Computer Engineering Commons^™

Geon: Geophysical Data Add The 3rd Dimension In Geospatial Studies, R. Aldouri, George R. Keller, Ann Q. Gates, J. Rasillo, Leonardo Salayandia, Vladik Kreinovich, John M. Seeley, P. Taylor, S. Holloway

Departmental Technical Reports (CS)

A major trend in GIS is the addition of subsurface information to provide a 3-D perspective on data. Geophysical data provide information about subsurface structures and conditions, but require considerable analysis. The 4-D emphasis with the GEON projects has required the development of many sophisticated tools to allow users to utilize geophysical datasets that will be available on the GEON grid. Our group has created tools that will allow users to search new gravity and magnetic databases of the entire U.S. These tools will extract specific records from an Oracle database, and display the points over a map, grid and …

Computing Higher Central Moments For Interval Data, Vladik Kreinovich, Luc Longpre, Scott Ferson, Lev Ginzburg

Departmental Technical Reports (CS)

Higher central moments are very useful in statistical analysis: the third moment M3 characterizes asymmetry of the corresponding probability distribution, the fourth moment M4 describes the size of the distribution's tails, etc. When we know the exact values x1,...,xn, we can use the known formulas for computing the corresponding sample central moments. In many practical situations, however, we only know intervals [x1],...,[xn] of possible values of xi; in such situations, we want to know the range of possible values of Mm. In this paper, we propose algorithms that compute such ranges.

On-Line Algorithms For Computing Mean And Variance Of Interval Data, And Their Use In Intelligent Systems, Berlin Wu, Hung T. Nguyen, Vladik Kreinovich

Departmental Technical Reports (CS)

No abstract provided.

Application Of Kolmogorov Complexity To Advanced Problems In Mechanics, Vladik Kreinovich, Isaak A. Kunin

Departmental Technical Reports (CS)

In the 1960s, A.N. Kolmogorov described the main reason why a mathematical correct solution to a system of differential equations may be not physically possible: Traditional mathematical analysis tacitly assumes that all numbers, no matter how large or how small, are physically possible. From the engineering viewpoint, however, a number like 10^{10^10} is not possible, because it exceeds the number of particles in the Universe. In this paper, we extend Kolmogorov's ideas from discrete objects to continuous objects known with given accuracy epsilon, and show how this extension can clarify the analysis of dynamical systems.

Using Fft-Based Data Processing Techniques To Characterize Asphaltic Concrete Mixtures, Scott A. Starks, Vladik Kreinovich, Roberto Araiza, Soheil Nazarian, J. Adidhela

Departmental Technical Reports (CS)

A natural way to test the quality of a pavement is to send signals with different frequencies through the pavement and compare the results with the signals passing through an ideal pavement. For this comparison, we must determine how, for the corresponding mixture, the elasticity E depends on the frequency f in the range from 0.1 to 10^5 Hz. It is very expensive to perform measurements in high frequency area (above 20 Hz). To avoid these measurements, we can use the fact that for most of these mixtures, when we change a temperature, the new dependence changes simply by scaling. …

Using 1-D Radar Observations To Detect A Space Explosion Core Among The Explosion Fragments: Sequential And Distributed Algorithms, P. Debroux, J. Boehm, Vladik Kreinovich, Gang Xiang, J. Beck, K. Tupelly, R. Kandathi, Luc Longpre, K. Villaverde

Departmental Technical Reports (CS)

A radar observes the result of a space explosion. Due to radar's low horizontal resolution, we get a 1-D signal s(t) representing different 2-D slices. Based on these slices, we must distinguish between the body at the core of the explosion and the slowly out-moving fragments. We propose new algorithms for processing this 1-D data. Since these algorithms are time-consuming, we also exploit the possibility of parallelizing these algorithms.

Geometry Of Protein Structures. I. Why Hyperbolic Surfaces Are A Good Approximation For Beta-Sheets, Boguslaw Stec, Vladik Kreinovich

Departmental Technical Reports (CS)

Protein structure is invariably connected to protein function. To analyze the structural changes of proteins, we should have a good description of basic geometry of proteins' secondary structure. A beta-sheet is one of important elements of protein secondary structure that is formed by several fragments of the protein that form a surface-like feature. The actual shapes of the beta-sheets can be very complicated, so we would like to approximate them by simpler geometrical shapes from an approximating family. Which family should we choose? Traditionally, hyperbolic (second order) surfaces have been used as a reasonable approximation to the shape of beta-sheets. …

Fuzzy And Probabilistic Models Of Association Information In Sensor Networks, Leon Reznik, Vladik Kreinovich

Departmental Technical Reports (CS)

The paper considers the problem of improving accuracy and reliability of measurement information acquired by sensor networks. It offers the way of integrating sensor measurement results with association information available or a priori derived at aggregation nodes. The models applied for describing both sensor sensor results and association information are reviewed with consideration given to both neuro-fuzzy and probabilistic models and methods. The information sources, typically available in sensor systems, are classified according to the model (fuzzy or probabilistic), which seems more feasible to be applied. The integration problem is formulated as an optimization problem.

