基于树的多关键词搜索算法在网络监控系统中的应用

介绍了基于树的多关键词快速文本搜索算法,并针对该算法在实际应用中的问题提出了改进措施,在不增加预处理时间和内存空间消耗的前提下有效避免搜索中漏搜和多搜,无损于该算法的高效性。

CSMCCVA:Framework of cross-modal semantic mapping based on cognitive computing of visual and auditory sensations

Cross-modal semantic mapping and cross-media retrieval are key problems of the multimedia search engine.This study analyzes the hierarchy,the functionality,and the structure in the visual and auditory sensations of cognitive system,and establishes a brain-like cross-modal semantic mapping framework based on cognitive computing of visual and auditory sensations.The mechanism of visual-auditory multisensory integration,selective attention in thalamo-cortical,emotional control in limbic system and the memory-enhancing in hippocampal were considered in the framework.Then,the algorithms of cross-modal semantic mapping were given.Experimental results show that the framework can be effectively applied to the cross-modal semantic mapping,and also provides an important significance for brain-like computing of non-von Neumann structure.

FAST MUSIC SPECTRUM PEAK SEARCH VIA METROPOLIS-HASTINGS SAMPLER

A fast MUltiple SIgnal Classification (MUSIC) spectrum peak search algorithm is devised, which regards the power of the MUSIC spectrum function as target distribution up to a constant of proportionality, and uses Metropolis-Hastings (MH) sampler, one of the most popular Markov Chain Monte Carlo (MCMC) techniques, to sample from it. The proposed method reduces greatly the tremendous computation and storage costs in conventional MUSIC techniques i.e., about two and four orders of magnitude in computation and storage costs under the conditions of the experiment in the paper respectively.

Design of hybrid damping controller based on multi-target gravitational search optimization algorithm in a multi-machine power system with high penetration of PV park

A mathematical approach was proposed to investigate the impact of high penetration of large-scale photovoltaic park(LPP) on small-signal stability of a power network and design of hybrid controller for these units.A systematic procedure was performed to obtain the complete model of a multi-machine power network including LPP.For damping of oscillations focusing on inter-area oscillatory modes,a hybrid controller for LPP was proposed.The performance of the suggested controller was tested using a 16-machine 5-area network.The results indicate that the proposed hybrid controller for LPP provides sufficient damping to the low-frequency modes of power system for a wide range of operating conditions.The method presented in this work effectively indentifies the impact of increased PV penetration and its controller on dynamic performance of multi-machine power network containing LPP.Simulation results demonstrate that the model presented can be used in designing of essential controllers for LPP.

An improved channel estimation with multipath search for MIMO-OFDM systems

This paper addresses the problem of channel estimation for broadband MIMO-OFDM systems. An improved channel estimator with multipath time delay detection and channel gain estimation is proposed. In the algorithm, we used the correlation of the channel taps and a well-designed adjustment scheme to increase the accuracy of the time delay detection. The most attractive advantage is that the complicated matrix calculation is replaced by search steps which can acquire the channel order and estimate the channel parameters without significantly increasing the complexity of the system. Computer simulation showed that the proposed algorithm can track the time delays adaptively and, consequently, improve the channel estimation performance.

Power system stabilizer design using hybrid multi-objective particle swarm optimization with chaos

A novel technique for the optimal tuning of power system stabilizer (PSS) was proposed,by integrating the modified particle swarm optimization (MPSO) with the chaos (MPSOC).Firstly,a modification in the particle swarm optimization (PSO) was made by introducing passive congregation (PC).It helps each swarm member in receiving a multitude of information from other members and thus decreases the possibility of a failed attempt at detection or a meaningless search.Secondly,the MPSO and chaos were hybridized (MPSOC) to improve the global searching capability and prevent the premature convergence due to local minima.The robustness of the proposed PSS tuning technique was verified on a multi-machine power system under different operating conditions.The performance of the proposed MPSOC was compared to the MPSO,PSO and GA through eigenvalue analysis,nonlinear time-domain simulation and statistical tests.Eigenvalue analysis shows acceptable damping of the low-frequency modes and time domain simulations also show that the oscillations of synchronous machines can be rapidly damped for power systems with the proposed PSSs.The results show that the presented algorithm has a faster convergence rate with higher degree of accuracy than the GA,PSO and MPSO.

