This article deals with some properties of Galton-Watson branching processes in varying environments. A necessary and suffcient condition for relative recurrent state is presented, and a series of ratio limit properti...This article deals with some properties of Galton-Watson branching processes in varying environments. A necessary and suffcient condition for relative recurrent state is presented, and a series of ratio limit properties of the transition probabilities are showed.展开更多
Cellular Automaton （CA） based traffic flow models have been extensively studied due to their effectiveness and simplicity in recent years. This paper develops a discrete time Markov chain （DTMC） analytical framewo...Cellular Automaton （CA） based traffic flow models have been extensively studied due to their effectiveness and simplicity in recent years. This paper develops a discrete time Markov chain （DTMC） analytical framework for a Nagel-Schreckenberg and Fukui Ishibashi combined CA model （W^2H traffic flow model） from microscopic point of view to capture the macroscopic steady state speed distributions. The inter-vehicle spacing Maxkov chain and the steady state speed Markov chain are proved to be irreducible and ergodic. The theoretical speed probability distributions depending on the traffic density and stochastic delay probability are in good accordance with numerical simulations. The derived fundamental diagram of the average speed from theoretical speed distributions is equivalent to the results in the previous work.展开更多
The authors consider generalized statistically self-affine recursive fractals K with random numbers of subsets on each level. They obtain the Hausdorff dimensions of K without considering whether the subsets on each l...The authors consider generalized statistically self-affine recursive fractals K with random numbers of subsets on each level. They obtain the Hausdorff dimensions of K without considering whether the subsets on each level are non-overlapping or not. They also give some examples to show that many important sets are the special cases of their models.展开更多
Cloud data sharing service, which allows a group of people to work together to access and modify the shared data, is one of the most popular and efficient working styles in the enterprises. However, the cloud server i...Cloud data sharing service, which allows a group of people to work together to access and modify the shared data, is one of the most popular and efficient working styles in the enterprises. However, the cloud server is not completely trusted, and its security could be compromised by monetary reasons or caused by hacking and hardware errors. Therefore, despite of having advantages of scalability and flexibility, cloud storage service comes with privacy and the security concerns. A straightforward method to protect the user's privacy is to encrypt the data stored at the cloud. To enable the authenticated users to access the encrypted cloud data, a practical group key management algorithm for the cloud data sharing application is highly desired. The existing group key management mechanisms presume that the server is trusted. But, the cloud data service mode does not always meet this condition. How to manage the group keys to support the scenario of the cloud storage with a semi-trusted cloud server is still a challenging task. Moreover, the cloud storage system is a large-scale and open application, in which the user group is dynamic. To address this problem, we propose a practical group key management algorithm based on a proxy re-encryption mechanism in this paper. We use the cloud server to act as a proxy tore-encrypt the group key to allow authorized users to decrypt and get the group key by their private key. To achieve the hierarchical access control policy, our scheme enables the cloud server to convert the encrypted group key of the lower group to the upper group. The numerical analysis and experimental results further validate the high efficiency and security of the proposed scheme.展开更多
The Energy based Ultra-Wideband Multipath Routing(EUMR) algorithm for Ad hoc sensor network is proposed. It utilizes the function of UWB positioning to reduce the network communication delay and route overhead. Furthe...The Energy based Ultra-Wideband Multipath Routing(EUMR) algorithm for Ad hoc sensor network is proposed. It utilizes the function of UWB positioning to reduce the network communication delay and route overhead. Furthermore,the algorithm considers energy consumption,the residual energy and node hops of communication paths to make energy consumption more balanced and extend the network lifetime. Then routing which is stable,energy-saving and low-delay is realized. Simulation results show that the algorithm has better performance on saving energy,route overhead,stability and extending network lifetime.展开更多
This paper proposes a new image restoration technique, in which the resulting regularized image approximates the optimal solution steadily. The affect of the regular-ization operator and parameter on the lower band an...This paper proposes a new image restoration technique, in which the resulting regularized image approximates the optimal solution steadily. The affect of the regular-ization operator and parameter on the lower band and upper band energy of the residue of the regularized image is theoretically analyzed by employing wavelet transform. This paper shows that regularization operator should generally be lowstop and highpass. So this paper chooses a lowstop and highpass operator as regularization operator, and construct an optimization model which minimizes the mean squares residue of regularized solution to determine regularization parameter. Although the model is random, on the condition of this paper, it can be solved and yields regularization parameter and regularized solution. Otherwise, the technique has a mechanism to predict noise energy. So, without noise information, it can also work and yield good restoration results.展开更多
