The Internet of Things (IoT) is a network of interconnected objects, which congregate and exchange gigantic amounts of data. Usually, predeployed embedded sensors sense this massive data. Soon, several applications of...
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This study investigates the structure of the detonation front in a stoichiometric H2-air mixture (2H2-O2-3.76N2), seeded with 2000,ppm of NO, at 25,kPa and 293,K, for two channel positions: centered and near thewalls ...
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In this paper, we propose a via-less fully screen-printed reconfigurable intelligent surface which can establish a second line-of-sight communication from 23.5GHz to 29.5GHz. By serially connecting the H shaped resona...
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Continual learning, focused on sequentially learning multiple tasks, has gained significant attention recently. Despite the tremendous progress made in the past, the theoretical understanding, especially factors contr...
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Continual learning, focused on sequentially learning multiple tasks, has gained significant attention recently. Despite the tremendous progress made in the past, the theoretical understanding, especially factors contributing to catastrophic forgetting, remains relatively unexplored. In this paper, we provide a general theoretical analysis of forgetting in the linear regression model via Stochastic Gradient Descent (SGD) applicable to both under-parameterized and overparameterized regimes. Our theoretical framework reveals some interesting insights into the intricate relationship between task sequence and algorithmic parameters, an aspect not fully captured in previous studies due to their restrictive assumptions. Specifically, we demonstrate that, given a sufficiently large data size, the arrangement of tasks in a sequence-where tasks with larger eigenvalues in their population data covariance matrices are trained later-tends to result in increased forgetting. Additionally, our findings highlight that an appropriate choice of step size will help mitigate forgetting in both under-parameterized and overparameterized settings. To validate our theoretical analysis, we conducted simulation experiments on both linear regression models and Deep Neural Networks (DNNs). Results from these simulations substantiate our theoretical findings. Copyright 2024 by the author(s)
DNA barcodes,short and unique DNA sequences,play a crucial role in sample identification when processing many samples simultaneously,which helps reduce experimental ***,the low quality of long-read sequencing makes it...
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DNA barcodes,short and unique DNA sequences,play a crucial role in sample identification when processing many samples simultaneously,which helps reduce experimental ***,the low quality of long-read sequencing makes it difficult to identify barcodes accurately,which poses significant challenges for the design of barcodes for large numbers of samples in a single sequencing ***,we present a comprehensive study of the generation of barcodes and develop a tool,PRO,that can be used for selecting optimal barcode sets and *** formulate the barcode design problem as a combinatorial problem and prove that finding the optimal largest barcode set in a given DNA sequence space in which all sequences have the same length is theoretically *** practical applications,we developed the novel method PRO by introducing the probability divergence between two DNA sequences to expand the capacity of barcode kits while ensuring demultiplexing ***,the maximum size of the barcode kits designed by PRO is 2,292,which keeps the length of barcodes the same as that of the official ones used by Oxford Nanopore Technologies(ONT).We validated the performance of PRO on a simulated nanopore dataset with high error *** demultiplexing accuracy of PRO reached 98.29%for a barcode kit of size 2,922,4.31%higher than that of Guppy,the official demultiplexing *** the size of the barcode kit generated by PRO is the same as the official size provided by ONT,both tools show superior and comparable demultiplexing accuracy.
Three types of halide-perovskite-based fast-acting fluorescent materials have been demonstrated for high-speed visible light communication. All-inorganic metal-halide perovskite CsPbI3 was utilized to generate red col...
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With the increasing demand for greener and more energy efficient transportation solutions, electric vehicles (EVs) have emerged to be the future of transportation across the globe. However, currently, one of the bigge...
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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.
Deep learning (DL) has seen great success in the computer vision (CV) field, and related techniques have been used in security, healthcare, remote sensing, and many other areas. As a parallel development, visual data ...
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We propose two types of intelligent reflecting systems based on programmable metasurfaces and mirrors to focus the incident optical power towards a visible light communication receiver. We derive the required phase gr...
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