In this paper it is emphasized that human language has two rather different dimensions corresponding to two different language systems: lexical/semantic and grammatical. These two language systems are supported by dif...In this paper it is emphasized that human language has two rather different dimensions corresponding to two different language systems: lexical/semantic and grammatical. These two language systems are supported by different brain structures (temporal and frontal), and based in different learning strategies (declarative and procedural). In cases of brain pathology, each one can be independently impaired (Wernicke aphasia and Broca aphasia). While the lexical/semantic language system may have appeared during human evolution long before the contemporary man, the grammatical language system probably represents a relatively recent acquisition. Language grammar may be the departing ability for the development of the metacognitive executive functions and is probably based in the ability to internally represent actions.展开更多
This essay elaborates as thoroughly as possible the theory of internal compensation of the natural language system, and proves that the general distinctive function, which vanishes because of the loss or decrease of o...This essay elaborates as thoroughly as possible the theory of internal compensation of the natural language system, and proves that the general distinctive function, which vanishes because of the loss or decrease of one or more sub-systems or units with their distinctive function, will be compensated with the increase of others or something new to guarantee the general balance of the whole system and fulfill the need of communication. By just discussing some phenomena of internal compensation at the phonological level here, this essay reveals some interesting rules and gives new explanations to some phenomena that have not been explained or not explained properly, then prove the theory’s function of explanation.展开更多
Background:Foreign Language Anxiety(FLA)represents a substantial affective barrier that undermines cognitive performance,motivation,and retention in language learners.Emerging evidence highlights mindfulness-based int...Background:Foreign Language Anxiety(FLA)represents a substantial affective barrier that undermines cognitive performance,motivation,and retention in language learners.Emerging evidence highlights mindfulness-based interventions as promising strategies for enhancing emotional regulation and reducing anxiety across educational contexts.This review synthesizes current research on mindfulness as a psychological intervention,aims to evaluate its efficacy in alleviating FLA,and discusses its broader implications for health-focused educational policy and practice.Methods:Following PRISMA guidelines,we systematically reviewed studies examining the relationships between mindfulness and FLA.Our search of four major databases(November 2023)initially identified 346 articles using terms like“mindfulness AND language anxiety.”After screening,14 studies met our criteria:(1)empirical research in English on mindfulness-FLA relationships;(2)no publication date restrictions.Two independent reviewers selected studies,excluding two due to methodological limitations.We conducted a narrative synthesis given the study heterogeneity(9 correlational and 5 intervention studies).Results:9 non-intervention studies demonstrated that mindfulness is negatively associated with FLA,with 3 studies highlighting the mediating roles of self-efficacy and resilience.5 intervention studies reported inconsistent results regarding the efficacy of mindfulness-based interventions in reducing FLA.Conclusions:The findings suggest that while mindfulness holds promise as a tool to address FLA,its mechanisms and effectiveness require further investigation.This study underscores the need for rigorous research,including Randomized Controlled Trials(RCTs),to inform evidence-based integration of mindfulness into foreign language curricula.For educational policymakers and practitioners,these insights highlight the importance of adopting mindfulness interventions cautiously,ensuring they are tailored to students’needs and supported by evidence.展开更多
Anxiety,motivation,and strategy have long been seen as critical in second language acquisition.This study presents a systematic review of the literature on these variables in terms of their relationship with one anoth...Anxiety,motivation,and strategy have long been seen as critical in second language acquisition.This study presents a systematic review of the literature on these variables in terms of their relationship with one another,their effects on learning outcomes,and how they are affected by technology-assisted tools in the teaching of Chinese as a second language.This study includes 24 articles for the review study based on the criteria and process of the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocol(PRISMA-P)and the clustering techniques of VOSviewer.It is found that 1)anxiety,motivation,and strategy were interrelated,that is,motivation was negatively associated with anxiety but positively related to strategy,while strategy could positively predict anxiety;2)anxiety could both positively and negatively affect learning outcomes,while motivation and strategy could both positively and insignificantly influence learning outcomes;3)the technology-assisted tools used in the classroom could both positively and negatively affect the levels of these variables and learning outcomes in the L2 Chinese context.The need to explore more complicated relationships between language-specific individual variables themselves and other possible factors that affect these variables,such as cultural ones,are also discussed for future research.展开更多
