Department of Electrical and Systems Engineering

ESE Senior Design, 2012-2013
Ken Laker, Peter Scott

ESE Home Page > ESE Undergraduate Labs > Senior Design > 2012-2013 Abstracts


The Smarter Train

Eric He, Adish Mohnot, David Robinson, and Daniel Wiegard

Advisor: Prof. Jan Van der Spiegel


Train travel is one of the largest forms of public transportation in the world, especially for commuters. However, the journey time of passengers is excessive and the frequency of trains at stations is lacking. This is mainly because a train must come to a full stop at every station. Therefore every passenger on the train must stop at every station, regardless of his or her destination.


This system provides a control scheme for trains which monitors current train conditions and specifications to decrease travel time and increase the frequency of trains arriving at a station. This is primarily accomplished by eliminating the need for an entire train to come to a complete stop. With this control system and the automatic couplers, railway switches, and self-powered cars that are already being used in various parts of the world, it is possible for a train to pass a station and release one or more cars which independently stop at said station. Meanwhile another independent car can originate from the station and automatically connect to the passing train. This control system dictates train movement and connections as well as the state of railway switch to achieve such functionality.


The control scheme greatly reduces travel time and increases frequency of train operations by virtually  eliminating  the  need  for  an  entire  train  to  stop  at  each  station.  The system is implemented through a computer model, which outputs a visual representation of a train system

in action.


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Green Pocket Retailing

Authors: Hilary Grosskopf, Isabella Obediente, Melisa Satili, Anthony Scafidi

Advisor:  Dr. Scott and Dr Sobkiw


Green Pocket Retailing aims to support apparel retailers by helping them meet their sustainability goals and reduce their transportation costs, while increasing sales through providing an improved in-store experience for the customer. Our system includes two important components:

With our Green Star System (GSS), retailers can calculate and track their carbon emissions. Using characteristics of each product order, entered by the retailer, the GSS uses stored values and equations to calculate the time and environmental impact of each combination of transportation modes available to the retailer. The retailer can compare choices and choose the option that best suits their goals, then save and track their costs and environmental transportation practices over time.

Through the second part of our solution, Consumer Product Pages (CPP), retailers can relay compelling facts and environmental information to customers through a QR code that is attached to the product hangtag. The retailer can access the customer activity reports and easily update product information stored in the QR.

The GSS and CPP systems work together to allow retailers to internally work on optimizing their transportation network, while aligning consumer interests by showing differentiating aspects of products and environmental practices to consumers.

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Authors: Joon Hyeong (Ryan) Im, Michelle Leong, Mehdi Charfi, and Xiujie (Amy) Guo

Advisor:  Govind Shah and Prof. K. R. Laker


Today,  more  than  ever  before,  organizations  of  any  size  are  emphasizing collaboration in order to achieve success in the form of higher productivity, innovative solutions,  or  any  type  of  positive  value  added  to  the  organization.  Given  the complexities   of   corporate   structure   and   projects   themselves,   understanding collaboration and how to improve it has become a necessity. In order to progress, there is a need for improvement in collaboration among a group of people. However, there exists a significant amount of conflicting professional insight of what collaboration is exactly. Depending on the individual or their respective industry, collaboration can be viewed in many different settings. Therefore, this project thoroughly investigates what collaboration is and how it can be measured. In order to do so, the scope of a small group of individuals has been set to signify the environment in which this system will be utilized.

The  approach  this  system  takes  is  to  identify  several  crucial  parameters  of collaboration, quantify these parameters, and use a mathematical model to render an end  product  that  provides  suggestions  for  optimal  allocation  of  team  members  to specific  tasks.  Additional  outputs  include  recommendations  for  individuals  on  what areas of collaborative skills and which partnerships within a team should be improved upon.

