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Fault diagnosis of insulators in aerial images is an essential task of power line inspection to maintain the reliability, safety, and sustainability of power transmission. This paper develops a novel method for intelligent diagnosis of electrical insulators based on deep learning, termed Box-Point Detector, which consists of a deep convolutional neural network followed by two parallel branches of convolutional heads. These two branches are utilized to locate the fault region and estimate insulator endpoints, which presents a new representation for insulator faults. Endpoints of the faulty insulator string can provide detailed and correlative information for enhancing the diagnosis capability of component-dependent faults that occur on component bodies. The proposed Box-Point Detector implements all predictions including region and endpoint into one network thus forms an efficient end-to-end structure, and adopts a smaller downsampling ratio to generate high resolution feature-maps in order to preserve more original information for small size faults. Experimental results indicate that Box-Point Detector can accurately diagnose high-voltage insulator faults in real-time under various conditions. Compared with some previous works using Faster R-CNN, SSD, and cascading network, our Box-Point Detector shows more competitively capabilities with high accuracy and robustness.

Insulator fault in the transmission lines is the main factor of power transmission accident. The images captured from the aerial inspection can be utilized to detect the fault of insulators for further maintenance. For automatic transmission lines inspection system, the insulator fault detection is an interesting and challenging task due to the complex background and diversified insulators. In this paper, we propose a novel insulator fault detection method based on multi-level perception for aerial images. The multi-level perception is implemented by an ensemble architecture which combines three single-level perceptions. These single-level perceptions include the low level, middle level, and high level that are named by the attention to the insulator fault. They detect the insulator fault in the entire image, multi-insulator image, and single-insulator image, respectively. To address the filtering problem in the combination of three single-level perceptions, an ensemble method is proposed for generating the final results. For training the detection models employed in the multi-level perception, a powerful deep meta-architecture so-called single shot multibox detector (SSD) is utilized. The well-trained SSD models can automatically extract high quality features from aerial images instead of manually extracting features. By using the multi-level perception, the advantages of global and local information can achieve a favorable balance. Moreover, limited inspection images are fully utilized by the proposed method. Fault detection recall and precision of the proposed method are 93.69% and 91.23% testing in the practical inspection data, and insulator fault under various conditions can be correctly detected in the aerial images. The experimental results show that the proposed method can enhance the accuracy and robustness significantly.

Lead-free has been a goal that people pursue due to the environmental pollution caused by lead in lead-based materials. K0.5Na0.5NbO3(KNN) is one of the most promising lead-free piezoelectric materials. Theoretically, the piezoelectric properties of single crystals are much better than those of polycrystalline materials. However, it is difficult to fabricate uniform KNN-based crystals by the high-temperature melt method because of volatilization of elements. This method also needs complicated equipment and is expensive. Here, a seed-free, solid-state crystal growth (SFSSCG) method was used to prepare Mn, Li, and Bi co-doped KNN crystals, which show an ultrahigh piezoelectric coefficient of about 1050 pC N−1, around one order of magnitude higher than that of pure KNN ceramics. Furthermore, the effective piezoelectric coefficient d33* of this crystal can reach 2290 pm V−1 at a unipolar electric field of 10 kV cm−1. This crystal also shows a high Curie temperature and good ferroelectricity. It is expected that the lead-free KNN-based single crystals fabricated by this simple method show promise for high performance ferroelectric and piezoelectric applications in industry and are environment-friendly.

All-solid-state lithium batteries (ASSLBs) using sulfide solid electrolytes (SSEs) offer an attractive option for energy storage applications. Lithium anode is the ultimate goal for ASSLBs, but lithium-indium (Li-In) alloy anode is more widely utilized in lab testing owing to the quite stable interface and elimination for the risk of short circuit. However, vigorous growth of Li-In dendrites in SSE is discovered in the present work when a full cell (LiNbO3 coated LiNi0.6Co0.2Mn0.2O2//Li6PS5Cl//Li-In) is cycled in high loading and high rate. Our study demonstrates that Li-In anode is unstable towards SSEs at high current, which induces Li-In dendrite growth enclosing electrolyte particles and eventually results in cell death after a long cycling. The morphology and growth mechanism of Li-In dendrites are revealed by scanning transmission electron microscopy-electron energy loss spectroscopy (STEM-EELS) analysis and density function theory (DFT) calculations. Moreover, the differences between Li and Li-In dendrites are systematically compared.

