This article reviews the psychological and neuroscience achievements in concept learning since 2010 from the perspectives of individual learning and social learning,and discusses several issues related to concept lear...This article reviews the psychological and neuroscience achievements in concept learning since 2010 from the perspectives of individual learning and social learning,and discusses several issues related to concept learning,including the assistance of machine learning about concept learning.In terms of individual learning,current evidence shows that the brain tends to process concrete concepts through typical features(shared features);and for abstract concepts,semantic processing is the most important cognitive way.In terms of social learning,interpersonal neural synchrony(INS)is considered the main indicator of efficient knowledge transfer(such as teaching activities between teachers and students),but this phenomenon only broadens the channels for concept sources and does not change the basic mode of individual concept learning.Ultimately,this article argues that the way the human brain processes concepts depends on the concept’s own characteristics,so there are no“better”strategies in teaching,only more“suitable”strategies.展开更多
The rhetorical structure of abstracts has been a widely discussed topic, as it can greatly enhance the abstract writing skills of second-language writers. This study aims to provide guidance on the syntactic features ...The rhetorical structure of abstracts has been a widely discussed topic, as it can greatly enhance the abstract writing skills of second-language writers. This study aims to provide guidance on the syntactic features that L2 learners can employ, as well as suggest which features they should focus on in English academic writing. To achieve this, all samples were analyzed for rhetorical moves using Hyland’s five-rhetorical move model. Additionally, all sentences were evaluated for syntactic complexity, considering measures such as global, clausal and phrasal complexity. The findings reveal that expert writers exhibit a more balanced use of syntactic complexity across moves, effectively fulfilling the rhetorical objectives of abstracts. On the other hand, MA students tend to rely excessively on embedded structures and dependent clauses in an attempt to increase complexity. The implications of these findings for academic writing research, pedagogy, and assessment are thoroughly discussed.展开更多
The existing abstractive text summarisation models only consider the word sequence correlations between the source document and the reference summary,and the summary generated by models lacks the cover of the subject ...The existing abstractive text summarisation models only consider the word sequence correlations between the source document and the reference summary,and the summary generated by models lacks the cover of the subject of source document due to models'small perspective.In order to make up these disadvantages,a multi‐domain attention pointer(MDA‐Pointer)abstractive summarisation model is proposed in this work.First,the model uses bidirectional long short‐term memory to encode,respectively,the word and sentence sequence of source document for obtaining the semantic representations at word and sentence level.Furthermore,the multi‐domain attention mechanism between the semantic representations and the summary word is established,and the proposed model can generate summary words under the proposed attention mechanism based on the words and sen-tences.Then,the words are extracted from the vocabulary or the original word sequences through the pointer network to form the summary,and the coverage mechanism is introduced,respectively,into word and sentence level to reduce the redundancy of sum-mary content.Finally,experiment validation is conducted on CNN/Daily Mail dataset.ROUGE evaluation indexes of the model without and with the coverage mechanism are improved respectively,and the results verify the validation of model proposed by this paper.展开更多
Transactions of Nanjing University of Aeronautics&Astronautics(TNUAA)is a bimonthly journal facing international academic community.Emphasizing prompt and effective dissemination of key data and new scientific ins...Transactions of Nanjing University of Aeronautics&Astronautics(TNUAA)is a bimonthly journal facing international academic community.Emphasizing prompt and effective dissemination of key data and new scientific insights,TNUAA publishes experimental and theoretical papers bearing on applications to all branches of aeronautics,astronautics and civil aviation.TNUAA is currently indexed by Engineering Index(Ei Compendex,USA),Scopus(Sco,Holland),Chemical Abstracts(CA,USA),P.Ж.(Russia),EBSCO(USA),SA(England),Zbl(Germany),Cambridge Scientific Abstracts(CSA),Chinese Science Citation Database(CSCD,China),National Knowledge Infrastructure(CNKI,China)and Chinese S&T Journal Citation Reports(China).展开更多
A large variety of complaint reports reflect subjective information expressed by citizens.A key challenge of text summarization for complaint reports is to ensure the factual consistency of generated summary.Therefore...A large variety of complaint reports reflect subjective information expressed by citizens.A key challenge of text summarization for complaint reports is to ensure the factual consistency of generated summary.Therefore,in this paper,a simple and weakly supervised framework considering factual consistency is proposed to generate a summary of city-based complaint reports without pre-labeled sentences/words.Furthermore,it considers the importance of entity in complaint reports to ensure factual consistency of summary.Experimental results on the customer review datasets(Yelp and Amazon)and complaint report dataset(complaint reports of Shenyang in China)show that the proposed framework outperforms state-of-the-art approaches in ROUGE scores and human evaluation.It unveils the effectiveness of our approach to helping in dealing with complaint reports.展开更多
