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A mobile molecular Doppler wind lidar (DWL) based on double-edge technique is presented for wind measurement at altitudes from 10km to 40km. A triple Fabry-Perot etalon is employed as a frequency discriminator to determine the Doppler shift proportional to the wind velocity. The lidar operates at 355 nm with a 45-cm aperture telescope and a matching azimuth-over-elevation scanner that can provide full hemispherical pointing. In order to guarantee the wind accuracy, different forms of calibration function of detectors in different count rates response range would be especially valuable. The accuracy of wind velocity iteration is improved greatly because of application of the calibration function of linearity at the ultra low light intensity especially at altitudes from 10km to 40km. The calibration functions of nonlinearity make the transmission of edge channel 1 and edge channel 2 increase 38.9% and 27.7% at about 1 M count rates, respectively. The dynamic range of wind field measurement may also be extended because of consideration of the response function of detectors in their all possible operating range.

Zheng Li, Yongtao Wang. Finite Element Analysis and Structural Optimization of a Permanent Magnet Spherical Actuator // Electronics and Electrical Engineering. -Kaunas: Technologija, 2011. -No. 8(114). -P. 67-72.In order to derive the characteristics and adjust the electromagnetic system to the ultimate purpose of achieving better torque output and material usage reduction with constraints, this paper presents the finite element analysis and using improved niche genetic algorithm to the optimal design of a permanent magnet spherical actuator. The magnetic field distribution and torque calculation model based on finite element software are introduced and discussed. The proposed optimization algorithm surmounts effectively the local convergence problem of standard genetic algorithm. The sharing-between-population mechanism is proposed by means of using the better factor of population, saving best result strategy and enhancing global and partial searching ability for earlier achievement of optimal solution. The results show the output torque has been increased and the material has been effectively saved by comparison, which provides the references for related problems. Ill. 5, bibl. 15, tabl. 6 (in English; abstracts in English and Lithuanian). Zheng Li, Yongtao Wang. Sferinės pavaros su nuolatiniu magnetu struktūros optimizavimas ir baigtinių elementų tyrimas // Elektronika ir elektrotechnika. -Kaunas: Technologija, 2011. -Nr. 8(114). -P. 67-72.Siekiant padidinti elektromagnetinių sistemų sukimo momentą atliktas baigtinių elementų tyrimas ir sferinės pavaros su nuolatiniu magnetu struktūros optimizavimas taikant genetinį algoritmą. Sudarytas modelis, skirtas magnetinio lauko pasiskirstymo įvertinimui ir sukimo momento apskaičiavimui taikant baigtinių elementų metodą. Nustatyta, kad sukimo momentas padidėjo. Il. 5, bibl. 15, lent. 6 (anglų kalba; santraukos anglų ir lietuvių k.).

State-of-the-art hand gesture recognition methods have investigated the spatiotemporal features based on 3D convolutional neural networks (3DCNNs) or convolutional long short-term memory (ConvLSTM). However, they often suffer from the inefficiency due to the high computational complexity of their network structures. In this paper, we focus instead on the 1D convolutional neural networks and propose a simple and efficient architectural unit, Multi-Kernel Temporal Block (MKTB), that models the multi-scale temporal responses by explicitly applying different temporal kernels. Then, we present a Global Refinement Block (GRB), which is an attention module for shaping the global temporal features based on the cross-channel similarity. By incorporating the MKTB and GRB, our architecture can effectively explore the spatiotemporal features within tolerable computational cost. Extensive experiments conducted on public datasets demonstrate that our proposed model achieves the state-of-the-art with higher efficiency. Moreover, the proposed MKTB and GRB are plug-and-play modules and the experiments on other tasks, like video understanding and video-based person re-identification, also display their good performance in efficiency and capability of generalization.

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