Effect of Mg2+-Fe3+ replacement on physical and electrical properties of the system MgxZn0.3Fe2.7−xO4±δ

X-ray analysis and d.c. electrical resistivity have been studied for the system Mg _x Zn_0.3Fe_2.7–x O_4± . The apparent density, X-ray density and porosity were also studied. It was found that the lattice parameter is independent of the substitution of iron ions with magnesium ions. Density, X-ray density and porosity do depend on replacement of the iron ions by magnesium ions. Two regions of resistivity were found; one region indicates the p-type and another one the n-type. This behaviour depends on the excess or deficiency and type of valency of the iron ions in the composition.     

Stability analysis of bilinear systems under aperiodic sampled-data control

This note considers the problem of local stability of bilinear systems with aperiodic sampled-data linear state feedback control. The sampling intervals are time-varying and upper bounded. It is shown that the feasibility of some linear matrix inequalities (LMIs), implies the local asymptotic stability of the sampled-data system in an ellipsoidal region containing the equilibrium. The method is based on the analysis of contractive invariant sets, and it is inspired by the dissipativity theory. The results are illustrated by means of numerical examples.     

Optimal Machine Learning Enabled Performance Monitoring for Learning Management Systems

Learning Management System (LMS) is an application software that is used in automation, delivery, administration, tracking, and reporting of courses and programs in educational sector. The LMS which exploits machine learning (ML) has the ability of accessing user data and exploit it for improving the learning experience. The recently developed artificial intelligence (AI) and ML models helps to accomplish effective performance monitoring for LMS. Among the different processes involved in ML based LMS, feature selection and classification processes find beneficial. In this motivation, this study introduces Glowworm-based Feature Selection with Machine Learning Enabled Performance Monitoring (GSO-MFWELM) technique for LMS. The key objective of the proposed GSO-MFWELM technique is to effectually monitor the performance in LMS. The proposed GSO-MFWELM technique involves GSO-based feature selection technique to select the optimal features. Besides, Weighted Extreme Learning Machine (WELM) model is applied for classification process whereas the parameters involved in WELM model are optimally fine-tuned with the help of Mayfly Optimization (MFO) algorithm. The design of GSO and MFO techniques result in reduced computation complexity and improved classification performance. The presented GSO-MFWELM technique was validated for its performance against benchmark dataset and the results were inspected under several aspects. The simulation results established the supremacy of GSO-MFWELM technique over recent approaches with the maximum classification accuracy of 0.9589.     

A classification-based privacy-preserving decision-making for secure data sharing in Internet of Things assisted applications

The introduction of the Internet of Things (IoT) paradigm serves as pervasive resource access and sharing platform for different real-time applications. Decentralized resource availability, access, and allocation provide a better quality of user experience regardless of the application type and scenario. However, privacy remains an open issue in this ubiquitous sharing platform due to massive and replicated data availability. In this paper, privacy-preserving decision-making for the data-sharing scheme is introduced. This scheme is responsible for improving the security in data sharing without the impact of replicated resources on communicating users. In this scheme, classification learning is used for identifying replicas and accessing granted resources independently. Based on the trust score of the available resources, this classification is recurrently performed to improve the reliability of information sharing. The user-level decisions for information sharing and access are made using the classification of the resources at the time of availability. This proposed scheme is verified using the metrics access delay, success ratio, computation complexity, and sharing loss.     

Computational modeling of flow over an ogee spillway

This paper presents an investigation into the hydraulics of regular ogee-profile spillways. The free-surfaces of the fluid for several flow heads as measured in the hydraulics laboratory are used as benchmarks. The finite element computational fluid dynamics software, ADINA, was used to predict the free surface over an ogee spillway and thus model the flow field. Since the actual flow is turbulent the k-ε flow model was used. For the cases considered in this paper, ADINA predicted reasonable free surface results that are consistent with general flow characteristics over spillways. The results are also in close agreement with measured free-surface profiles over the entire length of the spillway.     

On the importance of specific interface area in clay nanocomposites of PMMA filled with synthetic nano-mica

In clay nanocomposites, the specific interface area is the key factor determining potential improvements of properties. Nevertheless, in most systematic studies of nanocomposites little emphasis is put on assuring and characterizing dispersion quality. To probe the influence of dispersion quality, we compare nanocomposites filled with two layered silicates which were made by melt compounding and solution blending, respectively. Poly(methyl methacrylate) (PMMA) is chosen here as a thermoplastic model matrix which was compounded with a synthetic nano-mica (O-hect) and commercial Bentone with typical diameters of 5–7 μm and <300 nm, respectively.     

An enhanced symbiosis organisms search algorithm: an empirical study

Many nature-inspired optimization algorithms have recently been proposed to solve difficult optimization problems where the mathematical gradient-based approaches could not be used. However, those approaches were often not tested on a proper set of problems. Moreover, statistical tests are sometimes not used to validate the conclusions. Therefore, empirical analyses of such approaches are needed. In this paper, a very recent nature-inspired approach, symbiosis organisms search (SOS), is investigated. A set of unbiased and characteristically different problems are used to study the performance of SOS. In addition, a comparison with some recent optimization methods is conducted. Then, the effect of SOS only parameter, eco_size, is studied, and the use of different random distributions is also explored. Finally, three simple SOS variants are proposed and compared to the original SOS. Conclusions are validated using nonparametric statistical tests.

     

A phase‑locked loop using ESO‑based loop flter for grid‑connected converter: performance analysis

An extended state observer (ESO)-based loop flter is designed for the phase-locked loop (PLL) involved in a disturbed gridconnected converter (GcC). This ESO-based design enhances the performances and robustness of the PLL, and, therefore, improves control performances of the disturbed GcCs. Besides, the ESO-based LF can be applied to PLLs with extra flters for abnormal grid conditions. The unbalanced grid is particularly taken into account for the performance analysis. A tuning approach based on the well-designed PI controller is discussed, which results in a fair comparison with conventional PItype PLLs. The frequency domain properties are quantitatively analysed with respect to the control stability and the noises rejection. The frequency domain analysis and simulation results suggest that the performances of the generated ESO-based controllers are comparable to those of the PI control at low frequency, while have better ability to attenuate high-frequency measurement noises. The phase margin decreases slightly, but remains acceptable. Finally, experimental tests are conducted with a hybrid power hardware-in-the-loop benchmark, in which balanced/unbalanced cases are both explored. The obtained results prove the efectiveness of ESO-based PLLs when applied to the disturbed GcC.     

A phase-locked loop using ESO-based loop filter for grid-connected converter:performance analysis

An extended state observer(ESO)-based loop filter is designed for the phase-locked loop(PLL)involved in a disturbed grid-connected converter(GcC).This ESO-based...