Physical Sciences and Mathematics Commons^™

Toward Energy Efficient Systems Design For Data Centers, Bing Luo

Wayne State University Dissertations

Surge growth of numerous cloud services, Internet of Things, and edge computing promotes continuous increasing demand for data centers worldwide. Significant electricity consumption of data centers has tremendous implications on both operating and capital expense. The power infrastructure, along with the cooling system cost a multi-million or even billion dollar project to add new data center capacities. Given the high cost of large-scale data centers, it is important to fully utilize the capacity of data centers to reduce the Total Cost of Ownership. The data center is designed with a space budget and power budget. With the adoption of high-density …

Bundle: Taming The Cache And Improving Schedulability Of Multi-Threaded Hard Real-Time Systems, Corey Tessler

Wayne State University Dissertations

For hard real-time systems, schedulability of a task set is paramount. If a task set is not deemed schedulable under all conditions, the system may fail during operation and cannot be deployed in a high risk environment. Schedulability testing has typically been separated from worst-case execution time (WCET) analysis. Each task’s WCET value is calculated independently and provided as input to a schedulability test. However, a task’s WCET value is influenced by scheduling decisions and the impact of cache memory. Thus, schedulability tests have been augmented to include cache-related preemption delay (CRPD). From this classical perspective, the effect of cache …

Attention-Based Models For Deep Reinforcement Learning, Elaheh Barati

Wayne State University Dissertations

Attention mechanism has shown promising results in many fields of machine learning such as image captioning and machine translation. In this work, we focus on attention-based models for deep reinforcement learning. We concentrate on developing deep neural networks

that are fed with a sequence of high-dimensional raw pixels. Particularly, we design attention-based models for challenging tasks including navigation, autonomous driving, and video captioning. In these tasks, deep reinforcement learning algorithms facilitate training of their sophisticated models, and the attention mechanism serves different purposes. In the navigation and autonomous driving tasks, through the attention mechanism, our model attends over different views …

A Comparative Study Of Kendall-Theil Sen, Siegel Vs Quantile Regression With Outliers, Ahmad Farooqi

Wayne State University Dissertations

Researchers in social and behavioral sciences usually interested in study the relationship between a response variable Y_i and one or more independent predictors〖 X〗_i either for the purpose of explanation or prediction. Ordinary Least Square Regression is a parametric approach used to study this kind of relationship. One of the disadvantages of Ordinary Least Square is it does not fit well in the presence of outliers in the response variable Y_i or both in the response variable Y_i and the predictor variable〖 X〗_i, also if the data were sampled from a non-normal distribution. Quantile Regression, Theil-Sen regression, and the modified …

Utilizing Knowledge Bases In Information Retrieval For Clinical Decision Support And Precision Medicine, Saeid Balaneshinkordan

Wayne State University Dissertations

Accurately answering queries that describe a clinical case and aim at finding articles in a collection of medical literature requires utilizing knowledge bases in capturing many explicit and latent aspects of such queries. Proper representation of these aspects needs knowledge-based query understanding methods that identify the most important query concepts as well as knowledge-based query reformulation methods that add new concepts to a query. In the tasks of Clinical Decision Support (CDS) and Precision Medicine (PM), the query and collection documents may have a complex structure with different components, such as disease and genetic variants that should be transformed to …

The Use Of Cultural Algorithms To Learn The Impact Of Climate On Local Fishing Behavior In Cerro Azul, Peru, Khalid Kattan

Wayne State University Dissertations

Recently it has been found that the earth’s oceans are warming at a pace that is 40% faster than predicted by a United Nations panel a few years ago. As a result, 2019 has become the warmest year on record for the earth’s oceans. That is because the oceans have acted as a buffer by absorbing 93% of the heat produced by the greenhouse gases [40].