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Authors: Blair Canner, William Dib, Charlie Gao, & Eric Szeto

Advisor:  Dr. Ali Jadbabaie


Understanding the intricacies of the market and price dynamics of various stocks is a challenge to anyone who has ever delved into this asset class in hope of generating capital gains as an additional source of income. Currently, there are many funds, such as mutual funds, exchange traded funds, and index funds that offer their services and expertise to the general investor to help manage their money. However, investing in these funds requires paying additional fees, which chips away at the returns of the general investor. Given the current state of the financial system, these fees are chipping away at an already repressed rate of return.


The approach this project takes is to provide the general investor with a tool to build a custom long-term portfolio of stocks, based on Markowitz’s modern portfolio theory, that they can manage themselves. This eliminates expensive fees associated with the funds as well as confusion, due to a lack of expertise, investors may have when directly investing in the stock market.


After collecting the historical stock prices of all the companies in the S&P 500, a full model was developed in order to optimize a portfolio that achieves the user’s target return while minimizing risk. The model was backtested over a 5, 7, and 10-year period and the optimal portfolio was able to beat the returns of the S&P 500 index on both an absolute and risk-adjusted basis. Additionally, a web interface was created to assist the user in assessing their financial investing needs.


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Authors: Jessica Jiang, Taylor Lee & Connie Wu

Advisor: Prof. Jan Van der Spiegel


There are approximately 285 million visually impaired individuals in the world. For these individuals, familiarity with their surrounding environment is critical to ensuring personal safety due to their limited vision. Although their mobility is aided by assistive walking tools, including white canes and guide dogs, users can only use them to determine if there is an obstruction in their path but not what that object is. Studies have shown that unexpected obstacles are one of the main causes for accidents while the visually impaired are walking. Therefore, the hearSight system tackles this problem by identifying pedestrian signs and informing users of detours.

To utilize the system, the user presses a button to take an image, which is then processed an image processing algorithm stored on a PandaBoard computer development platform. If a pedestrian sign is detected, the identity of the sign is vocalized through earphones. Otherwise, the user is informed that no sign was detected. By amplifying the user’s knowledge of what obstacles lie 10 to 30 feet ahead, the system greatly complements the user’s existing walking aids.

Weighing 1.4 pounds, the hearSight system successfully identifies and vocalizes the identity of 23 pedestrian signs with 95% accuracy when tested over 233 trials. Vocalized descriptions are then given to the user in as fast as 3 seconds, the average time a visually impaired individual takes to walk 12 feet. Given these results, the hearSight system is technology that is pivotal to greatly enhancing personal safety for the visually impaired.

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fastER: Simulating Patient Flow to Reduce Emergency Room Wait Times and Costs

Authors: Omar Beiruty, Tarang Kapoor, Ashutosh Patra, John Robinson

Advisor: Prof. Nancy Hanrahan

Special Resource: Suzanna Ho, RN"


Rising healthcare costs and patient demand have increased the need for more efficient allocation of healthcare resources.  Within hospital systems, the emergency department has traditionally been a large and inefficient cost center.  Solutions that can reduce ER costs and patient wait times are incredibly valuable and in-demand. 

fastER models patient flow from entrance until discharge in a given emergency department by utilizing queuing theory. This yields two valuable insights. First, it can predict an incoming patient’s wait time given his ailment and/or triage category (level of medical severity). Second, fastER can provide sensitivity analysis on how patient wait times vary given different ER’s resources levels.

The impact of the product is twofold.  First, it provides crucial wait time information to incoming patients through a VoiceXML application.  Patients are able to hear what their wait time will be through an easily accessible phone call.  Also, by providing wait time information, emergency departments can deter low-severity patients from unnecessarily utilizing costly ER resources.  Second, a hospital administrator can utilize fastER’s sensitivity results to determine the ER resource level that meets hospital-specific wait time targets. This will allow them to minimize costs while maintaining acceptable wait times.

In summary, fastER models patient flow through an emergency department system, providing critical information to both patient and hospital administrators. Through fastER, this information can be used to reduce ER wait times and costs.

