Physical Sciences and Mathematics Commons^™

Esterification Pretreatment Of Free Fatty Acid In Biodiesel Production, From Laboratory To Industry, Ming Chai, Qingshi Tu, Jeffrey Y. Yang, Mingming Lu

United States Environmental Protection Agency: Publications

In the United States, biodiesel producers usually follow the 19.8:1 methanol-to-FFA molar ratio for free fatty acid (FFA) esterification, as suggested by the National Renewable Energy Laboratory (NREL) without optimization studies. In this paper, both laboratory studies and industrial practices of the esterification process were compared, and an optimization study of a used vegetable oil with 5% FFA was conducted. The optimal conditions of this oil, i.e., methanol-to-FFA molar ratio of 40:1, and sulfuric acid usage of 10%, fell out of the suggested range of 19.8:1. The activation energy of the esterification reaction is 20.7 kJ/mol at the optimized condition …

Performance Modeling And Optimization Techniques For Heterogeneous Computing, Supada Laosooksathit

Doctoral Dissertations

Since Graphics Processing Units (CPUs) have increasingly gained popularity amoung non-graphic and computational applications, known as General-Purpose computation on GPU (GPGPU), CPUs have been deployed in many clusters, including the world's fastest supercomputer. However, to make the most efficiency from a GPU system, one should consider both performance and reliability of the system.

This dissertation makes four major contributions. First, the two-level checkpoint/restart protocol that aims to reduce the checkpoint and recovery costs with a latency hiding strategy in a system between a CPU (Central Processing Unit) and a GPU is proposed. The experimental results and analysis reveals some benefits, …

A Reduced Probabilistic Neural Network For The Classification Of Large Databases, Abdelhadi Lotfi, Abdelkader Benyettou

Turkish Journal of Electrical Engineering and Computer Sciences

The probabilistic neural network (PNN) is a special type of radial basis neural network used mainly for classification problems. Due to the size of the network after training, this type of network is usually used for problems with a small-sized training dataset. In this paper, a new training algorithm is presented for use with large training databases. Application to the handwritten digit database shows that the reduced PNN performs better than the standard PNN for all of the studied cases with a big gain in size and processing speed. This new type of neural network can be used easily for …

Optimization Of Job Shop Scheduling Problems Using Modified Clonal Selection Algorithm, Yilmaz Atay, Hali̇fe Kodaz

Turkish Journal of Electrical Engineering and Computer Sciences

Artificial immune systems (AISs) are one of the artificial intelligence techniques studied a lot in recent years. AISs are based on the principles and mechanisms of the natural immune system. In this study, the clonal selection algorithm, which is used commonly in AISs, is modified. This algorithm is applied to job shop scheduling problems, which are one of the most difficult optimization problems. For applying application results to the optimum solution, parameter values giving the optimum solution are determined by analyzing the parameters in the algorithm. The obtained results are given in detail in the tables and figures. The best …

Extremum-Seeking For Nonlinear Discrete-Time Systems With Application To Hcci Engines, H. Zargarzadeh, S. Jagannathan, J. A. Drallmeier

Electrical and Computer Engineering Faculty Research & Creative Works

For many control applications, identifying an optimal operating point by maximizing/minimizing a performance function is important. This paper applies the extremum-seeking method to nonaffine, nonlinear discrete-time systems stabilized by an optimal adaptive controller. First, a novel averaging method is used for the nonlinear discrete-time systems to show that their output unique extrema are stable equilibrium points. Then, a singular perturbation method in discrete time is employed to show that the overall closed loop system will dynamically converge to the extremum. The applicability of this scheme is numerically verified on a Homogeneous Charge Compression Ignition (HCCI) model validated experimentally and expressed …

Reformulations For Control Systems And Optimization Problems With Impulses, Jacob Blanton

LSU Doctoral Dissertations

This dissertation studies two different techniques for analyzing control systems whose dynamics include impulses, or more specifically, are measure-driven. In such systems, the state trajectories will have discontinuities corresponding to the atoms of the Borel measure driving the dynamics, and these discontinuities require further definition in order for the control system to be treated with the broad range of results available to non-impulsive systems. Both techniques considered involve a reparameterization of the system variables including state, time, and controls. The first method is that of the graph completion, which provides an explicit reparameterization of the time and state variables. The …

