The time dilation formulas of both the specific relativity and the general relativity could be understood as children of a common expression that uses a factor dependent on the specific energy. Surprisingly when such factor is used to define the relativistic mass, the equation that arises is an extraordinary approximation of the mass and energy relation. An entangled mathematical perspective of both time and mass that opens up again the question of what their definition really is, and which are the factors that modify such variables.
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 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 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.
Artificial Intelligence (AI) is a cognitive science to enables human to explore many intelligent ways to model our sensing and reasoning processes. Industrial AI is a systematic discipline to enable engineers to systematically develop and deploy AI algorithms with repeating and consistent successes. In this paper, the key enablers for this transformative technology along with their significant advantages are discussed. In addition, this research explains Lighthouse Factories as an emerging status applying to the top manufacturers that have implemented Industrial AI in their manufacturing ecosystem and gained significant financial benefits. It is believed that this research will work as a guideline and roadmap for researchers and industries towards the real-world implementation of Industrial AI.
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.
Cyber-Physical Production Systems (CPPSs) are complex manufacturing systems which aim to integrate and synchronize machine world and manufacturing facility to the cyber computational space. However, having intensive interconnectivity and a computational platform is crucial for real-world implementation of CPPSs. In this paper, the potential impacts of blockchain technology in development and realization of real-world CPPSs are discussed. A unified three-level blockchain architecture is proposed as a guideline for researchers and industries to clearly identify the potentials of blockchain and adapt, develop, and incorporate this technology with their manufacturing developments towards Industry 4.0.