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This paper studies the performance of a proximity content distribution scheme over IEEE 802.11s mesh networks with reasonable user density among combinations of three network configurations and two transport mechanisms. For content access control, Hyperledger Sawtooth Blockchain with PoET (Proof of Elapsed Time) consensus algorithm is used as a decentralised storage of non-repudiated and rapid transactions for granting content access and distributing the content decryption key. An extensive performance evaluation of the content distribution and content access control protocols using ns-3 simulator was conducted. The results show that the integration of Blockchain and UDP multicast content distribution in a hybrid mesh network topology is highly feasible.

For the operational safety and stability of electrical system, effective power flow control in meshed high voltage direct current (HVDC) grids makes sense. In order to realize the objective of controlling several lines simultaneously and independently in a convenient way, interline dc power flow controller (IDCPFC) has been introduced. To cover some shortages of present IDCPFC topologies, an improved triple interline dc power flow controller (TI-DCPFC), capable of controlling power flow of two lines actively, has been proposed in this paper. To explain it thoroughly and explicitly, its operational principle is illustrated combined with the mathematic equations firstly. Then, to validate its capacity of dealing with occasions of bidirectional flows and the dual-freedom control function, the theoretical control strategy and simulation results in a typical working mode are referred to comprehensively.

In recent years, the construction of VSC-HVDC projects have been vigorously promoted in China, and its system structures and technical characteristics are quite different from LCC-HVDC projects. Therefore, this paper first describes and compares the typical system structures and technical characteristics of various projects based on the existing VSC-HVDC projects in China, and then taking actual project as an example, the protection configurations and functional principles of AC protection zone, AC connecting bus protection zone, converter protection zone and DC protection zone are analyzed. Finally, the configuration schemes of each protection function are analyzed.

The rapid development of fresh food e-commerce provides an effective solution for increasing farmers’ income, meeting consumers’ needs and reducing the loss of fresh food circulation. As the key link of fresh food e-commerce logistics, the distribution is of great significance to improve consumer satisfaction and reducing the operating cost of e-commerce enterprises. This article divides the distribution regions of fresh food e-commerce through the LinkRank community detection algorithm based on the complex networks, explores and constructs a method of the division of the terminal distribution regions for fresh food e-commerce logistics by using simulated annealing algorithm to optimizes the network modularity, and verified the effectiveness of the method by analysing the case of Jingkou District of Zhenjiang City. Hope to offer a reference for fresh food e-commerce to construct the logistics distribution system suitably.

Bushing fault is one of the prime reasons causing transformer faults, among which the failure rates caused by humidified insulation is in the first place. Based on the experimental results of damp bushing models, Frequency Domain Spectroscopy (FDS) test and disassemble test were implemented on three 500kV bushings from two substations that failed to dissolved gas analysis (DGA) test. Multidimensional analysis of these fault bushings was carried out based on the results of FDS test, dielectric loss test and partial discharge test under high voltage, moisture content of the insulation paper, and a comparison with the FDS test of a new 500kV bushing. Results show that the technology of FDS has obvious advantage in diagnosing of the moistened bushing, and it shows high sensitivity at low frequency. It can be regarded as the criterion for moistened bushing whether the tangent value of the medium loss angle of 1mHz~10mHz frequency band of the FDS test exceeds 10%. 1

The discovery of gene-disease associations is important for the prevention, diagnosis and treatment of diseases. The studies on gene-disease associations have produced diverse data, which can facilitate the gene-disease association prediction. Integrating diverse information is critical for developing high-accuracy prediction models. In this paper, we propose a heterogeneous network-based method that enhances gene-disease association prediction by using graph embedding and ensemble learning, abbreviated as “HNEEM”. A heterogeneous network is constructed based on gene-disease associations, gene-chemical associations and disease-chemical associations, to combine diverse information. The network uses genes, diseases and chemicals as nodes, and uses their associations as edges. The graph embedding methods are utilized to extract representation vectors of nodes in the heterogeneous network, and the feature vectors of genes and diseases are merged to represent gene-disease pairs, and the random forest is employed to build the prediction model based on gene-disease pairs. We consider six types of graph embedding methods, and take the individual graph embedding method-generated features to build prediction models and use them as base predictors, and then combine base predictors to develop the ensemble learning model HNEEM. We comprehensively compare different graph embedding methods, and results demonstrate that the graph embedding methods produce satisfying results in the gene-disease association prediction, and integrating different graph embedding methods can make further improvements. In computational experiments, HNEEM produces better results compared to the state-of-the-art gene-disease perdition methods, and HNEEM is robust to the data richness as well. Moreover, the usefulness of the proposed method HNEEM is validated by the case studies. In conclusion, HNEEM is a promising method for predicting gene-disease associations.

