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:
The design process often requires delays in the wireless network and loss of packets. The solar lighting system provides a clean environment so that it can operate for a long time. Solar Wireless Network Control System (SWNCS) offers a multi-service infrastructure solution for developed and underdeveloped countries. The system provides access to Wi-Fi / WIMAX, video surveillance and a wireless sensor for weather monitoring, powered by solar energy. This system is compatible with all applications. This study focuses on delayed SWNCS and packet hopping for stochastic wireless communications. Delays and loss of wireless networks vary stochastically. This stochastic approach to wasted time and packets for wireless networks such as Wi-Fi and WiMAX are typical for commercial use. Delays and packet losses are constructed using Markovan circuits as models of a stochastic wireless network. Based on this model, SWNCS has developed new approaches to avoid packets and loss of time. The linear matrix inequality (LMI) methodology is used to analyze the robust model predictive controller (RMPC) approach for SWNCS. SWNCS delays are known by the Markov chain as a normal variable. SWNCs are represented by a discrete Markov jump system with unlimited standard delay. The full state feedback controller can be designed using the LMI kit based on the SWNCS model. The modelling and simulation show the performance of the proposed project. The proposed control algorithm provides a numerical example to verify the reliability of the results. The standards are used to determine the reliability and functionality of the main structures and are taken from LMI. In addition, the effectiveness of a solid stability analysis is illustrated by a numerical example.
With the increasing use of a variety of services and applications in the real world network environment, identifying malicious behavior in traffic patterns generated by different applications has become challenging. Many existing methods use a technique and a dataset with specific limitations. But in the real world, applications may have different datasets. In addition, the nonlinear behavior of the dataset is another challenge for detecting anomalous data. Several researches have been done in this area, but it is still an open research topic and less used in the real world. In general, existing methods consider a set of assumptions about training data and validation methods, while the created system cannot be used in the real world. In this paper, we present a new approach to create a valid attack dataset. Also, a new validation strategy is provided and so an SVM-based feature selection method is proposed to implement the intrusion detection system. The evaluation results show that the proposed feature selection method improves the system accuracy by considering the important features of the real network during the modeling process.
