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Abstract: Optimized configuration of energy industry is an issue for resource combination and optimization, which includes continuous variable and discrete variable and belongs to the optimal power flow research. In order to improve the solution quality and the counting efficiency, this paper gives the solution using the mixed Greedy Algorithm and Genetic Algorithm: Use the superiority of Greedy Algorithm to obtain the original resource distribution solution space in the structure. This algorithm can minimize the spatial scale. And then utilizes the Genetic Algorithm to select the original solution space based on the overall situation and improve its application efficiency. The test case matches the anticipation. [Copyright &y& Elsevier]

Abstract: It is shown that the flow in the low permeability medium is nonlinear, which is quite different from the general Darcy flow. In this paper, we first present a survey of methods that has been used to analyze the low permeability well problems for the past 10 years, then we present two new coupled models that behaves better in complex situations. We assume that there are two different zones near the wellbore and the flow characteristics in the inner zone is different from that in the outer zone, and there is an connecting interface between them, as mentioned before, we called them coupled models. In this paper, we also give four different types of the typical curves for four different models and use the methods of alternating iteration algorithm to solve the nonlinear differential equation system. These four different types of the curves will cover the typical problems that will possibly be encountered when exploring the low permeability reservoirs. [Copyright &y& Elsevier]

Abstract: Distinguished from former literature which focuses on the static or balanced analysis, this paper established the timevarying parameters model based on state space model to find the dynamic relationship between China''s energy consumption and economic growth. After applying Chow test, unit root test and cointegration test, this paper estimated the parameters of state space model with Kalman Filter Algorithm, then found and analyzed their internal regularity. [Copyright &y& Elsevier]

Abstract: In order to apply cockroach swarm optimization (CSO) algorithm to more function optimization and improve its accuracy, this paper improve CSO by modifying chase-swarming behavior of cockroach, and apply the modified CSO to optimize several Benchmark Problems. The results of simulation experiments illustrate that modified CSO has stronger convergence performance and highly-accuracy optimization results compared with Particle Swarm Optimization (PSO) and Chaotic Particle Swarm Optimization (CPSO). [Copyright &y& Elsevier]

Abstract: Object-oriented Framework (OOF) enable reuse at both code level and design level by capturing the commonalities of an application domain into a set of carefully designed abstract classes with well-defined collaborations .It is very difficult to use OOF because the sizes of the framework are often large and many of the existing frameworks suffer from the lack of proper manuals and documentation. In this paper, the concept of Maximum Sharing sub-Edge Tree (MSET) is proposed. Based on the MSET, we propose an algorithm for mining the framework hot-spot instantiation pattern. [Copyright &y& Elsevier]

Abstract: Finding the lowest common ancestor (LCA) of two nodes in a binary tree has been focused both in graph theory and computer science. The paper puts forward and proves an analytic criterion for the LCA of two neighboring nodes in a complete binary tree. The criterion mainly concerns addition, subtraction and bitwise operations, needs no searching procedures and thus is easy to implement in software programming as well as hardware programming. An algorithm that has logarithmic time complexity is also presented with C-language implementation in the paper. [Copyright &y& Elsevier]

Abstract: In the course of mining frequent neighboring class set, present algorithms have some redundant candidate and repetitive computing, which are only able to efficiently extract short frequent neighboring class set, and so this paper proposes an algorithm of fast duplex mining frequent neighboring class set, which is suitable for mining any frequent neighboring class set. This algorithm adopts two methods to generate candidate frequent neighboring class set in the mining course. One is using top-down search strategy to generate candidate by numerical index, the other is using anti-code of front this candidate to generate next candidate frequent neighboring class set. The course of top-down search strategy used by the algorithm isn’t different from traditional top-down search strategy, which uses numerical index to generates k-subset of (k+1)-non frequent neighboring class set. By the two methods, the algorithm may delete redundant candidate and repetitive computing. The algorithm creates digital database of neighboring class set via neighboring class weight, according to character of database, it also uses digit logical operation to computes support. The result of experiment indicates that the algorithm is faster and more efficient than present algorithms when mining frequent neighboring class set in large spatial data. [Copyright &y& Elsevier]

