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The Florida Tech Scholarship Repository system captures, stores, indexes, preserves, and distributes digital research material.2020-06-03T20:08:35ZA Bio-inspired Classification System for Cyber-Physical-Human Identity Resolution
http://hdl.handle.net/11141/3133
A Bio-inspired Classification System for Cyber-Physical-Human Identity Resolution
Michel, Mary Catherine (Kay)
The Internet has created a need for understanding complex technology and identities today.
Cybercrime can take years to solve, and a systematic design may aid in more rapid resolution.
Classification of identities involves the arrangement of shared qualities or characteristics
known as features set expression, useful for identifying specific types of cybercriminals
based on empirical evidence and logic. In order for classification of a cyber identity to be
explainable and acceptable to researchers, a holistic systematic approach is beneficial to
organize natural and synthetic features of living and non-living organisms into a standardized
model. Proven scientific methods in the biology domain are primary inspirations in this
research. I defined one such classification system that takes input evidence from
Time/context-Cyber-Physical-Human (TCPH) dimensions and infers generalized to specific
classes of individuals using an ontology with restrictive logic and bio-inspired visualizations.
A sharable and extensible classification system with a common vocabulary can be used as a
reference for understanding effective identity feature composition, expression, and logic.
What if a method exists that can help people understand with whom they are really
communicating on the Internet, what the intentions are, and if the other identity is human?
To answer the question, an approach needs to support emerging technology and human
behavior and should be codified into a systematic broad identity classification scheme with
built-in logic to study, experiment, and map related evidence over time. The problem area
currently involves disparate static tools and a lack of understanding of technology, humans,
and identities. Although several classification methods exist in various domains, an
extensible systematic design for linking a range of identities does not and would be beneficial in solving cybercrime cases. Today’s methods often produce inconsistent or unexplainable
results when applied to nondeterministic human behavior patterns. In addition, the changing
Internet infrastructure and emerging technology creates a gap that necessitates a solution that
consistently evaluates key identity attributes effectively over time. The solution could aid in
understanding combined types of identities temporally linked to multidimensional elements
for faster resolution. Challenges exist in creating an identity specification and designing a
modular classification method to support emerging features and accumulated evidence.
This research introduces a novel classification scheme consisting of feature sets and logic,
all mappable to a broad range of quantified identity classes such as humans, generalized
profiles, targeted cybercriminals, and unique person. The design was inspired by biological
vocabularies and visualizations for systematic, shared use such as the gene ontology and
genome goal for a complete mapping and understanding of all human genes. In this work,
TCPH aspects were designed within a classification system and evaluated with simulated
representations of real-world cybercrime and identity evidence. The design is instantiated
with prototyped ontology property axiom descriptive logic and simulated evidence to
demonstrate problem resolution effectiveness. The classification system was assessed with
multiple case trials to determine effectiveness and accuracy of extensible identity modeled
classes. Research contributions attempt to revolutionize the cyber-physical problem space
with a formal holistic specification of identities and prototyped design that classifies inferred
identities based on mapped multidimensional feature evidence expression logic. The phased
design approach introduces an initial concept in Chapter 4 that advanced into a redesigned
bio-inspired identity classification system prototype with four interconnected, trackable
TCPH dimensions in Chapter 5. Experiment trials and visualizations which demonstrate
theoretical salience and variance provide new insights for understanding and sharing
knowledge of present and future identities. Research goals include a classification system
experiment platform that supports a common identity understanding, general to specific class
resolution, and aid in comprehension of future complex hybrid identity composition.
Thesis (Ph.D.) - Florida Institute of Technology, 2020.
2020-05-01T00:00:00ZOptimal Control of Coefficients for the Second Order Parabolic Free Boundary Problems
http://hdl.handle.net/11141/3130
Optimal Control of Coefficients for the Second Order Parabolic Free Boundary Problems
Hagverdiyev, Ali
Dissertation aims to analyze inverse Stefan type free boundary problem for the second
order parabolic PDE with unknown parameters based on the additional information given
in the form of the distribution of the solution of the PDE and the position of the free
boundary at the final moment. This type of ill-posed inverse free boundary problems
arise in many applications such as biomedical engineering problem about the laser ablation of biomedical tissues, in-flight ice accretion modeling in aerospace industry, and
various phase transition processes in thermophysics and fluid mechanics. The set of unknown parameters include a space-time dependent diffusion, convection and reaction coefficients, density of the sources, time-dependent boundary flux and the free boundary.
