“…In this process, heuristic algorithms based on natural body algorithms, have been used to guide the synthesis of rare earth-doped luminescent powders with high quantum yield. Heuristic algorithms include the genetic algorithm (GA), particle swarm optimization (PSO), and simulated annealing (SA) ( Hopper and Turton, 2001 ; Hamza et al, 2017 ; Ozdemir and Karaboga, 2019 ). GA is a global random search optimization algorithm that uses the “survival of the fittest” mechanism to derive relationships between the material properties and the mole percentage of each raw material, and is often used to guide chemical synthesis optimization problems ( Katoch et al, 2021 ).…”
Up-conversion (or anti-Stokes) luminescence refers to the phenomenon whereby materials emit high energy, short-wavelength light upon excitation at longer wavelengths. Lanthanide-doped up-conversion nanoparticles (Ln-UCNPs) are widely used in biomedicine due to their excellent physical and chemical properties such as high penetration depth, low damage threshold and light conversion ability. Here, the latest developments in the synthesis and application of Ln-UCNPs are reviewed. First, methods used to synthesize Ln-UCNPs are introduced, and four strategies for enhancing up-conversion luminescence are analyzed, followed by an overview of the applications in phototherapy, bioimaging and biosensing. Finally, the challenges and future prospects of Ln-UCNPs are summarized.
“…In this process, heuristic algorithms based on natural body algorithms, have been used to guide the synthesis of rare earth-doped luminescent powders with high quantum yield. Heuristic algorithms include the genetic algorithm (GA), particle swarm optimization (PSO), and simulated annealing (SA) ( Hopper and Turton, 2001 ; Hamza et al, 2017 ; Ozdemir and Karaboga, 2019 ). GA is a global random search optimization algorithm that uses the “survival of the fittest” mechanism to derive relationships between the material properties and the mole percentage of each raw material, and is often used to guide chemical synthesis optimization problems ( Katoch et al, 2021 ).…”
Up-conversion (or anti-Stokes) luminescence refers to the phenomenon whereby materials emit high energy, short-wavelength light upon excitation at longer wavelengths. Lanthanide-doped up-conversion nanoparticles (Ln-UCNPs) are widely used in biomedicine due to their excellent physical and chemical properties such as high penetration depth, low damage threshold and light conversion ability. Here, the latest developments in the synthesis and application of Ln-UCNPs are reviewed. First, methods used to synthesize Ln-UCNPs are introduced, and four strategies for enhancing up-conversion luminescence are analyzed, followed by an overview of the applications in phototherapy, bioimaging and biosensing. Finally, the challenges and future prospects of Ln-UCNPs are summarized.
“…According to the nature of the algorithm, the optimization algorithms can be categorized into three categories: deterministic algorithms, stochastic algorithms and hybrid algorithms which is a mixture of deterministic and stochastic algorithms. Figure 2 illustrates the categories of this classification [ 27 ]. Fig.…”
Computed tomography (CT) helps the radiologist in the rapid and correct detection of a person infected with the coronavirus disease 2019 (COVID-19), and this by showing the presence of the ground-glass opacity in the lung of with the virus. Tracking the evolution of the spread of the ground-glass opacity (GGO) in the lung of the person infected with the virus needs to study more than one image in different times. The various CT images must be registration to identify the evolution of the ground glass in the lung and to facilitate the study and identification of the virus. Due to the process of registration images is essentially an improvement problem, we present in this paper a new HPSGWO algorithm for registration CT images of a lung infected with the COVID-19. This algorithm is a hybridization of the two algorithms Particle swarm optimization (PSO) and Grey wolf optimizer (GWO). The simulation results obtained after applying the algorithm to the test images show that the proposed approach achieved high-precision and robust registration compared to other methods such as GWO, PSO, Firefly Algorithm (FA), and Crow Searcha Algorithms (CSA).
“…GA is an abstractionoriented search method that is based on Darwin's theory of evolution and natural selection of biological systems and represents them in mathematical operators such as crossover or recombination, mutation, selection of the fittest individual, and reproduction. There are thousands of research papers and hundreds of books on GA because GA is so successful in solving a wide variety of optimization problems [35], [36]. The basic algorithm is summarized below [33]- [37]:…”
Polyphase filter banks (PFBs) are the most preferred multirate structures for subband coding in Digital Signal Processing (DSP) and communication. For PFB design, there are many important design parameters such as filter length and frequency selectivity. Also, to realize the desired frequency response in designs, stopband and passband attenuation are of considerable importance. In PFB design, researchers and practitioners frequently use iterative and meta-heuristic optimization methods. Heuristic techniques have a significant problem-solving ability in continuous and discrete solution space. Therefore, they give better results than other suggested methods, and their performance depends on the control parameters. In this study, Artificial Bee Colony (ABC) algorithm was employed for suggested design problem of PFB. In the first stage, the control parameters of the ABC algorithm were examined to improve the performance of the proposed PFB problem. In the second stage, the analysis was carried out by changing filter lengths (8-256) and filter band frequencies (0.3-0.7/0.4-0.6). All results obtained were also compared with the Particle Swarm Optimization algorithm (PSO) and the Genetic algorithm (GA). Finally, a DSP application of PFB was carried out according to best results achieved by the ABC algorithm for filter lengths and frequencies.
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