Institution
Dalian University of Technology
Education•Dalian, 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 published on a yearly basis
Papers
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TL;DR: In this paper, a review of the recent progress of fabrication, properties, and structural applications of high-performance and multifunctional cementitious composites with carbon nanofibers, carbon nanotubes and nano graphite platelets is presented.
Abstract: As structural materials, cementitious materials are quasi-brittle and susceptible to cracking, and have no functional properties. Nanotechnology is introduced into cementitious materials to address these issues. Nano materials, especially nano carbon materials (NCMs) were found to be able to improve/modify the mechanical property, durability and functional properties of cementitious materials due to their excellent intrinsic properties and composite effects. Here, this review focuses on the recent progress of fabrication, properties, and structural applications of high-performance and multifunctional cementitious composites with NCMs including carbon nanofibers, carbon nanotubes and nano graphite platelets. The improvement/modification mechanisms of these NCMs to composites are also discussed.
284 citations
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TL;DR: A facile synthesis strategy for preparing Fe3O4@ZIF-8 magnetic core-shell microspheres has been successfully developed as mentioned in this paper, which involves first pre-treating the magnetic cores with an anionic polyelectrolyte to alter the surface charge of the particles and adsorb Zn2+ cations to initiate nucleation.
284 citations
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TL;DR: Corncob residue, the main by-product in the furfural industry, is used as a precursor to prepare porous carbon by a simple and direct thermal treatment: one-step activation without pre-carbonization.
284 citations
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01 Jun 2016TL;DR: The proposed sequential training method for convolutional neural networks to effectively transfer pre-trained deep features for online applications is applied to visual tracking problem by transferring deep features trained on massive annotated visual data and is shown to significantly improve tracking performance.
Abstract: Due to the limited amount of training samples, finetuning pre-trained deep models online is prone to overfitting. In this paper, we propose a sequential training method for convolutional neural networks (CNNs) to effectively transfer pre-trained deep features for online applications. We regard a CNN as an ensemble with each channel of the output feature map as an individual base learner. Each base learner is trained using different loss criterions to reduce correlation and avoid over-training. To achieve the best ensemble online, all the base learners are sequentially sampled into the ensemble via important sampling. To further improve the robustness of each base learner, we propose to train the convolutional layers with random binary masks, which serves as a regularization to enforce each base learner to focus on different input features. The proposed online training method is applied to visual tracking problem by transferring deep features trained on massive annotated visual data and is shown to significantly improve tracking performance. Extensive experiments are conducted on two challenging benchmark data set and demonstrate that our tracking algorithm can outperform state-of-the-art methods with a considerable margin.
284 citations
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TL;DR: The results indicate that the different biological encoding of numbers may be shaped by visual reading experience during language acquisition and other cultural factors such as mathematics learning strategies and education systems, which cannot be explained completely by the differences in languages per se.
Abstract: The universal use of Arabic numbers in mathematics raises a question whether these digits are processed the same way in people speaking various languages, such as Chinese and English, which reflect differences in Eastern and Western cultures. Using functional MRI, we demonstrated a differential cortical representation of numbers between native Chinese and English speakers. Contrasting to native English speakers, who largely employ a language process that relies on the left perisylvian cortices for mental calculation such as a simple addition task, native Chinese speakers, instead, engage a visuo-premotor association network for the same task. Whereas in both groups the inferior parietal cortex was activated by a task for numerical quantity comparison, functional MRI connectivity analyses revealed a functional distinction between Chinese and English groups among the brain networks involved in the task. Our results further indicate that the different biological encoding of numbers may be shaped by visual reading experience during language acquisition and other cultural factors such as mathematics learning strategies and education systems, which cannot be explained completely by the differences in languages per se.
283 citations
Authors
Showing all 61205 results
Name | H-index | Papers | Citations |
---|---|---|---|
Yang Yang | 171 | 2644 | 153049 |
Yury Gogotsi | 171 | 956 | 144520 |
Hui Li | 135 | 2982 | 105903 |
Michael I. Posner | 134 | 414 | 104201 |
Anders Hagfeldt | 129 | 600 | 79912 |
Jian Zhou | 128 | 3007 | 91402 |
Chao Zhang | 127 | 3119 | 84711 |
Bin Wang | 126 | 2226 | 74364 |
Chi Lin | 125 | 1313 | 102710 |
Tao Zhang | 123 | 2772 | 83866 |
Bo Wang | 119 | 2905 | 84863 |
Zhenyu Zhang | 118 | 1167 | 64887 |
Liang Cheng | 116 | 1779 | 65520 |
Anthony G. Fane | 112 | 565 | 40904 |
Xuelong Li | 110 | 1044 | 46648 |