976 resultados para Multi-parameter Screen


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We consider single-source, single-sink (ss-ss) multi-hop relay networks, with slow-fading Rayleigh links. This two part paper aims at giving explicit protocols and codes to achieve the optimal diversity-multiplexing tradeoff (DMT) of two classes of multi-hop networks: K-parallel-path (KPP) networks and Layered networks. While single-antenna KPP networks were the focus of the first part, we consider layered and multi-antenna networks in this second part. We prove that a linear DMT between the maximum diversity d(max). and the maximum multiplexing gain of 1 is achievable for single-antenna fully-connected layered networks under the half-duplex constraint. This is shown to be equal to the optimal DMT if the number of relaying layers is less than 4. For the multiple-antenna case, we provide an achievable DMT, which is significantly better than known lower bounds for half duplex networks. Along the way, we compute the DMT of parallel MIMO channels in terms of the DMT of the component channel. For arbitrary ss-ss single-antenna directed acyclic networks with full-duplex relays, we prove that a linear tradeoff between maximum diversity and maximum multiplexing gain is achievable using an amplify-and-forward (AF) protocol. Explicit short-block-length codes are provided for all the proposed protocols. Two key implications of the results in the two-part paper are that the half-duplex constraint does not necessarily entail rate loss by a factor of two as previously believed and that simple AN protocols are often sufficient to attain the best possible DMT.

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We consider single-source, single-sink multi-hop relay networks, with slow-fading Rayleigh fading links and single-antenna relay nodes operating under the half-duplex constraint. While two hop relay networks have been studied in great detail in terms of the diversity-multiplexing tradeoff (DMT), few results are available for more general networks. In this two-part paper, we identify two families of networks that are multi-hop generalizations of the two hop network: K-Parallel-Path (KPP) networks and Layered networks. In the first part, we initially consider KPP networks, which can be viewed as the union of K node-disjoint parallel paths, each of length > 1. The results are then generalized to KPP(I) networks, which permit interference between paths and to KPP(D) networks, which possess a direct link from source to sink. We characterize the optimal DMT of KPP(D) networks with K >= 4, and KPP(I) networks with K >= 3. Along the way, we derive lower bounds for the DMT of triangular channel matrices, which are useful in DMT computation of various protocols. As a special case, the DMT of two-hop relay network without direct link is obtained. Two key implications of the results in the two-part paper are that the half-duplex constraint does not necessarily entail rate loss by a factor of two, as previously believed and that, simple AF protocols are often sufficient to attain the best possible DMT.

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The paper presents a novel slicing based method for computation of volume fractions in multi-material solids given as a B-rep whose faces are triangulated and shared by either one or two materials. Such objects occur naturally in geoscience applications and the said computation is necessary for property estimation problems and iterative forward modeling. Each facet in the model is cut by the planes delineating the given grid structure or grid cells. The method, instead of classifying the points or cells with respect to the solid, exploits the convexity of triangles and the simple axis-oriented disposition of the cutting surfaces to construct a novel intermediate space enumeration representation called slice-representation, from which both the cell containment test and the volume-fraction computation are done easily. Cartesian and cylindrical grids with uniform and non-uniform spacings have been dealt with in this paper. After slicing, each triangle contributes polygonal facets, with potential elliptical edges, to the grid cells through which it passes. The volume fractions of different materials in a grid cell that is in interaction with the material interfaces are obtained by accumulating the volume contributions computed from each facet in the grid cell. The method is fast, accurate, robust and memory efficient. Examples illustrating the method and performance are included in the paper.

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In this paper we analyze a deploy and search strategy for multi-agent systems. Mobile agents equipped with sensors carry out search operation in the search space. The lack of information about the search space is modeled as an uncertainty density distribution over the space, and is assumed to be known to the agents a priori. In each step, the agents deploy themselves in an optimal way so as to maximize per step reduction in the uncertainty density. We analyze the proposed strategy for convergence and spatial distributedness. The control law moving the agents has been analyzed for stability and convergence using LaSalle's invariance principle, and for spatial distributedness under a few realistic constraints on the control input such as constant speed, limit on maximum speed, and also sensor range limits. The simulation experiments show that the strategy successfully reduces the average uncertainty density below the required level.

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We propose certain discrete parameter variants of well known simulation optimization algorithms. Two of these algorithms are based on the smoothed functional (SF) technique while two others are based on the simultaneous perturbation stochastic approximation (SPSA) method. They differ from each other in the way perturbations are obtained and also the manner in which projections and parameter updates are performed. All our algorithms use two simulations and two-timescale stochastic approximation. As an application setting, we consider the important problem of admission control of packets in communication networks under dependent service times. We consider a discrete time slotted queueing model of the system and consider two different scenarios - one where the service times have a dependence on the system state and the other where they depend on the number of arrivals in a time slot. Under our settings, the simulated objective function appears ill-behaved with multiple local minima and a unique global minimum characterized by a sharp dip in the objective function in a small region of the parameter space. We compare the performance of our algorithms on these settings and observe that the two SF algorithms show the best results overall. In fact, in many cases studied, SF algorithms converge to the global minimum.

