Visual Pattern Mining With Similarity Metrics For Model-Free Trading In The Korean Futures Market,
2026
Missouri University of Science and Technology
Visual Pattern Mining With Similarity Metrics For Model-Free Trading In The Korean Futures Market, Juhyeon Jang, Jaeyun Kim, David Enke
Engineering Management and Systems Engineering Faculty Research & Creative Works
The fractal market hypothesis highlights multi-scale dynamics in financial time series and provides a theoretical foundation for pattern-based analysis. This study proposes a model-free visual pattern mining framework that transforms high-frequency market data into image representations to support intelligent decision-making. By converting 1-minute KOSPI200 futures data into candlestick chart and Bollinger band images, the method effectively captures structural patterns and volatility dynamics. The framework applies similarity metrics and Intersection over Union (IoU)-based visual comparison to identify historically similar patterns and generate intelligent trading signals without model training or complex parameter tuning. Experimental results demonstrate that combining visual features of candlestick …
Artificial Intelligence In Human Spaceflight Safety-Critical Systems: A Requirements Framework For Ai-Enabled Computer-Based Control Systems,
2026
Embry-Riddle Aeronautical University
Artificial Intelligence In Human Spaceflight Safety-Critical Systems: A Requirements Framework For Ai-Enabled Computer-Based Control Systems, Liz Bosch
Doctoral Dissertations and Master's Theses
Currently, there is no governing standard that addresses the safe integration of AI into computer-based control systems (CBCS) in human spaceflight. The computer-based control expectations of those safety-critical systems on the International Space Station (ISS) are captured in SSP 50038, Computer-Based Control System Safety Requirements, with one caveat: the standard was not designed with AI applications in mind. SSP 50038 does not cover the probabilistic behavior, opacity, and training-data dependency of modern AI/ML systems. The objectives of this work is to develop an AI taxonomy relevant to safety characteristics (determinism, transparency, data dependency, failure predictability), systematically map AI characteristics against …
Demonstrating Sysml V2’S Utility With Syside And Syson For Systems Modeling,
2026
Embry-Riddle Aeronautical University
Demonstrating Sysml V2’S Utility With Syside And Syson For Systems Modeling, Quinn Galen
Student Research Symposium (SRS)
This study highlights the practical utility of SysML v2’s kernel language, a formal, text based foundation for consistent, cross tool model definitions, in Model Based Systems Engineering (MBSE), using Air Traffic Management (ATM) as an illustrative example. SysIDE, an open source textual editor, enables rapid model creation with the kernel’s concise syntax, allowing users to define system components and behaviors (e.g., ATM radar or flight path interactions) with real time validation. SysON, a web based graphical tool, complements this by facilitating collaborative visualization of system architectures. Using ATM as an example case, we can showcase how the kernel language enhances …
Ai-Scm Cmm: A Capability Maturity Model For Artificial Intelligence Integration In Supply Chain Management,
2026
Dakota State University
Ai-Scm Cmm: A Capability Maturity Model For Artificial Intelligence Integration In Supply Chain Management, Lordt Becklines, Omar F. El-Gayar, Patti Brooks, Insu Park
Annual Research Symposium
Artificial intelligence is increasingly deployed in supply chain management, yet many organizations struggle to align adoption efforts with process readiness, data quality, governance, and workforce capabilities, and they still lack validated supply chain specific roadmap for assessing readiness, sequencing investments, and reducing implementation risk. This study develops and evaluates a Capability Maturity Model for Artificial Intelligence Integration in Supply Chain Management to address that gap. Using a design science research approach, the study synthesizes prior literature and practitioner knowledge to define maturity dimensions, capability indicators, and staged progression levels for AI integration in supply chain contexts. The artifact and assessment …
A Causal Inference Methodology For Root-Cause Diagnosis In Nonstationary Industrial Time Series,
2026
Old Dominion University
