This study proposes an image-based three-dimensional(3D)vector reconstruction of industrial parts that can gener-ate non-uniform rational B-splines(NURBS)surfaces with high fidelity and flexibility.The contributions o...This study proposes an image-based three-dimensional(3D)vector reconstruction of industrial parts that can gener-ate non-uniform rational B-splines(NURBS)surfaces with high fidelity and flexibility.The contributions of this study include three parts:first,a dataset of two-dimensional images is constructed for typical industrial parts,including hex-agonal head bolts,cylindrical gears,shoulder rings,hexagonal nuts,and cylindrical roller bearings;second,a deep learning algorithm is developed for parameter extraction of 3D industrial parts,which can determine the final 3D parameters and pose information of the reconstructed model using two new nets,CAD-ClassNet and CAD-ReconNet;and finally,a 3D vector shape reconstruction of mechanical parts is presented to generate NURBS from the obtained shape parameters.The final reconstructed models show that the proposed approach is highly accurate,efficient,and practical.展开更多
OBJECTIVE:To explore the correlation between diagnostic information of tongue and gastroscopy results of patients with chronic gastritis.METHODS:Frequent pattern growth(FP-Growth),SPSS Modeler was used to analyze the ...OBJECTIVE:To explore the correlation between diagnostic information of tongue and gastroscopy results of patients with chronic gastritis.METHODS:Frequent pattern growth(FP-Growth),SPSS Modeler was used to analyze the correlation rules between the image information of tongue parameters and the characteristics of the stomach and duodenum seen under gastroscopy.RESULTS:Ranking in order of confidence:cyanotic tongue,slippery fur,yellow fur and spotted tongue were sequently associated with both gastric antrum mucosal hyperemia or edema and gastric antrum mucosal erythema/macula.L,one value of tongue coating color,which counted among(30,60),tooth-marked tongue and b,one value of tongue coating color,which counted in the range of(5,20)were sequently associated with gastric antrum mucosal erythema/macula.A,one value of tongue body color,which counted in the range of(0,20),was related to both gastric antrum mucosal hyperemia or edema and gastric antrum mucosal erythema/macula.a,one value of tongue coating color,which counted in the range of(15,35),was associated with gastric antrum mucosal erythema/macula.There are a total of 9 strong correlation rules.CONCLUSIONS:Cyanotic tongue,slippery fur,yellow fur,the CIE Lab value of tongue coating,a,the value of tongue body color,spotted tongue,and tooth-marked tongue are all related to the gastric antrum mucosal hyperemia or edema and gastric antrum mucosal erythema/macula.The conditions of gastric mucosa could be predicted by the examination of the above related image information of tongue.展开更多
We present a model for self-adjustment of social conventions to small perturbations, and investigate how perturbations can influence the convergence of social convention in different situations. The experimental resul...We present a model for self-adjustment of social conventions to small perturbations, and investigate how perturbations can influence the convergence of social convention in different situations. The experimental results show that the sensitivity of social conventions is determined by not only the perturbations themselves but also the agent adjustment functions for the perturbations; and social conventions are more sensitive to the outlier agent number than to the strategy fluctuation magnitudes and localities of perturbations.展开更多
Hardware/software（HW/SW） partitioning is one of the key processes in an embedded system.It is used to determine which system components are assigned to hardware and which are processed by software.In contrast with p...Hardware/software（HW/SW） partitioning is one of the key processes in an embedded system.It is used to determine which system components are assigned to hardware and which are processed by software.In contrast with previous research that focuses on developing efficient heuristic,we focus on the pre-process of the task graph before the HW/SW partitioning in this paper,that is,enumerating all the sub-graphs that meet the requirements.Experimental results showed that the original graph can be reduced to 67% in the worst-case scenario and 58% in the best-case scenario.In conclusion,the reduced task graph saved hardware area while improving partitioning speed and accuracy.展开更多
