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 in the following manner: CHs are dynamically selected in each transmission round based on the nodes' CVs. The algorithm considered the patient's condition classification to guarantee safety and attain a response speed appropriate for their current state. So, data is categorized into Very-Critical, Critical, and Normal data classes using the supervised learning vector quantization (LVQ) classifier. Very Critical data is sent to the emergency center to dispatch an ambulance, Critical data is transmitted to a doctor, and Normal data is sent to a data center. This methodology promotes efficient and reliable intra-network communication, ensuring prompt and precise data transmission, and reducing frequent recharging. Comparative analyses reveal that the proposed algorithm outperforms ERRS (Energy-Efficient and Reliable Routing Scheme) and LEACH (low energy adaptive clustering hierarchy) regarding network longevity by 27% and 33%, augmenting network stability by 12% and 45% over the aforementioned protocols, respectively. The performance was conducted in OMNeT++ simulator
Localization is an essential demand in wireless sensor networks (WSNs). It relies on several types of measurements. This paper focuses on positioning in 3-D space using time-of-arrival- (TOA-) based distance measurements between the target node and a number of anchor nodes. Central localization is assumed and either RF, acoustic or UWB signals are used for distance measurements. This problem is treated by using iterative gradient descent (GD), and an iterative GD-based algorithm for localization of moving sensors in a WSN has been proposed. To localize a node in 3-D space, at least four anchors are needed. In this work, however, five anchors are used to get better accuracy. In GD localization of a moving sensor, the algo
... Show MoreThis study aims to determine the impact of organization values as an independent variable across its dimensions (organization management values, organization mission values, relations management values, and environment management values) on achieve the strategic success which is the dependent variable and include its dimensions (environmental analysis, creative thinking, strategic decision, effective implementation, and leadership capacities). The study is conducted in the Iraq Oil Ministry. It deployed the analytical descriptive approach. It focuses on the study problem enquiries throughout addressing several principal and sub-hypothesizes in regards to cause and effect relationship. To achieve this result
... Show MoreThe purpose of this paper is to gain a good understanding about wake region behind the car body due to the aerodynamic effect when the air flows over the road vehicle during its movement. The main goal of this study is to discuss the effect of the geometry on the wake region and the aerodynamic drag coefficient. Results will be achieved by using two different shapes, which are the fastback and the notchback. The study will be implemented by the Computational Fluid Dynamic (CFD) by using STAR-CCM+® software for the simulation. This study investigates the steady turbulent flow using k-epsilon turbulence model. The results obtained from the simulation show that the region of the air separation behind the vehicle
... Show MoreThe performance of sewage pumps stations affected by many factors through its work time which produce undesired transportation efficiency. This paper is focus on the use of artificial neural network and multiple linear regression (MLR) models for prediction the major sewage pump station in Baghdad city. The data used in this work were obtained from Al-Habibia sewage pump station during specified records- three years in Al-Karkh district, Baghdad. Pumping capability of the stations was recognized by considering the influent input importance of discharge, total suspended solids (TSS) and biological oxygen demand (BOD). In addition, the chemical oxygen demands (COD), pH and chloride (Cl). The proposed model performanc
... Show MoreThe Experiment was carried out to determine the level vibration transfer in three axes Horizontal X, Lateral Y and Vertical Z direction to seat driver tractor, Vector sum of vibration and Daily Vibration Exposure (8 hours) in seat driver tractor, and vibration in steering wheel tractor, Heart Rate, Systolic and Diastolic blood pressure and temperature were measure to all Drivers before and after used Chisel plow in operation tillage. Statistical analysis system was used, Split-Split Plot Design under Randomized Complete Block Design, Three factors were used in this experiment included Two types of Soil Moist and Dry soil which represented main plot, Three Velocity Tractor was second factor included 1.6,3.5 and 5.4 km/hr and Three Drivers Tr
... Show MoreDue to the urgent need to develop technologies for continuous glucose monitoring in diabetes individuals, poten tial research has been applied by invoking the microwave tech niques. Therefore, this work presents a novel technique based on a single port microwave circuit, antenna structure, based on Metamaterial (MTM) transmission line defected patch for sensing the blood glucose level in noninvasive process. For that, the proposed antenna is invoked to measure the blood glu cose through the field leakages penetrated to the human blood through the skin. The proposed sensor is constructed from a closed loop connected to an interdigital capacitor to magnify the electric field fringing at the patch center. The proposed an tenna sensor i
... Show MoreThe objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.
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