A multi-objective gravitational search algorithm based approach of power system stability enhancement with UPFC

On the basis of the theoretical analysis of a single-machine infinite-bus （SMIB）, using the modified linearized Phil- lips-Heffron model installed with unified power flow controller （UPFC）, the potential of the UPFC supplementary controller to enhance the dynamic stability of a power system is evaluated by measuring the electromechanical controllability through singular value decomposition （SVD） analysis. This controller is tuned to simultaneously shift the undamped electromeehanical modes to a prescribed zone in the s-plane. The problem of robust UPFC based damping controller is formulated as an optimization problem according to the eigenvalue-based multi-objective function comprising the damping factor, and the damping ratio of the undamped electromechanical modes to be solved using gravitational search algorithm （GSA） that has a strong ability to find the most optimistic results. The different loading conditions are simulated on a SMIB system and the rotor speed deviation, internal voltage deviation, DC voltage deviation and electrical power deviation responses are studied with the effect of this flexible AC transmission systems （FACTS） controller. The results reveal that the tuned GSA based UPFC controller using the proposed multi-objective function has an excellent capability in damping power system with low frequency oscillations and greatly enhances the dynamic stability of the power systems.

Multi-objectives and Simulation Models for Develop Production Line in Automobiles Manufacturing System

Automotive manufacturing is complex and includes the coordination of design in the manufacturing system. The manufacturing approaches over the past few years, disassembly have been a key issue, and it seems that simulation models are usually tailored to address a narrow set of industrial issues. This paper describes the development of the production line in the automobile manufacturing system through design, operation, and maintenance, based on multi-objectives of Algorithm and Simulation Model called MOA-SM. The both models are being developed at three different levels： the production line in the body and assembly shop, supply chain, and the production plan. The optimization tries to involve more objectives to solve the issues in manufacturing system. A solution that may optimize one performance measure may deteriorate since other performance solutions are difficult. The resulting algorithms are comparable to the simulation and multi-object in terms of success rate, assembly times, peak forces, moments, and have assembly times superior to those of a benchmark blind search algorithm.

USER SELECTION FOR SINR-BASED UPLINK MULTIUSER MIMO SYSTEMS

To avoid the exhaustive search, we propose a fast user selection algorithm for Signal-to-Interference-plus-Noise-Ratio (SINR)-based multiuser Multiple-Input Multiple-Output (MIMO) systems with Alamouti Space-Time Block Code (STBC) transmit scheme. A locally optimal selection criterion is proposed at first. Then, the incremental selection approach is applied, which selects one among the residual available users to maximize the minimum user SINR step by step. Simulation results show that the fast algorithm gains over 90% of the diversity benefit achieved by the exhaustive search selection, and that the fast algorithm has much lower computational burden than the exhaustive search one, for the scenario where the number of all the available users is much greater than that of the selected users.

3D Engineering Model Retrieval Based on Enhanced Shape Distributions

To reuse and share the valuable knowledge embedded in repositories of engineering models for accelerating the design process, improving product quality, and reducing costs, it is crucial to devise search engines capable of matching 3D models efficiently and effectively. In this paper, an enhanced shape distributions-based technique of using geometrical and topological information to search 3D engineering models represented by polygonal meshes was presented. A simplification method of polygonal meshes was used to simplify engineering model as the pretreatment for generation of sample points. The method of sampling points was improved and a pair of functions that was more sensitive to shape was employed to construct a 2D shape distribution. Experiments were conducted to evaluate the proposed algorithm utilizing the Engineering Shape Benchmark (ESB) database. The experiential results suggest that the search effectiveness is significantly improved by enforcing the simplification and enhanced shape distributions to engineering model retrieval.

