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The Professional Constructor, Full Issue, Volume 45, Number 02

The Professional Constructor

No abstract provided.

Investigating Hierarchical Effects Of Adaptive Signal Control System On Crash Severity Using Random-Parameter Ordered Regression Models Incorporating Observed Heterogeneity, Weimin Jin, Mashrur Chowdhury, M. Sabbir Salek, Sakib Mahmud Khan, Patrick Gerard

Publications

No abstract provided.

Pert, Cpm And The Tangled History Of Network Scheduling, Charles Christopher Smith, Vivek Sharma, Gregory B. Baecher

The Professional Constructor

The origins of two network scheduling techniques: The Program Evaluation Review Technique (PERT); and the Critical Path Method (CPM) are examined. Prior accounts hold that each are different and were created separately. PERT, developed within the U. S. Navy’s highly classified POLARIS nuclear missile program which began in 1955. CPM, the creation of American industrial concerns E. I. du Pont de Nemours (du Pont) and Remington Rand UNIVAC. With the objective of settling “an acrimonious dispute over parentage,” this research examines the literature and the original forms of PERT and CPM noting their ‘dead ring’ resemblances, synchronous development timelines, while …

Clemson Commencement Program, August 2020, Clemson University

Clemson Commencement Programs

No abstract provided.

Bilevel And Multi-Objective Optimization Of Electricity Price Setting With Carbon Emission Consideration, Vikas Garg

All Theses

In this proposed thesis, we present a bilevel optimization model for setting the electricity prices according to Time-and-Level-of-Use (TLOU) policy. In TLOU, different price brackets are used for different periods during the day according to the actual load consumed by the customers. In our bilevel optimization model, we consider the retailer as the leader of the problem and customers as the followers. The retailer aims at maximizing the profit, and the customers seek to minimize their electricity costs. Using the bilevel optimization model, we compare the emissions model that considers the weighted sum of profits and emissions as the objective …

Multi-Point Monin–Obukhov Similarity Theory In The Convective Atmospheric Surface Layer Using Matched Asymptotic Expansions, Mengjie Ding

All Dissertations

The multi-point Monin-Obukhov similarity theory (MMO) scaling properties of the surface-layer statistics were derived analytically, including one-point fluctuation statistics, multi-point statistics, and the mean velocity profile. The Monin-Obukhov similarity theory (MOST) is the foundation for understanding the atmospheric surface layer. While many surface-layer statistics has been shown to follow MOST, a number of important statistics do not conform to MOST due to the incomplete similarity. MMO was proposed by Tong & Nguyen (2015) to address the issue of the incomplete similarity and has been successfully used in predicting turbulence spectra. However, both MOST and MMO were proposed as hypotheses based …

The Role Of Substrate Elasticity In Droplet Splashing, Bailey Basso

All Theses

Drop impact onto elastic substrates is important in applications such as spray coating, bioprinting, forensic analysis, and aerosol drug delivery. The dynamics of impact are complex and include a sequence of events that cause a drop to splash or deposit, form a corrugated leading edge with a well-defined number of spines that may or may not pinchoff into satellite drops during spreading, and finally retraction of the main drop to an equilibrium configuration. Careful experiments are performed to quantify droplet impact on soft gel substrates made of either PDMS silicone or gelatin hydrogels of varying elastic modulus. High-speed photography and …

A Comparison Of Machine Learning And Traditional Demand Forecasting Methods, Franz Stoll

All Theses

Obtaining accurate forecasts has been a challenging task to achieve for many organizations, both public and private. Today, many firms choose to share their internal information with supply chain partners to increase planning efficiency and accuracy in the hopes of making appropriate critical decisions. However, forecast errors can still increase costs and reduce profits. As company datasets likely contain both trend and seasonal behavior, this motivates the need for computational resources to find the best parameters to use when forecasting their data. In this thesis, two industrial datasets are examined using both traditional and machine learning (ML) forecasting methods. The …

Vlsi Architecture For Polar Codes Using Fast Fourier Transform-Like Design, Weihang Tan

All Theses

Polar code is a novel and high-performance communication algorithm with the ability to theoretically achieving the Shannon limit, which has attracted increasing attention recently due to its low encoding and decoding complexity. Hardware optimization further reduces the cost and achieves better timing performance enabling real-time applications on resource-constrained devices. This thesis presents an area-efficient architecture for a successive cancellation (SC) polar decoder. Our design applies high-level transformations to reduce the number of Processing Elements (PEs), i.e., only log₂ N pre-computed PEs are required in our architecture for an N-bit code.

