Physical Sciences and Mathematics Commons^™

A Comparison Of New Methods For Generating Energy-Minimizing Configurations Of Patchy Particles, Eric Jankowski, Sharon C. Glotzer

Eric Jankowski

Increasingly complex particles are pushing the limits of traditional simulation techniques used to study self-assembly. In this work, we test the use of a learning-augmented Monte Carlo method for predicting low energy configurations of patchy particles shaped like “Tetris®” pieces. We extend this method to compare it against Monte Carlo simulations with cluster moves and introduce a new algorithm—bottom-up building block assembly—for quickly generating ordered configurations of particles with a hierarchy of interaction energies.

Joint Routing And Link Rate Allocation Under Bandwidth And Energy Constraints In Sensor Networks, Maggie Cheng, Xuan Gong, Lin Cai

Computer Science Faculty Research & Creative Works

In sensor networks, both energy and bandwidth are scarce resources. in the past, many energies efficient routing algorithms have been devised in order to maximize network lifetime, in which wireless link bandwidth has been optimistically assumed to be sufficient. This article shows that ignoring the bandwidth constraint can lead to infeasible routing solutions. as energy constraint affects how data should be routed, link bandwidth also affects not only the routing topology but also the allowed data rate on each link. in this paper, we discuss the sufficient condition on link bandwidth that makes a routing solution feasible, then provide mathematical …

A Neural Network: Family Competition Genetic Algorithm And Its Application In Electromagnetic Optimization, Chien Hsun Chen, P. Y. Chen, H. Weng

Chien Hsun Chen

This study proposes a neural network-family competition genetic algorithm (NN-FCGA) for solving the electromagnetic (EM) optimization and other general-purpose optimization problems. The NN-FCGA is a hybrid evolutionary-based algorithm, combining the good approximation performance of neural network (NN) and the robust and effective optimum search ability of the family competition genetic algorithms (FCGA) to accelerate the optimization process. In this study, the NN-FCGA is used to extract a set of optimal design parameters for two representative design examples: the multiple section low-pass filter and the polygonal electromagnetic absorber. Our results demonstrate that the optimal electromagnetic properties given by the NN-FCGA are …

Diversity Graphs, P Blain, C Davis, Allen G. Holder, J Silva, C Vinzant

Mathematics Faculty Research

Bipartite graphs have long been used to study and model matching problems, and in this paper we introduce the bipartite graphs that explain a recent matching problem in computational biology. The problem is to match haplotypes to genotypes in a way that minimizes the number of haplotypes, a problem called the Pure Parsimony problem. The goal of this work is not to address the computational or biological issues but rather to explore the mathematical structure through a study of the underlying graph theory.

Radiotherapy Optimal Design: An Academic Radiotherapy Treatment Design System, Ryan Acosta, William Brick, A Hanna, Allen G. Holder, D Lara, G Mcquilen, D Nevin, P Uhlig, B Salter

Mathematics Faculty Research

Optimally designing radiotherapy and radiosurgery treatments to increase the likelihood of a successful recovery from cancer is an important application of operations research. Researchers have been hindered by the lack of academic software that supports head-to-head comparisons of different techniques, and this article addresses the inherent difficulties of designing and implementing an academic treatment planning system. In particular, this article details the algorithms and the software design of Radiotherapy optimAl Design (RAD).

Experimental Design, Synthesis And Application Of Molecular Micelle Modified Polymeric Nanoparticles For Drug Delivery Systems And Free Radical Detection, Gabriela M. Ganea Visser

LSU Doctoral Dissertations

Biodegradable and biocompatible polymeric nanoparticles such as poly (lactide-co-glycolide) (PLGA) nanoparticles have been extensively studied as drug delivery systems for a variety of pharmaceutical agents. Nanoparticle surface properties are primarily determined by the emulsifiers used in the synthesis process, which have a significant impact on nanoparticle physico-chemical and biological properties. Anionic amino acid – based molecular micelles were used in the emulsification process to prepare monodisperse, small (below 100 nm) PLGA nanoparticles with a well defined spherical shape. Such molecular micelle – modified nanoparticles were used as drug carriers for delivery of antioxidants. Thymoquinone is a natural antioxidant, and an …

