1. IntroductionHumans have the ability (or competence) to think logically, and this is an undeniable fact. However,what this ability consists in is a difficult question. It might be said that logical ability consists ...1. IntroductionHumans have the ability (or competence) to think logically, and this is an undeniable fact. However,what this ability consists in is a difficult question. It might be said that logical ability consists in theknowledge of a set of logic rules. But what are those logic rules? For centuries logicians have devel-展开更多
Damage detection in structures is performed via vibra-tion based structural identification. Modal information, such as fre-quencies and mode shapes, are widely used for structural dama-ge detection to indicate the hea...Damage detection in structures is performed via vibra-tion based structural identification. Modal information, such as fre-quencies and mode shapes, are widely used for structural dama-ge detection to indicate the health conditions of civil structures.The deep learning algorithm that works on a multiple layer neuralnetwork model termed as deep autoencoder is proposed to learnthe relationship between the modal information and structural stiff-ness parameters. This is achieved via dimension reduction of themodal information feature and a non-linear regression against thestructural stiffness parameters. Numerical tests on a symmetri-cal steel frame model are conducted to generate the data for thetraining and validation, and to demonstrate the efficiency of theproposed approach for vibration based structural damage detec-tion.展开更多
Experimentation data of perspex glass sheet cutting, using CO2 laser, with missing values were modelled with semi-supervised artificial neural networks. Factorial design of experiment was selected for the verification...Experimentation data of perspex glass sheet cutting, using CO2 laser, with missing values were modelled with semi-supervised artificial neural networks. Factorial design of experiment was selected for the verification of orthogonal array based model prediction. It shows improvement in modelling of edge quality and kerf width by applying semi-supervised learning algorithm, based on novel error assessment on simulations. The results are expected to depict better prediction on average by utilizing the systematic randomized techniques to initialize the neural network weights and increase the number of initialization. Missing values handling is difficult with statistical tools and supervised learning techniques; on the other hand, semi-supervised learning generates better results with the smallest datasets even with missing values.展开更多
多视角数据的涌现对传统单视角聚类算法提出了挑战.利用单视角聚类算法独立地对每个视角进行划分,再通过集成机制获取全局划分的方法,人为地割裂了视角之间的内在联系,难以获得理想的聚类效果.针对此问题,提出了一个多视角聚类模型.该...多视角数据的涌现对传统单视角聚类算法提出了挑战.利用单视角聚类算法独立地对每个视角进行划分,再通过集成机制获取全局划分的方法,人为地割裂了视角之间的内在联系,难以获得理想的聚类效果.针对此问题,提出了一个多视角聚类模型.该模型不仅考虑了视角内的划分质量,还兼顾了视角间的协同学习机制.对于视角内的划分,为了捕捉更为准确的簇内结构信息,采用多代表点的簇结构表示策略;对于视角间的协同学习机制,假设簇中代表点在不同视角下,其代表性保持.因此,在该模型基础上提出了基于代表点一致性约束的多视角模糊聚类算法(multi-view fuzzy clustering with a medoid invariant constraint,简称MFCMddI).该算法通过最大化两两相邻视角下代表点权重系数的乘积之和来保证代表点一致性.MFCMddI的目标函数可通过引入拉格朗日乘子和KKT条件进行优化.在人工数据集以及真实数据集上的实验结果均表明,该算法相对于所引入的对比算法而言具有一定的优势.展开更多
Since the existing single-layer networked control systems have some inherent limitations and cannot effectively handle the problems associated with unreliable networks, a novel two-layer networked learning control sys...Since the existing single-layer networked control systems have some inherent limitations and cannot effectively handle the problems associated with unreliable networks, a novel two-layer networked learning control system (NLCS) is proposed in this paper. Its lower layer has a number of local controllers that are operated independently, and its upper layer has a learning agent that communicates with the independent local controllers in the lower layer. To implement such a system, a packet-discard strategy is firstly developed to deal with network-induced delay and data packet loss. A cubic spline interpolator is then employed to compensate the lost data. Finally, the output of the learning agent based on a novel radial basis function neural network (RBFNN) is used to update the parameters of fuzzy controllers. A nonlinear heating, ventilation and air-conditioning (HVAC) system is used to demonstrate the feasibility and effectiveness of the proposed system.展开更多
A novel multicast communication model using a RingNet hierarchy is proposed. The RingNet hierarchy consists of 4 tiers: border router tier, access gateway tier, access proxy tier and mobile host tier. Within the hiera...A novel multicast communication model using a RingNet hierarchy is proposed. The RingNet hierarchy consists of 4 tiers: border router tier, access gateway tier, access proxy tier and mobile host tier. Within the hierarchy, the upper 2 tiers are dynamically organized into logical rings with network entities. A novel hierarchical secure access control scheme on key management is proposed based on the RingNet model. Network entities within the multicast hierarchy belong to different privileged local groups. Network entities of the higher-privileged local groups have the right to derive the keys held by network entities of the lower-privileged local groups, and the reverse operation is not allowed. With the key management approach, any insertion and changing of local group key will not affect other local groups. The analytical result shows that the scheme has higher security than Lin’s.展开更多
