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.
Shortly after the comparative analysis of Codding et al. was published, I prepared a comment on the article that I submitted for publication. In response to feedback from the editors, I eventually revised the manuscript substantially. That revised version has now been published. In this paper, I share the original submission of the comment, which focuses on important considerations for future studies of risk-‐ sensitive foraging. Meanwhile, Codding and his colleagues have published a response to my comment. They exhibit some confusion about my position, which they describe as “paradoxical.” In a reply to their response, I have therefore added some clarifying remarks at the end of this paper
This paper presents a prime aspect of Augmented and Virtual Reality development in the field of healthcare. We explored several recent works and articles and a comparison between generic application development and immersive technology-based application is included. The paper talks about more practical approaches that can be taken to enhance the effectiveness of the application.
The resources (infrastructure) to complete this study are provided by the University of Cincinnati’s Center for Simulation and Virtual Environment Research (UCSIM). And several experiments and projects in the field of health care are used as a reference to make conclusions.
There has been a lot of discussion and application of social media marketing in libraries. Not surprisingly, many libraries manage multiple social media accounts on top of traditional marketing strategies. However, not many libraries have developed a strategic digital marketing strategy that synthesizes areas such as video marketing, email marketing, search engine optimization (SEO), mobile marketing, and even outreach through traditional marketing channels. These additional digital marketing channels are equally as important as social media, yet play different roles in attracting, retaining, and engaging users. As users spend an increasing amount of time online searching, it is essential for them to identify the right library resources in a search engine, find the right event in their email and social media, and develop a sense of loyalty through valuable content generated in videos and blogs. Planning for channel overlap as well as users that a campaign may have missed is an essential part of this strategy. This paper is intended to provide an overview of the multi-channel digital marketing landscape and its application in libraries. Recommended actions are provided as well.
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.