Parameter Identification Of A Separately Excited Dc Motor Via Inverse Problem Methodology, Mounir Hadef, Mohamed Rachid Mekideche

Turkish Journal of Electrical Engineering and Computer Sciences

Identification is considered to be among the main applications of inverse theory and its objective for a given physical system is to use data which is easily observable, to infer some of the geometric parameters which are not directly observable. In this paper, a parameter identification method using inverse problem methodology is proposed. The minimisation of the objective function with respect to the desired vector of design parameters is the most important procedure in solving the inverse problem. The conjugate gradient method is used to determine the unknown parameters, and Tikhonov's regularization method is then used to replace the original …

An Optimization Approach For The Cascade Vulnerability Problem, Christian Servin

Open Access Theses & Dissertations

In inter-connected systems, where several computers share information with each other, problems may arise when inappropriate information starts to flow through. For example, let us consider a simple scenario of a university composed of three departments: payroll, financial aid, and academic services. We know that the payroll department deals with sensitive information, such as social security numbers, dates of birth, amounts of wages, etc. The financial aid department may use information that payroll owns. Similarly, the academic department communicates with the financial aid department. An intruder can take advantage of this network connectivity and create an inappropriate flow of information …

Softcomputing Identification Techniques Of Asynchronous Machine Parameters: Evolutionary Strategy And Chemotaxis Algorithm, Nouri Benaïdja

Turkish Journal of Electrical Engineering and Computer Sciences

Softcomputing techniques are receiving attention as optimisation techniques for many industrial applications. Although these techniques eliminate the need for derivatives computation, they require much work to adjust their parameters at the stage of research and development. Issues such as speed, stability, and parameters convergence remain much to be investigated. This paper discusses the application of the method of reference model to determine parameters of asynchronous machines using two optimisation techniques. Softcomputing techniques used in this paper are evolutionary strategy and the chemotaxis algorithm. Identification results using the two techniques are presented and compared with respect to the conventional simplex technique …

Rfid-Enabled Warehouse Optimization: Lessons From Early Adopters In The 3pl Industry, S. F. Wamba, T. R. Coltman, Katina Michael

Faculty of Informatics - Papers (Archive)

This paper presents the impact of RFID technology on the picking and shipping processes of one RFID-enabled warehouse in the 3PL industry. The findings from our study confirm initial results from many studies where RFID implementation has been shown to enable business process redesign, improve data quality, real-time data collection and synchronization and enhance system integration. In this study we show that the full potential of RFID technology is dependent upon the involvement of all supply chain members involved in implementation. Moreover, firms considering implementing RFID technology need to take into account their investment in complementary assets such as employee …

Optimal Irrigation Management For Sloping, Blocked-End Borders, Jorge Jose Escurra

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

A robust mathematical model of one-dimensional flow for sloping, blocked-end border irrigation was developed using the four-point implicit method to solve the Saint-Venant equations, the volume-balance solution method, and the implementation of new algorithms to avoid numerical instability and solution divergence. The model has the capability of successfully simulating all surface irrigation phases in blocked-end borders for a range of inflow rates (0.01 - 0.05 m³/s per m), longitudinal slopes (up to 1.00%), and border lengths (100 - 500 m).

