An intelligent hybrid approach for hepatitis disease diagnosis: Combining enhanced k‐means clustering and improved ensemble learning

In real world, the automatic detection of liver disease is a challenging problem among medical practitioners. The intent of this work is to propose an intelligent hybrid approach for the diagnosis of hepatitis disease. The diagnosis is performed with the combination of k‐means clustering and improved ensemble‐driven learning. To avoid clinical experience and to reduce the evaluation time, ensemble learning is deployed, which constructs a set of hypotheses by using multiple learners to solve a liver disease problem. The performance analysis of the proposed integrated hybrid system is compared in terms of accuracy, true positive rate, precision, f‐measure, kappa statistic, mean absolute error, and root mean squared error. Simulation results showed that the enhanced k‐means clustering and improved ensemble learning with enhanced adaptive boosting, bagged decision tree, and J48 decision tree‐based intelligent hybrid approach achieved better prediction outcomes than other existing individual and integrated methods.     

Design of Dual-Gate P-type IMOS Based Industrial Purpose Pressure Sensor

Silicon - In this treatise, we have proposed a Single Material Gate–Dual Gate Impact Ionization Metal Oxide Semiconductor (SMG DG-IMOS) based Pressure Sensor. The pressure sensor has the most...     

Kinetics of droplet growth in liquid—liquid phase separation of polymer—diluent systems: experimental results

Liquid—liquid thermally induced phase separation of the polymer—diluent system isotactic poly(propylene)—diphenyl ether was studied under an optical microscope. It was found that as the system phase separated, droplets of a diluent-rich phase formed within a polymer-rich matrix. These droplets grew in size and decreased in number by a process known as coarsening. The scaling exponent relating droplet diameter and time was determined. The scaling exponent was found to be a strong function of the droplet phase volume fraction, and this strong dependence on volume fraction was relatively insensitive to temperature. The influence of the ratio of interfacial tension between the phases and the viscosity of the matrix phase was less significant on the growth rate of the droplets.     

Effect of coupling agents on thermal and electrical properties of mica/epoxy composites

The influence of 3-aminopropyltriethoxysilane, 3-glycidyloxypropyltrimethoxysilane, and neoalkoxytric(dioctyl pyrophosphato)zirconate on thermal expansion behavior, dielectric strength, and arc resistance of mica/epoxy composites has been investigated. The addition of mica up to 30% resulted in the reduction of thermal expansion with respect to neat resin. However, the coefficient of linear thermal expansion of 30% mica treated with aminosilane was the least among the various coupling agent-coated filler/epoxy composites. Mica (30%)/epoxy composites showed the highest dielectric strength values (26 kV/mm), but the highest arc resistance was obtained in zirconate-treated mica (30%)/epoxy composite. © 1995 John Wiley & Sons, Inc.     

State of the academic field of IS in India

The field of information systems (IS) remains ill-defined, facing problems of recognition and identity crisis. Several papers and debates have been dedicated on this topic for over three decades. The focus of these debates have largely centered on the state of the IS field in Americas and Europe and with a limited study conducted in the Asia–Pacific context. This study attempts to assess the field in the Indian context and highlight the challenges and issues faced by IS faculties in India. Based on literature survey of the seminal papers in the field, we identified the salient topics of interest to IS researchers: identity of the IS field; diversity of the field; research approaches, methods and rigor; reference disciplines; journals and conferences; and IS course and curriculum. A two-phase study was carried out to explore the interest generated by the IS field in India. In the first phase, secondary data review of leading business schools in India was carried out to understand their focus on IS as an academic discipline. In the second phase, we conducted interviews of IS researchers from the premium business schools in India. In our study, we analyze the research focus of IS faculties in B-schools in India, analyze the composition of the faculty pool and the nature of research work undertaken by them. Our study points at the restricted focus of IS researchers in India around a few narrow areas, with a significant breadth of topics not being explored for research. We found the identity struggle of the field to be prominent, which was further compounded by the limited number of active, IS researchers. The growing importance of qualitative techniques in IS research, the challenges of developing a sound base in multiple reference disciplines and the need for making IS course interesting for business school students were some of the other significant observations. Our study also highlighted the paradox of the success of the IT industry in India leading to reduced enrollment of IS courses in B-Schools. We conclude by providing recommendations to B-school deans and directors.     

