Soil–conduit interaction: an artificial intelligence application for reinforced concrete and corrugated steel conduits

Neural Computing and Applications - Marston’s load theory is commonly used for understanding the soil–conduit interaction. However, there are no practical methods available which can...     

Selective chaotic maps Tiki-Taka algorithm for the S-box generation and optimization

Neural Computing and Applications - Cryptography often involves substituting (and converting) the secret information into dummy data so that it could reach the desired destination without leakage....     

A systematic review on emperor penguin optimizer

Neural Computing and Applications - Emperor Penguin Optimizer (EPO) is a recently developed metaheuristic algorithm to solve general optimization problems. The main strength of EPO is twofold....     

Feature Selection and Extraction Methods for Power Systems Transient Stability Assessment Employing Computational Intelligence Techniques

One of the important aspects in achieving better performance for transient stability assessment (TSA) of power systems employing computational intelligence (CI) techniques is by incorporating feature reduction techniques. For small power system the number of features may be small but when larger systems are considered the number of features increased as the size of the systems increases. Apart from employing faster CI techniques to achieve faster and accurate TSA of power system, feature reduction techniques are needed in reducing the input features while preserving the needed information so as to make faster training of the CI technique. This paper presents feature reductions techniques used, namely correlation analysis and principle component analysis, in reducing number of input features presented to two CI techniques for TSA, namely probabilistic neural network (PNN) and least squares support vector machines (LS-SVM). The proposed feature reduction techniques are implemented and tested on the IEEE 39-bus test system and 87-bus Malaysia’s power system. Numerical results are presented to demonstrate the performance of the feature reduction techniques and its effects on the accuracies and time taken for training the two CI techniques.     

Energy-efficient clustering in mobile ad-hoc networks using multi-objective particle swarm optimization

A mobile ad hoc network (MANET) is dynamic in nature and is composed of wirelessly connected nodes that perform hop-by-hop routing without the help of any fixed infrastructure. One of the important requirements of a MANET is the efficiency of energy, which increases the lifetime of the network. Several techniques have been proposed by researchers to achieve this goal and one of them is clustering in MANETs that can help in providing an energy-efficient solution. Clustering involves the selection of cluster-heads (CHs) for each cluster and fewer CHs result in greater energy efficiency as these nodes drain more power than noncluster-heads. In the literature, several techniques are available for clustering by using optimization and evolutionary techniques that provide a single solution at a time. In this paper, we propose a multi-objective solution by using multi-objective particle swarm optimization (MOPSO) algorithm to optimize the number of clusters in an ad hoc network as well as energy dissipation in nodes in order to provide an energy-efficient solution and reduce the network traffic. In the proposed solution, inter-cluster and intra-cluster traffic is managed by the cluster-heads. The proposed algorithm takes into consideration the degree of nodes, transmission power, and battery power consumption of the mobile nodes. The main advantage of this method is that it provides a set of solutions at a time. These solutions are achieved through optimal Pareto front. We compare the results of the proposed approach with two other well-known clustering techniques; WCA and CLPSO-based clustering by using different performance metrics. We perform extensive simulations to show that the proposed approach is an effective approach for clustering in mobile ad hoc networks environment and performs better than the other two approaches.     

Characterization of acoustic signals due to surface discharges on H.V. glass insulators using wavelet radial basis function neural networks

A hybrid model incorporating wavelet and radial basis function neural network is presented which is used to detect, identify and characterize the acoustic signals due to surface discharge activity and hence differentiate abnormal operating conditions from the normal ones. The tests were carried out on cleaned and polluted high voltage glass insulators by using surface tracking and erosion test procedure of international electrotechnical commission 60587. A laboratory experiment was conducted by preparing the prototypes of the discharges. This study suggests a feature extraction and classification algorithm for surface discharge classification, which when combined together reduced the dimensionality of the feature space to a manageable dimension, by “marrying” the wavelet to radial basis function neural network very high levels of classification are achieved. Wavelet signal treatment toolbox is used to recover the surface discharge acoustic signals by eliminating the noisy portion and to reduce the dimension of the feature input vector. A radial basis function neural network classifier was used to classify the surface discharge and assess the suitability of this feature vector in classification. This learning method is proved to be effective by applying the wavelet radial basis function neural network in the classification of surface discharge fault data set. The test results show that the proposed approach is efficient and reliable.     

Transference and retrieval of voice message over low signal strength in satellite communication

This paper presents a method of transferring voice using short messaging service in satellite communication system. The method is especially applicable in a situation where signal strength is low and voice call is not possible. In a tunnel, basement or environment with bad climate conditions, signal strength usually gets weak which make voice call difficult but SMS works in such situation. An application has been developed using J2ME language in order to test the proposed method. For experimentation, Thuraya SG-2520 satellite phone has been used.     

Effect of microstructure and fusion temperature on the electrical and optical properties of vanadate glasses

The electrical and optical properties of binary semiconducting oxide glasses containing 45 mol % V₂O₅ and 55 mol % GeO₂ fused and equilibrated at various temperatures (T ) in air were measured.T was varied over the range from 1000 to 1350° C. Their electrical and optical properties are shown to be sensitive to microstructure and melt temperature. We suggest that the change inT caused progressive microstructure changes of these glasses, which dramatically affected the electronic conductivity and the activation enthalpy for conduction.     

Spin glass behaviour in the Co2−xZnxTiO4 compound

A.c. susceptibility measurements were carried out on the disordered spinel system Co_2–x Zn _x TiO₄ (0<x<1) between 10 and 80 K. Our measurements show three peaks in the versus T curve for Co₂TiO₄ and CoZnTiO₄ compounds. In both compounds two peaks are very close to each other, indicating that the Néel and semi-spin glass temperatures are very close. A third peak indicates the presence of the semi-spin glass to spin glass transition. In Co_1.5Zn_0.5TiO₄ only one peak is observed which indicates spin glass ordering at 26 K. Furthermore, the A-site canting present in Co₂TiO₄ and CoZnTiO₄ has a collinear and magnetic structure, indicating strong A-B coupling. X-ray analysis indicated that compounds of the system Co₂Zn_xTiO₄ synthesized with cubic symmetry. From transport properties it was found that the activation energy and thermoelectric coefficient decrease with increasing concentration of Zn in the system. The mobility of the system calculated from infrared measurements is typically of the order of 10^–9cm²V^–1s^–1.     

A spectroscopic study of vanadium-phosphate glasses containing vanadium chloride

The optical properties of vanadium-phosphate glasses containing various amounts of (V₂O₅)₅₀(P₂O₅)_50–x (VCl₃) _x , wherex = 0.05, 0.06, 0.08 and 0.1, were measured as a function of VCl₃ content. It is found that by adding VCl₃ to the melt when the glass is formed, the added chlorine which acts as an oxidizing agent alters the ratio of concentration of vanadium ions and thus the absorption coefficient. Data on absorption in this study show that the power law,() =B() –E ₀) ⁿ / is best followed forn = 3, and the absorption is solely due to vanadium oxide. Furthermore, the infrared absorption spectra of this system were investigated in the wave number range 400 to 4600cm^–1. The addition of VCl₃ to the vanadium-phosphate glasses does not seem to introduce any new absorption band in this range as compared with the spectrum of a pure vanadium-phosphate glass. Furthermore, no significant difference in the absorption spectra was observed by annealing the V₂O₅-P₂O₅ glasses up to 200° C.