Digital Commons Network^™

A Method Of Heuristic Human-Llm Collaborative Source Search, Yi Chen, Sihang Qiu, Zhengqiu Zhu, Yatai Ji, Yong Zhao, Rusheng Ju

Journal of System Simulation

Abstract: Traditional source search algorithms are prone to local optimization, and source search methods combining crowdsourcing and human-AI collaboration suffer from low cost-efficiency due to human intervention. In this study, we proposed a lightweight human-AI collaboration framework that utilized multi-modal large language models (MLLMs) to achieve visual-language conversion, combined chain-of-thought (CoT) reasoning to optimize decision-making, and constructed a heuristic strategy that incorporated probability distribution filtering and a balance between exploitation and exploration. The effectiveness of the framework was verified by experiments. The human-AI alignment heuristic strategy with large language model adaptation design provides a new idea to reduce manual …

Optimization Of Order Picking And Sorting Coordintion In “Goods-To-Person” System, Liang Ren, Zerong Zhou, Yunfeng Ma

Journal of System Simulation

Abstract: To improve the order picking and sorting collaboration with time windows in the "goods-to-person" system, a mathematical model aiming to minimize the number of sorting batches was established. With the characteristics of this issue considered, a hybrid variable neighborhood search (HVNS) algorithm based on the "classified loading" strategy was proposed for solutions. The numerical experimental results show that the HVNS algorithm can obtain high-quality solutions while shortening the solution time; different order structures have varying effects on the utilization of the loading capacity of sorting automated guided vehicles (AGVs); under the tested experimental conditions, the collaborative operation mode …

Measurement Of Luminous Intensity Distribution For Film And Television Led Light Sources And Its Simulation Research In Game Engines, Jingyi Suo, Baihong Lu, Che Qu

Journal of System Simulation

Abstract: To address the issues of mismatched photometric characteristics between light sources in virtual environments and real-world lighting during film and television lighting design and lighting preview using game engines, a testing solution for measuring the luminous intensity distribution for film and television LED light sources was proposed, building upon existing luminaire light intensity distribution testing systems. Based on the obtained data, a light source calibration process was constructed in the UE5 to correctly simulate the photometric characteristics of light sources in the virtual environment. Simulation results have shown that the calibration process can accurately and efficiently reproduce the …

Research On Cooperative Interference Allocation Of Jamming Resources Based On Improved Genetic Algorithm, Zhixia Xu, Rui Wang, Nan Sun, Bing He, Xiaowei Shen, Xiaofei Zhu

Journal of System Simulation

Abstract: To address the cooperative interference allocation of jamming tasks, a cooperative interference allocation method of jamming resources was proposed based on the improved genetic algorithm. In search and tracking modes of the target radar, a threat level assessment was conducted by the technique for order preference by similarity to an ideal solution (TOPSIS) based on the entropy weight method. The factors affecting the jamming effectiveness of jammers were analyzed. A cooperative interference evaluation model of jamming effectiveness was established, and the allocation model of jamming resources was built with the total interference effectiveness of multiple jammers as the …

Research On Infrared And Visible Light Fusion Method Based On Resnet-50 And Laplacian Filtering, Xiao Wang, Xiangyang Li, Feng Liang, Zhili Zhang

Journal of System Simulation

Abstract: In order to solve the problem that existing infrared and visible light image fusion techniques often suffer from artifacts caused by insufficient contrast, spectral distortion, and high computational complexity, a fusion framework based on ResNet-50 and Laplacian filtering was proposed. ResNet-50 was used to extract shallow and deep features, followed by multi-scale feature fusion. Laplacian filtering was applied to optimize feature information, and an automatic discriminator was introduced to further improve the fusion effect. Simulation results show that, compared with comparison algorithms, the proposed method achieves an average increase of 2.71% and 2.16% in information entropy, 5.98% and …