Universal Digital Library—Future research directions

This paper starts with a description of the present status of the Digital Library of India Initiative. As part of this initiative large corpus of scanned text is available in many Indian languages and has stimulated a vast amount of research in Indian language technology briefly described in this paper. Other than the Digital Library of India Initiative which is part of the Million Books to the Web Project initiated by Prof Raj Reddy of Carnegie Mellon University, there are a few more initiatives in India towards taking the heritage of the country to the Web. This paper presents the future directions for the Digital Library of India Initiative both in terms of growing collection and the technical challenges in managing such large collection poses.

Immune response-based algorithm for optimization of dynamic environments

A novel immune algorithm suitable for dynamic environments (AIDE) was proposed based on a biological immune response principle.The dynamic process of artificial immune response with operators such as immune cloning,multi-scale variation and gradient-based diversity was modeled.Because the immune cloning operator was derived from a stimulation and suppression effect between antibodies and antigens,a sigmoid model that can clearly describe clonal proliferation was proposed.In addition,with the introduction of multiple populations and multi-scale variation,the algorithm can well maintain the population diversity during the dynamic searching process.Unlike traditional artificial immune algorithms,which require randomly generated cells added to the current population to explore its fitness landscape,AIDE uses a gradient-based diversity operator to speed up the optimization in the dynamic environments.Several reported algorithms were compared with AIDE by using Moving Peaks Benchmarks.Preliminary experiments show that AIDE can maintain high population diversity during the search process,simultaneously can speed up the optimization.Thus,AIDE is useful for the optimization of dynamic environments.

Benefiting from providing multi-dimensional view of peers in overlay of P2P streaming system

Most overlay of existing P2P streaming systems just focus on the view point of video content data.An multi-dimensional overlay for the P2P streaming system(MDOPS) is proposed for providing multi-dimensional view including video data,peers' service capability and online stability based on locality sensitive hashing.MDOPS organizes all Live/VoD peers and the above multi-dimensional information in a one-dimensinal DHT,uses range resource information publish/search and introduces multiple load balancing methods.MDOPS maintains an additional candidate coordinating peer list with high qualified peers who own the video data the peer would possibly access currently and in future.This list could speed up the process of searching peers for data scheduling layer.Simulation experiment based on trace of real streaming system has testified that MDOPS can effectively improve the quality of search results and smooth load distribution among peers without increasing the cost of resource publish/search.

Control of Neural Network Feedback Linearization Based on Chaotic Particle Swarm Optimization

A new chaotic particle swarm algorithm is proposed in order to avoid the premature convergence of the particle swarm optimization and the shortcomings of the chaotic optimization, such as slow searching speed and low accuracy when used in the multivariable systems or in large search space. The new algorithm combines the particle swarm algorithm and the chaotic optimization, using randomness and ergodicity of chaos to overcome the premature convergence of the particle swarm optimization. At the same time, a new neural network feedback linearization control system is built to control the single-machine infinite-bus system. The network parameters are trained by the chaos particle swarm algorithm, which makes the control achieve optimization and the control law of prime mover output torque obtained. Finally, numerical simulation and practical application validate the effectiveness of the method.

A Parallel Search System for Dynamic Multi-Objective Traveling Salesman Problem

This paper introduces a parallel search system for dynamic multi-objective traveling salesman problem. We design a multi-objective TSP in a stochastic dynamic environment. This dynamic setting of the problem is very useful for routing in ad-hoc networks. The proposed search system first uses parallel processors to identify the extreme solutions of the search space for each ofk objectives individually at the same time. These solutions are merged into the so-called hit-frequency matrix E. The solutions in E are then searched by parallel processors and evaluated for dominance relationship. The search system is implemented in two different ways master-worker architecture and pipeline architecture.

