scholarly journals A data‐driven measurement placement to evaluate the well‐being of distribution systems operation

2021 ◽  
Author(s):  
Mohammad Jafarian ◽  
Alireza Soroudi ◽  
Andrew Keane
Keyword(s):  
Distribution Systems ◽  
Well Being ◽  
Data Driven ◽  
Measurement Placement

Data-Driven Indicators Applied to Power Distribution Systems

2020 ◽  
Author(s):  
Diana Estefania Cherrez Barragan ◽  
Giulianno Bolognesi Archilli ◽  
Luiz Carlos Pereira da Silva
Keyword(s):  
Power Distribution ◽  
Distribution Systems ◽  
Data Driven ◽  
Power Distribution Systems

scholarly journals Promoting Well-being Among Neurology Residents: A Data-Driven Approach

2020 ◽  
Vol 4 (5) ◽  
pp. 469-474 ◽  
Author(s):  
Vijay K Ramanan ◽  
Jery D. Inbarasu ◽  
Lauren M. Jackson ◽  
Lyell K. Jones ◽  
James P. Klaas
Keyword(s):  
Well Being ◽  
Data Driven ◽  
Data Driven Approach

A Scalable Data-Driven Monitoring Approach for Distribution Systems

2015 ◽  
Vol 64 (5) ◽  
pp. 1292-1305 ◽  
Author(s):  
Mohsen Ferdowsi ◽  
Andrea Benigni ◽  
Artur Lowen ◽  
Behzad Zargar ◽  
Antonello Monti ◽  
...  
Keyword(s):  
Distribution Systems ◽  
Data Driven

scholarly journals Measurement of Well-Being in Gerontopsychiatric Nursing Home Residents: Development of the Laurens Well-Being Inventory for Gerontopsychiatry

2018 ◽  
Vol 31 (3) ◽  
pp. 136-148 ◽  
Author(s):  
Elja van der Wolf ◽  
Susan A. H. van Hooren ◽  
Wim Waterink ◽  
Lilian Lechner
Keyword(s):  
Nursing Home ◽  
Nursing Home Residents ◽  
Reliability And Validity ◽  
Well Being ◽  
Data Driven ◽  
Potential Measurement ◽  
First Results ◽  
Test Retest Reliability ◽  
Responsiveness To Change ◽  
Final Instrument

Background: The gerontopsychiatric population consists of nursing home residents with combined psychiatric and physical disabilities. A validated measure to assess well-being among this population is currently not available. This article is a first step toward the development of a well-being instrument for the gerontopsychiatric population. Methods: Potential measurement items were gathered and selected with the help of both gerontopsychiatric residents and care professionals. A total of 295 residents and their primary professional caregivers were interviewed. Theoretical and data-driven considerations were applied in the methodological process of scale construction. Results: The final instrument comprised of 30 items within 3 dimensions of well-being (physical, social, and psychological well-being). Reliability and validity were found to be adequate for all dimensions and subscales. Conclusions: The Laurens Well-Being Inventory for Gerontopsychiatry measures well-being in gerontopsychiatric nursing home residents. The first results regarding reliability and validity are promising. More research is needed especially to examine test–retest reliability and responsiveness to change.

scholarly journals Data-Driven Incident Detection in Power Distribution Systems

2021 ◽  
Author(s):  
Nayara Aguiar ◽  
Vijay Gupta ◽  
Rodrigo D. Trevizan ◽  
Babu R. Chalamala ◽  
Raymond H. Byrne
Keyword(s):  
Power Distribution ◽  
Distribution Systems ◽  
Data Driven ◽  
Incident Detection ◽  
Power Distribution Systems

scholarly journals Integrating diverse data sources to predict disease risk in dairy cattle

2021 ◽  
Author(s):  
Jana Lasser ◽  
Caspar Matzhold ◽  
Christa Egger-Danner ◽  
Birgit Fuerst-Waltl ◽  
Franz Steininger ◽  
...  
Keyword(s):  
Dairy Cattle ◽  
Disease Risk ◽  
Point Of Care ◽  
High Sensitivity ◽  
Well Being ◽  
Added Value ◽  
Data Driven ◽  
Full Potential ◽  
Life Domains ◽  
Livestock Farming

