Labelled Classifier with Weighted Drift Trigger Model using Machine Learning for Streaming Data Analysis

The term “data-drift” refers to a difference between the data used to test and validate a model and the data used to deploy it in production. It is possible for data to drift for a variety of reasons. The track of time is an important consideration. Data mining procedures such as classification, clustering, and data stream mining are critical to information extraction and knowledge discovery because of the possibility for significant data type and dimensionality changes over time. The amount of research on mining and analyzing real-time streaming data has risen dramatically in the recent decade. As the name suggests, it’s a stream of data that originates from a number of sources. Analyzing information assets has taken on increased significance in the quest for real-time analytics fulfilment. Traditional mining methods are no longer effective since data is acting in a different way. Aside from storage and temporal constraints, data streams provide additional challenges because just a single pass of the data is required. The dynamic nature of data streams makes it difficult to run any mining method, such as classification, clustering, or indexing, in a single iteration of data. This research identifies concept drift in streaming data classification. For data classification techniques, a Labelled Classifier with Weighted Drift Trigger Model (LCWDTM) is proposed that provides categorization and the capacity to tackle concept drift difficulties. The proposed classifier efficiency is contrasted with the existing classifiers and the results represent that the proposed model in data drift detection is accurate and efficient

Effects of ramped wall temperature and concentration on viscoelastic Jeffrey’s fluid flows from a vertical permeable cone

In thermo-fluid dynamics, free convection flows external to different geometries such as cylinders, ellipses, spheres, curved walls, wavy plates, cones etc. play major role in various industrial and process engineering systems. The thermal buoyancy force associated with natural convection flows can exert a critical role in determining skin friction and heat transfer rates at the boundary. In thermal engineering, natural convection flows from cones has gained exceptional interest. A theoretical analysis is developed to investigate the nonlinear, steady-state, laminar, non-isothermal convection boundary layer flows of viscoelastic fluid from a vertical permeable cone with a power-law variation in both temperature and concentration. The Jeffery’s viscoelastic model simulates the non-Newtonian characteristics of polymers, which constitutes the novelty of the present work. The transformed conservation equations for linear momentum, energy and concentration are solved numerically under physically viable boundary conditions using the finite-differences Keller-Box scheme. The impact of Deborah number (De), ratio of relaxation to retardation time (λ), surface suction/injection parameter (fw), power-law exponent (n), buoyancy ratio parameter (N) and dimensionless tangential coordinate (Ѯ) on velocity, surface temperature, concentration, local skin friction, heat transfer rate and mass transfer rate in the boundary layer regime are presented graphically. It is observed that increasing values of De reduces velocity whereas the temperature and concentration are increased slightly. Increasing λ enhance velocity however reduces temperature and concentration slightly. The heat and mass transfer rate are found to decrease with increasing De and increase with increasing values of λ. The skin friction is found to decrease with a rise in De whereas it is elevated with increasing values of λ. Increasing values of fw and n, decelerates the flow and also cools the boundary layer i.e. reduces temperature and also concentration. The study is relevant to chemical engineering systems, solvent and polymeric processes

The Peripheral Blood Transcriptome Identifies the Presence and Extent of Disease in Idiopathic Pulmonary Fibrosis

<div><h3>Rationale</h3><p>Peripheral blood biomarkers are needed to identify and determine the extent of idiopathic pulmonary fibrosis (IPF). Current physiologic and radiographic prognostic indicators diagnose IPF too late in the course of disease. We hypothesize that peripheral blood biomarkers will identify disease in its early stages, and facilitate monitoring for disease progression.</p> <h3>Methods</h3><p>Gene expression profiles of peripheral blood RNA from 130 IPF patients were collected on Agilent microarrays. Significance analysis of microarrays (SAM) with a false discovery rate (FDR) of 1% was utilized to identify genes that were differentially-expressed in samples categorized based on percent predicted D_LCO and FVC.</p> <h3>Main Measurements and Results</h3><p>At 1% FDR, 1428 genes were differentially-expressed in mild IPF (D_LCO >65%) compared to controls and 2790 transcripts were differentially- expressed in severe IPF (D_LCO >35%) compared to controls. When categorized by percent predicted D_LCO, SAM demonstrated 13 differentially-expressed transcripts between mild and severe IPF (< 5% FDR). These include CAMP, CEACAM6, CTSG, DEFA3 and A4, OLFM4, HLTF, PACSIN1, GABBR1, IGHM, and 3 unknown genes. Principal component analysis (PCA) was performed to determine outliers based on severity of disease, and demonstrated 1 mild case to be clinically misclassified as a severe case of IPF. No differentially-expressed transcripts were identified between mild and severe IPF when categorized by percent predicted FVC.</p> <h3>Conclusions</h3><p>These results demonstrate that the peripheral blood transcriptome has the potential to distinguish normal individuals from patients with IPF, as well as extent of disease when samples were classified by percent predicted D_LCO, but not FVC.</p> </div

Radiative and magnetohydrodynamics flow of third grade viscoelastic fluid past an isothermal inverted cone in the presence of heat generation/absorption

A mathematical analysis is presented to investigate the nonlinear, isothermal, steady-state, free convection boundary layer flow of an incompressible third grade viscoelastic fluid past an isothermal inverted cone in the presence of magnetohydrodynamic, thermal radiation and heat generation/absorption. The transformed conservation equations for linear momentum, heat and mass are solved numerically subject to the realistic boundary conditions using the second-order accurate implicit finite-difference Keller Box Method. The numerical code is validated with previous studies. Detailed interpretation of the computations is included. The present simulations are of interest in chemical engineering systems and solvent and low-density polymer materials processing