Optimization algorithm based on kinetic-molecular theory

Traditionally, the optimization algorithm based on physics principles has some shortcomings such as low population diversity and susceptibility to local extrema. A new optimization algorithm based on kinetic-molecular theory(KMTOA) is proposed. In the KMTOA three operators are designed: attraction, repulsion and wave. The attraction operator simulates the molecular attraction, with the molecules moving towards the optimal ones, which makes possible the optimization. The repulsion operator simulates the molecular repulsion, with the molecules diverging from the optimal ones. The wave operator simulates the thermal molecules moving irregularly, which enlarges the searching spaces and increases the population diversity and global searching ability. Experimental results indicate that KMTOA prevails over other algorithms in the robustness, solution quality, population diversity and convergence speed.

Low Leakage Power Sequential Circuits Using Multi-Vth at Nano-Scale Transistor

Leakage power is the dominant source of power dissipation for Sub-100 nm VLSI （very large scale integration） circuits. Various techniques were proposed to reduce the leakage power at nano-scale; one of these techniques is MTV （multi-threshold voltage） In this paper, the exact and optimal value of threshold voltage （Vth） for each transistor in any sequential circuit in the design is found, so that the value of the total leakage current in the design is at the minimum. This could be achieved by applying AI （artificial intelligence） search algorithm. The proposed algorithm is called LOAIS （leakage optimization using AI search）. LOAIS exploits the total slack time of each transistor＇s location and their contributions in the leakage current. It is introduced by AI heuristic search algorithms under 22 nm BSIM4 predictive technology model. The proposed approach saves around 80% of the sub-threshold leakage current without degrading the performance of the circuit.

Optimization of air quantity regulation in mine ventilation networks using the improved differential evolution algorithm and critical path method

In mine ventilation networks, the reasonable airflow distribution is very important for the production safety and economy. Three basic problems of the natural, full-controlled and semi-controlled splitting were reviewed in the paper. Aiming at the high difficulty semi-controlled splitting problem, the general nonlinear multi-objectives optimization mathematical model with constraints was established based on the theory of mine ventilation networks. A new algorithm, which combined the improved differential evaluation and the critical path method （CPM） based on the multivariable separate solution strategy, was put forward to search for the global optimal solution more efficiently. In each step of evolution, the feasible solutions of air quantity distribution are firstly produced by the improved differential evolu- tion algorithm, and then the optimal solutions of regulator pressure drop are obtained by the CPM. Through finite steps iterations, the optimal solution can be given. In this new algorithm, the population of feasible solutions were sorted and grouped for enhancing the global search ability and the individuals in general group were randomly initialized for keeping diversity. Meanwhile, the individual neighbor- hood in the fine group which may be closely to the optimal solutions were searched locally and slightly for achieving a balance between global searching and local searching, thus improving the convergence rate. The computer program was developed based on this method. Finally, the two ventilation networks with single-fan and multi-fans were solved. The results show that this algorithm has advantages of high effectiveness, fast convergence, good robustness and flexibility. This computer program could be used to solve lar^e-scale ~eneralized ventilation networks o^timization problem in the future.

Improved hyper-spherical search algorithm for voltage total harmonic distortion minimization in 27-level inverter

Multi-level inverters(MLIs)have become popular in different applications such as industrial power control systems and distributed generations.There are different forms of MLIs.The cascaded MLIs(CMLIs)have some special advantages among them such as more different output voltage levels using the same number of components and higher power quality.In this paper,a 27-level inverter switching algorithm considering total harmonic distortion(THD)minimization is investigated.Switching angles of the inverter switches are achieved by minimizing a THD-based objective function.In order to minimize the THD-based objective function,the hyper-spherical search(HSS)algorithm,as a novel optimization algorithm,is improved and the results of improved HSS(IHSS)are compared with HSS algorithm and other five evolutionary algorithms to show the advantages of IHSS algorithm.

基于小波消噪的EMD模型在GPS振动信号处理中的应用

经验模式分解和小波分解是当前有效处理非平稳信号的两种时频分析方法,它们各具有其优缺点,适用于不同的应用。从对GPS振动信号的预处理、时域和频域处理入手,结果分析表明,对GPS振动信号先进行小波滤波消除随机噪声的干扰,再应用经验模式分解更有利于变形特征信息的分离和提取,提取的信号与振动平台记录数据更加吻合。