Uncertainty sampling for action recognition via maximizing expected average precision

© 2018 International Joint Conferences on Artificial Intelligence. All right reserved. Recognizing human actions in video clips has been an important topic in computer vision. Sufficient labeled data is one of the prerequisites for the good performance of action recognition algorithms. However, while abundant videos can be collected from the Internet, categorizing each video clip is time-consuming. Active learning is one way to alleviate the labeling labor by allowing the classifier to choose the most informative unlabeled instances for manual annotation. Among various active learning algorithms, uncertainty sampling is arguably the most widely-used strategy. Conventional uncertainty sampling strategies such as entropy-based methods are usually tested under accuracy. However, in action recognition Average Precision (AP) is an acknowledged evaluation metric, which is somehow ignored in the active learning community. It is defined as the area under the precision-recall curve. In this paper, we propose a novel uncertainty sampling algorithm for action recognition using expected AP. We conduct experiments on three real-world action recognition datasets and show that our algorithm outperforms other uncertainty-based active learning algorithms

A model for ranking sentence pairs in parallel corpora

In this paper, the problem of ranking sentence pairs in parallel corpora was addressed for the first time. To solve this problem, a novel model was proposed. In this model, both syntax features and semantics features of sentence pairs are considered. Since most today's Statistical Machine Translation models depend on word alignment, features related to word alignment information are also included. Two experiments were carried out and the results showed that the model had promising performance

Applications of multi-walled carbon nanotube in electronic packaging

Thermal management of integrated circuit chip is an increasing important challenge faced today. Heat dissipation of the chip is generally achieved through the die attach material and solders. With the temperature gradients in these materials, high thermo-mechanical stress will be developed in them, and thus they must also be mechanically strong so as to provide a good mechanical support to the chip. The use of multi-walled carbon nanotube to enhance the thermal conductivity, and the mechanical strength of die attach epoxy and Pb-free solder is demonstrated in this work

Controlled Growth of Carbon Spheres Through the Mg-Reduction Route

Hollow spheres, hollow capsules and solid spheres of carbon were selectively synthesized by Mg-reduction of hexachlorobutadiene at appropriate reaction conditions. X-ray powder diffraction and Raman spectra reveal that the as-prepared materials have a well-ordered structure. A possible formation mechanism has been proposed

Differentiation potential of STRO-1+ dental pulp stem cells changes during cell passaging

<p>Abstract</p> <p>Background</p> <p>Dental pulp stem cells (DPSCs) can be driven into odontoblast, osteoblast, and chondrocyte lineages in different inductive media. However, the differentiation potential of naive DPSCs after serial passaging in the routine culture system has not been fully elucidated.</p> <p>Results</p> <p>DPSCs were isolated from human/rat dental pulps by the magnetic activated cell sorting based on STRO-1 expression, cultured and passaged in the conventional culture media. The biological features of STRO-1⁺DPSCs at the 1^stand 9^thpassages were investigated. During the long-term passage, the proliferation ability of human STRO-1⁺DPSCs was downregulated as indicated by the growth kinetics. When compared with STRO-1⁺DPSCs at the 1^stpassage (DPSC-P1), the expression of mature osteoblast-specific genes/proteins (alkaline phosphatase, bone sialoprotein, osterix, and osteopontin), odontoblast-specific gene/protein (dentin sialophosphoprotein and dentin sialoprotein), and chondrocyte-specific gene/protein (type II collagen) was significantly upregulated in human STRO-1⁺DPSCs at the 9^thpassage (DPSC-P9). Furthermore, human DPSC-P9 cells in the mineralization-inducing media presented higher levels of alkaline phosphatase at day 3 and day 7 respectively, and produced more mineralized matrix than DPSC-P9 cells at day 14. <it>In vivo </it>transplantation results showed that rat DPSC-P1 cell pellets developed into dentin, bone and cartilage structures respectively, while DPSC-P9 cells can only generate bone tissues.</p> <p>Conclusions</p> <p>These findings suggest that STRO-1⁺DPSCs consist of several interrelated subpopulations which can spontaneously differentiate into odontoblasts, osteoblasts, and chondrocytes. The differentiation capacity of these DPSCs changes during cell passaging, and DPSCs at the 9^thpassage restrict their differentiation potential to the osteoblast lineage <it>in vivo</it>.</p