Optimization Of Dynamic Weapon Target Assignment Considering Random Disturbances, Zhenzu Bai, Yizhi Hou, Zhangming He, Juhui Wei, Haiyin Zhou, Jiongqi Wang

Journal of System Simulation

Abstract: The impact of various random disturbances in the actual command and control environment of unmanned systems on problem modeling and solving of weapon target assignment was considered, and three types of uncertainty disturbance constraints were investigated. A multi-objective dynamic sensor weapon target assignment model was established. By considering the issues of model property changes caused by disturbances and insufficient robustness of the traditional single-operator solving algorithm, a multi-operator constrained multi-objective evolutionary framework based on the deep Q-network was proposed. The algorithm described the convergence, diversity, and feasibility of the population in both the objective and decision spaces. It established …

Survey Of Cooperative Multi-Agent Path Finding, Jun Xiong, Wenbo Zhang, Zhi Xiong, Feng Zhou, Bo Yang

Journal of System Simulation

Abstract: Cooperative multi-agent path finding (Co-MAPF) has been widely applied in fields such as UAV formation and multi-agent systems, which enhances the overall system efficiency through task collaboration, path planning, and task execution among multiple agents. This paper introduced three main system architectures, namely centralized, distributed, and hybrid, along with their advantages and disadvantages based on the definition of the Co-MAPF problem, categorized, and reviewed mainstream Co-MAPF algorithms, including those based on sampling, search, intelligent optimization, and learning. Furthermore, this paper analyzed the main current challenges faced by Co-MAPF algorithms on the basis of summarizing existing research and outlined the …

Interoperability Model And Application Of Military Training System For Combination Of Virtuality And Reality, Jianxing Gong, Hai Hu, Haihui Ren, Ruixiang Wu

Journal of System Simulation

Abstract: With the development of AI technology, VR technology, and combat simulation technology, in order to achieve the practical training effect of "how to fight and how to train soldiers", virtual and real training has become a widely popular military training mode. It has become a trend to integrate digital systems, virtual equipment, semi-physical models, physical models, and other heterogeneous systems to carry out training in the same training environment. Therefore, it is necessary to study the interoperability model and application of training systems for the combination of virtuality and reality. This paper proposed the definition of interoperability between virtuality …

Analysis Of Optimal Spectral Bands For Thermal Infrared Hyperspectral Image Reconstruction Driven By Physical Simulation Model, Yonghao Yang, Xiaoyu He

Journal of System Simulation

Abstract: To achieve accurate reconstruction of thermal infrared hyperspectral images under limited spectral bands, this paper proposed a reconstruction method based on physical modeling and simulation. Semi-global decomposition algorithm was adopted to invert the thermophysical properties of the scenario based on the physical model of thermal radiation, simulating and generating full-band hyperspectral data. An optimal spectral band selection strategy driven by a physical model was proposed, which integrated the sensitivity of temperature inversion and the separability of material spectra. Experiments were conducted on both simulated and measured datasets to evaluate the performance of material identification, temperature inversion, and spectral …

Research On Pac-Bayes-Based A2c Algorithm For Multi-Objective Reinforcement Learning, Xiang Liu, Qiankun Jin

Journal of System Simulation

Abstract: To address the theoretical challenges of exploration and exploitation trade-offs and uncertainty modeling in multi-objective reinforcement learning (MORL), this study developed a learning framework, MO-PAC, based on PAC-Bayes theory. By introducing a multi-objective stochastic Critic network and a dynamic preference mechanism, the framework extended the conventional A2C architecture, enabling adaptive and efficient approximation of complex Pareto fronts. Experimental results demonstrate that in multi-objective MuJoCo environments, MO-PAC outperforms baseline algorithms, achieving approximately 20% improvement in hypervolume and 60% increase in expected utility, while exhibiting superior convergence efficiency and robustness. It verifies both theoretical value and practical performance advantages in …