We also propose a customized loop-based shifting register to …

Topology Optimization Of Irregular Shaped Pressure Vessels Using A Level-Set Method, John Michal Kremar

All Theses

Advances in manufacturing capabilities, such as additive manufacturing, have expanded the design freedom given to engineers enabling more efficient designs through the use of complex geometries. However, determining the optimal geometric structure for a given set of performance criteria can be quite challenging when given such design freedom. One technique to do so is with the use of topology optimization methods, in which optimal material distribution within a given design space is determined. Many established topology optimization methods are developed such that a set of boundary conditions are prescribed to the design domain and remain fixed throughout the optimization process …

Gender Disparity Within The Ivory Tower: Do Perceived Organizational Support And Procedural Justice Predict Self-Discrepant Time Allocation?, Phoebe Xoxakos

All Theses

In the workplace, gender norms often affect women more negatively than men. Although women have demonstrated their abilities and competence in a variety of occupations and workplace settings, progress toward gender equity in academia is at a plateau. Using organizational support and organizational justice literature as a theoretical foundation, the purpose of the current study was to determine if two antecedents—perceived organizational support and procedural justice—influence how academics allocate their time spent on research, service, and teaching during the workweek and weekend. Ideal (i.e., preferred) time allocation and actual time allocation were examined. In addition, gender was proposed as a …

Data-Driven Control With Learned Dynamics, Wenjian Hao

All Theses

This research focuses on studying data-driven control with dynamics that are actively learned from machine learning algorithms. With system dynamics being identified using neural networks either explicitly or implicitly, we can apply control following either a model-based approach or a model-free approach. In this thesis, the two different methods are explained in detail and finally compared to shed light on the emerging data-driven control research field.

In the first part of the thesis, we first introduce state-of-art Reinforcement Learning (RL) algorithm representing data-driven control using a model-free learning approach. We discuss the advantages and shortcomings of the current RL algorithms …

The Robustness Gap For Uncertain Multiobjective Linear Programs, Lena Fritzen

All Theses

In robust multiobjective optimization, a new robustness gap is defined in [4]. This gap measures the minimal distance between the robust Pareto set and the Pareto sets of all scenarios. Upper and lower bounds of this gap are derived for the convex case. In this thesis, a deeper examination into the definition and application of this gap for uncertain multiobjective linear programs is presented. Numerical examples are developed and results are reported for the first time.

Inferring Networks With Gene Knockouts And Computational Algebra, Tilly Grace Erwin

All Theses

The network inference problem is a significant problem in systems biology. In this paper, we will describe an approach to this problem involving computational algebra. Specifically, given an unknown Boolean function, we can create a square-free monomial or pseudomonomial ideal whose primary decomposition encodes the possible sets of variables that the function can depend on, and whether those interactions are activations or inhibitions. We apply this problem to time series data generated from a non-linear ODE, built over unknown feed-forward loops, and subject to gene knockouts.

Exploiting The Nonlinear Stiffness Of Origami Folding To Enhance Robotic Jumping Performance, Samuel Reese Allison

All Theses

This research investigates the effects of using origami folding techniques to develop a nonlinear jumping mechanism with optimized dynamic performance. A previous theoretical investigation has shown the benefits of using a nonlinear spring element compared to a linear spring for improving the dynamic performance of a jumper. This study sets out to experimentally verify the effectiveness of utilizing nonlinear stiffness to achieve optimized jumping performance. The Tachi-Miura Polyhedron (TMP) origami structure is used as the nonlinear energy-storage element connecting two end-point masses. The TMP bellow exhibits a “strain-softening” nonlinear force-displacement behavior resulting in an increased energy storage compared to a …

Yield And Nutritional Composition Of Conventional And Bmr Pearl Millet Under Different Management Conditions, Madeline A. Oskey

All Theses

The main objectives of these studies were to evaluate the yield, composition and digestibility of conventional and BMR pearl millet (PM, Pennisetum glaucum) with different establishment dates or harvested at different maturity stages. A second objective was to evaluate the impact of mixing PM with cowpea on measured variables. Two trials were conducted in field plots (1.5 m x 6.1 m) as randomized complete block designs with a split plot arrangement of treatments. In trial 1, two varieties of PM (conventional and BMR) were planted at two different dates (14d apart) and harvested at early heading stage. In trial …

Investigating Rad51 And Dmc1 In Entamoeba Histolytica: Homologous Recombinases With Drug Target Potential, Rachel Evelyn Ham

