Engineering Commons^™

Blockchain-Enabled Authenticated Key Agreement Scheme For Mobile Vehicles-Assisted Precision Agricultural Iot Networks, Anusha Vangala, Ashok Kumar Das, Ankush Mitra, Sajal K. Das, Youngho Park

Computer Science Faculty Research & Creative Works

Precision Farming Has a Positive Potential in the Agricultural Industry Regarding Water Conservation, Increased Productivity, Better Development of Rural Areas, and Increased Income. Blockchain Technology is a Better Alternative for Storing and Sharing Farm Data as It is Reliable, Transparent, Immutable, and Decentralized. Remote Monitoring of an Agricultural Field Requires Security Systems to Ensure that Any Sensitive Information is Exchanged Only among Authenticated Entities in the Network. to This End, We Design an Efficient Blockchain-Enabled Authenticated Key Agreement Scheme for Mobile Vehicles-Assisted Precision Agricultural Internet of Things (IoT) Networks Called AgroMobiBlock. the Limited Existing Work on Authentication in Agricultural Networks …

Assessing The Impact Of Contact Tracing With An Agent-Based Model For Simulating The Spread Of Covid-19: The Irish Experience, Elizabeth Hunter, Sudipta Saha, Jwenish Kumawat, Ciara Carroll, John Kelleher, Claire Buckley, Conor Mcaloon, Patricia Kearney, Michelle Gilbert, Greg Martin

Articles

Contact tracing is an important tool in managing infectious disease outbreaks and Ireland used a comprehensive contact tracing program to slow the spread of COVID-19. Although the benefits of contact tracing seem obvious, it is difficult to estimate the actual impact contact tracing has on an outbreak because it is hard to separate the effects of contact tracing from other behavioural changes or interventions. To understand the impact contact tracing had in Ireland, we used an agent-based model that is designed to simulate the spread of COVID-19 through Ireland. The model uses real contact tracing data from the first year …

A Structured Narrative Prompt For Prompting Narratives From Large Language Models: Sentiment Assessment Of Chatgpt-Generated Narratives And Real Tweets, Christopher J. Lynch, Erik J. Jensen, Virginia Zamponi, Kevin O'Brien, Erika Frydenlund, Ross Gore

VMASC Publications

Large language models (LLMs) excel in providing natural language responses that sound authoritative, reflect knowledge of the context area, and can present from a range of varied perspectives. Agent-based models and simulations consist of simulated agents that interact within a simulated environment to explore societal, social, and ethical, among other, problems. Simulated agents generate large volumes of data and discerning useful and relevant content is an onerous task. LLMs can help in communicating agents' perspectives on key life events by providing natural language narratives. However, these narratives should be factual, transparent, and reproducible. Therefore, we present a structured narrative prompt …

Reality Analagous Synthetic Dataset Generation With Daylight Variance For Deep Learning Classification, Thomas Lee, Susan Mckeever, Jane Courtney

Conference papers

For the implementation of Autonomously navigating Unmanned Air Vehicles (UAV) in the real world, it must be shown that safe navigation is possible in all real world scenarios. In the case of UAVs powered by Deep Learning algorithms, this is a difficult task to achieve, as the weak point of any trained network is the reduction in predictive capacity when presented with unfamiliar input data. It is possible to train for more use cases, however more data is required for this, requiring time and manpower to acquire. In this work, a potential solution to the manpower issues of exponentially scaling …

A Monte Carlo Framework For Incremental Improvement Of Simulation Fidelity, Damian M. Lyons, James Finocchiaro, Misha Novitzky, Chris Korpela

Faculty Publications

Robot software developed in simulation often does not be- have as expected when deployed because the simulation does not sufficiently represent reality - this is sometimes called the `reality gap' problem. We propose a novel algorithm to address the reality gap by injecting real-world experience into the simulation. It is assumed that the robot program (control policy) is developed using simulation, but subsequently deployed on a real system, and that the program includes a performance objective monitor procedure with scalar output. The proposed approach collects simulation and real world observations and builds conditional probability functions. These are used to generate …