Background Owing to recent advances in virtual reality(VR)technologies,effective user interaction with dynamic content in 3D scenes has become a research hotspot.Moving target selection is a basic interactive task in ...Background Owing to recent advances in virtual reality(VR)technologies,effective user interaction with dynamic content in 3D scenes has become a research hotspot.Moving target selection is a basic interactive task in which the user performance research in tasks is significant to user interface design in VR.Different from the existing static target selection studies,the moving target selection in VR is affected by the change in target speed,angle and size,and lack of research on some key factors.Methods This study designs an experimental scenario in which the users play badminton under the condition of VR.By adding seven kinds of modal clues such as vision,audio,haptics,and their combinations,five kinds of moving speed and four kinds of serving angles,and the effect of these factors on the performance and subjective feelings in moving target selection in VR,is studied.Results The results show that the moving speed of the shuttlecock has a significant impact on the user performance.The angle of service has a significant impact on hitting rate,but has no significant impact on the hitting distance.The acquisition of the user performance by the moving target is mainly influenced by vision under the combined modalities;adding additional modalities can improve user performance.Although the hitting distance of the target is increased in the trimodal condition,the hitting rate decreases.Conclusion This study analyses the results of user performance and subjective perception,and then provides suggestions on the combination of modality clues in different scenarios.展开更多
Gears play an important role in virtual manufacturing systems for digital twins;however,the image of gear tooth defects is difficult to acquire owing to its non-convex shape.In this study,a deep learning network is pr...Gears play an important role in virtual manufacturing systems for digital twins;however,the image of gear tooth defects is difficult to acquire owing to its non-convex shape.In this study,a deep learning network is proposed to detect gear defects based on their point cloud representation.This approach mainly consists of three steps:(1)Various types of gear defects are classified into four cases(fracture,pitting,glue,and wear);A 3D gear dataset was constructed with 10000 instances following the aforementioned classification.(2)Gear-PCNet++introduces a novel Combinational Convolution Block,proposed based on the gear dataset for gear defect detection to effectively extract the local gear information and identify its complex topology;(3)Compared with other methods,experiments show that this method can achieve better recognition results for gear defects with higher efficiency and practicability.展开更多
Natural disasters are not negligible factors that have significant impacts on a country’s development. Madagascar cannot escape cyclones, floods and drought due to its geographical situation. The objective in this wo...Natural disasters are not negligible factors that have significant impacts on a country’s development. Madagascar cannot escape cyclones, floods and drought due to its geographical situation. The objective in this work is to assess the risks and vulnerability to these hazards in order to strengthen the resilience of the Malagasy population. Our approach is based on multi-criteria spatial analysis using the Analytical Hierarchy Process (AHP). The results form decision spatial information that can be used at the strategic level of natural risk and disaster management. This work focuses on the degree of vulnerability and it was found in this study that the Androy and Atsimo-Atsinanana regions are the most vulnerable to major hazards in Madagascar not only because of their exposure to risk but also because of their very low socio-economic status.展开更多
Our research focuses on creating a meta-model for generating a web mapping application. It was difficult for non-geomatics developers to implement a webmapping application. Indeed, this type of application uses geospa...Our research focuses on creating a meta-model for generating a web mapping application. It was difficult for non-geomatics developers to implement a webmapping application. Indeed, this type of application uses geospatial data that require geomatics skills. For this reason, in order to help non-geomatics developers to set up a webmapping application, we have designed a meta-model that automatically generates a webmapping application using model-driven engineering. The created meta-model is used by non-geomatics developers to explicitly write the concrete syntax specific to the webmapping application using the xtext tool. This concrete syntax is automatically converted into source code using the xtend tool without the intervention of the non-geomatics developers.展开更多
Human-computer interactions constitute an important subject for the development and popularization of information technologies,as they are not only an important frontier technology in computer science but also an impo...Human-computer interactions constitute an important subject for the development and popularization of information technologies,as they are not only an important frontier technology in computer science but also an important auxiliary technology in virtual reality(VR).In recent years,Chinese researchers have made significant advances in human-computer interactions.To systematically display China's latest advances in human-computer interactions and thus provide an impetus for the development of VR and other related fields,we have solicited articles for this special issue from experts in this area to participate in the review process.The following articles have been selected for publication in this special issue.展开更多
