Microcontroller Servomotor for Maximum Effective Power Point for Solar Cell System

In this paper a Maximum Power point (MPP) tracking algorithm is developed using dual-axis servomotor feedback tracking control system. An efficient and accurate servomotor system is used to increase the system efficiency and reduces the solar cell system coast. The proposed automatic servo control system based on PIC microcontroller which is used to control the photovoltaic (PV) modules. This servo system will track the sun rays in order to get MPP during the day using direct radiation. A photo cell is used to sense the direct sun radiation and feedback a signal to the PIC microcontroller, and then the decisions are made through the microcontroller and send a command to the servomotor system to achieve maximum power generation. The proposed system is demonstrated through simulation results. Finally, using the proposed system based on PIC microcontroller, the system will be more efficient, minimum cost, and maximum power transfer is obtained

MOLECULAR DETECTION OF SOME VIRULENCE GENE IN Proteus Mirabilis ISOLATED FROM URINARY TRACT INFECTION IN IRAQ

This study was concentrated for isolation and identification of 60 (35.2%) Proteus mirabilis isolates out of 170 urine samples from patients suffering from urinary tract infection  from different hospitals in Baghdad city during a period from September 2020 to January 2021. The isolates were cultivated on selective media and biochemical reactions were used to identify them confirmatory APi 20 E tests. The sixty selected isolates were tested for resistance against four antibiotics. The results shown that there were differences in the antibiotic resistance of isolates. High resistance to nalidixic acid and ampicillin were found among isolates as (75%) and (51%) respectively while the resistance of Proteus mirabilis isolates to amikacin and impenem, were(8.3%). Some important virulence factor to Proteus mirabilis was detected by using molecular techniques include PCR and it was found that only 18 (60%) of isolates gave positive result for rsbA at 467 bp. 27 (90%) of them gave positive result for luxS at 464 bp

Neuro-Fuzzy SVD Technique for Image Recognition and Safety in Construction Site

This paper presents a novel computer vision technique of intelligent recognition of safety in construction sites. The proposed technique relies on a new methodology for Neuro-Fuzzy Singular Value Decomposition (NFSVD). This methodology utilized unmanned safety worker’s wears. Where within a construction site entranced a multi-camera is used and fixed on a special frame inside the security Cabin. Before the workers allowed for entering the construction site, an automatic detecting, and an intelligent matching system has the ability to recognize the worker’s dress shapes and colors through a multi snap image. To improve the success of this methodology, the proposed technique empirically investigated, analyzed and verified to check the image frame quality, accept and reject indication, real-time complexity, diffusion, confusion and PSNR. The results performed by this technique demonstrated the robustness and reliability of this methodology for safety in the construction field

Forecasting Weekly COVID-19 Infection and Death Cases in Iraq Using an ARIMA Model

Coronavirus (COVID-19) is a contagious disease by SARS-CoV-2 that causes the extreme respiratory disorder. The virus has caused a global crisis that has had repercussions on public health, well-being, and all aspects of public and economic life. Infrastructure, information sources, preventive measures, treatment protocols, and various other resources have been put in place worldwide to combat the growth of this deadly disease. This study used the "AutoRegressive Integrated Moving Average" (ARIMA) forecasting technique to estimate the weekly confirmed cases and deaths from the coronavirus epidemic in Iraq. The data collection period was June 1, 2020, until August 31, 2021. The findings demonstrated the model's high accuracy, with an RMSE of 24.168 for the training data and 32.794 for the testing data