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检索条件"任意字段=Proceedings of the 12th ACM International Conference on Distributed and Event-based Systems"

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Machine Learning and Knowledge Extraction 7th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 international Cross-Domain conference, CD-MAKE 2023

Machine Learning and Knowledge Extraction 7th IFIP TC 5, TC ...

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Machine Learning and Knowledge Extraction 7th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 international Cross-Domain conference, CD-MAKE 2023

ISBN: (纸本)9783031408366

the proceedings contain 18 papers. the special focus in this conference is on Machine Learning and Knowledge Extraction. the topics include: Enhancing Trust in Machine Learning systems by Formal Methods: With an Application to a Meteorological Problem;sustainability Effects of Robust and Resilient Artificial Intelligence;the Split Matters: Flat Minima Methods for Improving the Performance of GNNs;probabilistic Framework based on Deep Learning for Differentiating Ultrasound Movie View Planes;standing Still Is Not an Option: Alternative Baselines for Attainable Utility Preservation;Memorization of Named Entities in Fine-Tuned BERT Models;event and Entity Extraction from Generated Video Captions;fine-Tuning Language Models for Scientific Writing Support;efficient Approximation of Asymmetric Shapley Values Using Functional Decomposition;domain-Specific Evaluation of Visual Explanations for Application-Grounded Facial Expression Recognition;human-in-the-Loop Integration with Domain-Knowledge Graphs for Explainable Federated Deep Learning;the Tower of Babel in Explainable Artificial Intelligence (XAI);Hyper-Stacked: Scalable and distributed Approach to AutoML for Big Data;transformers are Short-Text Classifiers;reinforcement Learning with Temporal-Logic-based Causal Diagrams;using Machine Learning to Generate a Dictionary for Environmental Issues.

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Real-time processing of geo-distributed financial data 21

Real-time processing of geo-distributed financial data

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15th acm international conference on distributed and event-based systems, DEBS 2021

作者： Kontaxakis, Antonios Deligiannakis, Antonios Arndt, Holger Burkard, Stefan Kettner, Claus-Peter Pelikan, Elke Noack, Kathleen Athena Research Centre and Technical University of Crete Greece Spring Techno GmbH and Co. Kg Germany

ISBN: (纸本)9781450385558

Enabling real-time processing of financial data streams is extremely challenging, especially considering that typical operations that interest investors often require combining data across (a potentially quadratic number of) different pairs of stocks. In this paper we present the architecture and the components of our system for the real-time processing of geo-distributed financial data at scale. Our system can scale to larger resources and utilizes a Synopses Data Engine in order to efficiently handle complex cross-stock queries, such as the ones required to detect systemic risk or to help forecast the value of some stock. the rich set of supported operations is depicted at the Visual Analytics component of our system. © 2021 acm.

关键词： Data handling

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An event-Driven Spectrum-Aware Routing Protocol based on Hungarian Algorithm in Cognitive Radio Sensor Networks

An Event-Driven Spectrum-Aware Routing Protocol Based on Hun...

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international conference on Communication systems and Network Technologies (CSNT)

作者： Hao Wang Long Tan Department of Computer Science and Technology Heilongjiang University Harbin China

An event-driven spectrum-aware routing algorithm based on the Hungarian algorithm (ESRH) is proposed to improve the spectrum utilization and the energy efficiency of cognitive radio sensor networks(CRSN). the method performs clustering in a distributed and self-organized manner and selects the node with the largest weight as the cluster head (CH). the Hungarian algorithm is used to assign the channels with smaller occupancy probability of primary user (PU), longer idle time and higher throughput to sensor nodes (SUs), which reduces the channel competition from SUs to PUs and improves the data transmission success rate. the gateway nodes and packet forwarding nodes are used for relay communication between clusters. Simulation results show that ESRH outperforms ESAC and ERP algorithms in terms of transmission performance, routing stability and network lifetime in a multi-round event-driven CRSN.

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Binary Logistic Regression based Intrusion Detection System for CAN bus Security 12

Binary Logistic Regression based Intrusion Detection System ...

