62 research outputs found

    An Adaptive Transmission Power Aware Multipath Routing Protocol for Mobile Ad hoc Networks

    Get PDF
    AbstractSelection of an optimal transmission power for forwarding packets in mobile ad hoc networks has many benefits over setting a common transmission power. These benefits are reduced congestion, reduced interference in the network, lesser number of collisions and reduced energy consumption. In this paper we have proposed a new multipath routing protocol Adaptive Transmission Power – AOMDV that is capable of dynamically changing the transmission power of control packets used for route discovery in the network. Comprehensive simulations are carried out on NS-2, the proposed protocol ATP-AOMDV is compared to AOMDV under various performance metrics like average end to end delay, packet delivery ratio, network throughput and residual battery of nodes to show ATP-AOMDV performs better than AOMDV in saving battery energy in highly mobile network with high traffic loads

    Evaluating the Prosthodontic Status of People Visiting a Dental Clinic in New Delhi, India

    Get PDF
    BACKGROUND: Oral diseases place a huge economic and social burden on the population in terms of pain, suffering and lost productivity, as well as expenditure on treatment and prevention. The elderly people are worst affected by tooth loss as edentulism further leads to deterioration of their existing frail general health. MATERIALS AND METHOD: The present study is an attempt to study the prosthodontic status of people attending a private clinic in Delhi from April to December 2018. Data was collected with the help of WHO Oral Health Assessment Form (2004) and survey was conducted as per guidelines of American Dental Association for Type III examination. Statistical analysis was done using SPSS 20.0. RESULTS: Out of 204 study subjects, 30.4% were completely dentulous, 7.4% were completely edentulous and rest were partially edentulous for the maxillary arch. While 34.8% were completely dentulous, 14.7% were completely edentulous and 50.5% were partially edentulous for the mandibular arch. Prosthodontic status for both the maxillary and mandibular arch was very poor with 79.4% and 85.3% individuals being devoid of any kind of prosthesis in the maxillary and mandibular arch respectively. CONCLUSION: The population of Delhi has a poor prosthodontics status. High cost of prosthetic treatment, lack of availability of skilled healthcare professionals, poor infrastructure and the general attitude of the population towards replacement of missing teeth are the major hindrances in the way of healthcare delivery system in our country. This has lead to the poor prosthodontic status in general population

    Modeling Biogeochemistry and Flow within Heterogeneous Formations in Variably-Saturated Media

    Get PDF
    This dissertation focuses on understanding the complex interactions between hydrological and geochemical processes, and specifically how these interactions are affected by subsurface heterogeneity across scales. Heterogeneity in the form of macropores and fractures provide preferential flowpaths and affect contaminant transport. Biogeochemical processes are also strongly affected by such heterogeneities. Any lithological layering or interface (e.g. plume fringe, wetland-aquifer boundary, etc.) increases biogeochemical activity around that interface. Hydrologic conditions, rainfall events, drainage patterns, and pH variations are also dominant controls on redox processes and thereby affect contaminant distribution and migration. An inherent limitation of modeling fate and transport of contaminants in the subsurface is that the interactions among biogeochemical processes are complex and non-linear. Therefore, this research investigates the effect of hydrological variations and physical heterogeneity on coupled biogeochemical processes across column and landfill scales. Structural heterogeneity in the form of macropore distributions (no macropore, single macropore, and multiple macropores) in experimental soil columns is investigated to accurately model preferential flow and tracer transport. This research is crucial to agricultural systems where soil and crop management practices modify soil structure and alter macropore densities. The comparison between deterministic and stochastic approaches for simulating preferential flow improved the characterization of interface parameters of the dual permeability model, and outlined the need for efficient sampling algorithms or additional datasets to yield unique (equifinal) soil hydraulic parameters. To evaluate the effect of heterogeneity on redox processes, repacked soil columns with homogeneous and heterogeneous (layered) profiles from soil cores collected at the Norman Landfill site, Oklahoma, USA were employed. Results indicate that heterogeneity in the form of textural layering is paramount in controlling redox processes in the layered column. To evaluate the effect of hydrologic conditions on redox processes, temporal data at the Norman landfill site was used. Results indicate that seasonal hydrologic variations exert dominant control over redox-sensitive concentrations. An integrated MCMC algorithm was devised to upscale linked biogeochemical processes from the column to the field scale. Results indicate that heterogeneity and hydrologic processes are paramount in controlling effective redox concentrations at the Norman landfill site

    Understanding and Predicting Vadose Zone Processes

    Get PDF
    Vadose zone hydrologic and biogeochemical processes play a significant role in the capture, storage and distribution of contaminants between the land surface and groundwater. One major issue facing geoscientists in dealing with investigations of the unsaturated zone flow and transport processes is the evaluation of heterogeneity of subsurface media. This chapter presents a summary of approaches for monitoring and modeling of vadose zone dynamics in the presence of heterogeneities and complex features, as well as incorporating transient conditions. Modeling results can then be used to provide early warning of soil and groundwater contamination before problems arise, provide scientific and regulatory credibility to environmental management decision-making process to enhance protection of human health and the environment. We recommend that future studies target the use of RTMs to identify and quantify critical interfaces that control large-scale biogeochemical reaction rates and ecosystem functioning. Improvements also need to be made in devising scaling approaches to reduce the disconnect between measured data and the scale at which processes occur

