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A Pervasive Multi-physiological Signal-Based Emotion Classification with Shapelet Transformation and Decision Fusion 17th

A Pervasive Multi-physiological Signal-Based Emotion Classif...

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17th EAI international conference on Collaborative computing: networking, Applications, and Worksharing, CollaborateCom 2021

作者： Zhang, Shichao Zheng, Xiangwei Zhang, Mingzhe Guo, Gengyuan Ji, Cun School of Information Science and Engineering Shandong Normal University Jinan China Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology Jinan China

ISBN: (纸本)9783030926342

Emotion classification is a hot pot at present. Since physiological signals are objective and difficult to hide, physiological signals are commonly used in emotion classification methods. However, traditional emotional classification based on physiological signals faced the following challenges: low accuracy and low interpretability. For this, this paper proposes a pervasive multi-physiological signal-based emotion classification with shapelet transformation and decision fusion (PMSEC). In PMSEC, the shapelet transformation and feature extraction are carried out for ECG, GSR, and RA, respectively. Following by, six sub-classifiers are constructed for different physiological signals. Lastly, decision-level fusion is implemented to obtain final emotion results. Experimental results show that the proposed PMSEC is not only highly competitive but also has a broad application prospect compared with EEG-based classification method. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Electrocardiograms

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Proposing innovative intruder detection system for host machines in cloud computing 9

Proposing innovative intruder detection system for host mach...

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9th international conference on System Modeling and Advancement in Research Trends, SMART 2020

作者： Chaturvedi, Amit Kumar Kumar, Punit Sharma, Kalpana Engineering College CS Deptt. Ajmer Rajasthan India Bhagwant University CS Deptt. Ajmer Rajasthan India

ISBN: (纸本)9781728189086

there is very significant role of Virtualization in cloud computing. the physical hardware in the cloud computing reside with the host machine and the virtualization software runs on it. the virtualization allows virtual machines to exist. the host machine shares its physical components such as memory, storage, and processor ultimately to handle the needs of the virtual machines. If an attacker effectively compromises one VM, it could outbreak others on the same host on the network over long periods of time. this is an gradually more popular method for cross-virtual-machine attacks, since traffic between VMs cannot be examined by standard IDS/IPS software programs. As we know that the cloud environment is distributed in nature and hence more susceptible to various types of intrusion attacks which include installing malicious software and generating backdoors. In a cloud environment, where organizations have hosted important and critical data, the security of underlying technologies becomes critical. To alleviate the hazard to cloud environments, Intrusion Detection Systems (IDS) are a cover of defense. In this paper, we are proposing an innovative model for Intrusion Detection System for securing Host machines in cloud infrastructure. this proposed IDS has two important features: (1) signature based and (2) prompt alert system. © 2020 IEEE.

关键词： Cloud computing

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A Blockchain Based Cloud Integrated IoT Architecture Using a Hybrid Design 16th

A Blockchain Based Cloud Integrated IoT Architecture Using a...

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16th EAI international conference on Collaborative computing: networking, Applications, and Worksharing, CollaborateCom 2020

作者： Rupa, Ch Srivastava, Gautam Gadekallu, thippa Reddy Maddikunta, Praveen Kumar Reddy Bhattacharya, Sweta Department of Computer Science VR Siddhartha Engineering College Vijayawada520007 India Department of Mathematics and Computer Science Brandon University BrandonMBR7A 6A9 Canada School of Information Technology and Engineering VIT - Vellore Tamilnadu India

ISBN: (纸本)9783030675394

the Internet of things (IoT) and its applications are gaining popularity in recent years due to features like ease of use and increased availability of the Internet. We can enhance the efficiency of IoT based systems by adding other advanced technologies like cloud infrastructure and blockchain technology. through these enhancements IoT applications can be accessed at any time from any place. However, a database is required for storing the information of the application. Cloud infrastructure is an ideal solution for storing IoT based applications as it provides remote services such as storage, computation, and analysis. the major drawback of these applications are their inability to provide security and privacy for data. Blockchain technology helps in overcoming these drawbacks with features like immutability, transparency, and distributed structure. In this paper, a blockchain based cloud integrated IoT application is proposed that can assist to identify intruders through virtual monitoring. the main advantage of this application is that it can operate in areas where manual monitoring is challenging and data is stored in a blockchain-based tamper-free environment. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Blockchain

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Real-time adaptable resource allocation for distributed data-intensive applications over cloud and edge environments 9

Real-time adaptable resource allocation for distributed data...

