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modeling of Thermal Processes in a Microcontroller system with the Use of Hybrid, Fractional Order Transfer Functions 21st

Modeling of Thermal Processes in a Microcontroller System wi...

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21st Polish Control conference, PCC 2023

作者： Oprzedkiewicz, Krzysztof Rosol, Maciej Mitkowski, Wojciech Department of Automatic Control and Robotics Faculty of Electrical Engineering Automatic Control Informatics and Biomedical Engineering AGH University of Science and Technology al. A Mickiewicza 30 Krakow30-059 Poland

ISBN: (纸本)9783031351693

In the paper the problem of modeling of thermal processes in microcontroller system is addressed. The proposed models allow to describe thermal processes during work of an evaluation system. The temperature in critical places of the system is measured using thermal camera. The proposed models have the form of hybrid transfer functions, containing both Integer Order (IO) and Fractional Order (FO) parts. The step responses of the proposed transfer functions are computed analytically. Results of experiments show that the proposed models are more accurate in the sense of Mean Square Error (MSE) cost function than typical transfer function models with delay. The proposed models can be applied to predict of overheating of microcotroller systems. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Microcontrollers

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modeling, optimization, and Musculoskeletal Simulation of Elbow-Wrist Exosuit

Modeling, Optimization, and Musculoskeletal Simulation of El...

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International conference on Advanced Robotics (ICAR)

作者： Ali KhalilianMotamed Bonab Daniele Leonardis Antonio Frisoli Domenico Chiaradia Department of Excellence in Robotics & AI Scuola Superiore Sant'Anna Institute of Mechanical Intelligence Pisa Italy

Exosuits present intriguing structural advantages compared to exoskeletons; nevertheless, accurately modeling and simulating their effectiveness when integrated with the musculoskeletal system of the user poses formidable challenges. As regards the upper limb, there are limited approaches and models in the literature that consider both the complexities of the musculoskeletal system and the optimization of the exosuit interface. In this work, we propose an extensive approach that considers both a mathematical model of a wrist-elbow exosuit, and simulations of a complex upper limb musculoskeletal system. The kinematic and dynamic model of the exosuit allows for the optimization of the anchor points, while the simulation provides information on muscular loading with and without assistance. In the presented results we have developed and validated personalized musculoskeletal models with kinematic, anthropometric, and electromyographic data we measured in a load-lifting task. The results of the simulations show the effectiveness of the optimized exosuit and reveal the impact of the exosuit at the level of the whole upper limb, and not limited to the actuated districts only.

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Predictive Optimal Dispatch for Islanded Distribution Grids considering Operating Reserve Constraints 21

Predictive Optimal Dispatch for Islanded Distribution Grids ...

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21st IEEE Mediterranean Electrotechnical conference (IEEE MELECON)

作者： Bruno, Sergio Giannoccaro, Giovanni Iurlaro, Cosimo La Scala, Massimo Menga, Marco Politecn Bari Dept Elect & Informat Engn Bari Italy

ISBN: (数字)9781665442800

ISBN: (纸本)9781665442800

In island distribution grids, the increase of renewable generation sources, whose output is stochastic in nature, implies that large amount of operating reserve must be guaranteed during the grid operation. In this paper, a methodology based on predictive optimal dispatch is proposed to optimize the use of energy resources taking into account operating reserve constraints. Reserve constraints are quantified through a probabilistic approach that takes into account the probabilistic distribution of forecasting errors. The methodology is applied to the distribution model of an actual Italian small island, supplied by a set of conventional diesel generators together with photovoltaic and storage resources. The performance of the proposed predictive approach is assessed considering the response of the system during different load and generation scenarios. The impacts of reserve provision is also studied considering the effect of an open-loop and a closed-loop control strategy.

关键词： Islanded microgrid model predictive control (MPC) optimal dispatch operating reserve optimization reserve constraints uncertainties

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21st CCF conference on Web Information systems and Applications in China, WISA 2024

21st CCF Conference on Web Information Systems and Applicati...

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21st CCF conference on Web Information systems and Applications in China, WISA 2024

