Digital Commons Network^™

Tweetace: A Fine-Grained Classification Of Disaster Tweets Using Transformer Model, Ademola Adesokan, Sanjay Madria, Long Nguyen

Computer Science Faculty Research & Creative Works

Disaster management teams play a crucial role in responding to catastrophic events with speed and efficiency. However, when faced with large data of disaster-related information, manual systems can struggle to classify the information accurately, especially when they are unavailable. This challenge highlights the need for integrating social media and implementing machine learning models to address the issue. However, the development of such models is dependent on the availability of adequately annotated data, which presents a significant obstacle in the field of crisis management. to address this challenge, our study focuses on the need for disaster event classification through social media. …

Towards A Domain-Agnostic Knowledge Graph-As-A-Service Infrastructure For Active Cyber Defense With Intelligent Agents, Prasad Calyam, Mayank Kejriwal, Praveen Rao, Jianlin Cheng, Weichao Wang, Linquan Bai, V. Sriram Siddhardh Nadendla, Sanjay Kumar Madria, Sajal K. Das, Rohit Chadha, Khaza Anuarul Hoque, Kannappan Palaniappan, Kiran Neupane, Roshan Lal Neupane, Sankeerth Gandhari, Mukesh Singhal, Lotfi Othmane, Meng Yu

Computer Science Faculty Research & Creative Works

Active cyber defense mechanisms are necessary to perform automated, and even autonomous operations using intelligent agents that defend against modern/sophisticated AI-inspired cyber threats (e.g., ransomware, cryptojacking, deep-fakes). These intelligent agents need to rely on deep learning using mature knowledge and should have the ability to apply this knowledge in a situational and timely manner for a given AI-inspired cyber threat. in this paper, we describe a 'domain-Agnostic knowledge graph-As-A-service' infrastructure that can support the ability to create/store domain-specific knowledge graphs for intelligent agent Apps to deploy active cyber defense solutions defending real-world applications impacted by AI-inspired cyber threats. Specifically, we …

Surviving Chatgpt In Healthcare, Zhengliang Liu, Lu Zhang, Zihao Wu, Xiaowei Yu, Chao Cao, Haixing Dai, Ninghao Liu, Jun Liu, Wei Liu, Quanzheng Li, Dinggang Shen, Xiang Li, Dajiang Zhu, Tianming Liu

Computer Science Faculty Research & Creative Works

At the dawn of Artificial General Intelligence (AGI), the emergence of large language models such as ChatGPT show promise in revolutionizing healthcare by improving patient care, expanding medical access, and optimizing clinical processes. However, their integration into healthcare systems requires careful consideration of potential risks, such as inaccurate medical advice, patient privacy violations, the creation of falsified documents or images, overreliance on AGI in medical education, and the perpetuation of biases. It is crucial to implement proper oversight and regulation to address these risks, ensuring the safe and effective incorporation of AGI technologies into healthcare systems. By acknowledging and mitigating …

Dual-View Preference Learning For Adaptive Recommendation, Zhongzhou Liu, Yuan Fang, Min Wu

Research Collection School Of Computing and Information Systems

While recommendation systems have been widely deployed, most existing approaches only capture user preferences in the , i.e., the user's general interest across all kinds of items. However, in real-world scenarios, user preferences could vary with items of different natures, which we call the . Both views are crucial for fully personalized recommendation, where an underpinning macro-view governs a multitude of finer-grained preferences in the micro-view. To model the dual views, in this paper, we propose a novel model called Dual-View Adaptive Recommendation (DVAR). In DVAR, we formulate the micro-view based on item categories, and further integrate it with the …

Need For Affect, Problematic Social Media Use And The Mediating Role Of Fear Of Missing Out In European And Arab Samples, Areej Babiker, Mohamed Basel Almourad, Constantina Panourgia, Sameha Alshakhsi, Christian Montag, Raian Ali

