Abstract: The method of the present invention provides a fast, robust, and automated multivariate statistical analysis of gas chromatography/mass spectroscopy (GC/MS) data sets. The method can involve systematic elimination of undesired, saturated peak masses to yield data that follow a linear, additive model. The cleaned data can then be subjected to a combination of PCA and orthogonal factor rotation followed by refinement with MCR-ALS to yield highly interpretable results.

Abstract: Various embodiments are provided for fully digital chaotic differential equation-based systems and methods. In one embodiment, among others, a digital circuit includes digital state registers and one or more digital logic modules configured to obtain a first value from two or more of the digital state registers; determine a second value based upon the obtained first values and a chaotic differential equation; and provide the second value to set a state of one of the plurality of digital state registers. In another embodiment, a digital circuit includes digital state registers, digital logic modules configured to obtain outputs from a subset of the digital shift registers and to provide the input based upon a chaotic differential equation for setting a state of at least one of the subset of digital shift registers, and a digital clock configured to provide a clock signal for operating the digital shift registers.

Abstract: The present invention provides an eigenvalue decomposition apparatus that can perform processing in parallel at high speed and high accuracy.

Abstract: An apparatus for solving a function, such as a mathematical function, may be configured to minimize cost indicators associated with solving the function. Embodiments may be used to compute, in a fast and efficient way, the results of a given mathematical function f(x) and to execute the required operations on the best possible computational elements available within the target platform. Embodiments may exploit a mixture of calculation/evaluation methods that can be implemented on each computational element of the platform in order to approximate the desired function within the desired degree of accuracy and at a low computational cost. Associated methods and computer program products may also be provided.

Abstract: System and method for controlling/analyzing a process by solving a system of linear equations in real-time. Linear equations that model the process are stored. In an off-line stage a partitioning strategy is determined based on the linear equations, including determining groups of values for recursively partitioning a set of values measured and/or computed from the process. In an on-line stage: current process data are received from the process, including measurements from the process, and composing a set of values; the linear equations are recursively solved for a first group of the set, where the first group partitions the set into respective subsets of values, and where the recursively solving produces solved values for respective first groups of the set/subset of values; the linear equations are solved for remaining unsolved values in the set, thereby producing solved values for the set, which are stored and are useable to control/analyze the process.

Abstract: A computer-readable medium includes executable instructions to define a target value, define an achievement boundary range, define specific values for the achievement boundary range, and combine the target value, achievement boundary range, and specific values associated with the achievement boundary range to form an absolute target metric object.

Abstract: A system, method, and computer program product are provided for determining at least one root of an n-dimensional function, utilizing triangulation. In operation, an n-dimensional function is received. Additionally, at least one root of the n-dimensional function is determined utilizing triangulation.

Abstract: Systems, devices, and methods for using an analog processor to solve computational problems. A digital processor is configured to track computational problem processing requests received from a plurality of different users, and to track at least one of a status and a processing cost for each of the computational problem processing requests. An analog processor, for example a quantum processor, is operable to assist in producing one or more solutions to computational problems identified by the computational problem processing requests via a physical evolution.

Abstract: Disclosed is a one-dimensional MFA systolic array for matrix computation using an MFA (modified Faddeeva algorithm), in which downward square MFA array processing and upward square MFA array processing are mapped to a one-dimensional array in horizontal directions, respectively. In each PE in the one-dimensional array, downward and upward MFA matrix calculations for two threads are executed. An input and an output are provided for each of PEs at both ends of the one-dimensional array.

Abstract: A specialized structure measures clock-to-data jitter in an optical memory interface by averaging the result of two second-order estimates of zero crossing using measured signal values on either side of the zero crossing. In one embodiment, a first estimate uses two sample points before the zero crossing and one sample point after while the second estimate uses one sample point before the zero crossing and sample two points after.

Abstract: Method and system for analyzing a linear programming problem or any other problem involving inequalities constraints set relating to multiple variables. An initial feasible region is calculated based on a sub-set of the constraints set. The feasible region is updated based on the additional constraints added one at a time. The method checks for feasibly, identifies active constraints, and provides end-points of the feasible region. The method may be applied to a control system or to a crossbar switch handling routing between multiple input and multiple outputs, such as digital data networking switch used to route TDM digital data streams being packet, frame or cell based, in a LAN, WAN, MAN or Internet application.

