Identification of critical erosion prone areas in the small agricultural watershed using USLE,GIS and remote sensing

In the present study, Karso watershed of Hazaribagh, Jharkhand State, India was divided into 200 × 200 grid cells and average annual sediment yields were estimated for each grid cell of the watershed to identify the critical erosion prone areas of watershed for prioritization purpose. Average annual sediment yield data on grid basis was estimated using Universal Soil Loss Equation (USLE). In general, a major limitation in the use of hydrological models has been their inability to handle the large amounts of input data that describe the heterogeneity of the natural system. Remote sensing (RS) technology provides the vital spatial and temporal information on some of these parameters. A recent and emerging technology represented by Geographic Information System (GIS) was used as the tool to generate, manipulate and spatially organize disparate data for sediment yield modeling. Thus, the Arc Info 7.2 GIS software and RS (ERDAS IMAGINE 8.4 image processing software) provided spatial input data to the erosion model, while the USLE was used to predict the spatial distribution of the sediment yield on grid basis. The deviation of estimated sediment yield from the observed values in the range of 1.37 to 13.85 percent indicates accurate estimation of sediment yield from the watershed.     

Casting/mold thermal contact heat transfer during solidification of Al-Cu-Si alloy (LM 21) plates in thick and thin molds

Heat flow at the casting/mold interface was assessed and studied during solidification of Al-Cu-Si (LM 21) alloy in preheated cast iron molds of two different thicknesses, coated with graphite and alumina based dressings. The casting and the mold were instrumented with thermocouples connected to a computer controlled temperature data acquisition system. The thermal history at nodal locations in the mold and casting obtained during experimentation was used to estimate the heat flux by solving the one-dimensional inverse heat conduction problem. The cooling rate and solidification time were measured using the computer-aided cooling curve analysis data. The estimated heat flux transients showed a peak due to the formation of a stable solid shell, which has a higher thermal conductivity compared with the liquid metal in contact with the mold wall prior to the occurrence of the peak. The high values of heat flux transients obtained with thin molds were attributed to mold distortion due to thermal stresses. For thin molds, assumption of Newtonian heating yielded reliable interfacial heat transfer coefficients as compared with one-dimensional inverse modeling. The time of occurrence of peak heat flux increased with a decrease in the mold wall thickness and increase in the casting thickness.     

Bridging the gap: effect of text query reformulation in multimodal retrieval

Multimedia Tools and Applications - Multimodal Retrieval provides new paradigms and methods aimed at effectively searching through the enormous volume of data. Multimodal retrieval is a well...     

Multi-Criteria Decision Making Approach for Watershed Prioritization Using Analytic Hierarchy Process Technique and GIS

Watershed prioritization based on the natural resources and physical processes involves locating critical areas of erosion, which produce maximum sediment yield to take up conservation activities on priority basis. The present study was taken up with a specific objective of prioritization of micro-watersheds using Multi-Criteria Decision Approach – Analytic Hierarchy Process (AHP) based SYI model (AHPSYI) under GIS environment for a case study area of Mayurakshi watershed in India. This method basically uses information of Potential Erosion Index (PEI) and Sediment Delivery Ratio (SDR), indicative of transport capacity. In the present study, sediment delivery factors viz., topography, vegetation cover, proximity to water courses and soil were translated into GIS layers and integrated using Boolean conditions to create a data layer of spatially distributed SDIs’ across the watershed. For assessment of PEI, important watershed parameters viz., land use/land cover, soil, slope, and drainage density maps were integrated in the GIS environment using Weighted Linear Combination method (WLC) by assigning weights to themes and ranks to features of individual theme using AHP technique. A comparison between AHPSYI based sub watershed prioritization map with that of prioritization map based on the observed sediment yield data revealed that about 78 % of the area showed concurrence. Thus, it can be inferred that the watershed prioritization based on only thematic layers can be dependable to maximum extent. Subsequently, proposed approach was adopted for prioritization of the study area at micro watershed scale, where area under high and very high categories together constitutes around 33 % of the study area. Around 100 micro-watersheds out of 276 watersheds are under moderate to very high category respectively, signifying the need for watershed management.     

