The advent of the Age of Information brings about bright prospects to Network-based Language Learning(NBLL).The thesis adopts the Engagement Theory as guided principles.The purpose is to use the novel NBLL model effec...The advent of the Age of Information brings about bright prospects to Network-based Language Learning(NBLL).The thesis adopts the Engagement Theory as guided principles.The purpose is to use the novel NBLL model effectively with the help of modern technology especially in less-developed areas.This thesis focuses on network-based experimental study.The research shows that the students under NBLL environment have cultivated the capabilities in information collection,computer operation,and information evaluation,as well as the abilities in problem solving,reasoning with criticism,and cooperating with others.展开更多
目的利用高分辨质谱鉴定银丹心脑通软胶囊的化学成分,与网络药理学研究结合,探讨银丹心脑通软胶囊“心脑同治”的活性成分及其潜在分子作用机制。方法基于UHPLC Q-Exactive Plus Orbitrap HRMS鉴定出的银丹心脑通软胶囊化学成分;通过TC...目的利用高分辨质谱鉴定银丹心脑通软胶囊的化学成分,与网络药理学研究结合,探讨银丹心脑通软胶囊“心脑同治”的活性成分及其潜在分子作用机制。方法基于UHPLC Q-Exactive Plus Orbitrap HRMS鉴定出的银丹心脑通软胶囊化学成分;通过TCMSP和SwissADME数据库,以口服利用度≥30%、类药性≥0.18和胃肠道吸收得分为“High”、类药性至少通过3个“Yes”来筛选活性成分,再检索活性成分的潜在作用靶点;通过OMIM、DisGeNET、GeneCards、TTD和PharmGKB数据库获取与心脑血管疾病相关靶基因。使用Venny软件获得两者的交集靶点,采用Cytoscape3.9.1分析软件结合STRING数据库对交集靶点进行蛋白互作网络分析和“药物-活性成分-靶点-疾病”网络构建,确定核心成分与靶点。利用DAVID数据库对银丹心脑通软胶囊治疗心脑血管疾病的潜在靶基因进行基因本体(GO)分析及京都基因与基因组百科全书富集分析(KEGG)预测其作用机制。最后将度值排名前5的靶点与主要活性成分进行分子对接模拟以验证网络药理学结果。结果通过UHPLC Q-Exactive Plus Orbitrap HRMS技术鉴定出银丹心脑通软胶囊中82个化学成分,主要包括黄酮类、有机酸类、菲醌类和二萜内酯类化合物;经TCMSP、SwissADME数据库筛选得到活性成分34个,如槲皮素、异樱花亭、二氢丹参酮I等,相对应的靶点389个,进一步筛选出治疗心脑血管疾病相关的潜在靶基因249个。GO和KEGG富集分析显示,银丹心脑通软胶囊的活性成分可能主要通过脂质与动脉粥样硬化通路、流体剪切应力与动脉粥样硬化、AGE-RAGE、IL-17、PI3K-Akt、HIF-1、TNF等通路来发挥治疗心脑血管疾病的作用。分子对接证实STAT3、HSP90AA1等与二氢丹参酮I、山柰酚、木犀草素等具有较高的亲和力。结论本研究初步预测了银丹心脑通软胶囊“心脑同治”其作用机制与动脉粥样硬化、炎症因子、细胞凋亡和氧化应激等方面有关,为后续作用机制的深度分析及临床应用提供科学依据。展开更多
EMS诱变育种是作物种质创新的重要手段,利用反向遗传学手段TILLING(targeting induced local lesions in genomes)筛选EMS突变体,是研究基因功能与获得优良种质的有效手段之一。本研究采用基于HRM,即高分辨率熔解曲线分析技术的TILLING...EMS诱变育种是作物种质创新的重要手段,利用反向遗传学手段TILLING(targeting induced local lesions in genomes)筛选EMS突变体,是研究基因功能与获得优良种质的有效手段之一。本研究采用基于HRM,即高分辨率熔解曲线分析技术的TILLING筛选方法(HRM-TILLING)进行突变体筛选技术体系的探索,通过设计不同大小扩增片段引物及Mg^(2+)浓度梯度,比较了不同条件下的HRM筛选效果,结果表明当扩增片段长度为150 bp,Mg^(2+)浓度为3.0 mmol/L时,可以有效区分DNA 16倍混合池中ARF7A基因存在碱基差异的两种茄子(Solanum melongena L.)材料,建立了一套基于HRM的茄子EMS突变体TILLING技术的筛选方法。以含有2000个M2株系的茄子(EP26)EMS突变体库为材料,筛选出1个ARF7A基因和2个Pad-1基因突变体株系。本研究建立的筛选技术体系可以快速、高效地筛选茄子EMS突变体,所筛选的突变体为进一步验证、获取茄子单性结实种质及功能基因组学的研究提供研究材料。展开更多
A network-based Virtual Private Network(VPN)architecture by using fundamental routing mechanism is proposed.This network is a virtual overlay network based on the relay of IP-in-IP tunneling of virtual routing modules...A network-based Virtual Private Network(VPN)architecture by using fundamental routing mechanism is proposed.This network is a virtual overlay network based on the relay of IP-in-IP tunneling of virtual routing modules.The packet format employs the encapsulation of IPSec ESP(Encapsulating Security Payload),an impact path code and an extended DS(Differentiated Services)code to support multi-path routing and QoS.Comparing with other models of VPN,this network system can be deployed in the current network with little investment,and it is easy to implement.The simulation result shows its performance is better than the traditional VPN system of black box mode.展开更多
An efficient and accurate prediction of a precise tidal level in estuaries and coastal areas is indispensable for the management and decision-making of human activity in the field wok of marine engineering. The variat...An efficient and accurate prediction of a precise tidal level in estuaries and coastal areas is indispensable for the management and decision-making of human activity in the field wok of marine engineering. The variation of the tidal level is a time-varying process. The time-varying factors including interference from the external environment that cause the change of tides are fairly complicated. Furthermore, tidal