Contributions To Global Optimization Using Interval Methods And Speculation, Angel Fernando Garcia Contreras

Open Access Theses & Dissertations

Most electronic devices we are familiar with, such as cell phones and computers, are small and require similarly small electronic components arranged and connected in small areas. Finding the right size and arrangement of the components inside a device can be a challenge. The manufacturing process of the components limits their possible size, some components have specific needs to operate at a certain speed, and the total area of the device is also limited. In portable devices, these designs have one important objective: that the entire device consumes the minimum amount of electricity possible, so the device can keep functioning …

Biofuel Feedstock Optimization Considering Different Land Cover Scenarios And Watershed Impacts, Rodney Wayne Vance

Open Access Theses & Dissertations

With an increased demand for renewable energy production, especially the conversion of biomass to biofuels, perennial grasses are gaining interest as a renewable source of biofuel feedstocks. Identifying the trade-offs between bioenergy crop cultivation and nutrient runoff, erosion, and water requirements will be important as the demand for these crops continues to grow. The primary objective of this study is develop an integrated optimal control model that estimates the potential effects on water quality and demand and soil erosion from cultivating switchgrass and other perennial grasses instead of conventional crops at the watershed scale. The Soil and Water Assessment Tool …

A Numerical Testbed For Remote Sensing Of Aerosols, And Its Demonstration For Evaluating Retrieval Synergy From A Geostationary Satellite Constellation Of Geo-Cape And Goes-R, Jun Wang, Xiaoguang Xu, Shouguo Ding, Jing Zeng, Robert Spurr, Xiong Liu, Kelly Chance, Michael I. Mishchenko

Department of Earth and Atmospheric Sciences: Faculty Publications

We present a numerical testbed for remote sensing of aerosols, together with a demonstration for evaluating retrieval synergy from a geostationary satellite constellation. The testbed combines inverse (optimal-estimation) software with a forward model containing linearized code for computing particle scattering (for both spherical and non-spherical particles). a kernel-based (land and ocean) surface bi-directional reflectance facility, and a linearized radiative transfer model for polarized radiance. Calculation of gas absorption spectra uses the HITRAN (HIgh-resolution TRANsmission molecular absorption) database of spectroscopic line parameters and other trace species cross-sections. The outputs of the testbed include not only the Stokes 4-vector elements and their …

Online Portfolio Selection: A Survey, Bin Li, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Online portfolio selection is a fundamental problem in computational finance, which has been extensively studied across several research communities, including finance, statistics, artificial intelligence, machine learning, and data mining. This article aims to provide a comprehensive survey and a structural understanding of online portfolio selection techniques published in the literature. From an online machine learning perspective, we first formulate online portfolio selection as a sequential decision problem, and then we survey a variety of state-of-the-art approaches, which are grouped into several major categories, including benchmarks, Follow-the-Winner approaches, Follow-the-Loser approaches, Pattern-Matching--based approaches, and Meta-Learning Algorithms. In addition to the problem formulation …

Degradation Of Hydrazine And Monomethylhydrazine For Fuel Waste Streams Using Alpha-Ketoglutaric Acid, Carolina Franco

Electronic Theses and Dissertations

Alpha-ketoglutaric acid (AKGA) is an organic acid important for the metabolism of essential amino acids as well as for the transfer of cellular energy. It is a precursor of glutamic acid which is produced by the human body during the Krebs Cycle. AKGA has a specific industrial interest as it can be taken as a dietary supplement and is also widely used as a building block in chemical synthesis. Collectively termed as hydrazine (HZs), hydrazine (HZ) and monomethylhydrazine (MMH) are hypergolic fuels that do not need an ignition source to burn. Because of the particular HZs' characteristics the National Aeronautics …

Simultaneous Optimization Of The Cavity Heat Load And Trip Rates In Linacs Using A Genetic Algorithm, Balša Terzić, Alicia S. Hofler, Cody J. Reeves, Sabbir A. Khan, Geoffrey A. Krafft, Jay Benesch, Arne Freyberger, Desh Ranjan

Physics Faculty Publications

In this paper, a genetic algorithm-based optimization is used to simultaneously minimize two competing objectives guiding the operation of the Jefferson Lab's Continuous Electron Beam Accelerator Facility linacs: cavity heat load and radio frequency cavity trip rates. The results represent a significant improvement to the standard linac energy management tool and thereby could lead to a more efficient Continuous Electron Beam Accelerator Facility configuration. This study also serves as a proof of principle of how a genetic algorithm can be used for optimizing other linac-based machines.

