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2011

University of Texas at El Paso

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Articles 1 - 30 of 138

Full-Text Articles in Engineering

In The Beginning Was The Word, And The Word Was Fuzzy, Vladik Kreinovich Dec 2011

In The Beginning Was The Word, And The Word Was Fuzzy, Vladik Kreinovich

Departmental Technical Reports (CS)

No abstract provided.


Why Bernstein Polynomials Are Better: Fuzzy-Inspired Justification, Jaime Nava, Olga Kosheleva, Vladik Kreinovich Dec 2011

Why Bernstein Polynomials Are Better: Fuzzy-Inspired Justification, Jaime Nava, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

It is well known that an arbitrary continuous function on a bounded set -- e.g., on an interval [a,b] -- can be, with any given accuracy, approximated by a polynomial. Usually, polynomials are described as linear combinations of monomials. It turns out that in many computational problems, it is more efficient to represent a polynomial as Bernstein polynomials -- e.g., for functions of one variable, a linear combination of terms (x-a)k * (b-x)n-k. In this paper, we provide a simple fuzzy-based explanation of why Bernstein polynomials are often more efficient, and we show how this informal explanation …


Constraint Optimization: From Efficient Computation Of What Can Be Achieved To Efficient Computation Of A Way To Achieve The Corresponding Optimum, Ali Jalal-Kamali, Martine Ceberio, Vladik Kreinovich Dec 2011

Constraint Optimization: From Efficient Computation Of What Can Be Achieved To Efficient Computation Of A Way To Achieve The Corresponding Optimum, Ali Jalal-Kamali, Martine Ceberio, Vladik Kreinovich

Departmental Technical Reports (CS)

In many practically useful cases, we know how to efficiently compute the exact range of a function over given intervals (and, possibly, under additional constraints). In other words, we know how to efficiently compute the minimum and maximum of a given function f(x1, ..., xn) on any box. From the practical viewpoint, it is important not only to find the value of the corresponding maximum or minimum, but also to know for what values of the parameters xi this optimum is attained. We prove a general result: that if we can efficiently compute the optimum, …


Semi-Heuristic Poverty Measures Used By Economists: Justification Motivated By Fuzzy Techniques, Karen Villaverde, Nagwa Albehery, Tonghui Wang, Vladik Kreinovich Dec 2011

Assessment Of Functional Impairment In Human Locomotion: A Fuzzy-Motivated Approach, Murad Alaqtash, Thompson Sarkodie-Gyan, Vladik Kreinovich Dec 2011

Assessment Of Functional Impairment In Human Locomotion: A Fuzzy-Motivated Approach, Murad Alaqtash, Thompson Sarkodie-Gyan, Vladik Kreinovich

Departmental Technical Reports (CS)

Many neurological disorders result in disordered motion. The effects of a disorder can be decrease by an appropriate rehabilitation. To make rehabilitation efficient, we need to monitor the patient and check how well he or she improves. In our previous papers, we proposed a fuzzy-based semi-heuristic method of gauging how well a patient improved. Surprisingly, this semi-heuristic method turned out to be more efficient that we expected. In this paper, we provide a justification for this efficiency.

In the future, it is desirable to combine this fuzzy-assessment approach with results by Alavarez-Alvarez, Trivino, and Cordon who use fuzzy techniques …


Efficient Approximation For Security Games With Interval Uncertainty, Chris Kiekintveld, Vladik Kreinovich Dec 2011

Constraint Problems: Computability Is Equivalent To Continuity, Martine Ceberio, Vladik Kreinovich Nov 2011

Estimating Correlation Under Interval Uncertainty, Ali Jalal-Kamali, Vladik Kreinovich Nov 2011

Estimating Correlation Under Interval Uncertainty, Ali Jalal-Kamali, Vladik Kreinovich

Departmental Technical Reports (CS)

