Physical Sciences and Mathematics Commons^™

Bayesian Function-On-Function Regression For Multi-Level Functional Data, Mark J. Meyer, Brent A. Coull, Francesco Versace, Paul Cinciripini, Jeffrey S. Morris

Jeffrey S. Morris

Medical and public health research increasingly involves the collection of more and more complex and high dimensional data. In particular, functional data|where the unit of observation is a curve or set of curves that are finely sampled over a grid -- is frequently obtained. Moreover, researchers often sample multiple curves per person resulting in repeated functional measures. A common question is how to analyze the relationship between two functional variables. We propose a general function-on-function regression model for repeatedly sampled functional data, presenting a simple model as well as a more extensive mixed model framework, along with multiple functional posterior …

Functional Regression, Jeffrey S. Morris

Jeffrey S. Morris

Functional data analysis (FDA) involves the analysis of data whose ideal units of observation are functions defined on some continuous domain, and the observed data consist of a sample of functions taken from some population, sampled on a discrete grid. Ramsay and Silverman's 1997 textbook sparked the development of this field, which has accelerated in the past 10 years to become one of the fastest growing areas of statistics, fueled by the growing number of applications yielding this type of data. One unique characteristic of FDA is the need to combine information both across and within functions, which Ramsay and …

Ordinal Probit Wavelet-Based Functional Models For Eqtl Analysis, Mark J. Meyer, Jeffrey S. Morris, Craig P. Hersh, Jarret D. Morrow, Christoph Lange, Brent A. Coull

Jeffrey S. Morris

Current methods for conducting expression Quantitative Trait Loci (eQTL) analysis are limited in scope to a pairwise association testing between a single nucleotide polymorphism (SNPs) and expression probe set in a region around a gene of interest, thus ignoring the inherent between-SNP correlation. To determine association, p-values are then typically adjusted using Plug-in False Discovery Rate. As many SNPs are interrogated in the region and multiple probe-sets taken, the current approach requires the fitting of a large number of models. We propose to remedy this by introducing a flexible function-on-scalar regression that models the genome as a functional outcome. The …

On Combining Neighbouring Extremals With Control Parameterization, Chongyang Liu, Qun Lin, Ryan Loxton, Kok Lay Teo

Chongyang Liu

In this paper, we consider the neighbouring extremals for a class of optimal control problems with control constraints. We first solve the optimal control problem using control parameterization method to obtain the optimal open-loop control and the optimal reference state. Then, a neighbouring feedback control law is derived for small state perturbations caused by changes on reference state at switching times.

Nonlinear State-Dependent Impulsive System In Fed-Batch Culture And Its Optimal Control, Bangyu Shen, Xiaojing Wang, Chongyang Liu

Chongyang Liu

In this paper, a nonlinear impulsive controlled system, in which the volume of feeding is taken as the control function, is proposed to formulate the fed-batch fermentation process.In the system, both impulsive moments and jumps size of state are state-dependent. Some important properties of the system are investigated. To maximize the concentration of target product at the terminal time, an optimal control model involving the nonlinear state-dependent impulsive controlled system is presented.The optimal control problem is subject to the continuous state inequality constraint and the control constraint. The existence of optimal control is also obtained. In order to derive the …

Horizontal Well’S Path Planning: An Optimal Switching Control, Zhaohua Gong, Kok Lay Teo, Chongyang Liu, Enmin Feng

Chongyang Liu

In this paper, we consider a three-dimensional horizontal well’s path planning problem, where the well’s path evolves as a combination of several constant-curvature smooth turn segments. The problem is formulated as an optimal switching control problem subject to continuous state inequality constraints. By applying the time-scaling transformation and constraint transcription in conjunction with local smooth approximation technique, the optimal switching control problem is approximated by a sequence of optimal parameter selection problems with only box constraints, each of which is solvable by gradient-based optimization techniques. The optimal path planning problems of the wells Ci-16-Cp146 and Jin27 in Liaohe oil field …

Application Of Colloidal Gas Aphron Suspensions Produced From Sapindus Mukorossi For Arsenic Removal From Contaminated Soil, Soumyadeep Mukhopadhyay Dr, Sumona Mukherjee Ms, Mohd Ali Hashim Dr, Bhaskar Sen Gupta Dr

