Search Results (9)

Magnetic induction (MI)-operated wireless sensor networks (WSNs), due to their similar performance in air, underwater, and underground mediums, are rapidly emerging networks that offer a wide range of applications, including mine prevention, power grid maintenance, underground pipeline monitoring, and upstream oil monitoring. MI-based wireless underground sensor networks (WUSNs), utilizing small antenna coils, offer a viable solution by providing consistent channel conditions. The cross-layer protocols address the specific challenges of WUSNs, leading to improved network performance and enhanced operational capabilities in real-world applications. This work proposes a distributed cross-layer solution, leveraging the hybrid marine predator naked mole rat algorithm (MPNMRA) for MI-operated WUSNs. The solution, called DECMN (distributed energy-throughput efficient cross-layer network using MPNMRA), is designed to optimize the MI communication channels, MI relay coils (MI waveguide), and MI waveguide with 3D coils to fulfill quality of service (QoS) parameters, while achieving energy savings and throughput gains. DECMN utilizes the interactions between various layers to develop cross-layer protocols based on MPNMRA. Simulation results demonstrate the effectiveness of DECMN, offering energy savings, increased throughput, and reliable transmissions within the performance limits. Full article

Circular antenna arrays (CAAs) find extensive utility in a range of cutting-edge communication applications such as 5G networks, the Internet of Things (IoT), and advanced beamforming technologies. In the realm of antenna design, the side lobes levels (SLL) in the radiation pattern hold significant importance within communication systems. This is primarily due to its role in mitigating signal interference across the entire radiation pattern’s side lobes. In order to suppress the subsidiary lobe, achieve the required primary lobe orientation, and improve directivity, an optimization problem is used in this work. This paper introduces a method aimed at enhancing the radiation pattern of CAA by minimizing its SLL using a Hybrid Sooty Tern Naked Mole-Rat Algorithm (STNMRA). The simulation results show that the hybrid optimization method significantly reduces side lobes while maintaining reasonable directivity compared to the uniform array and other competitive metaheuristics. Full article

This paper introduces a parallel meta-heuristic algorithm called Cuckoo Flower Search (CFS). This algorithm combines the Flower Pollination Algorithm (FPA) and Cuckoo Search (CS) to train Multi-Layer Perceptron (MLP) models. The algorithm is evaluated on standard benchmark problems and its competitiveness is demonstrated against other state-of-the-art algorithms. Multiple datasets are utilized to assess the performance of CFS for MLP training. The experimental results are compared with various algorithms such as Genetic Algorithm (GA), Grey Wolf Optimization (GWO), Particle Swarm Optimization (PSO), Evolutionary Search (ES), Ant Colony Optimization (ACO), and Population-based Incremental Learning (PBIL). Statistical tests are conducted to validate the superiority of the CFS algorithm in finding global optimum solutions. The results indicate that CFS achieves significantly better outcomes with a higher convergence rate when compared to the other algorithms tested. This highlights the effectiveness of CFS in solving MLP optimization problems and its potential as a competitive algorithm in the field. Full article

An increased dependency on plant-based resources for food, shelter, and medicinal usage has increased their sustainable and unsustainable exploitation. To use this resource sustainably, plant tissue culture (PTC) is one important technology. Among different PTC techniques, thin cell layer (TCL) technology is a relatively simple and easily adaptable technique for in vitro cultures of plants. This technique uses small explants about 0.5–2 mm in thickness excised from different plant organs. It has been successfully used in the large-scale propagation of vegetables, legumes, and plants with medicinal benefits. TCL technology has proven to be effective in stimulating various organogenic responses when combined with various new methods such as nanotechnology or microtome-based explantation, especially in tree species. It is considered an important tool in plant biotechnology. Although the morphogenetic response per explant is usually higher in conventional explants, the appropriate use of plant growth regulators and geometric factors in TCL has the potential to make it more efficient and beneficial. This article provides an overview of the concept of TCL as applied to different plant species, particularly trees, since there are few, if any, summaries of TCL technology, especially in trees. This review will certainly revitalize this important technology so that it can be used effectively for successful mass propagation in the field of plant tissue culture. Full article

