Topic Recommendation For Github Repositories: How Far Can Extreme Multi-Label Learning Go?,
2023
Singapore Management University
Topic Recommendation For Github Repositories: How Far Can Extreme Multi-Label Learning Go?, Ratnadira Widyasari, Zhipeng Zhao, Thanh Le Cong, Hong Jin Kang, David Lo
Research Collection School Of Computing and Information Systems
GitHub is one of the most popular platforms forversion control and collaboration. In GitHub, developers are ableto assign related topics to their repositories, which is helpfulfor finding similar repositories. The topics that are assigned torepositories are varied and provide salient descriptions of therepository; some topics describe the technology employed in aproject, while others describe functionality of the project, itsgoals, and its features. Topics are part of the metadata of arepository and are useful for the organization and discoverabilityof the repository. However, the number of topics is large andthis makes it challenging to assign a relevant set of topics to arepository. …
The Use Of Artificial Intelligence To Detect Students Sentiments And Emotions In Gross Anatomy Reflections,
2023
Old Dominion University
The Use Of Artificial Intelligence To Detect Students Sentiments And Emotions In Gross Anatomy Reflections, Krzysztof J. Rechowicz, Carrie A. Elzie
VMASC Publications
Students' reflective writings in gross anatomy provide a rich source of complex emotions experienced by learners. However, qualitative approaches to evaluating student writings are resource heavy and timely. To overcome this, natural language processing, a nascent field of artificial intelligence that uses computational techniques for the analysis and synthesis of text, was used to compare health professional students' reflections on the importance of various regions of the body to their own lives and those of the anatomical donor dissected. A total of 1365 anonymous writings (677 about a donor, 688 about self) were collected from 132 students. Binary and trinary …
Proactive Conversational Agents,
2023
Singapore Management University
Proactive Conversational Agents, Lizi Liao, Grace Hui Yang, Chirag Shah
Research Collection School Of Computing and Information Systems
Conversational agents, or commonly known as dialogue systems, have gained escalating popularity in recent years. Their widespread applications support conversational interactions with users and accomplishing various tasks as personal assistants. However, one key weakness in existing conversational agents is that they only learn to passively answer user queries via training on pre-collected and manually-labeled data. Such passiveness makes the interaction modeling and system-building process relatively easier, but it largely hinders the possibility of being human-like hence lowering the user engagement level. In this tutorial, we introduce and discuss methods to equip conversational agents with the ability to interact with end …
Automated Registration Of Titanium Metal Imaging Of Aircraft Components Using Deep Learning Techniques,
2023
Air Force Institute of Technology
Automated Registration Of Titanium Metal Imaging Of Aircraft Components Using Deep Learning Techniques, Nathan A. Johnston
Theses and Dissertations
Studies have shown a connection between early catastrophic engine failures with microtexture regions (MTRs) of a specific size and orientation on the titanium metal engine components. The MTRs can be identified through the use of Electron Backscatter Diffraction (EBSD) however doing so is costly and requires destruction of the metal component being tested. A new methodology of characterizing MTRs is needed to properly evaluate the reliability of engine components on live aircraft. The Air Force Research Lab Materials Directorate (AFRL/RX) proposed a solution of supplementing EBSD with two non-destructive modalities, Eddy Current Testing (ECT) and Scanning Acoustic Microscopy (SAM). Doing …
Strategic Action Execution Through Regret Matching In Press Diplomacy,
2023
Air Force Institute of Technology
Strategic Action Execution Through Regret Matching In Press Diplomacy, Leif D. White
Theses and Dissertations
To take most advantage of collaboration, negotiation is paramount to succeed in press Diplomacy. Humans use this construct to work towards self victory or sometimes towards an alternative strategic objective undefined in the game’s rules. To emulate this behavior, this thesis examines how to use communication to enable the victory or defeat of any other player in the game. This research develops a press Diplomacy agent, Lyre, that can work to attain these specific objectives in Diplomacy through the regret matching algorithm (RM). We also study how Lyre can begin Diplomacy with the goal to win, then shift strategies to …
Learning And Understanding User Interface Semantics From Heterogeneous Networks With Multimodal And Positional Attributes,
2023
Singapore Management University