The impact of the oceanic warming has already been felt in terms of the periodic warming of the Pacific Ocean as an effect of the ENSO process. The ENSO process is a cycle of …

Learning From Heterogeneous Data, Lu Wang

Wayne State University Dissertations

Data with both heterogeneity and homogeneity is now ubiquitous due to the development of multitudinous data collection techniques. To encode the data heterogeneity and homogeneity, we focus on unsupervised and supervised learning approaches. In unsupervised learning, to consider both data heterogeneity and homogeneity, we develop three clustering frameworks to maximize the heterogeneity among data sub-groups and homogeneity within each data sub-group for over-dispersed data in three different data types, i.e., alphabetic, network and mixed feature types data. In supervised learning, the traditional approaches, however, either build a global model for a whole group including all sub-groups, which fail to consider …

3d Surface Registration Using Geometric Spectrum Of Shapes, Hajar Hamidian

Wayne State University Dissertations

Morphometric analysis of 3D surface objects are very important in many biomedical applications and clinical diagnoses. Its critical step lies in shape comparison and registration. Considering that the deformations of most organs such as heart or brain structures are non-isometric, it is very difficult to find the correspondence between the shapes before and after deformation, and therefore, very challenging for diagnosis purposes.

To solve these challenges, we propose two spectral based methods. The first method employs the variation of the eigenvalues of the Laplace-Beltrami operator of the shape and optimize a quadratic equation in order to minimize the distance between …

Reporting Number Needed To Treat In Clinical Trials Published In Physical Therapy Specific Literature 1989 - 2018, Susan Ann Talley

Wayne State University Dissertations

Evidence-based practice requires physical therapists to make clinical decisions about the best intervention to use when providing services to patients/clients. Although null hypothesis significance testing (NHST) is frequently used to interpret the outcome of a clinical trial investigating the comparative effectiveness of an intervention, statistical significance does not directly translate into clinical importance. Number needed to treat (NNT) is a measure of effect size (ES) that may be particularly useful when translating the results from clinical trials to PT clinical practice. The purpose of this study was to conduct a bibliometric content analysis of the methods of reporting research results …

Capso: A Multi-Objective Cultural Algorithm System To Predict Locations Of Ancient Sites, Samuel Dustin Stanley

Wayne State University Dissertations

ABSTRACT

CAPSO: A MULTI-OBJECTIVE CULTURAL ALGORITHM SYSTEM TO PREDICT LOCATIONS OF ANCIENT SITES

by

SAMUEL DUSTIN STANLEY

August 2019

Advisor: Dr. Robert Reynolds

Major: Computer Science

Degree: Doctor of Philosophy

The recent archaeological discovery by Dr. John O’Shea at University of Michigan of prehistoric caribou remains and Paleo-Indian structures underneath the Great Lakes has opened up an opportunity for Computer Scientists to develop dynamic systems modelling these ancient caribou routes and hunter-gatherer settlement systems as well as the prehistoric environments that they existed in. The Wayne State University Cultural Algorithm team has been interested assisting Dr. O’Shea’s archaeological team by …

The Dynamic Nature And Biophysical Characterization Of Isu1, Fe-S Cluster Assembly Scaffold Protein In Saccharomyces Cerevisiae, And Its Significance To Human Disease, Brianne Elizabeth Lewis

Wayne State University Dissertations

Mitochondrial Fe-S cluster biosynthesis is accomplished within yeast utilizing the biophysical characteristics of the “Isu1” scaffold protein. As a member of a highly homologous protein family, Isu1 has sequence conservation with orthologs and a conserved ability to assemble [2Fe-2S] clusters. Regardless of species, scaffold orthologs can exist in both “disordered” and “structured” conformations and is directly related to conformations utilized during Fe-cofactor assembly. During assembly, the scaffold directs the delivery and the utilization of both Fe(II) and sulfide substrates in order to produce [2Fe-2S] clusters, however Zn(II) binding can alter the activity of the scaffold with stabilizing the protein in …

Machine Learning Methods For The Analysis Of Clinical Conversation, Md Mehedi Hasan

Wayne State University Dissertations

Motivational Interviewing (MI) is an evidence-based communication technique to increase intrinsic motivation and self-efficacy for behavior change. This goal is achieved through the exploration of the patient's own desires, ability, reasons, need for and commitment to the targeted behavior change. However, communication science approaches to understanding the efficacy of MI are inherently limited by traditional qualitative coding methods which is a time-consuming and resource-intensive process. Thus, an efficient method is required to automate the coding process which will accelerate the pace of communication research in behavioral science. The specific provider behaviors responsible for the elicitation of change talk, are also …

