Technology Reports of Kansai University (ISSN: 04532198) is a monthly peer-reviewed and open-access international Journal. It was first built in 1959 and officially in 1975 till now by kansai university, japan. The journal covers all sort of engineering topic, mathematics and physics. Technology Reports of Kansai University (TRKU) was closed access journal until 2017. After that TRKU became open access journal. TRKU is a scopus indexed journal and directly run by faculty of engineering, kansai university.
Technology Reports of Kansai University (ISSN: 04532198) is a peer-reviewed journal. The journal covers all sort of engineering topic as well as mathematics and physics. the journal's scopes are
in the following fields but not limited to:
In a wireless communication system, one component that plays an important role is an antenna. On the radar system, it takes the characteristics of low profile and lightweight antennas. So, the current technology trends have focused a lot on the design of printed antennas. The type of printed meander dipole antenna was chosen because it was able to reduce the dimensions of the usual dipole arm. In this paper, the authors designed and simulated the antenna using CST Studio Suite. Then we fabricated and measured both a single element and eight-element antennas to verify the antenna performance. The antenna works at S-Band frequency. This antenna using Rogers RO-4003C (lossy) as a substrate with relative permittivity 3.55, thickness 1.524 mm, and has the advantage of being more resistant to input power (power handling) than FR-4. The realization of eight-element antennas is using for a 3-dimensional monopulse tracking air surveillance radar. The simulation results show functional return loss that is less than -15 dB. The radiation pattern is directional. Single element gain is more than 5 dB, while eight elements gain 13.78 dB, and the antenna input impedance is 50 W. So, the antenna has been qualified to the desired specification and can be used as a reference antenna for air surveillance radar system.
So far, various methods have been proposed to deal with cyber-attacks, but many of them are not capable of running in the real environment or do not have enough accuracy to detect different types of attacks. In this paper, using the features of k-means clustering algorithm, ineffective data in detection process are removed from the dataset. Then, the accuracy of attack detection increases by using the Gray Wolf Optimization (GWO) algorithm and replacing stronger wolves based on their degree of suitability. In each iteration of the algorithm, the fitness is computed and if it improves the algorithm is repeated again, otherwise the algorithm terminates. The main purpose of the proposed method is to increase the accuracy of detection as well as reduce the likelihood of getting stuck in local optimal points. The simulation results on 4 different types of attacks in the NSL-KDD and synthetic dataset show that about 3.2% better detection accuracy is obtained rather than other researches by adjusting the parameters of the gray wolf algorithm, as a conclusion, the proposed method has the necessary efficiency for detecting attacks on computer networks