A formula has been developed that defines the relativity of time in a novel approach. In the present paper, this is particularized for cases of temporary dilation due to speed and gravity. Using the previous equation, that serves as basis of the “Time Theory” proposed, an interpretation of the nature of black holes, their formation, growth, and dimension can be developed. Which ultimately leads to an alternative understanding of mass and energy.
A new formula has been developed that determines the passage of time. In the paper, this is particularized for cases of temporary dilation due to speed and gravity.
Additionally, using the previous equation, an interpretation of the nature of black holes, their formation, growth, and dimension can be developed.
Moreover, and based on all of the above, a different way of understanding mass and space is proposed. Which ultimately implies an alternative expression that relates mass and energy.
The development of complex and dependable systems like autonomous vehicles relies increasingly on the use of systems modeling language (SysML). In fact, SysML has become a de facto standard for systems engineering. With model-driven engineering, a SysML model serves as a reference for the early defect detection of the system under design: the earlier the errors are detected, the less is the cost of handling the errors. Mutation testing is a fault-based technique that has recently seen its applications to SysML behavioral models (e.g., state machine diagrams). Specifically, a system's state-transition design can be fed to a model checker where mutants are automatically generated and then killed against the desired design specifications (e.g., safety properties). In this paper, we present a novel approach based on process mining to improve the effectiveness and efficiency of the SysML mutation testing based on model checking. In our approach, the mutation operators are applied directly to the state machine diagram. These mutants are then fed as traces into a process mining tool and checked according to the event logs. Our initial results indicates that the process mining approach kills more mutants faster than the model checking method.
It is shown in present study that Rainflow method is unable to accurately estimate fatigue life ofcomponents under random loading, almost always. The inconsistencies between results of Rainflowmethod and hysteresis curve are also discussed. Alike the Peak counting method, it is shown that Shadowmethod doesn’t consider the possibility of deformation within individual cycles. Hence, Moshrefifar andAzamfar method is proposed as a novel technique having accurate results in different analytical condi-tions which are in good consistence with results obtained from hysteresis curves. Authors finally proposean algorithm as well as a C language program for this method.