Soumyadeep Mukhopadhyay Dr

Colloidal gas aphron dispersions (CGAs) can be described as a system of microbubbles suspended homogenously in a liquid matrix. This work examines the performance of CGAs in comparison to surfactant solutions for washing low levels of arsenic from an iron rich soil. Sodium Dodecyl Sulfate (SDS) and saponin, a biodegradable surfactant, obtained from Sapindus mukorossi or soapnut fruit were used for generating CGAs and solutions for soil washing. Column washing experiments were performed in down-flow and up flow modes at a soil pH of 5 and 6 using varying concentration of SDS and soapnut solutions as well as CGAs. Soapnut …

Towards Measuring Interventions In Rainfed Areas, Hippu Salk Kristle Nathan, Rajendra, Srijit Mishra

Srijit Mishra

This paper underlines the process through which we have arrived at the indicators for various thematic nodes to measure and evaluate interventions or comprehensive pilots in rainfed areas. We conceptualize a simple four stage process, i.e., ‘objective or goal formulation’, 'means finding', 'targets settings' and 'indicator identification', which we refer to as OMTI (Objective-Means-Target-Indicators) framework. In indicator literature, this kind of framework can be categorized under "thematic framework" or "goal oriented framework". The operationalization of OMTI framework highlights its nuances and brings forth its limitations. In order to overcome some of these limitations, we validate the OMTI framework using the …

Performance Evaluation Of Natural Iron-Rich Sandy Soil As A Low-Cost Adsorbent For Removal Of Lead From Water, Yee Sern Ng, Bhaskar Sen Gupta, Mohd Ali Hashim

Ng Yee-Sern

Technical feasibility of natural iron-rich sandy soil as a low-cost adsorbent for removal of lead from water was investigated . The soil, which had an iron content of 3,719 mg/kg, was collected from Hulu Langat, Malaysia, and was used for adsorption studies without any surface modification through chemical treatment. The effects of pH, solution: soil ratio and initial lead concentration on the adsorption efficiency were studied using response surface methodology based on Box–Behnken experimental design. The results showed that pH of the solution had the highest impact on the adsorption efficiency whereby adsorption efficiency of 97% could be achieved at …

In The Wake Of Charlie Hebdo, Muqtedar Khan

Muqtedar Khan

The essay reflects on the consequences of the Paris shooting.

An Optimal Threshold Strategy In The Two-Envelope Problem With Partial Information, Martin Egozcue, Luis Fuentes García

Martin Egozcue

No abstract provided.

The Topology Of Tile Invariants, Michael P. Hitchman

Michael P. Hitchman

In this note, we use techniques in the topology of 2-complexes to recast some tools that have arisen in the study of planar tiling questions. With spherical pictures, we show that the tile counting group associated to a set T of tiles and set of regions tileable by T is isomorphic to a quotient of the second homology group of a 2-complex built from T. In this topological setting, we derive some well-known tile invariants, one of which we apply to the solution of a tiling question involving modified rectangles.

The Symbiotic Relationship Between Information Retrieval And Informetrics, Dietmar Wolfram

Dietmar Wolfram

Informetrics and information retrieval (IR) represent fundamental areas of study within information science. Historically, researchers have not fully capitalized on the potential research synergies that exist between these two areas. Data sources used in traditional informetrics studies have their analogues in IR, with similar types of empirical regularities found in IR system content and use. Methods for data collection and analysis used in informetrics can help to inform IR system development and evaluation. Areas of application have included automatic indexing, index term weighting and understanding user query and session patterns through the quantitative analysis of user transaction logs. Similarly, developments …

Intelligent Water Drops Algorithm For Coordinating Between Cluster Spacecraft In A Communications-Denied Environment, Jeremy Straub

Jeremy Straub

This paper presents a modification of Shah-Hosseini’s Intelligent Water Drops (IWD) technique that can be utilized for collaborative control of multiple spacecraft in environments where communications are limited, intermittent or denied. It presents Shah- Hosseini’s base IWD algorithm as well as refinements thereof, which simplify it, making it more suitable for more computationally constrained environments (such as small spacecraft and UAVs). A framework for testing the proposed approach as well as several implementation impediments are discussed.

