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Author(s):  
Hangda Xie ◽  
Xueye Chen

Abstract This article focuses on the influence of fractal-like tree node (FTN) on the mixing efficiency and pressure drop of the micromixer. The mixing efficiency of FTN micromixers with different branch angle δ = 30°, 60° and 90° are compared at six kinds of Reynolds (Res). We can get that the micromixer with δ = 90° has higher mixing efficiency at any Re. The mixing results of the center FTN and the stagger FTN micromixer show that the center FTN has better mixing effect. The angle of FTN and the number of FTN are the key to improve the mixing efficiency. They are also the key to change the pressure drop in the microchannel. The FTN can slow down the pressure drop and maintain the stable pressure drop between two adjacent FTNs. The way to obtain a more stable pressure range is to increase the distance between two adjacent FTN. This provides a reliable reference for maintaining a stable pressure in the microchannel.


2020 ◽  
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2019 ◽  
Vol 11 (7) ◽  
pp. 149
Author(s):  
Yi-Cheng Chen ◽  
Yueh-Peng Chou ◽  
Yung-Chen Chou

Research on digital image processing has become quite popular and rapid in recent years, and scholars have proposed various image verification mechanisms. Similarly , blockchain technology has also become very popular in recent years. This paper proposes a new image verification mechanism based on the Merkle tree technique in the blockchain. The Merkle tree root in the blockchain mechanism provides a reliable environment for storage of image features. In image verification, the verification of each image can be performed by the Merkle tree mechanism to obtain the hash value of the Merkle tree node on the path. In addition, the method combines the Inter-Planetary File System (IPFS) to improve the availability of images. The main purpose of this paper is to achieve the goal of image integrity verification. The proposed method can not only verify the integrity of the image but also restore the tampered area in the case of image tampering. Since the proposed method employs the blockchain mechanism, the image verification mechanism does not need third party resources . The verification method is performed by each node in the blockchain network. The experimental results demonstrate that the proposed method successfully achieved the goal of image authentication and tampered area restoration.


Author(s):  
Zhan Peng ◽  
Yuping Wang ◽  
Wei Yue

Multi-string matching (MSM) is a core technique searching a text string for all occurrences of some string patterns. It is widely used in many applications. However, as the number of string patterns increases, most of the existing algorithms suffer from two issues: the long matching time, and the high memory consumption. To address these issues, in this paper, a fast matching engine is proposed for large-scale string matching problems. Our engine includes a filter module and a verification module. The filter module is based on several bitmaps which are responsible for quickly filtering out the invalid positions in the text, while for each potential matched position, the verification module confirms true pattern occurrence. In particular, we design a compact data structure called Adaptive Matching Tree (AMT) for the verification module, in which each tree node only saves some pattern fragments of the whole pattern set and the inner structure of each tree node is chosen adaptively according to the features of the corresponding pattern fragments. This makes the engine time and space efficient. The experiments indicate that, our matching engine performs better than the compared algorithms, especially for large pattern sets.


2015 ◽  
Vol 103 (1) ◽  
pp. 139-159
Author(s):  
Ziqi Wang ◽  
Haotian Zhang ◽  
Anoop Sarkar

Abstract This paper describes the design and implementation of a Python-based interface for wide coverage Lexicalized Tree-adjoining Grammars. The grammars are part of the XTAG Grammar project at the University of Pennsylvania, which were hand-written and semi-automatically curated to parse real-world corpora. We provide an interface to the wide coverage English and Korean XTAG grammars. Each XTAG grammar is lexicalized, which means at least one word selects a tree fragment (called an elementary tree or etree). Derivations for sentences are built by combining etrees using substitution (replacement of a tree node with an etree at the frontier of another etree) and adjunction (replacement of an internal tree node in an etree by another etree). Each etree is associated with a feature structure representing constraints on substitution and adjunction. Feature structures are combined using unification during the combination of etrees. We plan to integrate our toolkit for XTAG grammars into the Python-based Natural Language Toolkit (NLTK: nltk.org). We have provided an API capable of searching the lexicalized etrees for a given word or multiple words, searching for a etree by name or function, display the lexicalized etrees to the user using a graphical view, display the feature structure associated with each tree node in an etree, hide or highlight features based on a regular expression, and browsing the entire tree database for each XTAG grammar.


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