scholarly journals Data Exchange Network: The Danish Elite Network

Connections ◽  
2015 ◽  
Vol 35 (1) ◽  
Author(s):  
Christoph Houman Ellersgaard ◽  
◽  
Anton Grau Larsen ◽  
Keyword(s):  
Data Exchange ◽  
Data Exchange Network ◽  
Exchange Network

ACTIVE INFORMATION GATHERING IN INFOSLEUTHTM

2000 ◽  
Vol 09 (01n02) ◽  
pp. 3-27 ◽  
Author(s):  
MARIAN NODINE ◽  
JERRY FOWLER ◽  
TOMASZ KSIEZYK ◽  
BRAD PERRY ◽  
MALCOLM TAYLOR ◽  
...  
Keyword(s):  
Data Exchange ◽  
Environmental Data ◽  
Distributed Environment ◽  
Distributed Query Processing ◽  
Agent Based ◽  
Intelligence System ◽  
Distributed Query ◽  
Information Monitoring ◽  
Data Exchange Network ◽  
Exchange Network

InfoSleuth is an agent-based system that can be configured to perform many different information management activities in a distributed environment. InfoSleuthTM agents provide a number of complex query services that require resolving ontology-based queries over dynamically changing, distributed, heterogeneous resources. These include distributed query processing, location-independent single-resource updates, event and information monitoring, statistical or inferential data analysis, and trend discovery in complex event streams. It has been used in numerous applications, including the Environmental Data Exchange Network and the Competitive Intelligence System.

Smart Grid Using Internet of Things

2021 ◽  
pp. 251-271
Author(s):  
Kuldeep Singh Kaswan ◽  
Jagjit Singh Dhatterwal ◽  
Nitin Kumar Gaur
Keyword(s):  
Internet Of Things ◽  
Smart Grid ◽  
Transmission Lines ◽  
Data Exchange ◽  
Service Providers ◽  
Data Exchange Network ◽  
Network Backbone ◽  
Worldwide Network ◽  
Exchange Network ◽  
Online Service Providers

The IoT (internet of things) is a network of people and stuff at any moment, anytime, for anyone, with any network or service. IoT is therefore a major complex worldwide network backbone for online service providers. The smart grid (SG) is one of IoT's main applications. SG is an interconnected data exchange network that gathers and analyzes data obtained from transmission lines, generation stations, and customers through the power grid. The internet of things has risen as the basis of creativity for energy grids. The chapter is based on the idea that, if one grid station transmitting electricity to customers is cut off due to some defects of IoT-based systems, all grid station loads can be connected to another system so that power is not disrupted. The authors discuss the IoT and SG and their relationship in this chapter. The best advantages for SG and specifications can be addressed in the SG works, creative innovations using IoT in SG, IoT software, and facilities in SG.

scholarly journals Data Exchange Network: The 2012 Malian Conflict Network

Connections ◽  
2014 ◽  
Vol 34 (1) ◽  
Author(s):  
Olivier Walther ◽  
◽  
Dimitris Christopoulos ◽  
Keyword(s):  
Data Exchange ◽  
Data Exchange Network ◽  
Exchange Network

Study on Equipment Quality Monitoring Information Transmission System Based on BeiDou Navigation Satellite System Short Message Communication

2014 ◽  
Vol 602-605 ◽  
pp. 3712-3715
Author(s):  
Da Quan Deng ◽  
Wan Lin Li ◽  
Yan Chen ◽  
Fang Zhao
Keyword(s):  
Management System ◽  
Data Exchange ◽  
Information Quality ◽  
Satellite System ◽  
Quality Monitoring ◽  
Equipment Management ◽  
Short Message ◽  
Data Exchange Network ◽  
Exchange Network ◽  
Wide Geographic Distribution

Because the equipment management of wide geographic distribution and it is difficult to obtain real-time equipment quality status for the equipment management system. The system built a quality monitoring and management system of distributed equipment, formed the command and data exchange network based on Beidou satellite system, achieved the timely transmission of information quality monitoring equipment, accurated grasp equipment status, realized the equipment safeguard informatization, accurated security provides the means to support.

Exploring the association between KRAS mutations and depression in non-small cell lung cancer (NSCLC) patients.

2017 ◽  
Vol 35 (31_suppl) ◽  
pp. 114-114
Author(s):  
Jenny Jing Li ◽  
Jessica Harper ◽  
Nizar Bhulani ◽  
David E. Gerber ◽  
Saad A. Khan ◽  
...  
Keyword(s):  
Data Exchange ◽  
Standard Of Care ◽  
Clinic Visit ◽  
Wild Type ◽  
Distress Screening ◽  
Kras Mutations ◽  
Stage 4 ◽  
Patient Health ◽  
Nsclc Patients ◽  
Exchange Network

114 Background: Previous studies have demonstrated a higher rate of depression in cancer patients harboring KRAS mutations. We evaluated the feasibility of using secondary Electronic Medical Record (EMR) data to examine the association of KRAS mutations with depression in NSCLC patients. Methods: We identified cases with NSCLC from an institutional Cancer Registry. Tumor molecular profiles were obtained as standard of care. Depression was assessed using the Patient Health Questionnaire-2 (PHQ-2), which is part of the institution’s universal Distress Screening tool completed at the time of clinic visit. PHQ-2 score of 2 and above was considered positive for depression. Data was extracted from EMR via Clinical Data Exchange Network bioinformatics tool and confirmed by chart review. Results: Of the 692 NSCLC patients, KRAS status was known in 174 cases: 40 (23%) were KRAS mutated and 134 (77%) were KRAS wild type. 101 (58%) had stage 4 NSCLC. PHQ-2 score was 0 in 146 (83.9%), 1 in 7 (4%), 2 in 19 (10.9%), and > 2 in 2 (1.1%). The rate of positive PHQ-2 for KRAS mutated vs wild type was 15% vs 11% (p = NS). Conclusions: This study in patients with NSCLC did not demonstrate an association between KRAS mutation and depression. Bioinformatics studies harnessing EMR data are a feasible platform to assess the association of genomic data with clinical outcomes and validated algorithms are needed.

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

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