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21st International conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, CPAIOR 2024

21st International Conference on the Integration of Constrai...

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21st International conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, CPAIOR 2024

ISBN: (纸本)9783031605963

The proceedings contain 21 papers. The special focus in this conference is on Integration of Constraint Programming, Artificial Intelligence, and Operations Research. The topics include: Acquiring Constraints for a Non-linear Transmission Maintenance Scheduling Problem;efficiently Mining Closed Interval Patterns with Constraint Programming;Local Alterations of the Lagrange Multipliers for Enhancing the Filtering of the AtMostNValue Constraint;Single Constant Multiplication for SAT;towards a Generic Representation of Combinatorial Problems for Learning-Based Approaches;accelerating Continuous Variable Coherent Ising Machines via Momentum;decision-Focused Predictions via Pessimistic Bilevel optimization: A Computational study;bi-objective Discrete Graphical Model optimization;an Exploration of Exact Methods for Effective Network Failure Detection and Diagnosis;UNSAT Solver Synthesis via Monte Carlo Forest Search;a Hybrid Approach Integrating Generalized Arc Consistency and Differential Evolution for Global optimization;assessing Group Fairness with Social Welfare optimization;modeling and Exploiting Dominance Rules for Discrete optimization with Decision Diagrams;ViolationLS: Constraint-Based Local Search in CP-SAT;ULD Build-Up Scheduling with Logic-Based Benders Decomposition;a Benders Decomposition Approach for a Capacitated Multi-vehicle Covering Tour Problem with Intermediate Facilities;don’t Explain Noise: Robust Counterfactuals for Randomized Ensembles;Certifying MIP-Based Presolve Reductions for 0–1 Integer Linear Programs;learning to Solve Job Shop Scheduling Under Uncertainty.

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Identification of Unstable Linear systems using Data-driven Koopman Analysis 21

Identification of Unstable Linear Systems using Data-driven ...

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21st International conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)

作者： Ketthong, Patinya Samkunta, Jirayu Nghia Thi Mai Hashikura, Kotaro Kamal, Md Abdus Samad Murakami, Iwanori Yamada, Kou Gunma Univ Grad Sch Sci & Technol 1-5-1 Tenjincho Kiryu Gumma 3768515 Japan Thai Nichi Inst Technol Fac Engn Bangkok Thailand Posts & Telecommun Inst Technol Dept Elect & Elect Km10 Hanoi Vietnam Gunma Univ Div Mech Sci & Technol 1-5-1 Tenjincho Kiryu Gumma 3768515 Japan

ISBN: (纸本)9798350381566;9798350381559

system identification plays a crucial role in modern control techniques, enabling the data-driven learning of input-output maps or mathematical models. However, practical applications face challenges as the actual number of states is often unknown, and observed variables may be limited. Additionally, unstable systems present further difficulties, as their outputs rapidly diverge or saturate, hindering long-term measurement. This paper addresses these challenges by proposing a novel input-aware modeling method for unstable linear systems using data-driven Koopman analysis. Unlike traditional Koopman analysis which focuses solely on state dynamics, our method explicitly incorporates the influence of the input function u(t). This enables us to accurately capture the complete behavior of the system, even under the influence of external control signals. By leveraging Koopman operator theory on augmented state-input data, we capture both the intrinsic dynamics and the sensitivity to external control, crucial for accurate prediction and control of unstable systems. This input-aware approach extends the capabilities of data-driven Koopman analysis to improve modeling and control of complex unstable systems in various applications.

关键词： Sparse modeling HAVOK algorithm system identification

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Fault-Aware Service Scheduling optimization Framework in Edge Data Center 21

Fault-Aware Service Scheduling Optimization Framework in Edg...

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21st IEEE International conference on Mobile Ad-Hoc and Smart systems (MASS)

作者： Zhang, Yaqiang Zhao, Yaqian Shi, Hongzhi Gao, Fei Xu, Guangyuan Chen, Xiaolin Li, Xiao IEIT Syst Co Ltd Jinan 250101 Peoples R China Inspur Beijing Elect Informat Ind Co Ltd Beijing 100095 Peoples R China

ISBN: (纸本)9798350363999;9798350364002

Edge data centers can provide abundant computing, memory, and storage resources for mobile terminal users with low latency to meet the needs of various services and computing tasks. However, due to the uncertainty of its environment compared with the cloud data center, the failure frequency is higher on the edge side, which brings great challenges to user service satisfaction. To mitigate this challenge, minimize the impact of failures on edge data centers, and provide higher reliability for continuous service operation, this paper proposes a fault-aware service scheduling optimization framework. We first explore the impact of the failure scenario and define the state of edge data center resources. Secondly, for the case containing faults, we define it as the target model between fault awareness and task energy efficiency. Finally, a decision-generation technique based on agent learning is proposed to find the service scheduling decision that can minimize the impact of failures. Extensive experiments are conducted, and evaluation results demonstrate that our proposed fault-aware services scheduling technique can effectively improve system reliability and availability.

