Computer Sciences Commons^™

Optimal Selection And Investment-Allocation Decisions For Sustainable Supplier Development Practices, Chunguang Bai, Kannan Govindan, Dileep G. Dhavale

School of Business

Organization’s sustainability performance is influenced by its suppliers’ sustainability performance. This relationship makes sustainable supplier development a strategic competitive option for a buyer or focal organization. When considering sustainable supplier development practices (SSDPs) adoption, organizations have to balance and consider their limited financial resources and operational constraints. It becomes necessary to both select the best SSDPs set and investment allocation among the selected SSDP set such that the organization can maximize overall sustainability performance level. In this paper, an integrated formal modeling methodology using DEMATEL, the NK model, and multi-objective linear programming model is used support this objective. The proposed …

The Impact Of Government Data Open Platform Construction On Promoting The Development Of Digital Government: An Econometric Analysis Based On Psm Model, Taitian Mao, Tang Gan, Jinliang Chen

Journal of Scientific Information Research

[Purpose/significance]Open government data is the direction of the digital development of government, and exploring the impact of the Open Government Data Platform （OGDP） on the development of digital government is of guiding significance in advancing the goal of modernizing the national governance system and governance capacity. [Method/process]Based on the establishment or not of OGDP, this paper uses the propensity score matching method to investigate the causal relationship between OGDP construction and digital government development by using the cross-sectional data of 101 prefecture-level cities across China in 2019 as the research sample for empirical analysis. [Result/conclusion]Overcoming sample selection bias and eliminating …

Sentiment Analysis Of Online Healthy Community Based On Semantic Enhancement, Pu Han, Ye Dongyu

Journal of Scientific Information Research

[Purpose/significance]In order to make full use of the value of text dependent syntactic information and prior emotion knowledge in emotion analysis， a semantic enhanced online healthy community emotion analysis model was proposed. [Method/process]Firstly， feature vectors for pre-processed online health community data are generated by Word2Vec and BERT; then local and global information of online review text are extracted using TextCNN and BiLSTM respectively based on dual-channel idea; then sentiment knowledge and dependency grammar information are merged in graph attention networks for semantic enhancement; finally， dual-channel features are fused and perform online health community sentiment classification in fully connected layer. [Result/conclusion]The …

Research On The Construction Of Knowledge Graph Of Intangible Cultural Heritage From The Perspective Of Aigc, Yucheng Chen, Li Yang, Jiangfeng Liu, Fan Yang

Journal of Scientific Information Research

[Purpose/significance]Intangible cultural heritage is an important component of human civilization, which is of great significance for protecting and promoting national spirit, enhancing national identity and cohesion. [Method/process]This paper explores how to utilize the advantages of  AIGC, combined with traditional deep learning methods, then construct a comprehensive and efficient map of intangible cultural heritage knowledge. [Result/conclusion]In the classification study of intangible cultural heritage projects, the fine-tuned Baihuan-7B has the best effect, with an macro-F1 value of 0.7688. In the extraction of intangible cultural heritage attribute information, RoBERTa has the best effect, with an F1 value of 0.7085. The …

Digital Frontiers In Aesthetics: Applying Dewey's Insights To Generative Ai, Malcolm F. Lathrop-Allen

Student Publications

The last few years have seen the emergence of ‘artificially intelligent’ systems en masse, which perform tasks which had previously only been possible by human intelligence. Arguably, the impact of ‘AI 2.0’ has been felt most prominently in the art world — artists have panicked as DALL-E, Midjourney, and other image generation algorithms manufacture pieces which previously required weeks of painstaking labor to create. This project seeks to develop a more critical framework for this novel mode of artistic creation and propose better ways of thinking about, using, and “becoming with” artificial intelligence in the domain of artistry. The first …

Tea Shop Manager, Ruben Becerril

Posters - 2024

Tea Shop Manager is meant to be a business simulator game. Business is a subject that is difficult to learn especially as a child who may not understand how the world works yet. Business is all about its application to the real world, as a result the game will:

• Bring aspects of business, simplify it, and then apply it to a semi-realistic setting such as managing a shop.

