Privacy-preserving iris authentication using fully homomorphic encryption

Multimedia Tools and Applications - Rapid advancement in technology has led to the use of biometric authentication in every field. In particular, from the past few years, iris recognition systems...     

Effects of DEM Source,Spatial Resolution and Drainage Area Threshold Values on Hydrological Modeling

Water Resources Management - Automated computation of hydrological and morphometric parameters of any watershed are not only depended on Digital Elevation Model (DEM) resolution but also affected...     

Phytoplankton primary production, chlorophyll-a and nutrient concentrations in the water column of mountainous Lake Phewa, Nepal

The seasonal patterns of phytoplankton primary production, chlorophyll‐a concentration, cell number and several other limnological variables in Lake Phewa, located in the active monsoon zone in Central Himalaya, Nepal, were studied for a year beginning in April 2001. During the study period, the gross primary production and chlorophyll‐a concentrations were relatively low during the monsoon season. The phytoplankton cell number, represented by 24 genera, also fluctuated seasonally, but tended to increase in the pre‐ and post‐monsoon period. These results suggest that the monsoon plays a crucial role in the primary production and phytoplankton dynamics for Lake Phewa. Among the phytoplankton species, Microcystis aeruginosa, a representative species for eutrophic lakes, was the dominant phytoplankton. At the same time, however, it is clear that the lake is not yet heavily eutrophic. The present study suggests that the exchange of lake water during the monsoon season contributes to maintaining the health of the lake against further degradation. Nevertheless, the silt carried in the monsoon rain run‐off from the lake's catchment area suggests increasingly serious degradation problems for this small mountainous lake.     

Reliability studies on GaAs MESFETs fabricated using spin-onplatinum source

GaAs MESFETs were fabricated using a spin-on platinum source as the gate material. They were subsequently aged at 200°C for up to 1000 h. DC electrical characterisation of the MESFETs was carried out during various stages of annealing. The aging behaviour of these MESFETs was compared with those fabricated using conventionally evaporated platinum sources. The results show that the performance of the MESFETs fabricated using a spin-on platinum source is comparable to those of MESFETs fabricated using a conventionally evaporated platinum source     

Hyperion, IKONOS, ALI, and ETM+ sensors in the study of African rainforests

The goal of this research was to compare narrowband hyperspectral Hyperion data with broadband hyperspatial IKONOS data and advanced multispectral Advanced Land Imager (ALI) and Landsat-7 Enhanced Thematic Mapper Plus (ETM+) data through modeling and classifying complex rainforest vegetation. For this purpose, Hyperion, ALI, IKONOS, and ETM+ data were acquired for southern Cameroon, a region considered to be a representative area for tropical moist evergreen and semi-deciduous forests. Field data, collected in near-real time to coincide with satellite sensor overpass, were used to (1) quantify and model the biomass of tree, shrub, and weed species; and (2) characterize forest land use/land cover (LULC) classes.The study established that even the most advanced broadband sensors (i.e., ETM+, IKONOS, and ALI) had serious limitations in modeling biomass and in classifying forest LULC classes. The broadband models explained only 13-60% of the variability in biomass across primary forests, secondary forests, and fallows. The overall accuracies were between 42% and 51% for classifying nine complex rainforest LULC classes using the broadband data of these sensors. Within individual vegetation types (e.g., primary or secondary forest), the overall accuracies increased slightly, but followed a similar trend. Among the broadband sensors, ALI sensor performed better than the IKONOS and ETM+ sensors.When compared to the three broadband sensors, Hyperion narrowband data produced (1) models that explained 36-83% more of the variability in rainforest biomass, and (2) LULC classifications with 45-52% higher overall accuracies. Twenty-three Hyperion narrowbands that were most sensitive in modeling forest biomass and in classifying forest LULC classes were identified and discussed.     

Fuzzy Multiobjective and Linear Programming Based Management Models for Optimal Land-Water-Crop System Planning

In this article, linear programming and fuzzy optimization models are developed for planning and management of available land-water-crop system of Mahanadi-Kathajodi delta in eastern India. The models are used to optimize the economic return, production and labour utilization, and to search the related cropping patterns and intensities with specified land, water, fertilizer and labour availability, and water use pattern constraints. Due to extreme backwardness of the study area, it has been decided to keep all the three objectives of the linear programming models at the same priority level to obtain the compromised solution in a fuzzy environment that incorporates the imprecision in fuzzy goals and fuzzy constraints. These non-structural models facilitate the conjunctive use of available surface water and groundwater resources. A comparative evaluation along with the benefit-cost ratios of the existing and proposed farming systems is also presented.