ISBN: (纸本)9789819777068

The proceedings contain 50 papers. The special focus in this conference is on Web Information systems and Applications in China. The topics include: GTGNN: Global Graph and Taxonomy Tree for Graph Neural Network Session-Based Recommendation;dual Learning Model of Code Summary and Generation Based on Transformer;relation-Oriented Temporal Knowledge Graphs Completion Based on Recurrent Neural Network;MMPDRec: A Denoising Model for Knowledge Concepts Recommendation Using Metapaths;SPR: A Similar Projection Revisor for Complex Logical Reasoning over Knowledge Graphs;An Generative Entity Relation Extraction Model Based on UIE for Legal Text;uncertain Knowledge Graph Completion with Rule Mining;MAGAN: Mode Information and Attention-Based GAN for Realistic Time Series Data Synthesis;a study on Context-Matching-Based Joint Training for Chinese Coreference Resolution;DFCDR: Domain-Aware Feature Decoupling and Fusion for Cross-Domain Recommendation;two-stage Enhancement for Recommendation systems Based on Contrastive Learning;popularity-Aware Graph Neural Network with Global Context for Session-Based Recommendation;Enhancing Sentiment Analysis for Chinese Texts Using a BERT-Based Model with a Custom Attention Mechanism;contrastive Learning-Based Cross-Domain Data Augmentation for Aspect-Based Sentiment Analysis;a Dynamic Convergence Criterion for Fast K-means Computations;efficient p-Biclique Query on Large Bipartite Networks;high-Dimensional Nearest Neighbor Search-Based Blocking in Entity Resolution;top-k Collective Spatial Keyword Approximate Query;SMSRD: A streaming Graph Data Management system Based on Relational Database;PLIS: Persistent Learned Index for strings;dataset Construction for Fine-Grained Emotion Analysis in Catering Review Data;database Parameters Tuning via Bayesian optimization with Domain Knowledge;attribute Multiplex Network Graph Clustering: Joint Contrastive And High-Order Proximity;reliable Community Search over Dynamic Bipartite Graphs;a Hierarchica

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The Petroleum system of Offshore Somalia: A Potential Mega-Province 84

The Petroleum System of Offshore Somalia: A Potential Mega-P...

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84th EAGE Annual conference and Exhibition

作者： Pantano, J. Casey, E. Schofield, K. Coastline Exploration Ltd. U3 Explore

ISBN: (纸本)9781713884156

Offshore Eastern Africa emerged as a major new petroleum province through the second decade of the 21st century. A combination of Jurassic source rocks and Cretaceous and Tertiary clastic reservoirs came together to deliver world-class gas discoveries in the offshore basins of Kenya, Tanzania and Mozambique. While the same petroleum system clearly extended northwards into offshore Somalia, political instability in the Horn of Africa suppressed interest in exploration, although an extensive 2D seismic dataset was collected in the period 2014-16. The authors have used those data to generate a play-level analysis of the petroleum system on the Somali passive margin. A likely source interval in the Jurassic rift/sag sequence has been interpreted on good quality attribute-processed 2D seismic data and burial history/maturity modeling has shown that, unlike the equivalent interval to the south, across a large portion of the basin largely still within the oil window. © 2023 84th EAGE Annual conference and Exhibition. All rights reserved.

关键词： Seismology

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Bound Tightening Using Rolling-Horizon Decomposition for Neural Network Verification 21st

Bound Tightening Using Rolling-Horizon Decomposition for Neu...

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21st International conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR)

作者： Zhao, Haoruo Hijazi, Hassan Jones, Haydn Moore, Juston Tanneau, Mathieu Van Hentenryck, Pascal Georgia Inst Technol Atlanta GA 30308 USA Los Alamos Natl Lab Los Alamos NM 87545 USA Univ Penn Philadelphia PA 19104 USA

ISBN: (纸本)9783031606014;9783031605994

Neural network verification aims at providing formal guarantees on the output of trained neural networks, to ensure their robustness against adversarial examples and enable deployment in safety-critical applications. This paper introduces a new approach to neural network verification using a novel mixed-integer programming (MIP) rolling-horizon decomposition method. The algorithm leverages the layered structure of neural networks by employing optimization-based bound tightening (OBBT) on smaller sub-graphs of the original network in a rolling-horizon fashion and tightening the bounds in parallel. This strategy strikes a balance between achieving tighter bounds and ensuring the tractability of the underlying mixed-integer programs. Extensive numerical experiments, conducted on instances from the VNN-COMP benchmark library, demonstrate that the proposed approach yields significantly improved bounds compared to existing efficient bound propagation methods. Notably, the proposed method proves effective in solving open verification problems. Our code is built and released as part of the open-source mathematical modeling tool Gravity (https://***/ coin- or/Gravity), which is extended to support generic neural network models.

关键词： Neural Network Verification optimization-Based Bound Tightening Mixed-Integer Programming Decomposition

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Counterfactual and Semifactual Explanations in Abstract Argumentation: Formal Foundations, Complexity and Computation 21

Counterfactual and Semifactual Explanations in Abstract Argu...

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21st International conference on Principles of Knowledge Representation and Reasoning, KR 2024

作者： Alfano, Gianvincenzo Greco, Sergio Parisi, Francesco Trubitsyna, Irina Department of Informatics Modeling Electronics and System Engineering University of Calabria Italy

ISBN: (纸本)9781956792058

Explainable Artificial Intelligence and Formal Argumentation have received significant attention in recent years. Argumentation frameworks are useful for representing knowledge and reasoning on it. Counterfactual and semifactual explanations are interpretability techniques that provide insights into the outcome of a model by generating alternative hypothetical instances. While there has been important work on counterfactual and semifactual explanations for Machine Learning (ML) models, less attention has been devoted to these kinds of problems in argumentation. In this paper, we explore counterfactual and semifactual reasoning in abstract Argumentation Framework. We investigate the computational complexity of counterfactual- and semifactual-based reasoning problems, showing that they are generally harder than classical argumentation problems such as credulous and skeptical acceptance. Finally, we show that counterfactual and semifactual queries can be encoded in weak-constrained Argumentation Framework, and provide a computational strategy through ASP solvers. © 2024 Proceedings of the International conference on Knowledge Representation and Reasoning. All rights reserved.

