Prediction of spot welding parameters using fuzzy logic controlling

The Resistance Spot Welding (RSW) represents one of the most important welding processes. The resistance spot welding quality depends on the process parameters like welding current, electrode force and welding time and their chosen levels. In this work, the experimental part is validated by the simulation part, where the last will be used later for predicting the results for new data with a very acceptable percentage of accuracy. This study presents an experimental work of the resistance spot welding for two similar sheets of Austenitic Stainless Steels (AISI 304) that are intended to be held together in one point by the pressure of the electrodes, with high magnitude of electrical current to be applied, where the resistance spot welding parameters (welding current and welding time) are changeable to show each of the parameter’s action on the welded material properties (The Maximum Shear Load that the metal can be subject to besides The Nugget Zone Diameter of the welded contact area). The experimental work in this study delivers genuine and important data that will be the basis for the Fuzzy Logic Controller (FLC), which will be set up then. The Artificial Intelligence (which is presented by the fuzzy logic controller) role is to predict the optimal welded material parameters for any given resistance spot welding parameters, and to discover the probability of expulsion, failure, or breaking in the welding process before it takes place or happens, where in this study, the FLC predicted the optimum value of the maximum shear load for RSW, which occurs at the welding time=20 cycle and the welding current=8 KA, while the estimated optimum value of the Nugget Diameter by FLC for RSW is found at welding time=20 cycle and welding current=8 KA.This prediction will save the metal parts and the electrodes of welding, besides saving the cost and the effor

Prediction of spot welding parameters using fuzzy logic controlling

The Resistance Spot Welding (RSW) represents one of the most important welding processes. The resistance spot welding quality depends on the process parameters like welding current, electrode force and welding time and their chosen levels. In this work, the experimental part is validated by the simulation part, where the last will be used later for predicting the results for new data with a very acceptable percentage of accuracy. This study presents an experimental work of the resistance spot welding for two similar sheets of Austenitic Stainless Steels (AISI 304) that are intended to be held together in one point by the pressure of the electrodes, with high magnitude of electrical current to be applied, where the resistance spot welding parameters (welding current and welding time) are changeable to show each of the parameter’s action on the welded material properties (The Maximum Shear Load that the metal can be subject to besides The Nugget Zone Diameter of the welded contact area). The experimental work in this study delivers genuine and important data that will be the basis for the Fuzzy Logic Controller (FLC), which will be set up then. The Artificial Intelligence (which is presented by the fuzzy logic controller) role is to predict the optimal welded material parameters for any given resistance spot welding parameters, and to discover the probability of expulsion, failure, or breaking in the welding process before it takes place or happens, where in this study, the FLC predicted the optimum value of the maximum shear load for RSW, which occurs at the welding time=20 cycle and the welding current=8 KA, while the estimated optimum value of the Nugget Diameter by FLC for RSW is found at welding time=20 cycle and welding current=8 KA.This prediction will save the metal parts and the electrodes of welding, besides saving the cost and the effor

Pixel steganography method for grayscale image steganography on colour images

The process of hiding secret data within a host signal is known as steganography; its design parameters are imperceptibility, concealment capacity, and recovered data quality. A case of images, one of the existing methods based on modification of the host image pixels is called Block Pixel Hiding Method (BPHM), which has good imperceptibility and high-capacity concealment but does not guarantee the quality of the secret image recovered. This article proposes a method that improves results BPHM based on band selection and search algorithm global called Improved Pixel Hiding Method (IPHM). According to the simulations carried out, the results obtained with IPHM are better than those obtained with BPHM. They are similar to one of the more popular methods in imaging steganography known as Quantization Index Modulation (QIM). Steganography is the method of hiding hidden data within a host signal, with imperceptibility, concealment capacity, and retrieved data quality as design criteria. In the case of images, Block Pixel Hiding Method (BPHM) is one of the available methods based on modifying the host picture pixels, which has good imperceptibility and high-capacity concealment but does not guarantee the quality of the hidden picture recovered. Improved Pixel Hiding Method is a method proposed in this article that improves BPHM outcomes by using band selection and a global search algorithm (IPHM). The results obtained using IPHM are better than those achieved with BPHM, according to simulations. They're related to Quantization Index Modulation, which is one of the most widely used picture steganography techniques (QIM)

Random Forest-Based Approach for Maximum Power Point Tracking of Photovoltaic Systems Operating under Actual Environmental Conditions

Many maximum power point tracking (MPPT) algorithms have been developed in recent years to maximize the produced PV energy. These algorithms are not sufficiently robust because of fast-changing environmental conditions, efficiency, accuracy at steady-state value, and dynamics of the tracking algorithm. Thus, this paper proposes a new random forest (RF) model to improve MPPT performance. The RF model has the ability to capture the nonlinear association of patterns between predictors, such as irradiance and temperature, to determine accurate maximum power point. A RF-based tracker is designed for 25 SolarTIFSTF-120P6 PV modules, with the capacity of 3 kW peak using two high-speed sensors. For this purpose, a complete PV system is modeled using 300,000 data samples and simulated using the MATLAB/SIMULINK package. The proposed RF-based MPPT is then tested under actual environmental conditions for 24 days to validate the accuracy and dynamic response. The response of the RF-based MPPT model is also compared with that of the artificial neural network and adaptive neurofuzzy inference system algorithms for further validation. The results show that the proposed MPPT technique gives significant improvement compared with that of other techniques. In addition, the RF model passes the Bland–Altman test, with more than 95 percent acceptability

An Improved Fuzzy Logic Controller Design for PV Inverters Utilizing Differential Search Optimization

