Experimental study on a novel thermal storage refrigerant-heated radiator coupled with air source heat pump heating system

Clustering models have been used to automatically identify groups in children with cerebral palsy using their clinical observable data Current models used a limited data (eg gait data) and without integrating the underlying data uncertainty Thus, this could be lead to unreliable clustering results The objectives of this present work were to: (1) develop a new clustering approach to integrate multimodal biomechanical data; (2) incorporate prior biomechanical knowledge extracted from multiple data sources to improve the reliability of the clustering results Thus, a new variant of classical evidential C-means (ECM) method called US-ECM (Uncertainty-Space Evidential C-means) was developed and implemented We tested the performance and robustness of the proposed method on a synthetic database of children with cerebral palsy Using Davies−Bouldin index, computational results showed that the use of multimodal data leads to a better clustering result Moreover, the integration of prior knowledge about the uncertainty space of each parameter of interest allowed the clustering algorithm to be converged quickly as well as the clustering performance to be improved significantly In fact, our new clustering method could be used to assist the clinicians in their decision making process (diagnosis, evaluation of medical intervention outcomes, communications with medical professionals) in a more reliable manner

Clustering of Children with Cerebral Palsy with Prior Biomechanical Knowledge Fused from Multiple Data Sources

This paper presents a traceable measurement method developed in the Laboratory of National Measurement Standards for Electricity and Time (NMS Lab for Electricity and Time) - National Standardization Agency of Indonesia for calibrating current coil in order to obtain correction and uncertainty estimation of the current coil windings number (N). Current coils as objects of this research were 10-turn and 50-turn current coil. Calibration was performed using standard multiproduct calibrator (MPC) and two auxiliary devices, current coil F-5500 and clamp meter F-337. Correction and uncertainty values of N current coil were evaluated for DC and AC supplied current using formulation developed based on principle of current division between current coil output and supplied current from MPC. Based on evaluation result analysis, the expanded uncertainties of this method span from 0.47% to 1.0% (when supplied by DC current) and from 0.57% to 1.1% (when supplied by AC current) for 10-turn current coil, and span from 0.44% to 0.65% (when supplied by DC current) and from 0.54% to 0.96% (when supplied by AC current) for 50-turn current coil. Moreover, it also showed that the largest uncertainty component came from current coil F-5500. Meanwhile, the largest correction for 10-turn current coil was obtained 1.2% at 10 A DC, and for 50-turn current coil was obtained -0.47% at 700 A AC. Verification of the calibration and evaluation methods had also been carried out and it indicated that the calibration and analysis methods developed can be used to examine the performance of the current coil.

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A method for calibrating 10-turn and 50-turn current coil using multiproduct calibrator

This paper presents a calculation algorithm for verifying on-line of the manufacturing process stability in large and mass series of some cylindrical parts from axes type. Through experimental investigations, we conducted a statistical control on a sample parts batch to determine the machining accuracy of some checking turret lathes. In the first phase, we performed a statistical analysis of the technological process preceding the manufacture of cylindrical parts in large and mass series. For checking the normality assumption of the deviations for parts machined, we established the main statistical parameters as being arithmetic mean and standard deviation. With these parameters, I could calculate the fraction of probable defective parts. In the second phase, we determined the control limits for the arithmetic mean and standard deviation. With these parameters I could pursue in chronological order the actual achievement of the workpiece size. In this way, I could check the technological process stability on-line for well-defined period's time, between two successive adjustments of the machine-tools. Introduction. Following the actual technological manufacturing process of the cylindrical parts from the axes type, these will have deviations from the dimensional accuracy and geometric shape [2 and 7]. The main factors contributing to the processing deviations emergence are [1, 6, 8 and 9]: the geometrical inaccuracy of machine-tools; the imprecision of the measuring instruments used; the fastener imprecision of workpiece and of the cutting tools; the wear of cutting tools; the variation and modification during the cutting process the thermal parameters for machine tools, fastener devices, workpiece and cutting tools; the elastic deformation of the technological system; the unevenness of cutting depth; the variation of internal stresses into the processing material.

https://hal.archives-ouvertes.fr/hal-01508639/document

Statistical Control of the Technological Process Stability to Manufacturing Cylindrical Parts into High Series

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Vratislav Horálek

Papers

Analysis of basic probability distributions, their properties and use in determining type B evaluation of measurement uncertainties