Artificial Intelligence and Robotics Commons^™

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 …

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, 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, 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, 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, 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, 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, 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, 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, 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, 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, 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, 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, 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 …

Sensorless Control Of Pmsm Based On An Improved Super-Twisting Sliding-Mode Observer, Shiyu Chen, Xinmin Chen, Xionglong Hu, Heng Wang, Yepeng Han, Jiajie Chen

Journal of System Simulation

Abstract: To address the chattering in back electromotive force estimation and the gain mismatch across a wide speed range when using a conventional super-twisting sliding-mode observer in the sensorless control system of a permanent-magnet synchronous motor, this paper proposed an improved adaptive-gain super-twisting sliding-mode observer. A linear correction term was introduced into the super-twisting algorithm and integrated with a gain adaptation law based on speed feedback, enabling the system to achieve finite-time convergence and high-precision back electromotive force estimation over a wide speed range. A variable-gain adaptive complex-coefficient filter was constructed to effectively suppress the harmonic components in the observed …

Line Spectrum Enhancement Technology Based On Second-Order Vector Hydrophone, Zhengkai Wang, Yirong Yu, Qing Hu

Journal of System Simulation

Abstract: In view of the problem of limited detection of line spectrum signals in low signal-to-noise ratio underwater environments, a spatial-temporal cooperative line spectrum enhancement technology based on a two-dimensional second-order vector hydrophone was proposed. A receiving signal model of the two-dimensional second-order vector hydrophone was established to clarify the spatial characteristics of its output signals. For spatial signal processing, the signals from each channel of the vector hydrophone were fused to suppress noise, and a channel combination method with high spatial directivity gain was proposed to achieve spatial processing gain. For temporal signal processing, an adaptive line spectrum enhancer …

Dodaf-Opm-Sd Cross-Layer Automated Mapping Method Based On A Unified Semantic Bridge, Lei Cheng, Gang Xiao, Binbin Wang, Siming Peng, Haozhe Liang, Xiangwu Gong

Journal of System Simulation

Abstract: To address the problems of the inability of DoDAF views to directly drive simulations and the insufficient cross-layer semantic alignment and consistency verification, a DoDAF-OPM-SD cross-layer semantic automated/semi-automated mapping and verification method was proposed in this paper. Targeting tactical/operational-level problems dominated by "conservation+feedback+time delay", the proposed method reduced manual mapping under expert adjudication based on a "minimal executable view set". The object-process methodology served as a semantic bridge to map architectural elements into the stock-flow-feedback structures of system dynamics; semantic embedding disambiguation, integer programming harmonization, and K-nearest neighbor parameter completion were integrated; end-to-end traceability was connected through traceability identifiers, …

Design And Implementation Of Hdrt Real-Time Simulation System, Huiji Zheng, Guangsen Wang, Qing Liu, Kang Wang, Zhiwei Wang, Zhenyu Zhang, Shuo Wang, Zhu Liu

Journal of System Simulation

Abstract: In view of the real-time simulation requirements of large-scale complex systems such as power electronics, a hidden dragon real-time(HDRT) simulation system was developed. The strict time constraints of simulation tasks were guaranteed based on a resource-dedicated real-time scheme, supporting fixed-step and multi-rate simulations from the second level to the hundred-nanosecond level. A hybrid CPU-field programmable gate array(FPGA) architecture was adopted to accelerate computation. The system could utilize multiple simulators for parallel simulation and realized microsecond-level real-time data interaction between simulators through a dedicated PCIe switch. A single simulator could be expanded through I/O interface equipment, supporting a maximum input …

Numerical Simulation Of Water Tank Solidification In A Firefighting Aircraft Under High-Altitude Cold-Soak Conditions, Guanmian Liu, Zhihang Cheng, Hejun Qin, Kangzhi Yang, Qing Wen, Kun Gao

Journal of System Simulation

Abstract: A systematic numerical simulation study was conducted to address the issue of internal water tank solidification in firefighting aircraft under high-altitude low-temperature conditions. Based on computational fluid dynamics methods, a solidification-melting model considering fluid-structure interaction heat transfer and phase change processes was adopted. Through reasonable simplification of the complex geometric model, a quasi-three-dimensional computational model suitable for engineering analysis was developed. The influence laws of key parameters, including high-altitude cold-soak temperature, ground initial water temperature, and cold-soak time, on the freezing characteristics of the water tank were investigated. Combining with the parameter influence laws, a safety criterion using the …

