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- Title
- AIRPORT SECURITY: EXAMINING THE CURRENT STATE OF ACCEPTANCE OF BIOMETRICS AND THE PROPENSITY OF ADOPTING BIOMETRIC TECHNOLOGY FOR AIRPORT ACCESS CONTROL.
- Creator
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Sumner, Kristine, Liberman, Aaron, University of Central Florida
- Abstract / Description
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The terrorist attacks of September 11, 2001 propelled the issue of aviation security to the forefront of the U.S. domestic agenda. Although hundreds of individual airports exist in the U.S., the travel activities at each of these airports combine to holistically comprise an aviation system that represents a significant portion of the U.S. social and economic infrastructure. Disruption at one airport resulting from a criminal act, such as terrorism, could exert detrimental effects upon the...
Show moreThe terrorist attacks of September 11, 2001 propelled the issue of aviation security to the forefront of the U.S. domestic agenda. Although hundreds of individual airports exist in the U.S., the travel activities at each of these airports combine to holistically comprise an aviation system that represents a significant portion of the U.S. social and economic infrastructure. Disruption at one airport resulting from a criminal act, such as terrorism, could exert detrimental effects upon the aviation system and U.S national security (9/11 Commission, 2004). Each U.S. airport is individually responsible for various aspects of security including the control of physical access to sensitive and secure areas and facilities (9/11 Commission, 2004). Biometric technology has been examined as one method of enhancing airport access control to mitigate the possibility of criminal acts against airports. However, successful implementation of biometric technology depends largely on how individual security directors at each airport perceive, understand, and accept that technology. Backgrounds, attitudes, and personal characteristics influence individual decisions about technology implementation (Rogers, 1995; Tornatzky and Fleischer, 1990). This study examines the problem of airport access control, as well as, the current trends in biometric technology. Utilizing a survey of airport security directors and security managers, this study draws upon innovation diffusion theory and organizational theories to determine what personal, organizational, and technical variables contribute to the propensity of airport security directors and managers to adopt biometric technology for airport access control.
Show less - Date Issued
- 2007
- Identifier
- CFE0001693, ucf:47220
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0001693
- Title
- Computer Method for Airport Noise Exposure Forecast.
- Creator
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Bateman, John M., Ventre, Gerald G., Engineering
- Abstract / Description
-
Florida Technological University College of Engineering Thesis; The major problem facing air transportation for the next decade is aircraft noise. The noise level due to the operation of large jet aircraft has created a very serious annoyance problem to the people living near of adjacent to jet airports. The noise problem has developed both for take-off and landing operations of these aircraft with take -off noise causing the greatest annoyance factor. A technique called Noise Exposure...
Show moreFlorida Technological University College of Engineering Thesis; The major problem facing air transportation for the next decade is aircraft noise. The noise level due to the operation of large jet aircraft has created a very serious annoyance problem to the people living near of adjacent to jet airports. The noise problem has developed both for take-off and landing operations of these aircraft with take -off noise causing the greatest annoyance factor. A technique called Noise Exposure Forcast (NEF) has been developed to identify the annoyance factor of these noises to people and activities on the ground. With these NEF ratings or numbers, planners can better determined the type of buildings and activities to locate in the vicinity of airports. This paper presents a computer method for determining NEF areas or contours which eliminate the necessity of performing laborous hand calculations and iterations normally required to determine a given NEF locus about an airport. A land use compatability table showing land use versus NEF numbers is given on page 3. A sample computer program is given on pages 21 through 25 of teh appendix and a sample computer output page is given on page 26. The computer technique developed for this paper can be used for any airport.
Show less - Date Issued
- 1972
- Identifier
- CFR0012156, ucf:53130
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFR0012156
- Title
- VERIFICATION OF FAA'S EMISSIONS AND DISPERSION MODELING SYSTEM (EDMS).
- Creator
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Martin, Anjoli, Wayson, Roger, University of Central Florida
- Abstract / Description
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Air quality has been a major environmental concern for many years. Recently the issue of airport emissions has presented growing concerns and is being studied in much more depth. Airport emissions come from a variety of point, line and area sources, making emissions modeling for airports very complex and more involved. Accurate air quality models, specific to airport needs, are required to properly analyze this complex array of air pollution sources created by airports. Accurate air quality...