关键词： Knowledge representation

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Explainable Recommendation system Based on Aspect-Based Sentiment Analysis 21

Explainable Recommendation System Based on Aspect-Based Sent...

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21st International Computer conference on Wavelet Active Media Technology and Information Processing, ICCWAMTIP 2024

作者： Xiaolong, Zhou Shijiao, Han Zhenze, Li School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China China Academy of Aerospace Science and Innovation Beijing China

ISBN: (纸本)9798331519254

At information age, the rapid increase of information caused Information Overload problem, which made recommendation system (RS) come into being and push forward the quick development. Nowadays RS has been widely used in human society. Meanwhile, RS also faces challenges like data sparsity and poor explainability. An effective way to address data sparsity challenge is to exploit content information (like review data) for modeling users and items. By further mining content information, deep relationship between user-item interactions can be uncovered and therefore the explanation for recommendation results can be provided. In order to fully mine the information in review data and make precise recommendation with corresponding explanation, a recommendation model for rating prediction task is proposed in this paper. It exploits aspect-based sentiment analysis related theory to mine review features, incorporates the modeling of user preference and item properties with fine-grained sentiment information, which solves problems that previous model has poor context feature extraction ability and the sentiment analysis results are lack of reliability. Extensive experiments show that this model outperforms baseline models in rating prediction task and can provide explanations for the rating prediction results in view of sentiment. © 2024 IEEE.

关键词： Prediction models

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Simulation and Analysis for 100kW standalone Hybrid Renewable Energy system

Simulation and Analysis for 100kW Standalone Hybrid Renewabl...

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IEEE IAS Global conference on Renewable Energy and Hydrogen Technologies (GlobConHT)

作者： Pandya, Bhavya Joshi, Siddharth Pandit Deendayal Energy Univ Dept Elect Engn Sch Energy Technol Gandhinagar 382426 Gujarat India PDPU SoET EED AP Gandhinagar 382426 Gujarat India APP Grp Energy Generat & Storage London England

ISBN: (纸本)9798350332117

Every day, environmental issues deteriorate further. The adoption of the industry 4.0 revolution, the use of renewable energy, advancements in control systems, and other 21st-century revolutions all call for a significant increase in power consumption. Including captive power facilities that can supply the local load is one way to address the requirement for electricity. A single renewable energy source frequently presents problems in terms of generating electricity due to the intermittent nature of renewables. Hybrid renewable energy systems are one of the most promising ways to meet the load demand. This paper focused on the modeling of large-scale hybrid renewable energy systems (HRES) with the incorporation of solar PV, wind energy conversion system (WECS), and battery energy storage system (BESS). This study also includes simulation and analysis of a large-scale hybrid renewable energy system with a DC load application. In this paper Gain Scheduling PI(GSPI) controlling technique is used for good stability and improvement of the response time of 100 kW HRES. MATLAB SIMULINK is used to evaluate the system for different combinations of supply and load.

关键词： HRES Solar PV WECS BESS

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Model Predictive Runtime Verification for Cyber-Physical systems with Real-Time Deadlines 21st

Model Predictive Runtime Verification for Cyber-Physical Sys...

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21st International conference on Formal modeling and Analysis of Timed systems

作者： Zhang, Pei Aurandt, Alexis Dureja, Rohit Jones, Phillip H. Rozier, Kristin Yvonne Iowa State Univ Ames IA 50011 USA IBM Corp Armonk NY 10504 USA

ISBN: (纸本)9783031426254;9783031426261

Cyber-physical systems often require fault detection of future events in order to mitigate the fault before failure occurs. Effective on-board runtime verification (RV) will need to not only determine the system's current state but also predict future faults by predetermined mitigation trigger deadlines. For example, if it takes three seconds to deploy the parachute of an Unmanned Aerial system (UAS), the deployment of the parachute must be triggered three seconds before it is needed to mitigate the impending crash. To allow for the detection of future faults by deadlines, we design a real-time Model Predictive Runtime Verification (MPRV) algorithm that uniquely uses current data traces whenever possible, predicting only the minimum horizon needed to make an on-deadline evaluation. Although MPRV is extensible to other RV engines, we deploy the algorithm on the R2U2 RV engine due to R2U2's resource-aware architecture, real-time guarantees, and deployment history. We demonstrate the utility of the MPRV algorithm through a quadcopter case study and evaluate the effectiveness of our implementation by conducting memory usage and runtime performance analysis in a resource-constrained FPGA environment.

关键词： Cyber Physical system

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