JFK Airport Research Articles

Prediction of flight departure delays caused by weather conditions adopting data-driven approaches

In this study, we utilize data-driven approaches to predict flight departure delays. The growing demand for air travel is outpacing the capacity and infrastructure available to support it. In addition, abnormal weather patterns caused by climate change contribute to the frequent occurrence of flight delays. In light of the extensive network of international flights covering vast distances across continents and oceans, the importance of forecasting flight delays over extended time periods becomes increasingly evident. Existing research has predominantly concentrated on short-term predictions, prompting our study to specifically address this aspect. We collected datasets spanning over 10 years from three different airports such as ICN airport in South Korea, JFK and MDW airport in the United States, capturing flight information at six different time intervals (2, 4, 8, 16, 24, and 48 h) prior to flight departure. The datasets comprise 1,569,879 instances for ICN, 773,347 for JFK, and 404,507 for MDW, respectively. We employed a range of machine learning and deep learning approaches, including Decision Tree, Random Forest, Support Vector Machine, K-nearest neighbors, Logistic Regression, Extreme Gradient Boosting, and Long Short-Term Memory, to predict flight delays. Our models achieved accuracy rates of 0.749 for ICN airport, 0.852 for JFK airport, and 0.785 for MDW airport in 2-h predictions. Furthermore, for 48-h predictions, our models achieved accuracy rates of 0.748 for ICN airport, 0.846 for JFK airport, and 0.772 for MDW airport based on our experimental results. Consequently, we have successfully validated the accuracy of flight delay predictions for longer time frames. The implications and future research directions derived from these findings are also discussed.

Little Amal’s New York Journey: The Big Puppet in the Big Apple

Little Amal’s New York Journey: The Big Puppet in the Big Apple

Tales of a Flow Stayed By Nothing: Menstruation in Immigration Detention


 
 
 When Fauziya Kassindja landed at New York’s JFK airport in 1994, she was seventeen, seeking asylum, and fleeing the brutal practice of female genital mutilation. She was also menstruating. Hours after her arrival, Fauziya was strip searched, forced to stand before a female officer “completely naked, soiled pad exposed, shamed beyond words.” She was then transferred to an off-site detention facility where she was strip- searched again. When Fauziya asked where she should place her soiled pad, the female guard responded: “I don’t know. Why don’t you eat it?” When Fauziya asked for a new pad, she was told she could ask for one the next morning. She was given absolutely nothing to stay her flow—not even toilet paper or paper towels. This was the beginning of Fauziya’s experience with immigration detention. She would remain there for sixteen months.
 
 

Review: Elizabeth Scheu Close: A Life in Modern Architecture, Powerhouse: The Life and Work of Judith Chafee

Review: <i>Elizabeth Scheu Close: A Life in Modern Architecture</i>, <i>Powerhouse: The Life and Work of Judith Chafee</i>

