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The Cucker-Smale (C-S) model describes an interacting particle system in which the connection weights decrease with increasing distance. This model features emergent behaviors by which the velocities of the particles converge to a common value without a central command. However, the consensus value of the original C-S flocking model is restricted to the leader-following consensus or average consensus. Moreover, for the short-range communication-based C-S model, consensus can only be obtained for specific initial configurations. In this paper, the short-range communication-based C-S model is extended to achieve distributed optimization, where the consensus value optimizes the objective function of the group for any bounded initial configuration. Simulation examples are provided to demonstrate the effectiveness of our approach.

Nonideal switching characteristics of voltage source inverter (VSI) will result in distortions in both phase currents and reference voltages of a permanent magnet synchronous machine (PMSM) drive system, which will also consequently introduce ripples into the output speed and shaft torque, and result in a performance deterioration in the state observation control. To solve this issue, a method of directly extracting and compensating the nonlinear voltage disturbance due to VSI nonlinearity employed in PMSM drives is proposed in this paper. Firstly, the distorted voltage due to VSI nonlinearity is directly extracted via a harmonic separation scheme, which can be easily compensated by a proportional integral controller afterwards. Since both 6th harmonic and DC terms of dq-axis distorted voltages due to VSI nonlinearity are well compensated, the proposed method shows sufficiently good performance under both $i_{d}=0$ and maximum torque per ampere controls ( $i_{d} < 0$ ), as verified on two prototype PMSMs being salient pole and non-salient pole, respectively, both developed for a low-speed rotary actuator. In addition, the application of proposed method to state observation controls such as the model-based sensorless control and the deadbeat predictive current control, is finally investigated. Test results manifest that the proposed method can effectively improve the accuracy of observed rotor position/speed, and the ability of current tracking.

In motor drives, distortions of phase voltages and currents are often caused by nonlinear effects of inverters such as dead time, turn-on delay, turn-off delay and voltage drop of power devices. To eliminate these distortions, the dead-time compensation voltage is usually investigated. Furthermore, the relationship between the dead-time compensation voltage and phase currents is nonlinear, which is related to not only the parameters mentioned above, but also the snubber and parasitic capacitance of inverters. A nonlinear function is constructed to model the nonlinear relationship in this paper. To identify the nonlinear function, a method based on artificial neural networks is proposed without inverter parameters. According to the criterion that the trajectory of voltage vector in $\alpha - \beta $ coordinate system is a circle, an adaptive law is constructed to modify the parameters of the nonlinear function. Therefore, the nonlinear dead-time compensation voltage model is obtained accurately, where the distortions of voltages and currents are reduced without any additional hardware. Applying this method to the current predictive control, the bandwidth of a current loop is increased by 500Hz. Effectiveness of the method is verified by experiments.

A novel method used to design wideband balanced bandpass filter (BPF) is validated through a dual-mode balanced BPF based on semicircular patch resonator. In order to arrange the differential-mode (DM) passband, TM 11 and TM31 modes are adopted. Approaches are employed to amend the disparity of the modes' resonant frequencies. For instance, two rows of vias are introduced to perturbed the electric field distribution of TM 11 mode, which can shift the resonant frequency of TM 11 mode to that of TM31 mode; two small patches are located at the balanced ports to decrease the resonant frequencies of TM 11 and TM31 mode. Subsequently, for the purpose of common-mode (CM) suppression, cascaded defected ground structures (DGSs) are etched in the ground plane under the differential transmission line. The wideband balanced BPF is fabricated and measured. The results agree with each other very well, which validate the feasibility of the proposed design concept.

In the mobile Internet era, demographic information plays an important role in many personalized services and research areas such as content recommendation [1], advertising [2], and behavioral prediction [3]. However, this information is treated as private data and is difficult to access. Therefore, the prediction of demographic information has aroused research interest. There are already some studies that predict demographic information based on user-generated content [4], smartphone sensor data, and user biometric data [5]. In this paper, we introduce a new method that uses App usage record data to predict the demographic information of smartphone users. App usage record data is a set of easily accessible, rich and insightful data. We propose a deep learning framework that uses a convolutional neural network(CNN) to predict the demographic information of smartphone users through app usage record data. We use a set of data with 6-months App usage record of about 5,000 users to train our prediction model. The CNN model we proposed has achieved good prediction performance on the training data set. In the comparative experiment, the prediction effect of our model is also better than the effect of the three classical machine learning algorithms.