variations are affected not only by periodic movement of celestial bodies but also by time-varying interference from the external environment. Consequently, for the efficient and precise tidal level prediction, a neuro-fuzzy hybrid technology based on the combination of harmonic analysis and adaptive network-based fuzzy inference system（ANFIS）model is utilized to construct a precise tidal level prediction system, which takes both advantages of the harmonic analysis method and the ANFIS network. The proposed prediction model is composed of two modules： the astronomical tide module caused by celestial bodies’ movement and the non-astronomical tide module caused by various meteorological and other environmental factors. To generate a fuzzy inference system（FIS） structure,three approaches which include grid partition（GP）, fuzzy c-means（FCM） and sub-clustering（SC） are used in the ANFIS network constructing process. Furthermore, to obtain the optimal ANFIS based prediction model, large numbers of simulation experiments are implemented for each FIS generating approach. In this tidal prediction study, the optimal ANFIS model is used to predict the non-astronomical tide module, while the conventional harmonic analysis model is used to predict the astronomical tide module. The final prediction result is performed by combining the estimation outputs of the harmonious analysis model and the optimal ANFIS model. To demonstrate the applicability and capability of the proposed novel prediction model, measured tidal level samples of Fort Pulaski tidal station are selected as the testing database. Simulation and experimental results confirm that the proposed prediction approach can achieve precise predictions for the tidal level with high accuracy, satisfactory convergence and stability.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
This paper investigates the remote tracking control problem of Network-based Agents with communication delays existing in both forward and feedback communication channels.A networked predictive tracking controller is ...This paper investigates the remote tracking control problem of Network-based Agents with communication delays existing in both forward and feedback communication channels.A networked predictive tracking controller is proposed to compensate the negative effects caused by bilateral time-delays in a wireless network.Furthermore,the problem of consecutive data loss in the feedback channel is solved using aforementioned controller,where lateral movement perturbations are introduced.Simulations and experiments are provided for several cases,which verify the realizability and effectiveness of the proposed controller.展开更多
A parallel neural network-based controller （PNNC） is presented for the motion control of underwater vehicles in this paper. It consists of a real-time part, a self-learning part and a desired-state programmer, and i...A parallel neural network-based controller （PNNC） is presented for the motion control of underwater vehicles in this paper. It consists of a real-time part, a self-learning part and a desired-state programmer, and it is different from normal adaptive neural network controller in structure. Owing to the introduction of the self-learning part, on-line learning can be performed without sample data in several sample periods, resulting in high learning speed of the controller and good control performance. The desired-state programmer is utilized to obtain better learning samples of the neural network to keep the stability of the controller. The developed controller is applied to the 4-degree of freedom control of the AUV “IUV- IV” and is successful on the simulation platform. The control performance is also compared with that of neural network controller with different structures such as normal adaptive neural network and different learning methods. Current effects and surge velocity control are also included to demonstrate the controller＇ s performance. It is shown that the PNNC has a great possibility to solve the problems in the control system design of underwater vehicles.展开更多
