968 resultados para TSP module
Resumo:
An integratedm odel is developed,b asedo n seasonailn puts of reservoiri nflow and rainfall in the irrigated area, to determine the optimal reservoir release policies and irrigation allocationst o multiple crops.T he model is conceptuallym ade up of two modules. Module 1 is an intraseasonal allocation model to maximize the sum of relative yieldso f all crops,f or a givens tateo f the systemu, singl inear programming(L P). The module takes into account reservoir storage continuity, soil moisture balance, and crop root growthw ith time. Module 2 is a seasonaal llocationm odel to derive the steadys tate reservoiro peratingp olicyu sings tochastidc ynamicp rogramming(S DP). 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 resultso f module 1 and the transitionp robabilitieso f seasonailn flow and rainfall form the input for module 2. The use of seasonailn puts coupledw ith the LP-SDP solution strategy in the present formulation facilitates in relaxing the limitations of an earlier study,w hile affectinga dditionali mprovementsT. he model is applied to an existing reservoir in Karnataka State, India.
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The acid-pyridine heterosynthon may be used as a `` molecular'' module to probe the structural landscape of the benzoic acid : isonicotinamide 1 : 1 cocrystal, BA: INA. Experimental structures of 1 : 1 cocrystals of fluorobenzoic acids (FBA) with isonicotinamide (INA) contain this heterosynthon and correspond to high-energy structures of 1 : 1 BA : INA.
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Although many sparse recovery algorithms have been proposed recently in compressed sensing (CS), it is well known that the performance of any sparse recovery algorithm depends on many parameters like dimension of the sparse signal, level of sparsity, and measurement noise power. It has been observed that a satisfactory performance of the sparse recovery algorithms requires a minimum number of measurements. This minimum number is different for different algorithms. In many applications, the number of measurements is unlikely to meet this requirement and any scheme to improve performance with fewer measurements is of significant interest in CS. Empirically, it has also been observed that the performance of the sparse recovery algorithms also depends on the underlying statistical distribution of the nonzero elements of the signal, which may not be known a priori in practice. Interestingly, it can be observed that the performance degradation of the sparse recovery algorithms in these cases does not always imply a complete failure. In this paper, we study this scenario and show that by fusing the estimates of multiple sparse recovery algorithms, which work with different principles, we can improve the sparse signal recovery. We present the theoretical analysis to derive sufficient conditions for performance improvement of the proposed schemes. We demonstrate the advantage of the proposed methods through numerical simulations for both synthetic and real signals.
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In this paper, we extend the characterization of Zx]/(f), where f is an element of Zx] to be a free Z-module to multivariate polynomial rings over any commutative Noetherian ring, A. The characterization allows us to extend the Grobner basis method of computing a k-vector space basis of residue class polynomial rings over a field k (Macaulay-Buchberger Basis Theorem) to rings, i.e. Ax(1), ... , x(n)]/a, where a subset of Ax(1), ... , x(n)] is an ideal. We give some insights into the characterization for two special cases, when A = Z and A = ktheta(1), ... , theta(m)]. As an application of this characterization, we show that the concept of Border bases can be extended to rings when the corresponding residue class ring is a finitely generated, free A-module. (C) 2014 Elsevier B.V. All rights reserved.
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In this paper we present a combination of technologies to provide an Energy-on-Demand (EoD) service to enable low cost innovation suitable for microgrid networks. The system is designed around the low cost and simple Rural Energy Device (RED) Box which in combination with Short Message Service (SMS) communication methodology serves as an elementary proxy for Smart meters which are typically used in urban settings. Further, customer behavior and familiarity in using such devices based on mobile experience has been incorporated into the design philosophy. Customers are incentivized to interact with the system thus providing valuable behavioral and usage data to the Utility Service Provider (USP). Data that is collected over time can be used by the USP for analytics envisioned by using remote computing services known as cloud computing service. Cloud computing allows for a sharing of computational resources at the virtual level across several networks. The customer-system interaction is facilitated by a third party Telecom Service provider (TSP). The approximate cost of the RED Box is envisaged to be under USD 10 on production scale.
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Three ternary co-crystals of the title compound are reported. The design strategy hinges on the identification of a robust synthon with O-H center dot center dot center dot N hydrogen bonds in a binary co-crystal. Construction of this module allows the tuning of pi center dot center dot center dot pi stacking interactions and weak hydrogen bonds to incorporate the third component into the crystal structure. Screening of various co-formers showed that a delicate balance of electrostatics is required for stacking to favor the formation of ternaries. A C-H center dot center dot center dot N hydrogen-bonded motif was also found to occur repetitively in the ternary co-crystals. The directional nature of weak hydrogen bonds allows them to be used effectively in this study.
