Energy transmission modes based on Tabu search and particle swarm hybrid optimization algorithm

In China, economic centers are far from energy storage bases, so it is significant to select a proper energy transferring mode to improve the efficiency of energy usage. To solve this problem, an optimal allocation model based on energy transfer mode was proposed after objective function for optimizing energy using efficiency was established, and then, a new Tabu search and particle swarm hybrid optimizing algorithm was proposed to find solutions. While actual data of energy demand and distribution in China were selected for analysis, the economic critical value in comparison between the long-distance coal transfer and electric power transmission was gained. Based on the above discussion, some proposals were put forward for optimal allocation of energy transfer modes in China. By comparing other three traditional methods that are based on regional price differences, freight rates and annual cost with the proposed method, the result indicates that the economic efficiency of the energy transfer can be enhanced by 3.14%, 5.78% and 6.01%, respectively.     

Swarm intelligence based dynamic obstacle avoidance for mobile robots under unknown environment using WSN

To solve dynamic obstacle avoidance problems, a novel algorithm was put forward with the advantages of wireless sensor network （WSN）. In view of moving velocity and direction of both the obstacles and robots, a mathematic model was built based on the exposure model, exposure direction and critical speeds of sensors. Ant colony optimization （ACO） algorithm based on bionic swarm intelligence was used for solution of the multi-objective optimization. Energy consumption and topology of the WSN were also discussed. A practical implementation with real WSN and real mobile robots were carried out. In environment with multiple obstacles, the convergence curve of the shortest path length shows that as iterative generation grows, the length of the shortest path decreases and finally reaches a stable and optimal value. Comparisons show that using sensor information fusion can greatly improve the accuracy in comparison with single sensor. The successful path of robots without collision validates the efficiency, stability and accuracy of the proposed algorithm, which is proved to be better than tradition genetic algorithm （GA） for dynamic obstacle avoidance in real time.     

Genetic Algorithm Based Combinatorial Auction Method for Multi-Robot Task Allocation

An improved genetic algorithm is proposed to solve the problem of bad real-time performance or inability to get a global optimal/better solution when applying single-item auction （SIA） method or combinatorial auction method to multi-robot task allocation. The genetic algorithm based combinatorial auction （GACA） method which combines the basic-genetic algorithm with a new concept of ringed chromosome is used to solve the winner determination problem （WDP） of combinatorial auction. The simulation experiments are conducted in OpenSim, a multi-robot simulator. The results show that GACA can get a satisfying solution in a reasonable shot time, and compared with SIA or parthenogenesis algorithm combinatorial auction （PGACA） method, it is the simplest and has higher search efficiency, also, GACA can get a global better/optimal solution and satisfy the high real-time requirement of multi-robot task allocation.     

Novel Real-Time Seam Tracking Algorithm Based on Vector Angle and Least Square Method

Real-time seam tracking can improve welding quality and enhance welding efficiency during the welding process in automobile manufacturing. However,the teaching-playing welding process, an off-line seam tracking method, is still dominant in automobile industry,which is less flexible when welding objects or situation change. A novel real-time algorithm consisting of seam detection and generation is proposed to track seam. Using captured 3D points, space vectors were created between two adjacent points along each laser line and then a vector angle based algorithm was developed to detect target points on the seam. Least square method was used to fit target points to a welding trajectory for seam tracking. Furthermore, the real-time seam tracking process was simulated in MATLAB/Simulink. The trend of joint angles vs. time was logged and a comparison between the off-line and the proposed seam tracking algorithm was conducted. Results show that the proposed real-time seam tracking algorithm can work in a real-time scenario and have high accuracy in welding point positioning.     

Multi-Object Tracking Based on Segmentation and Collision Avoidance

An approach to track multiple objects in crowded scenes with long-term partial occlusions is proposed.Tracking-by-detection is a successful strategy to address the task of tracking multiple objects in unconstrained scenarios,but an obvious shortcoming of this method is that most information available in image sequences is simply ignored due to thresholding weak detection responses and applying non-maximum suppression.This paper proposes a multi-label conditional random field (CRF) model which integrates the superpixel information and detection responses into a unified energy optimization framework to handle the task of tracking multiple targets.A key characteristic of the model is that the pairwise potential is constructed to enforce collision avoidance between objects,which can offer the advantage to improve the tracking performance in crowded scenes.Experiments on standard benchmark databases demonstrate that the proposed algorithm significantly outperforms the state-of-the-art tracking-by-detection methods.     