As a market trading mechanism, carbon emission trading plays an important role in effectively reducing the overall cost of carbon emission and achieving the "3060" carbon target.At present, the carbon emission trading mechanism has played a role in the world and become an effective means to promote climate governance.China's energy system has always been a high-carbon, high-coal system. The burning of fossil fuels releases a large amount of CO2, which is the main source of carbon emissions.With the improvement of people's living standards, electricity consumption continues to increase. If we want to achieve a substantial reduction in China's carbon emissions, we need to change the structure of the power generation system, which is dominated by coal.

With the increasing attention on oceanography, more effective exploration technology has been of great interests in the community of ocean engineering. Side-scan sonar is a popular imaging equipment for seabed topography; however, it is commonly used under 4 knots, which does not meet the actual demand of the modern oceanographic research. This paper proposes a high-speed side-scan sonar imaging scheme based on multi-beam forming technology. In this scheme, the digital signal processing system can adjust the maximum response direction of the receiving array by introducing appropriate phase shift or time delay to the output, so as to increase the scanning range and then improve operation efficiency. In order to verify the feasibility of this imaging algorithm, an ocean environment model is constructed, which simulates the acoustic propagation theory, the principle of seabed acoustic backscattering and the acoustic signal modulation method. After analyzing the acoustic characteristics of uniform linear array, an underwater acoustic transducer with multiple receiving subarrays is designed. In the process of simulated navigation, the receiving subarrays will generate the electrical signal containing seabed acoustic information. Based on the simulation signal, the parameters of the digital filter in the actual system can be determined in advance, which provides convenience for later processing. The time delay matrix of each receiving channel based on dynamic focusing beamforming method can be verified by imaging the seabed model. The processed acoustic data are combined with GPS information and heading angle to generate seabed scanning image in the host computer system. This paper mainly presents the imaging algorithm of multi-beam side-scan sonar digital signal processing system.

Basic configurations of various all-optical clocked flip-flops (FFs) and optical random access memory (RAM) based on the nonlinear polarization rotation (NPR) effect of low-polarization-dependent semiconductor optical amplifiers (SOA) are proposed. As the constituent elements, all-optical logic gates and all-optical SR latches are constructed by taking advantage of the SOA’s NPR switch. Different all-optical FFs (AOFFs), including SR-, D-, T-, and JK-types as well as an optical RAM cell were obtained by the combination of the proposed all-optical SR latches and logic gates. The effectiveness of the proposed schemes were verified by simulation results and demonstrated by a D-FF and 1-bit RAM cell experimental system. The proposed all-optical clocked FFs and RAM cell are significant to all-optical signal processing.

The slippage fault diagnosis of dampers in aerial images is a challenging task for an automatic transmission line inspection system. In this paper, an effective and reliable slippage fault diagnosis method based on a deep learning technique and distance constraint method for aerial images is proposed. In the detection stage, the Faster Regions with Convolutional Neural Network (R-CNN) is employed. It takes the aerial images as input, detects the dampers in the image by learning the basic features of dampers, and outputs the coordinates of the dampers in a single image. In the diagnosis stage, the distance between adjacent dampers in the horizontal axis is calculated through the damper coordinates obtained in the detection stage, and the relationship between the distance and the selected threshold is the judgment basis of slippage fault diagnosis. The results show that the slippage fault of dampers can be quickly and accurately diagnosed in the aerial images by the proposed method.

Liquid nitrogen has been working as an important medium in fire extinguishing and prevention, due to its efficiency in oxygen exclusion and heat removal. Such a technique is especially crucial for coal industry in China. We built a tunnel model with a temperature monitor system (with 36 thermocouples installed) to experimentally study heat and mass transfer of liquid nitrogen in non-homogeneous coal porous media (CPM), and expected to optimize parameters of liquid nitrogen injection in engineering applications. Results indicate that injection location and amount of liquid nitrogen, together with air leakage, significantly affect temperature distribution in CPM, and non-equilibrium heat inside and outside of coal particles. The injection position of liquid nitrogen determines locations of the lowest CPM temperature and liquid nitrogen residual. In the deeper coal bed, coal particles take longer time to reach thermal equilibrium between their surface and inside. Air leakage accelerates temperature increase at the bottom of the coal bed, which is a major reason leading to fire prevention inefficiency. Measurement fluctuation of CPM temperature may be caused by incomplete contact of coal particles with liquid nitrogen flowing in the coal bed. Moreover, the secondary temperature drop (STD) happens and grows with the more injection of liquid nitrogen, and the STD phenomenon is explained through temperature distributions at different locations.