To achieve numerical stability over the specified parameter ranges, the model was divided into three parts: (1) advance-phase …

Optimization In The Undergraduate Curriculum, Allen Holder

Mathematical Sciences Technical Reports (MSTR)

A discussion of how an optimization course fits into the undergraduate mathematics curriculum

Optimizing Product Line Designs: Efficient Methods And Comparisons, Alexandre Belloni, Robert Freund, Matthew Selove, Duncan Simester

Business Faculty Articles and Research

We take advantage of recent advances in optimization methods and computer hardware to identify globally optimal solutions of product line design problems that are too large for complete enumeration. We then use this guarantee of global optimality to benchmark the performance of more practical heuristic methods. We use two sources of data: (1) a conjoint study previously conducted for a real product line design problem, and (2) simulated problems of various sizes. For both data sources, several of the heuristic methods consistently find optimal or near-optimal solutions, including simulated annealing, divide-and-conquer, product-swapping, and genetic algorithms.

Radiotherapy Optimal Design: An Academic Radiotherapy Treatment Design System, R Acosta, W Brick, A Hanna, Allen Holder, D Lara, G Mcquillen, D Nevin, P Uhlig, B Salter

Mathematical Sciences Technical Reports (MSTR)

Optimally designing radiotherapy and radiosurgery treatments to increase the likelihood of a successful recovery from cancer is an important application of operations research. Researchers have been hindered by the lack of academic software that supports head-to-head comparisons of different techniques, and this article addresses the inherent difficulties of designing and implementing an academic treatment planning system. In particular, this article details the algorithms and the software design of Radiotherapy optimAl Design (RAD).

Optimal Treatments For Photodynamic Therapy, Allen G. Holder, D Llagostera

Mathematics Faculty Research

Photodynamic therapy is a complex treatment for neoplastic diseases that uses the light-harvesting properties of a photosensitizer. The treatment depends on the amount of photosensitizer in the tissue and on the amount of light that is focused on the targeted area. We use a pharmacokinetic model to represent a photosensitizer's movement through the anatomy and design treatments with a linear program. This technique allows us to investigate how a treatment's success varies over time.

Utility-Based Adaptation In Mission-Oriented Wireless Sensor Networks, Sharanya Eswaran, Archan Misra, Thomas La Porta

Research Collection School Of Computing and Information Systems

This paper extends the distributed network utility maximization (NUM) framework to consider the case of resource sharing by multiple competing missions in a military-centric wireless sensor network (WSN) environment. Prior work on NUM-based optimization has considered unicast flows with sender-based utilities in either wireline or wireless networks. We extend the NUM framework to consider three key new features observed in mission-centric WSN environments: i) the definition of an individual mission's utility as a joint function of data from multiple sensor sources ii) the consumption of each senders (sensor) data by multiple receivers (missions) and iii) the multicast-tree based dissemination of …

Optimization Of Magneto-Optical Kerr Setup: Analyzing Experimental Assemblies Using Jones Matrix Formalism, Christian Binek

Christian Binek Publications

We present a comparative study on an experimental and theoretical optimization of magneto-optical Kerr setups based on photoelastic modulation and phase sensitive detector methodology. The first and second harmonics, Iomega,2omega, of the reflected light intensity are measured for a CoO/Co magnetic reference film. The magnetic field dependence of the optical off-diagonal Fresnel reflection coefficients rps and rsp follows the sample magnetization. Different Kerr setups provide various dependencies of Iomega,2omega on the reflection coefficients and, hence, on the Kerr ellipticity epsilonK and rotation thetaK. Jones matrix formalism has been used to analyze the impact of a systematic variation of relative analyzer …

Analysis Of Synthetic Diamond Wafer Interferograms Using A Parallelized Simulated Annealing Algorithm, Matthew Demas

Honors Scholar Theses

Diamonds are known for both their beauty and their durability. Jefferson National Lab in Newport News, VA has found a way to utilize the diamond's strength to view the beauty of the inside of the atomic nucleus with the hopes of finding exotic forms of matter. By firing very fast electrons at a diamond sheet no thicker than a human hair, high energy particles of light known as photons are produced with a high degree of polarization that can illuminate the constituents of the nucleus known as quarks. The University of Connecticut Nuclear Physics group has responsibility for crafting these …