A Causal Inference Methodology For Root-Cause Diagnosis In Nonstationary Industrial Time Series, Cansu Yalim
Knowledge and Creativity Expo
Industrial fault diagnosis lacks a procedure that learns time-varying causal structure from observational time series, makes identifiability limits explicit, and uses intervention-based reasoning to support root-cause assessment under industrial constraints. Although predictive maintenance can reduce downtime, diagnosis is often expert-rule-based or association-driven; pipelines may elevate downstream symptoms alongside true drivers and provide limited guidance on which feasible action would change a fault trajectory under current operating conditions. Because operating phases and fault progression create regime shifts, industrial systems rarely follow a single stable mechanism. This study develops and evaluates a three-stage, regime-aware causal diagnostic protocol based on a time-varying Dynamic …
Optimizing Warranty Policies For Remanufactured Products: When Should They Be Longer, Shorter, Or Identical To New Product Warranties?,
2026
Air Force Institute of Technology
Optimizing Warranty Policies For Remanufactured Products: When Should They Be Longer, Shorter, Or Identical To New Product Warranties?, Kunpeng Li, Jun-Yeon Lee
Faculty Publications
Manufacturers adopt different warranty strategies for remanufactured products, offering shorter, identical, or longer warranty periods compared to new products. However, prior research has only focused on manufacturers offering either shorter or identical warranties. In addition, the existing literature has not captured the diminishing returns of warranties, i.e., as the warranty coverage increases, its incremental benefits begin to decrease but the costs continue to increase. To address these gaps, we develop an optimization model that jointly considers pricing and warranty decisions while accounting for warranty’s diminishing effect on consumer’s willingness to pay for remanufactured products. We show that all three observed …
Analogy2kg: An Automatic Pipeline For Deriving Knowledge Graphs From Long-Text Analogies,
2026
Sensors Directorate, Air Force Research Laboratory
Analogy2kg: An Automatic Pipeline For Deriving Knowledge Graphs From Long-Text Analogies, Kara Combs, Lance E. Champagne, Bruce A. Cox, Christine M. Schubert Kabban, Trevor Bihl, Grace Lemming
Faculty Publications
Analogical reasoning is an increasingly popular, lightweight solution to enable large language model (LLM)-level reasoning without computational complexity. Still, it has yet to be adopted due to its reliance on strictly hand-formatted data. Therefore, we propose Analogy2KG (“Analogy to Knowledge Graph”), as an automatic pipeline that transforms text into a KG format via a fine-tuned version of information extraction (IE) algorithms for long-text analogies. The need to verify that the complex underlying analogical structure of the data is maintained was done via paired samples tests in the creation and validation of this pipeline. Graph density was used to evaluate the …
Multi-Objective Optimization Of Waste Incineration For Minimal Carbon Monoxide And Sulfur Dioxide Emission And Rate Maximization: A Case Study Of Mbezi, Mkuranga-Pwani, Tanzania,
2026
Department of Mechanical and Industrial Engineering, College of Engineering and Technology, University of Dar es Salaam, Dar es Salaam, Tanzania, P. O. Box 35131 Dar es Salaam, Tanzania
Multi-Objective Optimization Of Waste Incineration For Minimal Carbon Monoxide And Sulfur Dioxide Emission And Rate Maximization: A Case Study Of Mbezi, Mkuranga-Pwani, Tanzania, Grangay M. Nyanghura, Enock W. Nshama
Tanzania Journal of Science
Incineration is widely employed for hazardous waste disposal, but results in harmful flue gas emissions. This study optimizes a double-chamber incineration process to reduce sulfur dioxide (SO2) and carbon monoxide (CO) emissions while maximizing the incineration rate. The effects of waste mass, primary chamber temperature (PT), and secondary chamber temperature (ST) were analyzed using a full factorial design of 27 experiments. ANOVA revealed that mass had the greatest impact on emissions and incineration time, ST had a moderate effect, and PT had little influence. Regression analysis provided models for incineration time, CO, and SO2 emissions. Single-objective optimization using sequential quadratic …
