Two Improvements in Grover＇s Algorithm

When the current Grover algorithm is applied to searching some targets in an unsorted quantum database, the differences of the significance for each target are not taken into consideration. When the targets are more than a quarter of the total items, the probability of finding targets rapidly falls with the increase of the targets, and when the targets are more than half of the total items, the algorithm will be invalidated. Aiming at these problems, flrstly, an improvement based on the weighted targets is proposed in which each target is endowed a weight coefficient according to its significance. Using these different weight coefficients, we give a quantum superposition of all target states, which may make the probability for each target equal to its weight coefficient. Secondly, an improved phase matching is proposed in which two directions of phase rotation are same, and two magnitudes are determined by the inner product of the superposition of target states and the initial system state. When this inner product is more than 1/2, using the improved phase matching. The targets can be found with a probability of 100% and by the only one Grover iteration. Finally, the validity of these measures is validated by a simple searching example.     

Quantum-Inspired Evolutionary Algorithm for Continuous Space Optimization

A quantum-inspired evolutionary algorithm based on the probability amplitudes of Quantum bits （qubits） is proposed. The chromosome is comprised of qubits whose probability amplitudes comprise gene chain. The qubits on chromosome are evolved by quantum rotation gates, and are mutated by quantum non-gates. For the rotation direction of quantum rotation gate, a convenient method is proposed. The formula of the magnitude of rotation angle is constructed based on the gradient of fitness function. In this method, the probability amplitudes of each qubit are regarded as two paratactic genes, each chromosome contains two gene chains, and each of gene chains represents an optimization solutiong which can accelerate convergence process for the same number of chromosomes. By two optimization examples of function extremum and of neural network weights, the experimental results show that the approach is superior to common quantum evolutionary algorithm and simple genetic algorithm in both search capability and optimization efficiency.     

An Efficient Quantum Mechanism Based Fair Non-Repudiation Protocol

In this paper, an efficient quantum public key signature based fair non-repudiation message exchanging protocol is proposed. This protocol could guarantee fairness which means both the receiver and the sender could get the evidences of each other at the end of message transmission. Compared with the traditional nonrepudiation protocols, this protocol provides higher security because of the superiority of quantum cryptography as well as enhances the running time efficiency and reliability since it avoids the involvement of TTP （Trusted third party）.     

A Novel Least-Entanglement-Assisted Asymmetric Quantum Codes Based on Sliding Grill

We propose new methods for constructing novel entanglement-asslsted asymmetric quantum codes based on combinatorial designs and sliding grill. Based on a special case of combinatorial designs, our proposed method can construct a type of parity check matrix with greater column weight and better decoding performance. Combined with the characteristic of asymmetric quantum chan- nel, we propose new method of sliding grill. Mother matrix and submatrix can be constructed. The null space of the parlty-check matrix gives entanglement-asslsted asymmetric quantum code. Tanner graph of the code has a girth of at least 6. Our proposed quantum code has higher code rate with the same error correction capability. These families of entanglement-asslsted asymmetric quantum codes consume only one copy of maximally entangled state （ebit）, and outperform other quantum codes based on similar construction method according to our numerical computation.     

Detection and Location of Objects from Mobile Mapping System Integrated with CCD Cameras

During the last decade, spatio-temporal databases have become increasingly important in many applications such as geographic information systems （GIS） and engineering information systems. This paper discusses the design and implementation of a geocomputing platform for the development of location-based services （LBS） focusing on mobile mapping. During the analysis, design, and implementation of the geocomputing platform, an effective method is proposed for the real-time processing of geographic information acquired by a camera attached to a personal digital assistant （PDA）. This method combines location information given by the global position system （GPS） with man＇s ability to recognize the location of objects and their geographical relationship to improve object mapping.     

Sensitivity of Pr+3: LaCl3infrared quantum counter

The NEPλand response time of the Pr³⁺:LaCl3Infra-red Quantum Counter have been measured for the wavelengths 1.48 μ, 1.58 μ, 2.03 μ and 2.33 μ at the nominal temperatures of 300°K, 77°K, and 4.2°K. The experimental arrangement is described and suggestions for improvement are made. The best results obtained are anNEP_{2.03_mu} = 2 times 10^{-5}watts(c/s)^{-1/2}and a temperature independent response time of 20-30 ms.     

施耐德Quantum PLC在河钢宣钢360M2烧结机的应用

施耐德公司的Quantum PLC系统以较高的灵活性、安全性、可追溯性以及高生产性,使之成为了宣钢3台360M2烧结机使用的控制系统,本文详细介绍了Quantum PLC自动控制系统的组成、特点和功能,及在烧结机自动控制系统中关键技术的应用.     

最优相位协变量子克隆

在量子信息科学中，量子克隆理论是基础理论, 它提供量子密码术的绝对安全性. 我们得到d维空间最优1→M=d+1相位协变量子克隆的具体变换, 然后将这种克隆机推广到1→M=kd+1 (k为整数)情况, 并得到具体的变换. 利用2维空间非最优2→M=2k+1相位协变量子克隆的形式, 我们得到最优的克隆变换. 两种类型的量子克隆机的拷贝忠信度符合已有的理论值.     

