In this paper, we propose a resource-aware aggregation mapping approach for service function chain. Simulation results show that the proposed mapping approach achieves better performance in terms of blocking probabili...
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This paper proposes an electrical generation scheme, for interplanetary missions, utilizing an MW-scale two-excitation generator (TEG), a rectifier, and an isolated parallel output DC-DC converter (iPOD). The TEG cons...
This paper proposes an electrical generation scheme, for interplanetary missions, utilizing an MW-scale two-excitation generator (TEG), a rectifier, and an isolated parallel output DC-DC converter (iPOD). The TEG consists of a 9-phase stator configuration with two rotor segments: a wound field (WF) rotor and a permanent magnet (PM) rotor. This configuration allows for a quick response to power variations. By adjusting the injected current to the WF segment, the generator’s total back electromotive force (emf) can be varied, subsequently affecting the output power. This flexibility enables a wide power range for the thruster without requiring modifications to the mechanical rotation speed. The TRG’s output is rectified using a passive rectifier and then connected to the iDC2, which provides two outputs. The primary output connects to a high-voltage DC bus, supplying power to the thruster, while the auxiliary output feeds the low-voltage DC (LVDC) bus for the spacecraft’s power system. The auxiliary output of the converter provides an additional degree of freedom to support power changes in the thruster since the WF segment’s range is limited. Not only iPOD structure allow enhanced control over thruster power but also enables the NEP system to act as a backup power source for the spacecraft’s electricalsystems, complementing primary sources like batteries and solar panels. iPOD converts the passive rectifier output through a series switch and a high-frequency transformer that isolates the propulsion system from the power system. This configuration offers control over the power delivered to the thruster, while the auxiliary output regulates power for the LVDC link.
As smart load adoption grows on the electric power system, potential for losing load diversity increases, possibly in ways that impact system stability. Cloud computing resources are able to coordinate large amounts o...
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In the contemporary era of information technology, the exponential surge in data has rendered colossal potential value, which would be fully unlocked through data circulation and sharing. However, when the data contai...
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A recommender system(RS)relying on latent factor analysis usually adopts stochastic gradient descent(SGD)as its learning ***,owing to its serial mechanism,an SGD algorithm suffers from low efficiency and scalability w...
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A recommender system(RS)relying on latent factor analysis usually adopts stochastic gradient descent(SGD)as its learning ***,owing to its serial mechanism,an SGD algorithm suffers from low efficiency and scalability when handling large-scale industrial *** at addressing this issue,this study proposes a momentum-incorporated parallel stochastic gradient descent(MPSGD)algorithm,whose main idea is two-fold:a)implementing parallelization via a novel datasplitting strategy,and b)accelerating convergence rate by integrating momentum effects into its training *** it,an MPSGD-based latent factor(MLF)model is achieved,which is capable of performing efficient and high-quality *** results on four high-dimensional and sparse matrices generated by industrial RS indicate that owing to an MPSGD algorithm,an MLF model outperforms the existing state-of-the-art ones in both computational efficiency and scalability.
The machine learning frameworks flourished in the last decades, allowing artificial intelligence to get out of academic circles to be applied to enterprise domains. This field has significantly advanced, but there is ...
The machine learning frameworks flourished in the last decades, allowing artificial intelligence to get out of academic circles to be applied to enterprise domains. This field has significantly advanced, but there is still some meaningful improvement to reach the subsequent expectations. The proposed framework, named AI $$^{2}$$ , uses a natural language interface that allows non-specialists to benefit from machine learning algorithms without necessarily knowing how to program with a programming language. The primary contribution of the AI $$^{2}$$ framework allows a user to call the machine learning algorithms in English, making its interface usage easier. The second contribution is greenhouse gas (GHG) awareness. It has some strategies to evaluate the GHG generated by the algorithm to be called and to propose alternatives to find a solution without executing the energy-intensive algorithm. Another contribution is a preprocessing module that helps to describe and to load data properly. Using an English text-based chatbot, this module guides the user to define every dataset so that it can be described, normalized, loaded, and divided appropriately. The last contribution of this paper is about explainability. The scientific community has known that machine learning algorithms imply the famous black-box problem for decades. Traditional machine learning methods convert an input into an output without being able to justify this result. The proposed framework explains the algorithm’s process with the proper texts, graphics, and tables. The results, declined in five cases, present usage applications from the user’s English command to the explained output. Ultimately, the AI $$^{2}$$ framework represents the next leap toward native language-based, human-oriented concerns about machine learning framework.
In this study, we address the challenge of low-rank model compression in the context of in-memory computing (IMC) architectures. Traditional pruning approaches, while effective in model size reduction, necessitate add...
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ISBN:
(数字)9783982674100
ISBN:
(纸本)9798331534646
In this study, we address the challenge of low-rank model compression in the context of in-memory computing (IMC) architectures. Traditional pruning approaches, while effective in model size reduction, necessitate additional peripheral circuitry to manage complex dataflows and mitigate dislocation issues, leading to increased area and energy overheads. To circumvent these drawbacks, we propose leveraging low-rank compression techniques, which, unlike pruning, streamline the dataflow and seamlessly integrate with IMC architectures. However, low-rank compression presents its own set of challenges, namely i) suboptimal IMC array utilization and ii) compromised accuracy. To address these issues, we introduce a novel approach i) employing shift and duplicate kernel (SDK) mapping technique, which exploits idle IMC columns for parallel processing, and ii) group lowrank convolution, which mitigates the information imbalance in the decomposed matrices. Our experimental results demonstrate that our proposed method achieves up to 2.5× speedup or +20.9% accuracy boost over existing pruning techniques.
作者：
Mendaz, KheiraMiloudi, HoucineYounes, KhadidjaIRECOM Laboratory
Department of Electrical Engineering Faculty of Science and Technology University of Belhadj Bouchaib Ain Temouchent N101 Route de Sidi Bel Abbes Ain Temouchent46000 Algeria APELEC Laboratory
Electrical Engineering Department School of Engineering Science Djillali Liabes University P.O.B. 89 Sidi Bel Abbes22000 Algeria Department of Electrical Engineering
Faculty of Science and technology University of Belhadj Bouchaib Ain Temouchent N101 Route de Sidi Bel Abbes Ain Temouchent46000 Algeria
Speed squirrel cage motor control is an area of research that has been in evidence for some time now. In this paper, a nonlinear controller is presented for the squirrel cage motor drives, based on a combination betwe...
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The Army Research laboratory (ARL) and Boston University (BU) have established the Center for Semiconductor Modeling of Materials and Devices (CSM), bringing together government, academia, and industry in a collaborat...
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We report the first demonstration of single silicon vacancy center creation in 20 nm nanodiamonds using silicon ion implantation combined with thermal annealing. Room-temperature single photon emission with linewidth ...
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