Computer Engineering Commons^™

Towards Optimal Few-Parametric Representation Of Spatial Variation: Geometric Approach And Environmental Applications, Misha Kosheleva, Octavio Lerma, Craig Tweedie

Departmental Technical Reports (CS)

In this paper, we use geometric approach to showthat under reasonable assumption, the spatialvariability of a field f(x), i.e., the expectedvalue F(z)=E[(f(x+z)-f(x))²], has the formF(z)=|Σ g_ij*z_i*z_j|^α.We explain how to find g_ij and αfrom the observations, and how to optimally place sensorsin view of this spatial variability.

Measures Of Deviation (And Dependence) For Heavy-Tailed Distributions And Heir Estimation Under Interval And Fuzzy Uncertainty, Nitaya Buntao, Vladik Kreinovich

Departmental Technical Reports (CS)

Traditionally, in science and engineering, most statistical techniques are based on the assumption that the random variables are normally distributed. For such distributions, a natural characteristic of the "average" value is the mean, and a natural characteristic of the deviation from the average is the variance. However, in many practical situations, e.g., in economics and finance, we encounter probability distributions for which the variance is infinite; such distributions are called heavy-tailed. For such distributions, we describe which characteristics can be used to describe the average and the deviation from the average, and how to estimate these characteristics under interval …

Collaborative And Distributed Algorithms For Localization In Wireless Sensor Networks Based On The Solution Of Spatially Constrained Local And Sub-Local Problems, Juan De Dios Cota

Open Access Theses & Dissertations

In this research we present algorithms for the distributed and collaborative localization of nodes for applications in wireless sensor networks. The algorithms are distributed in the sense that each node can estimate its own position using only range information and position estimates from neighboring nodes. The algorithms aim at achieving good accuracy with low computational complexity and low energy consumption. We consider the full localization process consisting of an initialization stage followed by a refinement stage.

For initialization, we propose a \emph{bilateration} algorithm where each node uses a set of anchors and their respective ranges to solve a set of …

Algorithms For Training Large-Scale Linear Programming Support Vector Regression And Classification, Pablo Rivas Perea

Open Access Theses & Dissertations

The main contribution of this dissertation is the development of a method to train a Support Vector Regression (SVR) model for the large-scale case where the number of training samples supersedes the computational resources. The proposed scheme consists of posing the SVR problem entirely as a Linear Programming (LP) problem and on the development of a sequential optimization method based on variables decomposition, constraints decomposition, and the use of primal-dual interior point methods. Experimental results demonstrate that the proposed approach has comparable performance with other SV-based classifiers. Particularly, experiments demonstrate that as the problem size increases, the sparser the solution …

Software And Hardware Techniques To Aid In Automating And Troubleshooting Hybrid Systems That Fabricate Three-Dimensional Electronics, Mohammed Alawneh

Open Access Theses & Dissertations

Various issues in automating the fabrication of three dimensional electronics were addressed in this thesis. The three dimensional electronics were fabricated by a stereolithoraphy and direct print hybrid system. Hardware and software limitations were discussed and possible solutions were implemented. Various automation software tools were developed, specifically a computer aided design to printed electronics conversion software compatible with various stages.

Effects Of The Usage Of Parallel Hardware Architectures In The Simulation Of Artificial Neural Networks Training Process, Carlos Beas

Open Access Theses & Dissertations

Long training times and non-ideal performance have been a big impediment in further continuing the use of Artificial Neural Networks for real world applications. Current research is currently focused on two areas of study that aim to address this problem. The first approach seeks to overcome large training times by devising faster learning algorithms where a set of interconnection weights for which the network produces negligible error takes a less amount of computation to find [Sun98]. The second approach aims to address the impediment by implementing existing training algorithms but on parallel hardware architectures.

While both approaches provide promising advances …

2d Gaussian Object Motion Detection, Miguel Angel Chaidez

Open Access Theses & Dissertations

Dr. John Moya, and associated research assistants, have previously created an image-change recognition algorithm (JESSE) to mark changes within an image. The focus of this thesis is to present a physical application and modification of this algorithm in order to detect a surgeon's hand and verify chip placement on a printed circuit board.