Transatlantic Railroad

Transatlantic Railroad Mary Burke (bio) This story was first published in the Irish Times on 18 May 2018, immediately prior to the referendum on the Eight Amendment, and is reprinted with permission by the author and original publisher. It has been revised here for publication in Éire-Ireland. Set in 1992 and told through the first-person perspective of a young woman who is pregnant, the story narrativizes a little-known transatlantic journeying that Irish women made to the United States in the later stages of the twentieth century. Organized by Catholic organizations, women with unplanned pregnancies were sent to stay with Catholic host families for the duration of their pregnancies, and after birth the babies were then subsequently adopted in the United States. "Transatlantic Railroad" thus contributes to the historical accounting of the many exilic journeys that women have had to make from Ireland as a direct result of the illegalities of abortion services and the absence of comprehensive reproductive health care and medical services there. ________ It is 1992. Too late in the century to be running away for the reason I am running and too late to be running so far. 500 years after Columbus and 400 years after the first university on Irish soil, from what I'm reading in the in-flight magazine. You'd think both Ireland and America would know better by now than to be transporting young women in my situation. And I am 20. You'd think I'd know better by now than to have agreed to being transported. Up the pole. Bun in the oven. In trouble. I'm making a list in the journal the agency wants me to keep of all the vague terms the Irish have for unwanted pregnancy. The journal has a picture of the Virgin Mary on the cover with her hands clasped [End Page 159] and her eyes thrown up to heaven, looking like this whole sorry business was sheer embarrassment. Never has a spokeswoman been so badly matched with her charity. ________ A "host family" the agency called them. They are the host and I am the parasite. The foolish single Irish girl who got herself knocked up. (Knocked up. I must add that one to the list.) The Catholic agency that arranges for holy shows like me to hide out with a pious family until the baby has been quietly born and adopted by another Catholic family gave me a choice of available hosts: a farming family in Cavan or an Irish American family in Connecticut. Some local Catholic charity in Connecticut would take care of my expenses. ________ Connecticut. In America, no less. ________ Jesus Christ! Did they really think I'd choose a farm in Cavan over some place in America? I think I know Connecticut from the telly. Near New York. Rich. Big cars. Mansions. Macy's and Blooming-dales on the main streets of fancy towns. ________ My hosts are Mr. and Mrs. Murphy. "Welcome, Orla," Mrs. Murphy says at Arrivals, with what seems to be genuine warmth. Maybe this is going to be okay. But my heart sinks as they drive me from JFK Airport. With every few miles northward, we seem to get farther and farther from the possibility of department stores. We pass what they tell me with obvious pride is a large and famous Connecticut public university, but it is in the middle of nowhere. There are cows grazing in fields around the campus. In the name of God, where were the nightclubs and pubs that always huddled close to campuses? They talk at length about the Catholic church in their neighboring town. It seems I will be brought there every Sunday. I begin to see tractors on the road as we approach what they called their hometown. I had travelled thousands of miles to get away from tractors on the road and seeing cows up close. Why hadn't I looked up Connecticut in the World Book Encyclopedia at home? And that word "hometown" that they keep using. Once we approached the place I can see that this wasn't what I would've called a "town." If you call something...

Coffee Culture

Coffee Culture Jan Garden Castro (bio) The Coffeehouse Resistance: Brewing Hope in Desperate Times Sarina Prabasi Green Writers Press www.greenwriterspress.com 224 pages; Print, $19.95 Sarina Prabasi's The Coffeehouse Resistance journeys through selected memories that led this Nepali-heritage woman born in Amsterdam to marry an Ethiopian man, move to the United States, and become a fervent spokesperson for immigrant rights and safe communities. The subtitle Brewing Hope in Desperate Times further alerts us that Prabasi's memoir focuses on brewing activist strategies and coffee. The author avoids the word racism and rarely mentions the dark and tan skin colors of her family of four. Six engaging chapters have sections separated by coffee bean emojis which focus on overcoming a particular challenge related to family, researching coffee's Ethiopian origins, and becoming American. The main years covered are from 2009 to 2018. In the opening scene, set in 2011, readers meet author Sarina, eighteen-month old Juni, and her husband Elias as they arrive at JFK Airport on a humid July night. The next day, as they open the door of their small, as-yet-unseen Hudson Heights apartment rented online, claustrophobia sets in. Next, the downstairs neighbor complains that their fan is too noisy. Prabasi confides, I wonder what we're going to do with these old towels, with a downstairs neighbor who can hear our fan, with an active daughter in a dollhouse apartment, in a city of millions with no job, no real connections. For the first time since we decided to move, I feel a little afraid. Prabasi then skips through memory and growing up: "There's an irony in the fact that I am writing a memoir. Or perhaps it makes perfect sense. I have a deep fear of forgetting. I've had to let go of places, friends, family, over and over again." The author shares a few early memories, such as her best friend Julie's move to the United States and her family's move back to Nepal in fifth grade, but not that, growing up, she also lived in India and China. The reader learns that, thanks to education, Sabrina's father, born in a remote Nepali village, became an academic at an "acclaimed university" and later a senior diplomat. Her father both sends her to Nepal's American international school and also overrides his own mother's adherence to cultural traditions that ban menstruating women from the kitchen and from the dinner table. College in [End Page 22] Massachusetts seems like a lonely time until Sarina discovers the Haymarket Café, named for the May 4, 1884 "Haymarket Affair" in Chicago that led to International Workers Day. This introduces the coffeehouse-as-study hall and meeting place theme. "Addis Ababa" is the next chapter. Sarina is working for a nonprofit in Washington, D. C. when her boss invites her to be part of a work trip to Addis Ababa, Ethiopia. Sarina had heard about the city from her father's travels there in the late 1960's. Readers aren't given the exact year, only told that when she and her boss Liz arrive, many soldiers with rifles are at the airport. Liz speaks Amharic, and she and Sarina visit her favorite places—they buy coffee freshly-roasted coffee at Tomoca. One page and five years later, roughly around 2007-8, Sarina is regularly visiting Ethiopia for work. She has become a macchiato coffee aficionado, often accompanied by Elias, a cute taxi guy who's a childhood friend of one of her co-workers. As they become close over macchiatos, Elias starts a restaurant, they begin living together, and the political situation in Ethiopia worsens. Unlike the novels by Ethiophian author Maaza Mengiste, which delve into the high losses of life as a result of military power struggles that began in the mid-1930s and are ongoing, this memoir understates the disappearance of one of Elias's friends, Elias's own arrest, and the man following him. Sarina gets a diplomat friend to call off the man shadowing Elias. Even Prabasi's account suggesting that a national election has been rigged...

