Search

Heuristic optimization algorithms have been proved to be powerful in solving nonlinear and complex optimization problems; therefore, many effective optimization algorithms have been applied to solve optimization problems in real-world scenarios. This paper presents a modification of the recently proposed Gaining–Sharing Knowledge (GSK)-based algorithm and applies it to optimize resource scheduling in the Internet of Vehicles (IoV). The GSK algorithm simulates different phases of human life in gaining and sharing knowledge, which is mainly divided into the senior phase and the junior phase. The individual is initially in the junior phase in all dimensions and gradually moves into the senior phase as the individual interacts with the surrounding environment. The main idea used to improve the GSK algorithm is to divide the initial population into different groups, each searching independently and communicating according to two main strategies. Opposite-based learning is introduced to correct the direction of convergence and improve the speed of convergence. This paper proposes an improved algorithm, named parallel opposition-based Gaining–Sharing Knowledge-based algorithm (POGSK). The improved algorithm is tested with the original algorithm and several classical algorithms under the CEC2017 test suite. The results show that the improved algorithm significantly improves the performance of the original algorithm. When POGSK was applied to optimize resource scheduling in IoV, the results also showed that POGSK is more competitive.

Supplemental material, sj-pdf-1-jag-10.1177_0733464820972888 for Personal Determinants of Burden Among Indonesian Female Caregivers of Older Adults in Taiwan by Carol Troy, Tjin Anna, John J. Perez C. and Jeng Liu in Journal of Applied Gerontology

Supplemental material, sj-pdf-1-jag-10.1177_0733464820972888 for Personal Determinants of Burden Among Indonesian Female Caregivers of Older Adults in Taiwan by Carol Troy, Tjin Anna, John J. Perez C. and Jeng Liu in Journal of Applied Gerontology

Optical turbulence plays an important role in the propagation of electromagnetic waves through the atmosphere because it broadens and distorts the optical beam. A variety of optical, thermal, and acoustic instruments are used to detect the atmospheric turbulence and an acoustic echosounder has proven to be a valuable tool to probe the fine dynamic structure of atmospheric turbulence within first hundred meters above the surface. The first planar acoustic echosounder constructed at the Naval Postgraduate School was by Weingartner and Wroblewski, under Walters' supervision. Moxcey later modified this design by reducing the number of drivers from 25 to 19 and placing the drivers closer together into a hexagonal, close-packed array. This thesis explored the potential sources of the transducer ringing and implemented solutions to the problem. Additionally, we also improved the receiving sensitivity of the echosounder and lowered the electronics noise when receiving. Finally, we applied these techniques to another array assembled with new drivers to improve its performance compared to the previous echosounder array, while measuring and quantifying the level of improvement achieved. http://archive.org/details/improvementofnco109451221 Lieutenant Commander, Republic of China Navy Approved for public release; distribution is unlimited.