Physical Sciences and Mathematics Commons^™

Online Arima Algorithms For Time Series Prediction, Chenghao Liu, Hoi, Steven C. H., Peilin Zhao, Jianling Sun

Research Collection School Of Computing and Information Systems

Autoregressive integrated moving average (ARIMA) is one of the most popular linear models for time series forecasting due to its nice statistical properties and great flexibility. However, its parameters are estimated in a batch manner and its noise terms are often assumed to be strictly bounded, which restricts its applications and makes it inefficient for handling large-scale real data. In this paper, we propose online learning algorithms for estimating ARIMA models under relaxed assumptions on the noise terms, which is suitable to a wider range of applications and enjoys high computational efficiency. The idea of our ARIMA method is to …

Mechanisms For Improving Information Quality In Smartphone Crowdsensing Systems, Francesco Restuccia

Doctoral Dissertations

"Given its potential for a large variety of real-life applications, smartphone crowdsensing has recently gained tremendous attention from the research community. Smartphone crowdsensing is a paradigm that allows ordinary citizens to participate in large-scale sensing surveys by using user-friendly applications installed in their smartphones. In this way, fine-grained sensing information is obtained from smartphone users without employing fixed and expensive infrastructure, and with negligible maintenance costs.

Existing smartphone sensing systems depend completely on the participants' willingness to submit up-to-date and accurate information regarding the events being monitored. Therefore, it becomes paramount to scalably and effectively determine, enforce, and optimize the …

An Efficient Method For Optimizing Segmentation Parameters, Jacob D' Avy, Wei-Wen Hsu, Chung-Hao Chen, Andreas F. Koschan, Mongi Abidi

Electrical & Computer Engineering Faculty Publications

Segmenting an image into meaningful regions is an important step in many computer vision applications such as facial recognition, target tracking and medical image analysis. Because image segmentation is an ill-posed problem, parameters are needed to constrain the solution to one that is suitable for a given application. For a user, setting parameter values is often unintuitive. We present a method for automating segmentation parameter selection using an efficient search method to optimize a segmentation objective function. Efficiency is improved by utilizing prior knowledge about the relationship between a segmentation parameter and the objective function terms. An adaptive sampling of …

Stabilized Least Squares Migration, Graham Ganssle

LSU New Orleans Theses and Dissertations

Before raw seismic data records are interpretable by geologists, geophysicists must process these data using a technique called migration. Migration spatially repositions the acoustic energy in a seismic record to its correct location in the subsurface. Traditional migration techniques used a transpose approximation to a true acoustic propagation operator. Conventional least squares migration uses a true inverse operator, but is limited in functionality by the large size of modern seismic datasets. This research uses a new technique, called stabilized least squares migration, to correctly migrate seismic data records using a true inverse operator. Contrary to conventional least squares migration, this …

Analysis Of The Fabrication Conditions In Organic Field-Effect Transistors, Rachel M. Rahn, Yan Zhao, Jianguo Mei

The Summer Undergraduate Research Fellowship (SURF) Symposium

Polymer-based organic field-effect transistors have raised substantial awareness because they enable low-cost, solution processing techniques, and have the potential to be implemented in flexible, disposable organic electronic devices. The performance of these devices is highly dependent on the processing conditions, as well as the intrinsic properties of the polymer. Processing conditions play an important role in semiconductor film formation and device performance. These factors may provide an important link between structure and performance. In this study, an empirical analysis tool, Process Scout, was applied to assess processing factors such as polymer concentration and silicon modification. This sanctioned the creation of …

Ad-Hoc Automated Teller Machine Failure Forecast And Field Service Optimization, Michelle L. F. Cheong, Ping Shung Koo, B. Chandra Babu

