Computer Engineering Commons^™

Is There A Correlation Between Wikidata Revisions And Trending Hashtags On Twitter?, Paula Dooley

Dissertations

Twitter is a microblogging application used by its members to interact and stay socially connected by sharing instant messages called tweets that are up to 280 characters long. Within these tweets, users can add hashtags to relate the message to a topic that is shared among users. Wikidata is a central knowledge base of information relying on its members and machines bots to keeping its content up to date. The data is stored in a highly structured format with the added SPARQL protocol and RDF Query Language (SPARQL) endpoint to allow users to query its knowledge base.

Forecasting Anomalous Events And Performance Correlation Analysis In Event Data, Sonya Leech [Thesis]

Dissertations

Classical and Deep Learning methods are quite common approaches for anomaly detection. Extensive research has been conducted on single point anomalies. Collective anomalies that occur over a set of two or more durations are less likely to happen by chance than that of a single point anomaly. Being able to observe and predict these anomalous events may reduce the risk of a server’s performance. This paper presents a comparative analysis into time-series forecasting of collective anomalous events using two procedures. One is a classical SARIMA model and the other is a deep learning Long-Short Term Memory (LSTM) model. It then …

Expressing Trust With Temporal Frequency Of User Interaction In Online Communities, Ekaterina Yashkina, Arseny Pinigin, Jooyoung Lee, Manuel Mazzara, Akinlolu Solomon Adekotujo, Adam Zubair, Luca Longo

Conference papers

Reputation systems concern soft security dynamics in diverse areas. Trust dynamics in a reputation system should be stable and adaptable at the same time to serve the purpose. Many reputation mechanisms have been proposed and tested over time. However, the main drawback of reputation management is that users need to share private information to gain trust in a system such as phone numbers, reviews, and ratings. Recently, a novel model that tries to overcome this issue was presented: the Dynamic Interaction-based Reputation Model (DIBRM). This approach to trust considers only implicit information automatically deduced from the interactions of users within …

Estimation And Prediction Of The Human Gait Dynamics For The Control Of An Ankle-Foot Prosthesis, Guilherme Aramizo Ribeiro

Dissertations, Master's Theses and Master's Reports

With the growing population of amputees, powered prostheses can be a solution to improve the quality of life for many people. Powered ankle-foot prostheses can be made to behave similar to the lost limb via controllers that emulate the mechanical impedance of the human ankle. Therefore, the understanding of human ankle dynamics is of major significance. First, this work reports the modulation of the mechanical impedance via two mechanisms: the co-contraction of the calf muscles and a change of mean ankle torque and angle. Then, the mechanical impedance of the ankle was determined, for the first time, as a multivariable …

Mesh Node Communication System For Fire Figthers, Eric E. Hamke, Trace Norris, Jessica E. Ladd, Jeffrey K. Eaton, Jicard J. Malveaux, Manish Bhattarai, Ramiro Jordan, Manel Martinez-Ramon

Electrical & Computer Engineering Technical Reports

This report describes the prototype and demonstration of a reliable local area network (LAN) of devices able to interconnect a crew of fire fighters with a communications node. The data consists of images for thermal cameras at a given rate and other low bandwith data taken from the different sensors of the fire fighter gear, that are connected to the transmitter using a Bluetooth personal area network (PAN). The physical environment is indoors and it is expected that all nodes of the communication networks are distributed in different positions into a building.

Accelerating Reverse Engineering Image Processing Using Fpga, Matthew Joshua Harris

Browse all Theses and Dissertations

In recent decades, field programmable gate arrays (FPGAs) have evolved beyond simple, expensive computational components with minimal computing power to complex, inexpensive computational engines. Today, FPGAs can perform algorithmically complex problems with improved performance compared to sequential CPUs by taking advantage of parallelization. This concept can be readily applied to the computationally dense field of image manipulation and analysis. Processed on a standard CPU, image manipulation suffers with large image sets processed by highly sequential algorithms, but by carefully adhering to data dependencies, parallelized FPGA functions or kernels offer the possibility of significant improvement through threaded CPU functions. This thesis …

