In this work, we consider the list-decodability and list-recoverability of codes in the zero-rate regime. Briefly, a code C Ď rqsn is (p, , L)-list-recoverable if for all tuples of input lists (Y1, . . ., Yn) with eac...
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ISBN:
(纸本)9783959773614
In this work, we consider the list-decodability and list-recoverability of codes in the zero-rate regime. Briefly, a code C Ď rqsn is (p, , L)-list-recoverable if for all tuples of input lists (Y1, . . ., Yn) with each Yi Ď rqs and |Yi| ", the number of codewords c P C such that ci R Yi for at most pn choices of i P rns is less than L;list-decoding is the special case of "1. In recent work by Resch, Yuan and Zhang (ICALP 2023) the zero-rate threshold for list-recovery was determined for all parameters: that is, the work explicitly computes p*:"p*(q, , L) with the property that for all Ε ą 0 (a) there exist positive-rate (p* - Ε, , L)-list-recoverable codes, and (b) any (p* + Ε, , L)-list-recoverable code has rate 0. In fact, in the latter case the code has constant size, independent on n. However, the constant size in their work is quite large in 1/Ε, at least |C| ě (1Ε)O(qL). Our contribution in this work is to show that for all choices of q, and L with q ě 3, any (p* + Ε, , L)-list-recoverable code must have size Oq,,L(1/Ε), and furthermore this upper bound is complemented by a matching lower bound Ωq,,L(1/Ε). This greatly generalizes work by Alon, Bukh and Polyanskiy (IEEE Trans. Inf. Theory 2018) which focused only on the case of binary alphabet (and thus necessarily only list-decoding). We remark that we can in fact recover the same result for q "2 and even L, as obtained by Alon, Bukh and Polyanskiy: we thus strictly generalize their work. Our main technical contribution is to (a) properly define a linear programming relaxation of the list-recovery condition over large alphabets;and (b) to demonstrate that a certain function defined on a q-ary probability simplex is maximized by the uniform distribution. This represents the core challenge in generalizing to larger q (as a binary simplex can be naturally identified with a one-dimensional interval). We can subsequently re-utilize certain Schur convexity and convexity properties established for a related function
Advanced Very High Resolution Radiometer(AVHRR)onboard National Oceanic and Atmospheric Administration(NOAA)satellites can provide over 40 years of global remote sensing observations,which can be used to retrieve long...
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Advanced Very High Resolution Radiometer(AVHRR)onboard National Oceanic and Atmospheric Administration(NOAA)satellites can provide over 40 years of global remote sensing observations,which can be used to retrieve long-term aerosol optical depth(AOD).This is of great significance to the study of global climate *** this paper,we proposed an algorithm to jointly calculate AOD and land surface properties from AVHRR *** assumptions that AOD doesn’t vary in adjacent space and earth surface property doesn’t vary in two days,the algorithm considered non-Lambertian surface reflection based on the shape of bidirectional reflectance distribution function(BRDF shape)and obtained AOD and surface property by optimal estimation(OE)*** algorithm has been applied to NOAA-7,9,11,14,16,18,and 19 satellites and AVHRR-retrieved AOD with 5×10 km over China(15°–60°N,70°–140°E)has been obtained from 1982 to *** of AVHRR-retrieved AOD against AErosol RObotic NETwork(AERONET)(in and around China)and China Aerosol Remote Sensing Network(CARSNET)AOD show good consistency with 62.62%points within the uncertainty ofΔτ=±(0.05+0.25τ)and root-mean-square error(RMSE)of *** comparison of the monthly mean AOD of multiple AOD datasets in the‘Beijing’,‘Dalanzadgad’,‘NCU_Taiwan’and‘Kanpur’stations shows that the results of the algorithm are *** yearly averaged AOD data also has similar agreements with MERRA-2(The Modern-Era Retrospective analysis for Research and Applications,Version 2)and AVHRRDB data(AVHRR‘Deep Blue’aerosol data set).The multi-year mean correlation coefficient is 0.70 and 0.61 and the percentages within the uncertainty are 80.01%and 67.29%compared with MERRA-2 AOD and AVHRRDB AOD respectively.