In order to make equipment run safely, economically and continuously, some new maintenance models were put forward to improve the equipment after-sale maintenance service, such as E-maintenance, third-party maintenanc...In order to make equipment run safely, economically and continuously, some new maintenance models were put forward to improve the equipment after-sale maintenance service, such as E-maintenance, third-party maintenance, etc. To certain extent, the models solved the problem of the distance between the manufacturer and customer and the dispersion of the maintenance technologies, however, those resources are still widely distributed and do not collaborate efficiently. In this paper, a network-based collaborative maintenance service model was proposed for after-sales equipment to solve the problem of maintenance resources integration. Concretely, equipment designers, maintainers, spare parts suppliers and maintenance experts were grouped together to establish dynamic alliance. The leader of the alliance is the manufacturer under guaranty period or equipment user exceeding the guaranty period. The process of maintenance service was divided into three stages which are fault diagnosis, maintenance decision and maintenance implementation. The sub-alliances were established to carry out maintenance work at each stage. In addition, the business process of network-based collaborative maintenance was analyzed and collaborative business system for equipment＇s after-sales collaborative maintenance service was designed. In the end, an informational economics model of network-based collaborative maintenance was established to demonstrate the effectiveness of this maintenance model.展开更多
文摘The advent of the Age of Information brings about bright prospects to Network-based Language Learning(NBLL).The thesis adopts the Engagement Theory as guided principles.The purpose is to use the novel NBLL model effectively with the help of modern technology especially in less-developed areas.This thesis focuses on network-based experimental study.The research shows that the students under NBLL environment have cultivated the capabilities in information collection,computer operation,and information evaluation,as well as the abilities in problem solving,reasoning with criticism,and cooperating with others.
文摘目的利用高分辨质谱鉴定银丹心脑通软胶囊的化学成分,与网络药理学研究结合,探讨银丹心脑通软胶囊“心脑同治”的活性成分及其潜在分子作用机制。方法基于UHPLC Q-Exactive Plus Orbitrap HRMS鉴定出的银丹心脑通软胶囊化学成分;通过TCMSP和SwissADME数据库,以口服利用度≥30%、类药性≥0.18和胃肠道吸收得分为“High”、类药性至少通过3个“Yes”来筛选活性成分,再检索活性成分的潜在作用靶点;通过OMIM、DisGeNET、GeneCards、TTD和PharmGKB数据库获取与心脑血管疾病相关靶基因。使用Venny软件获得两者的交集靶点,采用Cytoscape3.9.1分析软件结合STRING数据库对交集靶点进行蛋白互作网络分析和“药物-活性成分-靶点-疾病”网络构建,确定核心成分与靶点。利用DAVID数据库对银丹心脑通软胶囊治疗心脑血管疾病的潜在靶基因进行基因本体(GO)分析及京都基因与基因组百科全书富集分析(KEGG)预测其作用机制。最后将度值排名前5的靶点与主要活性成分进行分子对接模拟以验证网络药理学结果。结果通过UHPLC Q-Exactive Plus Orbitrap HRMS技术鉴定出银丹心脑通软胶囊中82个化学成分,主要包括黄酮类、有机酸类、菲醌类和二萜内酯类化合物;经TCMSP、SwissADME数据库筛选得到活性成分34个,如槲皮素、异樱花亭、二氢丹参酮I等,相对应的靶点389个,进一步筛选出治疗心脑血管疾病相关的潜在靶基因249个。GO和KEGG富集分析显示,银丹心脑通软胶囊的活性成分可能主要通过脂质与动脉粥样硬化通路、流体剪切应力与动脉粥样硬化、AGE-RAGE、IL-17、PI3K-Akt、HIF-1、TNF等通路来发挥治疗心脑血管疾病的作用。分子对接证实STAT3、HSP90AA1等与二氢丹参酮I、山柰酚、木犀草素等具有较高的亲和力。结论本研究初步预测了银丹心脑通软胶囊“心脑同治”其作用机制与动脉粥样硬化、炎症因子、细胞凋亡和氧化应激等方面有关,为后续作用机制的深度分析及临床应用提供科学依据。
基金Supported by the National Natural Scjence Foun-dation of China(90104029)
文摘A network-based Virtual Private Network(VPN)architecture by using fundamental routing mechanism is proposed.This network is a virtual overlay network based on the relay of IP-in-IP tunneling of virtual routing modules.The packet format employs the encapsulation of IPSec ESP(Encapsulating Security Payload),an impact path code and an extended DS(Differentiated Services)code to support multi-path routing and QoS.Comparing with other models of VPN,this network system can be deployed in the current network with little investment,and it is easy to implement.The simulation result shows its performance is better than the traditional VPN system of black box mode.