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Authors: Markus Beissinger (CIS), Krishna Kaliannan, Varant Zanoyan (CIS)

Advisors: Prof. Mitch Marcus, Prof. Robert Stine


This year, over 300 million individuals around the globe are purchasing a laptop. Of these individuals, over 58% will seek significant help from online sites, each spending an average of three weeks performing research prior to making a purchase. The majority of these individuals spend such a long time trying to find the right laptop because they struggle to understand how technical specifications, such as “RAM”, “processor speed” and “hard drive speed” relate to laptop uses, such as “gaming”, “listening to music”, and “watching HD movies.”

Sperch ( is an intelligent laptop recommendation engine designed to reduce the amount of time consumers spend looking for laptops from three weeks to a matter of minutes. First, Sperch continuously scans the internet, collecting the latest laptop review information from blogs, review websites, tweets and laptop distributors. Second, using the latest algorithms from the field of natural language processing, Sperch analyzes these reviews to learn the strengths and weaknesses of laptops on the market, and to learn relationships between technical specifications and laptop uses. Finally, Sperch has an intuitive, easy-to-use interface wherein consumers indicate how they plan to use a laptop and Sperch delivers a ranked list of laptop recommendations from which users can conveniently choose.

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Authors: Young Hyun (Albert) Kwon, Yu Chen (Martin) Pan, Perk Lun Lim, Kaiyu (Alex) Zhang

Advisor Prof. Andre' DeHon, Prof. Boon Thau Loo

Denial-of-service (DoS) is an attack on critical services of the Internet by overloading them with unwanted (disorderly) traffic, thereby preventing them from servicing legitimate clients. To mitigate this issue, we introduce our product called ROTORouter (Route Orderly Traffic Only Router). ROTORouter is a router that can identify authorized data-flows and filter the disorderly packets before they reach the end servers. ROTORouter also allows for dynamic restructuring of the network topology to defend against DoS attacks via software called RapidNet. ROTORouter was developed on a developmental platform called NetFPGA10G, a programmable hardware and software platform that enables for rapid prototyping of networking devices.

In our experimental set up, we show that ROTORouter performs equally as well as a typical router under normal conditions, and achieves 5 times the throughput of a typical router under a DoS attack. We can thus maintain sufficient throughput for many different tasks, such as remote desktop and video streaming, even under attack. Additionally, despite the added complexity for filtering, ROTORouter utilizes only a third of the available resources of our platform, making our router feasible for many different applications.

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Making PennMed Medicaid Compliant

Authors: Pratham Mittal, Salil Gupta and Ridhima Parvathaneni

Advisor: Prof. Barry Silverman

Recently, the Centers for Medicare & Medicaid Services (CMS) began using readmission rate as apublicly reported metric, with plans to lower reimbursement to hospitals with excess risk-standardized readmission rates. Our client, PennMed’s Cardiac Center, is hence affected by this policy and our project is to make the Center Medicare compliant. To do so, we have designed and implemented an agent based readmission risk model that can help the Center model various clinical and out-patient interventions, conduct a virtual comparative analysis with the status quo and predict efficacies.


The first phase of the study included an analysis of parameters that predict readmissions the best and a cognitive analysis of a typical patient's attitudes. Using these factors, the agents' behaviors were designed and optimized to mirror that of actual patients. The second phase put these patient agents in the context of the existing hospital workflows. This allowed us to see where in the hospital workflows is a patient's health diminishing the most and where lies the highest scope for improvement. In the third and last phase, various clinical and outpatient interventions were studied and modeled, which allowed us to access which of these prospective interventions were most effective and at what point in the workflows.


The preliminary results of the agent based model show that Penn's Care Connect Program, whereby nurses make follow up calls with patients, is the most effective of prospective interventions, especially in the first month immediately after discharge.

