Multi-scale Space-time Registration of Growing Plants
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In this paper, we introduce a new method for the space-time registration of a growing plant that is based on matching the plant at different geometric scales. The proposed method starts with the creation of a topological skeleton of the plant at each time step. This skeleton is then used to segment the plant into parts that we call branches. Then these branches are further divided into smaller segments that possess a simple geometric structure. These segments are matched between two time steps using a random forest classifier based on their topological and geometric features. Then, for each pair of segments matched, a point-wise registration is devised using a non-rigid registration method based on a local ICP. We applied our method to various types of plants, including arabidopsis, tomato plant and maize. We established three different metrics for 3D point-wise shape correspondence to test the accuracy, continuity, and cycle consistency of the mapping. We then compared our method with the state-of-the-art. Our results show that our approach achieves better or similar results with a shorter running time.Weak consistency
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This article considers simultaneous attainability of consistency and availability. The approaches to determining the maximum possible levels of accessibility for different consistency models are compared. The necessity of introducing quantitative metrics for these two indicators and review the prior articles with quantitative estimates of consistency is advocated. The importance of this problem is confirmed, and directions for modeling the parameters of the applied problem using numerical experiments are proposed.
Weak consistency
Quantitative Analysis
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If a statistical or a voting decision procedure is used by several subpopulations and if each reaches an identical conclusion, then one might expect this conclusion to be the outcome for the full group. It is shown that this property fails to hold for large classes of decision procedures. The geometric reasons why the consistency does not hold are described. A general theorem is given to characterize the procedures that satisfy this property of “weak consistency”.
Weak consistency
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Consistency of treatment effects across different regions in multiregional clinical trials (MRCTs) has been an important question for the regulatory authorities. Many consistency definitions are proposed in literature. One of the definitions of consistency is expressed as qualitative consistency, whereas inconsistency is defined as qualitative treatment by region interaction. This article focuses on the qualitative consistency and extends Gail-Simon and Sasabuchi's one-sided multivariate likelihood ratio tests. Simulations are used to evaluate operating characteristics of these qualitative consistency assessment approaches. For a given number of regions, the guideline for setting significance level, and consistency cut-off are explored.
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This paper investigates subject matching in the National University of Singapore (NUS). The matching process is conducted in a primary market and a secondary market. In the primary market, students and departments are matched by a centralized matching procedure, based on their submitted preferences. Students who are not satisfied with their allocations in the primary market can choose to join the secondary market. By comparing matching results in these two markets, we show how a centralized matching procedure and a decentralized matching procedure can work together to produce a desirable outcome, especially in a many-to-many matching market.
Optimal matching
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We develop inference for a two-sided matching model where the characteristics of agents on one side of the market are endogenous due to pre-matching investments. The model can be used to measure the impact of frictions in labour markets using a single cross-section of matched employer-employee data. The observed matching of workers to firms is the outcome of a discrete, two-sided matching process where firms with heterogeneous preferences over education sequentially choose workers according to an index correlated with worker preferences over firms. The distribution of education arises in equilibrium from a Bayesian game: workers, knowing the distribution of worker and firm types, invest in education prior to the matching process. Although the observed matching exhibits strong cross-sectional dependence due to the matching process, we propose an asymptotically valid inference procedure that combines discrete choice methods with simulation.
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Once the sectoral growth-rates of the economy are outlined by the Central Planning Authorities, the problem that follows is how to break them up for the different regions. Such problems can be tackled both in a consistent framework and in an optimization scheme. We propose to construct a consistency model only. We include in it both inter-sectoral consistency and inter-regional consistency.
Time consistency
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