27 resultados para Coastal trade


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The impact of gate-to-source/drain overlap length on performance and variability of 65 nm CMOS is presented. The device and circuit variability is investigated as a function of three significant process parameters, namely gate length, gate oxide thickness, and halo dose. The comparison is made with three different values of gate-to-source/drain overlap length namely 5 nm, 0 nm, and -5 nm and at two different leakage currents of 10 nA and 100 nA. The Worst-Case-Analysis approach is used to study the inverter delay fluctuations at the process corners. The drive current of the device for device robustness and stage delay of an inverter for circuit robustness are taken as performance metrics. The design trade-off between performance and variability is demonstrated both at the device level and circuit level. It is shown that larger overlap length leads to better performance, while smaller overlap length results in better variability. Performance trades with variability as overlap length is varied. An optimal value of overlap length of 0 nm is recommended at 65 nm gate length, for a reasonable combination of performance and variability.

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We consider a complex, additive, white Gaussian noise channel with flat fading. We study its diversity order vs transmission rate for some known power allocation schemes. The capacity region is divided into three regions. For one power allocation scheme, the diversity order is exponential throughout the capacity region. For selective channel inversion (SCI) scheme, the diversity order is exponential in low and high rate region but polynomial in mid rate region. For fast fading case we also provide a new upper bound on block error probability and a power allocation scheme that minimizes it. The diversity order behaviour of this scheme is same as for SCI but provides lower BER than the other policies.

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Artificial Neural Networks (ANNs) have been found to be a robust tool to model many non-linear hydrological processes. The present study aims at evaluating the performance of ANN in simulating and predicting ground water levels in the uplands of a tropical coastal riparian wetland. The study involves comparison of two network architectures, Feed Forward Neural Network (FFNN) and Recurrent Neural Network (RNN) trained under five algorithms namely Levenberg Marquardt algorithm, Resilient Back propagation algorithm, BFGS Quasi Newton algorithm, Scaled Conjugate Gradient algorithm, and Fletcher Reeves Conjugate Gradient algorithm by simulating the water levels in a well in the study area. The study is analyzed in two cases-one with four inputs to the networks and two with eight inputs to the networks. The two networks-five algorithms in both the cases are compared to determine the best performing combination that could simulate and predict the process satisfactorily. Ad Hoc (Trial and Error) method is followed in optimizing network structure in all cases. On the whole, it is noticed from the results that the Artificial Neural Networks have simulated and predicted the water levels in the well with fair accuracy. This is evident from low values of Normalized Root Mean Square Error and Relative Root Mean Square Error and high values of Nash-Sutcliffe Efficiency Index and Correlation Coefficient (which are taken as the performance measures to calibrate the networks) calculated after the analysis. On comparison of ground water levels predicted with those at the observation well, FFNN trained with Fletcher Reeves Conjugate Gradient algorithm taken four inputs has outperformed all other combinations.

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The name `Seven Pagodas' has served as a nickname for the south Indian port of Mahabalipuram since the early European explorers used it as landmark for navigation as they could see summits of seven temples from the sea. There are many theories concerning the name Seven Pagodas. The present study has compared coastline and adjacent seven monuments illustrated in a 17th century Portolan Chart (maritime map) with recent remote sensing data. This analysis throws new light on the name ``Seven Pagodas'' for the city. This study has used DEM of the site to simulate the coastline which is similar to the one depicted in the old portolan chart. Through this, the then sea level and corresponding flooding extent according to topography of the area and their effect on monuments could be analyzed. Most importantly this work has in the process identified possibly the seven monuments that constituted the name Seven Pagodas and this provides an alternative explanation to one of the mysteries of history. This work has demonstrated unique method of studying coastal archaeological sites. As large numbers of heritage sites around the world are on coastlines, this methodology has potential to be very useful for coastal heritage preservation and management.