Treatments Of Chlamydia Trachomatis And Neisseria Gonorrhoeae, Ken Kun Zhao

Mathematics Theses

Chlamydia Trachomatis and Neisseria Gonorrhoeae rank as the two most commonly reported sexually transmitted diseases (STDs) in the United States. Under limited budget, publicly funded clinics are not able to screen and treat the two diseases for all patients. They have to make a decision as to which group of population shall go through the procedure for screening and treating the two diseases. Therefore, we propose a cubic integer programming model on maximizing the number of units of cured diseases. At the same time, a two-step algorithm is established to solve the cubic integer program. We further develop a web-server, …

Approximations With Improving Error Bounds For Makespan Minimization In Batch Manufacturing, Whitney Samuel Weyerman

Theses and Dissertations

Multipurpose batch manufacturing systems allow a suite of job types to be processed with a fixed set of machines. These types of systems are commonly found in chemical processing, as well as in computer systems and the service industry. In this thesis we consider the problem of sequencing jobs entering the manufacturing system in order to minimize makespan, or total time to complete processing of the jobs. We formulate this problem as a dynamic programming problem and illustrate the computational difficulty of solving this problem. We give a method for simulation of the system by representing each machine in the …

Beam Selection In Radiotherapy Design, M Ehrgott, Allen G. Holder, Josh Reese

Mathematics Faculty Research

The optimal design of a radiotherapy treatment depends on the collection of directions from which radiation is focused on the patient. These directions are manually selected by a physician and are typically based on the physician's previous experiences. Once the angles are chosen, there are numerous optimization models that decide a fluency pattern (exposure times) that best treats a patient. So, while optimization techniques are often used to decide the length of time a patient is exposed to a high-energy particle beam, the directions themselves are not optimized. The problem with optimally selecting directions is that the underlying mixed integer …

Some Combinational Optimization Problems On Radio Network Communication And Machine Scheduling, Xin Wang

Dissertations

The combinatorial optimization problems coming from two areas are studied in this dissertation: network communication and machine scheduling.

In the network communication area, the complexity of distributed broadcasting and distributed gossiping is studied in the setting of random networks. Two different models are considered: one is random geometric networks, the main model used to study properties of sensor and ad-hoc networks, where ri points are randomly placed in a unit square and two points are connected by an edge if they are at most a certain fixed distance r from each other. The other model is the so-called line-of-sight networks, …

Synthesis Design Of Artificial Magnetic Metamaterials Using A Genetic Algorithm, Chien Hsun Chen, P. Y. Chen, H. Wang, J. H. Tsai, W. X. Ni

Chien Hsun Chen

In this article, we present a genetic algorithm (GA) as one branch of artificial intelligence (AI) for the optimization-design of the artificial magnetic metamaterial whose structure is automatically generated by computer through the filling element methodology. A representative design example, metamaterials with permeability of negative unity, is investigated and the optimized structures found by the GA are presented. It is also demonstrated that our approach is effective for the synthesis of functional magnetic and electric metamaterials with optimal structures. This GA-based optimization-design technique shows great versatility and applicability in the design of functional metamaterials.

The Influence Of Dose Grid Resolution On Beam Selection Strategies In Radiotherapy Treatment Design, Ryan Acosta, Matthias Ehrgott, Allen G. Holder, Daniel Nevin, Josh Reese, Bill Salter

Mathematics Faculty Research

The design of a radiotherapy treatment includes the selection of beam angles (geometry problem), the computation of a fluence pattern for each selected beam angle (intensity problem), and finding a sequence of configurations of a multilef collimator to deliver the treatment (realization problem). While many mathematical optimization models and algorithms have been proposed for the intensity problem and (to a lesser extent) the realization problem, this is not the case for the geometry problem. In clinical practice, beam directions are manually selected by a clinician and are typically based on the clinician’s experience. Solving the beam selection problem optimally is …

An Introduction To Systems Biology For Mathematical Programmers, Evind Almaas, Allen G. Holder, Kevin D. Livingstone

