This paper presents a classification method using Inertial Measurement Unit (IMU) in order to classify six human upper limb activities. The study was also carried out to investigate whether theses activities are being performed normally or abnormally using two different neural networks: Artificial neural network (ANN) and convolutional neural network (CNN). Human activities that were included in the study: arm flexion and extension, arm pronation and supination, shoulder internal and external rotations. Before activities categorization, training data was obtained by the means of an IMU sensor

Nowadays, the homing guidance is utilized in the existed and under development air defense systems (ADS) to effectively intercept the targets. The targets became smarter and capable to fly and maneuver professionally and the tendency to design missile with a small warhead became greater, then there is a pressure to produce a more precise and accurate missile guidance system based on intelligent algorithms to ensure effective interception of highly maneuverable targets. The aim of this paper is to present an intelligent guidance algorithm that effectively and precisely intercept the

Daily, a big extent of colored, partially treated textile effluents drained into the sanitation systems causing serious environmental concerns. Therefore, the decolorization treatment process of wastewater is crucial to improve effluent quality. In the present study, 3 different sorbent materials, nano zerovalent iron (nZVI), activated carbon (AC), and green-synthesized nano zerovalent iron (GT-nZVI), have been prepared for raw textile wastewater decolourization. The prepared nanomaterials were characterized via X-ray diffraction (XRD) spectroscopy, scanning electron microscopy (SEM), energy

Understanding of deterioration mechanisms in sewers helps asset managers in developing prediction models for estimating whether or not sewer collapse is likely. Effective utilisation of deterioration prediction models along with the development and use of life cycle maintenance cost analysis contribute to reducing operation and maintenance costs in sewer systems. This article presents a model for life-cycle maintenance planning of deteriorating sewer network as a multi-objective optimisation problem that treats the sewer network condition and service life as well as life-cycle maintenance cost

This paper presents a framework for optimizing condition assessment policies by balancing the revealed value of information with the cost of obtaining such information. The computational platform is based on augmenting the asset condition state with an expected level of accuracy. Inaccuracies due to condition assessment reliability are evaluated using the partially observable Markov decision process. The single objective genetic algorithm is used to select the most cost-effective assets to assess considering information inaccuracy under a fixed budget. The model is extended using

With ageing water and sewer infrastructure in North America, assessing the condition of these assets has received increased attention in the past few years. Condition assessment is an integral component in any asset management program. Determining the condition of buried infrastructure tends to be more cumbersome, costly and error-prone compared to other surface infrastructure like roads and buildings. For sewers, CCTV is considered the industry standard for condition assessment technologies. For pressurized water pipelines, technologies tend to be more costly and uncertain (e.g

This paper illustrates the design of proportional–integral–derivative controller (PID) controller of 10 KW air heaters for achieving the set point temperature as fast as possible with minimum response overshoot. Computational fluid dynamic (CFD) numerical simulations are utilized to predict the natural response of 10 KW input power for the air heater. CFD results are validated with experimental empirical correlations that insure the reliability of open loop results. The open loop response of CFD transient simulations is used to model the air heater transfer function and design the classical

This study investigates the feasibility of applying coagulation/flocculation process for real textile wastewater treatment. Batch experiments were performed to detect the optimum performance of four different coagulants; Ferric Sulphate (Fe2(SO4)3), Aluminium Chloride (AlCl3), Aluminium Sulphate (Al2(SO4)3) and Ferric Chloride (FeCl3) at diverse ranges of pH (1–11) on the removal of chemical oxygen demand (COD), total suspended solids (TSS), colour, total nitrogen (TN) and turbidity from real textile wastewater. At pH 9, FeCl3 demonstrated the most effective removal for all studied

The gaining sharing knowledge based optimization algorithm (GSK) is recently developed metaheuristic algorithm, which is based on how humans acquire and share knowledge during their life-time. This paper investigates a modified version of the GSK algorithm to find the best feature subsets. Firstly, it represents a binary variant of GSK algorithm by employing a probability estimation operator (Bi-GSK) on the two main pillars of GSK algorithm. And then, the chaotic maps are used to enhance the performance of the proposed algorithm. Ten different types of chaotic maps are considered to adapt the

In this work, the Artificial Neural Networks (ANN) are used to model a chaotic system. A method based on the Non-dominated Sorting Genetic Algorithm II (NSGA-II) is used to determine the best parameters of a Multilayer Perceptron (MLP) artificial neural network. Using NSGA-II, the optimal connection weights between the input layer and the hidden layer are obtained. Using NSGA-II, the connection weights between the hidden layer and the output layer are also obtained. This ensures the necessary learning to the neural network. The optimized functions by NSGA-II are the number of neurons in the