Abstract: A first representation of an electrical network includes a first set of simultaneous linear algebraic equations (SLAE's). A second representation of an electrical network includes a second set of SLAE's. The equations of the SLAE's include a number of unknowns and have coefficients for the respective unknowns. A number of the coefficients are expressed in algebraic form. The coefficients of one such equation from one of the sets of SLAE's are for respective elements of the set's respective electrical network and the unknowns are for respective operating properties of the set's respective electrical network. Results are derived in pairs for each unknown of each respective one of the SLAE's. The pairs of results are compared in a specified manner to determine a network equivalence. The results are derived from the SLAE's and expressed in algebraic form, so that the comparing of the pairs of results includes comparing algebraic expressions.

Abstract: A system for solving linear equations comprises a first circuit including a first multiplication module for multiplying a first row of a matrix by a first instance of a vector variable to generate a first product, and a first linear solver module for calculating an updated first element of the vector variable using the first product. A second circuit includes a second multiplication module for multiplying a second row of the matrix by a second instance of the vector variable to generate a second product, and a second linear solver module for calculating an updated second element of the vector variable using the second product. An interface module updates the second instance of the vector variable with the first updated element, and updates the first instance of the vector variable with the second updated element.

Abstract: A method of performing loadflow calculations for controlling voltages and power flow in a power network by reading on-line data of given/specified/scheduled/set network variables/parameters and using control means, so that no component of the power network is overloaded as well as there is no over/under voltage at any nodes in the network following a small or large disturbances. A loadflow calculation method could be any method including invented Patel Decoupled Loadflow (PDL) method, and Decoupled Gauss-Seidel-Patel Loadflow (DGSPL) method. The invented Patel Decoupled Loadflow (PDL) calculation method is characterized in 1) the use of the same coefficient matrix [GB] for both the p-f and q-e sub-problems of the loadflow calculation; 2) almost no effort in the modified mismatch calculations in the iteration process; and 3) all the nodes in both the sub-problems being active, no refactorization of [GB] required for implementation of Q-limit violations.

Abstract: When a Cholesky decomposition or a modified Cholesky decomposition is performed on a sparse symmetric positive definite matrix using a shared memory parallel computer, the discrete space in a problem presented by the linear simultaneous equations expressed by the sparse matrix is recursively sectioned into two sectioned areas and a sectional plane between the areas. The sectioning operation is stopped when the number of nodes configuring the sectional plane reaches the width of a super node. Each time the recursively halving process is performed, a number is sequentially assigned to the node in the sectioned area in order from a farther node from the sectional plane. The node in the sectional plane is numbered after assigning a number to the sectioned area each time the recursively halving process is performed.

Abstract: In computing the overall material constant of a composite material, a virtual composite material is defined as the one that predetermined material components are dispersed in a form of spherical particles in a matrix phase at known volume fractions, and a nonlinear equation having the overall material constant of the virtual composite material as an unknown is prepared. Next, the overall material constant of the composite material is computed by solving the nonlinear equation. The nonlinear equation is a recursive nonlinear equation which is obtained by defining the material constant in the surrounding areas of the spherical particles as the overall material constant of the composite material to be computed. The volume fraction of a material component dispersed in the composite material is computed using the recursive nonlinear equation.

Abstract: According to the preferred embodiments, a system or method is provided that involves the programming of a computer or other processing device with a software, hardware or firmware configured to create a processing tool (i.e., referred to herein as a tool box) that can be configured to provide one or more operational function based on new mathematical principles described herein for the purposes of, e.g., synthesizing or analyzing shapes and the like.

Abstract: Described are software tools and techniques for use in power system operations and control, enabling direct non-iterative solution and estimation of the state of a power system. Knowledge of the state of a power system is essential for secure, reliable and efficient operation of the system. Power system measurement data including the phasor data, as well as power system parameter and topology data are utilized. A set of redundant nonlinear equations, quadratic or third-order in form is formulated. The nonlinear equations are then solved directly for the state of the power grid. The methodology is non-iterative and offers a direct solution that does not depend on initial guess values or convergence of iterations, thus offering a more robust tool for energy management systems and power systems operation and control.

