Research On Campus Epidemic Evolution Based On Multi-Scale Modeling And Simulation In Microscopic & Microscopic View, Mingwei Hu, Wenjie Yang

Journal of System Simulation

Abstract: High density of population leads to high possibility of cross-infection. It is necessary to focus on campus epidemic prevention and control. Basing on existing studies in macroscopic or microscopic view, this paper proposed a multi-scale means to analyze a short-term evolution of Corona virus disease 2019 (COVID-19) on campus and estimated the efficiency of prevention strategies. Macroscopic model was based on the susceptible-exposed-infections-recovered(SEIR) model, which exported the time curve of the number of asymptomatic patients and symptomatic patients. Microscopic model combined discrete event simulation modeling and agent-based modeling to simulate the behavior of campus students and the state evolution …

Recursive Subspace-Based Model Refinement Method For Digital Twin Of Thermal Power Unit, Yanbo Zhao, Yuanli Cai, Huaizhong Hu

Journal of System Simulation

Abstract: Due to factors such as simplified assumptions or equipment characteristic deviation, modeling errors are inevitable in the mechanism modeling of thermal power units. To deal with the problem, this paper proposes a novel model refinement method based on recursive subspace for the digital twin of thermal power units. Firstly, the digital twin models are built based on mechanism analysis and combined with small sample data of typical conditions, ensuring interpretability and generalization performance. Secondly, based on the recursive subspace identification method, the refinement model is built and updated online in real time to compensate for the modeling error, improving …

Modeling And Analysing Of Complex Combat Systems Based On Symbiosis Theory, Xiangrui Tian, Jie Ying, Rui Yao, Xiaodong Wan

Journal of System Simulation

Abstract: As the combat systems develop towards clustering, coordination, unmanned, and intelligent direction, traditional combat system modeling methods are unable to reflect the complexity and intelligence of the combat systems. By drawing on symbiosis theory, this paper models and analyzes complex combat systems, and decomposes the complex combat system into various subsystems according to combat missions. The combat units, interaction modes, and combat environments in the subsystems are analyzed. The paper builds mathematical models to capture the collaborative interaction relationships between combat units, finally constructing a symbiotic model of complex combat systems. By the symbiosis principles and methods, quantitative analysis …

Driving Method Of Virtual Multi-Person Disassembly And Assembly Task For Aeroengine, Qiuwei Zeng, Zhaoyong Hu, Zhile Wang, Ruilin Zhang, Gang Zou

Journal of System Simulation

Abstract: To meet the needs of virtual multi-person collaborative disassembly and assembly system for different disassembly and assembly tasks, this paper proposes a data-driven method with configurable task sequence. Taking an aeroengine prototype as the research object, the paper studies the task elements of multi-person collaborative disassembly and assembly. It parameterizes and expresses the task based on JSON (JavaScript object notation) and drives the task sequence by JSON parametrical files, defining the interactive operation of each task step. The practice shows that this method is applied to the multi-person collaborative disassembly and assembly system, which makes the system configurable and …

Heterogeneous Multi-Ant Colony Algorithm Combining Competitive Interaction Strategy And Eliminatingreconstructing Mechanism, Chen Feng, Xiaoming You, Sheng Liu

Journal of System Simulation

Abstract: The traditional ant colony algorithm has many problems in convergence and diversity when solving the traveling salesman problem (TSP). Therefore, this paper proposes a heterogeneous multi-ant colony algorithm that combines the competitive interaction strategy and the eliminating-reconstructing mechanism (CEACO) to overcome these shortcomings. Firstly, the algorithm uses a competitive interaction strategy, which adjusts the interaction period adaptively according to the Hamming distance of different groups in different periods. Competition coefficients are adopted to differentiate matching interaction objects for interaction. The matched objects interact with each other through the optimal solution and pheromone matrix. This mechanism achieves a balance between …

Multi-Model Soft Sensor Modeling Under Help-Training Strategy, Luosuyang He, Weili Xiong

Journal of System Simulation

Abstract: Due to the strong nonlinearity, multi-stage coupling, and the small number of labeled samples in complex industrial processes, it is difficult for traditional global soft sensor models to accurately describe the whole process. Therefore, a multi-model soft sensor modeling method under the helptraining strategy is proposed. This method uses a fuzzy C-means (FMC) clustering algorithm to mine similar samples in the sample set and build several sub-models. By introducing the help-training strategy, a collaborative training framework based on main and auxiliary learners is formed, and a confidence evaluation mechanism is designed to eliminate error samples and expand the modeling …

Spatio-Temporal Association Rule Mining Of Traffic Congestion In A Large-Scale Road Network Based On Trajectory Data, Qifan Zhou, Haixu Liu, Zhipeng Dong, Yin Xu

