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Disclaimer and Policy

In no event shall Excel Business Solutions (EBS) be liable for any direct, indirect, incidental, special, or consequential damage(s), including damage(s) causing loss of profit, revenue, data or usage, incurred by you or any third party, arising from the use of our products/services.

The file(s) and/or code that are generated by Excel Business Solutions' consultants shall not be disclosed to, sold, or used by any third party unless such activity is specifically authorized and permitted in writing within the scope of the original proposal and agreement (The Agreement) between you, the Customer, and Excel Business Solutions.

Excel Business Solutions does not guarantee the completion of any project within a precise time frame. Nevertheless, as Excel Business Solutions strives to provide the best service and deliver all projects in a timely manner whenever possible, you, the Customer, acknowledge that unexpected events may occur that could delay delivery and/or affect the final cost of the project.

The preliminary quote is based upon the Customerís initial verbal and written representation of his project to EBS and is subject to change and modification during the developmental process, depending on the changing requirements of the Customer and EBSí workload. Should such modification of the project occur, the Agreement will be deemed to have been amended to allow time for such modification and the price and delivery date to the Customer to have been adjusted accordingly.

This Agreement, constitutes the entire agreement of the parties hereto and supersedes all prior representations, proposals, discussions, and communications, whether oral or in writing.

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Monte Carlo Simulation

A Monte Carlo algorithm is often a numerical Monte Carlo method used to find solutions to mathematical problems (which may have many variables) that cannot easily be solved, for example, by integral calculus, or other numerical methods. For many types of problems, its efficiency relative to other numerical methods increases as the dimension of the problem increases. Or it may be a method for solving other mathematical problems that relies on (pseudo-)random numbers. Monte Carlo methods are useful for modeling phenomena with significant uncertainty in inputs, such as the calculation of risk in business. Monte Carlo methods have also proven efficient in solving coupled integral differential equations of radiation fields and energy transport, and thus these methods have been used in global illumination computations which produce photorealistic images of virtual 3D models, with applications in video games, architecture, design, computer generated films, special effects in cinema, business, economics and other fields. The advantage Monte Carlo methods offer increases as the dimensions of the problem increase.
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