Comprehensive Study For Characterization Of Blending And Heat Treatment Of Organic-Based Polymer Thin Films, Ruaa M. Ali, Atyaf H. Kazem, Khalidah G. Hasan

Baghdad Science Journal

Thin films of Polypyrrole (PPy)/Cupper Phthalocyanine (CuPc) have been prepared by the spin coating technique on glass substrates, Samples were prepared in a blending ratio (50:50) in addition to pure PPy and CuPc at room temperature, these samples were annealed at (473K) and then characterized by X ray diffraction (XRD), Energy Dispersive Spectroscopy (EDX) and Scanning electron microscopy (FESEM) at different magnifications power. XRD patterns reveal that pure polypyr role is amorphous. A wide peak was seen at roughly 2θ= 24° with an average crystallite size of roughly 56 nm and CuPc had a polycrystalline structure. Annealing results …

A Social Media-Based Framework For Marketing Architectural Design Firms In Egypt During Global Economic Downturn, Ayman Ahmed Ezzat Othman, Yara Ahmed Maarek

Architectural Engineering

Purpose – The global economic downturn has greatly impacted the construction industry and architectural design firms (ADFs). Social media, however, provides a strategic avenue to enhance the visibility and resilience of ADFs. This paper aims to develop a framework integrating social media as an innovative marketing approach for mitigating the impacts of the global economic downturn on ADFs in Egypt.

Design/methodology/approach – A qualitative and quantitative research approach was designed to accomplish four objectives. The literature review examined the global economic downturn and marketing ADFs. Three case studies investigated the role of social media in marketing ADFs during economic uncertainties. …

Nuclear Binding Energy Prediction For Some Odd-Mass Number Nuclei By Artificial Neural Network (Ann), Ruya H. Ibrahim, Akram Mohammed Ali

Baghdad Science Journal

Machine learning models called artificial neural networks (ANNs) are widely used in many fields and real-world applications. The parameter vector that forms the basis of these models needs to be evaluated computationally. We calculated the ground-level binding energy of 146 nuclei with an odd mass number using three different models:the integrated nuclear model,the liquid drop model and the experimental model. The results of these models were compared with our theoretical results calculated by the artificial intelligence network. The mean squared error of the target and output values and how close they are to zero were calculated, and the degree of …

Dual-Channel Supply Chain Network Equilibrium Model Under Retailers’ Risk Aversion, Hongchun Wang, Caifeng Lin, Xinyi He, Haiyue Yin

Journal of System Simulation

Abstract: To study the network equilibrium problem of dual-channel supply chains under the background of retailers' risk aversion, a dual-channel supply chain network equilibrium model including multiple competitive suppliers, manufacturers, retailers, and demand markets was established. The Mean-CVaR method was employed to quantify retailers' risk aversion characteristics, and variational inequalities were utilized to characterize the equilibrium conditions of decision-makers at each tier of the supply chain. The projection contraction algorithm was applied to solve the model and conduct numerical analysis, thereby revealing the impact of retailers' risk aversion behavior on equilibrium outcomes. The simulation results indicate that a higher …

Using Physics-Informed Neural Networks For Solving 2Nd-Order Volterra Integro-Differential Equation By Deepxde Library, Oday Ahmed Jasim, Abdulghafor M. Al-Rozbayani

Baghdad Science Journal

Many disciplines widely use deep learning (DL) as a key tool for investigating the behavior of various systems. Deep learning (DL) has recently been utilized to solve differential equations using physics-based input. Physics-informed neural networks (PINNs) are a novel DL model that excels at solving both inverse and forward non-linear PDE problems. PINNs may be trained as surrogate models for approximation solutions to the VIDE without label data by embedding the physical information outlined by PDEs in feedforward NNs. The objective of this study is to solve the second-order Volterra integral-differential equations (2nd-order VIDEs) for the first time using PINN …

Robust Emergency Dispatch Method Considering Dynamic Frequency Security And N-K Contingency, Tao Huang, Zhi Zhang, Yujie Ding, Yanbo Chen, Jing Wang, Wenqian Zhang