Recent advancements in large language models(LLMs)have driven remarkable progress in text process-ing,opening new avenues for medical knowledge discovery.In this study,we present ERQA,a mEdical knowledge Retrieval and...Recent advancements in large language models(LLMs)have driven remarkable progress in text process-ing,opening new avenues for medical knowledge discovery.In this study,we present ERQA,a mEdical knowledge Retrieval and Question-Answering framework powered by an enhanced LLM that integrates a semantic vector database and a curated literature repository.The ERQA framework leverages domain-specific incremental pretraining and conducts supervised fine-tuning on medical literature,enabling retrieval and question-answering(QA)tasks to be completed with high precision.Performance evaluations implemented on the coronavirus disease 2019(COVID-19)and TripClick data-sets demonstrate the robust capabilities of ERQA across multiple tasks.On the COVID-19 dataset,ERQA-13B achieves state-of-the-art retrieval metrics,with normalized discounted cumulative gain at top 10(NDCG@10)0.297,recall values at top 10(Recall@10)0.347,and mean reciprocal rank(MRR)=0.370;it also attains strong abstract summarization performance,with a recall-oriented understudy for gisting evaluation(ROUGE)-1 score of 0.434,and QA performance,with a bilingual evaluation understudy(BLEU)-1 score of 7.851.The comparable performance achieved on the TripClick dataset further under-scores the adaptability of ERQA across diverse medical topics.These findings suggest that ERQA repre-sents a significant step toward efficient biomedical knowledge retrieval and QA.展开更多
Objective:Generative artificial intelligence(AI)technology,represented by large language models(LLMs),has gradually been developed for traditional Chinese medicine(TCM);however,challenges remain in effectively enhanci...Objective:Generative artificial intelligence(AI)technology,represented by large language models(LLMs),has gradually been developed for traditional Chinese medicine(TCM);however,challenges remain in effectively enhancing AI applications for TCM.Therefore,this study is the first systematic review to analyze LLMs in TCM retrospectively,focusing on and summarizing the evidence of their performance in generative tasks.Methods:We extensively searched electronic databases for articles published until June 2024 to identify publicly available studies on LLMs in TCM.Two investigators independently selected and extracted the related information and evaluation metrics.Based on the available data,this study used descriptive analysis for a comprehensive systematic review of LLM technology related to TCM.Results:Ten studies published between 2023 and 2024 met our eligibility criteria and were included in this review,including 40%LLMs in the TCM vertical domain,40%containing TCM data,and 20%honoring the TCM contribution,with a foundational model parameter range from 1.8 to 33 billion.All included studies used manual or automatic evaluation metrics to evaluate model performance and fully discussed the challenges and contributions through an overview of LLMs in TCM.Conclusions:LLMs have achieved significant advantages in TCM applications and can effectively address intelligent TCM tasks.Further in-depth development of LLMs is needed in various vertical TCM fields,including clinical and fundamental research.Focusing on the functional segmentation development direction of generative AI technologies in TCM application scenarios to meet the practical needs-oriented demands of TCM digitalization is essential.展开更多
In the era of big data,data-driven technologies are increasingly leveraged by industry to facilitate autonomous learning and intelligent decision-making.However,the challenge of“small samples in big data”emerges whe...In the era of big data,data-driven technologies are increasingly leveraged by industry to facilitate autonomous learning and intelligent decision-making.However,the challenge of“small samples in big data”emerges when datasets lack the comprehensive information necessary for addressing complex scenarios,which hampers adaptability.Thus,enhancing data completeness is essential.Knowledge-guided virtual sample generation transforms domain knowledge into extensive virtual datasets,thereby reducing dependence on limited real samples and enabling zero-sample fault diagnosis.This study used building air conditioning systems as a case study.We innovatively used the large language model(LLM)to acquire domain knowledge for sample generation,significantly lowering knowledge acquisition costs and establishing a generalized framework for knowledge acquisition in engineering applications.This acquired knowledge guided the design of diffusion boundaries in mega-trend diffusion(MTD),while the Monte Carlo method was used to sample within the diffusion function to create information-rich virtual samples.Additionally,a noise-adding technique was introduced to enhance the information entropy of these samples,thereby improving the robustness of neural networks trained with them.Experimental results showed that training the diagnostic model exclusively with virtual samples achieved an accuracy of 72.80%,significantly surpassing traditional small-sample supervised learning in terms of generalization.This underscores the quality and completeness of the generated virtual samples.展开更多
Mirror neuron system （MNS） represents one past decade, and it has been found to involve in multiple of the most important discoveries of cognitive neuroscience in the aspects of brain functions including action unde...Mirror neuron system （MNS） represents one past decade, and it has been found to involve in multiple of the most important discoveries of cognitive neuroscience in the aspects of brain functions including action understanding, imitation, language understanding, empathy, action prediction and speech evolution. This manuscript reviewed the function of MNS in action understanding as well as language evolution, and specifically assessed its roles as the bridge from body language to fluent speeches. Then we discussed the speech defects of autism patients due to the disruption of MNS. Finally, given that MNS is plastic in adult brain, we proposed MNS targeted therapy provides an efficient rehabilitation approach for brain damages conditions as well as autism patients.展开更多
