Hybrid Approach
Recently Published Documents





2021 ◽  
Vol 63 ◽  
pp. 103028
Hakan Kekül ◽  
Burhan Ergen ◽  
Halil Arslan

Qiubing Ren ◽  
Mingchao Li ◽  
Rui Kong ◽  
Yang Shen ◽  
Shengli Du

2021 ◽  
Anton Sergeevich Evseenkov ◽  
Denis Kamilevich Kuchkildin ◽  
Konstantin Igorevich Krechetov ◽  
Semyon Alexandrovich Ospishchev ◽  
Victor Sergeevich Kotezhekov ◽  

Abstract The presented article is dedicated to creation and testing of probabilistic ensemble computational tool for operational forecasting of well production in short term (STF). The ensemble consisted of models based on such physical and mathematical tools as: the equation of non-stationary filtration, material balance, Darcy's law and machine learning models. After calculations by each model, their forecasts are combined into a single ensemble forecast. The hybrid approach is based on the Monte Carlo method on Markov chains as a separate probabilistic model using Bayes’ formula. In this case, statistical weights of each model (the degree of confidence in each model) is determined in the form of a probability distribution based on the reliability of previously performed forecasts. The test results presented in this article were obtained on the real field data. The obtained forecasts of individual models and the ensemble were compared to real data. Real data tool usage analysis showed that the proposed approach gives a small error in comparison with actual measurements. Efficiency of calculations allows to automatically adapt the model to the entire well production history (several hundred wells) within a few hours.

Saurabh Jha ◽  
Ashok Kumar Mehta

2021 ◽  
Alan Horan ◽  
Siobhán Masterson ◽  
Cathal O'Donnell ◽  
David Hennelly

Abstract BackgroundMuch research has occurred internationally with regard to the prehospital ETI (endotracheal intubation), however to date little is known of Paramedics perception of the procedure. In order to gain insight into procedural perception Irish Advanced Paramedics (AP) were invited to participate in an electronic survey. This survey attempted to gather information surrounding AP’s experience of education for and performance of ETI, to identify procedural barriers and gain insight in to the continuing developmental needs of AP’s to maintain confidence and competence in ETI performance. MethodsAn online questionnaire was created and AP’s employed by the National Ambulance Service and the Dublin Fire Brigade, were invited to participate. The objective was to measure the characteristics, attitudes and perceived barriers to ETI by AP’s in Ireland. Participants were asked to categorise their personal characteristics of ETI (frequency, techniques, barriers) through a series of 36 structured questions and answers. ResultsOf the 524 AP surveyed the response rate was 27% (n=140) 77.9% of respondents perform ETI 10 times or less per year. 26.6% of respondents maintain a personal airway management log book. 97.8% of respondents reported ETI as being an important AP skill. Most felt confident at performing the procedure but felt it was of moderate difficulty. There was a lack of consensus on the definition of a failed intubation attempt. Initial supervised intubation practice in Hospital or the clinical skill lab was felt to be very important. Most respondents felt that there should be a minimum number of intubations performed by a paramedic each year, and that if this number was not achieved in the pre-hospital setting in-hospital practice should be an available alternative.Conclusion ETI is perceived to be an important skill by Paramedics. In practice there is wide variances in standards of data reporting, continuing assessment and competency assurance in ETI. A hybrid approach of individuals maintaining an airway portfolio which encompasses a clinical airway logbook, self-directed airway simulation with periodic senior peer appraisal and in-hospital clinical feedback may be the best approach for Paramedics with limited pre-hospital advanced airway management opportunities.

Sawsan Almahmoud ◽  
Bassam Hammo ◽  
Bashar Al-Shboul ◽  
Nadim Obeid

Sheng Pu ◽  
Hua Luo ◽  
Shixiong Xing ◽  
Chuan Sun

Cellulose ◽  
2021 ◽  
Xiong Xiao ◽  
Yucheng  Zhong ◽  
Mingyang Cheng ◽  
Lei Sheng ◽  
Dan Wang ◽  

Khaled A. Al-Utaibi ◽  
M. Muzamil ◽  
Ayesha Sohail ◽  
Fatima Alam ◽  
Alessandro Nutini ◽  

Dengue infection affects more than half of the world’s population, with 1 billion symptomatic cases identified per year and several distinct genetic serotypes: DENV 1–4. Transmitted via the mosquito bite, the dengue virus infects Langerhans cells. Monocytes, B lymphocytes, and mast cells infected with dengue virus produce various cytokines although it is not clear which ones are predominant during DHF disease. A mathematical model of the Dengue virus infection is developed according to complex dynamics determined by many factors. Starting from a state of equilibrium that we could define as “virus-free” asymptotically stable with a viral reproduction number lower than one which means a very effective action of the innate immune system: it stops the infectious process, the mathematical analysis of stability in the presence of the virus demonstrates that the proposed model is dynamically influenced. Dengue fever affects more than half of the world’s population, with 1 billion symptomatic cases and multiple genetic serotypes confirmed each year, which simulates a network of interactions between the various populations involved without considering the speeds of the processes in question which are indicated in a separate computation. In this research, a hybrid approach of petri nets is utilized to connect the discrete models of dengue.

2021 ◽  
Alok Thatikunta ◽  
Nita Parekh

Insertion and deletion (INDELs) mutations, the most common type of structural variation in the human genome, have been implicated in numerous human traits and diseases including rare genetic disorders and cancer. Next generation sequencing (NGS) technologies have drastically reduced the cost of sequencing whole genomes, greatly contributing to genome-wide detection of structural variants. However, due to large variations in INDEL sizes and presence of low complexity and repeat regions, their detection remains a challenge. Here we present a hybrid approach, HyINDEL, which integrates clustering, split-mapping and assembly-based approaches, for the detection of INDELs of all sizes (from small to large) and also identifies the insertion sequences. The method starts with identifying clusters of discordant and soft-clip reads which are validated by depth-of-coverage and alignment of soft-clip reads to identify candidate INDELs, while the assembly -based approach is used in identifying the insertion sequence. Performance of HyINDEL is evaluated on both simulated and real datasets and compared with state-of-the-art tools. A significant improvement in recall and F-score metrics as well as in breakpoint support is observed on using soft-clip alignments. It is freely available at https://github.com/alok123t/HyINDEL.

Sign in / Sign up

Export Citation Format

Share Document