Abstract: Location information is critical essential and indispensable for many applications of wireless sensor networks. Beacon-based localization schemes are more precise than beacon-free ones, but the beacon nodes are more expensive than ordinary sensor nodes. Recently, there has been much focus on mobile-beacon based localization, for they can lower the cost while keeping the localization precision. This paper surveys the current state of the art for mobilebeacon based localization algorithms. We give the taxonomy of these schemes including range-base vs. range-free, single beacon vs. multi-beacons, omni-directional vs. directional antenna. Moreover, we also give a review of path planning methods which are critical to localization algorithm with mobile beacon, and we classify them into static and real-time schemes. We briefly introduce the steps of each localization and path planning algorithm, which serves as an introduction and survey for researchers interested in the area of localization of wireless sensor networks. [Copyright &y& Elsevier]

Abstract: To save time, improve flexibility and guarantee accuracy of the navigation system of the mobile robots, a multifunction landmark and a new navigation algorithm are proposed in this paper. With the new algorithm and landmark the mobile robots can be located by only a single landmark, and can be navigated in a large area by serial landmarks. The simple configuration and the convenient material of the landmark increased the system''s flexibility and decreased the complexity of the algorithm. From the experimental results it can be concluded that the navigation system has fast navigation speed and high navigation accuracy. [Copyright &y& Elsevier]

Abstract: Orthogonal frequency division multiplexing (OFDM) suffers from a high peak-to-average power ratio (PAPR).Tone reservation is a popular PAPR reduction technique that uses a set of reserved tones to design a peak-canceling signal. In this paper, the performance and complexity of clipping noise guided, complex base-band active-set methods based on tone reservation for PAPR reduction are analyzed and simulated. The simulation results show that the two clipping noise guided methods, the adaptive scale method and constant scale method, have better performance than complex base-band active-set methods. Furthermore, the complexity of the constant scale algorithm is lower than the adaptive scale and the complex base-band active-set algorithm. [Copyright &y& Elsevier]

Abstract: Chaos immune optimization algorithm on distribution service restoration after faults is presented to improve the probability for optimal solution in this paper, which is integrated the characteristic of chaotic optimization with artificial immunity algorithm. In the proposed algorithm, excellent global search ability of chaotic optimization is regarded as “thick search” to initialize the antibody of immune algorithm, and local search of artificial immune algorithm is applied to replace “thin search” in the chaotic optimization, which assures the population diversity and avoids getting to stuck in local minima to a certain degree. A living example for a certain district distribution in Chongqing is analyzed by the method presented in this paper. The result shows that chaos immune optimization algorithm in the paper might improve convergence speed and precision of restoration and avoid premature convergence. [Copyright &y& Elsevier]

Abstract: According to these shortcomings when Apriori is used to mining spatial topology association rules. This paper proposes an algorithm of mining spatial topology association rules based on complement set, which is used to mining spatial multilayer transverse association rules from spatial database. This algorithm generate candidate frequent topological itemsets not only by up search strategy as Apriori, but also by computing complement set of candidate from up search strategy, which is suitable for mining any spatial topological frequent itemsets. This algorithm compresses a kind of spatial topological relation to form an integer. By the way, firstly, the algorithm may efficiently reduce some storage space when creating mining database. Secondly, the algorithm is fast to obtain topological relation between two spatial objects, namely, it may easily compute support of candidate frequent itemsets. Finally, the algorithm may fast generate candidate via double search strategy, i.e. one is that it connects (k+1)-candidate frequent itemsets of k-frequent itemsets as up search strategy, the other is that it computes complement set of (k+1)- candidate frequent itemsets. The result of experiment indicates that the algorithm is able to extract spatial multilayer transverse association rules from spatial database via efficient data store, and it is very efficient to extract any frequent topology association rules. [Copyright &y& Elsevier]

