Understanding Terrorist Organizations with a Dynamic Model

Terrorist organizations change over time because of processes such as recruitment and training as well as counter-terrorism (CT) measures, but the effects of these processes are typically studied qualitatively and in separation from each other. Seeking a more quantitative and integrated understanding, we constructed a simple dynamic model where equations describe how these processes change an organization's membership. Analysis of the model yields a number of intuitive as well as novel findings. Most importantly it becomes possible to predict whether counter-terrorism measures would be sufficient to defeat the organization. Furthermore, we can prove in general that an organization would collapse if its strength and its pool of foot soldiers decline simultaneously. In contrast, a simultaneous decline in its strength and its pool of leaders is often insufficient and short-termed. These results and other like them demonstrate the great potential of dynamic models for informing terrorism scholarship and counter-terrorism policy making.Comment: To appear as Springer Lecture Notes in Computer Science v2: vectorized 4 figures, fixed two typos, more detailed bibliograph

Laser speckle effects on hard target differential absorption lidar

Reflection of laser light from a diffuse surface exhibits a complex interference pattern known as laser speckle. Measurement of the reflected intensity from remote targets, common to ``hard-target`` differential absorption lidar (DIAL) requires consideration of the statistical properties of the reflected light. The authors have explored the effects of laser speckle on the noise statistics for CO{sub 2} DIAL. For an ensemble of independent speckle patterns it is predicted that the variance for the measured intensity is inversely proportional to the number of speckle measured. They have used a rotating drum target to obtain a large number of independent speckle and have measured the predicted decrease in the variance after correlations due to system drifts were accounted for. Measurements have been made using both circular and linear polarized light. These measurements show a slight improvement in return signal statistics when circular polarization is used. The authors have conducted experiments at close range to isolate speckle phenomena from other phenomena, such as atmospheric turbulence and platform motion thus allowing them to gain a full understanding of speckle. They have also studied how to remove correlation in the data due to albedo inhomogeneities producing a more statistically independent ensemble of speckle patterns. They find that some types of correlation are difficult to remove from the data

Cross-Correlation Techniques for Determining Absorbed Laser Lines in Remote Sensing

Multi-wavelength differential absorption lidar (DIAL) can be used for remote sensing of atmospheric effluents. If the composition of a remote chemical mixture is known apriori, the wavelengths used by the multi-wavelength lidar can be directly determined via absorption cross sections. Laser lines that are absorbed by a chemical, i.e. “on-lines”, are used along with a few non-absorbed laser lines, i.e. “off-lines”. If a remote chemical mixture is unknown, then measurements are usually made with as many different laser lines as possible to reveal a chemical signature. Only after the return signals at all of these lines are processed, averaged or smoothed, does one have a chance of determining which lines were actually absorbed by the remote chemical species. This can be a lengthy process depending upon the amount of pulse averaging needed to reduce random fluctuations and noise below the level of the chemical absorption signal. Further more, the wavelength variations of the target reflectivity create a fixed spectral pattern which is imposed on the atmospheric chemical absorption spectrum.</jats:p