The Evaluation of Operator's Mental Workload in Operation Control Center Division in the Railway Industry

Author(s):  
Livia Putri Sulistiyo ◽  
Maya Arlini Puspasari
Author(s):  
Tetiana Shmelova ◽  
Yuliya Sikirda

In this chapter, the authors propose the application of artificial intelligence (namely expert system and neural network) for estimating the mental workload of air traffic controllers while working at different control centers (sectors): terminal control center, approach control center, area control center. At each air traffic control center, air traffic controllers will perform the following procedures: coordination between units, aircraft transit, climbing, and descending. So with the help of the artificial intelligence (AI) and its branches expert system and neural network, it is possible to estimate the mental workload of dispatchers for a different number of aircraft, compare the workload intensity of the air traffic control sectors, and optimize the workload between sectors and control centers. The differentiating factor of an AI system from a standard software system is the characteristic ability to learn, improve, and predict. Real dispatchers, students, graduate students, and teachers of the National Aviation University took part in these researches.


2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Zhikang Zhai ◽  
Ying Yang ◽  
Yu Shen ◽  
Yuxiong Ji ◽  
Yuchuan Du

This paper envisions and assesses the performance of an autonomous bus-on-demand (ABoD) system. We take Fuyang, Zhejiang, China, as the study area to investigate the spatiotemporal distribution of bus travel demand during workdays, and we propose replacing inefficient bus routes with the ABoD system. Agent-based models with various bus dispatching and operation control strategies are constructed to evaluate the performance of the ABoD system. The behaviors and interactions of the agents, passengers, autonomous buses, and a control center are designed. After the verification of the simulated bus travel demand with real-world demand, a series of scenarios with various ABoD operation strategies are simulated. The simulation results show that, in comparison with both current fixed-schedule bus services and the optimized bus dispatching strategies, the ABoD system occupies fewer road resources and utilizes bus vehicles more efficiently. Besides, the system is adaptive to the sudden surge in bus travel demand and is economically sustainable.


2013 ◽  
Vol 83 (1) ◽  
pp. 59-66 ◽  
Author(s):  
Francisco Plácido Nogueira Arcanjo ◽  
Paulo Roberto Santos ◽  
Álvaro Jorge Madeiro Leite ◽  
Francisco Sulivan Bastos Mota ◽  
Sérgio Duarte Segall

More than two billion people suffer from anemia worldwide, and it is estimated that more than 50 % of cases are caused by iron deficiency. In this community intervention trial, we evaluated infants aged 10 to 23 months of age (n = 171) from two public child day-care centers. Intervention lasted 18 weeks. The 50-g individual portion (uncooked) of fortified rice provided 56.4 mg of elemental iron as ferric pyrophosphate. Capillary blood samples to test for anemia were taken at baseline and at endpoint. The objective of this study was to evaluate the impact of rice fortified with iron (Ultrarice®) on hemoglobin and anemia prevalence compared with standard household rice. For the fortified rice center, baseline mean hemoglobin was 113.7 ± 9.2 g/L, and at endpoint 119.5 ± 7.7 g/L, p < 0.0001; for the standard rice center, baseline mean hemoglobin value was 113.5 ± 40.7 g/L, and at endpoint 113.6 ± 21.0, p = 0.99. Anemia prevalence for the fortified rice center was 27.8 % (20/72) at baseline, and 11.1 % (8/72) at endpoint, p = 0.012; for the control center, 47.1 % (33/70) were anemic at baseline, and 37.1 % (26/70) at the end of the study, p = 0.23. The Number Needed to Treat (NNT) was 4. In this intervention, rice fortified with iron given weekly was effective in increasing hemoglobin levels and reducing anemia in infants.


Author(s):  
Randall L. Harris ◽  
John R. Tole ◽  
Arye R. Ephrath ◽  
A. Thomas Stephens

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