Combinatorial Formulas Related to an Efficient Representation of Permutations

Author(s):  
Amalya Mihnea ◽  
Bhagyalakshmi Patchipalu
2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Bilal Elghadyry ◽  
Faissal Ouardi ◽  
Sébastien Verel

AbstractWeighted finite-state transducers have been shown to be a general and efficient representation in many applications such as text and speech processing, computational biology, and machine learning. The composition of weighted finite-state transducers constitutes a fundamental and common operation between these applications. The NP-hardness of the composition computation problem presents a challenge that leads us to devise efficient algorithms on a large scale when considering more than two transducers. This paper describes a parallel computation of weighted finite transducers composition in MapReduce framework. To the best of our knowledge, this paper is the first to tackle this task using MapReduce methods. First, we analyze the communication cost of this problem using Afrati et al. model. Then, we propose three MapReduce methods based respectively on input alphabet mapping, state mapping, and hybrid mapping. Finally, intensive experiments on a wide range of weighted finite-state transducers are conducted to compare the proposed methods and show their efficiency for large-scale data.


Author(s):  
Luigi Carassale ◽  
Mirko Maurici

The component mode synthesis based on the Craig-Bampton method has two strong limitations that appear when the number of the interface degrees of freedom is large. First, the reduced-order model obtained is overweighed by many unnecessary degrees of freedom. Second, the reduction step may become extremely time consuming. Several interface reduction techniques addressed successfully the former problem, while the latter remains open. In this paper we tackle this latter problem through a simple interface-reduction technique based on an a-priory choice of the interface modes. An efficient representation of the interface displacement field is achieved adopting a set of orthogonal basis functions determined by the interface geometry. The proposed method is compared with other existing interface reduction methods on a case study regarding a rotor blade of an axial compressor.


2016 ◽  
Vol 23 (4) ◽  
pp. 14-20 ◽  
Author(s):  
Touradj Ebrahimi ◽  
Siegfried Foessel ◽  
Fernando Pereira ◽  
Peter Schelkens

Author(s):  
Marc Feix ◽  
Dominique Lepelley ◽  
Vincent Merlin ◽  
Jean-Louis Rouet ◽  
Laurent Vidu

Author(s):  
K. Akanksha

Radar is a detection system that uses radio waves to determine the range, angle or velocity of objects. It can be used to detect aircraft, ships, spacecraft, guided missiles, motor vehicles, weather formations, and terrain. A radar system consist of a transmitting antenna, a receiving antenna (often same antenna is used for transmitting and receiving) and a receiver and process to determine properties of the objects. In our project we are detecting the target position of the obstacles that come in our way be it in military, aircrafts, ships, clouds, etc. using MATLAB. Using MATLAB, you can: analyze data, develop algorithms, create models and applications. The language, apps, and build in math functions enable you to quickly explore multiple approaches to arrive at a solution. Using MATLAB and Simulink we are doing radar visualizer.


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