The presence of the bird nests on the electric power tower becomes a hazard to the safety and stability of the transmission line. In recent years, detecting the bird nests on the transmission line by using drones is being one of the essential missions of power inspection. The migration of image processing methods from computer vision to power image identification has increasingly becoming a trend. The detection method combining Single Shot Detector and HSV color space filter is proposed in this paper to identify the bird nests by making use of the image features with a large color span under different illumination angles. The fine-tuned Single Shot Detector network is trained and utilized to identify the bird nests and the detection result is clipped which called sub-images. Then the sub-images are filtered by the selector based on HSV color space, who contains none object of bird nests can be removed by the pixel percentage. The experimental results show that the proposed method can accurately detect the bird nests in the testing transmission line inspection images, and the accuracy can be up to 98.23%. Compared with other single traditional methods, the proposed bird nests detection method combining the deep learning and the HSV color space filter greatly enhances the detection accuracy.

The vortex light field has helically shaped wavefront and phase singularities where each photon carries orbital angular momentum (OAM). Its unique properties allow the vortex light field to spatially distinguish incoherent scattered light from coherent non-scattered light, which thus can therefore be used as a spatial filter element. And in the strong scattering environment, this spatial filtering effect is particularly remarkable. The principle of spatial filtering was analyzed and studies of vortex light field in strong scattering environment were introduced. The underwater lidar ranging experiment using the vortex light field was designed to prove that the vortex light field can improve the accuracy of the underwater lidar through its spatial filtering in strong scattering environment. And with strong scattering, this spatial filtering improves the range accuracy more significantly.

With the widely application of Unmanned Aerial Vehicle (UAV) in transmission lines inspection, the aerial images taken by UAVs can be utilized to detect insulator and its fault for further maintenance. In this paper, we propose a detection method for insulator and its fault based on Faster Regions with Convolutional Neural Network (Faster R-CNN). The proposed method contains a convolutional network followed by a region proposal network and a object detector. The results show that the proposed method can realize effective detection of insulators and achieve a precision of 94% and a recall of 88% on the testing dataset. Additionally, the computation cost of the proposed method meets the requirements of real-time detection.

This paper proposes a volleyball trajectory tracking method adapting to occlusion scenes. Firstly, the target volleyball is obtained in the video manually and the Kalman filter algorithm combined with Continuously Adaptive Mean Shift (CAMSHIFT) algorithm is used to track and determine the size and position of the volleyball in each frame of video, and then it is determined whether there exists an occlusion. If there is no occlusion, positions of the volleyball in each frame of video are connected to obtain the trajectory of the volleyball. If there is occlusion, the Kalman filter algorithm is used to predict the positions of the volleyball in the occlusion section, and the size remains unchanged. Finally, the positions of the volleyball in each frame of video is connected to a line to obtain the trajectory of the volleyball motion. The proposed approach solves the problem of more complicated video background in volleyball movement. When the volleyball is blocked, it can accurately predict the volleyball movement trajectory so as to accurately track the volleyball movement trajectory under dynamic and occlusion scenes.

The influence of environment changing, e.g. background beam change, trees waggle, and rain or snow day brings More difficult for moving target detecting. A background dynamic generation algorithm is presented in the paper, and the background dynamic generation algorithm is used to dynamically construct background image, the impact of the environment change is reduced in a certain extent for the moving target detection. Secondly, the background difference method is used to detect the moving target, when the moving target exists, the direction and the coordinate of the moving target is determined according to the result of continuous 2 frame images subtract the background. Finally, an algorithm for calculating the rotation angle of the pan/tilt/zoom is presented, the horizontal rotation angle and the vertical rotation angle of the pan/tilt/zoom is calculated according to the pan/tilt/zoom rotation angle algorithm, and the moving target detection and automatic tracking function is realized.

The purpose of this research is to model a hypersonic vehicle in the pull-up phase and provide an insight into the inherent dynamics. Based on Newtonian mechanics, the theoretical flight dynamic model of the pull-up phase of reentry motion is established; Based on MATLAB/SIMULINK, simulation model for reentry hypersonic vehicle was modeled. Lifting body hypersonic vehicle aerodynamic data is obtained by high-accuracy CFD code which copyright by CAAA. We adopted feedback linearization control theory, pitching angle holding control laws in order to keep maximum lift-drag ratio glider, the six degree of freedom (DOF) simulation validate the control law. The simulation results show some hypersonic flight characteristics, including static unstable, earth radius and rotationeffects and high-coupledcharacteristics. The simulation model and results provide a useful reference for a hypersonic vehicle's dynamics analysis, control law design and overall design.

