Methodology to Predict Daily Groundwater Levels by the Implementation of Machine Learning and Crop Models

The continuous decline of groundwater levels caused by variations in climatic conditions and crop water demands is an increased concern for the agricultural community. It is necessary to understand the factors that control these changes in groundwater levels so that we can better address declines and develop improved conservation practices that will lead to a more sustainable use of water. In this study, two machine learning techniques namely support vector regression (SVR) and the nonlinear autoregressive with exogenous inputs (NARX) neural network were implemented to predict daily groundwater levels in a well located in the Mississippi Delta Region (MDR). Results of the NARX model indicate that a Bayesian regularization algorithm with two hidden nodes and 100 time delays was the best architecture to forecast groundwater levels. In another study, the SVR and the NARX model were compared for the prediction of groundwater withdrawal and recharge periods separately. Results from this study showed that input data classified by seasons lead to incremental improvements in the model accuracy, and that the SVR was the most efficient machine learning model with a Mean Squared Error (MSE) of 0.00123 m for the withdrawal season. Analysis of input variables such as previous daily groundwater levels (Gw), precipitation (Pr), and evapotranspiration (ET) showed that the combination of Gw+Pr provides the optimal set for groundwater prediction and that ET degraded the modeling performance, especially during recharge seasons. Finally, the CROPGRO-Soybean crop model was used to simulate the impacts of different volumes of irrigation on the crop height and yield, and to generate the daily irrigation requirements for soybean crops in the MDR. Four irrigation threshold scenarios (20%, 40%, 50% and 60%) were obtained from the CROGRO-Soybean model and used as inputs in the SVR to evaluate the predicted response of daily groundwater levels to different irrigation demands. This study demonstrated that conservative irrigation management, by selecting a low irrigation threshold, can provide good yields comparable to what is produced by a high volume irrigation management practice. Thus, lower irrigation volumes can have a big impact on decreasing the amount of groundwater withdrawals, while still maintaining comparable yields

Methodology to Predict Daily Groundwater Levels by the Implementation of Machine Learning and Crop Models

The continuous decline of groundwater levels caused by variations in climatic conditions and crop water demands is an increased concern for the agricultural community. It is necessary to understand the factors that control these changes in groundwater levels so that we can better address declines and develop improved conservation practices that will lead to a more sustainable use of water. In this study, two machine learning techniques namely support vector regression (SVR) and the nonlinear autoregressive with exogenous inputs (NARX) neural network were implemented to predict daily groundwater levels in a well located in the Mississippi Delta Region (MDR). Results of the NARX model indicate that a Bayesian regularization algorithm with two hidden nodes and 100 time delays was the best architecture to forecast groundwater levels. In another study, the SVR and the NARX model were compared for the prediction of groundwater withdrawal and recharge periods separately. Results from this study showed that input data classified by seasons lead to incremental improvements in the model accuracy, and that the SVR was the most efficient machine learning model with a Mean Squared Error (MSE) of 0.00123 m for the withdrawal season. Analysis of input variables such as previous daily groundwater levels (Gw), precipitation (Pr), and evapotranspiration (ET) showed that the combination of Gw+Pr provides the optimal set for groundwater prediction and that ET degraded the modeling performance, especially during recharge seasons. Finally, the CROPGRO-Soybean crop model was used to simulate the impacts of different volumes of irrigation on the crop height and yield, and to generate the daily irrigation requirements for soybean crops in the MDR. Four irrigation threshold scenarios (20%, 40%, 50% and 60%) were obtained from the CROGRO-Soybean model and used as inputs in the SVR to evaluate the predicted response of daily groundwater levels to different irrigation demands. This study demonstrated that conservative irrigation management, by selecting a low irrigation threshold, can provide good yields comparable to what is produced by a high volume irrigation management practice. Thus, lower irrigation volumes can have a big impact on decreasing the amount of groundwater withdrawals, while still maintaining comparable yields

A Similarity Measure for Material Appearance

We present a model to measure the similarity in appearance between different materials, which correlates with human similarity judgments. We first create a database of 9,000 rendered images depicting objects with varying materials, shape and illumination. We then gather data on perceived similarity from crowdsourced experiments; our analysis of over 114,840 answers suggests that indeed a shared perception of appearance similarity exists. We feed this data to a deep learning architecture with a novel loss function, which learns a feature space for materials that correlates with such perceived appearance similarity. Our evaluation shows that our model outperforms existing metrics. Last, we demonstrate several applications enabled by our metric, including appearance-based search for material suggestions, database visualization, clustering and summarization, and gamut mapping.Comment: 12 pages, 17 figure

A Web Implementation of A Generalized NEP

The Networks of Evolutionary Processors (NEPs) are computing mechanisms directly inspired from the behavior of cell populations more specifically the point mutations in DNA strands. These mechanisms are been used for solving NP-complete problems by means of a parallel computation postulation. This paper describes an implementation of the basic model of NEP using Web technologies and includes the possibility of designing some of the most common variants of it by means the use of the web page design which eases the configuration of a given problem. It is a system intended to be used in a multicore processor in order to benefit from the multi thread use

Social Media Sites Use Intensity and Job Burnout Among the U.S. and Thai Employees

This research explored the effect of social network sites (SNS) use intensity in the workplace on three aspects of job burnout. The data were collected from non-teaching employees from universities in the U.S. (N = 174) and in Thailand (N = 182). Results from partial least squares regression revealed some evidence of the u-curve relationship between SNS use intensity and depersonalization in both countries. However, the u-curve relationship between SNS use and lack of personal accomplishment is only supported in U.S. samples. This suggests that while a moderate degree of SNS use at work tends to lower burnout, a high degree of use appears to create more burnout. The results also reveal a strong positive linkage between SNS use intensity and emotional exhaustion in U.S. samples. Overall, these findings imply that allowing employees to use SNS can provide some benefits, but it is important that employees do not overuse SNS to avoid burnout

