Abstract: A method for classifying input data includes receiving the input data that describe an object, wherein the input data corresponds to plural classes; associating the input data with voxels that describe the object; calculating a real-number sequence X(n), which is associated with a measured parameter P that describes the object; quantizing the real-number sequence X(n) to generate a finite set sequence Q(n), where n describes a number of levels; generating a voxel-based weight matrix for each class of the input data; and calculating a score S for each class of the plural classes, based on a corresponding voxel-based weight matrix. The score S is a number that indicates a likelihood that the input data associated with a given sample belongs to a class of the plural classes.

Abstract: A method for controlling a direct contact membrane distillation (DCMD) system, the method including modeling the DCMD system with differential-algebraic equations (DAEs), wherein the DAEs include process states {tilde over (x)}(tk) and an input state u(tk); selecting a value for the input variable u(tk) for a time tk; estimating the process states {tilde over (x)}(tk) based on the DAEs and the input state u(tk); checking that a boundedness function G applied to the process states {tilde over (x)}(tk) is smaller than a desired steady-state point ?e; and minimizing an objective function, which depends on the process states {tilde over (x)}(tk) and the input state u(tk), to determine an updated input state u(tk+1) for a next time tk+1. The process states {tilde over (x)}(tk) include temperatures and heat flow rates.

Abstract: A method for classifying input data includes receiving the input data that describe an object, wherein the input data corresponds to plural classes; associating the input data with voxels that describe the object; calculating a real-number sequence X(n), which is associated with a measured parameter P that describes the object; quantizing the real-number sequence X(n) to generate a finite set sequence Q(n), where n describes a number of levels; generating a voxel-based weight matrix for each class of the input data; and calculating a score S for each class of the plural classes, based on a corresponding voxel-based weight matrix. The score S is a number that indicates a likelihood that the input data associated with a given sample belongs to a class of the plural classes.