In this work, a feasible and low-cost approach is proposed for level measurement in multiphase systems inside tanks used for petroleum-derived oil production. The developed level sensor system consisted of light-emitting diodes (LEDs), light-dependent resistor (LDR), and a low-cost microprocessor. Two different types of oil were tested: AW460 and AW68. Linear regression (LR) was applied for 11 scenarios and showed a direct correlation between the level of oil and the sensor’s output. The measurement with AW460 oil presented a perfect linear behavior, while for AW68, a higher standard deviation was obtained justifying the occurrence of the nonlinearity in several scenarios. In order to overcome the nonlinear effect, two machine learning (ML) techniques were tested: K-nearest neighbors regression (KNNR) and multilayer perceptron (MLP) neural network regression. The highest correlation coefficient ( R2 ) and the lowest root mean squared error (RMSE) were obtained for AW68 with MLP. Therefore, MLP was used for regression (level prediction for water, oil, and emulsion) as well as classification (identify the type of oil in the reservoir) simultaneously. The suggested network exhibited a high accuracy for oil identification (99.801%) and improved linear performance in regression ( R2 = 0.9989 and RMSE = 0.065).
DOCUMENT
Abstract Healthcare organizations operate within a network of governments, insurers, inspection services and other healthcare organizations to provide clients with the best possible care. The parties involved must collaborate and are accountable to each other for the care provided. This has led to a diversity of administrative processes that are supported by a multi-system landscape, resulting in administrative burdens among healthcare professionals. Management methods, such as Enterprise Architecture (EA), should help to develop and manage such landscapes, but they are systematic, while the network of healthcare parties is dynamic. The aim of this research is therefore to develop an EA framework that fits the dynamics of network organizations (such as long-term healthcare). This research proposal outlines the practical and scientific relevance of this research and the proposed method. The current status and next steps are also described.
DOCUMENT
from the article: Supply chain integration intensifies through digitalisation of business administration (BA) processes. However, it is unclear whether differences exist between the public and private sector in development or implementation of supply chain integration solutions. The large scope of the supply chain, being a large network of companies working together towards one end product, is limited for this study to e-procurement processes. The related software solutions are included. This study starts with a theoretical snapshot of e-procurement. This is followed by a process viewpoint of the e-procurement function. Next five different forms of e-procurement cooperation are presented seen from an actors network viewpoint. The utilisation of these forms create insight in the differences between the public and private sector in their e-procurement adoption behaviour. The process maturity scan results shows that the process maturity between the two sectors is comparable. However, this only explains the differences per sector concerning their ability to improve and control their processes in general. For reliability, this step is followed by three in-depth interviews combined with analyses of recent e-procurement behaviour studies involving the two sectors. The final step compares the maturity outcome with the in-depth data results. Both sectors show certain forms of coalition in the e-procurement. Where ‘competition’ is a construct that drives the private sector, the public sector has cost control as a driver towards collaboration and integration within e-procurement. This can only partially be explained by the past European financial crises. Differences are found in digital collaboration and the integration itself. The most important difference lies in the European tendering procedure to which the public sector (unlike the private) is restricted. In nature an e-procurement design and development project does not fit the prescribed procedures.
DOCUMENT
Wat zijn belangrijke succesfactoren om onderzoek, onderwijs en ondernemen bij elkaar te brengen, zó dat 'het klikt'. De uitdaging voor de toekomst van bedrijven in de smart factoryligt bij data science: het omzetten van ruwe (sensor) data naar (zinnige) informatie en kennis, waarmee producten en diensten verbeterd kunnen worden. Tevens programma van het symposium t.g.l. inauguratie 3 december 2015
MULTIFILE
Dit eindrapport behandelt het onderzoek van CDM@Airports, gericht op Collaborative Decision Making in de logistieke processen van luchtvrachtafhandeling op Nederlandse luchthavens. Dit project, met een looptijd van ruim twee jaar, is gestart op 8 november 2021 en geëindigd op 31 december 2023. HET PROJECT CDM@AIRPORTS OMVAT DRIE WERKPAKKETTEN: 1. Projectmanagement, dit betreft de algehele aansturing van het project incl. stuurgroep, werkgroep en stakeholdermanagement. 2. Onderzoeksactiviteiten, bestaande uit a) cross-chain-samenwerking, b) duurzaamheid en c) adoptie van digitale oplossingen voor datagedreven logistiek. 3. Management van een living lab, een ‘quadruple-helix-setting’ die fysieke en digitale leeromgevingen integreert voor onderwijs en multidisciplinair toegepast onderzoek.
MULTIFILE
Het Nieuwe Telen (HNT) heeft in haar theoretisch kader de teeltprocessen ingedeeld in zes balansen. De energiebalans, de waterbalans en de assimilatenbalans van de plant en de CO2 balans, de vochtbalans en de energiebalans van de kas. In dit project is onderzocht of de mineralenbalans, de ecologische balans en de hormoonbalans nuttige aanvullingen zijn op de bestaande balansen van HNT. Aanbevelingen: faciliteer onderzoek naar metingen die het mogelijk maken de status van de plant te volgen m.b.t. de mineralenbalans en ecologische balans.
DOCUMENT
