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The Eocene deposits of the Kutch basin are characterized by predominance of plane-laminated shales and low diversity mollusc faunas. These features reflect a low energy, restricted environment. A thin molluscan shell bed stands out in this backdrop because it produced a very diverse assemblage of bivalves and gastropods. Palaeosynecological analysis of the benthic mollusc assemblages from different stratigraphic levels of the Eocene of Kutch, including the shell bed, was carried out by testing for standard ecological models of rank-abundance. The specific abundance data from the shell bed c onform to the log-normal model indicating stable, resource-rich environment. On the other hand, low diversity and often high abundance of opportunist species from other levels reflect harsh ecological conditions for molluscs. Analyses of habitat preferences and habits of the genera from the shell bed indicate shallow to very shallow shelf environment. It is inferred that this exotic assemblage of shells was brought in this quiet, restricted environment by storm surges from open part of the sea. High degree of shell fragmentation and high content of micrite matrix corroborate this interpretation.

Seven species belonging to the gastropod family Volutidae are reported for the first time from Kutch, Gujarat, India. They arePrestrombusaff.Prestrombus rockeiCox, 1931,Indovoluta humberti(d'Archiac and Haime, 1854),Indovoluta multidentata(d'Archiac and Haime, 1854),Involuta daviesiCox, 1931,Involuta coxinew species,Athleta(Volutocorbis)harnaiensisCox, 1931, andLyriacf.Lyria punjabensisEames, 1952. Indovolutinae new subfamily, constituted of the Paleogene generaPrestrombusDouvillé, 1929,IndovolutaEames, 1956,InvolutaCox, 1931, andLyrischapaAldrich, 1911, and the Cretaceous genusGosaviaStoliczka, 1865, is proposed. These forms have elaborate development of columellar plaits. All of these genera evolved in the western part of the Indian subcontinent. They, exceptLyrischapa, also largely remained restricted to this area.Lyrischapaflourished in the Americas after possibly migrating through the southern margin of the relict Tethys Ocean and crossing the Atlantic Ocean. It is argued that the geographic and temporal restriction of this new subfamily was due to lecithotrophic larval development.UUID:http://zoobank.org/14bc056f-1d2e-4674-b624-9eb8e856a1f0

The Bagh Group of rocks, more popularly known as the ‘Bagh Beds’, in the Narmada Valley in central India provides a detailed account of sedimentation under shifting paleoecological-paleoenvironmental conditions in response to the Late Cretaceous greenhouse state and associated sea level rise. The present paper provides a review of the stratigraphic status of the Bagh Group along with a detailed account of prevalent sedimentological and paleontological information. Three distinct lithounits (of formation status) within the Bagh Group depict gradual change in depositional conditions, viz., a fluvial to fluvio-marine estuarine condition during the lowermost Nimar Sandstone (Cenomanian), followed by a restricted shallow marine platform—tidal flat during the Nodular Limestone (Turonian) and finally a relatively high-energy open shallow marine condition during topmost Coralline Limestone (Coniacian). Invertebrate body fossils of marine affinity are abundant with sporadic vertebrates (shark teeth, dinosaur bones etc.), foraminifers and trace fossils mostly within the limestone units. Amongst the invertebrates, ammonites (mainly Placenticeras) and echinoids (prevalent Hemiaster) are quite abundant with significant numbers of bivalves (predominantly Inoceramus), brachipods (Malwirhynchia) and bryozoans. Varied distribution and association of the invertebrates in different lithounits manifest change in paleoecolgical–paleodepositional control parameters during entire sedimentation. The prevalent transgressive sequence in the epicontinental basin signifies the effect of sea level rise under the Late Cretaceous greenhouse condition in the Narmada Valley in central India.

Stabilizing videos and detecting moving objects are important tasks in many computer vision applications, though it becomes challenging because of the presence of atmospheric turbulence that causes random pixel shifting and blurring of the videos. This paper proposes an improved method for correcting geometrical distortions of videos degraded by atmospheric turbulence while keeping moving objects unaltered. In this method, three different techniques are used to generate three different masks, which are then combined together to generate a more accurate mask. This mask is employed to properly detect the moving objects and finally fusing with the background a stabilized video output is obtained. The performance of this method is tested by applying it on different real-world datasets. A comparison with an existing method shows that the proposed method gives better detection of moving objects and improved stabilization of the degraded videos.

