Digital Frontiers In Aesthetics: Applying Dewey's Insights To Generative Ai,
2024
Gettysburg College
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 …
Multi-Aspect Rule-Based Ai: Methods, Taxonomy, Challenges And Directions Towards Automation, Intelligence And Transparent Cybersecurity Modeling For Critical Infrastructures,
2024
Edith Cowan University
Multi-Aspect Rule-Based Ai: Methods, Taxonomy, Challenges And Directions Towards Automation, Intelligence And Transparent Cybersecurity Modeling For Critical Infrastructures, Iqbal H. Sarker, Helge Janicke, Mohamed A. Ferrag, Alsharif Abuadbba
Research outputs 2022 to 2026
Critical infrastructure (CI) typically refers to the essential physical and virtual systems, assets, and services that are vital for the functioning and well-being of a society, economy, or nation. However, the rapid proliferation and dynamism of today's cyber threats in digital environments may disrupt CI functionalities, which would have a debilitating impact on public safety, economic stability, and national security. This has led to much interest in effective cybersecurity solutions regarding automation and intelligent decision-making, where AI-based modeling is potentially significant. In this paper, we take into account “Rule-based AI” rather than other black-box solutions since model transparency, i.e., human …
A Computer Vision Solution To Cross-Cultural Food Image Classification And Nutrition Logging,
2024
Loyola University Chicago
A Computer Vision Solution To Cross-Cultural Food Image Classification And Nutrition Logging, Rohan Sethi, George K. Thiruvathukal
Computer Science: Faculty Publications and Other Works
The US is a culturally and ethnically diverse country, and with this diversity comes a myriad of cuisines and eating habits that expand well beyond that of western culture. Each of these meals have their own good and bad effects when it comes to the nutritional value and its potential impact on human health. Thus, there is a greater need for people to be able to access the nutritional profile of their diverse daily meals and better manage their health. A revolutionary solution to democratize food image classification and nutritional logging is using deep learning to extract that information from …
Shutting Out Noise And Understanding Artificial Intelligence,
2024
University of Michigan Law School
Shutting Out Noise And Understanding Artificial Intelligence, Lauren J. Yu
Michigan Law Review
A review of Noise: A Flaw in Human Judgment. By Daniel Kahneman, Olivier Sibony and Cass R. Sunstein, and You Look Like a Thing and I Love You: How Artificial Intelligence Works and Why It’s Making the World a Weirder Place. By Janelle Shane.
Implementation And Evaluation Of Ai-Based Citizen Question-Answer Recommender (Acqar) To Enhance Citizen Service Delivery In Singapore Public Sector: A Case Study,
2024
Singapore Management University
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 …
Can Organizational Focus On Responsible Ai Lead To Improved Ai Adoption By Employees?,
2024
Singapore Management University
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, …
Integrating Artificial Intelligence For Automated Storytelling In Turn-Based Strategy Games,
2024
Lindenwood University
Integrating Artificial Intelligence For Automated Storytelling In Turn-Based Strategy Games, Timothy Ripper
Theses
This project is inspired by turn-based strategy games, Final Fantasy Tactics, X-Com 2, and modern turn-based strategy games. This project is structured around the use of artificial intelligence for storytelling within strategy games. The focus of this project utilizes artificial intelligence in creating a quest generation system for storytelling. The resulting quest system creates new quests dynamically after communicating with an artificial intelligence allowing players to potentially experience an ever-expanding story from quests
Design, Analysis, And Drop Assembly Of Interlocking Rigid Bodies,
2024
Dartmouth College
Design, Analysis, And Drop Assembly Of Interlocking Rigid Bodies, Amy K. Sniffen
Dartmouth College Ph.D Dissertations
This work presents a system of interlocking blocks that can be used to build a wide variety of structures. The blocks slide together to form structures that interlock geometrically like a puzzle to form semi-permanent structures without the need for cement or friction lock. The blocks are designed to be easy to fabricate, assemble, and disassemble. Contributions of the block designs include a novel interlocking joint structure; the joints are wedge-shaped, allowing for error mitigation during assembly and allowing structures to be assembled without jamming even if there is manufacturing error. We introduce planar, 3D, and volumetric designs using these …
Measuring Jury Perception Of Explainable Machine Learning And Demonstrative Evidence,
2024
University of Nebraska-Lincoln
Measuring Jury Perception Of Explainable Machine Learning And Demonstrative Evidence, Rachel Edie Sparks Rogers
Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–
Subjective pattern comparison has been subject to increased scrutiny by the courts and by the general public, resulting in an increased interest in pattern comparison algorithms that provide quantitative assessments of similarity for use by forensic scientists. While these algorithms would mark an improvement over current subjective comparison methods, individuals without a statistical background may struggle with the statistical concepts and language necessary for describing algorithmic methods. If algorithms are to be used, examiners must be able to testify about their use in a way that is accessible to the jury. In a series of studies, we conduct an assessment …
Testing The Capability Of Ai Art Tools For Urban Design,
2024
Singapore Management University
Testing The Capability Of Ai Art Tools For Urban Design, Connor Phillips, Junfeng Jiao, Emmalee Clubb
Research Collection College of Integrative Studies
This study aimed to evaluate the performance of three artificial intelligence (AI) image synthesis models, Dall-E 2, Stable Diffusion, and Midjourney, in generating urban design imagery based on scene descriptions. A total of 240 images were generated and evaluated by two independent professional evaluators using an adapted sensibleness and specificity average metric. The results showed significant differences between the three AI models, as well as differing scores across urban scenes, suggesting that some projects and design elements may be more challenging for AI art generators to represent visually. Analysis of individual design elements showed high accuracy in common features like …