Show moreAir quality has been a major environmental concern for many years. Recently the issue of airport emissions has presented growing concerns and is being studied in much more depth. Airport emissions come from a variety of point, line and area sources, making emissions modeling for airports very complex and more involved. Accurate air quality models, specific to airport needs, are required to properly analyze this complex array of air pollution sources created by airports. Accurate air quality models are needed to plan for increased growth of current airports and address concerns over proposed new ones. The Federal Aviation Administration's (FAA) Emissions and Dispersion Modeling System (EDMS) is a program that is the required model for assessing emissions from airport sources. This research used EDMS Version 4.21, which incorporates the EPA dispersion model AERMOD, to model detailed airport data and compare the model's predicted values to the actual measured carbon monoxide concentrations at 25 locations at a major U.S. airport. Statistics relating the model characteristics as well as trends are presented. In this way, a thorough investigation of the accuracy of the EDMS modeled values of carbon monoxide was possible. EDMS modeling included two scenarios, the first scenario referred to as practice detail included general airport information that a modeler could find from the airport being studied and the second scenario referred to as research detail utilized very detailed information from observer logs during a three day observation period. Each of the modeling scenarios was compared to the field measured data and to each other. These comparisons are important to insure the model is adequately describing emissions sources at airports. Data analysis of this study was disappointing since measured levels of CO were generally higher than modeled values. Since EDMS is continually changing and improving perhaps these results can help enhance future models.
Show less - Date Issued
- 2006
- Identifier
- CFE0001282, ucf:46903
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0001282
- Title
- ANALYSIS OF AIRCRAFT ARRIVAL DELAY AND AIRPORT ON-TIME PERFORMANCE.
- Creator
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Bai, Yuqiong, Abdel-Aty, Mohamed, University of Central Florida
- Abstract / Description
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In this research, statistical models of airport delay and single flight arrival delay were developed. The models use the Airline On-Time Performance Data from the Federal Aviation Administration (FAA) and the Surface Airways Weather Data from the National Climatic Data Center (NCDC). Multivariate regression, ANOVA, neural networks and logistic regression were used to detect the pattern of airport delay, aircraft arrival delay and schedule performance. These models are then integrated in the...
Show moreIn this research, statistical models of airport delay and single flight arrival delay were developed. The models use the Airline On-Time Performance Data from the Federal Aviation Administration (FAA) and the Surface Airways Weather Data from the National Climatic Data Center (NCDC). Multivariate regression, ANOVA, neural networks and logistic regression were used to detect the pattern of airport delay, aircraft arrival delay and schedule performance. These models are then integrated in the form of a system for aircraft delay analysis and airport delay assessment. The assessment of an airport¡¯s schedule performance is discussed. The results of the research show that the daily average arrival delay at Orlando International Airport (MCO) is highly related to the departure delay at other airports. The daily average arrival delay can also be used to evaluate the delay performance at MCO. The daily average arrival delay at MCO is found to show seasonal and weekly patterns, which is related to the schedule performance. The precipitation and wind speed are also found contributors to the arrival delay. The capacity of the airport is not found to be significant. This may indicate that the capacity constraint is not an important problem at MCO. This research also investigated the delays at the flight level, including the flights with delay ¡Ý0 minute and the flights with delay ¡Ý15min, which provide the delay pattern of single arrival flights. The characteristics of single flight and their effect on flight delay are considered. The precipitation, flight distance, season, weekday, arrival time and the time spacing between two successive arriving flights are found to contribute to the arrival delay. We measure the time interval of two consecutive flights spacing and analyze its effect on the flight delay and find that for a positively delayed flight, as the time space increases, the probability of the flights being delayed will decrease. While it was possible to calculate the immediate impact of originating delays, it is not possible to calculate their impact on the cumulative delay. If a late departing aircraft has no empty space in its down line schedule, it will continue to be late. If that aircraft enters a connecting airport, it can pass its lateness on to another aircraft. In the research we also consider purifying only the arrival delay at MCO, excluding the flights with originating delay >0. The model makes it possible to identify the pattern of the aircraft arrival delay. The weather conditions are found to be the most significant factors that influence the arrival delay due to the destination airport.
Show less - Date Issued
- 2006
- Identifier
- CFE0001049, ucf:46808
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0001049
- Title
- PERFORMANCE IMPLICATIONS OF ALTERNATIVE COLOR-CODESIN AIRPORT X-RAY BAGGAGE SCREENING.
- Creator
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Hilscher, Matthew, Jentsch, Florian, University of Central Florida
- Abstract / Description
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This research investigated both cognitive and affective influences of alternative color combinations in a search task paradigm. The effects of re-mapping the existing, comparatively arbitrarily color codes of baggage X-ray images, were explored. Alternative color-codes were evaluated for improving the economy of visual search in X-ray baggage screening. Using a 2 x 2 between-groups design, the perceptual aspects of color-codes varying in degree of visual agreeability (accordant or discordant)...
