Eco‐friendly synthesis of silver nanoparticles and its larvicidal property against fourth instar larvae of Aedes aegypti

In this study, larvicidal activity of silver nanoparticles (AgNPs) synthesised using apple extract against fourth instar larvae of Aedes aegypti was determined. As a result, the AgNPs showed moderate larvicidal effects against Ae. aegypti larvae (LC₅₀  = 15.76 ppm and LC₉₀  = 27.7 ppm). In addition, comparison of larvicidal activity performance of AgNPs at high concentration prepared using two different methods showed that Ae. aegypti larvae was fully eliminated within the duration of 2.5 h. From X‐ray diffraction, the AgNP crystallites were found to exhibit face centred cubic structure. The average size of these AgNPs as estimated by particle size distribution was in the range of 50–120 nm. The absorption maxima of the synthesised Ag showed characteristic Ag surface plasmon resonance peak. This green synthesis provides an economic, eco‐friendly and clean synthesis route to Ag.Inspec keywords: silver, nanofabrication, X‐ray diffraction, zoology, particle size, nanoparticles, biomedical materials, nanomedicineOther keywords: time 2.5 h, size 50 nm to 120 nm, silver nanoparticle, larvicidal property, instar larvae, Aedes aegypti, larvicidal effect, larvicidal activity performance, X‐ray diffraction, nanoparticle particle size distribution, absorption maxima, silver surface plasmon resonance peak     

Adaptive neuro-fuzzy inference system multi-objective optimization using the genetic algorithm/singular value decomposition method for modelling the discharge coefficient in rectangular sharp-crested side weirs

In the present article, the adaptive neuro-fuzzy inference system (ANFIS) is employed to model the discharge coefficient in rectangular sharp-crested side weirs. The genetic algorithm (GA) is used for the optimum selection of membership functions, while the singular value decomposition (SVD) method helps in computing the linear parameters of the ANFIS results section (GA/SVD-ANFIS). The effect of each dimensionless parameter on discharge coefficient prediction is examined in five different models to conduct sensitivity analysis by applying the above-mentioned dimensionless parameters. Two different sets of experimental data are utilized to examine the models and obtain the best model. The study results indicate that the model designed through GA/SVD-ANFIS predicts the discharge coefficient with a good level of accuracy (mean absolute percentage error?=?3.362 and root mean square error?=?0.027). Moreover, comparing this method with existing equations and the multi-layer perceptron–artificial neural network (MLP-ANN) indicates that the GA/SVD-ANFIS method has superior performance in simulating the discharge coefficient of side weirs.     

Additive Manufacturing of Porous Structures for Unmanned Aerial Vehicles Applications

Unmanned aerial vehicles (UAVs) have shown promising benefits in many applications. This has been enabled by the emergence of additive manufacturing (AM), which give the designers a large amount of geometrical freedom. In this paper, a novel design process of fused deposition modeling (FDM) combining both topology and infill optimization is introduced for AM of high performance porous structures. Tensile testing of FDM printed samples is first carried out to study the effect of the build orientation on the mechanical properties of acrylonitrile butadiene styrene (ABS) samples. It is found that samples built perpendicular to the load axis are the weakest with a tensile strength of 29 MPa and Young's modulus of 1960 MPa. The materials properties are fed to the finite elements analysis (FEA) for geometrical topology optimization, aiming to maximize stiffness and reduce weight of those parts. Afterwards, an infill optimization is carried out on the topology optimized parts using different mesostructures such as honeycomb, triangular, and rectangular to achieve high structural performance. The results showed that triangular pattern with 50% infill density had the lowest developed stresses, less mass, and strain energy when compared to other structures. Optimum UAVs parts of a quadcopter are successfully manufactured, assembled, and tested.

     

Fuzzy-HLSTM (Hierarchical Long Short-Term Memory) for Agricultural Based Information Mining

This research proposes a machine learning approach using fuzzy logic to build an information retrieval system for the next crop rotation. In case-based reasoning systems, case representation is critical, and thus, researchers have thoroughly investigated textual, attribute-value pair, and ontological representations. As big databases result in slow case retrieval, this research suggests a fast case retrieval strategy based on an associated representation, so that, cases are interrelated in both either similar or dissimilar cases. As soon as a new case is recorded, it is compared to prior data to find a relative match. The proposed method is worked on the number of cases and retrieval accuracy between the related case representation and conventional approaches. Hierarchical Long Short-Term Memory (HLSTM) is used to evaluate the efficiency, similarity of the models, and fuzzy rules are applied to predict the environmental condition and soil quality during a particular time of the year. Based on the results, the proposed approaches allows for rapid case retrieval with high accuracy.     

