Dalian University of Technology

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.

A new image encryption algorithm based on non-adjacent coupled map lattices

Abstract: We propose an image encryption scheme based on a new spatiotemporal chaotic system.The encryption scheme is not the one time pad encryption.The proposed image encryption has a large key space and high security. We propose a new image encryption algorithm which is based on the spatiotemporal non-adjacent coupled map lattices. The system of non-adjacent coupled map lattices has more outstanding cryptography features in dynamics than the logistic map or coupled map lattices does. In the proposed image encryption, we employ a bit-level pixel permutation strategy which enables bit planes of pixels permute mutually without any extra storage space. Simulations have been carried out and the results demonstrate the superior security and high efficiency of the proposed algorithm.

BioWordVec, improving biomedical word embeddings with subword information and MeSH.

Abstract: Distributed word representations have become an essential foundation for biomedical natural language processing (BioNLP), text mining and information retrieval. Word embeddings are traditionally computed at the word level from a large corpus of unlabeled text, ignoring the information present in the internal structure of words or any information available in domain specific structured resources such as ontologies. However, such information holds potentials for greatly improving the quality of the word representation, as suggested in some recent studies in the general domain. Here we present BioWordVec: an open set of biomedical word vectors/embeddings that combines subword information from unlabeled biomedical text with a widely-used biomedical controlled vocabulary called Medical Subject Headings (MeSH). We assess both the validity and utility of our generated word embeddings over multiple NLP tasks in the biomedical domain. Our benchmarking results demonstrate that our word embeddings can result in significantly improved performance over the previous state of the art in those challenging tasks. Machine-accessible metadata file describing the reported data (ISA-Tab format)

Dopamine as the coating agent and carbon precursor for the fabrication of N-doped carbon coated Fe3O4 composites as superior lithium ion anodes

Abstract: Dopamine is an excellent and flexible agent for surface coating of inorganic nanoparticles and contains unusually high concentrations of amine groups. In this study, we demonstrate that through a controlled coating of a thin layer of polydopamine on the surface of α-Fe(2)O(3) in the dopamine aqueous solution, followed by subsequent carbonization, N-doped carbon-encapsulated magnetite has been synthesized and shows excellent electrochemical performance as anode material for lithium-ion batteries. Due to the strong binding affinity to iron oxide and excellent coating capability of this new carbon precursor, the conformal polydopamine derived carbon is continuous and uniform, and its thickness can be tailored. Moreover, due to the high percentage of nitrogen content in the precursor, the resulting carbon layer contains a moderate amount of N species, which can substantially improve the electrochemical performance. The composites synthesized by this facile method exhibit superior electrochemical performance, including remarkably high specific capacity (>800 mA h g(-1) at a current of 500 mA g(-1)), high rate capability (595 and 396 mA h g(-1) at a current of 1000 and 2000 mA g(-1), respectively) and excellent cycle performance (200 cycles with 99% capacity retention), which adds to the potential as promising anodes for the application in lithium-ion batteries.