Convex combinations in judgment aggregation

As location data are widely available to portable devices, trajectory tracking of moving objects has become an essential technology for most location-based services. To maintain such streaming data of location updates from mobile clients, conventional approaches such as time-based regular location updating and distance-based location updating have been used. However, these methods suffer from the large amount of data, redundant location updates, and large trajectory estimation errors due to the varying speed of moving objects. In this paper, we propose a simple but efficient online trajectory data reduction method for portable devices. To solve the problems of redundancy and large estimation errors, the proposed algorithm computes trajectory errors and finds a recent location update that should be sent to the server to satisfy the user requirements. We evaluate the proposed algorithm with real GPS trajectory data consisting of 17 201 trajectories. The intensive simulation results prove that the proposed algorithm always meets the given user requirements and exhibits a data reduction ratio of greater than 87 % when the acceptable trajectory error is greater than or equal to 10 meters.

In this paper, we propose a new method for correcting the depth image, which was obtained by applying a matching scheme to stereo images and often includes parts with large error, based on the sparsity of depth image. When the depth image is obtained by a stereo matching, a small pixel correspondence error causes large estimation errors in the depth image. Also, original depth image can be considered to have sparsity the same as many natural signals without noise. So we correct the depth image that was obtained by the stereo matching, based on the sparsity of the original depth image. First, the depth image parts with a higher probability of containing large estimation errors are selected as the areas in which the depth has relatively large difference from that which was obtained by applying the median filter to the estimated depth image. Second, the depth image is applied with the inpainting procedure based on the data sparsity [1] as shown in Fig. 1 in which the data of the selected area are treated as being lost. In particular the depth image in a region, which corresponds to an object in 3-D space, is wavelet transformed by SA-DWT (Shape-Adaptive Discrete Wavelet Transform). The smaller wavelet coefficients are truncated to zero with a threshold procedure. With decreasing threshold value, the wavelet transform, smaller coefficient zeroing, and the inverse wavelet transform processes are repeated until the processed depth image is converged. Experiments show that the proposed method is able to remove large errors in the depth image which had been obtained by the stereo matching scheme.

Quality and cloud flags of GOSAT/FTS: Fourier Transform Spectrometer onboard Greenhouse gasses Observation Satellite products taking into account cirrus clouds and thick aerosols are considered and proposed. Influence due to cirrus and thick aerosol on estimation of column CO2 and CH4 with GOSAT/FTS data is clarified. Relatively large estimation errors are observed in column CO2 and CH4 retrievals with FTS data in some atmospheric conditions. In order to find such cases, retrieval results and quality/cloud flags in the GOSAT/FTS data products are checked. Through the investigation, it is found that relatively large error is caused by convergence problem due to cirrus clouds and thick aerosols. In the proposed paper, some of the cases of which relatively large estimation error is occurred at the Saga TCCON (The Total Carbon Column Observing Network) site are investigated. Also, a comparative study is conducted between standard products provided by NASA/JPL and the Levenberg-Marquardt based least square method of column CO2 and CH4 retrieval. It is suggested that some improvements of estimation accuracy of column CO2 and CH4 retrieval with GOSAT/FTS data can be expected.

A semi-linguistic fuzzy approach to multi-actor decision-making: Application to aggregation of experts' judgments

Separating generalizable from source-specific preference heterogeneity in the fusion of revealed and stated preferences

We introduce a new algorithm, K-best-first search (KBFS), which is a generalization of the well known best-first search (BFS). In KBFS, each iteration simultaneously expands the K best nodes from the open-list (rather than just the best as in BFS). We claim that KBFS outperforms BFS in domains where the heuristic function has large errors in estimation of the real distance to the goal state or does not predict dead-ends in the search tree. We present empirical results that confirm this claim and show that KBFS outperforms BFS by a factor of 15 on random trees with dead-ends, and by a factor of 2 and 7 on the Fifteen and Twenty-Four tile puzzles, respectively. KBFS also finds better solutions than BFS and hill-climbing for the number partitioning problem. KBFS is only appropriate for finding approximate solutions with inadmissible heuristic functions.

