The frequent and widespread use of medicines and personal care products, particularly in the residential environment, tends to raise concerns about environmental and human health impacts. On the other hand, carbon dioxide accumulation in the atmosphere is a problem with numerous environmental consequences. Microalgae are being used to bioremediate toxins and capture CO2. The current study aimed to confirm the possibility of removing pharmaceutical contaminant (Ranitidine) at different concentrations by using the Chlorella Sorokiniana MH923013 microalgae strain during the growth time. As part of the experiment, carbon dioxide was added to the culture medium three times per week. Explanatory results revealed that gas doses directly affect microalgae growth and removal efficiency, as evidenced by faster and more productive cell adaptation compared to control cultures. The development profile of microalgae is significantly influenced by pure carbon dioxide bubbles. When compared to control flasks, carbon dioxide increased the specific growth rate and doubling time. During the 312 hours microalgae cultivation period, the Chlorella strain recorded the highest pollutant removal efficiency (58%), particularly at the pollutant concentration of 5 mg/l CO2.
In this study, a fast block matching search algorithm based on blocks' descriptors and multilevel blocks filtering is introduced. The used descriptors are the mean and a set of centralized low order moments. Hierarchal filtering and MAE similarity measure were adopted to nominate the best similar blocks lay within the pool of neighbor blocks. As next step to blocks nomination the similarity of the mean and moments is used to classify the nominated blocks and put them in one of three sub-pools, each one represents certain nomination priority level (i.e., most, less & least level). The main reason of the introducing nomination and classification steps is a significant reduction in the number of matching instances of the pixels belong to the c
... Show MoreIn This paper, sky radio emission background level associated with radio storm burst for the Sun and Jupiter is determined at frequency (20.1 MHz). The observation data for radio Jove telescope for the Sun and Jupiter radio storm observations data are loaded from NASA radio Jove telescope website, the data of Sunspot number are loaded from National Geophysical Data Center, (NGDC). Two radio Jove stations [(Sula, MT), (Lamy, NM)] are chose from data website for these huge observations data. For the Sun, twelve figures are used to determine the relation between radio background emission, and the daily Sunspot number. For Jupiter a twenty four figures are used to determine the relation between radio background emission and diffraction betwe
... Show MoreNanosilica was extracted from rice husk, which was locally collected from the Iraqi mill at Al-Mishikhab district in Najaf Governorate, Iraq. The precipitation method was used to prepared Nanosilica powder from rice husk ash, after treating it thermally at 700°C, followed by dissolving the silica in the alkaline solution and getting a sodium silicate solution. Two samples of the final solution were collected to study the effect of filtration on the purity of the sample by X-ray fluorescence spectrometry (XRF). The result shows that the filtered samples have purity above while the non-filtered sample purity was around The structure analysis investigated by the X-ray diffraction (XRD), found that the Nanosilica powder has an amorphous
... Show MoreThe Enhanced Thematic Mapper Plus (ETM+) that loaded onboard the Landsat-7 satellite was launched on 15 April 1999. After 4 years, the image collected by this sensor was greatly impacted by the failure of the system’s Scan Line Corrector (SLC), a radiometry error.The median filter is one of the basic building blocks in many image processing situations. Digital images are often distorted by impulse noise due to errors generated by the noise sensor, errors that occur during the conversion of signals from analog-to-digital, as well as errors generated in communication channels. This error inevitably leads to a change in the intensity of some pixels, while some pixels remain unchanged. To remove impulse noise and improve the quality of the
... Show MoreThe goal of this research is to develop a numerical model that can be used to simulate the sedimentation process under two scenarios: first, the flocculation unit is on duty, and second, the flocculation unit is out of commission. The general equation of flow and sediment transport were solved using the finite difference method, then coded using Matlab software. The result of this study was: the difference in removal efficiency between the coded model and operational model for each particle size dataset was very close, with a difference value of +3.01%, indicating that the model can be used to predict the removal efficiency of a rectangular sedimentation basin. The study also revealed
The Adaptive Optics technique has been developed to obtain the correction of atmospheric seeing. The purpose of this study is to use the MATLAB program to investigate the performance of an AO system with the most recent AO simulation tools, Objected-Oriented Matlab Adaptive Optics (OOMAO). This was achieved by studying the variables that impact image quality correction, such as observation wavelength bands, atmospheric parameters, telescope parameters, deformable mirror parameters, wavefront sensor parameters, and noise parameters. The results presented a detailed analysis of the factors that influence the image correction process as well as the impact of the AO components on that process
Surveillance cameras are video cameras used for the purpose of observing an area. They are often connected to a recording device or IP network, and may be watched by a security guard or law enforcement officer. In case of location have less percentage of movement (like home courtyard during night); then we need to check whole recorded video to show where and when that motion occur which are wasting in time. So this paper aims at processing the real time video captured by a Webcam to detect motion in the Scene using MATLAB 2012a, with keeping in mind that camera still recorded which means real time detection. The results show accuracy and efficiency in detecting motion