Статті в журналах: "Scalable modeling and control"

1

Voice, Thomas. "STOCHASTICALLY SCALABLE FLOW CONTROL." Probability in the Engineering and Informational Sciences 23, no. 4 (July 14, 2009): 675–98. http://dx.doi.org/10.1017/s0269964809990076.

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Recent advances in the mathematical analysis of flow control have prompted the creation of the Scalable TCP (STCP) and Exponential RED (E-RED) algorithms. These are designed to be scalable under the popular deterministic delay stability modeling framework. In this article, we analyze stochastic models of STCP and STCP combined with E-RED link behavior. We find that under certain plausible network conditions, these probabilistic models also exhibit scalable behavior. In particular, we derive parameter choice schemes for which the equilibrium coefficients of variation of flow rates are bounded, however large, fast, or complex the network. Our model is shown to exhibit behavior similar to the mean field convergence that has recently been observed in TCP.

2

Zengin, Ahmet. "Modeling discrete event scalable network systems." Information Sciences 181, no. 5 (March 2011): 1028–43. http://dx.doi.org/10.1016/j.ins.2010.10.023.

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Chernyi, Sergei G., Aleksei V. Vyngra, and Bogdan P. Novak. "Physical modeling of an automated ship’s list control system." Journal of Intelligent & Fuzzy Systems 39, no. 6 (December 4, 2020): 8399–408. http://dx.doi.org/10.3233/jifs-189158.

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In order to implement and demonstrate all the processes associated with the real stability trial system on vessels, a ship’s model was made. The developed model consists of electrical and hardware parts. It is concluded that the model is applicable for the study of issues of automatic control of the ship’s list, simulating various loading options. Scalable loading studies of various types and sizes of cargo were carried out. The results of the study showed the correct operation of the model according to a specified algorithm. To work with the microcontroller and to code, the mathematical modeling environment Matlab/Simulink was used. The results of the study showed that the created control system is able to secure the vessel during various types of loading operations, speed up the loading process, thus reducing the time spent at the port stay and save port costs.

4

Kim, Byungju, Dongha Lee, Jinoh Oh, and Hwanjo Yu. "Scalable disk-based topic modeling for memory limited devices." Information Sciences 516 (April 2020): 353–69. http://dx.doi.org/10.1016/j.ins.2019.12.058.

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5

Yin, Hang, Anastasia Varava, and Danica Kragic. "Modeling, learning, perception, and control methods for deformable object manipulation." Science Robotics 6, no. 54 (May 26, 2021): eabd8803. http://dx.doi.org/10.1126/scirobotics.abd8803.

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Perceiving and handling deformable objects is an integral part of everyday life for humans. Automating tasks such as food handling, garment sorting, or assistive dressing requires open problems of modeling, perceiving, planning, and control to be solved. Recent advances in data-driven approaches, together with classical control and planning, can provide viable solutions to these open challenges. In addition, with the development of better simulation environments, we can generate and study scenarios that allow for benchmarking of various approaches and gain better understanding of what theoretical developments need to be made and how practical systems can be implemented and evaluated to provide flexible, scalable, and robust solutions. To this end, we survey more than 100 relevant studies in this area and use it as the basis to discuss open problems. We adopt a learning perspective to unify the discussion over analytical and data-driven approaches, addressing how to use and integrate model priors and task data in perceiving and manipulating a variety of deformable objects.

6

Gómez, Abel, Xabier Mendialdua, Konstantinos Barmpis, Gábor Bergmann, Jordi Cabot, Xabier de Carlos, Csaba Debreceni, Antonio Garmendia, Dimitrios S. Kolovos, and Juan de Lara. "Scalable modeling technologies in the wild: an experience report on wind turbines control applications development." Software and Systems Modeling 19, no. 5 (January 22, 2020): 1229–61. http://dx.doi.org/10.1007/s10270-020-00776-8.

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Rocha, André M., Pedro Casau, and Rita Cunha. "A Control Algorithm for Early Wildfire Detection Using Aerial Sensor Networks: Modeling and Simulation." Drones 6, no. 2 (February 11, 2022): 44. http://dx.doi.org/10.3390/drones6020044.

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This work presents an algorithm for an Aerial Sensor Network (ASN) composed of fixed-wing Unmanned Aerial Vehicles (UAVs) that performs surveillance and detects the early signs of a wildfire in a given territory. The main goal is to cover a given area while prioritizing areas of higher fire hazard risk. The proposed algorithm is scalable to any number of aircraft and can use any kind of fire hazard risk map as long as it contains bounded and nonnegative values. Two different dynamical models associated with the movement of fixed-wing UAVs are proposed, tested, and compared through simulations. Lastly, we propose a workflow to size the ASN in order to maximize the probability of detection of wildfires for a particular risk profile.

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Vermulst, Bas J. D., Jorge L. Duarte, Elena A. Lomonova, and Korneel G. E. Wijnands. "Scalable multi‐port active‐bridge converters: modelling and optimised control." IET Power Electronics 10, no. 1 (January 2017): 80–91. http://dx.doi.org/10.1049/iet-pel.2016.0191.

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Yang, Jingyu, Wen Shi, Huanjing Yue, Kun Li, Jian Ma, and Chunping Hou. "Spatiotemporally scalable matrix recovery for background modeling and moving object detection." Signal Processing 168 (March 2020): 107362. http://dx.doi.org/10.1016/j.sigpro.2019.107362.

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Wydrowski, B., L. L. H. Andrew, and M. Zukerman. "MaxNet: a congestion control architecture for scalable networks." IEEE Communications Letters 7, no. 10 (October 2003): 511–13. http://dx.doi.org/10.1109/lcomm.2003.818888.

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11

Abrar O. Alkhamisi and Fathy Alboraei, Abrar O. Alkhamisi and Fathy Alboraei. "Privacy-aware Decentralized and Scalable Access Control Management for IoT Environment." journal of king abdulaziz university computing and information technology sciences 8, no. 1 (April 4, 2019): 71–84. http://dx.doi.org/10.4197/comp.8-1.7.

