Digital Commons Network^™

Agent Based Terrain Generator: Cruthú, Lawrence L. O'Boyle

Masters Theses

Terrain generation models are applied in different industries and fields of study. Current techniques assist in planning transportation networks, visualizing population migrations, conducting epidemiology research, and training self-driving cars and drones. Many current applications and research models generate complex realistic artifacts, e.g., trees, rivers, coastlines, populations, and even cities. Unfortunately, most of these techniques are described and implemented separately. Techniques do not work together to generate a complete holistic view. This thesis proposes a model, Cruthú (Gaelic for "creation"), that provides a novel platform allowing for complete world generation by integrating existing research and algorithms. The model is inspired by …

Exploring The Impact Of Pretrained Bidirectional Language Models On Protein Secondary Structure Prediction, Dillon G. Daudert

Masters Theses

Protein secondary structure prediction (PSSP) involves determining the local conformations of the peptide backbone in a folded protein, and is often the first step in resolving a protein's global folded structure. Accurate structure prediction has important implications for understanding protein function and de novo protein design, with progress in recent years being driven by the application of deep learning methods such as convolutional and recurrent neural networks. Language models pretrained on large text corpora have been shown to learn useful representations for feature extraction and transfer learning across problem domains in natural language processing, most notably in instances where the …

Deep Reinforcement Learning For Autonomous Search And Rescue, Juan Gonzalo Cárcamo Zuluaga

Masters Theses

Unmanned Aerial Vehicles (UAVs) are becoming more prevalent every day. In addition, advances in battery life and electronic sensors have enabled the development of diverse UAV applications outside their original military domain. For example, Search and Rescue (SAR) operations can benefit greatly from modern UAVs since even the simplest commercial models are equipped with high-resolution cameras and the ability to stream video to a computer or portable device. As a result, autonomous unmanned systems (ground, aquatic, and aerial) have recently been employed for such typical SAR tasks as terrain mapping, task observation, and early supply delivery. However, these systems were …

Peer Attention Modeling With Head Pose Trajectory Tracking Using Temporal Thermal Maps, Corey Michael Johnson

Masters Theses

Human head pose trajectories can represent a wealth of implicit information such as areas of attention, body language, potential future actions, and more. This signal is of high value for use in Human-Robot teams due to the implicit information encoded within it. Although team-based tasks require both explicit and implicit communication among peers, large team sizes, noisy environments, distance, and mission urgency can inhibit the frequency and quality of explicit communication. The goal for this thesis is to improve the capabilities of Human-Robot teams by making use of implicit communication. In support of this goal, the following hypotheses are investigated: …

Synthesis And Evaluation Of Acetylcholine Molecularly Imprinted Polymers, Nathaniel Donald Thiemann

Masters Theses

Polymers imprinted with acetylcholine during synthesis were prepared in order to evaluate their potential for implementation as a novel recognition element in acetylcholine biosensors. Biosensors, such as the glucose monitor, are used to rapidly detect and quantify a target analyte. Acetylcholine biosensors have already been produced using enzymatic recognition elements, but they are currently expensive and plagued by short viability. Molecularly imprinted polymers are not only cheap and durable, but have also been successfully used as a recognition element in biosensors for other analytes. Therefore, computational tools were used to rationally design acetylcholine molecularly imprinted polymers. Three chemicals, itaconic acid, …

A Survey Of Security And Privacy In Mobile Cloud Computing, Bhuvaneswari Rayapuri

Masters Theses

Cloud Computing is an emerging technology that provides shared processing resources and data to computers and other devices on demand. On the other hand, Mobile Computing allows transmission of data, voice and video. From these two there emerges a new concept Mobile Cloud Computing which not only overcomes the problems of Mobile Computing but also integrates Cloud Computing into Mobile Environments to overcome obstacles related to Performance, Security and Environment. This paper also provides a decent description on Security and Privacy, its related problems, threats and challenges. This paper first provides details on survey of Mobile Cloud Computing, then it …

Improved Crpd Analysis And A Secure Scheduler Against Information Leakage In Real-Time Systems, Ying Zhang

Masters Theses

"Real-time systems are widely applied to the time-critical fields. In order to guarantee that all tasks can be completed on time, predictability becomes a necessary factor when designing a real-time system. Due to more and more requirements about the performance in the real-time embedded system, the cache memory is introduced to the real-time embedded systems.