Research Collection School Of Computing and Information Systems

As part of its overall effort to maintain good customer service while managing operational efficiency and reducing cost, a bank in Singapore has embarked on using data and decision analytics methodologies to perform better ad-hoc ATM failure forecasting and plan the field service engineers to repair the machines. We propose using a combined Data and Decision Analytics Framework which helps the analyst to first understand the business problem by collecting, preparing and exploring data to gain business insights, before proposing what objectives and solutions can and should be done to solve the problem. This paper reports the work in analyzing …

Stochastic Optimization Via Forward Slice, Bob A. Salim, Lurdes Y. T. Inoue

UW Biostatistics Working Paper Series

Optimization consists of maximizing or minimizing a real-valued objective function. In many problems, the objective function may not yield closed-form solutions. Over many decades, optimization methods, both deterministic and stochastic, have been developed to provide solutions to these problems. However, some common limitations of these methods are the sensitivity to the initial value and that often current methods only find a local (non-global) extremum. In this article, we propose an alternative stochastic optimization method, which we call "Forward Slice", and assess its performance relative to available optimization methods.

Design And Verification Environment For High-Performance Video-Based Embedded Systems, Michael Mefenza Nentedem

Graduate Theses and Dissertations

In this dissertation, a method and a tool to enable design and verification of computation demanding embedded vision-based systems is presented. Starting with an executable specification in OpenCV, we provide subsequent refinements and verification down to a system-on-chip prototype into an FPGA-Based smart camera. At each level of abstraction, properties of image processing applications are used along with structure composition to provide a generic architecture that can be automatically verified and mapped to the lower abstraction level. The result is a framework that encapsulates the computer vision library OpenCV at the highest level, integrates Accelera's System-C/TLM with UVM and QEMU-OS …

Principal Component Analysis And Optimization: A Tutorial, Robert Reris, J. Paul Brooks

Statistical Sciences and Operations Research Publications

No abstract provided.

Determination Of Electromagnetic Properties Of Steel For Prediction Of Stray Losses In Power Transformers, Leonardo Strac, Damir Zarko

Turkish Journal of Electrical Engineering and Computer Sciences

This paper introduces a method for determination of equivalent linear electromagnetic parameters (constant complex permeability and electrical conductivity) of nonlinear magnetic steel, which can be used in a time-harmonic finite-element simulation to yield the same losses in the volume of that material as the measured ones. The conductivity and the static hysteresis loop of the steel have been measured, from which complex permeability as a function of flux density has been extracted. The indirect measurement of losses in various samples of nonmagnetic and magnetic steel has been carried out using a physical model of a transformer core with a coil. …

Superior Decoupled Control Of Active And Reactive Power For Three-Phase Voltage Source Converters, Hesam Rahbarimagham, Erfan Maali Amiri, Behrooz Vahidi, Gevorg Babamalek Gharehpetian, Mehrdad Abedi

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents an active-reactive power control strategy for voltage source converters (VSCs) based on derivation of the direct and quadrature components of the VSC output current. The proposed method utilizes a multivariable proportional-integral controller and provides almost completely decoupled control capability of the active and reactive power with almost full disturbance rejection due to step changes in the power exchanged between the VSC and the grid. It also imposes fast transient response and zero steady-state error as compared to the conventional power control approaches. The applicability of the proposed power control strategy for providing the robust stability of the …

Effective Auto Encoder For Unsupervised Sparse Representation, Faria Mahnaz

Wayne State University Theses

High dimensionality and the sheer size of unlabeled data available today demand

new development in unsupervised learning of sparse representation. Despite of recent

advances in representation learning, most of the current methods are limited when

dealing with large scale unlabeled data. In this study, we propose a new unsupervised

method that is able to learn sparse representation from unlabeled data efficiently. We

derive a closed-form solution based on the sequential minimal optimization (SMO)

for training an auto encoder-decoder module, which efficiently extracts sparse and

compact features from any data set with various size. The inference process in the

proposed learning …

The Impact Of Increased Optimization Problem Dimensionality On Cultural Algorithm Performance, Yang Yang

