scholarly journals Permutation Steganography for Polygonal Meshes Based on Coding Tree

2010 ◽  
Vol 9 (4) ◽  
pp. 55-60 ◽  
Author(s):  
Shihchun Tu ◽  
Hungwei Hsu ◽  
Wenkai Tai
Keyword(s):  
Binary Tree ◽  
Experimental Results ◽  
Affine Transformations ◽  
Complete Binary Tree ◽  
Polygonal Meshes ◽  
Maximal Capacity

We propose a coding tree for permutation steganography in polygonal meshes. Instead of conceptually building a complete binary tree for remaining embedding/extracting primitives to encode/decode bitstream, our method lengthens bitstream by exploiting the coding tree of the primitives, a binary tree which is a little bit skewed. The coding tree has higher levels than the complete binary tree so that as experimental results show, the average capacity of our approach is more about 0.39 bit/vertex than that of Bogomjakov et al. [5], and the improvement of the maximal capacity comes up to 40% of Bogomjakov et al. [5]. Still, our method has the minimal capacity same with Bogomjakov et al. [5], and is simple and easy to implement as well. This ordering is obtained based on the mesh connectivity [14], making our method robust to geometric affine transformations. Also, the primitive rearrangement does not distort the cover media and cause suspicion of the hidden message

Automatic Ship Routing with High Reliability and Efficiency between Two Arbitrary Points at Sea

2018 ◽  
Vol 72 (2) ◽  
pp. 430-446
Author(s):  
Shuaidong Jia ◽  
Zeyuan Dai ◽  
Lihua Zhang
Keyword(s):  
Binary Tree ◽  
High Reliability ◽  
Spatial Database ◽  
Experimental Results ◽  
Ship Routing ◽  
Shortest Distance ◽  
Tree Index ◽  
Tree Method

Due to the limitations of the existing methods (for example, the route binary tree method) that can only automatically generate routes based on a single chart, a method for automatically generating the shortest distance route based on an obstacle spatial database is proposed. Using this proposed method, the route between two arbitrary points at sea can be automatically generated. First, the differences in accuracy and updating time of charts are quantitatively analysed. Next, the mechanism for updating obstacles is designed, an obstacle spatial database is constructed, and the obstacle data extracted from multiple charts are fused. Finally, considering the effect of efficiency on the amount of obstacle data, a route window and an improved R-tree index are designed for quickly extracting and querying the obstacle database. The experimental results demonstrate that compared with existing methods, the proposed method can generate the shortest distance between two arbitrary points at sea and eliminates the limitation of the area of the chart. In addition, with data from multiple charts, the route generated by the proposed method is more reliable than that of the existing methods, and it is more efficient.

Binary Trees and the n-Cutset Property

1991 ◽  
Vol 34 (1) ◽  
pp. 23-30 ◽  
Author(s):  
Peter Arpin ◽  
John Ginsburg
Keyword(s):  
Positive Integer ◽  
Partially Ordered Set ◽  
Binary Tree ◽  
Ordered Set ◽  
Maximal Chain ◽  
Binary Trees ◽  
Complete Binary Tree ◽  
Maximal Elements ◽  
Extremal Case ◽  
Result Theorem

AbstractA partially ordered set P is said to have the n-cutset property if for every element x of P, there is a subset S of P all of whose elements are noncomparable to x, with |S| ≤ n, and such that every maximal chain in P meets {x} ∪ S. It is known that if P has the n-cutset property then P has at most 2n maximal elements. Here we are concerned with the extremal case. We let Max P denote the set of maximal elements of P. We establish the following result. THEOREM: Let n be a positive integer. Suppose P has the n-cutset property and that |Max P| = 2n. Then P contains a complete binary tree T of height n with Max T = Max P and such that C ∩ T is a maximal chain in T for every maximal chain C of P. Two examples are given to show that this result does not extend to the case when n is infinite. However the following is shown. THEOREM: Suppose that P has the ω-cutset property and that |Max P| = 2ω. If P — Max P is countable then P contains a complete binary tree of height ω

scholarly journals A Novel Mathematical Formula for Retrieval Algorithm

2014 ◽  
Vol 2014 ◽  
pp. 1-5
Author(s):  
Yuping Qin ◽  
Hamid Reza Karimi ◽  
Aihua Zhang ◽  
Qiangkui Leng
Keyword(s):  
Binary Tree ◽  
Experimental Results ◽  
Retrieval Algorithm ◽  
Mathematical Formula ◽  
Structure Code

