SHAREOK Repository
Not a member yet
49261 research outputs found
Sort by
Configurations of a southern place: a postcolonial, southern urban inquiry into place-making in Norwood, Johannesburg.
No full textPlace theory in geography has largely been a northern scholarly endeavor. Yet there is much to learn about place-making in global south cities. Southern urban scholars argue that understanding cities of and from the vantage point of global south, significantly expands urban scholarship in a way that northern-derived theory cannot do. My research experiments with two growing bodies of literature to study the making of a southern place. Drawing from postcolonial and southern urban theory, I use a process of theory unbundling (Lawhon and Le Roux, 2020) to provincialize relational place-making (Pierce, Martin and Murray, 2011). My empirical case studies the spatial practices and logics of place-making by people who live and work in the streets and public spaces in Johannesburg, South Africa. In experimenting with theory unbundling as a tool to dislocate northern-derived theory, I find that relational place-making cannot travel south as is, because, how power and democracy is conceptualized in northern literature is empirically different in a southern place. The negotiatory tactics of how public space is shared but also claimed for private gain, and how marginalized people’s behaviors are monitored and controlled, foregrounds what I call the staying power from being in place, and that place-making depends far more on what is permissible than what is lawful. I use and expand on an existing southern urban concept, ‘permissions’ (Lawhon, Pierce and Makina, 2017), to understand place-making when it falls in the liminal space between state law and order and unlawful, unregulated spatial practices. Through these findings I make room in urban scholarship to further research spatial practices and logics that occur outside of the operating systems of the modern state - underpinned by democratic values attached to private property and a rights-based approach to accessing the city
Three Essays Conceptually Exploring Implications for Artificial Intelligence in Marketing
No full textThis dissertation comprises three essays that conceptually explore the implications of artificial intelligence (AI) in marketing. AI is increasingly becoming integrated into every facet of marketing. As AI reshapes marketing relationships, it provides a path forward toward developing, adopting, or adapting conceptual frameworks, measurements, decision-making logics, and processes to reflect the digital world. Each of the three essays focuses on different facets of marketing utilizing distinct theoretical frameworks, research contexts, and methods. Essay one focuses on text-based communications, essay two focuses on AI personalized environments; whereas, essay three focuses on the new product development process of a business-to-business (B2B) AI marketing firm. These essays advance theory and practice to help us understand the implications of AI in marketing.
In essay one, I provide an evidence-informed answer to the following question: How are text-based communications in the echoverse reshaping marketing tasks and objectives? Given that automated textual analysis (ATA) methods are the window through which scholars and practitioners understand, predict, and co-create text-based communication in the echoverse, a systematic literature review of the marketing literature employing ATA methods is conducted. In doing so, a novel sampling procedure that applies supervised machine learning to rank long-form text assets in terms of relevancy is developed, which was used to identify empirical articles that employed ATA to gain marketing insights and predictions in the echoverse. The synthesis reveals how text-based communication reshapes four key marketing objectives: amplifying and de-amplifying content, tuning content, leveraging product reviews, and enhancing brand performance.
In essay two, I introduce a central concept from the field of ecology— ecological specialization—the breadth of a specie’s utilization of resources to the field of marketing and provide a typology of personalized digital environments. Specifically, I conceptualize how the resources within a firm’s content library interact with the degree of personalization to curate their digital marketing environment. Using a proprietary dataset including 7,174 email subscribers who opted to receive email marketing communications and opened at least one email between January 1, 2018, and June 30, 2018, from an Artificial Intelligence (AI) email marketing company that employs topic modeling to identify, curate, and deliver personalized emails to each individual customer based on customers’ observed preferences, the concept of specialization, along with its implications for AI-personalized digital environments, was examined. I show how the underlying assumptions of traditional marketing metrics may limit marketers’ ability to understand AI-personalized environments. The paper provides recommendations to marketers and new pathways for future research.