In many engineering situations, we are interested in finding the correlation ρ between different quantities x and y based on the values xi and yi of these quantities measured in different situations i. Measurements are never absolutely accurate; it is therefore necessary to take this inaccuracy into account when estimating the correlation ρ. Sometimes, we know the probabilities of different values of measurement errors, but in many cases, we only know the upper bounds Δxi and Δyi on the corresponding measurement errors. In such situations, after we get the measurement results Xi and Yi …


Visko: Semantic Web Support For Information And Science Visualization, Nicholas Del Rio, Paulo Pinheiro Da Silva Nov 2011

Towards Interval Techniques For Model Validation, Jaime Nava, Vladik Kreinovich Oct 2011

Propagating Range (Uncertainty) And Continuity Information Through Computations: From Real-Valued Intervals To General Sets, Vladik Kreinovich Oct 2011

Propagating Range (Uncertainty) And Continuity Information Through Computations: From Real-Valued Intervals To General Sets, Vladik Kreinovich

Departmental Technical Reports (CS)

One of the main problems of interval computations is to find an enclosure Y that contains the range f(X1, ..., Xn) of a given function f(x1, ..., xn) over given intervals X1, ..., Xn. Most of the techniques for estimating this range are based on propagating the range through computations. Specifically, we follow the computations of f(x1, ..., xn) step-by-step: we start with ranges X1, ..., Xn of the inputs, and then we sequentially compute the enclosures for the ranges of …


No-Free-Lunch Result For Interval And Fuzzy Computing: When Bounds Are Unusually Good, Their Computation Is Unusually Slow, Ildar Batyrshin, Martine Ceberio, Vladik Kreinovich Sep 2011

A Heuristic For Selecting The Cycle Length For Fairio, Sarala Arunagiri, Y. Kwok, Patricia J. Teller, R. A. Portillo, S. Seelam Sep 2011

Extreme Distributions On Intervals, Monchaya Chiangpradit, Wararit Panichkitkosolkul, Hung T. Nguyen, Vladik Kreinovich Sep 2011

Computation In Quantum Space-Time Could Lead To A Super-Polynomial Speedup, Vladik Kreinovich, Michael Zakharevich Aug 2011

Reconstructing An Open Order From Its Closure, With Applications To Space-Time Physics And To Logic, Francisco Zapata, Vladik Kreinovich Aug 2011

How To Tell When A Product Of Two Partially Ordered Spaces Has A Certain Property?, Francisco Zapata, Olga Kosheleva, Karen Villaverde Aug 2011

How To Tell When A Product Of Two Partially Ordered Spaces Has A Certain Property?, Francisco Zapata, Olga Kosheleva, Karen Villaverde

Departmental Technical Reports (CS)

In this paper, we describe how checking whether a givenproperty F is true for a product A1 X A2 of partiallyordered spaces can be reduced to checking several relatedproperties of the original spaces Ai.

This result can be useful in the analysis of propertiesof intervals [a,b] = {x: a <= x <= b}over general partially ordered spaces -- such as the spaceof all vectors with component-wise order or the set of allfunctions with component-wise ordering f <= g <-->for all x (f(x) <= g(x)). When we consider sets of pairs ofsuch objects A1 X A2, it is natural to define the orderon this set in terms of orders in A1 and A2 -- this is, e.g.,how ordering and intervals are defined on the set R2 of all2-D vectors.

This result …


Density-Based Fuzzy Clustering As A First Step To Learning The Rules: Challenges And Possible Solutions, Gözde Ulutagay, Vladik Kreinovich Aug 2011

Linear Neural Networks Revisited: From Pagerank To Family Happiness, Vladik Kreinovich Aug 2011

A Simple Physics-Motivated Equivalent Reformulation Of P=Np That Makes This Equality (Slighty) More Plausible, Jaime Nava, Vladik Kreinovich Aug 2011

A Simple Physics-Motivated Equivalent Reformulation Of P=Np That Makes This Equality (Slighty) More Plausible, Jaime Nava, Vladik Kreinovich