Research On Word Segmentation Of Ancient Books Based On Domain Large Language Model,
2024
1.Department of Criminal Science and Technology, Jiangsu Police Institute, Nanjing 210031
Research On Word Segmentation Of Ancient Books Based On Domain Large Language Model, Danhao Zhu, Zhao Zhixiao, Na Wu, Xiyu Wang
Journal of Scientific Information Research
[Purpose/significance]In this paper, we take the automatic text segmentation of ancient books as an entry point, introduce the "Xunzi" series of large language models, and explore the performance of large language models on the task of word division of ancient texts. [Method/process]This paper constructs an instruction dataset based on the Zuozhuan, with data cleaning and organisation.on this basis, 1 000 pieces were extracted from it as test data, then 500, 1 000, 2 000, and 5 000 pieces of data were used as training data to fine-tune the instructions and test their performance, respectively. [Result/conclusion]The experimental results show that only …
Sentiment Analysis Of Online Healthy Community Based On Semantic Enhancement,
2024
1.School of Management，Nanjing University of Posts & Telecommunications, Nanjing 210003
2.Jiangsu Provincial Key Laboratory of Data Engineering and Knowledge Service, Nanjing 210023
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,
2024
1.National Science Library, Chinese Academy of Sciences, Beijing 100190
2.Department of Information Resourses Management, School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190
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 …
Exploring The Potential Of Chatgpt In Automated Code Refinement: An Empirical Study,
2024
Singapore Management University
Exploring The Potential Of Chatgpt In Automated Code Refinement: An Empirical Study, Qi Guo, Shangqing Liu, Junming Cao, Xiaohong Li, Xin Peng, Xiaofei Xie, Bihuan Chen
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 …
Development Of An Explainable Artificial Intelligence Model For Asian Vascular Wound Images,
2024
Woodlands Health
Development Of An Explainable Artificial Intelligence Model For Asian Vascular Wound Images, Zhiwen Joseph Lo, Malcolm Han Wen Mak, Shanying Liang, Yam Meng Chan, Cheng Cheng Goh, Tina Peiting Lai, Audrey Hui Min Tan, Patrick Thng, Patrick Thng, Tillman Weyde, Sylvia Smit
Research Collection School Of Computing and Information Systems
Chronic wounds contribute to significant healthcare and economic burden worldwide. Wound assessment remains challenging given its complex and dynamic nature. The use of artificial intelligence (AI) and machine learning methods in wound analysis is promising. Explainable modelling can help its integration and acceptance in healthcare systems. We aim to develop an explainable AI model for analysing vascular wound images among an Asian population. Two thousand nine hundred and fifty-seven wound images from a vascular wound image registry from a tertiary institution in Singapore were utilized. The dataset was split into training, validation and test sets. Wound images were classified into …
Experience Report: Identifying Common Misconceptions And Errors Of Novice Programmers With Chatgpt,
2024
Singapore Management University
Experience Report: Identifying Common Misconceptions And Errors Of Novice Programmers With Chatgpt, Hua Leong Fwa
Research Collection School Of Computing and Information Systems
Identifying the misconceptions of novice programmers is pertinent for informing instructors of the challenges faced by their students in learning computer programming. In the current literature, custom tools, test scripts were developed and, in most cases, manual effort to go through the individual codes were required to identify and categorize the errors latent within the students' code submissions. This entails investment of substantial effort and time from the instructors. In this study, we thus propose the use of ChatGPT in identifying and categorizing the errors. Using prompts that were seeded only with the student's code and the model code solution …
Creative And Correct: Requesting Diverse Code Solutions From Ai,
2024
Monash University
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,
2024
Singapore Management University
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 …
Assessing Ai Detectors In Identifying Ai-Generated Code: Implications For Education,
2024
Singapore Management University
Assessing Ai Detectors In Identifying Ai-Generated Code: Implications For Education, Wei Hung Pan, Ming Jie Chok, Jonathan Leong Shan Wong, Yung Xin Shin, Yeong Shian Poon, Zhou Yang, Chun Yong Chong, David Lo, Mei Kuan Lim
Research Collection School Of Computing and Information Systems
Educators are increasingly concerned about the usage of Large Language Models (LLMs) such as ChatGPT in programming education, particularly regarding the potential exploitation of imperfections in Artificial Intelligence Generated Content (AIGC) Detectors for academic misconduct.In this paper, we present an empirical study where the LLM is examined for its attempts to bypass detection by AIGC Detectors. This is achieved by generating code in response to a given question using different variants. We collected a dataset comprising 5,069 samples, with each sample consisting of a textual description of a coding problem and its corresponding human-written Python solution codes. These samples were …
Filter-Based Stance Network For Rumor Verification,
2024
Singapore Management University
Filter-Based Stance Network For Rumor Verification, Jun Li, Yi Bin, Yunshan Ma, Yang Yang, Zi Huang, Tat‑Seng Chua
Research Collection School Of Computing and Information Systems
Rumor verification on social media aims to identify the truth value of a rumor, which is important to decreasethe detrimental public effects. A rumor might arouse heated discussions and replies, conveying differentstances of users that could be helpful in identifying the rumor. Thus, several works have been proposedto verify a rumor by modelling its entire stance sequence in the time domain. However, these works ignorethat such a stance sequence could be decomposed into controversies with different intensities, which could beused to cluster the stance sequences with the same consensus. In addition, the existing stance extractors fail toconsider both the impact …