Learning And Understanding User Interface Semantics From Heterogeneous Networks With Multimodal And Positional Attributes, Meng Kiat Gary Ang, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
User interfaces (UI) of desktop, web, and mobile applications involve a hierarchy of objects (e.g., applications, screens, view class, and other types of design objects) with multimodal (e.g., textual and visual) and positional (e.g., spatial location, sequence order, and hierarchy level) attributes. We can therefore represent a set of application UIs as a heterogeneous network with multimodal and positional attributes. Such a network not only represents how users understand the visual layout of UIs but also influences how users would interact with applications through these UIs. To model the UI semantics well for different UI annotation, search, and evaluation tasks, …
The Vehicle Routing Problem With Simultaneous Pickup And Delivery And Occasional Drivers,
2023
Singapore Management University
The Vehicle Routing Problem With Simultaneous Pickup And Delivery And Occasional Drivers, Vincent F. Yu, Grace Aloina, Panca Jodiawan, Aldy Gunawan, Tsung-C. Huang
Research Collection School Of Computing and Information Systems
This research addresses the Vehicle Routing Problem with Simultaneous Pickup and Delivery and Occasional Drivers (VRPSPDOD), which is inspired from the importance of addressing product returns and the emerging notion of involving available crowds to perform pickup and delivery activities in exchange for some compensation. At the depot, a set of regular vehicles is available to deliver and/or pick up customers’ goods. A set of occasional drivers, each defined by their origin, destination, and flexibility, is also able to help serve the customers. The objective of VRPSPDOD is to minimize the total traveling cost of operating regular vehicles and total …
Modeling Daily Fantasy Basketball,
2023
California Polytechnic State University, San Luis Obispo
Modeling Daily Fantasy Basketball, Martin Jiang
Master's Theses
Daily fantasy basketball presents interesting problems to researchers due to the extensive amounts of data that needs to be explored when trying to predict player performance. A large amount of this data can be noisy due to the variance within the sport of basketball. Because of this, a high degree of skill is required to consistently win in daily fantasy basketball contests. On any given day, users are challenged to predict how players will perform and create a lineup of the eight best players under fixed salary and positional requirements. In this thesis, we present a tool to assist daily …
A Review On Learning To Solve Combinatorial Optimisation Problems In Manufacturing,
2023
Singapore Management University
A Review On Learning To Solve Combinatorial Optimisation Problems In Manufacturing, Cong Zhang, Yaoxin Wu, Yining Ma, Wen Song, Zhang Le, Zhiguang Cao, Jie Zhang
Research Collection School Of Computing and Information Systems
An efficient manufacturing system is key to maintaining a healthy economy today. With the rapid development of science and technology and the progress of human society, the modern manufacturing system is becoming increasingly complex, posing new challenges to both academia and industry. Ever since the beginning of industrialisation, leaps in manufacturing technology have always accompanied technological breakthroughs from other fields, for example, mechanics, physics, and computational science. Recently, machine learning (ML) technology, one of the crucial subjects of artificial intelligence, has made remarkable progress in many areas. This study thoroughly reviews how ML, specifically deep (reinforcement) learning, motivates new ideas …
Of Inventorship And Patent Ownership: Examining The Intersection Between Artificial Intelligence And Patent Law,
2023
Singapore Management University
Of Inventorship And Patent Ownership: Examining The Intersection Between Artificial Intelligence And Patent Law, Cheng Lim Saw, Zheng Wen Samuel Chan
Research Collection Yong Pung How School Of Law
Artificial intelligence (“AI”) has garnered much attention in recent years, with capabilities spanning the operation of self-driving cars to the emulation of the great artistic masters of old. The field has now been ostensibly enlarged in light of the professed abilities of AI machines to autonomously generate patentable inventions. This article examines the present state of AI technology and the suitability of existing patent law frameworks in accommodating it. Looking ahead, the authors also offer two recommendations in a bid to anticipate and resolve the challenges that future developments in AI technology might pose to patent law. In particular, the …
Prudex-Compass: Towards Systematic Evaluation Of Reinforcement Learning In Financial Markets,
2023
Singapore Management University