A Scalable Backward Chaining-Based Reasoner For A Semantic Web, Hui Shi, Kurt Maly, Steven Zeil

Computer Science Faculty Publications

In this paper we consider knowledge bases that organize information using ontologies. Specifically, we investigate reasoning over a semantic web where the underlying knowledge base covers linked data about science research that are being harvested from the Web and are supplemented and edited by community members. In the semantic web over which we want to reason, frequent changes occur in the underlying knowledge base, and less frequent changes occur in the underlying ontology or the rule set that governs the reasoning. Interposing a backward chaining reasoner between a knowledge base and a query manager yields an architecture that can support …

Swarm Intelligence As An Optimization Technique, Alma Bregaj

UBT International Conference

Optimization techniques inspired by swarm intelligence have become increasingly popular during the last years. Swarm intelligence is based on nature-inspired behaviours and is successfully applied to optimisation problems in a variety of fields. The advantage of these approaches over traditional techniques is their robustness and flexibility. These properties make swarm intelligence a successful design paradigm for algorithms that deal with increasingly complex problems. In this paper I am focused on the comparison between different swarm-based optimisation algorithms and I have presented some examples of real practical applications of these algorithms.

Modeling And Control Of Nanoparticle Bloodstream Concentration For Cancer Therapies, Scarlett S. Bracey

Doctoral Dissertations

Currently, the most commonly used treatments for cancerous tumors (chemotherapy, radiation, etc.) have almost no method of monitoring the administration of the treatment for adverse effects in real time. Without any real time feedback or control, treatment becomes a "guess and check" method with no way of predicting the effects of the drugs based on the actual bioavailability to the patient's body. One particular drug may be effective for one patient, yet provide no benefit to another. Doctors and scientists do not routinely attempt to quantifiably explain this discrepancy. In this work, mathematical modeling and analysis techniques are joined together …

Energy Systems Analysis For A Solar Economy, Dharik Sanchan Mallapragada

Open Access Dissertations

The use of solar energy for human needs faces challenges owing to its relatively low energy intensity and intermittent availability, coupled with the constrained availability of renewable carbon and land resources. This study uses systems analysis tools to identify carbon and energy efficient transformations of solar energy for different purposes, including transportation fuels and grid-scale energy storage. These efforts have been complemented with a feasibility analysis of existing fossil-energy and other hybrid pathways.

In an era of limited fossil resources, liquid fuels from sustainably available (SA) biomass could meet the energy needs of the transportation sector. We present a method …

On The Performance Of A Hybrid Genetic Algorithm In Dynamic Environments, Quan Yuan, Zhixin Yang

Mathematics Faculty Research Publications

The ability to track the optimum of dynamic environments is important in many practical applications. In this paper, the capability of a hybrid genetic algorithm (HGA) to track the optimum in some dynamic environments is investigated for different functional dimensions, update frequencies, and displacement strengths in different types of dynamic environments. Experimental results are reported by using the HGA and some other existing evolutionary algorithms in the literature. The results show that the HGA has better capability to track the dynamic optimum than some other existing algorithms.