Solvent Effects And Charge Transfer States In Organic Photovoltaics, Kangmin Liu

Wayne State University Dissertations

Due to their various advantages, including lightweight, flexible, and cheap manufacturing, organic photovoltaic materials have gained enormous research interest. Over nearly two decades, the power conversion efficiency of organic solar devices has increased dramatically. However, it is still low compared to traditional inorganic semiconductors. In order to improve efficiency, a better understanding of the basic thermodynamic properties of the light-to-electricity power conversion process is needed. One nontrivial aspect of organic solar cells is the low dielectric constant, which leads to tightly-bound excitons upon vertical excitations. The separation of electron-hole pairs requires a larger driving force to overcome the Coulombic binding …

Functional Characterization Of Accessory Proteins And Novel Activities In Direct And Indirect Trna Aminoacylation, Udumbara Menike Rathnayake

Wayne State University Dissertations

Indirect tRNA aminoacylation is essential for most bacteria and archaea, particularly when these species do not have genes encoding asparaginyl- and/or glutaminyl-tRNA synthetase (AsnRS and GlnRS). In the absence of AsnRS, the first step in Asn-tRNAAsn synthesis involves misacylation of tRNAAsn with aspartate to produce Asp-tRNAAsn; this reaction is catalyzed by a non-discriminating aspartyl-tRNA synthetase (ND-AspRS). Subsequently, in bacteria, an amidotransferase called GatCAB converts Asp-tRNAAsn to Asn-tRNAAsn. An analogous, two-step processes exist to produce Gln-tRNAGln. In this case, a non-discriminating glutamyl-tRNA synthetase (ND-GluRS) misacylates tRNAGln to produce Glu-tRNAGln, which is then converted to Gln-tRNAGln by GatCAB. The central hub of …

A Proficient Two-Stage Stratified Randomized Response Strategy, Tanveer A. Tarray, Housila P. Singh

Journal of Modern Applied Statistical Methods

A stratified randomized response model based on R. Singh, Singh, Mangat, and Tracy (1995) improved two-stage randomized response strategy is proposed. It has an optimal allocation and large gain in precision. Conditions are obtained under which the proposed model is more efficient than R. Singh et al. (1995) and H. P. Singh and Tarray (2015) models. Numerical illustrations are also given in support of the present study.

Simple Unbalanced Ranked Set Sampling For Mean Estimation Of Response Variable Of Developmental Programs, Girish Chandra, Dinesh S. Bhoj, Rajiv Pandey

Journal of Modern Applied Statistical Methods

An unbalanced ranked set sampling (RSS) procedure on the skewed survey variable is proposed to estimate the population mean of a response variable from the area of developmental programs which are generally implemented under different phases. It is based on the unbalanced RSS under linear impacts of the program and is compared with the estimators based on simple random sampling (SRS) and balanced RSS. It is shown that the relative precision of the proposed estimator is higher than those of the estimators based on SRS and balanced RSS for three chosen skewed distributions of survey variables.

Extended Method For Several Dichotomous Covariates To Estimate The Instantaneous Risk Function Of The Aalen Additive Model, Luciane Teixeira Passos Giarola, Mario Javier Ferrua Vivanco, Marcelo Angelo Cirillo, Fortunato Silva Menezes

Journal of Modern Applied Statistical Methods

The instantaneous risk function of Aalen’s model is estimated considering dichotomous covariates, using parametric accumulated risk functions to smooth cumulative risk of Aalen by grouping the individuals into sets named parcels. This methodology can be used for data with dichotomous covariates.