This study proposes a segmented approach to analyzing diabetes risk factors using the dataset diabete_custom.xlsx(150 individuals,14 medical and behavioral variables).The combination of KMeans with logistic regression...This study proposes a segmented approach to analyzing diabetes risk factors using the dataset diabete_custom.xlsx(150 individuals,14 medical and behavioral variables).The combination of KMeans with logistic regression and KMeans with decision tree enabled the definition of three clusters corresponding to low,moderate,and high risk,while identifying key variables such as blood glucose,BMI,and heredity.The hybrid models improve accuracy and interpretability compared to KMeans alone,with the decision tree being slightly more effective in unbalanced clusters.These findings provide a foundation for personalized interventions,including targeted screening,glycemic and nutritional monitoring,physical activity,and educational campaigns tailored to each risk profile.展开更多
Semiconductor manufacturing (SM) system is one of the most complicated hybrid processes involved continuously variable dynamical systems and discrete event dynamical systems. The optimization and scheduling of semicon...Semiconductor manufacturing (SM) system is one of the most complicated hybrid processes involved continuously variable dynamical systems and discrete event dynamical systems. The optimization and scheduling of semiconductor fabrication has long been a hot research direction in automation. Bottleneck is the key factor to a SM system, which seriously influences the throughput rate, cycle time, time-delivery rate, etc. Efficient prediction for the bottleneck of a SM system provides the best support for the consequent scheduling. Because categorical data (product types, releasing strategies) and numerical data (work in process, processing time, utilization rate, buffer length, etc.) have significant effect on bottleneck, an improved adaptive network-based fuzzy inference system (ANFIS) was adopted in this study to predict bottleneck since conventional neural network-based methods accommodate only numerical inputs. In this improved ANFIS, the contribution of categorical inputs to firing strength is reflected through a transformation matrix. In order to tackle high-dimensional inputs, reduce the number of fuzzy rules and obtain high prediction accuracy, a fuzzy c-means method combining binary tree linear division method was applied to identify the initial structure of fuzzy inference system. According to the experimental results, the main-bottleneck and sub-bottleneck of SM system can be predicted accurately with the proposed method.展开更多
Markov decision process(MDP)offers a general framework for modelling sequential decision making where outcomes are random.In particular,it serves as a mathematical framework for reinforcement learning.This paper intro...Markov decision process(MDP)offers a general framework for modelling sequential decision making where outcomes are random.In particular,it serves as a mathematical framework for reinforcement learning.This paper introduces an extension of MDP,namely quantum MDP(q MDP),that can serve as a mathematical model of decision making about quantum systems.We develop dynamic programming algorithms for policy evaluation and finding optimal policies for q MDPs in the case of finite-horizon.The results obtained in this paper provide some useful mathematical tools for reinforcement learning techniques applied to the quantum world.展开更多
Geometric morphometrics （GM） is an important method of shape analysis and increasingly used in a wide range of scientific disciplines. Presently, a single character comparison system of geometric morphometric data i...Geometric morphometrics （GM） is an important method of shape analysis and increasingly used in a wide range of scientific disciplines. Presently, a single character comparison system of geometric morphometric data is used in almost all empirical studies, and this approach is sufficient for many scientific problems. However, the estimation of overall similarity among taxa or objects based on multiple characters is crucial in a variety of contexts （e.g. （semi-）automated identification, phenetic relationships, tracing of character evolution, phylogenetic reconstruction）. Here we propose a new web-based tool for merging several geometric morphometrics data files from multiple characters into a single data file. Using this approach information from multiple characters can be compared in combination and an overall similarity estimate can be obtained in a convenient and geometrically rigorous manner. To illustrate our method, we provide an example analysis of 25 dung beetle species with seven Procrustes superimposed landmark data files representing the morphological variation of body features： the epipharynx, right mandible, pronotum, elytra, hindwing, and the metendosternite in dorsal and lateral view. All seven files were merged into a single one containing information on 649 landmark locations. The possible applications of such merged data files in different fields of science are discussed.展开更多