Nimesulide and beta-cyclodextrin inclusion complexes: physicochemical characterization and dissolution rate studies

Complex formation of nimesulide (N) and β-cyclodextrin (βCD) in aqueous solution and in solid state and the possibility of improving the solubility and dissolution rate of nimesulide via complexation with βCD were investigated. Phase solubility studies indicated the formation of a 1:1 complex in solution. The value of the apparent stability constant Kc was 158.98 M^-1. Solid inclusion complexes of N and βCD were prepared by kneading and coevaporation methods. Differential scanning calorimetry (DSC) studies indicated the formation of solid inclusion complexes of N-βCD at a 1:2 molar ratio in both the methods. Solid complexes of N-βD (1:1 and 1:2 M) exhibited higher rates of dissolution and dissolution efficiency values than the corresponding physical mixtures and pure drug. Higher dissolution rates were observed with kneaded complexes than with those prepared by coevaporation. Increases of 25.6- and 38.7-fold in the dissolution rate were observed, respectively, with N-βCD 1:1 and 1:2 kneaded complexes.     

Groundwater management and development by integrated remote sensing and geographic information systems: prospects and constraints

Groundwater is one of the most valuable natural resources, which supports human health, economic development and ecological diversity. Overexploitation and unabated pollution of this vital resource is threatening our ecosystems and even the life of future generations. With the advent of powerful personal computers and the advances in space technology, efficient techniques for land and water management have evolved of which RS (remote sensing) and GIS (geographic information system) are of great significance. These techniques have fundamentally changed our thoughts and ways to manage natural resources in general and water resources in particular. The main intent of the present paper is to highlight RS and GIS technologies and to present a comprehensive review on their applications to groundwater hydrology. A detailed survey of literature revealed six major areas of RS and GIS applications in groundwater hydrology: (i) exploration and assessment of groundwater resources, (ii) selection of artificial recharge sites, (iii) GIS-based subsurface flow and pollution modeling, (iv) groundwater-pollution hazard assessment and protection planning, (v) estimation of natural recharge distribution, and (vi) hydrogeologic data analysis and process monitoring. Although the use of these techniques in groundwater studies has rapidly increased since early nineties, the success rate is very limited and most applications are still in their infancy. Based on this review, salient areas in need of further research and development are discussed, together with the constraints for RS and GIS applications in developing nations. More and more RS- and GIS-based groundwater studies are recommended to be carried out in conjunction with field investigations to effectively exploit the expanding potential of RS and GIS technologies, which will perfect and standardize current applications as well as evolve new approaches and applications. It is concluded that both the RS and GIS technologies have great potential to revolutionize the monitoring and management of vital groundwater resources in the future, though some challenges are daunting before hydrogeologists/hydrologists.     

A survey on review summarization and sentiment classification

Knowledge and Information Systems - With increasingly more people using online services, purchasing products, and reviewing them, it becomes crucial to have a system that can provide a crisp...     

M-Curves path planning model for mobile anchor node and localization of sensor nodes using Dolphin Swarm Algorithm

Wireless Networks - Location information of a sensor node is the primary concern to process the sensed data in Wireless Sensor Networks (WSNs). The location of the sensor node is used in other...     

Energy-Efficient Load Balancing Strategy for Wireless Sensor Networks using Quasi-oppositional based Jaya Optimization

Wireless Personal Communications - The area of wireless sensor networks (WSNs) has gained significant attention from researchers due to its expansive range of applications, such as industrial...     

A Probabilistic Nonlinear Model for Forecasting Daily Water Level in Reservoir

Accurate prediction and monitoring of water level in reservoirs is an important task for the planning, designing, and construction of river-shore structures, and in taking decisions regarding irrigation management and domestic water supply. In this work, a novel probabilistic nonlinear approach based on a hybrid Bayesian network model with exponential residual correction has been proposed for prediction of reservoir water level on daily basis. The proposed approach has been implemented for forecasting daily water levels of Mayurakshi reservoir (Jharkhand, India), using a historic data set of 22 years. A comparative study has also been carried out with linear model (ARIMA) and nonlinear approaches (ANN, standard Bayesian network (BN)) in terms of various performance measures. The proposed approach is comparable with the observed values on every aspect of prediction, and can be applied in case of scarce data, particularly when forcing parameters such as precipitation and other meteorological data are not available.