the proceedings contain 28 papers. the special focus in this conference is on Big Data and Artificial Intelligence. the topics include: DLMLP with Elastic-Net Regularization for Hyperspectral Image Classific...
ISBN:
(纸本)9783031818202
the proceedings contain 28 papers. the special focus in this conference is on Big Data and Artificial Intelligence. the topics include: DLMLP with Elastic-Net Regularization for Hyperspectral Image Classification;disEvD: A Benchmark Dataset for Disruptive event Identification from Online Social Network;adaptive Temporal Random Walks for Graph Representation;SDG_HHAG Framework: Homogeneous and Heterogeneous Attributed Graphs;dynamic Deployment of Serverless Data Pipeline on Fog Nodes;Matrix Factorization of Large Scale Data Using Block based Approach and GPU Acceleration;Advanced HLS for Reconfigurable Image Processing in Big Data systems;explainable Detection and Analysis of Cauliflower Leaf Diseases;MARINE: A Computer Vision Model for Detecting Rare Predator-Prey Interactions in Animal Videos;a Novel Multi-task Learning Framework for Predicting Traffic Congestion;MLN-geeWhiz: Supporting Complex Data Analysis Including Visualization;gCDR: A Group Aided Cross-Domain Recommendation Framework;CKELM: Unified Approach to Parking Space Classification for All Weather Types;GCN-MLP Framework for EEG-based Vigilance Estimation for Variable Data Length;Deep Learning Framework for Early Diagnosis of COPD and Respiratory Diseases Using Lung Sound Analysis;evaluating the Cultural Sensitivity of Large Language Models in Mental Health Support: A Framework Inspired by Ubuntu Values;explainable Graph Neural Networks to Identify Potential Atoms and Chemical Bonds of Drug Candidates from Drug Target Interactions;enhancing Cardiovascular Disease Prediction Among Middle-Aged Individuals Using Reinforcement Learning Dynamic Ensemble Selection with Customizable Actions and Exploration-Exploitation Balance;evaluating Deep Learning Embedding Techniques for Code Smell Detection;fedNorm: Optimised Federated Learning Strategy Using Hybrid Regularisation Norm;efficient Self-Supervised Contrastive Learning with Representation Mixing;Smart E-learning Development Tool Using Generative AI and Retri
Since current versions of Reversible Data Hidden in Encrypted Images (RDH-EI) rely on a single data-hider, recovering the original image will not be possible in the eventthat the data-hider is compromised. In order t...
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the proceedings contain 10 papers. the special focus in this conference is on Smart Cities and Green ICT systems. the topics include: Towards Better Modeling of Bicycle Lateral Motion: Model Development, Naturalistic ...
ISBN:
(纸本)9783031709654
the proceedings contain 10 papers. the special focus in this conference is on Smart Cities and Green ICT systems. the topics include: Towards Better Modeling of Bicycle Lateral Motion: Model Development, Naturalistic Data Acquisition, and Model Validation;small Vehicle Damage Detection with Acceleration Spectrograms: An Autoencoder-based Anomaly Detection Approach;modeling the Traffic Scene in Intelligent Transport systems for Cooperative Connected Automated Mobility;a Technique for Authentic Fatigue Driving Detection Using Nighttime Infrared Images;identifying Challenges in Remote Driving;decision Tree based Incident Detection for distributed Progressive Signal System in an Organic Traffic Control System;monitoring Traffic Congestion Using Trust-based Smart Road Signs;infrastructure-Assisted Collective Perception Service with Emphasis on Vulnerable Road User Perception.
event sourcing is increasingly used and implemented in event-basedsystems for maintaining the evolution of application state. However, unbounded event logs are impracticable for many systems, as it is difficult to al...
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ISBN:
(纸本)9781450357821
event sourcing is increasingly used and implemented in event-basedsystems for maintaining the evolution of application state. However, unbounded event logs are impracticable for many systems, as it is difficult to align scalability requirements and long-term runtime behavior withthe corresponding storage requirements. To this end, we explore the design space of log pruning approaches suitable for event-sourced systems. Furthermore, we survey specific log pruning mechanisms for event-sourced logs. In a brief evaluation, we point out the trade-offs when applying pruning to event logs and highlight the applicability of log pruning to event-sourced systems.
distributedevent-sourced systems adopt a fairly new architectural style for data-intensive applications that maintains the full history of the application state. However, the performance implications of such systems ...
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ISBN:
(纸本)9781450357821
distributedevent-sourced systems adopt a fairly new architectural style for data-intensive applications that maintains the full history of the application state. However, the performance implications of such systems are not yet well explored, let alone how the performance of these systems can be improved. A central issue is the lack of systematic performance engineering approaches that take into account the specific characteristics of these systems. To address this problem, we suggest a methodology for performance engineering and performance analysis of distributedevent-sourced systemsbased on specific measurements and subsequent, targeted optimizations. the methodology blends in well into existing software engineering processes and helps developers to identify bottlenecks and to resolve performance issues. Using our structured approach, we improved an existing event-sourced system prototype and increased its performance considerably.
