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Conformance Testing of Link 16 Message Standard based on ATC-Gen 4

Conformance Testing of Link 16 Message Standard based on ATC...

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4th IEEE International conference on Electronic Information and Communication Technology, ICEICT 2021

作者： Tian, Wanyong Chen, Chilian Zhao, Lulu 20th Institute Xi’an China

ISBN: (纸本)9781665432030

Message standard is the key factor of data link. It specifies the standardized message formats and rules for realizing tactical functions. the complexity of message standard including thousands of rules described in natural language which is prone to ambiguous interpretations poses great challenges in conformance testing. modeling and simulation (M&S) has been a core technology for conformance testing of message standard. In this paper, Automated Test Case Generator (ATC-Gen) which is initiated by Joint Interoperability Test Command (JITC) for Link 16 testing is studied. It greatly increases the simulation-based testing capabilities and automation of the testing processes. We discuss the ATC-Gen methodology and show the experiment results based on modeling and simulation (M&S) framework and Discrete Event system (DEVS) model. ©2021 IEEE

关键词： Discrete event simulation

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Effective Searching for the Honeybee Queen in a Living Colony

Effective Searching for the Honeybee Queen in a Living Colon...

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IEEE International conference on Automation Science and Engineering (CASE)

作者： Jan Blaha Jan Mikula Tomáš Vintr Jiří Janota Jiří Ulrich Tomáš Rouček Fatemeh Rekabi-Bana Laurenz Alexander Fedotoff Martin Stefanec thomas Schmickl Farshad Arvin Miroslav Kulich Tomáš Krajník Faculty of Electrical Engineering Czech Technical University in Prague Czechia Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Czechia Computer Science Department Durham University United Kingdom Department of Zoology Artificial Life Lab Institute of Biology University of Graz Graz Austria

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

Despite the importance of honeybees as pollinators for the entire ecosystem and their recent decline threatening agricultural production, the dynamics of the living colony are not well understood. In our EU H2020 RoboRoyale project, we aim to support the pollination activity of the honeybees through robots interacting with the core element of the honeybee colony, the honeybee queen. In order to achieve that, we need to understand how the honeybee queen behaves and interacts with the surrounding worker bees. To gather the necessary data, we observe the queen with a moving camera, and occasionally, we instruct the system to perform selective observations elsewhere. In this paper, we deal with the problem of searching for the honeybee queen inside a living colony. We demonstrate that combining spatio-temporal models of queen presence with efficient search methods significantly decreases the time required to find her. this will minimize the chance of missing interesting data on the infrequent behaviors or queen-worker interactions, leading to a better understanding of the queen’s behavior over time. Moreover, a faster search for the queen allows the robot to leave her more frequently and gather more data in other areas of the honeybee colony.

关键词： Computer aided software engineering Automation Biological system modeling Ecosystems Robot vision systems Production Search problems Cameras Path planning Robots

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Cyber Twin-Enabled Real-Time AI Orchestration for Advanced IoT Security and Dynamic Software optimization

Cyber Twin-Enabled Real-Time AI Orchestration for Advanced I...

引用

Mobile Networks and Wireless Communications (ICMNWC), IEEE International conference on

作者： Krishna Chaitanya Sunkara Pareshwar Prasad Barmola Ravi K S Vishal Shukla Umang Soni Amol Sapatnekar Oracle Cloud Engineering Data Center Design & Modeling AL/ML Expert North Carolina USA Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun India Department of Mechanical Engineering Vidyavardhaka College of Engineering Mysuru India Department of Mechanical Engineering Ramdeobaba University Nagpur India Department of Electronics & Communication Engineering Faculty of Engineering and Technology Parul institute of Engineering and Technology Parul University Gujarat India Faculty of Law Symbiosis Law School Symbiosis International (Deemed University) Pune India

