Digital Commons Network^™

Modeling, Dynamical Analysis, And Lmplementation Of Switched Memristive Neural Networks, Zhuang Qu, Shaohua Zhang, Cong Wang, Hongli Zhang, Xinkai Li, Ping Ma

Journal of System Simulation

Abstract: To simulate the dynamic functional switching of brain networks, a time-switched memristive Hopfield neural network (TSM-HNN) model is proposed. The model utilizes external time-sequential signals to control memristive synapses, allowing it to dynamically generate multi-scroll chaotic attractors of varying numbers and morphologies without altering the system's structure. This overcomes the limitation of traditional chaotic systems, which can typically only produce a single type of attractor. The model exhibits complex chaotic behavior, high sensitivity to initial conditions, and coexisting attractors. Its physical feasibility has been verified through PSPice circuit simulations. This enhanced complexity and randomness give the model significant potential …

Design And Research Of A Microfocus X-Ray Tube, Haodong Zhao, Shizong Wei, Daolong Yu, Zhixia Liu, Yuezhong Chen, Ji Xu

Journal of System Simulation

Abstract: With the rapid advancement of high-resolution imaging and Micro-nano detection technology, microfocus X-ray sources show great potential for applications in industrial non-destructive testing, biomedical imaging, and material microstructure analysis. Achieving a focal spot size below 10 μm is essential for enhancing spatial resolution. However, traditional X-ray tubes are constrained by heat source dimensions, electron beam divergence, and limited focusing capabilities, which makes it challenging to simultaneously achieve focal spot miniaturization and adequate radiation intensity. In this study, a hot cathode electron gun is modeled using CST particle studio. Simulations are conducted to analyze the influence of the first anode …

Research On Characteristics Of Inclined Jet Flow For Aircraft De-Icing Based On Multiphysics Coupling, Zhiwei Xing, Hongbin Zhang, Ke Sun, Wenliang Miao

Journal of System Simulation

Abstract: To address the complex multiphysics coupling and lack of theoretical guidance for spray parameters in aircraft ground de-icing, a simulation model based on the Phase-Field method and Realizable k-ε turbulence model is proposed to investigate inclined jet flow over airfoil surfaces. The model enables the numerical reconstruction of jet impingement, liquid film flow, and unsteady heat transfer processes, providing a framework to elucidate the regulatory mechanisms of jet angles on momentum distribution and thermal characteristics. The simulation results reveal distinct variations in the flow and heat-transfer characteristics at different jet inclination angles. At a jet angle of 15°, the …

Physics-Driven Efficient Simulation Platform For Warhead-Target Engagement And Damage Assessment, Yidan Cui, Jingyao Ke, Yufeng Zheng, Kun Xue

Journal of System Simulation

Abstract: To address the limitations of incomplete physical modeling, low computational efficiency, fragmented simulation workflows, and insufficient visual immersion in existing damage simulations of fragment warheads, this paper proposes and develops a physics-driven, high-efficiency visualization platform for warhead-target engagement and damage assessment. The platform implements a full-chain, closed-loop simulation framework covering scenario configuration, force-field computation, fragment dispersion, warhead-target intersection, and damage evaluation. A finite element-discrete element (JK2024-06) coupled dynamics framework is established, integrating a detonation model, shell expansion correction, and fragment velocity inheritance to accurately reproduce the complete dynamic process from detonation to dispersion. A three-level acceleration algorithm based on …

Research On Simulation Technology Of Sea Yawing Test For Amphibious Vehicles, Yue Zhong, Wenlong Ji, Shiqi Feng, Feng Xu, Shuangping Ye

Journal of System Simulation

Abstract: Addressing the challenges of achieving extreme operating conditions and understanding the boundary conditions of yaw performance in offshore yaw tests for amphibious vehicles, a heading-flow direction angle mapping analysis method based on computational fluid dynamics (CFD) simulation and a three-dimensional hydrodynamic stratified model is proposed. Under environmental conditions of second-level (wave height of 0.5 m, wind speed of 3.3 m/s) and third-level (wave height of 1.0 m, wind speed of 5.1 m/s) sea states, a hundred-meter yaw test is simulated to reveal the nonlinear evolution law of yaw displacement and heading-flow direction angle. The research indicates that the extreme …