关键词： Edge Data Center Fault-Aware Deep Reinforcement Learning Service Scheduling

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21st Polish Control conference, PCC 2023

21st Polish Control Conference, PCC 2023

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21st Polish Control conference, PCC 2023

ISBN: (纸本)9783031351723

The proceedings contain 79 papers. The special focus in this conference is on Polish Control. The topics include: MOOforest – Multi-objective optimization to Form Decision Tree Ensemble;b-Spline Identification of Cascade Control system on the Example of Building Heating system;tracking optimization in Nonparametric Identification of Time-Varying Nonlinear systems;three-Dimensional Analysis of the Retinal Vessels;modeling of Biotechnological Processes During the Cultivation of Medicinal Plants In Vitro;employment of a Nonlinear Adaptive Control system for Improved Control of Dissolved Oxygen in Sequencing Batch Reactor;mathematical Calculation of the Boundary Conditions for the Formation of Heavy Metals Chalcogenides Poorly Soluble Compounds (Zn, Cd, Hg);mobile Application for Skin Lesions Classification;automatic Artifact Removal from Dermoscopic Images;bayesian Fault Diagnosis for Induction Motors During startup in Frequency Domain;software system Testing as an optimization Problem;a Model-Based Approach to Testing Software Control systems Described by Linear Differential Equations;Reactive Control Algorithm for F1TENTH Autonomous Vehicles in Unknown Dynamic Environments;the Influence of the Relative Vehicles Speed on the Environmental Perception-Tests on Slovakia Ring;multiple Hypothesis Planning for Vehicle Control;automotive Radar Detection Level modeling with Neural Networks;robotic system Specification Language Use Case;tactile Feedback Glove Working in Virtual Reality;control system for Humanoid Robot;On FOPID Controller Tuning of a Legless Capsubot Robot;experimental Assessment for Radar-Based Estimation of Host Vehicle Speed During Traction Events;Prototype of Turbine Propulsion system with Controllable Thrust Vector for Long-Range Unmanned VTOL Aircraft;identification of Ship’s Hull Mathematical Model with Numerical Methods;Eigensystem Realization Algorithm (ERA) in Simulation of Dynamic Response of Marine Autonomous Surface Ships (MASS);ship Dynamic Posit

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Maximizing Resource Utilization using Hybrid Cloud-based Task Allocation Algorithm 21

Maximizing Resource Utilization using Hybrid Cloud-based Tas...

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21st IEEE International conference on Mobile Ad-Hoc and Smart systems (MASS)

作者： Mishra, Sambit Kumar Mohith, G. K. H. Ambati, Sai Teja Guduru, Krishna Koushik Senapati, Rajiv SRM Univ AP Dept Comp Sci & Engn Amaravati Andhra Pradesh India

ISBN: (纸本)9798350363999;9798350364002

Cloud computing operates similarly to a utility, providing users with on-demand access to various hardware and software resources, billed according to usage. These resources are primarily virtualized, with virtual machines (VMs) serving as critical components. However, task allocation within VMs presents significant challenges, as uneven distribution can lead to underloading or overloading, causing system inefficiencies and potential failures. This study addresses these issues by proposing a novel hybrid task allocation algorithm that combines the strengths of the Artificial Bee Colony (ABC) algorithm with Particle Swarm optimization (PSO). Our approach aims to enhance resource utilization and reduce the risks of VM overload or underload. We conduct a comprehensive evaluation of the proposed hybrid algorithm against traditional ABC and PSO algorithms, focusing on their effectiveness in managing diverse task loads. The results of our empirical analysis indicate that our hybrid approach outperforms the conventional algorithms, leading to better resource utilization and more accurate task allocation. These findings have significant implications for optimizing task allocation in cloud computing environments, and we suggest potential avenues for future research to further refine these strategies.

关键词： Task Scheduling Virtual Machines Cloud Computing Artificial Bee Colony Particle Swarm optimization

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21st Polish Control conference, PCC 2023

21st Polish Control Conference, PCC 2023

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21st Polish Control conference, PCC 2023

ISBN: (纸本)9783031351693

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Concept of a causality-driven fault diagnosis system for cyber-physical production systems 21

Concept of a causality-driven fault diagnosis system for cyb...

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IEEE 21st International conference on Industrial Informatics (INDIN)

作者： Mehling, Carl Willy Pieper, Sven Ihlenfeldt, steffen Fraunhofer IWU Digitalizat Prod Dresden Germany Fraunhofer IWU Prod Syst & Factory Automat Chemnitz Germany

ISBN: (纸本)9781665493130

The automated production of individualized products in a cyber-physical production system (CPPS) requires the combined automation of software and machine components. While this leads to increased productivity, the complexity of the CPPS may result in long unplanned downtimes when faults occur, and no system model is available to guide the maintenance team. Knowledge-driven, data-driven or hybrid modeling are available approaches in the literature to obtaining a system model. While expert-driven and data-driven modeling face limited applicability to CPPS, hybrid models, combining both approaches can offer a solution. This paper proposes a causality-driven hybrid model for fault diagnosis in complex CPPS, represented in a causal knowledge graph (CKG). The CKG serves as a transparent system model for collaborative human-machine fault diagnosis. We provide a concept for the continuous hybrid learning of the CKG, a maturity model to classify the resulting CKG's fault diagnosis capabilities, and the industrial setting inspiring the approach.

