Three-phase four-wire shunt active power filter based on the SOGI filter and Lyapunov function for DC bus control

The three-phase four-wire shunt active power filter (SAPF) was developed to suppress the harmonic currents generated by nonlinear loads, and for the compensation of unbalanced nonlinear load currents, reactive power, and the harmonic neutral current. In this work, we consider instantaneous reactive power theory (PQ theory) for reference current identification based on the following two algorithms: the classic low-pass filter (LPF) and the second-order generalized integrator (SOGI) filter. Furthermore, since an important process in SAPF control is the regulation of the DC bus voltage at the capacitor, a new controller based on the Lyapunov function is also proposed. A complete simulation of the resultant active filtering system confirms its validity, which uses the SOGI filter to extract the reference currents from the distorted line currents, compared with the traditional PQ theory based on LPF. In addition, the simulation performed also demonstrates the superiority of the proposed approach, for DC bus voltage control based on the Lyapunov function, compared with the traditional proportional-integral (PI) controller. Both novel approaches contribute towards an improvement in the overall performance of the system, which consists of a small rise and settling time, a very low or nonexistent overshoot, and the minimization of the total harmonic distortion (THD).     

Schedule-Based Cooperative Multi-agent Reinforcement Learning for Multi-channel Communication in Wireless Sensor Networks

Wireless sensor networks (WSNs) have become an important component in the Internet of things (IoT) field. In WSNs, multi-channel protocols have been developed to overcome some limitations related to the throughput and delivery rate which have become necessary for many IoT applications that require sufficient bandwidth to transmit a large amount of data. However, the requirement of frequent negotiation for channel assignment in distributed multi-channel protocols incurs an extra-large communication overhead which results in a reduction of the network lifetime. To deal with this requirement in an energy-efficient way is a challenging task. Hence, the Reinforcement Learning (RL) approach for channel assignment is used to overcome this problem. Nevertheless, the use of the RL approach requires a number of iterations to obtain the best solution which in turn creates a communication overhead and time-wasting. In this paper, a Self-schedule based Cooperative multi-agent Reinforcement Learning for Channel Assignment (SCRL CA) approach is proposed to improve the network lifetime and performance. The proposal addresses both regular traffic scheduling and assignment of the available orthogonal channels in an energy-efficient way. We solve the cooperation between the RL agents problem by using the self-schedule method to accelerate the RL iterations, reduce the communication overhead and balance the energy consumption in the route selection process. Therefore, two algorithms are proposed, the first one is for the Static channel assignment (SSCRL CA) while the second one is for the Dynamic channel assignment (DSCRL CA). The results of extensive simulation experiments show the effectiveness of our approach in improving the network lifetime and performance through the two algorithms.

     

Evolutionary research of optimal strategies for exclusive positioned clustering in simulated environment of collective robotics

One of the captivating characteristics of social insects, in spite of their rudimentary individual constitution, is the ability by which they have to solve complicated problems in an elastic and robust way. This includes elasticity which ensures the adaptation of the insect system to the unpredictable changes of their environment, and robustness which guarantees a functioning continuity of the system, in spite of the possible failure of a certain number of its elements in the achievement of their individual missions. From this point of view, fields of research have emerged over the past decades, with the aim of trying to reveal the secret behind the relationship between individual and society, so perfectly designed in nature. Collective robotics is one of those fields where we try to find microscopic rules allowing a group of autonomous robots, mobile and with limited capacity, to carry out a specific macro-task, such as exclusive positioned heap formation. The idea, behind this, is to use a model of oriented reactive agent simulation, to seek the relations which can link the local perceptions of the simulated robots with their basic actions, in order to make the above mentioned gathering task a success. An evolutionary approach is used for this purpose, making it possible to discover the functional control relations of these simulated robots. An analogy with the precepts specific to the ant community is established and results of simulation indicating the effectiveness of the detected rules are presented.     

Sulphated polysaccharides from Indian samples of Enteromorpha compressa (Ulvales,Chlorophyta): Isolation and structural features

Heteroglycan and xyloglucan rich fractions were extracted from Indian samples of Enteromorpha compressa in 25% yield by sequential extractions with water and alkali. This heteroglycan is sulfated and has an apparent molecular mass of 55 kDa. Chemical structural analysis of this polysaccharide revealed a branched structure having 1,4- and 1,2,4-linked rhamnose 3-sulphate, 1,4-linked glucose, 1,3- and 1,6- linked galactose, 1,4- and terminally linked glucuronic acid and 1,4-linked xylose partially sulfated on O-2. Chemical and spectroscopic analysis showed that the 4-M KOH extracted hemicellulosic fraction contained an unusual β-(1,4)-linked linear xyloglucan. Enzyme hydrolysis and analysis of the resulting fragments by matrix-assisted laser desorption ionization-time of flight-mass spectrometry (MALDI-TOF-MS) showed that this linear polymer contained partially sulfated Glc₃Xyl₂ or Glc₄Xyl₂ as oligomeric building subunits.     

