Uniform fractional part: a simple fast method for generating continuous random variates

A known theorem in probability is adopted and through a probabilistic approach, it is generalized to develop a method for generating random deviates from the distribution of any continuous random variable. This method, which may be considered as an approximate version of the Inverse Transform algorithm, takes two random numbers to generate a random deviate, while maintaining all the other advantages of the Inverse Transform method, such as the possibility of generating ordered as well as correlated deviates and being applicable to all density functions, regardless of their parameter value

Effect of thin film truncation thickness on the heat transfer underestimation from an evaporating droplet on a partial wetting surface

The thin liquid film near the contact line is important for droplet evaporation on a heated surface, however, it remains a challenge for modeling and simulation since it operates from macroscale down to nanoscale. The nanoscale thin film profile has long been unknown; besides in CFD simulations the meshing work for the thin film could be extremely consuming therefore a truncation is needed to disregard the very thin part of the thin film region. The present study is an attempt to simplify the thin film modeling for partially wetting liquids, based on a recent Atomic Force microscope (AFM) experiments that suggested the partially wetting nanoscale thin film are closely following the macroscale profiles. We conduct a theoretical study on an evaporating sessile droplet and evaluate the effect of thin film truncation size on the overall heat transfer. A small spherical droplet with less than 1mm diameter is investigated and the wall superheat is 1 C°. The contact angles are ranged from 5o to 85o. We evaluate the effect of the dimensionless truncation ratio, i.e. the ratio of the truncation size and droplet height on the overall heat transfer underestimation. The results show that the dimensionless truncation ratio has a critical effect on the heat transfer calculation while the contact angle and the droplet size have relatively weaker influences. It is due to the fact that the variation of truncation ratio has much more effect on the size of the neglecting thin film region.Papers presented at the 13th International Conference on Heat Transfer, Fluid Mechanics and Thermodynamics, Portoroz, Slovenia on 17-19 July 2017 .International centre for heat and mass transfer.American society of thermal and fluids engineers

Promises of artificial intelligence in neuroradiology:a systematic technographic review

Purpose To conduct a systematic review of the possibilities of artificial intelligence (AI) in neuroradiology by performing an objective, systematic assessment of available applications. To analyse the potential impacts of AI applications on the work of neuroradiologists. Methods We identified AI applications offered on the market during the period 2017–2019. We systematically collected and structured information in a relational database and coded for the characteristics of the applications, their functionalities for the radiology workflow and their potential impacts in terms of ‘supporting’, ‘extending’ and ‘replacing’ radiology tasks. Results We identified 37 AI applications in the domain of neuroradiology from 27 vendors, together offering 111 functionalities. The majority of functionalities ‘support’ radiologists, especially for the detection and interpretation of image findings. The second-largest group of functionalities ‘extends’ the possibilities of radiologists by providing quantitative information about pathological findings. A small but noticeable portion of functionalities seek to ‘replace’ certain radiology tasks. Conclusion Artificial intelligence in neuroradiology is not only in the stage of development and testing but also available for clinical practice. The majority of functionalities support radiologists or extend their tasks. None of the applications can replace the entire radiology profession, but a few applications can do so for a limited set of tasks. Scientific validation of the AI products is more limited than the regulatory approval

Facilitating the transition to an inverter dominated power system : experimental evaluation of a non-intrusive add-on predictive controller

The transition to an inverter-dominated power system is expected with the large-scale integration of distributed energy resources (DER). To improve the dynamic response of DERs already installed within such a system, a non-intrusive add-on controller referred to as SPAACE (set point automatic adjustment with correction enabled), has been proposed in the literature. Extensive simulation-based analysis and supporting mathematical foundations have helped establish its theoretical prevalence. This paper establishes the practical real-world relevance of SPAACE via a rigorous performance evaluation utilizing a high fidelity hardware-in-the-loop systems test bed. A comprehensive methodological approach to the evaluation with several practical measures has been undertaken and the performance of SPAACE subject to representative scenarios assessed. With the evaluation undertaken, the fundamental hypothesis of SPAACE for real-world applications has been proven, i.e., improvements in dynamic performance can be achieved without access to the internal controller. Furthermore, based on the quantitative analysis, observations, and recommendations are reported. These provide guidance for future potential users of the approach in their efforts to accelerate the transition to an inverter-dominated power system

