981 resultados para dynamic matching
Resumo:
We consider a dynamic model where traders in each period are matched randomly into pairs who then bargain about the division of a fixed surplus. When agreement is reached the traders leave the market. Traders who do not come to an agreement return next period in which they will be matched again, as long as their deadline has not expired yet. New traders enter exogenously in each period. We assume that traders within a pair know each other's deadline. We define and characterize the stationary equilibrium configurations. Traders with longer deadlines fare better than traders with short deadlines. It is shown that the heterogeneity of deadlines may cause delay. It is then shown that a centralized mechanism that controls the matching protocol, but does not interfere with the bargaining, eliminates all delay. Even though this efficient centralized mechanism is not as good for traders with long deadlines, it is shown that in a model where all traders can choose which mechanism to
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A novel approach of normal ECG recognition based on scale-space signal representation is proposed. The approach utilizes curvature scale-space signal representation used to match visual objects shapes previously and dynamic programming algorithm for matching CSS representations of ECG signals. Extraction and matching processes are fast and experimental results show that the approach is quite robust for preliminary normal ECG recognition.
Exclusive Nightclubs and Lonely Hearts Columns: Nonmonotone Participation in Optional Intermediation
Resumo:
In many decentralised markets, the traders who benefit most from an exchange do not employ intermediaries even though they could easily afford them. At the same time, employing intermediaries is not worthwhile for traders who benefit little from trade. Together, these decisions amount to non-monotone participation choices in intermediation: only traders of middle “type” employ intermediaries, while the rest, the high and the low types, prefer to search for a trading partner directly. We provide a theoretical foundation for this, hitherto unexplained, phenomenon. We build a dynamic matching model, where a trader’s equilibrium bargaining share is a convex increasing function of her type. We also show that this is indeed a necessary condition for the existence of non-monotone equilibria.
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A novel approach of automatic ECG analysis based on scale-scale signal representation is proposed. The approach uses curvature scale-space representation to locate main ECG waveform limits and peaks and may be used to correct results of other ECG analysis techniques or independently. Moreover dynamic matching of ECG CSS representations provides robust preliminary recognition of ECG abnormalities which has been proven by experimental results.
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The application of energy minimisation methods for stereo matching has been demonstrated to produce high quality disparity maps. However the majority of these methods are known to be computationally expensive, requiring minutes or even hours of computation. We propose a fast minimisation scheme that produces strongly competitive results for significantly reduced computation, requiring only a few seconds of computation. In this paper, we present our iterated dynamic programming algorithm along with a quadtree subregioning process for fast stereo matching.
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In this article, we evaluate the use of simple Lee-Goldburg cross-polarization (LG-CP) NMR experiments for obtaining quantitative information of molecular motion in the intermediate regime. In particular, we introduce the measurement of Hartmann-Hahn matching profiles for the assessment of heteronuclear dipolar couplings as well as dynamics as a reliable and robust alternative to the more common analysis of build-up curves. We have carried out dynamic spin dynamics simulations in order to test the method's sensitivity to intermediate motion and address its limitations concerning possible experimental imperfections. We further demonstrate the successful use of simple theoretical concepts, most prominently Anderson-Weiss (AW) theory, to analyze the data. We further propose an alternative way to estimate activation energies of molecular motions, based upon the acquisition of only two LG-CP spectra per temperature at different temperatures. As experimental tests, molecular jumps in imidazole methyl sulfonate, trimethylsulfoxonium iodide, and bisphenol A polycarbonate were investigated with the new method.
Resumo:
The objective of this thesis is the development of a multibody dynamic model matching the observed movements of the lower limb of a skier performing the skating technique in cross-country style. During the construction of this model, the formulation of the equation of motion was made using the Euler - Lagrange approach with multipliers applied to a multibody system in three dimensions. The description of the lower limb of the skate skier and the ski was completed by employing three bodies, one representing the ski, and two representing the natural movements of the leg of the skier. The resultant system has 13 joint constraints due to the interconnection of the bodies, and four prescribed kinematic constraints to account for the movements of the leg, leaving the amount of degrees of freedom equal to one. The push-off force exerted by the skate skier was taken directly from measurements made on-site in the ski tunnel at the Vuokatti facilities (Finland) and was input into the model as a continuous function. Then, the resultant velocities and movement of the ski, center of mass of the skier, and variation of the skating angle were studied to understand the response of the model to the variation of important parameters of the skate technique. This allowed a comparison of the model results with the real movement of the skier. Further developments can be made to this model to better approximate the results to the real movement of the leg. One can achieve this by changing the constraints to include the behavior of the real leg joints and muscle actuation. As mentioned in the introduction of this thesis, a multibody dynamic model can be used to provide relevant information to ski designers and to obtain optimized results of the given variables, which athletes can use to improve their performance.
Resumo:
Preparation of optically active compounds is of high importance in modern medicinal chemistry. Despite recent advances in the field of asymmetric synthesis, resolution of racemates still remains the most utilized way for preparation of single enantiomers in industrial scale due to its cost-efficiency and simplicity. Enzymatic kinetic resolution (KR) of racemates is a classical method for separation of enantiomers. One of its drawbacks is the limitation of target enantiomer yield to 50%. Dynamic Kinetic Resolution (DKR) allows to reach yields up to 100% by in situ racemization of the less reactive enantiomer. In the first part of this thesis, a number of half-sandwich ruthenium complexes were prepared and evaluated as catalysts for racemization of optically active secondary alcohols. A leading catalyst, Bn5CpRu(CO)2Cl, was identified. The catalyst discovered was extensively characterized by its application for DKR of a broad range of secondary alcohols in a wide range of reaction loadings (1 mmol – 1 mol). Cost-efficient chromatography-free procedure for preparation of this catalyst was developed. Further, detailed kinetic and mechanistic studies of the racemization reactions were performed. Comparison of racemization rates in the presence of Bn5CpRu(CO)2Cl and Ph5CpRu(CO)2Cl catalysts reveals that the performance of the catalytic system can be adjusted by matching of the electronic properties of the catalysts and the substrates. Moreover, dependence of the rate-limiting step from the electronic properties of the reagents was observed. Important conclusions about reaction mechanism were made. Finally, an alternative approach to DKR of amines based on space separated vessels was addressed. This procedure allows the combination of thermolabile enzyme with racemization catalysts active only at high temperatures.