Abstract: A method for evaluating a function of a finite field of characteristic p into itself, for an element x of the field, uses an evaluation, for the element x, of a polynomial formed by a plurality of monomials. The evaluation of the polynomial includes the following steps: determining monomials the degree of which is an integer power of the characteristic p by successive raisings of the element x to the power p; and determining monomials the degree of which is different from an integer power of the characteristic p on the basis of the determined monomials, the degree of which is an integer power of the characteristic p, and by at least one multiplication. An evaluating device is also provided.

Abstract: An input polynomial, in symbolic form, is received, classified, pre-processed, and factored. The input polynomial is classified as a constant, a univariate polynomial, or a multivariate polynomial. Various pre-processing is performed depending on the classification. After the input polynomial is pre-processed, the remaining polynomial is factored using a polynomial factoring algorithm. By pre-processing the input polynomial, the complexity of the polynomial to be factored is reduced, which reduces the computational expense of the polynomial factoring algorithm.

Abstract: An optimization system and method includes determining a best gradient as a sparse direction in a function having a plurality of parameters. The sparse direction includes a direction that maximizes change of the function. This maximum change of the function is determined by performing an optimization process that gives maximum growth subject to a sparsity regularized constraint. An extended Baum Welch (EBW) method can be used to identify the sparse direction. A best step size is determined along the sparse direction by finding magnitudes of entries of direction that maximizes the function restricted to the sparse direction. A solution is recursively refined for the function optimization using a processor and storage media.

Abstract: Circuitry for solving linear matrix equations involving a resultant matrix, an unknown matrix and a product matrix that is a product of the resultant matrix and the unknown matrix includes matrix decomposition circuitry for triangulating an input matrix to create a resultant matrix having a plurality of resultant matrix elements on a diagonal, and having a further plurality of resultant matrix elements arranged in columns below the resultant matrix elements on the diagonal. The matrix decomposition circuitry includes an inverse square root multiplication path that computes diagonal elements of the resultant matrix having an inverse square root module, and the said inverse square root module computes inverses of the diagonal elements to be used in multiplication in place of division by a diagonal element. Latency is hidden by operating on each nth row of a plurality of matrices prior to any (n+1)th row.

Abstract: The method of performing cipher block chaining using elliptic polynomial cryptography allows for the encryption of messages through elliptic polynomial cryptography and, particularly, with the utilization of cipher block chaining based upon both the elliptic polynomial and its twist, regardless of whether the elliptic polynomial and its twist are isomorphic with respect to one another. The method of performing cipher block chaining is based on the elliptic polynomial discrete logarithm problem. It is well known that an elliptic polynomial discrete logarithm problem is a computationally “difficult” or “hard” problem.

Abstract: A method for using a system to compute a solution to a partial differential equation (PDE) broadly comprises the steps of determining the true accuracy required (TAR) to solve the PDE, determining an architecture according to the TAR that performs a plurality of calculations to solve the PDE, determining a time allowed (TA) and a time required (TR) based on the architecture to solve the PDE, rejecting the PDE if the TR is less than or equal to the TA, configuring a plurality of programmable devices with the architecture, initiating the calculations, and ceasing the calculations when an accuracy criteria is met or when the TA expires. The system broadly comprises a plurality of programmable devices, a plurality of storage elements, a device bus, a plurality of printed circuit (PC) boards, and a board to board bus.

Abstract: Similarities between simplex projection with upper bounds and L1 projection are explored. Criteria for a-priori determination of sequence in which various constraints become active are derived, and this sequence is used to develop efficient algorithms for projecting a vector onto the L1-ball while observing box constraints. Three projection methods are presented. The first projection method performs exact projection in O(n2) worst case complexity, where n is the space dimension. Using a novel criteria for ordering constraints, the second projection method has a worst case complexity of O(n log n). The third projection method is a worst case linear time algorithm having O(n) complexity. The upper bounds defined for the projected entries guide the L1-ball projection to more meaningful predictions.

Abstract: A method is given to facilitate discovery of the positive integers which may be the numerator and denominator which form the basis of some universal constants. Solutions are given for both ?, the ratio of the circumference of a circle to its diameter, and ?, the base of the natural logarithm. A short computer code is provided as a simple tool for finding the two integers if they exist. It is suggested that reduction of these integers to the one or more primary numbers of which they are composed might be a useful tool in the quest to find a link between the separate physical models of the universe.