Abstract: A new quantum-behaved particle swarm optimization algorithm with inverse proportional inertia weight is presented and proved in this paper. Also a robust design method of optimization is used by optimizing the robustness of both the system objective function and constraint functions in solving the problem of breach of condition to the constraint functions. Comparing the solution of the traditional optimization and the solution of the robust optimal design, the robust design parameters display a significant stability in performance when the value of the parameters changed and all the optimizations are solved by this new efficient algorithm. [Copyright &y& Elsevier]

Abstract: In frequent neighboring class set mining, when generating candidate frequent itemset, present algorithms have some redundant candidate and repetitive computing, and so this paper proposes an algorithm of complementary mining frequent neighboring class set, which is suitable for mining any frequent neighboring class set. This algorithm adopts double search strategies to generate candidate frequent neighboring class set in the mining course. One is using down-up search strategy to generate candidate, namely, it connects two k-frequent neighboring class sets to generate (k+1)-candidate frequent neighboring class set. The other is computing complement set of (k+1)-candidate to generate next candidate frequent neighboring class set. By the two ways, the algorithm may delete redundant candidate and repetitive computing. The algorithm creates digital database of neighboring class set via neighboring class weight, according to character of database, it also uses digit logical operation to computes support. The result of experiment indicates that the algorithm is faster and more efficient than present algorithms when mining frequent neighboring class set in large spatial data. [Copyright &y& Elsevier]

Abstract: In this paper, we analyzed the multi-instance multi-label (MIML) learning structure which proposed by Zhou. In realworld, there are many problems mentioned in complicated systems, traditional MIML structure would only consider the initial and final state, when facing with more tanglesome system, the lack of middle decision layer will affect the whole capability of system. The new proposed structure – layered MIML frame will help us to solve these tasks more easily by middle layer with reward mechanism. Finally, we use RoboCup Simulation 2D as platform to verify our frame and algorithms, the result shows the frame presented is valid and well-performed. [Copyright &y& Elsevier]

Abstract: With the development of multicore architectures, multicore real-time scheduling has become a hot topic. Cache warm-up overheads introduced by task migration between two cores lead to some tasks miss deadlines in time-critical systems. In this paper, we propose a scheduling algorithm based on push-assisted model, which is a hardware mechanism used to proactive migrate cache lines of tasks. Our scheduling algorithm provides software support for proactive migration. It is shown that our algorithm is effective in some examples. [Copyright &y& Elsevier]

Abstract: Recent research shows that CoSaMP with partially known support has better performance than traditional CoSaMP. However, there is lack of theoretical analysis for this algorithm. In this paper, we propose a new algorithm which combines CoSaMP with Shannon sampling and obtain the theoretical guarantee. The proposed method measures partially known support part of a sparse signal with Shannon sampling and measures the rest part with compressive sensing. Comparisons with previous related works are shown. [Copyright &y& Elsevier]

Abstract: Supporting high mobility will be an important character of the future wireless communication systems. It challenges the channel estimation technique a lot and there are two tough problems in front of us, they are multi-path fading channel and bandwidth efficiency. Orthogonal Frequency Division Multiplexing (OFDM) technique changed the frequency selective multi-path fading channel into flat fading channel in frequency domain which effectively mitigates the effects of multi-path propagation and, hence, increase data rate. In this paper, we discuss the principle of MIMO-OFDM systems based on the introduction of fading channels. Furthermore, the channel estimation technique in MIMO-OFDM system is investigated, with the emphasis on training-assisted channel estimation method. Firstly, we summarize and analyses the exiting channel estimation methods in MIMO-OFDM system. Secondly, we proposed a new channel estimation method for MIMO-OFDM system based on training sequence. A novel pilot pattern with higher frequency efficiency is established and we use a reasonable manner to insert pilot so that the system greatly reduced the training cycle, increased data rates. Finally, in order to track the time-varying channel, an improved direct decision method is further adopted. Theoretical analysis and numerical results show that the new channel estimation scheme can offer a good performance and a high ability to track the time-varying channel. [Copyright &y& Elsevier]

Abstract: Fuzzy association rules are easily understood by users. Simulated annealing algorithm is an effective approximation algorithm which is suitable for solving large-scale combinatorial optimization problem. In this paper we proposed a classifier design method based on simulated annealing algorithm and fuzzy association rules. It can achieve satisfied accuracy and a small number of classification rules. Experiments demonstrated the effectiveness and advantages of the proposed algorithm. [Copyright &y& Elsevier]

