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:
Due to its ability to transmit a high rate data stream with maintaining robustness against multipath fading, high spectrum efficiency and efficient implementation, OFDM has been widely used in various communications systems such as DVB, WIFI and WIMAX. It is also considered as a candidate for the air interface of the current and future high speed mobile communications standards such as LTE, LTE advanced. It is also very appropriate for multi-band cognitive radio systems. However, OFDM suffers from some drawbacks. One of them is the Out of Band (OOB) leakage due to high spectral sidelobe which produce interference neighboring bands and then degrade the system performance. Several schemes have been proposed to reduce the OOB emission such as filtering, windowing, precoding etc. in this paper, a hybrid approach based on two Beek’s precoding techniques is proposed and showing a high OOB emission reduction with the same complexity. Simulation results verified the advantages of this scheme as compared with other well-known techniques
Aircraft flight control system tends to use Electromechanical actuators (EMAs), so the condition monitoring of aircraft actuators become more important under varying environmental and operational conditionIn. This paper introduces a new approach to monitoring surface roughness for aircraft actuators. The proposed technique starts with current and vibration signal as fault indicator. Them to extract the useful features discrete wavelet transform (DWT) was implemented. To overcome lamentations related with redundancy features that effect on diagnostic accuracy and time taken for Classification orthogonal Fuzzy neighborhood preserving analysis with QR decomposition (FNPA-QR) which is used first time for electrical motor condition motoring. In real time under variable and constant working. Time Delay Neural Network (TDNN) was presented to classify faults and predict their severity. The results achieved from simulation prove the ability of the present method in successfully diagnosis the various type of faults