Bayesian Hierarchical Models for Measuring Varietal Improvement in Tobacco Yield and Quality

We measure the economic impact of varietal improvement and technological change in flue-cured tobacco across quantity (e.g., yield) and quality dimensions under a voluntary quality constraint. Since 1961, flue-cured tobacco breeders in the United States have been subject to the Minimum Standards Program that sets limits on acceptable quality characteristics for commercial tobacco varieties. We implement a Bayesian hierarchical model to measure the contribution of breeding efforts to changes in tobacco yields and quality between 1954 and 2017. The Bayesian model addresses limited data for varieties in the trials and allows easy generation of the necessary parameters of economic interest.

Topological Design of a Mortar Base Plate under Impact Loads

In this work, the topology optimization of a mortar base plate is analysed under impact loading conditions. Usually, in this case, only ordinary topology optimization under volume constraints is considered. However, to reduce the quality of the mortar base plate and facilitate engineering applications, the topological optimization problem of the continuum of the base plate under the engineering and quality constraint is considered. A finite element model has been established and verified by testing for the mortar base plate. The variable density method was used to obtain the topological optimization results of the base plate based on the force transmission path, and then the structure was reconstructed. The mass of the optimization model of the base plate is 12.78% lower than that of the original model. In comparison with the original base plate before optimization, the results show that the maximum deformation and stress of the base plate decreased by 16.85% and 35.52%, respectively. Also, the firing stability of the mortar meets requirements, which not only meet the design requirement but also provide a reference for the performance improvement and structural optimization design of the base plate.

Video coding and constant quality evaluation using 4k aomenc-AV1 and rav1e-AV1 formats

It is much expected from the relatively novel, open, royalty-free AV1 (Alliance for Open Media (AOMedia) Video 1) standard. At this moment, there are many new variants of AV1 format. It is designed for efficient video internet delivery and high-quality video transmission. AV1 is recognized as Google?s VP9 format successor. One of the reference tools used so far for testing AV1 is libaom- AV1. Nevertheless, due to its time-consuming performance, there are now different available standalone solutions for experimental analysis. Here, one such solution AOMedia?s standalone aomenc (aomenc-AV1) is tested in order to analyze quality assessment based on constant quality constraint factor. Three different metrics are calculated for various 4k video content of the same frame rate. Moreover, rav1e implementation was tested for the same visual data, where rav1e-AV1 also represents an AV1 video encoder, which is considered reliable and suitable in most cases, where libaom is not applicable. In this paper, the comparison results between aomenc-AV1 and rav1e-AV1 are shown.

Key Frame Extraction of Multi-Resolution Remote Sensing Images Under Quality Constraint

In key frame extraction of multi-resolution remote sensing image using traditional key frame image feature extraction method, only the feature information of remote sensing images, rather than cluster operation of the remote sensing images is considered, which leads to low efficiency and poor quality of extraction results. To this end, the key frame extraction algorithm of multi-resolution remote sensing image under quality constraint was proposed. Through similarity between image features and the selected image frame, rough key frame can be extracted. On this basis, the key frame extraction of multi resolution remote sensing image based on quality constraints was used to perform clustering operation for multi-resolution remote sensing image corresponding to rough key frame, which shortened the time length for retrieval of key frame image. According to the clustering results, multi-resolution remote sensing images were divided into several clusters. The key frame of each cluster can be obtained by calculating the distance between remote sensing image and cluster center. For key frames that had been determined, their quality was evaluated to meet standard, so as to realize effective extraction of key frame of multi-resolution remote sensing images. The experimental results show that the proposed method can significantly improve the quality of key frame extraction of multi-resolution remote sensing images.