基金The National Natural Science Foundation of China under contract No.51379002the Fundamental Research Funds for the Central Universities of China under contract Nos 3132016322 and 3132016314the Applied Basic Research Project Fund of the Chinese Ministry of Transport of China under contract No.2014329225010
文摘An efficient and accurate prediction of a precise tidal level in estuaries and coastal areas is indispensable for the management and decision-making of human activity in the field wok of marine engineering. The variation of the tidal level is a time-varying process. The time-varying factors including interference from the external environment that cause the change of tides are fairly complicated. Furthermore, tidal variations are affected not only by periodic movement of celestial bodies but also by time-varying interference from the external environment. Consequently, for the efficient and precise tidal level prediction, a neuro-fuzzy hybrid technology based on the combination of harmonic analysis and adaptive network-based fuzzy inference system（ANFIS）model is utilized to construct a precise tidal level prediction system, which takes both advantages of the harmonic analysis method and the ANFIS network. The proposed prediction model is composed of two modules： the astronomical tide module caused by celestial bodies’ movement and the non-astronomical tide module caused by various meteorological and other environmental factors. To generate a fuzzy inference system（FIS） structure,three approaches which include grid partition（GP）, fuzzy c-means（FCM） and sub-clustering（SC） are used in the ANFIS network constructing process. Furthermore, to obtain the optimal ANFIS based prediction model, large numbers of simulation experiments are implemented for each FIS generating approach. In this tidal prediction study, the optimal ANFIS model is used to predict the non-astronomical tide module, while the conventional harmonic analysis model is used to predict the astronomical tide module. The final prediction result is performed by combining the estimation outputs of the harmonious analysis model and the optimal ANFIS model. To demonstrate the applicability and capability of the proposed novel prediction model, measured tidal level samples of Fort Pulaski tidal station are selected as the testing database. Simulation and experimental results confirm that the proposed prediction approach can achieve precise predictions for the tidal level with high accuracy, satisfactory convergence and stability.
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supported in part by the National Natural Science Foundation of China(61333003,61690212)
文摘This paper investigates the remote tracking control problem of Network-based Agents with communication delays existing in both forward and feedback communication channels.A networked predictive tracking controller is proposed to compensate the negative effects caused by bilateral time-delays in a wireless network.Furthermore,the problem of consecutive data loss in the feedback channel is solved using aforementioned controller,where lateral movement perturbations are introduced.Simulations and experiments are provided for several cases,which verify the realizability and effectiveness of the proposed controller.
文摘A parallel neural network-based controller （PNNC） is presented for the motion control of underwater vehicles in this paper. It consists of a real-time part, a self-learning part and a desired-state programmer, and it is different from normal adaptive neural network controller in structure. Owing to the introduction of the self-learning part, on-line learning can be performed without sample data in several sample periods, resulting in high learning speed of the controller and good control performance. The desired-state programmer is utilized to obtain better learning samples of the neural network to keep the stability of the controller. The developed controller is applied to the 4-degree of freedom control of the AUV “IUV- IV” and is successful on the simulation platform. The control performance is also compared with that of neural network controller with different structures such as normal adaptive neural network and different learning methods. Current effects and surge velocity control are also included to demonstrate the controller＇ s performance. It is shown that the PNNC has a great possibility to solve the problems in the control system design of underwater vehicles.
基金supported by National Natural Science Foundation of China (Grant No. 70301012)National Hi-tech Research and Development Program of China (863 Program, Grant No. 2006AA04Z369-1)Innovative Talent Project of the Third Stage of "211" Project, Chongqing University, China (Grant No. S-09107)
文摘In order to make equipment run safely, economically and continuously, some new maintenance models were put forward to improve the equipment after-sale maintenance service, such as E-maintenance, third-party maintenance, etc. To certain extent, the models solved the problem of the distance between the manufacturer and customer and the dispersion of the maintenance technologies, however, those resources are still widely distributed and do not collaborate efficiently. In this paper, a network-based collaborative maintenance service model was proposed for after-sales equipment to solve the problem of maintenance resources integration. Concretely, equipment designers, maintainers, spare parts suppliers and maintenance experts were grouped together to establish dynamic alliance. The leader of the alliance is the manufacturer under guaranty period or equipment user exceeding the guaranty period. The process of maintenance service was divided into three stages which are fault diagnosis, maintenance decision and maintenance implementation. The sub-alliances were established to carry out maintenance work at each stage. In addition, the business process of network-based collaborative maintenance was analyzed and collaborative business system for equipment＇s after-sales collaborative maintenance service was designed. In the end, an informational economics model of network-based collaborative maintenance was established to demonstrate the effectiveness of this maintenance model.
