Departmental Technical Reports (CS)Copyright (c) 2022 University of Texas at El Paso All rights reserved.
https://scholarworks.utep.edu/cs_techrep
Recent documents in Departmental Technical Reports (CS)en-usFri, 02 Dec 2022 01:34:18 PST3600Why Color Optical Computing
https://scholarworks.utep.edu/cs_techrep/1774
https://scholarworks.utep.edu/cs_techrep/1774Thu, 01 Dec 2022 12:46:43 PST
In this paper, we show that requirements that computations be fast and noise-resistant naturally lead to what we call color-based optical computing.
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Victor L. Timchenko et al.Hunting Habits of Predatory Birds: Theoretical Explanation of an Empirical Formula
https://scholarworks.utep.edu/cs_techrep/1772
https://scholarworks.utep.edu/cs_techrep/1772Thu, 01 Dec 2022 12:46:42 PST
Predatory birds play an important role in an ecosystem. It is therefore important to study their hunting behavior, in particular, the distribution of their waiting time. A recent empirical study showed that the waiting time is distributed according to the power law. In this paper, we use natural invariance ideas to come up with a theoretical explanation for this empirical dependence.
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Adilene Alaniz et al.Aquatic Ecotoxicology: Theoretical Explanation of Empirical Formulas
https://scholarworks.utep.edu/cs_techrep/1773
https://scholarworks.utep.edu/cs_techrep/1773Thu, 01 Dec 2022 12:46:42 PST
To analyze the effect of pollution on marine life, it is important to know how exactly the concentration of toxic substances decreases with time. There are several semi-empirical formulas that describe this decrease. In this paper, we provide a theoretical explanation for these empirical formulas.
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Demetrius R. Hernandez et al.Dielectric Barrier Discharge (DBD) Thrusters -- Aerospace Engines of the Future: Invariance-Based Analysis
https://scholarworks.utep.edu/cs_techrep/1771
https://scholarworks.utep.edu/cs_techrep/1771Thu, 01 Dec 2022 12:46:41 PST
One of the most prospective aerospace engines is a Dielectric Barrier Discharge (DBD) thruster -- an effective electric engine without moving parts. Originally designed by NASA for flights over other planets, it has been shown to be very promising for Earth-based flights as well. The efficiency of this engine depends on the proper selection of the corresponding electric field. To make this selection, we need to know, in particular, how its thrust depends on the atmospheric pressure. At present, for this dependence, we only know an approximate semi-empirical formula. In this paper, we use natural invariance requirements to come up with a theoretical explanation for this empirical dependence, and to propose a more general family of models that can lead to more accurate description of the DBD thruster's behavior.
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Alexis Lupo et al.Resource Allocation for Multi-Tasking Optimization: Explanation of an Empirical Formula
https://scholarworks.utep.edu/cs_techrep/1770
https://scholarworks.utep.edu/cs_techrep/1770Thu, 01 Dec 2022 12:46:40 PST
For multi-tasking optimization problems, it has been empirically shown that the most effective resource allocation is attained when we assume that the gain of each task logarithmically depends on the computation time allocated to this task. In this paper, we provide a theoretical explanation for this empirical fact.
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Alan Gamez et al.Anomaly Detection in Crowdsourcing: Why Midpoints in Interval-Valued Approach
https://scholarworks.utep.edu/cs_techrep/1769
https://scholarworks.utep.edu/cs_techrep/1769Thu, 01 Dec 2022 12:46:39 PST
In many practical situations -- e.g., when preparing examples for a machine learning algorithm -- we need to label a large number of images or speech recordings. One way to do it is to pay people around the world to perform this labeling; this is known as crowdsourcing. In many cases, crowd-workers generate not only answers, but also their degrees of confidence that the answer is correct. Some crowd-workers cheat: they produce almost random answers without bothering to spend time analyzing the corresponding image. Algorithms have been developed to detect such cheaters. The problem is that many crowd-workers cannot describe their degree of confidence by a single number, they are more comfortable providing an interval of possible degrees. To apply anomaly-detecting algorithms to such interval data, we need to select a single number from each such interval. Empirical studies have shown that the most efficient selection is when we select the arithmetic average. In this paper, we explain this empirical result by showing that arithmetic average is the only selection that satisfies natural invariance requirements.