Vibration Characteristics Of Compact Hydraulic System Pipelines Based On Two-Way Fluid- Structure Interaction, Lichen Shi, Xujia Feng, Weitao Dou, Yanyan Li

Journal of System Simulation

Abstract: Amid growing demands for green manufacturing, equipment miniaturization, and high efficiency, compact hydraulic systems are critical in disassembly, assembly, and transport operations due to their high power density and flexibility. However, severe vibration in the pipeline systems significantly compromises equipment reliability. This study investigates the dynamic response mechanism of a compact on-board hydraulic pipeline system, using a specific piece of disassembly and assembly equipment with spatially constrained clamp placement as a case study, through a two-way fluid-structure interaction method, and optimizes the clamp layout. The results show that resonance occurs when the excitation frequency of the hydraulic oil pressure …

Research On Automated Generation Method Of Data-Based Architectural View Products, Kui Wang, Tianrong Gao, Cheng Chen, Mengyin Cui, Ping Wang, Xiaoping Wang, Huaijin Ge

Journal of System Simulation

Abstract: To address the issue of insufficient consistency among view products in the architectural design process, this paper proposes an automatic view product generation method based on the architecture metamodel. To enhance the consistency of view products, the method abandons the traditional post-design verification approach. Instead, it uses the information flow/data flow defined in the metamodel as the benchmark, and through explicit associations among architectural data as well as mapping relationships between view products and data, automatically derives and generates behavioral view products from structural and classificational view products. A prototype tool developed based on this method has been validated …

Research Of Data-Model Integrated Digital Twin-Based Health Intelligent Monitoring For Multi-Stage Centrifugal Compressors, Xiaomo Jiang, Jigang Meng, Huaiyu Hui, Wenqing Meng, Haibin Yang, Huize Chen

Journal of System Simulation

Abstract: To address the challenges of insufficient real-time monitoring capability and weak coupling between physical entities and virtual models in the long-term safe and reliable operation of multi-stage centrifugal compressors under complex operating conditions, this paper proposes a digital twin construction method based on data-model fusion for intelligent health monitoring. A unit-system-component hierarchical virtual twin model is established to achieve the coordinated mapping of geometric structure, operational behavior, and monitoring data of the compressor. By integrating a terminal-edge-cloud collaborative architecture, data-driven models are dynamically coupled with the virtual twin to construct a digital twin-based health monitoring platform, enabling operating state …

Design Of A Simulation Dataset For Fine-Grained Detection Of Space Target Sequence Images, Shiyan Wang, Danpu Zhao, Haikun Hong

Journal of System Simulation

Abstract:

With the increasing number of space objects such as satellites, there is a growing need for fine-grained detection and recognition of distant space targets. However, obtaining real observational data remains difficult due to high costs and insufficient annotation detail. To overcome these limitations, asynthetic dataset generation system based on multi-module collaboration is developed. Using joint simulation with STK and Blender, the proposed system simulates optical imaging conditions of space targets and automatically produces sequential images along with corresponding fine-grained labels. A large-scale simulation dataset is constructed for fine-grained detection in space target image sequences. It contains …

Robotic Digital Twin Modeling Method Integrating Mbse And Modelica, Zaiwu Mei, Jiangman Zhou, Cong Zhang, Yiping Gao, Zerun Zhu

Journal of System Simulation

Abstract: To address the issues of disconnection between system architecture design and dynamic simulation, as well as the limited reusability and scalability of models in robotic digital twin modeling, a modular modeling approach integrating MBSE (model-based systems engineering) and Modelica is proposed. The method employs MBSE for system architecture design and requirement traceability, and combines Modelica for multi-domain dynamic simulation, forming a full-chain digital twin model from system design to physical behavior simulation. Standardized interfaces and a generic component model library are developed to decouple and integrate mechanical, electrical, and control subsystems, enabling rapid model assembly and functional expansion. A …

