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arXiv 2024年

作者： Saleh, Alaa Donta, Praveen Kumar Morabito, Roberto Motlagh, Naser Hossein Lovén, Lauri Center for Ubiquitous Computing University of Oulu Finland Distributed Systems Group TU Wien Vienna Austria Department of Communication Systems EURECOM France Department of Computer Science University of Helsinki Finland

This article introduces Follow-Me AI, a concept designed to enhance user interactions with smart environments, optimize energy use, and provide better control over data captured by these environments. Through AI agents that accompany users, Follow-Me AI negotiates data management based on user consent, aligns environmental controls as well as user communication and computes resources available in the environment with user preferences, and predicts user behavior to proactively adjust the smart environment. The manuscript illustrates this concept with a detailed example of Follow-Me AI in a smart campus setting, detailing the interactions with the building's management system for optimal comfort and efficiency. Finally, this article looks into the challenges and opportunities related to Follow-Me AI. © 2024, CC BY-NC-ND.

关键词： Energy efficiency

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Towards a Unified Flow Description Language for CPPSs: An Example with Material Flows

Towards a Unified Flow Description Language for CPPSs: An Ex...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Jana Gödeke Maximilian Horstrup Peter Detzner Department for AI and Autonomous Systems Fraunhofer Institute for Material Flow and Logistics Dortmund Germany Ruhr University Bochum Faculty of Computer Science Distributed and Networked Systems Group Bochum Germany

ISBN: (数字)9798350361230

ISBN: (纸本)9798350361247

This paper presents a unified approach for repre-senting multiple domains alongside production in cyber-physical production systems (CPPSs) through domain-specific languages (DSLs). The approach is illustrated using material flows (MFs) as an example. The paper identifies requirements for DSLs in CPPSs and MFs, including concurrency, synchronization, constraints, and heterogeneity support. Subsequently, a plugin system is in-troduced for the existing Production Flow Description Language (PFDL), which allows users to incorporate additional domain-specific functionality in the form of plugins. To demonstrate this approach, we present the MF plugin, resulting in the combined PFDLMF. This showcases the reusability of such an approach and the easy integration of new CPPS domains. We envision the convergence of the PFDL with plugins towards a unified flow description language for CPPSs. A practical CPPS use-case demonstrates the expressiveness of the PFDLMF in modeling and executing complex MFs in an agent-based architecture.

关键词： Concurrent computing Production systems DSL Synchronization Manufacturing automation Domain specific languages Convergence

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Polyjuice: High-performance transactions via learned concurrency control

arXiv

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arXiv 2021年

作者： Wang, Jiachen Ding, Ding Wang, Huan Christensen, Conrad Wang, Zhaoguo Chen, Haibo Li, Jinyang Institute of Parallel and Distributed Systems Shanghai Jiao Tong University China Shanghai AI Laboratory China Engineering Research Center for Domain-specific Operating Systems Ministry of Education China Department of Computer Science New York University

Concurrency control algorithms are key determinants of the performance of in-memory databases. Existing algorithms are designed to work well for certain workloads. For example, optimistic concurrency control (OCC) is better than twophase- locking (2PL) under low contention, while the converse is true under high contention. To adapt to different workloads, prior works mix or switch between a few known algorithms using manual insights or simple heuristics. We propose a learning-based framework that instead explicitly optimizes concurrency control via offline training to maximize performance. Instead of choosing among a small number of known algorithms, our approach searches in a "policy space" of fine-grained actions, resulting in novel algorithms that can outperform existing algorithms by specializing to a given workload. We build Polyjuice based on our learning framework and evaluate it against several existing algorithms. Under different configurations of TPC-C and TPC-E, Polyjuice can achieve throughput numbers higher than the best of existing algorithms by 15% to 56%. Copyright © 2021, The Authors. All rights reserved.

关键词： Concurrency control

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Phase-field modeling and effective simulation of non-isothermal reactive transport

arXiv

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arXiv 2023年

作者： Bringedal, Carina Jaust, Alexander Department of Computer science Electrical engineering and Mathematical sciences Western Norway University of Applied Sciences Norway Institute for Modelling Hydraulic and Environmental Systems University of Stuttgart Germany Institute for Parallel and Distributed Systems University of Stuttgart Germany

We consider single-phase flow with solute transport where ions in the fluid can precipitate and form a mineral, and where the mineral can dissolve and release solute into the fluid. Such a setting includes an evolving interface between fluid and mineral. We approximate the evolving interface with a diffuse interface, which is modeled with an Allen-Cahn equation. We also include effects from temperature such that the reaction rate can depend on temperature, and allow heat conduction through fluid and mineral. As Allen-Cahn is generally not conservative due to curvature-driven motion, we include a reformulation that is conservative. This reformulation includes a non-local term which makes the use of standard Newton iterations for solving the resulting non-linear system of equations very slow. We instead apply L-scheme iterations, which can be proven to converge for any starting guess, although giving only linear convergence. The three coupled equations for diffuse interface, solute transport and heat transport are solved via an iterative coupling scheme. This allows the three equations to be solved more efficiently compared to a monolithic scheme, and only few iterations are needed for high accuracy. Through numerical experiments we highlight the usefulness and efficiency of the suggested numerical scheme and the applicability of the resulting *** Codes 35R37, 65M08, 65M22, 76D10, 76D05, 76V05, 80A32, 80M12 © 2023, CC BY.

