Physical Sciences and Mathematics Commons^™

A Simple Quantitative Model Of Cognitive Tradeoff Phenomenon, Griselda Acosta, Eric Smith, Vladik Kreinovich

Departmental Technical Reports (CS)

A recent study of chimpanzees has shown that on the individual basis, they are, surprisingly, much better than humans in simple tasks requiring intelligence and memory. A usual explanation -- called cognitive tradeoff -- is that a human brain has sacrificed some of its data processing (computation) abilities in favor of enhancing the ability to communicate; as a result, while individual humans may not be as smart as possible, jointly, we can solve complex problems. A similar cognitive tradeoff phenomenon can be observed in computer clusters: the most efficient computer clusters are not formed from the fastest, most efficient computers, …

Logarithms Are Not Infinity: A Rational Physics-Related Explanation Of The Mysterious Statement By Lev Landau, Francisco Zapata, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Nobel-prize winning physicist Lev Landau liked to emphasize that logarithms are not infinity -- meaning that from the physical viewpoint, logarithms of infinite values are not really infinite. Of course, from a literally mathematical viewpoint, this statement does not make sense: one can easily prove that logarithm of infinity is infinite. However, when a Nobel-prizing physicist makes a statement, you do not want to dismiss it, you want to interpret it. In this paper, we propose a possible physical explanation of this statement. Namely, in physics, nothing is really infinite: according to modern physics, even the Universe is finite in …

Why Grade Distribution Is Often Multi-Modal: An Uncertainty-Based Explanation, Olga Kosheleva, Christian Servin, Vladik Kreinovich

Departmental Technical Reports (CS)

There are many different independent factors that affect student grades. There are many physical situations like this, in which many different independent factors affect a phenomenon, and in most such situations, we encounter normal distribution -- in full accordance with the Central Limit Theorem, which explains that in such situations, distribution should be close to normal. However, the grade distribution is definitely not normal -- it is multi-modal. In this paper, we explain this strange phenomenon, and, moreover, we explain several observed features of this multi-modal distribution.

Optimal Distribution Of Testing Resources Between Different System Levels, Griselda Acosta, Eric Smith, Vladik Kreinovich

Departmental Technical Reports (CS)

When designing a system, we need to perform testing and checking on all levels of the system hierarchy, from the most general system level to the most detailed level. Our resources are limited, so we need to find the best way to allocate these resources, i.e., we need to decide how much efforts to use of each of the levels. In this paper, we formulate this problem in precise terms, and provide a solution to the resulting optimization problem.

Decision Theory Explains "Telescoping Effect" -- That Our Time Perception Is Biased, Laxman Bokati, Vladik Kreinovich

Departmental Technical Reports (CS)

People usually underestimate time passed since distant events, and overestimate time passed since recent events. There are several explanations for this "telescoping effect", but most current explanations utilize specific features of human memory and/or human perception. We show that the telescoping effect can be explained on a much basic level of decision theory, without the need to invoke any specific ways we perceive and process time.

When Revolutions Happen: Algebraic Explanation, Julio Urenda, Vladik Kreinovich

Departmental Technical Reports (CS)

At first glance, it may seem that revolutions happen when life becomes really intolerable. However, historical analysis shows a different story: that revolutions happen not when life becomes intolerable, but when a reasonably prosperous level of living suddenly worsens. This empirical observation seems to contradict traditional decision theory ideas, according to which, in general, people's happiness monotonically depends on their level of living. A more detailed model of human behavior, however, takes into account not only the current level of living, but also future expectations. In this paper, we show that if we properly take these future expectations into account, …

High Concentrations Naturally Lead To Fuzzy-Type Interactions And To Gravitational Wave Bursts, Oscar Galindo, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Fuzzy logic is normally used to describe the uncertainty of human knowledge and human reasoning. Physical phenomena are usually described by probabilistic models. In this paper, we show that in extremal conditions, when the concentrations are very large, some formulas describing physical interactions become fuzzy-type. We also show the observable consequences of such fuzzy-type formulas: they lead to bursts of gravitational waves.

Physics's Need For Interval Uncertainty And How It Explains Why Physical Space Is (At Least) 3-Dimensional, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

One of the fundamental problems of modern physics is the problem of divergence: e.g., when we try to compute the overall energy of the electric field generated by a charged elementary particle, we get a physically meaningless infinite value. In this paper, we show that one way to avoid these infinities is to take into account that measurements are always imprecise -- and thus, we never get the exact values of the physical quantities, only intervals of possible values. We also show that 3-dimensional space is the simplest one in which such interval uncertainty is inevitable. This may explain why …

Computer-Aided Classification Of Impulse Oscillometric Measures Of Respiratory Small Airways Function In Children, Nancy Selene Avila

Open Access Theses & Dissertations

Computer-aided classification of respiratory small airways dysfunction is not an easy task. There is a need to develop more robust classifiers, specifically for children as the classification studies performed to date have the following limitations: 1) they include features derived from tests that are not suitable for children and 2) they cannot distinguish between mild and severe small airway dysfunction.

