AN INNOVATIVE DATA QUERY SYSTEM FOR COMMON INTERESTS OF NEIGHBOURS

Internet recognition bakes an essential motivation towards peer to determine file talking about. For understanding the peer to determine file talking about system, an important qualifying qualifying criterion to is efficiency of file location.  Inside our work we submit a peer to determine file talking about system that's closeness-aware additionally to Interest-clustered based on structured peer to determine system. It forms close nodes to cluster after which groups general interest nodes into sub-cluster that is founded on hierarchical topology and apply a wise file replication to boost file query effectiveness. The forecasted system can keep each and every advantage of distributed hash tables above unstructured peer to determine systems. It's closeness-aware additionally to Interest-clustered utilizes an intellectual file replication to boost file research competence and places files sticking with the same interests with one another which makes them available through routing function. The device will progress intra-sub-cluster file searching completely through several approaches. It evolves an overlay for every group that bond lesser capacity nodes towards advanced capacity nodes for spread file querying during remaining from of node overload. Recommended system utilizes range of positive file data to make sure that file requester can recognize whether requested for file reaches its close by nodes

Why do women in India not use public toilets?: patterns and determinants of usage by women in Warangal City

This paper is part of an extended study to assess the needs of women for public toilets (PT) and sanitation facilities in the city of Warangal, Telangana, India. A quantitative dip-stick study with a sample size of 197 women followed by 21 in-depth interviews was undertaken among a cross-section of women from various walks of life, different ages and qualifications. From the content analysis of the interviews and network analysis of the most commonly co-occurring words, the broad themes that emerged as sanitation needs of women in public spaces were related to high demand for exclusive toilets for women with specific facilities and caretakers who collect money and keep the toilets clean, with particular need for women caretakers to add to the feeling of security. A strong need greater number of well-maintained sanitation facilities in places such as bus stops and railway stations and access to the toilets from main roads rather from interior roads were other aspects that emerged

Preparative Regimen Dosing for Hematopoietic Stem Cell Transplantation in Patients with Chronic Kidney Disease: Analysis of the Literature and Recommendations

AbstractHematopoietic stem cell transplantation (HSCT) is a potentially life-saving therapy that has traditionally been associated with high treatment-related mortality due to direct regimen toxicity and a high incidence of graft-versus-host disease. Historically, pre-existing renal insufficiency has been considered an exclusion criterion for transplantation. The advent of nonmyeloablative conditioning regimens as a less toxic modality for treatment has made HSCT more accessible to elderly patients and patients with comorbidities, such as renal impairment. However, there is no clear standard for how to dose preparative regimens for patients with chronic renal impairment who undergo HSCT. This article serves as a review of the current literature to provide dosing recommendations for commonly used preparative agents in the setting of chronic kidney disease, with the aim of providing optimal dosing for this patient population

Zero Crossing Point Detection in a Distorted Sinusoidal Signal Using Decision Tree Classifier

Zero-crossing point detection in a sinusoidal signal is essential in the case of various power systems and power electronics applications like power system protection and power converters controller design. In this paper, 96 data sets are created from a distorted sinusoidal signal based on MATLAB simulation. Dis- torted sinusoidal signals are generated in MATLAB with various noise and harmonic levels. In this pa- per, a decision tree classi er is used to predict the zero crossing point in a distorted signal based on input fea- tures like slope, intercept, correlation and Root Mean Square Error (RMSE). Decision tree classi er model is trained and tested in the Google Colab environment. As per simulation results, it is observed that decision tree classi er is able to predict the zero-crossing points in a distorted signal with maximum accuracy of 98.3 % for noise signals and 100 % for harmonic distorted signals

Nations within a nation: variations in epidemiological transition across the states of India, 1990–2016 in the Global Burden of Disease Study

18% of the world's population lives in India, and many states of India have populations similar to those of large countries. Action to effectively improve population health in India requires availability of reliable and comprehensive state-level estimates of disease burden and risk factors over time. Such comprehensive estimates have not been available so far for all major diseases and risk factors. Thus, we aimed to estimate the disease burden and risk factors in every state of India as part of the Global Burden of Disease (GBD) Study 2016

Non-Zero Crossing Point Detection in a Distorted Sinusoidal Signal Using Logistic Regression Model

Non-Zero crossing point detection in a sinusoidal signal is essential in case of various power system and power electronics applications like power system protection and power converters controller design. In this paper 96 data sets are created from a distorted sinusoidal signal based on MATLAB simulation. Distorted sinusoidal signals are generated in MATLAB with various noise and harmonic levels. In this paper, logistic regression model is used to predict the non-zero crossing point in a distorted signal based on input features like slope, intercept, correlation and RMSE. Logistic regression model is trained and tested in Google Colab environment. As per simulation results, it is observed that logistic regression model is able to predict all non-zero-crossing point in a distorted signal

Non-Zero Crossing Point Detection in a Distorted Sinusoidal Signal Using Logistic Regression Model

Non-Zero crossing point detection in a sinusoidal signal is essential in case of various power system and power electronics applications like power system protection and power converters controller design. In this paper 96 data sets are created from a distorted sinusoidal signal based on MATLAB simulation. Distorted sinusoidal signals are generated in MATLAB with various noise and harmonic levels. In this paper, logistic regression model is used to predict the non-zero crossing point in a distorted signal based on input features like slope, intercept, correlation and RMSE. Logistic regression model is trained and tested in Google Colab environment. As per simulation results, it is observed that logistic regression model is able to predict all non-zero-crossing point in a distorted signal

Applying mechanistic models to reliability evaluation of mechanical components - An illustration

The traditional reliability analyses, considers components to be in binary state, either functional or faulty, and does not consider the concept of multi state or intermediate states between these two binary states. However, there are several components, which need to be operated in different states and their failure criterion also depend on these states. Hence, when dealing with these types of components one should use multi state concept. This can be achieved by modeling the components with mechanistic models, which can give a new dimension for reliability analysis for multiple states. The mechanistic model approach is based on the first principles of science and engineering which provides details about the various failure mechanisms and thereby improved understanding of the associated root causes of the failure and driving forces responsible for component failures. In this paper a general methodology for modeling the components with mechanistic models has been explained and is further illustrated with an example component. A case study on feed water system (consisting of control valves and other mechanical components) of a typical nuclear reactor has been presented. (C) 2011 Elsevier Ltd. All rights reserved