• Concepts and skills will be taught through the user’s interaction with the game.

• Show statistics based on management performance.

Objective.Gg: Uniting Scholastic Esports, Douglas Beirne

Posters - 2024

Objective.gg is a startup recruitment platform within the scholastic esports scene that seeks to unite esports prospects with collegiate esports programs in an effective manner. Objective.gg seeks to accomplish its mission by operating an online platform that allows prospects and collegiate coaches to create their own profiles and connect with one another, building a community in the process. This platform will begin with a free tier, but additional features will be offered through a subscription-based model with two additional pricing tiers to choose from. The online platform will be supported by free online and paid in-person tournaments for Objective.gg platform …

Atlas, James P . Clark

Posters - 2024

• Problem: Hard for new gym goers to know how to achieve their goals.
• Motivation: I had a hard time figuring out how to achieve the goals I wanted in the gym. A lot of it was just not knowing what to do or how to do it.
• Solution: I want to create an application that will display some basic information, such as maintenance calories and current weight. It will be able to assist with calculations that need to take place to achieve a certain fitness goal.

Delivered Mobile App, Juni Ejere

Posters - 2024

This platform is a mail delivery notification system to assist school mailrooms, specifically the St. Mary’s University mailroom, in notifying users of the mailroom when packages have arrived, creating one location where all mail information can be found and overall improving the efficiency of the mailroom. Students and faculty at St. Mary’s University have access to a mail room to receive packages. This is very useful, especially for those who stay on campus or who want an external location to receive mail. Now that recipients receive an email when a package is delivered, the main concern of picking up a …

Exploring Neural Networks For Developing A Chess Learning Platform With Integrated Ai Agent, Lauren Escobedo

Posters - 2024

Chess is a highly strategic, complex, and long-form game that has been popular for many centuries. Due to the aforementioned complexities of this game, new players often have a hard time learning how to effectively and successfully play. With the recent developments in machine learning algorithms, new opportunities arise to create artificially intelligent tutors - not only for chess, but for all subjects. This project aims to develop a product which investigates the integration of an artificially intelligent “coach”, named Chesster, to train the player, which is trained on a neural network machine learning algorithm.

Nookipedia, Shyann Francis

Posters - 2024

Animal Crossing involves managing around 9000 items within a gameplay environment. This abundance of items makes it difficult for players to effectively track progress and navigate through their possessions. The primary motivation of Nookipedia is to enhance overall gameplay experience by streamlining achievement management, thereby reducing unnecessary interactions with non-playable characters (NPCs) and enabling players to focus more on core game activities. By improving inventory organization and reducing clutter, the aim is to create a smoother and more immersive gaming experience for players.

Parallelized Quadtrees For Image Compression In Cuda And Mpi, Aidan Jones

Senior Honors Theses

Quadtrees are a data structure that lend themselves well to image compression due to their ability to recursively decompose 2-dimensional space. Image compression algorithms that use quadtrees should be simple to parallelize; however, current image compression algorithms that use quadtrees rarely use parallel algorithms. An existing program to compress images using quadtrees was upgraded to use GPU acceleration with CUDA but experienced an average slowdown by a factor of 18 to 42. Another parallelization attempt utilized MPI to process contiguous chunks of an image in parallel and experienced an average speedup by a factor of 1.5 to 3.7 compared to …

Global Challenges In Accessing Mental Health Services And Addressing The Impact Of Alzheimer’S Disease And Depression, Padmapriya Velupillai Meikandan

Master's Theses (2009 -)

This research project focuses on developing a quantum sensing system that can detect biomarkers associated with health disorders, like Alzheimer’s and depression. Our goal is to create a sensitive and highly selective quantum sensing device using a diamond nitrogen vacancy (NV) center. To train and test our quantum machine learning algorithms we will preprocess data from the available Human Connectome Project dataset. This dataset forms the basis of our quantum-based methods. The core of our project revolves around developing quantum machine learning algorithms that utilize techniques such as Support Vector Machines and neural networks to diagnose health disorders using data …