Abstract: Model transformations are frequently applied in model-driven development to bridge between languages on a different level of abstraction and formality. In This paper, we define a transformation from UML 2.0 Activity diagram(UML-AD for short) to YAWL, a formal workflow language that is able to capture all of the 20 workflow patterns reported in. The transformation is mainly concerned on the control-flow aspects of UML-AD models. We illustrate the transformation challenges and present a suitable transformation algorithm. The benefit of the transformation is threefold. First, it clarifies the semantics of UML-AD via a mapping to YAWL. Second, the deployment of UML-AD business process models as workflows is simplified. Third, UML-AD models can be analyzed with YAWL verification tools. a [Copyright &y& Elsevier]

Abstract: The Completions of Inverse M-matrices Patterns have been discussed widely. But the researches are all aimed at the patterns whose entries in diagonal positions are all specified. In the paper, we will drop the condition and mark the diagonal entries about its specified or unspecified. We will discuss the completion theorem and algorithm of the partial inverse M-matrix whose graph is a Ω-tree. [Copyright &y& Elsevier]

Abstract: Many applications of Wireless Sensor Network need to determine the node''s absolute or relative position automatically and accurately. An improved DV-Hop localization algorithm is proposed in this paper. Three levels of correction will be implemented. First, the average hop distance error of all the beacon nodes is eliminated. Second, the overlap of the path is eliminated. And third, the average hop distance of network is calculated. The simulation results show that the proposed improvements can enhance the localization accuracy and coverage of the nodes. [Copyright &y& Elsevier]

Abstract: This paper introduces the granular computing thought and method into evolutionary algorithm. Take the solving process of the evolutionary algorithm as an information system; adopt the equivalent relation to divide the solution space and objective function, form subspace granule or objective function granule. On this basis, we proposed the conception of granularity fitness landscape. We use the methods of binary granular computing to find the relation between subspace granule and objective function granule, express the dependency of objective function to the individuals at macroscopic. Take this as foundation to carry out the mutation operator what was direct by granular fitness landscape, this operator can improve the convergence rate of the evolutionary algorithm remarkable. [Copyright &y& Elsevier]

Abstract: Protein-protein interaction (PPI) network is essential to understand the fundamental processes governing cell biology. It is well known that document classification systems are potential to accelerate the curation process by retrieving PPI-related documents. However, it is usually a case that there is an imbalanced two class data set on text classification. Learning from imbalanced data sets is an important challenge to the machine learning community. In this paper, we compare the performance of several document classifiers on one PPI document set and vary the size of the number of positives and the ratio of the number of positives to the number of negatives on training set and testing set in the experiment. Through the experiment, we try to find what kind of classification algorithm is suitable for imbalanced PPI document classification. [Copyright &y& Elsevier]

Abstract: In the paper, least squares support vector machine trained by chaos particle swarm optimization (CPSO-LSSVM) is applied in the classification. Chaos particle swarm optimization algorithm is introduced to select the suitable training parameters of least squares support vector machine. That is because chaos particle swarm optimization algorithm can avoid being trapped in local optimum and gaining the global optimum quickly in the process of search by combining particle swarm optimization with chaos queues. The experimental results demonstrate that least squares support vector machine trained by chaos particle swarm optimization is best classification results in the three classification algorithms. [Copyright &y& Elsevier]

Abstract: This paper introduces a practical monitoring system, which integrates RFID transceivers with kinds of pressure sensors to enable to locate the real time position of miners under the mine as well as to detect kinds of pressure parameters, which are critical for the mining process. The background UDP software platform uses a modified round robin algorithm to communicate with sub-stations under the mine to obtain the real-time information. User platform uses the B/S structure to enable end users to use the IE browser only to access the system anywhere with Internet connected. [Copyright &y& Elsevier]