Recognizing actions according to video features is an important problem in a wide scope of applications. In this paper, we propose a temporal scale.invariant deep learning framework for action recognition, which is ro...Recognizing actions according to video features is an important problem in a wide scope of applications. In this paper, we propose a temporal scale.invariant deep learning framework for action recognition, which is robust to the change of action speed. Specifically, a video is firstly split into several sub.action clips and a keyframe is selected from each sub.action clip. The spatial and motion features of the keyframe are extracted separately by two Convolutional Neural Networks(CNN) and combined in the convolutional fusion layer for learning the relationship between the features. Then, Long Short Term Memory(LSTM) networks are applied to the fused features to formulate long.term temporal clues. Finally, the action prediction scores of the LSTM network are combined by linear weighted summation. Extensive experiments are conducted on two popular and challenging benchmarks, namely, the UCF.101 and the HMDB51 Human Actions. On both benchmarks, our framework achieves superior results over the state.of.the.art methods by 93.7% on UCF.101 and 69.5% on HMDB51, respectively.展开更多
Trustworthy service composition is an extremely important task when service composition becomes infeasible or even fails in an environment which is open,autonomic,uncertain and deceptive.This paper presents a trustwor...Trustworthy service composition is an extremely important task when service composition becomes infeasible or even fails in an environment which is open,autonomic,uncertain and deceptive.This paper presents a trustworthy service composition method based on an improved Cross generation elitist selection,Heterogeneous recombination,Catacly-smic mutation(CHC) Trustworthy Service Composition Method(CHC-TSCM) genetic algorithm.CHCTSCM firstly obtains the total trust degree of the individual service using a trust degree measurement and evaluation model proposed in previous research.Trust combination and computation then are performed according to the structural relation of the composite service.Finally,the optimal trustworthy service composition is acquired by the improved CHC genetic algorithm.Experimental results show that CHC-TSCM can effectively solve the trustworthy service composition problem.Comparing with GODSS and TOCSS,this new method has several advantages:1) a higher service composition successrate;2) a smaller decline trend of the service composition success-rate,and 3) enhanced stability.展开更多
基金supported by NNSF of China(6053408070571079)Open Fundation of SKLSE of Wuhan University (2008-07-03)
文摘This article deals with some properties of Galton-Watson branching processes in varying environments. A necessary and suffcient condition for relative recurrent state is presented, and a series of ratio limit properties of the transition probabilities are showed.
基金supported by the National Basic Research Program of China (Grant No 2007CB310800)the National Natural Science Foundation of China (Grant Nos 60772150 and 60703018)the National High Technology Research and Development Program of China (Grant No 2008AA01Z208)
文摘Cellular Automaton （CA） based traffic flow models have been extensively studied due to their effectiveness and simplicity in recent years. This paper develops a discrete time Markov chain （DTMC） analytical framework for a Nagel-Schreckenberg and Fukui Ishibashi combined CA model （W^2H traffic flow model） from microscopic point of view to capture the macroscopic steady state speed distributions. The inter-vehicle spacing Maxkov chain and the steady state speed Markov chain are proved to be irreducible and ergodic. The theoretical speed probability distributions depending on the traffic density and stochastic delay probability are in good accordance with numerical simulations. The derived fundamental diagram of the average speed from theoretical speed distributions is equivalent to the results in the previous work.
基金This research is partly supported by NNSF of China (60204001) the Youth Chengguang Project of Science and Technology of Wuhan City (20025001002)
文摘The authors consider generalized statistically self-affine recursive fractals K with random numbers of subsets on each level. They obtain the Hausdorff dimensions of K without considering whether the subsets on each level are non-overlapping or not. They also give some examples to show that many important sets are the special cases of their models.
基金partially supported by National Natural Science Foundation of China No.61202034,61232002,61303026,6157237861402339CCF Opening Project of Chinese Information Processing No.CCF2014-01-02+2 种基金the Program for Innovative Research Team of Wuhan No.2014070504020237Fundamental Application Research Plan of Suzhou City No.SYG201312Natural Science Foundation of Wuhan University No.2042016gf0020
文摘Cloud data sharing service, which allows a group of people to work together to access and modify the shared data, is one of the most popular and efficient working styles in the enterprises. However, the cloud server is not completely trusted, and its security could be compromised by monetary reasons or caused by hacking and hardware errors. Therefore, despite of having advantages of scalability and flexibility, cloud storage service comes with privacy and the security concerns. A straightforward method to protect the user's privacy is to encrypt the data stored at the cloud. To enable the authenticated users to access the encrypted cloud data, a practical group key management algorithm for the cloud data sharing application is highly desired. The existing group key management mechanisms presume that the server is trusted. But, the cloud data service mode does not always meet this condition. How to manage the group keys to support the scenario of the cloud storage with a semi-trusted cloud server is still a challenging task. Moreover, the cloud storage system is a large-scale and open application, in which the user group is dynamic. To address this problem, we propose a practical group key management algorithm based on a proxy re-encryption mechanism in this paper. We use the cloud server to act as a proxy tore-encrypt the group key to allow authorized users to decrypt and get the group key by their private key. To achieve the hierarchical access control policy, our scheme enables the cloud server to convert the encrypted group key of the lower group to the upper group. The numerical analysis and experimental results further validate the high efficiency and security of the proposed scheme.
