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Analysis of Behavioral Facilitation Tweets Considering the Emotion of Disaster Victims

Analysis of Behavioral Facilitation Tweets Considering the E...

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IEEE international conference on Big Data and Cloud computing (BdCloud)

作者： Futo Yamamoto Tadahiko Kumamoto Akiyo Nadamoto Graduate School of Natural Science Konan University Kobe Japan Faculty of Information and Computer Science Chiba Institute of Technology Narashino Japan Faculty of Intelligence and Information Konan University Kobe Japan

When disasters such as typhoons, floods, earthquakes, and wildfires occurred, people post a great deal of information that encourage disaster victims to take action on Twitter. We call such information that encourages people to take action “Behavioral Facilitation Tweet (following BF-tweet).” We believe that such information has a significant impact on the behavior of disaster victims. However, some BF-tweets are useful but others are not, because the content of BF-tweets varies. Useful information can encourage disaster victims to take appropriate action. On the other hand, useless information is an obstacle when the system quickly conveys accurate information to disaster victims. When the tweet is a BF-tweet, useless information can be detrimental to the victim. Furthermore, useful information for the victim depends on their emotion. Therefore, we believe that presenting useful information according to the situation of disaster victims can encourage them to take more appropriate actions. In this paper, we focus on the victim's negative emotions and analyze the characteristics of useful behavioral facilitation information for each emotion. Specifically, we analyze the negative emotions of the target disaster victims and group them into four categories: “trepidation/fear/anxiety”, “worry”, “trouble”, and “discomfort.” The results of the analysis show that it is better to present different types of information depending on the type of negative emotions felt by the victims.

关键词： Rain Tropical cyclones Social networking (online) Earthquakes Blogs Focusing Fires

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Risk Perception and Misinformation in Brazilian Twitter during COVID-19 Infodemic

Risk Perception and Misinformation in Brazilian Twitter duri...

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IEEE international conference on Big Data and Cloud computing (BdCloud)

作者： Rafael S. Medina Ferreira Ana Paula Couto da Silva Fabricio Murai Department of Computer Science Universidade Federal de Minas Gerais Belo Horizonte Brazil Worcester Polytechnic Institute Worcester MA USA

During the COVID-19 pandemic, different groups had different perceptions of how dangerous the coronavirus was. This difference in behavior was intensified by the large amount of misinformation shared across social media. This work presents an analysis aimed at understanding the extent to which people perceived risk at different levels, and at uncovering the relationship between these differences and the spread of misinformation. In particular, we focus on Brazil, because it is well-known that its Ministry of Health has sponsored campaigns that raised suspicious regarding the effectiveness of the vaccines. To achieve this goal, we gathered tweets written in Portuguese related to the COVID-19 and analyzed their psycholinguistic traits. Among those traits, we found ‘Anxiety’ to be a good proxy for risk perception. We validate this choice by showing that, at moments of high (resp. low) infection rates in the world, the Anxiety score was higher (resp. lower). We grouped users into “low” and “high” risk perception based on the users' anxiety score, and analyzed the relation of each group with the spread of misinformation. Our results show that Twitter users with a lower perceived risk were more inclined to share fake news and harmful information, while the group with a higher level of anxiety tends to share more scientifically-backed information. This is an important step towards helping minimize the spread of false and harmful health information around the internet.

关键词： COVID-19 Social networking (online) Pandemics Anxiety disorders Blogs Transformers Vaccines

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Enhancing the Efficiency of UAV Swarms Communication in 5G Networks through a Hybrid Split and Federated Learning Approach

Enhancing the Efficiency of UAV Swarms Communication in 5G N...

