Traffic complexity

ABSTRACT The workload of air traffic controllers plays a crucial role in the safety and efficiency of air traffic as it is the prime factor to determine airspace capacity. Workload is the result of traffic complexity which can be described by different sets of parameters. In order to find a small, yet reliable set of complexity parameters that describe controller workload in the Hungarian Air Traffic Control system, a study with multiple steps was conducted and the results are presented in this paper. Information on the most important complexity factors was aquired from experts through interviews and questionnaires and as a result, different sets of parameters were created. To validate the method for gathering information as well as the applicability of complexity factors for airspace capacity estimation, a neural network based model was used. The results indicate that even smaller sets of parameters can be helpful in estimating workload. 

In Section 2, we provide a brief description of the structure of a general ATC system and the safety analysis techniques related to the system elements focusing on human components. In Section 3, a method is presented for the determination of the set of air traffic complexity parameters to be used for sector capacity estimation. In Section 4 we summarize the results of a neural network based sector capacity estimation model with different sets of complexity factors as input parameters and in Section 5, we give final conclusions. 

The substantive part of the questionnaire contained the possible air traffic complexity factors listed above and the respondents were required to rate them subjectively (relying on their own experience) based on two aspects. The first aspect was the extra workload generated by the unfavorable state of the given parameter. The respondents were asked to mark each parameter with a number from 1 to 5 based on their thoughts about the workload generated (with 1 standing for no or very low workload and 5 for very high workload). 

Christien, R., Benkouar, A. 2003. Air Traffic Complexity Indicators ATC Sectors Classification. Proceedings of the fifth USA/Europe Air Traffic Management R D Seminar, Budapest, Hungary. 

Gianazza, D., Guittet, K. 2006. Evaluation of air traffic complexity metrics using neural networks and sector status. Proceedings of the 2nd International Conference on Research in Air Transportation, ICRAT2006, Belgrade, Serbia and Montenegro. 

The pipelines wear and increase of their total length, complex natural-technical and social terms of operation of the most hazardous objects e g., nuclear and heating power plants, chemical and microbiological enterprises, air-space systems, hydro-technical installations, all types of traffic, etc. — here are the reasons of urgent necessity to use as much as possible the NDT and TD systems. 

December 13, 1991, a benzoic acid tairk exploded causing six deaths and three injuries at the Dutch chemical firm DSM s chemical complex in Rotterdam Harbor. Shipping traffic was halted for an hour in the world s busiest port while the fire was controlled. 

When enrichment episodes occur in the real world, but not in the laboratory under federal certification tests, real-world emissions are significantly higher than predicted. Further complicating emissions prediction is that aggressive driver behavior and complex traffic flow characteristics play a large role in enrichment occurrence. Current vehicle activity simulation models can predict average speeds and traffic volumes very well, but poorly predict the hard-accel-eration events that lead to enrichment. 

Turner, G.R. Tartakoff, A.M. (1989). The response of the Golgi complex to microtubule alterations The roles of metabolic energy and membrane traffic in Golgi complex organization. J. Cell Biol. 109,2081-2088. 

Wu CC et al. Proteomic analysis of two functional states of the Golgi complex in mammary epithelial cells. Traffic 2000 1 769-782. 

Saraste, J. and Kuismanen, E. Pathways of protein sorting and membrane traffic between the rough endoplasmic reticulum and the Golgi complex. Semin. Cell Biol. 3 343-355,1992. 

The nucleus is surrounded by the nuclear envelope, which takes on a lumenal structure connected to the endoplasmic reticulum. The transport of proteins into (and out of) the nucleus occurs through the nuclear pore complex (NPC), a large complex composed of more than 100 different proteins (Talcott and Moore, 1999). Because NPC forms an aqueous pore across the two membranes, small proteins less than 9 nm in diameter can pass through it simply by diffusion. However, most of the transports of both proteins and RNAs are mediated by an active transport mechanism. It is now clear that there is heavy traffic through the NPC in both directions. Proteins are not only imported into the nucleus but also actively exported from it as well. There are many reasons for nuclear export. One reason is to send some shuttle proteins back after their import another is for some viral proteins to export their replicated genomes outside the nucleus. 

A simple example of the first method is to screen requests to ensure that they come from an acceptable (i.e., previously identified) domain name and Internet protocol address. Firewalls may also use more complex rules that analyze the application data to determine if the traffic should be allowed through. For example, the firewall may require user authentication (i.e., use of a password) to access the system. How a firewall determines what traffic to let through depends on which network layer it operates at and how it is configured. Some of the pros and cons of various methods to control traffic flowing in and out of the network are provided in table 9.12. 

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