A self-learning particle swarm optimizer for global optimization problems

Particle swarm optimization (PSO) has been shown as an effective tool for solving global optimization problems. So far, most PSO algorithms use a single learning pattern for all particles, which means that all particles in a swarm use the same strategy. This monotonic learning pattern may cause the lack of intelligence for a particular particle, which makes it unable to deal with different complex situations. This paper presents a novel algorithm, called self-learning particle swarm optimizer (SLPSO), for global optimization problems. In SLPSO, each particle has a set of four strategies to cope with different situations in the search space. The cooperation of the four strategies is implemented by an adaptive learning framework at the individual level, which can enable a particle to choose the optimal strategy according to its own local fitness landscape. The experimental study on a set of 45 test functions and two real-world problems show that SLPSO has a superior performance in comparison with several other peer algorithms.     

Environmental-aware virtual data center network

Cloud computing services have recently become a ubiquitous service delivery model, covering a wide range of applications from personal file sharing to being an enterprise data warehouse. Building green data center networks providing cloud computing services is an emerging trend in the Information and Communication Technology (ICT) industry, because of Global Warming and the potential GHG emissions resulting from cloud services. As one of the first worldwide initiatives provisioning ICT services entirely based on renewable energy such as solar, wind and hydroelectricity across Canada and around the world, the GreenStar Network (GSN) was developed to dynamically transport user services to be processed in data centers built in proximity to green energy sources, reducing Greenhouse Gas (GHG) emissions of ICT equipments. Regarding the current approach, which focuses mainly in reducing energy consumption at the micro-level through energy efficiency improvements, the overall energy consumption will eventually increase due to the growing demand from new services and users, resulting in an increase in GHG emissions. Based on the cooperation between Mantychore FP7 and the GSN, our approach is, therefore, much broader and more appropriate because it focuses on GHG emission reductions at the macro-level. This article presents some outcomes of our implementation of such a network model, which spans multiple green nodes in Canada, Europe and the USA. The network provides cloud computing services based on dynamic provision of network slices through relocation of virtual data centers.     

Bead-based polymerase chain reaction on a microchip

We present a bead-based approach to microfluidic polymerase chain reaction (PCR), enabling fluorescent detection and sample conditioning in a single microchamber. Bead-based PCR, while not extensively investigated in microchip format, has been used in a variety of bioanalytical applications in recent years. We leverage the ability of bead-based PCR to accumulate fluorescent labels following DNA amplification to explore a novel DNA detection scheme on a microchip. The microchip uses an integrated microheater and temperature sensor for rapid control of thermal cycling temperatures, while the sample is held in a microchamber fabricated from (poly)dimethylsiloxane and coated with Parylene. The effects of key bead-based PCR parameters, including annealing temperature and concentration of microbeads in the reaction mixture, are studied to achieve optimized device sensitivity and detection time. The device is capable of detecting a synthetically prepared section of the Bordetella pertussis genome in as few as 10 temperature cycles with times as short as 15?min. We then demonstrate the use of the procedure in an integrated device; capturing, amplifying, detecting, and purifying template DNA in a single microfluidic chamber. These results show that this method is an effective method of DNA detection which is easily integrated in a microfluidic device to perform additional steps such as sample pre-conditioning.     

Extrinsic calibration of a camera and laser range finder using a new calibration structure of a plane with a triangular hole

Sensor fusion of a camera and laser range finder is important for the autonomous navigation of mobile robots. Finding the transformation between the camera and laser range finder is the first necessary step for the fusion of information. Many algorithms have been proposed, but these tend to require many different steps in order to achieve reliable and accurate results. A calibration structure that has triangular hole on its plane is proposed for the extrinsic calibration of a camera and laser range finder. Locations of laser scan data that are invisible on the calibration plane can be determined using property on the proposed calibration structure. First, we classify the laser scan data into two groups where one is on the plane and the other is off the plane. Then, we determine the absolute location of the laser scan data on the plane through a search of the parameters of the line. Finally, we can establish 3D-3D correspondences between the camera and laser range finder. Extrinsic calibration between a camera and laser range finder is found using a conventional 3D-3D transformation computing algorithm. Keywords: Calibration k]camera k]extrinsic calibration k]laser range finder     

A study on the dynamic characteristics of the Korean Yi-dynasty bell type structure

The dynamic characteristics of the Korean Yi-dynasty bell type structure, including the acoustic effects, are analyzed both theoretically and experimentally. The numerical solutions of natural frequencies and mode shape for membrane and flexural behavior are obtained by using the NASTRAN program for the finite element method with plate shell elements of triangular and quadrilateral types. Test bells, A and B types similar to the Kap-Sa bell in Kong-Ju chosen among typical Korean Yi-dynasty bells, are manufactured on different scales to the original bell. To consider the effects of the variation of the structural dimension on the dynamic response, these bells are analyzed with respect to the variation of the thickness of the wall and the bottom rim and the asymmetric Dang-Jwas. The impact method with the Fast Fourier Transform Analyzer is adopted to experimentally assess the dynamic response. Results are in good agreement with the numerical solutions.     

