951 resultados para GONDWANA MARGIN
Resumo:
In this paper, we present dynamic voltage and frequency Managed 256 x 64 SRAM block in 65 nm technology, for frequency ranging from 100 MHz to 1 GHz. The total energy is minimized for any operating frequency in the above range and leakage energy is minimized during standby mode. Since noise margin of SRAM cell deteriorates at low voltages, we propose static noise margin improvement circuitry, which symmetrizes the SRAM cell by controlling the body bias of pull down NMOS transistor. We used a 9T SRAM cell that isolates Read and hold noise margin and has less leakage. We have implemented an efficient technique of pushing address decoder into zigzag- super-cut-off in stand-by mode without affecting its performance in active mode of operation. The read bit line (RBL) voltage drop is controlled and pre-charge of bit lines is done only when needed for reducing power wastage.
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Learning to rank from relevance judgment is an active research area. Itemwise score regression, pairwise preference satisfaction, and listwise structured learning are the major techniques in use. Listwise structured learning has been applied recently to optimize important non-decomposable ranking criteria like AUC (area under ROC curve) and MAP(mean average precision). We propose new, almost-lineartime algorithms to optimize for two other criteria widely used to evaluate search systems: MRR (mean reciprocal rank) and NDCG (normalized discounted cumulative gain)in the max-margin structured learning framework. We also demonstrate that, for different ranking criteria, one may need to use different feature maps. Search applications should not be optimized in favor of a single criterion, because they need to cater to a variety of queries. E.g., MRR is best for navigational queries, while NDCG is best for informational queries. A key contribution of this paper is to fold multiple ranking loss functions into a multi-criteria max-margin optimization.The result is a single, robust ranking model that is close to the best accuracy of learners trained on individual criteria. In fact, experiments over the popular LETOR and TREC data sets show that, contrary to conventional wisdom, a test criterion is often not best served by training with the same individual criterion.
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Based on the an earlier CFD analysis of the performance of the gas-dynamically controlled laser cavity [1]it was found that there is possibility of optimizing the geometry of the diffuser that can bring about reductions in both size and cost of the system by examining the critical dimensional requirements of the diffuser. Consequently,an extensive CFD analysis has been carried out for a range of diffuser configurations by simulating the supersonic flow through the arrangement including the laser cavity driven by a bank of converging – diverging nozzles and the diffuser. The numerical investigations with 3D-RANS code are carried out to capture the flow patterns through diffusers past the cavity that has multiple supersonic jet interactions with shocks leading to complex flow pattern. Varying length of the diffuser plates is made to be the basic parameter of the study. The analysis reveals that the pressure recovery pattern during the flow through the diffuser from the simulation, being critical for the performance of the laser device shows its dependence on the diffuser length is weaker beyond a critical lower limit and this evaluation of this limit would provide a design guideline for a more efficient system configuration.The observation based on the parametric study shows that the pressure recovery transients in the near vicinity of the cavity is not affected for the reduction in the length of the diffuser plates up to its 10% of the initial size, indicating the design in the first configuration that was tested experimentally has a large factor of margin. The flow stability in the laser cavity is found to be unaffected since a strong and stable shock is located at the leading edge of the diffuser plates while the downstream shock and flow patterns are changed, as one would expect. Results of the study for the different lengths of diffusers in the range of 10% to its full length are presented, keeping the experimentally tested configuration used in the earlier study [1] as the reference length. The conclusions drawn from the analysis is found to be of significance since it provides new design considerations based on the understanding of the intricacies of the flow, allowing for a hardware optimization that can lead to substantial size reduction of the device with no loss of performance.
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The Indian Ocean earthquake of 26 December 2004 led to significant ground deformation in the Andaman and Nicobar region, accounting for ~800 km of the rupture. Part of this article deals with coseismic changes along these islands, observable from coastal morphology, biological indicators, and Global Positioning System (GPS) data. Our studies indicate that the islands south of 10° N latitude coseismically subsided by 1–1.5 m, both on their eastern and western margins, whereas those to the north showed a mixed response. The western margin of the Middle Andaman emerged by >1 m, and the eastern margin submerged by the same amount. In the North Andaman, both western and eastern margins emerged by >1 m. We also assess the pattern of long-term deformation (uplift/subsidence) and attempt to reconstruct earthquake/tsunami history, with the available data. Geological evidence for past submergence includes dead mangrove vegetation dating to 740 ± 100 yr B.P., near Port Blair and peat layers at 2–4 m and 10–15 m depths observed in core samples from nearby locations. Preliminary paleoseismological/tsunami evidence from the Andaman and Nicobar region and from the east coast of India, suggest at least one predecessor for the 2004 earthquake 900–1000 years ago. The history of earthquakes, although incomplete at this stage, seems to imply that the 2004-type earthquakes are infrequent and follow variable intervals
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This paper presents an approach for identifying the faulted line section and fault location on transmission systems using support vector machines (SVMs) for diagnosis/post-fault analysis purpose. Power system disturbances are often caused by faults on transmission lines. When fault occurs on a transmission system, the protective relay detects the fault and initiates the tripping operation, which isolates the affected part from the rest of the power system. Based on the fault section identified, rapid and corrective restoration procedures can thus be taken to minimize the power interruption and limit the impact of outage on the system. The approach is particularly important for post-fault diagnosis of any mal-operation of relays following a disturbance in the neighboring line connected to the same substation. This may help in improving the fault monitoring/diagnosis process, thus assuring secure operation of the power systems. In this paper we compare SVMs with radial basis function neural networks (RBFNN) in data sets corresponding to different faults on a transmission system. Classification and regression accuracy is reported for both strategies. Studies on a practical 24-Bus equivalent EHV transmission system of the Indian Southern region is presented for indicating the improved generalization with the large margin classifiers in enhancing the efficacy of the chosen model.