Virtual Reality And Analysis Framework For Studying Different Layout Designs, Madison Glines

Browse all Theses and Dissertations

This thesis describes the tools for studying different design prototypes. The goal was to develop effective tools to study these designs using a data-driven approach. “Proof of concept” experiments were conducted, in which participants were allowed to interact with a virtual environment depicting different designs as data pertaining to their virtual location and orientation was recorded for later analysis. The designs included “flat” store racks, as opposed to racks with more varied shapes, as well as “curved” racks. Focus of the design studies was to assist in identifying optimal locations for different product types. The automated data collection mechanisms required …

Securing Modern Cyberspace Using A Multi-Faceted Approach, Yu Li

Browse all Theses and Dissertations

Security has become one of the most significant concerns for our cyberspace. Securing the cyberspace, however, becomes increasingly challenging. This can be attributed to the rapidly growing diversities and complexity of the modern cyberspace. Specifically, it is not any more dominated by connected personal computers (PCs); instead, it is greatly characterized by cyber-physical systems (CPS), embedded systems, dynamic services, and human-computer interactions. Securing modern cyberspace therefore calls for a multi-faceted approach capable of systematically integrating these emerging characteristics. This dissertation presents our novel and significant solutions towards this direction. Specifically, we have devised automated, systematic security solutions to three critical …

A Network Agent-Based Model Of Ethnocentrism And Intergroup Cooperation, Carlos M. Lemos, Ross J. Gore, Laurence Lessard-Phillips, F. Leron Shults

VMASC Publications

We present a network agent-based model of ethnocentrism and intergroup cooperation in which agents from two groups (majority and minority) change their communality (feeling of group solidarity), cooperation strategy and social ties, depending on a barrier of “likeness” (affinity). Our purpose was to study the model’s capability for describing how the mechanisms of preexisting markers (or “tags”) that can work as cues for inducing in-group bias, imitation, and reaction to non-cooperating agents, lead to ethnocentrism or intergroup cooperation and influence the formation of the network of mixed ties between agents of different groups. We explored the model’s behavior via four …

Neutrosophic Set Is A Generalization Of Intuitionistic Fuzzy Set, Inconsistent Intuitionistic Fuzzy Set (Picture Fuzzy Set, Ternary Fuzzy Set), Pythagorean Fuzzy Set, Q-Rung Orthopair Fuzzy Set, Spherical Fuzzy Set, And N-Hyperspherical Fuzzy Set, While Neutrosophication Is A Generalization Of Regret Theory, Grey System Theory, And Three-Ways Decision (Revisited), Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

In this paper we prove that Neutrosophic Set (NS) is an extension of Intuitionistic Fuzzy Set (IFS) no matter if the sum of single-valued neutrosophic components is < 1, or > 1, or = 1. For the case when the sum of components is 1 (as in IFS), after applying the neutrosophic aggregation operators one gets a different result from that of applying the intuitionistic fuzzy operators, since the intuitionistic fuzzy operators ignore the indeterminacy, while the neutrosophic aggregation operators take into consideration the indeterminacy at the same level as truth-membership and falsehood-nonmembership are taken. NS is also more flexible and effective because it …

Improvement Of The Material’S Mechanical Characteristics Using Intelligent Real Time Control Interfaces In Hfc Hardening Process, Florentin Smarandache, Luige Vladareanu, Mihaiela Iliescu, Victor Vladareanu, Alexandru Gal, Octavian Melinte, Adrian Margean

Branch Mathematics and Statistics Faculty and Staff Publications

The paper presents Intelligent Control (IC) Interfaces for real time control of mechatronic systems applied to Hardening Process Control (HPC) in order to improvement of the material’s mechanical characteristics. Implementation of IC laws in the intelligent real time control interfaces depends on the particular circumstances of the models characteristics used and the exact definition of optimization problem. The results led to the development of the IC interfaces in real time through Particle Swarm Optimization (PSO) and neural networks (NN) using off- line the regression methods.

