Non-Uniform Discretization-based Ordinal Regression for Monocular Depth Estimation of an Indoor Drone

At present, the main methods of solving the monocular depth estimation for indoor drones are the simultaneous localization and mapping (SLAM) algorithm and the deep learning algorithm. SLAM requires the construction of a depth map of the unknown environment, which is slow to calculate and generally requires expensive sensors, whereas current deep learning algorithms are mostly based on binary classification or regression. The output of the binary classification model gives the decision algorithm relatively rough control over the unmanned aerial vehicle. The regression model solves the problem of the binary classification, but it carries out the same processing for long and short distances, resulting in a decline in short-range prediction performance. In order to solve the above problems, according to the characteristics of the strong order correlation of the distance value, we propose a non-uniform spacing-increasing discretization-based ordinal regression algorithm (NSIDORA) to solve the monocular depth estimation for indoor drone tasks. According to the security requirements of this task, the distance label of the data set is discretized into three major areas—the dangerous area, decision area, and safety area—and the decision area is discretized based on spacing-increasing discretization. Considering the inconsistency of ordinal regression, a new distance decoder is produced. Experimental evaluation shows that the root-mean-square error (RMSE) of NSIDORA in the decision area is 33.5% lower than that of non-uniform discretization (NUD)-based ordinal regression methods. Although it is higher overall than that of the state-of-the-art two-stream regression algorithm, the RMSE of the NSIDORA in the top 10 categories of the decision area is 21.8% lower than that of the two-stream regression algorithm. The inference speed of NSIDORA is 3.4 times faster than that of two-stream ordinal regression. Furthermore, the effectiveness of the decoder has been proved through ablation experiments.

A method for the solution of the homogeneous inventory-production optimisation problem

The subject of this paper is the inventory-production problem, which is a one of the optimization problems in a decision area in which inventory volume and production volume are considered together. There are many approaches to this problem but for the first time, this problem is modelled by means of a capacitated graph network and a solution to the problem is proposed on the basis of this model which consists of finding the maximum flow with the minimum sum of production and inventory cost. In this article, only a solution for one kind of product for the deterministic inventory-production optimisation problem is presented and for this one kind of product, a maximum flow with a minimum cost for each considered demand period is calculated. The maximum flow with minimum cost is a solution to the homogenous inventory-production optimisation problem. The solution to the one kind of product for the inventoryproduction problem consist of maximum flow with minimum cost for a total demand from all periods, which has been taken into consideration.

Multi-Objective Virtual Power Plant Construction Model Based on Decision Area Division

Virtual power plant (VPP) is an effective technology form to aggregate the distributed energy resources (DERs), which include distributed generation (DG), energy storage (ES) and demand response (DR). The establishment of a unified and coordinated control of VPP is an important means to achieve the interconnection of energy internet. Therefore, this paper focuses on the research of VPP construction model. Firstly, a preliminary introduction on all kinds of the DERs is carried out. According to the relevant guidelines, the decision area of the VPP is carefully divided, and the decision variables representing the various resources in the area are determined. Then, in order to get a VPP with low daily average cost, good load characteristics, high degree of DG consumption and high degree of resource aggregation, a multi-objective VPP construction model based on decision area division is established, and various constraints including geographic information are considered. The improved bat algorithm based on priority selection is used to solve this model. Finally, the correctness and effectiveness of the model are verified by an example.

Using confidence inferred from pupil-size to dissect perceptual task-strategy: support for a bounded decision-formation process

During perceptual decisions subjects often rely more strongly on early rather than late sensory evidence even in tasks when both are equally informative about the correct decision. This early psychophysical weighting has been explained by an integration-to-bound decision process, in which the stimulus is ignored after the accumulated evidence reaches a certain bound, or confidence level. Here, we derive predictions about how the average temporal weighting of the evidence depends on a subject’s decision-confidence in this model. To test these predictions empirically, we devised a method to infer decision-confidence from pupil size in monkeys performing a disparity discrimination task. Our animals’ data confirmed the integration-to-bound predictions, with different internal decision-bounds accounting for differences between animals. However, the data could not be explained by two alternative accounts for early psychophysical weighting: attractor dynamics either within the decision area or due to feedback to sensory areas, or a feedforward account due to neuronal response adaptation. This approach also opens the door to using confidence more broadly when studying the neural basis of decision-making.