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In recent years, the Internet of Things (IoT) plays a vital role in our daily activities .Owing to the increased number of vulnerabilities on the IoT devices, security becomes critical in the untrustworthy IoT environment. Access control is one of the top security concerns, however, implementing the traditional access control mechanisms in the resource-constrained nature of the IoT devices is a challenging task. With the emergence of blockchain technology, several recent research works have focused on the adoption of blockchain in IoT to resolve the security concerns. Despite, integrating the blockchain in the resource-constrained IoT context is difficult. To overcome these obstacles, the proposed work presents a privacy-aware IoT security architecture to ensure the access control based on Smart contract for resource-constrained and distributed IoT devices. The design of the proposed architecture incorporates three main components such as the contextual blockchain gateway, decentralized revocation manager, and non-interactive zero-knowledge proof based validation. By modeling the contextual blockchain gateway, the proposed architecture ensures the dynamic authentication and authorization based on the contextual information and access policies. Instead of integrating the blockchain technology into resource-constrained IoT devices, the smart contract-based distributed access control system with the contextual blockchain gateway provides the scalable solution. With the association of decentralized revocation manager in the smart contract, it prevents the resource access from the unauthorized users by dynamically generating and updating the revoked user list of all the nodes in the smart contract. Moreover, the proposed architecture employs the non-interactive zeroknowledge proof cryptographic protocol to ensure the transaction privacy within the smart contract. Consequently, it maintains the trade-off between the transparency and privacy while ensuring the security for the distributed IoT environment.

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Ali, Ahmed Hussein, and Abdelfatah Kouidere. "Fuzzy Graph Modeling and Clustering Analysis of Nonlinear Dynamical Systems." Babylonian Journal of Mathematics 2023 (April 20, 2023): 18–22. http://dx.doi.org/10.58496/bjm/2023/004.

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Analyzing stability and designing control strategies for interconnected nonlinear dynamical systems poses mathematical challenges due to combinatorial growth in complexity. This paper develops a methodology integrating fuzzy graph theory with spectral clustering techniques to enable tractable certification of stability properties. Fuzzy similarity relations between state variables model imprecise couplings within the nonlinear dynamics. Representing these relations through graph adjacency matrices facilitates partitioning strongly connected states using spectral algorithms. Stability of the overall fuzzy state graph is inferred from the spectral radii of decoupled fuzzy subgraphs. The graph-theoretic abstraction provides a coarse-grained lens into nonlinear stability properties while circumventing computational barriers. The fuzzy graph modeling and spectral partitioning pipeline ultimately streamlines control synthesis targeting local clustered subdynamics. Case studies on power network stabilization, swarm navigation, and process operations showcase scalable applications to high-dimensional complex systems. The integrated fuzzy graph and spectral clustering approach provides a systematic toolkit for analysis and control of heavily interconnected nonlinear dynamical systems across engineering domains.

13

Barrett-Snyder, Kieran, Susan Lane, Nathan Lazarus, W. Alberts, and Brendan Hanrahan. "Printing a Pacinian Corpuscle: Modeling and Performance." Micromachines 12, no. 5 (May 18, 2021): 574. http://dx.doi.org/10.3390/mi12050574.

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The Pacinian corpuscle is a highly sensitive mammalian sensor cell that exhibits a unique band-pass sensitivity to vibrations. The cell achieves this band-pass response through the use of 20 to 70 elastic layers entrapping layers of viscous fluid. This paper develops and explores a scalable mechanical model of the Pacinian corpuscle and uses the model to predict the response of synthetic corpuscles, which could be the basis for future vibration sensors. The −3dB point of the biological cell is accurately mimicked using the geometries and materials available with off-the-shelf 3D printers. The artificial corpuscles here are constructed using uncured photoresist within structures printed in a commercial stereolithography (SLA) 3D printer, allowing the creation of trapped fluid layers analogous to the biological cell. Multi-layer artificial Pacinian corpuscles are vibration tested over the range of 20–3000 Hz and the response is in good agreement with the model.

14

Xiao, Qiang, Zhuang Zhi Han, and Hong Wei Zhang. "Signal Simulation of Target Tracking System of Fire-Control Radar Based on HLA." Advanced Materials Research 926-930 (May 2014): 1831–35. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.1831.

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.Target tracking is not only an important operation mode of fire-control radar, but also the primary task of the fire-control system. Firstly, scalable and reusable signal-level target tracking simulation system of fire-control radar based on HLA is developed. Then starting from the signal-level simulation model, by antenna module, receiver and signal processing module, filtering and prediction module, control system modules being organically combined, target tracking system modeling and simulation is completed. The simulation result indicates that the simulation system can carry out the dynamical process of target tracking effectively, it is of some reference value for the research on training simulation system design of fire-control radar and electronic warfare system evaluation .

15

Wang, Chen, Xu Wu, Ziyu Xie, and Tomasz Kozlowski. "Scalable Inverse Uncertainty Quantification by Hierarchical Bayesian Modeling and Variational Inference." Energies 16, no. 22 (November 20, 2023): 7664. http://dx.doi.org/10.3390/en16227664.

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Inverse Uncertainty Quantification (IUQ) has gained increasing attention in the field of nuclear engineering, especially nuclear thermal-hydraulics (TH), where it serves as an important tool for quantifying the uncertainties in the physical model parameters (PMPs) while making the model predictions consistent with the experimental data. In this paper, we present an extension to an existing Bayesian inference-based IUQ methodology by employing a hierarchical Bayesian model and variational inference (VI), and apply this novel framework to a real-world nuclear TH scenario. The proposed approach leverages a hierarchical model to encapsulate group-level behaviors inherent to the PMPs, thereby mitigating existing challenges posed by the high variability of PMPs under diverse experimental conditions and the potential overfitting issues due to unknown model discrepancies or outliers. To accommodate computational scalability and efficiency, we utilize VI to enable the framework to be used in applications with a large number of variables or datasets. The efficacy of the proposed method is evaluated against a previous study where a No-U-Turn-Sampler was used in a Bayesian hierarchical model. We illustrate the performance comparisons of the proposed framework through a synthetic data example and an applied case in nuclear TH. Our findings reveal that the presented approach not only delivers accurate and efficient IUQ without the need for manual tuning, but also offers a promising way for scaling to larger, more complex nuclear TH experimental datasets.