In order to realize autonomous landing of the unmanned aerial vehicle (UAV) in power patrolling, a visual method vision based on Faster Regions with Convolutional Neural Network (Faster R-CNN) for UAVs is studied. In this paper, we design the landing sign of the combination of concentric circles and pentagon, and propose the Faster R-CNN recognition algorithm which can be used to identify the target sign. Faster R-CNN successfully identifying the landing mark is the most important step for the UAV autonomous landing. Then, the estimation algorithm of position and direction based on vision is proposed. Position and direction for the UAV landing can be obtained based on least squares ellipse fitting and Shi-Tomasi corner detection method after the landing sign is effectively identified by Faster R-CNN. The experimental results show that it can achieve recognition speed of nearly 81 millisecond each frame and 97.8% accuracy by using Faster R-CNN for detection and identification. The proposed method has better identification accuracy compared with three target identification methods, the Support Vector Machine (SVM) classification, the Back Propagation (BP) neural network and You Only Look Once (YOLO) based on deep learning. The position and direction estimation error of the vision algorithm is within the allowable range, and it can meet the UAV real-time landing requirements.

To reduce data collection time for deep learning of robust robotic grasp plans, we explore training from a synthetic dataset of 6.7 million point clouds, grasps, and analytic grasp metrics generated from thousands of 3D models from Dex-Net 1.0 in randomized poses on a table. We use the resulting dataset, Dex-Net 2.0, to train a Grasp Quality Convolutional Neural Network (GQ-CNN) model that rapidly predicts the probability of success of grasps from depth images, where grasps are specified as the planar position, angle, and depth of a gripper relative to an RGB-D sensor. Experiments with over 1,000 trials on an ABB YuMi comparing grasp planning methods on singulated objects suggest that a GQ-CNN trained with only synthetic data from Dex-Net 2.0 can be used to plan grasps in 0.8sec with a success rate of 93% on eight known objects with adversarial geometry and is 3x faster than registering point clouds to a precomputed dataset of objects and indexing grasps. The Dex-Net 2.0 grasp planner also has the highest success rate on a dataset of 10 novel rigid objects and achieves 99% precision (one false positive out of 69 grasps classified as robust) on a dataset of 40 novel household objects, some of which are articulated or deformable. Code, datasets, videos, and supplementary material are available at http://berkeleyautomation.github.io/dex-net ., To appear at Robotics: Science and Systems 2017

It is necessary to carry out regular maintenance and replacement of the traditional power transformer pressure and humidity absorber in the long running time. When the transformer in use to upgrade or retrofit, usually need to find a simple, practical solution. Conventional moisture absorbers require the use of silica gel particles or similar desiccant to absorb water, the need for regular replacement of desiccant. In order to improve the working efficiency of desiccant and reduce the cost of desiccant replacement, this paper introduces the latest technology of dual-channel maintenance-free moisture absorber, describes the working principle of the device and the advantages of the element, and its application prospects in the power industry Outlook.

The pure electric minivan is different from electric car. Combined with a given vehicle, vehicle simulation model established in Cruise software, complete simulation by setting tasks for the selected models designed drivetrain. Simulation results show that: The design of the transmission ratio can best meet the performance requirements of the matching target power analysis and simulation of electric minivan provides a new way, with practical guidance.

Wind power prediction of wind farm plays a decisive role in stable electric power system operation.The BP neural network’s basic principle was introduced, and the numerical weather prediction (NWP) data and power data of wind farm as the training data of BP neural network was selected and trained; a linear regression model about the sample prediction error was presented, which considers the coupling relationship between the individual sample prediction error, the individual sample prediction error of BP neural network was selected as the regression factor, the individual sample prediction result of BP neural network was modified. As the modified prediction results performing, the prediction algorithm of short-term wind power considering the sample prediction error correction, has good self-learning and adaptive ability of BP neural network. It has overcome the shortcoming that the BP neural network has only considered the overall the prediction error of training samples, but without considered the prediction error of individual samples. This has further improved the prediction accuracy of BP neural network.

