Caregiving services are currently the weakest part of China’s social security system for the elderly. It is well needed to investigate the fac-tors affecting the unmet care needs of the elderly with disabilities. Based on the Behavioral Model of Health Services Use (BMHSU), this paper explores the needs and influencing factors of care services for the disabled elderly in urban and rural areas using data from the 2018 Project of Social Policy Support System for Disadvantaged Families in China. The demand for care services of the disabled elderly in central and western areas is significantly higher than that in eastern, along with that in rural areas significantly higher than that in urban areas. The demands for care services of the disabled elderly in urban and rural areas are significantly affected by tendency factors, resource factors, and need factors. Urban and rural attributes, worried pension and LCI are the common influencing factors for the care service demand of the disabled elderly from economically disadvantaged families and ordinary families. The demands for care services of the disabled elderly were associated with tendencies, resources, and needs, increased chronic disease prevention and mental health services benefit caregivers.
With the further advancement of the research on marine environmental science, more and more attention has been paid to modern data monitoring technology. In order to obtain the current water quality information quickly, this paper combines the advantages of Canopy algorithm and FFCM algorithm, and proposes an improved Canopy-FFCM clustering algorithm. The algorithm firstly uses Canopy algorithm to quickly obtain the best clustering number, and then iterates through FFCM algorithm. Through the use of FCM algorithm, FFCM algorithm and improved Canopy-FFCM algorithm to conduct simulation analysis on samples for many times respectively, the experimental results show that compared with the traditional algorithm, the improved algorithm effectively reduces the time required for the analysis process and has good application value.
Considering the problems of the lack of tracking the intelligent target, which is “smart” enough to escape from the detection by maximizing the estimation error in the current tracking methods by multi-UAVs, a cooperative control method for tracking intelligent target by two UAVs is proposed based on Lyapunov guidance vector field. The mathematical model of an intelligent target is established. According to the multi-UAV distributed intelligent target state fusion estimation method, the target state information is obtained to control two UAVs to circle the target through the Lyapunov guidance vector method. The simulation results demonstrated that the method enables two UAVs to track the intelligent target stably and improve the intelligent target’s positioning accuracy effectively
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