This paper analyses the influence of transfer function choice and learning rate on a multilayer neural network in the classi fication process. The neural network is implemented in the Java programming language.
In the last decade, cloud computing has become an extremely important business assistant that offers significantly lower costs than traditional computer-aided resource provision and greater adaptability to business changes. Thus, it helps them to achieve their business goals. The development of cloud computing poses significant risks, which serve as a partial barrier to their use by the businesses. Security and protection of information are considered to be one of the most critical points in the use of cloud computing. Compared to traditional solutions, cloud computing moves application software and databases to large data centers where information and service management are not always secure and reliable. As a result of this, the community and businesses have many concerns and questions about the security of data and applications in cloud infrastructures. In addition, concerns about data security and applications also arise due to the fact that both user data and applications are managed by the cloud provider. Clouds typically use a standardized data and application security architecture, while the demand for consumer and business services is steadily growing and becoming more diverse and with more sophisticated software design that leads to continuous upgrades to data security models in cloud computing. Due to the different methods of implementation in cloud computing service delivery models, the demand for a reasonable level of data protection is of utmost importance. The purpose of this publication is to propose a new information security model, which offers a solution for improving the use of sensitive data by introducing a three-factor authentication – an improvement of preventive control.
The goal of this paper is to study algorithm for detection and classification of moving objects based on parameter estimates from their GPS signal shadow. The suggested algorithm uses satellite GPS signals to create radio barriers and to detect moving terrestrial targets. It can be examined as an algorithm for secondary application of the wireless technologies (SAWT). This technology is extremely modern and up-to-date and can find application in Industry 4.0 with regard to the reduction of the electromagnetic radiations. The GPS signals included shadow from several moving vehicles, processed in MATLAB environment in order to obtain the estimations of their parameters. In IBM SPSS Statistics, Scheffe test is used for classifying the moving objects. The results reveal that proposed signal processing of the GPS signal shadow combined with this statistical approach can be successfully applied in practice for object classification.