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Artykuły w czasopismach na temat „Computer Simulation Models -Network Forming Liquids”

Autor: Grafiati
Data publikacji: 7 września 2023
Data aktualizacji: 31 lipca 2025

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Sprawdź 18 najlepszych artykułów w czasopismach naukowych na temat „Computer Simulation Models -Network Forming Liquids”.

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1

Stolyarchuk, Maxim, Marina Botnari, and Luba Tchertanov. "Vitamin K Epoxide Reductase Complex–Protein Disulphide Isomerase Assemblies in the Thiol–Disulphide Exchange Reactions: Portrayal of Precursor-to-Successor Complexes." International Journal of Molecular Sciences 25, no. 8 (2024): 4135. http://dx.doi.org/10.3390/ijms25084135.

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The human Vitamin K Epoxide Reductase Complex (hVKORC1), a key enzyme that converts vitamin K into the form necessary for blood clotting, requires for its activation the reducing equivalents supplied by its redox partner through thiol–disulphide exchange reactions. The functionally related molecular complexes assembled during this process have never been described, except for a proposed de novo model of a ‘precursor’ complex of hVKORC1 associated with protein disulphide isomerase (PDI). Using numerical approaches (in silico modelling and molecular dynamics simulation), we generated alternative
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Yang, Xing, Zhen Qian, Xuhong Zhang, et al. "Cascading-Failures Effect on Heterogeneous Internet of Things Systems under Targeted Selective Attack." Security and Communication Networks 2022 (March 21, 2022): 1–13. http://dx.doi.org/10.1155/2022/6848156.

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With the rapid development of the Internet of Things (IoT), the physical system and the network space are further deeply integrated, forming a larger-scale IoT heterogeneous fusion system. The attack mode considered in the security mechanism research of traditional large-scale complex systems is relatively simple; only simple attack types such as random attacks on physical systems or network systems are considered. In addition, existing attack modalities such as selectivity, locality, and distribution cannot fully consider the characteristics of security threats in the IoT system. In this pape
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Pantalé, Olivier. "Development and Implementation of an ANN Based Flow Law for Numerical Simulations of Thermo-Mechanical Processes at High Temperatures in FEM Software." Algorithms 16, no. 1 (2023): 56. http://dx.doi.org/10.3390/a16010056.

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Numerical methods based on finite element (FE) have proven their efficiency for many years in the thermomechanical simulation of forming processes. Nevertheless, the application of these methods to new materials requires the identification and implementation of constitutive and flow laws within FE codes, which sometimes pose problems, particularly because of the strongly non-linear character of the behavior of these materials. Computational techniques based on machine learning and artificial neural networks are becoming more and more important in the development of these models and help the FE
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Shenoy, Vighnesh, Prathvi Shenoy, and Santhosh Krishnan Venkata. "Accurate Liquid Level Measurement with Minimal Error: A Chaotic Observer Approach." Computation 12, no. 2 (2024): 29. http://dx.doi.org/10.3390/computation12020029.

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This paper delves into precisely measuring liquid levels using a specific methodology with diverse real-world applications such as process optimization, quality control, fault detection and diagnosis, etc. It demonstrates the process of liquid level measurement by employing a chaotic observer, which senses multiple variables within a system. A three-dimensional computational fluid dynamics (CFD) model is meticulously created using ANSYS to explore the laminar flow characteristics of liquids comprehensively. The methodology integrates the system identification technique to formulate a third-ord
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Fedorovich, Oleg, Igor Chepkov, Mikhail Lukhanin, Yurii Pronchakov, Kseniia Rybka, and Yuliia Leshchenko. "Modeling of supply logistics and training of military personnel for the successful use of weapons in a combat area." RADIOELECTRONIC AND COMPUTER SYSTEMS, no. 3 (October 4, 2022): 33–46. http://dx.doi.org/10.32620/reks.2022.3.03.

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The problem of multivariate nature is formed and solved, which is related to the modeling of logistics actions regarding various military equipment and weapons that enter the zone of military conflict. The relevance of the research is related to the comprehensive solution to the problem of the logistical nature of the supply and mastering modern various weapons by the military to create parity of forces in the military conflict zone. The current study creates a complex of logistic methods and models that allow analyzing training of the military, supply of weapons, ammunition and spare parts to
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Merayo, David, Alvaro Rodríguez-Prieto, and Ana María Camacho. "Prediction of Mechanical Properties by Artificial Neural Networks to Characterize the Plastic Behavior of Aluminum Alloys." Materials 13, no. 22 (2020): 5227. http://dx.doi.org/10.3390/ma13225227.