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Background Advances in cancer diagnosis and treatment have significantly improved survival rates, through their subsequent health needs are often not adequately addressed by current health services. National Health and Medical Research Council (NHMRC) Partnerships Project awarded a national collaborative project to develop, trial and evaluate clinical benefits and cost effectiveness of an e-health enabled structured health promotion intervention - The Women’s Wellness after Cancer Program (WWACP). The aim of this e-health enabled multimodal intervention is to improve health related quality of life in women previously treated for target cancers. Aim The WWACP is a 12-week web based, interactive, holistic program. Primary outcomes for this project are to promote a positive change in health-related quality of life (HRQoL) and reduction in Body Mass Index (BMI) in the women undertaking WWACP compared to women who receive usual care. Secondary outcomes include managing other side effects of cancer treatment through evidence-based nutrition and exercise practices, dealing with stress, sleep, menopause and sexuality issues. Methods The single-blinded multi-center randomized controlled trial recruited a toatl of 330 women within 24 months of completion of chemotherapy and /or radiotherapy. Women were randomly assigned to either a usual care or intervention group. Women provided with the intervention were provided with an interactive iBook and journal, web interface, and three virtual consultations by experienced cancer nurses. A variety of methods were utilized, to enable positive self- efficacy and lifestyle changes. These include online coaching with a registered nurse trained in the intervention, plus written educational and health promotional information. The program has been delivered through the e-health enabled interfaces, which enables virtual delivery via desktop and mobile computing devices. Importantly this enables accessibility for rural and regional women in Australia who are frequently geographically disadvantaged in terms of health care provision. Results Research focusing on alternative methods of delivering post treatment / or survivorship care in cancer utilizing web based interfaces is limited, but emerging evidence suggests that Internet interventions can increase psychological and physical wellbeing in cancer patients. The WWACP trial aims to establish the effectiveness of delivery of the program in terms of positive patient outcomes and cost effective, flexibility. The trial will be completed in September and results will be presented at the conference. Conclusions Women after acute hematological, breast and gynecological cancer treatments demonstrate good cancer survival rates and face residual health problems which are amenable to behavioral interventions. The conclusion of active treatment is a key 'teachable moment' in which sustainable positive lifestyle change can be achieved if patients receive education and psychological support which targets key treatment related health problems and known chronic disease risk factors.

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We explore the fuse of information on co-occurrence of domains in multi-domain proteins in predicting protein-protein interactions. The basic premise of our work is the assumption that domains co-occurring in a polypeptide chain undergo either structural or functional interactions among themselves. In this study we use a template dataset of domains in multidomain proteins and predict protein-protein interactions in a target organism. We note that maximum number of correct predictions of interacting protein domain families (158) is made in S. cerevisiae when the dataset of closely related organisms is used as the template followed by the more diverse dataset of bacterial proteins (48) and a dataset of randomly chosen proteins (23). We conclude that use of multi-domain information from organisms closely-related to the target can aid prediction of interacting protein families.

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A method of testing for parametric faults of analog circuits based on a polynomial representation of fault-free function of the circuit is presented. The response of the circuit under test (CUT) is estimated as a polynomial in the applied input voltage at relevant frequencies in addition to DC. Classification or Cur is based on a comparison of the estimated polynomial coefficients with those of the fault free circuit. This testing method requires no design for test hardware as might be added to the circuit fly some other methods. The proposed method is illustrated for a benchmark elliptic filter. It is shown to uncover several parametric faults causing deviations as small as 5% from the nominal values.

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Our attention, is focused on designing an optimal procurement mechanism which a buyer can use for procuring multiple units of a homogeneous item based on bids submitted by autonomous, rational, and intelligent suppliers. We design elegant optimal procurement mechanisms for two different situations. In the first situation, each supplier specifies the maximum quantity that can be supplied together with a per unit price. For this situation, we design an optimal mechanism S-OPT (Optimal with Simple bids). In the more generalized case, each supplier specifies discounts based on the volume of supply. In this case, we design an optimal mechanism VD-OPT (Optimal with Volume Discount, bids). The VD-OPT mechanism uses the S-OPT mechanism as a building block. The proposed mechanisms minimize the cost to the buyer, satisfying at the same time, (a) Bayesian, incentive compatibility and (b) interim individual rationality.

