Gravity investigations do have certain known limitations, the two most prominent perhaps being deep resolution and the non-uniqueness of the solution. We utilized the principle of the physical geometry a two-dimensional dike in the inversion process across tectonic line in the Chubu District, Honshu-in the Japan Alps. The location is probably where the Tsunan-Matsumoto tectonic line interacts with the Itoigawa-Shizuoka Tectonic Line (ISTL). Two-dimensional modeling results consistent with previous works on gravity and reflection and/or refraction prospecting are given to depict the probable sub-surface structure. We conclude that the Bouguer gravity anomaly low to the Southwest or Western side of the tectonic trace is due to thrust of lower density sedimentary rocks deeper into the higher density lower crust to a depth range of approximately 3.5∼4.0 km below the Earth surface.
The scope of this research is computer worm detection. Computer worm has been defined as a process that can cause a possibly evolved copy of it to execute on a remote computer. It does not require human intervention to propagate neither does it attach itself to an existing computer file. It spreads very rapidly. Modern computer worm authors obfuscate the code to make it difficult to detect the computer worm. This research proposes to use machine learning methodology for the detection of computer worms. More specifically, ensembles are used. The research deviates from existing detection approaches by using dark space network traffic attributed to an actual worm attack to train and validate the machine learning algorithms. It is also obtained that the various ensembles perform comparatively well. Each of them is therefore a candidate for the final model. The algorithms also perform just as well as similar studies reported in the literature.
In the recently developed Spatial Reference System that is designed to check and control the accuracy of the three-dimensional coordinate measuring machines and tooling equipment (Metronom US., Inc., Ann Arbor: http://www.metronomus.com), the coordinates of the edges of the instrument are computed from distances of the bars. The use of distances in industrial application is fast gaining momentum just as in Geodesy and in Geophysical applications and thus necessitating efficient algorithms to solve the nonlinear distance equations. Whereas the ranging problem with minimum known stations was considered in our previous contribution in the same Journal, the present contribution extends to the case where one is faced with many distance observations than unknowns (overdetermined case) as is usually the case in practise. Using the Gauss-Jacobi Combinatorial approach, we demonstrate how one can proceed to position without reverting to iterative and linearizing procedures such as Newton's or Least Squares approach.
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