Simultaneous nonrigid registration of multiple point sets and atlas construction

Group-wise registration of a set of shapes represented by unlabeled point-sets is a challenging problem since, usually this involves solving for point correspondence in a nonrigid motion setting. In this paper, we propose a novel and robust algorithm that is capable of simultaneously computing the mean shape represented by a probability density function from multiple unlabeled point-sets and registering them non-rigidly to this emerging mean shape. This algorithm avoids the correspondence problem by minimizing the Jensen-Shannon (JS) divergence between the point sets. We motivate the use of the JS divergence by pointing out its close relationship to hypothesis testing. We derive the analytic gradient of the cost function in order to efficiently achieve the optimal solution. JS-divergence is symmetric with no bias toward any of the given shapes to be registered and whose mean is being sought. A by product of the registration process is a probabilistic atlas defined as the convex combination of the probability densities of the input point sets being aligned. Our algorithm can be especially useful for creating atlases of various shapes present in images as well as for simultaneously (rigidly or non-rigidly) registering 3D range data sets without having to establish any correspondence. We present experimental results on real and synthetic data.     

Horizontal Voting Ensemble Based Predictive Modeling System for ColonCancer

Colon cancer is the third most commonly diagnosed cancer in the world. Most colon AdenoCArcinoma (ACA) arises from pre-existing benign polyps in the mucosa of the bowel. Thus, detecting benign at the earliest helps reduce the mortality rate. In this work, a Predictive Modeling System (PMS) is developed for the classification of colon cancer using the Horizontal Voting Ensemble (HVE) method. Identifying different patterns in microscopic images is essential to an effective classification system. A twelve-layer deep learning architecture has been developed to extract these patterns. The developed HVE algorithm can increase the system’s performance according to the combined models from the last epochs of the proposed architecture. Ten thousand (10000) microscopic images are taken to test the classification performance of the proposed PMS with the HVE method. The microscopic images obtained from the colon tissues are classified into ACA or benign by the proposed PMS. Results prove that the proposed PMS has ~8% performance improvement over the architecture without using the HVE method. The proposed PMS for colon cancer reduces the misclassification rate and attains 99.2% of sensitivity and 99.4% of specificity. The overall accuracy of the proposed PMS is 99.3%, and without using the HVE method, it is only 91.3%.     

Extranasal Staphylococcus aureus colonization predisposes to bloodstream infections in patients on hemodialysis with noncuffed internal jugular vein catheters

Introduction: Staphylococcal infection of endogenous origin is an important cause of morbidity and mortality in patients who receive hemodialysis (HD). The risk of such infections in nasal carriers of the organism is well defined. Extranasal carriage of the organism at extranasal sites may pose similar risks. Methods: A total of 70 patients about to undergo internal jugular vein catheterization for HD were enrolled in this prospective observational study. Swab cultures were obtained from anterior nares, posterior pharynx, axillae, toe web spaces, and vascular access sites at baseline and 1 week later. A patient was defined as a persistent carrier when the same organism was grown in both samples. Staphylococcus aureus bloodstream infections were assessed by blood and catheter tip cultures over a 90‐day period. Findings: The mean age of the patients was 43.71 ± 16.2 years. Persistent S. aureus carriage at anterior nares, throat, axilla, toe web spaces, vascular access site, and all sites was documented in 27.9%, 11.4%, 40%, 32.9%, 4.3%, and 64.2% of patients, respectively. Fifteen patients developed S. aureus infections. Catheter related S. aureus infections (CRI) were more likely in persistent carriers than nonpersistent carriers with odds ratios (95% CI) of 10.2 (2.8–37.1), 8.6 (1.7–42.2), 17.3 (3.4–86.0), 3.0 (0.9–9.8), and 1.9 (0.2–22.4) for anterior nares, throat, axilla, toe web spaces, and vascular access site carriers, respectively. The probability of developing CRI in persistent S. aureus carriers was 55% compared to none in noncarriers at 90 days (P = 0.04). Discussion: Extranasal S. aureus carriage is as significant a risk factor as nasal carriage for staphylococcal infections in patients on HD through catheters. The study is limited by lack of molecular phenotyping.     

Can twice weekly hemodialysis expand patient access under resource constraints?

The convention of prescribing hemodialysis on a thrice weekly schedule began empirically when it seemed that this frequency was convenient and likely to treat symptoms for a majority of patients. Later, when urea was identified as the main target and marker of clearance, studies supported the prevailing notion that thrice weekly dialysis provided appropriate clearance of urea. Today, national guidelines on hemodialysis from most countries recommend patients receive at least thrice weekly therapy. However, resource constraints in low‐ and middle‐income countries (LMIC) have resulted in a substantial proportion of patients using less frequent hemodialysis in these settings. Observational studies of patients on twice weekly dialysis show that twice weekly therapy has noninferior survival rates compared with thrice weekly therapy. In fact, models of urea clearance also show that twice weekly therapy can meet urea clearance “targets” if patients have significant residual function or if they follow a protein‐restricted diet, as may be common in LMIC. Greater reliance on twice weekly therapy, at least at the start of hemodialysis, therefore has potential to reduce health care costs and increase access to renal replacement therapy in low‐resource settings; however, randomized control trials are needed to better understand long‐term outcomes of twice versus thrice weekly therapy.