ISBN: (数字)9798331528348

ISBN: (纸本)9798331528355

the rapid expansion of Internet of things (IoT) ecosystems has increased the complexity and vulnerability of software systems, making them more susceptible to security breaches and performance inefficiencies. Traditional security and optimization techniques struggle to keep up with the dynamic nature of IoT networks. this calls for the development of advanced frameworks that can adapt in real-time to evolving threats and operational requirements. this paper introduces Cyber Twins, an AI-driven framework designed for real-time security and software optimization in IoT environments. Cyber Twins leverage artificial intelligence and digital twin technology to create dynamic cyber representations of physical IoT devices and software processes. the framework integrates reinforcement learning for adaptive optimization, convolutional neural networks (CNNs) for anomaly detection, and graph neural networks (GNNs) for real-time threat analysis. By continuously synchronizing with live IoT data, Cyber Twins enable proactive threat detection and autonomous system optimization, ensuring a secure and high-performing IoT ecosystem. the proposed framework combines Federated Learning (FL) for distributed intelligence and Reinforcement Learning (RL) for adaptive decision-making. Key advancements include (1) a 35% improvement in intrusion detection accuracy compared to traditional methods, (2) a 40% reduction in false positive rates, and (3) a 25% increase in dynamic software adaptation speed. Experiments conducted on a simulated IoT environment with 1,000 devices demonstrated scalability and resilience under varying network conditions. Additionally, the framework achieved a 20% decrease in latency during AI model updates and a 30% reduction in computational overhead, ensuring efficient resource utilization.

关键词： Ecosystems Reinforcement learning Software Real-time systems threat assessment Internet of things Security Artificial intelligence optimization Resilience

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A Linearized optimization Method for Distributed Generation Planning Studies

A Linearized Optimization Method for Distributed Generation ...

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20th IEEE International conference on Environment and Electrical Engineering (EEEIC) / 4th IEEE Industrial and Commercial Power systems Europe conference (I and CPS Europe)

作者： Ghofrani, Mahmoud Univ Washington Bothell Sch STEM Bothell WA 98011 USA

ISBN: (纸本)9781728174556

Utilizing renewable energy sources as distributed generation (DG) reduces the pollutant emissions of conventional fossil-fueled generation. Optimized planning is required to prevent serious technical issues resulting from poor implementation. this paper presents an optimization scheme which simplifies the problem by using linearization. Power flow equations are linearized at steady-state operating points, and sensitivity coefficients are calculated for constraints such as voltage and distribution system flow limits. Linear programming (LP) finds the optimal capacities of DG units. Compared to commonly used artificial intelligence (AI) techniques which are computationally expensive, the proposed method is more efficient for finding the optimal capacity of DGs in large distribution systems. the proposed framework is appropriate for planning applications in which efficiency and accuracy are prioritized.

关键词： Distributed generation distribution systems linearized power flow optimization planning renewable energy sensitivity analysis

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Impact of forecasting errors on microgrid optimal power management

Impact of forecasting errors on microgrid optimal power mana...

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20th IEEE International conference on Environment and Electrical Engineering (EEEIC) / 4th IEEE Industrial and Commercial Power systems Europe conference (I and CPS Europe)

作者： Macas, Martin Orlando, Sergio Costea, Stefan Novak, Petr Chumak, Oleksiy Kadera, Petr Kopejtko, Petr Czech Tech Univ Czech Inst Informat Robot & Cybernet Prague Czech Republic Eaton European Innovat Ctr Prague Czech Republic

ISBN: (数字)9781728174556

ISBN: (纸本)9781728174556

the paper presents a DC microgrid model and its power management system based on metaheuristical optimization of a rolling horizon. the crucial components of such a system are forecasts of photovoltaic production and load power. the paper experimentally demonstrates how the forecasting error affects power management in terms of increased operational costs and increased probability of constraints violation. It is demonstrated that the benefits of the optimized power scheduling decrease linearly with increasing mean absolute percentage error (MAPE) of load and photovoltaic production forecast. In our scenario, the state-of-charge constraints for electric vehicle battery were not affected by inaccurate forecasts, which is very important for the electric vehicle user's acceptance of the power management system.