In recent years, the application of style transfer has become more and more widespread. Traditional deep learning-based style transfer networks often have problems such as image distortion, loss of detailed information, partial content disappearance, and transfer errors. The style transfer network based on deep learning that we propose in this article is aimed at dealing with these problems. Our method uses image edge information fusion and semantic segmentation technology to constrain the image structure before and after the migration, so that the converted image maintains structural consistency and integrity. We have verified that this method can successfully suppress image conversion distortion in most scenarios, and can generate good results.

In this paper, a robust control strategy based on model reference control is proposed to achieve the high-performance speed control when the moment of inertia is variable. This strategy consists of a model reference controller and a robust compensator. The model reference controller is proposed to achieve the ideal dynamic response and the robust compensator is proposed to compensate the effect of inertia mismatch. The two controllers are proportion-integral (PI) controller, which parameters are designed and discussed. The tunning parameters are reduced to two adjustable parameters, which are expected response angular frequency and maximum inertia ratio. Although the inertia is variable, the maximum ratio of inertia can be known. The effectiveness of this strategy is verified by simulation results and experiment results.

In this paper, a hybrid SAW-resonator/lumped-element dual-band bandstop filter with continuously tunable bandwidths (BWs) is reported. It is based on hybrid-technology design approach in which N identical dual-resonance filter cells-shaped by two SAW resonators, one coupling capacitor, two inductors and two varactors-are cascaded in series by N-l transmission lines $Z_{0}$ . In this manner, two stopband notches with enhanced fractional bandwidths (FBWs) which are larger than the electromechanical coupling coefficient ( $k_{t^{2}}$ ) can be achieved. The continuously variable BWs are realized by adjusting the bias voltages of varactor diodes. For practical validation, a prototype using commercially-available one-port SAW resonators and chip LE components is designed, built and tested. It exhibits two stop-bands centered at 868.7 and 916.7 MHz that respectively expose continuous BW tuning between $1.06-3.27 k_{t^{2}}$ and $0.89-2.62 k_{t^{2}}$ .

In this paper, a miniaturized dual-mode dual-band bandpass filter (BPF) with controllable frequency ratio based on patch-loaded substrate integrated waveguide (PSIW) cavity is proposed. In order to realize the dual-band bandpass filter, two metallized blind vias are introduced along the symmetrical plane to provide an additional mode nominated as LC mode. By utilizing the additional mode and TEM 001 mode in PSIW cavity, dual-band bandpass response is achieved. Moreover, the introduced blind vias can make frequency shifting of LC mode while not affect TEM 001 mode. As a result, the frequency ratio of the two passbands can be controlled. For demonstration, a dual-band filter operating at 1.09 and 3.58 GHz is designed, fabricated and measured. The insertion losses are measured to be 1.24 dB and 2.23 dB with the measured return losses better than 17 dB.

A compact triple-mode bandpass filter (BPF) is proposed in this paper based on a capacitive-loaded isosceles right-angled triangular (IRAT) patch resonator. In order to realize triple-mode response, metallic vias array is introduced along the symmetrical axis. An additional mode nominated as LC mode is generated, making the perturbed IRAT resonator operate below its former fundamental resonate frequency, and thus miniaturization has been achieved. Through the metallic vias array and the capacitive-loaded patch, the first mode (LC mode) and the third mode (TM 010 ) are shifted toward the second mode (TM 110 ) to form a passband. Moreover, three transmission zeros (TZs) can be obtained in the upper stopband. As a result, the designed filter has featured both compact size and high selectivity characteristics with three TZs. For validation, a triple-mode filter centered at 3.04 GHz was fabricated, and the measured return losses are better than 27 dB and the minimum in-band insertion loss is 0.65 dB.

Under large interference, in order to keep the surface-mounted permanent magnet synchronous motor with better operating characteristics, real-time identification of the parameters such as resistance, inductance and flux linkage during motor operation becomes very necessary. This paper proposes an online self-applicable identification method for motor parameters based on recursive least squares method. The parameter identification model is analyzed in Matlab / Simulink, which proves that the method can accurately identify the values of resistance, inductance and flux linkage parameters. It also proves the value of this method.

The traditional online upgrade of the digital signal processor (DSP) program is realized through the serial communication interface (SCI) or the serial peripheral interface (SPI), it needs to solidify the pin level. When the upgrade is repeated, it must be powered off and restarted, which is difficult to meet all application scenarios. In view of this situation, a new method to upgrade DSP program online by using controller area network (CAN) bus is proposed. By pre-programming the boot program and adding a jump function, the upper computer can send binary file to update application program repeatedly. Experiments show that this method is simple, anti-interference and fast programming, which greatly improves the maintenance efficiency of the system.

