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:
Zhonghua er bi yan hou tou jing wai ke za zhi = Chinese journal of otorhinolaryngology head and neck surgery
Interventional Pulmonology
Interventional Pulmonology (middletown, de.)
This paper presented an accredited model to predict the age of marine snail, which dealt with heuristics data problems and overcomes the restrictions in the mysterious and complex relationship that links the input data to predict results. Measuring the abalone age is a very important process in many aspects, especially economic ones; Abalone economic value is linked strongly to their age. An artificial neural network which is the algorithm proposed that is compatible with solving that data throughout the training
In the capabilities of today technologies, IoT become a merging technology that wildly apply nowadays. Meanwhile, at the same time since IoT technology become more in getting much popularity. At the same time, botnet infection that infect IoT become increasing. Consequently, that’s is a lot botnet detection is infected IoT devices. Based on Cybersecurity Malaysia there are various attack on the IoT via botnet. Then a number of researchers has proposed many various methods in order to detect IoT botnet such as machine learning, deep learning, graph theory and others method. This paper has reviewed the number of detection methods that will propose previous researcher in this review. This paper provides summarize of type of IoT botnet method according on the researcher method. This paper also lists some IoT devices that been attack based on previous paper. The contribution of this paper is to give the community the better understanding of detection method that getting much popularity nowadays to be applied. There a lot of botnet manufactured is difficult to detect. Previous researcher proposed several detections and several methods. The review of previous work is for community understanding. In the capabilities of today technologies, IoT become a merging technology that wildly apply nowadays. Meanwhile, at the same time since IoT technology become more in getting much popularity. At the same time, botnet infection that infect IoT become increasing. Consequently, that’s is a lot botnet detection is infected IoT devices. Based on Cybersecurity Malaysia there are various attack on the IoT via botnet. Then a number of researchers has proposed many various methods in order to detect IoT botnet such as machine learning, deep learning, graph theory and others method. This paper has reviewed the number of detection methods that will propose previous researcher in this review. This paper provides summarize of type of IoT botnet method according on the researcher method. This paper also lists some IoT devices that been attack based on previous paper. The contribution of this paper is to give the community the better understanding of detection method that getting much popularity nowadays to be applied. There a lot of botnet manufactured is difficult to detect. Previous researcher proposed several detections and several methods. The review of previous work is for community understanding
