Development of a doorframe-typed swinging seedling pick-up device for automatic field transplantation

A doorframe-typed swing seedling pick-up device for automatic field transplanters was developed and evaluated in a laboratory. The device, consisting of a path manipulator and two grippers, can move the pins slowly to extract seedlings from the tray cells and return quickly to the pick-up point for the next extraction. The path manipulator was constructed with the creative design of type-Ⅱ mechanism combination in series. It consists of an oscillating guide linkage mechanism and a grooved globoidal cam mechanism. The gripper is a pincette-type mechanism using the pick-up pins to penetrate into the root mass for seedling extraction. The dynamic analysis of the designed seedling pick-up device was simulated with ADAMS software. Being the first prototype, various performance tests under local production conditions were conducted to find out the optimal machine operation parameters and transplant production conditions. As the gripper with multiple fine pins was moved by the swing pick-up device, it can effectively complete the transplanting work cycle of extracting, transferring, and discharging a seedling. The laboratory evaluation showed that the pick-up device equipped with two grippers can extract 80 seedlings/min with a 90% success and a 3% failure in discharging seedlings, using 42-day-old tomato plantlets. The quality of extracting seedlings was satisfactory

Learning Competitive and Discriminative Reconstructions for Anomaly Detection

Most of the existing methods for anomaly detection use only positive data to learn the data distribution, thus they usually need a pre-defined threshold at the detection stage to determine whether a test instance is an outlier. Unfortunately, a good threshold is vital for the performance and it is really hard to find an optimal one. In this paper, we take the discriminative information implied in unlabeled data into consideration and propose a new method for anomaly detection that can learn the labels of unlabelled data directly. Our proposed method has an end-to-end architecture with one encoder and two decoders that are trained to model inliers and outliers' data distributions in a competitive way. This architecture works in a discriminative manner without suffering from overfitting, and the training algorithm of our model is adopted from SGD, thus it is efficient and scalable even for large-scale datasets. Empirical studies on 7 datasets including KDD99, MNIST, Caltech-256, and ImageNet etc. show that our model outperforms the state-of-the-art methods.Comment: 8 page

Amphibian Species Contribute Similarly to Taxonomic, but not Functional and Phylogenetic Diversity: Inferences from Amphibian Biodiversity on Emei Mountain

Understanding the relationships between species, communities, and biodiversity are important challenges in conservation ecology. Current biodiversity conservation activities usually focus on species that are rare, endemic, distinctive, or at risk of extinction. However, empirical studies of whether such species contribute more to aspects of biodiversity than common species are still relatively rare. The aim of the present study was to assess the contribution of individual amphibian species to different facets of biodiversity, and to test whether species of conservation interest contribute more to taxonomic, functional, and phylogenetic diversity than do species without special conservation status. To answer these questions, 19 000 simulated random communities with a gradient of species richness were created by shuffling the regional pool of species inhabiting Emei Mountain. Differences of diversity values were then computed before and after removing individual species in these random communities. Our results indicated that although individual species contributed similarly to taxonomic diversity, their contribution to functional and phylogenetic diversity was more idiosyncratic. This was primarily driven by the diverse functional attributes of species and the differences in phylogenetic relationships among species. Additionally, species of conservation interest did not show a significantly higher contribution to any facet of biodiversity. Our results support the claims that the usefulness of metrics based only on species richness is limited. Instead, assemblages that include species with functional and phylogenetic diversity should be protected to maintain biodiversity