Elitism-based immune genetic algorithm and its application to optimization of complex multi-modal functions

A novel immune genetic algorithm with the elitist selection and elitist crossover was proposed, which is called the immune genetic algorithm with the elitism （IGAE）. In IGAE, the new methods for computing antibody similarity, expected reproduction probability, and clonal selection probability were given. IGAE has three features. The first is that the similarities of two antibodies in structure and quality are all defined in the form of percentage, which helps to describe the similarity of two antibodies more accurately and to reduce the computational burden effectively. The second is that with the elitist selection and elitist crossover strategy IGAE is able to find the globally optimal solution of a given problem. The third is that the formula of expected reproduction probability of antibody can be adjusted through a parameter r, which helps to balance the population diversity and the convergence speed of IGAE so that IGAE can find the globally optimal solution of a given problem more rapidly. Two different complex multi-modal functions were selected to test the validity of IGAE. The experimental results show that IGAE can find the globally maximum/minimum values of the two functions rapidly. The experimental results also confirm that IGAE is of better performance in convergence speed, solution variation behavior, and computational efficiency compared with the canonical genetic algorithm with the elitism and the immune genetic algorithm with the information entropy and elitism.     

Distributed power allocation over indoor multi-pico stations

A low-complexity distributed power allocation algorithm is proposed to reduce the interference and improve the transmitting rate of edge users. Different scenarios are considered and user experience of indoor communication is promoted. The simulation results prove the effectiveness of our algorithm. The proposed power control scheme ensures that more users can achieve their required rate and the fairness of different users is improved. Besides, more than 50% energy can be saved without loss in outage ability, and energy efficiency is also promoted. In addition, the proposed algorithm can be extended to scenarios that the required rates of pico stations can be changed periodically.     

Bus coordination holding control for transit hubs under APTS

To increase the passenger transferring efficiency, the bus coordination holding control for transit hubs, which is as an important dynamic dispatching method for improving the service level of transit hubs, was studied in the framework of bus coordination dispatching mode. Firstly, the bus coordination holding control flow was studied based on Advanced Public Transportation Systems (APTS) environment. Then a control model was presented to optimize the bus vehicle holding time, and a genetic algorithm was designed as the solving method. In the end, an example was given to illustrate the effectiveness of the control strategy and the algorithm.     

Reduced parameter model on trajectory tracking data with applications

The data fusion in tracking the same trajectory by multi-measurernent unit (MMU) is considered. Firstly, the reduced parameter model (RPM) of trajectory parameter (TP), system error and random error are presented,and then the RPM on trajectory tracking data (TTD) is obtained, a weighted method on measuring elements (ME) is studied and criteria on selection of ME based on residual and accuracy estimation are put forward. According to RPM,the problem about selection of ME and self-calibration of TTD is thoroughly investigated. The method improves data accuracy in trajectory tracking obviously and gives accuracy evaluation of trajectory tracking system simultaneously.     

3D Model Retrieval Method Based on Affinity Propagation Clustering

In order to improve the accuracy and efficiency of 3D model retrieval, the method based on affinity propagation clustering algorithm is proposed. Firstly, projection ray-based method is proposed to improve the feature extraction efficiency of 3D models. Based on the relationship between model and its projection, the intersection in 3D space is transformed into intersection in 2D space, which reduces the number of intersection and improves the efficiency of the extraction algorithm. In feature extraction, multi-layer spheres method is analyzed. The two-layer spheres method makes the feature vector more accurate and improves retrieval precision. Secondly, Semi-supervised Affinity Propagation (S-AP) clustering is utilized because it can be applied to different cluster structures. The S-AP algorithm is adopted to find the center models and then the center model collection is built. During retrieval process, the collection is utilized to classify the query model into corresponding model base and then the most similar model is retrieved in the model base. Finally, 75 sample models from Princeton library are selected to do the experiment and then 36 models are used for retrieval test. The results validate that the proposed method outperforms the original method and the retrieval precision and recall ratios are improved effectively.     

Multiple k-hop clusters based routing scheme to preserve source-location privacy in WSNs

Privacy is becoming one of the most notable challenges threatening wireless sensor networks （WSNs）. Adversaries may use RF （radio frequency） localization techniques to perform hop-by-hop trace back to the source sensor＇s location. A multiple k-hop clusters based routing strategy （MHCR） is proposed to preserve source-location privacy as well as enhance energy efficiency for WSNs. Owing to the inherent characteristics of intra-cluster data aggregation, each sensor of the interference clusters is able to act as a fake source to confuse the adversary. Moreover, dummy traffic could be filtered efficiently by the cluster heads during the data aggregation, ensuring no energy consumption be burdened in the hotspot of the network. Through careful analysis and calculation on the distribution and the number of interference clusters, energy efficiency is significantly enhanced without reducing the network lifetime. Finally, the security and delay performance of MHCR scheme are theoretically analyzed. Extensive analysis and simulation results demonstrate that MHCR scheme can improve both the location privacy security and energy efficiency markedly, especially in large-scale WSNs.     

