Employment of Emergency Advanced Nurses of Turkey: A Discrete-Event Simulation Application

Atalan, Abdulkadir; Dönmez, Cem Çağrı

doi:10.3390/pr7010048

Cited by 14 publications

(11 citation statements)

References 26 publications

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“…Robotic TMR: Tele-healthcare [507] Surgery [508][509][510][511] Monitoring: care and wellness [511] DDPPPT: diagnosis and rehabilitation [508,511] MERT: training [511] 11. Simulation HFMPO: Operation process improvement and optimization, resource planning, emergency room efficiency improvement [512][513][514][515][516][517] MERT: clinical or midwifery education and training, clinical The intricacy of the disruptive and transformative powers of industry 4.0 including the process of globalization of the world economy is a prerequisite for the successful operation and disruption of logistics which is well-known today as logistics 4.0 [534,535]. In fact, the formation of logistics 4.0 banks in particular on cutting-edge technologies and the digitalization of business processes [534].…”

Section: Convergence Of Disruptive Technologies In Healthcarementioning

confidence: 99%

The Hype and Disruptive Technologies of Industry 4.0 in Major Industrial Sectors: A State of the Art

Bongomin¹,

Yemane²,

Kembabazi³

et al. 2020

Preprint

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Very well into the dawn of the fourth industrial revolution (industry 4.0), we hardly distinguish between what is artificial and what is natural (e.g. man-made virus and natural virus). Thus, the level of discombobulation among people, companies or countries is indeed unprecedented. The fact that industry 4.0 is explosively disrupting or retrofitting each and every industrial sector, makes industry 4.0 the famous buzzword amongst researchers today. However, the insight of industry 4.0 disruption in the industrial sectors remains ill-defined in both academic and non-academic literature. The present study aimed at identifying industry 4.0 neologisms, understanding the industry 4.0 disruption and illustrating the disruptive technologies convergence in the major industrial sectors. A total of 99 neologisms of industry 4.0 were identified. Industry 4.0 disruption in Education industry (Education 4.0), Energy industry (Energy 4.0), Agriculture industry (Agriculture 4.0), Healthcare industry (Healthcare 4.0), and Logistics industry (Logistics 4.0) are described. The convergence of 12 disruptive technologies including 3D printing, Artificial intelligence, Augmented reality, Big Data, Blockchain, Cloud computing, Drones, Internet of things, Nanotechnology, Robotics, Simulation and Synthetic biology in agriculture, healthcare and logistics industries are illustrated.

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Section: Convergence Of Disruptive Technologies In Healthcarementioning

confidence: 99%

The Hype and Disruptive Technologies of Industry 4.0 in Major Industrial Sectors: A State of the Art

Bongomin¹,

Yemane²,

Kembabazi³

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Independent variables and dependent variables are the cornerstones of the design of experiment [13]. It is one of the best methods developed to measure the effect of independent variables on dependent variables in the design of experiment [14], [15]. In this study, four different independent variables and one dependent variable are defined to calculate the optimum value of the quality sugar score.…”

Section: Introductionmentioning

confidence: 99%

Yüksek Kaliteli Şeker Elde Etmek İçin Deney Tasarımı Optimizasyonunun Geliştirilmesi

Atalan

Atalan²

2021

İstatistik Ve Uygulamalı Bilimler Dergisi

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This study aimed to use the design of experiment technique to calculate the optimum values of dependent and independent variables considered in the production of quality sugar. This study consists of two stages. Firstly, four different independent variables and one dependent variable data were used for this study. The levels and limits of independent factors were determined as a result of descriptive statistical analysis. They were considered the experiment as a two-level system; a full-factorial design of experiment, including 2 4 experiments with three replications, was made. Statistical analysis was performed using the data obtained, and it was determined whether the independent variables had an effect on the dependent variable. In the second stage of the study, the optimization model developed in order to obtain optimum results for both dependent and independent variables was run. According to the optimum data obtained in the optimization model, the quality-sugar score was calculated as 13.5821 according to 95% confidence and prediction interval, while the color of sugar was determined to be brown.

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“…However, such studies do not consider the position of patients and the suitability of hospitals in the next activity. The ambulance service system has a dynamic structure due to real-time situations [1], [16], [26]. In such structured systems, optimization methods give limited answers.…”

Section: Introductionmentioning

confidence: 99%

Ambulance Service for Hospital Selection: Optimization With Discrete-Event Simulation Application for Yozgat Province of Turkey

Atalan

2021

Mühendislik Bilimleri Ve Araştırmaları Dergisi

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This study aims to develop a new approach in the ambulance service to refer the patient not to the nearest hospital but to a suitable hospital that responds better to his/her illness. Due to the lack of staff and equipment in a hospital, patients are often very likely to be transferred to another hospital. A case study was performed with a discrete-event simulation method for an improved ambulance service flowchart in this research. The case study was conducted in Yozgat province of Turkey, including two hospitals (city and university), one emergency call center, and six ambulance stations. Each of them has one vehicle. The data used covers the one-year from January 2018 to January 2019. The method developed for this study resulted in a 21.14 % improvement in ambulance service. The most crucial point that was noteworthy among the findings was that referral of the patient to the most appropriate hospital, rather than the nearest hospital, was important in terms of both dispatching time and the life-threatening condition of the patient.

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Employment of Emergency Advanced Nurses of Turkey: A Discrete-Event Simulation Application

Cited by 14 publications

References 26 publications

The Hype and Disruptive Technologies of Industry 4.0 in Major Industrial Sectors: A State of the Art

The Hype and Disruptive Technologies of Industry 4.0 in Major Industrial Sectors: A State of the Art

Yüksek Kaliteli Şeker Elde Etmek İçin Deney Tasarımı Optimizasyonunun Geliştirilmesi

Ambulance Service for Hospital Selection: Optimization With Discrete-Event Simulation Application for Yozgat Province of Turkey

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