There are different techniques in implementing visual recognition and motion detection with smart systems but the high cost and complicated calibration of these systems make them impractical. The goal was to create a system that is simple, inexpensive and applicable to multiple applications that will allow the …

Development Of Load Balancing Algorithm Based On Analysis Of Multi-Core Architecture On Beowulf Cluster, Damian Valles

Open Access Theses & Dissertations

In this work, analysis, and modeling were employed to improve the Linux Scheduler for HPC use. The performance throughput of a single compute-node of the 23 node Beowulf cluster, Virgo 2.0, was analyzed to find bottlenecks and limitations that affected performance in the processing hardware where each compute-node consisted of two quad-core processors with eight gigabytes of memory. The analysis was performed using the High Performance Linpack (HPL) benchmark.

In addition, the processing hardware of the compute-node was modeled using an Instruction per Cycle (IPC) metric that was estimated using linear regression. Modeling data was obtained by using the Tuning …

Utepcam: A Scalable Wireless Vision Sensor Architecture For Computational, Power And Bandwidth Constrained Scenarios, Ricardo Zepeda

Open Access Theses & Dissertations

UTEPcam is a low cost and power vision sensor node system. UTEPcam is composed of an Atmel atmega32 8-bit microcontroller, a CY7C09099V static RAM chip, an OV6620 CMOS image sensor, a XBEE transceiver and a SD Flash memory card, and four logic gates. UTEPcam's simple yet efficiently architecture enables it to capture video at one frame per second. At its absolute highest, it is estimated that UTEPcam consumes only 1.321 Amps. When in standby, UTEPcam consumes 21 microamps. Furthermore, UTEPcam's program takes up only 1Kbyte of memory space.

UTEPcam's CPU, a simple 8-bit MCU, is unlike most vision sensor node …

Estimating Mean Under Interval Uncertainty And Variance Constraint, Ali Jalal-Kamali, Luc Longpre, Misha Kosheleva

Departmental Technical Reports (CS)

Universal Approximation With Uninorm-Based Fuzzy Neural Networks, Andre Lemos, Vladik Kreinovich, Walmir Caminhas, Fernando Gomide

Departmental Technical Reports (CS)

Fuzzy neural networks are hybrid models capable to approximate functions with high precision and to generate transparent models, enabling the extraction of valuable information from the resulting topology. In this paper we will show that the recently proposed fuzzy neural network based on weighted uninorms aggregations uniformly approximates any real functions on any compact set. We will describe the network topology and inference mechanism and show that the universal approximation property of this network is valid for a given choice of operators.

Testing Shock Absorbers: Towards A Faster Parallelizable Algorithm, Christian Servin

Departmental Technical Reports (CS)

Cars are equipped with shock absorbers, which are designed to smooth out the shocks on the road. In practice, there is a need to test them. To test the shock absorbers, we need to estimate the values of the shock absorber's parameters. If we did not have any measurement errors, then two measurements would be sufficient to determine the parameters. However, in reality, there are measurement errors. Usually, in engineering practice, it is assumed that the errors are normally distributed with 0 mean, so we can use least squares method to test it. In practice, we often only know the …

Fundamental Physical Equations Can Be Derived By Applying Fuzzy Methodology To Informal Physical Ideas, Eric Gutierrez, Vladik Kreinovich

Departmental Technical Reports (CS)

Fuzzy methodology transforms expert ideas -- formulated in terms of words from natural language -- into precise rules and formulas. In this paper, we show that by applying this methodology to intuitive physical ideas, we can get fundamental physical equations. This fact provides an additional justification for the fuzzy methodology.

