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Articles 361 - 390 of 1793

Full-Text Articles in Computer Sciences

Robots Still Outnumber Humans In Web Archives In 2019, But Less Than In 2012, Himarsha R. Jayanetti, Kritika Garg, Sawood Alam, Michael L. Nelson, Michele C. Weigle Jan 2023

Robots Still Outnumber Humans In Web Archives In 2019, But Less Than In 2012, Himarsha R. Jayanetti, Kritika Garg, Sawood Alam, Michael L. Nelson, Michele C. Weigle

College of Sciences Posters

To identify robots and human users in web archives, we conducted a study using the access logs from the Internet Archive’s (IA) Wayback Machine in 2012 (IA2012), 2015 (IA2015), and 2019 (IA2019), and the Portuguese Web Archive (PT) in 2019 (PT2019). We identified user sessions in the access logs and classified them as human or robot based on their browsing behavior. In 2013, AlNoamany et al. [1] studied the user access patterns using IA access logs from 2012. They established four web archive user access patterns: single-page access (Dip), access to the same page at multiple archive times (Dive), access …

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Adhd Prediction Through Analysis Of Eye Movements With Graph Convolution Network, Gavindya Jayawardena, Sampath Jayarathna, Yi He Jan 2023

Adhd Prediction Through Analysis Of Eye Movements With Graph Convolution Network, Gavindya Jayawardena, Sampath Jayarathna, Yi He

College of Sciences Posters

Processing speech with background noise requires appropriate parsing of the distorted auditory signal, fundamental language abilities as well as higher signal-to-noise ratio. Adolescents with ADHD have difficulty processing speech with background noise due to reduced inhibitory control and working memory capacity. In this study we utilize Audiovisual Speech-In-Noise performance and eye-tracking measures of young adults with ADHD compared to age-matched controls, and generate graphs for ADHD evaluation using the eye-tracking data. We form graphs utilizing the eight eye-tracking features (fixation count, average, total, and standard deviation of fixation duration, max and min saccade peak velocity, min, average, and standard deviation …

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A Novel Parking Management In Smart City Vehicular Datacenters, Syed Rizvi, Susan Zehra, Steven Olariu Jan 2023

A Novel Parking Management In Smart City Vehicular Datacenters, Syed Rizvi, Susan Zehra, Steven Olariu

College of Sciences Posters

Researchers have shown that most vehicles spend the majority of their time parked in parking garages, lots, or driveways. During this time, their computing resources are unused and untapped. This has led to substantial interest in Vehicular Cloud, an area of research in which each vehicle acts as a computation node. The main difference between traditional cloud computing and vehicular cloud computing is the availability of nodes. In traditional clouds, nodes are available 24/7, while in vehicular clouds, nodes (vehicles) are only available while parked in parking lots. This creates a dynamic environment as vehicles enter and exit parking garages …

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Scalable Quantum Edge Detection Method For D-Nisq Imaging Simulations: Use Cases From Nuclear Physics And Medical Image Computing, Emmanuel Billias, Nikos Chrisochoides Jan 2023

Scalable Quantum Edge Detection Method For D-Nisq Imaging Simulations: Use Cases From Nuclear Physics And Medical Image Computing, Emmanuel Billias, Nikos Chrisochoides

The Graduate School Posters

Edge Detection is one of the computationally intensive modules in image analysis. It is used to find important landmarks by identifying a significant change (or “edge”) between pixels and voxels. We present a hybrid Quantum Edge Detection method by improving three aspects of an existing widely referenced implementation, which for our use cases generates incomprehensible results for the type and size of images we are required to process. Our contributions are in the pre- and post-processing (i.e., classical phase) and a quantum edge detection circuit: (1) we use space- filling curves to eliminate image artifacts introduced by the image decomposition, …

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Metaenhance: Metadata Quality Improvement For Electronic Theses And Dissertations, Muntabir H. Choudhury, Lamia Salsabil, Himarsha R. Jayanetti, Jian Wu Jan 2023

