ANDES: efficient evaluation of NOT-twig queries in relational databases

Despite a large body of work on XPath query processing in relational environment, systematic study of queries containing not-predicates have received little attention in the literature. Particularly, several xml supports of industrial-strength commercial rdbms fail to efficiently evaluate such queries. In this paper, we present an efficient and novel strategy to evaluate not -twig queries in a tree-unaware relational environment. not -twig queries are XPath queries with ancestor–descendant and parent–child axis and contain one or more not-predicates. We propose a novel Dewey-based encoding scheme called Andes (ANcestor Dewey-based Encoding Scheme), which enables us to efficiently filter out elements satisfying a not-predicate by comparing their ancestor group identifiers. In this approach, a set of elements under the same common ancestor at a specific level in the xml tree is assigned same ancestor group identifier. Based on this scheme, we propose a novel sql translation algorithm for not-twig query evaluation. Experiments carried out confirm that our proposed approach built on top of an off-the-shelf commercial rdbms significantly outperforms state-of-the-art relational and native approaches. We also explore the query plans selected by a commercial relational optimizer to evaluate our translated queries in different input cardinality. Such exploration further validates the performance benefits of Andes.     

Distributed probabilistic inferencing in sensor networks using variational approximation

This paper considers the problem of distributed inferencing in a sensor network. It particularly explores the probabilistic inferencing problem in the context of a distributed Boltzmann machine-based framework for monitoring the network. The paper offers a variational mean-field approach to develop communication-efficient local algorithm for variational inferencing in distributed environments (VIDE). It compares the performance of the proposed approximate variational technique with respect to the exact and centralized techniques. It shows that the VIDE offers a much more communication-efficient solution at very little cost in terms of the accuracy. It also offers experimental results in order to substantiate the scalability of the proposed algorithm.     

Computer Vision Techniques Applied for Diagnostic Analysis of Retinal OCT Images: A Review

The retina is a tiny layer at the posterior pole of an eye and is made up of tissues sensitive to light, these tissues generate nerve signals that pass through the optic nerve to the brain. A retinal disorder occurs when the retina malfunctions; glaucoma, diabetic retinopathy and pathologic myopia are retinal disorders and principal causes of blindness worldwide. These retinal disorders are often diagnosed and treated by an ophthalmologist. However, to accurately assess a retinal disease, ophthalmologist would need qualitative and quantitative analysis of the disease, it’s early and current statistics, but acquisition of these measurements are not possible through manual techniques, there should be automated computer aided diagnosis (CAD) systems to assist ophthalmologists. In this comprehensive review, an analysis and evaluation has been performed of different computer vision and image processing approaches applied to OCT images for automatic diagnosis of retinal disorders. We also reported disease causes, symptoms and pathologies manifestations within OCT images, which can serve as baseline knowledge for development of an automated CAD system. Hence, this disease specific review offers a good understanding to analyze visual impairments from retinal OCT images which will help researcher to design enhanced therapeutic systems for retinal disorders.     

Unconstrained handwritten character recognition based on fuzzy logic

This paper presents an innovative approach called box method for feature extraction for the recognition of handwritten characters. In this method, the binary image of the character is partitioned into a fixed number of subimages called boxes. The features consist of vector distance (γ) from each box to a fixed point. To find γ the vector distances of all the pixels, lying in a particular box, from the fixed point are calculated and added up and normalized by the number of pixels within that box. Here, both neural networks and fuzzy logic techniques are used for recognition and recognition rates are found to be around 97 percent using neural networks and 98 percent using fuzzy logic. The methods are independent of font, size and with minor changes in preprocessing, it can be adopted for any language.     

