The extraction process of chlorophyll from dehydrated and pulverized alfalfa plant were studied by percolation method. Two  solvent systems were used for the extraction namely; Ethanol-water and Hexane-Toluene systems . The effect of circulation rate, solvent concentration, and solvent volume to solid weight ratio were studied. In  both ethanol water, and Hexane-Toluene systems it appears that solvent concentration is the most effective variable.

Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

An intrusion detection system (IDS) is key to having a comprehensive cybersecurity solution against any attack, and artificial intelligence techniques have been combined with all the features of the IoT to improve security. In response to this, in this research, an IDS technique driven by a modified random forest algorithm has been formulated to improve the system for IoT. To this end, the target is made as one-hot encoding, bootstrapping with less redundancy, adding a hybrid features selection method into the random forest algorithm, and modifying the ranking stage in the random forest algorithm. Furthermore, three datasets have been used in this research, IoTID20, UNSW-NB15, and IoT-23. The results are compared with the three datasets men

Some of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems.  Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic.  Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance.  In this study, two different sets of select

When Romanticism had passed since its appearance at the end of the eighteenth century, it seemed that this important intellectual and philosophical development had been absent but not really lost. Romanticism remained in the poems of poets, philosophers and writers even after they had escaped cultural life in general. If it is difficult to itemize all the principles of romance, the apparent is the assertion of individualism and the love of autism with nature and its potential with its mysteries as well as the glorification of emotion, compared to the mental orientation of the writers in the seventeenth century in their classical approach. The language is the most important to what the Romans have proven in their poetry and their artistic wo

High vehicular mobility causes frequent changes in the density of vehicles, discontinuity in inter-vehicle communication, and constraints for routing protocols in vehicular ad hoc networks (VANETs). The routing must avoid forwarding packets through segments with low network density and high scale of network disconnections that may result in packet loss, delays, and increased communication overhead in route recovery. Therefore, both traffic and segment status must be considered. This paper presents real-time intersection-based segment aware routing (RTISAR), an intersection-based segment aware algorithm for geographic routing in VANETs. This routing algorithm provides an optimal route for forwarding the data packets toward their destination

Cryptographic applications demand much more of a pseudo-random-sequence
generator than do most other applications. Cryptographic randomness does not mean just
statistical randomness, although that is part of it. For a sequence to be cryptographically
secure pseudo-random, it must be unpredictable.
The random sequences should satisfy the basic randomness postulates; one of them is
the run postulate (sequences of the same bit). These sequences should have about the same
number of ones and zeros, about half the runs should be of length one, one quarter of length
two, one eighth of length three, and so on.The distribution of run lengths for zeros and ones
should be the same. These properties can be measured determinis