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Institution

Tongji University

EducationShanghai, China
About: Tongji University is a education organization based out in Shanghai, China. It is known for research contribution in the topics: Population & Adsorption. The organization has 76116 authors who have published 81176 publications receiving 1248911 citations. The organization is also known as: Tongji & Tóngjì Dàxué.


Papers
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Book ChapterDOI
07 Oct 2012
TL;DR: This paper presents the Least Squares Regression (LSR) method for subspace segmentation, which takes advantage of data correlation, which is common in real data and significantly outperforms state-of-the-art methods.
Abstract: This paper studies the subspace segmentation problem which aims to segment data drawn from a union of multiple linear subspaces. Recent works by using sparse representation, low rank representation and their extensions attract much attention. If the subspaces from which the data drawn are independent or orthogonal, they are able to obtain a block diagonal affinity matrix, which usually leads to a correct segmentation. The main differences among them are their objective functions. We theoretically show that if the objective function satisfies some conditions, and the data are sufficiently drawn from independent subspaces, the obtained affinity matrix is always block diagonal. Furthermore, the data sampling can be insufficient if the subspaces are orthogonal. Some existing methods are all special cases. Then we present the Least Squares Regression (LSR) method for subspace segmentation. It takes advantage of data correlation, which is common in real data. LSR encourages a grouping effect which tends to group highly correlated data together. Experimental results on the Hopkins 155 database and Extended Yale Database B show that our method significantly outperforms state-of-the-art methods. Beyond segmentation accuracy, all experiments demonstrate that LSR is much more efficient.

521 citations

Journal ArticleDOI
Bing Yan1
TL;DR: A general strategy to functionalize MOF hosts with lanthanide ions, compounds, or other luminescent species (organic dyes or carbon dots) and to assemble types of photofunctional hybrid systems based on lanthanides-functionalized MOFs is proposed.
Abstract: ConspectusMetal–organic frameworks (MOFs) possess an important advantage over other candidate classes for chemosensory materials because of their exceptional structural tunability and properties. Luminescent sensing using MOFs is a simple, intuitive, and convenient method to recognize species, but the method has limitations, such as insufficient chemical selectivity and signal loss. MOFs contain versatile building blocks (linkers or ligands) with special chemical reactivity, and postsynthetic modification (PSM) provides an opportunity to exploit and expand their unique properties. The linkers in most MOFs contain aromatic subunits that can readily display luminescence after ultraviolet or visible (typically blue) excitation, and this is the main luminescent nature of most MOFs. The introduction of photoactive lanthanide ions (Ln3+) into the MOF hosts may produce new luminescent signals at different positions from that of the MOF linker, but this depends on the intramolecular energy transfer (antenna effec...

520 citations

Journal ArticleDOI
TL;DR: Six learning algorithms including biogeography-based optimization, particle swarm optimization, genetic algorithm, ant colony optimization, evolutionary strategy, and population-based incremental learning are used to train a new dendritic neuron model (DNM) and are suggested to make DNM more powerful in solving classification, approximation, and prediction problems.
Abstract: An artificial neural network (ANN) that mimics the information processing mechanisms and procedures of neurons in human brains has achieved a great success in many fields, e.g., classification, prediction, and control. However, traditional ANNs suffer from many problems, such as the hard understanding problem, the slow and difficult training problems, and the difficulty to scale them up. These problems motivate us to develop a new dendritic neuron model (DNM) by considering the nonlinearity of synapses, not only for a better understanding of a biological neuronal system, but also for providing a more useful method for solving practical problems. To achieve its better performance for solving problems, six learning algorithms including biogeography-based optimization, particle swarm optimization, genetic algorithm, ant colony optimization, evolutionary strategy, and population-based incremental learning are for the first time used to train it. The best combination of its user-defined parameters has been systemically investigated by using the Taguchi’s experimental design method. The experiments on 14 different problems involving classification, approximation, and prediction are conducted by using a multilayer perceptron and the proposed DNM. The results suggest that the proposed learning algorithms are effective and promising for training DNM and thus make DNM more powerful in solving classification, approximation, and prediction problems.

