Agent-based time delay margin in consensus of multi-agent systems by an event-triggered control method: Concept and computation

This paper deals with defining the concept of agent-based time delay margin and computing its value in multi-agent systems controlled by event-triggered based controllers. The agent-based time delay margin specifying the time delay tolerance of each agent for ensuring consensus in event-triggered controlled multi-agent systems can be considered as complementary for the concept of (network) time delay margin, which has been previously introduced in some literature. In this paper, an event-triggered control method for achieving consensus in multi-agent systems with time delay is considered. It is shown that the Zeno behavior is excluded by applying this method. Then, in a multi-agent system controlled by the considered event-triggered method, the concept of agent-based time delay margin in the presence of a fixed network delay is defined. Moreover, an algorithm for computing the value of the time delay margin for each agent is proposed. Numerical simulation results are also provided to verify the obtained theoretical results.     

Modulation Based Combination of High Level Features Generated from SCCF & Contourlet Transforms for CBIR Applications

The need for suitable and cost-effective technologies rise with the growth of the internet of things (IoT) applications. These aim at handling voluminous data transmission in addition to minimum energy and latency cost constraints. LoRa networks are recommended for applications in confined spaces, long ranges, and less battery consumption requirements. However, the end devices in these networks communicate to all gateways in their ranges, thereby expediting energy unproductively in redundant transmissions. In our article, we explore the possibilities of whether LoRa networks could employ the advantages of clustering and propose two algorithms, path-based and data-centric, for such networks. We suggest that LoRaWAN technology with clustering can be apt for long-range, low power consumption IoT applications in the future. We study the impact of network density, node range, and cluster range on the energy consumption in data transmissions. The algorithms are compared with the inherent star-based communication of LoRa networks based on energy consumed, and our results show that, for dense deployments, clustering becomes advantageous.

     

An Improvement Energy Consumption Policy Using Communication Reduction in Wireless Body Sensor Network

Dedicated short-range communications (DSRC) is an important wireless technology for current and future automotive safety and mitigation of traffic jams. In this work, we have designed a Coplanar waveguide microstrip patch antenna with linear, upper and bottom and side slots for application in DSRC. The patch antenna was designed using glass epoxy substrate (FR4). Various parametric analyses such as the current distribution, reflection coefficient, radiation pattern on E- and H-plane as well as the realized gain (dB) were performed. The results were obtained by simulation using high-frequency structure simulator tool. The proposed antenna covers a frequency band of 5.8–5.9 GHz which is highly dedicated to the DSRC wireless communication technology for enhancement of safety of the automotive transport system. The designed antenna shows a good return loss of ??19 dB at 5.9 GHz.The designed antenna shows a promising gain, return loss and radiation pattern for use in DSRC for automotive transport systems.

     

Effect of Ag‐NPs synthesised by Chamaemelum nobile extract on the inflammation and oxidative stress induced by carrageenan in mice paw

An environmentally friendly and rapid procedure was developed to synthesise silver nanoparticles (Ag‐NPs) by Chamaemelum nobile extract and to evaluate its in vivo anti‐inflammatory and antioxidant activities. The ultraviolet–visible absorption spectrum of the synthesised Ag‐NPs showed an absorbance peak at 422. The average size of spherical nanoparticles was 24 nm as revealed by transmission electron microscopy. Fourier transform infra‐red spectroscopy analysis supported the presence of biological active compounds involved in the reduction of Ag ion and X‐ray diffraction confirmed the crystalline structure of the metallic Ag. The anti‐inflammatory and antioxidant activity of the Ag‐NPs was investigated against carrageenan‐induced paw oedema in mice. The levels of malondialdehyde (MDA) and antioxidant enzymes superoxide dismutase, catalase, glutathione peroxidase and inflammatory cytokines tumour necrosis factor (TNF‐α), interferon gamma and interleukin (IL)‐6, IL‐1β were assessed in this respect. The results demonstrated that anti‐inflammatory activity of the Ag‐NPs might be due to the ability of the nanoparticles to reduce IL‐1β, IL‐6 and TNF‐α. Moreover, reduction of antioxidant enzymes along with an increase in MDA level shows that the anti‐inflammatory activity of the synthesised Ag‐NPs by C. nobile is attributed to its ameliorating effect on the oxidative damage.Inspec keywords: silver, nanoparticles, nanofabrication, ultraviolet spectra, visible spectra, particle size, transmission electron microscopy, Fourier transform infrared spectra, X‐ray diffraction, crystal structure, enzymes, molecular biophysics, tumours, biomedical materials, nanomedicineOther keywords: Chamaemelum nobile extract, oxidative stress, mice paw, silver nanoparticles, antiinflammatory activity, antioxidant activity, ultraviolet‐visible absorption spectrum, spherical nanoparticle size, transmission electron microscopy, Fourier transform infrared spectroscopy, biological active compounds, X‐ray diffraction, crystalline structure, carrageenan‐induced paw oedema, malondialdehyde, antioxidant enzymes, superoxide dismutase, catalase, glutathione peroxidase, inflammatory cytokines, tumour necrosis factor, interferon gamma, interleukin, IL‐1β, IL‐6, TNF‐α, MDA level, Ag     

Evaluation of antifungal effect of iron‐oxide nanoparticles against different Candida species