Advanced Machine Learning Approaches For Predicting Mental Health Disorders Following Long Covid Diagnosis, Manoj Purohit

Master's Theses (2009 -)

After the global spread of COVID-19, the enduring effects of Long COVID and its health implications have emerged as a significant global issue, affecting people worldwide. The lingering symptoms post a COVID-19 infection can significantly affect individuals who had previously contracted the virus, exerting considerable influence over their mental well-being. Prolonged recuperation associated with Long COVID has been connected with the emergence of symptoms such as depression and anxiety, all of which can have adverse effects on emotional health. This project delves into an in-depth analysis of healthcare data pertaining to Long COVID from the Froedtert Health (FH) Medical System …

Gradual Memory Safety, Jack Phillips

All NMU Master's Theses

This paper extends the theory of Gradual Types to include memory safe Region-Types and Region-Based Memory Management. It also makes advancements in the capabilities of Region-Based systems. Lastly, it presents the Svejk language and Hasek Type System.

Network Level Detection Of Iot Attacks Via Time Series Shape Mining, Srijani Basu

Masters Theses

This research proposes a method, for detecting intrusions in the Internet of Things (IoT) realm. This approach was specifically tested using datasets containing both benign, and attacks on smart home devices like the Belkin Wemo Power Switch, Lifx Smart Bulb, Amazon Echo, and Netatmo Welcome Camera. These attacks consist of specification-compliant volumetric DDoS attacks, which can be both direct and reflective, with very low traffic volumes implemented in an ON-OFF pattern. Here, the ON-OFF pattern can be referred to as a pulse attack strategy.

We combined non-linear statistical moving averages, and Dynamic Time Warping into a single framework that can …

Enhancing Cybersecurity Awareness In The United Arab Emirates: An Assessment Of Current Practices And The Development Of An Ai-Enhanced Mobile Application, Meera Humaid Alalawi

Theses

In today's interconnected world, individuals, private corporations, public institutions, and governments face increasingly sophisticated cyber threats and attacks, highlighting the critical need for individuals and organizations to understand cybersecurity comprehensively. Cyberattacks have affected many countries and infrastructures in different sectors worldwide, including the United Arab Emirates (UAE), which has become a main target for cybercrime due to its booming economy and tourism. The UAE considers cybersecurity an increasingly critical issue in our digital world, and increasing cybersecurity awareness among residents is essential to protect themselves and their organizations from cyberattacks. The primary objectives of this study are to identify key …

Creative And Correct: Requesting Diverse Code Solutions From Ai, Scott Blyth, Markus Wagner, Christoph Treude

Research Collection School Of Computing and Information Systems

AI foundation models have the capability to produce a wide array of responses to a single prompt, a feature that is highly beneficial in software engineering to generate diverse code solutions. However, this advantage introduces a significant trade-off between diversity and correctness. In software engineering tasks, diversity is key to exploring design spaces and fostering creativity, but the practical value of these solutions is heavily dependent on their correctness. Our study systematically investigates this trade-off using experiments with HumanEval tasks, exploring various parameter settings and prompting strategies. We assess the diversity of code solutions using similarity metrics from the code …

Exploring The Potential Of Chatgpt In Automated Code Refinement: An Empirical Study, Guo Qi, Junming Cao, Xiaofei Xie, Shangqing Liu, Xiaohong Li, Bihuan Chen, Xin Peng

Research Collection School Of Computing and Information Systems

Code review is an essential activity for ensuring the quality and maintainability of software projects. However, it is a time-consuming and often error-prone task that can significantly impact the development process. Recently, ChatGPT, a cutting-edge language model, has demonstrated impressive performance in various natural language processing tasks, suggesting its potential to automate code review processes. However, it is still unclear how well ChatGPT performs in code review tasks. To fill this gap, in this paper, we conduct the first empirical study to understand the capabilities of ChatGPT in code review tasks, specifically focusing on automated code refinement based on given …

Unleashing The Power Of Clippy In Real-World Rust Projects, Chunmiao Li, Yijun Yu, Haitao Wu, Luca Carlig, Shijie Nie, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