With the development of virtual reality(VR)and human-computer interaction technology,how to use natural and efficient interaction methods in the virtual environment has become a hot topic of research.Gesture is one of...With the development of virtual reality(VR)and human-computer interaction technology,how to use natural and efficient interaction methods in the virtual environment has become a hot topic of research.Gesture is one of the most important communication methods of human beings,which can effectively express users'demands.In the past few decades,gesture-based interaction has made significant progress.This article focuses on the gesture interaction technology and discusses the definition and classification of gestures,input devices for gesture interaction,and gesture interaction recognition technology.The application of gesture interaction technology in virtual reality is studied,the existing problems in the current gesture interaction are summarized,and the future development is prospected.展开更多
Knowledge plays a critical role in artificial intelligence.Recently,the extensive success of pre-trained language models(PLMs)has raised significant attention about how knowledge can be acquired,maintained,updated and...Knowledge plays a critical role in artificial intelligence.Recently,the extensive success of pre-trained language models(PLMs)has raised significant attention about how knowledge can be acquired,maintained,updated and used by language models.Despite the enormous amount of related studies,there is still a lack of a unified view of how knowledge circulates within language models throughout the learning,tuning,and application processes,which may prevent us from further understanding the connections between current progress or realizing existing limitations.In this survey,we revisit PLMs as knowledge-based systems by dividing the life circle of knowledge in PLMs into five critical periods,and investigating how knowledge circulates when it is built,maintained and used.To this end,we systematically review existing studies of each period of the knowledge life cycle,summarize the main challenges and current limitations,and discuss future directions.展开更多
A new ontology-based question expansion （OBQE） method is proposed for question similarity calculation in a frequently asked question （FAQ） answering system. Traditional question similarity calculation methods use ...A new ontology-based question expansion （OBQE） method is proposed for question similarity calculation in a frequently asked question （FAQ） answering system. Traditional question similarity calculation methods use ＂word＂ to compose question vector, that the semantic relations between words are ignored. OBQE takes the relation as an important part. The process of the new system is：① to build two-layered domain ontology referring to WordNet and domain corpse;② to expand question trunks into domain cases;③ to use domain case composed vector to calculate question similarity. The experimental result shows that the performance of question similarity calculation with OBQE is being improved.展开更多
The input of a network is the key problem for Chinese word sense disambiguation utilizing the neural network. This paper presents an input model of the neural network that calculates the mutual information between con...The input of a network is the key problem for Chinese word sense disambiguation utilizing the neural network. This paper presents an input model of the neural network that calculates the mutual information between contextual words and the ambiguous word by using statistical methodology and taking the contextual words of a certain number beside the ambiguous word according to (-M,+N).The experiment adopts triple-layer BP Neural Network model and proves how the size of a training set and the value of Mand Naffect the performance of the Neural Network Model. The experimental objects are six pseudowords owning three word-senses constructed according to certain principles. The tested accuracy of our approach on a closed-corpus reaches 90.31%, and 89.62% on an open-corpus. The experiment proves that the Neural Network Model has a good performance on Word Sense Disambiguation.展开更多
基金supported by the Aeronautical Science Foundation of China,No.2023Z0680510022021 Special Scientific Research on Civil Aircraft Project+1 种基金the Natural Science Foundation of China,Nos.61572056 and 61872347the Special Plan for the Development of Distinguished Young Scientists of ISCAS,No.Y8RC535018.
