Search

With the development of electronic packaging, the performance of microchip is crucial for the reliability of solder joints. The α-CoSn 3 with some performance have been studied by researchers continuously. However, there is a little study on doping α-(Co, Cu)Sn 3 that Cu is regard as a common element of electronic packaging. In this paper, different concentrations of Cu (0~9.375 at.%) were used to replace the Co atoms in α-CoSn 3 intermetallic(IMC). The thermodynamic stability and electronic structure of α-(Co, Cu)Sn 3 were calculated by the first-principles. The results show that the formation enthalpy and cohesive energy of α-(Co 1-x , Cu x )Sn 3 (x=0~0.375) are negative values, means the α-(Co, Cu)Sn 3 configurations can be formed and exist stably. With the increasing of Cu atoms, the formation enthalpy and cohesive energy increased, the formation of α-(Co, Cu)Sn 3 became difficult and unstable configurations. By analyzing the density of states(DOS) , the increasing of Cu atoms make the main peak deviate from Fermi level gradually and form two main peaks under Fermi level. Besides, the increase of Cu concentrations decreases NEF, indicating the bonding is weakened.

The strategy action and reform for Quality Powerful Nation were briefly described. The feasibility and necessity of taking the manufacturing quality of auto parts as the touchstone and breakthrough point of the strategy were discussed. The purpose and significance of constructing the platform which publics the quality grade of automobile parts were expounded from three aspects of producers, consumers and regulatory authorities. The research contents of the platform construction were listed. The application value of the platform was summarized.

One typical case of label noise indicates that some samples have been incorrectly labeled in data. Label noise of training samples will significantly affect the learning performances such that the classification accuracy will be reduced. Presently, many results of identifying samples of incorrect labels have been proposed. Most of them are based on the consideration of classifier based accuracy. Therefore, the performance of used classifier is directly related to the result of filtering samples with noise label. In this paper, a neighborhood strategy is introduced into analyzing label noise data, it is mainly because such classifier is superior to several popular classifiers. Not only the neighborhood classifier based algorithm is designed to remove samples with noise label, but also such type of filter is compared with the nearest neighborhood based filter. The experimental results demonstrate that our neighborhood classifier based filter performs well because higher classification accuracy can be achieved. This study suggests new trends for considering neighborhood approach to complex data.

In the neighborhood rough set model, with the increasing of the size of information granules, the neighborhood classifier based on the majority voting rule is easy to misjudge the classes of testing samples. To remedy this deficiency, a strategy of attribute reduction based on the idea of the minimum mean distance is proposed in this paper. Firstly, a neighborhood relation is presented by a distance function. Secondly, neighborhood mean distance classifier judges the class of testing sample with the minimum mean distance instead of the majority voting rule in the decision system. Finally, the experimental results on 8 UCI data sets tell us that the reduct obtained by our strategy can not only decrease the conditional entropy, but also provide better classification performances in larger scale information granules.

In rough set theory, forward heuristic algorithm selects the most important attribute in the process of attribute reduction until the given constraint is satisfied. However, the attributes selected by such strategy may bring us over-fitting. To solve such problem, a new heuristic algorithm is designed: the importance of the attribute is obtained by cross validation and then the Early Stopping is employed to terminate the algorithm if over-fitting occurs. Based on the neighborhood rough set, the heuristic algorithm is compared with the new method over several UCI data sets. The experimental results show that: 1) the proposed algorithm can effectively alleviate over-fitting; 2) the reduct obtained by the new algorithm may offer us better classification performances.

Decision-theoretic rough set model interprets the parameters of existing probabilistic rough sets by introducing Bayesian theory to minimize the risks of classification. It is a representative probabilistic rough set model. As an important extension of decision-theoretic rough set model, fuzzy decision-theoretic rough set model can deal with numerical data directly. To investigate the attribute reduction of fuzzy decision-theoretic rough set model, we propose a heuristic algorithm. The heuristic algorithm is used to find the minimum condition attribute subset and it minimizes the decision cost of fuzzy decision-rough set model. Four UCI datasets are employed to test our heuristic algorithm. The experimental results indicate that it does minimize the decision cost of fuzzy decision-theoretic rough set model.

Cloud Radio Access Network (C-RAN) is a novel network architecture, which can solve many challenges of operators when facing the ever-increasing user demands. Specially, the operating expense (OPEX) of C-RAN is an issue of common concern. In this paper, we evaluate the energy consumption of the architecture based on a 10G EPON front-haul considering the daily user behaviour. The simulation results present the energy consumption distributions of C-RAN with daily user behaviour and in different quality of service (QoS).

Most of the innovation designs of mechanical and electrical products are willing to take an improved design of the present products, which not only inherit the advantages of the current products, but also improve the efficiency and reliability of the design. Optimum method of evolutionary design scheme by feature lines and colour based on CBR is studied. This paper provides the division and quantification of product form element, the method and process of extracting form feature lines of case products. The double models of BP neural network of corresponding relation of feature lines, colour parameters and form perceptual image, and of form perceptual image, product function, product capability and performance and product sales is founded, which is further taken as fitness function of GA. The application process of this method is illustrated by an example of innovation design of family car form.

The current work deals with the problem of resource management in P2P networks. The topological properties of the overlay network are critical factors that dominate the performance of P2P networks. The inverse Kautz digraph is a good topology to construct the overlay network. We discuss an efficient DHT-based overlay network (MREIK) with Byzantine fault tolerance. MREIK based on many rings which embeds inverse Kautz digraphs, to enable multi-path P2P routing. Each node maintains a maximum limited number of 2d + 3 entries in its routing table, and any resource is distributed at an exit node based on the longest prefix matching rule. It supports both exact and similarity resources search efficiently. MREIK reduces REIK with one ring maintenance cast and provides high quality routing service.