The existing software bug localization models treat the source file as natural language, which leads to the loss of syntactical and structure information of the source file. A bug localization model based on syntactic...The existing software bug localization models treat the source file as natural language, which leads to the loss of syntactical and structure information of the source file. A bug localization model based on syntactical and semantic information of source code is proposed. Firstly, abstract syntax tree(AST) is divided based on node category to obtain statement sequence. The statement tree is encoded into vectors to capture lexical and syntactical knowledge at the statement level.Secondly, the source code is transformed into vector representation by the sequence naturalness of the statement. Therefore,the problem of gradient vanishing and explosion caused by a large AST size is obviated when using AST to the represent source code. Finally, the correlation between bug reports and source files are comprehensively analyzed from three aspects of syntax, semantics and text to locate the buggy code. Experiments show that compared with other standard models, the proposed model improves the performance of bug localization, and it has good advantages in mean reciprocal rank(MRR), mean average precision(MAP) and Top N Rank.展开更多
With the continuous growth of online news articles,there arises the necessity for an efficient abstractive summarization technique for the problem of information overloading.Abstractive summarization is highly complex...With the continuous growth of online news articles,there arises the necessity for an efficient abstractive summarization technique for the problem of information overloading.Abstractive summarization is highly complex and requires a deeper understanding and proper reasoning to come up with its own summary outline.Abstractive summarization task is framed as seq2seq modeling.Existing seq2seq methods perform better on short sequences;however,for long sequences,the performance degrades due to high computation and hence a two-phase self-normalized deep neural document summarization model consisting of improvised extractive cosine normalization and seq2seq abstractive phases has been proposed in this paper.The novelty is to parallelize the sequence computation training by incorporating feed-forward,the self-normalized neural network in the Extractive phase using Intra Cosine Attention Similarity(Ext-ICAS)with sentence dependency position.Also,it does not require any normalization technique explicitly.Our proposed abstractive Bidirectional Long Short Term Memory(Bi-LSTM)encoder sequence model performs better than the Bidirectional Gated Recurrent Unit(Bi-GRU)encoder with minimum training loss and with fast convergence.The proposed model was evaluated on the Cable News Network(CNN)/Daily Mail dataset and an average rouge score of 0.435 was achieved also computational training in the extractive phase was reduced by 59%with an average number of similarity computations.展开更多
Azadirachtin,a complex tetratriterpenoid limonin with potent insecticidal properties,is the most widely used biological pesticide worldwide.Its versatile pharmacological applications include the inhibition of tumor gr...Azadirachtin,a complex tetratriterpenoid limonin with potent insecticidal properties,is the most widely used biological pesticide worldwide.Its versatile pharmacological applications include the inhibition of tumor growth and anti-malarial,anti-bacterial,and anti-inflammatory properties.Azadirachtin plays a pivotal role in pest control and novel drug development.The primary source of azadirachtin is the neem tree(Azadirachta indica A.Juss),with an azadirachtin content ranging from 0.3%to 0.5%.Despite the market demand for botanical pesticides reaching approximately 100,000 tons per year,the annual neem production in China is only 1.14 tons.Although azadirachtin can be obtained through plant extraction or chemical synthesis,the quantity obtained does not meet the market demand in China.The sluggish pace of azadirachtin biosynthesis results from the limited availability of genetic information and the complexity of the synthetic pathway.Recent advancements in azadirachtin biosynthesis hold promise as an efficient collection method.In this study,we explored the physicochemical properties,biological activities,mechanisms of action,and acquisition methods of azadirachtin.We also delved into recent progress in azadirachtin biosynthesis and assessed potential future usage challenges.This study aims to establish a theoretical foundation for the scientific application and efficient synthesis of azadirachtin,offering valuable reference information to the industry.展开更多