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We present a generic method/model for multi-objective design optimization of laminated composite components, based on vector evaluated particle swarm optimization (VEPSO) algorithm. VEPSO is a novel, co-evolutionary multi-objective variant of the popular particle swarm optimization algorithm (PSO). In the current work a modified version of VEPSO algorithm for discrete variables has been developed and implemented successfully for the, multi-objective design optimization of composites. The problem is formulated with multiple objectives of minimizing weight and the total cost of the composite component to achieve a specified strength. The primary optimization variables are - the number of layers, its stacking sequence (the orientation of the layers) and thickness of each layer. The classical lamination theory is utilized to determine the stresses in the component and the design is evaluated based on three failure criteria; failure mechanism based failure criteria, Maximum stress failure criteria and the Tsai-Wu failure criteria. The optimization method is validated for a number of different loading configurations - uniaxial, biaxial and bending loads. The design optimization has been carried for both variable stacking sequences, as well fixed standard stacking schemes and a comparative study of the different design configurations evolved has been presented. (C) 2007 Elsevier Ltd. All rights reserved.

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In this paper, we study the behaviour of the slotted Aloha multiple access scheme with a finite number of users under different traffic loads and optimize the retransmission probability q(r) for various settings, cost objectives and policies. First, we formulate the problem as a parameter optimization problem and use certain efficient smoothed functional algorithms for finding the optimal retransmission probability parameter. Next, we propose two classes of multi-level closed-loop feedback policies (for finding in each case the retransmission probability qr that now depends on the current system state) and apply the above algorithms for finding an optimal policy within each class of policies. While one of the policy classes depends on the number of backlogged nodes in the system, the other depends on the number of time slots since the last successful transmission. The latter policies are more realistic as it is difficult to keep track of the number of backlogged nodes at each instant. We investigate the effect of increasing the number of levels in the feedback policies. Wen also investigate the effects of using different cost functions (withn and without penalization) in our algorithms and the corresponding change in the throughput and delay using these. Both of our algorithms use two-timescale stochastic approximation. One of the algorithms uses one simulation while the other uses two simulations of the system. The two-simulation algorithm is seen to perform better than the other algorithm. Optimal multi-level closed-loop policies are seen to perform better than optimal open-loop policies. The performance further improves when more levels are used in the feedback policies.

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A system of many coupled oscillators on a network can show multicluster synchronization. We obtain existence conditions and stability bounds for such a multicluster synchronization. When the oscillators are identical, we obtain the interesting result that network structure alone can cause multicluster synchronization to emerge even when all the other parameters are the same. We also study occurrence of multicluster synchronization when two different types of oscillators are coupled.

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Increased emphasis on rotorcraft performance and perational capabilities has resulted in accurate computation of aerodynamic stability and control parameters. System identification is one such tool in which the model structure and parameters such as aerodynamic stability and control derivatives are derived. In the present work, the rotorcraft aerodynamic parameters are computed using radial basis function neural networks (RBFN) in the presence of both state and measurement noise. The effect of presence of outliers in the data is also considered. RBFN is found to give superior results compared to finite difference derivatives for noisy data. (C) 2010 Elsevier Inc. All rights reserved.

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The increased availability of image capturing devices has enabled collections of digital images to rapidly expand in both size and diversity. This has created a constantly growing need for efficient and effective image browsing, searching, and retrieval tools. Pseudo-relevance feedback (PRF) has proven to be an effective mechanism for improving retrieval accuracy. An original, simple yet effective rank-based PRF mechanism (RB-PRF) that takes into account the initial rank order of each image to improve retrieval accuracy is proposed. This RB-PRF mechanism innovates by making use of binary image signatures to improve retrieval precision by promoting images similar to highly ranked images and demoting images similar to lower ranked images. Empirical evaluations based on standard benchmarks, namely Wang, Oliva & Torralba, and Corel datasets demonstrate the effectiveness of the proposed RB-PRF mechanism in image retrieval.

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A novel stress induced martenistic phase transformation is reported in an initial B2-CuZr nanowire of cross-sectional dimensions in the range of 19.44 x 19.44-38.88 x 38.88 angstrom(2) and temperature in the range of 10-400 K under both tensile and compressive loading. Extensive Molecular Dynamic simulations are performed using an inter-atomic potential of type Finnis and Sinclair. The nanowire shows a phase transformation from an initial B2 phase to BCT (body-centered-tetragonal) phase with failure strain of similar to 40% in tension, whereas in compression, comparatively a small B2 -> BCT phase transformation is observed with failure strain of similar to 25%. Size and temperature dependent deformation mechanisms which control ultimately the B2 -> BCT phase transformation are found to be completely different for tensile and compressive loadings. Under tensile loading, small cross-sectional nanowire shows a single step phase transformation, i.e. B2 -> BCT via twinning along {100} plane, whereas nanowires with larger cross-sectional area show a two step phase transformation, i.e. B2 -> R phase -> BCT along with intermediate hardening. In the first step, nanowire shows phase transformation from B2 -> R phase via twinning along {100} plane, afterwards the nanowire deforms via twinning along {110} plane which cause further transformation from R phase -> BCT phase. Under compressive loading, the nanowire shows crushing along {100} plane after a single step phase transformation from B2 -> BCT. Proper tailoring of such size and temperature dependent phase transformation can be useful in designing nanowire for high strength applications with corrosion and fatigue resistance. (C) 2009 Elsevier Ltd. All rights reserved.