Wireless Sensor Networks (WSNs) have a wonderful potential to interconnect with the physical world and collect data. Data estimation, long lifespan, deployment, routing, task scheduling, safety, and localization are the primary performance difficulties for WSNs. WSNs are made up of sensor nodes set up with minimal battery power to monitor and reveal the occurrences in the sensor field. Detecting the location is a difficult task, but it is a crucial characteristic in many WSN applications. Locating all of the sensor nodes efficiently to obtain the precise location of an occurrence is a critical challenge. Surveillance, animal monitoring, tracking of moving objects, and forest fire detection are just a few of the applications that demand precise location determination. To cope with localization challenges in WSNs, there is a variety of localization algorithms accessible in the literature. The goal of this research is to use various optimization strategies to solve the localization problem. In this work, a modified learning enthusiasm-based teaching–learning-based optimization (mLebTLBO) algorithm is used to cope with a 2D localization problem applying the notion of an exclusive anchor node and movable target nodes. A modified LebTLBO algorithm seeks to increase overall efficiency by assessing the exploration and exploitation abilities. The computational results reveal that this technique outperforms others with respect to localization errors in a 2D environment of WSN. Full article

The structural, energetic, and electronic properties of single-layer graphene doped with boron and nitrogen atoms with varying doping concentrations and configurations have been investigated here via first-principles density functional theory calculations. It was found that the band gap increases with an increase in doping concentration, whereas the energetic stability of the doped systems decreases with an increase in doping concentration. It was observed that both the band gaps and the cohesive energies also depend on the atomic configurations considered for the substitutional dopants. Stability was found to be higher in N-doped graphene systems as compared to B-doped graphene systems. The electronic structures of B- and N-doped graphene systems were also found to be strongly influenced by the positioning of the dopant atoms in the graphene lattice. The systems with dopant atoms at alternate sublattices have been found to have the lowest cohesive energies and therefore form the most stable structures. These results indicate an ability to adjust the band gap as required using B and N atoms according to the choice of the supercell, i.e., the doping density and substitutional dopant sites, which could be useful in the design of graphene-based electronic and optical devices. Full article

Two-dimensional materials have attracted great scientific attention due to their unusual and fascinating properties for use in electronics, spintronics, photovoltaics, medicine, composites, etc. Graphene, transition metal dichalcogenides such as MoS₂, phosphorene, etc., which belong to the family of two-dimensional materials, have shown great promise for gas sensing applications due to their high surface-to-volume ratio, low noise and sensitivity of electronic properties to the changes in the surroundings. Two-dimensional nanostructured semiconducting metal oxide based gas sensors have also been recognized as successful gas detection devices. This review aims to provide the latest advancements in the field of gas sensors based on various two-dimensional materials with the main focus on sensor performance metrics such as sensitivity, specificity, detection limit, response time, and reversibility. Both experimental and theoretical studies on the gas sensing properties of graphene and other two-dimensional materials beyond graphene are also discussed. The article concludes with the current challenges and future prospects for two-dimensional materials in gas sensor applications. Full article

Environmentally responsive poly(N-isopropylacrylamide) brushes were grafted from the surface of polymer particles or flat surfaces in order to generate reversible hydrophilic and hydrophobic surfaces. The use of atom transfer radical polymerization was demonstrated for the grafting of polymer brushes as it allows efficient control on the amount of grafted polymer. The polymer particles were generated with or without surfactant in the emulsion polymerization and their surface could be modified with the atom transfer radical polymerization (ATRP) initiator. The uniform functionalization of the surface with ATRP initiator was responsible for the uniform grafting of polymer brushes. The grafted brushes responded reversibly with changes in temperature indicating that the reversible responsive behavior could be translated to the particle surfaces. The particles were observed to adsorb and desorb protein and virus molecules by changing the temperatures below or higher than 32 °C. The initiator functionalized particles could also be adsorbed on the flat surfaces. The adsorption process also required optimization of the heat treatment conditions to form a uniform layer of the particles on the substrate. The grafted polymer brushes also responded to the changes in temperatures similar to the spherical particles studied through water droplets placed on the flat substrates. Full article

This review aims to present recent advances in the synthesis and structure characterization as well as the properties of polymer layered silicate nanocomposites. The advent of polymer layered silicate nanocomposites has revolutionized research into polymer composite materials. Nanocomposites are organic-inorganic hybrid materials in which at least one dimension of the filler is less than 100 nm. A number of synthesis routes have been developed in the recent years to prepare these materials, which include intercalation of polymers or pre-polymers from solution, in-situ polymerization, melt intercalation etc. The nanocomposites where the filler platelets can be dispersed in the polymer at the nanometer scale owing to the specific filler surface modifications, exhibit significant improvement in the composite properties, which include enhanced mechanical strength, gas barrier, thermal stability, flame retardancy etc. Only a small amount of filler is generally required for the enhancement in the properties, which helps the composite materials retain transparency and low density. Full article