A new concept of language field and its value structure are presented in this paper for the first time and a describing framework is set forth for researching computational model of reasoning. On this basis we have es...A new concept of language field and its value structure are presented in this paper for the first time and a describing framework is set forth for researching computational model of reasoning. On this basis we have established a model of qualitative reasoning of causal relations and fuzzy integrated algorithm. Furthermore we have found a lot of its applications.展开更多
With direct expression of individual application domain patterns and ideas,domain-specific modeling language（DSML） is more and more frequently used to build models instead of using a combination of one or more gener...With direct expression of individual application domain patterns and ideas,domain-specific modeling language（DSML） is more and more frequently used to build models instead of using a combination of one or more general constructs.Based on the profile mechanism of unified modeling language（UML） 2.2,a kind of DSML is presented to model simulation testing systems of avionic software（STSAS）.To define the syntax,semantics and notions of the DSML,the domain model of the STSAS from which we generalize the domain concepts and relationships among these concepts is given,and then,the domain model is mapped into a UML meta-model,named UML-STSAS profile.Assuming a flight control system（FCS） as system under test（SUT）,we design the relevant STSAS.The results indicate that extending UML to the simulation testing domain can effectively and precisely model STSAS.展开更多
The recent developments in Multimedia Internet of Things(MIoT)devices,empowered with Natural Language Processing(NLP)model,seem to be a promising future of smart devices.It plays an important role in industrial models...The recent developments in Multimedia Internet of Things(MIoT)devices,empowered with Natural Language Processing(NLP)model,seem to be a promising future of smart devices.It plays an important role in industrial models such as speech understanding,emotion detection,home automation,and so on.If an image needs to be captioned,then the objects in that image,its actions and connections,and any silent feature that remains under-projected or missing from the images should be identified.The aim of the image captioning process is to generate a caption for image.In next step,the image should be provided with one of the most significant and detailed descriptions that is syntactically as well as semantically correct.In this scenario,computer vision model is used to identify the objects and NLP approaches are followed to describe the image.The current study develops aNatural Language Processing with Optimal Deep Learning Enabled Intelligent Image Captioning System(NLPODL-IICS).The aim of the presented NLPODL-IICS model is to produce a proper description for input image.To attain this,the proposed NLPODL-IICS follows two stages such as encoding and decoding processes.Initially,at the encoding side,the proposed NLPODL-IICS model makes use of Hunger Games Search(HGS)with Neural Search Architecture Network(NASNet)model.This model represents the input data appropriately by inserting it into a predefined length vector.Besides,during decoding phase,Chimp Optimization Algorithm(COA)with deeper Long Short Term Memory(LSTM)approach is followed to concatenate the description sentences 4436 CMC,2023,vol.74,no.2 produced by the method.The application of HGS and COA algorithms helps in accomplishing proper parameter tuning for NASNet and LSTM models respectively.The proposed NLPODL-IICS model was experimentally validated with the help of two benchmark datasets.Awidespread comparative analysis confirmed the superior performance of NLPODL-IICS model over other models.展开更多
A well-recognized fact is that addressing the impacts of climate change on vulnerable communities and minority groups remains a central focus toward achieving the Sustainable Development Goals,specifically Goals 11 an...A well-recognized fact is that addressing the impacts of climate change on vulnerable communities and minority groups remains a central focus toward achieving the Sustainable Development Goals,specifically Goals 11 and 13.Approaches for effective adaptation to climate change through national and local efforts fundamentally aim to create environmentally sustainable,socially inclusive,and economically vibrant communities.This paper associates the impacts of climate change to the preservation of threatened minority languages in semi-arid areas in Northern Ghana.This review relies on primary and secondary sources on climate-induced migration,minority languages,and threats of language loss through a keyword search followed by rigorous content analysis.The study confirms that forced displacement due to harsh climatic and other environmental conditions is currently occurring in the upper regions(Upper East and Upper West Regions)of Ghana with minority linguistic groups being forced to migrate to the southern part of the country,where their culture and language are threatened due to large linguistic groups.The literature well establishes the north-south mobility with various debates on its root causes.However,the phenomenon is understudied along with the lack of specific national strategies for addressing it and the associated language loss.Therefore,the need emerges for further studies to enhance the current understanding of the phenomenon to inform policy interventions and protect minority languages threatened by climate-induced migration.The focus on an understudied subject and geographic scope makes the findings extremely relevant for the expansion of knowledge on internal migration in the context of climate change in Northern Ghana.展开更多