Arrival Time Based Traffic Signal Optimization For Intelligent Transportation Systems, Vamsi Paruchuri, Sriram Chellappan, Rathinasamy B. Lenin

Computer Science Faculty Research & Creative Works

Road Transportation is a crucial component of today's society, which drives several facets of our lives. The goal of intelligent transportation systems (ITS) is to improve the effectiveness, efficiency, and safety of the transportation system. Traffic signals are an elementary component of all road transportation systems. In order to maximize the productivity of a city, traffic signals must be able to efficiently control the flow of vehicles. Traditionally, current traffic signal optimization is based on traffic arrival rates, either estimated or forecasted. In this paper, we illustrate that arrival time-based solutions can outperform arrival rate-based approaches. To the best of …

Tools And Methods To Optimize The Analysis Of Telescopic Performance Metrics On Sofia, Steven R. Wilson, Holger Jakob, Stefan Teufel, Zaheer Ali, Jeffrey Van Cleve, Brian Eney, Greg Perryman

STAR Program Research Presentations

SOFIA is an infrared observatory mounted on a modified 747 engineered to do infrared astronomy at 45000 feet. The telescope equipment contains a number of sensors and stabilizers that allow the telescope to capture images while mounted in a moving plane. We have developed methods to analyze the performance of the telescope assembly that will help improve the stabilization and image capturing performance of the observatory. Here we present reusable methods to analyze telescope performance data that will enable improvements in the quality of the scientific data that is produced by the SOFIA. This poster focuses on the multi-flight performance …

Using Economic Instruments To Develop Effective Management Of Invasive Species: Insights From A Bioeconomic Model, Shana M. Mcdermott, Rebecca E. Irwin, Brad W. Taylor

Dartmouth Scholarship

Economic growth is recognized as an important factor associated with species invasions. Consequently, there is increasing need to develop solutions that combine economics and ecology to inform invasive species management. We developed a model combining economic, ecological, and sociological factors to assess the degree to which economic policies can be used to control invasive plants. Because invasive plants often spread across numerous properties, we explored whether property owners should manage invaders cooperatively as a group by incorporating the negative effects of invader spread in management decisions (collective management) or independently, whereby the negative effects of invasive plant spread are ignored …

Informative Retesting For Hierarchical Group Testing, Michael S. Black

Department of Statistics: Dissertations, Theses, and Student Research

Group testing is the process of pooling samples (e.g., blood, chemical compounds) from multiple sources and testing the pooled material for some binary characteristic. It is used in pathogen screening for humans and animals, drug discovery studies, electrical systems testing, and many other applications. Group testing has traditionally been used for two main types of investigations: 1) the identification of positive specimens and 2) the estimation of a characteristic’s prevalence in a population. This dissertation focuses on the identification process. We propose new identification procedures that exploit the heterogeneity among samples in order to reduce the number of tests needed …

√(X2 + Μ) Is The Most Computationally Efficient Smooth Approximation To |X|: A Proof, Carlos Ramirez, Reinaldo Sanchez, Vladik Kreinovich, Miguel Argaez

Departmental Technical Reports (CS)

In many practical situations, we need to minimize an expression of the type |c₁| + ... + |c_n|. The problem is that most efficient optimization techniques use the derivative of the objective function, but the function |x| is not differentiable at 0. To make optimization efficient, it is therefore reasonable to approximate |x| by a smooth function. We show that in some reasonable sense, the most computationally efficient smooth approximation to |x| is the function √(x² + μ), a function which has indeed been successfully used in such optimization.

Near-Optimal Compressed Sensing Guarantees For Total Variation Minimization, Deanna Needell, R. Ward

CMC Faculty Publications and Research

Consider the problem of reconstructing a multidimensional signal from an underdetermined set of measurements, as in the setting of compressed sensing. Without any additional assumptions, this problem is ill-posed. However, for signals such as natural images or movies, the minimal total variation estimate consistent with the measurements often produces a good approximation to the underlying signal, even if the number of measurements is far smaller than the ambient dimensionality. This paper extends recent reconstruction guarantees for two-dimensional images x ∈ ℂN2 to signals x ∈ ℂNd of arbitrary dimension d ≥ 2 and to isotropic total variation problems. In this …

Generalized Local Test For Local Extrema In Single-Variable Functions, Eleftherios Gkioulekas

School of Mathematical & Statistical Sciences Faculty Publications

We give a detailed derivation of a generalization of the second derivative test of single-variable calculus which can classify critical points as local minima or local maxima (or neither), whenever the traditional second derivative test fails, by considering the values of higher-order derivatives evaluated at the critical points. The enhanced test is local, in the sense that it is only necessary to evaluate all relevant derivatives at the critical point itself, and it is reasonably robust. We illustrate an application of the generalized test on a trigonometric function where the second derivative test fails to classify some of the critical …