Estimating Controlled Direct Effects Of Restrictive Feeding Practices In The `Early Dieting In Girls' Study, Yeying Zhu, Debashis Ghosh, Donna L. Coffman, Jennifer S. Williams

Debashis Ghosh

In this article, we examine the causal effect of parental restrictive feeding practices on children’s weight status. An important mediator we are interested in is children’s self-regulation status. Traditional mediation analysis (Baron and Kenny, 1986) applies a structural equation modelling (SEM) approach and decomposes the intent-to-treat (ITT) effect into direct and indirect effects. More recent approaches interpret the mediation effects based on the potential outcomes framework. In practice, there often exist confounders that jointly influence the mediator and the outcome. Inverse probability weighting based on propensity scores are used to adjust for confounding and reduce the dimensionality of confounders simultaneously. …

Equivalence Of Kernel Machine Regression And Kernel Distance Covariance For Multidimensional Trait Association Studies, Wen-Yu Hua, Debashis Ghosh

Debashis Ghosh

Associating genetic markers with a multidimensional phenotype is an important yet challenging problem. In this work, we establish the equivalence between two popular methods: kernel-machine regression (KMR), and kernel distance covariance (KDC). KMR is a semiparametric regression framework that models covariate effects parametrically and genetic markers non-parametrically, while KDC represents a class of methods that include distance covariance (DC) and Hilbert-Schmidt independence criterion (HSIC), which are nonparametric tests of independence. We show that the equivalence between the score test of KMR and the KDC statistic under certain conditions can lead to a novel generalization of the KDC test that incorporates …

A General Approach To Goodness Of Fit For U Processes, Debashis Ghosh, Youngjoo Cho

Debashis Ghosh

Goodness of fit procedures are essential tools for assessing model adequacy in statistics. In this work, we present a general theory and approach to goodness of fit techniques based on U-processes for the accelerated failure time (AFT) model. Many of the examples will focus on U-statistics of order 2. While many authors have proposed goodness of fit tests for U-statistics of order one, less has been developed for higher order U-statistics. In this paper, we propose goodness of fit tests for U-statistics of order 2 by using theoretical results from Nolan and Pollard (1987) and Nolan and Pollard (1988). We …

A Boosting Algorithm For Estimating Generalized Propensity Scores With Continuous Treatments, Yeying Zhu, Donna L. Coffman, Debashis Ghosh

Debashis Ghosh

In this article, we study the causal inference problem with a continuous treatment variable using propensity score-based methods. For a continuous treatment, the generalized propensity score is defined as the conditional density of the treatment-level given covariates (confounders). The dose–response function is then estimated by inverse probability weighting, where the weights are calculated from the estimated propensity scores. When the dimension of the covariates is large, the traditional nonparametric density estimation suffers from the curse of dimensionality. Some researchers have suggested a two-step estimation procedure by first modeling the mean function. In this study, we suggest a boosting algorithm to …

Optimization Of A Photovoltaic Pumping System In Bejaia (Algeria) Climate, Rahrah Karima Jr, Djamila Rekioua Pr

REKIOUA Djamila Dr

Photovoltaic energy is used in different applications and especially in water pumping and irrigation in remote areas. However, the performances of a photovoltaic pumping system can be degraded with variations of insolation and in order to maximize the efficiency of the photovoltaic energy system, it is necessary to track the maximum power point of the PV array. Many methods have been developed to determine the maximum power point (MPP). In this paper we present the results of performance optimization of a PV pumping system in Bejaia (Algeria) climate. The pumped water is desired to satisfy the domestic needs of three …

Testing Hypotheses About Medical Test Accuracy: Considerations For Design And Inference, Adam J. Branscum, Dunlei Cheng, J Jack Lee

Dunlei Cheng

Developing new medical tests and identifying single biomarkers or panels of biomarkers with superior accuracy over existing classifiers promotes lifelong health of individuals and populations. Before a medical test can be routinely used in clinical practice, its accuracy within diseased and non-diseased populations must be rigorously evaluated. We introduce a method for sample size determination for studies designed to test hypotheses about medical test or biomarker sensitivity and specificity. We show how a sample size can be determined to guard against making type I and/or type II errors by calculating Bayes factors from multiple data sets simulated under null and/or …

A Facile And Acid-Free Approach Towards The Preparation Of Sulphonated Multi-Walled Carbon As A Strong Protonic Acid Catalyst For Biodiesel Production, Eng-Poh Ng Dr.