All Works

Purpose: The growing awareness and concern about the excessive use of social media have led to an increasing number of studies investigating the underlying factors contributing to this behavior. In the literature, it is discussed that problematic social media use (PSMU) can impact individuals’ mental health and well-being. Drawing on the Interaction of Person-Affect-Cognition-Execution (I-PACE) model, this study aimed to examine the association between the need for affect (affect approach and affect avoidance) and PSMU (operationalized via the social media disorder scale), as well as the mediating role of fear of missing out (FoMO) in that relation. Participants and Methods: …

Social Media Bot Detection With Deep Learning Methods: A Systematic Review, Kadhim Hayawi, Susmita Saha, Mohammad Mehedy Masud, Sujith Samuel Mathew, Mohammed Kaosar

All Works

Social bots are automated social media accounts governed by software and controlled by humans at the backend. Some bots have good purposes, such as automatically posting information about news and even to provide help during emergencies. Nevertheless, bots have also been used for malicious purposes, such as for posting fake news or rumour spreading or manipulating political campaigns. There are existing mechanisms that allow for detection and removal of malicious bots automatically. However, the bot landscape changes as the bot creators use more sophisticated methods to avoid being detected. Therefore, new mechanisms for discerning between legitimate and bot accounts are …

Bypassing Multiple Security Layers Using Malicious Usb Human Interface Device, Mathew Nicho, Ibrahim Sabry

All Works

The Universal Serial Bus (USB) enabled devices acts as a trusted tool for data interchange, interface, and storage for the computer systems through Human Interface Devices (HID) namely the keyboard, mouse, headphone, storage media and peripherals that use the USB port. However, with billions of USB enabled devices currently in use today, the attacker’s potential to seamlessly leverage this device to perform malicious activities by bypassing security layers presents serious risk to systems administrators. The paper thus presents a comprehensive review of the multiple attacks that can be leveraged using USB devices and the corresponding vulnerabilities including countermeasures. This is …

Comments Of The Cordell Institute On Ai Accountability, Neil M. Richards, Woodrow Hartzog, Jordan Francis

Scholarship@WashULaw

These comments are a response to the National Telecommunications and Information Administration's 2023 request for comment on AI accountability (AI Accountability RFC, NTIA–2023–0005).

Responding to NTIA’s recent inquiry into AI assurance and accountability, we offer two main arguments regarding the importance of substantive legal protections. First, a myopic focus on concepts of transparency, bias mitigation, and ethics (for which procedural compliance efforts such as audits, assessments, and certifications are proxies) is insufficient when it comes to the design and implementation of accountable AI systems. We call rules built around transparency and bias mitigation “AI half-measures,” because they provide the appearance …

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 …

Liquid Tab, Nathan Hulet

Williams Honors College, Honors Research Projects

Guitar transcription is a complex task requiring significant time, skill, and musical knowledge to achieve accurate results. Since most music is recorded and processed digitally, it would seem like many tools to digitally analyze and transcribe the audio would be available. However, the problem of automatic transcription presents many more difficulties than are initially evident. There are multiple ways to play a guitar, many diverse styles of playing, and every guitar sounds different. These problems become even more difficult considering the varying qualities of recordings and levels of background noise.

Machine learning has proven itself to be a flexible tool …

A Different Way To Penetrate Nba Defenses, Trey Trucksis

Williams Honors College, Honors Research Projects

This project proposal will document the design, configuration, and penetration testing of a network consisting of three routers (labeled as Lakers, Celtics, Cavaliers), one switch (labeled as NBA), and three end devices (labeled as Kali, Windows 10, and Ubuntu) each connected to one of three routers present on the network. Each router will be attached to a different subnet on the network. The network will be secured using encrypted passwords on the router interfaces, OSPF MD5 authentication between the routers, port security on the switch, as well as Access Control Lists to to control the privileges of each subnetwork accordingly. …

Development Of Machine Learning Based Approach To Predict Fuel Consumption And Maintenance Cost Of Heavy-Duty Vehicles Using Diesel And Alternative Fuels, Sasanka Katreddi