Metaenhance: Metadata Quality Improvement For Electronic Theses And Dissertations, Muntabir H. Choudhury, Lamia Salsabil, Himarsha R. Jayanetti, Jian Wu

College of Sciences Posters

Metadata quality is crucial for digital objects to be discovered through digital library interfaces. Although DL systems have adopted Dublin Core to standardize metadata formats (e.g., ETD-MS v1.11), the metadata of digital objects may contain incomplete, inconsistent, and incorrect values [1]. Most existing frameworks to improve metadata quality rely on crowdsourced correction approaches, e.g., [2]. Such methods are usually slow and biased toward documents that are more discoverable by users. Artificial intelligence (AI) based methods can be adopted to overcome this limit by automatically detecting, correcting, and canonicalizing the metadata, featuring quick and unbiased responses to document metadata. …

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X-Disetrac: Distributed Eye-Tracking With Extended Realities, Bhanuka Mahanama, Sampath Jayarathna Jan 2023

X-Disetrac: Distributed Eye-Tracking With Extended Realities, Bhanuka Mahanama, Sampath Jayarathna

College of Sciences Posters

Humans use heterogeneous collaboration mediums such as in-person, online, and extended realities for day-to-day activities. Identifying patterns in viewpoints and pupillary responses (a.k.a eye-tracking data) provide informative cues on individual and collective behavior during collaborative tasks. Despite the increasing ubiquity of these different mediums, the aggregation and analysis of eye-tracking data in heterogeneous collaborative environments remain unexplored. Our study proposes X-DisETrac: Extended Distributed Eye Tracking, a versatile framework for eye tracking in heterogeneous environments. Our approach tackles the complexity by establishing a platform-agnostic communication protocol encompassing three data streams to simplify data aggregation and …

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Covid-19 Crowd Detection, Mustafa Ibrahim, Aly M. Zeineldin, Yameen Khan, Ayman Elmesalami, Soad Ibrahim Jan 2023

Covid-19 Crowd Detection, Mustafa Ibrahim, Aly M. Zeineldin, Yameen Khan, Ayman Elmesalami, Soad Ibrahim

OUR Journal: ODU Undergraduate Research Journal

Object detection was introduced by researchers for face detection. Researchers explain how the detected face is divided into minor frames to be recognized by the algorithm. Due to COVID-19 and government regulations, many people face problems going to shopping centers and shop safely. It has been very hard for both the government and the people to manage social distancing. In our study, we developed a system using Raspberry Pi-4 that will detect the distance between people along with counting the number of distance and mask violations. An error message will appear on the screen in red, showing the total number …

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A Deep Bilstm Machine Learning Method For Flight Delay Prediction Classification, Desmond B. Bisandu, Irene Moulitsas Jan 2023

A Deep Bilstm Machine Learning Method For Flight Delay Prediction Classification, Desmond B. Bisandu, Irene Moulitsas

Journal of Aviation/Aerospace Education & Research

This paper proposes a classification approach for flight delays using Bidirectional Long Short-Term Memory (BiLSTM) and Long Short-Term Memory (LSTM) models. Flight delays are a major issue in the airline industry, causing inconvenience to passengers and financial losses to airlines. The BiLSTM and LSTM models, powerful deep learning techniques, have shown promising results in a classification task. In this study, we collected a dataset from the United States (US) Bureau of Transportation Statistics (BTS) of flight on-time performance information and used it to train and test the BiLSTM and LSTM models. We set three criteria for selecting highly important features …

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Material Extrusion-Based Additive Manufacturing: G-Code And Firmware Attacks And Defense Frameworks, Haris Rais Jan 2023

Material Extrusion-Based Additive Manufacturing: G-Code And Firmware Attacks And Defense Frameworks, Haris Rais

Theses and Dissertations

Additive Manufacturing (AM) refers to a group of manufacturing processes that create physical objects by sequentially depositing thin layers. AM enables highly customized production with minimal material wastage, rapid and inexpensive prototyping, and the production of complex assemblies as single parts in smaller production facilities. These features make AM an essential component of Industry 4.0 or Smart Manufacturing. It is now used to print functional components for aircraft, rocket engines, automobiles, medical implants, and more. However, the increased popularity of AM also raises concerns about cybersecurity. Researchers have demonstrated strength degradation attacks on printed objects by injecting cavities in the …