A new measure for evaluating spatially related properties of traffic information credibility

With the wide applications of sensor network technology in traffic information acquisition systems, a new measure will be quite necessary to evaluate spatially related properties of traffic information credibility. The heterogeneity of spatial distribution of information credibility from sensor networks is analyzed and a new measure, information credibility function （ICF）, is proposed to describe this heterogeneity. Three possible functional forms of sensor ICF and their corresponding expressions are presented. Then, two feasible operations of spatial superposition of sensor ICFs are discussed. Finally, a numerical example is introduced to show the calibration method of sensor ICF and obtain the spatially related properties of expressway in Beijing. The results show that the sensor ICF of expressway in Beijing possesses a negative exponent property. The traffic information is more abundant at or near the locations of sensor, while with the distance away from the sensor increasing, the traffic information credibility will be declined by an exponential trend. The new measure provides theoretical bases for the optimal locations of traffic sensor networks and the mechanism research of spatial distribution of traffic information credibility.     

Sensor array calibration for uniform rectangular array in presence of mutual coupling and sensor gain-and-phase errors

The sensor array calibration methods tailored to uniform rectangular array （URA） in the presence of mutual coupling and sensor gain-and-phase errors were addressed. First, the mutual coupling model of the URA was studied, and then a set of steering vectors corresponding to distinct locations were numerically computed with the help of several time-disjoint auxiliary sources with known directions. Then, the optimization modeling with respect to the array error matrix （defined by the product of mutual coupling matrix and sensor gain-and-phase errors matrix） was constructed. Two preferable algorithms （called algorithm I and algorithm II） were developed to minimize the cost function. In algorithm I, the array error matrix was regarded as a whole parameter to be estimated, and the exact solution was available. Compared to some existing algorithms with the similar computation framework, algorithm I can make full use of the potentially linear characteristics of URA＇s error matrix, thus, the calibration precision was obviously enhanced. In algorithm II, the array error matrix was decomposed into two matrix parameters to be optimized. Compared to algorithm I, it can further decrease the number of unknowns and, thereby, yield better estimation accuracy. However, algorithm II was incapable of producing the closed-form solution and the iteration operation was unavoidable. Simulation results validate the excellent performances of the two novel algorithms compared to some existing calibration algorithms.     

Predicting configuration performance of modular product family using principal component analysis and support vector machine

A novel configuration performance prediction approach with combination of principal component analysis（PCA） and support vector machine（SVM） was proposed.This method can estimate the performance parameter values of a newly configured product through soft computing technique instead of practical test experiments,which helps to evaluate whether or not the product variant can satisfy the customers＇ individual requirements.The PCA technique was used to reduce and orthogonalize the module parameters that affect the product performance.Then,these extracted features were used as new input variables in SVM model to mine knowledge from the limited existing product data.The performance values of a newly configured product can be predicted by means of the trained SVM models.This PCA-SVM method can ensure that the performance prediction is executed rapidly and accurately,even under the small sample conditions.The applicability of the proposed method was verified on a family of plate electrostatic precipitators.     

Effects of magnetic fields on Fe-Si composite electrodeposition

Coatings containing Fe-Si particles were electrodeposited on 3.0wt% Si steel sheets under magnetic fields. The effects of magnetic flux density （MFD）, electrode arrangement and current density on the surface morphology, the silicon content in the coatings and the cathode current efficiency were investigated. When a magnetic field was applied parallel to the current and when the MFD was less than 0.5 T, numerous needle-like structures appeared on the coating surface. With increasing MFD, the needle-like structures weakened and were transformed into dome-shaped structures. Meanwhile, compared to results obtained in the absence of a magnetic field, the silicon content in the coatings significantly increased as the MFD was increased for all of the samples obtained using a vertical electrode system. However, in the case of an aclinic electrode system, the silicon content decreased. Furthermore, the cathode current efficiency was considerably diminished when a magnetic field was applied. A possible mechanism for these phenomena was discussed.     