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12th IEEE international conference on Identification, Information and Knowledge in the Internet of things, IIKI 2024

作者： Alfardus, Asma Rawat, Danda B. Department of Electrical Engineering and Computer Science WashingtonDC20059 United States

ISBN: (纸本)9798331510633

the complex distributed systems installed in vehicles represent the cutting edge of the automotive industry. Electronic control units communicate with each other by sending and receiving messages over a well-known protocol called the Controller Area Network (CAN) bus system. Car Broadcast is a new, but insecure, way to communicate between external electronic devices. However, today's vehicles are on the brink of security because the CAN network lacks a secure authentication and authorization mechanism. the rise in cyber attacks such as spoofing, spoofing and most commonly denial of service attacks is the result of uncertain measures in the CAN bus network. Although many intrusion detection systems have been developed to provide more secure communication in the vehicle, CAN is still far from being the most secure communication protocol. Since cyber attacks can come from a little-known or completely unknown source, it is essential to take a probabilistic approach based on previous observations from previous attacks. therefore, we propose a new intrusion detection system that uses binary logistic regression (BLR) to detect and mitigate attacks on a CAN bus network. Binary logistic regression is a very popular predictive model that is widely used in various fields. In binary logistic regression, data is first analyzed, then the probability of individual events is estimated by observing previous data, and then a binary classification model is created. An evaluation of the well-known Nsl-kdd and Kdd-99 datasets shows that our proposed method has a dominant overall performance. the final detection rate is 099.031% using Nsl-kdd with a positive rate as low as 00.073% and the rate of detection is 099.043% using kdd-99 with a positive false rate as low as 00.046%˙ Specifically, to detect denial of service (DoS) attacks, the proposed system achieved a detection rate of 099.061% and 099.098% in Nsl-kdd and kdd-99 dataset respectively. Comparative evaluation confirmed that BLR i

关键词： Automotive industry

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2022 14th international conference on Contemporary Computing, IC3 2022

2022 14th International Conference on Contemporary Computing...

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14th international conference on Contemporary Computing, IC3 2022

ISBN: (纸本)9781450396752

the proceedings contain 103 papers. the topics discussed include: web application based text encryption;improving classifier efficiency by expanding number of functions in the dataset;brain tumor classification using machine learning and deep learning algorithms: a comparison classifying brain MRI images on the basis of location of tumor and comparing the various machine learning and deep learning models used to predict best performance;identification of undamaged buildings after the event of disaster using deep learning;SVM and logistic regression for facial palsy detection utilizing facial landmark features;implementation of zero-phase zero frequency resonator algorithm on FPGA;an exhaustive investigation on resource-aware client selection mechanisms for cross-device federated learning;advanced malware and their impact on virtualization: a case study on hybrid feature extraction using deep memory introspection;and achieving multilevel elasticity for distributed stream processing systems in the cloud environment: a review and conceptual framework.

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Scenario2Vector: Scenario Description Language based Embeddings for Traffic Situations 21

Scenario2Vector: Scenario Description Language Based Embeddi...

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12th acm/IEEE international conference on Cyber-Physical systems (ICCPS) part of CPS-IoT

作者： Harder, Aron Ranjit, Jaspreet Behl, Madhur Univ Virginia Dept Comp Sci Charlottesville VA 22903 USA

ISBN: (纸本)9781450383530

A popular metric for measuring progress in autonomous driving has been the "miles per intervention". this is nowhere near a sufficient metric and it does not allow for a fair comparison between the capabilities of two autonomous vehicles (AVs). In this paper we propose Scenario2Vector - a Scenario Description Language (SDL) based embedding for traffic situations that allows us to automatically search for similar traffic situations from large AV data-sets. Our SDL embedding distills a traffic situation experienced by an AV into its canonical components - actors, actions, and the traffic scene. We can then use this embedding to evaluate similarity of different traffic situations in vector space. We have also created a first of its kind, Traffic Scenario Similarity (TSS) dataset which contains human ranking annotations for the similarity between traffic scenarios. Using the TSS data, we compare our SDL embedding with textual caption based search methods such as Sentence2Vector. We find that Scenario2Vector outperforms Sentence2Vector by 13%;and is a promising step towards enabling fair comparisons among AVs by inspecting how they perform in similar traffic situations. We hope that Scenario2Vector can have a similar impact to the AV community that Word2Vec/Sent2Vec have had in Natural Language Processing datasets.

关键词： Autonomous vehicles

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Towards Efficient Oversubscription: On the Cost and Benefit of event-based Communication in MPI 12

Towards Efficient Oversubscription: On the Cost and Benefit ...

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12th IEEE/acm international Workshop on Runtime and Operating systems for Supercomputers, ROSS 2022

作者： Bierbaum, Jan Planeta, Maksym Hartig, Hermann Tu Dresden Germany Barkhausen Institut Germany

ISBN: (纸本)9781665475662

Contemporary HPC systems use batch scheduling of compute jobs running on exclusively assigned hardware resources. During communication, polling for progress is the state of the art as it promises minimal latency. Previous work on oversubscription and event-based communication, i.e. vacating the CPU while waiting for communication to finish, shows that these techniques can improve the overall system utilisation and reduce the energy consumption. Despite these findings, neither of the two techniques is commonly used in HPC systems today. We believe that the current lack of detailed studies of the low-level effects of event-based communication, a key enabler of efficient oversubscription for classical MPI-based applications, is a major obstacle to a wider adoption. We demonstrate that the sched_yield system call, which is often used for oversubscription scenarios, is not best suited for this purpose on modern Linux systems. Furthermore, we incorporate event-based communication into Open MPI and evaluate the effects on latency and energy consumption using an MPI micro-benchmark. Our results indicate that event-base communication incurs significant latency overhead but also saves energy. Both effects grow with the imbalance of the application using MPI. © 2022 IEEE.