Acupuncture,a form of traditional Chinese medicine with a history of 2,000 years in China,has gained wider acceptance worldwide as a complementary therapy.Studies have examined its effectiveness in various health cond...Acupuncture,a form of traditional Chinese medicine with a history of 2,000 years in China,has gained wider acceptance worldwide as a complementary therapy.Studies have examined its effectiveness in various health conditions and it is commonly used alongside conventional medical treatments.With the development of artificial intelligence(AI)technology,new possibilities for improving the efficacy and precision of acupuncture have emerged.This study explored the combination of traditional acupuncture and AI technology from three perspectives:acupuncture diagnosis,prescription,and treatment evaluation.The study aimed to provide cutting-edge direction and theoretical assistance for the development of an acupuncture robot.展开更多
This article examines the complex interplay between abstraction and representation in the ontology of images.Images inhabit an in-between space as tangible artifacts that also convey intangible ideas and meanings.The ...This article examines the complex interplay between abstraction and representation in the ontology of images.Images inhabit an in-between space as tangible artifacts that also convey intangible ideas and meanings.The analysis synthesizes perspectives from across the history of philosophy to elucidate how images bridge abstraction and representation through their form and function.It engages with ongoing epistemological and aesthetic debates concerning the dual nature of images.Plato’s theory of ideal forms is outlined as an early attempt to define abstraction.Modern semiotic theories are discussed for their insights into how images create meaning through codes and signs.Phenomenology offers an alternative approach by prioritizing the sensorial,affective impact of images.Poststructuralism problematizes representation in the context of mechanical reproduction and simulacra.While diverse,these philosophical frameworks all grapple with the issues images pose between abstract essence and concrete appearance,conceptual ideas and sensory manifestations.The article reveals the richness of images as liminal constructs that collapse dualisms in their creative interfacing of material forms and immaterial meanings.It concludes that this ontological ambiguity empowers images as mediators between imagination and perception,subjectivity and reality.展开更多
Artificial intelligence in general and software agents in particular are recognized as computer science disciplines that aim to model or simulate so-called intelligent human behaviors such as perception, decision-maki...Artificial intelligence in general and software agents in particular are recognized as computer science disciplines that aim to model or simulate so-called intelligent human behaviors such as perception, decision-making, understanding, learning, etc. This work presents an approach to designing a generic Intelligent Agent that can be used in a multi-agent system to solve a complex problem. The generic agent that is proposed can be instantiated as a concrete agent, which is enabled with learning and autonomy capabilities by using Artificial Neural Networks. To highlight the generic aspect, the proposition is instantiated to be used in agriculture, health and education. The instantiated software agent applied in agriculture can process images in real time and detect defect on plants’ leaf. In the health field, the agent process image to diagnose breast cancer. When applied in Education, the agent can load an image of a student’s script and grade it. The performance of the designed agent system has the same accuracy as that of the respective neural networks used to instantiate them. In the educational field, the software agent has an accuracy of 98.9% and in the health field, it has an accuracy of 99.56% while in the agricultural field, it has an accuracy of 97.2%.展开更多
Text summarization aims to generate a concise version of the original text.The longer the summary text is,themore detailed it will be fromthe original text,and this depends on the intended use.Therefore,the problem of...Text summarization aims to generate a concise version of the original text.The longer the summary text is,themore detailed it will be fromthe original text,and this depends on the intended use.Therefore,the problem of generating summary texts with desired lengths is a vital task to put the research into practice.To solve this problem,in this paper,we propose a new method to integrate the desired length of the summarized text into the encoder-decoder model for the abstractive text summarization problem.This length parameter is integrated into the encoding phase at each self-attention step and the decoding process by preserving the remaining length for calculating headattention in the generation process and using it as length embeddings added to theword embeddings.We conducted experiments for the proposed model on the two data sets,Cable News Network(CNN)Daily and NEWSROOM,with different desired output lengths.The obtained results show the proposed model’s effectiveness compared with related studies.展开更多
