Computer Engineering Commons^™

Comparisons Of Measurement Results As Constraints On Accuracies Of Measuring Instruments: When Can We Determine The Accuracies From These Constraints?, Christian Servin, Vladik Kreinovich

Departmental Technical Reports (CS)

For a measuring instrument, a usual way to find the probability distribution of its measurement errors is to compare its results with the results of measuring the same quantity with a much more accurate instrument. But what if we are interested in estimating the measurement accuracy of a state-of-the-art measuring instrument, for which no more accurate instrument is possible? In this paper, we show that while in general, such estimation is not possible; however, can uniquely determine the corresponding probability distributions if we have several state-of-the-art measuring instruments, and for one of them, the corresponding probability distribution is symmetric.

Fuzzy Xor Classes From Quantum Computing, Anderson Ávila, Murilo Schmalfuss, Renata Reiser, Vladik Kreinovich

Departmental Technical Reports (CS)

By making use of quantum parallelism, quantum processes provide parallel modelling for fuzzy connectives and the corresponding computations of quantum states can be simultaneously performed, based on the superposition of membership degrees of an element with respect to the different fuzzy sets. Such description and modelling is mainly focussed on representable fuzzy Xor connectives and their dual constructions. So, via quantum computing not only the interpretation based on traditional quantum circuit is considered, but also the notion of quantum process in the qGM model is applied, proving an evaluation of a corresponding simulation by considering graphical interfaces of the VPE-qGM …

Model Reduction: Why It Is Possible And How It Can Potentially Help To Control Swarms Of Unmanned Arial Vehicles (Uavs), Martine Ceberio, Leobardo Valera, Olga Kosheleva, Rodrigo A. Romero

Departmental Technical Reports (CS)

In many application areas, such as meteorology, traffic control, etc., it is desirable to employ swarms of Unmanned Arial Vehicles (UAVs) to provide us with a good picture of the changing situation and thus, to help us make better predictions (and make better decisions based on these predictions). To avoid duplication, interference, and collisions, UAVs must coordinate their trajectories. As a result, the optimal control of each of these UAVs should depend on the positions and velocities of all others -- which makes the corresponding control problem very complicated. Since, in contrast to controlling a single UAV, the resulting problem …

How To Estimate Expected Shortfall When Probabilities Are Known With Interval Or Fuzzy Uncertainty, Christian Servin, Hung T. Nguyen, Vladik Kreinovich

Departmental Technical Reports (CS)

To gauge the risk corresponding to a possible disaster, it is important to know both the probability of this disaster and the expected damage caused by such potential disaster ("expected shortfall"). Both these measures of risk are easy to estimate in the ideal case, when we know the exact probabilities of different disaster strengths. In practice, however, we usually only have a partial information about these probabilities: we may have an interval (or, more generally, fuzzy) uncertainty about these probabilities. In this paper, we show how to efficiently estimate the expected shortfall under such interval and/or fuzzy uncertainty.

Symbolic Aggregate Approximation (Sax) Under Interval Uncertainty, Chrysostomos D. Stylios, Vladik Kreinovich

Departmental Technical Reports (CS)

In many practical situations, we monitor a system by continuously measuring the corresponding quantities, to make sure that an abnormal deviation is detected as early as possible. Often, we do not have ready algorithms to detect abnormality, so we need to use machine learning techniques. For these techniques to be efficient, we first need to compress the data. One of the most successful methods of data compression is the technique of Symbolic Aggregate approXimation (SAX). While this technique is motivated by measurement uncertainty, it does not explicitly take this uncertainty into account. In this paper, we show that we can …

Optimizing Cloud Use Under Interval Uncertainty, Vladik Kreinovich, Esthela Gallardo

Departmental Technical Reports (CS)

One of the main advantages of cloud computing is that it helps the users to save money: instead of buying a lot of computers to cover all their computations, the user can rent the computation time on the cloud to cover the rare peak spikes of computer need. From this viewpoint, it is important to find the optimal division between in-house and in-the-cloud computations. In this paper, we solve this optimization problem, both in the idealized case when we know the complete information about the costs and the user's need, and in a more realistic situation, when we only know …

Which Bio-Diversity Indices Are Most Adequate, Olga Kosheleva, Craig Tweedie, Vladik Kreinovich

Departmental Technical Reports (CS)

One of the main objectives of ecology is to analyze, maintain, and enhance the bio-diversity of different ecosystems. To be able to do that, we need to gauge bio-diversity. Several semi-heuristic diversity indices have been shown to be in good accordance with the intuitive notion of bio-diversity. In this paper, we provide a theoretical justification for these empirically successful techniques. Specifically, we show that the most widely used techniques -- Simpson index -- can be justified by using simple fuzzy rules, while a more elaborate justification explains all empirically successful diversity indices.