16

Qiu, Rui, Hao Bai, Ruotian Yao, Chengxi Liu, Min Xu, Qi Chen, and Weichen Yang. "A Data–Physics-Driven Modeling Approach of Key Equipment for Large-Scale Distribution Network Simulation." Electronics 13, no. 9 (April 25, 2024): 1663. http://dx.doi.org/10.3390/electronics13091663.

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Fueled by pressing global climate concerns, the integration of large-scale renewable distributed generation sources, including distributed wind power and photovoltaics, along with electricity substitution loads into the distribution network has been accelerated to diminish carbon emissions. This shift introduces significant challenges and necessitates the advanced operation and control of distribution systems to accommodate these changes effectively. Against this backdrop, there is a growing expectation for an open and scalable central control mode, equipped with compatible interfaces, to offer a visionary development platform for the grid. This platform is anticipated to meet the evolving needs of future distribution system development, ensuring adaptability and forward compatibility. The aforementioned platform requires open, scalable, and interface-compatible models of key distribution network equipment as its foundation. To address the challenges presented, this paper proposes a data–physics-driven modeling approach for automating simulations in distribution systems. This method employs a simplified and standardized system of linear differential equations with undetermined coefficients to capture the common physical characteristics of specific device types. The models designed through this approach are notably open, allowing for real-time data to refine undetermined coefficients and accurately depict the dynamic behavior of equipment over various periods. Their scalability also stands out, rendering them apt for large-scale distribution network simulations. The paper elaborates on models for distributed photovoltaic, wind turbine, energy storage, and electric vehicle, and demonstrates their application within an IEEE-33 node distribution network topology built on Python.

17

Nansai, Shunsuke, Rajesh Elara Mohan, Ning Tan, Nicolas Rojas, and Masami Iwase. "Dynamic Modeling and Nonlinear Position Control of a Quadruped Robot with Theo Jansen Linkage Mechanisms and a Single Actuator." Journal of Robotics 2015 (2015): 1–15. http://dx.doi.org/10.1155/2015/315673.

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The Theo Jansen mechanism is gaining widespread popularity among the legged robotics community due to its scalable design, energy efficiency, low payload-to-machine-load ratio, bioinspired locomotion, and deterministic foot trajectory. In this paper, we perform for the first time the dynamic modeling and analysis on a four-legged robot driven by a single actuator and composed of Theo Jansen mechanisms. The projection method is applied to derive the equations of motion of this complex mechanical system and a position control strategy based on energy is proposed. Numerical simulations validate the efficacy of the designed controller, thus setting a theoretical basis for further investigations on Theo Jansen based quadruped robots.

18

Avila, Raudel, Chenhang Li, Yeguang Xue, John A. Rogers, and Yonggang Huang. "Modeling programmable drug delivery in bioelectronics with electrochemical actuation." Proceedings of the National Academy of Sciences 118, no. 11 (March 8, 2021): e2026405118. http://dx.doi.org/10.1073/pnas.2026405118.

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Drug delivery systems featuring electrochemical actuation represent an emerging class of biomedical technology with programmable volume/flowrate capabilities for localized delivery. Recent work establishes applications in neuroscience experiments involving small animals in the context of pharmacological response. However, for programmable delivery, the available flowrate control and delivery time models fail to consider key variables of the drug delivery system––microfluidic resistance and membrane stiffness. Here we establish an analytical model that accounts for the missing variables and provides a scalable understanding of each variable influence in the physics of delivery process (i.e., maximum flowrate, delivery time). This analytical model accounts for the key parameters––initial environmental pressure, initial volume, microfluidic resistance, flexible membrane, current, and temperature––to control the delivery and bypasses numerical simulations allowing faster system optimization for different in vivo experiments. We show that the delivery process is controlled by three nondimensional parameters, and the volume/flowrate results from the proposed analytical model agree with the numerical results and experiments. These results have relevance to the many emerging applications of programmable delivery in clinical studies within the neuroscience and broader biomedical communities.

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Kherbouche, Meriem, Galena Pisoni, and Bálint Molnár. "Model to Program and Blockchain Approaches for Business Processes and Workflows in Finance." Applied System Innovation 5, no. 1 (January 4, 2022): 10. http://dx.doi.org/10.3390/asi5010010.

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Business process modeling and verification have become an essential way to control and assure organizational evolution. We overview the opportunities for the application of blockchain in Business Process Management and Modeling in Finance and we focus on in-depth analysis of claim process in insurance as a use case. We investigate the utilization of blockchain technology for model checking of Workflow, Business Processes to ensure consistency, integrity, and security in a dynamically changing business environment. We create a UML profile for the blockchain, then we combine it with a UML activity diagram followed by a verification using Petri nets to guarantee a distributed computing system and scalable with mutable data. Our paper creates a unified picture of the approaches towards business processes modeling used in the financial industry organized around the set of premises intending to develop a future research agenda for blockchain business process modeling, specifically for the financial industry domain.

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Schild, Axel, Alexander Rose, Martin Grotjahn, and Bennet Luck. "A modular framework for optimal scheduling of industrial processes." at - Automatisierungstechnik 70, no. 1 (January 1, 2022): 31–37. http://dx.doi.org/10.1515/auto-2021-0131.

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Abstract This paper proposes an extended Petri net formalism as a suitable language for composing optimal scheduling problems of industrial production processes with real and binary decision variables. The proposed approach is modular and scalable, as the overall process dynamics and constraints can be collected by parsing of all atomic elements of the net graph. To conclude, we demonstrate the use of this framework for modeling the moulding sand preparation process of a real foundry plant.

21

Woo-Seop Rhee, Jun-Hwa Lee, and Sang-Ha Kim. "Scalable qDPMsub 2 mechanism: admission control for differentiated service networks." IEEE Communications Letters 7, no. 9 (September 2003): 454–56. http://dx.doi.org/10.1109/lcomm.2003.814719.

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22

Laurén, Mika, Giota Goswami, Anna Tupitsina, Suraj Jaiswal, Tuomo Lindh, and Jussi Sopanen. "General-Purpose and Scalable Internal-Combustion Engine Model for Energy-Efficiency Studies." Machines 10, no. 1 (December 30, 2021): 26. http://dx.doi.org/10.3390/machines10010026.

