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.     

Dual polarized triple band hybrid MIMO cylindrical dielectric resonator antenna for LTE2500/WLAN/WiMAX applications

In this communication, triple band hybrid multi‐input–multi‐output (MIMO) cylindrical dielectric resonator antenna (CDRA) with high isolation is examined. The proposed MIMO antenna includes two symmetric folded microstrip line feeding structures along with CDRA at two different ends of substrate. Two inverted L‐shaped strips on the ground plane are used to enhance the isolation (S₁₂ < ?15 dB) as well as to generates 2.7 GHz frequency band. Metallic strip on the ground plane act as an electromagnetic reflector and also enhance the isolation between two antennas (S₁₂ < ?20 dB). Archetype of proposed MIMO antenna design has been fabricated and tested to validate the simulated results. The proposed antenna operates at three different frequency bands 2.24–2.38 GHz, 2.5–3.26 GHz, and 4.88–7.0 GHz (S₁₁ < ?6 dB) with the fractional bandwidth 6.06%, 26.4%, and 35.7%, respectively. Folded microstrip lines generate path delay between the electric field lines and originate circular polarization characteristics in the frequency range 5.55–5.75 GHz with the fractional bandwidth of 3.55%. In order to satisfy the different performance requirement of MIMO antenna such as envelop correlation coefficient, mean effective gain, effective diversity gain, peak gain are also examined. The proposed antenna is found suitable for LTE2500, WLAN, and WiMAX applications. © 2016 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2016.     

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.     

Cutting force and hole quality analysis in micro-drilling of CFRP

Micro-drilling in carbon fiber reinforced plastic (CFRP) composite material is challenging because this material machining is difficult due to anisotropic, abrasive and non-homogeneous properties and also downscaling of cutting process parameters affect the cutting forces and micro-drilled hole quality extensively. In this work, experimental results based statistical analysis is applied to investigate feed and cutting speed effect on cutting force components and hole quality. Analysis of variance based regression equation is used to predict cutting forces and hole quality and their trend are described by response surface methodology. Results show that roundness error and delamination factor have similar trends to those of radial forces and thrust force, respectively. Non-linear trends of cutting forces and hole quality errors are observed during downscaling of the micro-drill feed value. Optimization results show that cutting forces and hole quality errors are minimum at a feed value which is almost equal to the tool edge radius rather than at the lowest feed value. Therefore, the presented results clearly show the influences of size effects on cutting forces and hole quality parameters in micro-drilling of CFRP composite material.     

Partitioning large networks without breaking communities

The identification of cohesive communities is a key process in social network analysis. However, the algorithms that are effective for finding communities do not scale well to very large problems, as their time complexity is worse than linear in the number of edges in the graph. This is an important issue for those interested in applying social network analysis techniques to very large networks, such as networks of mobile phone subscribers. In this respect, the contributions of this paper are twofold. First, we demonstrate these scaling issues using a prominent community-finding algorithm as a case study. Then, we show that a two-stage process, whereby the network is first decomposed into manageable subnetworks using a multilevel graph partitioning procedure, is effective in finding communities in networks with more than 10⁶ nodes.     

Stacking graphic elements to avoid over-plotting

An ongoing challenge for information visualization is how to deal with over-plotting forced by ties or the relatively limited visual field of display devices. A popular solution is to represent local data density with area (bubble plots, treemaps), color (heatmaps), or aggregation (histograms, kernel densities, pixel displays). All of these methods have at least one of three deficiencies:1) magnitude judgments are biased because area and color have convex downward perceptual functions, 2) area, hue, and brightness have relatively restricted ranges of perceptual intensity compared to length representations, and/or 3) it is difficult to brush or link to individual cases when viewing aggregations. In this paper, we introduce a new technique for visualizing and interacting with datasets that preserves density information by stacking overlapping cases. The overlapping data can be points or lines or other geometric elements, depending on the type of plot. We show real-dataset applications of this stacking paradigm and compare them to other techniques that deal with over-plotting in high-dimensional displays.     

A Unified Variational Volume Registration Method Based on Automatically Learned Brain Structures

We introduce a new volumetric registration technique that effectively combines active surfaces with the finite element method. The method simultaneously aligns multi-label automatic structural segmentation results, which can be obtained by the application of existing segmentation software, to produce an anatomically accurate 3D registration. This registration is obtained by the minimization of a single energy functional. Just like registering raw images, obtaining a 3D registration this way still requires solving a fundamentally ill-posed problem. We explain through academic examples as well as an MRI dataset with manual anatomical labels, which are hidden from the registration method, how the quality of a registration method can be measured and the advantages our approach offers.