In recent years, with the growing size and the importance of computer networks, it is very necessary to provide adequate protection for users data from snooping through the use of one of the protection techniques: encryption, firewall and intrusion detection systems etc. Intrusion detection systems is considered one of the most important components in the computer networks that deal with Network security problems. In this research, we suggested the intrusion detection and classification system through merging Fuzzy logic and Artificial Bee Colony Algorithm. Fuzzy logic has been used to build a classifier which has the ability to distinguish between the behavior of the normal user and behavior of the intruder. The artificial bee colony algorithm has been used to build the classifier which was used to classify the intrusion into one of the main types (DoS, R2L , U2R, Prob). The proposed system has the ability to detect and classify intrusion at high speed with a small percentage of false alarms as well as to detect the new attacks. The NSL-KDD dataset used in the training and testing the proposed system.The results of experiments showed that the efficiency of the proposed system performance were (97.59%) for the intrusion detection, and (0.12%) for the false alarms. Also, the Classification rates for classes (DoS, R2L,U2R,Prob) were (97.19, 77.09, 98.43, 93.23) Respectively, which is considered a superior performance comparing with other methods in the literature.
The manual classification of oranges according to their ripeness or flavor takes a long time; furthermore, the classification of ripeness or sweetness by the intensity of the fruit’s color is not uniform between fruit varieties. Sweetness and color are important factors in evaluating the fruits, the fruit’s color may affect the perception of its sweetness. This article aims to study the possibility of predicting the sweetness of orange fruits based on artificial intelligence technology by studying the relationship between the RGB values of orange fruits and the sweetness of those fruits by using the Orange data mining tool. The experiment has applied machine learning algorithms to an orange fruit image dataset and performed a co
... Show More
(20)
(14)
Abstract—The upper limb amputation exerts a significant burden on the amputee, limiting their ability to perform everyday activities, and degrading their quality of life. Amputee patients’ quality of life can be improved if they have natural control over their prosthetic hands. Among the biological signals, most commonly used to predict upper limb motor intentions, surface electromyography (sEMG), and axial acceleration sensor signals are essential components of shoulder-level upper limb prosthetic hand control systems. In this work, a pattern recognition system is proposed to create a plan for categorizing high-level upper limb prostheses in seven various types of shoulder girdle motions. Thus, combining seven feature groups, w
... Show More
(1)
Vehicular ad hoc networks (VANETs) are considered an emerging technology in the industrial and educational fields. This technology is essential in the deployment of the intelligent transportation system, which is targeted to improve safety and efficiency of traffic. The implementation of VANETs can be effectively executed by transmitting data among vehicles with the use of multiple hops. However, the intrinsic characteristics of VANETs, such as its dynamic network topology and intermittent connectivity, limit data delivery. One particular challenge of this network is the possibility that the contributing node may only remain in the network for a limited time. Hence, to prevent data loss from that node, the information must reach the destina
... Show More
(34)
(29)
Tissue culture of Catharanthus roseus was established under many parameters to insure good results for detection of the alkaloids present in this plant . It was found that NItsch and Nitsch medium containing 8µM Benzyladeninpurine plus Naphalene acetic acid were the best and the callus of C.roseus left to grow in the dark and had much better influence for the production of Alkloids. The precursor phenylalanine showed a better result than other precursor( tryptophan ) . Abscisic acid has an inhibitory effect on the production of Alkaloid
Photoacoustic is a unique imaging method that combines the absorption contrast of light or radio frequency waves with ultrasound resolution. When the deposition of this energy is sufficiently short, a thermo-elastic expansion takes place whereby acoustic waves are generated. These waves can be recorded and stored to construct an image. This work presents experimental procedure of laser photoacoustic two dimensional imaging to detect tumor embedded within normal tissue. The experimental work is accomplished using phantoms that are sandwiched from fish heart or blood sac (simulating a tumor) 1-14mm mean diameter embedded within chicken breast to simulate a real tissue. Nd: YAG laser of 1.064μm and 532nm wavelengths, 10ns pulse duration, 4
... Show MoreHeart disease identification is one of the most challenging task that requires highly experienced cardiologists. However, in developing nations such as Ethiopia, there are a few cardiologists and heart disease detection is more challenging. As an alternative solution to cardiologist, this study proposed a more effective model for heart disease detection by employing random forest and sequential feature selection (SFS). SFS is an effective approach to improve the performance of random forest model on heart disease detection. SFS removes unrelated features in heart disease dataset that tends to mislead random forest model on heart disease detection. Thus, removing inappropriate and duplicate features from the training set with sequential f
... Show More
(1)
(2)
(1)
(4)
(12)
(8)
(30)
(18)