Abstract: In this paper, considering the problem of low computing and low precision for the least square (LS) algorithm pilot- based in OFDM system, a novel channel estimation algorithm based on discrete Fourier transform (DFT) by transform domain, the proposed method will force time domain response value to zero beyond the length of cycle, the precision of estimation is improved, and setting threshold for time domain response within the length of the cycle to further reduce the noise on the impact of channel estimation. The proposed algorithm retains the advantages of LS algorithm, improve the accuracy of channel estimation, and simulation results show the effectiveness of algorithm. [Copyright &y& Elsevier]

Abstract: Remote sensing data has an important application value and scientific significance .in retrieval of lake surface temperature (LST). On September 6, 2008, China successfully launched two optical small satellites (respectively called HJ-1A, HJ-1B.) to monitor and predicate environment and disaster. HJ-1B satellite includes an infrared camera (IRS). The camera has a thermal infrared band which can dynamically monitor LST of large river basins in 4 days. HJ-IRS is a new sensor, so there are few papers researching on the retrieval of LST.The main goal of this paper is to introduce a practical method to obtain LST from HJ-IRS thermal data. In this paper, we reviewed primary algorithms of LST retrieval and mainly analyzed Qin′s mono-window algorithm retrieving LST from Landsat TM6 (Thematic Mapper) thermal data. This algorithm included two empirical relationships about atmospheric transmittance and atmospheric average temperature. But these relationships are only suitable for TM6. So on the basis of the spectral response function of HJ-IRS therma1 band we use radiance transfer software MODTRAN4 to simulate and calculate new coefficients in the two relationships. New algorithm requires three parameters: emissivity, vertical water vapor column and atmospheric temperature about 2 meters above the ground. We use two images of Lake Taihu to retrieve LST and validate the improved algorithm. Bias of LST retrieved from HJ-IRS data and the field measurements are smaller than 1.2K, which means this algorithm is applicable for HJ-IRS therma1 band to retrieve LST. [Copyright &y& Elsevier]

Abstract: The experimental amount for solving flutter derivative of bridge by free vibration method brought up by R.H.Scanlan is very large, and in process of extracting cross derivative it is difficult to achieve that frequency ratio and damping ratio of vertical motion and torsional motion of model is the same in all wind speed. Besides, the identification error of uncoupled derivative will be in coupled derivative. The paper presents an improved method based on Ibrahim time domain. Extracting all flutter derivatives of bridge deck with optimizing algorithm of DFP is better in solving the nonlinear parameter identification than the least squares method. [Copyright &y& Elsevier]

Abstract: There are many factors involved in slope stability evaluation and the principle ones acts differently under different slope environmental conditions. So the evaluation of slope stability demands for consideration for all kinds of factors generally with clear understanding of primary and secondary factors. Based on the theory of ant algorithms and cellular automaton, this paper puts forward a cellular ant algorithm and mathematic description with MATLAB to optimize the accuracy of slope stability evaluation and verifies the applicability of the algorithm through real project and achieves good results. [Copyright &y& Elsevier]

Abstract: Small Unmanned aerial vehicles commonly use PWM signals for servo control. In order to verify the flight controller design, it is necessary to measure the PWM control signals. There are two difficulties: real-time and high precision. The PWM signal must be measured per 20ms punctually and the pulse width must be accurate to 0.001ms. In this paper, a new pulse width measuring method based on VxWorks and PCI8554 timer card is introduced, including the structure of measurement system, measurement algorithm and VxWorks driver developing techniques of PCI device. By testing, this measurement system''s real-time and accuracy performance satisfied UAV test facilities’ requirements. [Copyright &y& Elsevier]

Abstract: License plate recognition system(LPRS) is one of the most important parts of the intelligent transportation system(ITS),and the license plate location is the most important step of the LPRS,it derectly affects the performance of the character segmentation and recognition afterward.In this paper,an effective algorithm of lisence plate location is proposed.In this method,Firstly we obtain high frequency coefficient through 1-D discrete wavelet transform. Then we process the image with median filtering, binarization and morphology operation.Finally,we label and record the connected regions. Then we can locate the candidate license plates according to the region information. Experiment proved that our method performs well in the long range and complex scenes,and performs well on located speed and robustness. [Copyright &y& Elsevier]