关键词： microgrid power management forecast fore-casting error optimization rolling horizon DC

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Experimental Validation of a Dynamic Equivalent Model for Microgrids

Experimental Validation of a Dynamic Equivalent Model for Mi...

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20th IEEE International conference on Environment and Electrical Engineering (EEEIC) / 4th IEEE Industrial and Commercial Power systems Europe conference (I and CPS Europe)

作者： Conte, Francesco D'Agostino, Fabio Massucco, Stefano Silvestro, Federico Bossi, Claudio Cabiati, Mattia Univ Genoa DITEN Genoa Italy Ric Sul Sistema Energet RSE SpA Milan Italy

ISBN: (纸本)9781728174556

this paper presents the results of an experimental validation of an equivalent modeling for microgrids. the main goal is to represent, with a simplified model, the dynamic response of a microgrid, in terms of active and reactive power exchanges at the point of common coupling, to variations of voltage and frequency. A nonlinear equivalent model with operational constraints is proposed. An identification procedure is used to define model parameters. To validate the approach, a set of experimental tests have been carried out on a real LV microgrid considering different configurations. Results show the effectiveness of the proposed technique and applicability to dynamic simulations.

关键词： dynamic equivalents microgrids gray-box modeling system identification experimental results

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optimization of an Embedded Phase Change Material Cooling Strategy Using Machine Learning 20

Optimization of an Embedded Phase Change Material Cooling St...

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20th InterSociety conference on thermal and thermomechanical Phenomena in Electronic systems (Itherm)

作者： Bhatasana, Meghavin Marconnet, Amy Purdue Univ Sch Mech Engn W Lafayette IN 47907 USA

ISBN: (纸本)9781728185392

Phase change materials (PCMs) have been widely investigated to function as a thermal buffer, particularly for components experiencing transient power loads. PCMs absorb some of the heat generated during periods of high-power dissipation and can enable longer periods of use before throttling of the processor or shut-off is required to prevent damage. Many studies with PCMs have focused on the functionality of PCM-laden heat sinks and, although these studies demonstrated extensions in high power operating times before the system overheated, the thermal pathway between the PCM-laden heat sink and heat source prevents their effective use as the heat generation rates increase. this study explores the concept of integrating PCMs at or near the silicon chip level near the heat source. Machine learning algorithms generate optimized patterns for balancing high heat storage zones and high thermal conductivity pathways within the embedded cooling layer on the backside of the silicon die. Reductions in both the hotspot temperatures and fluctuations in the transient temperature response highlights the effectiveness of embedded cooling and the machine learning algorithms provide a robust, efficient method for optimizing performance.

关键词： Embedded Cooling Phase Change Materials Machine Learning

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the digital management system of the tangible culture heritage for enhancing historic building governance in Malang, Indonesia 20

The digital management system of the tangible culture herita...

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20th Sustainable, Environment and Architecture, SENVAR 2020

作者： Santosa, H. Yudono, A. Adhitama, M.S. Architecture Department Faculty of Engineering Universitas Brawijaya Indonesia Urban Regional Planning Department Faculty of Engineering Universitas Brawijaya Indonesia