Many energy efficiency asynchronous duty-cycle MAC(media access control) protocols have been proposed in recent years.However,in these protocols,wireless sensor nodes almost choose their wakeup time randomly during th...Many energy efficiency asynchronous duty-cycle MAC(media access control) protocols have been proposed in recent years.However,in these protocols,wireless sensor nodes almost choose their wakeup time randomly during the operational cycle,which results in the packet delivery latency increased significantly on the multiple hops path.To reduce the packet delivery latency on multi-hop path and energy waste of the sender's idle listening,a new low latency routing-enhanced asynchronous duty-cycle MAC protocol was presented,called REA-MAC.In REA-MAC,each sensor node decided when it waked up to send the beacon based on cross-layer routing information.Furthermore,the sender adaptively waked up based on the relationship between the transmission request time and the wakeup time of its next hop node.The simulation results show that REA-MAC reduces delivery latency by 60% compared to RI-MAC and reduces 8.77% power consumption on average.Under heavy traffic,REA-MAC's throughput is 1.48 times of RI-MAC's.展开更多
Reduction of falls of elderly people has been an active research area for many years.Falls of older people can be signicantly reduced through the smart use of technologies.Such technologies can help older people to re...Reduction of falls of elderly people has been an active research area for many years.Falls of older people can be signicantly reduced through the smart use of technologies.Such technologies can help older people to regain mobility and reduce their reliance on community care services.Therefore,mobility aids,as one of the main components of these assistive technologies,are mainly discussed in this paper.Recent obstacle detection systems and mobility aids will be reviewed in this paper,where different features are explicitly addressed.展开更多
Techniques for mining information from distributed data sources accessible over the Internet are a growing area of research.The mobile Agent paradigm opens a new door for distributed data mining and knowledge discover...Techniques for mining information from distributed data sources accessible over the Internet are a growing area of research.The mobile Agent paradigm opens a new door for distributed data mining and knowledge discovery applications.In this paper we present the design of a mobile agent system which couples service discovery,using a logical language based application programming interface,and database access.Combining mobility with database access provides a means to create more efficient data mining applications.The processing of data is moved to network wide data locations instead of the traditional approach of bringing huge amount of data to the processing location.Our proposal aims at implementing system tools that will enable intelligent mobile Agents to roam the Internet searching for distributed data services.Agents access the data,discover patterns,extract useful information from facts recorded in the databases,then communicate local results back to the user.The user then generates a global data model through the aggregation of results provided by all Agents.This overcomes barriers posed by network congestion,poor security,and unreliability.展开更多
文摘1. IntroductionHumans have the ability (or competence) to think logically, and this is an undeniable fact. However,what this ability consists in is a difficult question. It might be said that logical ability consists in theknowledge of a set of logic rules. But what are those logic rules? For centuries logicians have devel-
文摘Damage detection in structures is performed via vibra-tion based structural identification. Modal information, such as fre-quencies and mode shapes, are widely used for structural dama-ge detection to indicate the health conditions of civil structures.The deep learning algorithm that works on a multiple layer neuralnetwork model termed as deep autoencoder is proposed to learnthe relationship between the modal information and structural stiff-ness parameters. This is achieved via dimension reduction of themodal information feature and a non-linear regression against thestructural stiffness parameters. Numerical tests on a symmetri-cal steel frame model are conducted to generate the data for thetraining and validation, and to demonstrate the efficiency of theproposed approach for vibration based structural damage detec-tion.
文摘Experimentation data of perspex glass sheet cutting, using CO2 laser, with missing values were modelled with semi-supervised artificial neural networks. Factorial design of experiment was selected for the verification of orthogonal array based model prediction. It shows improvement in modelling of edge quality and kerf width by applying semi-supervised learning algorithm, based on novel error assessment on simulations. The results are expected to depict better prediction on average by utilizing the systematic randomized techniques to initialize the neural network weights and increase the number of initialization. Missing values handling is difficult with statistical tools and supervised learning techniques; on the other hand, semi-supervised learning generates better results with the smallest datasets even with missing values.
