PAIDD: a hybrid P2P-based architecture for improving data distribution in social networks

Rapid growth in social networks(SNs)presents a unique scalability challenge for SN operators because of the massive amounts of data distribution among large number of concurrent online users.A request from any user may trigger hundreds of server activities to generate a customized page and which has already become a huge burden.Based on the theoretical model and analytical study considering realistic network scenarios,this article proposes a hybrid P2P-based architecture called PAIDD.PAIDD fulfills effective data distribution primarily through P2P connectivity and social graph among users but with the help of central servers.To increase system efficiency,PAIDD performs optimized content prefetching based on social interactions among users.PAIDD chooses interaction as the criteria because user’s interaction graph is measured to be much smaller than the social graph.Our experiments confirm that PAIDD ensures satisfactory user experience without incurring extensive overhead on clients’network.More importantly,PAIDD can effectively achieve one order of magnitude of load reduction at central servers.     

Prediction of the Magnetic Variation Field Based on Multiple Geomagnetic Components

A new method for the prediction of the geomagnetic variation time series based on multiple geomagnetic components is presented in this paper. The method used the data of multiple geomagnetic components (H, D, Z) with different kinds of combination (H, Z; H, D; H, D, Z) from a series of geomagnetic stations to predict the Z component (both in single-step prediction and multi-steps prediction). The comparison and analysis between the new method and the method based on single Z component are done in the paper. The results indicate that the new prediction method based on components (Z, H) has a higher precision than the model based on single Z component.     

Memory Nonfragile Output Feedback Robust MPC for Polytopic Time-delayed Systems with Constraints

International Journal of Control, Automation and Systems - This paper investigates memory nonfragile mixed-objective output feedback robust model predictive control (OFRMPC) for a class of...     

Fault detection and diagnostic method of diesel engine by combining rule-based algorithm and BNs/BPNNs

The stable operation of diesel engine is critical to the normal production of the industry, and the prevention, monitoring, and identification of faults are of great significance. At present, the fault research on diesel engines still has some defects, such as only few types of faults diagnosis are identified, the accuracy of fault diagnosis is still low, and fault identification is located at a fixed speed. A novel fault detection and diagnostic method of diesel engine by combining rule-based algorithm and Bayesian networks (BNs) or Back Propagation neural networks (BPNNs) is proposed. The signals are processed by wavelet threshold denoising and ensemble empirical mode decomposition. The signal-sensitive feature values are extracted from the decomposed intrinsic mode function. Seven faults are roughly identified using rule-based algorithm and finely identified using BNs or BPNNs. Results show the proposed fault diagnosis method has a good diagnostic performance for a wide range of rotation speeds when the training data for BNs and BPNNs are from fixed speeds. In addition, the influences of the layers of decomposed signals, sensor noise and external excitation interference on the fault diagnostic performance are also researched.     

Enhanced photoelectrochemical properties of TiO2 nanorod arrays decorated with CdS nanoparticles

TiO₂ nanorod arrays (TiO₂ NRAs) sensitized with CdS nanoparticles were fabricated via successive ion layer adsorption and reaction (SILAR), and TiO₂ NRAs were obtained by oxidizing Ti NRAs obtained through oblique angle deposition. The TiO₂ NRAs decorated with CdS nanoparticles exhibited excellent photoelectrochemical and photocatalytic properties under visible light, and the one decorated with 20 SILAR cycles CdS nanoparticles shows the best performance. This can be attributed to the enhanced separation of electrons and holes by forming heterojunctions of CdS nanoparticles and TiO₂ NRAs. This provides a promising way to fabricate the material for solar energy conversion and wastewater degradation.     

Highly efficient phosphate diester hydrolysis and DNA interaction by a new unsymmetrical FeIIINiII model complex

A new heterodinuclear mixed valence complex [Fe^IIINi^II(BPBPMP)(OAc)₂]ClO₄ 1 with the unsymmetrical N₅O₂ donor ligand 2-bis[{(2-pyridylmethyl)-aminomethyl}-6-{(2-hydroxybenzyl)(2-pyridylmethyl)}-aminomethyl]-4-methylphenol (H₂BPBPMP) has been synthesized and characterized. 1 crystallizes in the monoclinic system, space group P2₁/n, a=12.497(2), b=18.194(4), c=16.929(3) Å, β=94.11(3)°, V=3839.3(12) ų and has an Fe^IIINi^II(μ-phenoxo)-bis(μ-carboxylato) core. Solution studies of 1 indicate that a pH-induced change in the bridging acetate occurs and the formation of an active [(OH)Fe^III(μ-OH)Ni^II(OH₂)]⁺ species as the catalyst for phosphate diester hydrolysis and DNA interaction is proposed. In addition, the results presented here suggest that Ni^II would be a good candidate as a substitute of M^II in purple acid phosphatases.     

A novel method for estimating the track-soil parameters based on Kalman and improved strong tracking filters

A tracked vehicle has been widely used in exploring unknown environments and military fields. In current methods for suiting soil conditions, soil parameters need to be given and the traction performance cannot always be satisfied on soft soil. To solve the problem, it is essential to estimate track-soil parameters in real-time. Therefore, a detailed mathematical model is proposed for the first time. Furthermore, a novel algorithm which is composed of Kalman filter (KF) and improved strong tracking filter (STF) is developed for online track-soil estimation and named as KF–ISTF. By this method, the KF is used to estimate slip parameters, and the ISTF is used to estimate motion states. Then the key soil parameters can be estimated by using a suitable soil model. The experimental results show that equipped with the estimation algorithm, the proposed model can be used to estimate the track-soil parameters, and make the traction performance satisfied with soil conditions.     

A Novel Inclined Excitation Method for Crack Detection of Non-Ferromagnetic Materials Using Eddy Current Thermography

Strength of Materials - A novel inclined excitation method for eddy current thermography was proposed to eliminate the “fuzzy effect” together with the wavelet singularity-based image...     

Synthesis of plate-like single-crystal hydroxyapatite rods with c-axis orientation by biotemplate small intestinal submucosa

Since hydroxyapatite crystals are characteristically c-axis orientation on the surface of vertebrate long bone, c-axis orientation HAP biomimetic synthesized will find extensive applications in long bone growth, remodeling and fracture healing. In this paper, plate-like single-crystal HAP rods with c-axis orientation was successfully synthesized at bone mineralization conditions in vivo, with small intestinal submucosa membrane as biomineralization template. The samples were characterized by XRD, FIIR, SEM, TEM and EDS to unveil the phase structure, composition, morphology, and a plausible growth mechanism was proposed. The results showed that morphology of samples changed from flower-like to plate-like with extension reaction time from 1 day to 10 days. The plate-like HAp rods were single-crystal with c-axis orientation. A unit of plate-like HAP rods is about 70 µm and the width is 4 µm. Phase composition transformed from octocalcium phosphate and HAp biphase to HAp phase with very little octocalcium phosphate phase. Finally, biocompatibility of the samples was evaluated by CCK8. The samples without significant cytotoxicity conformed to the need for substitute materials of bone regeneration.