Atmospheric turbulence causes non-uniform geometric deformation of images due to random fluctuation of refractive index throughout the imaging path. The identification of moving objects in a turbulent medium is a fundamental preprocessing step in computer vision. In this paper, a new mask generation process is proposed that removes misdetection due to turbulence in the medium. In this regard, the first step is to estimate the background frame from the video and determine the difference images from the input frames with respect to the background frame. Then three different thresholding techniques: Otsu thresholding, maximum entropy based thresholding, and standard deviation and mean based thresholding, are applied on these difference images to generate three different masks. Finally, a refined mask is generated using these three masks which detects the moving objects from the degraded video. In simulation experiment, qualitative comparisons are conducted to evaluate the performance of the proposed method with a previous one and higher accuracy is obtained.

This paper presents an improved method to detect moving objects from videos distorted by atmospheric turbulence. The method is based on generating an accurate mask from the changing properties of pixel intensities from frame to frame. The background frame is estimated by calculating the median from a sufficient number of input frames. Three different masks are generated by thresholding the difference image and pixel shiftmap of each input frame with respect to the background. A final mask is then obtained by combining all these three masks, which is more accurate than the individual ones. The performance of the proposed method is compared with that of an existing method by applying them on real-world videos. Results show that the proposed method provides better detection of moving objects than the compared method.

Palaeobiogeographical distribution of gastropod genera from the Paleocene and the Eocene has been analysed. Based on this distribution, formal palaeobiogeographical provinces have been established and their relationships are sought. It has been found that the provinces were largely restricted to the palaeo-tropics and subtropics mainly of the northern hemisphere and they share a large proportion of their generic composition. The Northern Tropical Realm has been established to include these provinces. The distribution evinces presence of ocean surface currents in the tropics across longitudes. The possible currents moved through the relict Tethys Ocean, across the Atlantic Ocean and perhaps also across the Pacific. However, planktotrophic larvae of these benthic molluscs could not cross the deep ocean barrier that lay between the Northern Tropical Realm and the Austro-New Zealand Province of the southern hemisphere. The gastropod fauna in the latter province evolved independently. Distribution of all the provinces within palaeo-tropics and subtropics indicates strong control of temperature over it. Paleocene–Eocene Thermal Maximum appears to be responsible for extinction and range contraction of high latitude faunas. Low latitude faunas also suffered significant extinction. However, large diversification in the Eocene was a response to widespread transgression that coincided with the thermal event.

This paper addresses the problem of identifying and tracking moving objects in a video sequence having a time-varying background. This is a fundamental task in many computer vision applications, though a very challenging one because of turbulence that causes blurring and spatiotemporal movements of the background images. Our proposed approach involves two major steps. First, a moving object detection algorithm that deals with the detection of real motions by separating the turbulence-induced motions using a two-level thresholding technique is used. In the second step, a feature-based generalized regression neural network is applied to track the detected objects throughout the frames in the video sequence. The proposed approach uses the centroid and area features of the moving objects and creates the reference regions instantly by selecting the objects within a circle. Simulation experiments are carried out on several turbulence-degraded video sequences and comparisons with an earlier method confirms that ...

An analysis of the palaeobiogeographic distribution of the Oligocene corals of the world reveals strong specific endemism whereas large generic pandemism. Four palaeobiogeographic provinces are identified here based on this distribution: the Western Indian Province (WIP) represented by Kutch, the Mediterranean-Iranian Province (MIP) consisting of Greece, Italy and Iran, the Caribbean-Northern South American Province (CNSAP) composed of Antigua, Puerto Rico and Venezuela, and the Northwestern American Province (NAP) represented by the state of Washington, USA. Different basins within a province show some specific similarity whereas specific provincialism is nearly absolute. Genera show wide distribution—the WIP shows 82% similarity with the MIP and 36% with the CNSAP; the CNSAP has 69% similarity with the MIP. However, the NAP shows significant generic endemism. The tropical affinity, and wide and rapid dispersability of the Oligocene corals are evident from this distribution pattern. Dispersal beyond tropics was apparently limited. This explains the relatively higher endemism of the NAP. Generic exchange between the WIP and the MIP, both belonging to the Tethys Realm, has been known for gastropods. Affinity of these provinces with the CNSAP is worth noticing. This similarity reflects the presence of a trans-Atlantic current during the Oligocene. The circumtropical distribution of the coral genera also evinces protracted planktotrophic larval ontogeny. However, endemism in the species level indicates rapid evolution. This distribution pattern having tropical yet wide longitudinal extent of genera and provincialism of species resembles the present day distribution of corals. It reflects that the scleractinian coral biology had already attained modern aspects in the Oligocene.

