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检索条件"任意字段=21st International Conference on Architecture of Computing Systems"

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architecture of intercomponent interaction of a microprocessor-powered sustainable relay protection system based on open standards IoT 19

Architecture of intercomponent interaction of a microprocess...

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19th international conference on Future Networks and Communications, FNC 2024 / 21st international conference on Mobile systems and Pervasive computing, MobiSPC 2024 / 14th international conference on Sustainable Energy Information Technology, SEIT 2024

作者： Neftissov, Alexandr Biloshchytskyi, Andrii Kirichenko, Lalita Kazambayev, Ilyas Zhakupova, Kamila Urazayev, Dnislam Vatskel, Vladimir Astana IT University Astana010000 Kazakhstan Department of Information Technologies Kyiv National University of Construction and Architecture Kyiv01001 Ukraine

Nowadays, the problem of the coordination of relay protection systems during faults becomes widespread, as the trip of the circuit breaker must be fast. One of the solutions is the application of the Internet of Things. The object of this research is a relay protection system architecture, which uses elements of the Internet of Things and is based on open standards. The research aims to address the efficiency of using the Internet of Things in the relay protection systems, as well as the relevance of the proposed architecture. This architecture unifies processes encompassing relay protection, data collection, analysis, real-time communication protocols, and secure data transmission techniques. Apart from the increased quality of relay protection, it provides a well-organized framework for the precise and efficient acquisition, transmission, and analysis of data. As a result of the research, it was derived that the Internet of Things can be used in relay protection applications along with the proposed architecture if certain conditions are met. © 2024 The Authors. Published by Elsevier B.V.

关键词： Relay control systems

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Bird Detection and Recognition systems Through Machine Learning and Artificial Intelligent: Advancements and Future Opportunities 21st

Bird Detection and Recognition Systems Through Machine Learn...

引用

21st international Symposium on Distributed computing and Artificial Intelligence

作者： Rossi Labianca, Lautaro Alvarez Uruena, Jaime Curto Hernandez, Javier Garcia Serrada, Raul Air Inst IoT Digital Innovat Hub Spain Deep Tech Lab Ave SantiagoMadrigal 39 Salamanca 37003 Spain Univ Salamanca BISITE Res Grp Edificio Multiusos IDICalle Espejo 2 Salamanca 37007 Spain

ISBN: (纸本)9783031820724;9783031820731

The paper provides an overview of advancements in bird detection and recognition systems using Machine Learning and Artificial Intelligence (AI). It highlights the increasing adoption of wind farms amid rising electricity demand, underscoring their environmental impact on avian species. To address these ecological challenges, the development of bird recognition solutions is crucial. The paper analyzes various techniques, including radar systems, sound recognition, Convolutional Neural Networks (CNNs), electromagnetic detection, YOLOv5, and color segmentation, discussing their features, computational costs, and constraints. It concludes that while deep learning models offer superior results, they need a balance between accuracy and speed, alongside training with large and representative datasets. Ultimately, the paper aims to contribute to efforts aimed at mitigating the adverse effects of wind farms on bird populations through advanced technologies. Additionally, through this paper we intend to shed light over the state of the art on bird detection systems and provide insights that intends to solve some of these drawbacks.

关键词： Bird Recognition Bird detection Machine Learning Artificial Intelligence Computer Vision

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A Design Approach and Prototype Implementation for Factory Monitoring Based on Virtual and Augmented Reality at the Edge of Industry 4.0 21

A Design Approach and Prototype Implementation for Factory M...

引用

IEEE 21st international conference on Industrial Informatics (INDIN)

作者： Anagnostopoulos, Christos Mylonas, Georgios Fournaris, Apostolos P. Koulamas, Christos Athena Res & Innovat Ctr Ind Syst Inst Patras Greece

ISBN: (纸本)9781665493130

Virtual and augmented reality are currently enjoying a great deal of attention from the research community and the industry towards their adoption within industrial spaces and processes. However, the current design and implementation landscape is still very fluid, while the community as a whole has not yet consolidated into concrete design directions, other than basic patterns. Other open issues include the choice over a cloud or edge-based architecture when designing such systems. Within this work, we present our approach for a monitoring intervention inside a factory space utilizing both Virtual Reality (VR) and Augmented Reality (AR), based primarily on edge computing, while also utilizing the cloud. We discuss its main design directions, as well as a basic ontology to aid in simple description of factory assets. In order to highlight the design aspects of our approach, we present a prototype implementation, based on a use case scenario in a factory site, within the context of the EnerMan H2020 project.

关键词： augmented reality virtual reality extended reality Industry 4.0 edge computing

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Automating the Evaluation of Interoperability Effectiveness in Heterogeneous IoT systems 21

Automating the Evaluation of Interoperability Effectiveness ...