Eng-Poh Ng

No abstract provided.

Reduction Of Graphene Oxide Nanosheets By Natural Beta Carotene And Its Potential Use As Supercapacitor Electrode, Eng-Poh Ng Dr.

Eng-Poh Ng

No abstract provided.

Effect Of Extra-Framework Cations Of Ltl Nanozeolites To Inhibit Oil Oxidation, Eng-Poh Ng Dr.

Eng-Poh Ng

No abstract provided.

Anomalous Textures In Porphyritic Granite Of Andhra Pradesh (India), Eric R. Force

Eric R Force

Apparently perthitic textures of microcline phenocrysts in this rock are not due to exsolution but to deformation. Microscopic fracture planes show no offset, however, and are restricted to feldspar crystals, i.e. absent in quartz. A hypothesis of depth formation is presented, and possible shock origin discussed.

Geometry: Drawing From The Islamic Tradition, Carol Bier

Carol Bier

Getting students involved in careful observation and analysis and encouraging their exploration of cultural forms of expression is an excellent means of introducing mathematical ideas. Geometric patterns abound in Islamic art and architecture. Exhibiting great ingenuity over the centuries, Muslim artists and craftsmen created beautiful patterns to adorn architectural monuments and exquisite objects. The Alhambra in Spain and the Taj Mahal in India offer the most famous examples of extraordinary patterns using brick and glazed tile, or carved and inlaid marble. Other examples of patterns are made using metal, wood, and fiber. Students may gain conceptual and theoretical understanding of …

Inżynieria Chemiczna Ćw., Wojciech M. Budzianowski

Wojciech Budzianowski

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Tematyka Prac Doktorskich, Wojciech M. Budzianowski

Wojciech Budzianowski

No abstract provided.

The Number Of Subjects Per Variable Required In Linear Regression Analyses, Peter Austin, Ewout Steyerberg

Peter Austin

Objectives: To determine the number of independent variables that can be included in a linear regression model.

Study Design and Setting: We used a series of Monte Carlo simulations to examine the impact of the number of subjects per variable (SPV) on the accuracy of estimated regression coefficients and standard errors, on the empirical coverage of estimated confidence intervals, and on the accuracy of the estimated R2 of the fitted model.

Results: A minimum of approximately two SPV tended to result in estimation of regression coefficients with relative bias of less than 10%. Furthermore, with this minimum number of SPV, …

Statistical Power In Parallel Group Point Exposure Studies With Time-To-Event Outcomes: An Empirical Comparison Of The Performance Of Randomized Controlled Trials And The Inverse Probability Of Treatment Weighting (Iptw) Approach, Peter Austin, Tibor Schuster, Robert W. Platt

Peter Austin

Background: Estimating statistical power is an important component of the design of both randomized controlled trials (RCTs) and observational studies. Methods for estimating statistical power in RCTs have been well described and can be implemented simply. In observational studies, statistical methods must be used to remove the effects of confounding that can occur due to non-random treatment assignment. Inverse probability of treatment weighting (IPTW) using the propensity score is an attractive method for estimating the effects of treatment using observational data. However, sample size and power calculations have not been adequately described for these methods.

Methods: We used an extensive …

Moving Towards Best Practice When Using Inverse Probability Of Treatment Weighting (Iptw) Using The Propensity Score To Estimate Causal Treatment Effects In Observational Studies, Peter Austin, Elizabeth Stuart

Peter Austin

The propensity score is defined as a subject’s probability of treatment selection, conditional on observed baseline covariates.Weighting subjects by the inverse probability of treatment received creates a synthetic sample in which treatment assignment is independent of measured baseline covariates. Inverse probability of treatment weighting (IPTW) using the propensity score allows one to obtain unbiased estimates of average treatment effects. However, these estimates are only valid if there are no residual systematic differences in observed baseline characteristics between treated and control subjects in the sample weighted by the estimated inverse probability of treatment. We report on a systematic literature review, in …