Mixed reality (MR) is a rapidly expanding technology whose usability is constantly growing. Some applications of MR technology have already matured, while others are still in development. MR offers new possibilities i...
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Research on strain anomalies and large earthquakes based on temporal and spatial crustal activities has been rapidly growing due to data availability, especially in Japan and Indonesia. However, many research works us...
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Research on strain anomalies and large earthquakes based on temporal and spatial crustal activities has been rapidly growing due to data availability, especially in Japan and Indonesia. However, many research works used local-scale case studies that focused on a specific earthquake characteristic using knowledgedriven techniques, such as crustal deformation analysis. In this study, a data-driven-based analysis is used to detect anomalies using displacement rates and deformation pattern features extracted from daily global navigation satellite system(GNSS) data using a machine learning algorithm. The GNSS data with188 and 1181 continuously operating reference stations from Indonesia and Japan, respectively, are used to identify the anomaly of recent major earthquakes in the last two decades. Feature displacement rates and deformation patterns are processed in several window times with 2560 experiment scenarios to produce the best detection using tree-based algorithms. Tree-based algorithms with a single estimator(decision tree), ensemble bagging(bagging, random forest and Extra Trees), and ensemble boosting(AdaBoost, gradient boosting, LGBM, and XGB) are applied in the study. The experiment test using realtime scenario GNSSdailydatareveals high F1-scores and accuracy for anomaly detection using slope windowing 365 and 730 days of 91-day displacement rates and then 7-day deformation pattern features in tree-based algorithms. The results show the potential for medium-term anomaly detection using GNSS data without the need for multiple vulnerability assessments.
Multilevel phase-change memory is an attractive technology to increase storage capacity and density owing to its high-speed,scalable and non-volatile ***,the contradiction between thermal stability and operation speed...
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Multilevel phase-change memory is an attractive technology to increase storage capacity and density owing to its high-speed,scalable and non-volatile ***,the contradiction between thermal stability and operation speed is one of key factors to restrain the development of phase-change ***,N-doped Ge_(2)Sb_(2)Te_(5)-based optoelectronic hybrid memory is proposed to simultaneously implement high thermal stability and ultrafast operation *** picosecond laser is adopted to write/erase information based on reversible phase transition characteristics whereas the resistance is detected to perform information *** show that when N content is 27.4 at.%,N-doped Ge_(2)Sb_(2)Te_(5)film possesses high ten-year data retention temperature of 175℃and low resistance drift coefficient of 0.00024 at 85℃,0.00170 at 120℃,and 0.00249 at 150℃,respectively,owing to the formation of Ge–N,Sb–N,and Te–N *** SET/RESET operation speeds of the film reach 520 ps/13 *** parallel,the reversible switching cycle of the corresponding device is realized with the resistance ratio of three orders of ***-level reversible resistance states induced by various crystallization degrees are also obtained together with low resistance drift ***,the N-doped Ge_(2)Sb_(2)Te_(5)thin film is a promising phase-change material for ultrafast multilevel optoelectronic hybrid storage.
Purpose: This paper aims to explore the possibility of the use of TikTok for delivery virtual literacy instruction for Z generation to support their learning. Design/methodology/approach: A review of papers related to...
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One of the methods used to increase channel capacity is the Non-Orthogonal Multiple Access (NOMA) methods. The increase in channel capacity in PD-NOMA multiple access means that the maximum power used by each user in ...
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The goal of this study is to develop and test an automated integrated speech analysis system for detecting mild cognitive impairment (MCI) and dementia in spontaneous free speech. During the years 2010–2016, speech r...
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The field of video games is of great interest to researchers in computational intelligence due to the complex, rich and dynamic nature they provide. We propose using Genetic Programming with coevolution and lexicograp...
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Big data processing frameworks demands for scalable and efficient cluster management. Apache Spark has emerged as prominent big data processing framework providing high-speed data processing and analytics capabilities...
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