Abstract: Devices and methods for placing sensors underground are described. A preferred device has a first structure and a second structure that are placed into the ground. A third structure is connected to a portion of the first structure. The second structure is removed from the ground, leaving sensors or other equipment underground.

Abstract: A seismic wave generating device and methods for generating seismic waves having a relatively strong longitudinal energy and a relatively weak transverse energy are disclosed. A device may have a hollow casing and a striking member passing through the hollow casing, the striking member or the hollow casing bearing a spacing member. A method may drive the hollow casing into the earth, then remove earth from within the hollow casing. The method may place a striking member through the hollow casing and may drive the striking member further into the earth to create seismic waves with a relatively strong longitudinal energy and a relatively weak transverse energy.

Abstract: Methods and systems detect objects of interest in a spatio-temporal signal. According to one embodiment, a system processes a digital spatio-temporal input signal containing zero or more foreground objects of interest superimposed on a background. The system comprises a foreground/background separation module, a foreground object grouping module, an object classification module, and a feedback connection. The foreground/background separation module receives the spatio-temporal input signal and, according to one or more adaptable parameters, produces foreground/background labels designating elements of the spatio-temporal input signal as either foreground or background. The foreground object grouping module is connected to the foreground/background separation module and identifies groups of selected foreground-labeled elements as foreground objects. The object classification module is connected to the foreground object grouping module and generates object-level information related to the foreground object.

Abstract: Devices and methods for placing sensors underground are described. A preferred device has a first structure and a second structure that are placed into the ground. A third structure is connected to a portion of the first structure. The second structure is removed from the ground, leaving sensors or other equipment underground.

Abstract: A seismic wave generating device and methods for generating seismic waves having a relatively strong longitudinal energy and a relatively weak transverse energy are disclosed. A device may have a hollow casing and a striking member passing through the hollow casing, the striking member or the hollow casing bearing a spacing member. A method may drive the hollow casing into the earth, then remove earth from within the hollow casing. The method may place a striking member through the hollow casing and may drive the striking member further into the earth to create seismic waves with a relatively strong longitudinal energy and a relatively weak transverse energy.

Abstract: Methods and systems detect objects of interest in a spatio-temporal signal. According to one embodiment, a system processes a digital spatio-temporal input signal containing zero or more foreground objects of interest superimposed on a background. The system comprises a foreground/background separation module, a foreground object grouping module, an object classification module, and a feedback connection. The foreground/background separation module receives the spatio-temporal input signal and, according to one or more adaptable parameters, produces foreground/background labels designating elements of the spatio-temporal input signal as either foreground or background. The foreground object grouping module is connected to the foreground/background separation module and identifies groups of selected foreground-labeled elements as foreground objects. The object classification module is connected to the foreground object grouping module and generates object-level information related to the foreground object.

Abstract: Methods and systems detect objects of interest in a spatio-temporal signal. According to one embodiment, a system processes a digital spatio-temporal input signal containing zero or more foreground objects of interest superimposed on a background. The system comprises a foreground/background separation module, a foreground object grouping module, an object classification module, and a feedback connection. The foreground/background separation module receives the spatio-temporal input signal as an input and, according to one or more adaptable parameters, produces as outputs foreground/background labels designating elements of the spatio-temporal input signal as either foreground or background. The foreground object grouping module is connected to the foreground/background separation module and identifies groups of selected foreground-labeled elements as foreground objects.

Abstract: A method senses electromagnetic energy associated with a source over an area in N frequency bands and generates color image data representing at least a portion of the area. The data are arranged as pixels, and the data for a given pixel comprise chroma, hue, and intensity values. The N frequency bands constitute a mathematical basis in N-dimensional space, and one band establishes a first reference vector in the space. Equal parts of all bands establish a second reference vector. A reference plane contains the first and second reference vectors. The data for the pixel correspond to a point in the space, and that point and the second reference vector define a plane of interest. Hue is an angle between the reference plane and the plane of interest. Chroma is an angle between the point and the second reference vector. Intensity is the point's Euclidean norm.

Abstract: A method senses electromagnetic energy associated with a source over an area in N frequency bands and generates color image data representing at least a portion of the area. The data are arranged as pixels, and the data for a given pixel comprise chroma, hue, and intensity values. The N frequency bands constitute a mathematical basis in N-dimensional space, and one band establishes a first reference vector in the space. Equal parts of all bands establish a second reference vector. A reference plane contains the first and second reference vectors. The data for the pixel correspond to a point in the space, and that point and the second reference vector define a plane of interest. Hue is an angle between the reference plane and the plane of interest. Chroma is an angle between the point and the second reference vector. Intensity is the point's Euclidean norm.

Abstract: An apparatus and method for training a neural network model to classify patterns or to assess the value of decisions associated with patterns by comparing the actual output of the network in response to an input pattern with the desired output for that pattern on the basis of a Risk Differential Learning (RDL) objective function, the results of the comparison governing adjustment of the neural network model's parameters by numerical optimization. The RDL objective function includes one or more terms, each being a risk/benefit/classification figure-of-merit (RBCFM) function, which is a synthetic, monotonically non-decreasing, anti-symmetric/asymmetric, piecewise-differentiable function of a risk differential &dgr;, which is the difference between outputs of the neural network model produced in response to a given input pattern. Each RBCFM function has mathematical attributes such that RDL can make universal guarantees of maximum correctness/profitability and minimum complexity.