Design And Verification Of Manned-Unmanned Collaborative Combat Capability System Based On Mbse,
2026
Shenyang Aircraft Design and Research Institute, Shenyang 110066, China
Design And Verification Of Manned-Unmanned Collaborative Combat Capability System Based On Mbse, Fangbo Wang, Jian Guo, Chenglie Du, Yifan Liu, Pengpeng Zhang
Journal of System Simulation
Abstract: The traditional model-based systems engineering (MBSE) method has problems of failing to fully exhibit complex combat logics in manned-unmanned collaborative combat system modeling, neglecting the scenario constraints in interface modeling, and requiring long-term and costly algorithm verification. In order to solve the problems, a methodology and design tool based on MBSE was proposed. An integrated verification method of a system's operational logic, interface design, and algorithmic design was constructed, thus providing a digital and rapidly iterative verification approach for system simulation. A verification environment for multiple key algorithm simulations was established, effectively reducing the economic cost of building verification …
Review Of 3d Human Reconstruction Methods Empowering Vr/Ar,
2026
School of Informatics, Xiamen University, Xiamen 361102, China
Review Of 3d Human Reconstruction Methods Empowering Vr/Ar, Lisha Zhang, Yuchi Huo, Qi Ye, Anjun Chen, Shihui Guo, Jiming Chen
Journal of System Simulation
Abstract: 3D human reconstruction is critical for VR/AR. Early methods relied on multi-view cameras and depth sensors but were costly. Mid-term approaches using parametric human models enabled efficient single-image reconstruction, while implicit neural representations improved fidelity yet suffered from low efficiency. Currently, 3D Gaussian Splatting achieves high accuracy and real-time rendering as a new paradigm. Challenges include detail distortion and limited generalization, and future development will focus on VR/AR integration.
Research On Performance Evaluation Of P300 Brain-Computer Interface Under Environment Modeling And Simulation,
2026
Beijing Institute of Mechanical Equipment, Beijing 100854, China
Research On Performance Evaluation Of P300 Brain-Computer Interface Under Environment Modeling And Simulation, Xiaofei Ge, Jinling Lian, Jin Han, Xin'an Fan, Danmei Luo, Yuxiang Hua, Hao Liu, Lijian Zhang
Journal of System Simulation
Abstract: In the process of brain-computer interface(BCI) technology stepping from laboratory to practical application scenarios, it is difficult to make an accurate prediction and evaluation of the effect of real environment factors on the system performance. Therefore, a research method based on a multifactor simulation experiment was proposed. A controllable simulation experiment environment was constructed, and the parametric modeling of two key physical environmental factors, namely noise and light, was carried out. By taking the number of electroencephalogram channels as the system parameter, this paper systematically studied the influence mechanism of the aforementioned factors on the decoding performance of P300-BCI. …
Neural Radiance Fields Based On Explicit Feature Matching And Scaled Dot-Product Attention,
2026
School of Computer Science and Technology, Anhui University, Hefei 230601, China
Neural Radiance Fields Based On Explicit Feature Matching And Scaled Dot-Product Attention, Mingwei Cao, Fengna Wang, Zilong Wang, Haifeng Zhao
Journal of System Simulation
Abstract: To address the problems that neural radiance fields(NeRF) are prone to artifacts and texture blurring in novel view synthesis under sparse view input and complex scenes, this paper proposed neural radiance fields based on explicit feature matching and scaled dot-product attention(EMD-NeRF). A multiscale feature extraction network was used to extract multi-scale feature information from the input sparse views. A fusion dot-product module was utilized to calculate view interaction information as a shared branch. Cosine similarity was adopted as a matching clue for similarity embedding volume rendering. A regularization loss function was used to enhance the quality of the scene …
Integrating Geometric Priors And Importance Sampling For High-Fidelity Indoor Scene Reconstruction,
2026
School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China
Integrating Geometric Priors And Importance Sampling For High-Fidelity Indoor Scene Reconstruction, Tao Yang, Min Shi, Xigang Zhao, Suqin Wang, Qi Wang, Dengming Zhu
Journal of System Simulation