Aircraft design engineering is multi-disciplinary, which includes the flight control system, the aerodynamics and the propulsion system. Their design and verification need an interdepartmental coordination. Traditionally, the requirement analysis, the system design and simulation are processed independently. It is difficult to establish a standardized communication mechanism for engineers from different departments. Thus, there was a challenge to achieve the co-design of aircraft subsystem based on the standardized system architecture. This paper presents an integrated design and verification method of aircraft and propulsion system. The idea is to convert the system-level model to a standardized system architecture which contains structure and constraint. The system-level model based on Systems Modeling Language (SysML) can be exported to Extensible Markup Language (XML) which can rebuild the system architecture using Meta model. In this way, the system architecture becomes a guide for aircraft model-based design and verification.

A quad-band bandpass filter (BPF) based on isosceles right-angled triangular (RAT) resonator is proposed. By combining the two split-type dual-band frequency responses of the first and second resonant modes (LC mode and TM 100/010 z mode) in the isosceles RAT resonator, the filter features compact size. By utilizing the modal bypass couplings and the characteristic of split-type dual-band frequency responses, there are two transmission zeros (TZs) between each passband to improve the out-of-band performance of the filter. Also, the two via-holes connected the patch can control the first two bands independently, making the filter adjustable. The filter is fabricated and measured. The measured results demonstrate the attractive advantages of the designed quad-band BPF. Such as compact size and good performance.

As a new type of material, amorphous alloy has the advantages of low loss, low coercive force and high resistivity compared with traditional silicon steel. In this paper, the magnetic properties of amorphous stator core and silicon steel stator core are compared. The loss of amorphous stator core is only about 1/5 of silicon steel stator core at the same frequency and flux density. In this paper, a 1. 2kW two poles high speed three-phase asynchronous motor was analyzed as an example. In order to further improve the efficiency of the motor, the effects of the squirrel cage material, the number of bars and the diameter on the motor are considered. The simulation results show that the motor has the lowest loss and the highest efficiency under the condition that the copper bar is used as the squirrel cage material with the number of bars 18 and the diameter of the bar 3 mm.

The identification of power system vulnerable lines has an important meaning to predict the cascading failure, improve the power system security and prevent major power blackouts. This paper proposes a new vulnerable lines identification method considering the characteristics of high-speed railway load. The authors establish a correlation network depending on the data of high-speed railway load and N-1 probabilistic power flow calculation, meanwhile considering the topological structure and electrical coupling relationship between branches. The authors use improved weighted K-shell decomposition method to identify vulnerable lines based on the established correlation network. The accuracy and validity have been verified in the numerical simulation of IEEE-39 bus network.

The rapid development of ubiquitous and high-speed wireless communication technology has driven the increasingly serious demand for the Location-based Services (LBSs). In this circumstance, we propose a new crowd-sourced calibration-free and inertial sensor- independent indoor pedestrian localization approach, namely Mann-Whitney rank-sum testing via segments labeling (Marvel). In concrete terms, first of all, the motion paths are modeled by using the A* algorithm with the floor plan provided by the merchant, and then each motion path is segmented according to the preset expected localization accuracy. Second, by setting the signal similarity threshold, the Received Signal Strength (RSS) sequences which are collected by the human subjects following their daily routines in target environment are also segmented. Third, the proposed Marvel is adopted to cluster the motion path segments as well as RSS sequence segments respectively to construct the physical and signal logic graphs. Finally, by using the concept of backbone nodes diffusion mapping to establish the mapping relations between the physical and signal spaces, the pedestrian localization and the related motion analysis are conducted by the server. Furthermore, the extensive experimental results show that the proposed approach is capable of achieving higher localization accuracy compared with the current state-of-the-art approaches.

In recent years, neurofeedback training becomes a gradual non-pharmacological treatment trend for attention-deficit/ hyperactivity disorder (ADHD) to improve attention. In this study, we design a 3D game to improve and assess children with ADHD. We observed the brainwave change to integrate computer game training to explore the impact of training on children. In the process of the training, children can learn to focus and relax. And then children can further to control attention and meditation, helping to improve the efficiency of their learning and inhibit the frequency of ADHD symptoms. After training, we record these data and analyze the parameters and brainwave status. In addition, we found the progress obviously on children with ADHD through the game training. The prosed scheme can give a feedback and improve children's attention and meditation significantly.

