Search results for "PREDICTION"

Assembly Assistance System with Decision Trees and Ensemble Learning

2021

This paper presents different prediction methods based on decision tree and ensemble learning to suggest possible next assembly steps. The predictor is designed to be a component of a sensor-based assembly assistance system whose goal is to provide support via adaptive instructions, considering the assembly progress and, in the future, the estimation of user emotions during training. The assembly assistance station supports inexperienced manufacturing workers, but it can be useful in assisting experienced workers, too. The proposed predictors are evaluated on the data collected in experiments involving both trainees and manufacturing workers, as well as on a mixed dataset, and are compared …

Predictive pumping based on sensor data and weather forecast

2019

In energy production, peat extraction has a significant role in Finland. However, protection of nature has become more and more important globally. How do we solve this conflict of interests respecting both views? In peat production, one important phase is to drain peat bog so that peat production becomes available. This means that we have control over how we can lead water away from peat bog to nature without water contamination with solid and other harmful substances. In this paper we describe a novel method how fouling of water bodies from peat bog can be controlled more efficiently by using weather forecast to predict rainfall and thus, minimize the effluents to nature. peerReviewed

Influence of residual stress, surface roughness and crystallographic texture induced by machining on the corrosion behaviour of copper in salt-fog at…

2012

International audience; The influence of quadratic stress, crystallographic texture, lubrication and surface roughness generated by superfinish turning on the corrosion behaviour of pure copper was quantified in salt-fog atmosphere. This was done using statistical analysis (Pearson's correlation matrix). Three compounds were found after corrosion tests: atacamite/paratacamite and a black layer (mixture of the lubricant and the salt atmosphere). Surface characteristics were classified according to their decreasing influence on the formation of atacamite/paratacamite as follows: surface roughness and quadratic stress. Lubrication and the crystallographic texture have the lowest influence on c…

Input Selection Methods for Soft Sensor Design: A Survey

2020

Soft Sensors (SSs) are inferential models used in many industrial fields. They allow for real-time estimation of hard-to-measure variables as a function of available data obtained from online sensors. SSs are generally built using industries historical databases through data-driven approaches. A critical issue in SS design concerns the selection of input variables, among those available in a candidate dataset. In the case of industrial processes, candidate inputs can reach great numbers, making the design computationally demanding and leading to poorly performing models. An input selection procedure is then necessary. Most used input selection approaches for SS design are addressed in this …

Clinical implications of serum neurofilament in newly diagnosed MS patients: a longitudinal multicentre cohort study

2020

Abstract Background We aim to evaluate serum neurofilament light chain (sNfL), indicating neuroaxonal damage, as a biomarker at diagnosis in a large cohort of early multiple sclerosis (MS) patients. Methods In a multicentre prospective longitudinal observational cohort, patients with newly diagnosed relapsing-remitting MS (RRMS) or clinically isolated syndrome (CIS) were recruited between August 2010 and November 2015 in 22 centers. Clinical parameters, MRI, and sNfL levels (measured by single molecule array) were assessed at baseline and up to four-year follow-up. Findings Of 814 patients, 54.7% (445) were diagnosed with RRMS and 45.3% (369) with CIS when applying 2010 McDonald criteria (R…

Making sense of big data in health research: {T}owards an {EU} action plan

2016

Genome medicine 8(1), 71 (2016). doi:10.1186/s13073-016-0323-y

Urinary Metabolic Signatures Detect Recurrences in Non-Muscle Invasive Bladder Cancer

2019

Patients with non-muscle invasive bladder cancer (NMIBC) undergo lifelong monitoring based on repeated cystoscopy and urinary cytology due to the high recurrence rate of this tumor. Nevertheless, these techniques have some drawbacks, namely, low accuracy in detection of low-grade tumors, omission of pre-neoplastic lesions and carcinomas in situ (CIS), invasiveness, and high costs. This work aims to identify a urinary metabolomic signature of recurrence by proton Nuclear Magnetic Resonance (1H NMR) spectroscopy for the follow-up of NMIBC patients. To do this, changes in the urinary metabolome before and after transurethral resection (TUR) of tumors are analyzed and a Partial Least Square Dis…

Production of High Amounts of Hepatotoxin Nodularin and New Protease Inhibitors Pseudospumigins by the Brazilian Benthic Nostoc sp. CENA543

2017

Nostoc is a cyanobacterial genus, common in soils and a prolific producer of natural products. This research project aimed to explore and characterize Brazilian cyanobacteria for new bioactive compounds. Here we report the production of hepatotoxins and new protease inhibitors from benthic Nostoc sp. CENA543 isolated from a small, shallow, saline-alkaline lake in the Nhecolandia, Pantanal wetland area in Brazil. Nostoc sp. CENA543 produces exceptionally high amounts of nodularin-R. This is the first free-living Nostoc that produces nodularin at comparable levels as the toxic, bloom-forming, Nodularia spumigena. We also characterized pseudospumigins A-F, which are a novel family of linear te…

2015

The University of Minnesota Biocatalysis/Biodegradation Database and Pathway Prediction System (UM-BBD/PPS) has been a unique resource covering microbial biotransformation pathways of primarily xenobiotic chemicals for over 15 years. This paper introduces the successor system, enviPath (The Environmental Contaminant Biotransformation Pathway Resource), which is a complete redesign and reimplementation of UM-BBD/PPS. enviPath uses the database from the UM-BBD/PPS as a basis, extends the use of this database, and allows users to include their own data to support multiple use cases. Relative reasoning is supported for the refinement of predictions and to allow its extensions in terms of previo…

Use of deep learning methods to translate drug-induced gene expression changes from rat to human primary hepatocytes

2020

In clinical trials, animal and cell line models are often used to evaluate the potential toxic effects of a novel compound or candidate drug before progressing to human trials. However, relating the results of animal and in vitro model exposures to relevant clinical outcomes in the human in vivo system still proves challenging, relying on often putative orthologs. In recent years, multiple studies have demonstrated that the repeated dose rodent bioassay, the current gold standard in the field, lacks sufficient sensitivity and specificity in predicting toxic effects of pharmaceuticals in humans. In this study, we evaluate the potential of deep learning techniques to translate the pattern of …