关键词： Minerals

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Peer Discovery in Tree-Structured P2P Overlay Networks by Means of Connected Dominating Sets

Peer Discovery in Tree-Structured P2P Overlay Networks by Me...

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Conference on Local computer Networks (LCN)

作者： Peter Detzner Jana Gö deke Steffen Bondorf Department for AI and Autonomous Systems Fraunhofer Institute for Material Flow and Logistics Dortmund Germany Faculty of Computer Science Distributed and Networked Systems Group Ruhr University Bochum Bochum Germany

ISBN: (数字)9781665480017

ISBN: (纸本)9781665480024

A Peer-to-Peer (P2P) network consists of a large number of nodes, where each node may have different capabilities and properties. Finding peers with specific capabilities and properties is challenging. Thus, we propose a practical solution to the problem of peer discovery, which is finding peers in the network according to a specified query. We contribute a peer discovery for an m-ary tree-structured P2P network by utilizing a connected dominating set (CDS), a technique that is typically used in unstructured networks. Our approach of constructing the CDS requires no additional communication cost, while nodes can insert, update and remove data within ${\mathcal{O}}(1)$. Each node of the CDS – a dominating set node – maintains only a limited number of nodes. We confirm the properties of our proposed solution by using the ns-3 discrete-event simulator. This includes, besides the degree of decentralism of the peer discovery, also the heterogeneity of peers.

关键词： Overlay networks Upper bound Runtime Costs Peer-to-peer computing

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A Simulative Approach to AMR Fleet Sizing in Decentralized Multi-Robot Task Allocation

A Simulative Approach to AMR Fleet Sizing in Decentralized M...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Jana Gödeke Peter Detzner Department for AI and Autonomous Systems Fraunhofer Institute for Material Flow and Logistics Dortmund Germany Ruhr University Bochum Faculty of Computer Science Distributed and Networked Systems Group Bochum Germany

As the Industry 4.0 shifts towards the adoption of autonomous mobile robots (AMRs) in warehouses, decentralized decision-making has become a key design principle. Multi-robot task allocation (MRTA) is a problem that involves assigning tasks to AMRs while optimizing the performance of the system. However, modeling decentralized MRTA applications for optimization without a central instance poses significant challenges due to the autonomy and flexibility of AMRs. In this paper, we propose a simulative approach to address the fleet sizing problem combined with decentralized MRTA applications for AMRs. Based on simulation data, models have been developed that predict key performance indicators (KPIs) for different warehouse layouts and requirements, using techniques from machine learning and mathematical optimization. The model represents KPIs such as constraint satisfaction and utilization rates in a decentralized MRTA scenario including a self-organizing material flow application. Based on this model, we introduce a fleet size selection mechanism. This research contributes to the field of Industry 4.0 by providing a generalizable simulative approach that is adaptable to flexible warehouse environments, allowing for the application of any MRTA algorithm. Moreover, this approach allows the integration of different KPIs, facilitating the adaptation of requirements.

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A peer-to-peer mechanism for resource location and allocation over the grid 04

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Proceedings of the Second international conference on parallel and distributed Processing and Applications

作者： Hung-Chang Hsiao Mark Baker Chung-Ta King Computer and Communication Research Center National Tsing-Hua University Taiwan The Distributed Systems Group University of Portsmouth UK Department of Computer Science National Tsing-Hua University Taiwan

ISBN: (纸本)9783540241287

Recent advances in P2P lookup overlays provide an appealing solution for distributed search without relying on a single database server. In addition to performing resource discovery, these P2P substrates also offer membership management for dynamic peers. In this paper, we propose a publicly shared architecture called VC2A that takes advantage of a P2P lookup substrate for computational applications. VC2A targets computational master-slave applications. An application running in VC2A dynamically allocates resources from the system on the fly. These allocated resources then self-manage and -heal. We have implemented an architecture based on our previous efforts that include an enhanced P2P lookup overlay and a mobile agent system on top of this overlay. We show that VC2A is not only scalable but robust, and takes advantage of heterogeneity of the resources.

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The Role of Inference in the Anonymization of Medical Records

The Role of Inference in the Anonymization of Medical Record...