引用

21st international conference on Software architecture (ICSA)

作者： Bouloukakis, Georgios Georgantas, Nikolaos Kattepur, Ajay Hassan, Houssam Hajj Issarny, Valerie Inst Polytech Paris Telecom SudParis Palaiseau France Inria Paris Paris France Ericsson AI Res Delhi India

ISBN: (纸本)9798350359176;9798350359169

Internet of Things (IoT) applications consist of diverse resource-constrained/rich devices with a considerable portion being mobile. Such devices demand lightweight, loosely coupled interactions in terms of time, space, and synchronization. IoT protocols at the middleware layer support several interaction types (e.g., asynchronous messaging, streaming, etc.) ensuring successful interactions between devices that use the same protocol. Additionally, they introduce different Quality of Service (QoS) delivery modes for data exchange with respect to available device and network resources. On the other hand, interconnecting heterogeneous IoT devices requires mapping both their functional and QoS properties. This calls for advanced interoperability solutions integrated with QoS modeling and analysis techniques. This paper introduces an automated synthesis of QoS-aware mediating artifacts. Such mediators enable the interconnection between IoT devices employing heterogeneous middleware protocols. Additionally, representative QoS models are synthesized. Leveraging these models, system designers can evaluate the effectiveness of the interconnection in terms of end-to-end QoS. We evaluate the usefulness of our approach through experimentation with a case study employing heterogeneous middleware protocols. In particular, we statistically analyze through simulations the effect of varying system parameters on the end-to-end QoS.

关键词： IoT QoS Interoperability Middleware

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Proceedings - 2024 IEEE 21st international conference on Mobile Ad-Hoc and Smart systems, MASS 2024

Proceedings - 2024 IEEE 21st International Conference on Mob...

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21st IEEE international conference on Mobile Ad-Hoc and Smart systems, MASS 2024

ISBN: (纸本)9798350363999

The proceedings contain 97 papers. The topics discussed include: HydroDrone: multi-drone network for secure task management in smart water resource management;frequency hopping as diffusion: a new perspective on mitigating Bluetooth packet collisions in dense deployments;fault-aware service scheduling optimization framework in edge data center;VibroFM: towards micro foundation models for robust multimodal IoT sensing;how to budget privacy in federated learning? a correlated equilibrium perspective;a novel collaborative edge caching via user preference awareness and adaptive clustering in MENs;where care: a patient localization system for nursing homes;and collaborative user mobility prediction in distributed edge computing framework.

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Confident Security Relation for Edge computing-based loT Applications 21

Confident Security Relation for Edge Computing-based loT App...

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

作者： Almubarak, Hameed Jedidi, Ahmed Technical College of Dammam Technical and Vocational Training Corporation Department of Computer Engineering Saudi Arabia Ahlia University Dept. of Computer Engineering Manama Bahrain National School of Engineering Sfax University Tunisia

ISBN: (纸本)9798350374131

Smart city, health care, agriculture etc applications under the umbrella of the Internet of Things (loT) which they present a new technology with a millions of devices connected together. In the End, all loT devices are connected to cloud computing which the process of the data flow. However, loT applications generate a huge data flow which present a major problem with the system performance. In fact, edge computing is proposed as solution to solve the problem of data flow processing. Moreover, edge computing is the first line of the data processing mostly for the particular applications such as smart city which the huge number of the loT devices. The edge computing resources are limited performance compared to the cloud computing. This nature of the edge computing presents a major problem for the security issues in the loT applications. In fact, this paper proposes a novel security system to secure the relation between the loT devices and edge computing. Further, Confident Security Relation (CSR) suggests four levels which each one proposes recommendation about the security protocol applied. CSR is lined with the different requirements requested by loT application to improve the real time data processing. © 2024 IEEE.

关键词： Edge computing

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An Analysis of Different Text Representation Schemes for an Immune Clustering Algorithm 21st

An Analysis of Different Text Representation Schemes for an ...

引用

21st international Symposium on Distributed computing and Artificial Intelligence

作者： Ferraria, Matheus A. Balbi, Pedro P. de Castro, Leandro N. Univ Presbiteriana Mackenzie FCI PPGEEC Programa Pos Grad Engn Eletrica & Comp Sao Paulo SP Brazil State Univ Campinas Unicamp Sch Technol Grad Program Technol Sao Paulo SP Brazil Florida Gulf Coast Univ Human Ctr Artificial Intelligence & Nat Comp Res Ft Myers FL 33965 USA

ISBN: (纸本)9783031820724;9783031820731

This research investigates the challenges and effectiveness of various text representation methods (standard vector, grammar-based, and distributed), when applied to clustering short texts. The study explores Bag-of-Words for standard vector, Linguistic Inquiry and Word Count (LIWC), Part-of-Speech Tagging (POS-Tagging), and the Medical Research Council Psycholinguistic Database (MRC) for grammar-based, and Word2Vec, fastText, Doc2Vec, and SentenceBERT for distributed representations. Utilizing the aiNet bio-inspired clustering algorithm, the results reveal surprising findings, with grammar-based representations demonstrating competitive performance despite their simplicity, while standard vectors exhibit known challenges like high dimensionality. The study contributes insights into the properties of different text representations, providing a foundation for optimizing their application in clustering tasks with short and informal texts.

