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5th 5th Olympus - International conference on Supply Chain

作者： Dimara, Asimina Papaioannou, Alexios Krinidis, Stelios Anagnostopoulos, Christos-Nikolaos Democritus Univ Thrace DUTh Management Sci & Technol Dept Kavala Greece Univ Aegean UAEGEAN Dept Cultural Technol & Commun Intelligent Syst Lab Mitilini Greece Int Hellen Univ IHU Management Sci & Technol Dept Kavala Greece

ISBN: (纸本)9783031693434;9783031693441

The present research addresses the complicated challenges of modelling and enhancing processes in mixed-use harbors, focusing on Volos, where the convergence of many activities necessitates customized solutions for effective administration. This research initiates a case-specific investigation in response to the changing marine industry landscape, which is represented by the integration of shipping, recreation, and tourism inside the harbor of Volos. Real-world data from the Volos harbor was gathered using a hybrid methodology that blends mathematical modeling and simulation methodologies to inform the dynamic models. Volos is a microcosm that captures the challenges in establishing a balance between tourist,, commercial ships, and recreational boating. The modeling strategy provides a comprehensive representation of processes by taking interactions and possible conflicts into consideration. It is based on well-established harbor models that have been modified for mixed-use areas. In addition, cutting-edge optimization methods were used, considering environmental impact, traffic control, and resource use. Findings, which were obtained in the particular setting of the Volos harbor, show significant gains in resource allocation and operational efficiency, offering important new information for harbor management.

关键词： Mixed-use Harbor Optimization Harbor process Enhancement modeling and Simulation Traffic control Strategies

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Intelligent Algorithm System for Security Governance Driven by Big data in Autonomous Systems 2

Intelligent Algorithm System for Security Governance Driven ...

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2nd International conference on Machine Learning and Autonomous Systems, ICMLAS 2025

作者： Wang, Yiran Shanghai University of Political Science and Law Shanghai201500 China

ISBN: (纸本)9798331505745

With the advancement of big data encryption and decryption technology, the role of data in national governance and social governance has become increasingly prominent. In order to effectively deal with the increasingly complex security governance issues, this study proposes the novel big data-driven intelligent algorithm system. The purpose of this study is to optimize the challenges of the network attack identification, protection measures, and encryption processing of information leakage in security governance through real-time monitoring and predictive analysis of data. The core of the designed system includes two modules: network attack detection algorithm and information leakage modeling encryption algorithm. From a methodological perspective, this study proposes a model for predicting abnormal network traffic based on chaos dynamics. This groundbreaking model uses time series analysis to identify and locate potential DDoS attack traffic. At the same time, combined with information entropy theory, a cascade network attack chain analysis model for DDoS attack protection is designed. At the data security level, an encryption algorithm based on chaos theory is used to effectively protect against information leakage. Through experimental verification, it is known that the proposed encryption algorithm can effectively retain the original data during the information encryption and decryption process. At the same time, through encryption algorithm verification, the security and anti-attack ability of information are improved. © 2025 IEEE.

关键词： Information leakage

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A data-driven constitutive model for compressible polymeric foams 13th

A data-driven constitutive model for compressible polymeric ...

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13th European conference on Constitutive Models for Rubber

作者： Acan, A. K. Gargi, Y. Basdemir, S. Dal, H. Middle East Tech Univ Dept Mech Engn Ankara Turkiye Middle East Tech Univ CAD CAM Robot Ctr Ankara Turkiye