Measuring network resilience through connection patterns

Networks are at the core of modeling many engineering contexts, mainly in the case of infrastructures and communication systems. The resilience of a network, which is the property of the system capable of absorbing external shocks, is then of paramount relevance in the applications. This paper deals with this topic by advancing a theoretical proposal for measuring the resilience of a network. The proposal is based on the study of the shocks propagation along the patterns of connections among nodes. The theoretical model is tested on the real-world instances of two important airport systems in the US air traffic network: Illinois (including the hub of Chicago) and New York states (with JFK airport).

Spatial welfare effects of shared taxi operating policies for first mile airport access

Abstract With increasing availability of alternative mobility options for first/last mile, it is necessary to better understand how shared taxis are impacting airport access demand and consumer surplus. However, no study has been conducted to evaluate the welfare effects of the range of shared taxi matching and fare allocation policies for airport access. Using several data sources primarily from Port Authority of NY and NJ and The Taxi and Limousine Commission, a mode choice model is estimated for access to John F. Kennedy International Airport in New York City. The baseline model and data show that passengers have a value of time of $101 per hour, consistent with Harvey’s study from 1986. Airport taxi travelers are also elastic to cost in a similar manner to public transit. The model is used to evaluate two policies: a first (we call this wait-share policy) where taxis can offer shared rides for two passengers from the same zip code, incorporating an endogenous expected wait time variable; and a second (we call this space-share policy) where taxis match randomly arriving passengers from any zip codes in the city. These two policies reflect extreme ends of a spectrum of policies between waiting and detouring. Findings suggest that having a shared taxi option benefit passengers in NYC going to JFK airport by at least 10% increase in consumer surplus. However, the increase in taxi ridership comes at a cost to transit ridership. Furthermore, the population in NYC that benefits most is highly dependent on the type of shared taxi policy. A wait-share policy benefits passengers from the dense parts of Manhattan most, while a space-share policy distributes the benefits more to other boroughs. These insights can help policymakers set regulations in providing first/last mile ride-sharing taxi options in different cities around the world.

EIS Crossing Barriers and Work as a Espousal to Transform

Someone who buys Yahoo at this instant will get hold of their Asian stakes in Alibaba and Yahoo Japan (which is in part owned by SoftBank). Alibaba and SoftBank are going to be amongst the top 10 (if not top 5) global Internet players in the next 10 years. So many people deleted their Uber accounts in the wake of the ‘#DeleteUber’ movement that the ride-sharing company had to rapidly generate a mechanized way for customers to run off the service. The mass migration began on 27th January shortly after US President Donald Trump signed an executive order as an interim measure so to stop citizens from seven countries from entering the United States. This caused a large remonstration at New York’s JFK airport, supported by the New York Taxi Workers Alliance, who went on strike and stopped pickups in the area. Alibaba is going to formulate a gigantic move into the US and it is expected that Amazon and Jeff Bezos in its cross-hairs.

How We Came to Be: Evidence from Primate Relatives and Fossil Ancestors Offer Clues to How Human Capabilities for Birth, Posture, and Walking Evolved

How We Came to Be: Evidence from Primate Relatives and Fossil Ancestors Offer Clues to How Human Capabilities for Birth, Posture, and Walking Evolved

Dynamic Control of Runway Configurations and of Arrival and Departure Service Rates at JFK Airport Under Stochastic Queue Conditions