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Artificial Neural Networks (ANNs) have recently been proposed as an alterative method for salving certain traditional problems in power systems where conventional techniques have not achieved the desired speed, accuracy or efficiency. This paper presents application of ANN where the aim is to achieve fast voltage stability margin assessment of power network in an energy control centre (ECC), with reduced number of appropriate inputs. L-index has been used for assessing voltage stability margin. Investigations are carried out on the influence of information encompassed in input vector and target out put vector, on the learning time and test performance of multi layer perceptron (MLP) based ANN model. LP based algorithm for voltage stability improvement, is used for generating meaningful training patterns in the normal operating range of the system. From the generated set of training patterns, appropriate training patterns are selected based on statistical correlation process, sensitivity matrix approach, contingency ranking approach and concentric relaxation method. Simulation results on a 24 bus EHV system, 30 bus modified IEEE system, and a 82 bus Indian power network are presented for illustration purposes.
Intelligent Approach for Fault Diagnosis in Power Transmission Systems Using Support Vector Machines
Resumo:
This paper presents an approach for identifying the faulted line section and fault location on transmission systems using support vector machines (SVMs) for diagnosis/post-fault analysis purpose. Power system disturbances are often caused by faults on transmission lines. When fault occurs on a transmission system, the protective relay detects the fault and initiates the tripping operation, which isolates the affected part from the rest of the power system. Based on the fault section identified, rapid and corrective restoration procedures can thus be taken to minimize the power interruption and limit the impact of outage on the system. The approach is particularly important for post-fault diagnosis of any mal-operation of relays following a disturbance in the neighboring line connected to the same substation. This may help in improving the fault monitoring/diagnosis process, thus assuring secure operation of the power systems. In this paper we compare SVMs with radial basis function neural networks (RBFNN) in data sets corresponding to different faults on a transmission system. Classification and regression accuracy is reported for both strategies. Studies on a practical 24-Bus equivalent EHV transmission system of the Indian Southern region is presented for indicating the improved generalization with the large margin classifiers in enhancing the efficacy of the chosen model.
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In many real world prediction problems the output is a structured object like a sequence or a tree or a graph. Such problems range from natural language processing to compu- tational biology or computer vision and have been tackled using algorithms, referred to as structured output learning algorithms. We consider the problem of structured classifi- cation. In the last few years, large margin classifiers like sup-port vector machines (SVMs) have shown much promise for structured output learning. The related optimization prob -lem is a convex quadratic program (QP) with a large num-ber of constraints, which makes the problem intractable for large data sets. This paper proposes a fast sequential dual method (SDM) for structural SVMs. The method makes re-peated passes over the training set and optimizes the dual variables associated with one example at a time. The use of additional heuristics makes the proposed method more efficient. We present an extensive empirical evaluation of the proposed method on several sequence learning problems.Our experiments on large data sets demonstrate that the proposed method is an order of magnitude faster than state of the art methods like cutting-plane method and stochastic gradient descent method (SGD). Further, SDM reaches steady state generalization performance faster than the SGD method. The proposed SDM is thus a useful alternative for large scale structured output learning.
