The ASIASAFE road safety handbook: the best practices in traffic safety between Europe – Indonesia, Malaysia, and Vietnam

This handbook on Road Traffic Safety, titled "The ASIASAFE Road Safety Handbook: The Best Practices in Traffic Safety between Europe – Indonesia, Malaysia, and Vietnam," is a collaborative effort involving nine universities across Asia and Europe. It represents over three years of intensive research, discussions, and consultations with relevant agencies in participating countries. The six Asian universities involved are the Malaysia University of Science and Technology, Universiti Malaya (Malaysia), Universitas Gadjah Mada, Universitas Muhammadiyah (Indonesia), and Nguyen Tat Thanh University, University of Transport and Communications (Vietnam). The three European universities are Linkoping University (Sweden), University of Porto (Portugal), and University of Rome "Tor Vergata" (Italy). While every effort has been made to ensure the accuracy and relevance of the information provided in this handbook, it is essential to acknowledge that each country has its own unique conditions and circumstances concerning road traffic safety. Therefore, the content of this handbook should be adopted and adapted according to the specific situations and needs of individual countries. Readers are advised to exercise caution and discretion in implementing the recommendations and strategies outlined in this handbook, considering the local context and consulting with relevant authorities and experts as needed. The authors and contributing institutions do not accept any responsibility for the consequences of actions taken based on the information provided in this handbook

An Intrusion Detection System Based on Hybrid of Artificial Neural Network (ANN) and Magnetic Optimization Algorithm (MOA)

Intrusion Detection System is a type of security application that protects computer and network systems. A variety of techniques have been proposed to increase IDS accuracy. This research study focuses on improving an IDS detection performance by combining an Artificial Neural Network (ANN) with a Magnetic Optimization Algorithm (MOA), with the goal of increasing the classification rate and achieving high detection accuracy in IDS. The suggested ANNMOA result demonstrated that it is possible to improve IDS accuracy by up to 98.5 percent

An Intrusion Detection System Based on Hybrid of Artificial Neural Network (ANN) and Magnetic Optimization Algorithm (MOA)

Intrusion Detection System is a type of security application that protects computer and network systems. A variety of techniques have been proposed to increase IDS accuracy. This research study focuses on improving an IDS detection performance by combining an Artificial Neural Network (ANN) with a Magnetic Optimization Algorithm (MOA), with the goal of increasing the classification rate and achieving high detection accuracy in IDS. The suggested ANNMOA result demonstrated that it is possible to improve IDS accuracy by up to 98.5 percent