Particular behavior of spindle thermal deformation by thermal bending

Thermally induced errors reduce the accuracy in precision machining, and a great deal of research has been presented on compensation for these errors in machine tools. However, during the transition period after commencing or stopping spindle rotation, thermal deformation behavior is very complex. In particular, the y-directional movement of the vertical machining center cannot be explained by thermal expansion alone because of the relationship between deformation and temperature. Thermal bending that is generated from the thermal gradient in the structure causes this movement. In the research described in this paper, a theoretical explanation and an experimental verification is given for the particular behavior of spindle thermal deformation. As it is not easy to map the relationship of the compensation model, separation of the steady from the non-steady state in the mapping process is strongly recommended.     

Modelling of the mist formation in a segmented grinding wheel system

It has been found that using a segmented grinding wheel with a fluid chamber can significantly minimise the quantity of coolant while improving the ground surface integrity. The present investigation aims to explore the fluid flow mechanism in such a wheel system. To this end, the Weber theory for Newtonian jet instability was applied to quantitatively determine the contribution of coolant flow rate to mist and ligament modes. A semi-analytical model was then developed to predict the mist flow rate by taking into account both the grinding parameters and fluid properties. It was shown that the model prediction was in good agreement with experimental measurements. Because of the comprehensive integration of variables in the formulation, the model provides a good fundamental understanding of the mist formation and offers a practical guideline for the selection and use coolant in minimising the mist flow rate.     

Fluctuating NMDA Receptor Subunit Levels in Perirhinal Cortex Relate to Their Dynamic Roles in Object Memory Destabilization and Reconsolidation

Reminder cues can destabilize consolidated memories, rendering them modifiable before they return to a stable state through the process of reconsolidation. Older and stronger memories resist this process and require the presentation of reminders along with salient novel information in order to destabilize. Previously, we demonstrated in rats that novelty-induced object memory destabilization requires acetylcholine (ACh) activity at M₁ muscarinic receptors. Other research predominantly has focused on glutamate, which modulates fear memory destabilization and reconsolidation through GluN2B- and GluN2A-containing NMDARs, respectively. In the current study, we demonstrate the same dissociable roles of GluN2B- and N2A-containing NMDARs in perirhinal cortex (PRh) for object memory destabilization and reconsolidation when boundary conditions are absent. However, neither GluN2 receptor subtype was required for novelty-induced destabilization of remote, resistant memories. Furthermore, GluN2B and GluN2A subunit proteins were upregulated selectively in PRh 24 h after learning, but returned to baseline by 48 h, suggesting that NMDARs, unlike muscarinic receptors, have only a temporary role in object memory destabilization. Indeed, activation of M₁ receptors in PRh at the time of reactivation effectively destabilized remote memories despite inhibition of GluN2B-containing NMDARs. These findings suggest that cholinergic activity at M₁ receptors overrides boundary conditions to destabilize resistant memories when other established mechanisms are insufficient.     

Choline Acetyltransferase Induces the Functional Regeneration of the Salivary Gland in Aging SAMP1/Kl -/- Mice

Salivary gland dysfunction induces salivary flow reduction and a dry mouth, and commonly involves oral dysfunction, tooth structure deterioration, and infection through reduced salivation. This study aimed to investigate the impact of aging on the salivary gland by a metabolomics approach in an extensive aging mouse model, SAMP1/Klotho -/- mice. We found that the salivary secretion of SAMP1/Klotho -/- mice was dramatically decreased compared with that of SAMP1/Klotho WT (+/+) mice. Metabolomics profiling analysis showed that the level of acetylcholine was significantly decreased in SAMP1/Klotho -/- mice, although the corresponding levels of acetylcholine precursors, acetyl-CoA and choline, increased. Interestingly, the mRNA and protein expression of choline acetyltransferase (ChAT), which is responsible for catalyzing acetylcholine synthesis, was significantly decreased in SAMP1/Klotho -/- mice. The overexpression of ChAT induced the expression of salivary gland functional markers (α–amylase, ZO-1, and Aqua5) in primary cultured salivary gland cells from SAMP1/Klotho +/+ and -/- mice. In an in vivo study, adeno-associated virus (AAV)-ChAT transduction significantly increased saliva secretion compared with the control in SAMP1/Klotho -/- mice. These results suggest that the dysfunction in acetylcholine biosynthesis induced by ChAT reduction may cause impaired salivary gland function