Optimization Of Node Deployment For Three-Dimensional Heterogeneous Wsn In Elongated Structural Space, Jiguang Yang, Jiuyuan Huo, Fang Cao, Cong Mu

Journal of System Simulation

Abstract: To achieve effective coverage of key monitoring points in an elongated structural space, a heterogeneous wireless sensor network(HWSN) deployment optimization method combining the virtual force algorithm(VFA) and multi-strategy improved whale optimization algorithm(MSIWOA), namely HVF-MSIWOA, was proposed. A dynamic adaptive weight mechanism and a t-distribution perturbation operator with heterogeneous degrees of freedom were designed, enabling the whale optimization algorithm(WOA) to balance global exploration and local exploitation and jump out of local optima; combining the topological characteristics of the elongated space and node density distribution, an adaptive virtual force distance threshold between heterogeneous nodes was constructed; the mapping relationship between network …

Combat Effectiveness Evaluation Of Anti-Ship Missiles For Intelligent Autonomous Recognition, Long Zhang, Xuanming Feng, Zhen Lei, Bo Yang, Ying Wang

Journal of System Simulation

Abstract: To address the core issues of poor adaptability of static fusion strategies in existing recognition models, as well as the simplistic evaluation system and its disconnection from dynamic confrontation requirements, a practical four-dimensional evaluation system encompassing "recognition accuracy, antijamming stability, decision timeliness, and modal complementarity" was constructed, and an operational effectiveness composite index (OECI) capable of dynamically adapting to tactical scenarios was proposed. A multimodal dynamic attention fusion network (MDA-Net) for anti-ship missiles in complex confrontation environments was designed. Through heterogeneous feature decoupling, dynamic weighting of cross-modal attention, and a hierarchical gating decision mechanism, the autonomous evaluation and adaptive …

Infrared Image Generation Method Based On Improved Cyclegan, Qiqi Jin, Xiang Zhang, Li Gao, Lin Zhang, Junliang Yan, Peiyao Li

Journal of System Simulation

Abstract: To address the problems in current infrared image generation such as insufficient contrast between target and scene, excessively large discrepancies from real scenes, indistinct thermal source features, and great difficulty in constructing measured infrared image datasets, an improved CycleGAN-based infrared image generation method was proposed. By optimizing the network structure of the generator and adding a non-local module and a CBAM convolutional attention mechanism into the generator, the extraction capability of CycleGAN for infrared features was enhanced, enabling the network to capture the subtle features of targets more accurately; a perceptual loss function was introduced to improve the detail …

Counterfactual Explanations For Time Series Classification: From Localized Perturbations To Realistic Generation, Peiyu Li

All Graduate Theses and Dissertations, Fall 2023 to Present

Machine learning models are often used to classify signals collected over time, such as heart rhythms, movement recordings, industrial sensor measurements, and scientific observations. These models can be accurate, but they are often difficult to understand. Users may need to know not only what a model predicted, but also what would have needed to change for the model to reach a different decision.

This dissertation studies counterfactual explanations for time series data. A counterfactual explanation answers a “what-if” question. For example, if a model classifies a signal as one activity instead of another, the explanation shows how the signal would …

Wevit: Weight-Entangled Vision Transformers With Class-Specific Attention For Weakly Supervised Semantic Segmentation, Narges Saeedizadeh, Seyed Mohammad Jafar Jalali, Burhan Khan, Shady Mohamed

Research outputs 2022 to 2026

Weakly Supervised Semantic Segmentation (WSSS) is a challenging task in computer vision, as it relies on limited supervision to generate precise object localization maps, often using Class Activation Maps (CAMs). Traditional methods struggle with balancing localization accuracy and scalability due to their reliance on fixed network architectures and handcrafted strategies. Neural Architecture Search (NAS), despite its proven success in optimizing network designs across tasks, has not yet been explored in WSSS due to the need for efficient weight sharing. To address these limitations, we propose WEViT, a novel framework that integrates NAS with transformers to optimize network architectures and generate …

Cost-Effectiveness Evaluation Of Artificial Intelligence-Assisted Chest Radiograph Interpretation For Tuberculosis Screening In Rural Health Units In The Philippines, Harold Henrison C. Chiu, Bryan Christopher C. Lao, Gloanne C. Adolor

