Demonstrating Superresolution In Radar Range Estimation Using A Denoising Autoencoder,
2026
Chapman University
Demonstrating Superresolution In Radar Range Estimation Using A Denoising Autoencoder, Robert Czupryniak, Abhishek Chakraborty, Andrew N. Jordan, John C. Howell
Mathematics, Physics, and Computer Science Faculty Articles and Research
We apply machine learning methods to demonstrate radar range superresolution using a denoising autoencoder trained without supervision. Focusing on the estimation of a single physical parameter, the separation between two scatterers in the subwavelength regime, we constrain the network to a one-dimensional bottleneck layer with its size matched to the parameter dimensionality. We find that the bottleneck layer forms a reproducible, monotonic mapping with the true separation, showing that the network learns a low-dimensional representation directly aligned with the underlying physical parameter. We further show that this representation preserves the Fisher information of the signal, indicating that the network recovers …
Measuring The Tokenization Premium: A Cost Audit For Underserved Language Communities,
2026
CUNY John Jay College
Measuring The Tokenization Premium: A Cost Audit For Underserved Language Communities, Avijit Roy, Proma Roy, Hrishitva Patel
Publications and Research
Large language models are increasingly deployed as general-purpose educational and technical assistance systems, but their basic infrastructure does not treat languages equally. One underexamined source of disparity is tokenization: semantically equivalent content can require substantially different token counts across languages, affecting API cost, latency, and usable context length before a model is even invoked. We introduce the Tokenization Equity Audit (TEA), a reproducible benchmark for measuring tokenization premiums in technical tutoring content. TEA evaluates three widely used tokenizers, GPT-4o’s o200k base, Qwen2.5-7B, and Mistral-7B, on a 120-item Python debugging corpus translated from English into Bengali, Hindi, Arabic, Tamil, and Yoruba. …
Ai And The Music Industry: Its Current Status And A Speculative Projection Of Its Evolutionary Trajectory,
2026
Bowling Green State University
Ai And The Music Industry: Its Current Status And A Speculative Projection Of Its Evolutionary Trajectory, Rhett D. Morris, Clayton Rosati, Stefan Fritsch
Honors Projects
Music serves as one of society's biggest cultural outlets, allowing millions to share in what used to be a uniquely human form of expression. The commodification of music has built a huge industry full of companies and platforms that have used technology and property laws to shape music's relationship with the public. This study aims to look into the future to see how AI and its implementation could affect the structure of the music industry. To look into the future, this piece establishes two of the most pressing kinds of AI technology for the music industry and looks to contextualize …
Clinical Utility Of An Fda-Authorized Artificial Intelligence Imaging Platform In Interstitial Lung Disease Diagnosis,
2026
Thomas Jefferson University
Clinical Utility Of An Fda-Authorized Artificial Intelligence Imaging Platform In Interstitial Lung Disease Diagnosis, Arjun Prakash Tambe, Ryan Boente, Gautam George, Fayez Kheir, Omid Tahamtani Omran, Kavitha Selvan
Division of Pulmonary, Allergy, and Critical Care Medicine Faculty Papers
Background/Objectives: The diagnosis of interstitial lung disease (ILD) is challenging and frequently delayed. Clinically accessible and minimally invasive diagnostic tools are needed to expedite the diagnosis of ILD while minimizing risk to patients. Fibresolve is an imaging artificial intelligence (AI) tool recently approved by the Food and Drug Administration (FDA) for use in ILD diagnosis and made available to clinicians. The objective of this study was to describe its utility in clinical practice. Methods: We conducted a prospective, observational study of patients across the United States (US) in whom Fibresolve was utilized during routine clinical practice between July 2024 and …
Dynamind: A Dynamic Learned Index For Update-Intensive Workloads,
2026
Edith Cowan University
Dynamind: A Dynamic Learned Index For Update-Intensive Workloads, Jingxian Cheng, Yingfang Wang, Tianqing Zhu, Xu Yang, Ningning Cui, Jianxin Li
Research outputs 2022 to 2026
Learned indexes leverage machine learning models to approximate data distributions and predict key positions, offering better performance than traditional index structures such as B+Trees. As data in real-world applications evolve rapidly, the timely and efficient updating of learned indexes has become an increasingly important research problem, attracting growing attention in recent studies. However, under update-intensive workloads with frequent insertions and deletions, existing learned indexes cannot update the model in a timely manner. Moreover, they ignore the impact of deletions on model accuracy. These limitations lead to degraded prediction accuracy and increased query latency, undermining the core advantage of learned indexes. …
Graph Perturbation Analysis For Subgraph Counting,
2026
Singapore Management University