A Monte Carlo Framework For Incremental Improvement Of Simulation Fidelity, Damian Lyons, James Finocchiaro, Misha Novitsky, Chris Korpela

Faculty Publications

Robot software developed in simulation often does not be- have as expected when deployed because the simulation does not sufficiently represent reality - this is sometimes called the `reality gap' problem. We propose a novel algorithm to address the reality gap by injecting real-world experience into the simulation. It is assumed that the robot program (control policy) is developed using simulation, but subsequently deployed on a real system, and that the program includes a performance objective monitor procedure with scalar output. The proposed approach collects simulation and real world observations and builds conditional probability functions. These are used to generate …

Generating Reality-Analogous Datasets For Autonomous Uav Navigation Using Digital Twin Areas, Thomas Lee, Susan Mckeever, Jane Courtney

Conference papers

In order for autonomously navigating Unmanned Air Vehicles(UAVs) to be implemented in day-to-day life, proof of safe operation will be necessary for all realistic navigation scenarios. For Deep Learning powered navigation protocols, this requirement is challenging to fulfil as the performance of a network is impacted by how much the test case deviates from data that the network was trained on. Though networks can generalise to manage multiple scenarios in the same task, they require additional data representing those cases which can be costly to gather. In this work, a solution to this data acquisition problem is suggested by way …

Power-Over-Tether Unmanned Aerial System Leveraged For Trajectory Influenced Atmospheric Sensing, Daniel Rico

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

The use of unmanned aerial systems (UASs) in agriculture has risen in the past decade and is helping to modernize agriculture. UASs collect and elucidate data previously difficult to obtain and are used to help increase agricultural efficiency and production. Typical commercial off-the-shelf (COTS) UASs are limited by small payloads and short flight times. Such limits inhibit their ability to provide abundant data at multiple spatiotemporal scales. In this thesis, we describe the design and construction of the tethered aircraft unmanned system (TAUS), which is a novel power-over-tether UAS configured for long-term, high throughput atmospheric monitoring with an array of …

An End-To-End Trainable Method For Generating And Detecting Fiducial Markers, J Brennan Peace

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Existing fiducial markers are designed for efficient detection and decoding. The methods are computationally efficient and capable of demonstrating impressive results, however, the markers are not explicitly designed to stand out in natural environments and their robustness is difficult to infer from relatively limited analysis. Worsening performance in challenging image capture scenarios - such as poorly exposed images, motion blur, and off-axis viewing - sheds light on their limitations. The method introduced in this work is an end-to-end trainable method for designing fiducial markers and a complimentary detector. By introducing back-propagatable marker augmentation and superimposition into training, the method learns …

Evaluating Driving Performance Of A Novel Behavior Planning Model On Connected Autonomous Vehicles, Keyur Shah

Honors Scholar Theses

Many current algorithms and approaches in autonomous driving attempt to solve the "trajectory generation" or "trajectory following” problems: given a target behavior (e.g. stay in the current lane at the speed limit or change lane), what trajectory should the vehicle follow, and what inputs should the driving agent apply to the throttle and brake to achieve this trajectory? In this work, we instead focus on the “behavior planning” problem—specifically, should an autonomous vehicle change lane or keep lane given the current state of the system?

In addition, current theory mainly focuses on single-vehicle systems, where vehicles do not communicate with …

A Quantile-Based Approach For Transmission Expansion Planning, Jairo Cervantes, F. Fred Choobineh

Department of Electrical and Computer Engineering: Faculty Publications

Transmission expansion planning is an integral part of power system planning and consists of generating and selecting transmission proposals for maintaining sufficient transmission capacity to satisfy the electric load. Specifically, the desire to increase the use of renewable energy has exposed the limitations of transmission networks and has elevated the importance of transmission expansion planning. However, considering the random nature of renewable sources in conjunction with the power outages makes the planning process very challenging. We present a new procedure for selecting the best transmission enhancement proposal from a set of finite proposals under uncertainty. The selection is based on …

The Trolley Problem In Virtual Reality, Jungsu Pak, Ariane Guirguis, Nicholas Mirchandani, Scott Cummings, Uri Maoz

Student Scholar Symposium Abstracts and Posters

Would people react to the Trolley problem differently based on the medium? Immersive Virtual Reality Driving Simulator was used to examine participants respond to the trolley problem in a realistic and controlled simulated environment.