Numeral systems in natural languages show astonishing variety,though with very strong unifying tendencies that are increasing as many indigenous numeral systems disappear through language contact and globalization.Mos...Numeral systems in natural languages show astonishing variety,though with very strong unifying tendencies that are increasing as many indigenous numeral systems disappear through language contact and globalization.Most numeral systems make use of a base,typically 10,less commonly 20,followed by a wide range of other possibilities.Higher numerals are formed from primitive lower numerals by applying the processes of addition and multiplication,in many languages also exponentiation;sometimes,however,numerals are formed from a higher numeral,using subtraction or division.Numerous complexities and idiosyncrasies are discussed,as are numeral systems that fall outside this general characterization,such as restricted numeral systems with no internal arithmetic structure,and some New Guinea extended body-part counting systems.展开更多
In this research paper, we research on the automatic pattern abstraction and recognition method for large-scale database system based on natural language processing. In distributed database, through the network connec...In this research paper, we research on the automatic pattern abstraction and recognition method for large-scale database system based on natural language processing. In distributed database, through the network connection between nodes, data across different nodes and even regional distribution are well recognized. In order to reduce data redundancy and model design of the database will usually contain a lot of forms we combine the NLP theory to optimize the traditional method. The experimental analysis and simulation proves the correctness of our method.展开更多
According to the development of linguistics and language teaching,it can be inferred that various linguistic theories have played a significance role in language teaching.Considering the demands of society on the lang...According to the development of linguistics and language teaching,it can be inferred that various linguistic theories have played a significance role in language teaching.Considering the demands of society on the language teaching,it seems that Systematic-Functional(SF) Grammar benefits more in today's language teaching.In this paper,the four core ideas of system,multi-levels,functions,and context and their inspirations on language teaching are talked about.展开更多
Systemic-functional linguistics is one of the most influential linguistics schools in the recent 20 years.Though M.A.K.Halliday,the founder of Systemic-functional Linguistics,has not taken up any language teaching res...Systemic-functional linguistics is one of the most influential linguistics schools in the recent 20 years.Though M.A.K.Halliday,the founder of Systemic-functional Linguistics,has not taken up any language teaching research by himself,he has been putting great emphasis on language teaching and language learning.With the increasing influence of Systemic-functional Linguistics,more and more applied linguists and foreign language teachers are trying to use his theories to solve the problems in language teaching and learning,and have achieved a lot.展开更多
This study conducts a systematic literature review to investigate Language MOOC(LMOOC),a newly-emerged research field,and aims to explore two aspects of LMOOC:the effectiveness of LMOOCs and factors influencing langua...This study conducts a systematic literature review to investigate Language MOOC(LMOOC),a newly-emerged research field,and aims to explore two aspects of LMOOC:the effectiveness of LMOOCs and factors influencing language learning in LMOOCs.This study reviews 24 empirical studies from the Web of Science.After analyzing and integrating research findings,this paper mainly draws two conclusions:(1)as for the learning outcomes,LMOOCs can improve learners’overall language proficiency,oral competence,vocabulary knowledge,and capability to apply the learned knowledge to an unknown situation;besides,the fact that most learners take a positive attitude towards LMOOC also demonstrates the excellent learning outcomes of LMOOC;(2)to facilitate and prevent the language learning in LMOOC,five factors should be considered:participants’autonomy,course organization,intrinsic motivation and external conditions of participants,cultural and contextual support of course content,language and technological ability.The research design and implications of LMOOCs are also discussed in this study.展开更多
The existing data mining methods are mostly focused on relational databases and structured data, but not on complex structured data (like in extensible markup language(XML)). By converting XML document type descriptio...The existing data mining methods are mostly focused on relational databases and structured data, but not on complex structured data (like in extensible markup language(XML)). By converting XML document type description to the relational semantic recording XML data relations, and using an XML data mining language, the XML data mining system presents a strategy to mine information on XML.展开更多
