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At present, several provinces' power supply companies have established harmonic monitoring platform in China, by real-time monitoring the voltage and current of power grid, then upload these data to the main station to analyze and settle. The platform can collect about 1 TB(1TB=1000GB) data every day[12], these data contain all the indexes of power quality, but we can only use this platform to do some basal data analysis work, but not processing analysis with multi-indexes, so that it does not show strong supporting effort to the power grid operation. With the development of energy internet and the third industry, more and more unstructured data are impacting the power grid operation, how to make better use of big data technology to deal with the data from monitoring platform has became the focus of the power grid company. In this paper, some introduces of contents and characteristics of harmonic real-time monitoring platform and big data technology has been made, by comparing the way of using and settling data of platform to the big data technology, meanwhile by combining with the characteristics of power quality data, we analyze the combination of the two prospects. At last, the development direction of the advanced application for the harmonic line monitoring system is discussed in this paper.

The genomic scaffold filling problem has attracted a lot of attention recently. The problem is on filling an incomplete sequence (scaffold) I into I', with respect to a complete reference genome G, such that the number of adjacencies between G and I' is maximized. The problem is NP-complete and APX-hard, and admits a 1.2-approximation. However, the sequence input I is not quite practical and does not fit most of the real datasets (where a scaffold is more often given as a list of contigs). In this paper, we revisit the genomic scaffold filling problem by considering this important case when, (1) a scaffold S is given, the missing genes X = c(G) - c(S) can only be inserted in between the contigs, and the objective is to maximize the number of adjacencies between G and the filled S' and (2) a scaffold S is given, a subset of the missing genes X' subset X = c(G) - c(S) can only be inserted in between the contigs, and the objective is still to maximize the number of adjacencies between G and the filled S''. For problem (1), we present a simple NP-completeness proof, we then present a factor-2 greedy approximation algorithm, and finally we show that the problem is FPT when each gene appears at most d times in G. For problem (2), we prove that the problem is W[1]-hard and then we present a factor-2 FPT-approximation for the case when each gene appears at most d times in G.

To improve fuel economy and reduce operating costs are one of the future developments of the air transport. From another part, it is continually called for higher speed to satisfy the global reach and make the world as a neighbor. An airworthiness problem of supersonic civil aircraft is the propulsion system noise. The ACE (adaptive cycle engine) noise is explored at the state of takeoff based on the description and analysis of aero engine noise and supersonic air transport. The conceptual scheme of ACE is shown and then the calculation method of each component is studied, including fan, combustor, turbine and nozzle. The total noise level (EPN dB) is calculated and the impact of components noise is analyzed. The research shows that the ACE noise is lower than the supersonic aircraft Concorde but higher than actual subsonic civil engine. The nozzle and fan should be paid an attention at the noise suppression and the airport location for supersonic aircraft could be a condition of market acceptation.

Based on m-stems and semi-extensible structure, a model is presented to represent RNA planar pseudoknots, and corresponding dynamic programming algorithm is designed and implemented to predict arbitrary planer pseudoknots and simple non-planar pseudoknots with O(n4) time and O(n3) space. The algorithm folds total 245 sequences in the Pseudobase database, and the test results indicate that the algorithm has good accuracy, sensitivity and specificity. *Supported by National Natural Science Foundation of China (Grant Nos. 60573024 and 60573181), the Research Project of Shandong Economic University (01610784), and NSF of Shandong Provice (2005BS01014)

Hybrid carbon films composed of graphene film and porous carbon film may give full play to the advantages of both carbon materials, and have great potential for application in energy storage and conversion devices. Unfortunately, there are very few reports on fabrication of hybrid carbon films. Here we demonstrate a simple approach to fabricate free-standing sandwich-structured hybrid carbon film composed of porous amorphous carbon film and multilayer graphene film by chemical vapor deposition in a controllable and scalable way. Hybrid carbon films reveal good electrical conductivity, excellent flexibility, and good compatibility with substrate. Supercapacitors assembled by hybrid carbon films exhibit ultrahigh rate capability, wide frequency range, good capacitance performance, and high-power density. Moreover, this approach may provide a general path for fabrication of hybrid carbon materials with different structures by using different metals with high carbon solubility, and greatly expands the application scope of carbon materials.