文摘This study proposes an image-based three-dimensional(3D)vector reconstruction of industrial parts that can gener-ate non-uniform rational B-splines(NURBS)surfaces with high fidelity and flexibility.The contributions of this study include three parts:first,a dataset of two-dimensional images is constructed for typical industrial parts,including hex-agonal head bolts,cylindrical gears,shoulder rings,hexagonal nuts,and cylindrical roller bearings;second,a deep learning algorithm is developed for parameter extraction of 3D industrial parts,which can determine the final 3D parameters and pose information of the reconstructed model using two new nets,CAD-ClassNet and CAD-ReconNet;and finally,a 3D vector shape reconstruction of mechanical parts is presented to generate NURBS from the obtained shape parameters.The final reconstructed models show that the proposed approach is highly accurate,efficient,and practical.
基金Key Special Project of the National Key Research and Development Program of Ministry of Science and Technology(No.2017YFB1002300):Topic One:Multimodal Heterogeneous Efficient Acquisition of Traditional Chinese Medicine Big Data and Resource Library Construction(No.2017YFB1002301)and Topic Three:Multi-Scale Cognition Methods and Treatment Analysis Model of Traditional Chinese Medicine Based on Deep Learning(No.2017YFB1002303)from Big Data-Driven Traditional Chinese Medicine Intelligent Auxiliary Diagnostic Service SystemGraduation Design of“Cultivation Program”for Cross-cultivation of High-level Talents in Beijing Colleges and Universities in 2010(Scientific Research):the Research on the Clinical Diagnosis and Prediction System of Gastric Precancerous Lesions Based on Artificial Intelligence+2 种基金National Natural Science Foundation of China(No.30701071)the Sixth Batch of Academic Experience Inheritance of Traditional Chinese Medicine Experts(2017)“3+3”Project of Beijing Traditional Chinese Medicine Inheritance(No.2012-SZ-C-41)。
文摘OBJECTIVE:To explore the correlation between diagnostic information of tongue and gastroscopy results of patients with chronic gastritis.METHODS:Frequent pattern growth(FP-Growth),SPSS Modeler was used to analyze the correlation rules between the image information of tongue parameters and the characteristics of the stomach and duodenum seen under gastroscopy.RESULTS:Ranking in order of confidence:cyanotic tongue,slippery fur,yellow fur and spotted tongue were sequently associated with both gastric antrum mucosal hyperemia or edema and gastric antrum mucosal erythema/macula.L,one value of tongue coating color,which counted among(30,60),tooth-marked tongue and b,one value of tongue coating color,which counted in the range of(5,20)were sequently associated with gastric antrum mucosal erythema/macula.A,one value of tongue body color,which counted in the range of(0,20),was related to both gastric antrum mucosal hyperemia or edema and gastric antrum mucosal erythema/macula.a,one value of tongue coating color,which counted in the range of(15,35),was associated with gastric antrum mucosal erythema/macula.There are a total of 9 strong correlation rules.CONCLUSIONS:Cyanotic tongue,slippery fur,yellow fur,the CIE Lab value of tongue coating,a,the value of tongue body color,spotted tongue,and tooth-marked tongue are all related to the gastric antrum mucosal hyperemia or edema and gastric antrum mucosal erythema/macula.The conditions of gastric mucosa could be predicted by the examination of the above related image information of tongue.
基金Supported by the National Natural Science Foundation of China under Grant No 60803060, and the Excellent Young Teachers Program of Southeast University.
文摘We present a model for self-adjustment of social conventions to small perturbations, and investigate how perturbations can influence the convergence of social convention in different situations. The experimental results show that the sensitivity of social conventions is determined by not only the perturbations themselves but also the agent adjustment functions for the perturbations; and social conventions are more sensitive to the outlier agent number than to the strategy fluctuation magnitudes and localities of perturbations.