Show moreThis research investigated both cognitive and affective influences of alternative color combinations in a search task paradigm. The effects of re-mapping the existing, comparatively arbitrarily color codes of baggage X-ray images, were explored. Alternative color-codes were evaluated for improving the economy of visual search in X-ray baggage screening. Using a 2 x 2 between-groups design, the perceptual aspects of color-codes varying in degree of visual agreeability (accordant or discordant) and color contrast (high or low) were examined in terms of efficiency (reaction time) and effectiveness (detection accuracy). Three hypotheses were put forth; two postulated main effects for color contrast and for visual agreeability, and a third postulated an interaction. Additionally, for comparison purposes, a fifth group of participants was presented with a stimulus condition that represented the current industry standard for colorizing X-ray images. Out of 100 volunteers, data were usable for 95 participants who had been randomly assigned to one of five conditions. All participants were exposed to the same screening task. The screening task required participants to view 153 X-ray images in random order. Of these images, 36 contained a single threat item (knife, scissor, gun) among clutter. Analyses of variance revealed significant differences between conditions with respect to detection accuracy. Implications are that high-color contrast improves detection accuracy; specifically with respect to correct rejections, and that this effect on performance can be moderated by psycho-emotional mechanisms. Specifically, the impact of color-contrast was significantly more pronounced under conditions of accordant color combinations. Theoretical underpinnings and applications to other domains are discussed.
Show less - Date Issued
- 2005
- Identifier
- CFE0000345, ucf:52835
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0000345
- Title
- IMPROVING AIRLINE SCHEDULE RELIABILITY USING A STRATEGIC MULTI-OBJECTIVE RUNWAY SLOT ASSIGNMENT SEARCH HEURISTIC.
- Creator
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Hafner, Florian, Sepulveda, Alejandro, University of Central Florida
- Abstract / Description
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Improving the predictability of airline schedules in the National Airspace System (NAS) has been a constant endeavor, particularly as system delays grow with ever-increasing demand. Airline schedules need to be resistant to perturbations in the system including Ground Delay Programs (GDPs) and inclement weather. The strategic search heuristic proposed in this dissertation significantly improves airline schedule reliability by assigning airport departure and arrival slots to each flight in the...
Show moreImproving the predictability of airline schedules in the National Airspace System (NAS) has been a constant endeavor, particularly as system delays grow with ever-increasing demand. Airline schedules need to be resistant to perturbations in the system including Ground Delay Programs (GDPs) and inclement weather. The strategic search heuristic proposed in this dissertation significantly improves airline schedule reliability by assigning airport departure and arrival slots to each flight in the schedule across a network of airports. This is performed using a multi-objective optimization approach that is primarily based on historical flight and taxi times but also includes certain airline, airport, and FAA priorities. The intent of this algorithm is to produce a more reliable, robust schedule that operates in today's environment as well as tomorrow's 4-Dimensional Trajectory Controlled system as described the FAA's Next Generation ATM system (NextGen). This novel airline schedule optimization approach is implemented using a multi-objective evolutionary algorithm which is capable of incorporating limited airport capacities. The core of the fitness function is an extensive database of historic operating times for flight and ground operations collected over a two year period based on ASDI and BTS data. Empirical distributions based on this data reflect the probability that flights encounter various flight and taxi times. The fitness function also adds the ability to define priorities for certain flights based on aircraft size, flight time, and airline usage. The algorithm is applied to airline schedules for two primary US airports: Chicago O'Hare and Atlanta Hartsfield-Jackson. The effects of this multi-objective schedule optimization are evaluated in a variety of scenarios including periods of high, medium, and low demand. The schedules generated by the optimization algorithm were evaluated using a simple queuing simulation model implemented in AnyLogic. The scenarios were simulated in AnyLogic using two basic setups: (1) using modes of flight and taxi times that reflect highly predictable 4-Dimensional Trajectory Control operations and (2) using full distributions of flight and taxi times reflecting current day operations. The simulation analysis showed significant improvements in reliability as measured by the mean square difference (MSD) of filed versus simulated flight arrival and departure times. Arrivals showed the most consistent improvements of up to 80% in on-time performance (OTP). Departures showed reduced overall improvements, particularly when the optimization was performed without the consideration of airport capacity. The 4-Dimensional Trajectory Control environment more than doubled the on-time performance of departures over the current day, more chaotic scenarios. This research shows that airline schedule reliability can be significantly improved over a network of airports using historical flight and taxi time data. It also provides for a mechanism to prioritize flights based on various airline, airport, and ATC goals. The algorithm is shown to work in today's environment as well as tomorrow's NextGen 4-Dimensional Trajectory Control setup.
Show less - Date Issued
- 2008
- Identifier
- CFE0002067, ucf:47572
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0002067
