Structural health monitoring system based on multi-agent coordination and fusion for large structure

In practical applications of structural health monitoring technology, a large number of distributed sensors are usually adopted to monitor the big dimension structures and different kinds of damage. The monitored structures are usually divided into different sub-structures and monitored by different sensor sets. Under this situation, how to manage the distributed sensor set and fuse different methods to obtain a fast and accurate evaluation result is an important problem to be addressed deeply. In the paper, a multi-agent fusion and coordination system is presented to deal with the damage identification for the strain distribution and joint failure in the large structure. Firstly, the monitoring system is adopted to distributedly monitor two kinds of damages, and it self-judges whether the static load happens in the monitored sub-region, and focuses on the static load on the sub-region boundary to obtain the sensor network information with blackboard model. Then, the improved contract net protocol is used to dynamically distribute the damage evaluation module for monitoring two kinds of damage uninterruptedly. Lastly, a reliable assessment for the whole structure is given by combing various heterogeneous classifiers strengths with voting-based fusion. The proposed multi-agent system is illustrated through a large aerospace aluminum plate structure experiment. The result shows that the method can significantly improve the monitoring performance for the large-scale structure.     

A study on the monitoring model development for quality measurement of internet traffic

The recent trend of integration among new network services such as the long-term evolution (LTE) based on internet protocol (IP) needs reputable analyses and prediction information on the internet traffic. The IP along with increased internet traffics due to expanding new service platforms such as smartphones will reflect policies such as network QoS according to new services. The establishment of monitoring methods and analysis plans is thus required for the development of internet traffics that will analyze their status and predict their future. The paper with the speed of Internet traffic model is developed for monitoring the state of the experiment and verified. The problem is that the proposed service Internet service provider (ISP) to resolve the conflict between the occurrences can be considerably Internet traffic and that the state of data may be helpful in understanding. The paper advancement policy to reflect the network traffic volume of Internet services and users irradiation with increased traffic due to the development and management of the analysis was carried out experimental measurements.     

Effects of SO2 on selective catalytic reduction of NO with NH3 over a TiO2 photocatalyst

The effect of SO₂ gas was investigated on the activity of the photo-assisted selective catalytic reduction of nitrogen monoxide (NO) with ammonia (NH₃) over a TiO₂ photocatalyst in the presence of excess oxygen (photo-SCR). The introduction of SO₂ (300 ppm) greatly decreased the activity of the photo-SCR at 373 K. The increment of the reaction temperature enhanced the resistance to SO₂ gas, and at 553 K the conversion of NO was stable for at least 300 min of the reaction. X-ray diffraction, FTIR spectroscopy, thermogravimetry and differential thermal analysis, x-ray photoelectron spectroscopy (XPS), elemental analysis and N₂ adsorption measurement revealed that the ammonium sulfate species were generated after the reaction. There was a strong negative correlation between the deposition amount of the ammonium sulfate species and the specific surface area. Based on the above relationship, we concluded that the deposition of the ammonium sulfate species decreased the specific surface area by plugging the pore structure of the catalyst, and the decrease of the specific surface area resulted in the deactivation of the catalyst.     

Multiobjective PSO based adaption of neural network topology for pixel classification in satellite imagery

The proposed work involves the multiobjective PSO based adaption of optimal neural network topology for the classification of multispectral satellite images. It is per pixel supervised classification using spectral bands (original feature space). This paper also presents a thorough experimental analysis to investigate the behavior of neural network classifier for given problem. Based on 1050 number of experiments, we conclude that following two critical issues needs to be addressed: (1) selection of most discriminative spectral bands and (2) determination of optimal number of nodes in hidden layer. We propose new methodology based on multiobjective particle swarm optimization (MOPSO) technique to determine discriminative spectral bands and the number of hidden layer node simultaneously. The accuracy with neural network structure thus obtained is compared with that of traditional classifiers like MLC and Euclidean classifier. The performance of proposed classifier is evaluated quantitatively using Xie-Beni and β indexes. The result shows the superiority of the proposed method to the conventional one.     

