life scenes.Teachers plan to combine different task phases with visual images to closely link the tasks to the learner’s personal life and enhance the authenticity of the task.After the task is completed,the teacher understands the learner’s attitude and evaluation of the whole task through questionnaires,and analyzes the feasibility of the visual image applied to the foreign language classroom,the problems worthy of reflection,and suggestions for improvement.展开更多
Data are limitless. But those are usually not formed or created in our needs. Most of data providers deliver their data in Microsoft Excel spreadsheet, which is compatible with ArcGIS, the most widely used GIS （Geogr...Data are limitless. But those are usually not formed or created in our needs. Most of data providers deliver their data in Microsoft Excel spreadsheet, which is compatible with ArcGIS, the most widely used GIS （Geographic Information System） software in GIS sector. However, those table data contain much unnecessary information that do not need for a certain project. Using the raw data can increase processing times and reduce performance of geoprocessing tools. This study shows steps of how the raw data are being processed using ArcGIS ModelBuilder and Python script.展开更多
Along with the development and progress of the times, the living standard of the people has been gradually improved; when the living standards are improved, there has been also a new aesthetic demand. In terms of fash...Along with the development and progress of the times, the living standard of the people has been gradually improved; when the living standards are improved, there has been also a new aesthetic demand. In terms of fashion design, it is necessary to integrate more emotions into the designing process, so as to give people a better visual sense. The three elements of fashion design are divided into color, shape and material; these three elements contain many visual emotional languages. In this paper, the specific contents were analyzed.展开更多
In this paper, we conduct research on the novel mode of plane graphic design from the core angle of the primary visual language transmitting. Relationship between nationality and cosmopolitan processing in graphic des...In this paper, we conduct research on the novel mode of plane graphic design from the core angle of the primary visual language transmitting. Relationship between nationality and cosmopolitan processing in graphic design in the design of image symbol expression and significance of the symbol on the one hand require symbolic form must have enough openness and the cognitive function on the other hand with semiotics method can let the designer to extract the most representative and symbolic notation style to carry on the design expression. As a non- verbal symbols, from the perspective of the view, the design image is no national boundaries, but the human form to beauty and should express the symbolism of cognition is the same. In the form of the ethnic groups of the cosmopolitan codes are for identification of Chinese contemporary design possible effective methods. Our research proposes novel perspective of the design which is meaningful.展开更多
Visual methods in language teaching have come in very quickly; their introduction has been hastened by the development of the electronic and mechanical means for displaying visual materials. And the learning of langua...Visual methods in language teaching have come in very quickly; their introduction has been hastened by the development of the electronic and mechanical means for displaying visual materials. And the learning of language and the teaching of meaning have been a long-lasting and significant topic in applied linguistics. In this paper several aspects of language teaching including main features of language learning, different ways for teaching of meaning etc. have been discussed. Then, the visual element in language teaching and different kinds of visual materials such as sound film, audio-visual courses, television will be introduced with an application of visual materials in real language class. Then, after the above discussion, the final conclusion will be arrived that the ultimate goal of language teaching is meaning and visual element can be of great importance in the creation of a real situation in language teaching.展开更多
We present an approach to classify medical text at a sentence level automatically.Given the inherent complexity of medical text classification,we employ adapters based on pre-trained language models to extract informa...We present an approach to classify medical text at a sentence level automatically.Given the inherent complexity of medical text classification,we employ adapters based on pre-trained language models to extract information from medical text,facilitating more accurate classification while minimizing the number of trainable parameters.Extensive experiments conducted on various datasets demonstrate the effectiveness of our approach.展开更多
Mental image has often been believed to play a very large, even pivotal, role in both memory and motivation. However, with the lateralization of the brain, the treasure of mental image, a function dominated by the rig...Mental image has often been believed to play a very large, even pivotal, role in both memory and motivation. However, with the lateralization of the brain, the treasure of mental image, a function dominated by the right hemisphere of the brain, is often neglected in the realm of language learning, a function dominated by the left-brain. Thus, educational systems have largely, if not exclusively, catered to the logic, analytical left-brain, and unwisely phase out the imagery elements of the right brain. In this paper, therefore, the author argues that mental image should not be a property confined to children, who have more imagination. This kind of human treasure should be appropriately deployed through the process of language teaching and learning, for it can provide a strong impetus for language learning, thus making language-learning process more enjoyable and beneficial.展开更多
文摘We analyze the suitability of existing pre-trained transformer-based language models(PLMs)for abstractive text summarization on German technical healthcare texts.The study focuses on the multilingual capabilities of these models and their ability to perform the task of abstractive text summarization in the healthcare field.The research hypothesis was that large language models could perform high-quality abstractive text summarization on German technical healthcare texts,even if the model is not specifically trained in that language.Through experiments,the research questions explore the performance of transformer language models in dealing with complex syntax constructs,the difference in performance between models trained in English and German,and the impact of translating the source text to English before conducting the summarization.We conducted an evaluation of four PLMs(GPT-3,a translation-based approach also utilizing GPT-3,a German language Model,and a domain-specific bio-medical model approach).The evaluation considered the informativeness using 3 types of metrics based on Recall-Oriented Understudy for Gisting Evaluation(ROUGE)and the quality of results which is manually evaluated considering 5 aspects.The results show that text summarization models could be used in the German healthcare domain and that domain-independent language models achieved the best results.The study proves that text summarization models can simplify the search for pre-existing German knowledge in various domains.
