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Bonded NdFeB is a high performance composite magnetic materials which developed in recent years. Compression molding is the most important making method of bonded NdFeB magnets. The Characteristics of bonded NdFeB magnets are introduced. Based on test, research and lot production practice, the important effects of mould structure, press structure and compression molding actions on magnets’ quality are analyzed, The key techniques that controlling the quality of bonded NdFeB magnets are summarized.

A comparative analysis of the combination of flotation-magnetic -gravity separation with bulk-floatation process for recovering fine tin slime was carried out in a mineral processing plant. Compared to the bulk floatation process, the flotation-magnetic-gravity separation process resulted in a higher recovery of tin and showed advantages of small consumption of reagents and electric power, stable production index and easy operation.

The manufacture technology and mould structure of bonded NdFeB arc-magnets from press molding were described. The effects of the content of binder and additives, particle size of magnetic powder, the molding pressure, the treatment of magnet surface on the mechanical property, processing property, magnetic property and anti-oxidation property of press molding magnets were investigated. The press molding bonded magnets were prepared by using the MQP-B rapidly quenching NdFeB magnetic powder and epoxy binder. The magnetic properties are: Br = 0.722 T, Hcb = 457 kA/m, Hci = 718 kA/m, and (BH) max = 83.5 kJ/m3.

Sequence stratigraphic features of the Jurassic succession in Central Junggar Basin were investigated by integrating multiple materials including cores, well and seismic data. Due to their unique formation mechanism, sequences of the target interval were analyzed with a binary systems tract mode (each complete sequence contains a transgressive systems tract and a highstand systems tract) rather than the traditional one. Basic principles and analytical methods of high-resolution sequence stratigraphy were also applied to this research. By adopting cyclic correlation and hierarchical control techniques, eight sequences (Sq1-Sq8) were identified in the target interval. Especially, coal seams are of great significance in the sequence identification and they were considered to be closely relevant to maximum flooding surfaces (mfs).

P/M main bearing caps are important structure parts in automotive engines. They have special shape and high precision and endure complicated load in using. After analysis the structure and property characteristics, we use Fe-C-Cu-Ni material, double-action-floating-pressing technology, liquid-phase sintering technology to develop the P/M bearing caps. After a series of test, inspection and loading test, we defined the manufacture technology of bearing caps and realized mass production.

A nondestructive measurement approach is presented in this paper, which is capable of determining sugar content in cantaloupe from the dielectric property. The approach is based on measured equivalent capacitance and equivalent resistance of the cantaloupe, and on data analysis using quantum-behaved particle swarm optimization (QPSO) and Grey radial basis function (RBF) neural network. First, accumulated generating operation (AGO) in Grey forecasting is used to convert the initial observed data to obtain the accumulated data with strong regularity, which are employed to model and train the radial basis function neural network. Second, it adopted quantum-behaved particle swarm optimization algorithm to train the centers and widths of radial basis function. This model not only prevented the problem that the parameters of neural network are hard to be tuned, but also improved the network precision of prediction. Experimental results revealed that the predictive model as proposed has good predictive effect for the measurement of sugar in cantaloupes.

The stearate surface modified LDHs S-NiMgAl-Y was rapidly synthesized based on the coprecipitation coupled with the microwave hydrothermal treatment. The cone calorimeter data confirmed that composite S-NiMgAl-Y/EVA has the good functions of both the flame retardancy and smoke/toxic gas suppression. The tensile strength of S-NiMgAl-Y/EVA was increased to the maximum value of 25.6 MPa when the addition of 10 wt.% S-NiMgAl-Y to EVA. This value is markedly larger than that of the pristine EVA equaling 20.8 MPa. The composite material developed in the present work greatly contributes to the processing and application of the fire retardant material.

The injection molding of magnetic powder could cost-effectively mass-produce net shape magnets. The manufacture technology and properties testing method of composite powder and bonded NdFeB magnets from injection molding were described in detail. The effects of content of binder, additives and magnetic powder on the magnetic property, mechanical property and fluidity of injection molding magnets were investigated. Furthermore, the effect mechanism was revealed microcosmically. The injection molding bonded magnets were prepared by using the MQP-B rapidly quenching NdFeB magnetic powder and polyamide 12. The magnetic properties are: Br=0.539T, Hcb=345.37kA/m, Hci=681.02kA/m, and (BH)max=47.37kJ/m3.

The injection molding of magnetic powder could cost-effectively mass-produce net shape magnets. In order to prepare the injection molding bonded NdFeB permanent magnet material with better combined properties, the effect of binder on the magnetic property, mechanical property and fluidity of injection molding magnets and its mechanism microcosmically were investigated. The effect of additives such as silicone coupling agent, compound lubricants and antioxidant on the properties of injection molding magnets are discussed. The injection molding bonded magnets were prepared by using the MQP-B rapidly quenching NdFeB magnetic powder and polyamide 12. The magnetic properties are :Br=0.539T, Hcb=345.37kA/m, Hci=681.02kA/m, and (BH)max=47.37kJ/m3.

Vehicle segmentation is the key of the traffic video image analysis, the movement state of vehicles can be understudied to get traffic flow parameters. Based on the traffic scene characterized by gradual change, the paper present the background model reconstruction with time-space and self-similarity of background. Video frame image is differenced from background, and binary to get the vehicle template. According to the template, movement vehicle will be segmented from it, the results of the experiment confirmed the effectiveness of algorithm.

Queue length behind the stop line is an important parameter in the model of intersection signal control which is the base of urban traffic control. In this paper, the detection algorithms of queue length by the image information are proposed. At first, the background differential is used to extract the vehicle after the stop line, and then the three regional of the left, straight and right are identified, and finally at the different regions, tail of the vehicles queue is detected based on the change of image sequences gray, so the queue length is measured. The experimental results confirmed the effectiveness of the algorithm.