In underwater imaging, water waves cause severe geometric distortions and blurring of the acquired short-exposure images. Corrections for these distortions have been tackled reasonably well by previous efforts but still need improvement in the estimation of pixel shift maps to increase restoration accuracy. This paper presents a new algorithm that efficiently estimates the shift maps from geometrically distorted video sequences and uses those maps to restore the sequences. A nonrigid image registration method is employed to estimate the shift maps of the distorted frames against a reference frame. The sharpest frame of the sequence, determined using a sharpness metric, is chosen as the reference frame. A k-means clustering technique is employed to discard too-blurry frames that could result in inaccuracy in the shift maps’ estimation. The estimated pixel shift maps are processed to generate the accurate shift map that is used to dewarp the input frames into their nondistorted forms. The proposed method is applied on several synthetic and real-world video sequences, and the obtained results exhibit significant improvements over the state-of-the-art methods.

The cerithioids are a diverse group of gastropods found globally as fossil and living animals during the Cenozoic Era. Their systematics is riddled with problems stemming from large morphological variability, homoplasy, and wide geographical distribution. Six cerithioid species are described here from the lower Middle Eocene of Kutch, Gujarat, western India. All but two are new species. They are Palmerella kutchensis, Tenagodus? sowerbyi, Potamides archiaci, and Cerithium harudiensis. The rest are new records from Kutch and were known only from Pakistan. A palaeobiogeographical review based on major published records of benthic molluscs from Pakistan reveals strong endemism. The cerithioid faunas from different parts of Pakistan and this report from Kutch also show strong endemism and often quite localized development. It is argued here that unhindered faunal mixing was not possible in this province since these newly evolved basins were restricted in nature in their Lower Cenozoic history.

Three corbulid species were discriminated from the Cenozoic strata of Kutch, India. Two of them are Caestocorbula gujaratensis n. sp. and Bicorbula kutchensis n. sp. from the Palaeocene to Middle Eocene. The other species, Corbula trigonalis Sowerby, from the Lower Miocene is reassigned to Lenticorbula. The two new species co-occur in the same horizons. Palaeobiogeographical distribution of molluscs in general and corbulids in particular in the Indian subcontinent, especially of India and Pakistan, reveals high endemism. The distribution also evinces palaeobiogeographical closeness among the western Indian basins and Pakistan, thus entailing their inclusion in the same province. This province shows similarity in faunal composition with Africa and Middle East during the Lower Palaeogene whereas with southeast Asian basins during the Miocene. The pattern reflects a shift in biogeographical affinity of the province from Tethyan to Indo-Pacific.

This paper presents a novel approach in image restoration based on calculating the pixel shift-maps of geometrically distorted images in a video sequence and using these maps to obtain non-distorted frames by de-warping the originals. In the similar previous approaches, the reference frame in the image registration process for pixel shift-maps calculation is selected either using a blind image quality metric or simply using the first frame. However, the former technique may not estimate the best frame accurately in the sense of geometric distortion. As for the latter, there is always a possibility that the first frame is one of the most distorted ones in the sequence. In the proposed method, an optimal reference frame search algorithm is introduced to improve the quality of restored frames and to yield a stable video output. The proposed method was applied both to synthetic and real data sets, and simulation results show significant improvement in comparison to the state-of- the-art methods.

This paper addresses the problem of stabilizing underwater videos with non-uniform geometric deformations or warping due to a wavy water surface. It presents an improved method to correct these geometric deformations of the frames, providing a high-quality stabilized video output. For this purpose, a non-rigid image registration technique is employed to accurately align the warped frames with respect to a prototype frame and to estimate the deformation parameters, which in turn, are applied in an image dewarping technique. The prototype frame is chosen from the video sequence based on a sharpness assessment. The effectiveness of the proposed method is validated by applying it on both synthetic and real- world sequences using various quality metrics. A performance comparison with an existing method confirms the higher efficacy of the proposed method.