Towards A General Methodology For Designing Sub-Noise Measurement Procedures, Roberto Osegueda, George R. Keller, Scott A. Starks, R. Araiza, Dm. Bizyaev, Vladik Kreinovich

Departmental Technical Reports (CS)

In many practical situations, the measurement result z depends not only on the measured value x, but also on the parameters s describing the experiment's setting and on the values of some auxiliary quantities y; the dependence z=f(x,s,y) of z on x, s, and y is usually known. In the ideal case when we know the exact value of the auxiliary parameter y, we can solve the above equation and find the desired value x. In many real-life situations, we only know y with some uncertainty, and this uncertainty leads to additional uncertainty in x.

If we are trying to …

Interval-Valued And Fuzzy-Valued Random Variables: From Computing Sample Variances To Computing Sample Covariances, Jan B. Beck, Vladik Kreinovich, Berlin Wu

Departmental Technical Reports (CS)

Due to measurement uncertainty, often, instead of the actual values xi of the measured quantities, we only know the intervals [xi]=[Xi-Di,Xi+Di], where Xi is the measured value and Di is the upper bound on the measurement error (provided, e.g., by the manufacturer of the measuring instrument). In such situations, instead of the exact value of the sample statistics such as covariance C(x,y), we can only have an interval [C](x,y) of possible values of this statistic. It is known that in general, computing such an interval [C](x,y) for C(x,y) is an NP-hard problem. In this paper, we describe an algorithm that …

Modelling Measurement Processes As Timed Information Processes In Simplex Domains, Gracaliz P. Dimuro, Antonio C. Da Rocha Costa, Vladik Kreinovich

Departmental Technical Reports (CS)

This paper presents a domain-theoretic model for measurements and measuring instruments, by making explicit in simplex-domain structures two important aspects of measurement processes: the notion of standard representation relation, established between the (physical) values that are being measured and the meanings of the readings (semantic values) of the measuring instruments used to measure them, and the time time underlying every measurement process, in a way that it is possible to trace the hostory of every measuring process. We also present the modelling of measurements performed by combined measuring instruments synchrfonized in time. Finally, the domain-theoretic modelling of a sample measuring …

Group-Theoretic Approach As A General Framework For Sensors, Neural Networks, Fuzzy Control, And Genetic Boolean Networks, Hung T. Nguyen, Vladik Kreinovich, Chitta Baral, Valery D. Mazin

Departmental Technical Reports (CS)

When describing a system of interacting genes, a useful approximation is provided by a Boolean network model, in which each gene is either switched on or off - i.e., its state is described by a Boolean variable.

Recent papers by I. Shmulevich et al. show that although in principle, arbitrarily complex Boolean functions are possible, in reality, the corresponding Boolean networks can be well described by Boolean functions from one of the so-called Post classes - classes that are closed under composition. These classes were originally described by E. Post.

It is known that the Boolean model is only an …

Probabilities, Intervals, What Next? Extension Of Interval Computations To Situations With Partial Information About Probabilities, Vladik Kreinovich, Gennady N. Solopchenko, Scott Ferson, Lev Ginzburg, Richard Alo

Departmental Technical Reports (CS)

In many real-life situations, we are interested in the value of a physical quantity y that is difficult or impossible to measure directly. To estimate y, we find some easier-to-measure quantities x1,...,xn which are related to y by a known relation y=f(x1,...,xn). Measurements are never 100% accurate; hence, the measured values Xi are different from xi, and the resulting estimate Y=f(X1,...,Xn) is different from the desired value y=f(x1,...,x_n). How different?

Traditional engineering to error estimation in data processing assumes that we know the probabilities of different measurement error Dxi=Xi-xi.

In many practical situations, we only know the upper bound Di …

Fast Quantum Algorithms For Handling Probabilistic And Interval Uncertainty, Vladik Kreinovich, Luc Longpre

Departmental Technical Reports (CS)

No abstract provided.