Journal of System Simulation

Abstract: To address the risk of system inertia loss and frequency instability caused by grid integration of high-proportioned new energy and unit failures, an N-k robust emergency dispatch method considering dynamic frequency security constraints was proposed. With the consideration of the frequency response characteristics of variable-speed pumped storage, a dynamic frequency response model incorporating variable-speed pumped storage was constructed, and the nadir frequency constraint was established through second-order cone transformation. Information entropy theory was employed to quantify the uncertainty of unit failures, and an uncertainty set considering N-k unit failures was developed. A twostage robust emergency dispatch model considering N-k …

Vibration Control Of Offshore Wind Turbine Towers Based On Eddy Current Nonlinear Energy Sink, Xiangxing Yu, Yandong Zhao, Baolin Zhang

Journal of System Simulation

Abstract: To address the issue of tower vibrations induced by wind loads, which can damage the structure of wind turbines, a vibration control method for monopile offshore wind turbine towers based on an eddy current-nonlinear energy sink (EC-NES) was proposed. The dynamic model of monopile offshore wind turbines based on EC-NES was constructed according to the Euler-Lagrange equation, and based on the output response of FAST software, the unknown parameters of the model and the wind loads were identified in terms of parameters. The optimal parameters of EC-NES stiffness and damping were obtained using PSO. The eddy current damper …

Fault Diagnosis Method For Photovoltaic Systems Based On Multi-Strategy Fusion, Bin Li, Yuchuo Wang

Journal of System Simulation

Abstract: To address the problem of frequent PV system faults, a multimodal fusion fault diagnosis model based on the optimization of the improved lemming algorithm was proposed. The one-dimensional time series signals of PV currents and voltages were converted into two-dimensional images by Markov transformation field, and the spatial features of the original waveforms were mined by using multiscale CNN (MCCNN); BiGRU was used to extract the temporal dynamic features of the original waveforms, and complementary enhancement of the temporal and spatial features was realized by the feature fusion layer. The improved lemming algorithm was innovatively introduced to adaptively optimize …

Numerical Simulations Of Ship Liquid Tank Sloshing Based On Graph Neural Networks, Wenkang Zhang, Xiaofeng Sun, Yiping Zhong, Yong Yin

Journal of System Simulation

Abstract: To address the high consumption of computational resources in simulating ship liquid tank sloshing using computational fluid dynamics simulation methods, a data-driven numerical simulation model was proposed based on graph neural networks. An encoder-processor-decoder framework was employed in the proposed model. The encoder extracted features of fluid particles from the first five time steps. The processor learnt latent motion patterns of fluid and updated features, and the decoder predicted features of particles at subsequent time steps. The processor incorporated a self-attention mechanism to enable dynamic adjacency weight allocation and emphasize the influence of irregular tank wall regions. Training …

Lightweight Assembly Workpiece Detection Algorithm Based On Improved Yolov8, Shuheng Wu, Yongkui Liu, Lin Zhang, Yingying Xiao, Lihui Wang

Journal of System Simulation

Abstract: To address the issues of low recognition accuracy and slow detection speed with existing deep learning-based object detection algorithms for robotic automatic assembly tasks, a lightweight assembly workpiece object detection algorithm based on YOLOv8 was proposed. The PConv was introduced to improve the C2f module, and a new Faster_C2f module was designed to enhance the detection speed of the model. The SIoU loss function was employed to optimize the location prediction accuracy of the CIoU loss function and improve the localization accuracy of small targets. The high-level screening-feature fusion pyramid networks (HS-FPN) structure was used to improve the Neck …

Emotive Immersion: Eeg-Driven Ai Art In Immersive Visual Spaces (Full Dome), Yuming Chen, Gianni Corino

