23 resultados para Popular literature

em Indian Institute of Science - Bangalore - Índia


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The advent and evolution of geohazard warning systems is a very interesting study. The two broad fields that are immediately visible are that of geohazard evaluation and subsequent warning dissemination. Evidently, the latter field lacks any systematic study or standards. Arbitrarily organized and vague data and information on warning techniques create confusion and indecision. The purpose of this review is to try and systematize the available bulk of information on warning systems so that meaningful insights can be derived through decidable flowcharts, and a developmental process can be undertaken. Hence, the methods and technologies for numerous geohazard warning systems have been assessed by putting them into suitable categories for better understanding of possible ways to analyze their efficacy as well as shortcomings. By establishing a classification scheme based on extent, control, time period, and advancements in technology, the geohazard warning systems available in any literature could be comprehensively analyzed and evaluated. Although major advancements have taken place in geohazard warning systems in recent times, they have been lacking a complete purpose. Some systems just assess the hazard and wait for other means to communicate, and some are designed only for communication and wait for the hazard information to be provided, which usually is after the mishap. Primarily, systems are left at the mercy of administrators and service providers and are not in real time. An integrated hazard evaluation and warning dissemination system could solve this problem. Warning systems have also suffered from complexity of nature, requirement of expert-level monitoring, extensive and dedicated infrastructural setups, and so on. The user community, which would greatly appreciate having a convenient, fast, and generalized warning methodology, is surveyed in this review. The review concludes with the future scope of research in the field of hazard warning systems and some suggestions for developing an efficient mechanism toward the development of an automated integrated geohazard warning system. DOI: 10.1061/(ASCE)NH.1527-6996.0000078. (C) 2012 American Society of Civil Engineers.

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Non-stationary signal modeling is a well addressed problem in the literature. Many methods have been proposed to model non-stationary signals such as time varying linear prediction and AM-FM modeling, the later being more popular. Estimation techniques to determine the AM-FM components of narrow-band signal, such as Hilbert transform, DESA1, DESA2, auditory processing approach, ZC approach, etc., are prevalent but their robustness to noise is not clearly addressed in the literature. This is critical for most practical applications, such as in communications. We explore the robustness of different AM-FM estimators in the presence of white Gaussian noise. Also, we have proposed three new methods for IF estimation based on non-uniform samples of the signal and multi-resolution analysis. Experimental results show that ZC based methods give better results than the popular methods such as DESA in clean condition as well as noisy condition.

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Control systems arising in many engineering fields are often of distributed parameter type, which are modeled by partial differential equations. Decades of research have lead to a great deal of literature on distributed parameter systems scattered in a wide spectrum.Extensions of popular finite-dimensional techniques to infinite-dimensional systems as well as innovative infinite-dimensional specific control design approaches have been proposed. A comprehensive account of all the developments would probably require several volumes and is perhaps a very difficult task. In this paper, however, an attempt has been made to give a brief yet reasonably representative account of many of these developments in a chronological order. To make it accessible to a wide audience, mathematical descriptions have been completely avoided with the assumption that an interested reader can always find the mathematical details in the relevant references.

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The decentralized power is characterised by generation of power nearer to the demand centers, focusing mainly on meeting local energy needs. A decentralized power system can function either in the presence of grid, where it can feed the surplus power generated to the grid, or as an independent/stand-alone isolated system exclusively meeting the local demands of remote locations. Further, decentralized power is also classified on the basis of type of energy resources used-non-renewable and renewable. These classifications along with a plethora of technological alternatives have made the whole prioritization process of decentralized power quite complicated for decision making. There is abundant literature, which has discussed various approaches that have been used to support decision making under such complex situations. We envisage that summarizing such literature and coming out with a review paper would greatly help the policy/decision makers and researchers in arriving at effective solutions. With such a felt need 102 articles were reviewed and features of several technological alternatives available for decentralized power, the studies on modeling and analysis of economic, environmental and technological asibilities of both grid-connected (GC) and stand-alone (SA) systems as decentralized power options are presented. (C) 2009 Elsevier Ltd. All rights reserved.

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In this paper we consider the problem of computing an “optimal” popular matching. We assume that our input instance View the MathML source admits a popular matching and here we are asked to return not any popular matching but an optimal popular matching, where the definition of optimality is given as a part of the problem statement; for instance, optimality could be fairness in which case we are required to return a fair popular matching. We show an O(n2+m) algorithm for this problem, assuming that the preference lists are strict, where m is the number of edges in G and n is the number of applicants.

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Among different methods, the transmission-line or the impedance tube method has been most popular for the experimental evaluation of the acoustical impedance of any termination. The current state of method involves extrapolation of the measured data to the reflecting surface or exact locations of the pressure maxima, both of which are known to be rather tricky. The present paper discusses a method which makes use of the positions of the pressure minima and the values of the standing-wave ratio at these points. Lippert's concept of enveloping curves has been extended. The use of Smith or Beranek charts, with their inherent inaccuracy, has been altogether avoided. The existing formulas for the impedance have been corrected. Incidentally, certain other errors in the current literature have also been brought to light.Subject Classification: 85.20.

