In recent years, it has been evident that searching for alternative methods with low-price and eco-friendly features that produce high-quality adsorbents is in high demand. In the present work, Rice husk from Iraqi rice named (Amber) had been used as the primary source to produce rice husk ash (RHA) for the removal of the antibiotic metronidazole (Flagyl) from water. After optimum drying of rice husk, rice husk ash (RHA) was obtained at 600 °C using an electric oven. RHA has been investigated for properties using X-ray diffraction (XRD), porosity, and surface area (SA). The experimental work adsorption data were optimized to evaluate Langmuir and Freundlich constants. The thermodynamic parameters likely a change in Gipp's energy (ΔG), enthalpy (ΔH), and entropy (ΔS). The impacts of increasing temperature on adsorption capacity were investigated, and the results indicate that the pseudo-second-order kinetics model could be presented the dynamic adsorption data that it has. The resultant values for the heat of adsorption and the free energy indicated that adsorption of Flagyl is preferred at low temperatures.
Background: Sperm motility disorder is an important cause of infertility in male, and one of the causes of reduced motility of the sperm is the disorders of the mitochondria because it provides the required energy for sperm motility, Laser biostimulation or low-level laser therapy has a positive effect on the mitochondria and led to increasing the synthesis of ATP. Method: Twenty fresh human semen samples were used in this research study, each sample was separated into two portions, one was used as control which is not exposed to the laser beam and the other was irradiated with the wavelength of 410 nm diode laser with an output power of 100 mW and an exposure time of 60 seconds, then the measurement of
... Show MoreDust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system
... Show MoreIn cyber security, the most crucial subject in information security is user authentication. Robust text-based password methods may offer a certain level of protection. Strong passwords are hard to remember, though, so people who use them frequently write them on paper or store them in file for computer .Numerous of computer systems, networks, and Internet-based environments have experimented with using graphical authentication techniques for user authentication in recent years. The two main characteristics of all graphical passwords are their security and usability. Regretfully, none of these methods could adequately address both of these factors concurrently. The ISO usability standards and associated characteristics for graphical
... Show MoreSecure information transmission over the internet is becoming an important requirement in data communication. These days, authenticity, secrecy, and confidentiality are the most important concerns in securing data communication. For that reason, information hiding methods are used, such as Cryptography, Steganography and Watermarking methods, to secure data transmission, where cryptography method is used to encrypt the information in an unreadable form. At the same time, steganography covers the information within images, audio or video. Finally, watermarking is used to protect information from intruders. This paper proposed a new cryptography method by using thre
... Show MoreEmotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In
... Show MoreTolerance and its impact on building society