A common goal of conventional fisheries management is to maintain fishing mortality at a rate that ensures an adequate level of lifetime egg production (LEP) for population sustainability. However, larvae from young spawners can experience higher mortality rates than larvae of older spawners, reducing the effect of egg production by young females (hereafter, maternal age effects). This reduction leads to an error in LEP that can be accounted for by reducing the fishing mortality rate, but raises the question of the magnitude of these errors if they are present but not accounted for. Calculations using parameters from a typical long-lived fish demonstrated that maternal age effects resulted in large errors in estimates of lifetime reproduction when there was a large contrast in the larval mortality rate extending over the reproductive life span. Errors were small when maternal age effects reduced the reproductive potential of only the very youngest spawners, at ages when a small fraction of females are mature. A specific example using the empirically derived maternal age effect for black rockfish (Sebastes melanops) indicated that errors in traditional management would be small for this species.

Upsurges and downsurges are calculated and plotted for a simple pump discharge line provided with an air chamber. Basic parameters such as pipeline constant, air chamber parameter, pipe wall friction, and orifice resistance are used. The results of this paper can be used to determine the necessary volume of the air chamber. Computer studies indicate that the assumption of the rigid water column and the concentration of pipe friction at the pump end of the pipeline yields reasonably good results at the pump end; however, because of these assumptions, large errors in estimation of both upsurges and downsurges occur at the midpoint and particularly at the quarter point of the pipeline. Pipe friction has a substantially different effect on surges than that of the orifice resistance; these two effects should therefore be considered separately. A differential orifice is recommended and considered; this orifice should have a low resistance to flow out of the chamber.

The analysis of nutrient budgets is a common method for assessing the biogeochemical function of estuaries including denitrification and nutrient retention rates. The Land Ocean Interactions in the Coastal Zone (LOICZ) guidelines for constructing such budgets concentrate on the simplest case where an estuary or embryment is treated as a single box which is well-mixed both vertically and horizontally and at steady-state. We show that these simplifying assumptions can lead to significant and sometimes very large errors in estimates of internal retention (or production) rates. If the load to an estuary varies significantly through the year, the use of time-averaged concentrations of nutrient and salinity to calculate retention rates is shown to cause errors of up to 30% depending on the circumstances. The second case considered examines the consequences of treating an estuary which has significant long-estuary salinity and nutrient gradients as a well-mixed box. In a simple case considered, the calculated internal production from a distributed source is underestimated by a factor of two. The errors are shown to depend on the estuary's mixing and geometrical characteristic as well as on the location of the nutrient sources. The third case considers the errors in the calculated internal retention/production rates of treating an estuary with a two-layer circulation as a single-box system. The potential errors are severe. A comparison between a one-box analysis and a two-box analysis which accounts for the true estuarine circulation shows that the two analyses can yield calculated retention rates of opposite sign. In this situation, one configuration for the estuary would appear to sequester nutrient, whereas the other would be a net exporter of nutrient.

Geoneutrino observations, first achieved by KamLAND in 2005 and followed by Borexino in 2010, have accumulated statistics and improved sensitivity for more than ten years. The uncertainty of the geoneutrino flux at the surface is now reduced to a level small enough to set useful constraints on U and Th abundances in the Bulk Silicate Earth (BSE). However, in order to make inferences on earth’s compositional model, the contributions from the local crust need to be understood within a similar uncertainty. Here we develop a new method to construct a stochastic crustal composition model utilizing Bayesian inference. While the methodology has general applicability, it incorporates all the local uniqueness in its probabilistic framework. Unlike common approaches for this type of problem, our method does not depend on crustal segmentation into upper, (middle) and lower, whose classification and boundaries are not always well defined. We also develop a new modeling method to infer rock composition distributions that conserve mass balance and therefore do not bias the results. Combined with a new vast collection of geochemical data for rock samples in the Japan arc, we apply this method to geoneutrino observation at Kamioka, Japan. Currently a difficulty remains in the handling of correlations in the flux integration; we conservatively assume maximum correlation, which leads to large flux estimation errors of 60–70%. Despite the large errors, this is the first local crustal model for geoneutrino flux prediction with probabilistic error estimation in a reproducible way.

