Crime incidents embedding using restricted Boltzmann machines

We present a new approach for detecting related crime series, by unsupervised learning of the latent feature embeddings from narratives of crime record via the Gaussian-Bernoulli Restricted Boltzmann Machines (RBM). This is a drastically different approach from prior work on crime analysis, which typically considers only time and location and at most category information. After the embedding, related cases are closer to each other in the Euclidean feature space, and the unrelated cases are far apart, which is a good property can enable subsequent analysis such as detection and clustering of related cases. Experiments over several series of related crime incidents hand labeled by the Atlanta Police Department reveal the promise of our embedding methods.Comment: 5 pages, 3 figure

Research and development of a computer program for calculating rotor system dynamic response including foundation and pedestal flexibility effects

Details are presented of the research and development of a computer program for the calculation of Rotor System Dynamic Response including foundation and pedestal flexibility effects. Eight-coefficient bearings are used to permit elliptical orbit rotor motions. The bearings are mounted in massive, damped flexible pedestals, which are themselves mounted upon a foundation structure with distributed mass and stiffness properties. The foundation is in turn, supported on a number of flexible-damped supports. Different foundation properties in the horizontal and vertical directions are included. The results obtained are compared with data by other investigations. Applications of the code are described which validate various aspects of the analysis and the computer program