关键词： fault diagnosis cyber-physical production system artificial intelligence knowledge discovery cause effect analysis

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FhGenie: A Custom, Confidentiality-preserving Chat AI for Corporate and Scientific Use 21

FhGenie: A Custom, Confidentiality-preserving Chat AI for Co...

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21st International conference on Software Architecture (ICSA)

作者： Weber, Ingo Linka, Hendrik Mertens, Daniel Muryshkin, Tamara Opgenoorth, Heinrich Langer, stefan Fraunhofer Soc D-80686 Munich Germany Tech Univ Munich Sch CIT D-80333 Munich Germany

ISBN: (纸本)9798350366266;9798350366259

Since OpenAI's release of ChatGPT, generative AI has received significant attention across various domains. These AI-based chat systems have the potential to enhance the productivity of knowledge workers in diverse tasks. However, the use of free public services poses a risk of data leakage, as service providers may exploit user input for additional training and optimization without clear boundaries. Even subscription-based alternatives sometimes lack transparency in handling user data. To address these concerns and enable Fraunhofer staff to leverage this technology while ensuring confidentiality, we have designed and developed a customized chat AI called FhGenie (genie being a reference to a helpful spirit). Within few days of its release, thousands of Fraunhofer employees started using this service. As pioneers in implementing such a system, many other organizations have followed suit. Our solution builds upon commercial large language models (LLMs), which we have carefully integrated into our system to meet our specific requirements and compliance constraints, including confidentiality and GDPR. In this paper, we share detailed insights into the architectural considerations, design, implementation, and subsequent updates of FhGenie. Additionally, we discuss challenges, observations, and the core lessons learned from its productive usage.

关键词： software architecture practical experience artificial intelligence chatbot LLM enterprise production system GPT ChatGPT Azure OpenAI

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static Synchronous Compensator (stATCOM) Based Neural Network to Reducing system Oscillations and Improving Dynamic system Performance 21

Static Synchronous Compensator (STATCOM) Based Neural Networ...

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21st International Multi-conference on systems, Signals and Devices, SSD 2024

作者： Ahmed, Raghad Hameed Said Nouri, Ahmed Middle Technical University Department of Technical Electronic Baghdad Iraq Laboratoire CONPRi - ENIG Gabès École Nationale d'Ingénieurs Sfax Tunisia

ISBN: (纸本)9798350374131

The stability of the electrical network is considered a major challenge in the development of energy systems based on various sources. This research provides a comparison of the dynamic performance of FACTS devices such as stATCOM. These techniques, which are integrated stability devices with a multi-source power system, are used. The neural network technology unit is used to control FACTS devices to enhance the performance of power sources under abnormal and different conditions. Testing is conducted under conditions of three-phase short circuit to ground at different locations in the system. MATLAB/Simulink is used for modeling and simulation. The obtained results demonstrate the impact of the control unit based on stATCOM in reducing system oscillations and improving dynamic system performance during the post-fault period. The confirms the superior dynamic performance and quick fault recovery of the control unit. © 2024 IEEE.

关键词： static synchronous compensators

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FazyRV: Closing the Gap between 32-Bit and Bit-Serial RISC-V Cores with a Scalable Implementation 21

FazyRV: Closing the Gap between 32-Bit and Bit-Serial RISC-V...

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21st ACM International conference on Computing Frontiers (CF)

作者： Kissich, Meinhard Baunach, Marcel Graz Univ Technol Graz Austria

ISBN: (纸本)9798400705977

RISC-V processor cores with a 32-bit internal data path reach a boundary on their minimal size, requiring novel concepts to decrease silicon area and the cost of Internet of Things (IoT) devices. We propose a minimal-area open-source RV32I RISC-V core targeting the IoT and low-workload applications. Unlike cores with a similarly small area, FazyRV is inherently scalable to a data path width of 1, 2, 4, or 8 bits. FazyRV has manifold variants to achieve the smallest footprint at given performance requirements. This paper provides insight into FazyRV, its verification, and the resource utilization for five Field-Programmable Gate Array (FPGA) architectures. We also compare its performance with similar cores using the Embench benchmark suite. Based on the findings, we analyze and discuss optimization potentials in depth. Although FazyRV is implemented at the register transfer level, we achieve comparable results to hand-optimized cores at the gate level. In an exemplary IoT application, the whole system on chip is implemented in 77 Slices, or 645 Logic Cells for a Xilinx/AMD 7-Series or an iCE40 FPGA, respectively.

关键词： RISC-V Embedded systems Internet of Things Processor Architecture Digital system Design

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