Search results for "PREDICT"
showing 10 items of 2174 documents
Macrophytes in boreal streams: Characterizing and predicting native occurrence and abundance to assess human impact
2016
Abstract Macrophytes are a structurally and functionally essential element of stream ecosystems and therefore indispensable in assessment, protection and restoration of streams. Modelling based on continuous environmental gradients offers a potential approach to predict natural variability of communities and thereby improve detection of anthropogenic community change. Using data from minimally disturbed streams, we described natural macrophyte assemblages in pool and riffle habitats separately and in combination, and explored their variation across large scale environmental gradients. Specifically, we developed RIVPACS-type models to predict the presence and abundance of macrophyte taxa at …
Optimization of Synthetic Media Composition for Kluyveromyces marxianus Fed-Batch Cultivation
2021
The Kluyveromyces marxianus yeast recently has gained considerable attention due to its applicability in high-value-added product manufacturing. In order to intensify the biosynthesis rate of a target product, reaching high biomass concentrations in the reaction medium is mandatory. Fed-batch processes are an attractive and efficient way how to achieve high cell densities. However, depending on the physiology of the particular microbial strain, an optimal media composition should be used to avoid by-product synthesis and, subsequently, a decrease in overall process effi-ciency. Thus, the aim of the present study was to optimise the synthetic growth medium and feeding solution compositions (…
Efficient Parallel Sort on AVX-512-Based Multi-Core and Many-Core Architectures
2019
Sorting kernels are a fundamental part of numerous applications. The performance of sorting implementations is usually limited by a variety of factors such as computing power, memory bandwidth, and branch mispredictions. In this paper we propose an efficient hybrid sorting method which takes advantage of wide vector registers and the high bandwidth memory of modern AVX-512-based multi-core and many-core processors. Our approach employs a combination of vectorized bitonic sorting and load-balanced multi-threaded merging. Thread-level and data-level parallelism are used to exploit both compute power and memory bandwidth. Our single-threaded implementation is ~30x faster than qsort in the C st…
Feasibility Analysis For Constrained Model Predictive Control Based Motion Cueing Algorithm
2019
International audience; This paper deals with motion control for an 8-degree-of-freedom (DOF) high performance driving simulator. We formulate a constrained optimal control that defines the dynamical behavior of the system. Furthermore, the paper brings together various methodologies for addressing feasibility issues arising in implicit model predictive control-based motion cueing algorithms.The implementation of different techniques is described and discussed subsequently. Several simulations are carried out in the simulator platform. It is observed that the only technique that can provide ensured closed-loop stability by assuring feasibility over all prediction horizons is a braking law t…
Towards the Design of Robotic Drivers for Full-Scale Self-Driving Racing Cars
2019
Autonomous vehicles are undergoing a rapid development thanks to advances in perception, planning and control methods and technologies achieved in the last two decades. Moreover, the lowering costs of sensors and computing platforms are attracting industrial entities, empowering the integration and development of innovative solutions for civilian use. Still, the development of autonomous racing cars has been confined mainly to laboratory studies and small to middle scale vehicles. This paper tackles the development of a planning and control framework for an electric full scale autonomous racing car, which is an absolute novelty in the literature, upon which we report our preliminary experim…
Robust link prediction in criminal networks: A case study of the Sicilian Mafia
2020
Abstract Link prediction exercises may prove particularly challenging with noisy and incomplete networks, such as criminal networks. Also, the link prediction effectiveness may vary across different relations within a social group. We address these issues by assessing the performance of different link prediction algorithms on a mafia organization. The analysis relies on an original dataset manually extracted from the judicial documents of operation “Montagna”, conducted by the Italian law enforcement agencies against individuals affiliated with the Sicilian Mafia. To run our analysis, we extracted two networks: one including meetings and one recording telephone calls among suspects, respect…
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 Model Markup Language (PMML) Representation of Bayesian Networks: An Application in Manufacturing
2018
International audience; Bayesian networks (BNs) represent a promising approach for the aggregation of multiple uncertainty sources in manufacturing networks and other engineering systems for the purposes of uncertainty quantification, risk analysis, and quality control. A standardized representation for BN models will aid in their communication and exchange across the web. This article presents an extension to the predictive model markup language (PMML) standard for the representation of a BN, which may consist of discrete variables, continuous variables, or their combination. The PMML standard is based on extensible markup language (XML) and used for the representation of analytical models…
Opportunities for the Use of Business Data Analysis Technologies
2016
Abstract The paper analyses the business data analysis technologies, provides their classification and considers relevant terminology. The feasibility of business data analysis technologies handling big data sources is overviewed. The paper shows the results of examination of the online big data source analytics technologies, data mining and predictive modelling technologies and their trends.
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