基金Supported by the National Natural Science Foundation of China (60970016,61173032)
文摘Hardware/software（HW/SW） partitioning is one of the key processes in an embedded system.It is used to determine which system components are assigned to hardware and which are processed by software.In contrast with previous research that focuses on developing efficient heuristic,we focus on the pre-process of the task graph before the HW/SW partitioning in this paper,that is,enumerating all the sub-graphs that meet the requirements.Experimental results showed that the original graph can be reduced to 67% in the worst-case scenario and 58% in the best-case scenario.In conclusion,the reduced task graph saved hardware area while improving partitioning speed and accuracy.
基金National Key Research and Development(2016YFB1001405)Frontier Subject Key Research(QYZDY-SSW JSC041)National Natural Science Foundation of China(61802379).
文摘Background Owing to recent advances in virtual reality(VR)technologies,effective user interaction with dynamic content in 3D scenes has become a research hotspot.Moving target selection is a basic interactive task in which the user performance research in tasks is significant to user interface design in VR.Different from the existing static target selection studies,the moving target selection in VR is affected by the change in target speed,angle and size,and lack of research on some key factors.Methods This study designs an experimental scenario in which the users play badminton under the condition of VR.By adding seven kinds of modal clues such as vision,audio,haptics,and their combinations,five kinds of moving speed and four kinds of serving angles,and the effect of these factors on the performance and subjective feelings in moving target selection in VR,is studied.Results The results show that the moving speed of the shuttlecock has a significant impact on the user performance.The angle of service has a significant impact on hitting rate,but has no significant impact on the hitting distance.The acquisition of the user performance by the moving target is mainly influenced by vision under the combined modalities;adding additional modalities can improve user performance.Although the hitting distance of the target is increased in the trimodal condition,the hitting rate decreases.Conclusion This study analyses the results of user performance and subjective perception,and then provides suggestions on the combination of modality clues in different scenarios.
基金opening fund of State Key Laboratory of Lunar and Planetary Sciences(Macao University of Science and Technology),No.119/2017/A3the Natural Science Foundation of China,Nos.61572056 and 61872347the Special Plan for the Development of Distinguished Young Scientists of ISCAS,No.Y8RC535018.
文摘Gears play an important role in virtual manufacturing systems for digital twins;however,the image of gear tooth defects is difficult to acquire owing to its non-convex shape.In this study,a deep learning network is proposed to detect gear defects based on their point cloud representation.This approach mainly consists of three steps:(1)Various types of gear defects are classified into four cases(fracture,pitting,glue,and wear);A 3D gear dataset was constructed with 10000 instances following the aforementioned classification.(2)Gear-PCNet++introduces a novel Combinational Convolution Block,proposed based on the gear dataset for gear defect detection to effectively extract the local gear information and identify its complex topology;(3)Compared with other methods,experiments show that this method can achieve better recognition results for gear defects with higher efficiency and practicability.
基金This work has been supported by the National Natural Science Foundation of China under Grant No. 10471051, and also by the Key Project of Chinese National Programs for Fundamental Research and Development（973 program） through Grant No. 2004CB318000, and also by the Fundamental Research Funds for the Central Universities under Grant No. M2009027.
基金This work is supported by the National Natural Science Foundation of China （No. 60073020）, the University Natural Science Foundation of Jiangsu Province of China （No. 05KJB520119） and the Natural Science Foundation Project of Chongqing （No. CSTC2006BB2259）.
文摘Natural disasters are not negligible factors that have significant impacts on a country’s development. Madagascar cannot escape cyclones, floods and drought due to its geographical situation. The objective in this work is to assess the risks and vulnerability to these hazards in order to strengthen the resilience of the Malagasy population. Our approach is based on multi-criteria spatial analysis using the Analytical Hierarchy Process (AHP). The results form decision spatial information that can be used at the strategic level of natural risk and disaster management. This work focuses on the degree of vulnerability and it was found in this study that the Androy and Atsimo-Atsinanana regions are the most vulnerable to major hazards in Madagascar not only because of their exposure to risk but also because of their very low socio-economic status.