Modeling And Simulation Of Multi-Hop Routing In 3d Tunnel Wireless Sensor Networks, Fang Cao, Jiguang Yang, Jiuyuan Huo

Journal of System Simulation

Abstract: To address the unbalanced energy consumption and short network lifetime caused by the complex topology and strong energy coupling of three-dimensional tunnel wireless sensor networks, this study constructs a system-level operating model integrating spatial topology, energy evolution, and routing decision-making, and proposes an energy management for balanced and efficient routing (EMBER) algorithm based on the competition of tribes and cooperation of members (CTCM) algorithm. The optimal number of cluster heads is derived through tunnel spatial modeling. Clustering is performed using a Gaussian mixture model optimized by CTCM, and efficient cluster-head selection is achieved by combining data envelopment analysis. An …

Rrt*-Based Robotic Manipulator Path Planning With Artificial Potential Field Guidance And Accumulator-Based Adaptive Adjustment, Fangzheng Gao, Xu Guo, Quan Sun, Jiacai Huang, Zhongcai Zhang

Journal of System Simulation

Abstract: To address the problems of blind sampling, slow convergence, and path redundancy in robotic manipulator path planning in cluttered and unstructured three-dimensional environments, An RRT* algorithm integrating artificial potential field guidance and accumulator-based adaptive adjustment, namely APGA-RRT* (artificial potential field guidance and accumulator adaptive adjustment-RRT*). The proposed algorithm improves the overall planning performance from three aspects: sampling, expansion, and path optimization. In the sampling stage, a potential-field-guided sampling strategy based on target-distance weighting and virtual-target switching is constructed, obstacle suppression and safe-distance gating mechanisms are incorporated to dynamically adjust the guidance intensity, thereby enhancing target directivity and local escape …

Online Fine-Tuning Of Binocular Camera Extrinsic Parameters Based On Position-Iteration Dual Perception, Qian Long, Tuerhong Dilixiati, Qi Zheng, Lijun Shen

Journal of System Simulation

Abstract: In long-term operation of binocular systems, small drifts in extrinsic parameters may occur due to temperature changes, vibration, and mechanical shocks. As these drifts accumulate, the ranging error increases with distance and seriously degrades long-range measurement performance. Because online compensation is difficult, such small drifts are often neglected. To address this problem, an online fine-tuning method based on position-iteration dual perception is proposed. A multiplicative coupling weighting model is established by integrating spatial reliability with an iteration-stage modulation function. A three-stage progressive optimization algorithm is designed to balance convergence speed and robustness. A simulation framework for offline calibration and …

Review Of Evaluation Metrics For The Credibility Of Autonomous Driving Test Scenarios, Jiwei Li, Runmin Wang, Yu Zhu, Jingjun Cheng, Xiangmo Zhao

Journal of System Simulation

Abstract: Currently, scenario-based simulation testing has become a core technical approach for verifying autonomous driving system functionality. However, due to the absence of unified evaluation standards for simulation scenarios, significant differences exist among the metrics constructed and adopted by different studies, each with its own limitations. This hinders mutual recognition of research outcomes and prevents scientific measurement of scenario quality. This study systematically reviews relevant research from the past five years, categorizing autonomous driving test scenarios into four types: parameter-descriptive, trajectory-driven, environment-simulation, and perception-data-driven. It clarifies the core characteristics, application objectives, and generation mechanisms of each scenario type. Subsequently, focusing …

Hybrid Attention For Low-Overlap Point Cloud Registration, Huaijun Wang, Zonghua Yu, Chenxin Xu, Junhuai Li, Chenzhi Li, Junjie Yin

Journal of System Simulation

Abstract: To address the significant registration errors caused by large initial pose deviations in low overlap ratio point cloud, this paper presents a two-stage optimization method that integrates selfattention and cross-attention mechanisms. Orientation feature representation is enhanced using equivariant self-attention, semantic alignment is achieved through invariant cross-attention, and rotational equivariance is modeled with an octahedral group for coarse registration. Various attention variants are employed to aggregate features along the anchor dimension, and a local-to-global module is utilized for fine registration. On the 3DLoMatch dataset, the proposed method achieves a registration recall of 77.0% and an inlier ratio of 44.3%. Even …

