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As one of the most advanced non-destructive analytical techniques for nuclear wastes, tomographic Gamma Scanning (TGS) is able to give accurate quantitative and qualitative measurements of nuclear waste barrels. OSEM (Ordered Subsets Expectation Maximization) has been used in transmission TGS image reconstruction on account of its good reconstruction quality and ideal convergence rate. In this paper, an improved method—NMO-OSEM (Non-minimization optimization OSEM) was proposed, it's an iterative algorithm with corrected initial values optimized by non-minimization optimization method. To evaluate its performance, a TGS system is used to perform transmission measurements on barreled nuclear wastes. The results show: ①Compared with the reconstructed images by traditional OSEM under 6 transmission energies (122 keV, 344 keV, 779 keV, 964 keV, 1112 keV, 1408 keV), the improved NMO-OSEM has a great advantage in reducing the artifacts and effectively improving the quality of the reconstructed images. ②the attenuation coefficients values of 72 voxels under 3 emission energies (662 keV, 1173 keV and 1332 keV) reconstructed by the proposed algorithm are more accurate (range of error: 0.22%–13.83%) than reconstructed by traditional OSEM (range of error: 1.31%–32.21%), which proves this method has more stable reconstruction precision and could be regarded as an ideal option for real applications.

To control a multi-joints bipedal robot, it is necessary to choose a proper law of control that ensures the safe and stable motions of the robot. Even for the simplest postures, such as sitting and stand- ing, there are constraints to respect so that the inverse geometric model (MGI) would not have in nitive solutions. In this paper, a particular task of sitting-to-standing is simulated for a bipedal robot using MATLAB. The articulation evolution and the variation of the shoulder position are evaluated using typical control and hierarchical redundant control in which the cases of with and without constraints are both considered. The simulation results show that the hierarchi- cal redundant control has a better effect than the typical one, and when considering the constraints, the articulations' angular velocities vary more smoothly so that the motor is better protected.

For the need of improving the capacity of the geohazards monitoring, a professional monitoring system has been developed based on the Internet of things, WSN (Wireless Sensor Network) and network communication technology. The system consists of wireless sensing network, transmission network and data monitoring and analysis center. The WSN technology was used to organize network with displacement, tilt angle and rainfall in the wireless sensing network which could achieve perception and control all aspects of the monitoring area. The monitoring data can be transferred in two methods by the transmission network which was established based on the GSM and Beidou. The wireless sensing nodes can be controlled remotely by data monitoring and analysis center. For example, the acquisition interval can be modified remotely, the current data can be controlled to return immediately and sensing nodes can be controlled to entry into low power mode in order to save power, which means that Machine to Machine mode of geological disaster monitoring had been realized in the system.

Vast quantities of low-level solid nuclear wastes are produced in the operation and decommissioning of nuclear facilities. These radioactive nuclear wastes are usually contained in special drums. Consequently, these nuclear waste drums must be tested, classified and their levels measured before they are placed in a final repository. There are certain dangers during the detection process; there is an urgent need for a safe, efficient, and autonomous system to inspect these nuclear waste drums. This study describes the methods involved in scanning and measuring the vertical section of radioactive waste drums and describes using the programmable logic controller (PLC-SIEMENS S7-1200) in order to construct an automated system as well as a detection system. According to the waste drum test flow, we designed a control program that utilizes the STEP7 Software as well as a monitoring program using SIEMENS WinCC that is flexible within the computer's central monitoring system. In the future, this system may be applied beyond the scale of a laboratory; nuclear enterprises may be able to adopt this process for sampling checks on contaminated waste. This study ensures the detection efficiency of waste drums as well as the safety of their operators. Furthermore, the proposed system effectively promotes the disposal and management of radioactive waste, which has potential applications in engineering.

A parallel algorithm for terrain generation based on CUDA architecture is proposed in this paper, which aims to address the problems of high computational load and low efficiency when generating large scale terrains using the Perlin noise superposition method. The Perlin noise superposition method is combined with independent calculation of each point based on the characteristics of all adjacent points. The Perlin noise value of each terrain grid point is transferred to a GPU thread for calculation, so that the terrain generation process is executed in completely parallel in the GPU. Experimental results show that The GPU algorithm generates a grid of size 25000000 (25 million grid points) needs only 0.6355 s, while the original CPU algorithm takes 23.3723 s, so, the parallel processing algorithm can improve the efficiency of the terrain generation and meet the requirements for large-scale terrain generation compared with the original algorithm.

Noise is an important factor in image quality of TGS In according to the Neighborhood Homogeneous Measurement (NHM) was proposed to process the salt-pepper noise of TGS image system which avoided the shortcomings of traditional median filtering algorithm and improved median filtering algorithm. A cross noise measurement window was designed in adaptive median filtering algorithm to adjust the domain of image pixel, which divided image pixel into noise and signal point through the calculation results of NHM. The iteration method was introduced to inhibit noise signal. The results showed that adaptive median filtering algorithm could effectively reduce the salt-pepper noise of TGS image system.