Adding Possibilistic Knowledge To Probabilities Makes Many Problems Algorithmically Decidable, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Many physical theories accurately predict which events are possible and which are not, or -- in situations where probabilistic (e.g., quantum) effects are important -- predict the probabilities of different possible outcomes. At first glance, it may seem that this probabilistic information is all we need. We show, however, that to adequately describe physicists' reasoning, it is important to also take into account additional knowledge -- about what is possible and what is not. We show that this knowledge can be described in terms of possibility theory, and that the presence of this knowledge makes many problems algorithmically decidable.

From 1-D To 2-D Fuzzy: A Proof That Interval-Valued And Complex-Valued Are The Only Distributive Options, Christian Servin, Vladik Kreinovich, Olga Kosheleva

Departmental Technical Reports (CS)

While the usual 1-D fuzzy logic has many successful applications, in some practical cases, it is desirable to come up with a more subtle way of representing expert uncertainty. A natural idea is to add additional information, i.e., to go from 1-D to 2-D (and multi-D) fuzzy logic. At present, there are two main approaches to 2-D fuzzy logic: interval-valued and complex-valued. At first glance, it may seem that many other options are potentially possible. We show, however, that, under certain reasonable conditions, interval-valued and complex-valued are the only two possible options.

Coming Up With A Good Question Is Not Easy: A Proof, Joe Lorkowski, Luc Longpre, Olga Kosheleva, Salem Benferhat

Departmental Technical Reports (CS)

Ability to ask good questions is an important part of learning skills. Coming up with a good question, a question that can really improve one's understanding of the topic, is not easy. In this paper, we prove -- on the example of probabilistic and fuzzy uncertainty -- that the problem of selecting of a good question is indeed hard.

Why It Is Important To Precisiate Goals, Olga Kosheleva, Vladik Kreinovich, Hung T. Nguyen

Departmental Technical Reports (CS)

After Zadeh and Bellman explained how to optimize a function under fuzzy constraints, there have been many successful applications of this optimization. However, in many practical situations, it turns out to be more efficient to precisiate the objective function before performing optimization. In this paper, we provide a possible explanation for this empirical fact.

Setting Up A Highly Configurable, Scalable Nimbus Cloud Test Bed Running On A Manet, Joshua Mckee

Departmental Technical Reports (CS)

No abstract provided.

Simple Linear Interpolation Explains All Usual Choices In Fuzzy Techniques: Membership Functions, T-Norms, T-Conorms, And Defuzzification, Vladik Kreinovich, Jonathan Quijas, Esthela Gallardo, Caio De Sa Lopes, Olga Kosheleva, Shahnaz Shahbazova

Departmental Technical Reports (CS)

Most applications of fuzzy techniques use piece-wise linear (triangular or trapezoid) membership functions, min or product t-norms, max or algebraic sum t-conorms, and centroid defuzzification. Similarly, most applications of interval-valued fuzzy techniques use piecewise-linear lower and upper membership functions. In this paper, we show that all these choices can be explained as applications of simple linear interpolation.

A Natural Simple Model Of Scientists' Strength Leads To Skew-Normal Distribution, Komsan Suriya, Tatcha Sudtasan, Tonghui Wang, Octavio Lerma, Vladik Kreinovich

Departmental Technical Reports (CS)

In many practical situations, we have probability distributions which are close to normal but skewed. Several families of distributions were proposed to describe such phenomena. The most widely used is skew-normal distribution, whose probability density (pdf) is equal to the product of the pdf of a normal distribution and a cumulative distribution function (cdf) of another normal distribution. Out of other possible generalizations of normal distributions, the skew-normal ones were selected because of their computational efficiency, and not because they represent any real-life phenomena. Interestingly, it turns out that these distributions do represent a real-life phenomena: namely, in a natural …

Our Reasoning Is Clearly Fuzzy, So Why Is Crisp Logic So Often Adequate?, Hung T. Nguyen, Berlin Wu, Vladik Kreinovich

Departmental Technical Reports (CS)

Our reasoning is clearly fuzzy, so why is crisp logic so often adequate? We explain this phenomenon by showing that in the presence of noise, an arbitrary continuous (e.g., fuzzy) system can be well described by its discrete analog. However, as the description gets more accurate, the continuous description becomes necessary.