文摘The Energy based Ultra-Wideband Multipath Routing(EUMR) algorithm for Ad hoc sensor network is proposed. It utilizes the function of UWB positioning to reduce the network communication delay and route overhead. Furthermore,the algorithm considers energy consumption,the residual energy and node hops of communication paths to make energy consumption more balanced and extend the network lifetime. Then routing which is stable,energy-saving and low-delay is realized. Simulation results show that the algorithm has better performance on saving energy,route overhead,stability and extending network lifetime.
基金This work was supported by the National Natural Science Foundation of China(60204001, 60133010)the Scientific Research Fundation of Hunan Provincial Education Department(02C640)the Youth Chengguang Project of Science and Technology of Wuhan City(
文摘This paper proposes a new image restoration technique, in which the resulting regularized image approximates the optimal solution steadily. The affect of the regular-ization operator and parameter on the lower band and upper band energy of the residue of the regularized image is theoretically analyzed by employing wavelet transform. This paper shows that regularization operator should generally be lowstop and highpass. So this paper chooses a lowstop and highpass operator as regularization operator, and construct an optimization model which minimizes the mean squares residue of regularized solution to determine regularization parameter. Although the model is random, on the condition of this paper, it can be solved and yields regularization parameter and regularized solution. Otherwise, the technique has a mechanism to predict noise energy. So, without noise information, it can also work and yield good restoration results.
基金supported in part by the National High Technology Research and Development Program of China (863 Program) (2015AA016306)the National Nature Science Foundation of China (61231015)+2 种基金the Technology Research Program of Ministry of Public Security (2016JSYJA12)the Shenzhen Basic Research Projects (JCYJ20150422150029090)the Applied Basic Research Program of Wuhan City (2016010101010025)
文摘Recognizing actions according to video features is an important problem in a wide scope of applications. In this paper, we propose a temporal scale.invariant deep learning framework for action recognition, which is robust to the change of action speed. Specifically, a video is firstly split into several sub.action clips and a keyframe is selected from each sub.action clip. The spatial and motion features of the keyframe are extracted separately by two Convolutional Neural Networks(CNN) and combined in the convolutional fusion layer for learning the relationship between the features. Then, Long Short Term Memory(LSTM) networks are applied to the fused features to formulate long.term temporal clues. Finally, the action prediction scores of the LSTM network are combined by linear weighted summation. Extensive experiments are conducted on two popular and challenging benchmarks, namely, the UCF.101 and the HMDB51 Human Actions. On both benchmarks, our framework achieves superior results over the state.of.the.art methods by 93.7% on UCF.101 and 69.5% on HMDB51, respectively.
基金supported by the National Natural Science Foundation of China under Grants No.61272063,No.61300129,No.61273216,No.61202048,No.61100054the Excellent Youth Foundation of Hunan Scientific Committee under Grant No.11JJ1011+2 种基金the Hunan Provincial Natural Science Foundation of China under Grant No.12JJB009Scientific Research Fund of Hunan Provincial Education Department of China under Grants No.09K085,No.12K105the Zhejiang Provincial Natural Science Foundation of China under Grant No.LQ12F02011
文摘Trustworthy service composition is an extremely important task when service composition becomes infeasible or even fails in an environment which is open,autonomic,uncertain and deceptive.This paper presents a trustworthy service composition method based on an improved Cross generation elitist selection,Heterogeneous recombination,Catacly-smic mutation(CHC) Trustworthy Service Composition Method(CHC-TSCM) genetic algorithm.CHCTSCM firstly obtains the total trust degree of the individual service using a trust degree measurement and evaluation model proposed in previous research.Trust combination and computation then are performed according to the structural relation of the composite service.Finally,the optimal trustworthy service composition is acquired by the improved CHC genetic algorithm.Experimental results show that CHC-TSCM can effectively solve the trustworthy service composition problem.Comparing with GODSS and TOCSS,this new method has several advantages:1) a higher service composition successrate;2) a smaller decline trend of the service composition success-rate,and 3) enhanced stability.
