Using a Bayesian model for bankruptcy prediction : a comparative approach

The purpose of this study is to examine the impact of the choice of cut-off points, sampling procedures, and the business cycle on the accuracy of bankruptcy prediction models. Misclassification can result in erroneous predictions leading to prohibitive costs to firms, investors and the economy. To test the impact of the choice of cut-off points and sampling procedures, three bankruptcy prediction models are assessed- Bayesian, Hazard and Mixed Logit. A salient feature of the study is that the analysis includes both parametric and nonparametric bankruptcy prediction models. A sample of firms from Lynn M. LoPucki Bankruptcy Research Database in the U. S. was used to evaluate the relative performance of the three models. The choice of a cut-off point and sampling procedures were found to affect the rankings of the various models. In general, the results indicate that the empirical cut-off point estimated from the training sample resulted in the lowest misclassification costs for all three models. Although the Hazard and Mixed Logit models resulted in lower costs of misclassification in the randomly selected samples, the Mixed Logit model did not perform as well across varying business-cycles. In general, the Hazard model has the highest predictive power. However, the higher predictive power of the Bayesian model, when the ratio of the cost of Type I errors to the cost of Type II errors is high, is relatively consistent across all sampling methods. Such an advantage of the Bayesian model may make it more attractive in the current economic environment. This study extends recent research comparing the performance of bankruptcy prediction models by identifying under what conditions a model performs better. It also allays a range of user groups, including auditors, shareholders, employees, suppliers, rating agencies, and creditors' concerns with respect to assessing failure risk

Pick2Place: Task-aware 6DoF Grasp Estimation via Object-Centric Perspective Affordance

The choice of a grasp plays a critical role in the success of downstream manipulation tasks. Consider a task of placing an object in a cluttered scene; the majority of possible grasps may not be suitable for the desired placement. In this paper, we study the synergy between the picking and placing of an object in a cluttered scene to develop an algorithm for task-aware grasp estimation. We present an object-centric action space that encodes the relationship between the geometry of the placement scene and the object to be placed in order to provide placement affordance maps directly from perspective views of the placement scene. This action space enables the computation of a one-to-one mapping between the placement and picking actions allowing the robot to generate a diverse set of pick-and-place proposals and to optimize for a grasp under other task constraints such as robot kinematics and collision avoidance. With experiments both in simulation and on a real robot we demonstrate that with our method, the robot is able to successfully complete the task of placement-aware grasping with over 89% accuracy in such a way that generalizes to novel objects and scenes.Comment: IEEE International Conference on Robotics and Automation 202

Multi-mode Microscopic Hyperspectral Imager for the Sensing of Biological Samples

In this work, we develop a multi-mode microscopic hyperspectral imager (MMHI) for the detection of biological samples in transmission imaging, reflection imaging and fluorescence mode. A hyperspectral image cube can be obtained with 5 μm spatial resolution and 3 nm spectral resolution through push-broom line scanning. To avoid possible shadows produced by the high magnification objective with a short working distance, two illumination patterns are designed to ensure the co-axiality of the illumination and detection. Three experiments for the detection of zebrafish and fingerprints and the classification of disaster-causing microalgae verify the good capability and functionality of the system. Based on the detected spectra, we can observe the impacts of β-carotene and melanin in zebrafish, hemoglobin in the fingertip, and chlorophyll in microalgae, respectively. Multi-modes can be switched freely according to the application requirement and characteristics of different samples, like transmission mode for the transparent/translucent sample, reflection mode for the opaque sample and fluorescence mode for the fluorescent sample. The MMHI system also has strong potential for the non-invasive and high-speed sensing of bio or clinical samples

Changes in Soil C, N, and P Concentrations and Stoichiometry in Karst Trough Valley Area under Ecological Restoration: The Role of Slope Aspect, Land Use, and Soil Depth

This study aims to investigate the roles of slope aspect, land use and soil depth in altering the soil organic carbon (C), total nitrogen (N), and total phosphorus (P) traits in the karst trough valley area experiencing extensive ecological restoration. A total of 54 soil samples were collected at 0–10, 10–20, and 20–30 cm soil depths from secondary forest, plantation forest, and grassland on the relatively more shaded east-facing slope and the contrasting west-facing slope, respectively. The independent and interactive effects of slope aspect, land use, and soil depth on soil C, N, and P concentrations and stoichiometry were determined. The results show that soil C and N concentrations were markedly higher on the east-facing slope than on the west-facing slope, and soil P concentrations showed an opposite trend, leading to significant differences in soil C:P and N:P but not in C:N ratios between the two aspects. Soil C and N concentrations were not affected by land use, and soil P concentration was significantly higher in plantation forest than in secondary forest and grassland. Soil C and N concentrations significantly decreased with increasing soil depth, but soil P concentration presented no significant changes with soil depth. Both the land use and soil depth did not differ in terms of their elemental stoichiometry. There were no significant interactive effects of slope aspect, land use and soil depth on soil C, N, and P traits. Our results indicate that soil C, N, and P changes are more sensitive to slope aspect rather than land use and soil depth in the karst trough valley area under ecological restoration

Light-Sheet Microscopy for Surface Topography Measurements and Quantitative Analysis

A novel light-sheet microscopy (LSM) system that uses the laser triangulation method to quantitatively calculate and analyze the surface topography of opaque samples is discussed. A spatial resolution of at least 10 μm in z-direction, 10 μm in x-direction and 25 μm in y-direction with a large field-of-view (FOV) is achieved. A set of sample measurements that verify the system′s functionality in various applications are presented. The system has a simple mechanical structure, such that the spatial resolution is easily improved by replacement of the objective, and a linear calibration formula, which enables convenient system calibration. As implemented, the system has strong potential for, e.g., industrial sample line inspections, however, since the method utilizes reflected/scattered light, it also has the potential for three-dimensional analysis of translucent and layered structures