Iron‐oxide nanoparticles (IONPs) have been widely favoured due to their biodegradable, low cytotoxic effects and having reactive surface which can be altered with biocompatible coatings. Considering various medical applications of IONPs, the authors were encouraged to study whether IONPs could be effective against fungal infections caused by Candida species. In this study, IONPs were characterised by scanning electron microscopy, X‐ray diffraction, Fourier transform infrared spectroscopy and vibrating sample magnetometer. The goal of this study was to evaluate the antifungal activity of IONPs against different Candida spp. compared with fluconazole (FLC). IONPs were spherical with the size of 30–40 nm. The minimum inhibitory concentration (MIC) and minimum fungicidal concentration (MFC) values of IONPs ranged from 62.5 to 500 µg/ml and 500 to 1000 μg/ml, respectively. The MIC and MFC of FLC were in range of 16–128 μg/ml and 64–512 μg/ml, respectively. The growth inhibition value indicated that Candida tropicalis, Candida albicans and Candida glabrata spp. were most susceptible to IONPs. The finding showed that the IONPs possessed antifungal potential against pathogenic Candida spp. and could inhibit the growth of all the tested Candida spp. Further studies, both in vitro and in vivo (including susceptibility, toxicity, Probability of kill (PK) and efficacy studies) are needed to determine whether IONPs are suitable for medicinal purposes.Inspec keywords: iron compounds, nanoparticles, nanomedicine, biomedical materials, microorganisms, cellular biophysics, toxicology, drugs, scanning electron microscopy, X‐ray diffraction, Fourier transform infrared spectraOther keywords: antifungal effect, iron‐oxide nanoparticles, Candida species, biodegradable effects, cytotoxic effects, reactive surface, biocompatible coatings, medical applications, IONP, fungal infections, Candidiasis, immunocompromised hosts, antifungal drugs, resistant organisms, antifungal properties, side effects, chemical drugs, scanning electron microscopy, X‐ray diffraction, Fourier transform infrared spectroscopy, vibrating sample magnetometer, antifungal activity, disc diffusion, broth microdilution, minimal inhibitory concentration, minimum fungicidal concentration, Candida tropicalis, Candida Albicans, Candida glabrata, antifungal potential, Fe₃ O₄      

Designing a cellular manufacturing system considering decision style,skill and job security by NSGA-II and response surface methodology

Cell formation is a traditional problem in cellular manufacturing systems that concerns the allocation of parts, operators and machines to the cells. This paper presents a new mathematical programming model for cell formation in which operators’ personality and decision-making styles, skill in working with machines, and also job security are incorporated simultaneously. The model involves the following five objectives: (1) minimising costs of adding new machines to and removing machines from the cells at the beginning of each period, (2) minimising total cost of material handling, (3) maximising job security, (4) minimising inconsistency of operators’ decision styles in cells and (5) minimising cost of suitable skill. On account of the NP-hard nature of the proposed model, NSGA-II as a powerful meta-heuristic approach is used for solving large-sized problems. Furthermore, response surface methodology (RSM) is used for tuning the parameters. Lastly, MOPSO and two scalarization methods are employed for validation of the results obtained. To the best of our knowledge, this is the first study that presents a multi-objective mathematical model for cell formation problem considering operators’ personality and skill, addition and removal of machines and job security.     

On the performance of different capability indices under normal and non-normal distributions

In this article, we have examined the performance of some useful capability indices using normal and non-normal distributions. The confidence intervals are calculated and mean coverage rates are observed for different capability indices. The effects of symmetry and kurtosis of parent distributions are examined on the mean coverage rates of different capability indices. Moreover, we have investigated the robustness (of confidence interval) using the median and percentile-based indices. We have considered the well-known distributions including normal, gamma, t, Weibull, and chi-squared. For these process scenarios, we have observed that some indices resist disturbance only in symmetry of the parent distribution, some resist the disturbance in symmetry and kurtosis of the distribution, and some indices don’t resist against either type of disturbance.     

EEG‐based brain source localization using visual stimuli

Electroencephalography (EEG) is widely used in variety of research and clinical applications which includes the localization of active brain sources. Brain source localization provides useful information to understand the brain's behavior and cognitive analysis. Various source localization algorithms have been developed to determine the exact locations of the active brain sources due to which electromagnetic activity is generated in brain. These algorithms are based on digital filtering, 3D imaging, array signal processing and Bayesian approaches. According to the spatial resolution provided, the algorithms are categorized as either low resolution methods or high resolution methods. In this research study, EEG data is collected by providing visual stimulus to healthy subjects. FDM is used for head modelling to solve forward problem. The low‐resolution brain electromagnetic tomography (LORETA) and standardized LORETA (sLORETA) have been used as inverse modelling methods to localize the active regions in the brain during the stimulus provided. The results are produced in the form of MRI images. The tables are also provided to describe the intensity levels for estimated current level for the inverse methods used. The higher current value or intensity level shows the higher electromagnetic activity for a particular source at certain time instant. Thus, the results obtained demonstrate that standardized method which is based on second order Laplacian (sLORETA) in conjunction with finite difference method (FDM) as head modelling technique outperforms other methods in terms of source estimation as it has higher current level and thus, current density (J) for an area as compared to others.