基金supported by the National Natural Science Foundation of China(No.62376197)the Tianjin Science and Technology Program(No.23JCYBJC00360)the Tianjin Health Research Project(No.TJWJ2025MS045).
文摘Accessible communication based on sign language recognition(SLR)is the key to emergency medical assistance for the hearing-impaired community.Balancing the capture of both local and global information in SLR for emergency medicine poses a significant challenge.To address this,we propose a novel approach based on the inter-learning of visual features between global and local information.Specifically,our method enhances the perception capabilities of the visual feature extractor by strategically leveraging the strengths of convolutional neural network(CNN),which are adept at capturing local features,and visual transformers which perform well at perceiving global features.Furthermore,to mitigate the issue of overfitting caused by the limited availability of sign language data for emergency medical applications,we introduce an enhanced short temporal module for data augmentation through additional subsequences.Experimental results on three publicly available sign language datasets demonstrate the efficacy of the proposed approach.
基金The National Natural Science Foundation of China(No.60571048,60673186,60736015)the National High Technology Researchand Development Program of China(863Program)(No.2007AA01Z178)
文摘Since the specifications of most of the existing context-sensitive graph grammars tend to be either too intricate or not intuitive, a novel context-sensitive graph grammar formalism, called context-attributed graph grammar（CAGG）, is proposed. In order to resolve the embedding problem, context information of a graph production in the CAGG is represented in the form of context attributes of the nodes involved. Moreover, several properties of a set of confluent CAGG productions are characterized, and then an algorithm based on them is developed to decide whether or not a set of productions is confluent, which provides the foundation for the design of efficient parsing algorithms. It can also be shown through the comparison of CAGG with several typical context-sensitive graph grammars that CAGG is more succinct and, at the same time, more intuitive than the others, making it more suitably and effortlessly applicable to the specification of visual languages.
文摘In order to ensure the safety,quality and efficiency of computer numerical control(CNC)machine tool processing,a real-time monitoring and visible solution for CNC machine tools based on hyper text markup language(HTML)5 is proposed.The characteristics of the real-time monitoring technology of CNC machine tools under the traditional Client/Server(C/S)structure are compared and analyzed,and the technical drawbacks are proposed.Web real-time communication technology and browser drawing technology are deeply studied.A real-time monitoring and visible system for CNC machine tool data is developed based on Metro platform,combining WebSocket real-time communication technology and Canvas drawing technology.The system architecture is given,and the functions and implementation methods of the system are described in detail.The practical application results show that the WebSocket real-time communication technology can effectively reduce the bandwidth and network delay and save server resources.The numerical control machine data monitoring system can intuitively reflect the machine data,and the visible effect is good.It realizes timely monitoring of equipment alarms and prompts maintenance and management personnel.
文摘The original intention of visual question answering(VQA)models is to infer the answer based on the relevant information of the question text in the visual image,but many VQA models often yield answers that are biased by some prior knowledge,especially the language priors.This paper proposes a mitigation model called language priors mitigation-VQA(LPM-VQA)for the language priors problem in VQA model,which divides language priors into positive and negative language priors.Different network branches are used to capture and process the different priors to achieve the purpose of mitigating language priors.A dynamically-changing language prior feedback objective function is designed with the intermediate results of some modules in the VQA model.The weight of the loss value for each answer is dynamically set according to the strength of its language priors to balance its proportion in the total VQA loss to further mitigate the language priors.This model does not depend on the baseline VQA architectures and can be configured like a plug-in to improve the performance of the model over most existing VQA models.The experimental results show that the proposed model is general and effective,achieving state-of-the-art accuracy in the VQA-CP v2 dataset.