The Interplay of Modulus,Strength, and Ductility in Adhesive Design Using Biomimetic Polymer Chemistry

High‐performance adhesives require mechanical properties tuned to demands of the surroundings. A mismatch in stiffness between substrate and adhesive leads to stress concentrations and fracture when the bonding is subjected to mechanical load. Balancing material strength versus ductility, as well as considering the relationship between adhesive modulus and substrate modulus, creates stronger joints. However, a detailed understanding of how these properties interplay is lacking. Here, a biomimetic terpolymer is altered systematically to identify regions of optimal bonding. Mechanical properties of these terpolymers are tailored by controlling the amount of a methyl methacrylate stiff monomer versus a similar monomer containing flexible poly(ethylene glycol) chains. Dopamine methacrylamide, the cross‐linking monomer, is a catechol moiety analogous to 3,4‐dihydroxyphenylalanine, a key component in the adhesive proteins of marine mussels. Bulk adhesion of this family of terpolymers is tested on metal and plastic substrates. Incorporating higher amounts of poly(ethylene glycol) into the terpolymer introduces flexibility and ductility. By taking a systematic approach to polymer design, the region in which material strength and ductility are balanced in relation to the substrate modulus is found, thereby yielding the most robust joints.     

The control of sea lice in Atlantic salmon by selective breeding

Sea lice threaten the welfare of farmed Atlantic salmon and the sustainability of fish farming across the world. Chemical treatments are the major method of control but drug resistance means that alternatives are urgently needed. Selective breeding can be a cheap and effective alternative. Here, we combine experimental trials and diagnostics to provide a practical protocol for quantifying resistance to sea lice. We then combined quantitative genetics with epidemiological modelling to make the first prediction of the response to selection, quantified in terms of reduced need for chemical treatments. We infected over 1400 young fish with Lepeophtheirus salmonis, the most important species in the Northern Hemisphere. Mechanisms of resistance were expressed early in infection. Consequently, the number of lice per fish and the ranking of families were very similar at 7 and 17 days post infection, providing a stable window for assessing susceptibility to infection. The heritability of lice numbers within this time window was moderately high at 0.3, confirming that selective breeding is viable. We combined an epidemiological model of sea lice infection and control on a salmon farm with genetic variation in susceptibility among individuals. We simulated 10 generations of selective breeding and examined the frequency of treatments needed to control infection. Our model predicted that substantially fewer chemical treatments are needed to control lice outbreaks in selected populations and chemical treatment could be unnecessary after 10 generations of selection. Selective breeding for sea lice resistance should reduce the impact of sea lice on fish health and thus substantially improve the sustainability of Atlantic salmon production.     

Remote Steering of Self‐Propelling Microcircuits by Modulated Electric Field

The principles and design of “active” self‐propelling particles that can convert energy, move directionally on their own, and perform a certain function is an emerging multidisciplinary research field, with high potential for future technologies. A simple and effective technique is presented for on‐demand steering of self‐propelling microdiodes that move electroosmotically on water surface, while supplied with energy by an external alternating (AC) field. It is demonstrated how one can control remotely the direction of diode locomotion by electronically modifying the applied AC signal. The swimming diodes change their direction of motion when a wave asymmetry (equivalent to a DC offset) is introduced into the signal. The data analysis shows that the ability to control and reverse the direction of motion is a result of the electrostatic torque between the asymmetrically polarized diodes and the ionic charges redistributed in the vessel. This novel principle of electrical signal‐coded steering of active functional devices, such as diodes and microcircuits, can find applications in motile sensors, MEMs, and microrobotics.     

Alloying behavior and novel properties of CoCrFeNiMn high-entropy alloy fabricated by mechanical alloying and spark plasma sintering

An equiatomic CoCrFeNiMn high-entropy alloy was synthesized by mechanical alloying (MA) and spark plasma sintering (SPS). During MA, a solid solution with refined microstructure of 10 nm which consists of a FCC phase and a BCC phase was formed. After SPS consolidation, only one FCC phase can be detected in the HEA bulks. The as-sintered bulks exhibit high compressive strength of 1987 MPa. An interesting magnetic transition associated with the structure coarsening and phase transformation was observed during SPS process.