Abstract: Gaussian splatting suffers from geometric distortion during scene reconstruction, particularly in weakly textured indoor scenes. To address this issue, this paper proposes a high-precision indoor scene reconstruction method that integrates geometric priors and importance sampling. The proposed method fully considers the effect of the initialization process on reconstruction quality. An advanced feed-forward model is employed to generate high-quality geometric initialization, thus improving overall reconstruction stability and accuracy. An importance sampling strategy is introduced to mitigate the adverse effects of blurry images. Furthermore, a supervision mechanism based on a geometric prior model is designed to constrain the scene structure, further …
Analytical Reentry Guidance Method Based On Lift-To-Drag Ratio-Velocity Profile,
2026
Control and Simulation Center, Harbin Institute of Technology, Harbin 150080, China; National Key Laboratory of Modeling and Simulation for Complex Systems, Harbin 150080, China; Beijing Institute of Control & Electronic Technology, Beijing 100038, China
Analytical Reentry Guidance Method Based On Lift-To-Drag Ratio-Velocity Profile, Weibo Sun, Ping Ma, Yuxuan Wang, Songyan Wang, Tao Chao
Journal of System Simulation
Abstract: An analytical reentry guidance method based on the lift-to-drag ratio and velocity profile was proposed to address the challenges of precise flight time control and prohibited area avoidance for the hypersonic glide flight vehicle during the reentry phase. A reduced-order reentry motion model was established; the Chebyshev series was used to approximate its nonlinear integral terms and differential equations; analytical expressions for the glide trajectory were yielded. The analytical relationships among flight time, remaining range, and the lift-to-drag ratio and velocity profile were derived. The optimization problem of lift-to-drag ratio and velocity profile was converted into a segmented parameter …
Research And Analysis Of Algorithm For Detecting Surface Defects On Automotive Wheel Hubs Based On Ccl-Yolov8,
2026
Key Laboratory of Metallurgical Equipment and Control Units, Ministry of Education, Wuhan University of Science and Technology, Wuhan 430081, China; Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan 430081, China; Institute of Precision Manufacturing, Wuhan University of Science and Technology, Wuhan 430081, China
Research And Analysis Of Algorithm For Detecting Surface Defects On Automotive Wheel Hubs Based On Ccl-Yolov8, Yanjun Chen, Min Zhou, Meng Zha, Meizhou Zhang
Journal of System Simulation
Abstract: To address the challenges such as low detection efficiency, difficulties in identifying small defects, and poor accuracy in detecting surface defects on automotive wheel hubs, a lightweight neural network called CCL-YOLOv8 was proposed based on an improved YOLOv8n architecture. A synergistic improvement in both detection accuracy and efficiency was achieved through a three-stage model optimization strategy. A convolutional attention fusion module was introduced, which integrated convolution operations with self-attention mechanisms, thereby enhancing the model's ability to capture local features of small defects while perceiving global context under low signal-to-noise ratio conditions.A C2f-Star module was constructed to reduce computational overhead …
Research On Inter-Satellite Topology Design And Simulation Of Giant Leo Constellation Network With Consistent Pattern,
2026
University of Chinese Academy of Sciences, Beijing 100049, China; Institute of Software, Chinese Academy of Sciences, Beijing 100190, China
Research On Inter-Satellite Topology Design And Simulation Of Giant Leo Constellation Network With Consistent Pattern, Zhicheng Li, Shuaijun Liu, Lixiang Liu
Journal of System Simulation
Abstract: The giant low earth orbit (LEO) constellation network uses inter-satellite links to form an intersatellite topology, realizing the transmission of data between satellites. In order to adapt to the nature of uniform and symmetrical distribution of satellites in the constellation, this paper used a consistent connection pattern between satellites to construct an inter-satellite topology, and by analyzing the arrangement of non-mirror links in the constellation, it was found that the connection method of each link of the satellite itself could be independent of each other, which reduced the simulation complexity and the solution space of the inter-satellite topology. …