From Single To Double Use Expressions, With Applications To Parametric Interval Linear Systems: On Computational Complexity Of Fuzzy And Interval Computations, Joseph A Lorkowski

Departmental Technical Reports (CS)

In many practical problems, we need to estimate the range of a given expression f(x1, ..., xn) when each input xi belongs to a known interval [xi] -- or when each input xi is described by a known fuzzy set. It is known that this problem is easy to solve when we have a Single Use Expression, i.e., an expression in which each variable xi occurs only once. In this paper, we show that for similarly defined Double Use Expressions, the corresponding range estimation problem is NP-hard. Similar problems are analyzed for the problem of solving linear systems under interval …

Reducing Over-Conservative Expert Failure Rate Estimates In The Presence Of Limited Data: A New Probabilistic/Fuzzy Approach, Carlos M. Ferregut, F. Joshua Campos, Vladik Kreinovich

Departmental Technical Reports (CS)

Unique highly reliable components are typical for aerospace industry. For such components, due to their high reliability and uniqueness, we do not have enough empirical data to make statistically reliable estimates about their failure rate. To overcome this limitation, the empirical data is usually supplemented with expert estimates for the failure rate. The problem is that experts tend to be -- especially in aerospace industry -- over-cautious, over-conservative; their estimates for the failure rate are usually much higher than the actual observed failure rate. In this paper, we provide a new fuzzy-related statistically justified approach for reducing this over-estimation.

Least Sensitive (Most Robust) Fuzzy "Exclusive Or" Operations, Jesus E. Hernandez, Jaime Nava

Departmental Technical Reports (CS)

In natural language, "or" sometimes means "inclusive or" and sometimes means "exclusive or". To adequately describe commonsense and expert knowledge, it is therefore important to have not only t-conorms describing fuzzy "inclusive or" operations, but also fuzzy "exclusive or" operations f(a,b). Since the degrees of certainty are only approximately defined, it is reasonable to require that the corresponding operation be the least sensitive to small changes in the inputs. In this paper, we show that the least sensitive fuzzy "exclusive or" operation has the form f(a,b)=min(max(a,b),max(1-a,1-b)).

Adding Constraints -- A (Seemingly Counterintuitive But) Useful Heuristic In Solving Difficult Problems, Olga Kosheleva, Martine Ceberio, Vladik Kreinovich

Departmental Technical Reports (CS)

Intuitively, the more constraints we impose on a problem, the more difficult it is to solve it. However, in practice, difficult-to-solve problems sometimes get solved when we impose additional constraints and thus, make the problems seemingly more complex. In this methodological paper, we explain this seemingly counter-intuitive phenomenon, and we show that, dues to this explanation, additional constraints can serve as a useful heuristic in solving difficult problems.

Mamdani Approach To Fuzzy Control, Logical Approach, What Else?, Samuel Bravo, Jaime Nava

Departmental Technical Reports (CS)

In fuzzy control, two approaches are mainly used: Mamdani's approach, in which we represent the knowledge base as a disjunction of statements Ai(x) & Bi(u) corresponding to individual rules, and logical approach, in which the knowledge base is represented as a conjunction of the rules themselves Ai(x) --> Bi(u). Both approaches are known not to be perfect, so a natural question arises: what other approaches are possible? In this paper, we describe all possible approaches; alternative approaches use an "exclusive or" operation and correspond, e.g., to the fuzzy transform idea.

From Program Synthesis To Optimal Program Synthesis, Joaquin Reyna

Departmental Technical Reports (CS)

Fusing Continuous And Discrete Data, On The Example Of Merging Seismic And Gravity Models In Geophysics, Omar Ochoa, Aaron Velasco, Vladik Kreinovich

Departmental Technical Reports (CS)

Towards Optimal Placement Of Bio-Weapon Detectors, Chris Kiekintveld, Octavio Lerma

Departmental Technical Reports (CS)

Biological weapons are difficult and expensive to detect. Within a limited budget, we can afford a limited number of bio-weapon detector stations. It is therefore important to find the optimal locations for such stations. A natural idea is to place more detectors in the areas with more population -- and fewer in desert areas, with fewer people. However, such a commonsense analysis does not tell us how many detectors to place where. To decide on the exact placement of bio-weapon detectors, we formulate the placement problem in precise terms, and come up with an (almost) explicit solution to the resulting …

How To Tell When A Product Of Two Partially Ordered Spaces Has A Certain Property: General Results With Application To Fuzzy Logic, Francisco Zapata, Olga Kosheleva, Karen Villaverde

Departmental Technical Reports (CS)

Towards Optimal Sensor Placement In Multi-Zone Measurements, Octavio Lerma, Craig Tweedie, Vladik Kreinovich

Departmental Technical Reports (CS)

In multi-zone areas, where the boundaries change with time, it is desirable to place sensors in such a way that the boundary is covered at all times. In this paper, we describe the optimal sensor placement with this property. In this optimal placement, sensors are placed along a see-saw trajectory going between the current location of the boundary and its farthest future location.