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9th IEEE international conference on Cloud computing in Emerging Markets, CCEM 2020

作者： Tom-Ata, Jean-Didier Totow Kyriazis, Dimosthenis University of Piraeus Department of Digital Systems Piraeus Greece

ISBN: (纸本)9781728195766

Applications performance is strongly linked with the total load, the application deployment architecture and the amount of resources allocated by the cloud or edge computing environments. Considering that the majority of the applications tends to be data intensive, the load becomes quite dynamic and depends on the data aspects, such as the data sources locations, their distribution and the data processing aspects within an application that consists of micro-services. In this paper we introduce an analysis and prediction model that takes into account the characteristics of an application in terms of data aspects and the edge computing resources attributes, such as utilization and concurrency, in order to propose optimized resources allocation during runtime. © 2020 IEEE.

关键词： Resource allocation

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Proceedings - 2020 IEEE international conference on Cloud computing in Emerging Markets, CCEM 2020

Proceedings - 2020 IEEE International Conference on Cloud Co...

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9th IEEE international conference on Cloud computing in Emerging Markets, CCEM 2020

ISBN: (纸本)9781728195766

the proceedings contain 18 papers. the topics discussed include: real-time adaptable resource allocation for distributed data-intensive applications over cloud and edge environments;R peak detection in ECG signals using Chebfun;performance sensitivity of operating system parameters in microservice environments;sizing and coordinated scaling of microservices;managing congregations of people by predicting likelihood of a person being infected by a contagious disease like the COVID virus;biometric authentication security: an overview;ECOSTAR – energy conservation in swift through tiered storage architecture;and relevance of grid computing for India in the era of cloud computing.

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2018 9th international conference on computing, Communication and networking Technologies, ICCCNT 2018

2018 9th International Conference on Computing, Communicatio...

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9th international conference on computing, Communication and networking Technologies, ICCCNT 2018

ISBN: (纸本)9781538644300

the proceedings contain 266 papers. the topics discussed include: a k-factor CPU scheduling algorithm;an enhanced algorithm for variable reordering in binary decision diagrams;simulating pre-evacuation behavior in a virtual fire environment;real-time AQI monitoring system: an economical approach using wireless sensor network;horizon, a web-based user interface for managing services in OpenStack: an introspection;performance evaluation of nonlinear spatial filters on MR images;security and privacy designs based data encryption in cloud storage and challenges: a review;accelerative factor based spider monkey optimization;GSWA: a survivable dynamic multicast efficient RWA scheme in WDM mesh networks;a novel optimization approach for transmitter semi-angle and multiple transmitter configurations in indoor visible light communication links;CT-blocks: learning computational thinking by snapping blocks;a technique to reduce the capacitor size in two stage miller compensated opamp;RGB model based image enhancement technique for steganography;and an energy-efficient scheduling framework for cloud using learning automata.

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the AffectMove 2021 Challenge - Affect Recognition from Naturalistic Movement Data

The AffectMove 2021 Challenge - Affect Recognition from Natu...

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international conference on Affective computing and Intelligent Interaction Workshops and Demos (ACIIW)

作者： Temitayo Olugbade Roberto Sagoleo Simone Ghisio Nicolas Gold Amanda C De C Williams Beatrice De Gelder Antonio Camurri Gualtiero Volpe Nadia Bianchi-Berthouze University College London London United Kingdom Università di Genova GenovaItaly Maastricht University Maastricht The Netherlands

We ran the first Affective Movement Recognition (AffectMove) challenge that brings together datasets of affective bodily behaviour across different real-life applications to foster work in this area. Research on automatic detection of naturalistic affective body expressions is still lagging behind detection based on other modalities whereas movement behaviour modelling is a very interesting and very relevant research problem for the affective computing community. the AffectMove challenge aimed to take advantage of existing body movement datasets to address key research problems of automatic recognition of naturalistic and complex affective behaviour from this type of data. Participating teams competed to solve at least one of three tasks based on datasets of different sensors types and real-life problems: multimodal EmoPain dataset for chronic pain physical rehabilitation context, weDraw-l Movement dataset for maths problem solving settings, and multimodal Unige-Maastricht Dance dataset. To foster work across datasets, we also challenged participants to take advantage of the data across datasets to improve performances and also test the generalization of their approach across different applications.

关键词： Affective computing Social networking (online) Pain conferences Computational modeling Sensors Problem-solving

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Energy Efficiency for HDFS 9

Energy Efficiency for HDFS

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9th IEEE international conference on Cloud computing in Emerging Markets, CCEM 2020

作者： Das, Abhishek Snv, Bhargav Sanketh Reddy, N. Phalachandra, H.L. Pes University Dept. of Computer Science and Engineering Bangalore India Center for Cloud Computing and Big Data Pes University Bangalore India

