Wireless sensor applications are susceptible to energy constraints. Most of the energy is consumed in communication between wireless nodes. Clustering and data aggregation are the two widely used strategies for reducing energy usage and increasing the lifetime of wireless sensor networks. In target tracking applications, large amount of redundant data is produced regularly. Hence, deployment of effective data aggregation schemes is vital to eliminate data redundancy. This work aims to conduct a comparative study of various research approaches that employ clustering techniques for efficiently aggregating data in target tracking applications as selection of an appropriate clustering algorithm may reflect positive results in the data aggregati

In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func

Background: Prolapsed intervertebral disc is an important and common cause of low backache. MRI has now become universally accepted investigation for prolapsed intervertebral disc. We, however, regularly come across situations, when MRI shows diffuse disc bulges, even at multiple levels, which cannot be correlated clinically and when such cases are operated, no significant disc prolapse is found resulting in negative exploration. Objective: To evaluate the role of M.R.I. finding not only for diagnosis of disc herniation at lumbar region but also for localization the level of herniation Methods: A prospective study on seventy five symptomatic low backache and MRI confirmed prolapsed intervertebral disc patients at lumbo-sacral region were op

Introduction and Aim: Diabetes mellitus patients almost always struggle with a metabolic condition known as chronic hyperglycemia. According to the World Health Organization, osteoporosis is a progressive systemic skeletal disorder that is characterized by decreasing bone mass and microstructural breakdown of bone tissue that increases susceptibility to fracture and increased risk of breaking a bone. Here, we aimed to compare the levels of CatK and total oxidative state in patients with diabetes and osteoporosis among the female Iraqi population and study the possible relationship between them. Materials and Methods: This study included 40 females with diabetes (Group G1), 40 with diabetes and osteoporosis (Group G2) and 40 normal healthy f

The instant global trend towards developing tight reservoir is great; however, development can be very challenging due to stress and geomechanical properties effect in horizontal well placement and hydraulic fracturing design. Many parameters are known to be important to determine the suitable layer for locating horizontal well such as petrophysical and geomechanical properties. In the present study, permeability sensitivity to stress is also considered in the best layer selection for well placement. The permeability sensitivity to the stress of the layers was investigated using measurements of 27 core sample at different confining stress values. 1-D mechanical earth model (MEM) was built and converted to a 3-D full-field geomechanical mode

In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha

The ability to inhibit corrosion of low carbon steel in a salt solution (3.5%NaCl) has been checked with three real expired drugs (Cloxacillin, Amoxicillin, Ceflaxin) with variable concentrations (0, 250, 500, 750) mg/L were examined in the weight loss. The inhibition efficiency of the Cloxacillin 750 mg/L showed the highest value (82.8125 %) and the best inhibitor of the rest of the antibiotics. The different concentrations of Cloxacillin drug (0, 250, 500, 750) mg/L and temperature (25, 35, 45, 55) ^oC were studied as variables with potentiodynamic polarization, Scanning Electron Microscopy (SEM) for surface morphology and electrochemical impedance spectroscopy (EIS) depending on current values and the resistance of charge to

This paper introduces a non-conventional approach with multi-dimensional random sampling to solve a cocaine abuse model with statistical probability. The mean Latin hypercube finite difference (MLHFD) method is proposed for the first time via hybrid integration of the classical numerical finite difference (FD) formula with Latin hypercube sampling (LHS) technique to create a random distribution for the model parameters which are dependent on time [Formula: see text]. The LHS technique gives advantage to MLHFD method to produce fast variation of the parameters’ values via number of multidimensional simulations (100, 1000 and 5000). The generated Latin hypercube sample which is random or non-deterministic in nature is further integ

Flexible job-shop scheduling problem (FJSP) is one of the instances in flexible manufacturing systems. It is considered as a very complex to control. Hence generating a control system for this problem domain is difficult. FJSP inherits the job-shop scheduling problem characteristics. It has an additional decision level to the sequencing one which allows the operations to be processed on any machine among a set of available machines at a facility. In this article, we present Artificial Fish Swarm Algorithm with Harmony Search for solving the flexible job shop scheduling problem. It is based on the new harmony improvised from results obtained by artificial fish swarm algorithm. This improvised solution is sent to comparison to an overall best