The paper deals with the problem of cooperatively finding a source of an unknown environmental field by a relatively small group of robots whose communication range is finite. To solve this problem, a distributed cont...
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The primary bottleneck of blockchain is shifting from consensus to execution due to recent advances in DAG-based consensus algorithms supporting over 100k TPS. Many blockchain systems segregate execution from ordering...
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ISBN:
(数字)9798350352917
ISBN:
(纸本)9798350352924;9798350352917
The primary bottleneck of blockchain is shifting from consensus to execution due to recent advances in DAG-based consensus algorithms supporting over 100k TPS. Many blockchain systems segregate execution from ordering, missing the opportunity to harness potential parallelism in consensus-produced batches. In this paper, we propose a new deterministically orderable concurrency control algorithm, OptME, which improves the performance of execution phase by exploiting inherent parallelism among transactions. This algorithm analyzes transaction dependencies to extract parallelism, and determines the total order of transaction execution. OptME consists of three steps: (1) building a transaction dependency graph, (2) generating a parallel execution schedule, and (3) executing transactions based on the schedule. We employ several optimizations, including parallel dependency graph construction, early abort detection, and efficient reordering with an optimistic assumption. Our evaluation demonstrates that OptME achieves up to 350k TPS and outperforms a state-of-the-art concurrency control algorithm, even under high contention scenarios.
As the construction of the smart grid moves forward gradually, hundreds of millions of terminal devices will be linked to it. The central master station will be under tremendous pressure due to the enormous diverse da...
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In the past few years, the emergence of artificial intelligence combined with the surface electromyography (sEMG) paved the way to the development of smart and wearable electronic systems for human-machine interaction...
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This paper presents an agent-agnostic framework to control swarms of robots tasked with temporal and logical missions expressed as Metric Temporal Logic (MTL) formulas. We consider agents that can receive global comma...
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ISBN:
(纸本)9798350323658
This paper presents an agent-agnostic framework to control swarms of robots tasked with temporal and logical missions expressed as Metric Temporal Logic (MTL) formulas. We consider agents that can receive global commands from a high-level planner, but no inter-agent communication. Moreover, agents are grouped into sub-swarms whose number can vary over the mission time horizon due to splitting and merging. However, a strict upper bound on the maximum number of sub-swarms is imposed to ensure their safe operation in the environment. We propose a two-phase approach. In the first phase, we compute the trajectories of the sub-swarms, splitting, and merging actions using a Mixed Integer Linear Programming approach that ensures the satisfaction of the MTL specification with minimal swarm division over the mission time horizon. Moreover, it enforces the upper bound on the number of sub-swarms. In the second phase, splitting fractions for sub-swarms resulting from splitting actions are computed. A distributed randomized protocol with no interagent communication ensures agent assignments matching the splitting fractions. Finally, we show the operation and performance of the approach in simulations with multiple tasks that require swarm splitting or merging.
As the earth's temperature increases, efficient heating, cooling, and lean building designs are critical to ensure environmental longevity for future generations. Reducing the usage of chemically involved mechanis...
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ISBN:
(纸本)9798350333398
As the earth's temperature increases, efficient heating, cooling, and lean building designs are critical to ensure environmental longevity for future generations. Reducing the usage of chemically involved mechanisms such as cooling units with hydrofluorocarbon refrigerants and improving natural absorption or reflection of sunlight is vital for sustainability and mandatory in any intelligent city design. This paper focuses on active temperature control utilizing novel intelligent window system designs that permit interior and external fixation. In addition to providing new smart home capabilities, the proposed system aims to reduce energy consumption, further providing benefits, including consumer cost savings and a reduction of fossil fuel usage. The paper provides the experimental test bed design and prototype of the intelligent system termed TRASS (Temperature Regulating Autonomous Solar Shade). TRASS is a self-sufficient product with communication capabilities and autonomous use. As the experimental results show, the autonomous control of the prototype allows accurate temperature regulation by managing the amount of sunlight. The model incorporates rechargeable batteries and alternative energy, allowing older generational homes and buildings to employ the system without needing external power. The system continuously maintains necessary environmental conditions indoors without user interaction. However, TRASS permits manual adjustments to ensure proper management at desired conditions.
This article makes use of a damper control system to maximize the output power of a wind power system while minimizing variations in frequency damping. The controller, which is dependent on wind speed and frequency fl...
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The proceedings contain 142 papers. The topics discussed include: fault analysis of ship DC power system;event triggered and self-triggered formation control of multi agent systems;mitigating credit card fraud: a mach...
ISBN:
(纸本)9798350366570
The proceedings contain 142 papers. The topics discussed include: fault analysis of ship DC power system;event triggered and self-triggered formation control of multi agent systems;mitigating credit card fraud: a machine learning perspective;automatic license plate detection using information processing system vision and deep learning;face detection and recognition based intelligence surveillance robot for attendance system;Clusterboost: an Airbnb recommendation engine using metaclustering;key management in space integrated terrestrial network: a cybersecurity perspective;user profile based movie recommender system using machine learning;and utilization of non-orthogonal multiple access (NOMA) for spectral efficiency in mixed fading environments.
In the evolving field of cybersecurity, efficiently managing Attribute-Based Access control (ABAC) remains crucial due to complex attribute relationships. This paper introduces the ALBERT-PFN model, a novel access con...
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ISBN:
(纸本)9798350352900;9798350352894
In the evolving field of cybersecurity, efficiently managing Attribute-Based Access control (ABAC) remains crucial due to complex attribute relationships. This paper introduces the ALBERT-PFN model, a novel access control attribute mining approach that employs deep learning to transform ABAC challenges into joint entity and relationship extraction tasks. The model leverages ALBERT for contextual word embeddings and a Positional Feature Network (PFN) that dynamically interprets relationships between entities, significantly enhancing both the accuracy and automation of attribute mining. Experimental results show that ALBERT-PFN achieves a precision of 88.13%, a recall of 91.80%, and an F1 score of 89.93% in entity recognition, outperforming existing methods. In relationship extraction, it further excels with a precision of 81.55%, a recall of 72.94%, and an F1 score of 77.01%, underscoring its effectiveness in developing dynamic and precise ABAC policies.
Breast cancer is a common disease that predominantly affects women worldwide, with the potential to be fatal. Histopathologists utilize various criteria to examine tissue samples under a microscope for diagnosing canc...
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