All Theses

Entamoeba histolytica is the causative agent of amebic dysentery and is prevalent in developing countries. It has a biphasic lifecycle: active, virulent trophozoites and dormant, environmentally-stable cysts. Only cysts are capable of establishing new infections, and are spread by fecal deposition. Many unknown factors influence stage conversion, and synchronous encystation of E. histolytica is not currently possible in vitro. E. histolytica infections are treated with nitroimidazole drugs, such as metronidazole (Flagyl™). However, several clinical isolates have shown metronidazole resistance. Enhancing the amebicidal mechanisms of metronidazole through drug combination therapy may allow for more effective treatment. Metronidazole may cause amebic death …

A Multistate Survival Analysis For Sequential Follicular Lymphoma Treatment Leveraging National Lymphocare Study, Aashay Mahesh Mahesh Mehta

All Theses

Follicular lymphoma (FL), caused due to the abnormal growth of B-cells, is the most common form of indolent Non-Hodgkin's Lymphoma (NHL) in the United States. Majority of the patients diagnosed with FL are subjected to a series of treatment during their clinical course, thereby providing researchers an opportunity to evaluate sequential effect of different treatment regimens and identify significant risk factors affecting the survival of patients.

National Lymphocare Study (NLCS) is the largest (n = 2,740) prospective study conducted in the United States that collected information about different prognostic factors and outcomes required to conduct a comprehensive multi-state survival analysis. …

Exploratory Data Analysis And Point Process Modeling Of Amateur Radio Spots, Nicole Chris

All Theses

Amateur radio spots are studied by scientists for many reasons. The Reverse Beacon Network (RBN) records thousands of spots and their characteristics on a daily basis. Located at the public server, http://www.reversebeacon.net/, it is open to be downloaded and explored by all. A "spot" is by definition where a propagation path exists between a transmitter and a receptor location at a certain time and frequency (Miller et al., 2019). While this data can be useful to scientists, we do not have any knowledge to know when or how spots will occur. In this paper, we explore the idea of using …

Using Incremental Rehearsal For Subtraction Fact Fluency Among Elementary Students With Mathematics Difficulties, Friggita Johnson

All Dissertations

Students with or at-risk of learning disabilities in mathematics often experience working memory deficits that interfere with long-term retention of facts. Fact fluency reduces the cognitive demand on working memory to allow allocation of cognitive resources for processing more complex tasks. The current study used a single-case, multiple-baseline design to investigate the effectiveness of incremental rehearsal, an evidence-based drill-and-practice strategy, in improving subtraction fact fluency among elementary students with mathematics difficulties. Participants (N = 4) were three third-grade students and one fourth-grade student either with a formal diagnosis of learning disabilities in mathematics or low performing in mathematics without an …

The Child Care Tax Credit, Maternal Labor Supply, And Children’S Well-Being, Haibin Jiang

All Dissertations

This dissertation is comprised of three essays on the Child Care Tax Credit program in the United States. I analyze how the Child Care Tax Credit affects the budget constraints faced by mothers, and how changes in mothers' budget constraints affect maternal labor supply. Furthermore, I examine how the Child Care Tax Credit affects children's well-being through mothers' time allocation. Understanding the employment and time allocation adjustment of the women with young children, according to the tax programs and child care subsidies, is important for theoretical and practical reasons. Examining the influence of the tax subsidy on children's cognitive and …

Attack Resilient Pulse Based Synchronization, Zhenqian Wang

All Dissertations

Synchronization of pulse-coupled oscillators (PCOs) has gained significant attention recently due to increased applications in sensor networks and wireless communications. However, most existing results are obtained in the absence of malicious attacks. Given the distributed and unattended nature of wireless sensor networks, it is imperative to enhance the resilience of pulse-based synchronization against malicious attacks. To achieve this goal, we first show that by using a carefully designed phase response function (PRF), pulse-based synchronization of PCOs can be guaranteed despite the presence of a stealthy Byzantine attacker, even when legitimate PCOs have different initial phases. Next, we propose a new …

Traffic Analysis Resistant Infrastructure, Jonathan Oakley

All Dissertations

Network traffic analysis is using metadata to infer information from traffic flows. Network traffic flows are the tuple of source IP, source port, destination IP, and destination port. Additional information is derived from packet length, flow size, interpacket delay, Ja3 signature, and IP header options. Even connections using TLS leak site name and cipher suite to observers. This metadata can profile groups of users or individual behaviors.