Abstract: A specialized structure measures clock-to-data jitter in an optical memory interface by averaging the result of two second-order estimates of zero crossing using measured signal values on either side of the zero crossing. In one embodiment, a first estimate uses two sample points before the zero crossing and one sample point after while the second estimate uses one sample point before the zero crossing and sample two points after. An existing clock associated with an internal analog-to-digital converter is used to evenly space the samples in time. To simplify the second-order estimate calculations, the three samples of the exemplary embodiment are give x values of ?1, 0, and +1 respectively. Which of the two roots of the second-order estimates is used is based on the slope of the signal at the zero crossing.

Abstract: An approach that efficiently solves for a desired parameter of a system or device that can include both electrically large fast multipole method (FMM) elements, and electrically small QR elements. The system or device is setup as an oct-tree structure that can include regions of both the FMM type and the QR type. An iterative solver is then used to determine a first matrix vector product for any electrically large elements, and a second matrix vector product for any electrically small elements that are included in the structure. These matrix vector products for the electrically large elements and the electrically small elements are combined, and a net delta for a combination of the matrix vector products is determined. The iteration continues until a net delta is obtained that is within predefined limits. The matrix vector products that were last obtained are used to solve for the desired parameter.

Abstract: The problem of aligning multiple liquid chromatography mass spectrometry (LC-MS) runs to a common reference time frame is solved to facilitate comparison among LC-MS runs. The alignment of multiple LCMS can be achieved by solving a sparse system of linear equations to optimally stretch or compress local retention times for maximal similarity among the multiple runs. The multiple LCMS runs can be aligned simultaneously, thereby providing the advantage of efficient use of data by employing a sparse solver. A method of quality control in retention time alignment is also provided.

Abstract: A system and method are provided for a parallel processing of the Hamilton-Jacobi equation.

Abstract: Systems, methods and apparatus for factoring numbers are provided. The factoring may be accomplished by creating a factor graph, mapping the factor graph onto an analog processor, initializing the analog processor to an initial state, evolving the analog processor to a final state, and receiving an output from the analog processor, the output comprising a set of factors of the number. The factoring may be accomplished by generating a logic circuit representation of the factoring problem, such as a multiplication circuit, encoding the logic circuit representation as a discrete optimization problem, and solving the discrete optimization problem using a quantum processor. Output(s) of the logic circuit representation may be clamped such that the solving involves effectively executing the logic circuit representation in reverse to determine input(s) that corresponds to the clamped output(s).

Abstract: A system for evaluating the convergence to a solution for a matrix equation comprises at least one reconfigurable computing device such as a field programmable gate array (FPGA), an update storage element, a conversion element, a summation unit, and a comparator. The FPGA includes a plurality of configurable logic elements and a plurality of configurable storage elements, which are utilized to form the update storage element, the conversion element, the summation unit, and the comparator. The update storage element is configured to store a plurality of updates. The conversion element determines the absolute value of the updates. The summation unit accumulates the absolute values of the updates to produce a total sum, which is compared to a convergence factor by the comparator. Convergence is signaled when the total sum is less than the convergence factor.

Abstract: A system for a conjugate gradient iterative linear solver that calculates the solution to a matrix equation comprises a plurality of gamma processing elements, a plurality of direction vector processing elements, a plurality of x-vector processing elements, an alpha processing element, and a beta processing element. The gamma processing elements may receive an A-matrix and a direction vector, and may calculate a q-vector and a gamma scalar. The direction vector processing elements may receive a beta scalar and a residual vector, and may calculate the direction vector. The x-vector processing elements may receive an alpha scalar, the direction vector, and the q-vector, and may calculate an x-vector and the residual vector. The alpha processing element may receive the gamma scalar and a delta scalar, and may calculate the alpha scalar. The beta processing element may receive the residual vector, and may calculate the delta scalar and the beta scalar.

Abstract: First, calculations to solve a given set of simultaneous linear equations are performed using a conjugate gradient method and it is determined, each time the calculations are iterated, whether or not the calculations diverge. If it is determined that the calculations diverge, the initial value of a variable is set to the minimum value and calculations to solve the set of simultaneous linear equations are performed using a conjugate residual method. This allows the set of simultaneous linear equations to be solved even if it is not known whether or not its coefficient matrix is regular.