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Collaborative Consultation Doctors Model: Unifying Cnn And Vit For Covid-19 Diagnostic, Trong-Thuan Nguyen, Tam Nguyen, Minh-Triet Tran Jan 2023

Collaborative Consultation Doctors Model: Unifying Cnn And Vit For Covid-19 Diagnostic, Trong-Thuan Nguyen, Tam Nguyen, Minh-Triet Tran

Computer Science Faculty Publications

The COVID-19 pandemic presents significant challenges due to its high transmissibility and mortality risk. Traditional diagnostic methods, such as RT-PCR, have limitations that hinder timely and accurate screening. In response, AI-powered computer-aided imaging analysis techniques have emerged as a promising alternative for COVID-19 diagnosis. In this paper, we propose a novel approach that combines the strengths of Convolutional Neural Network (CNN) and Vision Transformer (ViT) to enhance the performance of COVID-19 diagnosis models. CNN excels at capturing spatial features in medical images, while ViT leverages self-attention mechanisms inspired by human radiologists. Additionally, our approach draws inspiration from subclinical diagnosis, a …

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Model Checking Time Window Temporal Logic For Hyperproperties, Ernest Bonnah, Luan Viet Nguyen, Khaza Anuarul Hoque Jan 2023

Model Checking Time Window Temporal Logic For Hyperproperties, Ernest Bonnah, Luan Viet Nguyen, Khaza Anuarul Hoque

Computer Science Faculty Publications

Hyperproperties extend trace properties to express properties of sets of traces, and they are increasingly popular in specifying various security and performance-related properties in domains such as cyber-physical systems, smart grids, and automotive. This paper introduces HyperTWTL, which extends Time Window Temporal Logic (TWTL)-a domain-specific formal specification language for robotics, by allowing explicit and simultaneous quantification over multiple execution traces. We propose two different semantics for HyperTWTL, synchronous and asynchronous, based on the alignment of the timestamps in the traces. Consequently, we demonstrate the application of HyperTWTL in formalizing important information-flow security policies and concurrency for robotics applications. Furthermore, we …

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Uit-Adrone: A Novel Drone Dataset For Traffic Anomaly Detection, Tung Minh Tran, Tu N. Vu, Tam Nguyen, Khang Nguyen Jan 2023

Uit-Adrone: A Novel Drone Dataset For Traffic Anomaly Detection, Tung Minh Tran, Tu N. Vu, Tam Nguyen, Khang Nguyen

Computer Science Faculty Publications

Anomaly detection plays an increasingly important role in video surveillance and is one of the issues that have attracted various communities, such as computer vision, machine learning, and data mining in recent years. Moreover, drones equipped with cameras have quickly been deployed to a wide range of applications, starting from border security applications to street monitoring systems. However, there is a notable lack of adequate drone-based datasets available to detect unusual events in the urban traffic environment, especially in roundabouts, due to the density of interaction between road users and vehicles. To promote the development of anomalous event detection with …

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Enabling Dapps Data Exchange With Hardware-Assisted Secure Oracle Network, Yue Li Jan 2023

Enabling Dapps Data Exchange With Hardware-Assisted Secure Oracle Network, Yue Li

Theses and Dissertations--Computer Science

Decentralized applications (dApps), enabled by the blockchain and smart contract technology, are known for allowing distrustful parties to execute business logic without relying on a central authority. Compared to regular applications, dApps offer a wide range of benefits, including security by design, trustless transactions, and resistance to censorship. However, dApps need to access real-world data to achieve their full potential, relying on the data oracles. Oracles act as bridges between blockchains and the outside world, providing essential data to the smart contracts that power dApps. A significant challenge in integrating oracles into the dApp ecosystem is the Oracle Problem …

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A Secure And Distributed Architecture For Vehicular Cloud And Protocols For Privacy-Preserving Message Dissemination In Vehicular Ad Hoc Networks, Hassan Mistareehi Jan 2023