Mathematics Faculty Research

Many recent advances in biology, medicine and health care are due to computational efforts that rely on new mathematical results. These mathematical tools lie in discrete mathematics, statistics & probability, and optimization, and when combined with savvy computational tools and an understanding of cellular biology they are capable of remarkable results. One of the most significant areas of growth is in the field of systems biology, where we are using detailed biological information to construct models that describe larger entities. This chapter is designed to be an introduction to systems biology for individuals in Operations Research (OR) and mathematical programming …

Model-Driven Search-Based Loop Fusion Optimization For Handwritten Code, Pamela Bhattacharya

LSU Master's Theses

The Tensor Contraction Engine (TCE) is a compiler that translates high-level, mathematical tensor contraction expressions into efficient, parallel Fortran code. A pair of optimizations in the TCE, the fusion and tiling optimizations, have proven successful for minimizing disk-to-memory traffic for dense tensor computations. While other optimizations are specific to tensor contraction expressions, these two model-driven search-based optimization algorithms could also be useful for optimizing handwritten dense array computations to minimize disk to memory traffic. In this thesis, we show how to apply the loop fusion algorithm to handwritten code in a procedural language. While in the TCE the loop fusion …

Evolutionary Methodology For Optimization Of Image Transforms Subject To Quantization Noise, Michael Ray Peterson

Browse all Theses and Dissertations

Lossy image compression algorithms sacrifice perfect imagereconstruction in favor of decreased storage requirements. Modelossy compression schemes, such as JPEG2000, rely upon the discrete wavelet transform (DWT) to achieve high levels of compression while minimizing the loss of information for image reconstruction. Some compression applications require higher levels of compression than those achieved through application of the DWT and entropy coding. In such lossy systems, quantization provides high compression rates at the cost of increased distortion. Unfortunately, as the amount of quantization increases, the performance of the DWT for accurate image reconstruction deteriorates. Previous research demonstrates that a genetic algorithm can …

Analysis And Optimization Of Mobile Phone Antenna Radiation Performance In The Presence Of Head And Hand Phantoms, Erdem Ofli, Chung-Huan Li, Nicolas Chavannes, Niels Kuster

Turkish Journal of Electrical Engineering and Computer Sciences

A commercial clam shell phone CAD model is used to numerically investigate the effect of a hand phantom on mobile phone antenna radiation performance. The simulation results show that the grip of the hand phantom is the most important parameter to antenna performance. The antenna is converted into a parameterized form, then optimized to achieve the targeted multi-band performance in real-usage conditions.

Mathematically Modeling Pcr: An Asymptotic Approximation With Potential For Optimization, Martha J. Garlick

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

A mathematical model for PCR (Polymerase Chain Reaction) is developed using the law of mass action. Differential equations are written from the chemical equations, preserving the detail of the complementary DNA single strand being extended one bas e pair at a time. The equations for the annealing stage are solved analytically. The method of multiple scales is used to approximate solutions for the extension stage. A map is then developed from the solutions to simulate PCR. The advantage of this model is the ability to use the map to optimize the process. Our results suggest that dynamically optimizing the extension …

Optimal Design Of Integrally Gated Cnt Field-Emission Devices Using A Genetic Algorithm, P. Y. Chen, Chien Hsun Chen, J. S. Wu, H. C. Wen, W. P. Wang

Chien Hsun Chen

A method to optimize the focusing quality of integrally gated CNT field-emission (FE) devices by combining field-emission modeling and a computational intelligence technique, genetic algorithm (GA), is proposed and demonstrated. In this work, the e-beam shape, as a characteristic parameter of electron-optical properties, is calculated by field-emission simulation modeling. Using a design tool that combines GA and physical modeling, a set of structural and electrical parameters for four FE device groups, including double-gate, triple-gate, quadruple-gate and quintuple-gate type, were optimized. The resultant FE devices exhibit satisfactory e-beam focusabilities and the extracted parameters with the best performance for each type of …