Prudex-Compass: Towards Systematic Evaluation Of Reinforcement Learning In Financial Markets, Shuo Sun, Molei Qin, Xinrun Wang, Bo An
Research Collection School Of Computing and Information Systems
The financial markets, which involve more than $90 trillion market capitals, attract the attention of innumerable investors around the world. Recently, reinforcement learning in financial markets (FinRL) has emerged as a promising direction to train agents for making profitable investment decisions. However, the evaluation of most FinRL methods only focuses on profit-related measures and ignores many critical axes, which are far from satisfactory for financial practitioners to deploy these methods into real-world financial markets. Therefore, we introduce PRUDEX-Compass, which has 6 axes, i.e., Profitability, Risk-control, Universality, Diversity, rEliability, and eXplainability, with a total of 17 measures for a systematic evaluation. …
Hybrid Modeling For Electrochemical Systems,
2023
Louisiana State University and Agricultural and Mechanical College
Hybrid Modeling For Electrochemical Systems, Luis Alejandro Briceno-Mena
LSU Doctoral Dissertations
The discovery of new materials like catalysts, polymeric films, and biomolecules, is driven by industrial needs such as improving reaction or separation selectivity, enhancing therapeutic effects on medical treatments, or reducing costs of replacement. However, deployment of these advances in industrial applications is often hindered by the lack of models needed for design and optimization. Due to the novelty of materials and devices, experimental data and first principles' knowledge are scarce, making it hard to build models either via data-driven or knowledge based approaches. In this context, a way to efficiently combine domain knowledge with data could provide a pathway …
Wifi-Based Human Activity Recognition Using Attention-Based Bilstm,
2023
TU Dublin
Wifi-Based Human Activity Recognition Using Attention-Based Bilstm, Amany Elkelany, Robert J. Ross, Susan Mckeever
Conference papers
Recently, significant efforts have been made to explore human activity recognition (HAR) techniques that use information gathered by existing indoor wireless infrastructures through WiFi signals without demanding the monitored subject to carry a dedicated device. The key intuition is that different activities introduce different multi-paths in WiFi signals and generate different patterns in the time series of channel state information (CSI). In this paper, we propose and evaluate a full pipeline for a CSI-based human activity recognition framework for 12 activities in three different spatial environments using two deep learning models: ABiLSTM and CNN-ABiLSTM. Evaluation experiments have demonstrated that the …
Generative Ai As A Tool For Environmental Health Research Translation.,
2023
University of Louisville
Generative Ai As A Tool For Environmental Health Research Translation., Lauren B. Anderson, Dhiraj Kanneganti, Mary Bentley Houk, Rochelle H. Holm, Ted Smith
Faculty and Staff Scholarship
One valuable application for generative artificial intelligence (AI) is summarizing research studies for non-academic readers. We submitted five articles to Chat Generative Pre-trained Transformer (ChatGPT) for summarization, and asked the article's author to rate the summaries. Higher ratings were assigned to more insight-oriented activities, such as the production of eighth-grade reading level summaries, and summaries highlighting the most important findings and real-world applications. The general summary request was rated lower. For the field of environmental health science, no-cost AI technology such as ChatGPT holds the promise to improve research translation, but it must continue to be improved (or improve itself) …
Comparing Boys’ And Girls’ Attitudes Toward Computer Science,
2023
University of California, Irvine
Comparing Boys’ And Girls’ Attitudes Toward Computer Science, Danielle Scott, Amiee Zou, Sharin Rawhiya Jacob, Debra Richardson, Mark Warschauer
Journal of Computer Science Integration
Women are severely underrepresented in computer science (CS) degrees and careers. While student interest is a key predictor of success, little is known about how elementary students from underserved groups, such as girls, develop their interest in CS. To address this issue, we examined the differences in attitudes between upper elementary girls and boys towards CS after participating in a yearlong, inquiry-based CS curriculum designed for diverse learners. Pre-and-post surveys on students’ attitudes towards CS (n = 108) were delivered before and after student participation in the curriculum. Results from the survey showed only two demonstrated significant differences between boys …
Demand Forecasting Method Of Emergency Materials Based On Metabolic Gray Markov,
2023
1.School of Economics and Management, Xi'an Aeronautical University, Xi'an 710077, China;
Demand Forecasting Method Of Emergency Materials Based On Metabolic Gray Markov, Long Ma, Baodong Qin, Na Lu, Meng Kou