Evaluación del mercado inmobiliario con fines de inversión. Caso: casco urbano del municipio de Barinas 2001-2005

Con el objetivo de evaluar el mercado inmobiliario del municipio Barinas con fines de inversión, se analizó el crecimiento de los precios de las viviendas usadas. Se consideró una población de 1.981 viviendas protocolizadas ante el Registro Subalterno durante el período 2001-2005 y distribuidas en 22 urbanizaciones. Se muestrearon 252 viviendas de 5 urbanizaciones. Se emplearon técnicas de regresión lineal y no lineal. Los principales resultados indican que: 1) El incremento de los precios de los inmuebles es acelerado, ajustándose a modelos no lineales que varían con la zona, y 2) En un contexto caracterizado principalmente por una gran demanda y facilidades de crédito, las inversiones son bien redituadas cuando se orientan a la compra de inmuebles de urbanizaciones bien ubicadas, sin problemas importantes de hábitat y que cumplan con los requisitos exigidos por los entes financieros, tal como ocurre con las urbanizaciones Palacio Fajardo, Los Lirios y Don Samuel

Changes in Soil Fungal Communities, Extracellular Enzyme Activities, and Litter Decomposition Across a Fire Chronosequence in Alaskan Boreal Forests

Wildfires are a pervasive disturbance in boreal forests, and the frequency and intensity of boreal wildfires is expected to increase with climate warming. Boreal forests store a large fraction of global soil organic carbon (C), but relatively few studies have documented how wildfires affect soil microbial communities and soil C dynamics. We used a fire chronosequence in upland boreal forests of interior Alaska with sites that were 1, 7, 12, 24, 55, ~90, and ~100 years post-fire to examine the short- and long-term responses of fungal community composition, fungal abundance, extracellular enzyme activity, and litter decomposition to wildfires. We hypothesized that post-fire changes in fungal abundance and community composition would constrain decomposition following fires. We found that wildfires altered the composition of soil fungal communities. The relative abundance of ascomycetes significantly increased following fire whereas basidiomycetes decreased. Post-fire decreases in basidiomycete fungi were likely attributable to declines in ectomycorrhizal fungi. Fungal hyphal lengths in the organic horizon significantly declined in response to wildfire, and they required at least 24 years to return to pre-fire levels. Post-fire reductions in fungal hyphal length were associated with decreased activities of hydrolytic extracellular enzymes. In support of our hypothesis, the decomposition rate of aspen and black spruce litter significantly increased as forests recovered from fire. Our results indicate that post-fire reductions in soil fungal abundance and activity likely inhibit litter decomposition following boreal wildfires. Slower rates of litter decay may lead to decreased heterotrophic respiration from soil following fires and contribute to a negative feedback to climate warming

Grupos estratégicos: su influencia en el desempeño de la industria bancaria venezolana y su relación con la cobertura geográfica

El objetivo de esta investigación fue determinar los grupos estratégicos de la industria bancaria venezolana y su influencia sobre el desempeño en el sector, así como su relación con la cober tura geográfica, durante el primer semestre del año 2008. Los resultados más relevantes fueron los siguientes: 1) Los grupos estratégicos combinan patrones de conductas. 2) Las diferentes estrategias adoptadas por los bancos no se expresaron en una diferenciación en los niveles de resultados económicos y financieros. 3) Los grupos bancarios llevan a cabo una estrategia de cobertura geográfica relacionada con la estrategia financiera

Designing public spaces though the principles of evolution and organization. Case Study: Square Ángel María Garibay, Toluca, State of Mexico

The Ángel María Garibay Kintana square, located in the historic center of the city of Toluca, State of Mexico, was remodeled in 2009, this transformation was necessary because the inside had a structural overload threatened the safety of underground parking therefore the afety of pedestrians on the outside. The principles of evolution -like remodeling, for example-were solved adequately from engineering, however, the impact of public furniture removal and vegetation turned the square into a place of transience, without considering the rganization principle (human interactions). This paper proposes that the principles of organization and evolution are components of a complex integrated system, whose bases are taken up for the functional design and dynamic public spaces, so that grant the possibility of multiple processes confluence of aesthetic, social and turn, enable local development in times of globalization and complexity provide benefits to the community.La plaza Ángel María Garibay Kintana, ubicada en el centro histórico de la ciudad de Toluca, Estado de México, fue remodelada en 2009; esta transformación fue necesaria debido a que su interior tenía una sobrecarga estructural que ponía en riesgo la seguridad el estacionamiento subterráneo y, por ende, la seguridad de los transeúntes en su exterior. Los principios de evolución –como la remodelación, por ejemplo–fueron resueltos adecuadamente desde la ingeniería; sin embargo, el impacto por la remoción del mobiliario público y e la vegetación convirtió a la plaza en un lugar de transitoriedad, sin contemplar el principio de organización (interacciones humanas). Este artículo propone que los principios de organización y evolución sean componentes de un sistema integral complejo, cuyos fundamentos sean retomados para el diseño funcional y dinámico de los espacios públicos, de forma que otorguen la posibilidad de confluencia de múltiples procesos estéticos, sociales y, a su vez, posibiliten el desarrollo local que en tiempos de la globalización y complejidad brindan beneficios a la comunida