ISBN: (纸本)9781032851648;9781003516880;9781032851389

Compressible polymeric foams exhibit a highly non-linear mechanical behaviour. Classical constitutive models have a fixed mathematical expression. Degree of porosity and the cellular structure of the foam affects the mechanical response significantly. In this regard, phenomenological constitutive models may not be successful in modeling a variety of compressible polymeric foams. data-driven constitutive modeling is a promising approach to solve this problem, here we propose an extended version of B-spline based data-driven framework (Dal, Denli, Acan, & Kaliske 2023) for compressible materials. The model adapts its control point values to reduce the error between data and prediction until a threshold is reached, and is thermodynamically consistent through the use of optimization constraints. The proposed model has been validated with closed-cell EPDM (ethylene propylene diene monomer) with three distinct foam densities. The uniaxial tension and the confined compression experiments were conducted to identify the mechanical behavior of the materials. A non-homogeneous uniaxial compression experiment was performed to validate the control points obtained through the simultaneous fitting of uniaxial tension and confined compression. Finite element analysis was conducted under conditions precisely replicated from the non-homogeneous uniaxial compression experiment. Furthermore, a comparison is performed between the classical constitutive models (Blatz & Ko 1962, Hill 1979) and the proposed data-driven approach. The results show that the data-driven approach is very promising to model the mechanical behavior of compressible polymeric materials.

关键词： Constitutive models

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Fe³⁺ and Mn²⁺ Removal from Water Solutions by Clinoptilolite Zeolites as a Potential Treatment for Groundwater Wells

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processES 2025年第4期13卷 1060-1060页

作者： Arenhardt, William D. Ketzer, Felipe Wancura, Joao H. C. Seraglio, Janaina Carasek, Fabio L. Zin, Guilherme Calisto, Jean F. F. Rodrigues, Clovis A. de Meneses, Alessandra C. Oliveira, Jose Vladimir Dal Magro, Jacir Community Univ Chapeco Reg Environm Sci Area BR-89809900 Chapeco SC Brazil Farroupilha Fed Inst Ind Proc Grp Technol & Control IPG TC BR-98280000 Panambi RS Brazil Univ Fed Santa Maria Lab Biomass & Biofuels L2B BR-97105900 Santa Maria RS Brazil Univ Vale Itajai Chem Pharmaceut Res Ctr NIQFAR BR-88302901 Itajai SC Brazil Univ Fed Santa Catarina Dept Chem Engn & Food Engn BR-88040 900 Florianopolis SC Brazil

This study presents data on the water quality of the Guarani Aquifer based on samples collected from distinct groundwater wells in the western region of Santa Catarina State, Brazil. Among the analyses performed, the results indicated the need for treatment to ensure suitability for human consumption, particularly concerning Fe3+ and Mn2+ ions. Accordingly, natural (NCLIN) and activated clinoptilolite (ACLIN) zeolites were evaluated for ion removal from synthetic aqueous solutions through adsorption. NCLIN demonstrated excellent performance in adsorbing Fe3+ and Mn2+ ions, achieving removal efficiencies of over 98% and 95%, respectively, at a controlled pH of 6.0 (NCLIN) or 4.0 (ACLIN). A non-linear approach to modeling adsorption kinetics indicated that the pseudo-second-order model best represented the experimental data. This finding suggests that the interaction between the adsorbent and Fe3+ and Mn2+ ions occur through electron sharing and chemisorption. Equilibrium modeling analysis revealed that adsorption on NCLIN occurred in a monolayer, whereas adsorption on ACLIN followed a multilayer pattern. This behavior is attributed to the activation process with H2SO4, which led to dealumination and the formation of HSO3- groups on the adsorbent surface.

关键词： heavy metals ion adsorption iron (III) manganese (II) potable water natural zeolite

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A Hybrid Update of the Fe-Si System by DSC, Thermodynamic modeling and Statistical Learning from Ladle Refining data of Electrical Steels

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METALLURGICAL AND MATERIALS TRANSACTIONS B-process METALLURGY AND MATERIALS processING SCIENCE 2025年第3期56卷 2249-2276页

作者： Bernhard, Michael Kavic, Daniel Presoly, Peter Wi, Tae-Gyu Park, Won-Bum Roessler, Roman Jungreithmeier, Alfred Ilie, Sergiu Bernhard, Christian Kang, Youn-Bae Univ Leoben Chair Ferrous Met Franz Josef Str 18 A-8700 Leoben Austria Pohang Univ Sci & Technol Grad Inst Ferrous & Eco Mat Technol 77 Cheongamro Pohang 37673 Gyeongbuk South Korea K1 MET GmbH Stahlstr 14 A-4020 Linz Austria Voestalpine Stahl GmbH Voestalpine Str 3 A-4020 Linz Austria Pohang Univ Sci & Technol Dept Mat Sci & Engn 77 Cheongamro Pohang 37673 Gyeongbuk South Korea