517 citations

Journal ArticleDOI
TL;DR: In patients with STEMI who were undergoing primary PCI, routine manual thrombectomy, as compared with PCI alone, did not reduce the risk of cardiovascular death, recurrent myocardial infarction, cardiogenic shock, or NYHA class IV heart failure within 180 days but was associated with an increased rate of stroke within 30 days.
Abstract: The primary outcome occurred in 347 of 5033 patients (6.9%) in the thrombectomy group versus 351 of 5030 patients (7.0%) in the PCI-alone group (hazard ratio in the thrombectomy group, 0.99; 95% confidence interval [CI], 0.85 to 1.15; P = 0.86). The rates of cardiovascular death (3.1% with thrombectomy vs. 3.5% with PCI alone; hazard ratio, 0.90; 95% CI, 0.73 to 1.12; P = 0.34) and the primary outcome plus stent thrombosis or target-vessel revascularization (9.9% vs. 9.8%; hazard ratio, 1.00; 95% CI, 0.89 to 1.14; P = 0.95) were also similar. Stroke within 30 days occurred in 33 patients (0.7%) in the thrombectomy group versus 16 patients (0.3%) in the PCI-alone group (hazard ratio, 2.06; 95% CI, 1.13 to 3.75; P = 0.02). Conclusions In patients with STEMI who were undergoing primary PCI, routine manual thrombectomy, as compared with PCI alone, did not reduce the risk of cardiovascular death, recurrent myocardial infarction, cardiogenic shock, or NYHA class IV heart failure within 180 days but was associated with an increased rate of stroke within 30 days. (Funded by Medtronic and the Canadian Institutes of Health Research; TOTAL ClinicalTrials.gov number, NCT01149044.)

515 citations

Journal ArticleDOI
TL;DR: Numerical results show that for both AF and DF protocols, the intercept probability performance of proposed optimal relay selection is strictly better than that of the traditional relay selection and multiple relay combining methods.
Abstract: In this paper, we explore the physical-layer security in cooperative wireless networks with multiple relays where both amplify-and-forward (AF) and decode-and-forward (DF) protocols are considered. We propose the AF and DF based optimal relay selection (i.e., AFbORS and DFbORS) schemes to improve the wireless security against eavesdropping attack. For the purpose of comparison, we examine the traditional AFbORS and DFbORS schemes, denoted by T-AFbORS and T-DFbORS, respectively. We also investigate a so-called multiple relay combining (MRC) framework and present the traditional AF and DF based MRC schemes, called T-AFbMRC and T-DFbMRC, where multiple relays participate in forwarding the source signal to destination which then combines its received signals from the multiple relays. We derive closed-form intercept probability expressions of the proposed AFbORS and DFbORS (i.e., P-AFbORS and P-DFbORS) as well as the T-AFbORS, T-DFbORS, T-AFbMRC and T-DFbMRC schemes in the presence of eavesdropping attack. We further conduct an asymptotic intercept probability analysis to evaluate the diversity order performance of relay selection schemes and show that no matter which relaying protocol is considered (i.e., AF and DF), the traditional and proposed optimal relay selection approaches both achieve the diversity order M where M represents the number of relays. In addition, numerical results show that for both AF and DF protocols, the intercept probability performance of proposed optimal relay selection is strictly better than that of the traditional relay selection and multiple relay combining methods.

510 citations


Authors

Showing all 76610 results

NameH-indexPapersCitations
Gang Chen1673372149819
Yang Yang1642704144071
Georgios B. Giannakis137132173517
Jian Li133286387131
Jianlin Shi12785954862
Zhenyu Zhang118116764887
Ju Li10962346004
Peng Wang108167254529
Qian Wang108214865557
Yan Zhang107241057758
Richard B. Kaner10655766862
Han-Qing Yu10571839735
Wei Zhang104291164923
Fabio Marchesoni10460774687
Feng Li10499560692
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023238
20221,051
20219,713
20208,502
20197,517
20186,352