Detention storages work for inundation contorol and water quality contorol. First flush is stored in the storage, treated after a rainfall event, and released to public water bodies like lakes, rivers, bays, etc. When rainfall forecasting by a radar is available and once a severe rainfall event is predicted, some amount of the stored first flush can be pre-released, and the resultant vacant capacity can be used for peak cut of the severe rainfall runoff to eliminate or reduce inundation volume. However large estimation error is inevitable in rainfall forecasting. In this paper, a basic study on on-line pre-release operation of a detention storage is reported, taking account of the large estimation error.

Production data analysis (PDA) is a subject to determine reservoir properties and predict future performance of single wells. It is normally conducted with either analytical methods or numerical history-matching methods. However, the analytical models normally have limited accuracy due to simplifying assumptions, while the history-match based on numerical simulations sacrifices computation load to increased accuracy. Therefore, in this study, the authors incorporated Ensemble Kalman Filter (EnKF) to improve PDA considering its superior efficiency in predicting system state and uncertainties. In this work, we applied the EnKF algorithm to single-well reservoir models to estimate permeability, skin factor, and drainage area. First, we tested the model accuracy after comparing the EnKF estimates to known reservoir properties. Next, we evaluated the cases with large estimation error and then adjusted the initial uncertainties and covariance of the static parameters. With confirmed improvements of property estimation in synthetic cases, the model is finally applied in a field study for further verifications. The results from this study confirmed that EnKF method could be an efficient solution for the modern PDA. They also indicate that accuracy issues are sometimes present when estimating skin factor and reservoir permeability simultaneously: large error exists in the property estimates, their uncertainties are overly reduced, and thus analysis and predicts are affected. By increasing the initial uncertainty bounds and adding minimum threshold values for the covariance, the property estimates could be improved, and reasonable uncertainty bounds are preserved. The methodology from this study is applicable for full-field evaluations.

Many tasks (e.g., search and summarization) result in an ordered list of items. In order to evaluate such an ordered list of items, we need to compare it with an ideal ordered list created by a human expert for the same set of items. To reduce any bias, multiple human experts are often used to create multiple ideal ordered lists. An interesting challenge in such an evaluation method is thus how to aggregate these different ideal lists to compute a single score for an ordered list to be evaluated. In this paper, we propose three new methods for aggregating multiple order judgments to evaluate ordered lists: weighted correlation aggregation, rank-based aggregation, and frequent sequential pattern-based aggregation. Experiment results on ordering sentences for text summarization show that all the three new methods outperform the state of the art average correlation methods in terms of discriminativeness and robustness against noise. Among the three proposed methods, the frequent sequential pattern-based method performs the best due to the flexible modeling of agreements and disagreements among human experts at various levels of granularity.

Dynamic firm performance and estimator choice: A comparison of dynamic panel data estimators

It is well-known in the pattern recognition community that the accuracy of classifications obtained by combining decisions made by independent classifiers can be substantially higher that the accuracy of the individual classifiers. In order to combine multiple segmentations we introduce two extensions to an expectation maximization (EM) algorithm for ground truth estimation based on multiple experts (Warfield et al., MICCAI 2002). The first method repeatedly applies the Warfield algorithm with a subsequent integration step. The second method is a multi-label extension of the Warfield algorithm. Both extensions integrate multiple segmentations into one that is closer to the unknown ground truth than the individual segmentations. In atlas-based image segmentation, multiple classifiers arise naturally by applying different registration methods to the same atlas, or the same registration method to different atlases, or both. We perform a validation study designed to quantify the success of classifier combination methods in atlas-based segmentation. By applying random deformations, a given ground truth atlas is transformed into multiple segmentations that could result from imperfect registrations of an image to multiple atlas images. We demonstrate that a segmentation produced by combining multiple individual registration-based segmentations is more accurate for the two EM methods we propose than for simple label averaging.