Electrical steels, also known as silicon steels, are essential materials in electrical applications due to their unique magnetic properties, which are enhanced by adding up to 3.5 wt pct Si. However, alloying with ferrosilicon FeSi75, a mixture of 25 wt pct Fe and 75 wt pct Si, during ladle refining faces steelmakers with metallurgical challenges, primarily due to the strong exothermic reaction during its dissolution in liquid steel. Here, solution thermodynamics of the Fe-Si system offer insights into the heat evolution and, therefore, superheating control for continuous casting. This study experimentally reassesses the binary Fe-Si system using Differential Scanning Calorimetry (DSC) and High-Temperature Laser Scanning Confocal Microscopy (HT-LSCM) to investigate phase equilibria between 0.50 and 12.50 wt pct Si and from 600 degrees C to 1550 degrees C. Thermodynamic modeling of the Fe-Si system was carried out in the CALPHAD framework, applying the Modified Quasichemical Model (MQM) for the liquid phase to consider the strong interactions between Fe and Si. In this way, the description of the liquid's mixing enthalpy and the activities of Fe and Si agree well with literature values. Deviations in liquidus and solidus temperatures, as measured by DSC, were reduced to within +/- 5 degrees C. Additionally, the solubility limits of Fe and Si in intermediate silicides were refined based on the most recently published measurements. A comprehensive statistical analysis of industrial ladle refining processes involving 172 t ladles revealed a heat increase of 4.73 degrees C per t of FeSi75, consistent with adiabatic thermodynamic calculations (5 degrees C per t FeSi75). These findings improve the precision of thermodynamic databases and provide valuable insights for optimizing heat management and process control in producing silicon steels.

关键词： Continuous casting

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Mechanical Structure Design and Motion Simulation analysis of a Lower Limb Exoskeleton Rehabilitation Robot Based on Human-Machine Integration

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SENSORS 2025年第5期25卷 1611-1611页

作者： Zhao, Chenglong Liu, Zhen Ou, Yuefa Zhu, Liucun Beibu Gulf Univ Guangxi Key Lab Ocean Engn Equipment & Technol Qinzhou 535011 Peoples R China Nagasaki Inst Appl Sci Dept Integrated Syst Engn Nagasaki 8510193 Japan Beibu Gulf Univ Adv Sci & Technol Res Inst Qinzhou 535001 Peoples R China Wenzhou Med Univ Sch Rehabil Med Wenzhou 325035 Peoples R China Shandong Xiehe Univ Sch Comp Jinan 250109 Peoples R China Kanagawa Univ Inst Informat Yokohama 2218686 Japan

Population aging is an inevitable trend in contemporary society, and the application of technologies such as human-machine interaction, assistive healthcare, and robotics in daily service sectors continues to increase. The lower limb exoskeleton rehabilitation robot has great potential in areas such as enhancing human physical functions, rehabilitation training, and assisting the elderly and disabled. This paper integrates the structural characteristics of the human lower limb, motion mechanics, and gait features to design a biomimetic exoskeleton structure and proposes a human-machine integrated lower limb exoskeleton rehabilitation robot. Human gait data are collected using the Optitrack optical 3D motion capture system. SolidWorks 3D modeling software Version 2021 is used to create a virtual prototype of the exoskeleton, and kinematic analysis is performed using the standard Denavit-Hartenberg (D-H) parameter method. Kinematic simulations are carried out using the Matlab Robotic Toolbox Version R2018a with the derived D-H parameters. A physical prototype was fabricated and tested to verify the validity of the structural design and gait parameters. A controller based on BP fuzzy neural network PID control is designed to ensure the stability of human walking. By comparing two sets of simulation results, it is shown that the BP fuzzy neural network PID control outperforms the other two control methods in terms of overshoot and settling time. The specific conclusions are as follows: after multiple walking gait tests, the robot's walking process proved to be relatively safe and stable;when using BP fuzzy neural network PID control, there is no significant oscillation, with an overshoot of 5.5% and a settling time of 0.49 s, but the speed was slow, with a walking speed of approximately 0.18 m/s, a stride length of about 32 cm, and a gait cycle duration of approximately 1.8 s. The model proposed in this paper can effectively assist patients in recovering their ability t