the development of a digital management system to support historical building assets' management process based on public participation is the latest innovation in preservation, conservation, and restoration activities of historical buildings. In line with the importance of applying Good Governance principles in the 4.0 Industrial Revolution in Malang city government, it is essential to develop a Governance Digitalization system to support sustainable tourism in heritage tourism management. this study aims to establish a digital management framework system for Tangible Culture Heritage based on HBIM to manage historical building assets in Malang. this system focus on the cultural heritage assets of Malang City that represents the three developments in the Dutch Indies architectural style. the BIM capability implemented in historical buildings in Heritage Building Information modeling (HBIM) terminology can bring complexity and depth of information to historical buildings towards a sustainable lifecycle heritage management framework. this research implements the 3D modeling automatic reconstruction method (3D Laser scanner) processed with Building Information modeling (BIM) based software. the process consisted of 3 (three) stages: identifying and mapping Historical Landmark Buildings, developing 3D content models, and generating HBIM data viewer application. this study's results reveal that using 3D laser scanning technology can accelerate the recording process and object modeling of the HBIM library, offering high accuracy and efficiency in recording complex structures and architectural elements. the final result of HBIM modeling is translated into interactively present the 3D model and 2D documentation of Historic Building Information Models through the HBIM mobile data viewer. © Published under licence by IOP Publishing Ltd.

关键词： 3D modeling

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Optimal Rotor Stabilization in an Electromagnetic Suspension system Using Takagi-Sugeno Fuzzy Models 20th

Optimal Rotor Stabilization in an Electromagnetic Suspension...

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20th International conference on Mathematical modeling and Supercomputer Technologies, MMST 2020

作者： Mukhin, Aleksey V. Lobachevsky State University Nizhny Novgorod Russia

ISBN: (纸本)9783030787585

the paper presents the results of solving the problem of designing stabilizing output controllers for an electromagnetic suspension system based on the use of Takagi-Sugeno fuzzy models. Two major problems were considered: the construction of stabilizing controllers and the construction of optimal controllers based on the quadratic performance criterion. To calculate the controllers, an original nonlinear mathematical model of the plant was replaced by an equivalent fuzzy model, which is a set of linear subsystems. For the synthesis of control laws, the apparatus of linear matrix inequalities was used. the calculated controllers for the fuzzy system were substituted into the original nonlinear object. the results of the mathematical modeling showed that using Takagi-Sugeno fuzzy models, it is possible to construct both a stabilizing controller and an optimal controller based on a quadratic performance criterion. the calculated controllers ensured rotor stabilization in a fairly wide range of initial deviations, up to the maximum possible values. Based on obtained results, it can be concluded that the presented approach, realized on the use of Takagi-Sugeno fuzzy models, allows one to describe the rotor dynamics in an electromagnetic suspension system in a wide range of initial disturbances. © 2021, Springer Nature Switzerland AG.

关键词： Controllers

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Two-Stage Multi-time Scale Energy Management & Control framework for Home Area Power Network

Two-Stage Multi-time Scale Energy Management & Control frame...

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20th IEEE International conference on Environment and Electrical Engineering (EEEIC) / 4th IEEE Industrial and Commercial Power systems Europe conference (I and CPS Europe)

作者： Minhas, Daud Mustafa Frey, Georg Saarland Univ Chair Automat & Energy Syst Saarbrucken Germany

ISBN: (纸本)9781728174556

the working phenomenon of the Energy Management system (EMS) in a smart home revolves extensively around the availability of cheap energy sources and the flexibility of users' load demands. In this paper, we introduce a home EMS that manages the load following energy supply entities (ESEs). A day-ahead scheduler observes the decision signals for various ESEs that minimizes the net energy cost for a consumer. Furthermore, a real-time robust control strategy is adopted to eradicate the phenomenon of uncertainties in the system. the uncertainties arise due to the intermittent nature of solar energy source and changeable load demands. this paper incorporates two-stage scheduling and controlling mechanism that works both in off-line and on-line modes to handle a device schedule and guarantees the availability of power at any time. At the first stage, a mixed-integer linear programming based algorithm activates the cost-effective energy in-feed from various ESEs. Whereas, the second stage enforces the power quality by balancing load demands with energy supply in real-time. Moreover, we implement the optimal scheduling decisions in real-time by incorporating MATLAB/Simulink based physical models of various components of the power system.

关键词： Nano-grid energy management system energy optimization day-ahead scheduling real-time robust control physical modeling

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