Lifetime estimation is critical for predicting the revenue of the photovoltaic (PV) plant to be built. Therefore it must be done before huge investments will be made to build and operate a PV plant. Since the degradation rate of PV modules features as a random variable, statistical models are commonly used to estimate the lifetime of PV modules. However, most existing researches select the statistical model to describe the degradation rate of PV modules empirically, and lack of basis. In this paper we propose a practical procedure for selecting the statistical model which describes the degradation rate of PV modules best. Based on the selected model, the lifetime of PV modules is estimated. We use probability plots and hypothesis tests to validate the distributional assumptions. Then we use negative log-likelihood values to further determine the distribution that describes the lifetimes best. Three classical distributions, i.e., Weibull, lognormal and exponential distributions, are considered. The life distributions at different stress levels are assumed to come from the same parametric family. Based on the assumption, the parameters of the hypothesized distributions are estimated using maximum likelihood estimation methods. It is found that the PV lifetimes follow a parametric location-scale distribution family, and they follow the Weibull distribution best. The conclusion is realistic from a physical point of view.

As a green and low-carbon transportation mode, walking is very flexible and punctual. It has a good development foundation in China and it is an ideal transportation method for solving short-distance travel and the connection with public transportation. It is indispensable in the urban transportation system. However, the current road traffic design often just meets the driving demand of drivers, while the pedestrian traffic demand is not considered enough, so the safety and convenience of pedestrians needs to be improved. In order to optimize the traffic environment for pedestrians, the common problems in the design of pedestrian crossing facilities at intersections as well as the suggestions for improvement are proposed, which can be used to provide some reference for traffic management departments as well as road traffic designers.

The high-order harmonic generally occurred in the connected transformer under the practical operation condition which will cause the transformer nonuniform heating and bring unexpected hazard. In this study, to analysis the thermal field distribution, a 3D finite element model of the connected transformer is established. The magnetic flux of the iron core, magnetic flux leakage of the tank wall and the frame clamps under operation condition were calculated. Also, the thermal field distribution and hot spot temperature of the iron core and clamps has been calculated using magnetic-thermal coupling method. The analysis results indicated that, when the high-order harmonic occurred, both of the magnetic flux of the iron core and magnetic flux leakage of the tank wall and the frame clamps were increased significantly. The magnetic flux leakage in the middle part of the tank became obviously. Therefore, the magnetic shielding at this part should be enhanced. The hot spot temperature of the iron core and clamps increases 6.7 °C and 1.7 °C, respectively. Thus, a rigorous monitoring should be implemented to prevent equipment insulation fail cause by the local overheat. The analysis results of paper could be used in the connected transformer optimal design and practical operation maintain.

Currently, traffic accidents are prone to happen at intersections. Traffic accidents are closely related to people's security. Thus, it has been one of the key research topics all over the world. Among all the intersections, un-signalized T-intersection is worse, because there are much more traffic conflicts. The rate of accident at such intersections is often much higher than that at regular intersections. Besides, the traffic access efficiency of un-signalized T-intersections is often much lower. Thus, it is very important to study traffic improvement measures to improve the traffic safety level as well as the traffic access efficiency of T-intersections. The traffic improvement measures proposed can be used to provide some reference for road traffic designers.

The quantification of myocardial blood flow (MBF) from cardiac positron emission tomography (PET) has been used for evaluating the abnormalities of coronary flow reserve for patients with known or suspected microvascular disease. We proposed a novel approach to automatic segmentation of the left ventricle (LV) and generating a personalized myocardial model from 82Rb myocardial perfusion positron emission tomography (PET) images using a scheme of 3-dimension (3-D) clustering and ellipsoid model fitting. The new methods were evaluated using 17 patients with normal myocardial perfusion (normal group) and 20 patients with myocardial perfusion defect (abnormal group) who underwent rest and stress 82Rb PET imaging. For comparisons, PET images were processed using k-means with 4 clusters (k-ms4), fuzzy c-means with 4 clusters (FCM4), and fuzzy c-means with 3 clusters (FCM3). The myocardial volume of both rest and stress studies of each patient was calculated. Paired t-test was used for the assessment of statistical significance in the difference between two measures and the Bland-Altman analysis was used to evaluate the agreement between the two measures. The personized myocardial model was successfully generated for all the 37 patients included in this study. The myocardial volume derived from FCM3 were higher than those estimated from the other methods being compared in this study. There were no significant differences between the k-ms4-derived and the FCM4-derived myocardial volume, whereas there were significant differences between the k-ms4-derived and FCM3-derived myocardial volume. The myocardial volume is calculated from FCM4 and FCM3 were also significantly different. Thus, our methods may have a potential of automatically segmenting the LV myocardial regions from myocardial perfusion PET images, whereas the performance of the new automated methods can be limited by the partial volume effect of the heart with a small LV cavity.