The ~3 μm fluorescence was investigated in the Ho2O3-doped transparent tellurite glass-ceramic for the first time. The branching-ratios and emission cross-sections were calculated. The glass-ceramics had high branching-ratio (20.5%) and large emission cross-section (1.76 × 10−20 cm2) corresponding to Ho3+:5I6→5I7 transition. After crystallization, the ~3 μm fluorescence intensity increased obviously excited by 640 nm laser diode. The broadband fluorescence about 3 μm was observed under excitation by a 1950-nm thulium-doped fiber lasers. The increased ~3 μm fluorescence intensity and narrowed spectrum demonstrated the Ho3+ ions embedded into the crystalline phase. These results indicate that the tellurite glass-ceramics may be a promising material for mid-infrared lasers.

National Natural Science Foundation of China [20844006]; National Basic Research Program of China (973 Program) [2010CB732203]; Fundamental Research Funds for the Central Universities [2010121055]; Scientific and Technological Innovation Platform of Fujia

To detect the heating problem of high voltage plant in substation, the paper analyzed the status of heating defect detection system for high voltage plant of substation in our country, proposed an improved system program based on infrared image processing. The program achieved the automatic detection of heating defect detection, and also can exactly locate the position of heating defect. Besides, its future work was also discussed.

A four-finger InGaAs/InP double heterojunction bipolar transistor is designed and fabricated successfully by using planarization technology. The emitter area of each finger is 1 ? 15?m2. The breakdown voltage is more than 7 V, the maximum collector current could be more than 100 mA. The current gain cutoff frequency is as high as 155 GHz and the maximum oscillation frequency reaches 253 GHz. The heterostructure bipolar transistor can offer more than 70mW class-A maximum output power at W band and the maximum power density can be as high as 1.2W/mm.

The layer structure of InGaAs/InP double heterojunction bipolar transistor (DHBT) is designed to enhance the frequency performance and breakdown voltage. The composition-graded base structure is used to decrease the base transit time. The InGaAs setback layer and two highly doped InGaAsP layers are used to eliminate the conduction band spike of the collector. The submicron-emitter InGaAs/InP DHBT is fabricated successfully. The base contact resistance is greatly decreased by optimization of contact metals. The breakdown voltage is more than 6 V. The current gain cutoff frequency is as high as 170 GHz and the maximum oscillation frequency reached 253 GHz. The DHBT with such high performances can be used to make W-band power amplifier.

In pass design of three-roll rolling process, accurate numerical model in deformation region is very important. Thus, the numerical model of round rod in flat triangle pass in three-roll tandem rolling process was proposed by mathematics analytic method in this paper. The parameters of numerical model, including arc length of the contact field, width of the contact field, rolling reduction(maximum, point) and rolling piece dimension at the exit, were established based on mathematical analysis.

We design and fabricate an InGaAs/InP double heterostructure bipolar transistor (DHBT). The spike of the conduction band discontinuity between InGaAs base and InP collector is successfully eliminated by insertion of an InGaAs layer and two InGaAsP layers. The current gain cutoff frequency and maximum oscillation frequency are as high as 155 and 144 GHz. The breakdown voltage in common-emitter configuration is more than 7 V. The high cutoff frequency and high breakdown voltage make high-speed and high-power circuits possible.

A new proposed Metal-Insulator-Metal (MIM) serie capacitor model for Monolithic Microwave Integrated Circuit is presented. The MIM serie capacitor model covers the frequency range up to 40 GHz for millimeter-wave circuit design application. The parasitic elements of model are extracted by parameters fitting optimization between the measured S-parameters and model simulated result. The relationship between the optimized parasitic element values and the dimension data of capacitor structure can be expressed.

A high power C-band monolithic voltage controlled oscillator (VCO) based on AlGaN/GaN HEMT is presented. The oscillator design utilizes a common-gate negative resistance structure, and a HEMT device acted as a varactor is used to control the VCO's oscillation frequency. The VCO operating at 20V drain bias and −3V gate bias exhibits an output power of 26 dBm at the center frequency of 5.96 GHz with dc-to-RF efficiency of 30%. Phase noise is estimated to be −96 dBc/Hz at 500 KHz offset. With the varactor's voltage from −1.5 V to −16 V, the frequency tuning range is from 5.61 GHz to 6.38 GHz. The measured results show high output power, good power flatness and good tuning linearity over the tuning band. This work demonstrates the potential for AlGaN/GaN HEMT technology to be used in high power microwave oscillator applications in very compact transceiver systems.

