Physical Sciences and Mathematics Commons^™

Coevolutionary Algorithms For The Optimization Of Strategies For Red Teaming Applications, Tirtha Ranjeet

Theses: Doctorates and Masters

Red teaming (RT) is a process that assists an organization in finding vulnerabilities in a system whereby the organization itself takes on the role of an “attacker” to test the system. It is used in various domains including military operations. Traditionally, it is a manual process with some obvious weaknesses: it is expensive, time-consuming, and limited from the perspective of humans “thinking inside the box”. Automated RT is an approach that has the potential to overcome these weaknesses. In this approach both the red team (enemy forces) and blue team (friendly forces) are modelled as intelligent agents in a multi-agent …

Cross-Layer Throughput Optimization With Power Control In Sensor Networks, Maggie Xiaoyan Cheng, Xuan Gong, Lin Cai, Xiaohua Jia

Computer Science Faculty Research & Creative Works

In wireless sensor networks, transmission power has a significant impact on network throughput as wireless interference increases with transmission power, and interference negatively impacts the network throughput. in this paper, we try to improve the network throughput through cross-layer optimization. We first present two algorithms to compute the transmission power of each node with the objectives of minimizing the total transmission power and minimizing the total interference, respectively, from which we can obtain a network topology that ensures a connected path from each source to the sink; then, we compute the maximum achievable throughput from the obtained topology by using …

Modeling Wireless Networks For Rate Control, David C. Ripplinger

Theses and Dissertations

Congestion control algorithms for wireless networks are often designed based on a model of the wireless network and its corresponding network utility maximization (NUM) problem. The NUM problem is important to researchers and industry because the wireless medium is a scarce resource, and currently operating protocols such as 802.11 often result in extremely unfair allocation of data rates. The NUM approach offers a systematic framework to build rate control protocols that guarantee fair, optimal rates. However, classical models used with the NUM approach do not incorporate partial carrier sensing and interference, which can lead to significantly suboptimal performance when actually …

A Study On Facility Planning Using Discrete Event Simulation: Case Study Of A Grain Delivery Terminal., Sarah M. Asio

Department of Industrial and Management Systems Engineering: Dissertations, Theses, and Student Research

The application of traditional approaches to the design of efficient facilities can be tedious and time consuming when uncertainty and a number of constraints exist. Queuing models and mathematical programming techniques are not able to capture the complex interaction between resources, the environment and space constraints for dynamic stochastic processes. In the following study discrete event simulation is applied to the facility planning process for a grain delivery terminal. The discrete event simulation approach has been applied to studies such as capacity planning and facility layout for a gasoline station and evaluating the resource requirements for a manufacturing facility. To …

Sharing-Aware Algorithms For Virtual Machine Colocation, Michael Sindelar, Ramesh Sitaraman, Prashant Shenoy

Ramesh Sitaraman

Virtualization technology enables multiple virtual machines (VMs) to run on a single physical server. VMs that run on the same physical server can share memory pages that have identical content, thereby reducing the overall memory requirements on the server. We develop sharing-aware algorithms that can colocate VMs with similar page content on the same physical server to optimize the benefits of inter-VM sharing. We show that inter-VM sharing occurs in a largely hierarchical fashion, where the sharing can be attributed to VM's running the same OS platform, OS version, software libraries, or applications. We propose two hierarchical sharing models: a …

Automated, Parallel Optimization Algorithms For Stochastic Functions, Dheeraj Chahal

All Dissertations

The optimization algorithms for stochastic functions are desired specifically for real-world and simulation applications where results are obtained from sampling, and contain experimental error or random noise. We have developed a series of stochastic optimization algorithms based on the well-known classical down hill simplex algorithm. Our parallel implementation of these optimization algorithms, using a framework called MW, is based on a master-worker architecture where each worker runs a massively parallel program. This parallel implementation allows the sampling to proceed independently on many processors as demonstrated by scaling up to more than 100 vertices and 300 cores.
This framework is highly …

Multi-Channel Peer-To-Peer Streaming Systems As Resource Allocation Problems, Miao Wang

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

In the past few years, the Internet has witnessed the success of Peer-to-Peer (P2P) streaming technology, which has attracted millions of users. More recently, commercial P2P streaming systems have begun to support multiple channels and a user in such systems is allowed to watch more than one channel at a time. We refer to such systems as multi-channel P2P streaming systems. In this dissertation, we focus on designing multi-channel P2P streaming systems with the goal of providing optimal streaming quality for all channels, termed as system-wide optimal streaming quality. Specifically, we design the systems from the perspective of how to …