Minimax Portfolio Optimization Under Interval Uncertainty, Meng Yuan, Xu Lin, Junzo Watada, Vladik Kreinovich

Departmental Technical Reports (CS)

In the 1950s, Markowitz proposed to combine different investment instruments to design a portfolio that either maximizes the expected return under constraints on volatility (risk) or minimizes the risk under given expected return. Markowitz's formulas are still widely used in financial practice. However, these formulas assume that we know the exact values of expected return and variance for each instrument, and that we know the exact covariance of every two instruments. In practice, we only know these values with some uncertainty. Often, we only know the bounds of these values -- i.e., in other words, we only know the intervals …

Towards The Possibility Of Objective Interval Uncertainty In Physics. Ii, Luc Longpre, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Applications of interval computations usually assume that while we only know an interval containing the actual (unknown) value of a physical quantity, there is the exact value of this quantity, and that in principle, we can get more and more accurate estimates of this value. Physicists know, however, that, due to uncertainty principle, there are limitations on how accurately we can measure the values of physical quantities. One of the important principles of modern physics is operationalism -- that a physical theory should only use observable properties. This principle is behind most successes of the 20th century physics, starting with …

Fuzzy (And Interval) Techniques In The Age Of Big Data: An Overview With Applications To Environmental Science, Geosciences, Engineering, And Medicine, Vladik Kreinovich, Rujira Ouncharoen

Departmental Technical Reports (CS)

In some practical situations -- e.g., when treating a new illness -- we do not have enough data to make valid statistical conclusions. In such situations, it is necessary to use expert knowledge -- and thus, it is beneficial to use fuzzy techniques that were specifically designed to process such knowledge. At first glance, it may seem that in situations when we have large amounts of data, the relative importance of expert knowledge should decrease. However, somewhat surprisingly, it turns out that expert knowledge is still very useful in the current age of big data. In this paper, we explain …

Wiener-Process-Type Evasive Aircraft Actions Are Indeed Optimal Against Anti-Aircraft Guns: Wiener's Data Revisited, Vladik Kreinovich, Olga Kosheleva

Departmental Technical Reports (CS)

In his 1940s empirical study of evasive aircraft actions, N.~Wiener, the father of cybernetics, founds out that the pilot's actions follow a Wiener-type-process. In this paper, we explain this empirical result by showing that such evasive actions are indeed optimal against the 1940s anti-aircraft guns.

Optimizing Pred(25) Is Np-Hard, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Usually, in data processing, to find the parameters of the models that best fits the data, people use the Least Squares method. One of the advantages of this method is that for linear models, it leads to an easy-to-solve system of linear equations. A limitation of this method is that even a single outlier can ruin the corresponding estimates; thus, more robust methods are needed. In particular, in software engineering, often, a more robust pred(25) method is used, in which we maximize the number of cases in which the model's prediction is within the 25% range of the observations. In …

Constraint Approach To Multi-Objective Optimization, Martine Ceberio, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In many practical situations, we would like to maximize (or minimize) several different criteria, and it is not clear how much weight to assign to each of these criteria. Such situations are ubiquitous and thus, it is important to be able to solve the corresponding multi-objective optimization problems. There exist many heuristic methods for solving such problems. In this paper, we reformulate multi-objective optimization as a constraint satisfaction problem, and we show that this reformulation explains two widely use multi-objective optimization techniques: optimizing a weighted sum of the objective functions and optimizing the product of normalized values of these functions.

Neighbor Discovery In Mobile Ad Hoc Networks, Esau Enrique Ruiz-Gaistardo

Open Access Theses & Dissertations

Neighbor Discovery (ND) is the process that initializes a reliable communication between one-hop neighbors in mobile ad hoc networks (MANETs). This process consists of scheduled exchanges of control messages, called â??Hello Messagesâ?? (HMs) between one-hop neighbors. HMs build bidirectional links that are used to announce the topology information. Each node uses ND and the topology information to populate its routing tables and to communicate with every other node in the network. In MANETs, ND process is a permanent process to discover one-hop neighbors. It is based on two parameters: 1) ND message interval (the period of time in between sending …

Multi-3d System: Advanced Manufacturing Through The Implementation Of Material Handling Robotics, Jose Luis Coronel Jr.