The Effect of Intensity-Modulated Radiotherapy to the Head and Neck Region on the Oral Innate Immune Response and Oral Microbiome: A Prospective Cohort Study of Head and Neck Tumour Patients

Neutrophils, also known as polymorphonuclear leukocytes (PMNs), form a significant component of the innate host response, and the consequence of the interaction between the oral microbiota and PMNs is a crucial determinant of oral health status. The impact of radiation therapy (RT) for head and neck tumour (HNT) treatment on the oral innate immune system, neutrophils in particular, and the oral microbiome has not been thoroughly investigated. Therefore, the objective of this study was to characterize RT-mediated changes in oral neutrophils (oPMNs) and the oral microbiome in patients undergoing RT to treat HNTs. Oral rinse samples were collected prior to, during and post-RT from HNT patients receiving RT at Dental Oncology at Princess Margaret Cancer Centre. The oPMNs counts and activation states were analysed using flow cytometry, and the oral microbiome was analysed using 16S rRNA gene sequencing. Statistically significant (p < 0.05) drops in oPMN counts and the activation states of the CD11b, CD16, CD18, CD64 and H3Cit markers from pre-RT to post-RT were observed. Moreover, exposure to RT caused a significant reduction in the relative abundance of commensal Gram-negative bacteria and increased the commensal Gram-positive microbes. Ionizing radiation for the treatment of HNTs simultaneously decreased the recruitment of oPMNs into the oral cavity and suppressed their activation state. The oral microbiome composition post-RT was altered significantly due to RT which may favour the colonization of specific microbial communities unfavourable for the long-term development of a balanced oral microbiome.     

Magnetization reversal mechanism of chemically synthesized linear chains of α-Fe nanospheres

Journal of Materials Science - We report upon synthesis of stable chains of magnetically aligned zero-valent α-Fe nanoparticles and investigation of their magnetization reversal mechanism. The...     

Robust performance analysis for uncertain negative‐imaginary systems

Negative‐imaginary systems are important in engineering practice as this class of systems appears quite often in practical problems, for example, lightly damped flexible structures with collocated position sensors and force actuators. In this paper, an analytical framework for robust performance of uncertain negative‐imaginary systems is proposed. The results are obtained by transforming negative‐imaginary systems into a bounded‐real framework via the positive‐real property. This paper deals with all the significant technical difficulties that appear due to the transformation and the punctured j ω‐axis frequency condition of negative‐imaginary systems. The problem is equivalently cast into a structured singular value condition that gives a quantitative performance test for this class of systems. This result also gives an analytical framework for robust stability when the perturbations are mixture of bounded‐real and negative‐imaginary uncertainties. A numerical example is presented to show the usefulness of the proposed methods. Copyright © 2011 John Wiley & Sons, Ltd.     

Architectural View of Flexible Aliphatic –OH Group Coordinated Hemi-Directed Pb(II)-Salen Coordination Polymer: Synthesis,Crystal Structure,Spectroscopic Insights,Supramolecular Topographies,and DFT Perspective

Journal of Inorganic and Organometallic Polymers and Materials - We serendipitously designed one novel 1D hetero-binuclear Zn(II)-Pb(II) coordination polymer, namely...     

Adsorption‐concentration polarization model for ultrafiltration in mixed matrix membrane

Adsorption has been found to be significant in ultrafiltration by mixed matrix membrane. Removal of very low molecular weight solutes compared to the molecular weight cut off of the membrane is facilitated by adsorption. The modeling of the adsorption coupled with concentration polarization is presented based on the mathematical approach developed by Gekas et al. (Gekas et al. Chem Eng Sci. 1993;48:2753–2765), from the first principles. However, extensive modifications were included in theoretical development including those suggested by Ruiz‐Bevia et al. (Ruiz‐Bevia et al. Chem Eng Sci. 1997;52:2343–2352). The developed model captured the rejection dynamics with the help of retention factor. The model equations were solved under the framework of boundary layer analysis, using the integral approach. Effects of the adsorption isotherm and the different parameters affecting the system performance were also investigated. Further, experimental validation of the model results with two different mixed matrix ultrafiltration studies was also elucidated. © 2014 American Institute of Chemical Engineers AIChE J, 60: 2354–2364, 2014