Graduate School of Business Publications

Background: Tuberculosis remains a major public health burden in the Philippines, where diagnostic delays are amplified by limited radiology capacity in rural health units (RHUs) and geographically isolated and disadvantaged areas (GIDAs). Computer-aided diagnosis (CAD) using artificial intelligence (AI)-assisted chest radiograph interpretation may shorten the screening pathway and reduce reliance on scarce specialist readers. However, its economic value for RHUbased tuberculosis screening has not been fully evaluated.
Methods: We developed a decision-tree cost-effectiveness model in Microsoft Excel 365 to compare AI-assisted chest radiograph interpretation with conventional manual radiologist or teleradiology interpretation among a theoretical annual cohort of 1,000 presumptive tuberculosis …

A Simulation Assessment Of The 'Law Of One Price', Caleb Wilkins

Computational and Data Sciences (MS) Theses

The ‘law of one price’ is an appealing notion regarding pricing of tradeable commodities that are priced in different currencies. It states that the prices of the same good in different markets should be equal after adjustment for exchange rates and that equality should persist through exchange rate fluctuations.

My research simulates the market conditions that should precipitate the ‘law of one price.’ Data was obtained from the simulated trade between algorithmic artificial intelligence agents that operated under induced boundedly rational market behaviors. Trade took place in two initially separate markets, a high-price market with a higher equilibrium price and …

Ai-Ready Libraries Require Ai-Ready Librarians: Building Organisational Capability For Digital Transformation, Salihin Mohammed Ali

Research Collection Library

Academic libraries worldwide are rapidly experimenting with artificial intelligence (AI) to enhance research, learning, discovery, operations, and user engagement. However, many institutions continue to approach AI adoption primarily through isolated pilots, individual experimentation, or technology-centric initiatives. While these efforts generate innovation, they often struggle to scale sustainably without corresponding organisational capability development. This presentation argues that AI-ready libraries require AI-ready librarians and proposes an organisational capability approach for sustainable AI transformation in academic libraries. Drawing from the development of a library-wide AI strategy plans at Singapore Management University, the presentation explores how AI capability-building can be operationalised across diverse functional …

Artificial Intelligence (Ai) In Forensic Psychology: An Umbrella Review Of Potentials And Pitfalls, Ysabel Thereze Ang Guevarra, Nur Eva Alisha Binte Mohamed Hisham, Andree Hartanto

Research Collection School of Social Sciences

Artificial intelligence (AI) is becoming increasingly embedded within forensic psychological practice, shaping how criminal risk, legal responsibility and public safety are assessed. AI tools are now used in recidivism prediction, behavioural analysis, deception detection and investigative support, high-stakes domains where errors can have profound consequences. Despite this rapid adoption, the existing literature remains fragmented, with most reviews confined to narrow subdomains and offering limited integrated synthesis of AI′s broader role in forensic psychology. Thus, this umbrella review addresses this gap by synthesising findings from 43 reviews obtained from five major databases, namely EBSCOhost ERIC, EBSCOhost PsycInfo, PubMed, Scopus and Web …

Alfred Russel Wallace Notes 42: How Accurate Are The Transcriptions Presented At The Alfred Russel Wallace Page Website?, Charles H. Smith

Faculty/Staff Personal Papers

A look is taken at the level of accuracy displayed by the transcriptions of Wallace writings offered at the Alfred Russel Wallace Page website, as determined by a ChatGPT analysis.

Sentinel: Evaluating Occlusion-Centered Next-Best-View Selection Using Rgb-Derived Pseudo-Geometry, Paul Nassar

Master's Theses

Three-dimensional cameras provide direct geometric measurements, but their cost, weight, power requirements, and calibration constraints can limit their use in various lightweight or large-scale sensing systems. A potential alternative is to use conventional two-dimensional RGB cameras together with geometric reconstruction models that infer a partial three-dimensional representation from images. This thesis evaluates that possibility for next-best-view (NBV) selection through Sentinel, an occlusion-centered system for static, object-centric scenes with known camera poses and intrinsics. Sentinel converts source RGB observations into pseudo-geometry using monocular depth or point-map predictions, combines those predictions with camera-ray evidence, identifies occluded unknown regions, and selects a candidate …