This paper investigates load-pull measurement of AlGaN/GaN high electron mobility transistors (HEMTs) at different numbers of gate fingers. Scalable small-signal models are extracted to analyze the relationship between each model's parameters and the number of device's gate fingers. The simulated S-parameters from the small-signal models are compared with the reflection coefficients measured from the load-pull measurement system at X-band frequencies of 8.8 and 10.4 GHz. The dependency between the number of device's gate fingers and load-pull characterization is presented.

Noise performance of AlGaN/GaN HEMT has received more and more worldwide attention in recent years. In this paper, a MMIC process in AlGaN/GaN technology has been developed. A LNA design is based on a AlGaN/GaN HEMT noise model and a complete model library of passive elements under the optimum bias for LNA design. The paper describes modeling, bias dependence of small-signal and noise parameters, circuit design of the LNA using noise model without transistor noise measurement, and demonstrates a NF of 2 dB at 8GHz.

88 nm-gate InP-based InAlAs/InGaAs HEMTs with the gate width of 75 μm have been designed and fabricated. They exhibited a current gain cutoff frequency (f T ) of 204 GHz and a maximum oscillation frequency (f max ) of 352 GHz at a drain-source voltage (V ds ) of 1.5 V and a gate-source voltage (V gs ) of 0 V. Excellent DC characteristics were also demonstrated with the DC peak transconductance (g m, max ) of 918 mS/mm and the maximum current density of 635 mA/mm.

There is asymmetric information between the headquarter and its subsidiaries. In order to maximize their utilities, subsidiaries incline to submit fake performance information, headquarter doesn't participate subsidiaries' business operation, so it can't identify these information. In order to control subsidiaries' behavior of manipulation, this paper sets up a “principal-agent” model, and then we obtain the optimal supervision mechanism and incentives contracts, which let subsidiaries submit truth performance information. Deductive mechanism show that, through improve the validity of supervision, the intensity of punishment, headquarter can reduce the probability of supervision and manipulation. When subsidiaries obtain specific share of profit, it can make them work hard, submit truth performance information and maximize utilities of headquarter.

Power system reliability is always one of the most important requirements in system operation and planning. For a long time, deterministic methods are widely used in system analysis, such as N-1 rule in transmission system static analysis, but the probability characteristics of the components failure have been ignored, and the risk of actual system can't been obtained exactly. Recently, large-range blackouts occurred frequently all over the world, especially in transmission system because of its numerous components and complex operation modes, which made the experts to worry about the effectiveness of the old methods, then a new way of assessing system risk is needed urgently. Probabilistic Reliability Assessment (PRA) Methodology firstly proposed by EPRI is a new method to perform risk-based reliability assessment. Unlike traditional deterministic methods, PRA Methodology calculates a measure of the probability of undesirable events and a measure of the severity or impact of the events, then combines them into a single reliability index - Probabilistic Reliability Index (PRI) and develops PRI program based on PRA Methodology. So far PRA Methodology has been widely accepted in North America and already been used by many utilities since 2001, but it hasn't been introduced into the domestic power system. In this paper, PRA Methodology is adopted to analysis Chongqing's transmission system of 2009, mainly including of system comprehensive analysis, connection section analysis, specific status analysis, danger point analysis, etc. The research conclusion can be applied to practical operation of the network to help electrical operator to finish their work, such as weak links location, influence range assessment and the optimal scheme choosing, then the system risk can be acquired quantitatively to provide technical support for leader decision and power system planning. This work has demonstrated that the PRA Methodology can address these new uncertainties and significantly improves the ability of conducting effective transmission operational planning.

For the 3D brain MRI parameterized statistical model segmentation method, the pre-processing method of brain image is brought forward for the model. First the DWM(directional weighted median) filter and Gaussian template are used to de-noise the brain MRI image. Then the Laplacian operator is used to sharpen the image, and the Robert operator is used to realize the edge detection, which can improve the measurement accuracy. And the MIP (maximum intensity projection) algorithm is applied to extract the largest connected component. The image of only brain vessel and part brain tissue can be obtained and the influence of background and no brain vessels like tissue to the images is eliminate. After pre-processing stage, the brain image is analyzed as the input to the parameterized statistical model. The small branches of the brain vessel can be segmented.

