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
Ongoing research is described that is focused upon modelling the space base information network and simulating its behaviours: simulation of spaced based communications and networking project. Its objective is to dem...Ongoing research is described that is focused upon modelling the space base information network and simulating its behaviours: simulation of spaced based communications and networking project. Its objective is to demonstrate the feasibility of producing a tool that can provide a performance evaluation of various eonstellation access techniques and routing policies. The architecture and design of the simulation system are explored. The algorithm of data routing and instrument scheduling in this project is described. Besides these, the key methodologies of simulating the inter-satellite link features in the data transmissions are also discussed. The performance of both instrument scheduling algorithm and routing schemes is evaluated and analyzed through extensive simulations under a typical scenario.展开更多
In this paper,a novel control structure called feedback scheduling of model-based networked control systems is proposed to cope with a flexible network load and resource constraints.The state update time is adjusted a...In this paper,a novel control structure called feedback scheduling of model-based networked control systems is proposed to cope with a flexible network load and resource constraints.The state update time is adjusted according to the real-time network congestion situation.State observer is used under the situation where the state of the controlled plant could not be acquired.The stability criterion of the proposed structure is proved with time-varying state update time.On the basis of the stability of the novel system structure,the compromise between the control performance and the network utilization is realized by using feedback scheduler. Examples are provided to show the advantage of the proposed control structure.展开更多
The optimization of network performance in a movement-assisted data gathering scheme was studied by analyzing the energy consumption of wireless sensor network with node uniform distribution. A theoretically analytica...The optimization of network performance in a movement-assisted data gathering scheme was studied by analyzing the energy consumption of wireless sensor network with node uniform distribution. A theoretically analytical method for avoiding energy hole was proposed. It is proved that if the densities of sensor nodes working at the same time are alternate between dormancy and work with non-uniform node distribution. The efficiency of network can increase by several times and the residual energy of network is nearly zero when the network lifetime ends.展开更多
Dynamic spectrum access technologies based on Cognitive Radio(CR) is under intensive research carried out by the wireless communication society and is expected to solve the problem of spectrum scarcity.However,most en...Dynamic spectrum access technologies based on Cognitive Radio(CR) is under intensive research carried out by the wireless communication society and is expected to solve the problem of spectrum scarcity.However,most enabling technologies related to dynamic spectrum access are con-sidered individually.In this paper,we consider these key technologies jointly and introduce a new implementation scheme for a Dynamic Spectrum Access Network Based on Cognitive Radio(DSAN-BCR).We start with a flexible hardware platform for DSAN-BCR,as well as a flexible protocol structure that dominates the operation of DSAN-BCR.We then focus on the state of the art of key technologies such as spectrum sensing,spectrum resources management,dynamic spectrum access,and routing that are below the network layer in DSAN-BCR,as well as the development of technologies related to higher layers.Last but not the least,we analyze the challenges confronted by these men-tioned technologies in DSAN-BCR,and give the perspectives on the future development of these technologies.The DSAN-BCR introduced is expected to provide a system level guidance to alleviate the problem of spectrum scarcity.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
The sensor virus is a serious threat,as an attacker can simply send a single packet to compromise the entire sensor network.Epidemics become drastic with link additions among sensors when the small world phenomena occ...The sensor virus is a serious threat,as an attacker can simply send a single packet to compromise the entire sensor network.Epidemics become drastic with link additions among sensors when the small world phenomena occur.Two immunization strategies,uniform immunization and temporary immunization,are conducted on small worlds of tree-based wireless sensor networks to combat the sensor viruses.With the former strategy,the infection extends exponentially,although the immunization effectively reduces the contagion speed.With the latter strategy,recurrent contagion oscillations occur in the small world when the spatial-temporal dynamics of the epidemic are considered.The oscillations come from the small-world structure and the temporary immunization.Mathematical analyses on the small world of the Cayley tree are presented to reveal the epidemic dynamics with the two immunization strategies.展开更多
Ensemble learning for anomaly detection of data structured into a complex network has been barely studied due to the inconsistent performance of complex network characteristics and the lack of inherent objective funct...Ensemble learning for anomaly detection of data structured into a complex network has been barely studied due to the inconsistent performance of complex network characteristics and the lack of inherent objective function. We propose the intuitionistic fuzzy set(IFS)-based anomaly detection, a new two-phase ensemble method for anomaly detection based on IFS, and apply it to the abnormal behavior detection problem in temporal complex networks.Firstly, it constructs the IFS of a single network characteristic, which quantifies the degree of membership,non-membership and hesitation of each network characteristic to the defined linguistic variables so that makes the unuseful or noise characteristics become part of the detection. To build an objective intuitionistic fuzzy relationship, we propose a Gaussian distribution-based membership function which gives a variable hesitation degree. Then, for the fuzzification of multiple network characteristics, the intuitionistic fuzzy weighted geometric operator is adopted to fuse multiple IFSs and to avoid the inconsistence of multiple characteristics. Finally, the score function and precision function are used to sort the fused IFS. Finally, we carry out extensive experiments on several complex network datasets for anomaly detection, and the results demonstrate the superiority of our method to state-of-the-art approaches, validating the effectiveness of our method.展开更多