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In metal forming, the plastic behavior of metallic alloys is directly related to their formability, and it has been traditionally characterized by simplified models of the flow curves, especially in the analysis by finite element simulation and analytical methods. Tools based on artificial neural networks have shown high potential for predicting the behavior and properties of industrial components. Aluminum alloys are among the most broadly used materials in challenging industries such as aerospace, automotive, or food packaging. In this study, a computer-aided tool is developed to predict two
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Terentyev, Alexey, Alexey Marusin, Sergey Evtyukov, Aleksandr Marusin, Anastasia Shevtsova, and Vladimir Zelenov. "Analytical Model for Information Flow Management in Intelligent Transport Systems." Mathematics 11, no. 15 (2023): 3371. http://dx.doi.org/10.3390/math11153371.

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The performance of this study involves the use of the zoning method based on the principle of the hierarchical relationship between probabilities. This paper proposes an analytical model allowing for the design of information and analysis platforms in intelligent transport systems. The proposed model uses a synthesis of methods for managing complex systems’ structural dynamics and solves the problem of achieving the optimal balance between the information situations existing for the object and the subject under analysis. A series of principles are formulated that govern the mathematical modeli
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Dubanov, A. A. "Methods for Applying Matrices when Creating Models of Group Pursuit." Advanced Engineering Research 23, no. 2 (2023): 191–202. http://dx.doi.org/10.23947/2687-1653-2023-23-2-191-202.

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Introduction. It is obvious that in the near future, the issues of equipping moving robotic systems with autonomous control elements will remain relevant. This requires the development of models of group pursuit. Note that optimization in pursuit tasks is reduced to the construction of optimal trajectories (shortest trajectories, trajectories with differential constraints, fuel consumption indicators). At the same time, the aspects of automated distribution by goals in group pursuit were not considered. To fill this gap, the presented piece of research has been carried out. Its result should b
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Vegge, Tejs. "(Invited) BIG-MAP - Going BIG to MAP an Accelerated Path to Sustainable Battery Materials Discovery." ECS Meeting Abstracts MA2024-02, no. 3 (2024): 342. https://doi.org/10.1149/ma2024-023342mtgabs.

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The large-scale European research initiative, the Battery Interface Genome – Materials Acceleration Platform (BIG-MAP), set forth to reinvent the ways we invent batteries in Europe by developing a distributed framework for accelerated autonomous discovery of sustainable battery materials and interfaces. A central element in this process is the development of a closed-loop MAP infrastructure, where multiple and geographically distributed laboratories or tenants can work jointly using autonomous workflows to co-optimize materials properties. Here, we show an example using the Fast INtention-Agno
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Tao, Sichen, Yuki Todo, Zheng Tang, Bin Li, Zhiming Zhang, and Riku Inoue. "A Novel Artificial Visual System for Motion Direction Detection in Grayscale Images." Mathematics 10, no. 16 (2022): 2975. http://dx.doi.org/10.3390/math10162975.

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How specific features of the environment are represented in the mammalian brain is an important unexplained mystery in neuroscience. Visual information is considered to be captured most preferentially by the brain. As one of the visual information elements, motion direction in the receptive field is thought to be collected already at the retinal direction-selective ganglion cell (DSGC) layer. However, knowledge of direction-selective (DS) mechanisms in the retina has remained only at a cellular level, and there is a lack of complete direction-sensitivity understanding in the visual system. Pre
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11

Ivanov, S. V. "NEURO-FUZZY MODELING OF A DECISION SUPPORT SYSTEM BY A GROUP OF UNMANNED AERIAL VEHICLES UNDER THE INFLUENCE OF THE EXTERNAL ENVIRONMENT." Vestnik komp'iuternykh i informatsionnykh tekhnologii, no. 230 (August 2023): 19–33. http://dx.doi.org/10.14489/vkit.2023.08.pp.019-033.

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The work discusses the relevance and concept of building an intelligent decision support system based on the use of elements of the theory of fuzzy sets together with the technology of neural networks. The existing requirements for the intellectualization of the control system of a heterogeneous group of unmanned aerial vehicles force developers to switch to the use of artificial intelligence technologies that allow for the training of complex energy-consuming algorithms and ensure their self-organized functioning when solving tasks for their intended purpose. Due to the fact that the process
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12

Gaidamakin, N. А., N. I. Sinadsky, and P. V. Sushkov. "COMPLEX SIMULATION-STATISTICAL METHOD FOR SYNTHESIZING CONDITIONALLY REAL DATA ARRAYS BASED ON A STRUCTURAL-PARAMETRIC MODEL OF INTERACTION BETWEEN USERS OF INFORMATION AND TELECOMMUNICATION SERVICES." Journal of the Ural Federal District. Information security 20, no. 1 (2020): 12–23. http://dx.doi.org/10.14529/secur200102.

