Digital Commons Network^™

Generalized Pentagonal Linear And Non-Linear Functions For Solving Fully Fuzzy Linear Programming Problems, Eman Hassan Ouda, Iden Hassan Hussein

Baghdad Science Journal

Fuzzy linear programming problems (FLPP) are advanced approaches for solving linear programming problems (LPP) that involve fuzzy coefficients and variables with constraints on the problem. Numerous applications exist for the pentagonal function and ranking membership in geometry and the sciences, especially mathematics. This study suggests a novel approach for solving fully fuzzy linear programming problems (FFLPP) using the ranking function with pentagonal functions. The project aims to determine the maximum (minimum) solution to the problems where all variables, including the objective function, constraints and the right hand, are pentagonal fuzzy numbers. Additionally, generalizations of both linear and nonlinear pentagonal functions …

On The Systems Of Distinct Representatives For The Family Of Sets Formed By Neighborhoods Of Vertices, Shahistha Hanif, K Arathi Bhat

Baghdad Science Journal

Currently, the theory of systems of distinct representatives is being carefully examined and reworked, often in a more general context. With time, considerable literature has grown, and new theories are proposed that require the system of distinct representatives to possess additional properties. In this article, one such context is considered. A graph is completely defined by the relationship between its vertices, also known as the neighborhood of vertices in graph theoretical context. Several parameters are defined based on the set of all neighborhoods of vertices and are explored. This article delves into the well-known problem of the existence of a …

Distance-Dependent Connectivity In The Brain Facilitates High Dynamical And Structural Complexity, Victor J. Barranca

Mathematics & Statistics Faculty Works

Recent experiments have revealed that the inter-regional connectivity of the cerebral cortex exhibits strengths spanning over several orders of magnitude and decaying with distance. We demonstrate this to be a fundamental organizing feature that fosters high complexity in both connectivity structure and network dynamics, achieving an advantageous balance between integration and differentiation of information. This is verified through analysis of a multi-scale neuronal network model with nonlinear integrate-and-fire dynamics, incorporating inter-regional connection strengths decaying exponentially with spatial separation at the macroscale as well as small-world local connectivity at the microscale. Through numerical simulation and optimization over the model parameterspace, we …

(R2164) The Nature Of The Big Bang Singularity In Inhomogeneous Szekeres Cosmological Frameworks, Ahmed M. Al-Haysah, Abdul-Majeed Al-Izeri

Applications and Applied Mathematics: An International Journal (AAM)

Without killing vector fields, the Szekeres metric is an explicit example of an anisotropic and inhomogeneous solution to the Einstein equations. The inhomogeneous Szekeres cosmological models (ISCM) within the Big Bang singularity (BBS) are obtained. This indicates that the Szekeres solution represents a more general class of exact solutions. It is known to exhibit axial symmetry. We investigate a Big Bang theory of the cosmos, which unexpectedly predicts that the universe started at the so-called BBS a finite length of time ago. A growing number of astrophysical researchers are using inhomogeneous extensions of the Friedmann-Lemaitre-Robertson-Walker (FLRW) solution and, by extension, …

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 …

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 …

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 …

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 …

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 …

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 …

Spatiotemporal Graph Convolution-Based Demand Forecasting And Simulation Analysis For Automotive Parts Supply Chain, Xiaobin Li, Bing Hu, Chao Yin, Bo Li, Jun Ma

Journal of System Simulation

Abstract: To address complex automotive after-sales parts supply network operations with insufficient demand forecasting accuracy, slow response, and low service efficiency, this study proposed a spatiotemporal graph convolution-based method for automotive parts supply chain demand forecasting. Sales network data of the automotive parts sales network was constructed as a heterogeneous graph, integrating node features like parts sales volume and value to build multi-dimensional node dependencies. A node update mechanism of the graph convolutional neural network was designed, combined with long short-term memory neural networks to capture temporal features, using spatiotemporal attention to integrate temporal and spatial features into updated nodes …

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 …

Read Well, Read Right: Developing Thai Reading Skills Of Third-Grade Students Through Phonics-Based Instruction Combined With Reading Skill Exercises, Wirachai Longkaeo, Sitah Thayati

Journal of Education Studies

This pre-experimental research aimed to 1) examine the effects of phonics-based instruction combined with reading skill exercises on Thai reading skills of third-grade students, and 2) investigate the learning process and factors contributing to the success of this instructional approach. A one-group pretest-posttest was employed. The target group consisted of 15 third-grade students from a private school in Chiang Mai Province, selected through purposive sampling based on their Thai reading assessment scores, identifying students with beginning-level reading foundations. The intervention lasted 10 hours. Research instruments included 1) a Thai reading skill test, and 2) observation and student reflection form. Quantitative …

