scholarly journals Advanced Data Acquisition System for Wind Energy Applications

2018 ◽  
Vol 47 (2) ◽  
pp. 124-130 ◽  
Author(s):  
Andras Nagy ◽  
Ingo Jahn
Keyword(s):  
Wind Energy ◽  
Data Acquisition ◽  
Load Capacity ◽  
Data Acquisition System ◽  
Renewable Energies ◽  
Acquisition System ◽  
Quality Data ◽  
High Quality ◽  
Validation Data ◽  
High Quality Data

Today renewable energies, particularly wind energy are important to meet 24 hour energy demands while keeping car­bon emissions low. As the cost of renewable energies are high, improving their efficiency is a key factor to reduce energy prices. High quality experimental data is essential to develop deeper understanding of the existing systems and to improve their efficiency.This paper introduces an unmanned airborne data acquisition system that can measure properties around wind-turbines to pro­vide new insight into aerodynamic performance and loss mech­anisms and to provide validation data for wind-turbine design methods. The described system is a flexible and portable platform for collecting high quality data from existing full-scale wind-tur­bine installations. This allows experiments to be conducted with­out scaling and with real-world boundary conditions.The system consists of two major parts: the unmanned flying platform (UAV) and the data acquisition system (DAQ). For the UAV a commercially available unit is selected, which has the ability to fly a route autonomously with sufficient preci­sion, the ability to hover, and sufficient load capacity to carry the DAQ system. The DAQ system in contrast, is developed in-house to achieve a high quality data collection capability and to increase flexibility.

scholarly journals Guidelines for Data Acquisition, Quality and Curation for Observational Research Designs (DAQCORD)

2020 ◽  
Vol 4 (4) ◽  
pp. 354-359
Author(s):  
Ari Ercole ◽  
Vibeke Brinck ◽  
Pradeep George ◽  
Ramona Hicks ◽  
Jilske Huijben ◽  
...  
Keyword(s):  
Data Acquisition ◽  
Health Research ◽  
Observational Studies ◽  
Data Curation ◽  
Quality Data ◽  
Observational Research ◽  
High Quality ◽  
High Quality Data ◽  
Research Designs ◽  
Research Questions

AbstractBackground:High-quality data are critical to the entire scientific enterprise, yet the complexity and effort involved in data curation are vastly under-appreciated. This is especially true for large observational, clinical studies because of the amount of multimodal data that is captured and the opportunity for addressing numerous research questions through analysis, either alone or in combination with other data sets. However, a lack of details concerning data curation methods can result in unresolved questions about the robustness of the data, its utility for addressing specific research questions or hypotheses and how to interpret the results. We aimed to develop a framework for the design, documentation and reporting of data curation methods in order to advance the scientific rigour, reproducibility and analysis of the data.Methods:Forty-six experts participated in a modified Delphi process to reach consensus on indicators of data curation that could be used in the design and reporting of studies.Results:We identified 46 indicators that are applicable to the design, training/testing, run time and post-collection phases of studies.Conclusion:The Data Acquisition, Quality and Curation for Observational Research Designs (DAQCORD) Guidelines are the first comprehensive set of data quality indicators for large observational studies. They were developed around the needs of neuroscience projects, but we believe they are relevant and generalisable, in whole or in part, to other fields of health research, and also to smaller observational studies and preclinical research. The DAQCORD Guidelines provide a framework for achieving high-quality data; a cornerstone of health research.

Machine learning & deep learning in data-driven decision making of drug discovery and challenges in high-quality data acquisition in the pharmaceutical industry

2021 ◽  
Author(s):  
Sethu Arun Kumar ◽  
Thirumoorthy Durai Ananda Kumar ◽  
Narasimha M Beeraka ◽  
Gurubasavaraj Veeranna Pujar ◽  
Manisha Singh ◽  
...  
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Deep Learning ◽  
Drug Discovery ◽  
Pharmaceutical Industry ◽  
Data Acquisition ◽  
Data Driven ◽  
Quality Data ◽  
High Quality ◽  
High Quality Data

Predicting novel small molecule bioactivities for the target deconvolution, hit-to-lead optimization in drug discovery research, requires molecular representation. Previous reports have demonstrated that machine learning (ML) and deep learning (DL) have substantial implications in virtual screening, peptide synthesis, drug ADMET screening and biomarker discovery. These strategies can increase the positive outcomes in the drug discovery process without false-positive rates and can be achieved in a cost-effective way with a minimum duration of time by high-quality data acquisition. This review substantially discusses the recent updates in AI tools as cheminformatics application in medicinal chemistry for the data-driven decision making of drug discovery and challenges in high-quality data acquisition in the pharmaceutical industry while improving small-molecule bioactivities and properties.

scholarly journals Development and Experimental Investigation of a Marine Vessel Utilizing the Energy Ship Concept for Far Offshore Wind Energy Conversion

2021 ◽  
Vol 10 (2) ◽  
pp. 305-317
Author(s):  
Mohd Najib Abdul Ghani Yolhamid ◽  
Mohd Norsyarizad Razali ◽  
M.N. Azzeri ◽  
Mohd Shukri Mohd Yusop ◽  
Ahmad Mujahid Ahmad Zaidi ◽  
...  
Keyword(s):  
Wind Energy ◽  
Data Acquisition ◽  
Data Acquisition System ◽  
Offshore Wind ◽  
Acquisition System ◽  
Offshore Wind Energy ◽  
Experimental Proof ◽  
Energy Capture ◽  
Wind Energy Conversion ◽  
Water Turbine

The energy ship is a concept for offshore wind energy capture which has received very little attention until today. To this date, there had not been yet an experimental proof of concept. In order to tackle this issue, an experimental platform and data acquisition system has been developed. A 5.5m long sailing catamaran served as a platform equipped with a 240mm diameter water turbine. The energy ship platform has been tested several times in the actual river to investigate the workability of the platform and data acquisition system. Results show that energy ship platform can produced 500W electric power for a true wind speed of 10 knots.

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