Multivariate modeling of pan evaporation in monthly temporal resolution using a hybrid evolutionary data-driven method (case study: Urmia Lake and Gavkhouni basins)

2021 ◽  
Vol 193 (6) ◽  
Author(s):  
Alireza Emadi ◽  
Sarvin Zamanzad-Ghavidel ◽  
Sina Fazeli ◽  
Soheila Zarei ◽  
Ali Rashid-Niaghi
Keyword(s):  
Temporal Resolution ◽  
Urmia Lake ◽  
Data Driven ◽  
Multivariate Modeling ◽  
Pan Evaporation

scholarly journals Digital Storytelling in Cultural Heritage: Audience Engagement in the Interactive Documentary New Life

2021 ◽  
Vol 13 (3) ◽  
pp. 1193
Author(s):  
Anna Podara ◽  
Dimitrios Giomelakis ◽  
Constantinos Nicolaou ◽  
Maria Matsiola ◽  
Rigas Kotsakis
Keyword(s):  
Cultural Heritage ◽  
Full Range ◽  
Social Dimension ◽  
Data Driven ◽  
Specific Interest ◽  
Key Factors ◽  
Audience Engagement ◽  
Main Research ◽  
The Social

This paper casts light on cultural heritage storytelling in the context of interactive documentary, a hybrid media genre that employs a full range of multimedia tools to document reality, provide sustainability of the production and successful engagement of the audience. The main research hypotheses are enclosed in the statements: (a) the interactive documentary is considered a valuable tool for the sustainability of cultural heritage and (b) digital approaches to documentary storytelling can provide a sustainable form of viewing during the years. Using the Greek interactive documentary (i-doc) NEW LIFE (2013) as a case study, the users’ engagement is evaluated by analyzing items from a seven-year database of web metrics. Specifically, we explore the adopted ways of the interactive documentary users to engage with the storytelling, the depth to which they were involved along with the most popular sections/traffic sources and finally, the differences between the first launch period and latest years were investigated. We concluded that interactivity affordances of this genre enhance the social dimension of cultural, while the key factors for sustainability are mainly (a) constant promotion with transmedia approach; (b) data-driven evaluation and reform; and (c) a good story that gathers relevant niches, with specific interest to the story.

scholarly journals Multiple target data-driven models to enable sustainable process manufacturing: An industrial bioprocess case study

2021 ◽  
Vol 296 ◽  
pp. 126242
Author(s):  
Oliver J. Fisher ◽  
Nicholas J. Watson ◽  
Laura Porcu ◽  
Darren Bacon ◽  
Martin Rigley ◽  
...  
Keyword(s):  
Data Driven ◽  
Multiple Target ◽  
Process Manufacturing ◽  
Target Data

scholarly journals Organisational Constraints in Data-driven Maintenance: a case study in the automotive industry

2020 ◽  
Vol 53 (3) ◽  
pp. 95-100
Author(s):  
P Savolainen ◽  
J Magnusson ◽  
M. Gopalakrishnan ◽  
E. Turanoglu Bekar ◽  
A. Skoogh
Keyword(s):  
Automotive Industry ◽  
Data Driven

scholarly journals Developing a Hybrid Data-Driven, Mechanistic Virtual Flow Meter - a Case Study

2020 ◽  
Vol 53 (2) ◽  
pp. 11692-11697
Author(s):  
M. Hotvedt ◽  
B. Grimstad ◽  
L. Imsland
Keyword(s):  
Data Driven ◽  
Flow Meter ◽  
Hybrid Data

A Systematic Function Recommendation Process for Data-Driven Product and Service Design

2017 ◽  
Vol 139 (11) ◽  
Author(s):  
Zhinan Zhang ◽  
Ling Liu ◽  
Wei Wei ◽  
Fei Tao ◽  
Tianmeng Li ◽  
...  
Keyword(s):  
Subjective Experience ◽  
Vital Role ◽  
Data Driven ◽  
Design Parameters ◽  
Sound Design ◽  
New Paradigm ◽  
Senior Managers ◽  
Product Service ◽  
Target User

This paper presents a systematic function recommendation process (FRP) to recommend new functions to an existing product and service. Function plays a vital role in mapping user needs to design parameters (DPs) under constraints. It is imperative for manufacturers to continuously equip an existing product/service with exciting new functions. Traditionally, functions are mostly formulated by experienced designers and senior managers based on their subjective experience, knowledge, creativity, and even heuristics. Nevertheless, against the sweeping trend of information explosion, it is increasingly inefficient and unproductive for designers to manually formulate functions. In e-commerce, recommendation systems (RS) are ubiquitously used to recommend new products to users. In this study, the practically viable recommendation approaches are integrated with the theoretically sound design methodologies to serve a new paradigm of recommending new functions to an existing product/service. The aim is to address the problem of how to estimate an unknown rating that a target user would give to a candidate function that is not carried by the target product/service yet. A systematic function → product recommendation process is prescribed, followed by a detailed case study. It is indicated that practically meaningful functional recommendations (FRs) can indeed by generated through the proposed FRP.

A Data-Driven Decision Support Tool at the service of Energy suppliers and Utilities for Tackling Energy Poverty: A case study in Greece

2021 ◽  
Author(s):  
Apostolos Arsenopoulos ◽  
Elissaios Sarmas ◽  
Andriana Stavrakaki ◽  
Ioanna Giannouli ◽  
John Psarras
Keyword(s):  
Decision Support ◽  
Decision Support Tool ◽  
Data Driven ◽  
Energy Poverty ◽  
Support Tool

scholarly journals Increasing the accuracy and temporal resolution of two-filter radon–222 measurements by correcting for the instrument response

2016 ◽  
Vol 9 (6) ◽  
pp. 2689-2707 ◽  
Author(s):  
Alan D. Griffiths ◽  
Scott D. Chambers ◽  
Alastair G. Williams ◽  
Sylvester Werczynski
Keyword(s):  
Temporal Resolution ◽  
Radon Concentration ◽  
Time Response ◽  
Slow Time ◽  
Flow Loop ◽  
Detector Performance ◽  
Convective Boundary ◽  
Near Surface ◽  
Instrument Response

Abstract. Dual-flow-loop two-filter radon detectors have a slow time response, which can affect the interpretation of their output when making continuous observations of near-surface atmospheric radon concentrations. While concentrations are routinely reported hourly, a calibrated model of detector performance shows that ∼ 40 % of the signal arrives more than an hour after a radon pulse is delivered. After investigating several possible ways to correct for the detector's slow time response, we show that a Bayesian approach using a Markov chain Monte Carlo sampler is an effective method. After deconvolution, the detector's output is redistributed into the appropriate counting interval and a 10 min temporal resolution can be achieved under test conditions when the radon concentration is controlled. In the case of existing archived observations, collected under less ideal conditions, the data can be retrospectively reprocessed at 30 min resolution. In one case study, we demonstrate that a deconvolved radon time series was consistent with the following: measurements from a fast-response carbon dioxide monitor; grab samples from an aircraft; and a simple mixing height model. In another case study, during a period of stable nights and days with well-developed convective boundary layers, a bias of 18 % in the mean daily minimum radon concentration was eliminated by correcting for the instrument response.

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