Dielectric and mechanical optimization properties of porous poly(ethylene‐co‐vinyl acetate) copolymer films for pseudo‐piezoelectric effect

In this article, the authors present a porous copolymer film with pseudo‐piezoelectric effects as a new candidate material for sensing applications. Porous films of poly(ethylene‐co‐vinyl acetate) (EVA) with a thicknesses ranging from 160 to 310 μm are fabricated by a coextrusion chemical foaming process and charged using a high‐voltage contact charging process. Output performances (piezoelectric constant and relative permittivity) with related thermal/mechanical stability are specifically studied as a function of the film porosity and of the electrical charging process. The piezoelectric constant d₃₃ increases with the cell porosity and an interesting piezoelectric constant close to 5.1 pC/N is achieved with a porous EVA film containing 65% of porosity. Actual results are then discussed using a theoretical solid–gas multilayer model to describe and predict the pseudo‐piezoelectric effect of porous polymer materials. The originality of this work lies in the fact that all the steps leading to optimize pseudo piezoelectric films are included, and also in the use of EVA which is not a standard piezoelectric material. Therefore, this work is a contribution in the development of low‐cost piezoelectric materials with potential applications as sensor in different fields such as medical, security, environment, sport, and transport. POLYM. ENG. SCI., 59:1455–1461 2019. © 2019 Society of Plastics Engineers     

Spectrum harvesting for heterogeneous wireless networks integration

Massive capacity demand is a major impetus behind the advances, in various ways, of today and near future wireless communication networks. To face this challenge, more wireless spectrum is needed, efficient usage of this spectrum is necessary, and adequate architectures are required. In this paper, we present a conceptual solution based on a cognitive-radio-inspired cellular network, for integrating idle spectrum resources of different wireless networks into a single mobile heterogeneous wireless network. We describe the conceptual architecture of this integrating network, referred to as Integrating cognitive-radio-inspired cellular network (I-CRICNet), and present a cooperative spectrum-harvesting scheme that keeps the former supplied with spectrum resources. In the latter scheme, we make extensive use of cross-correlated sequences (CSSs), for events signaling purposes. This choice is motived by the particularly interesting characteristics of the CSSs, namely, duration shortness, robustness to bad radio conditions, detection rather than decoding, and low probability of collision. As an illustration, we propose a reporting and detection scheme, in the context of OFDMA systems, and provide performance results from simulations to validate our proposal.

     

An Efficient Approach for Big Data Aggregation Mechanism in Heterogeneous Wireless Connected Sensor Networks

Recently and due to the impressive growth in the amounts of transmitted data over the heterogeneous sensor networks and the emerged related technologies especially the Internet of Things in which the number of the connected devices and the data consumption are remarkably growing, big data has emerged as a widely recognized trend and is increasingly being talked about. The term big data is not only about the volume of data, but also refers to the high speed of transmission and the wide variety of information that is difficult to collect, store and process using the available classical technologies. Although the generated data by the individual sensors may not appear to be significant, all the data generated through the many sensors in the connected sensor networks are able to produce large volumes of data. Big data management imposes additional constraints on the wireless sensor networks and especially on the data aggregation process, which represents one of the essential paradigms in wireless sensor networks. Data aggregation process can represent a solution to the problem of big data by allowing data from different sources to be combined to eliminate the redundant ones and consequently reduce the amounts of data and the consumption of the available resources in the network. The main objective of this work is to propose a new approach for supporting big data in the data aggregation process in heterogeneous wireless sensor networks. The proposed approach aims to reduce the data aggregation cost in terms of energy consumption by balancing the data loads on the heterogeneous nodes. The proposal is improved by integrating the feedback control closed loop to reinforce the balance of the data aggregation load on the nodes, maintaining therefore an optimal delay and aggregation time.

     

Polysaccharides from Sesamum indicum meal: Isolation and structural features

Defatted Sesamum indicum seed cake was extracted, following two separate sequences, and the effects of extraction medium on yield and composition of the extracts were compared. Polysaccharides extracted sequentially with dilute acid and alkali represented 250 mg/g of defatted meal. The isolated polymers contained arabinan, rhamnogalacturonan I (RG I) and arabinogalactan proteins. Polysaccharides extracted during chlorite treatment and with dilute alkali had a higher proportion of rhamnose, suggesting a more branched variety of polymer. Three extracts, which were further characterized by size exclusion chromatography, gave two overlapping peaks. Structural characterisation of hemicellulosic polysaccharides, isolated with KOH, using specific enzyme hydrolysis, ion exchange chromatography (HPAEC) and matrix assisted laser desorption ionisation-time-of-flight (MALDI-TOF) mass spectroscopy, showed that sesame meal xyloglucan (XG) contained XXXG, XXFG and XXLG, and XLLG (named according to Fry et al., 1993) as the major building sub-units in the ratio of 1:0.9:0.3. Hydrolysis with endo-β-(1 → 4)-d-xylanase and analysis of the xylan derived oligosaccharides showed the presence of monomeric xylose (40%), xylobiose (46%) and acidic xylan oligosaccharides containing 4-O-methyl-d-glucuronic acid residues (14%).     

Corrosion Control of Mild Steel Material in HCl Electrolyte by a Non-Steroidal Anti-Inflammatory Drug: Electrochemical and Kinetic Study

Protection of Metals and Physical Chemistry of Surfaces - The corrosion inhibition of mild steel by a drug substance, namely piroxicam, in HCl (1 M) solution was investigated. The Electrochemical...     

Novel Approach for Management of Automated IPv6 Network Simulation

Wireless Personal Communications - The complexity of network technologies and the variety of their equipment and settings make them difficult to evaluate, to simulate, and to deploy. IPv4 to IPv6...