Journal of System Simulation
Abstract: In order to improve the prediction accuracy of the demand for emergency materials of people affected by the disaster, a forecasting method based on metabolism-gray Markov's is proposed. To realize the dynamic prediction of the number of people affected by the disaster, according to demand forecast ideas, the prediction model of metabolism-gray Markov fused is constructed progressively through gray, Markov and metabolism theories. A flexible demand forecasting model for emergency supplies is built through safety stock theory to complete the balance of supply and demand between people number and the materials demand. The prediction results of different …
Se(3)-Based Finite-Time Fault-Tolerant Control Of Spacecraft Integrated Attitude-Orbit,
2023
College of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, China;
Se(3)-Based Finite-Time Fault-Tolerant Control Of Spacecraft Integrated Attitude-Orbit, Yafei Mei, Ying Liao, Kejie Gong, Xingyu Zheng
Journal of System Simulation
Abstract: For relative motion spacecraft, when the actuator fails and the external disturbance and system uncertainty occur simultaneously, a finite-time fault-tolerant control method is proposed on the basis of the robustness of sliding mode control. A single-rigid spacecraft integrated attitude-orbit model is established based on Lie Group SE(3), and the relative motion spacecraft error dynamic equation is derived in exponential coordinates. A class of non-singular fast terminal sliding surface is designed, and the equivalent adaptive method is adopted to design the controller to estimate and compensate the total disturbance. The proposed fault-tolerant control algorithm can be independent from fault diagnosis …
Research On Image Super-Resolution Reconstruction Based On Loss Extraction Feedback Attention Network,
2023
School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China;
Research On Image Super-Resolution Reconstruction Based On Loss Extraction Feedback Attention Network, Hong Sun, Yuxiang Zhang, Yuelan Ling
Journal of System Simulation
Abstract: Since the first application of convolutional neural network to the field of super-resolution image reconstruction (super-resolution convolutional neural network, SRCNN), a large number of studies have proved that deep learning can improve the effect of image reconstruction. Aiming at the too many parameters in the image super-resolution network and the insufficient utilization of image features resulting in less available high-frequency information, a loss extraction feedback attention network (LEFAN) is proposed to reuse parameters in a circular way and increase the reuse of low-resolution image features to capture more high-frequency information. The loss caused in the reconstruction process is extracted …
Research On Cooperative Path Planning Model Of Multiple Unmanned Vehicles In Real Environment,
2023
Academy of Army Armored Force, Beijing 100072, China;
Research On Cooperative Path Planning Model Of Multiple Unmanned Vehicles In Real Environment, Guohui Zhang, Xuan Wang, Yanan Zhang, Ang Gao
Journal of System Simulation
Abstract: The cluster combat application of unmanned ground vehicles(UVS) is a hot research issue of the intersection of artificial intelligence and battle command. Aiming at the cooperative path planning multiple unmanned vehicles not meeting the dynamic threat condition requirement, by combining the global path planning algorithm A-STAR with the local path planning algorithm RL, from the perspective of perception to behavioral decision making, the cooperative path planning model of multiple unmanned vehicles is studied. The cooperative combat situation threat algorithm, state and action space, reward function and sphere of influence function are designed, the sub-models of formation configuration strategy generation …
Dqn-Based Joint Scheduling Method Of Heterogeneous Tt&C Resources,
2023
1.Graduate School, Space Engineering University, Beijing 101416, China;
Dqn-Based Joint Scheduling Method Of Heterogeneous Tt&C Resources, Naiyang Xue, Dan Ding, Yutong Jia, Zhiqiang Wang, Yuan Liu
Journal of System Simulation
Abstract: Joint scheduling of heterogeneous TT&C resources as research object, a deep Q network (DQN) algorithm based on reinforcement learning is proposed. The characteristics of the joint scheduling problem of heterogeneous TT&C resources being fully analyzied and mathematical language being used to describe the constraints affecting the solution, a resource joint scheduling model is established. From the perspective of applying reinforcement learning, two neural networks with the same structure and the action selection strategies based onεgreedy algorithm are respectively designed after Markov decision process description, and DQN solution framework is established. The simulation results show that DQN-based heterogeneous …
