Efficient Mining of High Branching Factor Attribute Trees

2006 ◽  
Author(s):  
A. Termier ◽  
M. Rousset ◽  
M. Sebag ◽  
K. Ohara ◽  
T. Washio ◽  
...  
Keyword(s):  
Branching Factor

Synthesizing Designs With Interpart Dependencies Using Hierarchical Generative Adversarial Networks

2019 ◽  
Vol 141 (11) ◽  
Author(s):  
Wei Chen ◽  
Mark Fuge
Keyword(s):  
Constraint Satisfaction ◽  
Real World ◽  
Generative Models ◽  
Dependency Graph ◽  
Generative Adversarial Networks ◽  
Engineering Systems ◽  
Adversarial Networks ◽  
Latent Space ◽  
Branching Factor ◽  
Low Dimensional

Abstract Real-world designs usually consist of parts with interpart dependencies, i.e., the geometry of one part is dependent on one or multiple other parts. We can represent such dependency in a part dependency graph. This paper presents a method for synthesizing these types of hierarchical designs using generative models learned from examples. It decomposes the problem of synthesizing the whole design into synthesizing each part separately but keeping the interpart dependencies satisfied. Specifically, this method constructs multiple generative models, the interaction of which is based on the part dependency graph. We then use the trained generative models to synthesize or explore each part design separately via a low-dimensional latent representation, conditioned on the corresponding parent part(s). We verify our model on multiple design examples with different interpart dependencies. We evaluate our model by analyzing the constraint satisfaction performance, the synthesis quality, the latent space quality, and the effects of part dependency depth and branching factor. This paper’s techniques for capturing dependencies among parts lay the foundation for learned generative models to extend to more realistic engineering systems where such relationships are widespread.

scholarly journals An automatic system for the detection of dairy cows lying behaviour in free-stall barns

2013 ◽  
Vol 44 (2s) ◽  
Author(s):  
Simona M.C. Porto ◽  
Claudia Arcidiacono ◽  
Umberto Anguzza ◽  
Andrea Giummarra ◽  
Giovanni Cascone
Keyword(s):  
Dairy Cows ◽  
Dairy Cow ◽  
False Positive ◽  
Automatic System ◽  
Visual Recognition ◽  
Video Recording ◽  
Recording System ◽  
Sensitivity Index ◽  
Branching Factor ◽  
Accuracy Indices

In this paper, a method for the automatic detection of dairy cow lying behaviour in free-stall barns is proposed. A computer visionbased system (CVBS) composed of a video-recording system and a cow lying behaviour detector based on the Viola Jones algorithm was developed. The CVBS performance was tested in a head-to-head free stall barn. Two classifiers were implemented in the software component of the CVBS to obtain the cow lying behaviour detector. The CVBS was validated by comparing its detection results with those generated from visual recognition. This comparison allowed the following accuracy indices to be calculated: the branching factor (BF), the miss factor (MF), the sensitivity, and the quality percentage (QP). The MF value of approximately 0.09 showed that the CVBS missed one cow every 11 well detected cows. Conversely, the BF value of approximately 0.08 indicated that one false positive was detected every 13 well detected cows. The high value of approximately 0.92 obtained for the sensitivity index and that obtained for QP of about 0.85 revealed the ability of the proposed system to detect cows lying in the stalls.

scholarly journals Optimal branching factor for tree-based reliable multicast protocols

2002 ◽  
Vol 25 (11-12) ◽  
pp. 1018-1027 ◽  
Author(s):  
Christian Maihöfer ◽  
Kurt Rothermel
Keyword(s):  
Reliable Multicast ◽  
Multicast Protocols ◽  
Branching Factor
Sign in / Sign up

Export Citation Format

Share Document