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international Wireless Communications and Mobile computing conference, IWCMC

作者： Wenji He Haipeng Yao Fu Wang Zunliang Wang Zehui Xiong State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China School of Electronic & Engineering Beijing University of Posts and Telecommunications Beijing China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Tampines Singapore

The integration of unmanned aerial vehicles (UAVs) with 5G networks presents a promising opportunity to revolutionize wireless communication and provide high-speed internet access to remote areas. Nevertheless, the vast quantity of data generated by UAVs requires the implementation of efficient distributed learning techniques. In this study, we present a novel hybrid approach that merges Federated Learning (FL) and Split Learning (SL) to optimize the performance of UAV swarms in 5G networks. While FL is capable of reducing communication overhead and preserving privacy, SL can enhance the accuracy of the model through the utilization of the local computational resources of each device. To realize the hybrid approach, we first locally train the model on each UAV using split learning. Subsequently, the encrypted model parameters are transmitted to a central server for federated averaging. Finally, the updated model is dispatched back to each UAV for local fine-tuning, and this cycle is repeated until convergence is achieved. The hybrid approach capitalizes on the strengths of both FL and SL to minimize communication overhead and increase accuracy. To tackle the challenge of selecting the most suitable UAVs for participation in the learning process, we propose a multiagent algorithm that considers factors such as communication latency and training time. Our experimental results indicate that the proposed approach leads to substantial improvements in communication overhead and accuracy compared to conventional methods.

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Defensive Approach using Blockchain Technology against distributed Denial of Service attacks

Defensive Approach using Blockchain Technology against Distr...

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2021 international conference on Smart Systems and Advanced computing, SysCom 2021

作者： Mishra, Anupama Gupta, B.B. Peraković, Dragan Zhou, Zhili Swami Rama Himalayan University India National Institute of Technology Haryana Kurukshetra136119 India Asia University Taichung413 Taiwan Staffordshire University Stoke-on-TrentST4 2DE United Kingdom University of Zagreb Croatia Nanjing University of Information Science and Technology NUIST China

To maintain our network's security and fight cybercrime, we must stay up to date with the latest technological initiatives. Nowadays, DDoS (distributed Denial of Service) attacks include monetization and other risks and improvements in BGP (basic global protocol) routing have helped to combat these attacks. It is essential that we take all possible measures to maintain a safe space for online activities. The purpose of this work is to develop a botnet prevention system that leverages the advantages of Software Defined networking (SDN) along with the Blockchain. Here, we develop a mechanism to detect and mitigate botnets using blockchain and SDN. The results and performance shows that the proposed approach works efficiently. © 2021 Copyright for this paper by its authors.

关键词： Denial-of-service attack

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Improving Fog computing Infrastructure with Qos-Aware Resource Provisioning

Improving Fog Computing Infrastructure with Qos-Aware Resour...

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international conference on ICT in Business Industry & Government (ICTBIG)

作者： Dharmesh Dhabliya T. Kuppuraj Varun Ojha Primmia D R Divya Sharma Sanjiv Mathur Department of Information Technology Vishwakarma Institute of Technology Pune India Department of Computer Applications Karpagam Academy of Higher Education Coimbatore Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of ECE Prince Shri Venkateshwara Padmavathy Engineering College Chennai India Chitkara Centre for Research and Development Chitkara University Himachal Pradesh India Adjunct Faculty School of Mangement - PG Management JAIN (Deemed to be University) Bangalore Karnataka India

ISBN: (数字)9798331518981

ISBN: (纸本)9798331518998

In today's internet-enabled world, it's possible for everything to link to anything else. Because of this, a new way of working known as the Global Internet of Things has emerged, and it has begun to produce massive amounts of data. While it may be difficult to glean insights from streaming data, doing so has the potential to unleash technological marvels that will benefit society at large. It is critical to have a system in place to store, process, and forecast the data. Another active field of study, infrastructure development has seen a shift from centralised server systems to distributed cloud systems and is continuing to do so. There is a lot of room for investigation into the cloud's shortcomings in processing streaming data and making decisions in near real-time. Now that we have a network, the next step is to find a way to make it more useful and to distribute the load more evenly across the nodes via efficient routing. So that the network doesn't fail suddenly from too much traffic, the allocation is based on the present node load and the total network load. A balanced load on each node in the network is another result of optimised route selection. We built and tested a simple RL algorithm for an insignificant network that leverages the Q-Table. To get around the Q-Table's high level of complexity, an RL technique based on neural networks was suggested, which performs better on big networks. Over all time periods, the Proposed Deep RL technique outperforms Open Shortest Path First (OSPF) and Deep Neural Networks (DNN), achieving an accuracy of almost 92% in minimising average latency. In real-time applications, when minimising latency is crucial, its improved efficiency is evident.