Recently, fully convolutional network (FCN) and dilated convolution have shown significantly improvment in semantic segmentation task. Deep residual network (ResNet) has shown strong ability in object recognition. However, FCN-based methods utilize intermediate layers and spatial context information ineffectively. Repeated 2-step striding in ResNet is harmful for segmentation tasks. In this paper, we propose a new semantic segmentation method based on FCN and ResNet. Here, we combine the dilated convolution designed for semantic segmentation with residual unit to enlarge receptive field of ResNet. Meanwhile, “pre-activation” method is used in dilated residual unit. We propose a new segmentation architecture which intergrate multiple intermediate layers and global context information. We extract low-level features of intermediate layers with multi-path refinement which consists of relu-conv unit and chained residual pooling. Global context is gathered by a pyramid pooling method which is connected to the final output of ResNet. Outputs of these 2 modules are then fused to reach high-resolution prediction. In this way, global and local information from pyramid pooling can be enhanced by multi-path refinement. Fully-connected conditional random field is added as a “post-processing” after fusion to receive accurate boundary performance. Our proposed approach achieves 74.7% IoU on Cityscapes benchmark.

With the rapid development of Wireless Local Area Network (WLAN) technique, the indoor WLAN localization has caught significant attention. In this paper, a novel indoor WLAN localization approach by using the high-dimensional manifold alignment with limited calibration load is proposed. Different from the conventional dimension-reduction based manifold alignment approach which preserves a limited part of the Received Signal Strength (RSS) data information, we first construct an innovative objective function from the augmented physical locations and the corresponding RSS data. Second, the closed-form solution to the objective function is obtained by applying the Lagrange multiplier approach. Finally, the target location is estimated at the closest point in the manifold. Furthermore, we present some preliminary analysis towards the generalization of the proposed objective function to the scenario with multiple types of measurements used for the localization. The extensive analytical and experimental results demonstrate that the performance of the proposed approach is well with limited calibration load and can be further improved by using more calibrated locations with known RSS data.

A mesh network, which enjoys high connectivity, is very fragile to destroying events. These events will destroy some parts of the network and affect the network performance for a long time. Therefore, devising fault-tolerant routing algorithms for mesh networks is significantly important. In this paper, we introduce a Software-Defined Networking-based (SDN-based) fault-tolerant routing algorithm for a mesh network according to one existing wormhole routing technique because the concepts of SDN-based routing introduced recently and early wormhole routing are similar. Particularly, unlike the latter, we need not to assume that states of all nodes are known in advance. Instead, via the centralized management of the SDN controller, we propose a procedure to find the states of all nodes in flight. Moreover, with the management of OpenFlow flow tables, the implementation complexity of the routing algorithm can be simplified. Finally, we perform some simulation experiments to demonstrate the fault-tolerant capability of our SDN-based routing protocol.

It is known that the variable is strong coupling, nonlinear, multivariable and large time-delay dynamic characteristics in the raw cement vertical mill grinding process. Against the problem which is difficult to establish accurate mathematical model, this paper establishes a production index prediction model of vertical mill raw meal grinding process by using echo state network and Kalman Filter. And it's to use a cement plant raw cement vertical mill grinding process parameters to training and testing data of the model. After comparing with the BP neural network model, the experimental results show that the proposed modeling method is effective, and the raw cement vertical mill grinding process operation process stability has increased.

In recent decade, the Received Signal Strength (RSS) based indoor localization has caught significant attention, but it always suffers from the time-consuming and labor intensive fingerprint calibration. At the same time, the Simultaneous Localization and Mapping (SLAM) technique is considered with the low time and laboring cost, whereas the dedicated hardware is often required. To solve these problems, a novel indoor WLAN SLAM approach by using the Edge Detection based Gene Sequencing (EDGES) is proposed. First of all, a batch of RSS sequences is sporadically collected in target area. Second, the spectral clustering is conducted on RSS sequences to construct the cluster graphs, and then the EDGES approach is applied to assemble the cluster graphs into a logic graph. Finally, the mapping from the logic graph into ground-truth graph is established to realize indoor WLAN SLAM. The extensive experimental results prove that the proposed approach can achieve satisfying localization accuracy without site survey of location fingerprinting or motion sensing.