Wayne State University Theses

ABSTRACT

The Impact of Increased Optimization Problem Dimensionality on

Cultural Algorithm Performance

by

Yang Yang

August 2015

Advisor: Dr. Robert Reynolds

Major: Computer Science

Degree: Master of Science

In this thesis, we investigate the performance of Cultural Algorithms when dealing with the increasing dimensionality of optimization problems. The research is based on previous cultural algorithm approaches with the Cultural Algorithms Toolkit, CAT 2.0, which supports a variety of co-evolutionary features at both the knowledge and population levels. In this project, the system was applied to the solution of 60 randomly generated problems that ranged from 2-dimensional to 5-dimensional problem spaces. …

Contributions To The Solution Of Large Nonlinear Systems Via Model-Order Reduction And Interval Constraint Solving Techniques, Leobardo Valera

Open Access Theses & Dissertations

Many engineering problems boil down to solving partial differential equations (PDEs) that describe real-life phenomena. Nevertheless, efficiently and reliably solving such problems constitutes a major challenge in computational sciences and in engineering in general.

PDE-based systems can reach sizes so large after they are discretized. The large size in these problems generate several issues, among them we can mention: large space of storing, computing time, and the most important, lost of accuracy. A popular approach to solving such problems is assume that the PDE's solution is in a subspace, and the solution is sought there. This assumption and later searching …

Mathematical Modeling For Platform-Based Product Configuration Considering Total Life-Cycle Sustainability, Tian Lan

Theses and Dissertations--Mechanical and Aerospace Engineering

Many companies are using platform-based product designs to fulfill the requirements of customers while maintaining low cost. However, research that integrates sustainability into platform-based product design is still limited. Considering sustainability during platform-based design process is a challenge because the total life-cycle from pre-manufacturing, manufacturing and use to post-use stages as well as economic, environmental and societal performance in these stages must be considered. In this research, an approach for quantifying sustainability is introduced and a mathematical model is developed for identifying a more sustainable platform. Data from life-cycle assessment is used to quantify environmental factors; criteria from the Product …

Improving Processing By Adaption To Conditional Geostatistical Simulation Of Block Compositions, R. Tolosana-Delgado, Ute A. Mueller, K. G. Van Den Boogaart, C. Ward, J. Gutzmer

Research outputs 2014 to 2021

Exploitation of an ore deposit can be optimized by adapting the beneficiation processes to the properties of individual ore blocks. This can involve switching in and out certain treatment steps, or setting their controlling parameters. Optimizing this set of decisions requires the full conditional distribution of all relevant physical parameters and chemical attributes of the feed, including concentration of value elements and abundance of penalty elements. As a first step towards adaptive processing, the mapping of adaptive decisions is explored based on the composition, in value and penalty elements, of the selective mining units. Conditional distributions at block support are …

Optimization Schemes For The Inversion Of Bouguer Gravity Anomalies, Azucena Zamora

Open Access Theses & Dissertations

Data sets obtained from measurable physical properties of the Earth structure have helped advance the understanding of its tectonic and structural processes and constitute key elements for resource prospecting. 2-Dimensional (2-D) and 3-D models obtained from the inversion of geophysical data sets are widely used to represent the structural composition of the Earth based on physical properties such as density, seismic wave velocities, magnetic susceptibility, conductivity, and resistivity. The inversion of each one of these data sets provides structural models whose consistency depends on the data collection process, methodology, and overall assumptions made in their individual mathematical processes. Although sampling …

A Framework And System For A Multi-Model Decision Aid For Sustainable Farming Practices, Kasi Bharath Vegesana

Computational Modeling & Simulation Engineering Theses & Dissertations

Decision support systems (DSS) for farmers address the need for modeling multiple processes and scenarios that affect farmer decision making. Existing DSS have various drawbacks that stop them from being deployed as decision support tools. This research proposes a multi-model simulation framework that can be used to analyze farm management practices at the crop level, individual farm level and at the community level to show the impact and alternatives for smallholder farming practices. A generic crop growth model is proposed, based on existing equations. We run sensitivity analysis on the model to identify important variables. The outputs from the crop …

