This work aims to promote Chinese opera research in both musical and speech domains, with a primary focus on overcoming the data limitations. We introduce KunquDB, https://***/KunquDB, a relatively large-scale, well-a...
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Relativistic outflows often exhibit extreme observational characteristics due to beaming effects, which makes measuring their jet power a challenging task. Although the spectral energy distribution(SED) obtained from ...
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Relativistic outflows often exhibit extreme observational characteristics due to beaming effects, which makes measuring their jet power a challenging task. Although the spectral energy distribution(SED) obtained from multi-wavelength data can constrain the physical parameters of these jets, accurately estimating the Doppler factor remains difficult. To address this challenge, we assemble a comprehensive sample containing available SEDs of synchrotron and inverse Compton(IC) components, monochromatic luminosity, and broad-line region(BLR) emissions. We employ a parabolic equation to fit the synchrotron radiation SEDs,constraining jet physical parameters within the framework of a one-zone leptonic model. Our study delves into the jet properties and Doppler factor estimations, yielding the following key findings:(1) The fitting results of SED data for the entire sample reveal normal distributions of jet physical parameters for two subclasses of blazars.(2) Correlation analysis demonstrates that synchrotron peak luminosity exhibits a proportional relationship with both the radio and the γ-ray luminosities.(3) We introduce a novel method for estimating Doppler factors, which uncovers discrepancies between Doppler factors from this work and others from different techniques.
Early detection of Autism Spectrum Disorder (ASD) needs to be increased to prevent further adverse impacts. Thus, the classification between ASD and Typically Development (TD) individuals is an intriguing task. This r...
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This research investigates the effectiveness of Convolutional Neural Networks (CNNs) and Bidirectional Long Short-Term Memory (Bi-LSTM) networks in recognizing mental states through speech analysis. Leveraging the DAI...
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TikTok, a social networking site for uploading short videos, has become one of the most popular. Despite this, not all users are happy with the app;there are criticisms and suggestions, one of which is reviewed via th...
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Neural network pruning is a popular approach to reducing the computational complexity of deep neural *** recent years,as growing evidence shows that conventional network pruning methods employ inappropriate proxy metr...
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Neural network pruning is a popular approach to reducing the computational complexity of deep neural *** recent years,as growing evidence shows that conventional network pruning methods employ inappropriate proxy metrics,and as new types of hardware become increasingly available,hardware-aware network pruning that incorporates hardware characteristics in the loop of network pruning has gained growing attention,Both network accuracy and hardware efficiency(latency,memory consumption,etc.)are critical objectives to the success of network pruning,but the conflict between the multiple objectives makes it impossible to find a single optimal *** studies mostly convert the hardware-aware network pruning to optimization problems with a single *** this paper,we propose to solve the hardware-aware network pruning problem with Multi-Objective Evolutionary Algorithms(MOEAs).Specifically,we formulate the problem as a multi-objective optimization problem,and propose a novel memetic MOEA,namely HAMP,that combines an efficient portfoliobased selection and a surrogate-assisted local search,to solve *** studies demonstrate the potential of MOEAs in providing simultaneously a set of alternative solutions and the superiority of HAMP compared to the state-of-the-art hardware-aware network pruning method.
AI(Artificial Intelligence)workloads are proliferating in modernreal-time *** the tasks of AI workloads fluctuate over time,resourceplanning policies used for traditional fixed real-time tasks should be *** particular...
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AI(Artificial Intelligence)workloads are proliferating in modernreal-time *** the tasks of AI workloads fluctuate over time,resourceplanning policies used for traditional fixed real-time tasks should be *** particular,it is difficult to immediately handle changes inreal-time tasks without violating the deadline *** cope with thissituation,this paper analyzes the task situations of AI workloads and findsthe following two ***,resource planning for AI workloadsis a complicated search problem that requires much time for ***,although the task set of an AI workload may change over time,thepossible combinations of the task sets are known in *** on theseobservations,this paper proposes a new resource planning scheme for AIworkloads that supports the re-planning of *** of generatingresource plans on the fly,the proposed scheme pre-determines resourceplans for various combinations of ***,in any case,the workload isimmediately executed according to the resource plan ***,the proposed scheme maintains an optimized CPU(Central Processing Unit)and memory resource plan using genetic algorithms and applies it as soonas the workload *** proposed scheme is implemented in the opensourcesimulator SimRTS for the validation of its *** show that the proposed scheme reduces the energy consumptionof CPU and memory by 45.5%on average without deadline misses.
As one of the cancer types with the highest incidence rates, colorectal cancer (CRC) would benefit from treatments with fewer side effects and reduced treatment-resistant potential. One of the options is to harness th...
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In Internet of Things (IoT) systems that use various and limited devices, efficient use of resources is critical. However, since this problem is inherently complex, an enhanced meta-heuristic approach is proposed. In ...
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The convergence rate of both the FETI-DP (Finite Element Tearing and Interconnecting-Dual Primal) and the BDDC (Balancing Domain Decomposition by Constraints) domain decomposition methods strongly depend on the spectr...
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