Polyimide film has been used as an insulation material in the excitation winding of the high temperature superconducting motors. The existence of surface charge has a great influence on the breakdown characteristic. Direct fluorination is an effective method of polymers surface modification which can improve the electrical properties of original material. Therefore, it is necessary that the surface potential behaviors of fluorinated polyimide films under low temperature were studied to clarify the effects of fluorination time and low temperature. Polyimide specimens were fluorinated in a reaction kettle at 55 °C using a F2/N2 blend with volume fraction of 80% nitrogen and 0.05 MPa for 15, 30, 45 and 60 min, respectively. The specimens without fluorination were also prepared for reference. Corona charging was performed with pulse voltage at a relative humidity of ∼ 11% in atmospheric air. Then the specimens were cooled by liquid nitrogen in 10 s before and after corona charging. The surface potential was measured by the device of an electrostatic voltmeter. The experimental results indicate that the behaviors of surface potential in the surface of polyimide films are affected by the charge polarity, specimen temperature and fluorination time.

Epoxy resin as an insulating material is widely used in superconducting motors because of its excellent insulation properties under low temperature. However, epoxy has a relatively low thermal conductivity so it may be damaged by thermal breakdown. Tracking failure is a kind of thermal breakdown happened on polymer surface. In this paper, the tracking failure behaviors of Epoxy/BN (boron nitride) composites under low temperature were studied to clarify the effects of low temperature and BN particles on tracking performance. Tracking failure process under different pulse frequency was measured with a digital camera and an infrared thermal imager. The CCD camera was used to observe the failure process while the infrared imager was used to measure the thermal accumulation and decay process. Obtained results showed that the addition of BN fillers and low temperature had a significant inhibitory effect on tracking failure process. In liquid nitrogen environment, the time to tracking failure increased obviously. It is concluded that the ability to inhibit tracking is improved by reducing the temperature at the concentrated discharge region and increasing the heat dissipation region.

Silicone rubber (SiR) has been an important material widely used in the cable accessories in cross-linked polyethylene (XLPE) cables. The electrical tree is a serious threat to SiR insulation and it will cause breakdown when reaches the ground. The high carrying capacity of superconducting cable makes the magnetic flux density up to hundreds of mT around the conductor. However, the effect of high magnetic flux density on electrical tree in SiR has not been researched. In this paper, the magnetic flux density ranged from 0 to 400 mT. The electrodes were typical needle-plate electrodes. The frequency of the applied AC voltage was 50 Hz. The growth process of electrical tree was recorded by a microscope system and the pictures were taken. The experiment result indicated that the high magnetic flux density changes the tree structure and affects the growth of tree length and width.

High temperature superconducting (HTS) cable has now reached the stage where their application in power systems is in the process of being implemented. Polyimide film has been used as an insulation in HTS cable systems with the advantages of low temperature resistance, good mechanical properties and excellent dielectric properties. Due to the organic properties of polyimide, the breakdown of the films is one of main problems to the safety and reliability of HTS cable. Partial discharge (PD) events may lead to material degradation and total breakdown. Our recent researches have shown that fluorination as a chemical modification technology can influence the surface charge behaviors thus influence the PD characteristics of modified polyimide films. In this paper, the effect of fluorination time on the partial discharge and breakdown characteristics of fluorinated polyimide films have been carried out. Samples were surface fluorinated in a laboratory vessel at about 328 K (55 °C) using a F2/N2 mixture with 20% F2 by volume and 0.05 MPa (500 mbar) for 15, 30, 45 and 60 minutes, respectively. Atomic force acoustic microscope (AFM) was used to detect the surface topography of the samples. The PD characteristics results showed that the partial discharge quantity decreases with the fluorination time increasing from 0 min to 45 min and increases with the fluorination time increasing from 45 min to 60 min.

Polyethylene (PE) is widely used as insulating materials in superconducting motors because of its excellent insulation properties. Tracking failure is a typical thermal breakdown which is caused by thermal accumulation on polymer surface. In this paper, the tracking failure behaviors of PE/BN (boron nitride) composites under low temperature were studied to clarify the effects of low temperature and BN particles on tracking performance. Tracking failure process under different pulse frequency was measured with a digital camera and an infrared thermal imager. The CCD camera was used to observe the failure process while the infrared imager was used to measure the thermal accumulation and decay process. Obtained results showed that the low temperature and the addition of BN fillers had a significant inhibitory effect on tracking failure process. In liquid nitrogen environment, the time to tracking failure increased obviously. It is concluded that the ability to inhibit tracking is improved by reducing the temperature at the concentrated discharge region and increasing the heat dissipation region.