Shape Optimization For Drag Minimization Using The Navier-Stokes Equation, Chukwudi Paul Chukwudozie

LSU Master's Theses

Fluid drag is a force that opposes relative motion between fluid layers or between solids and surrounding fluids. For a stationary solid in a moving fluid, it is the amount of force necessary to keep the object stationary in the moving fluid. In addition to fluid and flow conditions, pressure drag on a solid object is dependent on the size and shape of the object. The aim of this project is to compute the shape of a stationary 2D object of size 3.5 m2 that minimizes drag for different Reynolds numbers. We solve the problem in the context of shape …

Truckload Shipment Planning And Procurement, Neo Nguyen

Graduate Theses and Dissertations

This dissertation presents three issues encountered by a shipper in the context of truckload transportation. In all of the studies, we utilize optimization techniques to model and solve the problems. Each study is inspired from the real world and much of the data used in the experiments is real data or representative of real data.

The first topic is about the freight consolidation in truckload transportation. We integrate it with a purchase incentive program to increase truckload utilization and maximize profit. The second topic is about supporting decision making collaboration among departments of a manufacturer. It is a bi-objective optimization …

High Dimensional Non-Linear Optimization Of Molecular Models, Joseph C. Fogarty

USF Tampa Graduate Theses and Dissertations

Molecular models allow computer simulations to predict the microscopic properties of macroscopic systems. Molecular modeling can also provide a fully understood test system for the application of theoretical methods. The power of a model lies in the accuracy of the parameter values which govern its mathematical behavior. In this work, a new software, called ParOpt, for general high dimensional non-linear optimization will be presented. The software provides a very general framework for the optimization of a wide variety of parameter sets. The software is especially powerful when applied to the difficult task of molecular model parameter optimization. Three applications of …

Concept Of Online Assisted Platform For Technologies And Management In Communications – Optimek, Galia Marinova, Vassil Guliashki, Ognyan Chikov

UBT International Conference

The paper describes the concept of a Multimodular Multydisciplinary platform, contacting through unified templates in a Portal with knowledge, with Useful INTERNET resources, in order to provide advanced research and education. Usually the online resources available are mainly in the area of e- and distance education, but still an understanding is missing for the scale and the use of studying and the systematization of the online resource. The new concept has an accent of the useful INTERNET resource and the development of a System of nets to it, in the aim of solving tasks and generating new knowledge in the …

Scalable Tuning Of Building Models To Hourly Data, Aaron Garrett, Joshua New

Research, Publications & Creative Work

Energy models of existing buildings are unreliable unless calibrated so that they correlate well with actual energy usage. Manual tuning requires a skilled professional and is prohibitively expensive for small projects, imperfect, nonrepeatable, and not scalable to the dozens of sensor channels that smart meters, smart appliances, and sensors are making available. A scalable, automated methodology is needed to quickly, intelligently calibrate building energy models to all available data, increase the usefulness of those models, and facilitate speed-and-scale penetration of simulation-based capabilities into the marketplace for actualized energy savings. The "Autotune" project is a novel, model-agnostic methodology that leverages supercomputing, …

Optimization Of Switch Virtual Keyboard By Using Computational Modelling, Xiao Zhang

Open Access Theses

In this thesis, I first reviewed some keyboard technologies used by people with motor difficulties, and described design elements that influence efficiency. I cast the design of a switch keyboard as an optimization problem, and arrangement of keys on such a keyboard as a Mixed Integer Programming problem. One significant variable in the MIP problem, the error rate, is related to several other variables. I treated modeling of the error rate as a parameter estimation problem, and used a data mining method. I designed HCI experiments to gather data for parameter estimation, using Bayesian logistic regression model. The empirical data …

Optimizing Bio-Retention Locations For Stormwater Management Using Genetic Algorithm, Dieu Huong Trinh, Ting Fong May Chui