ISBN: (纸本)9781728195766

the rapidly increasing growth of big data is leading to increased usage of distributed computing and clusters as this can enable tasks to be split and processed in parallel resulting in higher computational efficiency. Environments like Apache Hadoop use distributed file systems like the HDFS to support large clusters of typically commodity hardware to achieve the same. Commodity hardware present in HDFS consumes significant energy even when not in an active state, and considering our fragile ecosystem, reduction of the carbon footprint and conservation of energy in these environments is the focus of our work. We have evolved on a dynamic approach to Hadoop distributed File Systems (HDFS) that provides an energy efficient paradigm for Hadoop clusters by segregating the servers in the cluster to two 'Zones', a 'Hot-Zone', and a 'Cold-Zone'. We use energy efficient storage devices (SSDs), to store data that is frequently used for the hot zone. the Cold-Zone would have lesser energy efficient devices (HDDs) and would be used to store data that is not frequently used. the Hot-Zone would always be in an active state to compute while the cold zone would have the HDDs to be in a low power consumption state. We have also enhanced the block placement policy for HDFS to support dynamic block transfer among the two zones. © 2020 IEEE.

关键词： Energy efficiency

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9th EAI international conference on Cloud computing, CloudComp 2019 and the 4th EAI international conference on Smart Grid and Innovative Frontiers in Telecommunications, SmartGIFT 2019

9th EAI International Conference on Cloud Computing, CloudCo...

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9th EAI international conference on Cloud computing, CloudComp 2019 and the 4th EAI international conference on Smart Grid and Innovative Frontiers in Telecommunications, SmartGIFT 2019

ISBN: (纸本)9783030485122

the proceedings contain 55 papers. the special focus in this conference is on Cloud computing. the topics include: Rendering of three-Dimensional Cloud Based on Cloud computing;distributed Stochastic Alternating Direction Method of Multipliers for Big Data Classification;personalized Recommendation Algorithm Considering Time Sensitivity;cloud-Based Master Data Platform for Smart Manufacturing Process;a Semi-supervised Classification Method for Hyperspectral Images by Triple Classifiers with Data Editing and Deep Learning;A Survey of Image Super Resolution Based on CNN;design and Development of an Intelligent Semantic Recommendation System for Websites;a Lightweight Neural Network Combining Dilated Convolution and Depthwise Separable Convolution;resource Allocation Algorithms of Vehicle Networks with Stackelberg Game;research on Coordination Control theory of Greenhouse Cluster Based on Cloud computing;a Multi-objective Computation Offloading Method in Multi-cloudlet Environment;anomalous Taxi Route Detection System Based on Cloud Services;collaborative Recommendation Method Based on Knowledge Graph for Cloud Services;efficient Multi-user Computation Scheduling Strategy Based on Clustering for Mobile-Edge computing;Grazing Trajectory Statistics and Visualization Platform Based on Cloud GIS;Cloud-Based AGV Control System;a Parallel Drone Image Mosaic Method Based on Apache Spark;cycleSafe: Safe Route Planning for Urban Cyclists;prediction of Future Appearances via Convolutional Recurrent Neural Networks Based on Image Time Series in Cloud computing;video Knowledge Discovery Based on Convolutional Neural Network;time-Varying Water Quality Analysis with Semantical Mining Technology;a Survey of QoS Optimization and Energy Saving in Cloud, Edge and IoT;data-Driven Fast Real-Time Flood Forecasting Model for Processing Concept Drift;intelligent System Security Event Description Method.

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Emotion-Aware Transformer Encoder for Empathetic Dialogue Generation

Emotion-Aware Transformer Encoder for Empathetic Dialogue Ge...

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international conference on Affective computing and Intelligent Interaction Workshops and Demos (ACIIW)

作者： Raman Goel Seba Susan Sachin Vashisht Armaan Dhanda Delhi Technological University New Delhi India

Modern day conversational agents are trained to emulate the manner in which humans communicate. To emotionally bond with the user, these virtual agents need to be aware of the affective state of the user. Transformers are the recent state of the art in sequence-to-sequence learning that involves training an encoder-decoder model with word embeddings from utterance-response pairs. We propose an emotion-aware transformer encoder for capturing the emotional quotient in the user utterance in order to generate human-like empathetic responses. the contributions of our paper are as follows: 1) An emotion detector module trained on the input utterances determines the affective state of the user in the initial phase 2) A novel transformer encoder is proposed that adds and normalizes the word embedding with emotion embedding thereby integrating the semantic and affective aspects of the input utterance 3) the encoder and decoder stacks belong to the Transformer-XL architecture which is the recent state of the art in language modeling. Experimentation on the benchmark Facebook AI empathetic dialogue dataset confirms the efficacy of our model from the higher BLEU-4 scores achieved for the generated responses as compared to existing methods. Emotionally intelligent virtual agents are now a reality and inclusion of affect as a modality in all human-machine interfaces is foreseen in the immediate future.

关键词： Training Social networking (online) conferences Semantics Computer architecture Detectors Transformers

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