ABSTRACTLivestock farming is currently undergoing a digital revolution and becoming increasingly data-driven. Yet, such data often reside in disconnected silos making it impossible to leverage their full potential to improve animal well-being. Here, we introduce a precision medicine approach, bringing together information streams from a variety of life domains of dairy cattle to predict eight common and economically important diseases. Dairy cows are part of a highly industrialised environment. The animals and their surroundings are closely monitored and environmental, behavioural and physiological observations are readily accessible yet seldomly integrated. We use random forest classifiers trained on data from 5,828 animals in 166 herds in Austria to predict occurrences of lameness, acute and chronic mastitis, anoestrus, ovarian cysts, metritis, ketosis (hyperketonemia) and periparturient hypocalcemia (milk fever). To assess the importance of specific cattle life domains and individual features for these predictions, we use multivariate logistic regression and feature permutation approaches. We show that disease in dairy cattle is a product of the complex interplay between a multitude of life domains such as housing, nutrition or climate, and identify a range of features that were previously not associated with increased disease risk. For example, we can predict anoestrus with high sensitivity and specificity (F1=0.72) and find that housing, feed and husbandry variables such as barn design and time on pasture are most predictive of this disease. We also find previously unknown associations of features with disease risk, for example humid conditions, which significantly decrease the odds for ketosis. Our findings pave the way towards data-driven point-of-care interventions and demonstrate the added value of integrating all available data in the dairy industry to improve animal well-being and reduce disease risk.

scholarly journals Comparability of Water Infrastructure Resilience of Different Urban Structures

2021 ◽  
pp. 81-90
Author(s):  
Imke-Sophie Lorenz ◽  
Kevin Pouls ◽  
Peter F. Pelz
Keyword(s):  
Distribution Systems ◽  
Water Distribution ◽  
Critical Infrastructure ◽  
Well Being ◽  
Main Line ◽  
Economic Sectors ◽  
Urban Structures ◽  
Local Decision ◽  
German City ◽  
Local Decision Makers

AbstractUrban water distribution systems (WDS) ensure the demand-driven supply of a city at multiple ends. Well-being of the population as well as multiple economic sectors depend on its viability and thereby classify it as a critical infrastructure. Therefore, its behavior when exposed to changes is of interest to water suppliers as well as local decision-makers. It can be determined by resilience metrics, assessing the capability to meet and recover its functioning when exposed to disturbances. These disturbances can occur in form of changes in the water availability, the WDS topology, or the water demand pattern. Since networks as WDS are studied by graph theory, also different graph-theoretical resilience metrics were derived. In this work a well-established topology-based resilience metric is adapted and deployed to assess the present resilience of the urban main-line WDS of the German city of Darmstadt as well as of a suburb in the Rhine-Main region. Thereby, the intercomparability of the resilience for the different urban structures were of interest. Based on this analysis the comparability of different urban main-line WDS regarding their resilience is facilitated. Additionally, the conducted approach to allow for the comparability of absolute resilience values of urban structures of varying size can be applied to different resilience metrics as well as technical systems.

scholarly journals Disruptive Mood Dysregulation Disorder: symptomatic and syndromic thresholds and diagnostic operationalization

2019 ◽  
Author(s):  
Paola Paganella Laporte ◽  
Alicia Matijasevich ◽  
Tiago N. Munhoz ◽  
Iná S. Santos ◽  
Aluísio J. D. Barros ◽  
...  
Keyword(s):  
Early Adolescents ◽  
Well Being ◽  
Data Driven ◽  
Disruptive Mood Dysregulation Disorder ◽  
Three Stages ◽  
Clinically Significant ◽  
High Level ◽  
The Impact ◽  
Irritable Mood ◽  
Mood Dysregulation

AbstractObjectiveThe aim of this study is to identify the most appropriate threshold for Disruptive Mood Dysregulation Disorder (DMDD) diagnosis and the impact of potential changes in diagnostic rules on prevalence levels in the community.MethodTrained psychologists evaluated 3,562 pre-adolescents/early adolescents from the 2004 Pelotas Birth Cohort with the Development and Well-Being Behavior Assessment (DAWBA). The clinical threshold was assessed in three stages: symptomatic, syndromic and clinical operationalization. The symptomatic threshold identified the response category in each DAWBA item which separates normative misbehavior from a clinical indicator. The syndromic threshold identified the number of irritable mood and outbursts needed to capture pre-adolescents/early adolescents with high symptom levels. Clinical operationalization compared the impact of AND/OR rules for combining irritable mood and outbursts on impairment and levels of psychopathology.ResultsAt the symptomatic threshold, most irritable mood items were normative in their lowest response categories and clinically significant in their highest response categories. For outbursts some indicated a symptom even when present at only a mild level, while others did not indicate symptoms at any level. At the syndromic level, a combination of 2 out of 7 irritable mood and 3 out of 8 outburst indicators accurately captured a cluster of individuals with high level of symptoms. Analysis combining irritable mood and outbursts delineated non-overlapping aspects of DMDD, providing support for the OR rule in clinical operationalization. The best DMDD criteria resulted in a prevalence of 3%.ConclusionResults provide information for initiatives aiming to provide data-driven and clinically oriented operationalized criteria for DMDD.

Sign in / Sign up

Export Citation Format

Share Document