This paper proposes a novel adaptive synthetic inertia (SI) control scheme for the battery energy storage system (BESS) in the wind farm. The proposed approach dynamically adjusts the amplitude of the direct current (...
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作者：
Samant, Indu SekharPanda, SubhasisRout, Pravat Kumar
Department of Computer Science Engineering Odisha India
Department of Electrical Engineering Odisha India
Department of Electrical and Electronics Engineering Odisha India
Smart grids are advanced power systems that have the potential to bring enormous benefits to power consumers and providers. Smart grids utilize advanced communication and information technologies to deliver power more...
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Anemia among young people has positive correlation with susceptibility and impede cognitive *** per WHO 2019 statistics global prevalence rate of anemia is 33 percent. This work aims to predict anemia with inferences ...
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作者：
Lv, ChengDepartment of Computer Science
School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture Beijing100044 China
In response to the shortcomings of the SPOC course "Introduction to Computational Thinking"at Beijing University of Civil engineering and Architecture, the teaching team has transformed and improved the cour...
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Smart meters are an important component of the smart grid, and the large-scale deployment of meters on the user side generates a large amount of data that brings huge expenses to the smart grid. In addition, attackers...
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The hope for a futuristic global quantum internet that provides robust and high-capacity quantum information transfer lies largely on qudits,the fundamental quantum information carriers prepared in high-dimensional su...
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The hope for a futuristic global quantum internet that provides robust and high-capacity quantum information transfer lies largely on qudits,the fundamental quantum information carriers prepared in high-dimensional superposition ***,preparing and manipulating N-dimensional flying qudits as well as subsequently establishing their entanglement are still challenging tasks,which require precise and simultaneous maneuver of 2(N-1)parameters across multiple degrees of ***,using an integrated approach,we explore the synergy from two degrees of freedom of light,spatial mode and polarization,to generate,encode,and manipulate flying structured photons and their formed qudits in a four-dimensional Hilbert space with high quantum fidelity,intrinsically enabling enhanced noise resilience and higher quantum data *** four eigen spin–orbit modes of our qudits possess identical spatial–temporal characteristics in terms of intensity distribution and group velocity,thereby preserving long-haul coherence within the entirety of the quantum data transmission *** leveraging the bi-photon entanglement,which is well preserved in the integrated manipulation process,we present versatile spin–orbit cluster states in an extensive dimensional Hilbert *** cluster states hold the promise for quantum error correction which can further bolster the channel robustness in long-range quantum communication.
The paper presents the implementation of a Switched Capacitor Power Amplifier (SCPA) to be integrated into a Narrowband Internet of Things (NB-IoT) Transceiver. The SCPA is designed to operate at a frequency of 0.9GHz...
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Utilizing student-led case studies as an innovative educational tool can effectively introduce real-world practices into the power engineering classroom. By assigning students to draft a story around a case study, the...
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Knowledge Graphs (KGs) are potent frameworks for knowledge representation and reasoning. Nevertheless, KGs are inherently incomplete, leaving numerous uncharted relationships and facts awaiting discovery. Deep learnin...
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Knowledge Graphs (KGs) are potent frameworks for knowledge representation and reasoning. Nevertheless, KGs are inherently incomplete, leaving numerous uncharted relationships and facts awaiting discovery. Deep learning methodologies have proven effective in enhancing KG completion by framing it as a link prediction task, where the goal is to discern the validity of a triple comprising a head, relation, and tail. The significance of structural information in assessing the validity of a triple within a KG is well-established. However, quantifying this structural information poses a challenge. We need to pinpoint the metric that encapsulates the structural information of a triple and smoothly incorporate this metric into the link prediction learning process. In this study, we recognize the critical importance of the intersection among the k-hop neighborhoods of the head, relation, and tail when determining the validity of a triple. To address this, we introduce a novel randomized algorithm designed to efficiently generate intersection features for candidate triples. Our experimental results demonstrate that a straightforward fully-connected network leveraging these intersection features can surpass the performance of established KG embedding models and even outperform graph neural network baselines. Additionally, we highlight the substantial training time efficiency gains achieved by our network trained on intersection features. Copyright 2024 by the author(s)
The ultimate goal of any educational institution is to offer the best educational experience and impart knowledge effectively to students. Identifying students who need extra support and taking appropriate actions to ...
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