Shankar, Ravi

Healthcare organizations, realizing the potential of the Internet of Things (IoT)
technology, are rapidly adopting the technology to bring signi cant improvements in
the quality and e ectiveness of the service. However, these smart and interconnected
devices can act as a potential \back door" into a hospital's IT network, giving attack-
ers access to sensitive information. As a result, cyber-attacks on medical IoT devices
have been increasing since the last few years. It is a growing concern for all the
stakeholders involved, as the impact of such attacks is not just monetary or privacy
loss, but the lives of many patients are also at risk. Considering the various kinds of
IoT devices one may nd connected to a hospital's network, traditional host-centric
security solutions (e.g. antivirus, software patches) are at odds with realistic IoT
infrastructure (e.g. constrained hardware, lack of proper built-in security measures).
There is a need for security solutions which consider the challenges of IoT devices like
heterogeneity of technology and protocols used, limited resources in terms of battery
and computation power, etc. Accordingly, the goals of this thesis have been: (1) to
provide an in-depth understanding of vulnerabilities of medical IoT devices; (2) to in-
troduce a novel approach which uses a microservices-based framework as an adaptive and agile security solution to address the issue. The thesis focuses on OS Fingerprint-
ing attacks because of its signi cance for attackers to understand a target's network.
In this thesis, we developed three microservices, each one designed to serve a speci c
functionality. Each of these microservices has a small footprint with RAM usage of
approximately 50 MB. We also suggest how microservices can be used in a real-life
scenario as a software-based security solution to secure a hospital's network consisting
of di erent IoT devices.

With the increasing complexity of the system design, it has become very critical to
enhance system design productivity to meet with the time-to-market demands. Real Time
embedded system designers are facing extreme challenges in underlying architectural
design selection. It involves the selection of a programmable, concurrent, heterogeneous
multiprocessor architecture platform. Such a multiprocessor system on chip (MPSoC)
platform has set new innovative trends for the real-time systems and system on Chip
(SoC) designers. The consequences of this trend imply the shift in concern from
computation and sequential algorithms to modeling concurrency, synchronization and
communication in every aspect of hardware and software co-design and development.
Some of the main problems in the current deep sub-micron technologies characterized by
gate lengths in the range of 60-90 nm arise from non scalable wire delays, errors in signal
integrity and un-synchronized communication. These problems have been addressed by
the use of packet switched Network on Chip (NOC) architecture for future SoCs and
thus, real-time systems. Such a NOC based system should be able to support different levels of quality of service (QoS) to meet the real time systems requirements. It will
further help in enhancing the system productivity by providing a reusable communication
backbone. Thus, it becomes extremely critical to properly design a communication
backbone (CommB) for NOC. Along with offering different levels of QoS, CommB is
responsible directing the flow of data from one node to another node through routers,
allocators, switches, queues and links. In this dissertation I present a reusable component
based, design of CommB, suitable for embedded applications, which supports three types
of QoS (real-time, multi-media and control applications).

Enhanced system design productivity is key to satisfying time-to-market demands. One
will have to exploit design reuse methodology to meet project schedule requirements.
Integration of components often fails due to various concurrency violations.
Concurrency issues arise when components executing in parallel share resources and
interact with each other. Such a system may have intermittent, yet catastrophic failures,
if these concurrency issues are not addressed properly. In this thesis, we propose a
methodology for developing concurrency compliant components from a requirement
document. We have applied this methodology for developing process management and
memory management aspects of a Real Time Operating System (RTOS). In this
methodology, we start from a "customer' s" requirement document that is then mapped to
activity diagram, swimlane diagram, class diagrams, and use case diagrams. To evolve a
concurrency compliant design, we use the Message Sequence Chart plug-in for the
Labeled Transition State Analyzer (LTSA). This plug-in lets us use Message Sequence
Charts rather than coding in Finite State Processes (FSP). Later, we use MLDesigner to
simulate our R TOS sub-system and demonstrate proper behavior of this sub-system.

Sentiment Analysis has been researched in a variety of contexts but in this thesis, the focus is on sentiment analysis in Twitter, which poses its own unique challenges such as the use of slang, abbreviations, emoticons, hashtags, and user mentions. The 140-character restriction on the length of tweets can also lead to text that is difficult even for a human to determine its sentiment. Specifically, this study will analyze sentiment analysis of bilingual (U.S. English and Spanish language) Tweets. The hypothesis here is that Bilingual sentiment analysis is more accurate than sentiment analysis in a single language (English or Spanish) when analyzing bilingual tweets. In general, currently sentiment analysis in bilingual tweets is done against an English dictionary. For each of the test cases in this thesis’ experiment we will use the Python NLTK sentiment package.