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The explicit description of homogeneous operators and localization of a Hilbert module naturally leads to the definition of a class of Cowen-Douglas operators possessing a flag structure. These operators are irreducible. We show that the flag structure is rigid in the sense that the unitary equivalence class of the operator and the flag structure determine each other. We obtain a complete set of unitary invariants which are somewhat more tractable than those of an arbitrary operator in the Cowen-Douglas class. (C) 2014 Academie des sciences. Published by Elsevier Masson SAS. All rights reserved.
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The development of a viable adsorbed natural gas onboard fuel system involves synthesizing materials that meet specific storage target requirements. We assess the impact on natural gas storage due to intermediate processes involved in taking a laboratory powder sample to an onboard packed or adsorbent bed module. We illustrate that reporting the V/V (volume of gas/volume of container) capacities based on powder adsorption data without accounting for losses due to pelletization and bed porosity, grossly overestimates the working storage capacity for a given material. Using data typically found for adsorbent materials that are carbon and MOF based materials, we show that in order to meet the Department of Energy targets of 180 V/V (equivalent STP) loading at 3.5 MPa and 298 K at the onboard packed bed level, the volumetric capacity of the pelletized sample should be at least 245 V/V and the corresponding gravimetric loading varies from 0.175 to 0.38 kg/kg for pellet densities ranging from 461.5 to 1,000 . With recent revision of the DOE target to 263 V/V at the onboard packed bed level, the volumetric loadings for the pelletized sample should be about 373 V/V.
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It is well known that the impulse response of a wide-band wireless channel is approximately sparse, in the sense that it has a small number of significant components relative to the channel delay spread. In this paper, we consider the estimation of the unknown channel coefficients and its support in OFDM systems using a sparse Bayesian learning (SBL) framework for exact inference. In a quasi-static, block-fading scenario, we employ the SBL algorithm for channel estimation and propose a joint SBL (J-SBL) and a low-complexity recursive J-SBL algorithm for joint channel estimation and data detection. In a time-varying scenario, we use a first-order autoregressive model for the wireless channel and propose a novel, recursive, low-complexity Kalman filtering-based SBL (KSBL) algorithm for channel estimation. We generalize the KSBL algorithm to obtain the recursive joint KSBL algorithm that performs joint channel estimation and data detection. Our algorithms can efficiently recover a group of approximately sparse vectors even when the measurement matrix is partially unknown due to the presence of unknown data symbols. Moreover, the algorithms can fully exploit the correlation structure in the multiple measurements. Monte Carlo simulations illustrate the efficacy of the proposed techniques in terms of the mean-square error and bit error rate performance.
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Maximality of a contractive tuple of operators is considered. A characterization for a contractive tuple to be maximal is obtained. The notion of maximality for a submodule of the Drury-Arveson module on the -dimensional unit ball is defined. For , it is shown that every submodule of the Hardy module over the unit disc is maximal. But for we prove that any homogeneous submodule or submodule generated by polynomials is not maximal. A characterization of maximal submodules is obtained.
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We address the problem of reconstructing a sparse signal from its DFT magnitude. We refer to this problem as the sparse phase retrieval (SPR) problem, which finds applications in tomography, digital holography, electron microscopy, etc. We develop a Fienup-type iterative algorithm, referred to as the Max-K algorithm, to enforce sparsity and successively refine the estimate of phase. We show that the Max-K algorithm possesses Cauchy convergence properties under certain conditions, that is, the MSE of reconstruction does not increase with iterations. We also formulate the problem of SPR as a feasibility problem, where the goal is to find a signal that is sparse in a known basis and whose Fourier transform magnitude is consistent with the measurement. Subsequently, we interpret the Max-K algorithm as alternating projections onto the object-domain and measurement-domain constraint sets and generalize it to a parameterized relaxation, known as the relaxed averaged alternating reflections (RAAR) algorithm. On the application front, we work with measurements acquired using a frequency-domain optical-coherence tomography (FDOCT) experimental setup. Experimental results on measured data show that the proposed algorithms exhibit good reconstruction performance compared with the direct inversion technique, homomorphic technique, and the classical Fienup algorithm without sparsity constraint; specifically, the autocorrelation artifacts and background noise are suppressed to a significant extent. We also demonstrate that the RAAR algorithm offers a broader framework for FDOCT reconstruction, of which the direct inversion technique and the proposed Max-K algorithm become special instances corresponding to specific values of the relaxation parameter.
