987 research outputs found
Solid solution in the series sodium tungsten bronze, lithium tungsten bronze and tungstic oxide
The tungsten bronzes are a series of anionic substitutional solid solutions of alkali metal metatungstates and tungstic oxide. They are neither alloys nor intermetallic compounds, the term tungsten bronzes was adopted because of their remarkable metallic properties, e.g. luster, specific gravity and especially high electrical conductivity, which resembles to that of graphite. Due to its chemical inactivity and beautiful shades of color, it is used as a coating, especially in the plastic industry and for other ornamental products. The properties and the structure of these bronzes have not been investigated entirely satisfactory; within the last twenty years, only a few published information worth mentioning has been made. The present work is intended to find out some of these still unknown properties of the bronzes...For this purpose, the X-ray method of investigation was widely applied. It turned out that only with this method, satisfactory results could be made --Introduction, page 1
Fuzzy rule based profiling approach for enterprise information seeking and retrieval
With the exponential growth of information available on the Internet and various organisational intranets there is a need for profile based information seeking and retrieval (IS&R) systems. These systems should be able to support users with their context-aware information needs. This paper presents a new approach for enterprise IS&R systems using fuzzy logic to develop task, user and document profiles to model user information seeking behaviour. Relevance feedback was captured from real users engaged in IS&R tasks. The feedback was used to develop a linear regression model for predicting document relevancy based on implicit relevance indicators. Fuzzy relevance profiles were created using Term Frequency and Inverse Document Frequency (TF/IDF) analysis for the successful user queries. Fuzzy rule based summarisation was used to integrate the three profiles into a unified index reflecting the semantic weight of the query terms related to the task, user and document. The unified index was used to select the most relevant documents and experts related to the query topic. The overall performance of the system was evaluated based on standard precision and recall metrics which show significant improvements in retrieving relevant documents in response to user queries
An intelligent framework for monitoring students Affective Trajectories using adaptive fuzzy systems
Object Tracking in Vary Lighting Conditions for Fog based Intelligent Surveillance of Public Spaces
With rapid development of computer vision and artificial intelligence, cities are becoming more and more intelligent. Recently, since intelligent surveillance was applied in all kind of smart city services, object tracking attracted more attention. However, two serious problems blocked development of visual tracking in real applications. The first problem is its lower performance under intense illumination variation while the second issue is its slow speed. This paper addressed these two problems by proposing a correlation filter based tracker. Fog computing platform was deployed to accelerate the proposed tracking approach. The tracker was constructed by multiple positions' detections and alternate templates (MPAT). The detection position was repositioned according to the estimated speed of target by optical flow method, and the alternate template was stored with a template update mechanism, which were all computed at the edge. Experimental results on large-scale public benchmark datasets showed the effectiveness of the proposed method in comparison with state-of-the-art methods
Self-Organizing Traffic Flow Prediction with an Optimized Deep Belief Network for Internet of Vehicles
To assist in the broadcasting of time-critical traffic information in an Internet of Vehicles (IoV) and vehicular sensor networks (VSN), fast network connectivity is needed. Accurate traffic information prediction can improve traffic congestion and operation efficiency, which helps to reduce commute times, noise and carbon emissions. In this study, we present a novel approach for predicting the traffic flow volume by using traffic data in self-organizing vehicular networks. The proposed method is based on using a probabilistic generative neural network techniques called deep belief network (DBN) that includes multiple layers of restricted Boltzmann machine (RBM) auto-encoders. Time series data generated from the roadside units (RSUs) for five highway links are used by a three layer DBN to extract and learn key input features for constructing a model to predict traffic flow. Back-propagation is utilized as a general learning algorithm for fine-tuning the weight parameters among the visible and hidden layers of RBMs. During the training process the firefly algorithm (FFA) is applied for optimizing the DBN topology and learning rate parameter. Monte Carlo simulations are used to assess the accuracy of the prediction model. The results show that the proposed model achieves superior performance accuracy for predicting traffic flow in comparison with other approaches applied in the literature. The proposed approach can help to solve the problem of traffic congestion, and provide guidance and advice for road users and traffic regulators
Type-2 fuzzy sets applied to multivariable self-organizing fuzzy logic controllers for regulating anesthesia