Interference management via access control and mobility prediction in two-tier heterogeneous networks

Abstract： Two-tier heterogeneous networks （HetNets）, where the current cellular networks, i.e., macrocells, are overlapped with a large number of randomly distributed femtocells, can potentially bring significant benefits to spectral utilization and system capacity. The interference management and access control for open and closed femtocells in two-tier HetNets were focused. The contributions consist of two parts. Firstly, in order to reduce the uplink interference caused by MUEs （macrocell user equipments） at closed femtocells, an incentive mechanism to implement interference mitigation was proposed. It encourages femtoeells that work with closed-subscriber-group （CSG） to allow the interfering MUEs access in but only via uplink, which can reduce the interference significantly and also benefit the marco-tier. The interference issue was then studied in open-subscriber-group （OSG） femtocells from the perspective of handover and mobility prediction. Inbound handover provides an alternative solution for open femtocells when interference turns up, while this accompanies with PCI （physical cell identity） confusion during inbound handover. To reduce the PCI confusion, a dynamic PCI allocation scheme was proposed, by which the high handin femtocells have the dedicated PCI while the others share the reuse PCIs. A Markov chain based mobility prediction algorithm was designed to decide whether the femtoeell status is with high handover requests. Numerical analysis reveals that the UL interference is managed well for the CSG femtocell and the PCI confusion issue is mitigated greatly in OSG femtocell compared to the conventional approaches.     

Desulfurization ability of refining slag with medium basicity

The desulfurization ability of refining slag with relative lower basicity （B） and Al2O3 content （B = 3.5-5.0; 20wt%-25wt% Al2O3） was studied. Firstly, the component activities and sulfide capacity （Cs） of the slag were calculated. Then slag-metal equilibrium experiments were carried out to measure the equilibrium sulfur distribution （Ls）. Based on the laboratorial experiments, slag composition was optimized for a better desulfurization ability, which was verified by industrial trials in a steel plant. The obtained results indicated that an MgO-saturated CaO-Al2O3-SiO2-MgO system with the basicity of about 3.5-5.0 and the Al2O3 content in the range of 20wt%-25wt% has high activity of CaO （αCaO）, with no deterioration of Cs compared with conventional desulfurization slag. The measured Ls between high-strength low-alloyed （HSLA） steel and slag with a basicity of about 3.5 and an Al2O3 content of about 20wt% and between HSLA steel and slag with a basicity of about 5.0 and an Al2O3 content of about 25wt% is 350 and 275, respectively. The new slag with a basicity of about 3.5-5.0 and an Al2O3 content of about 20wt% has strong desulfurization ability. In particular, the key for high-efficiency desulfurization is to keep oxygen potential in the reaction system as low as possible, which was also verified by industrial trials.     

Production of HfO2 thin films using different methods： chemical bath deposition,SILAR and sol-gel process

Hafnium oxide thin films （HOTFs） were successfully deposited onto amorphous glasses using chemical bath deposition, successive ionic layer absorption and reaction （SILAR）, and sol-gel methods. The same reactive precursors were used for all of the methods, and all of the films were annealed at 300℃ in an oven （ambient conditions）. After this step, the optical and structural properties of the films produced by using the three different methods were compared. The structures of the films were analyzed by X-ray diffTaction （XRD）. The optical properties are investigated using the ultraviolet-visible （UV-VIS） spectroscopic technique. The film thickness was measured via atomic force microscopy （AFM） in the tapping mode. The surface properties and elemental ratios of the films were investigated and measured by scanning electron microscopy and energy-dispersive X-ray spectroscopy （EDX）. The lowest transmittance and the highest reflectance values were observed for the films produced using the SILAR method. In addition, the most intense characteristic XRD peak was observed in the diffraction pattern of the film produced using the SILAR method, and the greatest thickness and average grain size were calculated for the film produced using the SILAR method. The films produced using SILAR method contained fewer cracks than those produced using the other methods. In conclusion, the SILAR method was observed to be the best method for the production of HOTFs.     

Dielectric,piezoelectric, and ferroelectric properties of lanthanum-modified PZTFN ceramics

Specimens of Pb1-1.5xLax（Zr0.53 Ti0.47）1-y-zFeyNb2O3 （x = 0, 0.004, 0.008, 0.012, and 0.016, y = z = 0.01） （PZTFN） ceramics were synthesized by a semi-wet route. In the present study, the effect of La doping was investigated on the structural, microstructural, dielectric, piezoelectric, and ferroelectric properties of the ceramics. The results show that, the tetragonal （space group P4mm） and rhombohedral （space group R3c） phases are observed to coexist in the sample at x = 0.012. Microstructural investigations of all the samples reveal that La doping inhibits grain growth. Doping of La into PZTFN improves the dielectric, ferroelectric, and piezoelectric properties of the ceramics. The hys- teresis loops of all specimens exhibit nonlinear behavior. The dielectric, piezoelectric and ferroelectric properties show a maximum response atx 〉 0.012, which corresponds to the morphotropic phase boundary （MPB）.