A Precise Damage Assessment Method For Lethal Blast Warheads Against Quadruped Robots,
2026
State Key Laboratory of Explosion Science and Safety Protection, Beijing Institute of Technology, Beijing 100081, China
A Precise Damage Assessment Method For Lethal Blast Warheads Against Quadruped Robots, Xueqian Wang, Jianbing Men, Xin Zhou, Shuyou Wang, Mei Li
Journal of System Simulation
Abstract: To accurately evaluate the damage efficiency of a lethal blast warhead on quadruped robots, a typical quadruped robot replication model and vulnerability damage tree were constructed through Autodesk Inventor. The power field calculation model of a lethal blast warhead was introduced. Based on the high-precision collision detection and graphic rendering technology of UE, this paper carried out the intersection detection of destructive elements and targets and realistic scene visualization. A visualization system for damage assessment of quadruped robots by a lethal blast warhead was developed, featuring capabilities such as parametric modeling of the lethal blast warhead, power field evolution …
Simulation And Multi-Perspective Recognition Algorithm For Typical Trajectory Shapes,
2026
National Key Laboratory of Scattering and Radiation, Beijing 100080, China
Simulation And Multi-Perspective Recognition Algorithm For Typical Trajectory Shapes, Xuejian Feng, Han Ding, Yiqi Tong, Chaoying Huo, Yanjin Zhang
Journal of System Simulation
Abstract: Current trajectory simulation methods inadequately address geometric shape features and kinematic properties of the target trajectory. To bridge this gap, a target trajectory shape simulation algorithm based on kinematic laws was proposed. The polar coordinate equations and curvature equations of multiple trajectories were integrated. The aircraft state parameters were solved by combining kinematic equations. Angular Gaussian noise was introduced to enhance trajectory diversity and authenticity. Additionally, a multi-perspective trajectory shape recognition algorithm was designed, which could effectively integrate image and sequential multi-modal features by adopting a multilayer perceptron, enabling precise trajectory shape recognition. Experimental results demonstrate that the proposed …
Virtual Train Operation Platform Based On Digital Twin,
2026
CRRC Qingdao Sifang Rolling Stock Research Institute Co., Ltd., Qingdao 266000, China
Virtual Train Operation Platform Based On Digital Twin, Ziying Wang, Congjun Sun, Guihu Li, Tianhao Zhang
Journal of System Simulation
Abstract: In response to the limitations of traditional train operation simulation modeling, such as simplification, lack of adaptive adjustment capability for parameters, and proneness to error accumulation, a virtual train operation platform based on digital twin technology was proposed. A train model under specific railway lines was constructed. By combining with the intelligent operation and maintenance platform of the railway line, real-time train operation data was obtained and preprocessed. The adaptive chaos optimization algorithm was used to optimize the key parameters of train operation simulation online and establish a digital twin model of the railway line. This model adopted a …
Large-Scale Scene Registration Technology Based On 3d Gaussian Splatting Fusing Gps Prior Information,
2026
School of Computer and Artificial Intelligence, Henan University of Urban Construction, Pingdingshan 467036, China
Large-Scale Scene Registration Technology Based On 3d Gaussian Splatting Fusing Gps Prior Information, Fei Wan, Yong Yin
Journal of System Simulation
Abstract: To address the challenges of low computational efficiency, slow convergence, and limited accuracy in large-scale 3D scene registration, a 3D Gaussian splatting (3DGS) registration method integrating GPS prior information was proposed. Spatial position priors provided by GPS were utilized to establish initial alignment through coordinate system transformations, narrowing the registration search space. Dense point cloud models were efficiently reconstructed by combining 3DGS technology. Highprecision alignment was achieved through a two-stage optimization of GPS coarse registration and fine registration. Experiments demonstrate that the GPS-assisted method reduces translation errors by 25%~50% and increases success rates to 98% in vegetation-covered and …