Departmental Technical Reports (CS)

In our opinion, one of the reasons why the problem P=NP? is so difficult is that while there are good intuitive arguments in favor of P=/=NP, there is a lack of intuitive arguments in favor of P=NP. In this paper, we provide such an argument -- based on the fact that in physics, many dependencies are scale-invariant, their expression does not change if we simply change the unit in which we measure the corresponding input quantity (e.g., replace meters by centimeters). It is reasonable to imagine similar behavior for time complexity tA(n) of algorithms A: that the form …


All Kinds Of Behavior Are Possible In Chemical Kinetics: A Theorem And Its Potential Applications To Chemical Computing, Vladik Kreinovich Aug 2011

Efficient Geophysical Technique Of Vertical Line Elements As A Natural Consequence Of General Constraints Techniques, Rolando Cardenas, Martine Ceberio Aug 2011

A New Justification For Weighted Average Aggregation In Fuzzy Techniques, Jaime Nava Aug 2011

A New Justification For Weighted Average Aggregation In Fuzzy Techniques, Jaime Nava

Departmental Technical Reports (CS)

In many practical situations, we need to decide whether a given solution is good enough, based on the degrees ai to which different criteria are satisfied. In this paper, we show that natural requirements lead to the weighted average decision, according to which a solution is acceptable if w1 * a1 + ... + wn * an > t for some weights wi and threshold t.


Prediction In Econometrics: Towards Mathematical Justification Of Simple (And Successful) Heuristics, Vladik Kreinovich, Hung T. Nguyen, Songsak Sriboonchitta Aug 2011

How To Encourage Imperfect Individuals To Care More About Society In General: A Utility-Theory Approach, Vladik Kreinovich Aug 2011

I-Complexity And Discrete Derivative Of Logarithms: A Symmetry-Based Explanation, Vladik Kreinovich, Jaime Nava Aug 2011

I-Complexity And Discrete Derivative Of Logarithms: A Symmetry-Based Explanation, Vladik Kreinovich, Jaime Nava

Departmental Technical Reports (CS)

In many practical applications, it is useful to consider Kolmogorov complexity K(s) of a given string s, i.e., the shortest length of a program that generates this string. Since Kolmogorov complexity is, in general, not computable, it is necessary to use computable approximations K~(s) to K(s). Usually, to describe such an approximations, we take a compression algorithm and use the length of the compressed string as K~(s). This approximation, however, is not perfect: e.g., for most compression algorithms, adding a single bit to the string $s$ can drastically change the value K~(s) -- while …


The Cleanjava Language For Functional Program Verification, Yoonsik Cheon, Cesar Yeep, Melisa Vela Aug 2011

How Accurately Should We Write On The Board? When Marking Comments On Student Papers?, Martine Ceberio, Olga Kosheleva Aug 2011

High-Concentration Chemical Computing Techniques For Solving Hard-To-Solve Problems, And Their Relation To Numerical Optimization, Neural Computing, Reasoning Under Uncertainty, And Freedom Of Choice, Vladik Kreinovich, Olac Fuentes Aug 2011

Theoretical Explanation Of Bernstein Polynomials' Efficiency: They Are Optimal Combination Of Optimal Endpoint-Related Functions, Jaime Nava, Vladik Kreinovich Jul 2011

Theoretical Explanation Of Bernstein Polynomials' Efficiency: They Are Optimal Combination Of Optimal Endpoint-Related Functions, Jaime Nava, Vladik Kreinovich

Departmental Technical Reports (CS)

In many applications of interval computations, it turned out to be beneficial to represent polynomials on a given interval [x-, x+] as linear combinations of Bernstein polynomials (x- x - )k * (x+ - x)n-k. In this paper, we provide a theoretical explanation for this empirical success: namely, we show that under reasonable optimality criteria, Bernstein polynomials can be uniquely determined from the requirement that they are optimal combinations of optimal polynomials corresponding to the interval's endpoints.