On The Use Of Intervals In Scientific Computing: What Is The Best Transition From Linear To Quadratic Approximation?, Martine Ceberio, Vladik Kreinovich, Lev Ginzburg

Departmental Technical Reports (CS)

In many problems from science and engineering, the measurements are reasonably accurate, so we can use linearization (= sensitivity analysis) to describe the effect of measurement errors on the result of data processing. In many practical cases, the measurement accuracy is not so good, so, to get a good estimate of the resulting error, we need to take quadratic terms into consideration - i.e., in effect, approximate the original algorithm by a quadratic function. The problem of estimating the range of a quadratic function is NP-hard, so, in the general case, we can only hope for a good heuristic. Traditional …

Geometric Approach To Detecting And Locating Cracks In Thin Plates By Lamb Wave Reflection: Case Of Moving Transducer, Jose R. Mares, Roberto A. Osegueda, Nagaswaroopa Kaukuri, Vladik Kreinovich

Departmental Technical Reports (CS)

This paper portrays work for the development of a Lamb wave scanning method for the detection of defects in thin plates. The approach requires the generation of an ultrasonic A0 and S0-mode Lamb wave using an incident transmitter excited with a tone burst centered at a near non-dispersive frequency. With a fixed relative separation both transmitter and receiving transducer remotely scan a specific line section of the plate. The arrival time information coming from incident and reflected waves contain information associated with the location of reflection surfaces or potential flaws. The Hilbert-Huang transform is applied to the intrinsic mode functions …

From Intervals To? Towards A General Description Of Validated Uncertainty, Vladik Kreinovich, Gracaliz P. Dimuro, Antonio C. Da Rocha Costa

Departmental Technical Reports (CS)

In many real-life situations, we are interested in the physical quantities that are difficult or even impossible to measure directly. To estimate the value of such quantity y, we measure the values of auxiliary quantities x1,...,xn that are related to y by a known functional relation y=f(x1,...,xn), and we then use the results Xi of measuring xi to find the desired estimate Y=f(X1,..,Xn). Due to measurement errors, the measured values Xi are slightly different from the actual (unknown) values xi; as a result, our estimate Y is different from the actual value y=f(x1,...,xn) of the desired quantity.

When xi and …

Acknowledgment Use With Synthesized And Recorded Prompts, Karen Ward, Tasha Hollingsed, Javier A. Aldaz Salmon

Graduate Student Papers (CS)

Acknowledgments, e.g., “yeah” and “uh-huh,” are ubiquitous in human conversation but are rarer in human-computer interaction. What interface factors might contribute to this difference? Using a simple spoken-language interface that responded to acknowledgments, we compared subjects’ use of acknowledgments when the interface used recorded speech with that seen when the interface used synthesized speech. Contrary to our hypothesis, we saw a drop in the numbers of subjects using acknowledgments: subjects appeared to interpret the recorded-voice interface as signalling a more limited interface. These results were consistent for both Mexican Spanish and American English versions of the interface.

Post-Training Support For Learning Technology, Sam Snoddy Jr., David G. Novick

Departmental Papers (CS)

To examine the effects of post-training support, we studied the introduction of new gradebook software in a public high school. The school's 108 faculty members received training on the software, and approximately half of the faculty received posttraining support for eight weeks. The study measured the faculty's current computer usage, usage of earlier versions of the software, and their perceived skill levels in using the software. The data suggest that the faculty members who received post-training support maintained and raised their skill levels, while unsupported faculty had their skill levels decline.

Assessing Effectiveness Of Personality Style In Documentation, Kenneth Sayles, David G. Novick

Departmental Papers (CS)

This paper extends previous work by other researchers that indicated that users of computers preferred a computer with a personality that was similar to theirs. We conducted a similar experiment, but looking beyond preference to see if the personality of documentation would make a difference in the user’s performance. Our data suggest did not indicate that personality match affects performance; and if such a relationship exists it is likely to be weak. We discuss the related research, describe our methodology, present our results, and describe their implications and limitations.

Minimality Of Solution Update In Conflict Resolution: An Application Of Revision Programming To Von Neumann-Morgenstern Approach, Inna Pivkina, Vladik Kreinovich

Departmental Technical Reports (CS)

In a 1944 book that started game theory (and mathematical approach to conflict resolution), von Neumann and Morgenstern proposed the notion of a solution. When the situation changes, the old solution is often no longer a solution, so it needs to be updated. In practical applications, it is usually desirable to keep the solution change "minimal" in some reasonable sense. We show that for a seemingly straightforward formalization of this minimality, checking whether a change is minimal is NP-hard. We also show that by representing the notion of a solution as a collection of revision rules, we can produce a …

Sensitivity Analysis Of Neural Control, Chin-Wang Tao, Hung T. Nguyen, J. T. Yao, Vladik Kreinovich

Departmental Technical Reports (CS)

We provide explicit formulas that describe how sensitive the resulting signal of a neural network is to the measurement errors with which we measure the inputs.