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Annual IEEE Symposium on computer-Based Medical systems

作者： Athanasios Zigomitros Agusti Solanas Constantinos Patsakis Department of Informatics University of Piraeus Greece Smart Health Research Group Universitat Rovira i Virgili Tarragona Spain Distributed Systems Group School of Computer Science and Statistics Dublin Ireland

The quality of life has been significantly improved and one of the main reasons is the medical advances of the past decades. Nevertheless, to further advance the research and services in the field, practitioners, researchers and health organizations should share more information. While this need is indisputable, the sensitivity of the information demands that it is preprocessed, so that the published data are anonym zed and individuals cannot be identified. The scope of this work is to highlight the difficulties in providing automated anonymization approaches for medical records without consulting experts in the field. One of the major problems that is going to be highlighted is that Quasi-Identifiers (QI) are not independent. It is well known that combinations of QIs can be used to infer other relevant information. Nevertheless, this work tries to exploit the other way of information flow, we show how sensitive attributes can be exploited to derive information about the QIs, leading to many privacy hazards for the patients whose records are shared. To this extent, we illustrate some relevant examples and discuss probable counter-measures.

关键词： Diseases Cancer Heart Stomach Privacy Databases Lattices

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Software-defined event-based camera and vision algorithms for digitizing highly dynamic manufacturing tasks

Software-defined event-based camera and vision algorithms fo...

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2024 Low-Cost Digital Solutions for Industrial Automation, LoDiSA 2024

作者： Walker, Emily Turner, Christopher J. Oyekan, John Department of Automatic Control & Systems Engineering The University of Sheffield SheffieldS1 3JD United Kingdom Surrey Business School The University of Surrey Surrey GuildfordGU2 7XH United Kingdom Real Time & Distributed Systems Group Department of Computer Science University of York Heslington YorkYO10 5GH United Kingdom

ISBN: (纸本)9781837242672

Event-based cameras are inspired by the way the retina in the eye process information. Rather than capturing image frames at a constant rate, event cameras generate data asynchronously, based on changes in pixel value between frames. As a result, these cameras have a high spatiotemporal accuracy, low power constraints and reduced artefacts from motion blur. Hence, they represent favourable properties for digitizing highly dynamic manufacturing tasks such as machine vibrations and rapid human assembly actions. However, the costs of event-based cameras are prohibitively high for small to medium sized enterprises (SMEs). In this research, we present the development of a rig that combines low-cost visual sensors with low-cost algorithms to perform action recognition for highly dynamic manual manufacturing tasks. We applied our algorithms to achieve an action classification system via a novel threshold-based approach and in parallel use a neural network to perform classification of objects in the video feed. The results achieved demonstrated that our approach was able to successfully identify various rapid manual tasks being performed on identified objects. In addition to SMEs, our approach would be suited for providing low-cost digitization on legacy machines. © This is an open access article published by the IET under the Creative Commons Attribution License (http://***/licenses/by/3.0/).

关键词： Machine vibrations

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PupilRec: Leveraging Pupil Morphology for Recommending on Smartphones

PupilRec: Leveraging Pupil Morphology for Recommending on Sm...

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作者： Shen, Xiangyu Jiang, Hongbo Liu, Daibo Yang, Kehua Deng, Feiyang Lui, John C. S. Liu, Jiangchuan Dustdar, Schahram Luo, Jun Hunan University College of Computer Science and Electronic Engineering Hunan Changsha410082 China The City University of Hong Kong School of Graduate Studies Hong Kong The Chinese University of Hong Kong Computer Science and Engineering Department Hong Kong Simon Fraser University School of Computing Science BurnabyBCV5A 1S6 Canada Vienna University of Technology Distributed Systems Group Vienna1040 Austria Nanyang Technological University School of Computer Engineering 639798 Singapore

As mobile shopping has gradually become the mainstream shopping mode, recommendation systems are gaining an increasingly wide adoption. Existing recommendation systems are mainly based on explicit and implicit user behaviors. However, these user behaviors may not directly indicate users' inner feelings, causing erroneous user preference estimation and thus leading to inaccurate recommendations. Inspired by our key observation on the correlation between pupil size and users' inner feelings, we consider using the change of pupil size when browsing to model users' preferences, so as to achieve targeted recommendations. To this end, we propose PupilRec as a computer-vision-based recommendation framework involving a mobile terminal and a server side. On the mobile terminal, PupilRec collects users' pupil size change information through the front camera of smartphones;it then preprocesses the raw pupil size data before transmitting them to the server. On the server side, PupilRec utilizes the Tsfresh package and Random Forest algorithm to figure out the key time-series features directly implying user preferences. PupilRec then trains a neural network to fit a user preference model. Using this model, PupilRec predicts user preference to obtain a user-product matrix and further simplifies it by singular value decomposition. Finally, the real-time recommendation is achieved by a collaborative filtering module that retrieves recommended contents to users smartphones. We prototype PupilRec and conduct both experiments and field studies to comprehensively evaluate the effectiveness of PupilRec by recruiting 67 volunteers. The overall results show that PupilRec can accurately estimate users' preference and can recommend products users interested in. © 2014 IEEE.

关键词： Smartphones

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