文摘二语写作是二语习得研究领域的重要组成部分。运用CiteSpace软件对近十年发表在Journal of Second Language Writing的231篇实证研究论文进行可视化分析,研究发现:二语写作研究整体呈波动性上升趋势,研究规模较为稳定,研究关注度逐渐提升;二语写作研究领域暂未形成明显的核心作者和机构的合作网络;研究主题主要聚焦二语写作教学方法的多元化、二语写作反馈的多焦点、二语写作评估与测试的科学化,以及学习者个体差异的多维影响等方面。基于此,提出未来该领域发展需加强学者、机构之间的相互合作;关注个体学习者写作过程的认知特征与情感因素,尤其重视青少年二语学习过程的研究;扩大二语写作纵向研究规模,推动研究的深入发展。
基金supported by the National Natural Science Foundation of China under Grant Nos.62076117 and 62166026the Jiangxi Provincial Key Laboratory of Virtual Reality under Grant No.2024SSY03151.
文摘Dynamic sign language recognition holds significant importance, particularly with the application of deep learning to address its complexity. However, existing methods face several challenges. Firstly, recognizing dynamic sign language requires identifying keyframes that best represent the signs, and missing these keyframes reduces accuracy. Secondly, some methods do not focus enough on hand regions, which are small within the overall frame, leading to information loss. To address these challenges, we propose a novel Video Transformer Attention-based Network (VTAN) for dynamic sign language recognition. Our approach prioritizes informative frames and hand regions effectively. To tackle the first issue, we designed a keyframe extraction module enhanced by a convolutional autoencoder, which focuses on selecting information-rich frames and eliminating redundant ones from the video sequences. For the second issue, we developed a soft attention-based transformer module that emphasizes extracting features from hand regions, ensuring that the network pays more attention to hand information within sequences. This dual-focus approach improves effective dynamic sign language recognition by addressing the key challenges of identifying critical frames and emphasizing hand regions. Experimental results on two public benchmark datasets demonstrate the effectiveness of our network, outperforming most of the typical methods in sign language recognition tasks.
文摘Visual Query Language on Spatial Information (SIVQL) is one kind of visual query language based on the extension of Query by Example (QBE). It is a visual operation based on graphics or media object, such as point, line and area elements. In this paper, the relation calculation and query function of SIVQL have been studied and discussed by using set theory and relation algebra. The theory foundation of SIVQL has been investigated by the mathematical method. Finally, its application examples are also given with the specific information system.
文摘Color language has important meaning for children’s picture books.Understanding children’s preferences in terms of color language will be helpful when designers model computerized picture books in order to adapt to children’s visual senses and effectively stimulate children’s interest in reading.In this study,we aimed to further explore the general characteristics of children’s preference for colors,color depth and color matching forms in picture books.For the study,256 children between the ages of three and six were selected and divided into four groups.According to the implementation needs of the children’s color preference test,these childrenwere asked to complete a series of tasks so that their choices in the tasks could subsequently be analyzed.The tasks included making the following choices:selecting their preferred colors from nine options(red,orange,yellow,green,cyan,blue,purple,black and white);selecting their preferred color brightness fromthree different color shades;and indicating their preferences in relation to complementary colors,matching colors and pure colors.The experimental results showed that children aged between three and six mainly favor red,blue and yellow,and colors with a high degree of brightness.As children grow older,boys tend to prefer blue,and girls tend to prefer pink,with red remaining the favorite color of both genders.As for complementary colors,matching colors and solid colors,three-to six-year-old children prefer solid colors.In conclusion,it seems that color language preferences in children between the ages of three and six are very similar,which could be of use when designing children’s picture books to match their visual vocabulary and psychological cognition.
基金supported by Science and Technology Research Project of Jiangxi Education Department.Project Grant No.GJJ2203306.
文摘Multimodal sentiment analysis is an essential area of research in artificial intelligence that combines multiple modes,such as text and image,to accurately assess sentiment.However,conventional approaches that rely on unimodal pre-trained models for feature extraction from each modality often overlook the intrinsic connections of semantic information between modalities.This limitation is attributed to their training on unimodal data,and necessitates the use of complex fusion mechanisms for sentiment analysis.In this study,we present a novel approach that combines a vision-language pre-trained model with a proposed multimodal contrastive learning method.Our approach harnesses the power of transfer learning by utilizing a vision-language pre-trained model to extract both visual and textual representations in a unified framework.We employ a Transformer architecture to integrate these representations,thereby enabling the capture of rich semantic infor-mation in image-text pairs.To further enhance the representation learning of these pairs,we introduce our proposed multimodal contrastive learning method,which leads to improved performance in sentiment analysis tasks.Our approach is evaluated through extensive experiments on two publicly accessible datasets,where we demonstrate its effectiveness.We achieve a significant improvement in sentiment analysis accuracy,indicating the supe-riority of our approach over existing techniques.These results highlight the potential of multimodal sentiment analysis and underscore the importance of considering the intrinsic semantic connections between modalities for accurate sentiment assessment.