Abstract: Methods for increasing the processing speed of computational electromagnetic methods, such as the Method of Moments (MoM), may involve using efficient mapping of algorithms onto a Graphics Processing Unit (GPU) architecture. Various methods may provide speed/complexity improvements to either or both of: (1) direct solution via Lower-Upper (LU) factorization; and (2) iterative methods (e.g., Generalized Minimal Residual (GMRES) method).

Abstract: The Present invention provides a system and method for fast computing the Cholesky factorization of a positive definite matrix. In order to reduce the computation time of matrix factorizations, the present invention uses three atomic components, namely MA atoms, M atoms, and an S atom. The three kinds of components are arranged in a configuration that returns the Cholesky factorization of the input matrix.

Abstract: A method and apparatus for spatio-temporal compressive sensing, which allows accurate reconstruction of missing values in any digital information represented in matrix or tensor form, is disclosed. The method of embodiments comprises three main components: (i) a method for finding sparse, low-rank approximations of the data of interest that account for spatial and temporal properties of the data, (ii) a method for finding a refined approximation that better satisfies the measurement constraints while staying close to the low-rank approximations obtained by SRMF, and (iii) a method for combining global and local interpolation. The approach of embodiments also provides methods to perform common data analysis tasks, such as tomography, prediction, and anomaly detection, in a unified fashion.

Abstract: Non-negative matrix factorization, NMF, is combined with identification of a maximum margin classifier by minimizing a cost function that contains a generative component and the discriminative component. The relative weighting between the generative component and the discriminative component are adjusting during subsequent iterations such that initially, when confidence is low, the generative model is favored. But as the iterations proceed, confidence increases and the weight of the discriminative component is steadily increased until it is of equal weight as the generative model. Preferably, the cost function to be minimized is: min F , G ? 0 ? ? X - FG ? 2 + ? ? ( ? w ? 2 + C ? ? i = 1 n ? L ? ( y i , w · g i + b ) ) .

Abstract: Several full-spectrum imaging techniques have been introduced in recent years that promise to provide rapid and comprehensive chemical characterization of complex samples. One of the remaining obstacles to adopting these techniques for routine use is the difficulty of reducing the vast quantities of raw spectral data to meaningful chemical information. Multivariate factor analysis techniques, such as Principal Component Analysis and Alternating Least Squares-based Multivariate Curve Resolution, have proven effective for extracting the essential chemical information from high dimensional spectral image data sets into a limited number of components that describe the spectral characteristics and spatial distributions of the chemical species comprising the sample. There are many cases, however, in which those constraints are not effective and where alternative approaches may provide new analytical insights.

Abstract: Techniques are generally described for generating an identification number for an integrated circuit (IC). In some examples, methods for generating an identification of an IC may comprise selecting circuit elements of the IC, evaluating measurements of an attribute of the IC for the selected circuit elements, wherein individual measurements are associated with corresponding input vectors previously applied to the IC, solving a plurality of equations formulated based at least in part on the measurements taken of the attribute of the IC for the selected circuit elements to determine scaling factors for the selected circuit elements, and transforming the determined scaling factors for the selected circuit elements to generate an identification number of the IC. Additional variants and embodiments may also be disclosed.

Abstract: A system and method for solving a decision problem having Boolean combinations of linear and non-linear operations includes translating the non-linear real operations using a COordinate Rotation DIgital Computer (CORDIC) method programmed on a computer device into linear operations maintaining a given accuracy. Linear and translated linear operations are combined into a formula. Satisfiablity of the formula is solved using a decision procedure for Boolean combinations of linear operations over integers and reals.

Abstract: Approaches for performing simulation optimization for solving a constrained optimization problem are generally disclosed. One embodiment according to the present disclosure is to formulate a Lagrange equation having incorporated a Lagrange parameter, a first long run average function for an objective associated with the constrained optimization problem, and a second long run average function for a constraint associated with the constrained optimization problem. Then, to identify a parameter value that may lead to an extreme value for the Lagrange equation, in an iterative manner, averages of the first long run average function and the second long run average function are calculated, a gradient of the Lagrange equation is estimated, and the Lagrange parameter is updated.

Abstract: Described is a technology, such as implemented in a computational software program, by which a minimal polynomial is efficiently determined for a radical expression over the ring Z of integer numbers or the ring Q of rational numbers. The levels of the radical are grouped into a level permutation group that is used to find a level permutation set. An annihilation polynomial is found based upon the level permutation set. The annihilation polynomial is factored, and a selection mechanism selects the minimal polynomial based upon the annihilation polynomial's factors.

