Search results for "Format"
showing 10 items of 24643 documents
Application of Selected Methods of Black Box for Modelling the Settleability Process in Wastewater Treatment Plant
2017
Abstract The paper described how the results of measurements of inflow wastewater temperature in the chamber, a degree of external and internal recirculation in the biological-mechanical wastewater treatment plant (WWTP) in Cedzyna near Kielce, Poland, were used to make predictions of settleability of activated sludge. Three methods, namely: multivariate adaptive regression splines (MARS), random forests (RF) and modified random forests (RF + SOM) were employed to compute activated sludge settleability. The results of analysis indicate that modified random forests demonstrate the best predictive abilities.
A Novel Intelligent Technique of Invariant Statistical Embedding and Averaging via Pivotal Quantities for Optimization or Improvement of Statistical …
2020
In the present paper, for intelligent constructing efficient (optimal, uniformly non-dominated, unbiased, improved) statistical decisions under parametric uncertainty, a new technique of invariant embedding of sample statistics in a decision criterion and averaging this criterion over pivots’ probability distributions is proposed. This technique represents a simple and computationally attractive statistical method based on the constructive use of the invariance principle in mathematical statistics. Unlike the Bayesian approach, the technique of invariant statistical embedding and averaging via pivotal quantities (ISE&APQ) is independent of the choice of priors and represents a novelty i…
Robust Network Agreement on Logical Information
2011
Abstract Logical consensus is an approach to distributed decision making which is based on the availability of a network of agents with incomplete system knowledge. The method requires the construction of a Boolean map which defines a dynamic system allowing the entire network to consent on a unique, global decision. Previous work by the authors proved the method to be viable for applications such as intrusion detection within a structured environment, when the agent's communication topology is known in advance. The current work aims at providing a fully distributed protocol, requiring no a priori knowledge of each agent's communication neighbors. The protocol allows the construction of a r…
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…
Dynamic Design Intents Capture with Formal Ontology and Perdurants Object Concept for Collaborative Product Design
2016
Loss of design intents and related information throughout the lifecycle of products are common. Capturing design intents of an assembly, which include a temporal (dynamic) stages, is even harder. This research work aims to enhance the spatiotemporal mereotopology (STM) based ontology in tune with the contemporary efforts in this research domain. The main idea with such STM ontology is to capture dynamic design intents and develop an integrated data translation framework from Computer Aided Design (CAD) system to a visualization system. This integration framework is intended to enhance design sharing in a collaborative environment. In this paper, the framework is demonstrated with a simple m…
Big Data in operations and supply chain management: a systematic literature review and future research agenda
2021
In the era of digitalisation, the role of Big Data is proliferating, receiving considerable attention in all sectors and domains. The domain of operations and supply chain management (OSCM) is no different since it offers multiple opportunities to generate a large magnitude of data in real-time. Such extensive opportunities for data generation have attracted academics and practitioners alike who are eager to tap different elements of Big Data application in OSCM. Despite the richness of prior studies, there is limited research that extensively reviews the extant findings to present an overview of the different facets of this area. The current study addresses this gap by conducting a systema…
Study Regarding the Optimal Milling Parameters for Finishing 3D Printed Parts from ABS and PLA Materials
2018
Abstract In this paper we proposed to identify the optimum milling parameter required for finishing processes performed on 3Dprinted parts from ABS and PLA materials. We have identified the optimum milling parameters for a constant spindle speed of 3500 rot/min for face milling and profile contouring operations with different tools diameters. The study was performed on 3D printed specimens from ABS and PLA materials.
LMI-based 2D-3D Registration: from Uncalibrated Images to Euclidean Scene
2015
International audience; This paper investigates the problem of registering a scanned scene, represented by 3D Euclidean point coordinates , and two or more uncalibrated cameras. An unknown subset of the scanned points have their image projections detected and matched across images. The proposed approach assumes the cameras only known in some arbitrary projective frame and no calibration or autocalibration is required. The devised solution is based on a Linear Matrix Inequality (LMI) framework that allows simultaneously estimating the projective transformation relating the cameras to the scene and establishing 2D-3D correspondences without triangulating image points. The proposed LMI framewo…
Adaptive-gain extended Kalman filter: Extension to the continuous-discrete case
2009
In the present article we propose a nonlinear observer that merges the behaviors 1) of an extended Kalman filter, mainly designed to smooth off noise , and 2) of high-gain observers devoted to handle large perturbations in the state estimation. We specifically aim at continuous-discrete systems. The strategy consists in letting the high-gain self adapt according to the innovation. We define innovation computed over a time window and justify its usage via an important lemma. We prove the general convergence of the resulting observer.
Consistent Clustering of Elements in Large Pairwise Comparison Matrices
2018
[EN] In multi-attribute decision making the number of decision elements under consideration may be huge, especially for complex, real-world problems. Typically these elements are clustered and then the clusters organized hierarchically to reduce the number of elements to be simultaneously handled. These decomposition methodologies are intended to bring the problem within the cognitive ability of decision makers. However, such methodologies have disadvantages, and it may happen that such a priori clustering is not clear, and/or the problem has previously been addressed without any grouping action. This is the situation for the case study we address, in which a panel of experts gives opinions…