The error messages generated by the Rust compiler (rustc) are useful for developers to identify and diagnose suspicious code segments. Complementing the compiler, linters can also play an important role in promoting the adherence to certain coding style conventions and best practices. Prominent linters utilized in the Rust ecosystem include Clippy [1] and Rustfmt [2]. Among them, the Rust community particularly emphasizes on the importance of heeding the warnings provided by Clippy to mitigate common errors and promote the adoption of idiomatic conventions. Clippy provides a set of more than 600 lints in addition to the built-in rustc lints. These …

My Github Sponsors Profile Is Live!": Investigating The Impact Of Twitter/X Mentions On Github Sponsors, Youmei Fan, Tao Xiao, Hideaki Hata, Christoph Treude, Kenichi Matsumoto

Research Collection School Of Computing and Information Systems

GitHub Sponsors was launched in 2019, enabling donations to opensource software developers to provide financial support, as per GitHub’s slogan: “Invest in the projects you depend on”. However, a 2022 study on GitHub Sponsors found that only two-fifths of developers who were seeking sponsorship received a donation. The study found that, other than internal actions (such as offering perks to sponsors), developers had advertised their GitHub Sponsors profiles on social media, such as Twitter (also known as X). Therefore, in this work, we investigate the impact of tweets that contain links to GitHub Sponsors profiles on sponsorship, as well as …

Impact Of Government Outsourcing Contracts On High-Tech Vendors: An Empirical Study, Yi Dong, Nan Hu, Yonghua Ji, Chenkai Ni, Jing Xie

Research Collection School Of Computing and Information Systems

Outsourcing is an important strategic decision of high-tech firms. However, while the research has extensively studied the implications of outsourcing to high-tech clients, its impact on high-tech vendors remains underexplored. This study empirically estimates the impact of government outsourcing contracts on high-tech vendors. Employing the earnings-return analyses framework, we find that, for high-tech vendors engaged in government outsourcing contracts, the stock market places a higher value on each unit of unexpected earnings compared to other firms. Additionally, this impact becomes stronger for contracts with longer terms, for contracts outsourced by the U.S. government or by countries with better political and …

Can Organizational Focus On Responsible Ai Lead To Improved Ai Adoption By Employees?, Seema Chokshi

Dissertations and Theses Collection (Open Access)

The duality inherent in Artificial Intelligence technology entails that while AI has the potential to bring about transformative benefits to organizations, unintended consequences of AI applications could lead to biased and discriminatory outcomes, which could have negative consequences for the organization and society in general. Concerns about such unintended consequences are an impediment to AI adoption where unwilling employees and practitioners often fear ethical breaches, thereby, negatively impacting their engagement with AI driven applications. In response to these concerns various organizations and regulatory bodies have developed governing frameworks broadly known as Responsible AI standards, that set guidelines to design, …

Enabling Sustainable Mining Via Ai-Based Techniques, Nurul Asyikeen Binte Azhar

Dissertations and Theses Collection (Open Access)

The precedence-constrained production scheduling problem (PCPSP) in Long-Term Mine Planning (LTMP) is NP-hard and conventionally prioritizes the Net Present Value (NPV) of profits. Even so, heightened sustainability concerns necessitate heightened sustainable practices. Yet, research still lags. This dissertation addresses this paucity by integrating sustainability elements through Multi-Objective Optimization (MOO), introducing novel algorithms and proposing an uncertainty assessment within a dual Multi-Objective Evolutionary Algorithm (MOEA) setup.

Firstly, our systematic review of past LTMP research focused on the PCPSP and highlighted sustainability elements. Overall, it furnished real-world components incorporated into mathematical formulations, trends, quality of solutions (efficacy) and computation time (efficiency) of …

Sequential Recommendation: From Representation Learning To Reasoning, Lei Wang

Dissertations and Theses Collection (Open Access)

The recommender system is a crucial component of today's online services. It helps users navigate through an overwhelmingly large number of items and discovering those that interest them. Unlike general recommender systems, which recommend items based on the user's overall preferences, sequential recommender systems consider the order of user-item interactions. Sequential recommendations aim to predict the next item a user will interact with, given a sequence of previously interacted items, while considering the short-term and long-term dependencies among items.