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Hybrid powertrains that combine electric machines and internal-combustion engines offer substantial opportunities to increase the energy efficiency and minimize the exhaust emissions of vehicles and nonroad working machines. Due to the wide range of applications of such powertrains, simulation tools are used to evaluate and compare the energy efficiency of hybrid powertrains for application-specific working cycles in virtual environments. Therefore, the accurate modeling of the powertrain components of a hybrid system is important. This paper presents an agile calculation tool that can generate realistic fuel consumption data of a scalable diesel engine. This method utilizes a simple efficiency model of the combustion and crank train friction model to generate the fuel consumption map in the operating area of a typical diesel engine. The model parameters are calibrated to produce accurate fuel consumption data in the initial phase of system-level simulations. The proposed method is also validated by using three real engine datasets, and the comparison of results is presented.

23

Zhang, Qingyang. "Testing Differential Gene Networks under Nonparanormal Graphical Models with False Discovery Rate Control." Genes 11, no. 2 (February 5, 2020): 167. http://dx.doi.org/10.3390/genes11020167.

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The nonparanormal graphical model has emerged as an important tool for modeling dependency structure between variables because it is flexible to non-Gaussian data while maintaining the good interpretability and computational convenience of Gaussian graphical models. In this paper, we consider the problem of detecting differential substructure between two nonparanormal graphical models with false discovery rate control. We construct a new statistic based on a truncated estimator of the unknown transformation functions, together with a bias-corrected sample covariance. Furthermore, we show that the new test statistic converges to the same distribution as its oracle counterpart does. Both synthetic data and real cancer genomic data are used to illustrate the promise of the new method. Our proposed testing framework is simple and scalable, facilitating its applications to large-scale data. The computational pipeline has been implemented in the R package DNetFinder, which is freely available through the Comprehensive R Archive Network.

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Pauk, Jan Niklas, Janani Raju Palanisamy, Julian Kager, Krisztina Koczka, Gerald Berghammer, Christoph Herwig, and Lukas Veiter. "Advances in monitoring and control of refolding kinetics combining PAT and modeling." Applied Microbiology and Biotechnology 105, no. 6 (February 17, 2021): 2243–60. http://dx.doi.org/10.1007/s00253-021-11151-y.

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Abstract Overexpression of recombinant proteins in Escherichia coli results in misfolded and non-active protein aggregates in the cytoplasm, so-called inclusion bodies (IB). In recent years, a change in the mindset regarding IBs could be observed: IBs are no longer considered an unwanted waste product, but a valid alternative to produce a product with high yield, purity, and stability in short process times. However, solubilization of IBs and subsequent refolding is necessary to obtain a correctly folded and active product. This protein refolding process is a crucial downstream unit operation—commonly done as a dilution in batch or fed-batch mode. Drawbacks of the state-of-the-art include the following: the large volume of buffers and capacities of refolding tanks, issues with uniform mixing, challenging analytics at low protein concentrations, reaction kinetics in non-usable aggregates, and generally low re-folding yields. There is no generic platform procedure available and a lack of robust control strategies. The introduction of Quality by Design (QbD) is the method-of-choice to provide a controlled and reproducible refolding environment. However, reliable online monitoring techniques to describe the refolding kinetics in real-time are scarce. In our view, only monitoring and control of re-folding kinetics can ensure a productive, scalable, and versatile platform technology for re-folding processes. For this review, we screened the current literature for a combination of online process analytical technology (PAT) and modeling techniques to ensure a controlled refolding process. Based on our research, we propose an integrated approach based on the idea that all aspects that cannot be monitored directly are estimated via digital twins and used in real-time for process control. Key points • Monitoring and a thorough understanding of refolding kinetics are essential for model-based control of refolding processes. • The introduction of Quality by Design combining Process Analytical Technology and modeling ensures a robust platform for inclusion body refolding.

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Jin, Zhao, Jie Zhang, Shuyuan Wang, and Bingda Zhang. "Component-Oriented Modeling Method for Real-Time Simulation of Power Systems." Energies 16, no. 6 (March 15, 2023): 2731. http://dx.doi.org/10.3390/en16062731.

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This paper proposes a component-oriented modeling method for power system simulation, which optimizes the modeling process of the FPGA-based real-time digital simulator (FRTDS) to enhance its computational efficiency. In this paper, a component modeling method for various types of elements in the power system is presented, which makes the modeling process in FRTDS more user-friendly and highly scalable. By applying the concepts of combination and reconstruction of components to electrical components, the component-oriented modeling method becomes better suited for combined elements with fixed connection modes and elements that require online model replacement in the power system. Utilizing the characteristics of component-oriented modeling, the variable declaration structure and node elimination strategy in the simulation script are optimized, enabling the simulation script to fit better with the hardware structure of FRTDS. Additionally, a substation is simulated in FRTDS with a simulation step size of 50 µs, thus verifying the correctness of the component-oriented modeling method and its ability to improve the computational power of FRTDS.

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Rafique, Samina, M. Najam-ul-Islam, M. Shafique, and A. Mahmood. "Neuro-fuzzy control of sit-to-stand motion using head position tracking." Measurement and Control 53, no. 7-8 (July 15, 2020): 1342–53. http://dx.doi.org/10.1177/0020294020938079.

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Based on the clinical evidence that head position measured by the multisensory system contributes to motion control, this study suggests a biomechanical human-central nervous system modeling and control framework for sit-to-stand motion synthesis. Motivated by the evidence for a task-oriented encoding of motion by the central nervous system, we propose a framework to synthesize and control sit-to-stand motion using only head position trajectory in the high-level-task-control environment. First, we design a generalized analytical framework comprising a human biomechanical model and an adaptive neuro-fuzzy inference system to emulate central nervous system. We introduce task-space training algorithm for adaptive neuro-fuzzy inference system training. The adaptive neuro-fuzzy inference system controller is optimized in the number of membership functions and training cycles to avoid over-fitting. Next, we develop custom human models based on anthropometric data of real subjects. Using the weighting coefficient method, we estimate body segment parameter. The subject-specific body segment parameter values are used (1) to scale human model for real subjects and (2) in task-space training to train custom adaptive neuro-fuzzy inference system controllers. To validate our modeling and control scheme, we perform extensive motion capture experiments of sit-to-stand transfer by real subjects. We compare the synthesized and experimental motions using kinematic analyses. Our analytical modeling-control scheme proves to be scalable to real subjects’ body segment parameter and the task-space training algorithm provides a means to customize adaptive neuro-fuzzy inference system efficiently. The customized adaptive neuro-fuzzy inference system gives 68%–98% improvement over general adaptive neuro-fuzzy inference system. This study has a broader scope in the fields of rehabilitation, humanoid robotics, and virtual characters’ motion planning based on high-level-task-control scheme.