Procure-To-Pay Software In The Digital Age: An Exploration And Analysis Of Efficiency Gains And Cybersecurity Risks In Modern Procurement Systems, Drew Lane

MPA/MPP/MPFM Capstone Projects

Procure-to-Pay (P2P) softwares are an integral part of the payment and procurement processing functions at large-scale governmental institutions. These softwares house all of the financial functions related to procurement, accounts payable, and often human resources, helping to facilitate and automate the process from initiation of a payment or purchase, to the actual disbursal of funds. Often, these softwares contain budgeting and financial reporting tools as part of the offering. As such an integral part of the financial process, these softwares obviously come at an immense cost from a set of reputable vendors. In the case of government, these vendors mainly …

Testing And Validation Framework For Closed-Loop Physiology Management Systems For Critical And Perioperative Care, Farooq M. Gessa

Master’s Theses

The research aims at developing a framework for testing systems such as closed-loop physiology management systems to ensure that they are safe and effective for use with patients. Building medical devices that are both robust and safe is a challenge. There has been a tremendous increase in modernization and innovation of various medical systems but many of these systems either fail trials or are recalled due to safety issues.

Medical operation rooms require care teams responsible for monitoring the patients and other technical surgical devices. The care process requires a balancing administration that takes care of the drugs and fluids …

Analysis And Control Of Fiber-Reinforced Elastomeric Enclosures (Frees), Soheil Habibian

Master’s Theses

While rigid robots are extensively used in various applications, they are limited in the tasks they can perform and can be unsafe in close human-robot interactions. Soft robots on the other hand surpass the capabilities of rigid robots in several ways, such as compatibility with the work environments, degrees of freedom, manufacturing costs, and safe interactions with the environment. This thesis studies the behavior of Fiber-Reinforced Elastomeric Enclosures (FREEs) as a particular type of soft pneumatic actuator that can be used in soft manipulators. A dynamic lumped-parameter model is created to simulate the motion of a single FREE under various …

Dedicated Hardware For Machine/Deep Learning: Domain Specific Architectures, Angel Izael Solis

Open Access Theses & Dissertations

Artificial intelligence has come a very long way from being a mere spectacle on the silver screen in the 1920s [Hml18]. As artificial intelligence continues to evolve, and we begin to develop more sophisticated Artificial Neural Networks, the need for specialized and more efficient machines (less computational strain while maintaining the same performance results) becomes increasingly evident. Though these “new” techniques, such as Multilayer Perceptron’s, Convolutional Neural Networks and Recurrent Neural Networks, may seem as if they are on the cutting edge of technology, many of these ideas are over 60 years old! However, many of these earlier models, at …

Instance Segmentation And Object Detection In Road Scenes Using Inverse Perspective Mapping Of 3d Point Clouds And 2d Images, Chungyup Lee

Electronic Theses and Dissertations

The instance segmentation and object detection are important tasks in smart car applications. Recently, a variety of neural network-based approaches have been proposed. One of the challenges is that there are various scales of objects in a scene, and it requires the neural network to have a large receptive field to deal with the scale variations. In other words, the neural network must have deep architectures which slow down computation. In smart car applications, the accuracy of detection and segmentation of vehicle and pedestrian is hugely critical. Besides, 2D images do not have distance information but enough visual appearance. On …

Smart Parking Deck, Ryne Turner, Matthew Mcdade, Julie Aichinger, Laveréna Wienclaw

Williams Honors College, Honors Research Projects

The Smart Parking Deck employs elementary circuit design elements and mobile application development. Each device module uses laser proximity sensors to check the availability of an individual parking space and a Zigbee unit to communicate with the adjacent device module. The modules are connected to a network hub that manages all of the incoming and outgoing parking data. This data is displayed on the mobile application. The system is easily manageable and energy efficient, significantly decreasing the costs associated with other smart parking systems on the market. This system is aimed at decreasing commute time for students by allowing them …

Islands Of Fitness Compact Genetic Algorithm For Rapid In-Flight Control Learning In A Flapping-Wing Micro Air Vehicle: A Search Space Reduction Approach, Kayleigh E. Duncan