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In recent times, crowdsourcing over social networks has emerged as an active tool for complex task execution. In this paper, we address the problem faced by a planner to incen-tivize agents in the network to execute a task and also help in recruiting other agents for this purpose. We study this mecha-nism design problem under two natural resource optimization settings: (1) cost critical tasks, where the planner’s goal is to minimize the total cost, and (2) time critical tasks, where the goal is to minimize the total time elapsed before the task is executed. We define a set of fairness properties that should beideally satisfied by a crowdsourcing mechanism. We prove that no mechanism can satisfy all these properties simultane-ously. We relax some of these properties and define their ap-proximate counterparts. Under appropriate approximate fair-ness criteria, we obtain a non-trivial family of payment mech-anisms. Moreover, we provide precise characterizations of cost critical and time critical mechanisms.

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In this paper, the storage-repair-bandwidth (SRB) trade-off curve of regenerating codes is reformulated to yield a tradeoff between two global parameters of practical relevance, namely information rate and repair rate. The new information-repair-rate (IRR) tradeoff provides a different and insightful perspective on regenerating codes. For example, it provides a new motivation for seeking to investigate constructions corresponding to the interior of the SRB tradeoff. Interestingly, each point on the SRB tradeoff corresponds to a curve in the IRR tradeoff setup. We characterize completely, functional repair under the IRR framework, while for exact repair, an achievable region is presented. In the second part of this paper, a rate-half regenerating code for the minimum storage regenerating point is constructed that draws upon the theory of invariant subspaces. While the parameters of this rate-half code are the same as those of the MISER code, the construction itself is quite different.

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Coastal marine environments are important links between the continents and the open ocean. The coast off Mangalore forms part of the upwelling zone along the southeastern Arabian Sea. The temperature, salinity, density, dissolved oxygen and stable oxygen isotope ratio (delta O-18) of surface waters as well as those of bottom waters off coastal Mangalore were studied every month from October 2010 to May 2011. The coastal waters were stratified in October and November due to precipitation and runoff. The region was characterised by upwelled bottom waters in October, whereas the region exhibited a temperature inversion in November. The surface and bottom waters presented almost uniform properties from December until April. The coastal waters were observed to be most dense in January and May. Comparatively cold and poorly oxygenated bottom waters during the May sampling indicated the onset of upwelling along the region. delta O-18 of the coastal waters successfully documented the observed variations in the hydrographical characteristics of the Mangalore coast during the monthly sampling period. We also noted that the monthly variability in the properties of the coastal waters of Mangalore was related to the hydrographical characteristics of the adjacent open ocean inferred from satellite-derived surface winds, sea surface height anomaly data and sea surface temperatures.

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The agriculture, forestry and other land use (AFOLU) sector is responsible for approximately 25% of anthropogenic GHG emissions mainly from deforestation and agricultural emissions from livestock, soil and nutrient management. Mitigation from the sector is thus extremely important in meeting emission reduction targets. The sector offers a variety of cost-competitive mitigation options with most analyses indicating a decline in emissions largely due to decreasing deforestation rates. Sustainability criteria are needed to guide development and implementation of AFOLU mitigation measures with particular focus on multifunctional systems that allow the delivery of multiple services from land. It is striking that almost all of the positive and negative impacts, opportunities and barriers are context specific, precluding generic statements about which AFOLU mitigation measures have the greatest promise at a global scale. This finding underlines the importance of considering each mitigation strategy on a case-by-case basis, systemic effects when implementing mitigation options on the national scale, and suggests that policies need to be flexible enough to allow such assessments. National and international agricultural and forest (climate) policies have the potential to alter the opportunity costs of specific land uses in ways that increase opportunities or barriers for attaining climate change mitigation goals. Policies governing practices in agriculture and in forest conservation and management need to account for both effective mitigation and adaptation and can help to orient practices in agriculture and in forestry towards global sharing of innovative technologies for the efficient use of land resources. Different policy instruments, especially economic incentives and regulatory approaches, are currently being applied however, for its successful implementation it is critical to understand how land-use decisions are made and how new social, political and economic forces in the future will influence this process.