Journal of System Simulation

Abstract: A K neighbor-RElim (KNR) algorithm and a sequential KNbr-RElim (SKNR) algorithm are proposed to mine traffic congestion association rules and congestion propagation spatio-temporal association rules by vehicle trajectory data in a large-scale road network. The KNR algorithm extends the spatial topology constraint based on the RElim algorithm. The KNR can be used to mine the road links prone to congestion from the large-scale trajectory dataset in a large-scale road network and quantify the strength of association for congested road links. The SKNR algorithm expands the time dimension in the form of sliding window and can be applied for mining …

Result Validation Method Of Simulation Models Based On Piecewise Feature Extraction, Yucheng Luo, Ming'en Zhang, Fei Liu, Yingbo Lu, Feng Ye

Journal of System Simulation

Abstract: Verification, validation, and accreditation (VV&A) is a key means to ensure the credibility of simulation models, and model validation is the core link. In view of the unavailability of reference data, various sources of reference data, and strong subjectivity of expert validation in the result validation of the missile flight simulation model, a result validation method for the missile flight simulation model based on piecewise feature extraction of time series was proposed. Specifically, a comprehensive piecewise linear method for time series was first proposed. The method consisted of a linear piecewise algorithm based on the second-order derivative for extracting …

Intelligent Airport Crowd Management Technology Based On Digital Twin, Jinghui Zhong, Yutian Lin, Wenqiang Li, Wentong Cai

Journal of System Simulation

Abstract: Given the need for intelligent emergency control and management of airport crowds, a smart control scheme for airport crowds based on digital twin is proposed. The scheme constructs an integrated crowd control system framework with four dimensions, including digital layer, modeling layer, functional layer, and application layer. It discusses and demonstrates the application effect of five important application modules. By using a data-driven crowd simulation model and intelligent optimization algorithm, the proposed scheme realizes the dynamic prediction and control optimization of the airport crowd status. The scheme can effectively improve the efficiency and intelligence level of airport crowd control …

Optimization On Cold Chain Distribution Routes Considering Carbon Emissions Based On Improved Ant Colony Algorithm, Huifang Bao, Jie Fang, Jinsi Zhang, Chuansheng Wang

Journal of System Simulation

Abstract: As the comprehensive distribution cost is not considered comprehensively in the current cold chain distribution route optimization, this paper builds a path optimization model to minimize the comprehensive distribution cost. The model combines with the characteristics of fresh distribution, and comprehensively considers the transportation cost, carbon emission, refrigeration, cargo damage and time window constraints during cold chain transportation. Then, an improved ant colony algorithm is designed to solve this model. At the initial stage, the genetic algorithm is adopted to generate the initial pheromone, and then the ant colony algorithm is applied to conduct the subsequent optimization search. The …

Securing Edge Computing: A Hierarchical Iot Service Framework, Sajan Poudel, Nishar Miya, Rasib Khan

Posters-at-the-Capitol

Title: Securing Edge Computing: A Hierarchical IoT Service Framework

Authors: Nishar Miya, Sajan Poudel, Faculty Advisor: Rasib Khan, Ph.D.

Department: School of Computing and Analytics, College of Informatics, Northern Kentucky University

Abstract:

Edge computing, a paradigm shift in data processing, faces a critical challenge: ensuring security in a landscape marked by decentralization, distributed nodes, and a myriad of devices. These factors make traditional security measures inadequate, as they cannot effectively address the unique vulnerabilities of edge environments. Our research introduces a hierarchical framework that excels in securing IoT-based edge services against these inherent risks.

Our secure by design approach prioritizes …

Motivations Driving Video Research Podcasts: Impact On Value And Creation Of Research Video Presentations, My Doan, Anh Tran, Na Le

Posters-at-the-Capitol

Abstract

Purpose: The purpose of the study is to better understand the role and impact of video research podcasts in bridging the gap between academia and the general public, especially concerning the challenges of accessibility and comprehension of scholarly research.

Methods: A 10-question survey was administered to evaluate the effectiveness, utility, and acceptance of video recordings in research presentations. The survey also aimed to gather insights into the motivations, challenges, and benefits of using video podcasts for research dissemination. Results were then analyzed using the Unified Theory of Acceptance and Use of Technology (UTAUT) model.

Results: There were 102 respondents …

Parallel Algorithm For Testing The Singularity Of An N-Th Order Matrix, Ehab Alasadi

Al-Bahir Journal for Engineering and Pure Sciences

Analyze the possibilities of implementing a parallel algorithm to test the singularity of the N-th order matrix. Design and implement in ( C/C++) a solution based on sending messages between nodes using the PVM system library. Distribute the load among the nodes such that the computation time is as small as possible. Find out how the execution time and calculation acceleration depend on the number of nodes and the size of the problem (indicate the table and graphs). Based on the results, estimate the communication latency, for what size the task is (well) scalable on the given architecture, and what …

Alice In Cyberspace 2024, Stanley Mierzwa

Center for Cybersecurity

‘Alice in Cyberspace’ Conference Nurtures Women’s Interest, Representation in Cybersecurity