The expert system is an important field of the artificial intelligence. The traditional interface of the expert system is the command, menu and window at present. It limits the application of the expert system and emb...The expert system is an important field of the artificial intelligence. The traditional interface of the expert system is the command, menu and window at present. It limits the application of the expert system and embarrasses the enthusiasm of using expert system. Combining with the study on the expert system of network fault diagnosis, the natural language interface of the expert system has been discussed in this article. This interface can understand and generate Chinese sentences. Using this interface, the user and field experts can use the expert system to diagnose the fault of network conveniently. In the article, first, the extended production rule has been proposed. Then the methods of Chinese sentence generation from conceptual graphs and the model of expert system are introduced in detail. Using this model, the network fault diagnosis expert system and its natural language interface have been developed with Prolog.展开更多
文摘In this paper it is emphasized that human language has two rather different dimensions corresponding to two different language systems: lexical/semantic and grammatical. These two language systems are supported by different brain structures (temporal and frontal), and based in different learning strategies (declarative and procedural). In cases of brain pathology, each one can be independently impaired (Wernicke aphasia and Broca aphasia). While the lexical/semantic language system may have appeared during human evolution long before the contemporary man, the grammatical language system probably represents a relatively recent acquisition. Language grammar may be the departing ability for the development of the metacognitive executive functions and is probably based in the ability to internally represent actions.
文摘This essay elaborates as thoroughly as possible the theory of internal compensation of the natural language system, and proves that the general distinctive function, which vanishes because of the loss or decrease of one or more sub-systems or units with their distinctive function, will be compensated with the increase of others or something new to guarantee the general balance of the whole system and fulfill the need of communication. By just discussing some phenomena of internal compensation at the phonological level here, this essay reveals some interesting rules and gives new explanations to some phenomena that have not been explained or not explained properly, then prove the theory’s function of explanation.
文摘Background:Foreign Language Anxiety(FLA)represents a substantial affective barrier that undermines cognitive performance,motivation,and retention in language learners.Emerging evidence highlights mindfulness-based interventions as promising strategies for enhancing emotional regulation and reducing anxiety across educational contexts.This review synthesizes current research on mindfulness as a psychological intervention,aims to evaluate its efficacy in alleviating FLA,and discusses its broader implications for health-focused educational policy and practice.Methods:Following PRISMA guidelines,we systematically reviewed studies examining the relationships between mindfulness and FLA.Our search of four major databases(November 2023)initially identified 346 articles using terms like“mindfulness AND language anxiety.”After screening,14 studies met our criteria:(1)empirical research in English on mindfulness-FLA relationships;(2)no publication date restrictions.Two independent reviewers selected studies,excluding two due to methodological limitations.We conducted a narrative synthesis given the study heterogeneity(9 correlational and 5 intervention studies).Results:9 non-intervention studies demonstrated that mindfulness is negatively associated with FLA,with 3 studies highlighting the mediating roles of self-efficacy and resilience.5 intervention studies reported inconsistent results regarding the efficacy of mindfulness-based interventions in reducing FLA.Conclusions:The findings suggest that while mindfulness holds promise as a tool to address FLA,its mechanisms and effectiveness require further investigation.This study underscores the need for rigorous research,including Randomized Controlled Trials(RCTs),to inform evidence-based integration of mindfulness into foreign language curricula.For educational policymakers and practitioners,these insights highlight the importance of adopting mindfulness interventions cautiously,ensuring they are tailored to students’needs and supported by evidence.
文摘Anxiety,motivation,and strategy have long been seen as critical in second language acquisition.This study presents a systematic review of the literature on these variables in terms of their relationship with one another,their effects on learning outcomes,and how they are affected by technology-assisted tools in the teaching of Chinese as a second language.This study includes 24 articles for the review study based on the criteria and process of the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocol(PRISMA-P)and the clustering techniques of VOSviewer.It is found that 1)anxiety,motivation,and strategy were interrelated,that is,motivation was negatively associated with anxiety but positively related to strategy,while strategy could positively predict anxiety;2)anxiety could both positively and negatively affect learning outcomes,while motivation and strategy could both positively and insignificantly influence learning outcomes;3)the technology-assisted tools used in the classroom could both positively and negatively affect the levels of these variables and learning outcomes in the L2 Chinese context.The need to explore more complicated relationships between language-specific individual variables themselves and other possible factors that affect these variables,such as cultural ones,are also discussed for future research.