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Iglesias, Ramon, Federico Rossi, Rick Zhang, and Marco Pavone. "A BCMP network approach to modeling and controlling autonomous mobility-on-demand systems." International Journal of Robotics Research 38, no. 2-3 (June 28, 2018): 357–74. http://dx.doi.org/10.1177/0278364918780335.

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In this paper we present a queuing network approach to the problem of routing and rebalancing a fleet of self-driving vehicles providing on-demand mobility within a capacitated road network. We refer to such systems as autonomous mobility-on-demand (AMoD) systems. We first cast an AMoD system into a closed, multi-class Baskett–Chandy–Muntz–Palacios (BCMP) queuing network model capable of capturing the passenger arrival process, traffic, the state-of-charge of electric vehicles, and the availability of vehicles at the stations. Second, we propose a scalable method for the synthesis of routing and charging policies, with performance guarantees in the limit of large fleet sizes. Third, we explore the applicability of our theoretical results on a case study of Manhattan. Collectively, this paper provides a unifying framework for the analysis and control of AMoD systems, which provides a large set of modeling options (e.g. the inclusion of road capacities and charging constraints), and subsumes earlier Jackson and network flow models.

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Choi, Sun-O., and Jongbae Kim. "Smart Black Box DVR System in IT-Based Vehicle Emergency Rescue Environment." International Journal of Software Innovation 10, no. 1 (January 1, 2022): 1–10. http://dx.doi.org/10.4018/ijsi.309961.

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In this paper, the driving habits and patterns are analyzed by automatically recognizing vehicle accidents and recording event data when dangerous situations occur, applying connected car service through IT technology. In addition, SBDS designs the highly scalable modeling that reproduces videos which are recorded before and after accidents. SBDS provides emergency rescue and traffic information services by receiving IoT sensor data connected to have an embedded system in the vehicle and notifying the accident location and video information to the control center, using wireless network service even when the vehicle is dormant. In addition, it is possible to implement a wireless e-Call service by interlocking ECU information and vehicle sensor data in case an emergency occurs.

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Adnan Hussain, Hafiz, Zulkefli Mansor, Zarina Shukur, and Uzma Jafar. "Ether-IoT: A Realtime Lightweight and Scalable Blockchain-Enabled Cache Algorithm for IoT Access Control." Computers, Materials & Continua 75, no. 2 (2023): 3797–815. http://dx.doi.org/10.32604/cmc.2023.034671.

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Kolen, Sonja, Stefan Dähling, Timo Isermann, and Antonello Monti. "Enabling the Analysis of Emergent Behavior in Future Electrical Distribution Systems Using Agent-Based Modeling and Simulation." Complexity 2018 (2018): 1–16. http://dx.doi.org/10.1155/2018/3469325.

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In future electrical distribution systems, component heterogeneity and their cyber-physical interactions through electrical lines and communication lead to emergent system behavior. As the distribution systems represent the largest part of an energy system with respect to the number of nodes and components, large-scale studies of their emergent behavior are vital for the development of decentralized control strategies. This paper presents and evaluates DistAIX, a novel agent-based modeling and simulation tool to conduct such studies. The major novelty is a parallelization of the entire model—including the power system, communication system, control, and all interactions—using processes instead of threads. Thereby, a distribution of the simulation to multiple computing nodes with a distributed memory architecture becomes possible. This makes DistAIX scalable and allows the inclusion of as many processing units in the simulation as desired. The scalability of DistAIX is demonstrated by simulations of large-scale scenarios. Additionally, the capability of observing emergent behavior is demonstrated for an exemplary distribution grid with a large number of interacting components.

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LŐRINCZ, ANDRÁS, GYÖRGY HÉVÍZI, and CSABA SZEPESVÁRI. "OCKHAM'S RAZOR MODELING OF THE MATRISOME CHANNELS OF THE BASAL GANGLIA THALAMOCORTICAL LOOPS." International Journal of Neural Systems 11, no. 02 (April 2001): 125–43. http://dx.doi.org/10.1142/s0129065701000412.

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A functional model of the basal ganglia-thalamocortical (BTC) loops is described. In our modeling effort, we try to minimize the complexity of our starting hypotheses. For that reason, we call this type of modeling Ockham's razor modeling. We have the additional constraint that the starting assumptions should not contradict experimental findings about the brain. First assumption: The brain lacks direct representation of paths but represents directions (called speed fields in control theory). Then control should be concerned with speed-field tracking (SFT). Second assumption: Control signals are delivered upon differencing in competing parallel channels of the BTC loops. This is modeled by extending SFT with differencing that gives rise to the robust Static and Dynamic State (SDS) feedback-controlling scheme. Third assumption: Control signals are expressed in terms of a gelatinous medium surrounding the limbs. This is modeled by expressing parameters of motion in parameters of the external space. We show that corollaries of the model fit properties of the BTC loops. The SDS provides proper identification of motion related neuronal groups of the putamen. Local minima arise during the controlling process that works in external space. The model explains the presence of parallel channels as the means to avoiding such local minima. Stability conditions of the SDS predict that the initial phase of learning is mostly concerned with selection of sign for the inverse dynamics. The model provides a scalable controller. State description in external space instead of configurational space reduces the dimensionality problem. Falsifying experiment is suggested. Computer experiments demonstrate the feasibility of the approach. We argue that the resulting scheme has a straightforward connectionist representation exhibiting population coding and Hebbian learning properties.

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Díaz, Álvaro, and Héctor Kaschel. "Scalable Electronic Health Record Management System Using a Dual-Channel Blockchain Hyperledger Fabric." Systems 11, no. 7 (July 6, 2023): 346. http://dx.doi.org/10.3390/systems11070346.

