Cognitive assisted living ambient system: a survey

The demographic change towards an aging population is creating a significant impact and introducing drastic challenges to our society. We therefore need to find ways to assist older people to stay independently and prevent social isolation of these population. Information and Communication Technologies (ICT) provide various solutions to help older adults to improve their quality of life, stay healthier, and live independently for a time. Ambient Assisted Living (AAL) is a field to investigate innovative technologies to provide assistance as well as healthcare and rehabilitation to impaired seniors. The paper provides a review of research background and technologies of AAL

ROS Based Multi-sensor Navigation of Intelligent Wheelchair

Our society is moving towards an ageing society and the number of population with physical impairments and disabilities will increase dramatically. It is necessary to provide mobility support to these people so that they can live independently at home and integrated into the society. This paper presents a ROS (Robot Operating System) based multi-sensor navigation for an intelligent wheelchair that can help the elderly and disabled people. ROS provides an easy to use framework for rapid system development at a reduced cost. Some experimental results are given in the paper to demonstrate the feasibility and performance of the developed system

Multi-layered map based navigation and interaction for an intelligent wheelchair

Intelligent wheelchair is a paradigm of assisted living applications for elderly and disabled people. Its autonomous navigation and human-robot interaction is the major challenge. The previous intelligent wheelchair research has been mainly focused on geometric map based navigation, which is computational expensive in a large scale environment. This paper proposes the use of multi-layered maps for navigation and interaction of an intelligent wheelchair. The semantic information can improve the efficiency of path planning and navigation as well as extend the capability of task planning for the wheelchair. Some experimental results are given to demonstrate the feasibility and performance of the proposed approach

Characteristics of convective storm activity during the warm season over Anhui Province based on radar mosaic climatology and the possible causes

In order to understand the radar climatology characteristics of convective activity over Anhui Province, the climatological distribution and influencing factors of convective activity during the warm season (May-September) were investigated using Doppler radar mosaic data from five Next Generation Weather Radars and ERA5 reanalysis data between 2015 and 2020. Results indicate that: (1) There are obvious inter-monthly variations and spatial differences of convective activity during the warm season. The convective activity peaks during the Meiyu period, with the highest frequency in June and July, followed by May and August, and the lowest in September. The region with the highest convective in July and July is mainly distributed in the southwest-northeast direction. (2) It is found that the diurnal variation of convective number is bimodally distributed in summer (June-August), with the main peak in the afternoon and a subpeak in the early morning. In June, the peak convective activity mainly occurs in the early morning, which is related to the strengthening of low-level southwest airflow from night to early morning, and thus enhancing the moisture flux convergence in Anhui. In July, the peak convective activity appears in the afternoon, with a subpeak in the early morning. Note that the main peak is stronger and the duration is longer, which is related to the enhancement of convective available potential energy in Anhui in July. The second peak in early morning is also caused by the strengthening of the low-level southwest airflow, which is similar to that in June, but the intensity is weaker. Convective activity in August exhibits a single peak in the afternoon with the most significant diurnal variation, which shows a typical afternoon thermal convection type

Study of Top Dead Center Measurement and Correction Method in a Diesel Engine

Abstract: The thermal loss angle error analysis and maximum pressure determination method analysis were conducted first. Then the polytropic exponent method, the inflection point analysis, the loss function method and the symmetry method were utilized under different rotating speed, load and cooling water temperature, to calculate TDC in D6114 diesel engine and the results were compared with TDC position measured under the same condition with direct method of measurement. The study proved that (1) thermal loss angle of the diesel engine ranges from -1.0 ~ -0.6°CA; (2) Thermal loss angle is mainly affected by rotating speed and is reducing when rotate speed increases;(3) the symmetry method is generally the optimum for calculating the thermal loss angle of automotive diesel engines, with an error within 0.2°CA

Towards ROS Based Multi-robot Architecture for Ambient Assisted Living

The demographic trend is towards ageing in our society and the number of people with physical impairments and disabilities will increase dramatically in the future. It is necessary to deliver advanced healthcare and services to these people so that they can live independently and stay well at home throughout their lifespan. This paper presents a multi-robot architecture for ambient assisted living of the elderly and disabled, which is based on the robot operating system (ROS). A communication bridge is proposed for different means of human robot interaction, and ROS provides a framework for rapid system development with a reduced cost. Some experimental results are given in the paper to demonstrate the feasibility and performance of the proposed system. © 2013 IEEE

A Multi-Level Attention Model for Remote Sensing Image Captions

The task of image captioning involves the generation of a sentence that can describe an image appropriately, which is the intersection of computer vision and natural language. Although the research on remote sensing image captions has just started, it has great significance. The attention mechanism is inspired by the way humans think, which is widely used in remote sensing image caption tasks. However, the attention mechanism currently used in this task is mainly aimed at images, which is too simple to express such a complex task well. Therefore, in this paper, we propose a multi-level attention model, which is a closer imitation of attention mechanisms of human beings. This model contains three attention structures, which represent the attention to different areas of the image, the attention to different words, and the attention to vision and semantics. Experiments show that our model has achieved better results than before, which is currently state-of-the-art. In addition, the existing datasets for remote sensing image captioning contain a large number of errors. Therefore, in this paper, a lot of work has been done to modify the existing datasets in order to promote the research of remote sensing image captioning