This report describes the development of a low cost open source semiautonomous
robotic car and a way to communicate with it. It is a continuation of
prior research done by other students at FAU and published in recent ASEE
conferences.
The objective of this project was the development of a new robotic
platform with improved precision over the original, while still keeping the cost
down. It was developed with the aim to allow a hands-on approach to the
teaching of mathematics topics that are taught in the K-12 syllabus.
Improved robustness and reliability of the robotic platform for visually
solving math problems was achieved using a combination of PID loops to keep
track of distance and rotation. The precision was increased by changing the
position of the encoders to the shafts of each motor. A mobile application was developed to allow the student to draw the
geometric shapes on the screen before the car draws them. The mobile
application consists of two parts, the canvas that the user uses to draw the figure
and the configure section that lets the user change the parameters of the
controller.
Results show that the robot can draw standard geometric and complex
geometric shapes. It has high precision and sufficient accuracy, the accuracy can
be improved with some mechanical adjustments. During testing a Pythagorean
triangle was drawn to show visually the key mathematics concept.
The eventual goal of this project will be a K-12 class room study to obtain
the feedback of the teachers and students on the feasibility of using a robotic car
to teach math. Subsequent to that necessary changes will be made to
manufacture a unit that is easy to assemble by the teacher.

The visualization of recent episodes regarding apparently unjustifiable deaths of minorities, caused by police and federal law enforcement agencies, has been amplified through today's social media and television networks. Such events may seem to imply that issues concerning racial inequalities in America are getting worse. However, we do not know whether such indications are factual; whether this is a recent phenomenon, whether racial inequality is escalating relative to earlier decades, or whether it is better in certain regions of the nation compared to others. We have built a semantic engine for the purpose of querying statistics on various metropolitan areas, based on a database of individual deaths. Separately, we have built a database of demographic data on poverty, income, education attainment, and crime statistics for the top 25 most populous metropolitan areas. These data will ultimately be combined with government data to evaluate this hyp othesis, and provide a tool for predictive analytics. In this thesis, we will provide preliminary results in that direction. The methodology in our research consisted of multiple steps. We initially described our requirements and drew data from numerous datasets, which contained information on the 23 highest populated Metropolitan Statistical Areas in the United States. After all of the required data was obtained we decomposed the Metropolitan Statistical Area records into domain components and created an Ontology/Taxonomy via Protege to determine an hierarchy level of nouns towards identifying significant keywords throughout the datasets to use as search queries. Next, we used a Semantic Web implementation accompanied with Python programming language, and FuXi to build and instantiate a vocabulary. The Ontology was then parsed for the entered search query and returned corresponding results providing a semantically organized a nd relevant output in RDF/XML format.

This research proposes an Infrastructure to model complex systems for hydrological modeling.
Currently, the three main hydrological packages are: i) SEAWAT (modeling groundwater flow); ii) HECRAS
(modeling surface water flow); iii) HEC-HMS (modeling atmospheric water flow). Each of these models is self-contained and has a different timescale and simulation speed. Consequently, any integrated model will only run as fast as the slowest of the models. This makes it difficult to provide reliable and dynamic information on water levels and water availability for a given geographical region in a timely manner. The goal of this research is to facilitate the integration of multiple hydrological models from different hydrological packages by applying Electronic Design Automation (EDA) methodologies, including System Level Design (SLD) methodology, SystemC-AMS language, Python language and libraries (numpy, Statsmodels, and ctypes). The EDA methodology brings in the additional advantage of significantly improved simulation speed. The Infrastructure to Model Complex Systems applications is
demonstrated using the following SEAWAT benchmark problems: i) Case 1; ii) Henry; iii) Elder problem.
Simulation results from the aforementioned benchmarks are analyzed and discussed. Lastly, future research
work is presented.

This thesis describes the modeling of Martial Arts as a markup language. Up until now Martial Arts has already been documented in books, videos, tradition and other methods. Though to represent Martial Arts knowledge consistently and uniformly in a digital era, we introduce the Martial Arts Markup Language (MAML), which is based on XML. Because XML provides a standardized, serializable and portable format, MAML also enables sharing among students, teachers and their peers across different platforms, media and networks. MAML provides the ability, with appropriate XML tools, to document a Martial Arts style in a structured way. To achieve this, we first analyze the aspects that comprise Martial Arts; and how its states and processes relate to one another. We model in MAML describing the stances, transitions, punches, blocks, techniques, combinations, reactions and patterns used in Martial Arts. We discuss the implementation of MAML by observing and extracting the definable aspects in existing Martial Art Instructive Documents. The MAML Schema assures that the details of a Martial Arts Style’s elements are consistent. Current simulation efforts will be explained as well as areas for future development. We have described Martial Arts by observing what has already been done and creating a structured standard to document them. We hope to enable practitioners’ abilities to learn from and develop their arts by providing a resource in which they can interact with.

The human body is constantly sending, processing, and receiving information about its health. This internal communication process is often times achieved through tiny electrical signals, called Biomedical Signals (Biosignals). In this project, we investigate new ways to process Biosignals using embedded systems and computer simulations. We work with Texas Instruments’ OMAP L-138 Digital Signal Processor and Code Composer Studio IDE to process and analyze the electrical behavior of the human heart (ECG Biosignals). In addition to creating computer codes to process such signals, one expected outcome of this research project is a series of tutorials exploring Biomedical concepts and digital signal processing algorithms. Our goal is to make Biomedical Signal Processing widely accessible, hence our decision to design around low-cost hardware and software, and to make all documentation available online at http://smartsystems.eng.fau.edu/biomedical-signal-processing/.