    Benchmark problems for reactive transport modeling of the generation and attenuation of acid rock drainage

    Get PDF
    Acid rock drainage (ARD) is a problem of international relevance with substantial environmental and economic implications. Reactive transport modeling has proven a powerful tool for the process-based assessment of metal release and attenuation at ARD sites. Although a variety of models has been used to investigate ARD, a systematic model intercomparison has not been conducted to date. This contribution presents such a model intercomparison involving three synthetic benchmark problems designed to evaluate model results for the most relevant processes at ARD sites. The first benchmark (ARD-B1) focuses on the oxidation of sulfide minerals in an unsaturated tailing impoundment, affected by the ingress of atmospheric oxygen. ARD-B2 extends the first problem to include pH buffering by primary mineral dissolution and secondary mineral precipitation. The third problem (ARD-B3) in addition considers the kinetic and pH-dependent dissolution of silicate minerals under low pH conditions. The set of benchmarks was solved by four reactive transport codes, namely CrunchFlow, Flotran, HP1, and MIN3P. The results comparison focused on spatial profiles of dissolved concentrations, pH and pE, pore gas composition, and mineral assemblages. In addition, results of transient profiles for selected elements and cumulative mass loadings were considered in the intercomparison. Despite substantial differences in model formulations, very good agreement was obtained between the various codes. Residual deviations between the results are analyzed and discussed in terms of their implications for capturing system evolution and long-term mass loading predictions

    Surrogate Optimization of Deep Neural Networks for Groundwater Predictions

    Full text link
    Sustainable management of groundwater resources under changing climatic conditions require an application of reliable and accurate predictions of groundwater levels. Mechanistic multi-scale, multi-physics simulation models are often too hard to use for this purpose, especially for groundwater managers who do not have access to the complex compute resources and data. Therefore, we analyzed the applicability and performance of four modern deep learning computational models for predictions of groundwater levels. We compare three methods for optimizing the models' hyperparameters, including two surrogate model-based algorithms and a random sampling method. The models were tested using predictions of the groundwater level in Butte County, California, USA, taking into account the temporal variability of streamflow, precipitation, and ambient temperature. Our numerical study shows that the optimization of the hyperparameters can lead to reasonably accurate performance of all models (root mean squared errors of groundwater predictions of 2 meters or less), but the ''simplest'' network, namely a multilayer perceptron (MLP) performs overall better for learning and predicting groundwater data than the more advanced long short-term memory or convolutional neural networks in terms of prediction accuracy and time-to-solution, making the MLP a suitable candidate for groundwater prediction.Comment: submitted to Journal of Global Optimization; main paper: 25 pages, 19 figures, 1 table; online supplement: 11 pages, 18 figures, 3 table

    Attenuating Sulfidogenesis in a Soured Continuous Flow Column System With Perchlorate Treatment

    Get PDF
    Hydrogen sulfide production by sulfate reducing bacteria (SRB) is the primary cause of oil reservoir souring. Amending environments with chlorate or perchlorate [collectively denoted (per)chlorate] represents an emerging technology to prevent the onset of souring. Recent studies with perchlorate reducing bacteria (PRB) monocultures demonstrated that they have the innate capability to enzymatically oxidize sulfide, thus PRB may offer an effective means of reversing souring. (Per)chlorate may be effective by (i) direct toxicity to SRB; (ii) competitive exclusion of SRB by PRB; or (iii) reversal of souring through re-oxidation of sulfide by PRB. To determine if (per)chlorate could sweeten a soured column system and assign a quantitative value to each of the mechanisms we treated columns flooded with San Francisco bay water with temporally decreasing amounts (50, 25, and 12.5 mM) of (per)chlorate. Geochemistry and the microbial community structure were monitored and a reactive transport model was developed, Results were compared to columns treated with nitrate or untreated. Souring was reversed by all treatments at 50 mM but nitrate-treated columns began to re-sour when treatment concentrations decreased (25 mM). Re-souring was only observed in (per)chlorate-treated columns when concentrations were decreased to 12.5 mM and the extent of re-souring was less than the control columns. Microbial community analyses indicated treatment-specific community shifts. Nitrate treatment resulted in a distinct community enriched in genera known to perform sulfur cycling metabolisms and genera capable of nitrate reduction. (Per)chlorate treatment enriched for (per)chlorate reducing bacteria. (Per)chlorate treatments only enriched for sulfate reducing organisms when treatment levels were decreased. A reactive transport model of perchlorate treatment was developed and a baseline case simulation demonstrated that the model provided a good fit to the effluent geochemical data. Subsequent simulations teased out the relative role that each of the three perchlorate inhibition mechanisms played during different phases of the experiment. These results indicate that perchlorate addition is an effective strategy for both souring prevention and souring reversal. It provides insight into which organisms are involved, and illuminates the interactive effects of the inhibition mechanisms, further highlighting the versatility of perchlorate as a sweetening agent
    • 

    corecore