The configuration of a novel C-band spatial power combiner in waveguide is introduced. Employing the optimized Klopfenstein tapered slot antenna arrays, the waveguide-based power combiner based on 2times4 arrays at C band (3.6-4.4 GHz) was made. Its size is 70 mmtimes98 mmtimes170 mm and it is implemented by using eight commercial GaAs MMIC power amplifiers. CW power combiner measurements were performed with output power greater than 20 W (CW) at the frequency range from 3.6 to 4.4 GHz, where the maximum saturation output power is 46.82 dBm (48.08 W) at 4.35 GHz. The corresponding linear gain is about 9.5 dB,the PAE is approximately 26% and the efficiency is about 75%.

The aim of this study was to evaluate the clinical outcome of the hemilaminoplasty technique for the treatment of lumbar disc herniation (LDH). Forty-three cases of single-level LDH underwent a discectomy and hemilaminoplasty procedure. The preoperative JOA score and VAS of lower back and leg pain were 10.4+/-1.3, 7.8+/-2.1, and 8.6+/-1.7, respectively. The Cobb angle of lumbar sagittal alignment was 10.1+/-2.0. Twenty-five patients who agreed to lumbar discectomy through fenestration were enrolled as the control group. The postoperative JOA score and VAS of low back and leg pain of the hemilaminoplasty group were 19.4+/-1.3, 1.4+/-0.4, and 2.1+/-0.5, respectively. The Cobb angle was 29.2+/-1.9 degrees. There was no epidural scar observed in any of the patients. The Cobb angle of the hemilaminoplasty group was higher than that of the control group (p0.05), while the VAS was significantly lower (p0.05). Hemilaminoplasty is a useful method to improve clinical outcome, prevent epidural scar, and preserve the normal alignment of lumbar spine.

Global path planning is one of the key techniques of robotspsila intelligent control system, whose purpose is to find a collision-free path from the source position to the destination position according to some optimization criteria. The shaft robotpsilas global path planning in two-dimensional map is used as the study model to illuminate the path planning method of robot system based on simulated annealing dissipative Ant system. Comparing with the traditional ant system, the simulated annealing algorithm is used to enhance the global research ability of the method. Only the iterative best path is updated to increase the learning speed of the method. And the additional chaotic negative entropy is added in the system, which can be used to escape from the local minima and get the satisfied result. Finally the simulation results are provided to show the validity of the algorithm.

A novel watermark algorithm is proposed for copyright protection of JPEG2000 compressed cultural heritage images in digital museum system. Visually meaningful color logo is encoded as the watermark information. Due to its characteristics, the key problem is to decide how to hide as many bits information as possible into the image while ensuring the information can be retrieved correctly, even after various attacks. In this paper, a new method is proposed to resolve it. For the frequency domain of color logo after Daubechies9/7 wavelet transform, just only low frequency and intermediate frequency coefficient is chosen as the watermark code. In order to ensure both the robust and transparency, intermediate frequency coefficient after Daubechies9/7 wavelet transform is also proposed to embedding watermark code. To achieve the lowest computational cost and provide security, the lifting scheme was presented to implement the wavelet transform. The central contribution of this paper is to develop a watermark algorithm, resilient to like JPEG2000 lossy compression attack and other mainstream attacks, embedding compressed color logo image as watermark and extracting it correctly. Experimental results show that the proposed watermark scheme is computational and quite robust in face of various attacks such as JPEG2000 compression with high compression ratios, filtering, cropping, etc.

In this paper, A12O3 ultrathin film used as the surface passivation layer for AlGaN/GaN high electron mobility transistor (HEMT) is deposited by thermal atomic layer deposition (ALD), thereby avoiding plasma-induced damage and erosion to the surface. A comparison is made between the surface passivation in this paper and the conventional plasma enhanced chemical vapor deposition (PECVD) SiN passivation. A remarkable reduction of the gate leakage current and a significant increase in small signal radio frequency (RF) performance are achieved after applying Al2O3+BCB passivation. For the Al2O3+BCB passivated device with a 0.7 μm gate, the value of fmax reaches up to 100 GHz, but it decreases to 40 GHz for SiN HEMT. The fmax/ft ratio (≥ 4) is also improved after Al2O3+BCB passivation. The capacitance–voltage (C–V) measurement demonstrates that Al2O3+BCB HEMT shows quite less density of trap states (on the order of magnitude of 1010 cm−2) than that obtained at commonly studied SiN HEMT.