The use of social networking sites have been growing dramatically. This phenomenon promotes most news agencies to use social media platforms rather than traditional media platforms for news releases. The main differences between social and traditional media platforms are “Real-time news release” and “cross-platform extensions Contents posted on social media platforms require speed and richness. Therefore, web news editors find it relatively difficult to write an article with good title in a short time that attracts audience to click in and read through. In this study, we analyzed selected “web news headlines with high page views” to identify catchy headlines and similarities of keywords. We used dimension reduction method as our primary technique to identify the best keyword combinations that help news editors to write attractive news for higher page views and more actual readers on the social media platforms.

The modeling and measuring methods for V2G are reviewed. First, the concepts and the urgent problems of V2G are introduced. Then, the charging and discharging models of vehicle in power grid are analyzed. All of them cannot be used in active power measurement because they are established based on sinusoidal theory. Third, measuring methods of active power for V2G in recent years are summarized which are focus on the charging states. Finally, charge-discharge model of vehicles for V2G is established and the corresponding measuring method of active power is presented.

In order to solve the shortcomings of traditional D_S evidence theory in dealing with conflict evidence,this paper presents a new measure. This method combines the evidence distance with the normalization constant to determine the degree of conflict between the evidences. The degree of conflict as the basis for judging the conflict evidence. Calculates the trust degree and the false degree of the evidence, sorts the trust degree and the false degree of the evidence respectively, then weights the conflict evidence. Finally, use the Dempster combination rule as evidence fusion. Experiments show that the algorithm not only judge the conflict evidence effectively, but also improve the convergence speed and precision.

In view of the fact that the configuration of some equipment for EV battery swapping station was not taken into account and the analysis of the charging behavior during the operation process was relatively coarse, a comprehensive optimal allocation method of EV battery swapping station was proposed based on the ordered charging strategy. Firstly, a comprehensive optimal allocation model of spare battery pack, charging equipment and swapping equipment was constructed. Secondly, based on the TOU power price mechanism, an ordered charging strategy of electric vehicles was formulated under a certain configuration scheme. Thirdly, a method of calculating the users' waiting time based on the queuing theory was proposed. Furthermore, an improved genetic algorithm based on elitism preservation strategy was proposed. Finally, the validity and practicability of this method were verified by example analysis.

Aiming at the problem that the kNN algorithm is susceptible to the choice of k-nearest neighbors and the method of class judgment, this paper propose a kNN algorithm based on class contribution and feature weighting called DCT-kNN. Firstly, using traditional kNN to calculate accuarcy of original dataset and of the data lack of each dimension feature successively. Then by comparing two accuarcies to weight the feature and to calculate the weighted distance, by which the k-nearest neighbors are obtained. Finally, by using class contribution which combines the number of k-nearest neighbors and their mean distance, the final labels of the samples are obtained. The comparison experiment of UCI datasets showed a certain degree of improvement in classification accuracy of the proposed method.

FP-growth algorithm produces all the frequent item sets without producing a large number of candidate items. However, when the item set is too large, the branch of the spanning tree will be long, occupying the space too large, and the mining efficiency will be reduced. In this paper, the method of using dynamic insert node FP - tree structure, and all the back pointer, to generate a new type of FP - tree. This article also proposes Max-IFP maximum frequent patterns mining algorithm, using the new generation of FP - tree dug up all the maximum frequent item sets. The experimental results show that the new FP-tree occupies a smaller space, and the algorithm proposed in this paper is shorter and more effective than other algorithms when mining the maximum frequent item sets.

Due to the shortcomings of low efficiency and low accuracy of DNA microarray data, the paper proposes a feature gene selection algorithm based on ReliefF and PSO (RefFPSO). Firstly, ReliefF is used as the feature pre-filter to delete the genes with low correlation with the classification target. Then PSO is used as the search algorithm. Finally, the classification accuracy of SVM is used as the evaluation function of the feature subset to get the final optimal gene subset. Experiments show that this method can effectively put forward irrelevant genes and use fewer characteristic genes to obtain higher classification accuracy.