Genetic learning particle swarm optimization

Social learning in particle swarm optimization (PSO) helps collective efficiency, whereas individual reproduction in genetic algorithm (GA) facilitates global effectiveness. This observation recently leads to hybridizing PSO with GA for performance enhancement. However, existing work uses a mechanistic parallel superposition and research has shown that construction of superior exemplars in PSO is more effective. Hence, this paper first develops a new framework so as to organically hybridize PSO with another optimization technique for “learning.” This leads to a generalized “learning PSO” paradigm, the *L-PSO. The paradigm is composed of two cascading layers, the first for exemplar generation and the second for particle updates as per a normal PSO algorithm. Using genetic evolution to breed promising exemplars for PSO, a specific novel *L-PSO algorithm is proposed in the paper, termed genetic learning PSO (GL-PSO). In particular, genetic operators are used to generate exemplars from which particles learn and, in turn, historical search information of particles provides guidance to the evolution of the exemplars. By performing crossover, mutation, and selection on the historical information of particles, the constructed exemplars are not only well diversified, but also high qualified. Under such guidance, the global search ability and search efficiency of PSO are both enhanced. The proposed GL-PSO is tested on 42 benchmark functions widely adopted in the literature. Experimental results verify the effectiveness, efficiency, robustness, and scalability of the GL-PSO

Adaptive particle swarm optimization

An adaptive particle swarm optimization (APSO) that features better search efficiency than classical particle swarm optimization (PSO) is presented. More importantly, it can perform a global search over the entire search space with faster convergence speed. The APSO consists of two main steps. First, by evaluating the population distribution and particle fitness, a real-time evolutionary state estimation procedure is performed to identify one of the following four defined evolutionary states, including exploration, exploitation, convergence, and jumping out in each generation. It enables the automatic control of inertia weight, acceleration coefficients, and other algorithmic parameters at run time to improve the search efficiency and convergence speed. Then, an elitist learning strategy is performed when the evolutionary state is classified as convergence state. The strategy will act on the globally best particle to jump out of the likely local optima. The APSO has comprehensively been evaluated on 12 unimodal and multimodal benchmark functions. The effects of parameter adaptation and elitist learning will be studied. Results show that APSO substantially enhances the performance of the PSO paradigm in terms of convergence speed, global optimality, solution accuracy, and algorithm reliability. As APSO introduces two new parameters to the PSO paradigm only, it does not introduce an additional design or implementation complexity

Cloud computing resource scheduling and a survey of its evolutionary approaches

A disruptive technology fundamentally transforming the way that computing services are delivered, cloud computing offers information and communication technology users a new dimension of convenience of resources, as services via the Internet. Because cloud provides a finite pool of virtualized on-demand resources, optimally scheduling them has become an essential and rewarding topic, where a trend of using Evolutionary Computation (EC) algorithms is emerging rapidly. Through analyzing the cloud computing architecture, this survey first presents taxonomy at two levels of scheduling cloud resources. It then paints a landscape of the scheduling problem and solutions. According to the taxonomy, a comprehensive survey of state-of-the-art approaches is presented systematically. Looking forward, challenges and potential future research directions are investigated and invited, including real-time scheduling, adaptive dynamic scheduling, large-scale scheduling, multiobjective scheduling, and distributed and parallel scheduling. At the dawn of Industry 4.0, cloud computing scheduling for cyber-physical integration with the presence of big data is also discussed. Research in this area is only in its infancy, but with the rapid fusion of information and data technology, more exciting and agenda-setting topics are likely to emerge on the horizon

Heregulin β-1 Induces Loss of Cell-Cell Contact and Enhances Expression of MUC1 at the Cell Surface in HCC2998 and MKN45-1 Cells

Signal transduction and cell responses after stimulation with heregulin β-1 (HRG) are examined in HCC2998 and MKN45-1 cells, which have been used for a model system to study the formation of signet ring carcinomas, one of poorly differentiated adenocarcinomas. HRG stimulation causes rounding of the cells, responding to HRG. The adherens junction, which is present in the control cells, is disrupted and cell-cell interaction is lost after stimulation. Inhibition of phosphatidylinositol (PI)-3 kinase or p38 MAP kinase blocked this reaction, which indicates that the PI-3 kinase-p38 MAP kinase pathway is required for this reaction. Inhibition of the p38 MAP kinase pathway resulted in immediate restoration of cell-cell interaction. This result indicates that signaling for adherent molecules is strictly regulated by growth factor signaling. Expression of MUC1 at the cell surface is also observed and found to be expressed only after HRG stimulation. The total amount of MUC1 remains unchanged, suggesting that this amount is not due to induction of gene expression but to translocation of MUC1 from the inner membrane to the plasma membrane. This reaction is independent of the cytohesin pathway but dependent on PI-3 kinase activity. In addition to these reactions, HRG stimulates cell growth of both HCC2998 and MKN45-1 cells, depending on the ERK pathway given that the MEK inhibitor abolishes this effect. Therefore, HRG induces various reactions in HCC2998 and MKN45-1 cells by different pathways. These reactions are all related to characteristics of tumors, which implicates that HRG signaling can contribute to the formation of tumors

Quasiparticle states and quantum interference induce by magnetic impurities on a two-dimensional topological superconductor

We theoretically study the effect of localized magnetic impurities on two-dimensional topological superconductor (TSC). We show that the local density of states (LDOS) can be tuned by the effective exchange field $m$, the chemical potential $\mu$ of TSC, and the distance $\Delta r$ as well as relative spin angle $\alpha$ between two impurities. The changes in $\Delta r$ between two impurities alter the interference and result in significant modifications to the bonding and antibonding states. Furthermore, the bound-state spin LDOS induced by single and double magnetic impurity scattering, the quantum corrals, and the quantum mirages are also discussed. Finally, we briefly compare the impurities in TSC with those in topological insulators.Comment: J. Phys.: Condens. Matter 24, 145502 (2012

Design And Fabrication of Condenser Microphone Using Wafer Transfer And Micro-electroplating Technique

A novel fabrication process, which uses wafer transfer and micro-electroplating technique, has been proposed and tested. In this paper, the effects of the diaphragm thickness and stress, the air-gap thickness, and the area ratio of acoustic holes to backplate on the sensitivity of the condenser microphone have been demonstrated since the performance of the microphone depends on these parameters. The microphone diaphragm has been designed with a diameter and thickness of 1.9 mm and 0.6 $\mu$m, respectively, an air-gap thickness of 10 $\mu$m, and a 24% area ratio of acoustic holes to backplate. To obtain a lower initial stress, the material used for the diaphragm is polyimide. The measured sensitivities of the microphone at the bias voltages of 24 V and 12 V are -45.3 and -50.2 dB/Pa (at 1 kHz), respectively. The fabricated microphone shows a flat frequency response extending to 20 kHz.Comment: Submitted on behalf of EDA Publishing Association (http://irevues.inist.fr/handle/2042/16838

Fever Screening at Airports and Imported Dengue

Airport fever screening in Taiwan, July 2003–June 2004, identified 40 confirmed dengue cases. Results obtained by capture immunoglobulin (Ig) M and IgG enzyme-linked immunoassay, real time 1-step polymerase chain reaction, and virus isolation showed that 33 (82.5%) of 40 patients were viremic. Airport fever screening can thus quickly identify imported dengue cases