Groundwater Flow and Contaminant Transport Simulation with Imprecise Parameters

A methodology has been developed in this study wherein a genetic algorithm (GA) is used to find a global optimal solution to a groundwater flow and contaminant problem by incorporating an artificial neural network (ANN) to evaluate the objective function within the genetic algorithm. The study shows that an ANN-GA technique can be used to find the uncertainties in output parameters due to imprecision in input parameters. The ANN-GA methodology is applied to five case studies involving radial flow in a well, one-dimensional solute transport in steady uniform flow, a two-dimensional heterogeneous steady flow, a two-dimensional solute transport, and a two-dimensional unsteady groundwater flow to demonstrate the efficiency and effectiveness of the developed algorithm. The results show that, with this approach, one can successfully measure the uncertainty in groundwater flow and contaminant transport simulations and achieve a considerable reduction in computational effort when compared to the vertex method that has been widely used in the past.     

Sliding eigenvalue decomposition-based cross-term suppression in Wigner–Ville distribution

Journal of Computational Electronics - In this paper, a new method for the cross-term-free Wigner–Ville distribution (WVD) is proposed. The proposed method is based on sliding...     

Groundwater Numerical Simulation in an Open Pit Mine in a Limestone Formation Using MODFLOW

Numerical groundwater simulations of a complex limestone formation quarry in northern Spain enabled problems there to be quantified. A conceptual model of the aquifer, based on extensive in situ field work and information analysis was developed using MODFLOW. Steady state simulations as well as a first transient simulation were performed. The predictions matched the measured flows in the pit reasonably well, allowing practical scenarios of immediate interest to be simulated. Model calibration suggested a new permeability zonation, dependent of the degree of fracturing. The model provides a consistent quantitative framework with which new tests or operations can be evaluated in a cost effective manner.     

Multiple metastatic infections in a hemodialysis patient with untunneled internal jugular catheter

We present an end‐stage renal disease patient on dialysis with fever. The primary source was right internal jugular vein catheter which had metastatic infections in the body probably via an arteriovenous communication in a cavity in left lung. Patient had right psoas muscle abscess and a left kidney abscess. An ¹⁸F‐fluorodeoxyglucose‐positron emission spectroscopy scan was done to find out left kidney abscess. A search of literature did not reveal many patients of psoas abscess secondary to infection of hemodialysis access.     

Multinational Enterprises and the Geographical Clustering of Innovation

Research on the geographic clustering of economic activity dates back to the early twentieth century. It is recognized that in spite of advances in transportation and communications, clustering remains most critical, and is consequently prevalent, in knowledge-intensive fields. Multinational enterprises (MNEs) that increasingly base their value creation and competitive advantage on knowledge-intensive activities are key participants in clusters, affecting both the nature and intertemporal evolution of local innovative activities. However, the role of MNEs in clusters remains under-researched. This paper traces the origins of research on geographic clusters, identifies the seminal contributions focusing on the role of MNEs, discusses potential problems inherent to this area of inquiry and develops an organizing framework for new research.     

Performance modeling of DTN routing with heterogeneous and selfish nodes

The performance modeling study of Delay-Tolerant Network routing, in general, assumes the nodes to be homogeneous (in terms of features such as the coverage range) and uncompromised (in terms of forwarding messages). However, in realistic settings this may not be the case. The routing performance modeling of such realistic scenarios that involve multifariously-featured and egotistic nodes would be interesting and insightful. To this end, in this paper, we analytically model the routing behavior of such nodes using Ordinary Differential Equations for two different routing protocols namely, Epidemic Routing and Two-Hop Routing. Furthermore, we also study the degradation in the routing performance caused by an increase in the fraction of selfish nodes present in the heterogeneous node population. The proposed analytical model is validated via extensive simulations.     

Investigating the Financial Implications and Viability of Diversified Water Supply Systems in an Urban Water Supply Zone

Water Resources Management - Diversified water supply schemes can reduce both peak demand and overall demand in the urban water supply network. Consequently, they provide benefits to both the water...     

An energy efficient middleware for an ad-hoc AAL wireless sensor network

DIA (Dispositivo Inteligente de Alarma, in Spanish) is an AAL (Ambient Assisted Living) system that allows to infer a potential dangerous action of an elderly person living alone at home. This inference is obtained by a specific sensorisation with sensor nodes (portables and fixes) and a reasoning layer embedded in a PC that learns of the users behaviour patterns and advices when actual one differs significantly of the normal patterns. In AAL systems, energy is a limited resource therefore sensor devices need to be properly managed to conserve energy. In this paper, we introduce the design and implementation of innovative and specific mechanisms at the sensory layer middleware which is capable of, first to discriminate spurious motion detections assuming that these signals do not resemble the patterns of real motion detections and, second to reduce the dynamics of messages by a sensor signal processing in order to compress the whole information in one single event. The middleware achieves power saving by modifying the raw information from sensors and adapting it to the predefined semantic of the reasoning layer. It manages the important task of data processing from sensors (raw information), and transfers the pre-processed information into the top layer of reasoning in a more energy efficient way. We also address the trade-off between reducing power consumption and reducing delay for incoming data. We present results from experiments using our implementation of these mechanisms at the middleware that comprises from node firmware to the PC driver. The number of messages of the proposed method with respect to the raw data is reduced by approximately 98.5%. The resources used in the PIR signal processing is reduced by approximately 85%. The resulting delay introduced is small (10–19 s) but system dynamics is slow enough to avoid contextualisation errors or reduction of system performance. We consider these results as very satisfactory.     

Assessment of the Use of NaClO as an Alternative to H2O2 in the Oxidant-Titanium Ore-Simulated Solar Light System for Thiabendazole Degradation

Topics in Catalysis - The use of the magnetic fraction (MF) of a low-grade titanium ore (TO) and two oxidants (H2O2 and NaClO), testing each one separately, were compared in photo-Fenton like...