Flux Of Particulate Elements In The North Atlantic Ocean Constrained By Multiple Radionuclides, Christopher T. Hayes, Erin E. Black, Robert F. Anderson, Mark Baskaran, Ken O. Buesseler, Matthew A. Charette, Hai Cheng, J. Kirk Cochran, R. Lawrence Edwards, Patrick Fitzgerald, Phoebe J. Lam, Yanbin Lu, Stephanie O. Morris, Daniel C. Ohnemus, Frank J. Pavia, Gillian Stewart, Yi Tang

Environmental Science and Geology Faculty Research Publications

Sinking particles strongly regulate the distribution of reactive chemical substances in the ocean, including particulate organic carbon and other elements (e.g., P, Cd, Mn, Cu, Co, Fe, Al, and 232Th). Yet, the sinking fluxes of trace elements have not been well described in the global ocean. The U.S. GEOTRACES campaign in the North Atlantic (GA03) offers the first data set in which the sinking flux of carbon and trace elements can be derived using four different radionuclide pairs (238U:234Th ;210Pb:210Po; 228Ra:228Th; and 234U:230Th) at stations co-located with sediment trap fluxes for comparison. Particulate organic carbon, particulate P, and particulate Cd …

The Impact Of Sample Size In Cross-Classified Multiple Membership Multilevel Models, Hyewon Chung, Jiseon Kim, Ryoungsun Park, Hyeonjeong Jean

Journal of Modern Applied Statistical Methods

A simulation study was conducted to examine parameter recovery in a cross-classified multiple membership multilevel model. No substantial relative bias was identified for the fixed effect or level-one variance component estimates. However, the level-two cross-classification multiple membership factor variance components were substantially biased with relatively fewer groups.

Using Cyclical Components To Improve The Forecasts Of The Stock Market And Macroeconomic Variables, Kenneth R. Szulczyk, Shibley Sadique

Journal of Modern Applied Statistical Methods

Economic variables such as stock market indices, interest rates, and national output measures contain cyclical components. Forecasting methods excluding these cyclical components yield inaccurate out-of-sample forecasts. Accordingly, a three-stage procedure is developed to estimate a vector autoregression (VAR) with cyclical components. A Monte Carlo simulation shows the procedure estimates the parameters accurately. Subsequently, a VAR with cyclical components improves the root-mean-square error of out-of-sample forecasts by 50% for a stock market model with macroeconomic variables.

A Nonlinear Systems Framework For Cyberattack Prevention For Chemical Process Control Systems, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Recent cyberattacks against industrial control systems highlight the criticality of preventing future attacks from disrupting plants economically or, more critically, from impacting plant safety. This work develops a nonlinear systems framework for understanding cyberattack-resilience of process and control designs and indicates through an analysis of three control designs how control laws can be inspected for this property. A chemical process example illustrates that control approaches intended for cyberattack prevention which seem intuitive are not cyberattack-resilient unless they meet the requirements of a nonlinear systems description of this property.

Comparison Of Multiple Imputation Methods For Categorical Survey Items With High Missing Rates: Application To The Family Life, Activity, Sun, Health And Eating (Flashe) Study, Benmei Liu, Erin Hennessy, April Oh, Laura A. Dwyer, Linda Nebeling

Journal of Modern Applied Statistical Methods

Two multiple imputation methods, the Sequential Regression Multivariate Imputation Algorithm and the Cox-Lannacchione Weighted Sequential Hotdeck, were examined and compared to impute highly missing categorical variables from the Family Life, Activity, Sun, Health and Eating (FLASHE) study. This paper describes the imputation approaches and results from the study.

Dealing With Sensitive Quantitative Variables: A Comparison Of Sampling Designs For The Procedure Of Gupta And Thornton, Carlos Narciso Bouza Herrera, Prayas Sharma

Journal of Modern Applied Statistical Methods

The use of randomized response procedures allows diminishing the number of non-responses and increasing the accuracy of the responses. A new sampling strategy is developed where the reports are scrambled using the procedure of Gupta and Thornton. The estimator of the mean as well as the errors are developed for the Rao-Hartley-Cochran and Ranked Sets Sampling designs. The proposals are compared with the original model based on the use of simple random sampling.

