Qualitative Fault Detection and Hazard Analysis Based on Signed Directed Graphs for Large-Scale Complex Systems

Nowadays in modern industries, the scale and complexity of process systems are increased continuously. These systems are subject to low productivity, system faults or even hazards because of various conditions such as mis-operation, equipment quality change, externa

Automated and unsupervised detection of malarial parasites in microscopic images

<p>Abstract</p> <p>Background</p> <p>Malaria is a serious infectious disease. According to the World Health Organization, it is responsible for nearly one million deaths each year. There are various techniques to diagnose malaria of which manual microscopy is considered to be the gold standard. However due to the number of steps required in manual assessment, this diagnostic method is time consuming (leading to late diagnosis) and prone to human error (leading to erroneous diagnosis), even in experienced hands. The focus of this study is to develop a robust, unsupervised and sensitive malaria screening technique with low material cost and one that has an advantage over other techniques in that it minimizes human reliance and is, therefore, more consistent in applying diagnostic criteria.</p> <p>Method</p> <p>A method based on digital image processing of Giemsa-stained thin smear image is developed to facilitate the diagnostic process. The diagnosis procedure is divided into two parts; enumeration and identification. The image-based method presented here is designed to automate the process of enumeration and identification; with the main advantage being its ability to carry out the diagnosis in an unsupervised manner and yet have high sensitivity and thus reducing cases of false negatives.</p> <p>Results</p> <p>The image based method is tested over more than 500 images from two independent laboratories. The aim is to distinguish between positive and negative cases of malaria using thin smear blood slide images. Due to the unsupervised nature of method it requires minimal human intervention thus speeding up the whole process of diagnosis. Overall sensitivity to capture cases of malaria is 100% and specificity ranges from 50-88% for all species of malaria parasites.</p> <p>Conclusion</p> <p>Image based screening method will speed up the whole process of diagnosis and is more advantageous over laboratory procedures that are prone to errors and where pathological expertise is minimal. Further this method provides a consistent and robust way of generating the parasite clearance curves.</p

Ursodeoxycholic Acid Therapy in Pediatric Primary Sclerosing Cholangitis : Predictors of Gamma Glutamyltransferase Normalization and Favorable Clinical Course

Objective To investigate patient factors predictive of gamma glutamyltransferase (GGT) normalization following ursodeoxycholic acid (UDCA) therapy in children with primary sclerosing cholangitis. Study design We retrospectively reviewed patient records at 46 centers. We included patients with a baseline serum GGT level >= 50 IU/L at diagnosis of primary sclerosing cholangitis who initiated UDCA therapy within 1 month and continued therapy for at least 1 year. We defined "normalization" as a GGT level Results We identified 263 patients, median age 12.1 years at diagnosis, treated with UDCA at a median dose of 15 mg/kg/d. Normalization occurred in 46%. Patients with normalization had a lower prevalence of Crohn's disease, lower total bilirubin level, lower aspartate aminotransferase to platelet ratio index, greater platelet count, and greater serum albumin level at diagnosis. The 5-year survival with native liver was 99% in those patients who achieved normalization vs 77% in those who did not. Conclusions Less than one-half of the patients treated with UDCA have a complete GGT normalization in the first year after diagnosis, but this subset of patients has a favorable 5-year outcome. Normalization is less likely in patients with a Crohn's disease phenotype or a laboratory profile suggestive of more advanced hepatobiliary fibrosis. Patients who do not achieve normalization could reasonably stop UDCA, as they are likely not receiving clinical benefit. Alternative treatments with improved efficacy are needed, particularly for patients with already-advanced disease.Peer reviewe

Constrained state estimation using the ensemble Kalman filter

Recursive estimation of constrained nonlinear dynamical systems has attracted the attention of many researchers in recent years. In this work, we propose a constrained recursive formulation of the ensemble Kalman filter (CEnKF) that retains the advantages of unconstrained Ensemble Kalman Filter while systematically dealing with bounds on the estimated states. The efficacy of the proposed constrained state estimation algorithm using the EnKF is illustrated by application on a simulated gas-phase reactor problem.© IEE

SIGNED DIRECTED GRAPH BASED MODELING AND ITS VALIDATION FROM PROCESS KNOWLEDGE AND PROCESS DATA

This paper is concerned with the fusion of information from process data and process connectivity and its subsequent use in fault diagnosis and process hazard assessment. The Signed Directed Graph (SDG), as a graphical model for capturing process topology and connectivity to show the causal relationships between process variables by material and information paths, has been widely used in root cause and hazard propagation analysis. An SDG is usually built based on process knowledge as described by piping and instrumentation diagrams. This is a complex and experience-dependent task, and therefore the resulting SDG should be validated by process data before being used for analysis. This paper introduces two validation methods. One is based on cross-correlation analysis of process data with assumed time delays, while the other is based on transfer entropy, where the correlation coefficient between two variables or the information transfer from one variable to another can be computed to validate the corresponding paths in SDGs. In addition to this, the relationship captured by data-based methods should also be validated by process knowledge to confirm its causality. This knowledge can be realized by checking the reachability or the influence of one variable on another based on the corresponding SDG which is the basis of causality. A case study of an industrial process is presented to illustrate the application of the proposed methods