Graduate Theses, Dissertations, and Problem Reports (ETD)

One of the major contributors of human-made greenhouse gases (GHG) namely carbon dioxide (CO2), methane (CH4), and nitrous oxide (NOX) in the transportation sector and heavy-duty vehicles (HDV) contributing to about 27% of the overall fraction. In addition to the rapid increase in global temperature, airborne pollutants from diesel vehicles also present a risk to human health. Even a small improvement that could potentially drive energy savings to the century-old mature diesel technology could yield a significant impact on minimizing greenhouse gas emissions. With the increasing focus on reducing emissions and operating costs, there is a need for efficient and …

A Longitudinal Study Of Factors That Affect User Interactions With Social Media And Email Spam, Wojciech M. Mazurek

Graduate Theses, Dissertations, and Problem Reports (ETD)

Given the rapid growth of social media and the increasing prevalence of spam, it is crucial to understand users’ interactions with unsolicited content to develop effective countermeasures against spam. This thesis focuses on exploring the factors that influence users’ decisions to interact with spam on social media and email. It builds upon prior work, which serves as a foundation for further research and conducting a longitudinal analysis. Our results are based on the analysis of 221 responses collected through an online survey. The survey not only gathered demographic information such as age, gender, and race but also collected data on …

Multi-Label Text Classification With Transfer Learning, Likhitha Yelamanchili

Master's Projects

Multi-label text categorization is a crucial task in Natural Language Processing, where each text instance can be simultaneously assigned to numerous labels. This project's goal is to assess how well several deep learning models perform on a real-world dataset for multi-label text classification. We employed data augmentation techniques like Synonym Substitution and Random Word Substitution to address the problem of data imbalance. We conducted experiments on a toxic comment classification dataset to evaluate the effectiveness of several deep learning models including Bi-LSTM, GRU, and Bi-GRU, as well as fine- tuned pre-trained BERT models. Many metrics, including log loss, recall@k, and …

Hate Speech Detection In Hindi, Pranjali Prakash Bansod

Master's Projects

Social media is a great place to share one’s thoughts and to express oneself. Very often the same social media platforms become a means for spewing hatred.The large amount of data being shared on these platforms make it difficult to moderate the content shared by users. In a diverse country like India hate is present on social media in all regional languages, making it even more difficult to detect hate because of a lack of enough data to train deep/ machine learning models to make them understand regional languages.This work is our attempt at tackling hate speech in Hindi. We …

Ethical Design Of Computers: From Semiconductors To Iot And Artificial Intelligence, Sudeep Pasricha, Marilyn Wolf

School of Computing: Faculty Publications

Computing systems are tightly integrated today into our professional, social, and private lives. An important consequence of this growing ubiquity of computing is that it can have significant ethical implications of which computing professionals should take account. In most real-world scenarios, it is not immediately obvious how particular technical choices during the design and use of computing systems could be viewed from an ethical perspective. This article provides a perspective on the ethical challenges within semiconductor chip design, IoT applications, and the increasing use of artificial intelligence in the design processes, tools, and hardware-software stacks of these systems.

Adaptive Multiple Distributed Bidirectional Spiral Path Planning For Foraging Robot Swarms, Qi Lu, Ryan Luna

Computer Science Faculty Publications

The Distributed Deterministic Spiral Algorithm (DDSA) has shown great foraging efficiency in robot swarms. However, when the number of robots in the swarm increases, scalability becomes a significant bottleneck due to increased collisions among robots, making it challenging to deploy them in the search space (e.g., 20 robots). To address this issue, we propose an adaptive Multiple-Distributed Bidirectional Spiral Algorithm (MDBSA) that enhances scalability. Our proposed algorithm partitions the squared search arena into multiple identical squared regions and assigns robots to regions dynamically based on the number of regions. In each region, a bidirectional spiral search path is planned, and …