Self-Organization Approaches for Optimization in Cognitive Radio Networks

Cognitive radio （CR） is regarded as a promising technology for providing a high spectral efficiency to mobile users by using heterogeneous wireless network architectures and dynamic spectrum access techniques. However, cognitive radio networks （CRNs） may also impose some challenges due to the ever increasing complexity of network architecture, the increasing complexity with configuration and management of large-scale networks, fluctuating nature of the available spectrum, diverse Quality-of-Service （QoS） requirements of various applications, and the intensifying difficulties of centralized control, etc. Spectrum management functions with self-organization features can be used to address these challenges and realize this new network paradigm. In this paper, fundamentals of CR, including spectrum sensing, spectrum management, spectrum mobility and spectrum sharing, have been surveyed, with their paradigms of self-organization being emphasized. Variant aspects of self- organization paradigms in CRNs, including critical functionalities of Media Access Control （MAC）- and network-layer operations, are surveyed and compared. Furthermore, new directions and open problems in CRNs are also identified in this survey.     

A Probability Driven Quadri-Stage Contention Protocol for Mobile Ad Hoc Networks

The paper proposes a new contention based Time division multiple access （TDMA） Medium access control （MAC） protocol in wireless ad hoc networks, which can be termed Quadri-stage contention protocol （QSCP）. The QSCP protocol is free of both the ＂hidden terminal＂ and the ＂exposed terminal＂ problems. It is distributive and arbitrarily scalable. In the dedicated contention stage, nodes exchange their ＂Normalized accumulation and dissipation rate of payload （NADROP）＂ messages in 2-hop neighborhood, and then run a contention probability calculation algorithm to decide the probability of sending a contention frame. The algorithm guaran- tees that the number of time slot reserved by a node is proportional to its NADROP value, which can remarkably improve the end-to-end throughput when network load is heavy, and is more efficient in energy consumption. The simulation results demonstrate that QSCP performs better than the existing protocols.     

Best Effort Spectrum Allocation Scheme for Femtocell Networks in Dense Deployment

In orthogonal frequency division multiple access（OFDMA） based femtocell networks,the co-tier interference among femto base stations（FBS） becomes important in multiuser and densely deployed environment.In order to mitigate the co-tier interference and enhance the system total throughput,this paper proposed a best effort spectrum allocation scheme based on the extension of graph theory.In the scheme,a controller was proposed to collect the channel state information（CSI）of all femtocell user equipments（FUEs） in a certain range.Then,the controller evaluated the signal-to-interference Ratio（SIR） of each FUE and determined the set of its interference neighbors.By calculating the received power matrix（RPM） among FUEs and building interference graph matrix（IGM）,different spectrum resource blocks（RBs） were assigned to the users with interference relation,while users without interference relation shared the same RBs,which could increase the spectrum efficiency.Simulation results show that the proposed algorithm can significantly improve the RB usage efficiency compared with the basic graph coloring theory,and more than 80% improvement can be acquired in dense deployment scenario.Besides,the throughput of both cell edge macro user equipments（MUEs） and cell edge FUEs is guaranteed on the premise of low interference.     

A Scalable Peer-to-Peer Web Services Overlay for Semantic Discovery

The growing number of web services advocates distributed discovery infrastructures which are semantics-enabled. We introduce a novel approach for semantic discovery of web services in structured P2P-based （Peer-to-Peer） registries. We partition concepts into different CGs （Concept groups） and index these ordered concept sets in a two-phase semantic routing mechanism. Each node and query has one concept set as its unique ID. For each concept in the query, current node first route the query to a node with nodeID that shares a prefix as long as with the query, but a longer CG. Second, the query will be routed to a node sharing a longer prefix than that of the current node. Combining with semantic similarity calculation, our proposal guarantees that most existing services matching a query will be found with bounded costs in terms of number of nodes involved. The scalability and reliability of our approach are also confirmed through emulation tests.     

Action-Based Access Control Modelt

Access control is one of the powerful and generalized approaches for restricted resource access. The environmental state is introduced and the term “action” is defined based on roles, temporal states and environmental states. Actions can be used to capture security-relevant aspects of roles, environmental and temporal states in different information systems. Then, the action hierarchy, environmental hierarchy, temporal hierarchy and Action- based access control （ABAC） model are presented. ABAC is compared with the existing models and the result shows that the ABAC model can solve the problem of access control in information systems with mobile computation for its convenient and flexible designs. An application example of ABAC model is described at the end of the paper.     