关键词： lower limb exoskeleton rehabilitation robot structural design kinematic simulation

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Research on Spares Optimization Method of the Complex Electronic Information System Based on Monte Carlo Simulation

Research on Spares Optimization Method of the Complex Electr...

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2024 International conference on Mechatronics and Intelligent control, ICMIC 2024

作者： Lu, Yanchun Yang, Hongqi Lei, Ting Pan, Yong CEPREI Guangzhou510610 China Key Laboratory of Industrial Equipment Quality Big Data MIIT Guangzhou510610 China Guangdong Provincial Engineering Technology Research Center for Quality Big Data of High-end Equipment Guangzhou510610 China

ISBN: (数字)9781510686847

ISBN: (纸本)9781510686830

In order to solve the problems such as high maintenance cost and difficult spare parts optimization of the complex electronic information system, considering advantages of the generalized stochastic Petri Net (GSPN) in characterization and analysis of dynamic change process of complex system, the process and method of spare parts optimization based on Monte Carlo simulation are studied to achieve the best balance between the rate of mission success and the cost of maintenance. © 2025 SPIE.

关键词： Stochastic systems

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HeterSim: Enable Flexible Simulation for Heterogeneous Distributed Deep Learning Platform

HeterSim: Enable Flexible Simulation for Heterogeneous Distr...

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2024 International conference on Mechatronics and Intelligent control, ICMIC 2024

作者： Tang, Yinan Zhang, Hongwei Wang, Li Guo, Zhenhua Zhao, Yaqian Li, Rengang IEIT SYSTEM Co. Ltd. Beijing China

ISBN: (数字)9781510686847

ISBN: (纸本)9781510686830

Distributed deep learning has become an essential technique for accelerating deep learning, but its performance is often influenced by the heterogeneous computing nodes and heterogeneous communication networks within the distributed deep learning platform. Due to the high costs of practical deployment and running of distributed deep learning, it is almost impossible for researchers to optimize the training strategy of distributed deep learning tasks in real-world environments. In this paper, we propose HeterSim, a simulator specifically designed for heterogeneous distributed deep learning platforms. HeterSim enables flexible configuration of computing node performance and network connections, and supports to define and simulate distributed deep learning workloads using graph-based representations. HeterSim also allows for the modification of communication strategies in the distributed deep learning process, thereby assisting researchers in validating their designs for distributed deep learning. We verify the feasibility and flexibility of HeterSim, by generating a simulation platform at the scale of millions of nodes, and successfully simulate the distributed deep learning process of Resnet50. We aim to provide HeterSim as a flexible and user-friendly simulator for researchers, targeting heterogeneous distributed deep learning platforms, and helping researchers evaluate and optimize the strategy of distributed deep learning tasks at a lower cost. © 2025 SPIE.

关键词： Computer simulations Switches Deep learning Education and training data modeling modeling Computation time Computer architecture Manufacturing Mathematical modeling

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18th International KES conference on Agents and Multi-Agent Systems: Technologies and Applications, KES-AMSTA 2024

18th International KES Conference on Agents and Multi-Agent ...