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The 2004 earthquake left several traces of coseismic land deformation and tsunami deposits, both on the islands along the plate boundary and distant shores of the Indian Ocean rim countries. Researchers are now exploring these sites to develop a chronology of past events. Where the coastal regions are also inundated by storm surges, there is an additional challenge to discriminate between the deposits formed by these two processes. Paleo-tsunami research relies largely on finding deposits where preservation potential is high and storm surge origin can be excluded. During the past decade of our work along the Andaman and Nicobar Islands and the east coast of India, we have observed that the 2004 tsunami deposits are best preserved in lagoons, inland streams and also on elevated terraces. Chronological evidence for older events obtained from such sites is better correlated with those from Thailand, Sri Lanka and Indonesia, reiterating their usefulness in tsunami geology studies. (C) 2014 Elsevier Ltd. All rights reserved.

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Several operational aspects for thermal power plants in general are non-intuitive and involve simultaneous optimization of a number of operational parameters. In the case of solar operated power plants, it is even more difficult due to varying heat source temperatures induced by variability in insolation levels. This paper introduces a quantitative methodology for load regulation of a CO2 based Brayton cycle power plant using the `thermal efficiency and specific work output' coordinate system. The analysis shows that a transcritical CO2 cycle offers more flexibility under part load performance than the supercritical cycle in case of non-solar power plants. However, for concentrated solar power, where efficiency is important, supercritical CO2 cycle fares better than transcritical CO2 cycle. A number of empirical equations relating heat source temperature, high side pressure with efficiency and specific work output are proposed which could assist in generating control algorithms. (C) 2015 Elsevier B.V. All rights reserved.

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Saltwater intrusion into coastal aquifers is a global issue, exacerbated by increasing demands for freshwater in coastal regions. This study investigates into the parametric analysis on saltwater intrusion in a conceptual, coastal, unconfined aquifer considering wide range of freshwater draft and anticipated sea level rise. The saltwater intrusion under various circumstances is simulated through parametric studies using MODFLOW, MT3DMS and SEAWAT. The MODFLOW is used to simulate the groundwater flow system under changing hydro-dynamics in coastal aquifer. To simulate solute transport MT3DMS and SEAWAT is used. The saltwater intrusion process has direct bearing on hydraulic conductivity and inversely related to porosity. It may also be noted that increase in recharge rate considered in the study does not have much influence on saltwater intrusion. Effect of freshwater draft at locations beyond half of the width of the aquifer considered has marginal effect and hence can be considered as safe zone for freshwater withdrawals. Due to the climate change effect, the anticipated rise in sea level of 0.88 m over a century is considered in the investigation. This causes increase in salinity intrusion by about 25%. The combined effect of sea level rise and freshwater draft (C) 2015 The Authors. Published by Elsevier B.V.

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Computing the maximum of sensor readings arises in several environmental, health, and industrial monitoring applications of wireless sensor networks (WSNs). We characterize the several novel design trade-offs that arise when green energy harvesting (EH) WSNs, which promise perpetual lifetimes, are deployed for this purpose. The nodes harvest renewable energy from the environment for communicating their readings to a fusion node, which then periodically estimates the maximum. For a randomized transmission schedule in which a pre-specified number of randomly selected nodes transmit in a sensor data collection round, we analyze the mean absolute error (MAE), which is defined as the mean of the absolute difference between the maximum and that estimated by the fusion node in each round. We optimize the transmit power and the number of scheduled nodes to minimize the MAE, both when the nodes have channel state information (CSI) and when they do not. Our results highlight how the optimal system operation depends on the EH rate, availability and cost of acquiring CSI, quantization, and size of the scheduled subset. Our analysis applies to a general class of sensor reading and EH random processes.