However, the cache behavior is difficult to predict since the data will be loaded either on the cache or the memory. In order to taking the unexpected overhead, execution time are often enlarged by a certain (huge) factor. However, this will cause a waste of …

Smart Augmented Reality Instructional System For Mechanical Assembly, Ze-Hao Lai

Masters Theses

"Quality and efficiency are pivotal indicators of a manufacturing company. Many companies are suffering from shortage of experienced workers across the production line to perform complex assembly tasks such as assembly of an aircraft engine. This could lead to a significant financial loss. In order to further reduce time and error in an assembly, a smart system consisting of multi-modal Augmented Reality (AR) instructions with the support of a deep learning network for tool detection is introduced. The multi-modal smart AR is designed to provide on-site information including various visual renderings with a fine-tuned Region-based Convolutional Neural Network, which is …

Cloud Transactions And Caching For Improved Performance In Clouds And Dtns, Dileep Mardham

Masters Theses

"In distributed transactional systems deployed over some massively decentralized cloud servers, access policies are typically replicated. Interdependencies ad inconsistencies among policies need to be addressed as they can affect performance, throughput and accuracy. Several stringent levels of policy consistency constraints and enforcement approaches to guarantee the trustworthiness of transactions on cloud servers are proposed. We define a look-up table to store policy versions and the concept of "Tree-Based Consistency" approach to maintain a tree structure of the servers. By integrating look-up table and the consistency tree based approach, we propose an enhanced version of Two-phase validation commit (2PVC) protocol integrated …

Solidification Rate Detection Through Solid-Liquid Interface Tracking, Wei Luo

Masters Theses

”Studying the melt pool dynamics in laser powder bed fusion (LPBF) additive manufacturing is vital to predict the microstructure of the built part. High-speed synchrotron hard X-ray imaging is an advanced technique to monitor the LPBF process in situ and in real time. However, it is very challenging to track the solid-liquid interface due to the low image contrast, high image noise and unstable intensity of the image sequences.

In this paper, we propose an solid-liquid interface detector with human interaction to track the interface to compute the solidification rate of the melt pool. The proposed method includes six independent …

A Network Tomography Approach For Traffic Monitoring In Smart Cities, Ruoxi Zhang

Masters Theses

"Various urban planning and managing activities required by a Smart City are feasible because of traffic monitoring. As such, the thesis proposes a network tomography-based approach that can be applied to road networks to achieve a cost-efficient, flexible, and scalable monitor deployment. Due to the algebraic approach of network tomography, the selection of monitoring intersections can be solved through the use of matrices, with its rows representing paths between two intersections, and its columns representing links in the road network. Because the goal of the algorithm is to provide a cost-efficient, minimum error, and high coverage monitor set, this problem …

Analyzing Large Scale Trajectory Data To Identify Users With Similar Behavior, Tyler Clark Percy

Masters Theses

"In today's society, social networks are a popular way to connect with friends and family and share what's going on in your life. With the Internet connecting us all closer than ever before, it is increasingly common to use social networks to meet new friends online that share similar interests instead of only connecting with those you already know. For the problem of attempting to connect people with similar interests, this paper proposes the foundation for a Geo-social network that aims to extract the semantic meaning from users' location history and use this information to find the similarity between users. …

Classification Of Eeg Signals Of User States In Gaming Using Machine Learning, Chandana Mallapragada

Masters Theses

"In this research, brain activity of user states was analyzed using machine learning algorithms. When a user interacts with a computer-based system including playing computer games like Tetris, he or she may experience user states such as boredom, flow, and anxiety. The purpose of this research is to apply machine learning models to Electroencephalogram (EEG) signals of three user states -- boredom, flow and anxiety -- to identify and classify the EEG correlates for these user states. We focus on three research questions: (i) How well do machine learning models like support vector machine, random forests, multinomial logistic regression, and …

Reputation And Credit Based Incentive Mechanism For Data-Centric Message Delivery In Delay Tolerant Networks, Himanshu Jethawa

Masters Theses

"In a Data-centric Delay Tolerant Networks (DTNs), it is essential for nodes to cooperate in message forwarding in order to enable successful delivery of a message in an opportunistic fashion with nodes having their social interests defined. In the data-centric dissemination protocol proposed here, a source annotates messages (images) with keywords, and then intermediate nodes are presented with an option of adding keyword-based annotations in order to create higher content strength messages on path toward the destination. Hence, contents like images get enriched as there is situation evolution or learned by these intermediate nodes, such as in a battlefield, or …

An Approach For Formal Analysis Of The Security Of A Water Treatment Testbed, Sai Sidharth Patlolla

Masters Theses

"This thesis focuses on securing critical infrastructures such as chemical plants, manufacturing units, and power generating plants against attacks that disrupt the information flow from one component to another. Such systems are controlled by an Industrial Control System (ICS) that includes controllers communicating with each other, and with physical sensors and actuators, using a communications network.