Numerical Simulation Study On Flow-Induced Vibration Energy Harvesting Characteristics Of Piezoelectric Energy Harvester With Elliptical Cylinder Bluff-Body, Jiechao Lei, Long Li, Ji Yao

Journal of System Simulation

Abstract: To improve the self-powering efficiency of miniature internet of things devices, this paper establishes a fluid-structure-electric multi-field coupled computational fluid dynamics (CFD) model based on the ANSYS Fluent platform. It conducts a numerical simulation study on the flow-induced vibration energy harvesting characteristics of a piezoelectric cantilever beam energy harvester with an elliptical cylinder bluff-body. A systematic analysis is performed on the influence mechanism of flow velocity within the range of 0.1~0.5 m/s on the output power. The results indicate that the output power of the harvester exhibits phased growth with increasing flow velocity. In the range below 0.15 m/s, …

Generative Artificial Intelligence, Academic Integrity And Authentic Assessment Within An Irish University, Louise Nagle, Brigid Crowley, Laura Rafferty, Susan Horgan, Colin O'Brien

Publications

Academics need both an overarching policy on Generative Artificial Intelligence (Gen AI) use in teaching and learning, yet agency in its application across various disciplines. Clarity on the use of the technology for both students and staff is therefore a challenge and characterised by uncertainty given how its application is still unfamiliar. This research examines the organisational context in which Gen AI is being embraced and was conducted by the digital teaching support functions within an Irish university. Students and staff were surveyed (n=1,746) on various aspects of digital use within their education and workplace, including Gen AI. …

Lecturer-To-Lecturer Learning Model For Artificial Intelligence Adoption In African Universities: Opportunities And Challenges, Vincent C. Asogwa

Journal of Research Initiatives

Although artificial intelligence (AI) can transform teaching, research, and administrative processes, many African universities, including those in Eswatini and Nigeria, face challenges in implementing AI effectively because of inadequate infrastructure, lecturer skill gaps, and financial constraints. This study examines the opportunities and challenges associated with adopting the Lecturer-to-Lecturer Learning Model for AI in African universities. Grounded in social constructivism, the model emphasizes knowledge sharing through social interactions, which is particularly relevant in contexts where external resources are limited. The study employs content analysis of secondary data sources, including academic literature, institutional reports, and case studies on AI adoption in higher …

Does Gender Spell Success? Exploring Female Students' Perspectives Of Faculty At A Higher Educational Institution, Chitora Jackson, Terrence Hicks, Jill Channing, Arnold Nyarambi

Journal of Research Initiatives

Numerous studies have pointed to connections and positive interactions with faculty that result in positive outcomes for students (Beckowski & Gebauer, 2018; Jones, 2020; Trolian et al., 2021). However, despite this knowledge, there are still some areas related to this topic that remain under-researched. The purpose of this qualitative interpretative phenomenological study was to explore the lived experiences of female students at a higher educational institution and to understand how those experiences shape their perspectives of female and male faculty. Additionally, this study sought to discover how faculty gender influences their interactions with students and the similarities and differences between …

The Impact Of Ai-Driven Customer Relationship Management On Sustainable Performance: The Mediating Role Of Digital Customer Experience, Muhammad Ibrahim Jawad Al-Dulaimi

Journal of Economics and Administrative Sciences

This paper addresses the limited understanding of how Artificial Intelligence–driven Customer Relationship Management (AI-CRM) influences sustainable performance in emerging economies, particularly through the mediating role of digital customer experience. The study aims to examine the effect of AI-CRM on sustainable performance and investigate whether digital customer experience mediates this relationship. AI-CRM is operationalized through predictive and operational analytics, while sustainable performance is measured using the triple bottom line dimensions: economic, environmental, and social. A quantitative, cross-sectional research design was adopted. Data were collected through a structured questionnaire administered to 168 customers of hypermarkets affiliated with the Iraqi Ministry of Trade …

The Impact Of Organizational Ergonomics On Job Burnout: Evidence From Higher Education Institutions In Iraq, Zainab Shakir Jubair Al-Zalmi