A New Era in the Quest for Dark Matter

There is a growing sense of `crisis' in the dark matter community, due to the absence of evidence for the most popular candidates such as weakly interacting massive particles, axions, and sterile neutrinos, despite the enormous effort that has gone into searching for these particles. Here, we discuss what we have learned about the nature of dark matter from past experiments, and the implications for planned dark matter searches in the next decade. We argue that diversifying the experimental effort, incorporating astronomical surveys and gravitational wave observations, is our best hope to make progress on the dark matter problem.Comment: Published in Nature, online on 04 Oct 2018. 13 pages, 1 figur

Improved ground-state modulation characteristics in 1.3 μm InAs/GaAs quantum dot lasers by rapid thermal annealing

We investigated the ground-state (GS) modulation characteristics of 1.3 μm InAs/GaAs quantum dot (QD) lasers that consist of either as-grown or annealed QDs. The choice of annealing conditions was determined from our recently reported results. With reference to the as-grown QD lasers, one obtains approximately 18% improvement in the modulation bandwidth from the annealed QD lasers. In addition, the modulation efficiency of the annealed QD lasers improves by approximately 45% as compared to the as-grown ones. The observed improvements are due to (1) the removal of defects which act as nonradiative recombination centers in the QD structure and (2) the reduction in the Auger-related recombination processes upon annealing

Application of amino acid occurrence for discriminating different folding types of globular proteins

<p>Abstract</p> <p>Background</p> <p>Predicting the three-dimensional structure of a protein from its amino acid sequence is a long-standing goal in computational/molecular biology. The discrimination of different structural classes and folding types are intermediate steps in protein structure prediction.</p> <p>Results</p> <p>In this work, we have proposed a method based on linear discriminant analysis (LDA) for discriminating 30 different folding types of globular proteins using amino acid occurrence. Our method was tested with a non-redundant set of 1612 proteins and it discriminated them with the accuracy of 38%, which is comparable to or better than other methods in the literature. A web server has been developed for discriminating the folding type of a query protein from its amino acid sequence and it is available at http://granular.com/PROLDA/.</p> <p>Conclusion</p> <p>Amino acid occurrence has been successfully used to discriminate different folding types of globular proteins. The discrimination accuracy obtained with amino acid occurrence is better than that obtained with amino acid composition and/or amino acid properties. In addition, the method is very fast to obtain the results.</p

'Unite and conquer': enhanced prediction of protein subcellular localization by integrating multiple specialized tools

<p>Abstract</p> <p>Background</p> <p>Knowing the subcellular location of proteins provides clues to their function as well as the interconnectivity of biological processes. Dozens of tools are available for predicting protein location in the eukaryotic cell. Each tool performs well on certain data sets, but their predictions often disagree for a given protein. Since the individual tools each have particular strengths, we set out to integrate them in a way that optimally exploits their potential. The method we present here is applicable to various subcellular locations, but tailored for predicting whether or not a protein is localized in mitochondria. Knowledge of the mitochondrial proteome is relevant to understanding the role of this organelle in global cellular processes.</p> <p>Results</p> <p>In order to develop a method for enhanced prediction of subcellular localization, we integrated the outputs of available localization prediction tools by several strategies, and tested the performance of each strategy with known mitochondrial proteins. The accuracy obtained (up to 92%) surpasses by far the individual tools. The method of integration proved crucial to the performance. For the prediction of mitochondrion-located proteins, integration via a two-layer decision tree clearly outperforms simpler methods, as it allows emphasis of biologically relevant features such as the mitochondrial targeting peptide and transmembrane domains.</p> <p>Conclusion</p> <p>We developed an approach that enhances the prediction accuracy of mitochondrial proteins by uniting the strength of specialized tools. The combination of machine-learning based integration with biological expert knowledge leads to improved performance. This approach also alleviates the conundrum of how to choose between conflicting predictions. Our approach is easy to implement, and applicable to predicting subcellular locations other than mitochondria, as well as other biological features. For a trial of our approach, we provide a webservice for mitochondrial protein prediction (named YimLOC), which can be accessed through the AnaBench suite at http://anabench.bcm.umontreal.ca/anabench/. The source code is provided in the Additional File <supplr sid="S2">2</supplr>.</p> <suppl id="S2"> <title> <p>Additional file 2</p> </title> <text> <p>This file contains scripts for the online server YimLOC. Please note that there scripts only codes for the ready-to-use STACK-mem-DT described in the main text. The scripts do not provide the training process.</p> </text> <file name="1471-2105-8-420-S2.pdf"> <p>Click here for file</p> </file> </suppl