Promises of artificial intelligence in neuroradiology:a systematic technographic review

Purpose To conduct a systematic review of the possibilities of artificial intelligence (AI) in neuroradiology by performing an objective, systematic assessment of available applications. To analyse the potential impacts of AI applications on the work of neuroradiologists. Methods We identified AI applications offered on the market during the period 2017-2019. We systematically collected and structured information in a relational database and coded for the characteristics of the applications, their functionalities for the radiology workflow and their potential impacts in terms of 'supporting', 'extending' and 'replacing' radiology tasks. Results We identified 37 AI applications in the domain of neuroradiology from 27 vendors, together offering 111 functionalities. The majority of functionalities 'support' radiologists, especially for the detection and interpretation of image findings. The second-largest group of functionalities 'extends' the possibilities of radiologists by providing quantitative information about pathological findings. A small but noticeable portion of functionalities seek to 'replace' certain radiology tasks. Conclusion Artificial intelligence in neuroradiology is not only in the stage of development and testing but also available for clinical practice. The majority of functionalities support radiologists or extend their tasks. None of the applications can replace the entire radiology profession, but a few applications can do so for a limited set of tasks. Scientific validation of the AI products is more limited than the regulatory approval.</p

Radiologists in the loop:the roles of radiologists in the development of AI applications

Objectives To examine the various roles of radiologists in different steps of developing artificial intelligence (AI) applications. Materials and methods Through the case study of eight companies active in developing AI applications for radiology, in different regions (Europe, Asia, and North America), we conducted 17 semi-structured interviews and collected data from documents. Based on systematic thematic analysis, we identified various roles of radiologists. We describe how each role happens across the companies and what factors impact how and when these roles emerge. Results We identified 9 roles that radiologists play in different steps of developing AI applications: (1) problem finder (in 4 companies); (2) problem shaper (in 3 companies); (3) problem dominator (in 1 company); (4) data researcher (in 2 companies); (5) data labeler (in 3 companies); (6) data quality controller (in 2 companies); (7) algorithm shaper (in 3 companies); (8) algorithm tester (in 6 companies); and (9) AI researcher (in 1 company). Conclusions Radiologists can play a wide range of roles in the development of AI applications. How actively they are engaged and the way they are interacting with the development teams significantly vary across the cases. Radiologists need to become proactive in engaging in the development process and embrace new roles

Training opportunities of artificial intelligence (AI) in radiology:a systematic review

Objectives The aim is to offer an overview of the existing training programs and critically examine them and suggest avenues for further development of AI training programs for radiologists. Methods Deductive thematic analysis of 100 training programs offered in 2019 and 2020 (until June 30). We analyze the public data about the training programs based on their “contents,” “target audience,” “instructors and offering agents,” and “legitimization strategies.” Results There are many AI training programs offered to radiologists, yet most of them (80%) are short, stand-alone sessions, which are not part of a longer-term learning trajectory. The training programs mainly (around 85%) focus on the basic concepts of AI and are offered in passive mode. Professional institutions and commercial companies are active in offering the programs (91%), though academic institutes are limitedly involved. Conclusions There is a need to further develop systematic training programs that are pedagogically integrated into radiology curriculum. Future training programs need to further focus on learning how to work with AI at work and be further specialized and customized to the contexts of radiology wor

The Effect of Physical Illnesses on the Deprivation of Child Custody

The ultimate goal of child custody is the realization of children's benefits and to keep them out of harm.Therefore, if the parents lack base qualifications and abilities, the child custody will be deprived of them. Also in the article 1173 of the Civil Code, child custody deprivation from its holder is considered. Since one of the qualifications of child's supervisor is his (her) physical health, this paper, by analysis of jurists' opinions, is going to examine the impact of illnesses on child custody. It further surveys that if the guardian has an infectious illness, endangering child's physical health, or he (she) is not able to keep the child due to an incurable disease, his (her) custody will be void. But if the guardian be able to prevent the spread of illness to the child or does the affairs resulting the maintenance and upbringing of the child through an agent for example, child custody will be constant according to the legal rule