A method is proposed to retrieve mathematical formula in LaTeX documents. Firstly, we represent the retrieved mathematical formula by binary tree according to its LaTeX description, normalize the structure of the binary tree, and obtain the structure code and then search the mathematical formula table that is named by the structure code and the formula elements of the first two levels of the binary tree in the mathematical formula database. If the table exists, then we search the normalizing variable name preorder traversing sequence of the binary tree in the table and display the document information that contain the mathematical formula. The experimental results show that the algorithm realizes the retrieval of mathematical formula in LaTeX documents and has higher retrieval precision and faster retrieval speed.

Two Models of Additional Adjacencies between the Root and Descendants in a Complete Binary Tree Minimizing Total Path Length

2009 ◽  
Author(s):  
Kiyoshi Sawada ◽  
Sio-Iong Ao ◽  
Alan Hoi-Shou Chan ◽  
Hideki Katagiri ◽  
Osca Castillo ◽  
...  
Keyword(s):  
Binary Tree ◽  
Path Length ◽  
Complete Binary Tree ◽  
Total Path Length

Classification Methods in the Detection of New Suspicious Emails

2008 ◽  
Vol 07 (03) ◽  
pp. 209-217 ◽  
Author(s):  
S. Appavu Alias Balamurugan ◽  
G. Athiappan ◽  
M. Muthu Pandian ◽  
R. Rajaram
Keyword(s):  
Neural Network ◽  
Data Mining ◽  
Decision Tree ◽  
Binary Tree ◽  
Experimental Results ◽  
Classification Methods ◽  
Detection Rates ◽  
Naive Bayesian ◽  
The Past ◽  
Naïve Bayesian

Email has become one of the fastest and most economical forms of communication. However, the increase of email users has resulted in the dramatic increase of suspicious emails during the past few years. This paper proposes to apply classification data mining for the task of suspicious email detection based on deception theory. In this paper, email data was classified using four different classifiers (Neural Network, SVM, Naïve Bayesian and Decision Tree). The experiment was performed using weka on the basis of different data size by which the suspicious emails are detected from the email corpus. Experimental results show that simple ID3 classifier which make a binary tree, will give a promising detection rates.

A New SVM Multi-Class Classification Algorithm Based on Sample Scale and Distribution Area

2013 ◽  
Vol 712-715 ◽  
pp. 2529-2533
Author(s):  
Yu Ping Qin ◽  
Peng Da Qin ◽  
Shu Xian Lun ◽  
Yi Wang
Keyword(s):  
Binary Tree ◽  
Classification Performance ◽  
Classification Algorithm ◽  
Experimental Results ◽  
Leaf Node ◽  
Distribution Area ◽  
Root Node ◽  
Multi Class Classification

A new SVM multi-class classification algorithm is proposed. Firstly, the optimal binary tree is constructed by the scale and the distribution area of every class sample, and then the sub-classifiers are trained for every non-leaf node in the binary tree. For the sample to be classified, the classification is done from the root node until someone leaf node, and the corresponding class of the leaf node is the class of the sample. The experimental results show that the algorithm improves the classification precision and classification speed, especially in the situation that the sample scale is less but its distribution area is bigger, the algorithm can improve greatly the classification performance.

Color Quantization Based on Hierarchical Frequency Sensitive Competitive Learning

2010 ◽  
Vol 14 (4) ◽  
pp. 375-381
Author(s):  
Jun Zhang ◽  
◽  
Jinglu Hu
Keyword(s):  
Binary Tree ◽  
Competitive Learning ◽  
Tree Structure ◽  
Experimental Results ◽  
Color Quantization ◽  
Adaptive Procedure ◽  
Root Node ◽  
Binary Tree Structure

In this paper, we propose a Hierarchical Frequency Sensitive Competitive Learning (HFSCL) method to achieve Color Quantization (CQ). In HFSCL, the appropriate number of quantized colors and the palette can be obtained by an adaptive procedure following a binary tree structure with nodes and layers. Starting from the root node that contains all colors in an image until all nodes are examined by split conditions, a binary tree will be generated. In each node of the tree, a Frequency Sensitive Competitive Learning (FSCL) network is used to achieve two-way division. To avoid over-split, merging condition is defined to merge the clusters that are close enough to each other at each layer. Experimental results show that the proposed HFSCL has desired ability for CQ.

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