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Cardiovascular risk prediction: a comparative study of Framingham and PPA

#artificialintelligence

Disease risk estimates can be used as prognostic information and support for treating CVDs. The commonly used Framingham risk score (FRS) for CVD prediction is outdated for the modern population, so FRS may not be accurate enough. In this paper, a novel CVD prediction system based on machine learning is proposed. Methods: This study has been conducted with the data of 689 patients showing symptoms of CVD. Furthermore, the dataset of 5,209 CVD patients of the famous Framingham study has been used for validation purposes.


Turkey's constitutional reform: All you need to know

Al Jazeera

Last December, Turkey's ruling Justice and Development Party (AKP) unveiled a raft of constitutional amendments that aim to fundamentally change the way Turkey is governed. The controversial draft constitution, dubbed the "Turkish-style presidency", is seeking to replace the current parliamentary system with a presidential one paving the way for President Recep Tayyip Erdogan, who has held power for the past 13 years, first as prime minister and since 2014 as president, to become the sole executive authority in the country. The proposed constitution, which is currently being debated in parliament, foresees the creation of vice presidents and the abolition of the office of the prime minister. If the amendments are accepted, first by parliament and then in a referendum, there would no longer be a formal cabinet answerable to parliament. The president will have the power to appoint and fire ministers.


Displaying Speeches Method for Non-Crosstalk Online Agent

AAAI Conferences

In the field of self-help groups for recovering from developmental disorders or alcohol dependence or the other problem, a meeting of non-crosstalk style has been used. On the meeting style, participants speak about one topic without conversation with the other participants, and advising and asking to others are not recommended besides. We are proposing an online meeting system that is specialized to support non-crosstalk style meeting. Now, we would like to develop an online agent who can perform like a human participant or more useful for participants. Since the developments of above online meeting system and autonomous agents contribute to supporting many people in the self-help field, this study has an impact in the designing methods for making better well-being space environment. In order to inspire human behaviors to the agent, this paper shows analysis the results of online humans meetings using our proposed system. As the experimental results which were compared with a classical style system, it has revealed about proposed system as follows: (1) frustrating with rules of non-crosstalk is small, (2) conversational speech didn’t reduce, (3) conversational speeches were increasing along with the time but they are leading to prevent from decreasing the number of speeches, and (4) more sensitive to the speed of displaying speeches.


Physics-Informed Deep Learning: A Promising Technique for System Reliability Assessment

arXiv.org Machine Learning

Considerable research has been devoted to deep learning-based predictive models for system prognostics and health management in the reliability and safety community. However, there is limited study on the utilization of deep learning for system reliability assessment. This paper aims to bridge this gap and explore this new interface between deep learning and system reliability assessment by exploiting the recent advances of physics-informed deep learning. Particularly, we present an approach to frame system reliability assessment in the context of physics-informed deep learning and discuss the potential value of physics-informed generative adversarial networks for the uncertainty quantification and measurement data incorporation in system reliability assessment. The proposed approach is demonstrated by three numerical examples involving a dual-processor computing system. The results indicate the potential value of physics-informed deep learning to alleviate computational challenges and combine measurement data and mathematical models for system reliability assessment.


A Novel Fuzzy Logic Based Adaptive Supertwisting Sliding Mode Control Algorithm for Dynamic Uncertain Systems

arXiv.org Artificial Intelligence

This paper presents a novel fuzzy logic based Adaptive Super-twisting Sliding Mode Controller for the control of dynamic uncertain systems. The proposed controller combines the advantages of Second order Sliding Mode Control, Fuzzy Logic Control and Adaptive Control. The reaching conditions, stability and robustness of the system with the proposed controller are guaranteed. In addition, the proposed controller is well suited for simple design and implementation. The effectiveness of the proposed controller over the first order Sliding Mode Fuzzy Logic controller is illustrated by Matlab based simulations performed on a DC-DC Buck converter. Based on this comparison, the proposed controller is shown to obtain the desired transient response without causing chattering and error under steady-state conditions. The proposed controller is able to give robust performance in terms of rejection to input voltage variations and load variations.