关键词： Clustering Information retrieval Natural computing NLP Text Mining

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A microservices-based architecture for data and software management of heavy equipment digital twins 21

A microservices-based architecture for data and software man...

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IEEE 21st international conference on Industrial Informatics (INDIN)

作者： Zhidchenko, Victor startcev, Egor Kortelainen, Juha Zeb, Akhtar Torvikoski, Leo Torkabadi, Saeid Handroos, Heikki LUT Univ Dept Mech Engn Lappeenranta Finland VTT Tech Res Ctr Finland Knowledge driven Design Res Unit Espoo Finland Eurostep Oy Espoo Finland Eurostep AB Gothenburg Sweden

ISBN: (纸本)9781665493130

Digital twins improve the performance of heavy equipment and decrease its operational costs. To be effective, they must run along decades of a real machine lifecycle. Ensuring coherence between a real machine and its digital twin over such a long period is a challenging task that has not yet been well-studied. This task involves preserving the design and operational data and periodic execution of digital twin software that processes such data. The circumstances of heavy equipment operation complicate the task. This paper considers the problem of digital twin data and software management in light of the unique challenges related to heavy equipment. It presents an experimental case study for running digital twins of mobile log cranes using a data model and a microservices-based architecture developed by the authors. The results demonstrate the capability of the architecture for running physics-based digital twins of heavy equipment in a heterogeneous execution environment consisting of local, edge, and cloud computing resources.

关键词： digital twin simulation data model digitalisation cloud computing edge computing

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How to Budget Privacy in Federated Learning? A Correlated Equilibrium Perspective 21

How to Budget Privacy in Federated Learning? A Correlated Eq...

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

作者： Han, Xiaoying Hu, Qin Xu, Xiaohua Univ Sci & Technol China Dept Comp Sci & Technol Hefei Peoples R China Indiana Univ Dept Comp Sci Indianapolis IN 46204 USA

ISBN: (纸本)9798350363999;9798350364002

Facilitated by mobile edge computing (MEC), federated learning (FL) can be deployed at the network edge to protect the local data privacy of mobile devices for real-time data-driven applications. To further prevent privacy inference from local models, FL has been enhanced by differential privacy (DP) technology. The existing DP-enhanced FL studies focus on developing DP mechanisms and designing incentive schemes for DP implementation in FL, overlooking the issue of fair privacy budgeting among all clients. To fill this gap, we achieve fairness by balancing the privacy budget, model performance, and cost via defining a privacy budget determination (PBD) game among clients with similar local models. However, it is nontrivial to achieve this balance due to two challenges: the interdependency among clients regarding choosing privacy budgets and the unavailability of other devices' parameters. To resolve the first challenge, we employ the concept of correlated equilibrium (CE) to capture the mutual influences among clients in deciding privacy budgets. We then formulate an optimization problem with CE and individual rationality (IR) constraints to derive the optimal decision. For the second challenge, we exploit the centralized position of the aggregation server to help calculate the solution to the optimization problem. Experiments on real-world datasets demonstrate that the proposed mechanism ensures fairness while achieving superior client utility and global model performance.

关键词： Mobile edge computing federated learning differential privacy game theory

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NARS: Neuromorphic Acceleration through Register-streaming Extensions on RISC-V Cores 21

NARS: Neuromorphic Acceleration through Register-Streaming E...

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21st ACM international conference on computing Frontiers (CF)

作者： Manoni, Simone Scheffler, Paul Di Mauro, Alfio Zanatta, Luca Acquaviva, Andrea Benini, Luca Bartolini, Andrea Univ Bologna Bologna Italy Swiss Fed Inst Technol Zurich Switzerland

ISBN: (纸本)9798400704925

Spiking Neural Networks (SNNs) have emerged as a promising bio-inspired solution to address the need for low-latency, energy-efficient artificial intelligence systems. SNNs pose a challenge to traditional CPUs, GPUs and neural network accelerators due to their inherent sparsity, spike-based communication between neurons and complex activation functions. Many neuromorphic accelerators have been developed to handle this complex workload, but these systems are often designed solely to accelerate spiking networks, resulting in huge area costs and a lack of flexibility. We address this problem by proposing a novel mapping methodology for Convolutional SNNs (S-CNNs) on a general-purpose open-source RISC-V core equipped with Indirection streaming Semantic Registers, a lightweight ISA extension for accelerating sparse-dense linear algebra. NARS is the first work to map S-CNNs in a classical sparse-dense algebra paradigm. Our methodology shows that it is possible to achieve speedups on S-CNNs microkernels with sparsity degrees compatible with state-of-the-art S-CNNs ranging from 4.33x to 10.23x on a dense baseline and from 1.12x to 2.66x on a optimized dense implementation.

关键词： Neuromorphic computing Sparse Linear Algebra RISC-V

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