In essay three, I add the possibility of pivots to popular Stage-Gate® new product development processes (NPD). As conceived and operationalized with Stage-Gate®, one of five outcomes are possible decisions at each gate: go, stop, hold, recycle, or iterate. Borrowing from the entrepreneurship literature, I modify the process to include a sixth possible decision, a pivot. Pivots are triggered when a NPD project yields negative information or management believes that changes are necessary for the organization’s survival and growth, i.e., a continuation decision in a failing course of action—an escalation of commitment. Effectuation theory is used to understand how causal/effectual logic informs escalation of commitment decisions, including pivots in an organization’s NPD process. Through integrating the literature on Stage-Gate® NPD processes, entrepreneurial pivots, escalation of commitment theory, and effectuation theory, as well as using a case study of a business-to-business AI marketing organization’s NPD project with pivots, research propositions are offered for future research
Comparison of the period finding algorithms on white dwarf binaries in the Zwicky Transient Facility (ZTF) Data Release 3
Get PDFIrregular time series arise in most ground-based astronomical surveys due to atmospheric effects, missing observations, and instrumental issues that create erratic time intervals among data points and reduce data quality. Determining the exact period of a system can therefore be a problem. Building a correct mathematical formulation is required to analyze the unevenly-sampled data and reveal the hidden period information. Parametric techniques assume that the observable data can be represented as a linear combination of trigonometric functions of time. The non-parametric methods, on the other hand, are not affected by the assumptions about the shape of the underlying signal, which helps identify non-sinusoidal behavior.
In this thesis, we mainly consider two notable methods. The Lomb-Scargle periodogram Lomb(1976), and Scargle(1982), developed from the Least-Squares Spectral Analysis Vanicek(1969), is a known parametric algorithm for analyzing sampled time series for periodic signals irregularly. Conditional Entropy Graham(2013a), conversely, is an example of non-parametric approaches originating from the Shannon entropy Cincotta(1995), which uses the information theory and phase-folds the data at each trial frequency and estimates the conditional entropy of the data, where m is the magnitude, and is the phase of the signal. According to information theory, the period with the least entropy corresponds to the correct frequency of a stationary signal.
In this thesis, we compare these two methods and identify the approach that provides a better representation for the period of White Dwarf binaries we selected from Zwicky Transient Facility Data Release 3 Masci(2019) Bellm(2018). Lomb-Scargle Periodogram predicted periods of 7 sources and failed to find the correct periods of 8 sources from Burdge(2020). Additionally, out of 34 WD binaries from ZTF DR3, Lomb-Scargle found 33 of them correctly. Conditional Entropy periodogram, on the other hand, accurately predicted periods of all objects. We conclude that Conditional Entropy proves to be more powerful than the traditional methods for detecting periodicities in time series data
The performance and cost-benefit analysis of iron coagulants and polymer additive in enhancing seawater treatment during harmful algal blooms
Get PDFWater usage is growing at more than twice the rate of the population, and an increasing number of regions are reaching the limit at which water services can be sustainably delivered, specifically in arid regions (United Nations Water, 2007). Building large infrastructures such as water transfer systems and seawater desalination plants has gained support to alleviate water scarcity. Seawater reverse osmosis (SWRO) is one of the preferred technologies used in the treatment process of seawater desalination. The quality of the source water plays an important role in extending the membrane life in this system, where it can prevent membrane fouling which occurs because of pore-clogging or adsorption of solute on the membrane surface, which could be a result of the presence of harmful algal blooms. The objectives of this research are to determine the optimum coagulant dose of ferric chloride, ferric sulfate, and ferrous sulfate and the impact of pH on the coagulant dose for removing algae. Also, determining the impact of cationic organic polymer additive, which is polyDADMAC (e.g., Polydiallydimethylammounium Chloride), on floc stability and the minimum economic cost of the coagulants with and without polymer additive. The experiment was done on artificial seawater (33 g/L) containing 1 g/L of bentonite clay and 10 mg/L of sodium alginate to mimic the harmful algal blooms. It was observed that 40 mg/L FeCl3, 20 mg/L FeSO4, or 30 mg/L Fe2(SO4)3 at a pH of 8.25 has the highest turbidity removal, which highly improved the quality of seawater. Moreover, the addition of polyDADMAC to the iron coagulants increased the removal of water turbidity. Furthermore, the