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18th International KES conference on Agents and Multi-Agent Systems: Technologies and Applications, KES-AMSTA 2024

ISBN: (纸本)9789819764686

The proceedings contain 34 papers. The special focus in this conference is on Agents and Multi-Agent Systems: Technologies and Applications. The topics include: Fair Path Generation for Formation control Combining Ant Colony and Particle Swarm Optimizations;preference Definition in a Multi-agent System Approach for User-Centric Internet of Things Smart Environments;AI-Driven Nitrogen Stress Management in Cereal Crops via Drone Technology;agent-Based Simulation for Withdrawal of Energy-Inefficient Housing;resource Limitations of Business process Simulations: Literature Study;data Augmentation for Business process Alignment: Proof of Concept and Experimental Design;smart Scheduling in Urban Traffic: A Multi-Agent System for Dynamic Vanpooling;analysis of the Impact on Area Prices Using Propensity Score Matching, Considering the Proportions of Photovoltaic and Thermal Power Generation Simultaneously;consideration of Building a Simulator to Evaluate Methods to Maximize the Effectiveness of Advertising to Households;Human-AI-Collaboration SECI Model: The Knowledge Management Model of the Experts’ Tacit Knowledges with Augmented LLM-Based AI;modeling Agent Awareness After Hierarchical Managerial Training;development of An Application for Extracting Needs Related to Actual Gas Use Using Text Mining;Impact of Intelligent Systems in the Home Office on Employee Satisfaction—Lessons Learned from the COVID-19 Pandemic;agile Methodologies in Software Development: A Study of Effective Management Strategies for Companies in the Digital Era;predictive analysis of Cyclical Sales data;EMG Signal Classification Using Machine Learning for Augmentative Assistance in Cerebral Palsy;wellnessWave—Platform for the Digitization of the Romanian Public Medical System;TRIAGE Predictive Model Based on Artificial Neural Networks and Deep Learning;platform for Automated Assessment of Obstetric Ultrasounds, Using Machine Learning;identification of Fonts in Unstructured Environments Through Deep Lea

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Investigating the effects of spatial heterogeneity of multi-source profile soil moisture on spatial-temporal processes of high-resolution floods

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JOURNAL OF HYDROLOGY 2025年 652卷

作者： Yang, Han Zhang, Xiaoqi Yuan, Zhe Hong, Xiaofeng Yao, Liqiang Zhang, Xiuping Changjiang River Sci Res Inst Water Resources Dept Wuhan 430010 Peoples R China Changjiang River Sci Res Inst Hubei Key Lab Water Resources & Ecoenvironm Sci Wuhan 430010 Peoples R China Jiangxi Acad Water Sci & Engn Nanchang 330029 Peoples R China

Reliable spatial-temporal simulation and forecast of flood are crucial for accurate flood control. Profile soil moisture (PSM) is a key intermediate variable in rainfall-runoff transformation, its spatial heterogeneity affects the spatial-temporal processes of floods. However, soil moisture data in the current flood modeling researches are only the intermediately simulated values that lack spatial validation, how spatial heterogeneity in soil moisture affects high-resolution flood processes is still unclear. In contrast, soil moisture data derived from satellites are spatial observed values that can better represent real spatial distribution. This study is first to incorporate satellite-based data and hydrological modeled data to identify the effects of different spatial patterns of profile soil moisture on spatial-temporal processes of floods at 1 km x 1 km resolution. The distributed hydrological model (DDRM) and the European Space Agency Climate Change Initiative (ESA CCI) products are chosen to provide different PSM spatial patterns, under which, the DDRM is used to investigate corresponding spatial-temporal processes of floods. Four modeling scenarios (two DDRM-only scenarios and two assimilation scenarios) in two humid and one semi-arid catchments are set to see the different effects, and the spatial-temporal statistical analysis and the semi-variogram method are used to identify the spatial heterogeneity. Results indicate that both PSM and runoff show strong spatial heterogeneity with the values of C/(C0 + C) in the semi-variogram method higher than 0.8;for different periods, the decrease of spatial heterogeneity in PSM corresponds to the decrease of spatial heterogeneity in runoff;for different scenarios, soil moisture storage capacity (SMC) affects spatial heterogeneity of runoff more in the semi-arid catchment, and the change of sensitive parameters of spatial soil moisture is the main driver to change the spatial heterogeneity of runoff. The findings of t

关键词： Profile soil moisture Spatial heterogeneity Satellite products Distributed hydrological model Flood spatial-temporal process

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