Statistical properties yield even more information. The hidden Markov model can track the state of protocols where each state transition results in an observation. Format Transforming Encryption (FTE) encodes data as the payload …

Building A Strategy For Key Energy Transitions: Modeling Biophysical Economics, John Sherwood

All Dissertations

Economists rarely model the economy as explicitly bound by Earth's ecological systems. However, ecological systems act as constraints on the economy --- constraints that have historically been too far away from economic productivity to seriously consider. These ecological or biophysical constraints have been growing closer and more prominent as natural resources are depleted and environmental impacts increase. Modeling these constraints is what defines the emerging sub-discipline of biophysical economics, BPE. The goal of this dissertation is to map out and extend current biophysical economics modeling strategies. BPE provides the ideal framework to holistically understand energy transitions towards sustainability.

In Chapter …

A Study Of Quasi-Birth-Death Processes And Markovian Bitcoin Models, Kayla Doris Javier

All Dissertations

In this dissertation we study a variety of continuous-time Markov chains (CTMCs) and present new formulas that can be used to find the stationary distribution and the Laplace transforms of the transition functions. Our first set of results involve a level-dependent Quasi-Birth-Death (QBD) processes. We study the distribution of the state and the associated running maximum level at a fixed time t. We present new expressions for the Laplace transforms of the transition functions containing this information. This work involves making use of a collection of R-matrices often found in matrix analytic literature. We also show how our methods can …

Detecting Periods Of Eating In Everyday Life By Tracking Wrist Motion — What Is A Meal?, Surya Sharma

All Dissertations

Eating is one of the most basic activities observed in sentient animals, a behavior so natural that humans often eating without giving the activity a second thought. Unfortunately, this often leads to consuming more calories than expended, which can cause weight gain - a leading cause of diseases and death. This proposal describes research in methods to automatically detect periods of eating by tracking wrist motion so that calorie consumption can be tracked. We first briefly discuss how obesity is caused due to an imbalance in calorie intake and expenditure. Calorie consumption and expenditure can be tracked manually using tools …

Towards More Efficient Behavioral Coding Of Teamwork Via Machine Learning, Michelle Leigh Flynn

All Dissertations

Teams have been an integral part of organizational success for several decades and as such, researchers have sought to better understand all aspects of work teams. To better inform research and practice, Marks, Mathieu and Zaccaro (2001) advanced a theory and framework of team processes that has become a seminal piece in our field. Their theory proposed that ten team processes could be mapped on to three second order constructs (transition, action, and interpersonal phases). Mathieu and colleagues (2019) developed and validated a measure designed specifically to align with Marks et al. (2001) framework. While much needed, this measure is …

A Survey Of Changepoint Techniques For Time Series Data, Xueheng Shi

All Dissertations

Changepoint analysis has played an important role in modern time series study. Detection of changepoints helps modelling and prediction of time series and is found in applications of many fields. This dissertation focuses on the detection of mean structure changes in correlated time series. It consists of the results of three research projects on changepoint problems: (1) the comparison of changepoint techniques; (2) autocovariance estimation of an AR(p) time series with changepoints; and (3) L1-regularization in changepoint analysis.

In chapter 2 the single changepoint techniques, or At-Most-One-Changepoint (AMOC) tests are reviewed. A new AMOC test, Sum of Squared CUSUMz is …

Quantum And Classical Multilevel Algorithms For (Hyper)Graphs, Ruslan Shaydulin

All Dissertations

Combinatorial optimization problems on (hyper)graphs are ubiquitous in science and industry. Because many of these problems are NP-hard, development of sophisticated heuristics is of utmost importance for practical problems. In recent years, the emergence of Noisy Intermediate-Scale Quantum (NISQ) computers has opened up the opportunity to dramaticaly speedup combinatorial optimization. However, the adoption of NISQ devices is impeded by their severe limitations, both in terms of the number of qubits, as well as in their quality. NISQ devices are widely expected to have no more than hundreds to thousands of qubits with very limited error-correction, imposing a strict limit on …

Making Pandora’S Box: The Politics Of Science Funding, Grant A. Allard

All Dissertations

How do politics influence the geographic distribution of science funding? I investigate this question in the context of presidential politics. Science policy scholars endeavor to develop a systems-level understanding—using empirical data and quantitative analysis—of how governments make decisions about science. In the United States, one of the most important decisions that governments make is the allocation of federal funding from agencies such as the National Institutes of Health and National Science Foundation to researchers and universities. Science policy scholars typically explain the distribution of science funding through scientists’ or universities’ merit. I challenge these explanations’ assumption that presidential politics does …