This Dissertation describes the classification algorithms with high discriminative capacity to distinguish different levels of respiratory small airways function in children (Asthma, Small Airways Impairment, Possible Small Airways Impairment, and Normal lung function). This ability came from innovative feature selection, …

A Bottom-Up Modeling Methodology Using Knowledge Graphs For Composite Metric Development Applied To Traffic Crashes In The State Of Texas, Daniel Michael Mejia

Open Access Theses & Dissertations

Data is a key factor for understanding real-world phenomena. Data can be discovered and integrated from multiple sources and has the potential to be interpreted in a multitude of ways. Traffic crashes, for example, are common events that occur in cities and provide a significant amount of data that has potential to be analyzed and disseminated in a way that can improve mobility of people, and ultimately improve the quality of life. Improving the quality of life of city residents through the use of data and technology is at the core of Smart Cities solutions. Measuring the improvement that Smart …

Towards A More Efficient Representation Of Functions In Quantum And Reversible Computing, Oscar Galindo, Laxman Bokati, Vladik Kreinovich

Departmental Technical Reports (CS)

Many practical problem necessitate faster computations. Simple physical estimates show that the only way to achieve a drastic computation speedup is to use quantum -- or, more generally, reversible -- computing. Thus, we need to be able to transform the existing algorithms into reversible form. Such transformation schemes exist. However, such schemes are not very efficient. Indeed, in general, when we write an algorithm, we composed it of several pre-existing modules. It would be nice to be able to similarly compose a reversible version of our algorithm from reversible version of these moduli -- but the existing transformation schemes cannot …

Time-Reflective Text Representations For Semantic Evolution Tracking And Trend Analytics, Roberto Camacho Barranco

Open Access Theses & Dissertations

The extraction of significant, relevant, and useful trends from massive document collections, such as a streaming newswire or scientific publications, is a challenging and significant problem in many different fields, including intelligence analysis, recommendation systems, and scientific research. However, techniques that tackle trend analytics of such large text corpora are limited because research that addresses the temporal nature of these publications is still in its early stages. In this work, we first show that it is possible to capture the evolution of a story (or trend) by connecting the dots between different documents in a text corpus. The observed results …

Code Smells Quantification: A Case Study On Large Open Source Research Codebase, Swapnil Singh Chauhan

Open Access Theses & Dissertations

Research software has opened up new pathways of discovery in many and diverse disciplines. The research software is developed under unique budgetary and schedule constraints. The developers are often untrained transient workforce of graduate students and postdocs. As a result, the software quality hinders its sustainability beyond the immediate research goals. More importantly, the prevalent reward structures favor contributions in terms of research articles and systematically undervalues research code contributions. As a result, researchers and funding agencies do not allocate appropriate efforts or resources to the development, sustenance, and dissemination of research codebases. At the same time, there are no …

Amplification Vs The Natural Ear: A Test On The Effectiveness Of The Natural Ear On Adults Ability To Match Pitch In Song, Celeste Orozco

Open Access Theses & Dissertations

Background: Singing is a natural enjoyment of life; however, individuals tend to isolate themselves from this enjoyment due to their inability to match pitch accurately. A new technology, the Natural Ear provides altered auditory feedback to the user while singing. It is hypothesized that this feedback may aid in the userâ??s ability to match pitch.

Purpose: The purpose of this study is to compare the effects of the Natural Ear to amplification and no amplification conditions on pitch matching accuracy in song.

Study Design: This study used a complex counterbalance within-subjects design.

Methods: 50 adults from the El Paso Metropolitan …

Dedicated Hardware For Machine/Deep Learning: Domain Specific Architectures, Angel Izael Solis

Open Access Theses & Dissertations

Artificial intelligence has come a very long way from being a mere spectacle on the silver screen in the 1920s [Hml18]. As artificial intelligence continues to evolve, and we begin to develop more sophisticated Artificial Neural Networks, the need for specialized and more efficient machines (less computational strain while maintaining the same performance results) becomes increasingly evident. Though these “new” techniques, such as Multilayer Perceptron’s, Convolutional Neural Networks and Recurrent Neural Networks, may seem as if they are on the cutting edge of technology, many of these ideas are over 60 years old! However, many of these earlier models, at …

A Novel Set Of Weight Initialization Techniques For Deep Learning Architectures, Diego Aguirre

Open Access Theses & Dissertations

The importance of weight initialization when building a deep learning model is often underappreciated. Even though it is usually seen as a minor detail in the model creation cycle, this process has shown to have a strong impact on the training time of a network and the quality of the resulting model. In fact, the implications of choosing a poor initialization scheme range from leading to the creation of a poorly performing model to preventing optimization techniques (like stochastic gradient descent) from converging.

In this work, we introduce and evaluate a set of novel weight initialization techniques for deep learning …