In this paper, the control of a two-time-scale plant, where the sensor is connected to a linear controller/ actuator via a network is addressed. The slow and fast systems of singularly perturbed systems are used to pr...In this paper, the control of a two-time-scale plant, where the sensor is connected to a linear controller/ actuator via a network is addressed. The slow and fast systems of singularly perturbed systems are used to produce an estimate of the plant state behavior between transmission times, by which one can reduce the usage of the network. The approximate solutions of the whole systems are derived and it is shown that the whole systems via the network control are generally asymptotically stable as long as their slow and fast systems are both stable. These results are also extended to the case of network delay.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 modu...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
The dynamic working process of 52SFZ-140-207B type of hydraulic bumper isanalyzed. The modeling method using architecture-based neural networks is introduced. Using thismodeling method, the dynamic model of the hydrau...The dynamic working process of 52SFZ-140-207B type of hydraulic bumper isanalyzed. The modeling method using architecture-based neural networks is introduced. Using thismodeling method, the dynamic model of the hydraulic bumper is established; Based on this model thestructural parameters of the hydraulic bumper are optimized with Genetic algorithm. The result showsthat the performance of the dynamic model is close to that of the hydraulic bumper, and the dynamicperformance of the hydraulic bumper is improved through parameter optimization.展开更多
The traffic explosion and the rising of diverse requirements lead to many challenges for traditional mobile network architecture on flexibility, scalability, and deployability. To meet new requirements in the 5 G era,...The traffic explosion and the rising of diverse requirements lead to many challenges for traditional mobile network architecture on flexibility, scalability, and deployability. To meet new requirements in the 5 G era, service based architecture is introduced into mobile networks. The monolithic network elements(e.g., MME, PGW, etc.) are split into smaller network functions to provide customized services. However, the management and deployment of network functions in service based 5 G core network are still big challenges. In this paper, we propose a novel management architecture for 5 G service based core network based on NFV and SDN. Combined with SDN, NFV and edge computing, the proposed framework can provide distributed and on-demand deployment of network functions, service guaranteed network slicing, flexible orchestration of network functions and optimal workload allocation. Simulations are conducted to show that the proposed framework and algorithm are effective in terms of reducing network operating cost.展开更多
In previous researches on a model-based diagnostic system, the components are assumed mutually independent. Howerver , the assumption is not always the case because the information about whether a component is faulty ...In previous researches on a model-based diagnostic system, the components are assumed mutually independent. Howerver , the assumption is not always the case because the information about whether a component is faulty or not usually influences our knowledge about other components. Some experts may draw such a conclusion that 'if component m 1 is faulty, then component m 2 may be faulty too'. How can we use this experts' knowledge to aid the diagnosis? Based on Kohlas's probabilistic assumption-based reasoning method, we use Bayes networks to solve this problem. We calculate the posterior fault probability of the components in the observation state. The result is reasonable and reflects the effectiveness of the experts' knowledge.展开更多
Swarm intelligence inspired by the social behavior of ants boasts a number of attractive features, including adaptation, robustness and distributed, decentralized nature, which are well suited for routing in modern co...Swarm intelligence inspired by the social behavior of ants boasts a number of attractive features, including adaptation, robustness and distributed, decentralized nature, which are well suited for routing in modern communication networks. This paper describes an adaptive swarm-based routing algorithm that increases convergence speed, reduces routing instabilities and oscillations by using a novel variation of reinforcement learning and a technique called momentum.Experiment on the dynamic network showed that adaptive swarm-based routing learns the optimum routing in terms of convergence speed and average packet latency.展开更多
