A new class of LRS Bianchi type-II dark energy models with variable EoS parameter

A new class of dark energy models in a Locally Rotationally Symmetric Bianchi type-II (LRS B-II) space-time with variable equation of state (EoS) parameter and constant deceleration parameter have been investigated in the present paper. The Einstein’s field equations have been solved by applying a variation law for generalized Hubble’s parameter given by Berman: Nuovo Cimento 74:182 (1983) which generates two types of solutions for the average scale factor, one is of power-law type and other is of the exponential-law form. Using these two forms, Einstein’s field equations are solved separately that correspond to expanding singular and non-singular models of the universe respectively. The dark energy EoS parameter ω is found to be time dependent and its existing range for both models is in good agreement with the three recent observations of (i) SNe Ia data (Knop et al.: Astrophys. J. 598:102 (2003)), (ii) SNe Ia data collaborated with CMBR anisotropy and galaxy clustering statistics (Tegmark et al.: Astrophys. J. 606:702 (2004)) and latest (iii) a combination of cosmological datasets coming from CMB anisotropies, luminosity distances of high redshift type Ia supernovae and galaxy clustering (Hinshaw et al.: Astrophys. J. Suppl. 180:225 (2009); Komatsu et al. Astrophys. J. Suppl. 180:330 (2009)). The cosmological constant Λ is found to be a positive decreasing function of time and it approaches a small positive value at late time (i.e. the present epoch) which is corroborated by results from recent supernovae Ia observations. The physical and geometric behaviour of the universe have also been discussed in detail.     

Einstein-Maxwell field equations in isotropic coordinates: an application to neutron star and quark star

The photogravitational restricted three bodies within the framework of the post-Newtonian approximation is carried out. The mass of the primaries are assumed changed under the effect of continuous radiation process and oblateness effects of the two primaries. New perturbed locations of the triangular points are computed. In order to introduce a semi-analytical view, A Mathematica program is constructed so as to draw the locations of triangular points versus the whole range of the mass ratio μ taking into account the photo-gravitational effects, the relativistic corrections and/or oblateness effects. All the obtained figures are analyzed.     

Semi-automated procedures for shoreline extraction using single RADARSAT-1 SAR image

Coastline identification is important for surveying and mapping reasons. Coastline serves as the basic point of reference and is used on nautical charts for navigation purposes. Its delineation has become crucial and more important in the wake of the many recent earthquakes and tsunamis resulting in complete change and redraw of some shorelines. In a tropical country like Malaysia, presence of cloud cover hinders the application of optical remote sensing data. In this study a semi-automated technique and procedures are presented for shoreline delineation from RADARSAT-1 image. A scene of RADARSAT-1 satellite image was processed using enhanced filtering technique to identify and extract the shoreline coast of Kuala Terengganu, Malaysia. RADSARSAT image has many advantages over the optical data because of its ability to penetrate cloud cover and its night sensing capabilities. At first, speckles were removed from the image by using Lee sigma filter which was used to reduce random noise and to enhance the image and discriminate the boundary between land and water. The results showed an accurate and improved extraction and delineation of the entire coastline of Kuala Terrenganu. The study demonstrated the reliability of the image averaging filter in reducing random noise over the sea surface especially near the shoreline. It enhanced land-water boundary differentiation, enabling better delineation of the shoreline. Overall, the developed techniques showed the potential of radar imagery for accurate shoreline mapping and will be useful for monitoring shoreline changes during high and low tides as well as shoreline erosion in a tropical country like Malaysia.     

Dynamic Response of Machine Foundation on Layered Soil: Cone Model Versus Experiments

This paper presents the experimental validation of analytical solution based on cone model for machine foundation vibration analysis on layered soil. Impedance functions for a rigid massless circular foundation resting on a two layered soil system subjected to vertical harmonic excitation are found using cone model. Linear hysteretic material damping is introduced using correspondence principle. The frequency-amplitude response of a massive foundation is then computed using impedance functions. To verify the solution field experiments are conducted in two different layered soil systems such as gravel layer over in situ soil and gravel layer over concrete slab (rigid base). A total 72 numbers of vertical vibration tests on square model footing were conducted using Lazan type mechanical oscillator, varying the influencing parameters such as depth of top layer, static weight of foundation and dynamic force level. The frequency-amplitude response in general and in particular the resonant frequencies and resonant amplitudes predicted by cone model is compared with the results of experimental investigation, which shows a close agreement. Thus the cone model is reliable in its application to machine foundation vibration on layered soil.     