This paper presents an adaptive fuzzy logic controller (FLC) design technique for photovoltaic (PV) inverters using differential search algorithm (DSA). This technique avoids the exhaustive traditional trial and error procedure in obtaining membership functions (MFs) used in conventional FLCs. This technique is implemented during the inverter design phase by generating adaptive MFs based on the evaluation results of the objective function formulated by the DSA. In this work, the mean square error (MSE) of the inverter output voltage is used as an objective function. The DSA optimizes the MFs such that the inverter provides the lowest MSE for output voltage and improves the performance of the PV inverter output in terms of amplitude and frequency. The design procedure and accuracy of the optimum FLC are illustrated and investigated using simulations conducted for a 3 kW three-phase inverter in a MATLAB/Simulink environment. Results show that the proposed controller can successfully obtain the desired output when different linear and nonlinear loads are connected to the system. Furthermore, the inverter has reasonably low steady state error and fast response to reference variation

Emerging wireless communication technologies in Iraqi government: Exploring cloud, edge, and fog computing

This study aims to structure the implementation of a governmental cloud of things (CoT), edge computing (EC), and fog computing in Iraq in the context of sustainable wireless communication. A base of literature was built that included any challenges, opportunities, and best practices relevant to these innovative technologies to set up the background for this paper. A concept model was created that included core components (cognitive technologies and fog computing), key processes (resource analysis, infrastructure design), and stakeholders (governments, industry, community). A strategic methodology made up of stakeholder involvement, capacity building, and pilot projects was used in the project. Concerning IoT planned deployment and services provision, network infrastructure was put in place to support the devices and a higher level of security measures were recommended. Using scenario hypothesis, MATLAB simulator was employed to simulate data value distribution as well as received power distribution based on different institutions for 12 months. Monitoring and evaluation should be followed to measure performance indicators and effects on this process. Continuously improvement strategies were the highlight of the session which further stimulated innovations. Acquainted projects will be put in the function to extend the range of activities by including additional government agencies, regions, or sectors. Reporting of the collected data and funding will be done with stakeholders to share and pool knowledge

Prevalence of restless legs syndrome in pregnant women: a systematic review and meta-analysis

BACKGROUND: Restless legs syndrome (RLS) is a neurological disorder characterized by sleep disorders, which leads to adverse health consequences in the mother and fetus. Studies have reported different prevalence rates for RLS in pregnant women. This systematic review and meta-analysis aimed to estimate the prevalence of RLS in pregnant women. METHODS: A literature search was performed via national and international databases, including Scientific Information Database (SID), MagIran, IranMedex, Google Scholar, Science Direct, PubMed, ProQuest, and Scopus. In total, 31 articles were selected without a time limit. The random effects model was used to analyze the data, and the heterogeneity between the studies was examined using the I2 index. The analyses were performed in the Stata software, version 12 and R, version 4. RESULTS: The reviewed studies (n=31) were conducted on a total sample size of 59,151, and the prevalence of RLS in pregnant women was estimated at 21.4% [95% confidence interval CI: 17.7-25.1]. Asia with a prevalence rate of 18.5%, [95% CI: 13.8-23.1] and Europe with a prevalence rate of 25.5%, [95% CI: 19.5-31.6] had the lowest and highest RLS prevalence, respectively. No significant correlations were observed between the prevalence of RLS, publication year of the articles (P=0.972), and participants' age (P=0.202). CONCLUSION: According to the results, RLS is highly common in pregnant women, and it is essential to identify women with RLS to control and eliminate the adverse consequences of the disorder

Effect of Testosterone on Lead Acetate Toxicity in Male Albino Rats

The toxicity of lead acetate (L. A.) concerned to public health disruptor due to its persistence in the environment and it has the adverse influence on the human and animal health as well. It causes physiological,biochemical, and neurological dysfunctions in humans. Histologically it has a negative effect on the liver which is considered one of the major target organs where acts as detoxification machine by elimination the toxic substance from the blood in rich with it.  As well as it affects kidneys that are the two of the most filtering organs. Therefore the present study was aimed to investigate the histopathological effect of L.A. on liver and kidney tissues in male rats. Twenty male rats involved in the study were equally and randomly divided into two groups each of them involved 10 animals. Group I (castrated rats) and Group II (control) each group received 80mg/L of lead acetate dissolved in one liter distilled water by drinking for 15 days. Histological sections showed some alterations including abnormal architecture, cell degeneration, nuclear degeneration, hyperchromatic hepatocytes, immune cells, degeneration in tubules, dilation in sinusoids, dilation in central vein of liver increased bowman's space glomerular atrophy degeneration of tubular cells in liver and kidney tissues of rats in castrated rats from control group. But the size of degenerated tissue was more severe in castrated male rats. It was concluded that the castration process could produce a hypogonadism and decreased testosterone which owns many receptors in kidney and liver may produce adverse influence with L.A. administration

An Improved Walsh Function Algorithm for Use in Sinusoidal and Nonsinusoidal Power Components Measurement

This paper presents an improved Walsh function IWF algorithms as an alternative approach for active and reactive powers measurement in linear and nonlinear, balanced and unbalanced sinusoidal three-phase load system. It takes advantage of Walsh function unified approach, simple algorithm and its intrinsic high level of accuracy as a result of coefficient characteristics and energy behaviour representation. The developed algorithm was modeled on the Matlab Simulink software; different types of load, linear and nonlinear, were also modeled based on practical voltage and current waveforms and tested with the proposed improved Walsh algorithms. The IEEE standard 1459-2000 which is based on fast Fourier transform FFT approach was used as benchmark for the linear load system. The data obtained from laboratory experiment to determine power components in harmonic load systems using Fluke 435 power quality analyzer PQA which complies with IEC/EN61010-1-2001 standard was modeled and used to validate the improved algorithm for nonlinear load measurement. The results showed that the algorithm has the potential to effectively measure three-phase power components under different load conditions