Proper quality planning of limestone raw materials is an essential job of maintaining desired feed in cement plant. Rock-type identification is an integrated part of quality planning for limestone mine. In this paper,...Proper quality planning of limestone raw materials is an essential job of maintaining desired feed in cement plant. Rock-type identification is an integrated part of quality planning for limestone mine. In this paper, a computer vision-based rock-type classification algorithm is proposed for fast and reliable identification without human intervention. A laboratory scale vision-based model was developed using probabilistic neural network(PNN) where color histogram features are used as input. The color image histogram-based features that include weighted mean, skewness and kurtosis features are extracted for all three color space red, green, and blue. A total nine features are used as input for the PNN classification model. The smoothing parameter for PNN model is selected judicially to develop an optimal or close to the optimum classification model. The developed PPN is validated using the test data set and results reveal that the proposed vision-based model can perform satisfactorily for classifying limestone rocktypes. Overall the error of mis-classification is below 6%. When compared with other three classification algorithms, it is observed that the proposed method performs substantially better than all three classification algorithms.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
Node localization is commonly employed in wireless networks. For example, it is used to improve routing and enhance security. Localization algorithms can be classified as range-free or range-based. Range-based algorit...Node localization is commonly employed in wireless networks. For example, it is used to improve routing and enhance security. Localization algorithms can be classified as range-free or range-based. Range-based algorithms use location metrics such as ToA, TDoA, RSS, and AoA to estimate the distance between two nodes. Proximity sensing between nodes is typically the basis for range-free algorithms. A tradeoff exists since range-based algorithms are more accurate but also more complex. However, in applications such as target tracking, localization accuracy is very important. In this paper, we propose a new range-based algorithm which is based on the density-based outlier detection algorithm (DBOD) from data mining. It requires selection of the K-nearest neighbours (KNN). DBOD assigns density values to each point used in the location estimation. The mean of these densities is calculated and those points having a density larger than the mean are kept as candidate points. Different performance measures are used to compare our approach with the linear least squares (LLS) and weighted linear least squares based on singular value decomposition (WLS-SVD) algorithms. It is shown that the proposed algorithm performs better than these algorithms even when the anchor geometry about an unlocalized node is poor.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
Recent days,Image retrieval has become a tedious process as the image database has grown very larger.The introduction of Machine Learning(ML)and Deep Learning(DL)made this process more comfortable.In these,the pair-wi...Recent days,Image retrieval has become a tedious process as the image database has grown very larger.The introduction of Machine Learning(ML)and Deep Learning(DL)made this process more comfortable.In these,the pair-wise label similarity is used tofind the matching images from the database.But this method lacks of limited propose code and weak execution of misclassified images.In order to get-rid of the above problem,a novel triplet based label that incorporates context-spatial similarity measure is proposed.A Point Attention Based Triplet Network(PABTN)is introduced to study propose code that gives maximum discriminative ability.To improve the performance of ranking,a corre-lating resolutions for the classification,triplet labels based onfindings,a spatial-attention mechanism and Region Of Interest(ROI)and small trial information loss containing a new triplet cross-entropy loss are used.From the experimental results,it is shown that the proposed technique exhibits better results in terms of mean Reciprocal Rank(mRR)and mean Average Precision(mAP)in the CIFAR-10 and NUS-WIPE datasets.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.
基金This project was supported by the National "863" High-Tech Research and Development Program of China(2002AA7170)
文摘Ongoing research is described that is focused upon modelling the space base information network and simulating its behaviours: simulation of spaced based communications and networking project. Its objective is to demonstrate the feasibility of producing a tool that can provide a performance evaluation of various eonstellation access techniques and routing policies. The architecture and design of the simulation system are explored. The algorithm of data routing and instrument scheduling in this project is described. Besides these, the key methodologies of simulating the inter-satellite link features in the data transmissions are also discussed. The performance of both instrument scheduling algorithm and routing schemes is evaluated and analyzed through extensive simulations under a typical scenario.
文摘In this paper,a novel control structure called feedback scheduling of model-based networked control systems is proposed to cope with a flexible network load and resource constraints.The state update time is adjusted according to the real-time network congestion situation.State observer is used under the situation where the state of the controlled plant could not be acquired.The stability criterion of the proposed structure is proved with time-varying state update time.On the basis of the stability of the novel system structure,the compromise between the control performance and the network utilization is realized by using feedback scheduler. Examples are provided to show the advantage of the proposed control structure.
基金Project(60873081)supported by the National Natural Science Foundation of ChinaProject(NCET-10-0787)supported by Program for New Century Excellent Talents in UniversityProject(11JJ1012)supported by the Natural Science Foundation of Hunan Province,China
文摘The optimization of network performance in a movement-assisted data gathering scheme was studied by analyzing the energy consumption of wireless sensor network with node uniform distribution. A theoretically analytical method for avoiding energy hole was proposed. It is proved that if the densities of sensor nodes working at the same time are alternate between dormancy and work with non-uniform node distribution. The efficiency of network can increase by several times and the residual energy of network is nearly zero when the network lifetime ends.