The Cenozoic marine succession of Kutch, India, is rich in benthic molluscs and other invertebrates, but nautiloids are very scanty. Three nautiloid species, with two being new, are reported here: Deltoidonautilus vredenburgi n. sp. from the Early Eocene Naredi Formation, Cimomia forbesi ( d’Archiac and Haime, 1854 ) from the Middle Eocene Harudi Formation, and Aturia gujaratensis n. sp. from the Early Miocene Khari Nadi and Chhasra formations. Taphonomic and sedimentary features reveal that the Eocene nautiloids were parautochthonous whereas the Miocene species might have been transported post-mortally for some distance. Palaeobiogeographic distribution of the Cenozoic nautiloids of the Indian subcontinent and other parts of the world reveals that though the genera are pandemic the species are often endemic to a basin or a province. Specific endemism and pattern of broad faunal similarity of nautiloids among different provinces within the Tethys Realm (sensu Harzhauser et al., 2002 ) mimic those of the benthic molluscs during the Palaeogene.

A new algorithm for the turbulence degraded frames of an underwater object or scene to produce images with superior quality and higher resolution is presented. This approach is based on computing the centroid image of the sequence through an iterative scheme. A robust and fast optical flow technique is employed for pixel registration of all the frames against a reference frame and the pixel shift maps are determined. Using these shift maps, each distorted frame is restored through an image dewarping technique. A performance comparison between the proposed restoration approach and state-of-the-art is presented in terms of restoration time and accuracy. The effectiveness of the approach is demonstrated on both synthetic and real-world underwater videos.

In this paper, we present a new approach to track moving objects in videos having a dynamic background. At first, we apply an object detection algorithm that deals with the detection of real objects in a degraded video by separating them from turbulence-induced motions using a two-level thresholding technique. Then, a generalized regression neural network is used to track the detected objects throughout the frames in the video. The proposed approach utilizes the features of centroid and area of moving objects and creates the reference regions instantly by selecting the objects within a circle. The performance of the proposed approach is compared with that of an existing approach by applying them to turbulence degraded videos, and competitive results are obtained.

Underwater imaging poses significant challenges due to random dynamic distortions caused by reflection and refraction of light through the water waves. Moving object detection in a turbulent medium further imposes complexity in the imaging. In this paper, a new approach is proposed for turbulence compensation of a distorted underwater video while keeping the real motions unharmed. First, a geometrically stable frame is created from the distorted video that contains no moving objects. Then, a robust non-rigid image registration technique is used to estimate the motion vector fields of the distorted frames against the stable frame. The difference images of the distorted frames with respect to the stable frame, and the estimated motion vector fields are used to detect the real motion regions and to generate a mask for each frame to extract those regions. This proposed method is compared with an earlier method through both qualitative and quantitative analysis. Simulation experiments show that the proposed method provides better corrections to the effects of underwater turbulence whilst accurately preserving the moving objects.

Ultrasound (US) imaging is widely used in clinical diagnostics as it is an economical, portable, painless, comparatively safe, and non-invasive real-time tool. However, the image quality of US imaging is severely affected by the presence of speckle noise during the acquisition process. It is essential to achieve speckle-free high resolution US imaging for better clinical diagnosis. In this paper, we propose a speckle and blur reduction algorithm for US imaging based on artificial neural networks (ANNs). Here, speckle noise is modelled as a multiplicative noise following a Rayleigh distribution, whereas blur is modelled as a Gaussian blur function. The noise and blur variances are estimated by a cascade-forward back propagation (CFBP) neural network using a set of intensity and wavelet features of the US image. The estimated noise and blur variances are then used for speckle reduction by solving the inverse Rayleigh function, and for de-blurring, using the Lucy-Richardson algorithm. The proposed approach gives improved results for both qualitative and quantitative measures.