coagulation process using iron coagulants led to an increase of more than 90% of total organic carbon, and dissolved organic carbon removal in seawater contains sodium alginate and cultivated algae. When 5.45 mg/L polyDADMAC was added to the coagulants, the removal of total organic carbon and dissolved organic carbon reached more than 75% due to the presence of carbon in polyDADMAC. The iron coagulants and polyDADMAC addition to them have the same performance when tested on artificial seawater containing 10 mg/L cultivated algae instead of sodium alginate where the water turbidity decreases to less than 2 NTU. After the cost analysis was completed, it was found that ferric sulfate without the 5.45 mg/L polyDADMAC has the lowest cost of $0.421/m3 for plant capacity of 1,000 m3/day
Observation of the triboson process pp → W±W∓γ and limits on anomalous quartic gauge couplings with the ATLAS detector
Get PDFThis thesis presents a search for evidence of production from scattering with = 13 TeV at the Large Hadron Collider using 140 fb of integrated luminosity. The case where the bosons decay to opposite-flavor light leptons is considered, as other decay channels are dominated by backgrounds. Monte Carlo simulations are used to estimate the contributions of the process as well as various background processes to the channel. The contribution to the channel of processes with a misidentified or non-prompt photon in the final state are estimated with data-driven methods. A machine learning algorithm trained on Monte Carlo simulations is used to further increase the purity of \wwy events in the dataset. A maximum likelihood fit to the binned distribution of the machine learning discriminant is performed to determine the best-fit value of the \wwy contribution to the \emuy channel. From this, the expected \wwy production cross section in a fiducial region is determined to be fb. The observed cross section in the fiducial region will be measured after the \emuy dataset is unblinded.
Additionally, to study potential deviations from the Standard Model prediction in the \emuy channel, the ATLAS run-2 dataset is used to set upper and lower limits at the 95\% confidence level on 13 Wilson coefficients of an effective field theory extending the Standard Model with dimension-8 operators. Two methods to restore unitarity to the effective field theory are investigated: the clipping method as well as a dipole form factor model. The dependence of the Wilson coefficients' expected upper and lower limits on these two methods' parameters are presented
On the Prescribed Ricci Curvature of Noncompact Homogeneous Spaces with Two Isotropy Summands
Get PDFThe current dissertation works within the setting of noncompact homogeneous spaces /
in which is semi-simple. In particular, we frequently work with a decomposition of the
Lie algebra , = ⊕ '' ⊕ ', where ⊕ '' is the maximal compact in and ' is the
negative one eigenspace from the Cartan decomposition. In such a setting we primarily set
out to understand invariant metrics and Ricci curvature, and the relationship these are in
with Lie theoretic conditions. There are three basic components to this work with the second
holding most of our attention. The first component is an investigation into spaces, /, in
which we can always obtain some decomposition with ('', ') = 0 (what we call a Cartan
orthogonal pair), building out results indicating that there are many examples of such spaces.
The second component is an investigation into simply connected / with two isotropy
irreducible summands. Here, we classify such spaces and solve the so-called Prescribed
Ricci Curvature problem for all such /. The third component is an investigation into a
particularly nice setting of / with simple and having three irreducible summands in
which [_, _] ⊂ for each irreducible isotropy representation, _. Here, we provide Lie
theoretic conditions for obtaining diagonal , begin an investigation into the signature of
such spaces, and work through an example, (, 2)/(). A final consequence of these
three components is a description of the signature of all spaces / in which is simple
and / has negative scalar curvature for all metrics
Constraint of Vegetation Photosynthesis and Respiration Model (VPRM) Parameter Uncertainty Using a Markov Chain Monte Carlo (MCMC) Technique
Get PDFModeling the changes to the carbon cycle and their effects on the atmosphere is a key area of research for understanding climate change. The Vegetation Photosynthesis and Respiration Model (VPRM) is a light-use efficiency model that models the biogenic flux of carbon dioxide (CO2) known as Net Ecosystem Exchange (NEE). Previous studies used methods such as non-linear least squares in order to calibrate the parameters. One other method of calibrating parameters is the Metropolis-Hastings Markov Chain Monte Carlo (MCMC) technique. The MCMC technique has not been used previously due to how computationally expensive it is. The benefit of the MCMC technique is that it is a Bayesian technique that generates a probability distribution of the posterior parameters. This probability distribution can be used to quantify uncertainty in the posterior parameters.