Domain Adaptation In Unmanned Aerial Vehicles Landing Using Reinforcement Learning, Pedro Lucas Franca Albuquerque

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Landing an unmanned aerial vehicle (UAV) on a moving platform is a challenging task that often requires exact models of the UAV dynamics, platform characteristics, and environmental conditions. In this thesis, we present and investigate three different machine learning approaches with varying levels of domain knowledge: dynamics randomization, universal policy with system identification, and reinforcement learning with no parameter variation. We first train the policies in simulation, then perform experiments both in simulation, making variations of the system dynamics with wind and friction coefficient, then perform experiments in a real robot system with wind variation. We initially expected that providing …

Personal Universes: A Solution To The Multi-Agent Value Alignment Problem, Roman V. Yampolskiy

Faculty Scholarship

AI Safety researchers attempting to align values of highly capable intelligent systems with those of humanity face a number of challenges including personal value extraction, multi-agent value merger and finally in-silico encoding. State-of-the-art research in value alignment shows difficulties in every stage in this process, but merger of incompatible preferences is a particularly difficult challenge to overcome. In this paper we assume that the value extraction problem will be solved and propose a possible way to implement an AI solution which optimally aligns with individual preferences of each user. We conclude by analyzing benefits and limitations of the proposed approach.

Design And Implementation Of A Stand-Alone Tool For Metabolic Simulations, Milad Ghiasi Rad

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

In this thesis, we present the design and implementation of a stand-alone tool for metabolic simulations. This system is able to integrate custom-built SBML models along with external user’s input information and produces the estimation of any reactants participating in the chain of the reactions in the provided model, e.g., ATP, Glucose, Insulin, for the given duration using numerical analysis and simulations. This tool offers the food intake arguments in the calculations to consider the personalized metabolic characteristics in the simulations. The tool has also been generalized to take into consideration of temporal genomic information and be flexible for simulation …

On The Simulation And Mitigation Of Anisoplanatic Optical Turbulence For Long Range Imaging, Russell C. Hardie, Daniel A. Lemaster

Electrical and Computer Engineering Faculty Publications

We describe a numerical wave propagation method for simulating long range imaging of an extended scene under anisoplanatic conditions. Our approach computes an array of point spread functions (PSFs) for a 2D grid on the object plane. The PSFs are then used in a spatially varying weighted sum operation, with an ideal image, to produce a simulated image with realistic optical turbulence degradation. To validate the simulation we compare simulated outputs with the theoretical anisoplanatic tilt correlation and differential tilt variance. This is in addition to comparing the long- and short-exposure PSFs, and isoplanatic angle. Our validation analysis shows an …

Advances In Repurposing And Recycling Of Post-Vehicle-Application Lithium-Ion Batteries, Charles R. Standridge, Lindsay Corneal, Nicholas Baine

Mineta Transportation Institute

Increased electrification of vehicles has increased the use of lithium-ion batteries for energy storage, and raised the issue of what to do with post-vehicle-application batteries. Three possibilities have been identified: 1) remanufacturing for intended reuse in vehicles; 2) repurposing for non-vehicle, stationary storage applications; and 3) recycling, extracting the precious metals, chemicals and other byproducts. Advances in repurposing and recycling are presented, along with a mathematical model that forecasts the manufacturing capacity needed for remanufacturing, repurposing, and recycling. Results obtained by simulating the model show that up to a 25% reduction in the need for new batteries can be achieved …

Zion File System Simulator, Robert Adams, Frederic Paladin

Funded Articles

File systems are fundamental for computers and devices with data storage units. They allow operating systems to understand and organize streams of bytes and obtain readable files from them. There are numerous file systems available in the industry, all with their own unique features. Understanding how these file systems work is essential for computer science students, but their complex nature can be difficult and challenging to grasp, especially for students at the beginning of their career. The Zion File System Simulator was designed with this in mind. Zion is a teaching and experimenting tool, in the form of a small …