High levels of flight delays require implementation of airport congestion mitigation tools. In this paper, we optimize the use of airport capacity at the tactical level in the face of operational uncertainty. We formulate an original Dynamic Programming model that jointly and dynamically selects runway configurations and the balance of arrival and departure service rates at a busy airport to minimize congestion costs, under stochastic queue dynamics and stochastic operating conditions. Control is exercised as a function of flight schedules, of arrival and departure queue lengths, and of weather and wind conditions. We implement the model in a realistic setting at JFK Airport. The exact Dynamic Programming algorithm terminates within reasonable time frames. In addition, we implement an approximate one-step look-ahead algorithm that considerably accelerates execution of the model and results in close-to-optimal policies. Together, these solution algorithms enable online implementation of the model using real-time information on flight schedules and meteorological conditions. Application of the model shows that the optimal policy is path-dependent, i.e., it depends on prior decisions and on the stochastic evolution of arrival and departure queues during the day. This underscores the theoretical and practical need for integrating operating stochasticity into the decision-making framework. From comparisons with an alternative model based on deterministic queue dynamics, we estimate the benefit of considering queue stochasticity at 5% to 20%. Finally, comparisons with heuristics designed to imitate actual operating procedures suggest that the model can yield significant cost savings, estimated at 20% to 30%.

Verification column

The technical column on verification presents an invited contribution by César A. Muñoz, Aaron Dutle, Anthony Narkawicz, and Jason Upchurch at NASA Langley Research Center titled Unmanned Aircraft Systems in the National Airspace System: A Formal Methods Perspective in the July issue of the SIGLOG newsletter. In the past few years we have seen a dramatic increase in the number of hobbyist unmanned aircraft systems (UAS). In addition we have seen a push by several companies including Amazon to use UAS as a package delivery mechanism. The increasing numbers of UAS in our current airspace have introduced a new safety challenge. There have been some high-profile incidents that were reported widely in the media. One example was a drone being 100 feet within an commercial airliner at the JFK airport in New York in Aug 2015, while another was a near miss at the Los Angeles airport between a Lufthansa passenger jumbo jet and a UAS in March 2016. These are however not isolated incidents. The Federal Aviation Administration (FAA) records shows that there are hundreds of close calls between airplanes and UAS in the US airspace. Similar reports have been documented in the UK and Europe. This safety concern has prompted the development of a detect and avoid capability for the UAS that is designed to avoid aircraft in its vicinity. The article presents the work being done at the NASA Langley Research Center Formal Methods group in Hampton Virigina. I am very excited for this article to appear in the SIGLOG newsletter. This article I believe will be of interest to people not only in the logic, formal methods, and verification community but a broader and more general audience as well.

ANALYTICAL INDUCTION ON SECURITY PERCEPTIONS OF THE TURKISH AND AMERICAN CITIZENS WITH REGARD TO AIRPORT SECURITY PRACTICES

Airport and aviation security has become more sophisticated due to the globalization process, and advance in new technologies as well as innovations in the area of transportation and telecommunication. Thus, the present study aiming to provide insights towards airport security practices, attempts to analyze behavioral patterns of airline passengers regarding airport security practices and processes. The purpose of this study is to illustrate the impact of airport practices on perceptions of airline passengers. In order to collect the data, the researcher has conducted field observations at the JFK Airport and made interviews in 2010 with diverse ethnic groups including the Turkish and USA nationals amounting to 14 interviewees in total. In terms of units of analysis with regard to the present study, three aspects will be discussed within the context of qualitative methodology. First, habitat refers to the airport, which is a unique place where people from all around the world and different cultures can be present and interact each other. Second, groups include the Turkish and American citizens, which form a social group and a distinctive social entity. In order to eliminate biases and prejudgments between individual cultures, American and the Turkish citizens have been the main focus groups. By doing so, this study will contribute to the literature by showing how these two distinctive cultures view aspects of world affairs in a common way and share similar concerns. Third, practices are about the acts and activities at the airport, which can also be considered as a social setting.

A Note from the Guest Editor

What is citizenship? Who is a citizen? Such questions have been posed continuously since the birth of the nation-state, as well as many times before. A concept so often defined in academic literatures and popular discourse by its inverse or moments of greatest violence, citizenship can call to mind those outside of its boundaries: women, slaves, migrants. In comedic form, it is Tom Hanks in Terminal, limboed in a place of transit (New York’s JFK airport) because his country has dissolved overnight, while he was in flight. Far less comedic is the true story on which the film is based: Mehran Karimi Nasseri’s seventeen-year stay in Terminal 1 of Charles de Gaulle airport, Paris, after he claimed to have been expelled from Iran and while officials in France and Belgium refused him entry. In sadder terms, and in a more personal sense to those reading this from the halls of academia, it is the individuals on each and every one of your college campuses who may graduate but never work on the books, do research but never teach, hide their families in the shadows, hope to never get pulled over for speeding or a busted taillight, or any number of other considerations that most of us simply never contemplate.

