In Automatic Speech Recognition (ASR) the non-linear data projection provided by a one hidden layer Multilayer Perceptron (MLP), trained to recognize phonemes, and has previous experiments to provide feature enhancement substantially increased ASR performance, especially in noise. Previous attempts to apply an analogous approach to speaker identification have not succeeded in improving performance, except by combining MLP processed features with other features. We present test results for the TIMIT database which show that the advantage of MLP preprocessing for open set speaker identification increases with the number of speakers used to train the MLP and that improved identification is obtained as this number increases beyond sixty. We also present a method for selecting the speakers used for MLP training which further improves identification performance.
Wireless Body Area Sensor Network (WBASN) is gaining significant attention due to its applications in smart health offering cost-effective, efficient, ubiquitous, and unobtrusive telemedicine. WBASNs face challenges including interference, Quality of Service, transmit power, and resource constraints. Recognizing these challenges, this paper presents an energy and Quality of Service-aware routing algorithm. The proposed algorithm is based on each node's Collaboratively Evaluated Value (CEV) to select the most suitable cluster head (CH). The Collaborative Value (CV) is derived from three factors, the node's residual energy, the distance vector between nodes and personal device, and the sensor's density in each CH. The CEV algorithm operates i
... Show MoreA novel method for Network Intrusion Detection System (NIDS) has been proposed, based on the concept of how DNA sequence detects disease as both domains have similar conceptual method of detection. Three important steps have been proposed to apply DNA sequence for NIDS: convert the network traffic data into a form of DNA sequence using Cryptography encoding method; discover patterns of Short Tandem Repeats (STR) sequence for each network traffic attack using Teiresias algorithm; and conduct classification process depends upon STR sequence based on Horspool algorithm. 10% KDD Cup 1999 data set is used for training phase. Correct KDD Cup 1999 data set is used for testing phase to evaluate the proposed method. The current experiment results sh
... Show MorePower switches require snubbing networks for driving single – phase industrial heaters. Designing these networks, for controlling the maximum allowable rate of rise of anode current (di/dt) and excessive anode – cathode voltage rise (dv/dt) of power switching devices as thyristors and Triacs, is usually achieved using conventional methods like Time Constant Method (TCM), resonance Method (RM), and Runge-Kutta Method (RKM). In this paper an alternative design methodology using Fuzzy Logic Method (FLM) is proposed for designing the snubber network to control the voltage and current changes. Results of FLM, with fewer rules requirements, show the close similarity with those of conventional design methods in such a network of a Triac drivin
... Show MoreThe water supply network inside the building is of high importance due to direct contact with the user that must be optimally designed to meet the water needs of users. This work aims to review previous research and scientific theories that deal with the design of water networks inside buildings, from calculating the amount of consumption and the optimal distribution of the network, as well as ways to rationalize the use of water by the consumer. The process of pumping domestic water starts from water treatment plants to be fed to the public distribution networks, then reaching a distribution network inside the building till it is provided to the user. The design of the water supply network inside the building is
... Show MoreThis paper describes a new proposed structure of the Proportional Integral Derivative (PID) controller based on modified Elman neural network for the DC-DC buck converter system which is used in battery operation of the portable devices. The Dolphin Echolocation Optimization (DEO) algorithm is considered as a perfect on-line tuning technique therefore, it was used for tuning and obtaining the parameters of the modified Elman neural-PID controller to avoid the local minimum problem during learning the proposed controller. Simulation results show that the best weight parameters of the proposed controller, which are taken from the DEO, lead to find the best action and unsaturated state that will stabilize the Buck converter system performan
... Show MoreA particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.
The drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the
The 3D electro-Fenton technique is, due to its high efficiency, one of the technologies suggested to eliminate organic pollutants in wastewater. The type of particle electrode used in the 3D electro-Fenton process is one of the most crucial variables because of its effect on the formation of reactive species and the source of iron ions. The electrolytic cell in the current study consisted of graphite as an anode, carbon fiber (CF) modified with graphene as a cathode, and iron foam particles as a third electrode. A response surface methodology (RSM) approach was used to optimize the 3D electro-Fenton process. The RSM results revealed that the quadratic model has a high R2 of 99.05 %. At 4 g L-1 iron foam particles, time of 5 h, and
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