The use of computer in architectural design shouldn’t sacrifice the pursuit of a human-oriented built environment.The technological applications should be legitimated by the objectives and motivations in multiple dim...The use of computer in architectural design shouldn’t sacrifice the pursuit of a human-oriented built environment.The technological applications should be legitimated by the objectives and motivations in multiple dimensions,but not abuse its generative power against the social and cultural interests.This article is based upon our synthetic computational design research for high density indemnificatory housing in China(Fig.1),which challenges the conventional standard design for large scale social housing in the Industrial Era,and reflects our exploration for innovative,multi-disciplinary,systematic and synthetic design in the new design paradigm of computation.It also promotes to shift the privilege of cutting-edge design techniques and avant-garde concepts from the“High(end)Architecture”to the ordinary architecture during the unprecedented built-environment development in China.Architectural design should have no discrimination between the Olympic stadiums in the capital and the social housing in the subordinate developed cities,as they both need to be innovative and meaningful.The final design research outputs address sustainable transformation initiated by the residents during the whole life span of the housing.We believe that the human factor(including stakeholders,users,designers and builders)is even more important in architectural design,city planning,urban design,landscape and interior design while technology development is accelerating.Conceptualization,imagination and systemization would become significant pacemakers which perpetuate design innovation.展开更多
Debugging software code has been a challenge for software developers since the early days of computer programming. A simple need, because the world is run by software. So perhaps the biggest engineering challenge is f...Debugging software code has been a challenge for software developers since the early days of computer programming. A simple need, because the world is run by software. So perhaps the biggest engineering challenge is finding ways to make software more reliable. This review provides an overview of techniques developed over time in the field of software model checking to solve the problem of detecting errors in program code. In addition, the challenges posed by this technology are discussed and ways to mitigate them in future research and applications are proposed. A comprehensive examination of the various model verification methods used to detect program code errors is intended to lay the foundation for future research in this area.展开更多
Abstract is the epitome of the core idea of a journal paper.Excellent English abstract plays an important role in ensuring the quality of the paper and promoting its academic value in international exchanges.However,t...Abstract is the epitome of the core idea of a journal paper.Excellent English abstract plays an important role in ensuring the quality of the paper and promoting its academic value in international exchanges.However,there are still many problems in the English abstracts of many papers published in academic journals.This paper analyzes and summarizes the grammatical errors of articles,singular and plural nouns,predicate verbs,conjunctions,Chinglish from other English abstracts of some papers in a vehicle engineering academic journal retrieved from CNCN.cn,and then corrects them.It is expected to provide some guidance for editors,academic workers,and engineering students in writing papers.展开更多
提出了一种基于时间抽象状态机(timed abstract state machine,简称TASM)的AADL(architecture analysis and design language)模型验证方法.分别给出了AADL子集和TASM的抽象语法,并基于语义函数和类ML的元语言形式定义转换规则.在此基础...提出了一种基于时间抽象状态机(timed abstract state machine,简称TASM)的AADL(architecture analysis and design language)模型验证方法.分别给出了AADL子集和TASM的抽象语法,并基于语义函数和类ML的元语言形式定义转换规则.在此基础上,基于AADL开源建模环境OSATE(open source AADL tool environment)设计并实现了AADL模型验证与分析工具AADL2TASM,并基于航天器导航、制导与控制系统(guidance,navigation and control)进行了实例性验证.展开更多
文摘This article reviews the psychological and neuroscience achievements in concept learning since 2010 from the perspectives of individual learning and social learning,and discusses several issues related to concept learning,including the assistance of machine learning about concept learning.In terms of individual learning,current evidence shows that the brain tends to process concrete concepts through typical features(shared features);and for abstract concepts,semantic processing is the most important cognitive way.In terms of social learning,interpersonal neural synchrony(INS)is considered the main indicator of efficient knowledge transfer(such as teaching activities between teachers and students),but this phenomenon only broadens the channels for concept sources and does not change the basic mode of individual concept learning.Ultimately,this article argues that the way the human brain processes concepts depends on the concept’s own characteristics,so there are no“better”strategies in teaching,only more“suitable”strategies.
文摘The rhetorical structure of abstracts has been a widely discussed topic, as it can greatly enhance the abstract writing skills of second-language writers. This study aims to provide guidance on the syntactic features that L2 learners can employ, as well as suggest which features they should focus on in English academic writing. To achieve this, all samples were analyzed for rhetorical moves using Hyland’s five-rhetorical move model. Additionally, all sentences were evaluated for syntactic complexity, considering measures such as global, clausal and phrasal complexity. The findings reveal that expert writers exhibit a more balanced use of syntactic complexity across moves, effectively fulfilling the rhetorical objectives of abstracts. On the other hand, MA students tend to rely excessively on embedded structures and dependent clauses in an attempt to increase complexity. The implications of these findings for academic writing research, pedagogy, and assessment are thoroughly discussed.