Browse all Theses and Dissertations

On-going effective control of insect-scale Flapping-Wing Micro Air Vehicles could be significantly advantaged by active in-flight control adaptation. Previous work demonstrated that in simulated vehicles with wing membrane damage, in-flight recovery of effective vehicle attitude and vehicle position control precision via use of an in-flight adaptive learning oscillator was possible. Most recent approaches to this problem employ an island-of-fitness compact genetic algorithm (ICGA) for oscillator learning. The work presented provides the details of a domain specific search space reduction approach implemented with existing ICGA and its effect on the in-flight learning time. Further, it will be demonstrated that the proposed …

Towards Data And Model Confidentiality In Outsourced Machine Learning, Sagar Sharma

Browse all Theses and Dissertations

With massive data collections and needs for building powerful predictive models, data owners may choose to outsource storage and expensive machine learning computations to public cloud providers (Cloud). Data owners may choose cloud outsourcing due to the lack of in-house storage and computation resources or the expertise of building models. Similarly, users, who subscribe to specialized services such as movie streaming and social networking, voluntarily upload their data to the service providers' site for storage, analytics, and better services. The service provider, in turn, may also choose to benefit from ubiquitous cloud computing. However, outsourcing to a public cloud provider …

Abusive And Hate Speech Tweets Detection With Text Generation, Abhishek Nalamothu

Browse all Theses and Dissertations

According to a Pew Research study, 41% of Americans have personally experienced online harassment and two-thirds of Americans have witnessed harassment in 2017. Hence, online harassment detection is vital for securing and sustaining the popularity and viability of online social networks. Machine learning techniques play a crucial role in automatic harassment detection. One of the challenges of using supervised approaches is training data imbalance. Existing text generation techniques can help augment the training data, but they are still inadequate and ineffective. This research explores the role of domain-specific knowledge to complement the limited training data available for training a text …

Llvm-Ir Based Decompilation, Ilsoo Jeon

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Decompilation is a process of transforming an executable program into a source-like high-level language code, which plays an important role in malware analysis, and vulnerability detection. In this thesis, we design and implement the middle end of a decompiler framework, focusing on Low Level Language properties reduction using the optimization techniques, propagation and elimination. An open-source software tool, dagger, is used to translate binary code to LLVM (Low Level Virtual Machine) Intermediate Representation code. We perform data flow analysis and control flow analysis on the LLVM format code to generate high-level code using a Functional Programming Langauge (FPL), Haskell. The …

Internet Of Things In Smart Agriculture: Enabling Technologies, Abdul Salam, Syed Shah

Faculty Publications

In this paper, an IoT technology research and innovation roadmap for the field of precision agriculture (PA) is presented. Many recent practical trends and the challenges have been highlighted. Some important objectives for integrated technology research and education in precision agriculture are described. Effective IoT based communications and sensing approaches to mitigate challenges in the area of precision agriculture are presented.

Multirobot Confidence And Behavior Modeling: An Evaluation Of Telerobotic Performance And Efficiency, Nathan Lucas

Wayne State University Dissertations

There is considerable interest in multirobot systems capable of performing spatially distributed, hazardous, and complex tasks as a team. There is also growing interest in manned-unmanned teams leveraging the unique abilities of humans and automated machines working alongside each other. The limitations of human perception and cognition affect the ability of operators to integrate information from multiple mobile robots, switch between their spatial frames of reference, and divide attention among many sensory inputs and command outputs. Automation is necessary to help the operator manage increasing demands as the number of robots scales up. However, more automation does not necessarily equate …

Automatic Resource Management And Performance Optimization In Clusters, Yudi Wei

Wayne State University Dissertations

Virtual machine is a primary way to increase resource utilizations in data centers by encapsulating multi-resource demands for applications and providing performance isolation. Moreover, the resource configuration can change on the fly to satisfy performance target. Container is another popular way for fine-grained multi-resource allocation. In this disser- tation work, we aim to design and implement an automatic resource management system to improve application performance, optimize system efficiency and job completion times in virtual and physical clusters respectively.