关键词： Energy utilization

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the Influence of Wartime on distributed Team - Challenges, Leadership, Development: Ukraine Case 12

The Influence of Wartime on Distributed Team - Challenges, L...

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12th IEEE international conference on Intelligent Data Acquisition and Advanced Computing systems: Technology and Applications, IDAACS 2023

作者： Wolff, Carsten Verenych, Olena Turchaninova, Kateryna Dortmund University of Applied Science and Arts Dortmund44139 Germany Kyiv National University of Construction and Architecture Kyiv03037 Ukraine

ISBN: (纸本)9798350358056

the technological development of the last few years has made a contribution to the form of the work. the tendency to development of work environmental with features that are like those in real life has gone mainstream. the COVID-19 World Pandemic increased the rapidity of implementing these new environmental policies in businesses. Moreover, globalization and sustainability principles allow businesses to be more intercultural and more responsible for the environment. the approach to creating remote work is 'it' thing in business now. there are enough researcher results that evaluate the impact of remote work on teamwork. they marked merits and demerits and lightened the main changes in competencies as a leader and a team member by offering some time management and psychological approaches for organization and supporting high productivity during work time. However, russian aggression Ukraine, which has been starting since 2014 and received the second active phase on February 24, 2022, influenced the remote work. the business routine got new challenges. this paper is the first step toward understanding how a war can influence a team member and how it can influence remote work: Ukraine case. the main research questions that were formulated for this research were: (1) how much influence the war has on remote work;(2) if there has been a change in the team development model;and (3) how much influence the war has had on leadership competencies. the research was based on literature reviews and the authors' own experience. © 2023 IEEE.

关键词： distributed team project management remote work Tuckman Model wartime

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Blockchain for Transactive Energy Management of distributed Energy Resources in Smart Grid 21

Blockchain for Transactive Energy Management of Distributed ...

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12th acm international conference on Future Energy systems, e-Energy 2021

作者： Yang, Qing Wang, Hao Wu, Xiaoxiao Wang, Taotao Zhang, Shengli College of Electronics and Information Engineering Shenzhen University Shenzhen Guangdong China Department of Data Science and Ai Monash University MelbourneVIC Australia

ISBN: (纸本)9781450383332

this work presents the design and implementation of a blockchain system that enables the trustable transactive energy management for distributed energy resources (DERs). We model the interactions among DERs, including energy trading and flexible appliance scheduling, as a cost minimization problem. Considering the dispersed nature and diverse ownership of DERs, we develop a distributed algorithm to solve the optimization problem using the alternating direction method of multipliers (ADMM) method. Furthermore, we develop a blockchain system, on which we implement the proposed algorithm with the smart contract, to guarantee the transparency and correctness of the energy management. We prototype the blockchain in a small-scale test network and evaluate it through experiments using real-world data. the experimental results validate the feasibility and effectiveness of our design. © 2021 acm.

关键词： Smart power grids

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Towards autonomous semantic stream fusion for distributed video streams 21

Towards autonomous semantic stream fusion for distributed vi...

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15th acm international conference on distributed and event-based systems, DEBS 2021

作者： Nguyen-Duc, Manh Le-Tuan, Anh Hauswirth, Manfred Le-Phuoc, Danh Technical University of Berlin Open Distributed Systems Berlin Germany Open Distributed Systems Technical University of Berlin Fraunhofer Institute for Open Communication Systems Berlin Germany

ISBN: (纸本)9781450385558

Video streams are becoming ubiquitous in smart cities and traffic monitoring. Recent advances in computer vision with deep neural networks enable querying a rich set of visual features from these video streams. However, it is challenging to deploy these queries on edge devices due to the resource intensive nature of the computing operations of this sort. Hence, this paper will demonstrate our approach in pushing these computing operations closer to the video stream sources via autonomous stream fusion agents. these agents will facilitate an edge computing paradigm that enables edge devices to utilize its computing resources to serve federated queries over video streams. Our demonstration shows that edge devices can significantly alleviate the bottleneck of the centralized server in dealing with distributed video streams. © 2021 acm.

关键词： Deep neural networks

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