Predictive Software Models

2011 ◽  
pp. 782-782
Author(s):  
Thomas Zeugmann ◽  
Pascal Poupart ◽  
James Kennedy ◽  
Xin Jin ◽  
Jiawei Han ◽  
...  
Keyword(s):  
Software Models ◽  
Predictive Software

Approaches for Efficient Learning Software Models A Survey

2018 ◽  
Vol 6 (1) ◽  
pp. 108-113
Author(s):  
K. Laxmi Pradeep ◽  
◽  
K. Madhavi ◽  
Keyword(s):  
Software Models ◽  
Learning Software ◽  
Efficient Learning

scholarly journals Predictive Policing and Crime Control in The United States of America and Europe: Trends in a Decade of Research and the Future of Predictive Policing

2021 ◽  
Vol 10 (6) ◽  
pp. 234
Author(s):  
Ishmael Mugari ◽  
Emeka E. Obioha
Keyword(s):  
Crime Control ◽  
Predictive Accuracy ◽  
Criminal Activity ◽  
The United States ◽  
Modern Technology ◽  
Predictive Policing ◽  
Software Applications ◽  
Predictive Algorithms ◽  
Developed Nations ◽  
Predictive Software

There has been a significant focus on predictive policing systems, as law enforcement agents embrace modern technology to forecast criminal activity. Most developed nations have implemented predictive policing, albeit with mixed reactions over its effectiveness. Whilst at its inception, predictive policing involved simple heuristics and algorithms, it has increased in sophistication in the ever-changing technological environment. This paper, which is based on a literature survey, examines predictive policing over the last decade (2010 to 2020). The paper examines how various nations have implemented predictive policing and also documents the impediments to predictive policing. The paper reveals that despite the adoption of predictive software applications such as PredPol, Risk Terrain Modelling, HunchLab, PreMap, PRECOBS, Crime Anticipation System, and Azevea, there are several impediments that have militated against the effectiveness of predictive policing, and these include low predictive accuracy, limited scope of crimes that can be predicted, high cost of predictive policing software, flawed data input, and the biased nature of some predictive software applications. Despite these challenges, the paper reveals that there is consensus by the majority of the researchers on the importance of predictive algorithms on the policing landscape.

scholarly journals Does agricultural intensification cause tipping points in ecosystem services?

2021 ◽  
Author(s):  
Stephen C. L. Watson ◽  
Adrian C. Newton ◽  
Lucy E. Ridding ◽  
Paul M. Evans ◽  
Steven Brand ◽  
...  
Keyword(s):  
Ecosystem Services ◽  
Agricultural Intensification ◽  
Spatial Dynamics ◽  
Policy Option ◽  
List Type ◽  
Tipping Points ◽  
Software Models ◽  
Non Linear ◽  
Study Interval ◽  
The Impact

Abstract Context Agricultural intensification is being widely pursued as a policy option to improve food security and human development. Yet, there is a need to understand the impact of agricultural intensification on the provision of multiple ecosystem services, and to evaluate the possible occurrence of tipping points. Objectives To quantify and assess the long-term spatial dynamics of ecosystem service (ES) provision in a landscape undergoing agricultural intensification at four time points 1930, 1950, 1980 and 2015. Determine if thresholds or tipping points in ES provision may have occurred and if there are any detectable impacts on economic development and employment. Methods We used the InVEST suite of software models together with a time series of historical land cover maps and an Input–Output model to evaluate these dynamics over an 85-year period in the county of Dorset, southern England. Results Results indicated that trends in ES were often non-linear, highlighting the potential for abrupt changes in ES provision to occur in response to slight changes in underlying drivers. Despite the fluctuations in provision of different ES, overall economic activity increased almost linearly during the study interval, in line with the increase in agricultural productivity. Conclusions Such non-linear thresholds in ES will need to be avoided in the future by approaches aiming to deliver sustainable agricultural intensification. A number of positive feedback mechanisms are identified that suggest these thresholds could be considered as tipping points. However, further research into these feedbacks is required to fully determine the occurrence of tipping points in agricultural systems.

scholarly journals Drawing Reproducible Conclusions from Observational Clinical Data with OHDSI

2021 ◽  
Author(s):  
George Hripcsak ◽  
Martijn J. Schuemie ◽  
David Madigan ◽  
Patrick B. Ryan ◽  
Marc A. Suchard
Keyword(s):  
Large Scale ◽  
Open Science ◽  
Positive Control ◽  
Research Literature ◽  
Observational Research ◽  
Common Data Model ◽  
Administrative Claims ◽  
Open Approach ◽  
Operating Characteristics ◽  
Software Models

Summary Objective: The current observational research literature shows extensive publication bias and contradiction. The Observational Health Data Sciences and Informatics (OHDSI) initiative seeks to improve research reproducibility through open science. Methods: OHDSI has created an international federated data source of electronic health records and administrative claims that covers nearly 10% of the world’s population. Using a common data model with a practical schema and extensive vocabulary mappings, data from around the world follow the identical format. OHDSI’s research methods emphasize reproducibility, with a large-scale approach to addressing confounding using propensity score adjustment with extensive diagnostics; negative and positive control hypotheses to test for residual systematic error; a variety of data sources to assess consistency and generalizability; a completely open approach including protocol, software, models, parameters, and raw results so that studies can be externally verified; and the study of many hypotheses in parallel so that the operating characteristics of the methods can be assessed. Results: OHDSI has already produced findings in areas like hypertension treatment that are being incorporated into practice, and it has produced rigorous studies of COVID-19 that have aided government agencies in their treatment decisions, that have characterized the disease extensively, that have estimated the comparative effects of treatments, and that the predict likelihood of advancing to serious complications. Conclusions: OHDSI practices open science and incorporates a series of methods to address reproducibility. It has produced important results in several areas, including hypertension therapy and COVID-19 research.

Unique identification of elements in evolving software models

2013 ◽  
Vol 13 (2) ◽  
pp. 679-711 ◽  
Author(s):  
Sven Wenzel
Keyword(s):  
Software Models
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