School of Art, Design and Architecture

This paper proposes a rethinking of the “Future Screen” through the integration of affective computing, generative AI, and immersive spatial display. As an advanced screen paradigm, the full dome environment transcends flat, passive interfaces and enables dynamic, multisensory, and emotionally adaptive media experiences (Von Chamier-Waite, 2013). Building on this potential, the research presents Coids, an interactive dome installation. In this work, real-time emotional states are captured using EEG-based emotion recognition. These inputs dynamically shape AI-generated visuals within a shared immersive setting.Drawing on theories of immersion, presence, AI generated visuals and affect, the study explores how physiological data, even from low-resolution …

Advanced Ni-Co And Sn-Based Alloys Electrodeposition From Aqueous And Deep Eutectic Solvents, Narmin M. Hamadamin, Hassan H. Abdallah

Polytechnic Journal

Electrodeposition is a pivotal technique in materials science, enabling the fabrication of metal and alloy coatings with tailored properties for diverse industrial applications. Traditional aqueous electrolytes, while widely used, present limitations such as narrow electrochemical windows, hydrogen evolution, and environmental concerns. Deep eutectic solvents (DESs) have emerged as promising alternatives, offering broader electrochemical windows, reduced toxicity, and enhanced solubility for metal salts. This review comprehensively examines the principles and advancements in electrodeposition from both aqueous and DES media, focusing on the deposition of Ni-Co and Sn-based alloys, the role of additives, the electrodeposition of metal powders, and surface analysis techniques. …

Visualizing The Effect Of Process Pause On Virus Entrapment During Constant Flux Virus Filtration, Wenbo Xu, Xianghong Qian, Hironobu Shirataki, Daniel Straus, Sumith Ranil Wickramasinghe

Biomedical Engineering Faculty Publications and Presentations

Virus filtration is an essential unit operation used to validate clearance of adventitious virus during the manufacture of biopharmaceutical products such as monoclonal antibodies. Obtaining at least a 10,000-fold reduction in virus particles in the permeate is challenging as monoclonal antibodies are about half the size of the virus particles. Minute virus of mice, FDA-recommended model adventitious virus, was labeled with a fluorescent dye. Laser scanning confocal microscopy was used to determine the location of virus entrapment within the virus filtration membrane. Three different hollow fiber membranes made of regenerated cellulose and polyvinylidene fluoride were tested. Feed streams consisted of …

Detection Of The Linac Jaw Face Angle Misalignment Using High Energy Electron Beam Symmetry, Song Gao, Andres Cibrian, Jared Ohrt, Peter Balter

Faculty, Staff and Student Publications

Purpose: To demonstrate the usage of a high energy electron beam symmetry measured at different collimator angles to detect jaws face angle misalignments on Varian TrueBeam linear accelerators (linac) during acceptance and commissioning processes.

Methods: During the linac acceptance, all beams were steered to a symmetric shape with the gantry and collimator at 0°. We noted that the symmetries of higher energies electrons (e.g., 16 MeV, 20 MeV) changed over 2% when measured with the collimator at 90° and/or 270° for two linacs commissioned within 5-months of each other. Misaligned applicators were ruled out as the cause of this issue. …

Sex Differences In The Association Of Vascular Risk And Apoe Genotype With Cognitive Decline And Dementia: Evidence From A U.S. Longitudinal Study, Longjian Liu, Jintong Hou, Saishi Cui, Xiaopeng Zhao, Zuolu Liu, J. Craig Longenecker, Nathalie S May, Jin Jun Luo, Rose Ann Dimaria-Ghalili, Howard J. Eisen

Division of Cardiology Faculty Papers

BACKGROUND: Sex differences in the association between vascular factors and cognitive outcomes remain unclear. We aimed to investigate the associations of blood pressure metrics (hypertension, systolic blood pressure [SBP), pulse pressure, ankle and brachial pressures, and ankle to brachial pressure index [ABI]) with the risk of cognitive decline and dementia.

