The deep learning model depends on the specific requirements of our recommender system and the characteristics of the Arabic textual data we are working with it Consider experimenting with multiple models to determine...
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Evolutionary algorithms(EAs)have been used in high utility itemset mining(HUIM)to address the problem of discover-ing high utility itemsets(HUIs)in the exponential search *** have good running and mining performance,b...
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Evolutionary algorithms(EAs)have been used in high utility itemset mining(HUIM)to address the problem of discover-ing high utility itemsets(HUIs)in the exponential search *** have good running and mining performance,but they still require huge computational resource and may miss many *** to the good combination of EA and graphics processing unit(GPU),we propose a parallel genetic algorithm(GA)based on the platform of GPU for mining HUIM(PHUI-GA).The evolution steps with improvements are performed in central processing unit(CPU)and the CPU intensive steps are sent to GPU to eva-luate with multi-threaded *** show that the mining performance of PHUI-GA outperforms the existing *** mining 90%HUIs,the PHUI-GA is up to 188 times better than the existing EAs and up to 36 times better than the CPU parallel approach.
We tackle the task of generating opinion-based questions, focusing on providing users with samples of questions that express opinions relevant to their queries when utilizing search engines. The motivation is that Com...
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Misinterpreting satirical posts can contribute to the spread of misinformation and potentially be a source of what is commonly referred to as “fake news”. Satire is a form of humor that often involves exaggeration, ...
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In response to escalating road safety challenges within Algeria, marked by rising traffic volumes and urban development, the "TariqAmn Algeria" initiative emerges as a groundbreaking approach in traffic mana...
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作者：
Zhong, WenjieSun, TaoZhou, Jian-TaoWang, ZhuoweiSong, XiaoyuInner Mongolia University
College of Computer Science the Engineering Research Center of Ecological Big Data Ministry of Education the Inner Mongolia Engineering Laboratory for Cloud Computing and Service Software the Inner Mongolia Engineering Laboratory for Big Data Analysis Technology Hohhot010000 China Guangdong University of Technology
School of Computer Science and Technology Guangzhou510006 China Portland State University
Department of Electrical and Computer Engineering PortlandOR97207 United States
Colored Petri nets (CPNs) provide descriptions of the concurrent behaviors for software and hardware. Model checking based on CPNs is an effective method to simulate and verify the concurrent behavior in system design...
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In recent times, appropriate decision-making in challenging and critical situations has been very well supported by multicriteria decision-making (MCDM) methods. The technique for order of preference by similarity to ...
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Automatic semantic segmentation of magnetic resonance imaging (MRI) images using deep neural networks greatly assists in evaluating and planning treatments for various clinical applications. However, training these mo...
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Automatic semantic segmentation of magnetic resonance imaging (MRI) images using deep neural networks greatly assists in evaluating and planning treatments for various clinical applications. However, training these models is conditioned on the availability of abundant annotated data. Even if we annotate enough data, MRI images display considerable variability due to factors such as differences among patients, MRI scanners, and imaging protocols. This variability necessitates retraining neural networks for each specific application domain, which, in turn requires manual annotation by expert radiologists for all new domains. To relax the need for persistent data annotation, we develop a method for unsupervised federated domain adaptation using multiple annotated source domains. Our approach enables the transfer of knowledge from several annotated source domains for use in an unannotated target domain. Initially, we ensure that the target domain data shares similar representations with each source domain in a latent embedding space by minimizing the pair-wise distances between the distributions for the target and the source domains. We then employ an ensemble approach to leverage the knowledge obtained from all domains to build an integrated outcome. We perform experiments on two datasets to demonstrate our method is effective. Our implementation code is publicly available: https://***/navapatn/Unsupervised -Federated-Domain-Adaptation-for-Image-Segmentation new. IEEE
The accurate prediction of photovoltaic(PV)power generation is significant to ensure the economic and safe operation of power *** this end,the paper establishes a new digital twin(DT)empowered PV power prediction fram...
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The accurate prediction of photovoltaic(PV)power generation is significant to ensure the economic and safe operation of power *** this end,the paper establishes a new digital twin(DT)empowered PV power prediction framework that is capable of ensuring reliable data transmission and employing the DT to achieve high accuracy of power *** this framework,considering potential data contamination in the collected PV data,a generative adversarial network is employed to restore the historical dataset,which offers a prerequisite to ensure accurate mapping from the physical space to the digital ***,a new DT-empowered PV power prediction method is ***,we model a DT that encompasses a digital physical model for reflecting the physical operation mechanism and a neural network model(i.e.,a parallel network of convolution and bidirectional long short-term memory model)for capturing the hidden spatiotemporal *** proposed method enables the use of the DT to take advantages of the digital physical model and the neural network model,resulting in enhanced prediction ***,a real dataset is conducted to assess the effectiveness of the proposed method.
The concept of extension-based proofs models the idea of a valency argument, which is widely used in distributed computing. Extension-based proofs are limited in power: it has been shown that there is no extension-bas...
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