In this paper, novel interval and general type-2 self-organizing fuzzy logic controllers (SOFLCs) are proposed for the automatic control of anesthesia during surgical procedures. The type-2 SOFLC is a hierarchical adaptive fuzzy controller able to generate and modify its rule-base in response to the controller's performance. The type-2 SOFLC uses type-2 fuzzy sets derived from real surgical data capturing patient variability in monitored physiological parameters during anesthetic sedation, which are used to define the footprint of uncertainty (FOU) of the type-2 fuzzy sets. Experimental simulations were carried out to evaluate the performance of the type-2 SOFLCs in their ability to control anesthetic delivery rates for maintaining desired physiological set points for anesthesia (muscle relaxation and blood pressure) under signal and patient noise. Results show that the type-2 SOFLCs can perform well and outperform previous type-1 SOFLC and comparative approaches for anesthesia control producing lower performance errors while using better defined rules in regulating anesthesia set points while handling the control uncertainties. The results are further supported by statistical analysis which also show that zSlices general type-2 SOFLCs are able to outperform interval type-2 SOFLC in terms of their steady state performance
MetodologĂa para la identificaciĂłn y el análisis de procesos de intensificaciĂłn agrĂcola mediante la utilizaciĂłn de Sistemas de InformaciĂłn Geográfica e imágenes de satĂ©lite. Caso práctico en la cuenca del Guadiamar (proyecto SITCOVER)
Predictors of mistimed, and unwanted pregnancies among women of childbearing age in Rufiji, Kilombero, and Ulanga districts of Tanzania
Background: While unintended pregnancies pose a serious threat to the health and well-being of families globally, characteristics of Tanzanian women who conceive unintentionally are rarely documented. This analysis identifies factors associated with unintended pregnancies—both mistimed and unwanted—in three rural districts of Tanzania. Methods: A cross-sectional survey of 2,183 random households was conducted in three Tanzanian districts of Rufiji, Kilombero, and Ulanga in 2011 to assess women’s health behavior and service utilization patterns. These households produced 3,127 women age 15+ years from which 2,199 gravid women aged 15–49 were selected for the current analysis. Unintended pregnancies were identified as either mistimed (wanted later) or unwanted (not wanted at all). Correlates of mistimed, and unwanted pregnancies were identified through Chi-squared tests to assess associations and multinomial logistic regression for multivariate analysis. Results: Mean age of the participants was 32.1 years. While 54.1% of the participants reported that their most recent pregnancy was intended, 32.5% indicated their most recent pregnancy as mistimed and 13.4% as unwanted. Multivariate analysis revealed that young age (<20 years), and single marital status were significant predictors of both mistimed and unwanted pregnancies. Lack of inter-partner communication about family planning increased the risk of mistimed pregnancy significantly, and multi-gravidity was shown to significantly increase the risk of unwanted pregnancy. Conclusions: About one half of women in Rufiji, Kilombero, and Ulanga districts of Tanzania conceive unintentionally. Women, especially the most vulnerable should be empowered to avoid pregnancy at their own will and discretion
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Fabrication Flaw Density and Distribution In Repairs to Reactor Pressure Vessel and Piping Welds
The Pacific Northwest National Laboratory is developing a generalized fabrication flaw distribution for the population of nuclear reactor pressure vessels and for piping welds in U.S. operating reactors. The purpose of the generalized flaw distribution is to predict component-specific flaw densities. The estimates of fabrication flaws are intended for use in fracture mechanics structural integrity assessments. Structural integrity assessments, such as estimating the frequency of loss-of-coolant accidents, are performed by computer codes that require, as input, accurate estimates of flaw densities. Welds from four different reactor pressure vessels and a collection of archived pipes have been studied to develop empirical estimates of fabrication flaw densities. This report describes the fabrication flaw distribution and characterization in the repair weld metal of vessels and piping. This work indicates that large flaws occur in these repairs. These results show that repair flaws are complex in composition and sometimes include cracks on the ends of the repair cavities. Parametric analysis using an exponential fit is performed on the data. The relevance of construction records is established for describing fabrication processes and product forms. An analysis of these records shows there was a significant change in repair frequency over the years when these components were fabricated. A description of repair flaw morphology is provided with a discussion of fracture mechanics significance. Fabrication flaws in repairs are characterized using optimized-access, high-sensitivity nondestructive ultrasonic testing. Flaw characterizations are then validated by other nondestructive evaluation techniques and complemented by destructive testing
Specific Etiologies Associated With the Multiple Organ Dysfunction Syndrome in Children: Part 2
To describe a number of conditions and therapies associated with multiple organ dysfunction syndrome (MODS) presented as part of the Eunice Kennedy Shriver National Institute of Child Health and Human Development MODS Workshop (March 26–27, 2015). In addition, the relationship between burn injuries and MODS is also included although it was not discussed at the Workshop
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