基金supported by the National Social Science Foundation of China(2017CG29)the Science and Technology Research Project of Chongqing Municipal Education Commission(2019CJ50)the Natural Science Foundation of Chongqing(2017CC29).
文摘The existing abstractive text summarisation models only consider the word sequence correlations between the source document and the reference summary,and the summary generated by models lacks the cover of the subject of source document due to models'small perspective.In order to make up these disadvantages,a multi‐domain attention pointer(MDA‐Pointer)abstractive summarisation model is proposed in this work.First,the model uses bidirectional long short‐term memory to encode,respectively,the word and sentence sequence of source document for obtaining the semantic representations at word and sentence level.Furthermore,the multi‐domain attention mechanism between the semantic representations and the summary word is established,and the proposed model can generate summary words under the proposed attention mechanism based on the words and sen-tences.Then,the words are extracted from the vocabulary or the original word sequences through the pointer network to form the summary,and the coverage mechanism is introduced,respectively,into word and sentence level to reduce the redundancy of sum-mary content.Finally,experiment validation is conducted on CNN/Daily Mail dataset.ROUGE evaluation indexes of the model without and with the coverage mechanism are improved respectively,and the results verify the validation of model proposed by this paper.
文摘Transactions of Nanjing University of Aeronautics&Astronautics(TNUAA)is a bimonthly journal facing international academic community.Emphasizing prompt and effective dissemination of key data and new scientific insights,TNUAA publishes experimental and theoretical papers bearing on applications to all branches of aeronautics,astronautics and civil aviation.TNUAA is currently indexed by Engineering Index(Ei Compendex,USA),Scopus(Sco,Holland),Chemical Abstracts(CA,USA),P.Ж.(Russia),EBSCO(USA),SA(England),Zbl(Germany),Cambridge Scientific Abstracts(CSA),Chinese Science Citation Database(CSCD,China),National Knowledge Infrastructure(CNKI,China)and Chinese S&T Journal Citation Reports(China).
基金supported by National Natural Science Foundation of China(62276058,61902057,41774063)Fundamental Research Funds for the Central Universities(N2217003)Joint Fund of Science&Technology Department of Liaoning Province and State Key Laboratory of Robotics,China(2020-KF-12-11).
文摘A large variety of complaint reports reflect subjective information expressed by citizens.A key challenge of text summarization for complaint reports is to ensure the factual consistency of generated summary.Therefore,in this paper,a simple and weakly supervised framework considering factual consistency is proposed to generate a summary of city-based complaint reports without pre-labeled sentences/words.Furthermore,it considers the importance of entity in complaint reports to ensure factual consistency of summary.Experimental results on the customer review datasets(Yelp and Amazon)and complaint report dataset(complaint reports of Shenyang in China)show that the proposed framework outperforms state-of-the-art approaches in ROUGE scores and human evaluation.It unveils the effectiveness of our approach to helping in dealing with complaint reports.
基金supported by the National Key R&D Program of China (2018YFB1702700)。
文摘The existing software bug localization models treat the source file as natural language, which leads to the loss of syntactical and structure information of the source file. A bug localization model based on syntactical and semantic information of source code is proposed. Firstly, abstract syntax tree(AST) is divided based on node category to obtain statement sequence. The statement tree is encoded into vectors to capture lexical and syntactical knowledge at the statement level.Secondly, the source code is transformed into vector representation by the sequence naturalness of the statement. Therefore,the problem of gradient vanishing and explosion caused by a large AST size is obviated when using AST to the represent source code. Finally, the correlation between bug reports and source files are comprehensively analyzed from three aspects of syntax, semantics and text to locate the buggy code. Experiments show that compared with other standard models, the proposed model improves the performance of bug localization, and it has good advantages in mean reciprocal rank(MRR), mean average precision(MAP) and Top N Rank.
