A new class of bulk viscous universe with time dependent deceleration parameter and Λ-term

A new class of exact solutions of Einstein’s field equations with a bulk viscous fluid for an LRS Bianchi type-Ia obtained by using a time dependent deceleration parameter and cosmological term Λ. The coefficient of bulk viscosity is assumed to be a power function of mass density (ξ=ξ ₀ ρ ⁿ ). We have obtained a general solution of the field equations from which six models of the universe are derived: exponential, polynomial and sinusoidal form respectively. The behaviour of these models of the universe are also discussed in the frame of reference of recent supernovae Ia observations.      

Higher Dimensional Cosmological Implications Of A Decay Law For λ Term: Expressions For Some Observable Quantities

Implications of cosmological model with a cosmological term of the form , where β is a constant, are analyzed in multidimensional space time. The proper distance, the luminosity distance-redshift, the angular diameter distance-redshift, and look back time-redshift for the model are presented. It has been shown that models are found to be compatible with the present observations. This work, has thus generalized to higher dimensions the well-known result in four dimensional space time. It is found that the difference is significant at least in the principal to the anologous situation in four dimensional space time.     

Some Bianchi Type I Viscous Fluid Cosmological Models with a Variable Cosmological Constant

Some Bianchi type I viscous fluid cosmological models with a variable cosmological constant are investigated in which the expansion is considered only in two direction i.e. one of the Hubble parameter is zero. The viscosity coefficient of bulk viscous fluid is assumed to be a power function of mass density whereas the coefficient of shear viscosity is considered as constant in first case whereas in other case it is taken as proportional to scale of expansion in the model. The cosmological constant Λ is found to be positive and is a decreasing function of time which is supported by results from recent supernovae Ia observations. Some physical and geometric properties of the models are also discussed.     

A Simplified Semi-Automatic Technique for Highway Extraction from High-Resolution Airborne LiDAR Data and Orthophotos

Information on highways is an essential input for various geospatial applications, including car navigation, forensic analysis on highway geometries, and intelligent transportation systems. Semi-automatic and automatic extractions of highways are critical for the regular updating of municipal databases and for highway maintenance. This study presents a semi-automatic data processing approach for extracting highways from high-resolution airborne LiDAR height information and aerial orthophotos. The method was developed based on two data sets. Experimental results for the first testing site showed that the accuracy of the proposed method for highway extraction was 74.50 % for completeness and 73.13 % for correctness. Meanwhile, the completeness and correctness for the second testing site were 71.20 and 70.72 %, respectively. The proposed method was compared with an object-based approach on a different data set. The accuracy for highway extraction of the object-based approach was 64.29 % for completeness and 63.11 % for correctness, whereas that of the proposed method was 67.14 % for completeness and 65.08 % for correctness. This research aims to promote semi-automatic highway extraction from LiDAR data and orthophotos by proposing a new approach and a multistep post-processing technique. The proposed method provides an accurate final output that is valuable for a wide range of geospatial applications.     

Approaches for delineating landslide hazard areas using different training sites in an advanced artificial neural network model

The current paper presents landslide hazard analysis around the Cameron area, Malaysia, using advanced artificial neural networks with the help of Geographic Information System (GIS) and remote sensing techniques. Landslide locations were determined in the study area by interpretation of aerial photographs and from field investigations. Topographical and geological data as well as satellite images were collected, processed, and constructed into a spatial database using GIS and image processing. Ten factors were selected for landslide hazard including: 1) factors related to topography as slope, aspect, and curvature; 2) factors related to geology as lithology and distance from lineament; 3) factors related to drainage as distance from drainage; and 4) factors extracted from TM satellite images as land cover and the vegetation index value. An advanced artificial neural network model has been used to analyze these factors in order to establish the landslide hazard map. The back-propagation training method has been used for the selection of the five different random training sites in order to calculate the factor’s weight and then the landslide hazard indices were computed for each of the five hazard maps. Finally, the landslide hazard maps (five cases) were prepared using GIS tools. Results of the landslides hazard maps have been verified using landslide test locations that were not used during the training phase of the neural network. Our findings of verification results show an accuracy of 69%, 75%, 70%, 83% and 86% for training sites 1, 2, 3, 4 and 5 respectively. GIS data was used to efficiently analyze the large volume of data, and the artificial neural network proved to be an effective tool for landslide hazard analysis. The verification results showed sufficient agreement between the presumptive hazard map and the existing data on landslide areas.     