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 …

The Bias Report: An Automated News Aggregator For Political Bias Classification And News Summarization, Anant Joshi

Master's Projects

Political polarization is on the rise in the US, driven in large part by divisive news that goes viral on the Internet. Specifically, many media outlets use slanted language and publish misinformation in order to drive user traffic and engagement. Almost 80% of US citizens get their news from online sources, but there is a lack of public safeguards against biased news. A large amount of news is published online every day by media organizations, and it is impossible to manually analyze this amount of data. There is a clear need for automated, public-facing solutions in the current political climate …

Enhancing The Security Of Yioop Discussion Board, Prajna Gururaj Puranik

Master's Projects

Yioop is an open-source web portal that serves as a search engine and a discussion board, enabling users to create, join, and share content within groups. Data security is a critical concern for Yioop, as it involves storing and accessing user-generated data and generating statistical data. Yioop has an existing security mechanism in place, but continuous enhancements are needed to protect against potential vulnerabilities and cyber threats.

This project aims to strengthen the security of Yioop by implementing additional security measures that build upon the existing security mechanism. To prevent statistical attacks, this project extends differential privacy to mask the …

Static Taint Analysis Via Type-Checking In Typescript, Abhijn Chadalawada

Master's Projects

With the widespread use of web applications across the globe, and the ad- vancements in web technologies in recent years, these applications have grown more ubiquitous and sophisticated than ever before. Modern web applications face the constant threat of numerous web security risks given their presence on the internet and the massive influx of data from external sources. This paper presents a novel method for analyzing taint through type-checking and applies it to web applications in the context of preventing online security threats. The taint analysis technique is implemented in TypeScript using its built-in type-checking features, and then integrated into …

Face Anti-Spoofing And Deep Learning Based Unsupervised Image Recognition Systems, Enoch Solomon

Theses and Dissertations

One of the main problems of a supervised deep learning approach is that it requires large amounts of labeled training data, which are not always easily available. This PhD dissertation addresses the above-mentioned problem by using a novel unsupervised deep learning face verification system called UFace, that does not require labeled training data as it automatically, in an unsupervised way, generates training data from even a relatively small size of data. The method starts by selecting, in unsupervised way, k-most similar and k-most dissimilar images for a given face image. Moreover, this PhD dissertation proposes a new loss function to …

Network Intrusion Detection With Two-Phased Hybrid Ensemble Learning And Automatic Feature Selection, Asanka Kavinda Mananayaka, Sunnie S. Chung

Electrical and Computer Engineering Faculty Publications

The use of network connected devices has grown exponentially in recent years revolutionizing our daily lives. However, it has also attracted the attention of cybercriminals making the attacks targeted towards these devices increase not only in numbers but also in sophistication. To detect such attacks, a Network Intrusion Detection System (NIDS) has become a vital component in network applications. However, network devices produce large scale high-dimensional data which makes it difficult to accurately detect various known and unknown attacks. Moreover, the complex nature of network data makes the feature selection process of a NIDS a challenging task. In this study, …

Visualizing Dynamic Multivariate Networks, Bharat Kumar Kale

Graduate Research Theses & Dissertations

Many real-world networks are multivariate in nature and also evolve over time. Such a network whose nodes and/or edges along with their associated attributes, evolve over time is called A dynamic multivariate network (DMVN). For instance, in the scholarly community, researchers often collaborate with others. These collaborations have various attributes, such as scientific domain and number of publications, as well as they change over time. At any given point in time, the collaborations among researchers can be modeled as a network resulting in a collaboration network. When the changes in collaborations and associated attributes are also included in the network, …

Analysis Of The Effect Of Surface Roughness In Additive Manufacturing On Thermo-Hydraulic Performance By Ml Models Supported By Physics-Based Modeling, Kaylen A. Platt