A Secure And Distributed Architecture For Vehicular Cloud And Protocols For Privacy-Preserving Message Dissemination In Vehicular Ad Hoc Networks, Hassan Mistareehi

Theses and Dissertations--Computer Science

Given the enormous interest in self-driving cars, Vehicular Ad hoc NETworks (VANETs) are likely to be widely deployed in the near future. Cloud computing is also gaining widespread deployment. Marriage between cloud computing and VANETs would help solve many of the needs of drivers, law enforcement agencies, traffic management, etc. The contributions of this dissertation are summarized as follows: A Secure and Distributed Architecture for Vehicular Cloud: Ensuring security and privacy is an important issue in the vehicular cloud; if information exchanged between entities is modified by a malicious vehicle, serious consequences such as traffic congestion and accidents can …

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Crosshair Optimizer, Jason Torrence Jan 2023

Crosshair Optimizer, Jason Torrence

All Master's Theses

Metaheuristic optimization algorithms are heuristics that are capable of creating a "good enough'' solution to a computationally complex problem. Algorithms in this area of study are focused on the process of exploration and exploitation: exploration of the solution space and exploitation of the results that have been found during that exploration, with most resources going toward the former half of the process. The novel Crosshair optimizer developed in this thesis seeks to take advantage of the latter, exploiting the best possible result as much as possible by directly searching the area around that best result with a stochastic approach. This …

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Evaluation Of Edison's Data Science Competency Framework Through A Comparative Literature Analysis, Karl R. B. Schmitt, Linda Clark, Katherine M. Kinnaird, Ruth E. H. Wertz, Björn Sandstede Jan 2023

Evaluation Of Edison's Data Science Competency Framework Through A Comparative Literature Analysis, Karl R. B. Schmitt, Linda Clark, Katherine M. Kinnaird, Ruth E. H. Wertz, Björn Sandstede

Statistical and Data Sciences: Faculty Publications

During the emergence of Data Science as a distinct discipline, discussions of what exactly constitutes Data Science have been a source of contention, with no clear resolution. These disagreements have been exacerbated by the lack of a clear single disciplinary 'parent.' Many early efforts at defining curricula and courses exist, with the EDISON Project's Data Science Framework (EDISON-DSF) from the European Union being the most complete. The EDISON-DSF includes both a Data Science Body of Knowledge (DS-BoK) and Competency Framework (CF-DS). This paper takes a critical look at how EDISON's CF-DS compares to recent work and other published curricular or …

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Dynamic Predictions Of Thermal Heating And Cooling Of Silicon Wafer, Hitesh Kumar Jan 2023

Dynamic Predictions Of Thermal Heating And Cooling Of Silicon Wafer, Hitesh Kumar

Master's Projects

Neural Networks are now emerging in every industry. All the industries are trying their best to exploit the benefits of neural networks and deep learning to make predictions or simulate their ongoing process with the use of their generated data. The purpose of this report is to study the heating pattern of a silicon wafer and make predictions using various machine learning techniques. The heating of the silicon wafer involves various factors ranging from number of lamps, wafer properties and points taken in consideration to capture the heating temperature. This process involves dynamic inputs which facilitates the heating of the …

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Automated Evaluation For Distributed System Assignments, Nimesh Nischal Jan 2023

Automated Evaluation For Distributed System Assignments, Nimesh Nischal

Master's Projects

A distributed system can exist in numerous states, including many erroneous permutations that could have been addressed in the code. As distributed systems such as cloud computing and microservices gain popularity, involving distributed com- puting assignments is becoming increasingly crucial in Computer Science and related fields. However, designing such systems poses various challenges, such as considering parallel executions, error-inducing edge cases, and interactions with external systems. Typically, distributed assignments require students to implement a system and run multiple instances of the same code to behave as distributed. However, such assign- ments do not encourage students to consider the potential edge …

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Visualizing Classification Errors And Mislabeling In Machine Learning, Vedashree Bhandare Jan 2023

Visualizing Classification Errors And Mislabeling In Machine Learning, Vedashree Bhandare

