210 resultados para multiple regimes
Resumo:
The omega(1)-heterodecoupled-C-13-filtered proton detected NMR experiments are reported for the accurate quantification of enantiomeric excess in chiral molecules embedded in chiral liquid crystal. The differential values of both H-1-H-1 and C-13-H-1 dipolar couplings in the direct dimension and only H-1-H-1 dipolar couplings in the indirect dimension enable unraveling of overlapped enantiomeric peaks. The creation of unequal C-13-bound proton signal for each enantiomer in the INEPT block and non-uniform excitation of coherences in homonuclear multiple quantum experiments do not yield accurate quantification of enantiomeric excess. In circumventing these difficulties, a coupling dependent intensity correction factor has been invoked. (C) 2010 Elsevier B.V. All rights reserved.
Resumo:
A novel approach for simultaneous measurement of chirp (any parameter that can induce strain gradient on FBG) and temperature using a single FBG is proposed. Change in reflectivity at central wavelength of FBG reflection & Bragg wavelength shifts induced due to temperature were used for chirp & temperature measurements respectively. Theoretical resolution limit for chirp and temperature using an Optical Spectrum Analyzer (OSA) with 1pm wavelength resolution and >58dB dynamic range are 12.8fm and 1/13 degrees C respectively.
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In a typical sensor network scenario a goal is to monitor a spatio-temporal process through a number of inexpensive sensing nodes, the key parameter being the fidelity at which the process has to be estimated at distant locations. We study such a scenario in which multiple encoders transmit their correlated data at finite rates to a distant, common decoder over a discrete time multiple access channel under various side information assumptions. In particular, we derive an achievable rate region for this communication problem.
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Multiple UAVs are deployed to carry out a search and destroy mission in a bounded region. The UAVs have limited sensor range and can carry limited resources which reduce with use. The UAVs perform a search task to detect targets. When a target is detected which requires different type and quantities of resources to completely destroy, then a team of UAVs called as a coalition is formed to attack the target. The coalition members have to modify their route to attack the target, in the process, the search task is affected, as search and destroy tasks are coupled. The performance of the mission is a function of the search and the task allocation strategies. Therefore, for a given task allocation strategy, we need to devise search strategies that are efficient. In this paper, we propose three different search strategies namely; random search strategy, lanes based search strategy and grid based search strategy and analyze their performance through Monte-Carlo simulations. The results show that the grid based search strategy performs the best but with high information overhead.
Resumo:
Constellation Constrained (CC) capacity regions of two-user Single-Input Single-Output (SISO) Gaussian Multiple Access Channels (GMAC) are computed for several Non-Orthogonal Multiple Access schemes (NO-MA) and Orthogonal Multiple Access schemes (O-MA). For NO-MA schemes, a metric is proposed to compute the angle(s) of rotation between the input constellations such that the CC capacity regions are maximally enlarged. Further, code pairs based on Trellis Coded Modulation (TCM) are designed with PSK constellation pairs and PAM constellation pairs such that any rate pair within the CC capacity region can be approached. Such a NO-MA scheme which employs CC capacity approaching trellis codes is referred to as Trellis Coded Multiple Access (TCMA). Then, CC capacity regions of O-MA schemes such as Frequency Division Multiple Access (FDMA) and Time Division Multiple Access (TDMA) are also computed and it is shown that, unlike the Gaussian distributed continuous constellations case, the CC capacity regions with FDMA are strictly contained inside the CC capacity regions with TCMA. Hence, for finite constellations, a NO-MA scheme such as TCMA is better than FDMA and TDMA which makes NO-MA schemes worth pursuing in practice for two-user GMAC. Then, the idea of introducing rotations between the input constellations is used to construct Space-Time Block Code (STBC) pairs for two-user Multiple-Input Single-Output (MISO) fading MAC. The proposed STBCs are shown to have reduced Maximum Likelihood (ML) decoding complexity and information-losslessness property. Finally, STBC pairs with reduced sphere decoding complexity are proposed for two-user Multiple-Input Multiple-Output (MIMO) fading MAC.