The subfamily Eucycloceratinae Spath, 1928, belonging to the family Sphaeroceratidae, is an important Indo-Madagascan faunal element and is reported here from the Callovian of Kutch, India. Previously the subfamily was considered to consist of 14 morphospecies placed in four morphogenera. The present study is based on re-examination of the type material and more than 350 new specimens, collected with secure stratigraphical control, from sections in mainland Kutch. It reveals that the subfamily includes only two highly variable monospecific genera: Eucycloceras Spath, 1924 and Idiocycloceras Spath, 1928. Dimorphism in Eucycloceratinae, which was not previously recognized, is firmly established. Cladograms have been constructed, based on numerous morphological characters, which show relationships among different subfamilies of the Sphaeroceratidae and genera of the Macrocephalitinae and Eucycloceratinae. The palaeobiogeography and evolution of the Eucycloceratinae are discussed in the light of the new data.

This paper presents an algorithm for recovering an image from a sequence of distorted versions of it, where the distortions are caused by a wavy water surface. A robust non-rigid image registration technique is employed to determine the pixel shift maps of all the frames in the sequence against a reference frame. An iterative image dewarping algorithm is applied to correct the geometric distortions of the sequence. A non-local means filter is used to mitigate noise and improve the signal-to-noise ratio (SNR). The performance of our proposed method is compared against the state-of-the-art method. Results show that our proposed method performs significantly better in removing geometric distortions of the underwater images.

This paper proposes a high accuracy and fast image restoration approach to restore a sequence of atmospheric turbulence degraded frames of a remote object or scene. A coarse-to-fine optical flow technique is employed to estimate the dense motion fields of the frames against a reference frame. The First Register Then Average And Subtract (FRTAAS) method is used to correct the geometric distortions and restore a high quality sequence. Finally, a non-local means filter is applied to extract noise from each frame of the sequence. A performance comparison is presented between the proposed restoration method and an earlier method in terms of computational time and accuracy. The effectiveness of the proposed approach is demonstrated on both synthetic and real-life videos.

This paper presents a comparative study between field oriented control (FOC) and direct torque control (DTC), two most popular control strategies for inverter fed interior permanent magnet synchronous motor (IPMSM) drives. The comparison is done in four switch three phase (FSTP) inverter scheme instead of six switch three phase (SSTP) inverter scheme. The FSTP inverter scheme is better than SSTP inverter scheme because of the reduction in price, switching losses and the complexity of the control board. The comparison is based on various conditions such as normal operating condition, sudden change in load torque, speed reversal and change in stator resistance. To validate the effectiveness of the drive systems, simulation is carried out in MATLAB environment. The simulation results and comparative study have been found quite satisfactory.

Ribs appeared cryptically in the Middle Jurassic nautiloid Paracenoceras. These ribs were produced by crowding of growth lirae as a corollary of change in body size during paedomorphic evolution. Initially, they had no direct functional significance. Some other contemporary genera are found to have similar ribbing patterns, partially developed on either the flanks or venter of the adult body chamber. Subsequently in nautiloid phylogeny, ribs spread all around the whorl, becoming analogous to those of contemporary ammonites. Shell rugosity is observed to occur with increasing frequency in post‐Triassic nautiloids, paralleling the trend in ammonites. This is believed to be an outcome of the ‘arms race’ known as the Mesozoic marine revolution. Ribbing that was not at first adaptive in these nautiloids was subsequently co‐opted as a defensive adaptation. The evolution of this structure is a good example of exaptation.

A high precision and fast image restoration method is proposed to restore a geometrically corrected image from the atmospheric turbulence degraded video sequence of a static scenery. In this approach, we employ an optical flow technique to register all the frames of the distorted video to a reference frame and determine the flow fields. We use the First Register Then Average And Subtract-variant (FRTAASv) method to correct the geometric distortions using the computed flow fields. We present a performance comparison between our proposed restoration method and earlier Minimum Sum of Squared Differences (MSSD) image registration based FRTAASv method in terms of computational time and accuracy. Simulation experiments show that our proposed method provides higher accuracy with quicker processing time.

In this paper, a fast image restoration method is proposed to restore the true image from an atmospheric turbulence degraded video. A non-rigid image registration algorithm is employed to register all the frames of the video to a reference frame and determine the shift maps. The First Register Then Average And Subtract-variant (FRTAASv) method is applied to correct the geometric distortion of the reference frame. A performance comparison is presented between the proposed restoration method and the earlier Minimum Sum of Squared Differences (MSSD) image registration based FRTAASv method, in terms of processing time and accuracy. Simulation results show that the proposed method requires shorter processing time to achieve the same geometric accuracy.