Stateful applications are based on the state they hold and how it changes over time. this history of state changes is usually discarded as the application progresses. By building on concepts from event processing and ...
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ISBN:
(纸本)9781450357821
Stateful applications are based on the state they hold and how it changes over time. this history of state changes is usually discarded as the application progresses. By building on concepts from event processing and storing the application history, we envision a novel programming paradigm that supports retroaction. Retroactive computing introduces new opportunities for a developer to access and even modify an application timeline. By enabling the exploration of alternative scenarios, retroactive computing establishes powerful new ways to debug systems and introduces new approaches to solve problems. Initial work has shown the practicality and possibilities of this new programming paradigm and introduces further research questions and challenges.
Popularly known for powering cryptocurrencies such as Bitcoin and Ethereum, blockchains is seen as a disruptive technology capable of impacting a wide variety of domains, ranging from finance to governance, by offerin...
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ISBN:
(纸本)9781450357821
Popularly known for powering cryptocurrencies such as Bitcoin and Ethereum, blockchains is seen as a disruptive technology capable of impacting a wide variety of domains, ranging from finance to governance, by offering superior security, reliability, and transparency in a decentralized manner. In this tutorial presentation, we first study the original Bitcoin design, as well as Ethereum and Hyperledger, and reflect on their design from an academic perspective. We provide an overview of potential applications and associated research challenges, as well as a survey of ongoing research projects. We mention opportunities blockchain creates for event-basedsystems. Finally, we conclude with a walkthrough showing the process of developing a decentralized application (DApp), using a popular Smart Contract language (Solidity) for the blockchain platform of Ethereum.
Evaluation of distributed Complex event Processing (CEP) systems is a rather challenging task. To simplify this task, we developed the open simulation framework for distributed CEP, called DCEP-Sim. the goal of this t...
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ISBN:
(纸本)9781450357821
Evaluation of distributed Complex event Processing (CEP) systems is a rather challenging task. To simplify this task, we developed the open simulation framework for distributed CEP, called DCEP-Sim. the goal of this tutorial is to facilitate the process of using DCEP-Sim. Since DCEP-Sim is designed and implemented in the popular network simulator ns-3 we introduce the most important concepts of ns-3. Simulations in ns-3 are configured and executed though a main program called an ns-3 script. We use a simple example script to explain how simulations with DCEP-Sim are set up and executed. To give an idea how DCEP-Sim can be adjusted to particular needs, we explain how DCEP-Sim can be adapted (e.g., through changing the workload and the network topology) and how new distributed CEP solutions can be added by explaining how to add a new operator to DCEP-Sim.
the primary consumption of news is now increasingly online and has resulted in a large volume of online news from varied news outlets. Consequently, news aggregators have become popular for clustering, ranking and per...
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ISBN:
(纸本)9781450357821
the primary consumption of news is now increasingly online and has resulted in a large volume of online news from varied news outlets. Consequently, news aggregators have become popular for clustering, ranking and personalization of news which process millions of news articles each day. In addition, since news articles stream constantly, there is a need for a scalable event-based system which can facilitate news mining in an online fashion. To address these challenges, we propose a distributed framework to process news articles and cluster them to facilitate many news mining tasks. the core of our system is a novel and scalable distributed clustering algorithm using Locality Sensitive Hashing which is robust to outliers and noise. In addition, we also propose an online version of the clustering algorithm to dynamically maintain the news event clusters. We implement the proposed solution on Apache Spark. Using a large news collection with over 8 million news articles, we show that our approach outperforms widely-used clustering techniques such as K-Means both in run time and clustering quality.
Trade surveillance is an important concern in recent trading engines to detect and prevent fraudulent trades at earliest. In traditional trading platforms, to achieve high throughput and low latency requirements focus...
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ISBN:
(纸本)9781450357821
Trade surveillance is an important concern in recent trading engines to detect and prevent fraudulent trades at earliest. In traditional trading platforms, to achieve high throughput and low latency requirements focus of developers has always been on high-performance languages such as C, C++ and FPGA basedsystems. these systems have limitations of scalability and fault-tolerance. Withthe arrival of in-memory technology, these requirements can be met with Java-based frameworks like Ignite, Flink, Spark. In this paper, we propose a novel way of implementing trade surveillance architecture using Apache Ignite In-Memory Data Grid (IMDG). Paper discusses the engineering approach to tune system architecture on the single node in terms of achieving high throughput, low latency and then scaling out to multiple nodes.
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