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Alejandra De La Pena et al.Need for Optimal Distributed Measurement of Cumulative Quantities Explains the Ubiquity of Absolute and Relative Error Components
https://scholarworks.utep.edu/cs_techrep/1768
https://scholarworks.utep.edu/cs_techrep/1768Thu, 01 Dec 2022 12:46:38 PST
In many practical situations, we need to measure the value of a cumulative quantity, i.e., a quantity that is obtained by adding measurement results corresponding to different spatial locations. How can we select the measuring instruments so that the resulting cumulative quantity can be determined with known accuracy -- and, to avoid unnecessary expenses, not more accurately than needed? It turns out that the only case where such an optimal arrangement is possible is when the required accuracy means selecting the upper bounds on absolute and relative error components. This results provides a possible explanation for the ubiquity of such two-component accuracy requirements.
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Hector A. Reyes et al.How to Reach a Joint Decision with the Smallest Need for Compromise
https://scholarworks.utep.edu/cs_techrep/1766
https://scholarworks.utep.edu/cs_techrep/1766Thu, 01 Dec 2022 12:46:37 PST
Usually, people's interests do not match perfectly. So when several people need to make a joint decision, they need to compromise. The more people one has to coordinate the decision with, the fewer chances that each person's preferences will be properly taken into account. Therefore, when a large group of people need to make a decision, it is desirable to make sure that this decision can be reached by dividing all the people into small-size groups so that this decision can reach a compromise between the members of each group. In this paper, we use a recent mathematical result to describe the smallest possible group size for which such a joint decision is always possible.
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Sofia Holguin et al.Word Representation: Theoretical Explanation of an Empirical Fact
https://scholarworks.utep.edu/cs_techrep/1767
https://scholarworks.utep.edu/cs_techrep/1767Thu, 01 Dec 2022 12:46:37 PST
There is a reasonably accurate empirical formula that predicts, for two words i and j, the number Xij of times when the word i will appear in the vicinity of the word j. The parameters of this formula are determined by using the weighted least square approach. Empirically, the predictions are the most accurate if we use the weights proportional to a power of Xij. In this paper, we provide a theoretical explanation for this empirical fact.
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Leonel Escapita et al.Dialogs Re-enacted Across Languages
https://scholarworks.utep.edu/cs_techrep/1765
https://scholarworks.utep.edu/cs_techrep/1765Thu, 01 Dec 2022 12:46:36 PST
To support machine learning of cross-language prosodic mappings and other ways to improve speech-to-speech translation, we present a protocol for collecting closely matched pairs of utterances across languages, a description of the resulting data collection, and some observations and musings. This report is intended for 1) people using this corpus, 2) people extending this corpus, and 3) people designing similar collections of bilingual dialog data.
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Nigel Ward et al.How to Get the Most Accurate Measurement-Based Estimates
https://scholarworks.utep.edu/cs_techrep/1764
https://scholarworks.utep.edu/cs_techrep/1764Fri, 11 Nov 2022 09:12:22 PST
In many practical situations, we want to estimate a quantity y that is difficult -- or even impossible -- to measure directly. In such cases, often, there are easier-to-measure quantities x_{1}, ..., x_{n} that are related to y by a known dependence y = f(x_{1},...,x_{n}). So, to estimate y, we can measure these quantities x_{i} and use the measurement results to estimate y. The two natural questions are: (1) within limited resources, what is the best accuracy with which we can estimate y, and (2) to reach a given accuracy, what amount of resources do we need? In this paper, we provide answers to these two questions.
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Salvador Robles et al.How the Pavement Strength Changes With Time: AI Ideas Help to Explain Semi-Empirical Formulas
https://scholarworks.utep.edu/cs_techrep/1763
https://scholarworks.utep.edu/cs_techrep/1763Fri, 11 Nov 2022 09:12:21 PST
In this paper, we use AI ideas to provide a theoretical explanation for semi-empirical formulas that describe how the pavement strength changes with time, and how we can predict the pavement lifetime.
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Edgar Daniel Rodriguez Velasquez et al.How Hot Is Too Hot
https://scholarworks.utep.edu/cs_techrep/1761
https://scholarworks.utep.edu/cs_techrep/1761Fri, 11 Nov 2022 09:12:20 PST
A recent study has shown that the temperature threshold -- after which even young healthy individuals start feeling the effect of heat on their productivity -- is 30.5 ± 1 C. In this paper, we use decision theory ideas to provide a theoretical explanation for this empirical finding.
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Sofia Holguin et al.Why Seneca Effect?
https://scholarworks.utep.edu/cs_techrep/1762
https://scholarworks.utep.edu/cs_techrep/1762Fri, 11 Nov 2022 09:12:20 PST
Already ancients noticed that decrease is usually faster than growth -- whether we talk about companies or empires. A modern researcher Ugo Bardi confirmed that this phenomenon is still valid today. He called it Seneca effect, after the ancient philosopher Seneca -- one of those who observed this phenomenon. In this paper, we provide a natural explanation for the Seneca effect.
