Search

A high resolution range profile (HRRP) is a summation vector of the sub-echoes of the target scattering points acquired by a wide-band radar. Generally, HRRPs obtained in a non-cooperative complex electromagnetic environment are contaminated by strong noise. Effective pre-processing of the HRRP data can greatly improve the accuracy of target recognition. In this paper, a denoising and reconstruction method for HRRP is proposed based on a Modified Sparse Auto-Encoder, which is a representative non-linear model. To better reconstruct the HRRP, a sparse constraint is added to the proposed model and the sparse coefficient is calculated based on the intrinsic dimension of HRRP. The denoising of the HRRP is performed by adding random noise to the input HRRP data during the training process and fine-tuning the weight matrix through singular-value decomposition. The results of simulations showed that the proposed method can both reconstruct the signal with fidelity and suppress noise effectively, significantly outperforming other methods, especially in low Signal-to-Noise Ratio conditions. Keywords: High resolution range profile, Intrinsic dimension, Modified sparse auto-encoder, Signal denoise, Signal sparse reconstruction

Infrared image recognition in substation is always a difficult problem. In order to solve the problem of recognition of knife gate, insulator and other components in infrared image, the target location technology of deep learning is proposed to realize the detection and recognition of typical components in infrared image, and the multi-target detection algorithm YOLO is selected to locate and identify the defects. Firstly, the image preprocessing technology is used to process the collected image, so as to filter the interference of background and other factors on the equipment identification. Then, the infrared image is detected by the YOLO target detection model based on multi feature fusion, so as to locate the position of inspection equipment in the infrared image. Then, the type of equipment is identified by the trained equipment classification model. Finally, the algorithm is tested with a large number of pictures in the substation scene.

The stationary multi-pinhole (MPH) SPECT has the potential to achieve dynamic human myocardial perfusion imaging (MPI) with high sensitivity and high resolution. In this work, the sensitivity of MPH SPECT is 0.06%, four-fold higher than conventional SPECT (typically 0.015%), the dual-head SPECT was set up 77.6 degree. Acquisition time of stationary MPH SPECT was about 5 minutes, and Siemens Symbia T16 took approximately 15 minutes. For stationary MPH SPECT system, dedicated image reconstruction algorithm was developed. System calibration is necessary to ensure installation accuracy and obtain mechanical information for generating system transfer matrix, which will be employed to iterative reconstruction. Projection data were reconstructed using a Pixel-based Ordered Subset-expectation Maximization (POSEM) reconstruction algorithm with prior information. Reconstructed results showed that the image resolution obtained with stationary MPH is significantly better than Siemens Symbia T16, the image quality is also greatly improved compared to rotational LEHR SPECT. Meanwhile, the short acquisition time of MPH can reduce the possibility of artifacts due to patient movement. So it is potentially capable of dynamic 3D acquisition, and further more clinical trials for evaluating the system performances will be conducted.

A novel technology of multi-pinhole (MPH) SPECT for human myocardial perfusion imaging (MPI) by increasing angular sampling. In this study, the efficiency of MPH SPECT is 0.06%, four-fold higher than Dual-detector LEHR SPECT (typically 0.015%), we acquired projection data of patient MPI for rest and exercise with 12-pinhole collimator and Siemens Symbia T16. There are two cases for MPH SPECT scan in V mode: one view from -170°of main turning device, two views from -170°and -135°. Acquisition time of MPH SPECT was 5 minutes for single and dual angles, and the acquisition of Siemens was 15 minutes. MPH calibration is essential to generate system transfer matrix, which will be employed to iterative reconstruction. Projection data were reconstructed with a Pixel-based Ordered Subset-expectation Maximization (POSEM) reconstruction algorithm. Reconstructed results showed that dual-angle imaging results have better uniformity than single-angle imaging, and MPH SPECT has higher spatial resolution than Siemens Symbia T16 with reduced acquisition time. The short acquisition time of MPH can increase SPECT throughput and reduces the possibility of artifacts due to patient movement. More clinical trial for MPH dual angular sampling performance evaluation will be carried out.

This study studies are error registration algorithm for the maneuvering radar network, which is one of the difficult problems of multi-sensor registration. Wh en the maneuvering radar has no orientation bias, measurement equations of both attitude bias and mea surement bias can be established by using the commo n targets observed by different radars. Based on the equations, the real-time estimation of both attitud e bias and measurement bias can be obtained with the twofold unscented Kalman filter. The results show that t he method has a fast convergence rate. When the distan ce of the sensors is very long, both the absolute registration and the relative registration of attit ude bias and measurement bias can be implemented.

