Learning Disentangled Representation with Mutual Information Maximization for Real-Time UAV Tracking

Efficiency has been a critical problem in UAV tracking due to limitations in computation resources, battery capacity, and unmanned aerial vehicle maximum load. Although discriminative correlation filters (DCF)-based trackers prevail in this field for their favorable efficiency, some recently proposed lightweight deep learning (DL)-based trackers using model compression demonstrated quite remarkable CPU efficiency as well as precision. Unfortunately, the model compression methods utilized by these works, though simple, are still unable to achieve satisfying tracking precision with higher compression rates. This paper aims to exploit disentangled representation learning with mutual information maximization (DR-MIM) to further improve DL-based trackers' precision and efficiency for UAV tracking. The proposed disentangled representation separates the feature into an identity-related and an identity-unrelated features. Only the latter is used, which enhances the effectiveness of the feature representation for subsequent classification and regression tasks. Extensive experiments on four UAV benchmarks, including UAV123@10fps, DTB70, UAVDT and VisDrone2018, show that our DR-MIM tracker significantly outperforms state-of-the-art UAV tracking methods

KwaiYiiMath: Technical Report

Recent advancements in large language models (LLMs) have demonstrated remarkable abilities in handling a variety of natural language processing (NLP) downstream tasks, even on mathematical tasks requiring multi-step reasoning. In this report, we introduce the KwaiYiiMath which enhances the mathematical reasoning abilities of KwaiYiiBase1, by applying Supervised Fine-Tuning (SFT) and Reinforced Learning from Human Feedback (RLHF), including on both English and Chinese mathematical tasks. Meanwhile, we also constructed a small-scale Chinese primary school mathematics test set (named KMath), consisting of 188 examples to evaluate the correctness of the problem-solving process generated by the models. Empirical studies demonstrate that KwaiYiiMath can achieve state-of-the-art (SOTA) performance on GSM8k, CMath, and KMath compared with the similar size models, respectively.Comment: technical report. arXiv admin note: text overlap with arXiv:2306.16636 by other author

Enhanced growth rate of atmospheric particles from sulfuric acid

In the present-day atmosphere, sulfuric acid is the most important vapour for aerosol particle formation and initial growth. However, the growth rates of nanoparticles (<10 nm) from sulfuric acid remain poorly measured. Therefore, the effect of stabilizing bases, the contribution of ions and the impact of attractive forces on molecular collisions are under debate. Here, we present precise growth rate measurements of uncharged sulfuric acid particles from 1.8 to 10 nm, performed under atmospheric conditions in the CERN (European Organization for Nuclear Research) CLOUD chamber. Our results show that the evaporation of sulfuric acid particles above 2 nm is negligible, and growth proceeds kinetically even at low ammonia concentrations. The experimental growth rates exceed the hard-sphere kinetic limit for the condensation of sulfuric acid. We demonstrate that this results from van derWaals forces between the vapour molecules and particles and disentangle it from charge-dipole interactions. The magnitude of the enhancement depends on the assumed particle hydration and collision kinetics but is increasingly important at smaller sizes, resulting in a steep rise in the observed growth rates with decreasing size. Including the experimental results in a global model, we find that the enhanced growth rate of sulfuric acid particles increases the predicted particle number concentrations in the upper free troposphere by more than 50 %.Peer reviewe

Molecular understanding of the suppression of new-particle formation by isoprene

Nucleation of atmospheric vapours produces more than half of global cloud condensation nuclei and so has an important influence on climate. Recent studies show that monoterpene (C10H16) oxidation yields highly oxygenated products that can nucleate with or without sulfuric acid. Monoterpenes are emitted mainly by trees, frequently together with isoprene (C5H8), which has the highest global emission of all organic vapours. Previous studies have shown that isoprene suppresses new-particle formation from monoterpenes, but the cause of this suppression is under debate. Here, in experiments performed under atmospheric conditions in the CERN CLOUD chamber, we show that isoprene reduces the yield of highly oxygenated dimers with 19 or 20 carbon atoms - which drive particle nucleation and early growth - while increasing the production of dimers with 14 or 15 carbon atoms. The dimers (termed C-20 and C-15, respectively) are produced by termination reactions between pairs of peroxy radicals (RO2 center dot) arising from monoterpenes or isoprene. Compared with pure monoterpene conditions, isoprene reduces nucleation rates at 1.7 nm (depending on the isoprene = monoterpene ratio) and approximately halves particle growth rates between 1.3 and 3.2 nm. However, above 3.2 nm, C-15 dimers contribute to secondary organic aerosol, and the growth rates are unaffected by isoprene. We further show that increased hydroxyl radical (OH center dot) reduces particle formation in our chemical system rather than enhances it as previously proposed, since it increases isoprene-derived RO2 center dot radicals that reduce C-20 formation. RO2 center dot termination emerges as the critical step that determines the highly oxygenated organic molecule (HOM) distribution and the corresponding nucleation capability. Species that reduce the C-20 yield, such as NO, HO2 and as we show isoprene, can thus effectively reduce biogenic nucleation and early growth. Therefore the formation rate of organic aerosol in a particular region of the atmosphere under study will vary according to the precise ambient conditions.Peer reviewe

Nonlinear Model Predictive Control with Terminal Cost for Autonomous Vehicles Trajectory Follow

This paper presents a nonlinear model predictive control with terminal cost (NMPC–WTC) algorithm and its open/closed-loop system analysis and simulation validation for accurate and stable path tracking of autonomous vehicles. The path tracking issue is formulated as an optimal control problem. In order to improve the squeezing phenomenon of traditional NMPC, a discrete-time nonlinear model predictive controller with terminal cost is then designed, in which the state error of last step is augmented. The cost function of NMPC–WTC consists of two parts: (1) the traditional NMPC cost function responding to tracking errors and controller output, and (2) the augmented terminal cost. The algorithm was implemented on CasADi numerical optimization framework, which is free, open-source and developed for nonlinear optimization. The open-loop and closed-loop simulation results are then presented to demonstrate the improved performance in tracking accuracy and stability compared to traditional model predictive controller

Research on bridge cranes Energy-saving index reduction based on rough set theory

Bridge crane is one of the most widely used cranes in our country, which is indispensable equipment for material conveying in the modern production. The most important indicator of crane performances is energysaving. So it is of importance to research on the bridge cranes energysaving assessment. Thus the establishment of assessment index system is a necessary task. Rough set theory is applied widely for researching on incomplete and uncertain information processing. Through reducing the  properties by rough set theory, redundant properties are removed and an optimized index assessment system can be obtained.In this paper,establishing  the index system of the bridge crane based on  the full life cycle of the bridge crane firstly. Secondly,defining the decision attribute and the condition attributes. Thirdly,using rough set theory to reduce  the index system of the bridge crane.Finally,an optimized index assessment system of the bridge can be obtained. The research lays the foundation for solving weight for the next step. DOI: http://dx.doi.org/10.11591/telkomnika.v11i12.279