Graph Perturbation Analysis For Subgraph Counting, Hanhua Xiao, Yuchen Li, Kyriakos Mouratidis
PhD Student’s Publications Collection
Subgraph counting, which involves determining the frequency of a query graph within a data graph, has numerous applications such as query optimization, fraud detection, and evaluating the expressiveness of graph neural networks. Despite its importance, there has been no systematic study on the impact of adversarial graph perturbations on subgraph counts. In this work, we examine the kSub problem, which aims to identify k edge additions that maximize the count of a query graph. We prove that kSub is intractable due to its NP-hardness, even for constant approximation. To address this, we relax the problem into a top-k selection, termed …
Llm-As-A-Judge For Software Engineering: Literature Review, Vision, And The Road Ahead,
2026
Singapore Management University
Llm-As-A-Judge For Software Engineering: Literature Review, Vision, And The Road Ahead, Junda He, Jieke Shi, Terry Yue Zhuo, Christoph Treude, Jiamou Sun, Zhenchang Xing, Xiaoning Du, David Lo
Research Collection School Of Computing and Information Systems
The rapid integration of Large Language Models (LLMs) into software engineering (SE) has revolutionized tasks from code generation to program repair, producing a massive volume of software artifacts. This surge in automated creation has exposed a critical bottleneck: the lack of scalable and reliable methods to evaluate the quality of these outputs. Human evaluation, while effective, is very costly and time-consuming. Traditional automated metrics like BLEU rely on high-quality references and struggle to capture nuanced aspects of software quality, such as readability and usefulness. In response, the LLM-as-a-Judge paradigm, which employs LLMs for automated evaluation, has emerged. This approach leverages …
Leading The Change: Staff-Driven Ai Transformation In Smu Libraries’ Collection Team,
2026
Singapore Management University
Leading The Change: Staff-Driven Ai Transformation In Smu Libraries’ Collection Team, Siew Khim Lim, Fion Goh
Research Collection Library
No abstract provided.
Emergency Risk Dispatch For Integrated Electricity-Heat Systems Under Typhoon Disasters,
2026
College of Electrical Engineering, North China University of Water Resources and Electric Power, Zhengzhou 450045, China
Emergency Risk Dispatch For Integrated Electricity-Heat Systems Under Typhoon Disasters, Tongchui Liu, Lian Tan, Dongxuan Bao, Lanting Zeng, Pengfei Hou, Ronghua Ling
Journal of System Simulation
Abstract: The spatiotemporal randomness of typhoon movement paths leads to uncertain operational risks for integrated electricity-heat systems (IEHS), making it difficult to balance system risk controllability and dispatch economy. To tackle this problem, an emergency risk dispatch (ERD) method for IEHS under typhoon disasters is proposed. An ERD model for IEHS under typhoon disasters is established within the model predictive control framework. Based on the uncertainty of typhoon wind speed prediction, a moment-based ambiguity set for uncertain equipment component failures is constructed, and a distributionally robust chance-constrained ERD model is formulated. An approximation method based on worst-case conditional value-at-risk (WC-CVaR) …
Bi-Level Coordinated Scheduling And Optimization Of Power Systems Based On Stackelberg-Gmo,
2026
China Electric Power Research Institute Co., Ltd., Beijing 100192, China
Bi-Level Coordinated Scheduling And Optimization Of Power Systems Based On Stackelberg-Gmo, Yuanxing Zhang, Jianfeng Li, Taoyong Li, Linjuan Zhang, Jincheng Liu, Bin Li
Journal of System Simulation
Abstract: , To balance the interests of the power grid and the demand side, and achieve coordinated improvements in system economic efficiency, environmental friendliness, and renewable energy accommodation capacity, this paper proposes a bi-level coordinated scheduling model based on the Stackelberg game and the GMO. A leader-follower game model incorporating carbon emission constraints and multi-scenario stochastic constraints for photovoltaic generation is constructed, with the grid operator as the leader and EVs/V2G and energy storage as the followers, resolving the core contradiction between global optimization and individual rationality. The spatio-temporal stochastic characteristics of EV travel, the cycle life of energy storage …
Energy Management Method For Integrated Energy Driven By Users’ Social Attributes,
2026
State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China; Huairou Laboratory, Beijing 101400, China
Energy Management Method For Integrated Energy Driven By Users’ Social Attributes, Yankai Zhu, Yujing Huang, Qinghua Wang, Xiaoning Zhang, Fang Fang, Yuguang Niu
Journal of System Simulation
Abstract: To explore a new interaction mechanism between an energy service provider (ESP) and multiple users, this paper proposes a complex modeling and energy management method for integrated energy systems driven by users' social attributes. A multi-agent interaction framework comprising an ESP and user clusters is established. To maximize the ESP's operational benefit and minimize users' energy costs, a leader-follower game-based energy management model is established within a reinforcement learning framework, and a distributed collaborative solution algorithm combining Q-learning and quadratic programming is proposed. Simulation results show that, compared with the traditional integrated demand response method, consideration of users' social …