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Eclogites and associated high-pressure (HP) rocks in collisional and accretionary orogenic belts preserve a record of subduction and exhumation, and provide a key constraint on the tectonic evolution of the continents. Most eclogites that formed at high pressures but low temperatures at > 10-11 kbar and 450-650 degrees C can be interpreted as a result of subduction of cold oceanic lithosphere. A new class of high-temperature (HT) eclogites that formed above 900 degrees C and at 14 to 30 kbar occurs in the deep continental crust, but their geodynamic significance and processes of formation are poorly understood. Here we show that Neoarchaean mafic-ultramafic complexes in the central granulite facies region of the Lewisian in NW Scotland contain HP/HT garnet-bearing granulites (retrogressed eclogites), gabbros, Iherzolites, and websterites, and that the HP granulites have garnets that contain inclusions of omphacite. From thermodynamic modeling and compositional isopleths we calculate that peak eclogite-facies metamorphism took place at 24-22 kbar and 1060-1040 degrees C. The geochemical signature of one (G-21) of the samples shows a strong depletion of Eu indicating magma fractionation at a crustal level. The Sm-Nd isochron ages of HP phases record different cooling ages of ca. 2480 and 2330 Ma. We suggest that the layered mafic-ultramafic complexes, which may have formed in an oceanic environment, were subducted to eclogite depths, and exhumed as HP garnet-bearing orogenic peridotites. The layered complexes were engulfed by widespread orthogneisses of tonalite-trondhjemite-granodiorite (TTG) composition with granulite facies assemblages. We propose two possible tectonic models: (1) the fact that the relicts of eclogitic complexes are so widespread in the Scourian can be taken as evidence that a >90 km x 40 km-size slab of continental crust containing mafic-ultramafic complexes was subducted to at least 70 km depth in the late Archaean. During exhumation the gneiss protoliths were retrogressed to granulite facies assemblages, but the mafic-ultramafic rocks resisted retrogression. (2) The layered complexes of mafic and ultramafic rocks were subducted to eclogite-facies depths and during exhumation under crustal conditions they were intruded by the orthogneiss protoliths (TTG) that were metamorphosed in the granulite facies. Apart from poorly defined UHP metamorphic rocks in Norway, the retrogressed eclogites in the central granulite/retrogressed eclogite facies Lewisian region, NW Scotland have the highest crustal pressures so far reported for Archaean rocks, and demonstrate that lithospheric subduction was transporting crustal rocks to HP depths in the Neoarchaean. (C) 2012 International Association for Gondwana Research. Published by Elsevier B.V. All rights reserved.
Resumo:
The safety of an in-service brick arch railway bridge is assessed through field testing and finite-element analysis. Different loading test train configurations have been used in the field testing. The response of the bridge in terms of displacements, strains, and accelerations is measured under the ambient and design train traffic loading conditions. Nonlinear fracture mechanics-based finite-element analyses are performed to assess the margin of safety. A parametric study is done to study the effects of tensile strength on the progress of cracking in the arch. Furthermore, a stability analysis to assess collapse of the arch caused by lateral movement at the springing of one of the abutments that is elastically supported is carried out. The margin of safety with respect to cracking and stability failure is computed. Conclusions are drawn with some remarks on the state of the bridge within the framework of the information available and inferred information. DOI: 10.1061/(ASCE)BE.1943-5592.0000338. (C) 2013 American Society of Civil Engineers.
Resumo:
With ever increasing demand for electric energy, additional generation and associated transmission facilities has to be planned and executed. In order to augment existing transmission facilities, proper planning and selective decisions are to be made whereas keeping in mind the interests of several parties who are directly or indirectly involved. Common trend is to plan optimal generation expansion over the planning period in order to meet the projected demand with minimum cost capacity addition along with a pre-specified reliability margin. Generation expansion at certain locations need new transmission network which involves serious problems such as getting right of way, environmental clearance etc. In this study, an approach to the citing of additional generation facilities in a given system with minimum or no expansion in the transmission facility is attempted using the network connectivity and the concept of electrical distance for projected load demand. The proposed approach is suitable for large interconnected systems with multiple utilities. Sample illustration on real life system is presented in order to show how this approach improves the overall performance on the operation of the system with specified performance parameters.
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A new species of lygosomatine scincid lizard is described from the sacred forests of Mawphlang, in Meghalaya, northeastern India. Sphenomorphus apalpebratus sp. nov. possesses a spectacle or brille, an unusual feature within the Scincidae, and a first for the paraphyletic genus Sphenomorphus. The new species is compared with other members of the genus to which it is here assigned, as well as to members of the lygosomatine genera Lipinia and Scincella from mainland India, the Andaman and Nicobar Islands, and south-east Asia, to which it also bears resemblance. The new taxon is diagnosable in exhibiting the following combination of characters: small body size (SVL to 42.0 mm); moveable eyelids absent; auricular opening scaleless, situated in a shallow depression; dorsal scales show a line of demarcation along posterior edge of ventral pes; midbody scale rows 27-28; longitudinal scale rows between parietals and base of tail 62-64; lamellae under toe IV 8-9; supraoculars five; supralabials 5-6; infralabials 4-5; subcaudals 92; and dorsum golden brown, except at dorsal margin of lateral line, which is lighter, with four faintly spotted lines, two along each side of vertebral row of scales, that extend to tail base. The new species differs from its congeners in the lack of moveable eyelids, a character shared with several distantly related scincid genera.