文摘With the continuous growth of online news articles,there arises the necessity for an efficient abstractive summarization technique for the problem of information overloading.Abstractive summarization is highly complex and requires a deeper understanding and proper reasoning to come up with its own summary outline.Abstractive summarization task is framed as seq2seq modeling.Existing seq2seq methods perform better on short sequences;however,for long sequences,the performance degrades due to high computation and hence a two-phase self-normalized deep neural document summarization model consisting of improvised extractive cosine normalization and seq2seq abstractive phases has been proposed in this paper.The novelty is to parallelize the sequence computation training by incorporating feed-forward,the self-normalized neural network in the Extractive phase using Intra Cosine Attention Similarity(Ext-ICAS)with sentence dependency position.Also,it does not require any normalization technique explicitly.Our proposed abstractive Bidirectional Long Short Term Memory(Bi-LSTM)encoder sequence model performs better than the Bidirectional Gated Recurrent Unit(Bi-GRU)encoder with minimum training loss and with fast convergence.The proposed model was evaluated on the Cable News Network(CNN)/Daily Mail dataset and an average rouge score of 0.435 was achieved also computational training in the extractive phase was reduced by 59%with an average number of similarity computations.
基金supported by the Scientific and Technological Innovation Project of the Chinese Academy of Chinese Medical Sciences (C12021A04111 and C12021A04116)the Fundamental Research Funds for the Central Public Welfare Research Institutes (ZZ14-YQ-031 and ZZ13-YQ-040)+1 种基金the National Key Research and Development Project (2019YFC19066)the National Natural Science Foundation of China (32200308).
文摘Azadirachtin,a complex tetratriterpenoid limonin with potent insecticidal properties,is the most widely used biological pesticide worldwide.Its versatile pharmacological applications include the inhibition of tumor growth and anti-malarial,anti-bacterial,and anti-inflammatory properties.Azadirachtin plays a pivotal role in pest control and novel drug development.The primary source of azadirachtin is the neem tree(Azadirachta indica A.Juss),with an azadirachtin content ranging from 0.3%to 0.5%.Despite the market demand for botanical pesticides reaching approximately 100,000 tons per year,the annual neem production in China is only 1.14 tons.Although azadirachtin can be obtained through plant extraction or chemical synthesis,the quantity obtained does not meet the market demand in China.The sluggish pace of azadirachtin biosynthesis results from the limited availability of genetic information and the complexity of the synthetic pathway.Recent advancements in azadirachtin biosynthesis hold promise as an efficient collection method.In this study,we explored the physicochemical properties,biological activities,mechanisms of action,and acquisition methods of azadirachtin.We also delved into recent progress in azadirachtin biosynthesis and assessed potential future usage challenges.This study aims to establish a theoretical foundation for the scientific application and efficient synthesis of azadirachtin,offering valuable reference information to the industry.
基金supported by the National Natural Science Foundation of China (No.82305376)2021 Special Research Project of TCM Science and Technology Development Plan of Jiangsu Province (ZT202120)+1 种基金Luo Linxiu Teacher Development Funding Project (LLX202308)National Key Research and Development Plan Intelligent Robot (2022YFB4703100).
文摘Acupuncture,a form of traditional Chinese medicine with a history of 2,000 years in China,has gained wider acceptance worldwide as a complementary therapy.Studies have examined its effectiveness in various health conditions and it is commonly used alongside conventional medical treatments.With the development of artificial intelligence(AI)technology,new possibilities for improving the efficacy and precision of acupuncture have emerged.This study explored the combination of traditional acupuncture and AI technology from three perspectives:acupuncture diagnosis,prescription,and treatment evaluation.The study aimed to provide cutting-edge direction and theoretical assistance for the development of an acupuncture robot.
文摘This article examines the complex interplay between abstraction and representation in the ontology of images.Images inhabit an in-between space as tangible artifacts that also convey intangible ideas and meanings.The analysis synthesizes perspectives from across the history of philosophy to elucidate how images bridge abstraction and representation through their form and function.It engages with ongoing epistemological and aesthetic debates concerning the dual nature of images.Plato’s theory of ideal forms is outlined as an early attempt to define abstraction.Modern semiotic theories are discussed for their insights into how images create meaning through codes and signs.Phenomenology offers an alternative approach by prioritizing the sensorial,affective impact of images.Poststructuralism problematizes representation in the context of mechanical reproduction and simulacra.While diverse,these philosophical frameworks all grapple with the issues images pose between abstract essence and concrete appearance,conceptual ideas and sensory manifestations.The article reveals the richness of images as liminal constructs that collapse dualisms in their creative interfacing of material forms and immaterial meanings.It concludes that this ontological ambiguity empowers images as mediators between imagination and perception,subjectivity and reality.
