2018, Vol.13, No.5

Journal of Knowledge Information Technology and Systems 2023 KCI Impact Factor : 0.89

pISSN : 1975-7700 / eISSN : 2734-0570
https://journal.kci.go.kr/kkits

There are different types of diseases occur in plants and fruits due to the changes of not only the climate, weather, and seasons, but also the environmental factors like temperature, humidity, and rainfall etc. Diseases can change the structure of plants, fruits and also crops. The influence of plants and fruits disease affects our agriculture industry and agriculture sector. Diseases can interrupt our plant’s growth, fruits growth, production growth, and also makes an effect on economic growth all over the world. Farmers have a lot of experience in detecting problems and also they can identify the diseases in various plants. They can easily take care or actions for environmental factorial diseases but sometimes it’s not working. Technologies can support farmers to make their methods more reliable to improve farmer’s crops and fruits quality for a good production. Therefore in this study, we analyse different types of plum plant diseases and then use the linear regression model to know the condition of plum fruit size using plum growth, plum length and plum width. In result and discussion, we identify the environment factorial diseases in plum and also make a decision by verifying the plum fruits size after diseases occurred in Plum Plants.

Plant diseases are one of the most significance issues in agriculture fields. The diseases destroy fruits and are decreased the production rate. They also decrease the economic growth in worldwide and increase the demand about preventing plant diseases. The major cause of plant diseases is climate changes, weather conditions and environmental factors. To prevent the diseases, we need to identify the plant diseases about corresponding environmental factors. In this study, we analysis the plum data and identify the plant diseases with corresponding environmental factors by using Logistic Regression model. The first process is to identify the number of diseases and its type, and then implement Logistic Regression to predict the diseases by using environmental factors as inputs. Finally, we compare the actual value of diseases with predicted value of diseases, and need to check the accuracy of diseases by using correlation method. We also find the environmental factors for the reasons to forms more diseases. In result and discussion, it would be clearly explained about the plum diseases and their environmental factors.

The use of biomedical technology has been applied to all smart devices such as smart phones and tablet PCs, mainly shopping malls, medical systems, and financial institutions. The core of biomedical technology is the authentication function. Authentication verifies the validity of the identity at the remote server by the registered user. It is also a basic security service that allows access to remote servers. Passwords, smart cards, and biometrics are three commonly used elements in authentication. Remote user authentication schemes for various multi-server environments have been proposed by many researchers. Lin et al.'s suggested that the scheme of Baruah et al.'s is vulnerable to impersonation attacks, smart card theft attacks, etc. in a multi-server environment and proposed an improved scheme. However, there is a weakness of some parameter calculations as a result of Lin et al.'s analysis of the authentication scheme. It was revealed that users and servers were colluding, or when users' smart cards were stolen, they were vulnerable to impersonation attacks, smart card stolen attacks, replay attacks, and denial of service attacks. Thus, this paper logically reanalyzes and compares the vulnerabilities of the Lin et al 's scheme.