UAV flight control method based on deep reinforcement learning

Aiming at the intelligent perception and obstacle avoidance of UAV for the environment, an obstacle-avoidance flight decision method of UAV based on image information is proposed in this paper. Add Gate Recurrent Unit (GRU) to the neural network, and use the deep reinforcement learning algorithm DDPG to train the model. The special gates structure of GRU is utilized to memorize historical information, and acquire the variation law of the environment of UAV from the time sequential data including image information and UAV position and speed information to realize the dynamic perception of obstacles. Moreover, the basic framework and training method of the model are introduced, and the generalization ability of the model is tested. The experimental results show that the proposed method has better generalization ability and better adaptability to the environment

Design and simulation of a testing fixture for planar magnetic levitation system control using switched reluctance actuator

Author name used in this publication: Norbert C. CheungRefereed conference paper2008-2009 > Academic research: refereed > Refereed conference paperVersion of RecordPublishe

Integral sliding mode control with integral switching gain for magnetic levitation apparatus

Author name used in this publication: Norbert C. CheungRefereed conference paper2008-2009 > Academic research: refereed > Refereed conference paperVersion of RecordPublishe

A novel hybrid teaching learning based multi-objective particle swarm optimization

How to obtain a good convergence and well-spread optimal Pareto front is still a major challenge for most meta-heuristic multi-objective optimization (MOO) methods. In this paper, a novel hybrid teaching learning based particle swarm optimization (HTL-PSO) with circular crowded sorting (CCS), named HTL-MOPSO, is proposed for solving MOO problems. Specifically, the new HTL-MOPSO combines the canonical PSO search with a teaching-learning-based optimization (TLBO) algorithm in order to promote the diversity and improve search ability. Also, CCS technique is developed to improve the diversity and spread of solutions when truncating the external elitism archive. The performance of HTL-MOPSO algorithm was tested on several well-known benchmarks problems and compared with other state-of-the-art MOO algorithms in respect of convergence and spread of final solutions to the true Pareto front. Also, the individual contributions made by the strategies of HTL-PSO and CCS are analyzed. Experimental results validate the effectiveness of HTL-MOPSO and demonstrate its superior ability to find solutions of better spread and diversity, while assuring a good convergence

Towards run-time monitoring of web services conformance to business-level agreements

Web service behaviour is currently specified in a mixture of ways, often using methods that are only partially complete. These range from static functional specifications, based on interfaces in WSDL and preconditions in RIF, to business process simulations using executable process-based models such as BPEL, to detailed quality of service (QoS) agreements laid down in a service level agreement (SLA). This paper recognises that something similar to a SLA is required at the higher business level to govern the contract between service producers, brokers and consumers. We call this a business level agreement (BLA) and within this framework, seek to unify disparate aspects of functional specification, QoS and run-time verification. We propose that the method for validating a web service with respect to its advertised BLA should be based on run-time service monitoring. This is a position paper towards defining these goals

Transcriptional and Post-Transcriptional Regulation of Autophagy

Autophagy is a widely conserved process in eukaryotes that is involved in a series of physiological and pathological events, including development, immunity, neurodegenerative disease, and tumorigenesis. It is regulated by nutrient deprivation, energy stress, and other unfavorable conditions through multiple pathways. In general, autophagy is synergistically governed at the RNA and protein levels. The upstream transcription factors trigger or inhibit the expression of autophagyor lysosome-related genes to facilitate or reduce autophagy. Moreover, a significant number of noncoding RNAs (microRNA, circRNA, and lncRNA) are reported to participate in autophagy regulation. Finally, post-transcriptional modifications, such as RNA methylation, play a key role in controlling autophagy occurrence. In this review, we summarize the progress on autophagy research regarding transcriptional regulation, which will provide the foundations and directions for future studies on this self-eating process

Integrating Hydrologic Modeling Web Services With Online Data Sharing to Prepare, Store, and Execute Hydrologic Models

Web based applications, web services, and online data and model sharing technology are becoming increasingly available to support hydrologic research. This promises benefits in terms of collaboration, computer platform independence, and reproducibility of modeling workflows and results. In this research, we designed an approach that integrates hydrologic modeling web services with an online data sharing system to support web-based simulation for hydrologic models. We used this approach to integrate example systems as a case study to support reproducible snowmelt modeling for a test watershed in the Colorado River Basin, USA. We demonstrated that this approach enabled users to work within an online environment to create, describe, share, discover, repeat, modify, and analyze the modeling work. This approach encourages collaboration and improves research reproducibility. It can also be adopted or adapted to integrate other hydrologic modeling web services with data sharing systems for different hydrologic models

Gossamer Superconductivity near Antiferromagnetic Mott Insulator in Layered Organic Conductors

Layered organic superconductors are on the verge of the Mott insulator. We use Gutzwiller variational method to study a Hubbard model including a spin exchange coupling term. The ground state is found to be a Gossamer superconductor at small on-site Coulomb repulsion U and an antiferromagnetic Mott insulator at large U, separated by a first order phase transition. Our theory is qualitatively consistent with major experiments reported in organic superconductors.Comment: 5 pages, 3 figure

Antioxidant N-acetylcysteine attenuates the reduction of brg1 protein expression in the myocardium of type 1 diabetic rats

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