Facial recognition tech at JFK airport as DHS stalls on biometric exit system

Facial recognition tech at JFK airport as DHS stalls on biometric exit system

A New Multilevel Input Layer Artificial Neural Network for Predicting Flight Delays at JFK Airport

One of the biggest problems for major airline is predicting flight delay. Airlines try to reduce delays to gain the loyalty of their customers. Hence, a prediction model that airliners can use to forecast possible delays is of significant importance. In this regards, artificial neural network (ANN) techniques can be beneficial for this application. One of the main challenges of using ANNs is handling nominal variables. 1-of-N encoding is widely used to deal with this problem, however, this method is known to reduce the performance of ANN's by introducing multicollinearity. In this paper, we introduce a new type of multilevel input layer ANN that can handle nominal variables and is interpretable in a sense that one can easily see the relationships between different input variables and output variables. As a case study, the proposed method was applied to predict the delay of incoming flights at JFK airport, where the neurons of each sublayer of the input layer symbolize the delay sources at different levels of the system, and the activation of each neuron represents the possibility of being the source of overall delay. Finally, we compared the proposed approach with the traditional gradient descent back propagation ANN model and the proposed model was able to outperform the traditional backpropagation method in terms of the prediction error (root mean squared error) and time required to train the ANN model.

An Integrated Scheduling and Operations Approach to Airport Congestion Mitigation

Most flight delays are created by imbalances between demand and capacity at the busiest airports. Absent large increases in capacity, airport congestion can only be mitigated through scheduling interventions or improved capacity utilization. This paper presents an integrated approach that jointly optimizes the airport’s flight schedule at the strategic level and the utilization of airport capacity at the tactical level, subject to scheduling, capacity, and delay-reduction constraints. The capacity-utilization part involves controlling the runway configuration and the balance of arrival and departure service rates to minimize congestion costs. The schedule optimization reschedules a selected set of flights to reduce the demand-capacity mismatches while minimizing interference with airline competitive scheduling. We develop an original iterative solution algorithm that integrates a stochastic queuing model of airport congestion, a dynamic programming model of capacity utilization, and an integer programming model of scheduling interventions. The algorithm is shown to converge in reasonable computational times. Extensive computational results for JFK Airport suggest that substantial delay reductions can be achieved through limited changes in airline schedules. It is also shown that the proposed integrated approach to airport congestion mitigation performs significantly better than the typical sequential approach, where scheduling and operational decisions are made separately.

Alfonso W. Quiroz Norris (1956–2013)

Alfonso W. Quiroz Norris (1956–2013)

Airline consolidation and the distribution of traffic between primary and secondary hubs

Several airline consolidation events have recently been completed both in Europe and in the United States. The model we develop considers two airlines operating hub-and-spoke networks, using different hubs to connect the same spoke airports. We assume the airlines to be vertically differentiated, which allows us to distinguish between primary and secondary hubs. We conclude that this differentiation in air services becomes more accentuated after consolidation, with an increased number of flights being channeled through the primary hub. However, congestion can act as a brake on the concentration of flight frequency in the primary hub following consolidation. Our empirical application involves an analysis of Delta's network following its merger with Northwest. We find evidence consistent with an increase in the importance of Delta's primary hubs at the expense of its secondary airports. We also find some evidence suggesting that the carrier chooses to divert traffic away from those hub airports that were more prone to delays prior to the merger, in particular New York's JFK airport.

Can Tarmac Delays Be Minimized? An Application of Multiple-Stage Stochastic Linear Programming with Recourse

Airline and airport analysts must make operational decisions in a series of stages. They are challenged to minimize the impact of uncertainty to optimize constrained resources in a dynamic environment. Whereas sensitivity analysis may be appropriate for deterministic decision problems, such analysis may not be suitable for making decisions under uncertainty. This paper explains how aviation practitioners can improve ground movements based on some key operational variables (departure capacity and departure counts), as well as some random variables (taxi-out delays and departure demand). This paper also demonstrates how a multiple-stage stochastic program with recourse can help airline and airport operators generate a set of scenarios related to some initial conditions illustrated by the case of New York’s JFK airport.