Wide Baseline Matching Using Support Vector Regression

  In this paper, we newly solve wide baseline matching using support vector regression (SVR). High correct ratio initial matches are used to train SVR relationships, obtained by matching large-scale SIFT features and discarding some mismatches by our improved topological filtering scheme; and new matches are searched near the prediction given by trained SVR relationships. Both indoor and outdoor environments image pairs under wide baseline condition are tested, experiment results show that our algorithm automatically gain large numbers of accurate point correspondences

Minimizing risk probability for infinite discounted piecewise deterministic Markov decision processes

summary:The purpose of this paper is to study the risk probability problem for infinite horizon piecewise deterministic Markov decision processes (PDMDPs) with varying discount factors and unbounded transition rates. Different from the usual expected total rewards, we aim to minimize the risk probability that the total rewards do not exceed a given target value. Under the condition of the controlled state process being non-explosive is slightly weaker than the corresponding ones in the previous literature, we prove the existence and uniqueness of a solution to the optimality equation, and the existence of the risk probability optimal policy by using the value iteration algorithm. Finally, we provide two examples to illustrate our results, one of which explains and verifies our conditions and the other shows the computational results of the value function and the risk probability optimal policy

Ask more, know better: Reinforce-Learned Prompt Questions for Decision Making with Large Language Models

Large language models (LLMs) demonstrate their promise in tackling complicated practical challenges by combining action-based policies with chain of thought (CoT) reasoning. Having high-quality prompts on hand, however, is vital to the framework's effectiveness. Currently, these prompts are handcrafted utilizing extensive human labor, resulting in CoT policies that frequently fail to generalize. Human intervention is also required in order to develop grounding functions that ensure low-level controllers appropriately process CoT reasoning. In this paper, we take the first step towards a fully integrated end-to-end framework for task-solving in real settings employing complicated reasoning. To that purpose, we offer a new leader-follower bilevel framework capable of learning to ask relevant questions (prompts) and subsequently undertaking reasoning to guide the learning of actions to be performed in an environment. A good prompt should make introspective revisions based on historical findings, leading the CoT to consider the anticipated goals. A prompt-generator policy has its own aim in our system, allowing it to adapt to the action policy and automatically root the CoT process towards outputs that lead to decisive, high-performing actions. Meanwhile, the action policy is learning how to use the CoT outputs to take specific actions. Our empirical data reveal that our system outperforms leading methods in agent learning benchmarks such as Overcooked and FourRoom

Effects of oxygen enrichment on diesel spray flame soot formation in O₂/Ar atmosphere

In this study, diesel spray combustion at oxygen-enriched conditions (oxygen volume fraction of 21–70 %) with argon dilution is experimentally investigated in a constant-volume combustion chamber. Optical diagnostics are employed to study flame development, stabilization, and soot formation at oxygen-enriched conditions. To further verify the experimental observations, two-stage Lagrangian simulations are used to analyze the effects of oxygen on the formation and oxidation of soot precursors, polycyclic aromatic hydrocarbons. Results show that replacing nitrogen in air by argon leads to a 50 % reduction of the flame lift-off length, an increased soot flame temperature by 300 K, and higher soot concentrations. Flame morphology and structure still follow the classic conventional diesel combustion model in the oxygen range of 21–40 %, while changes are observed when oxygen levels are higher than 50 %. The width and length of the soot flame are shortened, and chemiluminescence from intermediate species like CO dominates the flame natural luminosity at the spray head, where the flame temperature reaches near 3000 K. Soot reduction mechanisms at high-degree oxygen-enrichment conditions are investigated. The intrinsic mixing-limited combustion of diesel sprays leads to unavoidable fuel-rich areas locally, but the shortened flame lift-off length and sufficient oxygen supply confines soot-forming conditions to a smaller, upstream region. The residence time of fuel parcels in this confined soot-forming area is shortened due to the larger local spray velocity. Thereafter, fuel parcels enter a high-temperature fuel-lean region, where the formed soot is oxidized rapidly.</p

Effects of oxygen enrichment on diesel spray flame soot formation in O₂/Ar atmosphere

In this study, diesel spray combustion at oxygen-enriched conditions (oxygen volume fraction of 21–70 %) with argon dilution is experimentally investigated in a constant-volume combustion chamber. Optical diagnostics are employed to study flame development, stabilization, and soot formation at oxygen-enriched conditions. To further verify the experimental observations, two-stage Lagrangian simulations are used to analyze the effects of oxygen on the formation and oxidation of soot precursors, polycyclic aromatic hydrocarbons. Results show that replacing nitrogen in air by argon leads to a 50 % reduction of the flame lift-off length, an increased soot flame temperature by 300 K, and higher soot concentrations. Flame morphology and structure still follow the classic conventional diesel combustion model in the oxygen range of 21–40 %, while changes are observed when oxygen levels are higher than 50 %. The width and length of the soot flame are shortened, and chemiluminescence from intermediate species like CO dominates the flame natural luminosity at the spray head, where the flame temperature reaches near 3000 K. Soot reduction mechanisms at high-degree oxygen-enrichment conditions are investigated. The intrinsic mixing-limited combustion of diesel sprays leads to unavoidable fuel-rich areas locally, but the shortened flame lift-off length and sufficient oxygen supply confines soot-forming conditions to a smaller, upstream region. The residence time of fuel parcels in this confined soot-forming area is shortened due to the larger local spray velocity. Thereafter, fuel parcels enter a high-temperature fuel-lean region, where the formed soot is oxidized rapidly.</p