Cepsim: Modelling And Simulation Of Complex Event Processing Systems In Cloud Environments, Wilson A. Higashino, Miriam Am Capretz, Luiz F. Bittencourt

Electrical and Computer Engineering Publications

The emergence of Big Data has had profound impacts on how data are stored and processed. As technologies created to process continuous streams of data with low latency, Complex Event Processing (CEP) and Stream Processing (SP) have often been related to the Big Data velocity dimension and used in this context. Many modern CEP and SP systems leverage cloud environments to provide the low latency and scalability required by Big Data applications, yet validating these systems at the required scale is a research problem per se. Cloud computing simulators have been used as a tool to facilitate reproducible and repeatable …

Measuring Autonomy And Solving General Stabilization Problems With Multi-Agent Systems, Rasheed A. Rajabzadeh

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Many distributed complex problems address a particular form of resource scheduling where proper resource management can cut costs by stabilizing a set of stochastic fluctuating parameters. Wireless sensor network communication, supply chain management, stock trading, intelligent traffic management, and smart grid systems are examples of these problems. Among the various solutions, a common strategy often used to address this type of problems is fluctuation reduction via resource buffering combined with load shifting. Respectively, stable wireless communication, demand for supplies, liquidity, traffic speed, and power demand reduce cost and can be achieved by properly managing sensor data buffers, warehouses, capital, distance …

A P2p Computing System For Overlay Networks, Grzegorz Chmaj, Krzysztof Walkowiak

Electrical & Computer Engineering Faculty Research

A distributed computing system is able to perform data computation and distribution of results at the same time. The input task is divided into blocks, which are then sent to system participants that offer their resources in order to perform calculations. Next, a partial result is sent back by the participants to the task manager (usually one central node). In the case when system participants want to get the final result, the central node may become overloaded, especially if many nodes request the result at the same time. In this paper we propose a novel distributed computation system, which does …

Simulation, Development And Deployment Of Mobile Wireless Sensor Networks For Migratory Bird Tracking, William P. Bennett Jr

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

This thesis presents CraneTracker, a multi-modal sensing and communication system for monitoring migratory species at the continental level. By exploiting the robust and extensive cellular infrastructure across the continent, traditional mobile wireless sensor networks can be extended to enable reliable, low-cost monitoring of migratory species. The developed multi-tier architecture yields ecologists with unconventional behavior information not furnished by alternative tracking systems at such a large scale and for a low-cost. The simulation, development and implementation of the CraneTracker software system is presented. The system is shown effective through multiple proxy deployments on wildlife and has been operational for 10 months …

Decision Strategies For A P2p Computing System, Grzegorz Chmaj, Krzysztof Walkowiak

Electrical & Computer Engineering Faculty Research

Peer-to-Peer (P2P) computing (also called ‘public-resource computing’) is an effective approach to perform computation of large tasks. Currently used P2P computing systems (e.g., BOINC) are most often centrally managed, i.e., the final result of computations is created at a central node using partial results – what may be not efficient in the case when numerous participants are willing to download the final result. In this paper, we propose a novel approach to P2P computing systems. We assume that results can be delivered to all peers in a distributed way using three types of network flows: unicast, Peer-to-Peer and anycast. We …

A Simulation Analysis Of Photovoltaic Ac Module Integrated Converters In Parallel, Under Controlled Edge Shading Conditions, Lynette O'Callaghan, Mick Mckeever, Brian Norton

Conference Papers

A DC and AC power simulation comparison of: a Photovoltaic (PV) array with a modular, parallel, AC converter configuration; and a series, string configuration with a central AC converter, is presented. The systems are simulated using a comprehensive range of edge shading scenarios and irradiance conditions. Power control and transformation circuitry must be designed for shade and module mismatch tolerance to prevent over-proportional power to shade losses, as average losses from Building Integrated PV (BIPV) systems are approximately 20 to 25%, due to shade, mismatch, differences in orientation and inclination, and temperature effects. 59.4% of the simulations showed gains in …