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Communication and information technologies have accelerated the implementation of electronic medical records, but at the same time, have put patient privacy, information security and health data at risk. An alternative to address the problem of security and privacy of medical data is the use of blockchain. Scalability has become one of the biggest challenges facing the development of blockchain-based electronic health records (EHRs). The purpose of this article is to implement and test a scalable blockchain-based EHR management system. For this reason, we present a scalable blockchain-based EHR management architecture. In this paper, we propose an EHR management model based on entities and user roles, adapt, and then implement with Hyperledger Fabric in a two-channel configuration. We develop a prototype in Fabric using a one-and two-channel configuration. We then designed and conducted an experiment to verify the performance of the proposed scheme in terms of scalability improvement. This scalable blockchain-based EHR management solution, such as the Hyperledger Fabric platform, offers a viable alternative to address scalability issues, as well as to protect patient's privacy and the security of their medical data.

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Hussain, Ishfaq, Shahid Ali Murtza, Muhammad Yasir Qadri, Martin Fleury, and Nadia N. Qadri. "Scalable, energy-aware system modeling and application-specific reconfiguration of MPSocs with a type-2 fuzzy logic system." Computers & Electrical Engineering 74 (March 2019): 292–304. http://dx.doi.org/10.1016/j.compeleceng.2019.01.015.

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Sun, Penghao, Julong Lan, Junfei Li, Jianpeng Zhang, Yuxiang Hu, and Zehua Guo. "A Scalable Deep Reinforcement Learning Approach for Traffic Engineering Based on Link Control." IEEE Communications Letters 25, no. 1 (January 2021): 171–75. http://dx.doi.org/10.1109/lcomm.2020.3022064.

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Zhao, Yining, and Alan Wood. "Duplication problem in treaty systems: Causes and solutions." Computer Science and Information Systems 11, no. 1 (2014): 291–308. http://dx.doi.org/10.2298/csis130204009z.

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Capabilities are a more scalable and adaptive access control approach compared with the conventional approaches such as ACLs, due to their being held and managed by users or agents in systems, but not the middleware. This feature makes capabilities more suitable in distributed environments that have dynamic populations. Treaties have been proposed to enhance the capability approach by introducing sequences of actions, such that treaties can capture characteristics of behaviours, and provide finer control over accesses. However there is a new problem brought by the behaviour modeling of treaties which is called duplication problem, which concerns preventing users from gaining unauthorized behaviour by duplicating treaties. In this paper we provide the formal definitions of treaty operations, and discuss the causes of the duplication problem, and how treaty operations can affect this. We also propose three models of treaty systems that aim to solve the duplication problem, and evaluating their performance and scalability.

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Musgrove, Hannah B., Amirus Saleheen, Jonathan M. Zatorski, Abhinav Arneja, Chance John Luckey, and Rebecca R. Pompano. "A Scalable, Modular Degasser for Passive In-Line Removal of Bubbles from Biomicrofluidic Devices." Micromachines 14, no. 2 (February 11, 2023): 435. http://dx.doi.org/10.3390/mi14020435.

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Bubbles are a common cause of microfluidic malfunction, as they can perturb the fluid flow within the micro-sized features of a device. Since gas bubbles form easily within warm cell culture reagents, degassing is often necessary for biomicrofluidic systems. However, fabrication of a microscale degasser that can be used modularly with pre-existing chips may be cumbersome or challenging, especially for labs not equipped for traditional microfabrication, and current commercial options can be expensive. Here, we address the need for an affordable, accessible bubble trap that can be used in-line for continuous perfusion of organs-on-chip and other microfluidic cultures. We converted a previously described, manually fabricated PDMS degasser to allow scaled up, reproducible manufacturing by commercial machining or fused deposition modeling (FDM) 3D printing. After optimization, the machined and 3D printed degassers were found to be stable for >2 weeks under constant perfusion, without leaks. With a ~140 µL chamber volume, trapping capacity was extrapolated to allow for ~5–20 weeks of degassing depending on the rate of bubble formation. The degassers were biocompatible for use with cell culture, and they successfully prevented bubbles from reaching a downstream microfluidic device. Both degasser materials showed little to no leaching. The machined degasser did not absorb reagents, while the FDM printed degasser absorbed a small amount, and both maintained fluidic integrity from 1 µL/min to >1 mL/min of pressure-driven flow. Thus, these degassers can be fabricated in bulk and allow for long-term, efficient bubble removal in a simple microfluidic perfusion set-up.

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Sahar, Guia Sana, Kazar Okba, Laouid Abdelkader, Yagoub Mohammed Amine, Reinhardt Euler, Ahcène Bounceur, and Mohammad Hammoudeh. "An Optimized Scalable Multi-ant Colony System for Multi-depot Vehicle Routing Problems Using a Reactive Multi-agent System." WSEAS TRANSACTIONS ON SYSTEMS 20 (August 10, 2021): 249–59. http://dx.doi.org/10.37394/23202.2021.20.28.

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The multi-depot vehicle routing problem is a variant of the vehicle routing problem that tries to minimize the total cost of providing the service from several depots to satisfy several client demands. This paper presents a multi-ant colony system to solve the multi-depot vehicle routing problem using a reactive agent-based approach. This approach is designed to effectively solve the problem, in which each reactive agent is inspired by modeling the behavior of the ant. We define two types of reactive agents whose behavior differs in the use of two kinds of pheromone trail. In order to refer to the two phases of the execution process, i.e., the assignment phase and the routing phase, every reactive agent cooperates with others to provide a scalable solution for the overall problem. The solution of the multi-depot vehicle routing problem is beneficial and helpful for many real applications. The performance evaluation of the proposed approach is done using instances from the literature, and the results obtained demonstrate good performance when compared with other approaches

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Kull, Tobias, Bernd Zeilmann, and Gerhard Fischerauer. "Modular Model Composition for Rapid Implementations of Embedded Economic Model Predictive Control in Microgrids." Applied Sciences 11, no. 22 (November 11, 2021): 10602. http://dx.doi.org/10.3390/app112210602.

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Economic model predictive control in microgrids combined with dynamic pricing of grid electricity is a promising technique to make the power system more flexible. However, to date, each individual microgrid requires major efforts for the mathematical modelling, the implementation on embedded devices, and the qualification of the control. In this work, a field-suitable generalised linear microgrid model is presented. This scalable model is instantiated on field-typical hardware and in a modular way, so that a class of various microgrids can be easily controlled. This significantly reduces the modelling effort during commissioning, decreases the necessary qualification of commissioning staff, and allows for the easy integration of additional microgrid devices during operation. An exemplary model, derived from an existing production facility microgrid, is instantiated, and the characteristics of the results are analysed.

