Learning causal representations from observational and interventional data in the absence of known ground-truth graph structures necessitates implicit latent causal representation learning. Implicit learning of causal...
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A mathematical model has been elaborated to determine the optimal structure of multilevel hierarchical asymmetric branched computer networks and the appropriate software has been developed. In the presented case study...
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Unmanned Aerial Vehicles (UAVs) offer the immense capability for allowing novel applications in a variety of domains including security, military, surveillance, medicine, and traffic monitoring. The prevalence of UAV ...
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Collaborative state estimation using different heterogeneous sensors is a fundamental prerequisite for robotic swarms operating in GPS-denied environments, posing a significant research challenge. In this paper, we in...
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The accurate annotation of transcription start sites(TSSs)and their usage are critical for the mechanistic understanding of gene regulation in different biological *** fulfill this,specific high-throughput experimenta...
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The accurate annotation of transcription start sites(TSSs)and their usage are critical for the mechanistic understanding of gene regulation in different biological *** fulfill this,specific high-throughput experimental technologies have been developed to capture TSSs in a genome-wide manner,and various computational tools have also been developed for in silico prediction of TSSs solely based on genomic *** of these computational tools cast the problem as a binary classification task on a balanced dataset,thus resulting in drastic false positive predictions when applied on the genome ***,we present Dee Re CT-TSS,a deep learningbased method that is capable of identifying TSSs across the whole genome based on both DNA sequence and conventional RNA sequencing *** show that by effectively incorporating these two sources of information,Dee Re CT-TSS significantly outperforms other solely sequence-based methods on the precise annotation of TSSs used in different cell ***,we develop a meta-learning-based extension for simultaneous TSS annotations on 10 cell types,which enables the identification of cell type-specific ***,we demonstrate the high precision of DeeReCT-TSS on two independent datasets by correlating our predicted TSSs with experimentally defined TSS chromatin *** source code for Dee Re CT-TSS is available at https://github.-com/Joshua Chou2018/Dee Re CT-TSS_release and https://***/biocode/tools/BT007316.
Production of green Hydrogen is increasingly helping the world achieve its energy transition goals. Compared to conventional methods, producing Hydrogen using green energy produces fewer carbon emissions. Furthermore,...
Production of green Hydrogen is increasingly helping the world achieve its energy transition goals. Compared to conventional methods, producing Hydrogen using green energy produces fewer carbon emissions. Furthermore, green Hydrogen can be produced from several renewable sources depending on the region’s potential. Photovoltaic systems are considered in this study to estimate green hydrogen production in the United Arab Emirates. The impact of electrolyzer and hydrogen tank capital expenses on green Hydrogen production has been extensively researched in the literature. However, the impact of the varying capital cost is often overlooked. In this work, we analyze the sensitivity of renewable systems’ costs to changes in the costs of producing Hydrogen, and employing it as energy storage.
Given a real dataset and a computation family, we wish to encode and store the dataset in a distributed system so that any computation from the family can be performed by accessing a small number of nodes. In this wor...
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ISBN:
(数字)9798350382846
ISBN:
(纸本)9798350382853
Given a real dataset and a computation family, we wish to encode and store the dataset in a distributed system so that any computation from the family can be performed by accessing a small number of nodes. In this work, we focus on the families of linear computations where the coefficients are restricted to a finite set of real values. For two-valued computations, a recent work presented a scheme that gives good feasible points on the access-redundancy tradeoff. This scheme is based on binary covering codes having a certain closure property. In a follow-up work, this scheme was extended to all finite coefficient sets, using a new additive-combinatorics notion called coefficient complexity. In the present paper, we explore non-binary covering codes and develop schemes that outperform the state-of-the-art for some coefficient sets. We provide a more general coefficient complexity definition and show its applicability to the access- redundancy tradeoff.
Delegating large-scale computations to service providers is a common practice which raises privacy concerns. This paper studies information-theoretic privacy-preserving delegation of data to a service provider, who ma...
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In this paper, we propose a highly efficient underwater image correction method that leverages structural similarity evaluation along with real-time performance from a traditional FUnIEGAN algorithm. The proposed appr...
In this paper, we propose a highly efficient underwater image correction method that leverages structural similarity evaluation along with real-time performance from a traditional FUnIEGAN algorithm. The proposed approach is designed for implementation on an embedded GPU module (Jetson Xavier NX), ensuring its practicality and versatility. Furthermore, our method incorporates algorithmic enhancements to significantly enhance color correction performance. To optimize computational resources, we employ automatic mixed precision (AMP), effectively reducing redundancy and enabling rapid processing. As a result, our method demonstrates improved object detection outcomes, achieving an impressive increase in frames per second (FPS) from approximately 55 FPS to about 77 FPS.
In this paper, we investigate the impact of fear on a food chain mathematical model with prey refuge and harvesting. The prey species reproduces by to the law of logistic growth. The model is adapted from version of t...
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