Computer Engineering Commons^™

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 …

Detecting Contaminated Fiber Connectors Using Sfp Optical Power Data, Christopher A. Mendoza

Open Access Theses & Dissertations

Fiber optic technology is an important part of communication networks enabling high-bandwidth transmissions over long and short distances. They do have their fair share of problems though, contamination being the biggest culprit. Contamination of fiber optic connectors can lead to serious performance degradation or even loss of signal. Detecting contaminated fiber connectors can take weeks or even months using traditional practices. There are standard cleanliness practices when dealing with optical connectors but still the problem seems to persist. This work presents an inequality to solve the detection portion of this problem. The proposed inequality uses power readings from the Small …

A New Approach To Multiplanar, Real-Time Simulation Of Physiological Knee Loads And Synthetic Knee Components Augmented By Local Composition Control In Fused Filament Fabrication, Joshua Taylor Green

Open Access Theses & Dissertations

Despite numerous advances in biomedical engineering, few developments in surgical simulation have been made outside of computational models. Cadavers remain the primary media on which surgical research and simulation is conducted. Most attempts to quantify the effects of orthopedic surgical methods fail to achieve statistical significance due to limited quantities of cadaver specimen, large variations among the cadaver population, and a lack of repeatability among measurement techniques. The general purpose of the research covered in this dissertation is to develop repeatable simulation of physiological loads and develop techniques to fabricate a synthetic-based replacement of cadaver specimens. Future work applying this …

Development Of A Desktop Material Extrusion 3d Printer With Wire Embedding Capabilities, Jose Francisco Motta

Open Access Theses & Dissertations

Printed circuit boards (PCB) have been widely used as a permanent solution for generating complex circuitries to power electronic devices. Over the years, PCB boards have proved to be reliable when powering electronic devices. However, when fabricating a printed circuit board, one must outsource to fabricate the boards when in prototype phase. Therefore, the risk of intellectual property theft and long lead time is an issue. The objective of this Thesis is to develop a hybrid multi-tool desktop material extrusion 3D printer that allows for easy integration (modularity) of tools to generate multi-functional 3D printed components.

The addition of an …

An Efficient Method For Online Identification Of Steady State For Multivariate System, Honglun None Xu

Open Access Theses & Dissertations

Most of the existing steady state detection approaches are designed for univariate signals. For multivariate signals, the univariate approach is often applied to each process variable and the system is claimed to be steady once all signals are steady, which is computationally inefficient and also not accurate. The article proposes an efficient online method for multivariate steady state detection. It estimates the covariance matrices using two different approaches, namely, the mean-squared-deviation and mean-squared-successive-difference. To avoid the usage of a moving window, the process means and the two covariance matrices are calculated recursively through exponentially weighted moving average. A likelihood ratio …

Improving Time-Of-Flight And Other Depth Images: Super-Resolution And Denoising Using Variational Methods, Salvador Canales Andrade

Open Access Theses & Dissertations

Depth information is a new important source of perception for machines, which allow them to have a better representation of the surroundings. The depth information provides a more precise map of the location of every object and surfaces in a space of interest in comparison with conventional cameras. Time of flight (ToF) cameras provide one of the techniques to acquire depth maps, however they produce low spatial resolution and noisy maps. This research proposes a framework to enhance and up-scale depth maps by using two different regularization terms: Total Generalized Variation (TGV) and Total Generalized Variation with a Structure Tensor …

The Effect Of Data Marshalling On Computation Offloading Decisions, Julio Alberto Reyes Muñoz

Open Access Theses & Dissertations

Computation offloading consists in allowing resource constrained computers, such as smartphones and other mobile devices, to use the network for the remote execution of resource intensive computing tasks in powerful computers. However, deciding whether to offload or not is not a trivial problem, and it depends in several variables related to the environment conditions, the computing devices involved in the process, and the nature of the task to be remotely executed. Furthermore, it comprises the optimal solution to some questions, like how to partition the application and where to execute the tasks.

The computation offloading decision problem has been widely …

Decision Making For Dynamic Systems Under Uncertainty: Predictions And Parameter Recomputations, Leobardo Valera

Open Access Theses & Dissertations

In this Thesis, we are interested in making decision over a model of a dynamic system. We want to know, on one hand, how the corresponding dynamic phenomenon unfolds under different input parameters (simulations). These simulations might help researchers to design devices with a better performance than the actual ones. On the other hand, we are also interested in predicting the behavior of the dynamic system based on knowledge of the phenomenon in order to prevent undesired outcomes. Finally, this Thesis is concerned with the identification of parameters of dynamic systems that ensure a specific performance or behavior.

