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Fog radio access network (Fog-RAN), which pushes the caching and computing capabilities to the network edge, is capable of efficiently delivering contents to users by using carefully designed caching placement and content replacement algorithms. In this paper, the transmission scheme design and coding parameter optimization will be considered for coded caching in Fog-RAN, where the reliability of content delivery, i.e., content outage probability, is used as the performance metric. The problemarXiv:1901.07316v1 fatcat:s33hq4pgi5ewhazh7vdzqoqsu4
more »... ill be formulated as a complicated multi-objective probabilistic combinatorial optimization. A novel maximum b-matching approach will then be proposed to obtain the Pareto optimal solution with fairness constraint. Based on the fast message passing approach, a distributed algorithm with a low memory usage of O(M + N) is also proposed, where M is the number of users and N is the number of Fog-APs. Although it is usually very difficult to derive the closed-form formulas for the optimal solution, the approximation formulas of the content outage probability will also be obtained as a function of coding parameters. The asymptotic optimal coding parameters can then be obtained by defining and deriving the outage exponent region (OER) and diversity-multiplexing region (DMR). Simulation results will illustrate the accuracy of the theoretical derivations, and verify the outage performance of the proposed approach. Therefore, this paper not only proposes a practical distributed Fog-AP selection algorithm for coded caching, but also provides a systematic way to evaluate and optimize the performance of Fog-RANs.
Each grasp configuration is defined as g i = (o, n, r, ω, c 1 , c 2 ), where o = (o x , o y , o z ) represents the origin lies at the middle of the line segment connecting two finger tips, n = (n x , n ...arXiv:2105.08502v1 fatcat:ejwwzbypnrd2za4oc4i7vanpdm
While the anti-tumor actions of ginsenosides from Panax notoginseng are well-studied, the anti-proliferative activity of 20(S)-protopanaxadiol saponins (PDS) in Sanchi ginseng on human ovarian cancer has not been reported, nor has its effect on migration of SKOV3 cells been investigated. In the present study, a wound-healing assay indicated that PDS inhibited the migration of SKOV3 cells, and a Matrigel™ tube formation assay demonstrated the presence of inhibitory tube-structures followingdoi:10.3892/ol.2016.4155 pmid:26998063 pmcid:PMC4774486 fatcat:lul72636graa7bo2ovhlzfbdo4
more »... ment with PDS. To date, there are no previous reports on the regulation of osteopontin (OPN), a glycophosphoprotein cytokine frequently expressed in ovarian carcinoma effusions by PDS. A reduction in the expression of OPN following PDS-treatment was observed using immunohistochemical and western blot experiments. These results suggest that PDS may be useful in the search for a potential ovarian cancer treatment.
Drought stress seriously affects crop growth, development, and grain production. Existing machine learning methods have achieved great progress in drought stress detection and diagnosis. However, such methods are based on a hand-crafted feature extraction process, and the accuracy has much room to improve. In this paper, we propose the use of a deep convolutional neural network (DCNN) to identify and classify maize drought stress. Field drought stress experiments were conducted in 2014. Thedoi:10.3390/sym11020256 fatcat:tihnsb77tba6voxnufovgsogtq
more »... riment was divided into three treatments: optimum moisture, light drought, and moderate drought stress. Maize images were obtained every two hours throughout the whole day by digital cameras. In order to compare the accuracy of DCNN, a comparative experiment was conducted using traditional machine learning on the same dataset. The experimental results demonstrated an impressive performance of the proposed method. For the total dataset, the accuracy of the identification and classification of drought stress was 98.14% and 95.95%, respectively. High accuracy was also achieved on the sub-datasets of the seedling and jointing stages. The identification and classification accuracy levels of the color images were higher than those of the gray images. Furthermore, the comparison experiments on the same dataset demonstrated that DCNN achieved a better performance than the traditional machine learning method (Gradient Boosting Decision Tree GBDT). Overall, our proposed deep learning-based approach is a very promising method for field maize drought identification and classification based on digital images.
GDP-Fuc, Galβ1,3-GlcNAc, Galβ1,3-GalNAc, Galβ1,4-GlcNAc (LacNAc), FKP and EcPpA were prepare previously in in our group Li et al. 2013 Li et al. , 2015 . ...doi:10.1093/glycob/cwv169 pmid:26703456 pmcid:PMC4813730 fatcat:ijevguhwqvc2tavnz5usknmziy
Deep learning (DL) based object detection has achieved great progress. These methods typically assume that large amount of labeled training data is available, and training and test data are drawn from an identical distribution. However, the two assumptions are not always hold in practice. Deep domain adaptive object detection (DDAOD) has emerged as a new learning paradigm to address the above mentioned challenges. This paper aims to review the state-of-the-art progress on deep domain adaptivearXiv:2002.06797v3 fatcat:mozths3lk5djndue6dzefxuq3q
more »... ject detection approaches. Firstly, we introduce briefly the basic concepts of deep domain adaptation. Secondly, the deep domain adaptive detectors are classified into five categories and detailed descriptions of representative methods in each category are provided. Finally, insights for future research trend are presented.
