Combinatorial Methods for String Processing

2009 ◽  
Author(s):  
Marios Hadjieleftheriou
Keyword(s):  

1979 ◽  
Vol 101 (1) ◽  
pp. 17-22 ◽  
Author(s):  
K. Phillips

A mathematical model for job scheduling in a specified context is presented. The model uses both linear programming and combinatorial methods. While designed with a view toward optimization of scheduling of facility and plant operations at the Deep Space Network (DSN) Station at Goldstone, the context is sufficiently general to be widely applicable. The general scheduling problem including options for scheduling objectives is discussed and fundamental parameters identified. Mathematical algorithms for partitioning problems germaine to scheduling are presented. A more detailed description of algorithms and of operational aspects of the model is planned for a later report.


1994 ◽  
Vol 31 (A) ◽  
pp. 115-129 ◽  
Author(s):  
W. Böhm ◽  
S. G. Mohanty

In this contribution we consider an M/M/1 queueing model with general server vacations. Transient and steady state analysis are carried out in discrete time by combinatorial methods. Using weak convergence of discrete-parameter Markov chains we also obtain formulas for the corresponding continuous-time queueing model. As a special case we discuss briefly a queueing system with a T-policy operating.


Mathematics ◽  
2018 ◽  
Vol 6 (12) ◽  
pp. 300 ◽  
Author(s):  
Guohui Chen ◽  
Li Chen

In this paper, we first introduce a new second-order non-linear recursive polynomials U h , i ( x ) , and then use these recursive polynomials, the properties of the power series and the combinatorial methods to prove some identities involving the Fubini polynomials, Euler polynomials and Euler numbers.


2018 ◽  
Vol 7 (2.7) ◽  
pp. 146
Author(s):  
Lakshmi Prasad Mudarakola ◽  
J K.R. Sastry ◽  
V Chandra Prakash

Thorough testing of embedded systems is required especially when the systems are related to monitoring and controlling the mission critical and safety critical systems. The embedded systems must be tested comprehensively which include testing hardware, software and both together. Embedded systems are highly intelligent devices that are infiltrating our daily lives such as the mobile in your pocket, and wireless infrastructure behind it, routers, home theatre system, the air traffic control station etc. Software now makes up 90% of the value of these devices. In this paper, authors present different methods to test an embedded system using test cases generated through combinatorial techniques. The experimental results for testing a TMCNRS (Temperature Monitoring and Controlling Nuclear Reactor System) using test cases generated from combinatorial methods are also shown.


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