Missing-Data-Tolerant Diffusion-Based Wind Power Scenario Forecasting Method,
2026
School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China; State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China
Missing-Data-Tolerant Diffusion-Based Wind Power Scenario Forecasting Method, Yingying Shi, Xiaochong Dong, Guobin Fu, Miaomiao Ma, Yanhe Li, Xuebin Wang
Journal of System Simulation
Abstract: To address the issue of error accumulation in traditional "imputation-then-forecasting" approaches, a missing data tolerant diffusion framework (MDTDF) is proposed. An XGBoost regression model is employed to map numerical weather prediction data into deterministic power forecasts. The encoder in the denoising network extracts temporal features, which are fused with the deterministic forecasts and fed into the decoder through a cross-attention mechanism to guide the denoising process. A historical constraint mechanism is introduced to directly utilize incomplete historical data and dynamically correct the denoising result at each step through sample gradient updates and noise injection guided by historical information. The …
Optimal Scheduling Of Virtual Power Plants Considering Photothermal Power Stations And Hydrogen Energy Utilization,
2026
School of Information Engineering, Nanchang Hangkong University, Nanchang 330038, China
Optimal Scheduling Of Virtual Power Plants Considering Photothermal Power Stations And Hydrogen Energy Utilization, Yousong Chen, Ruofa Cheng, Yi Liu, Yi Zhang, Zhihao Zuo
Journal of System Simulation
Abstract: To enhance the operational stability and low-carbon performance of virtual power plants (VPPs) with high shares of renewable energy, a coordinated dispatch model integrating concentrated solar power (CSP) plants with power-to-gas (P2G) and carbon capture is developed. An optimal VPP scheduling strategy is proposed, combining a stepped carbon trading mechanism with a compensation coefficient and dynamic hydrogen blending. To address multi-source uncertainties in wind power, CSP power, and loads, an envelope boundary model is used for simulation. Information gap decision theory (IGDT) is applied to provide customized solutions for decision-makers with different risk preferences. A bi-objective optimization model is …
Time-Step Relaxation Method For Simulation With Time-Sensitive Interactions,
2026
Institute of War Studies, Academy of Military Sciences, Beijing 100091, China
Time-Step Relaxation Method For Simulation With Time-Sensitive Interactions, Zhaopeng Liu, Kaidi Jin, Xunyun Liu, Dongao Zhou, Xinhai Xu
Journal of System Simulation
Abstract: In time-driven military simulation, time-step setting is a key technology for balancing operational efficiency and simulation accuracy. Based on the current research on time-step setting in military simulation, a trajectory spatiotemporal intersection calculation model is designed to address the performance bottleneck caused by the minimum time step, thus removing the constraints imposed on the minimum time step by interactions such as high-speed target detection and jamming. Experiments involving detection interaction scenarios are designed to verify the effectiveness of the model in preventing missed interactions and improving simulation efficiency.
A Review Of Spatial Indexing Technologies For Large-Scale Combat Simulation,
2026
Institute of War Studies, Academy of Military Sciences, Beijing 100091, China
A Review Of Spatial Indexing Technologies For Large-Scale Combat Simulation, Kaidi Jin, Xunyun Liu, Dongao Zhou, Yang Wang, Zhaopeng Liu
Journal of System Simulation
Abstract: The real-time performance and scalability of large-scale combat simulations are constrained by performance bottlenecks in spatial queries caused by massive numbers of dynamic entities. Spatial indexing technology becomes the key to solving this problem by establishing an efficient mapping between locations and entities. This paper reviews spatial indexing technologies in large-scale combat simulations. Based on an analysis of the core requirements for index structures in combat simulations, various indexing technologies along three main lines are examined: static indexing, dynamic optimization, and distributed parallelism. The principles, evolution, and applicability boundaries of these technologies are also examined, and their query and …
A Method For Assessing The Contribution Degree Of An Aviation Delivery System And Identifying Key Equipment,
2026
School of Aeronautics, Northwestern Polytechnical University, Xi'an 710012, China; National Key Laboratory of Aircraft Configuration Design, Xi'an 710072, China; Key Laboratory of Aircraft System of Systems Contribution and Synthetic Design, Ministry of Industry and Information Technology, Xi'an 710072, China
A Method For Assessing The Contribution Degree Of An Aviation Delivery System And Identifying Key Equipment, Xiaofeng Liu, Chengze Jiang, Xingyu Chen, Deyin Jiang, Bolin Shang, Bifeng Song
Journal of System Simulation