Characterization Of A Boron Carbide Heterojunction Neutron Detector, James E. Bevins

Theses and Dissertations

New methods for neutron detection have become an important area of research in support of national security objectives. In support of this effort, p-type B₅C on n-type Si heterojunction diodes have been built and tested. This research sought to optimize the boron carbide (BC) diode by coupling the nuclear physics modeling capability of GEANT4 and TRIM with the semiconductor device simulation tools. Through an iterative modeling process of controllable parameters, optimal device construction was determined such detection efficiency and charge collection were optimized. This allows an estimation of expected charge collection and efficiency given a set of operating …

A Two-View Learning Approach For Image Tag Ranking, Jinfeng Zhuang, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Tags of social images play a central role for text-based social image retrieval and browsing tasks. However, the original tags annotated by web users could be noisy, irrelevant, and often incomplete for describing the image contents, which may severely deteriorate the performance of text-based image retrieval models. In this paper, we aim to overcome the challenge of social tag ranking for a corpus of social images with rich user-generated tags by proposing a novel two-view learning approach. It can effectively exploit both textual and visual contents of social images to discover the complicated relationship between tags and images. Unlike the …

Solution Of A Certain Class Of Network Flow Problems With Cascaded Demand Aggregation And Capacity Allocation, Farzad Safaei, I. Ouveysi

Professor Farzad Safaei

This article develops analytical models for a class of networking problems that includes two cascaded stages of demand aggregation and capacity allocation. The solutions to these problems are required in real time as the demand fluctuates rapidly. The capacity allocation problem makes a large-scale integer programming problem too complex for practical applications. Using the Lagrangian relaxation technique and a suitably developed heuristic for multiplier adjustment, the computational complexity is reduced to such a degree that a real-time implementation of the algorithm is feasible. This article also develops efficient heuristics to aggregate demand. The proposed algorithm produces a near-optimal solution in …

Optimization Of Task Processing Schedules In Distributed Information Systems, Janusz R. Getta

Faculty of Informatics - Papers (Archive)

The performance of data processing in distributed information systems strongly depends on theefficient scheduling of the applications that access data at the remote sites. This work assumes atypical model of distributed information system where a central site is connected to a number ofremote and highly autonomous remote sites. An application started by a user at a central site isdecomposed into several data processing tasks to be independently processed at the remote sites.The objective of this work is to find a method for optimization of task processing schedules at acentral site. We define an abstract model of data and a system …

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 …

On Constrained Optimization Schemes For Joint Inversion Of Geophysical Datasets, Uram Anibal Sosa Aguirre

Open Access Theses & Dissertations

In the area of geological sciences, there exist several experimental techniques used to advance in the understanding of the Earth. We implement a joint inversion least-squares (LSQ) algorithm to characterize one dimensional Earth's structure by using seismic shear wave velocities as a model parameter. We use two geophysical datasets sensitive to shear velocities, namely Receiver Function and Surface Wave dispersion velocity observations, with a choice of an optimization method: Truncated Singular Value Decomposition (TSVD) or Primal-Dual Interior-Point (PDIP). The TSVD and the PDIP methods solve a regularized unconstrained and a constrained minimization problem, respectively. Both techniques include bounds into the …

Optimization Of A Pressure-Treating Process, Josean Velez

Undergraduate Journal of Mathematical Modeling: One + Two

A company that pressure-treats wood wants to minimize its annual cost without using more than 250 days of operation per year. In addition, they want to find the corresponding value of time, batches and cost for each category. We develop an expression in terms of boards per batch to model the total cost of the treatment process. We then take the derivative and use Newton's Method to find the number of boards per batch that minimizes total cost.

Modeling Direct Runoff Hydrographs With The Surge Function, Denis Voytenko

USF Tampa Graduate Theses and Dissertations

A surge function is a mathematical function of the form f(x)=ax^pe^-bx. We simplify the surge function by holding p constant at 1 and investigate the simplified form as a potential model to represent the full peak of a stream discharge hydrograph. The previously studied Weibull and gamma distributions are included for comparison. We develop an analysis algorithm which produces the best-fit parameters for every peak for each model function, and we process the data with a MATLAB script that uses spectral analysis to filter year-long, 15-minute, stream-discharge data sets. The filtering is necessary to locate the …