文摘Our research focuses on creating a meta-model for generating a web mapping application. It was difficult for non-geomatics developers to implement a webmapping application. Indeed, this type of application uses geospatial data that require geomatics skills. For this reason, in order to help non-geomatics developers to set up a webmapping application, we have designed a meta-model that automatically generates a webmapping application using model-driven engineering. The created meta-model is used by non-geomatics developers to explicitly write the concrete syntax specific to the webmapping application using the xtext tool. This concrete syntax is automatically converted into source code using the xtend tool without the intervention of the non-geomatics developers.
文摘Human-computer interactions constitute an important subject for the development and popularization of information technologies,as they are not only an important frontier technology in computer science but also an important auxiliary technology in virtual reality(VR).In recent years,Chinese researchers have made significant advances in human-computer interactions.To systematically display China's latest advances in human-computer interactions and thus provide an impetus for the development of VR and other related fields,we have solicited articles for this special issue from experts in this area to participate in the review process.The following articles have been selected for publication in this special issue.
文摘This study proposes a segmented approach to analyzing diabetes risk factors using the dataset diabete_custom.xlsx(150 individuals,14 medical and behavioral variables).The combination of KMeans with logistic regression and KMeans with decision tree enabled the definition of three clusters corresponding to low,moderate,and high risk,while identifying key variables such as blood glucose,BMI,and heredity.The hybrid models improve accuracy and interpretability compared to KMeans alone,with the decision tree being slightly more effective in unbalanced clusters.These findings provide a foundation for personalized interventions,including targeted screening,glycemic and nutritional monitoring,physical activity,and educational campaigns tailored to each risk profile.
基金Supported by the National Key Basic Research and Development Program of China (2009CB320602)the National Natural Science Foundation of China (60834004, 61025018)+2 种基金the Open Project Program of the State Key Lab of Industrial ControlTechnology (ICT1108)the Open Project Program of the State Key Lab of CAD & CG (A1120)the Foundation of Key Laboratory of System Control and Information Processing (SCIP2011005),Ministry of Education,China
文摘Semiconductor manufacturing (SM) system is one of the most complicated hybrid processes involved continuously variable dynamical systems and discrete event dynamical systems. The optimization and scheduling of semiconductor fabrication has long been a hot research direction in automation. Bottleneck is the key factor to a SM system, which seriously influences the throughput rate, cycle time, time-delivery rate, etc. Efficient prediction for the bottleneck of a SM system provides the best support for the consequent scheduling. Because categorical data (product types, releasing strategies) and numerical data (work in process, processing time, utilization rate, buffer length, etc.) have significant effect on bottleneck, an improved adaptive network-based fuzzy inference system (ANFIS) was adopted in this study to predict bottleneck since conventional neural network-based methods accommodate only numerical inputs. In this improved ANFIS, the contribution of categorical inputs to firing strength is reflected through a transformation matrix. In order to tackle high-dimensional inputs, reduce the number of fuzzy rules and obtain high prediction accuracy, a fuzzy c-means method combining binary tree linear division method was applied to identify the initial structure of fuzzy inference system. According to the experimental results, the main-bottleneck and sub-bottleneck of SM system can be predicted accurately with the proposed method.
基金partly supported by National Key R&D Program of China(No.2018YFA0306701)the Australian Research Council(Nos.DP160101652 and DP180100691)+1 种基金National Natural Science Foundation of China(No.61832015)the Key Research Program of Frontier Sciences,Chinese Academy of Sciences。
文摘Markov decision process(MDP)offers a general framework for modelling sequential decision making where outcomes are random.In particular,it serves as a mathematical framework for reinforcement learning.This paper introduces an extension of MDP,namely quantum MDP(q MDP),that can serve as a mathematical model of decision making about quantum systems.We develop dynamic programming algorithms for policy evaluation and finding optimal policies for q MDPs in the case of finite-horizon.The results obtained in this paper provide some useful mathematical tools for reinforcement learning techniques applied to the quantum world.