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We study the problem of matching applicants to jobs under one-sided preferences: that is, each applicant ranks a non-empty subset of jobs under an order of preference, possibly involving ties. A matching M is said to be rnore popular than T if the applicants that prefer M to T outnumber those that prefer T to M. A matching is said to be popular if there is no matching more popular than it. Equivalently, a matching M is popular if phi(M,T) >= phi(T, M) for all matchings T, where phi(X, Y) is the number of applicants that prefer X to Y. Previously studied solution concepts based oil the popularity criterion are either not guaranteed to exist for every instance (e.g., popular matchings) or are NP-hard to compute (e.g., least unpopular matchings). This paper addresses this issue by considering mixed matchings. A mixed matching is simply a probability distributions over matchings in the input graph. The function phi that compares two matchings generalizes in a natural manner to mixed matchings by taking expectation. A mixed matching P is popular if phi(P,Q) >= phi(Q,P) for all mixed matchings Q. We show that popular mixed matchings always exist. and we design polynomial time algorithms for finding them. Then we study their efficiency and give tight bounds on the price of anarchy and price of stability of the popular matching problem.

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We consider the problem of matching people to jobs, where each person ranks a subset of jobs in an order of preference, possibly involving ties. There are several notions of optimality about how to best match each person to a job; in particular, popularity is a natural and appealing notion of optimality. However, popular matchings do not always provide an answer to the problem of determining an optimal matching since there are simple instances that do not adroit popular matchings. This motivates the following extension of the popular rnatchings problem:Given a graph G; = (A boolean OR J, E) where A is the set of people and J is the set of jobs, and a list < c(1), c(vertical bar J vertical bar)) denoting upper bounds on the capacities of each job, does there exist (x(1), ... , x(vertical bar J vertical bar)) such that setting the capacity of i-th, job to x(i) where 1 <= x(i) <= c(i), for each i, enables the resulting graph to admit a popular matching. In this paper we show that the above problem is NP-hard. We show that the problem is NP-hard even when each c is 1 or 2.

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Preparation of semisolid slurry using a cooling slope is increasingly becoming popular, primarily because of the simplicity in design and ease control of the process. In this process, liquid alloy is poured down an inclined surface which is cooled from underneath. The cooling enables partial solidification and the incline provides the necessary shear for producing semisolid slurry. However, the final microstructure of the ingot depends on several process parameters such as cooling rate, incline angle of the cooling slope, length of the slope and initial melt superheat. In this work, a CFD model using volume of fluid (VOF) method for simulating flow along the cooling slope was presented. Equations for conservation of mass, momentum, energy and species were solved to predict hydrodynamic and thermal behavior, in addition to predicting solid fraction distribution and macrosegregation. Solidification was modeled using an enthalpy approach and a volume averaged technique for the different phases. The mushy region was modeled as a multi-layered porous medium consisting of fixed columnar dendrites and mobile equiaxed/fragmented grains. The alloy chosen for the study was aluminum alloy A356, for which adequate experimental data were available in the literature. The effects of two key process parameters, namely the slope angle and the pouring temperature, on temperature distribution, velocity distribution and macrosegregation were also studied.

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Objective : The main objective of this work was to study the antipyretic and antibacterial activity of C. erectus (Buch.-Ham.) Verdcourt leaf extract in an experimental albino rat model. Materials and Methods : The methanol extract of C. erectus leaf (MECEL) was evaluated for its antipyretic potential on normal body temperature and Brewers yeast-induced pyrexia in albino rats model. While the antibacterial activity of MECEL against five Gram (-) and three Gram () bacterial strains and antimycotic activity was investigated against four fungi using agar disk diffusion and microdilution methods. Result : Yeast suspension (10 mL/kg b.w.) elevated rectal temperature after 19 h of subcutaneous injection. Oral administration of MECEL at 100 and 200 mg/kg b.w. showed significant reduction of normal rectal body temperature and yeast-provoked elevated temperature (38.8 0.2 and 37.6 0.4, respectively, at 2-3 h) in a dose-dependent manner, and the effect was comparable to that of the standard antipyretic drug-paracetamol (150 mg/kg b.w.). MECEL at 2 mg/disk showed broad spectrum of growth inhibition activity against both groups of bacteria. However, MECEL was not effective against the yeast strains tested in this study. Conclusion : This study revealed that the methanol extract of C. erectus exhibited significant antipyretic activity in the tested models and antibacterial activity as well, and may provide the scientific rationale for its popular use as antipyretic agent in Khamptiss folk medicines.