文摘Sentence classification is the process of categorizing a sentence based on the context of the sentence.Sentence categorization requires more semantic highlights than other tasks,such as dependence parsing,which requires more syntactic elements.Most existing strategies focus on the general semantics of a conversation without involving the context of the sentence,recognizing the progress and comparing impacts.An ensemble pre-trained language model was taken up here to classify the conversation sentences from the conversation corpus.The conversational sentences are classified into four categories:information,question,directive,and commission.These classification label sequences are for analyzing the conversation progress and predicting the pecking order of the conversation.Ensemble of Bidirectional Encoder for Representation of Transformer(BERT),Robustly Optimized BERT pretraining Approach(RoBERTa),Generative Pre-Trained Transformer(GPT),DistilBERT and Generalized Autoregressive Pretraining for Language Understanding(XLNet)models are trained on conversation corpus with hyperparameters.Hyperparameter tuning approach is carried out for better performance on sentence classification.This Ensemble of Pre-trained Language Models with a Hyperparameter Tuning(EPLM-HT)system is trained on an annotated conversation dataset.The proposed approach outperformed compared to the base BERT,GPT,DistilBERT and XLNet transformer models.The proposed ensemble model with the fine-tuned parameters achieved an F1_score of 0.88.
文摘Task-based language teaching(TBLT)emphasizes the relevance of classroom tasks to real-life scenarios,while focusing on the learner’s personal life experiences as an important resource for classroom learning.This article is a teaching experiment based on task-based teaching method,which requires learners to complete a picture story about their daily life.The pictures are taken in real life scenes.Teachers plan to combine different task phases with visual images to closely link the tasks to the learner’s personal life and enhance the authenticity of the task.After the task is completed,the teacher understands the learner’s attitude and evaluation of the whole task through questionnaires,and analyzes the feasibility of the visual image applied to the foreign language classroom,the problems worthy of reflection,and suggestions for improvement.
文摘Data are limitless. But those are usually not formed or created in our needs. Most of data providers deliver their data in Microsoft Excel spreadsheet, which is compatible with ArcGIS, the most widely used GIS （Geographic Information System） software in GIS sector. However, those table data contain much unnecessary information that do not need for a certain project. Using the raw data can increase processing times and reduce performance of geoprocessing tools. This study shows steps of how the raw data are being processed using ArcGIS ModelBuilder and Python script.
文摘Along with the development and progress of the times, the living standard of the people has been gradually improved; when the living standards are improved, there has been also a new aesthetic demand. In terms of fashion design, it is necessary to integrate more emotions into the designing process, so as to give people a better visual sense. The three elements of fashion design are divided into color, shape and material; these three elements contain many visual emotional languages. In this paper, the specific contents were analyzed.
文摘In this paper, we conduct research on the novel mode of plane graphic design from the core angle of the primary visual language transmitting. Relationship between nationality and cosmopolitan processing in graphic design in the design of image symbol expression and significance of the symbol on the one hand require symbolic form must have enough openness and the cognitive function on the other hand with semiotics method can let the designer to extract the most representative and symbolic notation style to carry on the design expression. As a non- verbal symbols, from the perspective of the view, the design image is no national boundaries, but the human form to beauty and should express the symbolism of cognition is the same. In the form of the ethnic groups of the cosmopolitan codes are for identification of Chinese contemporary design possible effective methods. Our research proposes novel perspective of the design which is meaningful.
文摘Visual methods in language teaching have come in very quickly; their introduction has been hastened by the development of the electronic and mechanical means for displaying visual materials. And the learning of language and the teaching of meaning have been a long-lasting and significant topic in applied linguistics. In this paper several aspects of language teaching including main features of language learning, different ways for teaching of meaning etc. have been discussed. Then, the visual element in language teaching and different kinds of visual materials such as sound film, audio-visual courses, television will be introduced with an application of visual materials in real language class. Then, after the above discussion, the final conclusion will be arrived that the ultimate goal of language teaching is meaning and visual element can be of great importance in the creation of a real situation in language teaching.
文摘We present an approach to classify medical text at a sentence level automatically.Given the inherent complexity of medical text classification,we employ adapters based on pre-trained language models to extract information from medical text,facilitating more accurate classification while minimizing the number of trainable parameters.Extensive experiments conducted on various datasets demonstrate the effectiveness of our approach.
文摘Mental image has often been believed to play a very large, even pivotal, role in both memory and motivation. However, with the lateralization of the brain, the treasure of mental image, a function dominated by the right hemisphere of the brain, is often neglected in the realm of language learning, a function dominated by the left-brain. Thus, educational systems have largely, if not exclusively, catered to the logic, analytical left-brain, and unwisely phase out the imagery elements of the right brain. In this paper, therefore, the author argues that mental image should not be a property confined to children, who have more imagination. This kind of human treasure should be appropriately deployed through the process of language teaching and learning, for it can provide a strong impetus for language learning, thus making language-learning process more enjoyable and beneficial.