Traditional security models partition the security universe into two worlds, secure and insecure, but in the real world the partitions often overlap and information is leaked even through the physical observation which makes it much harder to analyze a Cyber physical system (CPS). To …

Card: Concealed And Remote Discovery Of Iot Devices In Victims' Home Networks, Sammie Lee Bush

Masters Theses

"Smart devices are becoming more common in the standard households. They range from lights to refrigerators and their functionality and applications continues to grow with consumer demand. This increase in networked, complex devices has also brought an increase in vulnerabilities in the average consumer's home. There now exists an Internet of Things (IoT) ecosystem that creates new attack vectors for adversaries to spread malware, build botnets, and participate in other malicious activities. We will overview some of these new attack vectors as well as go over a framework that would allow an adversary to target a user's home network and …

Mixed-Criticality Real-Time Task Scheduling With Graceful Degradation, Samsil Arefin

Masters Theses

”The mixed-criticality real-time systems implement functionalities of different degrees of importance (or criticalities) upon a shared platform. In traditional mixed-criticality systems, under a hi mode switch, no guaranteed service is provided to lo-criticality tasks. After a mode switch, only hi-criticality tasks are considered for execution while no guarantee is made to the lo-criticality tasks. However, with careful optimistic design, a certain degree of service guarantee can be provided to lo-criticality tasks upon a mode switch. This concept is broadly known as graceful degradation. Guaranteed graceful degradation provides a better quality of service as well as it utilizes the system resource …

Multiple Security Domain Non Deducibility In The Freedm Smart Grid Infrastructure, Manish Jaisinghani

Masters Theses

"The building block of today's world are not materials, but, computers and algorithms with communication networks between physical entities. A cyber physical system (CPS) is a system in which the cyber and physical entities of the system work together towards a common goal, for example a water treatment facility or an electricity distribution system. These cyber physical infrastructures affect day to day lives of people and hence become target point for the attackers to disrupt normal daily life. Owing to the complexity of a cyber physical system, the attacks have themselves become sophisticated and harder to detect. These sophisticated attacks …

Analyzing Sensor Based Human Activity Data Using Time Series Segmentation To Determine Sleep Duration, Yogesh Deepak Lad

Masters Theses

"Sleep is the most important thing to rest our brain and body. A lack of sleep has adverse effects on overall personal health and may lead to a variety of health disorders. According to Data from the Center for disease control and prevention in the United States of America, there is a formidable increase in the number of people suffering from sleep disorders like insomnia, sleep apnea, hypersomnia and many more. Sleep disorders can be avoided by assessing an individual's activity over a period of time to determine the sleep pattern and duration. The sleep pattern and duration can be …

Precise Energy Efficient Scheduling Of Mixed-Criticality Tasks & Sustainable Mixed-Criticality Scheduling, Sai Sruti

Masters Theses

"In this thesis, the imprecise mixed-criticality model (IMC) is extended to precise scheduling of tasks, and integrated with the dynamic voltage and frequency scaling (DVFS) technique to enable energy minimization. The challenge in precise scheduling of MC systems is to simultaneously guarantee the timing correctness for all tasks, hi and lo, under both pessimistic and optimistic (less pessimistic) assumptions. To the best of knowledge this is the first work to address the integration of DVFS energy conserving techniques with precise scheduling of lo-tasks of the MC model.

In this thesis, the utilization based schedulability tests and sufficient conditions for such …

Cyber-Physical Security Of An Electric Microgrid, Prashanth Palaniswamy

Masters Theses

"Cyber-physical systems (CPSs) are physical systems that are controlled or monitored by computer-based systems. CPSs are a combination of computation, networking, and physical processes. As CPSs are a combination of various diverse components, they are vulnerable to several security threats. Moreover, there are many different security domains (not just high/low, nor necessarily hierarchical). This paper utilizes previously developed multiple security domain nondeducibility (MSDND) to uncover potential integrity vulnerabilities in an electric microgrid. Invariants are manually generated using the insights obtained through MSDND analysis and use linear regression to automate the generation of invariants. The vulnerabilities are then mitigated, to the …

Defense In Depth Network Perimeter Security, Anuoluwapo Ope Fatokun

Masters Theses

Defense in depth network perimeter security has always be a topic of discussion for a long time as an efficient way of mitigating cyber-attacks. While there are no 100% mitigating method against cyber-attacks, a layered defense in depth network perimeter security can be used to mitigate against cyber-attacks. Research have shown a massive growth in cyber-crimes and there are limited number of cyber security expert to counter this attacks. EIU as an institution is taking up the responsibility of producing cyber security graduates with the new Master of Science in Cyber Security program that started in Fall 2017.

This research …