A Square Peg in a Round Hole: The Proper Substantial Similarity Test for Nonliteral Aspects of Computer Programs

Since the Third Circuit\u27s decision in Whelan Associates, Inc. v. Jaslow Dental Laboratory, Inc. expanded copyright protection to include the nonliteral aspects of computer programs, courts have struggled to find a way to properly determine substantial similarity between programs, a necessary element of copyright infringement. In the Third Circuit, courts dissect competing programs and compare them in a one-step procedure. The Ninth Circuit uses a two-part process to objectively, and then subjectively, compare program elements. In Computer Associates International, Inc. v. Altai, Inc. the Second Circuit recommended a three-part substantial similarity test to filter out unprotectable elements and compare the remaining core expression. This Comment argues that existing tests are inadequate because they fail to consider programs as a whole and use inappropriate analytical techniques resulting in the loss of protection for nonliteral elements. This Comment proposes the use of a two-tiered substantial similarity test that considers the computer program as an integrated whole and as separate components. This approach would enable courts to fully protect programmers\u27 rights in the original nonliteral aspects of their computer programs

Inverse modeling of soil characteristics from surface soil moisture observations: potential and limitations

International audienceLand surface models (LSM) are widely used as scientific and operational tools to simulate mass and energy fluxes within the soil vegetation atmosphere continuum for numerous applications in meteorology, hydrology or for geobiochemistry studies. A reliable parameterization of these models is important to improve the simulation skills. Soil moisture is a key variable, linking the water and energy fluxes at the land surface. An appropriate parameterisation of soil hydraulic properties is crucial to obtain reliable simulation of soil water content from a LSM scheme. Parameter inversion techniques have been developed for that purpose to infer model parameters from soil moisture measurements at the local scale. On the other hand, remote sensing methods provide a unique opportunity to estimate surface soil moisture content at different spatial scales and with different temporal frequencies and accuracies. The present paper investigates the potential to use surface soil moisture information to infer soil hydraulic characteristics using uncertain observations. Different approaches to retrieve soil characteristics from surface soil moisture observations is evaluated and the impact on the accuracy of the model predictions is quantified. The results indicate that there is in general potential to improve land surface model parameterisations by assimilating surface soil moisture observations. However, a high accuracy in surface soil moisture estimates is required to obtain reliable estimates of soil characteristics