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An approach to the automatic generation of efficient Field Programmable Gate Arrays (FPGAs) circuits for the Regular Expression-based (RegEx) Pattern Matching problems is presented. Using a novel design strategy, as proposed, circuits that are highly area-and-time-efficient can be automatically generated for arbitrary sets of regular expressions. This makes the technique suitable for applications that must handle very large sets of patterns at high speed, such as in the network security and intrusion detection application domains. We have combined several existing techniques to optimise our solution for such domains and proposed the way the whole process of dynamic generation of FPGAs for RegEX pattern matching could be automated efficiently.
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Dynamic Time Warping (DTW), a pattern matching technique traditionally used for restricted vocabulary speech recognition, is based on a temporal alignment of the input signal with the template models. The principal drawback of DTW is its high computational cost as the lengths of the signals increase. This paper shows extended results over our previously published conference paper, which introduces an optimized version of the DTW I hat is based on the Discrete Wavelet Transform (DWT). (C) 2008 Elsevier B.V. All rights reserved.
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This paper proposes methods to circumvent the need to attach physical markers to bones for anatomical referencing in computer-assisted orthopedic surgery. Using ultrasound, a bone could be non-invasively referenced, and so the problem is formulated as the need for dynamic registration. A method for correspondence establishment is presented, and the matching step is based on three least-squares algorithms: two that are typically used in registration methods such as ICP, and the third is a form of the Unscented Kalman filter that was adapted to work in this context. A simulation was developed in order to reliably evaluate and compare the dynamic registration methods
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INTRODUCTION Surgical decompression for lumbar spinal stenosis (LSS) has been associated with poorer outcomes in patients with pronounced low back pain (LBP) as compared to patients with predominant leg pain. This cross registry study assessed potential benefits of the interlaminar coflex® device as an add-on to bony decompression alone. METHODS Patients with lumbar decompression plus coflex® (SWISSspine registry) were compared with decompressed controls (Spine Tango registry). Inclusion criteria were LSS and a preoperative back pain level of ≥5 points. 1:1 propensity score-based matching was performed. Outcome measures were back and leg pain relief, COMI score improvement, patient satisfaction, complication, and revision rates. RESULTS 50 matched pairs without residual significant differences but age were created. At the 7-9 months follow-up interval the coflex® group had higher back (p=0.014) and leg pain relief (p<0.001) and COMI score improvement (p=0.029) than the decompression group. Patient satisfaction was 90% in both groups. No revision was documented in the coflex® and one in the decompression group (2.0%). DISCUSSION In the short-term, lumbar decompression with coflex® compared with decompression alone in patients with LSS and pronounced LBP at baseline is a safe and effective treatment option that appears beneficial regarding clinical and functional outcomes. However, residual confounding of non-measured covariables may have partially influenced our findings. Also, despite careful inclusion and exclusion of cases the cross registry approach introduces a potential for selection bias that we could not totally control for and that makes additional studies necessary.
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Although context could be exploited to improve performance, elasticity and adaptation in most distributed systems that adopt the publish/subscribe (P/S) communication model, only a few researchers have focused on the area of context-aware matching in P/S systems and have explored its implications in domains with highly dynamic context like wireless sensor networks (WSNs) and IoT-enabled applications. Most adopted P/S models are context agnostic or do not differentiate context from the other application data. In this article, we present a novel context-aware P/S model. SilboPS manages context explicitly, focusing on the minimization of network overhead in domains with recurrent context changes related, for example, to mobile ad hoc networks (MANETs). Our approach represents a solution that helps to efficiently share and use sensor data coming from ubiquitous WSNs across a plethora of applications intent on using these data to build context awareness. Specifically, we empirically demonstrate that decoupling a subscription from the changing context in which it is produced and leveraging contextual scoping in the filtering process notably reduces (un)subscription cost per node, while improving the global performance/throughput of the network of brokers without fltering the cost of SIENA-like topology changes.
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This paper reports on the development of an artificial neural network (ANN) method to detect laminar defects following the pattern matching approach utilizing dynamic measurement. Although structural health monitoring (SHM) using ANN has attracted much attention in the last decade, the problem of how to select the optimal class of ANN models has not been investigated in great depth. It turns out that the lack of a rigorous ANN design methodology is one of the main reasons for the delay in the successful application of the promising technique in SHM. In this paper, a Bayesian method is applied in the selection of the optimal class of ANN models for a given set of input/target training data. The ANN design method is demonstrated for the case of the detection and characterisation of laminar defects in carbon fibre-reinforced beams using flexural vibration data for beams with and without non-symmetric delamination damage.
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A novel algorithm for performing registration of dynamic contrast-enhanced (DCE) MRI data of the breast is presented. It is based on an algorithm known as iterated dynamic programming originally devised to solve the stereo matching problem. Using artificially distorted DCE-MRI breast images it is shown that the proposed algorithm is able to correct for movement and distortions over a larger range than is likely to occur during routine clinical examination. In addition, using a clinical DCE-MRI data set with an expertly labeled suspicious region, it is shown that the proposed algorithm significantly reduces the variability of the enhancement curves at the pixel level yielding more pronounced uptake and washout phases.