Software Development Approach For Discrete Simulators, Grzegorz Chmaj, Dawid Maksymilian Zydek

Electrical & Computer Engineering Faculty Research

Simulation is the most common approach to perform the problem research. Among several types of simulation, the most common way is the discrete simulation, which assumes the division of the time scale into fixed length time slots. Depending on investigated problem, simulation packages may be used or it could be necessary to design and create own simulation system. In this paper, we propose the complete pre-study scheme and the most commonly appearing implementation problems with suggested solutions. We also describe how to implement the exemplary simulator in C++.

A Relaxed Fusion Of Information From Real And Synthetic Images To Predict Complex Behavior, Damian M. Lyons, D. Paul Benjamin

Faculty Publications

An important component of cognitive robotics is the ability to mentally simulate physical processes and to compare the expected results with the information reported by a robot's sensors. In previous work, we have proposed an approach that integrates a 3D game-engine simulation into the robot control architecture. A key part of that architecture is the Match-Mediated Difference (MMD) operation, an approach to fusing sensory data and synthetic predictions at the image level. The MMD operation insists that simulated and predicted scenes are similar in terms of the appearance of the objects in the scene. This is an overly restrictive constraint …

Integrating Perception And Problem Solving To Predict Complex Object Behaviors, Damian M. Lyons, Sirhan Chaudhry, Marius Agica, John Vincent Monaco

Faculty Publications

One of the objectives of Cognitive Robotics is to construct robot systems that can be directed to achieve realworld goals by high-level directions rather than complex, low-level robot programming. Such a system must have the ability to represent, problem-solve and learn about its environment as well as communicate with other agents. In previous work, we have proposed ADAPT, a Cognitive Architecture that views perception as top-down and goaloriented and part of the problem solving process.

Our approach is linked to a SOAR-based problem-solving and learning framework. In this paper, we present an architecture for the perceptive and world modelling components …

Nato Human View Architecture And Human Networks, Holly A. H. Handley, Nancy P. Houston

Engineering Management & Systems Engineering Faculty Publications

The NATO Human View is a system architectural viewpoint that focuses on the human as part of a system. Its purpose is to capture the human requirements and to inform on how the human impacts the system design. The viewpoint contains seven static models that include different aspects of the human element, such as roles, tasks, constraints, training and metrics. It also includes a Human Dynamics component to perform simulations of the human system under design. One of the static models, termed Human Networks, focuses on the human-to-human communication patterns that occur as a result of ad hoc or deliberate …

A Hardware Framework For Yield And Reliability Enhancement In Chip Multiprocessors, Abhisek Pan

Masters Theses 1911 - February 2014

Device reliability and manufacturability have emerged as dominant concerns in end-of-road CMOS devices. Today an increasing number of hardware failures are attributed to device reliability problems that cause partial system failure or shutdown. Also maintaining an acceptable manufacturing yield is seen as challenge because of smaller feature sizes, process variation, and reduced headroom for burn-in tests. In this project we investigate a hardware-based scheme for improving yield and reliability of a homogeneous chip multiprocessor (CMP). The proposed solution involves a hardware framework that enables us to utilize the redundancies inherent in a multi-core system to keep the system operational in …

Utilizing Strategic Project Management Processes And The Nato Code Of Best Practice To Improve Management Of Experimentation Events, Andreas Tolk, Rafael E. Landaeta, Robert H. Kewley, Thomas T. Litwin

Computational Modeling & Simulation Engineering Faculty Publications

Systems engineering and project management are two core engineering management processes supported by core quantitative disciplines within engineering management problems. Traditional approaches to systems engineering focus on a single system being engineered and managed (i.e., project managed), while challenges addressing composition of systems of systems and the reuse of systems for new solutions require a strategic management approach that promote a process flow in which the outputs of one project (e.g., deliverables, knowledge, work documents) are captured for the benefit of other projects within and outside the project-based organization. Two other core processes of engineering management are therefore critical to …