基金supported by the Innovation Fund for Medical Sciences of the Chinese Academy of Medical Sciences(2021-I2M-1-033)the National Key Research and Development Program of China(2022YFF0711900).
文摘Recent advancements in large language models(LLMs)have driven remarkable progress in text process-ing,opening new avenues for medical knowledge discovery.In this study,we present ERQA,a mEdical knowledge Retrieval and Question-Answering framework powered by an enhanced LLM that integrates a semantic vector database and a curated literature repository.The ERQA framework leverages domain-specific incremental pretraining and conducts supervised fine-tuning on medical literature,enabling retrieval and question-answering(QA)tasks to be completed with high precision.Performance evaluations implemented on the coronavirus disease 2019(COVID-19)and TripClick data-sets demonstrate the robust capabilities of ERQA across multiple tasks.On the COVID-19 dataset,ERQA-13B achieves state-of-the-art retrieval metrics,with normalized discounted cumulative gain at top 10(NDCG@10)0.297,recall values at top 10(Recall@10)0.347,and mean reciprocal rank(MRR)=0.370;it also attains strong abstract summarization performance,with a recall-oriented understudy for gisting evaluation(ROUGE)-1 score of 0.434,and QA performance,with a bilingual evaluation understudy(BLEU)-1 score of 7.851.The comparable performance achieved on the TripClick dataset further under-scores the adaptability of ERQA across diverse medical topics.These findings suggest that ERQA repre-sents a significant step toward efficient biomedical knowledge retrieval and QA.
基金supported by the National Multidisciplinary Innovation Team of Traditional Chinese Medicine(ZYYCXTD-D-202204)China Postdoctoral Science Foundation(2023M742627)+1 种基金Postdoctoral Fellowship Program of CPSF(GZC20231928)Foundation of State Key Laboratory of Component-based Chinese Medicine(CBCM2023201).
文摘Objective:Generative artificial intelligence(AI)technology,represented by large language models(LLMs),has gradually been developed for traditional Chinese medicine(TCM);however,challenges remain in effectively enhancing AI applications for TCM.Therefore,this study is the first systematic review to analyze LLMs in TCM retrospectively,focusing on and summarizing the evidence of their performance in generative tasks.Methods:We extensively searched electronic databases for articles published until June 2024 to identify publicly available studies on LLMs in TCM.Two investigators independently selected and extracted the related information and evaluation metrics.Based on the available data,this study used descriptive analysis for a comprehensive systematic review of LLM technology related to TCM.Results:Ten studies published between 2023 and 2024 met our eligibility criteria and were included in this review,including 40%LLMs in the TCM vertical domain,40%containing TCM data,and 20%honoring the TCM contribution,with a foundational model parameter range from 1.8 to 33 billion.All included studies used manual or automatic evaluation metrics to evaluate model performance and fully discussed the challenges and contributions through an overview of LLMs in TCM.Conclusions:LLMs have achieved significant advantages in TCM applications and can effectively address intelligent TCM tasks.Further in-depth development of LLMs is needed in various vertical TCM fields,including clinical and fundamental research.Focusing on the functional segmentation development direction of generative AI technologies in TCM application scenarios to meet the practical needs-oriented demands of TCM digitalization is essential.
基金supported by the National Natural Science Foundation of China(No.62306281)the Natural Science Foundation of Zhejiang Province(Nos.LQ23E060006 and LTGG24E050005)the Key Research Plan of Jiaxing City(No.2024BZ20016).
文摘In the era of big data,data-driven technologies are increasingly leveraged by industry to facilitate autonomous learning and intelligent decision-making.However,the challenge of“small samples in big data”emerges when datasets lack the comprehensive information necessary for addressing complex scenarios,which hampers adaptability.Thus,enhancing data completeness is essential.Knowledge-guided virtual sample generation transforms domain knowledge into extensive virtual datasets,thereby reducing dependence on limited real samples and enabling zero-sample fault diagnosis.This study used building air conditioning systems as a case study.We innovatively used the large language model(LLM)to acquire domain knowledge for sample generation,significantly lowering knowledge acquisition costs and establishing a generalized framework for knowledge acquisition in engineering applications.This acquired knowledge guided the design of diffusion boundaries in mega-trend diffusion(MTD),while the Monte Carlo method was used to sample within the diffusion function to create information-rich virtual samples.Additionally,a noise-adding technique was introduced to enhance the information entropy of these samples,thereby improving the robustness of neural networks trained with them.Experimental results showed that training the diagnostic model exclusively with virtual samples achieved an accuracy of 72.80%,significantly surpassing traditional small-sample supervised learning in terms of generalization.This underscores the quality and completeness of the generated virtual samples.