Constructing the MIA Dataset

Chapter Three introduces the Measure of International Authority (MIA) index on delegation and pooling. The first two sections describe how the authors aggregate scores for individual IO bodies at particular stages of decision making in particular decision areas to estimate delegation and pooling at the level of an international organization. In short, it explains the algorithm that produces delegation and pooling scores. The third section presents descriptive statistics comparing delegation and pooling over time, across IOs, and across decision areas. The chapter concludes with tables that summarize the extent of delegation and pooling, in the aggregate and by decision area, for each of seventy-six IOs in the MIA dataset. The scores tap annual variation from 1950 (or date of IO creation) to 2010 (or date of IO death).

Parameterization of Subgrid-Scale Processes

In Chapters 4 and 5, we considered a system hydrodynamics equations and boundary conditions that constitute the mathematical basis of the circulation models of the atmosphere of a scale. They contain terms describing sources (sinks) of mass and energy involved in the phase transformation of atmospheric moisture and radiative processes in the system atmosphere – the Earth. Direct inclusion of these microscale and mesoscale processes in the atmospheric circulation model is inappropriate as: 1) this leads to an increase in the total number of grid points in the decision area, and 2) not all these processes can be described by precise differential equations.

THE USE OF AHP METHOD FOR SELECTION OF SUPPLIER

To increase flexibility in today’s global marketplace is needed to remain competitive and respond to rapidly changing markets. From that point of view, supplier selection represents one of the most important functions to be performed by the purchasing department. The supplier selection is a multi-criterion problem which includes both quantitative and qualitative criteria. In order to select the best suppliers, it is necessary to make a trade off between these criteria. The article deals with supplier selection using the Analytic Hierarchy Process (AHP). AHP provides a framework for making effective decisions in complex decision situations (e.g. vendor selection), helps to simplify and accelerate the natural process of decision making. AHP is a method of decomposition of complex unstructured situation into simpler components, thus creating a hierarchical system problem. The paper describes the general design of model supplier selection using the AHP with an application of the proposed model in a manufacturing company that selects a suitable supplier of three potential suppliers. The aim of this paper is to understand the strategic operating decision area of the supplier selection process and to aid decision makers with varying degrees of importance to reach consensus in rating alternative suppliers.

Outcomes of decision speed

Purpose – This paper aims to consider decision speed’s role in the largely neglected decision area of product elimination. Design/methodology/approach – Drawing on an inter-disciplinary theoretical background (e.g. organisational, decision speed and product elimination theories), the authors develop and test a framework for decision speed’s effects on the market and financial outcomes of a stratified random sample of 175 consumer product eliminations. Findings – In contrast to decision speed research that hypothesised (and often failed to confirm) linearity, results show inverted ∪-shaped decision speed-to-decision outcomes relationships, with curvatures moderated by product importance, environmental complexity and turbulence. Research limitations/implications – Findings are suggestive of several implications for the above theories (e.g. contribution to the dialogue about performance-enhancing value of rational vs incremental decision-making; evidence that excessive decision speed may become too much of a good thing). Certain design limitations (e.g. sampling consumer goods’ manufacturers only) point at avenues for future inquiry into the product elimination decision speed-to-outcomes link. Practical implications – Managerially, the findings suggest that product eliminations’ optimal market and financial outcomes depend on a mix of speed and search in decision-making and that this mix requires adjustments to different levels of product importance, interdependencies with other decision areas of the firm and environmental turbulence. Originality/value – The paper makes a twofold contribution. It enriches decision speed research, by empirically addressing speed’s outcomes in relation to a decision area that is not necessarily strategic and represents the first explicit empirical investigation into outcomes of decision speed in product line pruning decision-making.