Computing The Range Of Variance-To-Mean Ratio Under Interval And Fuzzy Uncertainty, Sio-Long Lo, Gang Xiang

Departmental Technical Reports (CS)

In many practical problems such as radar imaging, it is useful to compute the variance-to-mean ratio. The need is important because for the sum of k identical independent signal components, both the variance and the mean are multiplied by k, so this ratio is independent on k and thus, provides useful information about the components. In practice, we only know the samples values with uncertainty. It is therefore necessary to compute the variance-to-mean ratio under this uncertainty. In this paper, we present efficient algorithms for computing this ratio under interval and fuzzy uncertainty.

Towards Chemical Applications Of Dempster-Shafer-Type Approach: Case Of Variant Ligands, Jaime Nava

Departmental Technical Reports (CS)

Why Curvature In L-Curve: Combining Soft Constraints, Uram Anibal Sosa Aguirre, Martine Ceberio, Vladik Kreinovich

Departmental Technical Reports (CS)

In solving inverse problems, one of the successful methods of determining the appropriate value of the regularization parameter is the L-curve method of combining the corresponding soft constraints, when we plot the curve describing the dependence of the logarithm $x$ of the mean square difference on the logarithm $y$ of the mean square non-smoothness, and select a point on this curve at which the curvature is the largest. This method is empirically successful, but from the theoretical viewpoint, it is not clear why we should use curvature and not some other criterion. In this paper, we show that reasonable scale-invariance …

How To Bargain: An Interval Approach, Vladik Kreinovich, Hung T. Nguyen, Songsak Sriboonchitta

Departmental Technical Reports (CS)

Why L2 Topology In Quantum Physics, Chris Culellar, Evan Longpre, Vladik Kreinovich

Departmental Technical Reports (CS)

It is known that in quantum mechanics, the set S of all possible states coincides with the set of all the complex-valued functions f(x) for which the integral of |f(x)|² is 1. From the mathematical viewpoint, this set is a unit sphere in the space L² of all the functions for which this integralis finite. Because of this mathematical fact, usually the set S is considered with the topology induced by L², i.e., topology in which the basis of open neighborhood of a state f is formed by the open balls. This topology seem to work …

Cleanjava: A Formal Notation For Functional Program Verification, Yoonsik Cheon, Cesar Yeep, Melisa Vela

Departmental Technical Reports (CS)

Unlike a Hoare-style program verification, a functional program verification supports forward reasoning by viewing a program as a mathematical function from one program state to another and proving its correctness by essentially comparing two mathematical functions, the function computed by the program and its specification. Since it requires a minimal mathematical background and reflects the way programmers reason about the correctness of a program informally, it can be taught and practiced effectively. However, there is no formal notation supporting the functional program verification. In this paper, we propose a formal notation for writing functional program specifications for Java programs. The …

Power Vs. Performance Evaluation Of Synthetic Aperture Radar Image-Formation Algorithms And Implementations For Embedded Hec Environments (Ongoing Study), Ricardo Portillo, Sarala Arunagiri, Patricia J. Teller

Departmental Technical Reports (CS)

The continuing miniaturization and parallelization of processing hardware has facilitated the development of mobile and field-deployable systems that can accommodate terascale processing within once prohibitively small size and weight constraints. Unfortunately, the added computational capability of these small systems often comes at the cost of larger power demands, an already strained resource in these embedded systems. This study explores the power issues in a specific type of field-deployable system, Mobile Radar. Specifically, we focus on a computationally intensive phase of Synthetic Aperture Radar, Image Formation (IF), and evaluate performance tradeoffs in terms of time-to-solution, output image quality, and power consumption …