基金Sci-ence Foundation of Ministry of Education of China (No.FBB011469)
文摘Mirror neuron system （MNS） represents one past decade, and it has been found to involve in multiple of the most important discoveries of cognitive neuroscience in the aspects of brain functions including action understanding, imitation, language understanding, empathy, action prediction and speech evolution. This manuscript reviewed the function of MNS in action understanding as well as language evolution, and specifically assessed its roles as the bridge from body language to fluent speeches. Then we discussed the speech defects of autism patients due to the disruption of MNS. Finally, given that MNS is plastic in adult brain, we proposed MNS targeted therapy provides an efficient rehabilitation approach for brain damages conditions as well as autism patients.
文摘A new concept of language field and its value structure are presented in this paper for the first time and a describing framework is set forth for researching computational model of reasoning. On this basis we have established a model of qualitative reasoning of causal relations and fuzzy integrated algorithm. Furthermore we have found a lot of its applications.
基金Aeronautical Science Foundation of China (20095551025)
文摘With direct expression of individual application domain patterns and ideas,domain-specific modeling language（DSML） is more and more frequently used to build models instead of using a combination of one or more general constructs.Based on the profile mechanism of unified modeling language（UML） 2.2,a kind of DSML is presented to model simulation testing systems of avionic software（STSAS）.To define the syntax,semantics and notions of the DSML,the domain model of the STSAS from which we generalize the domain concepts and relationships among these concepts is given,and then,the domain model is mapped into a UML meta-model,named UML-STSAS profile.Assuming a flight control system（FCS） as system under test（SUT）,we design the relevant STSAS.The results indicate that extending UML to the simulation testing domain can effectively and precisely model STSAS.
基金Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2022R161)PrincessNourah bint Abdulrahman University,Riyadh,Saudi Arabia.The authors would like to thank the|Deanship of Scientific Research at Umm Al-Qura University|for supporting this work by Grant Code:(22UQU4310373DSR33).
文摘The recent developments in Multimedia Internet of Things(MIoT)devices,empowered with Natural Language Processing(NLP)model,seem to be a promising future of smart devices.It plays an important role in industrial models such as speech understanding,emotion detection,home automation,and so on.If an image needs to be captioned,then the objects in that image,its actions and connections,and any silent feature that remains under-projected or missing from the images should be identified.The aim of the image captioning process is to generate a caption for image.In next step,the image should be provided with one of the most significant and detailed descriptions that is syntactically as well as semantically correct.In this scenario,computer vision model is used to identify the objects and NLP approaches are followed to describe the image.The current study develops aNatural Language Processing with Optimal Deep Learning Enabled Intelligent Image Captioning System(NLPODL-IICS).The aim of the presented NLPODL-IICS model is to produce a proper description for input image.To attain this,the proposed NLPODL-IICS follows two stages such as encoding and decoding processes.Initially,at the encoding side,the proposed NLPODL-IICS model makes use of Hunger Games Search(HGS)with Neural Search Architecture Network(NASNet)model.This model represents the input data appropriately by inserting it into a predefined length vector.Besides,during decoding phase,Chimp Optimization Algorithm(COA)with deeper Long Short Term Memory(LSTM)approach is followed to concatenate the description sentences 4436 CMC,2023,vol.74,no.2 produced by the method.The application of HGS and COA algorithms helps in accomplishing proper parameter tuning for NASNet and LSTM models respectively.The proposed NLPODL-IICS model was experimentally validated with the help of two benchmark datasets.Awidespread comparative analysis confirmed the superior performance of NLPODL-IICS model over other models.
