A Combined Model and Data-Driven Approach for the Determination of Rotor Temperature in an Induction Machine

The need for protection of electrical machines comes as a demand of safety regulations in the automotive industry as well as a result of the general desire to obtain a robust and reliable electric powertrain. This paper introduces a hybrid method for estimating the temperature of the rotor of an Induction Machine (IM) based on a Nonlinear Autoregressive Network with Exogenous inputs (NARX) used as a prediction function within a particle filter. The temperature of the stator case is measured, and the information is used as an input to a NARX network and as a variable to a thermal process with first-order dynamics which serves as an observation function. Uncertainties of the NARX and thermal model are determined and used to correct the posterior estimate. Experimental data are used from a real IM test-bench and the results prove the applicability and good performance.

Active collaboration in relative observation for multi-agent visual simultaneous localization and mapping based on Deep Q Network

This article proposes a unique active relative localization mechanism for multi-agent simultaneous localization and mapping, in which an agent to be observed is considered as a task, and the others who want to assist that agent will perform that task by relative observation. A task allocation algorithm based on deep reinforcement learning is proposed for this mechanism. Each agent can choose whether to localize other agents or to continue independent simultaneous localization and mapping on its own initiative. By this way, the process of each agent simultaneous localization and mapping will be interacted by the collaboration. Firstly, a unique observation function which models the whole multi-agent system is obtained based on ORBSLAM. Secondly, a novel type of Deep Q Network called multi-agent systemDeep Q Network (MAS-DQN) is deployed to learn correspondence between Q value and state–action pair, abstract representation of agents in multi-agent system is learned in the process of collaboration among agents. Finally, each agent must act with a certain degree of freedom according to MAS-DQN. The simulation results of comparative experiments prove that this mechanism improves the efficiency of cooperation in the process of multi-agent simultaneous localization and mapping.

Collaborative Smartphone-Based User Positioning in a Multiple-User Context Using Wireless Technologies

For the localization of multiple users, Bluetooth data from the smartphone is able to complement Wi-Fi-based methods with additional information, by providing an approximation of the relative distances between users. In practice, both positions provided by Wi-Fi data and relative distance provided by Bluetooth data are subject to a certain degree of noise due to the uncertainty of radio propagation in complex indoor environments. In this study, we propose and evaluate two approaches, namely Non-temporal and Temporal ones, of collaborative positioning to combine these two cohabiting technologies to improve the tracking performance. In the Non-temporal approach, our model establishes an error observation function in a specific interval of the Bluetooth and Wi-Fi output. It is then able to reduce the positioning error by looking for ways to minimize the error function. The Temporal approach employs an extended error model that takes into account the time component between users’ movements. For performance evaluation, several multi-user scenarios in an indoor environment are set up. Results show that for certain scenarios, the proposed approaches attain over 40% of improvement in terms of average accuracy.

POTENTIAL CLINICAL CONSEQUENCES OF ADMINISTRATIVE ISSUES REGARDING MEDICATION IN HOME CARE PATIENTS

Home care professionals observe drug-related problems (DRPs) as administrative problems (e.g. inconsistent registration of (changes in) drug prescription) and side effects which may have clinical consequences for older patients. This study aims to determine the potential clinical impact of administrative problems. A retrospective descriptive study was performed, using reports of home care professionals of the eHOME system (system that assist monitoring/reporting DRPs). Administrative problems of a one year period were assessed by three experts on potential discomfort/clinical deterioration using a 3-point scale. 309 DRPs of 120 out of 451 patients (age ≥65) were assessed. Problems involved undelivered medication administration record lists (n=103,33.3%), inconsistent registration of drug prescription (n=188,60.9%) and insufficient drug delivery (n=18,5.8%). 58.2% of the DRPs had the potential to cause moderate to severe discomfort or clinical deterioration. The results underlines the importance of the observation function of home care professionals and the need to improve pharmaceutical administration issues.

Working Tools Study for JiaoLong Manned Submersible

The remarkable progress in deep submergence science with manned submersibles in the past 50 years has made it possible for us to directly explore the inaccessible underwater extreme environment. Basic research carried out at depths over 1,000 m in the deep ocean has provided dramatic and unique insights into some of the most compelling scientific questions ever posed. Deep research manned submersibles have been widely recognized as indispensable platforms for conducting deep-sea research. Whereas all deep-sea submersibles share the unique feature of direct observation function by scientists and pilots from the cabin, all manned submersibles are equipped with different tools to implement a wide range of jobs in different exploration purposes. These can directly affect productivity and each dive's outcomes, such that it would be meaningful to study the samplers, sensors, and other devices that have been installed on the different deep-sea research manned submersibles around the world. This article will also introduce the research and development status of the JiaoLong manned submersible's operational tools, which have been researched and tested during the sea trials and test operational phase over the past 9 years. Based on developed technologies, state-of-the-art tools are essential to achieve a high-efficiency use for each dive. The article brings forward discussion and suggestions for the development of JiaoLong's operational tools, followed by a conclusion from the perspective of JiaoLong's operation team.