Immersive Framework For Designing Trajectories Using Augmented Reality, Joseph Anderson, Leo Materne, Karis Cooks, Michelle Aros, Jaia Huggins, Jesika Geliga-Torres, Kamden Kuykendall, David Canales, Barbara Chaparro

Publications

The intuitive interaction capabilities of augmented reality make it ideal for solving complex 3D problems that require complex spatial representations, which is key for astrodynamics and space mission planning. By implementing common and complex orbital mechanics algorithms in augmented reality, a hands-on method for designing orbit solutions and spacecraft missions is created. This effort explores the aforementioned implementation with the Microsoft Hololens 2 as well as its applications in industry and academia. Furthermore, a human-centered design process and study are utilized to ensure the tool is user-friendly while maintaining accuracy and applicability to higher-fidelity problems.

Multimodal Fusion For Audio-Image And Video Action Recognition, Muhammad B. Shaikh, Douglas Chai, Syed M. S. Islam, Naveed Akhtar

Research outputs 2022 to 2026

Multimodal Human Action Recognition (MHAR) is an important research topic in computer vision and event recognition fields. In this work, we address the problem of MHAR by developing a novel audio-image and video fusion-based deep learning framework that we call Multimodal Audio-Image and Video Action Recognizer (MAiVAR). We extract temporal information using image representations of audio signals and spatial information from video modality with the help of Convolutional Neutral Networks (CNN)-based feature extractors and fuse these features to recognize respective action classes. We apply a high-level weights assignment algorithm for improving audio-visual interaction and convergence. This proposed fusion-based framework utilizes …

Dp-Smote: Integrating Differential Privacy And Oversampling Technique To Preserve Privacy In Smart Homes, Amr Tarek Elsayed, Almohammady Sobhi Alsharkawy, Mohamed Sayed Farag, Shaban Ebrahim Abu Yusuf

Al-Azhar Bulletin of Science

Smart homes represent intelligent environments where interconnected devices gather information, enhancing users’ living experiences by ensuring comfort, safety, and efficient energy management. To enhance the quality of life, companies in the smart device industry collect user data, including activities, preferences, and power consumption. However, sharing such data necessitates privacy-preserving practices. This paper introduces a robust method for secure sharing of data to service providers, grounded in differential privacy (DP). This empowers smart home residents to contribute usage statistics while safeguarding their privacy. The approach incorporates the Synthetic Minority Oversampling technique (SMOTe) and seamlessly integrates Gaussian noise to generate synthetic data, …

Tutorial: Knowledge-Infused Artificial Intelligence For Mental Healthcare, Kaushik Roy

Publications

Artificial Intelligence (AI) systems for mental healthcare (MHCare) have been ever-growing after realizing the importance of early interventions for patients with chronic mental health (MH) conditions. Social media (SocMedia) emerged as the go-to platform for supporting patients seeking MHCare. The creation of peer-support groups without social stigma has resulted in patients transitioning from clinical settings to SocMedia supported interactions for quick help. Researchers started exploring SocMedia content in search of cues that showcase correlation or causation between different MH conditions to design better interventional strategies. User-level Classification-based AI systems were designed to leverage diverse SocMedia data from various MH conditions, …

K-Perm: Personalized Response Generation Using Dynamic Knowledge Retrieval And Persona-Adaptive Queries, Kanak Raj, Kaushik Roy, Vamshi Bonagiri, Priyanshul Govil, Krishnaprasad Thirunarayan, Raxit Goswami, Manas Gaur

Publications

Personalizing conversational agents can enhance the quality of conversations and increase user engagement. However, they often lack external knowledge to tend to a user’s persona appropriately. This is particularly crucial for practical applications like mental health support, nutrition planning, culturally sensitive conversations, or reducing toxic behavior in conversational agents. To enhance the relevance and comprehensiveness of personalized responses, we propose using a two-step approach that involves (1) selectively integrating user personas and (2) contextualizing the response with supplementing information from a background knowledge source. We develop K-PERM (Knowledge-guided PErsonalization with Reward Modulation), a dynamic conversational agent that combines these elements. …

Exploring Alternative Approaches To Language Modeling For Learning From Data And Knowledge, Yuxin Zi, Kaushik Roy, Vignesh Narayanan, Amit Sheth

Publications

Despite their wide applications to language understanding tasks, large language models (LLMs) still face challenges such as hallucinations - the occasional fabrication of information, and alignment issues - the lack of associations with human-curated world models (e.g., intuitive physics or common-sense knowledge). Additionally, the black-box nature of LLMs makes it highly challenging to train them meaningfully in order to achieve a desired behavior. Specifically, the attempt to adjust LLMs’ concept embedding spaces can be highly intractable, which involves analyzing the implicit impact on LLMs’ numerous parameters and the resulting inductive biases. This paper proposes a novel architecture that wraps powerful …