METHODS: We conducted a population-based longitudinal analysis using data from the Atherosclerosis Risk in Communities (ARIC) study (begun in 1987-1989) in the United States. We analyzed a total of 12,268 participants aged 45-64 years who had validated exposure measurements, cognitive function tests (first administrated 1990-1992), and followed up for incidence …

Hybrid Pre-Trained Models With Machine Learning Classifier For Skin Cancer Classification, Toqa A. Sadoon, Asaad F. Qasim, Mohammed Khalaf, Ali M. Hasan

Baghdad Science Journal

Classification of skin lesions can be challenging because of the subtle variation on the skin surface due to the appearance of these lesions. In the other hand, the digital dermoscopy has been widely used by dermatologist to diagnose cancer. For accurate detection, the clinicians should have a lot of experiences, but human nature is prone to error, forgetfulness, tension, and speed in diagnosis, all of which can affect the accuracy of detection. For these reasons, automated skin lesion classification has been used by many researchers to help dermatologists in making the right and accurate decision during diagnosis. A preprocessing image …

Volumetric Video With Skateboarders: Creative Opportunities Of Working With An Emerging Screen Technology Beyond The Studio, Dani Landau, Diego Zamora

School of Art, Design and Architecture

Volumetric video is an emerging moving image technology in which each pixel is recorded witha location in three dimensions. Volumetric videos are normally created in studios using rigs made upof multiple cameras with LiDAR sensors and computers that combine the moving images. We tookthis technology out of the studio to explore variations of this technique in public skateparks. We foundthat as the technology is still in developing stages there are creative constraints: the lidar cameras sense at a limited distance to the subject, the image is of a relatively low resolution, and there are often glitches in theimage. In our …

The Assessment Of Soil Physico-Chemistry And Uptake Of Heavy Metals In Lumbricus Terrestris, Shahzad Anjum, Sidra Kanwal, Rana Manzoor Ahmad, Abdul Majid Khan, Muhammad Imran

Journal of Bioresource Management

Earthworms are considered ecosystem engineers, playing an essential role in soil fertility. Heavy metals are supposed to remain linked to soil for a very long time and can bio-accumulate swiftly in soil microbes, posing a severe threat to the environment. The current study was designed to investigate the bio-accumulation of heavy metals in Lumbricus terrestris and the impact of soil pH and texture on earthworm morphology and densities near industrial areas of the district of Okara, Punjab, Pakistan. The samples were collected from the locations of different industries using the quadrate method and analyzed for heavy metal accumulation by using …

The Gamification Of Online Dating: Exploring The Intersection Of Play, Choice, And Romance In Digital Spaces, Emma Taylor

School of Law, Humanities and Social Sciences

The rise of online dating platforms has transformed the way individuals approach romantic relationships, with many users increasingly engaging in these platforms as a form of entertainment in addition to finding meaningful connections. Central to this shift is the growing phenomenon of gamification, the incorporation of game-like elements, into non-game contexts. This article proposes to explore the gamification of online dating, examining how these game mechanics shape user behaviours, influence romantic choices, and impact relationship outcomes. By analysing the ways in which dating platforms integrate game-inspired features, this study will also assess the implications of gamified experiences for the nature …

Jupiter Mass Binary Objects Show A Minimum Acceleration, Mike Mcculloch

School of Engineering, Computing and Mathematics

Forty-two Jupiter Mass Binary Objects (JuMBOs) have been discovered in the Trapezium Cluster: either brown dwarf stars or planets mutually orbiting in pairs. Here it is shown that, just as in galaxies and wide binaries, the mutual orbits of the objects in each of these twin systems deviate from the Newtonian and level off around a mutual acceleration of 2��2/Θ=2×10−10 m/s2 supporting the minimum acceleration predicted by Quantised Inertia (QI), a theory that attributes inertial mass to an interaction between information horizons and quantum fields and predicts galaxy rotation without the need for dark matter. QI further predicts that the …