Optimal Summer Camp Layout, Anthony Bonifonte

Honors Papers

Convex optimization is an important branch of operations research. It generalizes linear programming and offers powerful tools for modelling problems and discovering optimal solutions to real world problems. Mathematically it is an interesting topic because it ties together many branches: linear algebra, multivariable calculus, and numerical analysis, to name a few. Modelling a problem as a convex optimization problem can be challenging but offers many benefits. Algorithm design is critically important to ensure precision of solutions that solve with minimal computation power. From an engineering perspective it is also incredibly useful, since many more situations can be modeled than with …

Change Detection Without Difference Image Computation Based On Multiobjective Cost Function Optimization, Turgay Çeli̇k, Zeki̇ Yetgi̇n

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we propose a novel method for unsupervised change detection in multi-temporal satellite images by using multiobjective cost function optimization via genetic algorithm (GA). The spatial image grid of the input multi-temporal satellite images is divided into two distinct regions, representing ``changed'' and ``unchanged'' regions between input images, via the intermediate change detection mask produced by the GA. The dissimilarity of pixels of ``changed'' regions and similarity of pixels of ``unchanged'' regions between input multi-temporal images are measured using image quality metrics which consider correlation, spectral distortion, radiometric distortion, and contrast distortion. The contextual information of each pixel …

Optimization Of Railway System Through The Application Of Advanced Technologies, Praveen Jha Dr

Praveen Jha Dr

Railway System can be made truly automated, modern, safe, profitable and timely by providing an integrated solution to the loads of problems in the Railway System in most scientific, effective and inexpensive manner through the application of state-of-art geo-spatial programs - Railways Automatic Tracking Program (RATP) and Program for Optimization and Automation of Railway System (POARS) - developed by the author for addressing the pertinent issues of safety and optimization of railway operations. This could put in place the Optimized Railway System (ORS) that could automatically control all the systems of railways. Real time tracking of trains could be done …

Packing Virtual Machines Onto Servers, David Luke Wilcox

Theses and Dissertations

Data centers consume a significant amount of energy. This problem is aggravated by the fact that most servers and desktops are underutilized when powered on, and still consume a majority of the energy of a fully utilized computer even when idle This problem would be much worse were it not for the growing use of virtual machines. Virtual machines allow system administrators to more fully utilize hardware capabilities by putting more than one virtual system on the same physical server. Many times, virtual machines are placed onto physical servers inefficiently. To address this inefficiency, I developed a new family of …

A Case Study Of Network Design For Middle East Water Distribution, Rachel Bullene

Theses and Dissertations

The Middle Eastern region encompassing Israel, Jordan, and the Palestinian Territories (West Bank and Gaza) is an arid region with fast growing populations. Adequate and equitable access to water for all the people of the region is crucial to the future of Middle East peace. However, the current water distribution system not only fails to provide an adequate and equitable allocation of water, but also results adverse impacts on the environment. This project involves building a mathematical model to aid decision-makers in designing an optimal water distribution network. A new method for incorporating uncertainty in optimization that is based on …

Cleaning Of Rivers Through The Application Of Advanced Technologies, Praveen Jha Dr

Praveen Jha Dr

Despite immense drain on our scarce resources, rivers remain polluted. Waste disposal into rivers on top of meager to absent infrastructural facilities, including treatment facilities, are the most important drivers of pollution. Unscientific development paradigm devoid of adequate environmental safeguards and failure of forestry sector to cope up with the challenge has led to the deteriorated condition of green cover and water. Several state-of-art geo-spatial programs developed by the author would be applied for generating optimum state-of-art plan. Three state-of-art geo-spatial programs - Multi-Algorithm Automation Program (MAAP), Data Automatic Modification Program (DAMP) and Multi-Stage Simulation Program (MUSSIP) - developed primarily …

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

Dr Samuel Fosso Wamba

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 …

Stochastic Optimization For Learning-Based Super-Resolution: Algorithms And Applications, Jun Zheng

Open Access Theses & Dissertations

Human beings get much of their information visually and depend on perception of images for many critical tasks, such as object identification, medical image analysis, photography, etc. In many visual-based applications, higher resolution images are required for perceiving and receiving critical information. A high resolution image can contribute to a better identification of a suspect's face, or a more accurate localization of a tumor in a mammogram, or a more pleasing view in high definition television, and so on. However, it is hard to obtain the high resolution images needed for some applications, for example, the cost of sensors increases …

A Particle Swarm Optimization Algorithm Based On Orthogonal Design, Jie Yang, Abdesselam Bouzerdoum, Son Lam Phung

Faculty of Informatics - Papers (Archive)