A Fuzzy Similarity-based Clustering Optimized by Particle Swarm Optimization

Traditional fuzzy clustering algorithms based on objective function is unable to determine the optimum number of clusters, sensitive to the initial cluster centers, and easily sunk into the issue of local optimum. A Fuzzy similarity-based clustering （FSBC） algorithm is proposed in this paper. This method consists three phases： first, the objective function is modified by integrating Fuzzy C-means （FCM） and Possibilistic C-means （PCM） method; second, using the density function from data for similarity-based clustering to automatically generate initial prototype without requesting users to specify; finally, the iteration process optimized by Particle swarm optimization （PSO） to obtain appropriate adjustment parameters that can provide better results, which avoids the local minimum problems of traditional methods. The experimental results on the synthetic data and UCI standard data sets show that the proposed algorithm has greater searching capability, less computational complexity, higher clustering precision.     

Novel Active Contour Model for Image Segmentation Based on Local Fuzzy Gaussian Distribution Fitting

A novel active contour model is proposed, which incorporates local information distributions in a fuzzy energy function to effectively deal with the intensity inhomogeneity. Moreover, the proposed model is convex with respect to the variable which is used for extracting the contour. This makes the model independent on the initial condition and suitable for an automatic segmentation. Furthermore, the energy function is minimized in a computationally efficient way by calculating the fuzzy energy alterations directly. Experiments are carried out to prove the performance of the proposed model over some existing methods. The obtained results confirm the efficiency of the method.     

PTCP Incast in Data Center Networks

In recent years, dual-homed topologies have appeared in data centers in order to offer higher aggregate bandwidth by using multiple paths simultaneously. Multipath TCP （MPTCP） has been proposed as a replacement for TCP in those topologies as it can efficiently offer improved throughput and better fairness. However, we have found that MPTCP has a problem in terms of incast collapse where the receiver suffers a drastic goodput drop when it simultaneously requests data over multiple servers. In this paper, we investigate why the goodput collapses even if MPTCP is able to actively relieve hot spots. In order to address the problem, we propose an equally-weighted congestion control algorithm for MPTCP, namely EW-MPTCP, without need for centralized control, additional infrastructure and a hardware upgrade. In our scheme, in addition to the coupled congestion control performed on each subflow of an MPTCP connection, we allow each subflow to perform an additional congestion control operation by weighting the congestion window in reverse proportion to the number of servers. The goal is to mitigate incast collapse by allowing multiple MPTCP subflows to compete fairly with a single-TCP flow at the shared bottleneck. The simulation results show that our solution mitigates the incast problem and noticeably improves goodput in data centers.     

A New Key Management Protocol to MANET

MANET （Mobile ad-hoc networks） are networks in which nodes are mobile and link connectivity might be changing all the time. The wireless and dis- tributed nature of MANET pose a great challenge to system security. Key management is an important and complex problem to the authentication and system security. The paper proposes a new method to the key management with high efficiency. Which,making use of the ideas of self-organization and local driven by intercross authenti-cation of CAs and threshold encryption. It＇s proved that the new method can reduce the communications delay and time delay in the key management process compared to other methods. So, it is a contribution to the field of key management in MANET.     

On the Design and Temporal Petri Net Verification of Grid Commerce Architecture

The emergence of Grid Computing settings lays a solid foundation for designing and constructing a next generation E-commerce environment. This work presents a new E-commerce architecture based on a Grid Computing environment, and models and analyzes the architecture using Temporal Petri nets （TPNs）. It can make sufficiently use of the Grid resources to implement various electronic bargains between the geographically dispersed users. By means of its TPN model, some main temporal properties are represented and verified formally.     

Joint Optimization of Subchannel Reassignment and Power Adaptation for Multicarrier Cooperative Systems

An amplify-and-forward multicarrier cooperative system was proposed in this paper. The optimal resource-allocation problem was investigated in terms of improving data rate. An effective resource-allocation algorithm was proposed based on three techniques, adaptive modulation, subchannel reassignment design and transmit power adaptation. The designed subchannel reassignment not only increases the average data rate, but also raises the threshold of ＂water-filling＂ in optimizing power allocation that can further increase data rate. Since the power allocation is based on the designed subchannel reassignment, the complexity of the proposed algorithm is reduced greatly. Simulation results show that the proposed algorithm effectively increases the system＇s average data rate.     

An Effective Gated Scheduling with Pre-defined QoS Cross-layer Design for Wireless Networks

The proposed M-gated scheduling algorithm rules the server in wireless networks stays with a station for at most M times gated services. By the method of embedded Markov chain and probability generating function we developed a model with vacations and acquired the theoretical value of average queue length and packet delay. Like E-limlted scheduling algorithm, its performance is close to that of the optimal polling scheme, exhaustive scheduling, but the inherent unfairness problem for the latter is avoided. And it also does not require the server to know the status of stations, queues information. Compared with E-limited, M-gated has less jitter and is more robust. We then use the derived quality of service parameter as the basis for cross-layer design. Simulations results show the network is more stable and can keep the queue length and the packets delay under QoS level. When putting E- limited and M-gated scheduling in the same cross-layer design scheme, the latter has less overhead especially when the system is heavily loaded.