Journal of Economics and Administrative Sciences

This research aims to examine organizational ergonomics and its impact on job burnout among a random sample of teaching and administrative staff employed at universities, colleges, and institutes within higher education institutions in Iraq. This topic is of considerable importance because improving organizational ergonomics can enhance the work environment, increase job performance, and promote employee well-being. The research also seeks to address the problem of occupational stress and excessive workloads resulting from increasing teaching and administrative tasks assigned to employees in higher education institutions. These pressures contribute to higher levels of job burnout and adversely affect employee performance and job …

The Impact Of Flexible Work Arrangements On Employee Performance: Evidence From Private Universities In Baghdad, Mariam Adeeb Rasheed, Noor Khalil Ibrahim

Journal of Economics and Administrative Sciences

This study examines the effect of Flexible Work Arrangements (FWAs) (flexible scheduling, compressed workweek, and telecommuting) on employee performance among administrative leaders in private universities in Baghdad. Addressing inconsistent findings in prior research regarding whether different forms of workplace flexibility contribute equally to employee performance. Guided by Social Exchange Theory, a quantitative cross-sectional design was employed using data collected from 321 administrative leaders across 15 private universities in Baghdad. Measurement reliability, convergent validity, discriminant validity, and confirmatory factor analysis were assessed using the covariance-based structural equation modeling (CB-SEM) procedure in SmartPLS4. The proposed hypotheses were subsequently tested through structural model …

Random Forest Algorithm Vs. Linear Regression For Financial Performance Determinants: Evidence From Iraqi Mixed-Sector Firms, Odaiy Obaid Zeidan, Mustafa Habib Mahdi

Journal of Economics and Administrative Sciences

This paper examines the predictive factors of financial performance among Iraqi mixed-sector firms, comparing the predictive power of traditional Ordinary Least Squares (OLS) regression with the Random Forest (RF) machine learning algorithm. Utilizing annual data from 11 firms over the period 2015–2020, the study measures financial performance using Return on Assets (ROA), Return on Equity (ROE), and Return on Sales (ROS). OLS regression identified the directional relationships and p-values, whereas Random Forest evaluated predictive accuracy and modeled nonlinear relationships. The OLS results indicate that firm size, liquidity, productivity, and cash-to-asset ratio have significant positive effects on financial performance, while the …

A Neutrosophic Memory-Integrity Calculus For Contradiction-Preserving Persistent Ai Agents, Rana Muhammad Zulqarnain, Saalam Ali

Neutrosophic Systems with Applications

Persistent AI agents increasingly convert interaction histories into long-lived memory, making memory transformation not retrieval alone—a central reliability problem. NMIC (Neutrosophic Memory-Integrity Calculus) formalizes the integrity of write, merge, consolidation, revision, and retrieval operations over persistent memory. Each proposition is represented through an evidence ledger carrying independent truth, indeterminacy, and falsity degrees together with reliability, provenance, temporal validity, contextual applicability, and inter-evidence dependence. A dependence-normalized hazard aggregation preserves simultaneous support and opposition while making the resulting state invariant to exact evidence duplication. Pure consolidation is governed by five integrity conditions: no support invention, no opposition invention, no manufactured certainty, contradiction …

Neutrokoopman: Channel-Preserving Koopman Spectral Analysis Of Nonlinear Dynamics With Truth, Indeterminacy, And Falsity Evidence, Ahmed Samy, Mohamed M. Abdelhafeez, K Venkatachalam, Mohamed Abouhawwash

Neutrosophic Systems with Applications

Modern dynamical systems increasingly operate with evidence that is not merely noisy but incomplete, contradictory, or only partially trustworthy. Conventional Koopman methods represent nonlinear dynamics through linear evolution of observables, while robust and adaptive variants address parameter and model uncertainty. They do not, however, preserve the semantic distinction between support, indeterminacy, and counter-support when those conditions are compressed into a single uncertainty variable. This paper develops NeutroKoopman, a channel-preserving Koopman framework in which the physical state is augmented by a single-valued neutrosophic evidence state ν_t = ( T_t,I_t,F_t ). Deterministic and Markovian formulations are …