The last decade has witnessed a great interest in using evolutionary algorithms, such as genetic algorithms, evolutionary strategies and particle swarm optimization (PSO), for multivariate optimization. This paper presents a hybrid algorithm for searching a complex domain space, by combining the PSO and orthogonal design. In the standard PSO, each particle focuses only on the error propagated back from the best particle, without “communicating” with other particles. In our approach, this limitation of the standard PSO is overcome by using a novel crossover operator based on orthogonal design. Furthermore, instead of the “generating-and-updating” model in the standard PSO, the elitism …

Redtnet: A Network Model For Strategy Games, Philip Hingston, Mike Preuss, Daniel Spierling

Research outputs pre 2011

In this work, we develop a simple, graph-based framework, RedTNet, for computational modeling of strategy games and simulations. The framework applies the concept of red teaming as a means by which to explore alternative strategies. We show how the model supports computer-based red teaming in several applications: realtime strategy games and critical infrastructure protection, using an evolutionary algorithm to automatically detect good and often surprising strategies.

The Impact Of Overfitting And Overgeneralization On The Classification Accuracy In Data Mining, Huy Nguyen Anh Pham

LSU Doctoral Dissertations

Current classification approaches usually do not try to achieve a balance between fitting and generalization when they infer models from training data. Such approaches ignore the possibility of different penalty costs for the false-positive, false-negative, and unclassifiable types. Thus, their performances may not be optimal or may even be coincidental. This dissertation analyzes the above issues in depth. It also proposes two new approaches called the Homogeneity-Based Algorithm (HBA) and the Convexity-Based Algorithm (CBA) to address these issues. These new approaches aim at optimally balancing the data fitting and generalization behaviors of models when some traditional classification approaches are used. …

A Species-Conserving Genetic Algorithm For Multimodal Optimization, Michael Scott Brown

CCE Theses and Dissertations

The problem of multimodal functional optimization has been addressed by much research producing many different search techniques. Niche Genetic Algorithms is one area that has attempted to solve this problem. Many Niche Genetic Algorithms use some type of radius. When multiple optima occur within the radius, these algorithms have a difficult time locating them. Problems that have arbitrarily close optima create a greater problem. This paper presents a new Niche Genetic Algorithm framework called Dynamic-radius Species-conserving Genetic Algorithm. This new framework extends existing Genetic Algorithm research.

This new framework enhances an existing Niche Genetic Algorithm in two ways. As the …

Optimization Of A Chemical Reaction Train, Bahar Sansar

Undergraduate Journal of Mathematical Modeling: One + Two

This project consists of the optimization of a chemical reactor train. The reactor considered here is the continuous stirred tank reactor (CSTR), one of the reactor models used in engineering. Given the design equation for the CSTR and the cost function for a reactor, the following values are determined; the optimum number of reactors in the reaction train, the volume of each reactor and the total cost.

An Approach Based On Particle Swarm Computation To Study The Nanoscale Dg Mosfet-Based Circuits, Fayacl Djeffal, Toufik Bendib, Redha Benzid, Abdelhamid Benhaya

Turkish Journal of Electrical Engineering and Computer Sciences

The analytical modeling of nanoscale Double-Gate MOSFETs (DG) requires generally several necessary simplifying assumptions to lead to compact expressions of current-voltage characteristics for nanoscale CMOS circuits design. Further, progress in the development, design and optimization of nanoscale devices necessarily require new theory and modeling tools in order to improve the accuracy and the computational time of circuits' simulators. In this paper, we propose a new particle swarm strategy to study the nanoscale CMOS circuits. The latter is based on the 2-D numerical Non-Equilibrium Green's Function (NEGF) simulation and a new extended long channel DG MOSFET compact model. Good agreement between …

Drinking Water Optimum Supply System (Dwoss) Through The Application Of Advanced Technologies, Praveen Jha Dr

Praveen Jha Dr

Paradigm shift in the approach for planning regarding supply of drinking water is mandatory since the current DPRs are unscientific and expensive. Planning for an optimum Drinking Water Supply System (ODWSS) that includes - optimization of Water Source Point (WSP), Water Treatment System (WTS), Water Storage Systems (WSSs), Water Distribution Points (WDP) and Water Supply Network (WSN); scientific estimation of long term demand of drinking water; minimization of physical and financial resources required for the plan implementation; water conservation and sanitation – could be done by applying several state-of-art geo-spatial programs developed by the author. Three programs - Multi-Algorithm Automation …