Master Physician Scheduling Problem, Aldy Gunawan, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

We study a real-world problem arising from the operations of a hospital service provider, which we term the master physician scheduling problem. It is a planning problem of assigning physicians’ full range of day-to-day duties (including surgery, clinics, scopes, calls, administration) to the defined time slots/shifts over a time horizon, incorporating a large number of constraints and complex physician preferences. The goals are to satisfy as many physicians’ preferences and duty requirements as possible while ensuring optimum usage of available resources. We propose mathematical programming models that represent different variants of this problem. The models were tested on a real …

Artificial Immune Systems And Particle Swarm Optimization For Solutions To The General Adversarial Agents Problem, Jeremy Mange

Dissertations

The general adversarial agents problem is an abstract problem description touching on the fields of Artificial Intelligence, machine learning, decision theory, and game theory. The goal of the problem is, given one or more mobile agents, each identified as either “friendly" or “enemy", along with a specified environment state, to choose an action or series of actions from all possible valid choices for the next “timestep" or series thereof, in order to lead toward a specified outcome or set of outcomes. This dissertation explores approaches to this problem utilizing Artificial Immune Systems, Particle Swarm Optimization, and hybrid approaches, along with …

Optimized Simulation Of Granular Materials, Seth R. Holladay

Theses and Dissertations

Visual effects for film and animation often require simulated granular materials, such as sand, wheat, or dirt, to meet a director's needs. Simulating granular materials can be time consuming, in both computation and labor, as these particulate materials have complex behavior and an enormous amount of small-scale detail. Furthermore, a single cubic meter of granular material, where each grain is a cubic millimeter, would contain a billion granules, and simulating all such interacting granules would take an impractical amount of time for productions. This calls for a simplified model for granular materials that retains high surface detail and granular behavior …

System Dynamics Modeling As A Quantitative-Qualitative Framework For Sustainable Water Resources Management: Insights For Water Quality Policy In The Great Lakes Region, Ali Mirchi

Dissertations, Master's Theses and Master's Reports - Open

Early water resources modeling efforts were aimed mostly at representing hydrologic processes, but the need for interdisciplinary studies has led to increasing complexity and integration of environmental, social, and economic functions. The gradual shift from merely employing engineering-based simulation models to applying more holistic frameworks is an indicator of promising changes in the traditional paradigm for the application of water resources models, supporting more sustainable management decisions. This dissertation contributes to application of a quantitative-qualitative framework for sustainable water resources management using system dynamics simulation, as well as environmental systems analysis techniques to provide insights for water quality management in …

Optimization Of Strategic Planning Processes For Configurable Products: Considerations For Global Supply, Demand, And Sustainability Issues, Edward Lawrence Umpfenbach

Wayne State University Dissertations

The assortment planning problem is to decide on the set of products that a retailer or manufacturer will offer to its customers to maximize profitability. While assortment planning research has been expanding in recent years, the current models are inadequate for the needs of a configurable product manufacturer. In particular, we address assortment planning for an automobile manufacturer. We develop models to integrate assortment planning and supply chain management, designed for use by a large automaker in its strategic planning phase. Our model utilizes a multinomial logit model transformed into a mixed integer linear program through the Charnes-Cooper transformation. It …

Fair Cost Sharing Auction Mechanisms In Last Mile Ridesharing, Duc Thien Nguyen

Dissertations and Theses Collection (Open Access)

With rapid growth of transportation demands in urban cities, one major challenge is to provide efficient and effective door-to-door service to passengers using the public transportation system. This is commonly known as the Last Mile problem. In this thesis, we consider a dynamic and demand responsive mechanism for Ridesharing on a non-dedicated commercial fleet (such as taxis). This problem is addressed as two sub-problems, the first of which is a special type of vehicle routing problems (VRP). The second sub-problem, which is more challenging, is to allocate the cost (i.e. total fare) fairly among passengers. We propose auction mechanisms where …