This study compares the MCMC technique to a non-linear least squares technique to determine its viability for use in the calibration of the VPRM. Observation data from four cropland sites from the AmeriFlux eddy covariance tower network were used with both techniques to fit the model to observations. Using the parameter correlations generated from the posterior probability distributions, a series of experiments were conducted to determine the sensitivity of the optimization of VPRM to the state vector.
The analysis of this study found that the MCMC technique reduced the RMSE of the VPRM predicted flux by more than a factor of two. The technique is viable on a site-by-site scale. However, scaling up the algorithm to more sites and land use types (LUTs) would be very computationally expensive and would necessitate the use of small batches of sites and averaging the results to prove viable. Using a single LUT to cover all cropland may also be too general and splitting the cropland LUT into different types of crops may further improve the VPRM overall
Examining Whether Collaboration Can Improve Memory for Binding of Real-World Object Features
Get PDFIndividuals can accurately store thousands of objects in their visual long-term memory.
However, when objects vary on numerous features, previous research found that individuals
struggle to bind the objects to their correct states (e.g., state of the studied coffee mug: full or
empty). We tested whether collaboration could serve to overcome chance-level exemplar-state
binding by conducting three recognition memory experiments. In Experiment 1A, participants
completed 2-AFC tests, in which they had to identify either which exemplars or which exemplarstate
conjunctions they had studied. Similar to previous research, we found that when
participants needed to identify the exemplar-state information together, they struggled to bind
this information and performed near-chance performance. In Experiment 1B, we used a withinsubject
design and tested whether collaboration could enhance memory for exemplar-state
binding at retrieval. To accommodate our design, we divided each task into two blocks, cutting
each task in half. We found that participants who remembered individually, and those who
worked collaboratively, demonstrated the ability to remember exemplars and the states of
exemplars they studied. Surprisingly, they were able to successfully remember this information
as a bound unit. In Experiment 2, we tested whether we could replicate this ability to
successfully bind when the task becomes more challenging. Using an old/new recognition test,
we found that participants who collaborated were able to discriminate above chance performance
for both tasks. Thus, we found evidence that exemplar-state binding is possible by individuals
who remember individually and that binding performance can be improved when individuals
collaborate to remember. However, it seems apparent that the amount of information participants
are required to bind impacts this ability
Cultivating a Culture for Inclusive Metadata
Get PDFUniversity of Central Oklahoma’s Max Chambers Library is committed to serving underrepresented communities. One way this is accomplished is through the professional catalogers' dedication to accurately and respectfully describing materials relating to underrepresented communities. They are actively taking steps to ameliorate these problematic practices that directly affect the Central community's access to library resources. In addition to retrospective projects, the library’s Systems division is working on creating a culture that supports inclusive metadata practices, both within the library and regionally in Oklahoma—which presents its own challenges in a deeply conservative state. Join us to learn about our initiatives and where we hope to take them next.N
Development and testing of an FPGA-controlled switched-integrator current amplifier for use in scanning tunnelling microscopy
Get PDFThe scanning tunnelling microscope (STM) is a very powerful analytic tool capable of achieving atomic resolution. Unfortunately, the STM is restricted to samples that are sufficiently conductive to allow adequate tunneling current for feedback control. The amplifier used to measure the tunneling current is the critical limiting component. If the amplifier could be made more sensitive, the STM could be operated at lower tunneling currents allowing lower conductivity samples to be studied. Most amplifiers used in STM employ a resistor feedback design, which become unstable at high gain necessitating a tradeoff between gain and bandwidth. One way to circumvent that stability problem is to use a capacitor feedback design (switched
integrator), which does not exhibit the same stability problem. This comes at the expense of added complexity because the output is the integral of the current and needs to be periodically reset. In this project, a switched-integrator current amplifier is constructed and explored. It consisted of an analog switched integrator controlled by a field-programmable-gate-array (FPGA) with a 16-bit analog-to-digital converter and an 18-bit digital-to-analog converter. A viable prototype was created which allowed for the exploration of the gain, phase, and time delay of such systems. This exploration helped further characterize the important design considerations and trade-offs necessary for such a system. A design sequence is proposed that allows for optimal planning based on the desired tunneling current and system bandwidth