Real-Time Algorithms For Statistical Analysis Of Interval Data, Berlin Wu, Hung T. Nguyen, Vladik Kreinovich

Departmental Technical Reports (CS)

When we have only interval ranges [xi] of sample values x1,...,xn, what is the interval [V] of possible values for the variance V of these values? There are quadratic time algorithms for computing the exact lower bound V- on the variance of interval data, and for computing V+ under reasonable easily verifiable conditions. The problem is that in real life, we often make additional measurements. In traditional statistics, if we have a new measurement result, we can modify the value of variance in constant time. In contrast, previously known algorithms for processing interval data required that, once a new data …

A New Differential Formalism For Interval-Valued Functions And Its Potential Use In Detecting 1-D Landscape Features, Vladik Kreinovich, Hung T. Nguyen, Gracaliz Pereira Dimuro, Antonio Carlos Da Rocha Costa, Benjamin Rene Callejas Bedregal

Departmental Technical Reports (CS)

In many practical problems, it is important to know the slope (derivative) dy/dx of one quantity y with respect to some other quantity x. For example, different 1-D landscape features can be characterized by different values of the derivative dy/dx, where y is an altitude, and x is a horizontal coordinate. In practice, we often know the values of y(x) for different x with interval uncertainty. How can we then find the set of possible values of the slope? In this paper, we formulate this problem of differentiating interval-values functions in precise terms, and we describe an (asymptotically) optimal algorithm …

Fast Multiplication Of Interval Matrices (Interval Version Of Strassen's Algorithm), Martine Ceberio, Vladik Kreinovich

Departmental Technical Reports (CS)

Strassen's algorithm multiplies two numerical matrices fast, but when applied to interval matrices, leads to excess width. We use Rump's interval arithmetic to propose an interval version of Strassen's algorithm whose only excess width is in second order terms.

Separating Components In Interval-Valued Images, Marilton Sanchotene De Aguiar, Gracaliz Pereira Dimuro, Antonio Carlos Da Rocha Costa, Andrei Finkelstein, Vladik Kreinovich

Departmental Technical Reports (CS)

In many applications of imaging, we would like to know whether we have an image of a single-component object or an image of an object that consists of several components. Many algorithms have been designed to solve this problem; however, these algorithms are all heuristic. Often, according to some reasonable methods, we have a single component, while according to some other equally reasonable methods, the same image have multiple components. It is desirable to produce reliable methods, so that if a method claims that there are multiple components, then it should mean that the observed data is incompatible with the …

Novel Approaches To Numerical Software With Result Verification, Laurent Granvilliers, Vladik Kreinovich, Norbert Mueller

Departmental Technical Reports (CS)

Traditional design of numerical software with result verification is based on the assumption that we know the algorithm f(x_1,...,xn) that transforms input x1,...,xn into the output y=f(x1,...,xn), and we know the intervals of possible values of the inputs. Many real-life problems go beyond this paradigm. In some cases, we do not have an algorithm f, we only know some relation (constraints) between xi and y. In other cases, in addition to knowing the intervals [xi], we may know some relations between xi; we may have some information about the probabilities of different values of xi, and we may know the …

Greedy Algorithms For Optimizing Multivariate Horner Schemes, Martine Ceberio, Vladik Kreinovich

Departmental Technical Reports (CS)

For univariate polynomials f(x1), Horner scheme provides the fastest way to compute the value. For multivariate polynomials, several different version of Horner scheme are possible; it is not clear which of them is optimal. In this paper, we propose a greedy algorithm that will hopefully lead to good computation times.

A univariate Horner scheme has another advantage: if the value x1 is known with uncertainty, and we are interested in the resulting uncertainty in f(x1), then Horner scheme leads to a better estimate for this uncertainty than many other ways of computing f(x1). The second greedy algorithm that we propose …

Interval Approach To Phase Measurements Can Lead To Arbitrarily Complex Sets - A Theorem And Ways Around It, Bharat C. Mulupuru, Vladik Kreinovich, Roberto Osegueda

Departmental Technical Reports (CS)

We are often interested in phases of complex quantities; e.g., in non-destructive testing of aerospace structures, important information comes from phases of Eddy current and magnetic resonance.

For each measurement, we have an upper bound D on the measurement error dx=X-x, so when the measurement result is X, we know that the actual value x is in [X-D,X+D]. Often, we have no information about probabilities of different values, so this interval is our only information about x. When the accuracy is not sufficient, we perform several repeated measurements, and conclude that x belongs to the intersection of the corresponding intervals. …

Interval Arithmetic, Affine Arithmetic, Taylor Series Methods: Why, What Next?, Nedialko S. Nedialkov, Vladik Kreinovich, Scott A. Starks

Departmental Technical Reports (CS)

In interval computations, the range of each intermediate result r is described by an interval [r]. To decrease excess interval width, we can keep some information on how r depends on the input x=(x1,...,xn). There are several successful methods of approximating this dependence; in these methods, the dependence is approximated by linear functions (affine arithmetic) or by general polynomials (Taylor series methods). Why linear functions and polynomials? What other classes can we try? These questions are answered in this paper.