文摘多视角数据的涌现对传统单视角聚类算法提出了挑战.利用单视角聚类算法独立地对每个视角进行划分,再通过集成机制获取全局划分的方法,人为地割裂了视角之间的内在联系,难以获得理想的聚类效果.针对此问题,提出了一个多视角聚类模型.该模型不仅考虑了视角内的划分质量,还兼顾了视角间的协同学习机制.对于视角内的划分,为了捕捉更为准确的簇内结构信息,采用多代表点的簇结构表示策略;对于视角间的协同学习机制,假设簇中代表点在不同视角下,其代表性保持.因此,在该模型基础上提出了基于代表点一致性约束的多视角模糊聚类算法(multi-view fuzzy clustering with a medoid invariant constraint,简称MFCMddI).该算法通过最大化两两相邻视角下代表点权重系数的乘积之和来保证代表点一致性.MFCMddI的目标函数可通过引入拉格朗日乘子和KKT条件进行优化.在人工数据集以及真实数据集上的实验结果均表明,该算法相对于所引入的对比算法而言具有一定的优势.
基金Supported by National Natural Science Foundation of China(60774059)Project of Science &Technology Commission of Shanghaiunicipality(061107031,06DZ22011,06ZR14131)+1 种基金the Sunlight Plan Following Project of Shanghai Municipal Education Commission and Shanghai Edu-ational Development Foundation(06GG10)Shanghai Leading Academic Disciplines(T0103)
文摘Since the existing single-layer networked control systems have some inherent limitations and cannot effectively handle the problems associated with unreliable networks, a novel two-layer networked learning control system (NLCS) is proposed in this paper. Its lower layer has a number of local controllers that are operated independently, and its upper layer has a learning agent that communicates with the independent local controllers in the lower layer. To implement such a system, a packet-discard strategy is firstly developed to deal with network-induced delay and data packet loss. A cubic spline interpolator is then employed to compensate the lost data. Finally, the output of the learning agent based on a novel radial basis function neural network (RBFNN) is used to update the parameters of fuzzy controllers. A nonlinear heating, ventilation and air-conditioning (HVAC) system is used to demonstrate the feasibility and effectiveness of the proposed system.
文摘A novel multicast communication model using a RingNet hierarchy is proposed. The RingNet hierarchy consists of 4 tiers: border router tier, access gateway tier, access proxy tier and mobile host tier. Within the hierarchy, the upper 2 tiers are dynamically organized into logical rings with network entities. A novel hierarchical secure access control scheme on key management is proposed based on the RingNet model. Network entities within the multicast hierarchy belong to different privileged local groups. Network entities of the higher-privileged local groups have the right to derive the keys held by network entities of the lower-privileged local groups, and the reverse operation is not allowed. With the key management approach, any insertion and changing of local group key will not affect other local groups. The analytical result shows that the scheme has higher security than Lin’s.
基金Projects(61103011,61170261) supported by the National Natural Science Foundation of China
文摘Many energy efficiency asynchronous duty-cycle MAC(media access control) protocols have been proposed in recent years.However,in these protocols,wireless sensor nodes almost choose their wakeup time randomly during the operational cycle,which results in the packet delivery latency increased significantly on the multiple hops path.To reduce the packet delivery latency on multi-hop path and energy waste of the sender's idle listening,a new low latency routing-enhanced asynchronous duty-cycle MAC protocol was presented,called REA-MAC.In REA-MAC,each sensor node decided when it waked up to send the beacon based on cross-layer routing information.Furthermore,the sender adaptively waked up based on the relationship between the transmission request time and the wakeup time of its next hop node.The simulation results show that REA-MAC reduces delivery latency by 60% compared to RI-MAC and reduces 8.77% power consumption on average.Under heavy traffic,REA-MAC's throughput is 1.48 times of RI-MAC's.
基金Shanghai Leading Academic Disciplines under Grant T0103Project of Science & Technology Commission of Shanghai Municipality under Grant 061107031 and 06ZR14131
文摘Reduction of falls of elderly people has been an active research area for many years.Falls of older people can be signicantly reduced through the smart use of technologies.Such technologies can help older people to regain mobility and reduce their reliance on community care services.Therefore,mobility aids,as one of the main components of these assistive technologies,are mainly discussed in this paper.Recent obstacle detection systems and mobility aids will be reviewed in this paper,where different features are explicitly addressed.
文摘Techniques for mining information from distributed data sources accessible over the Internet are a growing area of research.The mobile Agent paradigm opens a new door for distributed data mining and knowledge discovery applications.In this paper we present the design of a mobile agent system which couples service discovery,using a logical language based application programming interface,and database access.Combining mobility with database access provides a means to create more efficient data mining applications.The processing of data is moved to network wide data locations instead of the traditional approach of bringing huge amount of data to the processing location.Our proposal aims at implementing system tools that will enable intelligent mobile Agents to roam the Internet searching for distributed data services.Agents access the data,discover patterns,extract useful information from facts recorded in the databases,then communicate local results back to the user.The user then generates a global data model through the aggregation of results provided by all Agents.This overcomes barriers posed by network congestion,poor security,and unreliability.
