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Institution

Dalian University of Technology

EducationDalian, China
About: Dalian University of Technology is a education organization based out in Dalian, China. It is known for research contribution in the topics: Catalysis & Finite element method. The organization has 60890 authors who have published 71921 publications receiving 1188356 citations. The organization is also known as: Dàlián Lǐgōng Dàxué.


Papers
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Journal ArticleDOI
TL;DR: An extensive survey of the measurement methods proposed for UAV channel modeling that use low altitude platforms and discusses various channel characterization efforts is provided.
Abstract: Unmanned aerial vehicles (UAVs) have attracted great interest in rapid deployment for both civil and military applications. UAV communication has its own distinctive channel characteristics compared to the widely used cellular or satellite systems. Accurate channel characterization is crucial for the performance optimization and design of efficient UAV communication. However, several challenges exist in UAV channel modeling. For example, the propagation characteristics of UAV channels are under explored for spatial and temporal variations in non–stationary channels. Additionally, airframe shadowing has not yet been investigated for small size rotary UAVs. This paper provides an extensive survey of the measurement methods proposed for UAV channel modeling that use low altitude platforms and discusses various channel characterization efforts. We also review from a contemporary perspective of UAV channel modeling approaches, and outline future research challenges in this domain.

532 citations

Proceedings ArticleDOI
01 Jun 2021
TL;DR: Transformer as discussed by the authors proposes an attention-based feature fusion network, which effectively combines the template and search region features solely using attention, and achieves very promising results on six challenging datasets, especially on large-scale LaSOT, TrackingNet, and GOT-10k benchmarks.
Abstract: Correlation acts as a critical role in the tracking field, especially in recent popular Siamese-based trackers. The correlation operation is a simple fusion manner to consider the similarity between the template and the search region. However, the correlation operation itself is a local linear matching process, leading to lose semantic information and fall into local optimum easily, which may be the bottleneck of designing high-accuracy tracking algorithms. Is there any better feature fusion method than correlation? To address this issue, inspired by Transformer, this work presents a novel attention-based feature fusion network, which effectively combines the template and search region features solely using attention. Specifically, the proposed method includes an ego-context augment module based on self-attention and a cross-feature augment module based on cross-attention. Finally, we present a Transformer tracking (named TransT) method based on the Siamese-like feature extraction backbone, the designed attention-based fusion mechanism, and the classification and regression head. Experiments show that our TransT achieves very promising results on six challenging datasets, especially on large-scale LaSOT, TrackingNet, and GOT-10k benchmarks. Our tracker runs at approximatively 50 fps on GPU. Code and models are available at https://github.com/chenxin-dlut/TransT.

528 citations

Journal ArticleDOI
TL;DR: This Account outlines efforts to develop highly active Co(III)-based catalysts for the selective production of polycarbonates from the alternating copolymerization of CO(2) with epoxides and provides a thorough mechanistic understanding of the high activities, excellent selectivities, and unprecedented stereochemical control of these Co(II) based catalysts in the production of CO (2) copolymers.
Abstract: The use of carbon dioxide as a carbon source for the synthesis of organic chemicals can contribute to a more sustainable chemical industry. Because CO2 is such a thermodynamically stable molecule, few effective catalysts are available to facilitate this transformation. Currently, the major industrial processes that convert CO2 into viable products generate urea and hydroxybenzoic acid. One of the most promising new technologies for the use of this abundant, inexpensive, and nontoxic renewable resource is the alternating copolymerization of CO2 and epoxides to provide biodegradable polycarbonates, which are highly valuable polymeric materials. Because this process often generates byproducts, such as polyether or ether linkages randomly dispersed within the polycarbonate chains and/or the more thermodynamically stable cyclic carbonates, the choice of catalyst is critical for selectively obtaining the expected product.In this Account, we outline our efforts to develop highly active Co(III)-based catalysts fo...

528 citations

Journal ArticleDOI
01 May 2012
TL;DR: Experimental results and security analysis show that the scheme can not only achieve good encryption result, but also the key space is large enough to resist against common attacks.
Abstract: This paper proposes a novel confusion and diffusion method for image encryption. One innovation is to confuse the pixels by transforming the nucleotide into its base pair for random times, the other is to generate the new keys according to the plain image and the common keys, which can make the initial conditions of the chaotic maps change automatically in every encryption process. For any size of the original grayscale image, after being permuted the rows and columns respectively by the arrays generated by piecewise linear chaotic map (PWLCM), each pixel of the original image is encoded into four nucleotides by the deoxyribonucleic acid (DNA) coding, then each nucleotide is transformed into its base pair for random time(s) using the complementary rule, the times is generated by Chebyshev maps. Experiment results and security analysis show that the scheme can not only achieve good encryption result, but also the key space is large enough to resist against common attacks.

523 citations

Journal ArticleDOI
TL;DR: The dynamic covalent functionality of boronic acids with structure-directing potential has led researchers to develop a variety of self-organizing systems including macrocycles, cages, capsules, and polymers.
Abstract: Boronic acids can interact with Lewis bases to generate boronate anions, and they can also bind with diol units to form cyclic boronate esters. Boronic acid based receptor designs originated when L...

520 citations


Authors

Showing all 61205 results

NameH-indexPapersCitations
Yang Yang1712644153049
Yury Gogotsi171956144520
Hui Li1352982105903
Michael I. Posner134414104201
Anders Hagfeldt12960079912
Jian Zhou128300791402
Chao Zhang127311984711
Bin Wang126222674364
Chi Lin1251313102710
Tao Zhang123277283866
Bo Wang119290584863
Zhenyu Zhang118116764887
Liang Cheng116177965520
Anthony G. Fane11256540904
Xuelong Li110104446648
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023167
2022836
20216,974
20206,457
20196,261
20185,375