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The article presents a solution to the problem of synthesizing training tasks and data arrays when organizing a computer training platform for conducting practical exercises to investigate information security incidents. Two main stages of the synthesis of the background and situa-tional components of the conditionally real data arrays based on the structural-parametric model of interaction between users of information and telecommunication services are pro-posed: the formation of static and dynamic components. 14КОМПЛЕС НЫЙИ. ТОАИЦ-МЛИМПЧ К ЕЛЙИДЗ-ВЕИЛЛИУ МЙОДО Р 1Ь35Х / 2020Вступление в силу
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13

Wang, Yongliang, and Xin Zhang. "Dual bilinear cohesive zone model-based fluid-driven propagation of multiscale tensile and shear fractures in tight reservoir." Engineering Computations, November 1, 2022. http://dx.doi.org/10.1108/ec-01-2022-0013.

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PurposeHydrofracturing technology has been widely used in tight oil and gas reservoir exploitation, and the fracture network formed by fracturing is crucial to determining the resources recovery rate. Due to the complexity of fracture network induced by the random morphology and type of fluid-driven fractures, controlling and optimising its mechanisms is challenging. This paper aims to study the types of multiscale mode I/II fractures, the fluid-driven propagation of multiscale tensile and shear fractures need to be studied.Design/methodology/approachA dual bilinear cohesive zone model (CZM) b
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Ling, Shijia, Qiaoling Yi, Banru Lan, and Liangfang Liu. "Research progress of computer vision tasks based on deep learning and SAE network." Applied Mathematics and Nonlinear Sciences, April 10, 2023. http://dx.doi.org/10.2478/amns.2021.2.00271.

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Abstract In recent years, artificial intelligence has gradually become the core driving force of a new round of scientific and technological revolution and industrial transformation, and is exerting a profound impact on all aspects of human life. With the rapid development of Internet big data and high-performance parallel computing, relevant research in computer vision has made significant progress in the past few years, becoming one of the important application branches in the field of artificial intelligence. The exercise of image classification forming part of computer vision tasks involve
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15

Goswami, Yagyik, and Srikanth Sastry. "Liquid-liquid phase transition in deeply supercooled Stillinger-Weber silicon." PNAS Nexus, September 23, 2022. http://dx.doi.org/10.1093/pnasnexus/pgac204.

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Abstract The existence of a phase transition between two distinct liquid phases in single-component network-forming liquids (e.g., water, silica, silicon) has elicited considerable scientific interest. The challenge, both for experiments and simulations, is that the liquid-liquid phase transition occurs under deeply supercooled conditions, where crystallization occurs very rapidly. Thus, early evidence from numerical equation of state studies was challenged, with the argument that slow spontaneous crystallization had been misinterpreted as evidence of a second liquid state. Rigorous free energ
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Feng, Shuo, Huadong Fu, Huiyu Zhou, Yuan Wu, Zhaoping Lu, and Hongbiao Dong. "A general and transferable deep learning framework for predicting phase formation in materials." npj Computational Materials 7, no. 1 (2021). http://dx.doi.org/10.1038/s41524-020-00488-z.

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AbstractMachine learning has been widely exploited in developing new materials. However, challenges still exist: small dataset is common for most tasks; new datasets, special descriptors and specific models need to be built from scratch when facing a new task; knowledge cannot be readily transferred between independent models. In this paper we propose a general and transferable deep learning (GTDL) framework for predicting phase formation in materials. The proposed GTDL framework maps raw data to pseudo-images with some special 2-D structure, e.g., periodic table, automatically extracts featur
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Gao Yan-Li, Xu Wei-Nan, Zhou Jie, and Chen Shi-Ming. "Analysis of seepage behaviour in a binary two-layer coupled network." Acta Physica Sinica, 2024, 0. http://dx.doi.org/10.7498/aps.73.20240454.

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To Existing research on interdependent networks defines network functions either entirely on nodes or entirely on edges, meaning interdependence between nodes and nodes, or interdependence between edges and edges. However, the reality is not characterized solely by interdependence between individual elements' functionalities, meaning it is not entirely a single-element coupled network. There are cases where both nodes and edges depend on each other. Taking into account this realistic scenario, the paper proposes a binary interdependent network model with coupling between nodes and edges (BINNE
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Hossein, Jadidoleslamy. "DESIGNING A NOVEL APPROACH FOR FINGERPRINT BIOMETRIC DETECTION: BASED ON MINUTIAE EXTRACTION." December 28, 2012. https://doi.org/10.5121/ijbb.2012.2402.

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International Journal on Bioinformatics & Biosciences (IJBB) Vol.2, No.4, December 2012 DOI : 10.5121/ijbb.2012.2402 11 DESIGNING A NOVEL APPROACH FOR FINGERPRINT BIOMETRIC DETECTION: BASED ON MINUTIAE EXTRACTION Hossein Jadidoleslamy Information Technology Engineering Group, Department of Information Technology, Communications and Security, University of Malek Ashtar, Tehran, Iran tanha.hossein@gmail.com ABSTRACT People authentication based on fingerprint is one of the most important people authentication techniques which it used biology specifications. The main purpose of this paper is d
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