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Chuang, Tzu-Der, Yu-Jen Chen, Yi-Hau Chen, Shao-Yi Chien, and Liang-Gee Chen. "Architecture Design of Fine Grain Quality Scalable Encoder with CABAC for H.264/AVC Scalable Extension." Journal of Signal Processing Systems 60, no. 3 (June 9, 2009): 363–75. http://dx.doi.org/10.1007/s11265-009-0378-8.

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40

Lévy, Loup-Noé, Jérémie Bosom, Guillaume Guerard, Soufian Ben Amor, Marc Bui, and Hai Tran. "DevOps Model Appproach for Monitoring Smart Energy Systems." Energies 15, no. 15 (July 29, 2022): 5516. http://dx.doi.org/10.3390/en15155516.

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Energy systems are often socio-technical complex systems that are facing new challenges regarding technological and environmental changes. Because of their complex nature, they cannot be approached solely through analytical modeling, hence the inefficiency of most classical modeling approaches. In this article, a Hybrid Approach based on both systemic and analytical modeling is presented and applied to a case study. From this novel approach, a model—the Multi-Institution Building Energy System—is presented. It allowed us to highlight and detail the need for greater governance of energy systems. The socio-technical solutions identified to answer the issues of governance (Accuracy, Reliability and Fairness) were DevOps methodology and the use of Distributed Microservices Architecture. Based on this framework, the design of a Decision Support System assuring and exploiting state-of-the-art scalable tools for data management and machine learning factories is described in this article. Moreover, we wish to set up the conceptual basis necessary for the design of a generic theoretical framework of optimization applicable to complex socio-technical systems in the context of the management of a shared resource.

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Raman, Ritu. "Biofabrication of Living Actuators." Annual Review of Biomedical Engineering 26, no. 1 (July 3, 2024): 223–45. http://dx.doi.org/10.1146/annurev-bioeng-110122-013805.

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The impact of tissue engineering has extended beyond a traditional focus in medicine to the rapidly growing realm of biohybrid robotics. Leveraging living actuators as functional components in machines has been a central focus of this field, generating a range of compelling demonstrations of robots capable of muscle-powered swimming, walking, pumping, gripping, and even computation. In this review, we highlight key advances in fabricating tissue-scale cardiac and skeletal muscle actuators for a range of functional applications. We discuss areas for future growth including scalable manufacturing, integrated feedback control, and predictive modeling and also propose methods for ensuring inclusive and bioethics-focused pedagogy in this emerging discipline. We hope this review motivates the next generation of biomedical engineers to advance rational design and practical use of living machines for applications ranging from telesurgery to manufacturing to on- and off-world exploration.

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Wai, Benny, and Winston Zhou. "Designing and Implementing Real-Time Bus Time Predictions using Artificial Intelligence." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 11 (September 10, 2020): 636–48. http://dx.doi.org/10.1177/0361198120947715.

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Managing expectations is vital to ensuring commuter satisfaction with their public transportation service. When customers are given an estimated time for their bus and must wait way longer, they lose a sense of control over their commute and become frustrated. In this paper, we present a novel machine learning (ML) modeling approach in which we train and implement specialized models for every single segment of travel time and stop dwell time in our system to capture its uniqueness. The features for training the models include simple calendar and weather data. Most papers assume ideal operational conditions but in practice that’s almost never the case. Here, we combine our ML modeling approach with a flexible production-tested algorithm to combine model-generated dwell and travel time (or run time) predictions to produce predicted bus departure times. This algorithm is designed to handle real transit agency challenges like missing models (including those caused by changes to schedules and routes), timing points, and partially traveled segments. We also provide a reference architecture of how this algorithm can be brought to life in a scalable and cost-effective manner.

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Yao, Donggang, and Byung Kim. "Scaling Issues in Miniaturization of Injection Molded Parts." Journal of Manufacturing Science and Engineering 126, no. 4 (November 1, 2004): 733–39. http://dx.doi.org/10.1115/1.1813479.

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Miniaturization of injection molded parts causes changes in the relative contribution of relevant design and process parameters. As a result, scaling-related size effects occur. Size effects can be either of the first order or of the second order. First-order size effects can be predicted using standard modeling, while second order ones cannot. This paper deals with first-order size effects encountered in injection molding miniaturized parts. Through the scaling analysis of the heat transfer and flow process in injection molding, the size effects on the change of molding characteristics including viscous heating, freezing time, capillary force effect, and moldability were identified. Strategies were consequently proposed to alleviate or eliminate the scaling-related molding difficulties in molding ultrathin-wall parts and microparts. Particularly, a scalable filling process was presented, with experimental verification.

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Bradhurst, Richard, Danny Spring, Mark Stanaway, James Milner, and Tom Kompas. "A generalised and scalable framework for modelling incursions, surveillance and control of plant and environmental pests." Environmental Modelling & Software 139 (May 2021): 105004. http://dx.doi.org/10.1016/j.envsoft.2021.105004.

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45

Brinkschulte, Uwe. "Scalable Online Feasibility Tests for Admission Control in a Java Real-Time System." Real-Time Systems 32, no. 3 (February 10, 2006): 175–95. http://dx.doi.org/10.1007/s11241-005-4679-0.

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46

BONASTRE, O. M., S. NEVILLE, and C. E. PALAU. "MULTICAST CONGESTION CONTROL SRMSH APPROACH USING COMMUNICATING REAL-TIME STATE MACHINES." International Journal of Bifurcation and Chaos 20, no. 09 (September 2010): 2965–73. http://dx.doi.org/10.1142/s0218127410027519.

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New real-time applications frequently involve timing constraints related to accurate services from communication protocols. Concretely, real-time communication protocols utilize timers to implement these constraints between system event occurrences. In this context, the study of congestion control for Internet reliable multicast is at present an active research field related to real-time protocols. In this paper, the authors present an innovative real-time transport protocol named Scalable Reliable Multicast Stair Hybrid (SRMSH) as new hybrid multiple layer mechanism for multicast congestion control providing detection and recovery loss. This work is focused on formal specification of SRMSH approach using Communicating Real-Time State Machines as a formal method. Besides, SRMSH validation is presented within a formal proof framework in order to check the functional safety and liveness properties. As a result, authors outline a dynamical system framework in order to model behavior of their presented solution.