Bayesian And Semi-Bayesian Estimation Of The Parameters Of Generalized Inverse Weibull Distribution, Kamaljit Kaur, Kalpana K. Mahajan, Sangeeta Arora

Journal of Modern Applied Statistical Methods

Bayesian and semi-Bayesian estimators of parameters of the generalized inverse Weibull distribution are obtained using Jeffreys’ prior and informative prior under specific assumptions of loss function. Using simulation, the relative efficiency of the proposed estimators is obtained under different set-ups. A real life example is also given.

Of Typicality And Predictive Distributions In Discriminant Function Analysis, Lyle W. Konigsberg, Susan R. Frankenberg

Human Biology Open Access Pre-Prints

While discriminant function analysis is an inherently Bayesian method, researchers attempting to estimate ancestry in human skeletal samples often follow discriminant function analysis with the calculation of frequentist-based typicalities for assigning group membership. Such an approach is problematic in that it fails to account for admixture and for variation in why individuals may be classified as outliers, or non-members of particular groups. This paper presents an argument and methodology for employing a fully Bayesian approach in discriminant function analysis applied to cases of ancestry estimation. The approach requires adding the calculation, or estimation, of predictive distributions as the final step …

Fingerprinting Sediment Transport In River-Dominated Margins Using Combined Mineral Magnetic And Radionuclide Methods, Jinlong Wang, Weigou Zhang, M. Baskaran, Jinzhou Du, Feng Zhou, Hui Wu

Environmental Science and Geology Faculty Research Publications

Both magnetic properties and radionuclides are widely used to trace sediment transport in aquatic environments; however, these methods have not been used in combination. In this study, the East China Sea (ECS), a typical river-dominated margin, was chosen to demonstrate the advantages of combining these two methods to track sediment movements on a seasonal to annual timescale. The ratios between saturation isothermal remnant magnetization and anhysteretic remnant magnetization (χARM/SIRM) and 7Be/210Pbex activity ratios as well as mass balance of 7Be provide information on the seasonal transport of sediment from the Changjiang Estuary to the neighboring shelf. Both 210Pb budget and …

State Measurement Spoofing Prevention Through Model Predictive Control Design, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Security of chemical process control systems against cyberattacks is critical due to the potential for injuries and loss of life when chemical process systems fail. A potential means by which process control systems may be attacked is through the manipulation of the measurements received by the controller. One approach for addressing this is to design controllers that make manipulating the measurements received by the controller in any meaningful fashion very difficult, making the controllers a less attractive target for a cyberattack of this type. In this work, we develop a model predictive control (MPC) implementation strategy that incorporates Lyapunov-based stability …

A Distance Based Method For Solving Multi-Objective Optimization Problems, Murshid Kamal, Syed Aqib Jalil, Syed Mohd Muneeb, Irfan Ali

Journal of Modern Applied Statistical Methods

A new model for the weighted method of goal programming is proposed based on minimizing the distances between ideal objectives to feasible objective space. It provides the best compromised solution for Multi Objective Linear Programming Problems (MOLPP). The proposed model tackles MOLPP by solving a series of single objective sub-problems, where the objectives are transformed into constraints. The compromise solution so obtained may be improved by defining priorities in terms of the weight. A criterion is also proposed for deciding the best compromise solution. Applications of the algorithm are discussed for transportation and assignment problems involving multiple and conflicting objectives. …

On Some Ergodic Impulse Control Problems With Constraint, J. L. Menaldi, Maurice Robin

Mathematics Faculty Research Publications

This paper studies the impulse control of a general Markov process under the average (or ergodic) cost when the impulse instants are restricted to be the arrival times of an exogenous process, and this restriction is referred to as a constraint. A detailed setting is described, a characterization of the optimal cost is obtained as a solution of an HJB equation, and an optimal impulse control is identified.

Estimation Of Finite Population Mean By Using Minimum And Maximum Values In Stratified Random Sampling, Umer Daraz, Javid Shabbir, Hina Khan

Journal of Modern Applied Statistical Methods

In this paper we have suggested an improved class of ratio type estimators in estimating the finite population mean when information on minimum and maximum values of the auxiliary variable is known. The properties of the suggested class of estimators in terms of bias and mean square error are obtained up to first order of approximation. Two data sets are used for efficiency comparisons.