1,725,568 research outputs found
DataStream
No full textPresentation on DataStream and how it relates to Reusability aspect of the FAIR Principles. For the National Data Services Framework Summit 2019.</p
2029-01-14 - DataStream - CoreTrustSeal Requirements 2023-2025
No full textCoreTrustSeal certificatio
Why Datastream Permutations Need Diagnostics
No full textDatastream permutations are commonly used to test null hypotheses in animal social network analysis. Permutation methods are inherently stochastic and, like all stochastic processes, can be unreliable if appropriate diagnostic procedures aren't employed. Though datastream permutations are widely used in behavioural ecology, sufficient diagnostic checks have not yet been adopted to guarantee their reliability. In this paper we highlight that without proper checks, datastream permutations can be severely unreliable, but that using diagnostic tools developed for Markov chain Monte Carlo methods can improve the reliability of inferences
Datastream金融数据库使用
No full text主要内容：1、Datastream数据下载和常用分析工具；2、行业分析师怎样使用Datastream；3、宏观策略分析师怎样使用Datastream
How to chart variance on Datastream
No full textThis presentation shows how to chart the variance of a datatype of an instrument using Datastream
Enhanced transformer long short-term memory framework for datastream prediction
Get PDFIn machine learning, datastream prediction is a challenging issue, particularly when dealing with enormous amounts of continuous data. The dynamic nature of data makes it difficult for traditional models to handle and sustain real-time prediction accuracy. This research uses a multi-processor long short-term memory (MPLSTM) architecture to present a unique framework for datastream regression. By employing several central processing units (CPUs) to divide the datastream into multiple parallel chunks, the MPLSTM framework illustrates the intrinsic parallelism of long short-term memory (LSTM) networks. The MPLSTM framework ensures accurate predictions by skillfully learning and adapting to changing data distributions. Extensive experimental assessments on real-world datasets have demonstrated the clear superiority of the MPLSTM architecture over previous methods. This study uses the transformer, the most recent deep learning breakthrough technology, to demonstrate how well it can handle challenging tasks and emphasizes its critical role as a cutting-edge approach to raising the bar for machine learning
Novel link adaptation algorithm for multichannel wireless systems with datastream repetition
No full text© 2015 IEEE. The paper derives a novel link adaptation algorithm of modulation and coding schemes (MCS) and parameters of multichannel transmission choosing. The developed algorithm is based on a special type of MCS switching table and a new performance metric of system payload and is intended for wireless data transmission systems with capability of datastream repetition through different simultaneously active wireless channels. The presented scheme provides the best choice of MCS and datastream repetition parameters in terms of wireless system resources minimization with respect to maximum transmission speed and fixed uPER level (unrecoverable packet error rate for repetitive datastream)
Metodi Efficienti per il Trattamento di DataStream
No full textAl giorno d’oggi c’è la necessità di dover trattare una grossa quantità di dati provenienti da innumerevoli applicazioni e/o dispositivi, questo flusso di dati è chiamato DataStream.
Il DataStream è dunque un flusso di dati potenzialmente infinito che pone il problema della mancanza di un dispositivo di memoria ausiliaria che possa contenerlo.
Da qui la necessità di trovare dei metodi efficienti per ridurre la quantità di informazione da memorizzare e per interpretare l’andamento di tale flusso rispetto al dominio di interesse.
Wavelet: questo metodo utilizza delle funzioni matematiche per generare dei coefficienti a partire dai dati iniziali, al fine di memorizzare una minore quantità di informazione; i coefficienti wavelet godono di importanti proprietà.
Stream Cube: metodo per ridurre la quantità dei dati originali in modo da far emergere solo quelli di interesse.
Window: metodo che permette un’elaborazione degli ultimi n elementi filtrando le informazioni relative all’obiettivo prefissato.
Histogram: metodo che consente un’analisi immediata dell’andamento dei dati da analizzare.
Di ognuno di questi vengono illustrati alcuni algoritmi
Novel link adaptation algorithm for multichannel wireless systems with datastream repetition
Full text link© 2015 IEEE. The paper derives a novel link adaptation algorithm of modulation and coding schemes (MCS) and parameters of multichannel transmission choosing. The developed algorithm is based on a special type of MCS switching table and a new performance metric of system payload and is intended for wireless data transmission systems with capability of datastream repetition through different simultaneously active wireless channels. The presented scheme provides the best choice of MCS and datastream repetition parameters in terms of wireless system resources minimization with respect to maximum transmission speed and fixed uPER level (unrecoverable packet error rate for repetitive datastream)
- …