Abstract: A distribution network reconfiguration method based on simulated annealing immune (SAI) algorithm is proposed in this paper. According to the characteristics of reconfiguration, loop encoding is used and the public switches between loops are disposed in advance, so the individuals in evolution turn to be feasible. Besides, the historic and present optimal individuals are combined to construct vaccine dynamically, and not only the speed of evolution searching but also the individual performance can be improved by inoculation. On the other hand, the selection operator based on Boltzmann annealing method, high frequency mutation and immune supplement are used to keep the population diversity. Through the improvements, the early maturity is avoided effectively. Reconfiguration results show the prompt convergence and effectiveness of proposed method. [Copyright &y& Elsevier]

Abstract: This paper presents a fast optimal generator shedding algorithm which is on the basis of predictor-corrector method and time domain simulation for transient stability. It includes two parts that are the fast time domain simulation and optimal generator shedding. On the basis of the generator''s classical model and load''s constant impedance model, this paper use fourth-order Hamming predictor-correction formula to compute differential equations of the system with large step length, in order to improve computing speed. The second part shows how to calculate the sensitivity of transient stability constraint function to control variables, by the application of optimal control theory. Combined with the discrete characteristics of generator shedding, “Micro-step discrete method” is proposed, which is fast, accurate and so on. The advantages of this method are verified by analysis results of New England 39-bus test system. [Copyright &y& Elsevier]

Abstract: The paper adopts the method of modularized modeling, creating an electro-mechanic simulation model for a Microturbine Generation System (MTGS), including the micro-turbine engine, permanent magnetic synchronous generator, rectifier and inverter. In this paper, control strategy for grid-connected and islanding operations of a micro-turbine generation system is researched, the former adopts output voltage control strategy to maintain the output voltage of the load, and the latter adopts a dual closed-loop control algorithm based on PQ decoupling. A new control strategy to regulate the output power of MTGS based on the combination of decoupled control of output voltage and hysteresis current control is also introduced. Simulations have been done, and result proves the feasibility of the strategy. [Copyright &y& Elsevier]

Abstract: Power system restoration is well-recognized as one of the major technologies to improve system reliability. A high efficient restoration strategy is established and implemented with accurate information acquisition. Phasor measurement unit (PMU) provides a state-of-the-art information monitoring technology. In this paper, with PMU measurements, several algorithms are proposed to ensure complete observability of systems under regular operating conditions and during system restoration process. Case studies on IEEE 14, 30, 57, 118 and 300 – bus systems validate efficiency of the proposed algorithms. [Copyright &y& Elsevier]

Abstract: Wind power prediction is of great importance for the safety and stabilization of grids. The most important and difficult problem now is to enhance the prediction precision. BP (Backward Propagation) neural network has been used extensively in wind power prediction. But BP network is apt to getting into local minima and its convergence rate is slow. Tabu search is a kind of intelligent algorithm, which can achieve the global optimizations. This paper put forward a wind power prediction model of BP neural network optimized by tabu search algorithm with memory function. The result shows that with appropriate input parameters, the wind power prediction model of neural network based on tabu search algorithm can improve the prediction precision as well as the convergence rate. [Copyright &y& Elsevier]

Abstract: Distributed generation (DG), and especially microturbine generation (MTG) system, plays a significant role in Smart Grids. One of the most important variables of a MTG system is the fuel consumption. This paper defines a problem on fuel consumption of MTs for a sample load change that can be used for a 24-hour load change pattern. The aim is to optimize the speed governer parameters in order to minimize the fuel consumption of MTG. Differential Evolutionary Algorithm (DEA) is employed to solve the problem. The stability issue of the MTG system is also discussed in the paper. The simulation results show the effectiveness of a fine-tuned speed governer by using the proposed method. [Copyright &y& Elsevier]