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The Western Ghats (WG) of south India, a global biodiversity hotspot, has experienced complex geological history being part of Gondwana landmass and encountered extensive volcanic activity at the end of Cretaceous epoch. It also has a climatically and topographically heterogeneous landscape. Thus, the WG offer a unique setting to explore the influence of ecological and geological processes on the current diversity and distribution of its biota. To this end, three explicit biogeographical scenarios were hypothesized to evaluate the distribution and diversification of wet evergreen species of the WG - (1) southern WG was a refuge for the wet evergreen species during the Cretaceous volcanism, (2) phylogenetic breaks in the species phylogeny would correspond to geographic breaks (i.e., the Palghat gap) in the WG, and (3) species from each of the biogeographic subdivisions within the WG would form distinct clades. These hypotheses were tested on the centipede genus Digitipes from the WG which is known to be an ancient, endemic, and monophyletic group. The Digitipes molecular phylogeny was subjected to divergence date estimation using Bayesian approach, and ancestral areas were reconstructed using parsimony approach for each node in the phylogeny. Ancestral-area reconstruction suggested 13 independent dispersal events to explain the current distribution of the Digitipes species in the WG. Among these 13 dispersals, two dispersal events were at higher level in the Digitipes phylogeny and were from the southern WG to the central and northern WG independently in the Early Paleocene, after the Cretaceous Volcanism. The remaining 11 dispersal events explained the species' range expansions of which nine dispersals were from the southern WG to other biogeographic subdivisions in the Eocene-Miocene in the post-volcanic periods where species-level diversifications occurred. Taken together, these results suggest that southern WG might have served as a refuge for Digitipes species during Cretaceous volcanism.
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Transductive SVM (TSVM) is a well known semi-supervised large margin learning method for binary text classification. In this paper we extend this method to multi-class and hierarchical classification problems. We point out that the determination of labels of unlabeled examples with fixed classifier weights is a linear programming problem. We devise an efficient technique for solving it. The method is applicable to general loss functions. We demonstrate the value of the new method using large margin loss on a number of multi-class and hierarchical classification datasets. For maxent loss we show empirically that our method is better than expectation regularization/constraint and posterior regularization methods, and competitive with the version of entropy regularization method which uses label constraints.
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We report detailed evidence for a new paleo-suture zone (the Kumta suture) on the western margin of southern India. The c. 15-km-wide, westward dipping suture zone contains garnet-biotite, fuchsite-haematite, chlorite-quartz, quartz-phengite schists, biotite augen gneiss, marble and amphibolite. The isochemical phase diagram estimations and the high-Si phengite composition of quartz-phengite schist suggest a near-peak condition of c. 18 kbar at c. 550 degrees C, followed by near-isothermal decompression. The detrital SHRIMP U-Pb zircon ages from quartz-phengite schist give four age populations ranging from 3280 to 2993 Ma. Phengite from quartz-phengite schist and biotite from garnet-biotite schist have K-Ar metamorphic ages of ca. 1326 and ca. 1385 Ma respectively. Electron microprobe-CHIME ages of in situ zircons in quartz-phengite schist (ca. 3750 Ma and ca. 1697 Ma) are consistent with the above results. The Bondla ultramafic-gabbro complex in the west of the Kumta suture compositionally represents an arc with K-Ar biotite ages from gabbro in the range 1644-1536 Ma. On the eastern side of the suture are weakly deformed and unmetamorphosed shallow westward-dipping sedimentary rocks of the Sirsi shelf, which has the following upward stratigraphy: pebbly quartzite/sandstone, turbidite, magnetite iron formation, and limestone; farther east the lower lying quartzite has an unconformable contact with ca. 2571 Ma quartzo-feldspathic gneisses of the Dharwar block with a ca. 1733 Ma biotite cooling age. To the west of the suture is a c. 60-km-wide Karwar block mainly consisting of tonalite-trondhjemite-granodiorite (TTG) and amphibolite. The TTGs have U-Pb zircon magmatic ages of ca. 3200 Ma with a rare inherited core age of ca. 3601 Ma. The K-Ar biotite cooling age from the TTGs (1746 Ma and 1796 Ma) and amphibolite (ca. 1697 Ma) represents late-stage uplift. Integration of geological, structural and geochronological data from western India and eastern Madagascar suggest diachronous ocean closure during the amalgamation of Rodinia; in the north at around ca. 1380 Ma, and a progression toward the south until ca. 750 Ma. Satellite imagery based regional structural lineaments suggests that the Betsimisaraka suture continues into western India as the Kumta suture and possibly farther south toward a suture in the Coorg area, representing in total a c. 1000 km long Rodinian suture. (C) 2013 Elsevier B.V. All rights reserved.