Solid waste is a major issue in today's world. Which can be a contributing factor to pollution and the spread of vector-borne diseases. Because of its complicated nonlinear processes, this problem is difficult to model and optimize using traditional methods. In this study, a mathematical model was developed to optimize the cost of solid waste recycling and management. In the optimization phase, the salp swarm algorithm (SSA) is utilized to determine the level of discarded solid waste and reclaimed solid waste. An optimization technique SSA is a new method of finding the ideal solution for a mathematical relationship based on leaders and followers. It takes a lot of random solutions, as well as their outward or inward fluctuations, to find the optimal solution. This method also included multiple adaptive and random variables to guarantee that the solution space was explored and used in various optimization tasks. When all criteria are considered, the results of this study show that the SSA is efficient for least-distance path allocation. The simulation findings reveal a significant improvement over the well-known particle swarm optimization (PSO) algorithm, with recycling and disposal costs decreasing by 10% to 30%.
Wireless Body Area Network (WBAN) is a tool that improves real-time patient health observation in hospitals, asylums, especially at home. WBAN has grown popularity in recent years due to its critical role and vast range of medical applications. Due to the sensitive nature of the patient information being transmitted through the WBAN network, security is of paramount importance. To guarantee the safe movement of data between sensor nodes and various WBAN networks, a high level of security is required in a WBAN network. This research introduces a novel technique named Integrated Grasshopper Optimization Algorithm with Artificial Neural Network (IGO-ANN) for distinguishing between trusted nodes in WBAN networks by means of a classifica
... Show MoreIn this paper, the speed control of the real DC motor is experimentally investigated using nonlinear PID neural network controller. As a simple and fast tuning algorithm, two optimization techniques are used; trial and error method and particle swarm optimization PSO algorithm in order to tune the nonlinear PID neural controller's parameters and to find best speed response of the DC motor. To save time in the real system, a Matlab simulation package is used to carry out these algorithms to tune and find the best values of the nonlinear PID parameters. Then these parameters are used in the designed real time nonlinear PID controller system based on LabVIEW package. Simulation and experimental results are compared with each other and showe
... Show MoreThe Current status of biomedical waste of solid, liquid and gaseous formulations from medical and educational laboratories in Iraqi universities and research centers was assessed using a well-structured questionnaire. The questionnaire was distributed to scientists, researchers, medical technicians and graduate students who are directly involved in laboratoiy daily activities. The responses were analyzed statistically and interpreted accordingly. The results showed diat the frequency of questionnaire respondent's affiliation gave the highest percentage frequency (69.4%) with the questionnaire of Technical Medical Institute/Al-Mansour while constitute die responses of the Dnig Control Department/Ministry of Sciences and Technology gave the l
... Show MoreFuture wireless networks will require advance physical-layer techniques to meet the requirements of Internet of Everything (IoE) applications and massive communication systems. To this end, a massive MIMO (m-MIMO) system is to date considered one of the key technologies for future wireless networks. This is due to the capability of m-MIMO to bring a significant improvement in the spectral efficiency and energy efficiency. However, designing an efficient downlink (DL) training sequence for fast channel state information (CSI) estimation, i.e., with limited coherence time, in a frequency division duplex (FDD) m-MIMO system when users exhibit different correlation patterns, i.e., span distinct channel covariance matrices, is to date ve
... Show MoreObjective(s): The aim of this study is to determine the effectiveness of education program on Health Care Workers’ practices toward Primary Health Care Centers waste management and to identify the relationship between these practices and the demographic characteristics of the health workers. Methodology: A quasi- experimental design (pre-post tests) has been used in the present study for the period of November 16th 2014 to June 22nd 2015 .The allocated sample in the present study is consisted of (60) health care worker. The sample was randomly divided into two groups of (30) health care workers each. The stu
Increase in unconventional resources of calcium (Ca+2) for fowls, aquaculture and native animals was improved. This work was planned to define the most polymorph of calcium carbonate (CaCO3) that take place in the two types of chicken eggshells (local and imported type). In this research, the comparative analysis of calcium carbonate (CaCO3) content was approved for nominated eggshells of native strain and imported chicken via Field Emission Scanning Electron Microscope (FESEM), Transmission Electron Microscope (TEM), Fourier-Transform Infrared Spectroscopy (FTIR) and Powder X-Ray Diffraction (PXRD) analysis. The results demonstrate that native and imported chicken eggshells comprise calcite morph that ha
... Show MoreGas-lift technique plays an important role in sustaining oil production, especially from a mature field when the reservoirs’ natural energy becomes insufficient. However, optimally allocation of the gas injection rate in a large field through its gas-lift network system towards maximization of oil production rate is a challenging task. The conventional gas-lift optimization problems may become inefficient and incapable of modelling the gas-lift optimization in a large network system with problems associated with multi-objective, multi-constrained, and limited gas injection rate. The key objective of this study is to assess the feasibility of utilizing the Genetic Algorithm (GA) technique to optimize t