Khurshid Alam

Sarmed Wahab, Nasim Shakouri Mahmoudabadi, Sarmad Waqas et al.

This research aims at comparative analysis of shear strength prediction at slab-column connection, unifying machine learning, design codes and Finite Element Analysis. Current design codes (CDCs) of ACI 318-19 (ACI), Eurocode 2 (EC2), Compressive Force Path (CFP) method, Feed Forward Neural Network (FNN) based Artificial Neural Network (ANN), PSO-based FNN (PSOFNN), and BAT algorithm-based BATFNN are used. The study is complemented with FEA of slab for validating the experimental results and machine learning predictions.In the case of hybrid models of PSOFNN and BATFNN, mean square error is used as an objective function to obtain the optimized values of the weights, that are used by Feed Forward Neural Network to perform predictions on the slab data. Seven different models of PSOFNN, BATFNN, and FNN are trained on this data and the results exhibited that PSOFNN is the best model overall. PSOFNN has the best results for SCS=1 with highest value of R as 99.37% and lowest of MSE, and MAE values of 0.0275%, and 1.214% respectively which are better than the best FNN model for SCS=4 having the values of R, MSE, and MAE as 97.464%, 0.0492%, and 1.43%, respectively.

Simon Duque Anton, Daniel Fraunholz, Christoph Lipps et al.

The development in the area of wireless communication, mobile and embedded computing leads to significant changes in the application of devices. Over the last years, embedded devices were brought into the consumer area creating the Internet of Things. Furthermore, industrial applications increasingly rely on communication through trust boundaries. Networking is cheap and easily applicable while providing the possibility to make everyday life more easy and comfortable and industry more efficient and less time-consuming. One of the crucial parts of this interconnected world is sound and secure authentication of entities. Only entities with valid authorisation should be enabled to act on a resource according to an access control scheme. An overview of challenges and practices of authentication is provided in this work, with a special focus on context information as part of security solutions. It can be used for authentication and security solutions in industrial applications. Additional information about events in networks can aid intrusion detection, especially in combination with security information and event management systems. Finally, an authentication and access control approach, based on context information and - depending on the scenario - multiple factors is presented. The combination of multiple factors with context information makes it secure and at the same time case adaptive, so that the effort always matches, but never exceeds, the security demand. This is a common issue of standard cyber security, entities having to obey strict, inflexible and unhandy policies. This approach has been implemented exemplary based on RADIUS. Different scenarios were considered, showing that this approach is capable of providing flexible and scalable security for authentication processes.