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Omidshafiei, Shayegan, Ali–Akbar Agha–Mohammadi, Christopher Amato, Shih–Yuan Liu, Jonathan P. How, and John Vian. "Decentralized control of multi-robot partially observable Markov decision processes using belief space macro-actions." International Journal of Robotics Research 36, no. 2 (February 2017): 231–58. http://dx.doi.org/10.1177/0278364917692864.

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This work focuses on solving general multi-robot planning problems in continuous spaces with partial observability given a high-level domain description. Decentralized Partially Observable Markov Decision Processes (Dec-POMDPs) are general models for multi-robot coordination problems. However, representing and solving Dec-POMDPs is often intractable for large problems. This work extends the Dec-POMDP model to the Decentralized Partially Observable Semi-Markov Decision Process (Dec-POSMDP) to take advantage of the high-level representations that are natural for multi-robot problems and to facilitate scalable solutions to large discrete and continuous problems. The Dec-POSMDP formulation uses task macro-actions created from lower-level local actions that allow for asynchronous decision-making by the robots, which is crucial in multi-robot domains. This transformation from Dec-POMDPs to Dec-POSMDPs with a finite set of automatically-generated macro-actions allows use of efficient discrete-space search algorithms to solve them. The paper presents algorithms for solving Dec-POSMDPs, which are more scalable than previous methods since they can incorporate closed-loop belief space macro-actions in planning. These macro-actions are automatically constructed to produce robust solutions. The proposed algorithms are then evaluated on a complex multi-robot package delivery problem under uncertainty, showing that our approach can naturally represent realistic problems and provide high-quality solutions for large-scale problems.

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Barrera, Gabriele, Federico Scaglione, Federica Celegato, Marco Coïsson, Paola Tiberto, and Paola Rizzi. "Electroless Cobalt Deposition on Dealloyed Nanoporous Gold Substrate: A Versatile Technique to Control Morphological and Magnetic Properties." Nanomaterials 13, no. 3 (January 26, 2023): 494. http://dx.doi.org/10.3390/nano13030494.

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The connection of multidisciplinary and versatile techniques capable of depositing and modeling thin films in multistep complex fabrication processes offers different perspectives and additional degrees of freedom in the realization of patterned magnetic materials whose peculiar physical properties meet the specific needs of several applications. In this work, a fast and cost-effective dealloying process is combined with a fast, low-cost, scalable electroless deposition technique to realize hybrid magnetic heterostructures. The gold nanoporous surface obtained by the dealloying of an Au40Si20Cu28Ag7Pd5 ribbon is used as a nanostructured substrate for the electrodeposition of cobalt. In the first steps of the deposition, the Co atoms fill the gold pores and arrange themselves into a patterned thin film with harder magnetic properties; then they continue their growth into an upper layer with softer magnetic properties. The structural characterization of the hybrid magnetic heterostructures is performed using an X-ray diffraction technique and energy-dispersive X-ray spectroscopy, while the morphology of the samples as a function of the electrodeposition time is characterized by images taken in top and cross-section view using scanning electron microscopy. Then, the structural and morphologic features are correlated with the room-temperature magnetic properties deduced from an alternating-gradient magnetometer’s measurements of the hysteresis loop and first order reversal curves.

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Qiu, Rixuan, Xue Xue, Mingliang Chen, Jinkun Zheng, Sitong Jing, and Yuancheng Li. "A Fine-grained Dynamic Access Control Method for Power IoT Based on Kformer." Infocommunications journal 14, no. 4 (2022): 79–85. http://dx.doi.org/10.36244/icj.2022.4.11.

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The existing static ABAC(Attribute-Based Access Control) model cannot fully meet the increasingly complex, dynamic and scalable demands of the power grid. At the same time, its versatility and flexibility bring high costs. Additionally, the increasing complexity of organizational systems and the need for federated access to their resources make implementing and managing access control more challenging. This paper proposes a fine-grained dynamic access control method based on Kformer to automate authorization management tasks. We use Kformer, which filters and integrates external knowledge through feed-forward layers in Transformer. Then, we use BERT(Bidirectional Encoder Representations from Transformer) to perform feature extraction on the input fused text, extract the implied attribute-authority relationship from the log records and external documents, and finally, perform sequence modeling on the extracted attribute features and input the obtained results. The final authorization result is obtained by classification through the softmax function in the final fully connected layer. The authorization management of the user’s request to the object is dynamically completed. Finally, using the access data of the grid information system to evaluate the method proposed by us, the experimental results show that the model can continuously monitor the access behavior of users inside the grid information system, change the access rights of entities and adjust the policy in real-time, and carry out dynamic access authorization. At the same time, the accuracy of the generated access control policy can reach 87.73%.

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Dimonie, Doina, Nicoleta Dragomir, and Rusandica Stoica. "Attempts to Diminish the Drawbacks of Polylactic Acid Designed for 3D/4D Printing Technology-Fused Deposition Modeling." Materiale Plastice 58, no. 1 (April 5, 2021): 142–53. http://dx.doi.org/10.37358/mp.21.1.5454.

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In order to improve thermal behavior and dimensional strability of polylactic acid (PLA) designed both for 3D and 4D printing technology-fused deposition modeling (FDM) using a scalable procedure, the polymer was melt compounded with additives which control the morphology by crystallization and/or reinforcing. Using the formulations which provide polylactic acid (PLA) improved thermo-mechanical properties and desired dimensional stability, the new materials were shaped, on a laboratory line, as filaments for printing technology. The selected compounds were than scaled up on a 50 kg/h compounding line into granules which prove to have good shapability as filaments for printing technology (1.85 +/- 0.05 mm diameter, required ovality, good appearance and smooth surface) and performed properly at 3D printing. The obtained results proved that functional properties of PLA can be improved by various methods so that, depending on the reached performances, the new material can be converted through printing technology into items for performance applications. The novelty of the article is related to the fact that it identifies a modifying solution for controlling the morphology of a type of PLA designed for 3D printing that already has an advanced crystallinity.

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