To present the biodiversity information, a semantic model is required that connects all kinds of data about living creatures and their habitats. The model must be able to encode human knowledge for machines to be understood. Ontology offers the richest machine-interpretable (rather than just machine-processable) and explicit semantics that are being extensively used in the biodiversity domain. Various ontologies are developed for the biodiversity domain however a review of the current landscape shows that these ontologies are not capable to define the Indian biodiversity information though India is one of the megadiverse countries. To semantically analyze the Indian biodiversity information, it is crucial to build an ontology that describes all the essential terms of this domain from the unstructured format of the data available on the web. Since, the curation of the ontologies heavily depends on the domain where these are implemented hence there is no ideal methodology is defined yet to be ready for universal use. The aim of this article is to develop an ontology that semantically encodes all the terms of Indian biodiversity information in all its dimensions based on the proposed methodology. The comprehensive evaluation of the proposed ontology depicts that ontology is well built in the specified domain.
As human sight corresponds to the maximum amount of sensory data consumption with respect to visual information input. The loss of visual cognition is a great loss in terms of "data lost in acquisition/transit". Amongst other things, the loss of chromatic or colour data is a considerable loss for the visually impaired subject. This paper proposes a novel approach towards enabling the cognition of colours for the visually impaired users. It is done as a practical approach towards fulfilling multiple practical applications. This elusive goal is achieved by virtue of creating a family of 16 basic colours based on the CGA palette and converted to families. These colour families in turn are mapped to a glove with micro tactile vibration actuators mapped to the fulcrum points of the joints of each finger of one hand (total 15 actuators). Each finger corresponds to a colour family and its intensity is mapped on its respective finger joints based vibrators. Thus providing a very intuitive and least neural load based colour cognition. All the computation happens on a smart device which is wirelessly connected to the glove and a camera that translates the live input image and pre-processes the image into 16 colour palette based "blobs" which when overlapped by the hand, sends equivalent vibration signals to the glove, enabling an instantaneous access to colour data and that too very naturally.
Cystic nephroma is a rare benign cystic neoplasm of the kidney. The preoperative diagnosis with its malignant counterparts cystic partially differentiated nephroblastoma or cystic Wilms' tumor is not easy but is important when one is considering for nephron-sparing surgery.
Magnetic resonance (MR) images suffer from noise introduced by various sources. Due to this noise, diagnosis remains inaccurate. Thus, removal of noise becomes a very important task when dealing with MR images. In this paper, a denoising method has been discussed that makes use of non-local means filter and discrete total variation method. The proposed approach has been compared with other noise removal techniques like non-local means filter, anisotropic diffusion, total variation, and discrete total variation method, and it proves to be effective in reducing noise. The performance of various denoising methods is compared on basis of metrics such as peak signal-to-noise ratio (PSNR), mean square error (MSE), universal image quality index (UQI), and structure similarity index (SSIM) values. This method has been tested for various noise levels, and it outperformed other existing noise removal techniques, without blurring the image.
Recent days, Fractals, superfractals and examination of their dynamic nature are interesting and important notions of research in the field of Mathematics. In Fractal theory, Julia sets and Mandelbrot sets are two remarkable concepts for the researchers with many practical applications. This paper explores the various newborn J-sets (Julia sets) for the complex polynomial, z n + c, n ≥ 2 in GK-orbit. The main centre of point of this research paper is to originate new J-sets (Julia sets) with the understanding of their mathematical characteristics.
Abstract Background: Bone marrow-derived endothelial progenitor cells (EPCs) are critical for metastatic progression. Tetrathiomolybdate (TM), a copper-depleting compound inhibits angiogenesis and maintains tumor dormancy. This study explores the effect of TM on EPCs in patients (pts) at high risk for breast cancer (BC) recurrence. Methods: This phase II study enrolled Stage 3, 4 without evidence of disease (NED), and any node-positive triple negative (TN) BC pts. Only concomitant hormonal therapy was allowed. Pts received induction TM 180 mg daily at baseline (with exception of one pt) followed by an equal or lower daily dose (median 100mg, range 0-140) to maintain ceruloplasmin (Cp) level < 17 mg/dl (target for copper depletion). We monitored EPCs (CD45dim/CD133+/VEGFR2+), Cp, CEA and CA15-3 at baseline and monthly. To assess the association between Cp and EPCs over time, 3 independent mixed effects linear models with subject as a random effect were used to account for the correlation between observations on the same subject. All p-values were two-sided with statistical significance evaluated at the 0.10 alpha level. Results: 40 pts (28 adjuvant, 12 Stage 4 NED, 11 TN) were enrolled and 426 cycles of TM (average 10.65 per pt) were administered in the first 12 months on study. Median age was 50 yrs (29-66). Median number of tumor size and positive lymph nodes among adjuvant pts were 3.5 cm (1.2-7) and 9 (0-42), respectively. Of the patients receiving hormone therapy, 10 patients were on tamoxifen and 15 patients were on an aromatase inhibitor. 20% of patients were receiving a proton pump inhibitor (PPI). Median baseline Cp level was 28 mg/dL (20-47). 75% pts adequately copper depleted at month 1. 91% of TN patients copper depleted compared to hormone receptor positive subtypes (38-43%) and HER2/neu positive subtypes (40-67%). EPCs/ml decreased from baseline to last dose by 12 in pts that were copper-depleted (p=0.10) and by −52 in pts that did not achieve the copper depletion target (p=0.95). Multivariable modeling revealed an association of EPCs with Cp over time (p=0.005), with type of hormone therapy administered (p=0.007), and with co-administration of a PPI (p=0.0008). Six pts relapsed while on study in which a 200-fold increase in EPCs preceded an objective clinical relapse and a tumor marker rise by median of 1 month. Only grade 3/4 toxicity was hematologic, occurred in 20 cycles (4.7%) and resolved in 5-13 days with TM held and resumed at lower dose. Conclusions: TM is a well-tolerated oral copper chelator that may contribute to maintaining EPCs below baseline in copper-depleted pts. PPI may facilitate TM absorption. Molecular subtype and hormone therapy may impact on the ability to copper deplete. EPCs may have potential as a surrogate marker for early relapse and as a therapeutic target for interrupting the metastatic progression. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 2699. doi:1538-7445.AM2012-2699
IoT is evolving as a combination of interconnected devices over a particular network. In the proposed paper, we discuss about the security of IoT system in the wireless devices. IoT security is the platform in which the connected devices over the network are safeguarded over internet of things framework. Wireless devices play an eminent role in this kind of networks since most of the time they are connected to the internet. Accompanied by major users cannot ensure their end to end security in the IoT environment. However, connecting these devices over the internet via using IoT increases the chance of being prone to the serious issues that may affect the system and its data if they are not protected efficiently. In the proposed paper, the security of IoT in wireless devices will be enhanced by using ECC. Since the issues related to security are becoming common these days, an attempt has been made in this proposed paper to enhance the security of IoT networks by using ECC for wireless devices.
Software defect prediction (SDP) models help software development teams to identify defected modules. SDP models use historical data collected from different software repositories. This data may contain certain missing values which make data unfit for SDP model training. This study identifies the best imputation technique used to handle missing values in SDP dataset. Also we investigated for the best imputation technique along with feature selection method. Results showed that the linear regression followed by correlation-based feature is the best combination for building SDP models.
