Automatic Extraction of Water Bodies from Landsat Imagery Using Perceptron Model

Extraction of water bodies from satellite imagery has been widely explored in the recent past. Several approaches have been developed to delineate water bodies from different satellite imagery varying in spatial, spectral, and temporal characteristics. The current study puts forward an automatic approach to extract the water body from a Landsat satellite imagery using a perceptron model. Perceptron involves classification based on a linear predictor function that merges few characteristic properties of the object commonly known as feature vectors. The feature vectors, combined with the weights, sum up to provide an input to the output function which is a binary hard limit function. The feature vector in this study is a set of characteristic properties shown by a pixel of the water body. Low reflectance of water in SWIR band, comparison of reflectance in different bands, and a modified normalized difference water index are used as descriptors. The normalized difference water index is modified to enhance its reach over shallow regions. For this study a threshold value of 2 has been proved as best among the three possible threshold values. The proposed method accurately and quickly discriminated water from other land cover features.

Epidemic Spread Modeling with Time Variant Infective Population Using Pushdown Cellular Automata

The world without a disease is a dream of any human being. The disease spread if not controlled could cause an epidemic situation to spread and lead to pandemic. To control an epidemic we need to understand the nature of its spread and the epidemic spread model helps us in achieving this. Here we propose an epidemic spread model which considers not only the current infective population around the population but also the infective population which remain from the previous generations for computing the next generation infected individuals. A pushdown cellular automata model which is an enhanced version of cellular automata by adding a stack component is being used to model the epidemic spread and the model is validated by the real time data of H1N1 epidemic in Abu Dhabi.

CO2 Adsorption: Experimental Investigation and CFD Reactor Model Validation

The National Energy Technology Laboratory is investigating a new process for CO2 capture from large sources such as utility power generation facilities as an alternative to liquid amine based adsorption processes. Many of these advanced dry processes are based upon sorbents composed of supported polyamines. In this analysis, experiments have been conducted in a laboratory-scale fluidized bed reactor and compared to CFD reactor predictions using kinetics obtained from TGA tests. Batch experiments were conducted by flowing a mixture of CO2, H2O, and N2 (simulated flue gas) through a fluidized bed of sorbent material. The exit gas composition time series data is compared to CFD simulations using a 3-dimensional nonisothermal reacting multiphase flow model. The effects of the gas flow rate, distributor design, and particle size are explored through the CFD simulations. It is shown that the time duration for CO2 adsorption decreased for an increase in the gas flow. Fluid bed hydrodynamics indicated that there were regions in the reactor where the inert FCC particles segregated and defluidized; without adversely affecting the capacity of the sorbent to adsorb CO2. The details of the experimental facility and the model as well as the comparative analysis between the data and the simulation results are discussed.

Comparison of Back Propagation Neural Network and Genetic Algorithm Neural Network for Stream Flow Prediction

Comparison of stream flow prediction models has been presented. Stream flow prediction model was developed using typical back propagation neural network (BPNN) and genetic algorithm coupled with neural network (GANN). The study uses daily data from Nethravathi River basin (Karnataka, India). The study demonstrates the prediction ability of GANN. The statistical tests show that GANN model performs much better when compared to BPNN model.

Convenience Yield Value of International Emission Allowance Based on Call Options

Convenience yield is call options; spot holders attain excess investment revenues through holding spot assets instituted futures assets. Based on the hypothesis of convenience yields, our empirical results show that monthly convenience yield of emission allowance has significant options feature; convenience yield has strong correlation with price spread between spot and futures and their price volatility. The market information set is helpful to adjust portfolio policy and improve portfolio investment revenues of emission allowances.

Forecast of Sea Surface Acidification in the Northwestern Mediterranean Sea

Observation data from DYFAMED site, in northwestern Mediterranean Sea between 1995 and 2011, are used to study mathematical forecasts of sea water surface pH evolution over the next century. In a preliminary study, daily and monthly data have been used to compute total inorganic carbon (CT) and total alkalinity (AT) concentrations. Due to the arbitrary number of missing monthly observations from 1995 to 2011, mean pH values have been calculated from the available data in order to obtain a convenient monthly time series. Based on these results, we used in this paper a cubic spline method for interpolation within the range of known time series and then tested two extrapolation methods: linear and exponential smoothing. A 100-year simulated period is performed in order to have information beyond seasonal variations and observations. The mean seasonal variation allows us to draw forecast evolutions from 0.3 to 0.4 pH units decrease in the water surface at the end of the century. Although these simple forecasts do not pretend to present realistic predictions, these obtained theoretical results provide limits on pH variations in the northwestern Mediterranean Sea similar to those in the open ocean.

Dynamic Cellular Automata Based Epidemic Spread Model for Population in Patches with Movement

Epidemiology is the study of spread of diseases among the group of population. If not controlled properly, the epidemic would cause an enormous number of problems and lead to pandemic situation. Here in this paper we consider the situation of populated areas where people live in patches. A dynamic cellular automata model for population in patches is being proposed in this paper. This work not only explores the computing power of cellular automata in modeling the epidemic spread but also provides the pathway in reduction of computing time when using the dynamic cellular automata model for the patchy population when compared to the static cellular automata which is used for a nonpatchy homogeneous population. The variation of the model with movement of population among the patches is also explored which provides an efficient way for evacuation planning and vaccination of infected areas.

A Database Tool for Raising Awareness on the Life Cycle Environmental Impacts of Household Packaging Waste

Packaging is a key stage of the life cycle of a product regarding its environmental impact. Also, the contribution of the households in the success of packaging recycling programs is well documented. The aim of this paper is the presentation of the development of a computer-aided tool that assists consumers in minimising their everyday environmental impact via the environmental assessment of the products’ packaging coupled with the recycling behaviour of the consumer. The tool has been developed in Microsoft Access and consists of a user-friendly interface and four databases which contain data on the packaging materials of consumer products and their weights alongside with data for the recycling rates of various waste packaging materials in Greece. The user inputs the number of packages per product that he/she bought followed by his/her recycling habits. The tool then calculates the environmental impacts of his/her choices (both consumer and recycling). The key advantage of the developed computer tool is its simplicity, both conceptual and operable. On the other hand, its main drawback is that impact assessment data are based on Dutch conditions. Overall, the implications of the developed computer-aided tool for informing and raising consumer awareness on packaging waste recycling are enormous.