A Spatiotemporal Study Of Environmentally Associated Pulmonary Diseases In Georgia, Jason Raymond Baum

Walden Dissertations and Doctoral Studies

Exposures to particulate dust matter (PM10 and smaller) from aggregate comminution facilities (ACF) can lead to the onset of environmentally associated pulmonary diseases (EAPDs); acute and chronic asthma (Type I allergic hypersensitivity reaction), chronic pulmonary disease, interstitial lung disease (ILD), and lung cancer. In this environmental epidemiological research study, three primary spatial and spatiotemporal research questions related to nonoccupational exposures from 118 facilities across Georgia were evaluated. Secondary data analysis was conducted from the Centers for Disease Control and Prevention’s (CDC) 2018–2023 Behavioral Risk Factor Surveillance System (BRFSS) and the Metropolitan Statistical Areas, Micropolitan Statistical Areas, and Metropolitan Divisions to …

Human-Centered Ai Governance In K–12 Education: A Qualitative Content Analysis Of Policy Gaps In Massachusetts School Districts, Simone Elias, Noran Moffett, Jeremy Womack, Richard Brutti

Journal of Research Initiatives

Artificial intelligence (AI) and generative AI tools have rapidly permeated K–12 education, outpacing governance structures and raising urgent concerns about equity, student data privacy, and academic integrity (Eutsler et al., 2026; OECD, 2023). Although a growing body of scholarship proposes multi-level AI governance models for education, empirical evidence on implementing these frameworks at the district policy level remains limited. This article contributes to the field by first synthesizing and adapting a K–12 AI governance framework based on peer-reviewed and policy literature, structured around macro-meso-micro levels and six pillars: ethical and equity-centered use, data governance and privacy, teaching and academic integrity, …

Oral History As A Tool For First-Year Student Success, Justin Willis, Saul Araujo

Journal of Research Initiatives

First-year college students often face significant challenges as they transition into higher education, particularly when balancing academic responsibilities with employment. Many students work out of financial necessity, which can increase stress, limit campus engagement, and negatively affect academic performance and well-being. This qualitative case study explores how oral history methods can support first-year college students as they adjust to the demands of balancing education and work. Guided by Tinto’s Model of Student Retention and Kolb’s Experiential Learning Theory, the study examines how firsthand narratives from individuals who have navigated similar challenges can foster reflection, resilience, and practical skill development. The …

Key Factors Affecting Arable Land Areas In Iraq: An Analytical Economic Study (1990–2021), Duaa Emad Ahmed, Osamah Kadhim Jbara, Kais Hassan Alwan

Journal of Economics and Administrative Sciences

This paper aims to measure and analyze the factors affecting arable land areas in Iraq during the period (1990–2021), to determine the nature of the relationship between these factors in the short and long term. The study analyzed the relationship between the quantity of nitrogen and phosphate fertilizers used in agriculture, the volume of water inflow from the Tigris and Euphrates rivers, and investment allocations for land reclamation projects. It evaluated their impact on arable land areas in Iraq. Results using the ARDL methodology indicated a long-term cointegration relationship between the variables through the bounds test. The F-value reached 7.597. …

Diagnosing Influential Observations Via Hybrid Secretary–Osprey Optimization Algorithm (Hsooa) In Gamma Regression Models For Fasting Blood Glucose Data, Luay Adil Abduljabbar, Sabah Manfi Ridha

Journal of Economics and Administrative Sciences

Influence diagnostics are essential for identifying influential observations that may affect the estimation accuracy of regression models. Classical diagnostic measures such as Cook's Distance and DFFITS may become less effective in complex or highly dispersed datasets. In this study, a new Hybrid Secretary–Osprey Optimization Algorithm (HSOOA), based on the integration of the Secretary Bird Optimization Algorithm (SBOA) and the Osprey Optimization Algorithm (OOA), is proposed for influential observation detection in the Gamma Regression Model (GRM). This optimization framework successfully achieves an optimal balance between global exploration and local exploitation. The proposed HSOOA framework was applied to a real medical dataset …