基金supported by the National Natural Science Foundation of China(31672345,51305057,61379087)the Research Equipment Development Project of Chinese Academy of Sciences(YZ201509)a Humboldt Fellowship(M.B.) from Alexander von Humboldt Foundation
文摘Geometric morphometrics （GM） is an important method of shape analysis and increasingly used in a wide range of scientific disciplines. Presently, a single character comparison system of geometric morphometric data is used in almost all empirical studies, and this approach is sufficient for many scientific problems. However, the estimation of overall similarity among taxa or objects based on multiple characters is crucial in a variety of contexts （e.g. （semi-）automated identification, phenetic relationships, tracing of character evolution, phylogenetic reconstruction）. Here we propose a new web-based tool for merging several geometric morphometrics data files from multiple characters into a single data file. Using this approach information from multiple characters can be compared in combination and an overall similarity estimate can be obtained in a convenient and geometrically rigorous manner. To illustrate our method, we provide an example analysis of 25 dung beetle species with seven Procrustes superimposed landmark data files representing the morphological variation of body features： the epipharynx, right mandible, pronotum, elytra, hindwing, and the metendosternite in dorsal and lateral view. All seven files were merged into a single one containing information on 649 landmark locations. The possible applications of such merged data files in different fields of science are discussed.
基金National Key Research and Development(2016YFB1001405)Frontier Subject Key Research(QYZDY-SSW-JSC041)Chinese Academy of Sciences hundred people,National Natural Science Foundation of China(61572479)project support.
文摘With the development of virtual reality(VR)and human-computer interaction technology,how to use natural and efficient interaction methods in the virtual environment has become a hot topic of research.Gesture is one of the most important communication methods of human beings,which can effectively express users'demands.In the past few decades,gesture-based interaction has made significant progress.This article focuses on the gesture interaction technology and discusses the definition and classification of gestures,input devices for gesture interaction,and gesture interaction recognition technology.The application of gesture interaction technology in virtual reality is studied,the existing problems in the current gesture interaction are summarized,and the future development is prospected.
基金supported by the National Natural Science Foundation of China(No.62122077)CAS Project for Young Scientists in Basic Research,China(No.YSBR-040).
文摘Knowledge plays a critical role in artificial intelligence.Recently,the extensive success of pre-trained language models(PLMs)has raised significant attention about how knowledge can be acquired,maintained,updated and used by language models.Despite the enormous amount of related studies,there is still a lack of a unified view of how knowledge circulates within language models throughout the learning,tuning,and application processes,which may prevent us from further understanding the connections between current progress or realizing existing limitations.In this survey,we revisit PLMs as knowledge-based systems by dividing the life circle of knowledge in PLMs into five critical periods,and investigating how knowledge circulates when it is built,maintained and used.To this end,we systematically review existing studies of each period of the knowledge life cycle,summarize the main challenges and current limitations,and discuss future directions.
文摘A new ontology-based question expansion （OBQE） method is proposed for question similarity calculation in a frequently asked question （FAQ） answering system. Traditional question similarity calculation methods use ＂word＂ to compose question vector, that the semantic relations between words are ignored. OBQE takes the relation as an important part. The process of the new system is：① to build two-layered domain ontology referring to WordNet and domain corpse;② to expand question trunks into domain cases;③ to use domain case composed vector to calculate question similarity. The experimental result shows that the performance of question similarity calculation with OBQE is being improved.
文摘The input of a network is the key problem for Chinese word sense disambiguation utilizing the neural network. This paper presents an input model of the neural network that calculates the mutual information between contextual words and the ambiguous word by using statistical methodology and taking the contextual words of a certain number beside the ambiguous word according to (-M,+N).The experiment adopts triple-layer BP Neural Network model and proves how the size of a training set and the value of Mand Naffect the performance of the Neural Network Model. The experimental objects are six pseudowords owning three word-senses constructed according to certain principles. The tested accuracy of our approach on a closed-corpus reaches 90.31%, and 89.62% on an open-corpus. The experiment proves that the Neural Network Model has a good performance on Word Sense Disambiguation.