Resumo:
The problem of structural system identification when measurements originate from multiple tests and multiple sensors is considered. An offline solution to this problem using bootstrap particle filtering is proposed. The central idea of the proposed method is the introduction of a dummy independent variable that allows for simultaneous assimilation of multiple measurements in a sequential manner. The method can treat linear/nonlinear structural models and allows for measurements on strains and displacements under static/dynamic loads. Illustrative examples consider measurement data from numerical models and also from laboratory experiments. The results from the proposed method are compared with those from a Kalman filter-based approach and the superior performance of the proposed method is demonstrated. Copyright (C) 2009 John Wiley & Sons, Ltd.
Resumo:
Payment systems all over the world have grown into a complicated web of solutions. This is more challenging in the case of mobile based payment systems. Mobile based payment systems are many and consist of different technologies providing different services. The diffusion of these various technologies in a market is uncertain. Diffusion theorists, for example Rogers, and Davis suggest how innovation is accepted in markets. In the case of electronic payment systems, the tale of Mondex vs Octopus throws interesting insights on diffusion. Our paper attempts to understand the success potential of various mobile payment technologies. We illustrate what we describe as technology breadth in mobile payment systems using data from payment systems all over the world (n=62). Our data shows an unexpected superiority of SMS technology, over other technologies like NFC, WAP and others. We also used a Delphi based survey (n=5) with experts to address the possibility that SMS will gain superiority in market diffusion. The economic conditions of a country, particularly in developing countries, the services availed and characteristics of the user (for example number of un-banked users in large populated countries) may put SMS in the forefront. This may be true more for micro payments using the mobile.
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Pseudomonas putida CSV86, a soil bacterium, grows on 1- and 2-methylnaphthalene as the sole source of carbon and energy. In order to deduce the pathways for the biodegradation of 1- and 2-methylnaphthalene, metabolites were isolated from the spent medium and purified by thin layer chromatography. Emphasis has been placed on the structural characterisation of isolated intermediates by CC-MS, demonstration of enzyme activities in the cell free extracts and measurement of oxygen uptake by whole cells in the presence of various probable metabolic intermediates. The data obtained from such a study suggest the possibility of occurrence of multiple pathways in the degradation of 1- and 2-methylnaphthalene. We propose that, in one of the pathways, the aromatic ring adjacent to the one bearing the methyl moiety is oxidized leading to the formation of methylsalicylates and methylcatechols. In another pathway the methyl side chain is hydroxylated to -CH2-OH which is further converted to -CHO and -COOH resulting in the formation of naphthoic acid as the end product. In addition to this, 2-hydroxymethylnaphthalene formed by the hydroxylation of the methyl group of 2-methylnaphthalene undergoes aromatic ring hydroxylation. The resultant dihydrodiol is further oxidised by a series of enzyme catalysed reactions to form 4-hydroxymethyl catechol as the end product of the pathway.
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We present a frontier based algorithm for searching multiple goals in a fully unknown environment, with only information about the regions where the goals are most likely to be located. Our algorithm chooses an ``active goal'' from the ``active goal list'' generated by running a Traveling Salesman Problem (Tsp) routine with the given centroid locations of the goal regions. We use the concept of ``goal switching'' which helps not only in reaching more number of goals in given time, but also prevents unnecessary search around the goals that are not accessible (surrounded by walls). The simulation study shows that our algorithm outperforms Multi-Heuristic LRTA* (MELRTA*) which is a significant representative of multiple goal search approaches in an unknown environment, especially in environments with wall like obstacles.
Resumo:
Unmanned aerial vehicles (UAVs) have the potential to carry resources in support of search and prosecute operations. Often to completely prosecute a target, UAVs may have to simultaneously attack the target with various resources with different capacities. However, the UAVs are capable of carrying only limited resources in small quantities, hence, a group of UAVs (coalition) needs to be assigned that satisfies the target resource requirement. The assigned coalition must be such that it minimizes the target prosecution delay and the size of the coalition. The problem of forming coalitions is computationally intensive due to the combinatorial nature of the problem, but for real-time applications computationally cheap solutions are required. In this paper, we propose decentralized sub-optimal (polynomial time) and decentralized optimal coalition formation algorithms that generate coalitions for a single target with low computational complexity. We compare the performance of the proposed algorithms to that of a global optimal solution for which we need to solve a centralized combinatorial optimization problem. This problem is computationally intensive because the solution has to (a) provide a coalition for each target, (b) design a sequence in which targets need to be prosecuted, and (c) take into account reduction of UAV resources with usage. To solve this problem we use the Particle Swarm Optimization (PSO) technique. Through simulations, we study the performance of the proposed algorithms in terms of mission performance, complexity of the algorithms and the time taken to form the coalition. The simulation results show that the solution provided by the proposed algorithms is close to the global optimal solution and requires far less computational resources.
