Fast Low-rank Representation based Spatial Pyramid Matching for Image Classification

Spatial Pyramid Matching (SPM) and its variants have achieved a lot of success in image classification. The main difference among them is their encoding schemes. For example, ScSPM incorporates Sparse Code (SC) instead of Vector Quantization (VQ) into the framework of SPM. Although the methods achieve a higher recognition rate than the traditional SPM, they consume more time to encode the local descriptors extracted from the image. In this paper, we propose using Low Rank Representation (LRR) to encode the descriptors under the framework of SPM. Different from SC, LRR considers the group effect among data points instead of sparsity. Benefiting from this property, the proposed method (i.e., LrrSPM) can offer a better performance. To further improve the generalizability and robustness, we reformulate the rank-minimization problem as a truncated projection problem. Extensive experimental studies show that LrrSPM is more efficient than its counterparts (e.g., ScSPM) while achieving competitive recognition rates on nine image data sets.Comment: accepted into knowledge based systems, 201

A Data Driven Method for Multi-step Prediction of Ship Roll Motion in High Sea States

Ship roll motion in high sea states has large amplitudes and nonlinear dynamics, and its prediction is significant for operability, safety, and survivability. This paper presents a novel data-driven methodology to provide a multi-step prediction of ship roll motions in high sea states. A hybrid neural network is proposed that combines long short-term memory (LSTM) and convolutional neural network (CNN) in parallel. The motivation is to extract the nonlinear dynamic characteristics and the hydrodynamic memory information through the advantage of CNN and LSTM, respectively. For the feature selection, the time histories of motion states and wave heights are selected to involve sufficient information. Taken a scaled KCS as the study object, the ship motions in sea state 7 irregular long-crested waves are simulated and used for the validation. The results show that at least one period of roll motion can be accurately predicted. Compared with the single LSTM and CNN methods, the proposed method has better performance in predicting the amplitude of roll angles. Besides, the comparison results also demonstrate that selecting motion states and wave heights as feature space improves the prediction accuracy, verifying the effectiveness of the proposed method

Challenges and Countermeasures of Teachers’ Professional Development from the Perspective of Globalization

Under the influence of globalization, the intensification of international competition is in the final analysis the competition of education and talents. Teachers are the main body of teaching activities. Teachers’ professionalization is an important symbol to measure a country’s educational level. At present, the professional development of teachers in China is facing enormous challenges. In terms of concept, system and the allocation and utilization of educational resources, there are great problems. In order to meet the needs of teachers’ professional development in the perspective of globalization, the new era should promote the upgrading of teachers’ professional level from the aspects of renewal of ideas, improvement of system guarantee system, diversified development and integration and distribution of resources

Dynamic Lidar Ratio Calculation and Aerosol Vertical Extinction Coefficient Retrieval Based on Observed Visibility

Micropulse lidar (MPL) cannot directly retrieve the aerosol extinction coefficient under cloudy conditions and at night. Therefore, we used ground visibility, Fernald’s near-end solution method, and the linear correlation between the near-end lidar signal (photons) and ground aerosol extinction coefficient (correlation coefficient = 0.98), to calculate the lidar constant and lidar ratio (LR). We compared the aerosol optical depth (AOD) retrieved from MPL and the AOD retrieved from the multifilter rotating shadowband radiometer (MFRSR-7) at the same band (532 nm). The correlation coefficient was 0.77. The vertical distribution of aerosols in daytime and nighttime during summer was obtained from lidar in July at 00:00 and 12:00 Beijing time (UTC+8). In daytime, under clear sky conditions, the distribution displayed a unimodal and peak at approximately 2000 m. The distribution at night was more complicated than that in the day, with three results. The first was monotonically decreasing from ground to upper layer, with a peak at 600 m and two peaks at approximately 1200 m. In general, the aerosol extinction coefficient at nighttime is higher than that at daytime below 1200 m. The near-ground extinction coefficient at night is higher than in the day

A stochastic imperfection simulation method from high-fidelity measurements on cold-formed steel studs

This paper presents a stochastic imperfection simulation method towards cold-formed steel (CFS) studs, the data of which is generated from a high-thruput laser measurement device. An accurate hand-held laser scanner is applied to investigate about 19 types of CFS studs that widely used in current Chinese markets. point cloud models of which are reconstructed. A developed imperfection pattern recognition algorithm efficiently processes the high-fidelity point cloud models and automatically characterizes the imperfections based on the local, distortional, and global buckling modes. The measured imperfection data is statistically analyzed, where statistical models and inter-correlation models of mode imperfections are carefully obtained thereafter. The inter-correlation matrices and statistical models are parametrized for stochastic analysis. A data-driven stochastic imperfection simulation method thus is proposed based on the as-real correlation parameters and statistical data. The generated imperfection models are compared with the measured imperfections to validate the proposed simulation method. The investigation provides consolidated data foundations for the imperfection sensitivity analysis. The evaluation of CFS studs’ reliability can be insightfully conducted; thus, the imperfection design in the general specification is advised. The proposed imperfection simulation method based on inter-correlation parameters and as-measured statistical models also contributes to the development of trending simulation-based design of cold-formed steel structures.This work was financially supported by Quota Project for Promoting the Connotation Development of Colleges and Universities - Young Scholars of Beijing Talent Project (02082721010), Basic Research Funds for Municipal Universities (X21062). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author (s) and do not necessarily reflect the views of the sponsors or other participants