Coincidence Points And Common Fixed Points Of Cyclic Maps By Implicit Contractive Conditions, Abbas Karim Nahi, Salwa Salman Abed

Baghdad Science Journal

The study of common fixed points and coincidence points has occupied a large part of the priorities of researchers, especially in the metric space and its generalizations. This done by weakening the assumption of commutativity by using: compatible mappings, weakly compatible mappings, R-sub weakly commuting mapping, Cq-commuting maps, occasionally weakly compatible maps, etc. The notion of occasionally weakly compatible and occasionally weakly biased mappings reduces to weak compatibility due to the unique coincidence points of the involved maps. It was pointed out that some results did not lead to effective generalizations for occasionally weakly compatible maps and occasionally weakly biased …

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 …

The Dynamic Among The Producer, Consumer, And Predator In The Presence Of Fear, Hunting Cooperation, And Anti-Predator Behavior, Muslim Saad Jabbar, Raid Kamel Naji

Baghdad Science Journal

In general, the dynamic interactions that form the relationships between predators and prey within a food chain depend heavily on fear, hunting cooperation, and anti-predator defenses. These elements support species’ survival in their particular habitats, balance the ecosystem, and control the numbers of predators and prey. Therefore, a three-species food chain system consisting of producer-consumer-predator, which plays a crucial role in ecological dynamics, has been formulated mathematically. The objective is to investigate the influence of fear, hunting cooperation, and anti-predators on the dynamic behavior of the food chain system. Two types of functional responses have been utilized. The characteristics of …

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 …

Scheduling Method For Virtual Power Plants Based On Analysis And Forecasting Of Heterogeneous Load Characteristics, Runzhao Zhang, Yanbo Chen, Tao Huang, Haoxin Tian, Tuben Qiang, Zhi Zhang

Journal of System Simulation

Abstract: To improve the electricity supply-demand situation by rationally utilizing demand response resources, a two-layer optimal scheduling model for virtual power plants (VPPs) based on the analysis and forecasting of heterogeneous load characteristics was proposed. With the differences in response characteristics of multi-type loads considered, a demand response model for multi-type loads was constructed by using a customer baseline load (CBL) curve forecasting method that integrated dynamic scenario generation and K-means++ clustering. A two-layer optimal scheduling model for VPPs that incorporated load aggregators and demand response was established. In this model, the upper layer conducted optimal scheduling targeting maximizing the …

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 …

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 …

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 …

Satellite-Mediated Quantum Clock Synchronization: Towards Precise Timing At A Global Scale, Sage B. Ducoing

LSU Doctoral Dissertations

Accurate timekeeping is essential for scientific and technological advancements, particularly in areas of communication, networking, navigation, and high precision measurements. While many methods of time resolution are already established using classical resources, they fail to combine high precision outcomes with large-scale implementations. Additionally, numerous quantum networking architectures using satellite-assisted methods have demonstrated quantum communication on scales exceeding ground-based methods. For these reasons, we propose the use of a time synchronization method by which pairs of highly time-correlated photons are exchanged between clocks on satellites and clocks on Earth, al- lowing users to reconstruct the time offsets between their clocks. This …

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. …

Allfromair™ Ires (Gen 3) – System Architecture, Process Physics & Compliance Verification, Vesa Olavi Lius

Defensive Publications Series

This disclosure describes the ALLFROMAIR™ IRES (Gen 3), a unified thermodynamic platform integrating heating, cooling, ventilation, and atmospheric water generation (AWG) into a single hardware unit. The system utilizes an ”Anticubic” U-channel geometry with airflow velocities <2.5 m/s to minimize fan power according to the Cube Law. Key innovations include a ”Three-Stage Rocket” thermodynamic process and a ”Turbo Effect” where regenerative pre-cooling reduces compressor temperature lift (\Delta T \approx 5K), enabling practical COPs >30.

The disclosure specifically details a pressure-modulated spray nozzle matrix capable of switching between ”Flash Evaporation” (<300 µm droplets) and ”Film Wetting” modes to maximize latent heat transfer on Heresite P-413/Hydrophilic coated exchangers. The system solves historical displacement ventilation stratification (”The Bahco Problem”) via a scavenger heat exchanger (HX4) coupled to a hydronic floor loop. An integrated ”Water Ring” harvests and purifies condensate to EU Directive 2020/2184 standards, enabling decentralized potable water production for residential, commercial, and tropical applications.

Keywords:

Integrated Regenerative Energy System (IRES), ALLFROMAIR, Anticubic U-Channel, Low Lift Heat Pump, Atmospheric Water Generator (AWG), Pressure Modulated Spray Matrix, Flash Evaporation, Thermodynamic Up-Gearing, Heresite P-413, Hydrophilic Topcoat, Radiant-Assisted Displacement Ventilation, Twin-Leg Air Separation, EU Directive 2020/2184, Three-Stage Rocket Process.