文摘A well-recognized fact is that addressing the impacts of climate change on vulnerable communities and minority groups remains a central focus toward achieving the Sustainable Development Goals,specifically Goals 11 and 13.Approaches for effective adaptation to climate change through national and local efforts fundamentally aim to create environmentally sustainable,socially inclusive,and economically vibrant communities.This paper associates the impacts of climate change to the preservation of threatened minority languages in semi-arid areas in Northern Ghana.This review relies on primary and secondary sources on climate-induced migration,minority languages,and threats of language loss through a keyword search followed by rigorous content analysis.The study confirms that forced displacement due to harsh climatic and other environmental conditions is currently occurring in the upper regions(Upper East and Upper West Regions)of Ghana with minority linguistic groups being forced to migrate to the southern part of the country,where their culture and language are threatened due to large linguistic groups.The literature well establishes the north-south mobility with various debates on its root causes.However,the phenomenon is understudied along with the lack of specific national strategies for addressing it and the associated language loss.Therefore,the need emerges for further studies to enhance the current understanding of the phenomenon to inform policy interventions and protect minority languages threatened by climate-induced migration.The focus on an understudied subject and geographic scope makes the findings extremely relevant for the expansion of knowledge on internal migration in the context of climate change in Northern Ghana.
文摘Numeral systems in natural languages show astonishing variety,though with very strong unifying tendencies that are increasing as many indigenous numeral systems disappear through language contact and globalization.Most numeral systems make use of a base,typically 10,less commonly 20,followed by a wide range of other possibilities.Higher numerals are formed from primitive lower numerals by applying the processes of addition and multiplication,in many languages also exponentiation;sometimes,however,numerals are formed from a higher numeral,using subtraction or division.Numerous complexities and idiosyncrasies are discussed,as are numeral systems that fall outside this general characterization,such as restricted numeral systems with no internal arithmetic structure,and some New Guinea extended body-part counting systems.
文摘In this research paper, we research on the automatic pattern abstraction and recognition method for large-scale database system based on natural language processing. In distributed database, through the network connection between nodes, data across different nodes and even regional distribution are well recognized. In order to reduce data redundancy and model design of the database will usually contain a lot of forms we combine the NLP theory to optimize the traditional method. The experimental analysis and simulation proves the correctness of our method.
文摘According to the development of linguistics and language teaching,it can be inferred that various linguistic theories have played a significance role in language teaching.Considering the demands of society on the language teaching,it seems that Systematic-Functional(SF) Grammar benefits more in today's language teaching.In this paper,the four core ideas of system,multi-levels,functions,and context and their inspirations on language teaching are talked about.
文摘Systemic-functional linguistics is one of the most influential linguistics schools in the recent 20 years.Though M.A.K.Halliday,the founder of Systemic-functional Linguistics,has not taken up any language teaching research by himself,he has been putting great emphasis on language teaching and language learning.With the increasing influence of Systemic-functional Linguistics,more and more applied linguists and foreign language teachers are trying to use his theories to solve the problems in language teaching and learning,and have achieved a lot.
文摘This study conducts a systematic literature review to investigate Language MOOC(LMOOC),a newly-emerged research field,and aims to explore two aspects of LMOOC:the effectiveness of LMOOCs and factors influencing language learning in LMOOCs.This study reviews 24 empirical studies from the Web of Science.After analyzing and integrating research findings,this paper mainly draws two conclusions:(1)as for the learning outcomes,LMOOCs can improve learners’overall language proficiency,oral competence,vocabulary knowledge,and capability to apply the learned knowledge to an unknown situation;besides,the fact that most learners take a positive attitude towards LMOOC also demonstrates the excellent learning outcomes of LMOOC;(2)to facilitate and prevent the language learning in LMOOC,five factors should be considered:participants’autonomy,course organization,intrinsic motivation and external conditions of participants,cultural and contextual support of course content,language and technological ability.The research design and implications of LMOOCs are also discussed in this study.
文摘The existing data mining methods are mostly focused on relational databases and structured data, but not on complex structured data (like in extensible markup language(XML)). By converting XML document type description to the relational semantic recording XML data relations, and using an XML data mining language, the XML data mining system presents a strategy to mine information on XML.
基金This work was supported by the National Natural Science Foundation of China (No.60173066) .
文摘The expert system is an important field of the artificial intelligence. The traditional interface of the expert system is the command, menu and window at present. It limits the application of the expert system and embarrasses the enthusiasm of using expert system. Combining with the study on the expert system of network fault diagnosis, the natural language interface of the expert system has been discussed in this article. This interface can understand and generate Chinese sentences. Using this interface, the user and field experts can use the expert system to diagnose the fault of network conveniently. In the article, first, the extended production rule has been proposed. Then the methods of Chinese sentence generation from conceptual graphs and the model of expert system are introduced in detail. Using this model, the network fault diagnosis expert system and its natural language interface have been developed with Prolog.