Master's Projects

Deep neural networks have gained popularity and achieved high performance across multiple domains like medical decision-making, autonomous vehicles, decision support systems, etc. Despite this achievement, the internal workings of these models are opaque and are considered as black boxes due to their nested and non-linear structure. This opaque nature of the deep neural networks makes it difficult to interpret the reason behind their output, thus reducing trust and verifiability of the system where these models are applied. This paper explains a systematic approach to identify the clusters with most misclassifications or false label annotations. For this research, we extracted the …

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Proof-Of-Stake For Spartangold, Nimesh Ashok Doolani Jan 2023

Proof-Of-Stake For Spartangold, Nimesh Ashok Doolani

Master's Projects

Consensus protocols are critical for any blockchain technology, and Proof-of- Stake (PoS) protocols have gained popularity due to their advantages over Proof-of- Work (PoW) protocols in terms of scalability and efficiency. However, existing PoS mechanisms, such as delegated and bonded PoS, suffer from security and usability issues. Pure PoS (PPoS) protocols provide a stronger decentralization and offer a potential solution to these problems. Algorand, a well-known cryptocurrency, employs a PPoS protocol that utilizes a new Byzantine Agreement (BA) mechanism for consensus and Verifiable Random Functions (VRFs) to securely scale the protocol to accommodate many participants, making it possible to handle …

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Ubiquitous Application Data Collection In A Disconnected Distributed System, Deepak Munagala Jan 2023

Ubiquitous Application Data Collection In A Disconnected Distributed System, Deepak Munagala

Master's Projects

Despite some incredible advancements in technology, a significant population of the world does not have internet connectivity. These people lack access to crucial information that is easily available to the rest of the world. To solve this problem, we implement a Delay Tolerant Network (DTN) that allows users in disconnected regions access to the internet. This is enabled by collecting all data requests on the users’ phones and passing them to a device that can carry them to a connected region. This device can then collect the necessary information and give it back to the users in the disconnected region. …

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Influence Maximization Based On Community Detection And Dominating Sets, Ameya Marathe Jan 2023

Influence Maximization Based On Community Detection And Dominating Sets, Ameya Marathe

Master's Projects

An online platform where various people come together to share information and communicate is called a social network. These platforms are set apart from other means of communication mostly because you can follow and interact also with different people even some you never met, comment on their posts, and re-sharing their posts. Companies such as Amazon and Walmart use these platforms daily for marketing purposes, like spreading information regarding new products and services they offer. They carefully select a subset of users, called influencers, who are usually the ones with high influence over the rest of the users. Influencers receive …

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Airport Assignment For Emergency Aircraft Using Reinforcement Learning, Saketh Kamatham Jan 2023

Airport Assignment For Emergency Aircraft Using Reinforcement Learning, Saketh Kamatham

Master's Projects

The volume of air traffic is increasing exponentially every day. The Air Traffic Control (ATC) at the airport has to handle aircraft runway assignments for landing and takeoff and airspace maintenance by directing passing aircraft through the airspace safely. If any aircraft is facing a technical issue or problem and is in a state of emergency, it requires expedited landing to respond to that emergency. The ATC gives this aircraft priority to landing and assistance. This process is very strenuous as the ATC has to deal with multiple aspects along with the emergency aircraft. It is the duty of the …

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Rideshare Using Degrees Of Separation: A Social Network-Based Approach, Gokul Garikipati Jan 2023

Rideshare Using Degrees Of Separation: A Social Network-Based Approach, Gokul Garikipati

Master's Projects

Conventional ride-sharing services, such as Lyft and Uber, routinely match drivers with riders based on their proximity to each other, using GPS coordinates and mapping technology. The application then calculates the cost of the ride based on factors such as distance traveled and time spent in the car. The concept of six degrees of separation suggests that a maximum of 6 steps or relationships can connect any two individuals in the world. This idea could be applied to a ride-share service to provide a more personalized and efficient experience for users. Instead of just matching riders with drivers based on …

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Nft Artifact Prediction Using Machine Learning, Rishabh Pandey Jan 2023

