The Development and Application of 2BDQ-8 Rice Direct Sowing Machine

[Objective] The aim was to introduce the development and application of 2BDQ-8 rice direct sowing machine and provide a theoretical basis for rice mechanization production. [Method] 2BDQ-8 rice direct sowing machine was used for the promotion test in field of several cities and counties in Jiangsu Province,and artificial rice planting and mechanization rice planting were compared to explore the production and economic situation. [Result] 2BDQ-8 rice direct sowing machine had advantages such as high efficiency and low cost,the rice direct sowing machine saved about 30% compared to the artificial rice planting and mechanization rice planting,and the overall efficiency was significant. [Conclusion] 2BDQ-8 rice sowing machine was a production technology that had low cost and high efficiency,which should be widely applied.

Experimental Study on Working Performance of Rice Rope Direct Seeding Machine

Structure and sowing principles of rice rope direct seeding machine are introduced. In order to test the machine＇ s working performance, such as compacting effect, sowing depth, influence of sowing device to rice rope, etc., field experiments were conducted. It is concluded that mean slip ratio of compacting wheel 1 is 4.44%, wheel 2 is 5.58%, wheel 3 is 7.81%, and wheel 4 is 6.96%; mean depth of planting is 29.72 mm, and mean variability coefficient of planting depth is 6.39%. Maximum variability coefficient of planting depth is 8.40%. Rice rope＇s snapping is closely related with the machine＇s speed and guide thread wheel by sowing device orthogonal experiments. Test results show that the machine has a rational design, safe work and meets to the requirements of planting. This study has laid the foundation for further studying the project.

Dosimetric evaluation of CR, 3DCRT and two types of IMRT for breast cancer after conservative surgery

Objective: The purpose of this study was to compare the dose distribution and dose volume histogram (DVH) of the planning target volume (PTV) and organs at risk (OARs) among conventional radiation therapy (CR), three-dimensional conformal radiation therapy (3DCRT), two-step intensity-modulated radiation therapy (TS-IMRT) and direct machine parameter optimization intensity-modulated radiation therapy (DMPO-IMRT) after breast-conserving surgery. Methods: For each of 20 randomly chosen patients, 4 plans were designed using 4 irradiation techniques. The prescribed dose was 50 Gy/2 Gy/25 f, 95% of the planning target volume received this dose. The cumulated DVHs and 3D dose distributions of CR, 3DCRT, TS-IMRT and DMPO-IMRT plans were compared. Results: For the homogeneity indices, no statistically significant difference was observed among CR, 3DCRT, TS-IMRT and DMPO-IMRT while the difference of the conformality indices were statistically significant. With regard to the organs at risk, IMRT and 3DCRT showed a significantly fewer exposure dose to the ipsilateral lung than CR in the high-dose area while in the low-dose area, IMRT demonstrated a significant increase of exposure dose to ipsilateral lung, heart and contralateral breast compared with 3DCRT and CR. In addition, the monitor units (MUs) for DMPO-IMRT were approximately 26% more than those of TS-IMRT and the segments of the former were approximately 24% less than those of the latter. Conclusion: Compared with CR, 3DCRT and IMRT improved the homogeneity and conformity of PTV, reduced the irradiated volume of OARs in high dose area but IMRT increased the irradiated volume of OARs in low dose area. DMPO-IMRT plan has fewer delivery time but more MUs than TS-IMRT.

Surface texture formation in precision machining of direct laser deposited tungsten carbide

This paper focuses on an analysis of the surface texture formed during precision machining of tungsten carbide. The work material was fabricated using direct laser deposition （DLD） technology. The experiment included precision milling of tungsten carbide samples with a monolithic torus cubic boron nitride tool and grinding with diamond and alumina cup wheels. An optical surface profiler was applied to the measurements of surface textures and roughness profiles. In addition, the micro-geometry of the milling cutter was measured with the appli- cation of an optical device. The surface roughness height was also estimated with the application of a model, which included kinematic-geometric parameters and minimum uncut chip thickness. The research revealed the occurrence of micro-grooves on the machined surface. The surface roughness height calculated on the basis of the traditional kinematic-geometric model was incompatible with the measurements. However, better agreement between the theoretical and experimental values was observed for the minimum uncut chip thickness model.

Electromagnetic side-channel attack based on PSO directed acyclic graph SVM

Machine learning has a powerful potential for performing the template attack(TA) of cryptographic device. To improve the accuracy and time consuming of electromagnetic template attack(ETA), a multi-class directed acyclic graph support vector machine(DAGSVM) method is proposed to predict the Hamming weight of the key. The method needs to generate K(K ? 1)/2 binary support vector machine(SVM) classifiers and realizes the K-class prediction using a rooted binary directed acyclic graph(DAG) testing model. Further, particle swarm optimization(PSO) is used for optimal selection of DAGSVM model parameters to improve the performance of DAGSVM. By exploiting the electromagnetic emanations captured while a chip was implementing the RC4 algorithm in software, the computation complexity and performance of several multi-class machine learning methods, such as DAGSVM, one-versus-one(OVO)SVM, one-versus-all(OVA)SVM, Probabilistic neural networks(PNN), K-means clustering and fuzzy neural network(FNN) are investigated. In the same scenario, the highest classification accuracy of Hamming weight for the key reached 100%, 95.33%, 85%, 74%, 49.67% and 38% for DAGSVM, OVOSVM, OVASVM, PNN, K-means and FNN, respectively. The experiment results demonstrate the proposed model performs higher predictive accuracy and faster convergence speed.