Graduate Research Theses & Dissertations

Heat exchangers (HX) are crucial components of thermal control systems which facilitate proper transfer of heat in systems such as nuclear reactors. This research focuses on the heat transfer-enhancing effect associated with turbulence in fluid flowing conduits. Turbulence can be induced at low flow rates when surface roughness is present on channel walls. Rough surfaces are typically regarded as a flawed product of the Additive Manufacturing (AM) process during the construction of Heat Exchangers. Machining surface finishes onto AM parts is a typical post-processing method used to remove the roughness. Thorough investigations have not yet been published on the effects …

A Class Of Regression Models For Pairwise Comparisons Of Forensic Handwriting Comparison Systems, Cami M. Fuglsby

Electronic Theses and Dissertations

Handwriting analysis is a complex field largely living in forensic science and the legal realm. One task of a forensic document examiner (FDE) may be to determine the writer(s) of handwritten documents. Automated identification systems (AIS) were built to aid FDEs in their examinations. Part of the uses of these AIS (such as FISH[5] [7],WANDA [6], CEDAR-FOX [17], and FLASHID®2) are tomeasure features about a handwriting sample and to provide the user with a numeric value of the evidence. These systems use their own algorithms and definitions of features to quantify the writing and can be considered a black-box. The …

Strategies For Proper Security Practices In Small Financial Institutions, Adam Leffell

Walden Dissertations and Doctoral Studies

Financial institutions remain high targets for threat actors because of potentially lucrativefinancial gains from security breaches. Information technology (IT) security professionals in financial institutions are concerned about weak security strategies that could lead to security breaches. Grounded in the technology acceptance model (TAM), the purpose of this qualitative multiple case study was to explore strategies IT security professionals use to implement proper security practices to prevent security breaches. The participants were three IT security professionals from three different financial institutions that oversee the implementation of security policies and procedures. Data collection involved conducting semi-structured interviews and public documents. Through thematic …

Relationship Between Strategic Dexterity, Absorptive Capacity, And Competitive Advantage, Ifechide Monyei

Walden Dissertations and Doctoral Studies

Small- and medium-sized enterprise (SME) manufacturing executives and managers are concerned with the rapid technological changes involving artificial intelligence (AI), machine learning, and big data. To compete in the global landscape, effectively managing digital and artificial intelligence changes among SME manufacturing executives and managers is critical for leaders to compete in 2023 and beyond. Grounded in the dynamic capabilities view theory, the purpose of this quantitative correlation study was to examine the relationship between strategic dexterity, absorptive capacity, and competitive advantage. The participants were 66 executives and managers of SME manufacturing organizations who use big data and analytics daily and …

Perceptions And Knowledge Of Information Security Policy Compliance In Organizational Personnel, Jesus M. Mosqueda

Walden Dissertations and Doctoral Studies

All internet connected organizations are becoming increasingly vulnerable to cyberattacks due to information security policy noncompliance of personnel. The problem is important to information technology (IT) firms, organizations with IT integration, and any consumer who has shared personal information online, because noncompliance is the single greatest threat to cybersecurity, which leads to expensive breaches that put private information in danger. Grounded in the protection motivation theory, the purpose of this quantitative study was to use multiple regression analysis to examine the relationship between perceived importance, organizational compliance, management involvement, seeking guidance, and rate of cybersecurity attack. The research question for …

Knowledge-Sharing Practice As A Tool In Organizational Development In Nigerian Higher Educational Institutions, Emmanuel Ajiri Ojo

Walden Dissertations and Doctoral Studies

AbstractUnderstanding knowledge management is key to understanding organizational development and innovations. Inadequate knowledge-sharing practices in Nigerian educational institutions has impeded innovation and management development. The purpose of this qualitative modified Delphi study was to seek consensus among administrators from Nigerian educational institutions and scholars from Nigerian universities regarding knowledge-sharing practices that nourish innovation in Nigerian higher educational institutions. The organizational development framework was used to guide the study. Data collection included a nonprobability purposive sampling of 25 participants and three rounds of surveys administered online. A consensus was reached on eight factors after coding and thematic analysis: setting knowledge-sharing expectations, …