Aiming to solve the track refined tracking problem of the formation targets with the multi-sensor detections, intensive analysis on target echo characteristics of the formation targets, the centralized multi-sensor particle filter algorithm of formation targets are advanced. The algorithm set up a shape vector, which can represent the graph of each target in formation using shape and azimuth descriptor, then based on the measurement set to fall within the formation each target door of the waves, that associated to all graphics within each target formation might be associated measurement configuration for the object, through establish similarity model through space and shape similarity measurement step with the target state prediction value distance, at the same time, using the idea of selecting the master station to remove redundant images. Finally, achieve each formation target status updating, which based on particle filter using measurement set and the corresponding weight set. The analysis results of the simulation data show, this algorithm has obvious advantages in tracking accuracy, real-time performance and effective tracking rate three aspects, which can meet the engineering requirement of the track refined tracking of the formation targets with multi-sensor detections very well, is better than the algorithm based on data compression centralized multi-sensor multi-algorithm hypothesis which has superior performance in the traditional multi-sensor multi-target tracking algorithm.

Phase lock to an SRF cavity by using injection signal through output waveguide of a magnetron has been demonstrated [1, 3]. Amplitude control using magnetic field trimming and anode voltage modulation has been studied using MATLAB/Simulink simulations [2]. Based on these, we are planning to use an FPGA based digital LLRF system, which allows applying various types of control algorithms in order to achieve the required accelerating field stability. Since the 1497 MHz magnetron is still in the design stage, the proof of principle measurements of a commercial 2450 MHz magnetron are carried out to characterize the anode I-V curve, output power (the tube electronic efficiency), frequency dependence on the anode current (frequency pushing) and the Rieke diagram (frequency pulling by the reactive load). Based on early Simulink simulation, experimental data and extension of the Adler equation governing injection phase stability by Chen's model, the specification of the new LLRF control chassis for both 2450 and 1497MHz systems are presented in this paper., Proceedings of the 7th Int. Particle Accelerator Conf., IPAC2016, Busan, Korea

This paper discusses an application of the IPM (inverse perspective mapping) geometrical transform on the inspection power robot (SmartGuard). The SmartGuard is an autonomous robotic system for inspection substation equipment instead of people. Based on the stereo vision system, we proposed a Vision base road edge and obstacle detection system. Firstly, we construct the IPM( Inverse perspective mapping) structure from the vision system structure and the road plane in the substation. Secondly, make the monocular image transform of IPM, and get the edge of the road based on the line detection. Thirdly, do the stereo images IPM, based the transformed images, detect the different of the stereo remapping images to get the probable obstacle. Continues, we give a hypothesis testing obstacle detection approach to make the obstacle information more exactly. At last, we make the 2D map both the road edge and obstacle which could provide enough information for the robot navigation in the substation.

Aimed at the deficiency of the magnetic guide and RFID parking system used by substation inspection robot now, a laser navigation method is introduced, and a prototype laser navigation system is designed based on NAV200. The whole structure of the navigation system is presented; the data processing and navigation control algorithm are also described in detail. In order to verify the repetitive precision of the system, an experimental test has been carried out in a 500KV outdoor substation. Experimental results show that the laser navigation system works well, and the repetitive precision of navigation control is precise enough to help the robot fulfill inspection tasks.

To investigate the effect of nicorandil on the chronic air embolism-induced pulmonary hypertension and pulmonary vascular remodeling in rabbits. A total of 36 rabbits were randomly divided into control group, air embolic group, and air embolic + nicorandil treated group with 12 rabbits 0f each

Access to affordable essential medicines for noncommunicable, chronic diseases is critical in management of the diseases. This study aims to assess the availability, prices, and affordability of medicines for common chronic diseases in the Asia Pacific Region (APR). A secondary analysis of medicines price and availability data from the Health Action International’s (HAI) database was undertaken using the standardized WHO/HAI methodology. The median availability of any medicine in the public sector was 35.5% compared with 56.7% in the private sector. Countries paid 1.4 times the International Reference Price to procure lowest-priced generics (LPGs) and 9.1 times for innovator brands (IBs). Patients would have to spend 2.3 and 0.4 day’s wages to purchase one month’s treatment of a chronic disease for IBs and LPGs, respectively in the private sector. These findings highlight the need to increase availability, reduce prices, and improve affordability of the medicines. Refereed/Peer-reviewed

Background Little is known about the prices and availability of medicines for chronic diseases used by older people in the Asia Pacific Region. The objective of this study was to assess the availability and prices of essential medicines for chronic diseases in 11 countries, namely China, Fiji, India, Indonesia, Lao, Malaysia, Mongolia, the Philippines, Sri Lanka, Thailand and Vietnam. The study was carried out at an international level.