Understanding the …

Probabilistic Graphical Models Follow Directly From Maximum Entropy, Anh H. Ly, Francisco Zapata, Olac Fuentes, Vladik Kreinovich

Departmental Technical Reports (CS)

Probabilistic graphical models are a very efficient machine learning technique. However, their only known justification is based on heuristic ideas, ideas that do not explain why exactly these models are empirically successful. It is therefore desirable to come up with a theoretical explanation for these models' empirical efficiency. At present, the only such explanation is that these models naturally emerge if we maximize the relative entropy; however, why the relative entropy should be maximized is not clear. In this paper, we show that these models can also be obtained from a more natural -- and well-justified -- idea of maximizing …

How To Gauge The Accuracy Of Fuzzy Control Recommendations: A Simple Idea, Patricia Melin, Oscar Castillo, Andrzej Pownuk, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Fuzzy control is based on approximate expert information, so its recommendations are also approximate. However, the traditional fuzzy control algorithms do not tell us how accurate are these recommendations. In contrast, for the probabilistic uncertainty, there is a natural measure of accuracy: namely, the standard deviation. In this paper, we show how to extend this idea from the probabilistic to fuzzy uncertainty and thus, to come up with a reasonable way to gauge the accuracy of fuzzy control recommendations.

Normalization-Invariant Fuzzy Logic Operations Explain Empirical Success Of Student Distributions In Describing Measurement Uncertainty, Hamza Alkhatib, Boris Kargoll, Ingo Neumann, Vladik Kreinovich

Departmental Technical Reports (CS)

In engineering practice, usually measurement errors are described by normal distributions. However, in some cases, the distribution is heavy-tailed and thus, not normal. In such situations, empirical evidence shows that the Student distributions are most adequate. The corresponding recommendation -- based on empirical evidence -- is included in the International Organization for Standardization guide. In this paper, we explain this empirical fact by showing that a natural fuzzy-logic-based formalization of commonsense requirements leads exactly to the Student's distributions.

Simplest Polynomial For Which Naive (Straightforward) Interval Computations Cannot Be Exact, Olga Kosheleva, Vladik Kreinovich, Songsak Sriboonchitta

Departmental Technical Reports (CS)

One of the main problem of interval computations is computing the range of a given function over given intervals. It is known that naive interval computations always provide an enclosure for the desired range. Sometimes -- e.g., for single use expressions -- naive interval computations compute the exact range. Sometimes, we do not get the exact range when we apply naive interval computations to the original expression, but we get the exact range if we apply naive interval computations to an equivalent reformulation of the original expression. For some other functions -- including some polynomials -- we do not get …

Structural And Electrical Characterization Of Tin Oxide Resistive Switching, Arka Talukdar

Open Access Theses & Dissertations

Resistive switching in metal oxide is a phenomenon in which the metal oxide changes its resistance upon application of electric field and thus giving two states; high resistance state (HRS) and low resistance state (LRS). Many metal oxides have been investigated however very little is known about unipolar resistive switching in SnO2 though it has shown excellent resistive switching characteristics. Defects in the material play a vital role in resistive switching of the metal oxides. In this work, the role of defects in resistive switching of SnO2 are investigated in Ti/SnO2/Au structures. Two methods were used to control the concentration …

Safety Airway For Small Unmanned Aerial Vehicles Using A Gas Particles Behavior Analogy, Pablo Rangel

Open Access Theses & Dissertations

The United States Federal Aviation Administration (FAA) implemented the Part 107 legislation to allow the flight of Unmanned Aerial Vehicles (UAV) for commercial use (i.e. package deliveries, power transmission line inspections, etc.) in the National Airspace System (NAS). As a consequence of the newly introduced rules, there is an increased risk for accidents involving injured bystanders or damaged to property. The work within this document defines a UAV to UAV safety distance model that acts as a range sensor enabled "elastic bubble". The length of the UAV safety bubble contracts and expands upon changing airway wind speed conditions. It also …

G-Code Generation For Multi-Process 3d Printing, Callum Peter Bailey

Open Access Theses & Dissertations

Since the inception of stereolithography in the 1980s, interest in 3D printing has exploded, with desktop 3D printers now commercially accessible to the general public. In recent years, next-generation multifunctional technologies have been developed, which combine 3D printing with other technologies such as wire embedding, foil embedding, CNC machining, and robotic component placement, enabling complex parts to be made on a single multifunctional machine.

However, the complexity of these integrated processes exceeds the capabilities of established design tools. To this end, this Thesis aims to develop a multi-functional design solution that can automatically generate final control code for next-generation multifunctional …

Adaptive Switched Capacitor Voltage Boost For Thermoelectric Generation, Rene A. Brito

Open Access Theses & Dissertations

Thermoelectric generators (TEG) and other forms of energy harvesting often provide voltages that are not directly usable by traditional electronics as levels are too low from the TEG. While increasing the number of thermoelectric elements can ultimately increase the power output, there is a tradeoff between size and power. By implementing charge pumps, a proposed circuit technique is described that can boost the TEG output to levels that can be used for energy harvesting applications. Current voltage boost circuits for TEGs simply boost a voltage by a set amount. The proposed circuit consists of an analog chip, to provide several …

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 …