Abstract: Distributed Generation (DG), and especially microturbine generation (MTG) system, plays a significant role in Smart Grids. One of the most important variables of a MTG system is the governer speed. This paper defines a problem on transient speed response of MTs for a step load. The aim is to optimize the speed governer parameters in order to minimize the transient response of MTG. Differential Evolutionary Algorithm (DEA) is employed to solve the problem. The stability issue of the MTG system is also discussed in the paper. The simulation results show the effectiveness of a fine-tuned speed governer by using the proposed method. [Copyright &y& Elsevier]

Abstract: This paper proposes a Gaussian radial basis function network (GRBFN) based wind speed estimation algorithm for maximum power point tracking (MPPT) of wind power generation system (WPGS). A specific design of the proposed control algorithm for the WPGS with a doubly-fed induction generator (DFIG) is presented. The aerodynamic characteristics of the turbine are approximated by a GRBFN based nonlinear input-output mapping. Based on this nonlinear mapping, the wind speed is estimated from the measured generator electrical output power while taking into account the power losses in system and the dynamic process of shaft system. The estimated wind speed is then used to determine the optimum DFIG rotor speed for maximum wind power extraction. Then the DFIG rotor speed is controlled with the wind speed change, the maximum power extraction can be achieved. Simulation model of 1MW WPGS is built in MATLB/SIMULINK software. The validity and feasibility of the proposed control algorithm is verified by simulation experiment. The simulation results show that the wind speed can be estimated accurately and WPGS can operate in the optimum operating point without mechanical anemometer. [Copyright &y& Elsevier]

Abstract: This paper presents a method for using hydrogen storage to assist in integration of large scale photovoltaic (PV) generation system into the utility grid. An algorithm based on the simple exponential smoothing is used to suppress short term power fluctuations in PV generation. To facilitate economic dispatch by the system operator, the output of the exponential smoothing is held constant for a given dispatch interval. The more stable, step-wise constant power then acts as the power reference to be sent to the utility grid. The resulting power ripple (from the smoothing) and power error (from the step-wise forecast) is then absorbed by the hydrogen storage such that any PV power above the scheduled grid power curve is used to produce hydrogen using an electrolyzer and any power deficit is produced by a fuel cell. Simulation studies based on realistic irradiance data conducted in SIMULINK/SIMPOWER verifies the effectiveness of the developed method. [Copyright &y& Elsevier]

Abstract: Standalone solar power system provides simple yet flexible solution to certain applications which demand high mobility. This paper introduces the design of a single solar panel powered induction machine-driven water pump system, which is used in an on-board nanofilteration system. The system configuration is evaluated at the first stage to provide high ratio voltage step-up; and complementary PWM and space vector PWM scheme is chosen for dc-dc stage and dc-ac stage respectively; V/F based control scheme is designed and integrated with maximum power point tracking algorithm for the best use of solar panel. The control system is implemented digitally in a TMS320F2812 DSC. Meaningful mode of operation is tested and satisfactory experimental results are collected. [Copyright &y& Elsevier]

Abstract: This paper first briefly introduces the image of the principles of geometric distortions. And in the basis of analyzing polynomial algorithm on the coordinate conversion, it approaches a distortion algorithm non-uniform by region. The fixed focus image is established to the corresponding model and non-uniform divided to rectangular areas which are within a polynomial in a high order polynomial. By comparing the correction effect and devotion of time of the correction method between one order region and third order polynomial, the validity of the proposed method by the article can be verified. [Copyright &y& Elsevier]

Abstract: This paper considers the issue of generating centralized controller station in hybrid wireless mobile network containing centralized infrastructure together with distributed ad-hoc nodes. This kind of network works well in high dynamical environment, featuring much with traditional ad-hoc networks yet differs significantly in network coordination. We proposed an adaptive algorithm for network controller generation by evaluating every node in terms of living time and remaining energy. A new metric, namely average path length is proposed to evaluate the stabilizing time. Based on specific applications, weighted sum of above three metrics are calculated, with different weighted factors reasonably chosen, desired controller is selected with maximum output. We verify the algorithm finally in a prototype network and test results show that the proposed algorithm improves flexibility converging speed as well as anti-damage of the network. [Copyright &y& Elsevier]