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We consider the problem of matching people to items, where each person ranks a subset of items in an order of preference, possibly involving ties. There are several notions of optimality about how to best match a person to an item; in particular, popularity is a natural and appealing notion of optimality. A matching M* is popular if there is no matching M such that the number of people who prefer M to M* exceeds the number who prefer M* to M. However, popular matchings do not always provide an answer to the problem of determining an optimal matching since there are simple instances that do not admit popular matchings. This motivates the following extension of the popular matchings problem: Given a graph G = (A U 3, E) where A is the set of people and 2 is the set of items, and a list < c(1),...., c(vertical bar B vertical bar)> denoting upper bounds on the number of copies of each item, does there exist < x(1),...., x(vertical bar B vertical bar)> such that for each i, having x(i) copies of the i-th item, where 1 <= xi <= c(i), enables the resulting graph to admit a popular matching? In this paper we show that the above problem is NP-hard. We show that the problem is NP-hard even when each c(i) is 1 or 2. We show a polynomial time algorithm for a variant of the above problem where the total increase in copies is bounded by an integer k. (C) 2011 Elsevier B.V. All rights reserved.

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We study the problem of matching applicants to jobs under one-sided preferences; that is, each applicant ranks a non-empty subset of jobs under an order of preference, possibly involving ties. A matching M is said to be more popular than T if the applicants that prefer M to T outnumber those that prefer T to M. A matching is said to be popular if there is no matching more popular than it. Equivalently, a matching M is popular if phi(M, T) >= phi(T, M) for all matchings T, where phi(X, Y) is the number of applicants that prefer X to Y. Previously studied solution concepts based on the popularity criterion are either not guaranteed to exist for every instance (e.g., popular matchings) or are NP-hard to compute (e.g., least unpopular matchings). This paper addresses this issue by considering mixed matchings. A mixed matching is simply a probability distribution over matchings in the input graph. The function phi that compares two matchings generalizes in a natural manner to mixed matchings by taking expectation. A mixed matching P is popular if phi(P, Q) >= phi(Q, P) for all mixed matchings Q. We show that popular mixed matchings always exist and we design polynomial time algorithms for finding them. Then we study their efficiency and give tight bounds on the price of anarchy and price of stability of the popular matching problem. (C) 2010 Elsevier B.V. All rights reserved.

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We develop an optimal, distributed, and low feedback timer-based selection scheme to enable next generation rate-adaptive wireless systems to exploit multi-user diversity. In our scheme, each user sets a timer depending on its signal to noise ratio (SNR) and transmits a small packet to identify itself when its timer expires. When the SNR-to-timer mapping is monotone non-decreasing, timers of users with better SNRs expire earlier. Thus, the base station (BS) simply selects the first user whose timer expiry it can detect, and transmits data to it at as high a rate as reliably possible. However, timers that expire too close to one another cannot be detected by the BS due to collisions. We characterize in detail the structure of the SNR-to-timer mapping that optimally handles these collisions to maximize the average data rate. We prove that the optimal timer values take only a discrete set of values, and that the rate adaptation policy strongly influences the optimal scheme's structure. The optimal average rate is very close to that of ideal selection in which the BS always selects highest rate user, and is much higher than that of the popular, but ad hoc, timer schemes considered in the literature.

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Spectral efficiency is a key characteristic of cellular communications systems, as it quantifies how well the scarce spectrum resource is utilized. It is influenced by the scheduling algorithm as well as the signal and interference statistics, which, in turn, depend on the propagation characteristics. In this paper we derive analytical expressions for the short-term and long-term channel-averaged spectral efficiencies of the round robin, greedy Max-SINR, and proportional fair schedulers, which are popular and cover a wide range of system performance and fairness trade-offs. A unified spectral efficiency analysis is developed to highlight the differences among these schedulers. The analysis is different from previous work in the literature in the following aspects: (i) it does not assume the co-channel interferers to be identically distributed, as is typical in realistic cellular layouts, (ii) it avoids the loose spectral efficiency bounds used in the literature, which only considered the worst case and best case locations of identical co-channel interferers, (iii) it explicitly includes the effect of multi-tier interferers in the cellular layout and uses a more accurate model for handling the total co-channel interference, and (iv) it captures the impact of using small modulation constellation sizes, which are typical of cellular standards. The analytical results are verified using extensive Monte Carlo simulations.

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N-gram language models and lexicon-based word-recognition are popular methods in the literature to improve recognition accuracies of online and offline handwritten data. However, there are very few works that deal with application of these techniques on online Tamil handwritten data. In this paper, we explore methods of developing symbol-level language models and a lexicon from a large Tamil text corpus and their application to improving symbol and word recognition accuracies. On a test database of around 2000 words, we find that bigram language models improve symbol (3%) and word recognition (8%) accuracies and while lexicon methods offer much greater improvements (30%) in terms of word recognition, there is a large dependency on choosing the right lexicon. For comparison to lexicon and language model based methods, we have also explored re-evaluation techniques which involve the use of expert classifiers to improve symbol and word recognition accuracies.