International Conference on Hydroinformatics

To minimize the change of hydrological regime due to urbanization, stormwater best management practices have been enforced in the past few decades in certain urban areas. One approach is to implement small-scale hydrologic controls, such as bio-retention systems, throughout a catchment. Optimization techniques have also been applied to determine the locations that give the most hydrological benefits. However, optimization tools are commonly built in together with specific hydrological models. Thus, the choices and components of hydrological models are usually restricted. Furthermore, it is redundant to build another hydrological model that has a built-in optimization tool if a hydrological model, and …

Short-Term Optimization Of A Canal Network For Navigation And Water Management, Arnejan Van Loenen, Min Xu, Robin Engel

International Conference on Hydroinformatics

We present the design, implementation and operational use of a short-term optimization approach for the operational water management of the Twentekanalen canal system for navigation and water resources management. The system was originally designed for navigation and its construction had been completed in 1938. In the past decades, it also became increasingly important for the regional water management. In summer periods, the system provides the region with fresh water and helps to drain the area otherwise. The short-term optimization is implemented in the Operational Monitoring System for the National Regulated Water Systems for advising the operating staff on the operation …

Flood Resilience Assessment In Urban Drainage Systems Through Multi-Objective Optimisation, Carlos Martínez-Cano, Beheshtah Toloh, Arlex Sanchez-Torres, Zoran Vojinović, Damir Brdjanovic

International Conference on Hydroinformatics

In future years, economic development, urbanisation and heavy rainfall events are expected to increase in urban areas, in particular in developing countries. It is well known that urban development has a strong impact on the water cycle such as increase of flood peaks and volume, decrease of base flow, hydraulic stress and water pollution. Resilience measures are still needed to improve urban flood risk, the possibilities to provide indicators that could be used to characterize urban resilience related to flooding is outmost importance. The work described here presents an optimisation framework for urban drainage rehabilitation that incorporates in the decision …

An Optimization And Decision Support Tool For Long-Term Strategies In The Transformation Of Urban Water Infrastructure, Theo G. Schmitt, Silja Worreschk, Inka Kaufmann Alves, Frank Herold, Clemens Thielen

International Conference on Hydroinformatics

Predicted climatic, demographic and socio-economic developments cause major adaptions of urban water infrastructures. The central water supply and wastewater systems in Europe do not meet the increased requirements of resource efficiency and sustainability anymore. Especially in rural areas predicted demographic change and the particular differentiated settlement structure affect the functionality of present water infrastructures. These new challenges require extensive and flexible adaptions or even a long-term and dynamic system change of urban infrastructures. These long-term transformations of infrastructure systems require the design of innovative strategies. In the project presented, environmental engineers together with city planners, mathematicians and computer scientists develop …

Effective Data Management Enables Intelligent Utility Management, Gary L.S. Wong

International Conference on Hydroinformatics

Instrumentation and automation plays a vital role to managing the water industry. These systems generate vast amounts of data that must be effectively managed in order to enable intelligent decision making. Time series data management software, commonly known as data historians are used for collecting and managing real-time (time series) information. More advanced software solutions provide a data infrastructure or utility wide Operations Data Management System (ODMS) that stores, manages, calculates, displays, shares, and integrates data from multiple disparate automation and business systems that are used daily in water utilities. These ODMS solutions are proven and have the ability to …

An Optimization Model For Prioritizing Sewerage Maintenance Scheduling, Juan David Torres Turriago, Juan Pablo Rodriguez, Juan David Palacio

International Conference on Hydroinformatics

Water utility companies, responsible for providing water supply and sewerage services to the urban population, are constantly seeking to improve their service.In the case of sewer systems, effective scheduling of preventive maintenance of urban water infrastructure has been identified as an important activity in order to reduce costs and protect the integrity of citizens and the surrounding, both built and natural, environments. Consequently, with particular focus on Bogotá (Colombia), we developed an optimization model that generates a preventive maintenance plan on a set of zones withinthe city. These zones have in common a high failure probability over a defined time …