The n-type silicon integrated-back contact (IBC) solar cell has attracted much attention due to its high efficiency, whereas its performance is very sensitive to the wafer of low quality or the contamination during high temperature fabrication processing, which leads to low bulk lifetime τbulk. In order to clarify the influence of bulk lifetime on cell characteristics, two-dimensional (2D) TCAD simulation, combined with our experimental data, is used to simulate the cell performances, with the wafer thickness scaled down under various τbulk conditions. The modeling results show that for the IBC solar cell with high τbulk, (such as 1 ms–2 ms), its open-circuit voltage Voc almost remains unchanged, and the short-circuit current density Jsc monotonically decreases as the wafer thickness scales down. In comparison, for the solar cell with low τbulk (for instance, < 500 μs) wafer or the wafer contaminated during device processing, the Voc increases monotonically but the Jsc first increases to a maximum value and then drops off as the wafer's thickness decreases. A model combing the light absorption and the minority carrier diffusion is used to explain this phenomenon. The research results show that for the wafer with thinner thickness and high bulk lifetime, the good light trapping technology must be developed to offset the decrease in Jsc.

An optimized modeling method of 8 × 100 μm AlGaN/GaN-based high electron mobility transistor (HEMT) for accurate continuous wave (CW) and pulsed power simulations is proposed. Since the self-heating effect can occur during the continuous operation, the power gain from the continuous operation significantly decreases when compared to a pulsed power operation. This paper extracts power performances of different device models from different quiescent biases of pulsed current–voltage (I–V) measurements and compared them in order to determine the most suitable device model for CW and pulse RF microwave power amplifier design. The simulated output power and gain results of the models at Vgs = −3.5 V, Vds = 30 V with a frequency of 9.6 GHz are presented.

In this paper, the off-state breakdown characteristics of two different AlGaN/GaN high electron mobility transistors (HEMTs), featuring a 50-nm and a 150-nm GaN thick channel layer, respectively, are compared. The HEMT with a thick channel exhibits a little larger pinch-off drain current but significantly enhanced off-state breakdown voltage (BVoff). Device simulation indicates that thickening the channel increases the drain-induced barrier lowering (DIBL) but reduces the lateral electric field in the channel and buffer underneath the gate. The increase of BVoff in the thick channel device is due to the reduction of the electric field. These results demonstrate that it is necessary to select an appropriate channel thickness to balance DIBL and BVoff in AlGaN/GaN HEMTs.

Instantaneous wind speed spatial distribution of wind farm is the basis of the optimal control for wind turbines. A calculation method was proposed for the instantaneous wind speed spatial distribution in wind farm, which made the instantaneous wind speed spatial distribution is divided into wake and non-wake zone. For the non-wake zone, the instantaneous wind speed spatial distribution is mainly affected by the flow field coupling between wind turbines, in order to describe the influence accurately, a cross spectral matrix was constructed including the wind turbine mutual distance and the azimuth in wind farm, and the solving calculation process of the cross spectral matrix was deduced. For the wake zone, single wind turbine wake model and wake superposition model were established according to conservation of momentum, and then the average wind speed spatial distribution in wake zone was calculated. According to the average wind speed spatial distribution, the instantaneous wind speed spatial distribution was calculated. A wind farm is selected as case to verify the calculation method, and the results show that this calculation method can accurately describe the instantaneous wind speed spatial distribution of wind farm.

The automatic matching method of two curves is the central important issue in the fields of computer vision, automation and pattern recognition. The method can be widely used in the object dynamic track, content-based image retrieval and the automatic assembly of robot. In order to solve the easy serious error and lacking global description of the traditional method, the periodic curvature function is brought forward in the paper. The function is raised based on the concept of continues curvature. The curvature of the continuous function not only has the unchanged character among the circumvolving, translation and zooming but also has the global character of the curves. At the same time the Gaussian function is used to smooth the curves to improve the matching precision. In the experiment, the feasibility of the method is verified further. The method has the advantages of easy to realize and quick speed, and can be easily expand to the other similar systems.

AlGaN/GaN HEMT gate leakage increasing induced by passivation was investigated by employing double gate surface leakage test structure, circle and rectangular Schottky contact structure and metal float gate structure. It was demonstrated that surface leakage is not a major contributor to increasing of gate leakage. Increase of gate leakage depends on augmenting of Schottky contact edge effect and inhibiting "visual gate" between gate and drain