New PDE constrained optimal control framework in Hilbert-Besov spaces introduced in
U.G. Abdulla, Inverse Problems and Imaging, 7, 2(2013), 307-340; 10, 4(2016), 869-898
is employed, where the missing data and the free boundary are components of the control
vector, and optimality criteria are based on the final moment measurement of the temperature and position of the free boundary, and available information on the phase transition
temperature on the free boundary. The latter presents a key advantage in dealing with applications, where phase transition temperature is not known explicitly, but involve some
measurement error. Another advantage of the new variational approach is based on the
fact that for a given control parameter, Stefan boundary condition turns into Neumann
boundary condition on the given boundary, and parabolic PDE problem is solved in a
fixed domain, and therefore a perspective opens for the development of numerical methods of least computational cost. Discretization of the optimal control problem via method
of finite differences is pursued and the sequence of finite-dimensional optimal control
problems are introduced. The results of the dissertation are different depending on the
structure of the unknown diffusion coefficient. In the case if it is only time-dependent,
the well-posedness of the optimal control problem is established in Hilbert-Besov spaces.
Existence of the optimal control and convergence of the sequence of the discrete optimal
control problems to the continuous optimal control problem both with respect to functional and control is proved. The methods of the proof are based on uniform H
1
-energy
estimates in discrete Sobolev-Hilbert norms, weak compactness argument, Weierstrass
theorem in weak topology and weak convergence of the bilinear interpolations of the solutions of the discrete PDE problems to the solution of the optimal PDE problem in the
class of weakly differentiable functions. To prove similar results in the case when unknown diffusion coefficient is space-time dependent, a new Banach space is introduced.
The motivation for the new space is dictated with the optimal result on the convergence
of the bilinear interpolations of the grid functions in the class of weakly differentiable
functions, and establishment of the discrete H
1
-energy estimate under minimal assumptions on the diffusion coefficient. Existence of the optimal control and convergence of the
sequence of discrete optimal control problems to the continuous optimal control problem
both with respect to functional and control is proved in the setting of the new Banach
space.
Thesis - (Ph.D.) - Florida Institute of Technology, 2020.
2020-05-01T00:00:00ZCharacterization of Written Text Using Data and Network Science
http://hdl.handle.net/11141/3129
Characterization of Written Text Using Data and Network Science
Hamoodat, Harith A. Hamdon
The success of humans cannot be attributed to language, but it is certainly true
that language and humans are inseparable. Since the first language appeared, we
have seen that language continually evolving over space and social gatherings to
formed around 7,000 languages today. The origin and evolution of languages still
vague, and state-of-the-art in languages evolution still lack a comprehensive characterization. In general, this problem is mainly tackled by statistical measuring the
changes on the part of the language ( e.g., words and sounds). Given the current
availability of data and computational power, this dissertation proposes a comprehensive data-driven characterization of language evolution using vocabulary in
two main fields. First, extracted and classified the structural and chronological
relations between the languages using its vocabulary. Second, studied the Spatio-temporal effect on language vocabulary and its relation with socio-economic factors ( i.e., educational attainment). The results demonstrated that the proposed
method is capable of uncovering the relation between languages from both structural and chronological aspects, also we found that the vocabulary levels can reveal
the educational attainment of a resident population for specific areas and times.
Thesis (Ph.D.) - Florida Institute of Technology, 2020.
2020-05-01T00:00:00ZDesign, Analysis, and Demonstration of a Multipurpose Fluid Tank Dynamics Characterization Platform
http://hdl.handle.net/11141/3128
Design, Analysis, and Demonstration of a Multipurpose Fluid Tank Dynamics Characterization Platform
Hume, Cameron Ian
The development of a highly versatile multiphase fluid tank characterization platform is
essential to the analysis and improvement of propellant storage tanks. The performance of
these tanks is highly critical to the safety and performance of their carriers, especially in
the space industry where the propellant makes up the overwhelming majority of the mass
of the vehicle. This thesis outlines the design and development of a linear stage used to test
and validate the characteristic of multiphase fluids inside moving specific tanks. This
document will walk through the steps taken to bring a new linear stage to life, from the
development of effective requirements, through design and analysis to the demonstration
of the final product. The final product is a powerfully yet precise piece of machinery that
will add value to the area of fluids research for years to come.
Thesis (M.S.) - Florida Institute of Technology, 2020.
2020-05-01T00:00:00Z