Optimal Deep Learning Model Enabled Secure UAV Classification forIndustry 4.0

Emerging technologies such as edge computing, Internet of Things (IoT), 5G networks, big data, Artificial Intelligence (AI), and Unmanned Aerial Vehicles (UAVs) empower, Industry 4.0, with a progressive production methodology that shows attention to the interaction between machine and human beings. In the literature, various authors have focused on resolving security problems in UAV communication to provide safety for vital applications. The current research article presents a Circle Search Optimization with Deep Learning Enabled Secure UAV Classification (CSODL-SUAVC) model for Industry 4.0 environment. The suggested CSODL-SUAVC methodology is aimed at accomplishing two core objectives such as secure communication via image steganography and image classification. Primarily, the proposed CSODL-SUAVC method involves the following methods such as Multi-Level Discrete Wavelet Transformation (ML-DWT), CSO-related Optimal Pixel Selection (CSO-OPS), and signcryption-based encryption. The proposed model deploys the CSO-OPS technique to select the optimal pixel points in cover images. The secret images, encrypted by signcryption technique, are embedded into cover images. Besides, the image classification process includes three components namely, Super-Resolution using Convolution Neural Network (SRCNN), Adam optimizer, and softmax classifier. The integration of the CSO-OPS algorithm and Adam optimizer helps in achieving the maximum performance upon UAV communication. The proposed CSODL-SUAVC model was experimentally validated using benchmark datasets and the outcomes were evaluated under distinct aspects. The simulation outcomes established the supreme better performance of the CSODL-SUAVC model over recent approaches.     

A recursive state estimator in the presence of state inequality constraints

This paper proposes an optimal recursive estimator to estimate the states of a stochastic discrete time linear dynamic system when the states of the system are constrained with inequality constraints. The case when the constraints are strictly satisfied is treated independently from the case when some of the constraints are violated. For the first case, the well known Kalman filter estimator is used. In the second case, an algorithm which uses a series of successive orthogonalizations on the measurement subspaces is employed to obtain the optimal estimate. It is shown that the proposed estimator has several attractive properties such that it is an unbiased estimator. More importantly, compared to other estimator found in the literature, the proposed estimator needs less computational efforts, is numerically more stable and it leads to a smaller variance. To show the effectiveness of the proposed estimator, several simulation results are presented and discussed.     

Absolute Stability of Nonlinear Systems with Two Additive Time-varying Delay Components

In this paper, we present a new sufficient condition for absolute stability of Lure system with two additive time-varying delay components. This criterion is expressed as a set of linear matrix inequalities (LMIs), which can be readily tested by using standard numerical software. We use this new criterion to stabilize a class of nonlinear time-delay systems. Some numerical examples are given to illustrate the applicability of the results using standard numerical software.     

Absolute stability of nonlinear systems with two additive time-varying delay components

In this paper, we present a new sufficient condition for absolute stability of Lure system with two additive time-varying delay components. This criterion is expressed as a set of linear matrix inequalities (LMIs), which can be readily tested by using standard numerical software. We use this new criterion to stabilize a class of nonlinear time-delay systems. Some numerical examples are given to illustrate the applicability of the results using standard numerical software.     

Geometrical approach of planar hyper-redundant manipulators: Inverse kinematics,path planning and workspace

A new method for inverse kinematics for hyper-redundant manipulators is proposed in this paper to plan the path of the end-effector. The basic idea is that for a given smooth path consisting of points close enough to each other; computing the inverse kinematics for these points is carried out geometrically using the proposed method. In this method, the angles between the adjacent links are set to be the same, which makes lining up of two or more joint axes impossible; therefore, avoiding singularities. The manipulability index has been used to show how far the manipulator from the singularity configuration is. The determination of the workspace of the manipulator using the proposed method has been presented in this paper. The simulation results have been carried out on a planar and a three dimensional manipulators. The effectiveness of the proposed method is clearly demonstrated by comparing its result with results calculated by the well-known method of measuring manipulability which is used for singularity avoidance for the last two decades.