The immunoblots were imaged on an Odyssey ® CLx imaging system (Li-cor, Lincoln, NE) and analyzed with Image Studio Lite. ...pmid:30221032 pmcid:PMC6136846 fatcat:2g56e5o7ona7jn2kkrzdftfrza
Object detection in thermal images is an important computer vision task and has many applications such as unmanned vehicles, robotics, surveillance, and night vision. Deep learning-based detectors have achieved major progress, which usually need large amount of labelled training data. However, labelled data for object detection in thermal images is scarce and expensive to collect. How to take advantage of the large number labelled visible images and adapt them into thermal image domain isdoi:10.1155/2021/1837894 fatcat:24sh7zr5h5gbloz3jpfp3sgozm
more »... ed to solve. This paper proposes an unsupervised image-generation enhanced adaptation method for object detection in thermal images. To reduce the gap between visible domain and thermal domain, the proposed method manages to generate simulated fake thermal images that are similar to the target images and preserves the annotation information of the visible source domain. The image generation includes a CycleGAN-based image-to-image translation and an intensity inversion transformation. Generated fake thermal images are used as renewed source domain, and then the off-the-shelf domain adaptive faster RCNN is utilized to reduce the gap between the generated intermediate domain and the thermal target domain. Experiments demonstrate the effectiveness and superiority of the proposed method.
The main reason lies in that the governing body neglects to understand the compound mechanisms that act among the urban green space, social economy and environment subsystems for Beijing. ...doi:10.3390/su8100965 fatcat:ajsgeapkzndlvitk3kroluhmpy
(Wentong Li) conceived and designed the methodology; W.L. (Wentong Li) and H.H. performed the experiments; W.L. (Wentong Li) analyzed the data; F.Y. and W.L. (Wanyi Li) contributed materials; W.L. ... (Wentong Li) and H.H. wrote the paper. F.Y., W.L.(Wanyi Li) and P.W. supervised the study and reviewed this paper. All authors have read and agreed to the published version of the manuscript. ...doi:10.3390/s20061686 pmid:32197365 fatcat:eepawlthdbdijailgh674yddoi
Zhou J, Qi Y, Hou Y, Zhao J, Li Y, Xue X, et al. ...doi:10.1371/journal.pgen.1008235 pmid:31242182 pmcid:PMC6615638 fatcat:kx5o2wkw5jbgfkgtzdtnuouvii
Over the past several years, in order to solve the problem of malicious abuse of facial manipulation technology, face manipulation detection technology has obtained considerable attention and achieved remarkable progress. However, most existing methods have very impoverished generalization ability and robustness. In this paper, we propose a novel method for face manipulation detection, which can improve the generalization ability and robustness by bag-of-local-feature. Specifically, we extendarXiv:2103.07915v1 fatcat:3syy6tut5bhh7pnkjjtpl6bx3i
more »... ansformers using bag-of-feature approach to encode inter-patch relationships, allowing it to learn local forgery features without any explicit supervision. Extensive experiments demonstrate that our method can outperform competing state-of-the-art methods on FaceForensics++, Celeb-DF and DeeperForensics-1.0 datasets.
Li, et al., Robust object tracking guided by top-down spectral analysis visual attention, Neurocomputing (2014), http://dx. ... Li et al. / Neurocomputing ∎ (∎∎∎∎) ∎∎∎-∎∎∎ 7 Please cite this article as: W. ... Li et al. / Neurocomputing ∎ (∎∎∎∎) ∎∎∎-∎∎∎ 3 Table 1 1 Tracking Performance Scores. ...doi:10.1016/j.neucom.2014.11.006 fatcat:eri6al7kp5a33lfpjlmogd5epu
IFIP Advances in Information and Communication Technology
Sparse decomposition has been widely used in numerous applications, such as image processing, pattern recognition, remote sensing and computational biology. Despite plenty of theoretical developments have been proposed, developing, implementing and analyzing novel fast sparse approximation algorithm is still an open problem. In this paper, a new pursuit algorithm Double Least Squares Pursuit (DLSP) is proposed for sparse decomposition. In this algorithm, the support of the solution is obtaineddoi:10.1007/978-3-642-32891-6_44 fatcat:ljm74ppfgjgwxc3fkpl73dexa4
more »... y sorting the coefficients which are calculated by the first Least-Squares, and then the non-zero values over this support are detected by the second Least-Squares. The results of numerical experiment demonstrate the effectiveness of the proposed method, which is with less time complexity, more simple form, and gives close or even better performance compared to the classical Orthogonal Matching Pursuit (OMP) method.
., 2015; Li et al., 2014; He et al., 2011; 2013) was recently proposed by incorporation of the gradient smoothing technique with the standard finite element techniques. ...doi:10.1515/aoa-2017-0006 fatcat:gvd6bedyfzdtfpac7doqhte32a
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