For large-scale applications hosted in data center, automatic resource configuration is crucial to service availability and quality. The workload dynamics, cloud dynamics …

Mediaeval2019: Flood Detection In Time Sequence Satellite Images, Palavi Jain, Bianca Schoen-Phelan, Robert J. Ross

Conference papers

In this work, we present a flood detection technique from time series satellite images for the City-centered satellite sequences (CCSS) task in the MediaEval 2019 competition [1]. This work utilises a three channel feature indexing technique [13] along with a VGG16 pretrained model for automatic detection of floods. We also compared our result with RGB images and a modified NDWI technique by Mishra et al, 2015 [15]. The result shows that the three channel feature indexing technique performed the best with VGG16 and is a promising approach to detect floods from time series satellite images.

Autonomous Combat Robot, Andrew J. Szabo Ii, Chris Heldman, Tristin Weber, Tanya Tebcherani, Holden Leblanc, Fabian Ardeljan

Williams Honors College, Honors Research Projects

This honors project will also serve as an engineering senior design project.

The objective is to design and build the software and electrical systems for a 60 lb weight class combat robot that will function autonomously and outperform manually driven robots during competition.

While running autonomously, the robot will use LiDAR sensors to detect and attack opponent robots. This robot will also be able to be remote controlled in manual mode. This will mitigate the risk in case the autonomy or sensors fail. LED lights on the robot will indicate whether it is in autonomous or manual mode. The system …

Safe Pass, Alycia Riese, Julia Hariharan, Greg Synek, Jonathan Hall

Williams Honors College, Honors Research Projects

The purpose of this project is to design a sensor to be mounted on Class IV and higher vehicles to detect on-coming traffic. If traffic has been detected, the system is to warn drivers behind the stopped vehicle that passing is unsafe. The vehicle detection is to be implemented using a LiDAR detection method along with signal processing. A wireless transceiver is to transmit from the front radar module to the rear warning indicator module when the conditions are unsafe for passing. The project goals are to increase road safety and maintain traffic flow. The report details the challenges due …

Speech Enabled Navigation In Virtual Environments, Raksha Rajashekar

Browse all Theses and Dissertations

Navigating in a Virtual Environment with traditional input devices such as mouse, joysticks and keyboards provide limited maneuverability and is also time consuming. While working in a virtual environment, changing parameters to obtain the desired visualization requires time to achieve by manually entering parameter values in an algorithm to test outcomes. The following thesis presents an alternate user interface to reduce user efforts, while navigating within the Virtual Environment. The user interface is an Android application which is designed to accommodate spoken commands. This Speech Enabled User Interface termed as the Speech Navigation Application (SNA), provides the user with an …

Kbot: Knowledge-Enabled Personalized Chatbot For Self-Management Of Asthma In Pediatric Population, Dipesh Kadariya

Browse all Theses and Dissertations

Asthma, chronic pulmonary disease, is one of the major health issues in the United States. Given its chronic nature, the demand for continuous monitoring of patient’s adherence to the medication care plan, assessment of their environment triggers, and management of asthma control level can be challenging in traditional clinical settings and taxing on clinical professionals. A shift from a reactive to a proactive asthma care can improve health outcomes and reduce expenses. On the technology spectrum, smart conversational systems and Internet-of-Things (IoTs) are rapidly gaining popularity in the healthcare industry. By leveraging such technological prevalence, it is feasible to design …

Conditional Dilated Attention Tracking Model - C-Datm, Tyler Clayton Highlander

Browse all Theses and Dissertations

Current commercial tracking systems do not process images fast enough to perform target-tracking in real- time. State-of-the-art methods use entire scenes to locate objects frame-by-frame and are commonly computationally expensive because they use image convolutions. Alternatively, attention mechanisms track more efficiently by mimicking human optical cognitive interaction to only process small portions of an image. Thus, in this work we use an attention-based approach to create a model called C-DATM (Conditional Dilated Attention tracking Model) that learns to compare target features in a sequence of image-frames using dilated convolutions. The C-DATM is tested using the Modified National Institute of Standards …