Abstract: Semi-supervised cluster ensemble combines semi- supervised learning and cluster ensemble to increase the precision of clustering. And it conquers the disadvantages of the selectivity, bias, low precision and bad generalization. And conquers that unsupervised learning can’t take advantages of known information of datasets. As a result the precision, robustness and stability of cluster ensemble are increasing. Now semisupervised cluster ensemble is researched at the very outset. The paper''s main goal is to construct an algorithm of semi-supervised cluster ensemble. In this paper it includes as follows. First the advantages of semisupervised cluster ensemble are stated; Second the algorithm of semi-supervised cluster ensemble is established; Third the experiments of semi- supervised cluster ensemble, such as the results,the datasets, the types and the steps of experiments, are studied. [Copyright &y& Elsevier]

Abstract: With the rapid development of the Intemet, information overload and isotropic becomes worse and worse. Personalized services system''s birth partly resolved this problem. The traditional recommendation methods, such as content based recommendation and collaborative filtering, do help a lot. However, to some extent, it couldn’t authentically understand the preference of users. Considered the limitations of the traditional methods, tag recommedation spring up. This paper makes expanded research based on tag reccommendation. With semantic matching, a certain tag turns to a similar tag set. Acording to co-occurence of tags, a tag is expended to a ralated tag set. Integrate these tag set to generate recommendation list is better than single tag recomendation by experimental observation. Besides, this paper also adopt time degradatioin aglorithm which improved the recommender''s accuracy and efficiency. [Copyright &y& Elsevier]

Abstract: An improved spectral clustering approach based on differential evolution algorithm (DESC) is proposed in this paper. In our algorithm, we replace k-means with differential evolution (DE) as the final step in spectral clustering, thus it overcomes the deficiencies in sensitivity to initialization and local optima. Experimental results over artificial dataset and UCI dataset demonstrate DESC''s superiority in difficult clustering, steady performance and better accuracy. [Copyright &y& Elsevier]

Abstract: The parallelization of geo-computation is one of the kernels in High Performance Geographic Computing (HPGC). To gain the benefit provided by multi-core computer, lots of effort has been done on parallelizing classical serial algorithms, one of which is the plane sweep algorithm (PSA). A framework of parallelization when intersecting two sets of segments has been suggested. However, when focusing on the Minimum Bounding Rectangles (MBRs) in the filtration process in GIS, different optimization needs to be considered. In this paper, a parallel version of MBR based PSA is designed and implemented using OpenMP. The experiment results show that by carefully choosing the number of threads and semi-sets, the proposed algorithm can significantly outperform the serial version on real-life data sets with a high speed-up. [Copyright &y& Elsevier]

Abstract: String match algorithm is widely used in the area of data mining. In this paper, we present an approach for elevating the performance of this algorithm via GPU (Graphic Processing Unit). With the rapid development of Graphics Processing Unit to many-core multiprocessors, it shows great potential in many applications and high performance computing. Especially, the heterogeneous architecture CPU+GPU shows enthusiastic capacity to accelerate parallel applications. Till now, some research has been done for parallel implementation of string match algorithm on GPU. But there are some constraints for acceleration of this algorithm: firstly, if-branch exists in the algorithm which can cripple the performance of the parallel implementation; secondly, improper memory access may bring heavy latency generated by bank-conflict. This paper presents the optimization of global memory access, shared memory access and the elimination of if-branch for elevating the performance of string match algorithm BMH. Meanwhile, we explore the interesting characteristics of the parallel BMH string match algorithm implemented on GPU using CUDA. We found that the performance elevation is affected by the characteristic of pattern, which also proves the potential of GPU. [Copyright &y& Elsevier]

Abstract: The detection of small targets that submerges in the homogeneous image background is a difficult problem in the design of small targets detection algorithm. The concept of local reverse entropy combining the concepts of local ntropy with reverse entropy is proposed in this paper, which is to solve that problem by enhancing small targets. The norms of local signal-to-background ratio and elapsed time are used to demonstrate the performance of local reverse ntropy map. Both quantitative analysis and qualitative comparison confirm the validity and efficiency of the resented approach. [Copyright &y& Elsevier]