Open Access Theses & Dissertations

Since the rise of additive manufacturing (AM), innovation has been at the forefront. Additive Manufacturing systems that incorporate complex processes are steadily being developed. One example is the Multi3D System, which was designed to integrate the ability to print multi-material parts with that of embedding electronics. To achieve this automated process, the Multi3D incorporates a six-axis robotic arm to transfer a build platform containing a printed part, to various manufacturing stations (two fused deposition modeling (Stratasys, FDM400mc) systems and a computer numerical control router (Techno CNC Router). The robot is a Yaskawa Motoman MH50 chosen for its payload capacity of …

E-Quality Design Of Experiments For Structural Electronics, Oscar Murga

Open Access Theses & Dissertations

Additive Manufacturing (AM) is a technology utilized for creating complex parts by adding layers of material in order to create a three dimensional functional part. This technology has been pushed to a new level of functionality where mechanical parts are combined with electronic components to create Three-Dimensional Structural Electronics (3DSE) systems. This new technology has been used to replace Printed Circuit Boards (PCB), for 3D SE are light weight and can be created in any desired shape. Computer Aided Design (CAD) software is used to design the part and a Fused Deposition Modeling (FDM) machine is used to 3D print …

Re-Examining Resistance: Fan-Produced Queer Readings And Teen Wolf, Joshua J. Espinoza

Open Access Theses & Dissertations

MTV's popular television series, Teen Wolf (2011), has amassed a large online following of fans that create their own queer narratives through fan-fiction, subverting the show's hegemonic heteronormativity. Through a textual thematic analysis of Teen Wolf, this case study illustrates how online fandoms can subvert hegemony through queer readings of literary characters, resisting the dominant heteronormativity on network television. This article argues that rearticulating the showâ??s narratives into queer readings functions as a form of LGBT resistance, effectively counteracting the heteronormativity and hegemony portrayed on screen. This study examines how Teen Wolf approaches queer content, including homoeroticism and LGBT themes …

Low Power Design Techniques For Data Acquisition, Praveen Kumar Palakurthi

Open Access Theses & Dissertations

Semiconductor technology advancement continues to lead to smaller device geometries. Digital circuits have benefited from the technology scaling whereas analog circuits often suffer in terms of performance and noise immunity. As functionality continues to be integrated onto systems-on-chips, analog circuits consume increasingly more power than digital circuits and the objective of this Dissertation is to explore low power techniques in the context of both digital and analog circuits residing on the same silicon real estate.

As natural signals are in analog form, a necessity exists to convert these into digital form and then back again in order to exploit the …

Testing A Power Law Model Of Knowledge Propagation: Case Study Of The Out Of Eden Walk Project, Octavio Lerma, Leobardo Valera, Deana Pennington, Vladik Kreinovich

Departmental Technical Reports (CS)

To improve teaching and learning, it is important to understand how knowledge propagates. In general, when a new piece of knowledge is introduced, people start learning about it. Since the potential audience is limited, after some time, the number of new learners starts to decrease. Traditional models of knowledge propagation are based on differential equations; in these models, the number of new learners decreases exponentially with time. Recently, a new power law model for knowledge propagation was proposed. In this model, the number of learners decreases much slower, as a negative power of time. In this paper, we compare the …

How Design Quality Improves With Increasing Computational Abilities: General Formulas And Case Study Of Aircraft Fuel Efficiency, Joe Lorkowski, Olga Kosheleva, Vladik Kreinovich, Sergei Soloviev

Departmental Technical Reports (CS)

It is known that the problems of optimal design are NP-hard -- meaning that, in general, a feasible algorithm can only produce close-to-optimal designs. The more computations we perform, the better design we can produce. In this paper, we theoretically derive quantitative formulas describing how the design qualities improves with the increasing computational abilities. We then empirically confirm the resulting theoretical formula by applying it to the problem of aircraft fuel efficiency.

Computation Offloading Decisions For Reducing Completion Time, Salvador Melendez

Open Access Theses & Dissertations

Mobile devices are being widely used in many applications such as image processing, computer vision (e.g. face detection and recognition), wearable computing, language translation, and battlefield operations. However, mobile devices are constrained in terms of their battery life, processor performance, storage capacity, and network bandwidth. To overcome these issues, there is an approach called Computation Offloading, also known as cyber-foraging and surrogate computing. Computation offloading consists of migrating computational jobs from a mobile device to more powerful remote computing resources. Upon completion of the job, the results are sent back to the mobile device. However, a decision must be made; …