This paper presents a comprehensive Analysis of artificial intelligence (AI) techniques for advanced energy flow and power quality management in wind-PV-battery microgrids. The study compares optimization, machine lea...
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A key feature for most collaborative applications is their ability to distinguish access rights to shared documents in a dynamic group of collaborators. To achieve high availability and avoid single points of failure,...
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ISBN:
(纸本)9798350381993;9798350382006
A key feature for most collaborative applications is their ability to distinguish access rights to shared documents in a dynamic group of collaborators. To achieve high availability and avoid single points of failure, systems can replicate this access control policy across sites. Increasingly, Conflict-free Replicated Data Types (CRDTs) are used to this end. They embed conflict resolution strategies that take into account concurrent modifications to the policy but also to the document that it manages. However, few systems in the literature support multiple administrators, and those which do fall short of considering distributed applications where no node or group of nodes is central to its operation. To allow multiple concurrent edits of the policy in massively collaborative settings with no central server, we devise a specialized causal model that minimizes concurrency. Crucially our model allows to correct the document state in case operations have become unauthorized following a policy change. We apply our model to a CRDT replicating an access control policy with read and write rights on a collaborative document and admin rights on the policy. We end by studying flexible conflict resolution strategies, providing our underlying algorithms.
Autonomous target tracking with quadrotors has wide applications in many scenarios, such as cinematographic follow-up shooting or suspect chasing. Target motion prediction is necessary when designing the tracking plan...
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ISBN:
(纸本)9798350377712;9798350377705
Autonomous target tracking with quadrotors has wide applications in many scenarios, such as cinematographic follow-up shooting or suspect chasing. Target motion prediction is necessary when designing the tracking planner. However, the widely used constant velocity or constant rotation assumption can not fully capture the dynamics of the target. The tracker may fail when the target happens to move aggressively, such as sudden turn or deceleration. In this paper, we propose an intention-aware planner by additionally considering the intention of the target to enhance safety and robustness in aerial tracking applications. Firstly, a designated intention prediction method is proposed, which combines a user-defined potential assessment function and a state observation function. A reachable region is generated to specifically evaluate the turning intentions. Then we design an intention-driven hybrid A* method to predict the future possible positions for the target. Finally, an intention-aware optimization approach is designed to generate a spatial-temporal optimal trajectory, allowing the tracker to perceive unexpected situations from the target. Benchmark comparisons and real-world experiments are conducted to validate the performance of our method.
Even though data is continually being produced by a wide range of services, harnessing this data in an effective manner at different levels of abstraction is challenging. In this vision paper, we consider how data str...
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ISBN:
(纸本)9798400704437
Even though data is continually being produced by a wide range of services, harnessing this data in an effective manner at different levels of abstraction is challenging. In this vision paper, we consider how data streams representing real-world observations produced by geographically-distributed Internet of Things (IoT) devices can be used to adaptively fulfill a user's information needs. To solve this information need in a generic fashion, it is up to the underlying system to configure itself, split up processing across available resources, discover data sources, integrate available data, deal with uncertainty, integrate domain knowledge, etc. This is an interdisciplinary problem, and while many fields have considered the subproblems involved, this challenge requires a novel and integrated approach when these subproblems are put together. We propose Resource-intelligent Stream Reasoning as an overarching solution to tackle this interdisciplinary problem. We define a novel set of challenges that capture the need for an integrated approach, show the limitations in the the current state-of-the-art and define the future directions in order to realize Resource-intelligent Stream Reasoning.
Adversarial attacks in the Artificial Intelligence have received extensive coverage in the latest years. Such attacks have affected deep learning models and neural networks due to the weaknesses that are part of the A...
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Industrial controlsystems (ICS) play a crucial role in managing and controlling industrial assets. Due to their critical importance, adversaries are often highly motivated to target these systems, as a successful att...
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ISBN:
(纸本)9798350381993;9798350382006
Industrial controlsystems (ICS) play a crucial role in managing and controlling industrial assets. Due to their critical importance, adversaries are often highly motivated to target these systems, as a successful attack can disrupt the entire industry's operations. In general, to improve the system's security, proposed intrusion detection schemes often resort to traditional security mechanisms. As a consequence, due to their static nature, attackers can easily evade designed detection approaches. In light of this, this paper proposes a new dynamic network-based intrusion detection model for ICS, implemented in two phases. First, our scheme extracts network-related features to describe the current ICS environment behavior. Second, the security mechanisms are proactively selected based on the extracted network traffic behavior. As a result, our scheme can adjust the system's configuration based on the current assessed event. Experiments on a new dataset, featuring over 14 attack categories targeting a SCADA system revealed that traditional detection methods face challenges in handling diverse attack categories. Conversely, our proposed model improved the average true-positive rates by up to 20% while also improving the range of detected attacks.
Agricultural technology, ensuring reliability, and optimizing processes are paramount. This work explores the application of machine learning algorithms (ML) to two critical areas: agricultural advisory systems (AAS) ...
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Swarm robotics has garnered significant attention due to its ability to accomplish elaborate and synchronized tasks. Existing methodologies for motion planning of swarm robotic systems mainly encounter difficulties in...
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ISBN:
(纸本)9798350377712;9798350377705
Swarm robotics has garnered significant attention due to its ability to accomplish elaborate and synchronized tasks. Existing methodologies for motion planning of swarm robotic systems mainly encounter difficulties in scalability and safety guarantee. To address these limitations, we propose a Risk-aware swarm mOtion planner using conditional ValuE-at-Risk (ROVER) that systematically navigates large-scale swarms through cluttered environments while ensuring safety. ROVER formulates a finite-time model predictive control (FTMPC) problem predicated upon the macroscopic state of the robot swarm represented by a Gaussian Mixture Model (GMM) and integrates conditional value-at-risk (CVaR) to ensure collision avoidance. The key component of ROVER is imposing a CVaR constraint on the distribution of the Signed Distance Function between the swarm GMM and obstacles in the FTMPC to enforce collision avoidance. Utilizing the analytical expression of CVaR of a GMM derived in this work, we develop a computationally efficient solution to solve the non-linear constrained FTMPC through sequential linear programming. Simulations and comparisons with representative benchmark approaches demonstrate the effectiveness of ROVER in flexibility, scalability, and safety guarantee.
The development of an intelligent information system 'Smart Deposit' for mineral water recourse is an absolute innovation in this subject area. For oil and gas fields, smart well technologies have been used fo...
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Image denoising is needed if there is a need to remove noise while preserving details or structures in images in computing vision and image processing. Recent advancements in generative adversarial networks (GANs) and...
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