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Sean R. Aguilar et al.What Is the Most Adequate Fuzzy Methodology?
https://scholarworks.utep.edu/cs_techrep/1759
https://scholarworks.utep.edu/cs_techrep/1759Fri, 11 Nov 2022 09:12:19 PST
In practice, there is often a need to describe the relation y = f(x) between two quantities in algorithmic form: e.g., we want to describe the control value y corresponding to the given input x, or we want to predict the future value y based on the current value x. In many such cases, we have expert knowledge about the desired dependence, but experts can only describe their knowledge by using imprecise ("fuzzy") words from a natural language. Methodologies for transforming such knowledge into an algorithm y = f(x) are known as fuzzy methodologies. There exist several fuzzy methodologies, a natural question is: which of them is the most adequate? In this paper, we formulate the natural notion of adequacy: that if the expert rules are formulated based on some function y = f(x), then the methodology should reconstruct this function as accurately as possible. We show that none of the existing fuzzy methodologies is the most adequate in this sense, and we describe a new fuzzy methodology that is the most adequate.
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Noah Velasco et al.A General Commonsense Explanation of Several Medical Results
https://scholarworks.utep.edu/cs_techrep/1760
https://scholarworks.utep.edu/cs_techrep/1760Fri, 11 Nov 2022 09:12:19 PST
In this paper, we show that many recent experimental medical results about the effect of different factors on our health can be explained by common sense ideas.
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Olga Kosheleva et al.Why Five Stages of Solar Activity, Why Five Stages of Grief, Why Seven Plus Minus Two: A General Geometric Explanation
https://scholarworks.utep.edu/cs_techrep/1758
https://scholarworks.utep.edu/cs_techrep/1758Fri, 11 Nov 2022 09:12:18 PST
A recent paper showed that the solar activity cycle has five clear stages, and that taking theses stages into account helps to make accurate predictions of future solar activity. Similar 5-stage models have been effective in many other application area, e.g., in psychology, where a 5-stage model provides an effective description of grief. In this paper, we provide a general geometric explanations of why 5-stage models are often effective. This result also explains other empirical facts, e.g., the seven plus minus two law in psychology and the fact that only five space-time dimensions have found direct physical meaning.
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Miroslav Svitek et al.How to Describe Variety of a Probability Distribution: A Possible Answer to Yager's Question
https://scholarworks.utep.edu/cs_techrep/1757
https://scholarworks.utep.edu/cs_techrep/1757Fri, 11 Nov 2022 09:12:17 PST
Entropy is a natural measure of randomness. It progresses from its smallest possible value 0 -- when we have a deterministic case in which one alternative i occurs with probability 1 (pi = 1), to the largest possible value which is attained at a uniform distribution p1 = ... = pn = 1/n. Intuitively, both in the deterministic case and in the uniform distribution case, there is not much variety in the distribution, while in the intermediate cases, when we have several different values pi, there is a strong variety. Entropy does not seem to capture this notion of variety. In this paper, we discuss how we can describe this intuitive notion.
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Vladik KreinovichSeemingly Counter-Intuitive Features of Good-to-Great Companies Actually Make Perfect Sense: Possible Algorithmics-Based Explanations
https://scholarworks.utep.edu/cs_techrep/1755
https://scholarworks.utep.edu/cs_techrep/1755Fri, 11 Nov 2022 09:12:16 PST
In the late 1990s, researchers analyzed what distinguishes great companies from simply good ones. They found several features that are typical for great companies. Interestingly, most of these features seem counter-intuitive. In this paper, we show that from the algorithmic viewpoint, many of these features make perfect sense. Some of the resulting explanations are simple and straightforward, other explanations rely on complex not-well-publicized results from theoretical computer science.
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Francisco Zapata et al.Why Exponential Almon Lag Works Well in Econometrics: An Invariance-Based Explanation
https://scholarworks.utep.edu/cs_techrep/1754
https://scholarworks.utep.edu/cs_techrep/1754Fri, 11 Nov 2022 09:12:15 PST
In many econometric situations, we can predict future values of relevant quantities by using an empirical formula known as exponential Almon lag. While this formula is empirically successful, there have been no convincing theoretical explanation for this success. In this paper, we provide such a theoretical explanation based on general invariance ideas.
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Laxman Bokati et al.