关键词： Cloud computing Artificial neural networks Switches Quality of service Routing Real-time systems Software Resource management Servers Software defined networking

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Dynamic distributed Edge Resource Provisioning via Online Learning across Timescales 17

Dynamic Distributed Edge Resource Provisioning via Online Le...

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17th Annual IEEE international conference on Sensing, Communication and networking (IEEE SECON)

作者： You, Wencong Jiao, Lei Bhattacharya, Sourav Zhang, Yuan Univ Oregon Eugene OR 97403 USA Samsung AI Ctr Cambridge England Commun Univ China Beijing Peoples R China

ISBN: (纸本)9781728166308

The strategic management of distributed resources of mobile edge computing networks often requires managing different system components over different timescales. In this paper, we formulate a nonlinear mixed-integer program to capture the online optimization of the edge network's long-term cost, where we distribute workload more frequently on the fast timescale and provision resources less frequently on the slow timescale. We design a novel online learning framework consisting of three algorithms to make fast-timescale and slow-timescale fractional decisions, respectively, and round such decisions into integers. Our algorithms run in polynomial time in an online manner, jointly solving the original NP-hard problem that can contain arbitrary and unpredictable inputs. Via rigorous formal analysis, we prove a parameterized-constant competitive ratio as the performance guarantee for our approach. We conduct extensive evaluations with real-world data and confirm our approach's superiority over existing practices and state-of-the-arts.

关键词： Integer programming

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Pencil: A Pipelined Algorithm for distributed Stencils

Pencil: A Pipelined Algorithm for Distributed Stencils

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international conference on High Performance computing, networking, Storage and Analysis (SC)

作者： Wang, Hengjie Chandramowlishwaran, Aparna Univ Calif Irvine Irvine CA 92697 USA

ISBN: (纸本)9781728199986

Stencil computations are at the core of various Computational Fluid Dynamics (CFD) applications and have been well-studied for several decades. Typically they're highly memory-hound and as a result, numerous tiling algorithms have been proposed to improve its performance. Although efficient, most of these algorithms are designed for single iteration spaces on shared-memory machines. However, in CFD, we are confronted with multi-block structured girds composed of multiple connected iteration spaces distributed across many nodes. In this paper, we propose a pipelined stencil algorithm called Pencil for distributed memory machines that applies to practical CFD problems that span multiple iteration spaces. Based on an in-depth analysis of cache tiling on a single node, we first identify both the optimal combination of MPI and OpenMP for temporal tiling and the best tiling approach, which outperforms the stateof-the-art automatic parallelization tool Pluto by up to 1.92x. Then, we adopt DeepHalo to decouple the multiple connected iteration spaces so that temporal tiling can be applied to each space. Finally, we achieve overlap by pipelining the computation and communication without sacrificing the advantage from temporal cache tiling. Pencil is evaluated using 4 stencils across 6 numerical schemes on two distributed memory machines with Omni-Path and InfiniBand networks. On the Omni-Path system, Pencil exhibits outstanding weak and strong scalability for up to 128 nodes and outperforms MPI+OpenMP Funneled with space tiling by 1.33-3.41x on a multi-block grid with 32 nodes.

关键词： Computational fluid dynamics stencils multiple connected iteration spaces cache tiling pipelining distributedmemory machines

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Concurrent Wireless Cut-Through Forwarding: Ultra-Low Latency Multi-Hop Communication for the Internet of Things 16

Concurrent Wireless Cut-Through Forwarding: Ultra-Low Latenc...

