This study analysed student enrolments (as multivariate data) in 9 universities of technology of South Africa (UoT), in attempting to maximize the amount of information in data, using principal component analysis. The...
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The safe and reliable operation of lithium-ion batteries necessitates the accurate prediction of remaining useful life(RUL).However,this task is challenging due to the diverse ageing mechanisms,various operating condi...
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The safe and reliable operation of lithium-ion batteries necessitates the accurate prediction of remaining useful life(RUL).However,this task is challenging due to the diverse ageing mechanisms,various operating conditions,and limited measured *** data-driven methods are perceived as a promising solution,they ignore intrinsic battery physics,leading to compromised accuracy,low efficiency,and low *** response,this study integrates domain knowledge into deep learning to enhance the RUL prediction *** demonstrate accurate RUL prediction using only a single charging ***,a generalisable physics-based model is developed to extract ageing-correlated parameters that can describe and explain battery degradation from battery charging *** parameters inform a deep neural network(DNN)to predict RUL with high accuracy and *** trained model is validated under 3 types of batteries working under 7 conditions,considering fully charged and partially charged *** data from one cycle only,the proposed method achieves a root mean squared error(RMSE)of 11.42 cycles and a mean absolute relative error(MARE)of 3.19%on average,which are over45%and 44%lower compared to the two state-of-the-art data-driven methods,*** its accuracy,the proposed method also outperforms existing methods in terms of efficiency,input burden,and *** inherent relationship between the model parameters and the battery degradation mechanism is further revealed,substantiating the intrinsic superiority of the proposed method.
Magnetic Resonance Imaging (MRI) is considered a safe imaging modality since there is no use of ionizing radiation. However, safety concerns still arise due to Radiofrequency (RF)-induced heating of electrically condu...
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Transporting payload with precise swing angles and transfer times poses a challenging task in building construction, which is why gantry crane systems are extensively utilized. Various control strategies, including op...
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This letter investigates a desirable power allocation scheme for shared spectrum networks and formulate it as a constrained optimization model that falls into the nonlinear class fractional programming problems. The i...
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Reinforcement learning (RL) algorithms are traditionally evaluated and compared by their learning trends (i.e., average performance) over trials and time. However, the presence of a single learning trend in a curricul...
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作者:
Wan, JianBiomedical and Design Engineering
School of Engineering and Technology College of Engineering and Physical Sciences Aston University Department of Mechanical BirminghamB4 7ET United Kingdom
This paper proposes a hybrid set-theoretic method to implement guaranteed state estimation for nonlinear uncertain discrete-time systems. The proposed method represents a polytopic set exactly at each time instant by ...
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This study proposes a new forming design concept to produce vacuum hexagon socket screws using tube workpiece, and uses the finite element simulation software DEFORM-3D to simulate the multi-pass forming process of va...
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Metal-organic frameworks (MOFs) are porous materials with potential in biomedical applications such as sensing, drug delivery, and radiosensitization. However, how to tune the properties of the MOFs for such applicati...
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All biological processes use or produce *** microcalorimeters have been utilized to study the metabolic heat output of living organisms and heat production of exothermic chemical *** advances in microfabrication have ...
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All biological processes use or produce *** microcalorimeters have been utilized to study the metabolic heat output of living organisms and heat production of exothermic chemical *** advances in microfabrication have made possible the miniaturization of commercial microcalorimeters,resulting in a few studies on the metabolic activity of cells at the microscale in microfluidic *** we present a new,versatile,and robust microcalorimetric differential design based on the integration of heat flux sensors on top of microfluidic *** show the design,modeling,calibration,and experimental verification of this system by utilizing Escherichia coli growth and the exothermic base catalyzed hydrolysis of methyl paraben as use *** system consists of a Polydimethylsiloxane based flow-through microfluidic chip with two 46µl chambers and two integrated heat flux *** differential compensation of thermal power measurements allows for the measurement of bacterial growth with a limit of detection of 1707 W/m^(3),corresponding to 0.021OD(2·10^(7) bacteria).We also extracted the thermal power of a single Escherichia coli of between 1.3 and 4.5 pW,comparable to values measured by industrial *** system opens the possibility for expanding already existing microfluidic systems,such as drug testing lab-on-chip platforms,with measurements of metabolic changes of cell populations in form of heat output,without modifying the analyte and minimal interference with the microfluidic channel itself.
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