文摘Dynamic spectrum access technologies based on Cognitive Radio(CR) is under intensive research carried out by the wireless communication society and is expected to solve the problem of spectrum scarcity.However,most enabling technologies related to dynamic spectrum access are con-sidered individually.In this paper,we consider these key technologies jointly and introduce a new implementation scheme for a Dynamic Spectrum Access Network Based on Cognitive Radio(DSAN-BCR).We start with a flexible hardware platform for DSAN-BCR,as well as a flexible protocol structure that dominates the operation of DSAN-BCR.We then focus on the state of the art of key technologies such as spectrum sensing,spectrum resources management,dynamic spectrum access,and routing that are below the network layer in DSAN-BCR,as well as the development of technologies related to higher layers.Last but not the least,we analyze the challenges confronted by these men-tioned technologies in DSAN-BCR,and give the perspectives on the future development of these technologies.The DSAN-BCR introduced is expected to provide a system level guidance to alleviate the problem of spectrum scarcity.
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The sensor virus is a serious threat,as an attacker can simply send a single packet to compromise the entire sensor network.Epidemics become drastic with link additions among sensors when the small world phenomena occur.Two immunization strategies,uniform immunization and temporary immunization,are conducted on small worlds of tree-based wireless sensor networks to combat the sensor viruses.With the former strategy,the infection extends exponentially,although the immunization effectively reduces the contagion speed.With the latter strategy,recurrent contagion oscillations occur in the small world when the spatial-temporal dynamics of the epidemic are considered.The oscillations come from the small-world structure and the temporary immunization.Mathematical analyses on the small world of the Cayley tree are presented to reveal the epidemic dynamics with the two immunization strategies.
基金Supported by the National Natural Science Foundation of China under Grant No 61671142the Fundamental Research Funds for the Central Universities under Grant No 02190022117021
文摘Ensemble learning for anomaly detection of data structured into a complex network has been barely studied due to the inconsistent performance of complex network characteristics and the lack of inherent objective function. We propose the intuitionistic fuzzy set(IFS)-based anomaly detection, a new two-phase ensemble method for anomaly detection based on IFS, and apply it to the abnormal behavior detection problem in temporal complex networks.Firstly, it constructs the IFS of a single network characteristic, which quantifies the degree of membership,non-membership and hesitation of each network characteristic to the defined linguistic variables so that makes the unuseful or noise characteristics become part of the detection. To build an objective intuitionistic fuzzy relationship, we propose a Gaussian distribution-based membership function which gives a variable hesitation degree. Then, for the fuzzification of multiple network characteristics, the intuitionistic fuzzy weighted geometric operator is adopted to fuse multiple IFSs and to avoid the inconsistence of multiple characteristics. Finally, the score function and precision function are used to sort the fused IFS. Finally, we carry out extensive experiments on several complex network datasets for anomaly detection, and the results demonstrate the superiority of our method to state-of-the-art approaches, validating the effectiveness of our method.
基金the National Natural Science Foundation of China (No. 10671069, 60674046)
文摘In this paper, the control of a two-time-scale plant, where the sensor is connected to a linear controller/ actuator via a network is addressed. The slow and fast systems of singularly perturbed systems are used to produce an estimate of the plant state behavior between transmission times, by which one can reduce the usage of the network. The approximate solutions of the whole systems are derived and it is shown that the whole systems via the network control are generally asymptotically stable as long as their slow and fast systems are both stable. These results are also extended to the case of network delay.
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Supported by the National Natural Science Foundation of China (No. 60671049, 61172168)and Graduate Innovation Project of Heilongjiang (No. YJSCX2011-034HLI)
文摘The dynamic working process of 52SFZ-140-207B type of hydraulic bumper isanalyzed. The modeling method using architecture-based neural networks is introduced. Using thismodeling method, the dynamic model of the hydraulic bumper is established; Based on this model thestructural parameters of the hydraulic bumper are optimized with Genetic algorithm. The result showsthat the performance of the dynamic model is close to that of the hydraulic bumper, and the dynamicperformance of the hydraulic bumper is improved through parameter optimization.