In this thesis, we focus on sequential recommendation methods: from representation learning to large language model (LLM)-based reasoning. On the one …

Ct Image Segmentation Using Optimization Techniques Under Neutrosophic Domain, Doaa El-Shahat, Nourhan Talal, Jun Ye, Wen-Hua Cui

Neutrosophic Systems with Applications

In this paper, we introduce a hybrid technique between optimization algorithms and neutrosophic theory. This new hybridization can deal with uncertainties in brain computed tomography (CT) images in three different memberships very effectively. To prove the real-time application of this theory, a new segmentation method for brain CT medical images is presented. The grayscale medical image suffers from uncertainties and inconsistencies in the gray levels due to their bad luminance. The proposed technique addressed this problem by performing neutrosophic operations on gray levels based on the S membership function.

Lyraquist: Language Learning Via Music App, Vivian D'Souza, Siri Avula, Mahi Patel, Tanvi Singh, Ashley Bickham

Senior Theses

Lyraquist is a new language learning mobile app that encourages the practice of a foreign language through music. Language learners can connect their Spotify Premium account to Lyraquist to listen to music in their target languages and utilize tools such as translation and vocabulary lists to facilitate language practice. Through integration with Spotify, users can import and create Spotify playlists and search the service’s entire catalog. By combining daily listening habits with several tasks associated with language learning in one place, Lyraquist hopes to be a useful language learning tool.

Artificial General Intelligence And The Mind-Body Problem: Exploring The Computability Of Simulated Human Intelligence In Light Of The Immaterial Mind, Caleb Parks

Senior Honors Theses

In this thesis I explore whether achieving artificial general intelligence (AGI) through simulating the human brain is theoretically possible. Because of the scientific community’s predominantly physicalist outlook on the mind-body problem, AGI research may be limited by erroneous foundational presuppositions. Arguments from linguistics and mathematics demonstrate that the human intellect is partially immaterial, opening the door for novel analysis of the mind’s simulability. I categorize mind-body problem philosophies in a manner relevant to computer science based upon state transitions, and determine their ramifications on mind-simulation. Finally, I demonstrate how classical architectures cannot resolve so-called Gödel statements, discuss why this inability …

Modeling, Characterization, And Machine Learning Algorithm For Rectangular Choke Horn Antennas, Ibrahim N. Alquaydheb, Saleh A. Alfawaz, Amirreza Ghadimi Avval, Sara Ghayouraneh, Samir M. El-Ghazaly

Electrical Engineering and Computer Science Faculty Publications and Presentations

In this work, we present the design and modeling of a new type of choke horn antenna. It incorporates a rectangular waveguide and a rectangular choke acting as a parasitic element. The four-sided geometry of the antenna is applicable to systems that utilize rectangular waveguides. Also, it can overcome the need for rectangular-to-circular transition of transmission line or mode conversion. The main objective of this paper is to develop a model that calculates the far field radiation characteristics of the proposed antenna (analytical part) and to incorporate a finite element method (FEM) solver that adds to the theoretical solution (empirical …

Implementation And Evaluation Of Ai-Based Citizen Question-Answer Recommender (Acqar) To Enhance Citizen Service Delivery In Singapore Public Sector: A Case Study, Hui Shan Lee

Dissertations and Theses Collection (Open Access)

Government agencies prioritize citizen service delivery to foster trust with the public. Technological advancements, particularly in Artificial Intelligence (AI), hold promise for improving service provision and aligning government operations with citizens' needs. Yet the inherent inflexibility of Service Level Agreements (SLAs) often overlooks the nuances of human emotions and the varied nature of citizen inquiries, exacerbated by a lack of tools to guide appropriate responses. This dissertation aims to address the gaps of overlook of human emotions and non-support for appropriate responses, by exploring the following questions: (1) Can a predictive model incorporating both numeric and textual data effectively forecast …