Ultrasound (US) imaging is a widely used clinical diagnostic tool in medical imaging techniques. It is a comparatively safe, economical, painless, portable, and noninvasive real-time tool compared to the other imaging modalities. However, the image quality of US imaging is severely affected by the presence of speckle noise and blur during the acquisition process. In order to ensure a high-quality clinical diagnosis, US images must be restored by reducing their speckle noise and blur. In general, speckle noise is modeled as a multiplicative noise following a Rayleigh distribution and blur as a Gaussian function. Hereto, we propose an intelligent estimator based on artificial neural networks (ANNs) to estimate the variances of noise and blur, which, in turn, are used to obtain an image without discernible distortions. A set of statistical features computed from the image and its complex wavelet sub-bands are used as input to the ANN. In the proposed method, we solve the inverse Rayleigh function numerically for speckle reduction and use the Richardson-Lucy algorithm for de-blurring. The performance of this method is compared with that of the traditional methods by applying them to a synthetic, physical phantom and clinical data, which confirms better restoration results by the proposed method.

A position sensorless Surface Permanent Magnet Synchronous Motor (SPMSM) drive based on flux angle is presented in this paper. The motor equations are written in rotor fixed d-q reference frame. A PID controller is used to process the speed error to generate the reference torque current keeping the magnetizing current fixed. The estimated stator flux using Recurrent Neural Network (RNN) is used to find out the rotor position. The flux angle and the reference current phasor angle are used in vector rotator to generate the reference phase currents. Hysteresis current controller block controls the switching of the 3-phase inverter to apply voltage to the motor stator. Simulation studies on different operating conditions indicate the acceptability of the drive system. The drive system only requires a speed transducer and is free from position sensor requirement. The proposed control scheme is robust under load torque disturbances and motor parameter variations. It is also simple and low cost to implement in a practical environment.

Long-distance surveillance is a challenging task because of atmospheric turbulence that causes time-varying image shifts and blurs in images. These distortions become more significant as the imaging distance increases. This paper presents a new method for compensating image shifting in a video sequence while keeping real moving objects in the video unharmed. In this approach, firstly, a highly accurate and fast optical flow technique is applied to estimate the motion vector maps of the input frames and a centroid algorithm is employed to generate a geometrically correct frame in which there is no moving object. The second step involves applying an algorithm for detecting real moving objects in the video sequence and then restoring it with those objects unaffected. The performance of the proposed method is verified by comparing it with that of a state-of-the-art approach. Simulation experiments using both synthetic and real-life surveillance videos demonstrate that this method significantly improves the accuracy of image restoration while preserving moving objects.

This paper presents the application of artificial neural network for predicting the warping of images of remote objects or scenes ahead of time. The algorithm is based on estimating the pattern of warping of previously captured short-exposure frames through a generalized regression neural network (GRNN) and then predicting the warping of the upcoming frame. A high-accuracy optical flow technique is employed to estimate the dense motion fields of the captured frames, which are considered as training data for the GRNN. The proposed approach is independent of the pixel-oscillatory model unlike the state-of-the-art Kalman filter (KF) approach. Simulation experiments on synthetic and real-world turbulence degraded videos show that the proposed GRNN-based approach performs better than the KF approach in atmospheric warp prediction.

A high accuracy image dewarping method is proposed to restore images from non-uniformly warped video sequences degraded by atmospheric turbulence. This approach contains three major steps. First, a non-rigid image registration technique is employed to register all the frames in the sequence to a reference frame and estimate the motion fields. Second, an iterative First Register Then Average And Subtract (iFRTAAS) method is applied to correct the geometric deformations of the warped frames. The third step involves applying a non-local means filter for the compensation of noise and to improve the signal-to-noise ratio (SNR) of the restored reference frame. Simulations are carried out by applying the method to synthetic and real-life turbulence degraded videos and by determining various quality metrics. A performance comparison is presented between the proposed method and two earlier methods, which verifies that the proposed method provides significant improvement on the image restoration accuracy.