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CONSPECTUS: The halogen bond is an attractive interaction in which an electrophilic halogen atom approaches a negatively polarized species. Short halogen atom contacts in crystals have been known for around 50 years. Such contacts are found in two varieties: type I, which is symmetrical, and type II, which is bent. Both are influenced by geometric and chemical considerations. Our research group has been using halogen atom interactions as design elements in crystal engineering, for nearly 30 years. These interactions include halogen center dot center dot center dot halogen interactions (X center dot center dot center dot X) and halogen center dot center dot center dot heteroatom interactions (X center dot center dot center dot B). Many X center dot center dot center dot X and almost all X center dot center dot center dot B contacts can be classified as halogen bonds. In this Account, we illustrate examples of crystal engineering where one can build up from previous knowledge with a focus that is provided by the modern definition of the halogen bond. We also comment on the similarities and differences between halogen bonds and hydrogen bonds. These interactions are similar because the protagonist atoms halogen and hydrogen are both electrophilic in nature. The interactions are distinctive because the size of a halogen atom is of consequence when compared with the atomic sizes of, for example, C, N, and O, unlike that of a hydrogen atom. Conclusions may be drawn pertaining to the nature of X center dot center dot center dot X interactions from the Cambridge Structural Database (CSD). There is a clear geometric and chemical distinction between type I and type II, with only type II being halogen bonds. Cl/Br isostructurality is explained based on a geometric model. In parallel, experimental studies on 3,4-dichlorophenol and its congeners shed light on the nature of halogen center dot center dot center dot halogen interactions and reveal the chemical difference between Cl and Br. Variable temperature studies also show differences between type I and type II contacts. In terms of crystal design, halogen bonds offer a unique opportunity in the strength, atom size and interaction gradation; this may be used in the design of ternary cocrystals. Structural modularity in which an entire crystal structure is defined as a combination of modules is rationalized on the basis of the intermediate strength of a halogen bond. The specific directionality of the halogen bond makes it a good tool to achieve orthogonality in molecular crystals. Mechanical properties can be tuned systematically by varying these orthogonally oriented halogen center dot center dot center dot halogen interactions. In a further development, halogen bonds are shown to play a systematic role in organization of LSAMs (long range synthon aufbau module), which are bigger structural units containing multiple synthons. With a formal definition in place, this may be the right time to look at differences between halogen bonds and hydrogen bonds and exploit them in more subtle ways in crystal engineering.
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The standard approach to signal reconstruction in frequency-domain optical-coherence tomography (FDOCT) is to apply the inverse Fourier transform to the measurements. This technique offers limited resolution (due to Heisenberg's uncertainty principle). We propose a new super-resolution reconstruction method based on a parametric representation. We consider multilayer specimens, wherein each layer has a constant refractive index and show that the backscattered signal from such a specimen fits accurately in to the framework of finite-rate-of-innovation (FRI) signal model and is represented by a finite number of free parameters. We deploy the high-resolution Prony method and show that high-quality, super-resolved reconstruction is possible with fewer measurements (about one-fourth of the number required for the standard Fourier technique). To further improve robustness to noise in practical scenarios, we take advantage of an iterated singular-value decomposition algorithm (Cadzow denoiser). We present results of Monte Carlo analyses, and assess statistical efficiency of the reconstruction techniques by comparing their performance against the Cramer-Rao bound. Reconstruction results on experimental data obtained from technical as well as biological specimens show a distinct improvement in resolution and signal-to-reconstruction noise offered by the proposed method in comparison with the standard approach.
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In this paper we discuss the fabrication, working and characteristics of a thermoelectric generator made up of p and n type semiconductor materials. The device consists of Fe0.2Co3.8Sb11.5Te0.5 (zT = 1.04 at 818 K) as the n-type and Zn4Sb3 (zT= 0.8 at 550 K) as the p-type material synthesized by vacuum hot press method. Carbon paste has been used to join the semiconductor legs to metal (Molybdenum) electrodes to reduce the contact resistance. The multi-couple (4 legs) generator results a maximum output power of 1.083 mW at a temperature difference of 240 K between the hot and cold sides. In this investigation, an I-V characteristic, maximum output power of the thermoelectric module is presented. The efficiency of thermoelectric module is obtained as eta= 0.273 %.
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Representatives of several Internet service providers (ISPs) have expressed their wish to see a substantial change in the pricing policies of the Internet. In particular, they would like to see content providers (CPs) pay for use of the network, given the large amount of resources they use. This would be in clear violation of the ``network neutrality'' principle that had characterized the development of the wireline Internet. Our first goal in this article is to propose and study possible ways of implementing such payments and of regulating their amount. We introduce a model that includes the users' behavior, the utilities of the ISP and of the CPs, and, the monetary flow that involves the content users, the ISP and CP, and, in pUrticular, the CP's revenues from advertisements. We consider various game models and study the resulting equilibria; they are all combinations of a noncooperative game (in which the ISPs and CPs determine how much they will charge the users) with a ``cooperative'' one on how the CP and the ISP share the payments. We include in our model a possible asymmetric weighting parameter (that varies between zero to one). We also study equilibria that arise when one of the CPs colludes with the TSP. We also study two dynamic game models as well as the convergence of prices to the equilibrium values.