Abstract: The present invention relates to a solution-finding method, which finds an approximate solution of an equation having difficulty in obtaining an actual solution and a complicated equation in numerical analysis. The method obtains an approximate solution of an equation having a solution in a predetermined interval. Initial values are calculated based on upper and lower limits of the interval. The initial values are applied to a solution-finding equation, including a sign function and the upper and lower limits, and the solution-finding equation is arranged so that a definite integral formula for the sign function is included in the equation. The definite integral formula in the solution-finding equation is calculated using numerical integration, and results of the definite integral formula are applied to the solution-finding equation, thus obtaining an approximate solution. This performance is iterated until the approximate solution satisfies an allowable error.

Abstract: The overall material constant of a composite material is computed where the composite material includes multiple kinds of material components in a matrix phase, each of the material constants of the material components and the matrix phase being known. First, for the composite material, an equation, having the material constant of a virtual composite material as an unknown, is prepared by defining the virtual composite material in which each of the material components is dispersed in a form of spherical particles in the matrix phase at a known volume fractions. Next, the overall material constant of the virtual composite material is found as the overall material constant of the composite material by solving the equation. In this case, the equation is a recursive equation which is obtained using the self-consistent method. The volume fraction of a material component in the composite material is computed using the equation.

Abstract: An industrial production method and corresponding production equipment is specified, wherein, for providing the resources and/or energy needed, a load variation y(t) with time is forecast in an automated manner starting with expected environmental and planned production parameters. In at least one embodiment of this process, a forecast for the load variation y(t) with time is generated by linear interpolation in a manner which is clear for the user from parameter sets (p0, p1, . . . pn) provided with rules (R0, R1, . . . Rn) for allocating a respective load curve (Y0(t), y1(t), . . . yn(t)) for an expected parameter set (z).

Abstract: An apparatus for calculating a result of a scalar multiplication of a reference number with a reference point on an elliptic curve comprises a point selector and a processor. The point selector is configured to select randomly or pseudo-randomly an auxiliary point on the elliptic curve. The processor is configured to calculate the result of the scalar multiplication with a double-and-always-add process using the auxiliary point.

Abstract: A system for solving large-scale matrix equations comprises a plurality of field programmable gate arrays (FPGAs), a plurality of memory elements, a plurality of memory element controllers, and a plurality of processing elements. The FPGAs may include a plurality of configurable logic elements and a plurality of configurable storage elements. The memory elements may be accessible by the FPGAs and may store a matrix and a first vector. The memory element controllers may be formed from configurable logic elements and configurable storage elements and may supply at least a portion of a row of the matrix and at least a portion of the first vector. Each processing element may receive at least the row of the matrix and the first vector and solve an iteration for one element of the first vector.

Abstract: A model, which defines a mathematical problem, and multiple directives may be received. Each of the multiple directives may be mapped to a respective linear solver instance. The linear solver instances may be launched to execute in parallel. Each of the linear solver instances may use either a primal or a dual algorithm and may further use double arithmetic, exact arithmetic, or hybrid arithmetic, as specified by corresponding ones of the multiple directives. A linear solver instance that uses hybrid arithmetic may start by using double arithmetic and may use exact arithmetic after experiencing a numerical difficulty. After the numerical difficulty is resolved, the linear solver instance that uses hybrid arithmetic may restart and continue to solve the mathematical problem using double arithmetic. After one of the linear solver instances finds an optimal solution, others of the linear solver instances may be stopped and a report may be provided.

Abstract: Several full-spectrum imaging techniques have been introduced in recent years that promise to provide rapid and comprehensive chemical characterization of complex samples. One of the remaining obstacles to adopting these techniques for routine use is the difficulty of reducing the vast quantities of raw spectral data to meaningful chemical information. Multivariate factor analysis techniques, such as Principal Component Analysis and Alternating Least Squares-based Multivariate Curve Resolution, have proven effective for extracting the essential chemical information from high dimensional spectral image data sets into a limited number of components that describe the spectral characteristics and spatial distributions of the chemical species comprising the sample. There are many cases, however, in which those constraints are not effective and where alternative approaches may provide new analytical insights.