Dark energy model in anisotropic Bianchi type-III space-time with variable EoS parameter

A new dark energy model in anisotropic Bianchi type-III space-time with variable equation of state (EoS) parameter has been investigated in the present paper. To get the deterministic model, we consider that the expansion θ in the model is proportional to the eigen value s² ₂\sigma^{2}_{~2} of the shear tensor s^j _i\sigma^{j}_{~i}. The EoS parameter ω is found to be time dependent and its existing range for this model is in good agreement with the recent observations of SNe Ia data (Knop et al. in Astrophys. J. 598:102, 2003) and SNe Ia data with CMBR anisotropy and galaxy clustering statistics (Tegmark et al. in Astrophys. J. 606:702, 2004). It has been suggested that the dark energy that explains the observed accelerating expansion of the universe may arise due to the contribution to the vacuum energy of the EoS in a time dependent background. Some physical aspects of dark energy model are also discussed.     

River rafting in mountainous regions of Uttarakhand: Impacts, suggested mitigation measures and sustainability

Uttarakhand state in India is well known for its mountainous ecosystems,traditional communities and a variety of ecotourism destinations.Among various tourism activities,River Rafting along the banks of the Ganges River has increased tremendously for two decades,and has had unprecedented impacts on the traditional communities and the bio-diversity.Therefore,it is meaningful to do a comprehensive study on the various impacts associated with river rafting so as to suggest the pathways to achieve the environmental sustainability in this region.In this study,we collected primary data from randomly selected population units across all stake holders such as local people(n = 100),and camp personnel(n = 22),through a pre-tested questionnaire survey between August 2009 and May 2010.The questionnaire contains issues on culture,social,economic,institutional and associated perceived impacts on pollution and biodiversity including views for sustainability.Secondary information was also collected from various sources and government records to supplement and strengthen the analysis.The impacts were analyzed qualitatively through a ranking mechanism to facilitate the decision making process.The perception of the interviewee about the various possible impacts of rafting was discussed with mitigating mechanism.The ranking analysis as percollected data reveals that economy and education of local community was improved significantly;however aquatic and terrestrial fauna,social cohesion and pollution(water,air,land) were significantly deteriorated.The results show that the existing practices are not sufficient to address the adverse impacts.Improvement in practices is necessary,mainly in the policy regime.Based on the analysis,some measures are recommended on how to protect community interest and environment with the development of river rafting as an ecotourism opportunity.     

Hazard assessment in rockfall-prone Himalayan slopes along National Highway-58, India: rating and simulation

A massive disaster occurred in June 2013 in Kedarnath, India, due to cloudburst and extremely heavy rain along the Chorabari glacier. The resulting flash floods further aggravated the instability of natural and hill cut slopes at different places on the downstream side. The village Rambara that existed in close proximity of Kedarnath was swept away under flow of debris and water. The immediate surrounding area, which housed over a hundred and fifty shops and hotels, was completely washed away leaving no trace of civilization. This calamity in Uttarakhand is considered as India’s worst natural disasters after the tsunami in December 2004. On the downstream of the affected areas lie other pilgrim destinations that witness innumerable footfalls every year. Investigation of the health of the slopes on the routes to these destinations is therefore very important to ensure minimal damage to humans and machinery. The Himalayan terrain is a tectonically active mountain belt, having a large number of unstable natural and road cut slopes. Such slopes with rugged topography lie in the high seismic vulnerability zone. Further, the instability is aggravated by natural and anthropogenic activities increasing at a rapid and uncontrollable rate. In the light of the Kedarnath tragedy, more advanced research is being conducted along the National Highways to monitor and prevent slope/structure failures. This study was conducted to evaluate the hazard potential along National Highway-58, near Saknidhar village of Devprayag district by analysing rockfall using hazard rating systems and numerical simulation. Rockfall hazard rating systems were applied to evaluate the conditions of the slopes and to identify the associated risks. Based on the field and laboratory analyses, the parameters required for numerical models were determined. The bounce height, roll-out distance, kinetic energy and speed of the detached blocks were determined by using a competent rockfall simulator. The results obtained were used to identify rockfall risk in the region. Optimization strategies were applied during investigation by modifying the slope angle, ditch width and ditch angle to assess the possibility of a hazard to occur in different scenarios. The simulation studies revealed that an increasing slope angle could significantly increase the kinetic energy of the rock blocks. However, an increase in the ditch angle and the ditch width reduces the energy of moving blocks. The maximum bounce height above the slope varied from 0.003 m to 0.8 m for 10-kg blocks, whereas the maximum velocity and the maximum kinetic energy under such circumstances were 7.882 m/s and 379.89 J, respectively. The barrier capacity was found to be 233.18 J for 10-kg falling blocks at a height of 10.02 m. From the optimization studies, it was found that the risk can be reduced by up to 13 % if the slope of 70° has a ditch angle of 15° while on a flat ditch, the maximum risk will be at an angle of 65°. If the ditch angle is increased, the vertical component of the falling blocks is more effective than that in case of a flat ditch. These optimization studies lay foundation for advanced research for mitigation of rockfall hazards in similar potential areas.