Nft Artifact Prediction Using Machine Learning, Rishabh Pandey

Master's Projects

NFT Prediction Systems are web applications that provide their users with valuable insights about the artifact. These insights are useful for investors and collectors to make better decisions about their purchases. This project builds upon the same concept of prediction by developing a web application to dynamically provide recommendations based on user input and training an ML model to predict their cost. Preliminary work for the prediction system involved data collection, pre-processing, analysis, and filtering of large datasets from diverse sources. The project focused on the development of a user- friendly UI to enable seamless categorization of search results generated …

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Spartan Price Oracle: A Schelling-Point Based Decentralized Pirce Oracle, Sihan He Jan 2023

Spartan Price Oracle: A Schelling-Point Based Decentralized Pirce Oracle, Sihan He

Master's Projects

Nakamoto’s Bitcoin is the first decentralized digital cash system that utilizes a blockchain to manage transactions in its peer-to-peer network. The newer generation of blockchain systems, including Ethereum, extend their capabilities to support deployment of smart contracts within their peer-to-peer networks. However, smart contracts cannot acquire data from sources outside the blockchain since the blockchain network is isolated from the outside world. To obtain data from external sources, smart contracts must rely on Oracles, which are agents that bring data from the outside world to a blockchain network. However, guaranteeing that the oracle’s off-chain nodes are trustworthy remains a challenge. …

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The New Student: The Enhancement Of An Ebook To Support Emotional Connection, Rebecca Zumaeta Jan 2023

The New Student: The Enhancement Of An Ebook To Support Emotional Connection, Rebecca Zumaeta

Master's Projects

EBooks are a form of multimedia applications that encourage cognitive learning. Multimedia can also influence readers to have a deeper connection to the story. Understanding the influence of a static picture book versus an animated and audio guided eBook can prove valuable in developing learning media and other forms of content. In this research we take a published children's book and apply the content into a multimedia eBook. The purpose of the creation of the eBook is to compare the interest of a reader on a story when static format, when some multimedia is added and when the story is …

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High Performance Distributed File System Based On Blockchain, Ajinkya Rajguru Jan 2023

High Performance Distributed File System Based On Blockchain, Ajinkya Rajguru

Master's Projects

Distributed filesystem architectures use commodity hardware to store data on a large scale with maximum consistency and availability. Blockchain makes it possible to store information that can never be tampered with and incentivizes a traditional decentralized storage system. This project aimed to implement a decentralized filesystem that leverages the blockchain to keep a record of all the transactions on it. A conventional filesystem viz. GFS [1] or HDFS [2] uses designated servers owned by their organization to store the data and are governed by a master service. This project aimed at removing a single point of failure and makes use …

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Federated Learning For Protecting Medical Data Privacy, Abhishek Reddy Punreddy Jan 2023

Federated Learning For Protecting Medical Data Privacy, Abhishek Reddy Punreddy

Master's Projects

Deep learning is one of the most advanced machine learning techniques, and its prominence has increased in recent years. Language processing, predictions in medical research and pattern recognition are few of the numerous fields in which it is widely utilized. Numerous modern medical applications benefit greatly from the implementation of machine learning (ML) models and the disruptive innovations in the entire modern health care system. It is extensively used for constructing accurate and robust statistical models from large volumes of medical data collected from a variety of sources in contemporary healthcare systems [1]. Due to privacy concerns that restrict access …

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Exploration Of Digital Synthesis, Angelo Indre Jan 2023

Exploration Of Digital Synthesis, Angelo Indre

Williams Honors College, Honors Research Projects

“An Exploration of Digital Synthesis” is a comprehensive investigation into the world of digital audio and music production. The paper explores the fundamental concepts of sound synthesis, including MIDI, virtual instruments (VSTs), and the JUCE framework. The central focus of the paper is the implementation of a custom synthesizer, which serves as a case study for the practical application of digital synthesis. The paper addresses the key question of how to create a functioning synthesizer from scratch, providing detailed insights into the programming and design process. Overall, the paper represents a significant contribution to the fields of digital audio and …

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