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16th Annual international conference on distributed computing in Sensor Systems (DCOSS)

作者： Himmelmann, Nicolas Yuan, Dingwen Almon, Lars Hollick, Matthias Tech Univ Darmstadt Secure Mobile Networking Lab Dept Comp Sci Darmstadt Germany

ISBN: (纸本)9781728143514

Achieving low latency remains a challenge in today's industrial Internet of Things (IoT) applications, particularly if operated over wireless multi-hop networks. One idea that can distinctly reduce the multi-hop latency is the so-called cut-through forwarding, i.e., a node starts relaying a packet after it has only received a fraction of it by leveraging two radios. This paper proposes the novel concurrent wireless cut-through (CWCT) protocol based on a prototype design which combines two off-the-shelf IoT devices. To improve reliability and eliminate routing overhead, CWCT applies concurrent transmission and Golay error correction coding. Evaluation on a controlled topology and on a medium-size testbed shows the large reduction in latency of CWCT compared to Glossy and the high synchronicity of concurrent transmission. To further improve packet reliability, we need to reduce the out-of-band leakage.

关键词： wireless cut-through forwarding dual-radio platform ultra-low latency IoT concurrent transmission

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Cross-chain Oracle Based Data Migration Mechanism in Heterogeneous Blockchains 40

Cross-chain Oracle Based Data Migration Mechanism in Heterog...

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40th IEEE international conference on distributed computing Systems (ICDCS)

作者： Gao, Zhipeng Li, Hongli Xiao, Kaile Wang, Qian Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing Peoples R China

ISBN: (纸本)9781728170022

As things currently stand, the blockchain industry is siloed among many different platforms and protocols resulting in various islands of blockchains. Restrictions regarding assets transfers and data migration between different blockchains reduce the usability and comfort of users, and hinder novel developments within the blockchain ecosystem. Interoperability will be the main topics of next-generation blockchain technologies. In this paper, we focus on how to enable interoperability between two heterogeneous blockchains in the context of data migration. We first build an cross-chain data migration architecture based on data migration oracle. Second, we design a data migration mechanism based on former architecture. By employing the proposed data migration architecture, it is equivalent to opening a secure channel between two heterogeneous blockchains allowing secure data migration. By applying data migration mechanism, the confidentiality, integrity and security of migrated data can be well guaranteed.

关键词： heterogeneous blockchains data migration interoperability cross-chain oracle

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SeqDLM: a sequencer-based distributed lock manager for efficient shared file access in a parallel file system 22

SeqDLM: a sequencer-based distributed lock manager for effic...

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Proceedings of the international conference on High Performance computing, networking, Storage and Analysis

作者： Qi Chen Shaonan Ma Kang Chen Teng Ma Xin Liu Dexun Chen Yongwei Wu Zuoning Chen Tsinghua University China Alibaba Inc China National Supercomputing Center in Wuxi China Tsinghua University China and Chinese Academy of Engineering China

distributed locks are used to guarantee the distributed client-cache coherence in parallel file systems. However, they lead to poor performance in the case of parallel writes under high-contention workloads. We analyze the distributed lock manager and find out that lock conflict resolution is the root cause of the poor performance, which involves frequent lock revocations and slow data flushing from client caches to data servers. We design a distributed lock manager named SeqDLM by exploiting the sequencer mechanism. SeqDLM mitigates the lock conflict resolution overhead using early grant and early revocation while keeping the same semantics as traditional distributed locks. To evaluate SeqDLM, we have implemented a parallel file system called ccPFS using both SeqDLM and traditional distributed locks. Evaluations on 96 nodes show SeqDLM outperforms the traditional distributed locks by up to 10.3× for high-contention parallel writes on a shared file with multiple stripes.

关键词： sequencer file systems cache coherence high performance computing distributed lock

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