Economic significance of colonial invasions in Khejuri-Hijli coastal sector of Purba Medinipur district,West Bengal: A geographical review

Khejuri- Hijili coastal area, now extends over the Khejuri police station, is situated in the southeastern part of the district of Purba Medinipur of West Bengal, on the western bank of the Hugli river. Between 21°47'42"N-22°4'N latitudes and 87°45'4"E-88°18"E longitudes the area covers about 267.97 sq. km. At the confluence of the rivers Bhagirathi-Hugli and the Bay of Bengal, Hijili emerged as an island from the estuarine surroundings around 1400-1500 A.D. afterward the island became covered with natural mangroves. Gradually it became the abode of fishermen. To gather some primary data, household survey by different questionnaire, topographic survey was done. Secondary data are mainly produced by assembling historical charts, maps, literatures for the specified work of the area concerned. Historical records including documents, survey notes, maps and photographs provided valuable information about the study area. Remains of early structures, monuments, and office buildings have been vigilantly watched and written reports and research articles have been carefully studied for sequencing the socio-economic history of the area. Later on accuracy assessment was performed by comparing two sources of information: classification of map derived from old records and maps and the ground truth information. The output obtained by performing the above steps includes land use and other maps and charts. These outputs were then analyzed to detect the historical significance of Khejuri-Hijili sector of the Hugli estuary and its sequential deterioration. These changes in the study area that were identified from classified maps, charts and diagram were tabulated.     

Mechanical and Germination Characteristics of Stabilized Organic Soils

High-organic-content dredged soils are known to have inferior mechanical characteristics because they are highly compressible and have low shear strength. To recycle dredged soil with a high organic content as a top soil this study describes an investigation of the mechanical properties and germination characteristics of stabilized organic soils using unconfined compression tests, pH tests, and seed germination tests. Several mixtures with organic contents in the range 0–30% by mass and binder contents in the range 5–15% were prepared to evaluate the effects of the organic content on the mechanical and germination characteristics of the stabilized soils. The results show that an increase in the organic content leads to a decrease in the strength and pH of the stabilized organic soil, which are favorable conditions for germination. The germination rate increased significantly with the increasing organic content, and the plant growth rate also increased. The addition of a binder into the mixtures increased the strength of the soil; however, it also increased the pH and decreased the rate of seed germination and plant growth.     

Bulk viscous LRS Bianchi-I Universe with variable G and decaying Λ

The present study deals with spatially homogeneous and totally anisotropic locally rotationally symmetric (LRS) Bianchi type I cosmological model with variable G and Λ in presence of imperfect fluid. To get the deterministic model of Universe, we assume that the expansion (θ) in the model is proportional to shear (σ). This condition leads to A=ℓB ⁿ , where A, B are metric potential. The cosmological constant Λ is found to be decreasing function of time and it approaches a small positive value at late time which is supported by recent Supernovae Ia (SN Ia) observations. Also it is evident that the distance modulus curve of derived model matches with observations perfectly.     

Earthquake risk assessment in NE India using deep learning and geospatial analysis

Earthquake prediction is currently the most crucial task required for the probability, hazard, risk mapping, and mitigation purposes. Earthquake prediction attracts the researchers' attention from both academia and industries. Traditionally, the risk assessment approaches have used various traditional and machine learning models. However, deep learning techniques have been rarely tested for earthquake probability mapping. Therefore, this study develops a convolutional neural network (CNN) model for earthquake probability assessment in NE India. Then conducts vulnerability using analytical hierarchy process (AHP), Venn's intersection theory for hazard, and integrated model for risk mapping. A prediction of classification task was performed in which the model predicts magnitudes more than 4 Mw that considers nine indicators. Prediction classification results and intensity variation were then used for probability and hazard mapping, respectively. Finally, earthquake risk map was produced by multiplying hazard, vulnerability, and coping capacity. The vulnerability was prepared by using six vulnerable factors, and the coping capacity was estimated by using the number of hospitals and associated variables, including budget available for disaster management. The CNN model for a probability distribution is a robust technique that provides good accuracy. Results show that CNN is superior to the other algorithms, which completed the classification prediction task with an accuracy of 0.94, precision of 0.98, recall of 0.85, and F1 score of 0.91. These indicators were used for probability mapping, and the total area of hazard (21,412.94 km²), vulnerability (480.98 km²), and risk (34,586.10 km²) was estimated.     

Analytic hierarchy process and information value method-based landslide susceptibility mapping and vehicle vulnerability assessment along a highway in Sikkim Himalaya

In hilly areas, highway projects can be a cause of landslides as well as an element of vulnerability due to landslides. Hence, landslide susceptibility mapping of highway corridors can substantially mitigate loss of life and property. For this, a Landslide Susceptibility Assessment Model (LSAM) was developed for a corridor of 27 km along NH 10 in the East Sikkim. Landslide inducing factors viz. Aspect, Distance from Fault, Distance from Road, Drainage Density, Land use and Land cover, Lithology, Plan Curvature, Rainfall, Slope, Soil Depth, and Soil Texture were considered for the study. Results show that areas in proximity to the highway and areas with steeper slope had a higher landslide susceptibility than otherwise. Spatial explicit sensitivity analysis indicated that LSAM was sensitive to distance from the highway and slope. Vehicle vulnerability assessment of base year and horizon years showed that vulnerability increased through time. LSAM is appropriate for hazard mitigation for areas with poor historical data on landslides.