基金supported by China Ministry of Education-CMCC Research Fund Project No.MCM20160104National Science and Technology Major Project No.No.2018ZX03001016+1 种基金Beijing Municipal Science and technology Commission Research Fund Project No.Z171100005217001Fundamental Research Funds for Central Universities NO.2018RC06
文摘The traffic explosion and the rising of diverse requirements lead to many challenges for traditional mobile network architecture on flexibility, scalability, and deployability. To meet new requirements in the 5 G era, service based architecture is introduced into mobile networks. The monolithic network elements(e.g., MME, PGW, etc.) are split into smaller network functions to provide customized services. However, the management and deployment of network functions in service based 5 G core network are still big challenges. In this paper, we propose a novel management architecture for 5 G service based core network based on NFV and SDN. Combined with SDN, NFV and edge computing, the proposed framework can provide distributed and on-demand deployment of network functions, service guaranteed network slicing, flexible orchestration of network functions and optimal workload allocation. Simulations are conducted to show that the proposed framework and algorithm are effective in terms of reducing network operating cost.
文摘In previous researches on a model-based diagnostic system, the components are assumed mutually independent. Howerver , the assumption is not always the case because the information about whether a component is faulty or not usually influences our knowledge about other components. Some experts may draw such a conclusion that 'if component m 1 is faulty, then component m 2 may be faulty too'. How can we use this experts' knowledge to aid the diagnosis? Based on Kohlas's probabilistic assumption-based reasoning method, we use Bayes networks to solve this problem. We calculate the posterior fault probability of the components in the observation state. The result is reasonable and reflects the effectiveness of the experts' knowledge.
文摘Swarm intelligence inspired by the social behavior of ants boasts a number of attractive features, including adaptation, robustness and distributed, decentralized nature, which are well suited for routing in modern communication networks. This paper describes an adaptive swarm-based routing algorithm that increases convergence speed, reduces routing instabilities and oscillations by using a novel variation of reinforcement learning and a technique called momentum.Experiment on the dynamic network showed that adaptive swarm-based routing learns the optimum routing in terms of convergence speed and average packet latency.
文摘Proper quality planning of limestone raw materials is an essential job of maintaining desired feed in cement plant. Rock-type identification is an integrated part of quality planning for limestone mine. In this paper, a computer vision-based rock-type classification algorithm is proposed for fast and reliable identification without human intervention. A laboratory scale vision-based model was developed using probabilistic neural network(PNN) where color histogram features are used as input. The color image histogram-based features that include weighted mean, skewness and kurtosis features are extracted for all three color space red, green, and blue. A total nine features are used as input for the PNN classification model. The smoothing parameter for PNN model is selected judicially to develop an optimal or close to the optimum classification model. The developed PPN is validated using the test data set and results reveal that the proposed vision-based model can perform satisfactorily for classifying limestone rocktypes. Overall the error of mis-classification is below 6%. When compared with other three classification algorithms, it is observed that the proposed method performs substantially better than all three classification algorithms.
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.
文摘Node localization is commonly employed in wireless networks. For example, it is used to improve routing and enhance security. Localization algorithms can be classified as range-free or range-based. Range-based algorithms use location metrics such as ToA, TDoA, RSS, and AoA to estimate the distance between two nodes. Proximity sensing between nodes is typically the basis for range-free algorithms. A tradeoff exists since range-based algorithms are more accurate but also more complex. However, in applications such as target tracking, localization accuracy is very important. In this paper, we propose a new range-based algorithm which is based on the density-based outlier detection algorithm (DBOD) from data mining. It requires selection of the K-nearest neighbours (KNN). DBOD assigns density values to each point used in the location estimation. The mean of these densities is calculated and those points having a density larger than the mean are kept as candidate points. Different performance measures are used to compare our approach with the linear least squares (LLS) and weighted linear least squares based on singular value decomposition (WLS-SVD) algorithms. It is shown that the proposed algorithm performs better than these algorithms even when the anchor geometry about an unlocalized node is poor.
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.
文摘Recent days,Image retrieval has become a tedious process as the image database has grown very larger.The introduction of Machine Learning(ML)and Deep Learning(DL)made this process more comfortable.In these,the pair-wise label similarity is used tofind the matching images from the database.But this method lacks of limited propose code and weak execution of misclassified images.In order to get-rid of the above problem,a novel triplet based label that incorporates context-spatial similarity measure is proposed.A Point Attention Based Triplet Network(PABTN)is introduced to study propose code that gives maximum discriminative ability.To improve the performance of ranking,a corre-lating resolutions for the classification,triplet labels based onfindings,a spatial-attention mechanism and Region Of Interest(ROI)and small trial information loss containing a new triplet cross-entropy loss are used.From the experimental results,it is shown that the proposed technique exhibits better results in terms of mean Reciprocal Rank(mRR)and mean Average Precision(mAP)in the CIFAR-10 and NUS-WIPE datasets.