scholarly journals Cooperation and compressed data exchange between multiple gliders used to map oil spills in the ocean

2022 ◽  
Vol 118 ◽  
pp. 102999
Author(s):  
Yaomei Wang ◽  
Worakanok Thanyamanta ◽  
Neil Bose
Keyword(s):  
Data Exchange ◽  
Oil Spills ◽  
Compressed Data

scholarly journals Using Intel Xeon Phi coprocessors for execution of natural join on compressed data

2015 ◽  
pp. 534-542
Author(s):  
Е.В. Иванова ◽  
Л.Б. Соколинский
Keyword(s):  
High Performance ◽  
Data Exchange ◽  
Cluster Computing ◽  
Xeon Phi ◽  
Intel Xeon Phi ◽  
Computing Systems ◽  
Parallel Decomposition ◽  
Many Core ◽  
Compressed Data ◽  
Intel Xeon

В статье описывается сопроцессор баз данных для высокопроизводительных кластерных вычислительных систем с многоядерными ускорителями, использующий распределенные колоночные индексы с интервальной фрагментацией. Работа сопроцессора рассматривается на примере выполнения операции естественного соединения. Параллельная декомпозиция естественного соединения выполняется на основе использования распределенных колоночных индексов. Предложенный подход позволяет выполнять реляционные операции на кластерных вычислительных системах без массовых обменов данными. Приводятся результаты вычислительных экспериментов с использованием сопроцессоров Intel Xeon Phi, подтверждающие эффективность разработанных методов и алгоритмов. A database coprocessor for high-performance cluster computing systems with many-core accelerators is described. This coprocessor uses distributed columnar indexes with interval fragmentation. The operation of the coprocessor engine is considered by an example of natural join processing. The parallel decomposition of natural join operator is performed using distributed columnar indexes. The proposed approach allow one to perform relational operators on computing clusters without massive data exchange. The results of computational experiments on Intel Xeon Phi confirm the efficiency of the developed methods and algorithms.

Machine-Scored Syntax: Comparison of the CLAN Automatic Scoring Program to Manual Scoring

2020 ◽  
Vol 51 (2) ◽  
pp. 479-493
Author(s):  
Jenny A. Roberts ◽  
Evelyn P. Altenberg ◽  
Madison Hunter
Keyword(s):  
Data Exchange ◽  
Child Language ◽  
Exchange System ◽  
Absolute Point ◽  
Language Analysis ◽  
Search Patterns ◽  
Language Data ◽  
Report Accuracy ◽  
Point To Point ◽  
Automatic Scoring

Purpose The results of automatic machine scoring of the Index of Productive Syntax from the Computerized Language ANalysis (CLAN) tools of the Child Language Data Exchange System of TalkBank (MacWhinney, 2000) were compared to manual scoring to determine the accuracy of the machine-scored method. Method Twenty transcripts of 10 children from archival data of the Weismer Corpus from the Child Language Data Exchange System at 30 and 42 months were examined. Measures of absolute point difference and point-to-point accuracy were compared, as well as points erroneously given and missed. Two new measures for evaluating automatic scoring of the Index of Productive Syntax were introduced: Machine Item Accuracy (MIA) and Cascade Failure Rate— these measures further analyze points erroneously given and missed. Differences in total scores, subscale scores, and individual structures were also reported. Results Mean absolute point difference between machine and hand scoring was 3.65, point-to-point agreement was 72.6%, and MIA was 74.9%. There were large differences in subscales, with Noun Phrase and Verb Phrase subscales generally providing greater accuracy and agreement than Question/Negation and Sentence Structures subscales. There were significantly more erroneous than missed items in machine scoring, attributed to problems of mistagging of elements, imprecise search patterns, and other errors. Cascade failure resulted in an average of 4.65 points lost per transcript. Conclusions The CLAN program showed relatively inaccurate outcomes in comparison to manual scoring on both traditional and new measures of accuracy. Recommendations for improvement of the program include accounting for second exemplar violations and applying cascaded credit, among other suggestions. It was proposed that research on machine-scored syntax routinely report accuracy measures detailing erroneous and missed scores, including MIA, so that researchers and clinicians are aware of the limitations of a machine-scoring program. Supplemental Material https://doi.org/10.23641/asha.11984364

Nanosponges could soak up oil spills

Nature ◽  
2008 ◽  
Author(s):  
Rachel Courtland
Keyword(s):  
Oil Spills

Geoenvironmental and Geotechnical Data Exchange: Setting the Standard

2008 ◽  
Author(s):  
Scot D. Weaver ◽  
Thomas E. Lefchik ◽  
Marc I. Hoit ◽  
Kirk Beach
Keyword(s):  
Data Exchange ◽  
Geotechnical Data

Computing Cores for Existential Rules with the Standard Chase and ASP

2020 ◽  
Author(s):  
Markus Krötzsch
Keyword(s):  
Large Class ◽  
Data Exchange ◽  
Answer Set Programming ◽  
Query Answering ◽  
Universal Model ◽  
The Core ◽  
Universal Models ◽  
General Terms ◽  
Special Cases ◽  
The Many

To reason with existential rules (a.k.a. tuple-generating dependencies), one often computes universal models. Among the many such models of different structure and cardinality, the core is arguably the “best”. Especially for finitely satisfiable theories, where the core is the unique smallest universal model, it has advantages in query answering, non-monotonic reasoning, and data exchange. Unfortunately, computing cores is difficult and not supported by most reasoners. We therefore propose ways of computing cores using practically implemented methods from rule reasoning and answer set programming. Our focus is on cases where the standard chase algorithm produces a core. We characterise this desirable situation in general terms that apply to a large class of cores, derive concrete approaches for decidable special cases, and generalise these approaches to non-monotonic extensions of existential rules.

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