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Employing multiple base stations is an attractive approach to enhance the lifetime of wireless sensor networks. In this paper, we address the fundamental question concerning the limits on the network lifetime in sensor networks when multiple base stations are deployed as data sinks. Specifically, we derive upper bounds on the network lifetime when multiple base stations are employed, and obtain optimum locations of the base stations (BSs) that maximize these lifetime bounds. For the case of two BSs, we jointly optimize the BS locations by maximizing the lifetime bound using a genetic algorithm based optimization. Joint optimization for more number of BSs is complex. Hence, for the case of three BSs, we optimize the third BS location using the previously obtained optimum locations of the first two BSs. We also provide simulation results that validate the lifetime bounds and the optimum locations of the BSs.
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A systematic method is formulated to carry out theoretical analysis in a multilocus multiallele genetic system. As a special application, the Fundamental Theorem of Natural Selection is proved (in the continuous time model) for a multilocus multiallele system if all pairwise linkage disequilibria are zero.
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Bacterial FtsE gene codes for the ATP-binding protein, FtsE, which in complex with the transmembrane protein, FtsX, participates in diverse cellular processes. Therefore, regulated expression of FtsE and FtsX might be critical to the human pathogen, Mycobacterium tuberculosis, under stress conditions. Although ftsX gene of M. tuberculosis (MtftsX) is known to be transcribed from a promoter inside the upstream gene, ftsE, the transcriptional status of ftsE gene of M. tuberculosis (MtftsE) remains unknown. Therefore, the authors initiated transcriptional analyses of MtftsE, using total RNA from M. tuberculosis cells that were grown under stress conditions, which the pathogen is exposed to, in granuloma in tuberculosis patients. Primer extension experiments showed the presence of putative transcripts, T1, T2, T3, and T4. T1 originated from the intergenic region between the upstream gene, MRA_3135, and MtftsE. T2 and T3 were found initiated from within MRA_3135. T4 was transcribed from a region upstream of MRA_3135. RT-PCR confirmed co-transcription of MRA_3135 and MtftsE. The cloned putative promoter regions for T1, T2, and T3 elicited transcriptional activity in Mycobacterium smegmatis transformants. T1, T2, and T3, but no new transcript, were present in the M. tuberculosis cells that were grown under the stress conditions, which the pathogen is exposed to in granuloma in tuberculosis patients. It showed lack of modulation of MtftsE transcripts under the stress conditions tested, indicating that ftsE may not have a stress response-specific function in M. tuberculosis.
Resumo:
An integrated model is developed, based on seasonal inputs of reservoir inflow and rainfall in the irrigated area, to determine the optimal reservoir release policies and irrigation allocations to multiple crops. The model is conceptually made up of two modules, Module 1 is an intraseasonal allocation model to maximize the sum of relative yields of all crops, for a given state of the system, using linear programming (LP). The module takes into account reservoir storage continuity, soil moisture balance, and crop root growth with time. Module 2 is a seasonal allocation model to derive the steady state reservoir operating policy using stochastic dynamic programming (SDP). Reservoir storage, seasonal inflow, and seasonal rainfall are the state variables in the SDP. The objective in SDP is to maximize the expected sum of relative yields of all crops in a year. The results of module 1 and the transition probabilities of seasonal inflow and rainfall form the input for module 2. The use of seasonal inputs coupled with the LP-SDP solution strategy in the present formulation facilitates in relaxing the limitations of an earlier study, while affecting additional improvements. The model is applied to an existing reservoir in Karnataka State, India.