A biclustering problem consists of objects and an attribute vector for each object. Biclustering aims at finding a bicluster—a subset of objects that exhibit similar behavior across a subset of attributes, or vice versa. Biclustering in matrices with binary entries (“0”/“1”) can be simplified into the problem of finding submatrices with entries of “1.” In this paper, we consider a variant of the biclustering problem: the k-submatrix partition of binary matrices problem. The input of the problem contains an n×m matrix with entries (“0”/“1”) and a constant positive integer k. The k-submatrix partition of binary matrices problem is to find exactly k submatrices with entries of “1” such that these k submatrices are pairwise row and column exclusive and each row (column) in the matrix occurs in exactly one of the k submatrices. We discuss the complexity of the k-submatrix partition of binary matrices problem and show that the problem is NP-hard for any k≥3 by reduction from a biclustering problem in bipartite graphs.

This paper briefly reviews NP-hard optimization problems and theirin approximability. The hardness of solving CLIQUE problem isspecifically discussed. A dynamic-programming algorithm and its improvedversion for CLIQUE are reviewed and some additional analysis ispresented. The analysis implies that the improved algorithm, HEWN(hierarchical edge-weighted network), only provides a heuristic oruseful method, but cannot be called a polynomial algorithm.

A review is presented of studies of polymeric membranes by applying positron annihilation lifetime spectroscopy (PALS). PALS has been used to study subnanometer-sized holes, to determine their size distribution and free-volume fractions, and to probe molecular-sized vacancies in glassy polymers. At present, PALS is believed to be a highly effective physical method for the examination of polymeric membranes.

This paper improves Itai and Rodeh's algorithm for finding a shortest cycle in an undirected unweighted graph. Given an undirected unweighted graph G with n vertices,the algorithm can determine a cycle whose length is at most k+1 where k is the length of the shortest cycle in G. The results of the experiment show that the improved algorithm runs faster than the original one when the input graph meets some special features.

Given an undirected graph with vertex and edge weights and a subset of vertices called terminals, the bounded size graph clustering (BSGC) problem is to partition the vertices into clusters of size at most a given budget such that each cluster contains at most one terminal and the total size of the clusters is minimized, where the size of a cluster is defined as the total vertex weight in the subset plus the total edge weight at the boundary of the cluster. For BSGC on trees, we present a pseudo-polynomial time exact algorithm, which can be modified via rounding to yield a (1+\epsilon)-approximation in polynomial time violating the given budget by a 1+\epsilon factor.

Given a graph G=(V,E) with real positive edge weights, where each edge (u, v) is labeled either + or – depending on whether u and v have been deemed to be similar or dissimilar, the problem of correlation clustering with l clusters is to partition the vertices of G into at most l clusters to minimize the total weight of + edges between clusters and – edges within clusters. This problem for general graphs is APX-complete. A fixed-parameter tractable (FPT) algorithm is presented, where the parameter k is defined as the maximum, over all blocks B of the graph, of the number of vertices that must be removed from B to obtain a forest.

The k-means clustering is one of the most popular schemes for discovering clusters in data. Its aim is to minimize the mean squared distance from each data to its nearest center. A lot of variants of Lloyd's heuristic have been studied. Unfortunately, many research results haven't given any approximate ratio. In this paper, an algorithm is presented which can obtain the optimal clustering with the ration of at most 2. The main idea of this algorithm is that k points are selected by means of a very simple, randomized seeding technique and then the local search is implemented to improve the accuracy. Some examples are selected to verify our algorithm and got better results both the speed and accuracy than the former methods. The main algorithmic contribution is that the input points are used as the candidate sets to obtain the optimal clustering with a constant ratio by means of local search technique and one method of selecting initial points.