Abstract: Based on the delivery efficiency and delivery quality, a general aviation delivery system effectiveness evaluation model was constructed, and a calculation method of system contribution degree based on efficiency was given. By combining the system calculation experiment and simulation experiment based on agent-based modeling and simulation (ABMS), the design idea of the Monte Carlo simulation experiment for key equipment identification and equipment technology development trend analysis was sorted out, and the key equipment identification method based on ABMS and contribution evaluation was proposed. By taking the intercontinental long-range aviation delivery mission as an example, a variety of simulation experiments …
Fault-Tolerant Control Method For All-Type Actuator Faults Of Evtol Aircraft,
2026
Engineering Techniques Training Center, Civil Aviation University of China, Tianjin 300300, China; College of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, China
Fault-Tolerant Control Method For All-Type Actuator Faults Of Evtol Aircraft, Juan Wang, Guorui Li, Zhiyong Fan, Huijie Chen
Journal of System Simulation
Abstract: To address all-type actuator faults, especially nonlinear distortion issues, in multi-rotor eVTOL aircraft, a novel fault-tolerant control method was proposed. A fault function was established at the rotor speed level, and a fault-tolerant control algorithm combining dynamic robust nonsingular fast integral terminal sliding mode with a high-order finite-time disturbance observer was designed to achieve fault-tolerant control through rotor redundancy allocation. The nonsingular fast integral terminal sliding mode algorithm was improved, and a dynamic system containing actuator faults and their derivatives was constructed via a dynamic surface to achieve system convergence within finite time, avoiding the singularity and chattering problems …
Learning Evolution Modeling Of Multi-Cycle Nested Cloud Manufacturing Service Ecosystem,
2026
School of Information, Xi'an University of Finance and Economics, Xi'an 710100, China; Key Laboratory of Intelligent Finance Collaboration and Trusted Computing, Shaanxi Provincial Institutions of Higher Education, Xi'an 710100, China
Learning Evolution Modeling Of Multi-Cycle Nested Cloud Manufacturing Service Ecosystem, Fang Li, Deyu Zhou, Gang Wang, Guangjun Liu, Qi Hu
Journal of System Simulation
Abstract: In view of the lack of comprehensive consideration of the individual adaptability changes of enterprises caused by the collaborative governance mechanism among multiple manufacturing units and the overall evolution trend of the system in existing learning evolution models, this proposed a learning evolution model of multi-cycle nested cloud manufacturing service ecosystem. At the micro level, the adaptive linkage decision-making among multiple manufacturing units within the enterprise was achieved in the individual layer through the nesting of planning-readiness-execution-assessment (PREA) loops and OODA loops; at the macro level, the closed-loop simulation of the individual layer, organizational layer, and social layer was …
Study On Transient Electric Field Of Insulated Rail Joints In High-Speed Railway Stations Based On Dissado-Hill Model,
2026
School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
Study On Transient Electric Field Of Insulated Rail Joints In High-Speed Railway Stations Based On Dissado-Hill Model, Junli Li, Youpeng Zhang
Journal of System Simulation
Abstract: The transient electric field distribution of insulated rail joints in high-speed railway stations under lightning impulse voltages is critical to their normal operation. Under lightning impulse voltages, considering the relaxation polarization of the insulated rail joint material, a frequency-domain mathematical model of its transient electric field was established. Based on Dissado-Hill model, the measured frequency-domain dielectric spectra were fitted and analyzed to reveal the microstructural characteristics of insulated rail joints and the interaction characteristics between microscopic particles during the polarization process. The results indicate that the relative permittivity of insulated rail joints decreases with the increasing harmonic frequency of …
Intelligent Evaluation Method For Regional Air Superiority Based On Graph Convolutional Neural Network,
2026
Graduate School, National Defense University, Beijing 100091, China
Intelligent Evaluation Method For Regional Air Superiority Based On Graph Convolutional Neural Network, Peng He, Yubo Tang, Jingde Liu, Yujia Tian
Journal of System Simulation
Abstract: To address the dual challenges of the lack of quantification standards and sparse air combat samples in the superiority evaluation of modern air combat, an intelligent evaluation method for regional air superiority based on a graph convolutional neural network was proposed. The spatial grid method was employed to encode the air situation of the entire battlefield airspace into a new data representation, namely the air superiority matrix. A novel air superiority quantification model was applied to quantify the air superiority label values of spatial grids, and four key operational capabilities closely related to air superiority contention were selected as …