文摘Artificial intelligence in general and software agents in particular are recognized as computer science disciplines that aim to model or simulate so-called intelligent human behaviors such as perception, decision-making, understanding, learning, etc. This work presents an approach to designing a generic Intelligent Agent that can be used in a multi-agent system to solve a complex problem. The generic agent that is proposed can be instantiated as a concrete agent, which is enabled with learning and autonomy capabilities by using Artificial Neural Networks. To highlight the generic aspect, the proposition is instantiated to be used in agriculture, health and education. The instantiated software agent applied in agriculture can process images in real time and detect defect on plants’ leaf. In the health field, the agent process image to diagnose breast cancer. When applied in Education, the agent can load an image of a student’s script and grade it. The performance of the designed agent system has the same accuracy as that of the respective neural networks used to instantiate them. In the educational field, the software agent has an accuracy of 98.9% and in the health field, it has an accuracy of 99.56% while in the agricultural field, it has an accuracy of 97.2%.
基金funded by Vietnam National Foundation for Science and Technology Development(NAFOSTED)under Grant Number 102.05-2020.26。
文摘Text summarization aims to generate a concise version of the original text.The longer the summary text is,themore detailed it will be fromthe original text,and this depends on the intended use.Therefore,the problem of generating summary texts with desired lengths is a vital task to put the research into practice.To solve this problem,in this paper,we propose a new method to integrate the desired length of the summarized text into the encoder-decoder model for the abstractive text summarization problem.This length parameter is integrated into the encoding phase at each self-attention step and the decoding process by preserving the remaining length for calculating headattention in the generation process and using it as length embeddings added to theword embeddings.We conducted experiments for the proposed model on the two data sets,Cable News Network(CNN)Daily and NEWSROOM,with different desired output lengths.The obtained results show the proposed model’s effectiveness compared with related studies.
文摘The use of computer in architectural design shouldn’t sacrifice the pursuit of a human-oriented built environment.The technological applications should be legitimated by the objectives and motivations in multiple dimensions,but not abuse its generative power against the social and cultural interests.This article is based upon our synthetic computational design research for high density indemnificatory housing in China(Fig.1),which challenges the conventional standard design for large scale social housing in the Industrial Era,and reflects our exploration for innovative,multi-disciplinary,systematic and synthetic design in the new design paradigm of computation.It also promotes to shift the privilege of cutting-edge design techniques and avant-garde concepts from the“High(end)Architecture”to the ordinary architecture during the unprecedented built-environment development in China.Architectural design should have no discrimination between the Olympic stadiums in the capital and the social housing in the subordinate developed cities,as they both need to be innovative and meaningful.The final design research outputs address sustainable transformation initiated by the residents during the whole life span of the housing.We believe that the human factor(including stakeholders,users,designers and builders)is even more important in architectural design,city planning,urban design,landscape and interior design while technology development is accelerating.Conceptualization,imagination and systemization would become significant pacemakers which perpetuate design innovation.
文摘Debugging software code has been a challenge for software developers since the early days of computer programming. A simple need, because the world is run by software. So perhaps the biggest engineering challenge is finding ways to make software more reliable. This review provides an overview of techniques developed over time in the field of software model checking to solve the problem of detecting errors in program code. In addition, the challenges posed by this technology are discussed and ways to mitigate them in future research and applications are proposed. A comprehensive examination of the various model verification methods used to detect program code errors is intended to lay the foundation for future research in this area.
基金Educational Innovation Research Program of CSU(No.2022jy032)。
文摘Abstract is the epitome of the core idea of a journal paper.Excellent English abstract plays an important role in ensuring the quality of the paper and promoting its academic value in international exchanges.However,there are still many problems in the English abstracts of many papers published in academic journals.This paper analyzes and summarizes the grammatical errors of articles,singular and plural nouns,predicate verbs,conjunctions,Chinglish from other English abstracts of some papers in a vehicle engineering academic journal retrieved from CNCN.cn,and then corrects them.It is expected to provide some guidance for editors,academic workers,and engineering students in writing papers.
文摘提出了一种基于时间抽象状态机(timed abstract state machine,简称TASM)的AADL(architecture analysis and design language)模型验证方法.分别给出了AADL子集和TASM的抽象语法,并基于语义函数和类ML的元语言形式定义转换规则.在此基础上,基于AADL开源建模环境OSATE(open source AADL tool environment)设计并实现了AADL模型验证与分析工具AADL2TASM,并基于航天器导航、制导与控制系统(guidance,navigation and control)进行了实例性验证.