We consider the problem of indexing high-dimensional data for answering (approximate) similarity-search queries. Similarity indexes prove to be important in a wide variety of settings. In this paper we have presented an efficient similarity search for REIK network called SSREIK which is a novel framework that dynamically structure, in order to build distributed routing information. It allows the evaluation of range and nearest neighbor queries in a distributed manner and utilizes a set of distributed statistics and guarantees that all similar objects to the query are retrieved.

Large-scale P2P systems typically have hundreds of thousands of peers that involve frequent dynamic activities. Empirical studies have shown that participating nodes in P2P systems are not equivalent. Such heterogeneity has been taken into account in the design of P2P systems. In this paper, to achieve better scalability and improve the routing performance of REIK, we design a novel hierarchical REIK overlay network by exploiting super peers, HiREIK. REIK is an inverse Kautz based overlay network with Byzantine fault tolerance. In HiREIK, the peers are organized into clusters, and the clusters themselves are organized in a top-level overlay network. The results show that the hierarchical design can significantly reduce the expected number of hops in REIK system. We also propose a scalable design for managing the clusters and the super-peers.

Efficient routing protocol will receive a prolonged network lifetime. In this paper we propose an energy-efficient multi-hop routing protocol for wireless sensor networks (EEMR). It mainly includes nodes clustering and inter- cluster multi-hop routing selection. In clustering stage, we introduce an uneven clustering mechanism. Cluster heads which are closer to the base station (BS) have smaller cluster size than those farther from BS, thus they can preserve some energy for the purpose of inter-cluster data forwarding. What is more, we propose an energy-efficient multi-hop routing protocol executed by BS for inter-cluster communication. Our strategy is making the most of BS's energy, so the node energy in the network is saved furthest. Simulation results show that EEMR clearly prolongs the network lifetime over HEED.

With the increasing prominence of the Internet as a tool of commerce, security has become a tremendously important issue. One essential aspect for secure communication over networks is that of cryptography. The increasing prominence of mobile devices has increased the necessity for hardware implementations of cryptography algorithms. Tiger hash function is the new hash function proposed which is very fast and secure. To the best of our knowledge there are no known architecture design proposal except an FPGA design implementation for Tiger Hash In this paper, we describe a prototype for Tiger Hash Primitive Hardware Architecture, which increases the security and speed factors when implemented.

Efficiently locate data is a fundamental problem for future applications of wireless sensor networks (WSNs). It is known that distributed hash table (DHT) based Internet peer-to-peer (P2P) protocols provide near-optimum data lookup times for queries made on networks of distributed nodes. In this paper we propose a novel two-tier Chord based network protocol for serving efficient queries in WSNs (C2WSN), which has a

Byzantine faults in a peer-to-peer (P2P) system are re- sulted from adversarial and inconsistent peer behaviors. Faulty peers can disrupt the routing functions in the peer joining and lookup schemes. Byzantine attackers may col- lude with each other to paralyze the entire P2P network op- erations. We discover a novel DHT-based overlay networks (REIK) with Byzantine fault tolerance. REIK based on a ring which embeds an inverse Kautz digraph IK(d, m), to enable multi-path P2P routing. The inverse Kautz network provides multiple entry points and multiple routes between node pair. The REIK overlay is the first constant degree and O(log n) diameter DHT scheme with constant congestion and Byzantine fault tolerance. For large d 2, the REIK overlays handle random and Byzantine faults effectively, far beyond the capability of Chord and CAN.

The topological properties of Peer-to-Peer (P2P) overlay networks are critical factors that dominate the performance of these systems. The P2P networks need a topology with arbitrary size and degree, while the Kautz digraph is a topology with good properties such as constant degree and optimal network diameter O(logd N). However, the limitation of the Kautz digraph is its poor degree of extension. In this paper, we propose a novel P2P network with constant degree which is based on generalized Kautz digraph and the ring (BGKR). Resources are located by using a slightly modified approach of the distributed hash table (DHT) concept. Each data item is looked up on a set of nodes sharing the same prefix with key associated to that data item. This can be exploited for preserving load balancing in the network. Each node maintains a maximum limited number of 2d +1 entries in its routing table, and routing between any two nodes in BGKR can achieved in at most logd(((N(d-1))/d+1)+1) hops. The routing length of BGKR is shorter than KZCAN and D2B with the same degree when the P2P network is large scale.

The topological properties of peer-to-peer (P2P) overlay networks are critical factors that dominate the performance of these systems. The P2P networks need a topology with arbitrary size and degree, while the Kautz digraph is a topology with good properties such as constant degree and optimal network diameter (9(logd n). In this paper, We describe that KZCAN is a novel P2P network with constant expected degree. It is based on an overlay network preserving Kautz digraph connections dynamically, and on a distributed hash table (DHT) supporting efficient publish and search procedures. KZCAN shows that the DHT scheme with constant expected degree andean achieve logd(n/(d+1)) +1 diameter. The routing length of KZCAN is shorter than CAN or D2B with the same degree when the P2P network is large scale.

In this paper, by using the fixed point index method, we establish the existence of at least one or at least two positive solutions to m-point boundary value problem for the second order differential equation with an advanced argument {u"(t)+a(t)f(u(h(t)))=0, t isin (0,1), u(0)=0, Sigmai=1 m-2 kiu(xii)=u(1), where 0=xi0