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Fast In Fast Out (FIFO): Airplane Boarding Optimization Model

Authors: Tess Donnelly, Stefania Halac, Rachel Resek, Brittany Wohler

Advisor Dr. Peter Scott Mr. Richard Reinhart


An airplane on the ground is an airplane that is not making money. Therefore reducing ground time is crucial in increasing airlines’ profitability. Given that boarding is the main contributing factor in delaying departure, airlines would benefit in terms of profitability and customer satisfaction from optimizing this procedure. However, many airlines have yet to implement optimal boarding methods, and are thus foregoing potential cost savings.
Our project models the airplane boarding process and provides its stakeholders, the airlines, with optimal boarding methods. The model provides a unique approach to the boarding problem by incorporating more realistic inputs than previous models. Specific passenger demographic data were provided by a major airline to contribute to the accuracy of our results.
The model uses the application of Markov chains to simulate the boarding process for a commonly-used narrow body plane. A number of boarding procedures, both existing and modified, were tested through thousands of simulations to determine an average boarding time for each specified procedure. A sensitivity analysis was conducted, which tested for consistency of results under a number of situational factors and varied group sizes. In addition, a cost-benefit analysis was carried out to determine the savings potential for airlines. From these analyses, an optimal boarding method was recommended.


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Simulation Interface for Optimizing Daily Cross-docking Operations

Authors:  Frederick Abiprabowo, Napat Harinsuit, Samuel Lim, Willis Zhang

Advisor: Prof. Peter Hahn , Prof. Monique Guignard-Spielberg


Recent breakthroughs in the field of supply chain management have yielded exciting developments. Cross-docking - a logistic technique that consolidates inbound products - has emerged as a forerunner in reducing inventory holding and transportation costs. However, substantial challenges that prevent it from becoming widely adopted still exist, labor cost and item shipping delays being the most significant barriers.  Although extensive research has been performed on optimizing the physical dimensions of cross-docks, companies still lack tools to evaluate the efficacy of specific labor assignments and largely depend on arbitrary rule-of-thumb and intuition, which incur risks to labor cost.


Our team seeks to develop a model that utilizes discrete-event simulation to dynamically replicate the operations of a cross-docking facility. We aim to improve its accessibility by designing a data-driven simulation tool that can be used by floor managers. Through ExtendSim software and our collaboration with Damco, an international logistics industry leader, we have constructed a prototype to determine the impact of resource assignments on the cost of shipping per inbound container.


The data-driven model we have designed serves as a tool that enables floor managers to evaluate assignment strategies in a risk-free, costless environment. The model’s accuracy has been validated against month-long historical financial data and has been deployed on the Chesapeake facility, subsequently to be incorporated into other facilities with slight modifications


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Primate Hand Actuation Tracker (PHAT)

Authors: Cameron Cogan, David Hallac, Nicholas Howarth, Ashleigh Thomas, Samuel Wolfson

Advisor:  Prof. Jan Van der Spiegel, Dr. Milin Zhang

Currently, there is no treatment for nervous system injuries that leave victims paralyzed, but with undamaged limbs. A possible solution is to reroute the neural signal around the damaged area, so that the patient can control their own limbs. This next generation of prosthetics would be purely electrical, monitoring brain signals and wirelessly sending commands to muscle actuator circuits.

The first step in developing such prosthetics is to precisely map brain signals to motor output. To this end, a comprehensive, accurately time-stamped motion measurement system for a humanoid hand is required. We propose a two-pronged approach that is both inexpensive compared to prior solutions and does not introduce noise in the neurological recording spectrum (below 10 kHz). 

A glove fitted with an inertial sensor network is used to detect changes in relative position, and a traditional motion capture setup with three cameras placed orthogonally around the hand is used to monitor absolute position. The two data streams are integrated using a Kalman filter, the output of which is used to derive an accurate depiction of all 20 degrees of freedom in the humanoid hand using inverse kinematics.

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Stadium Traffic

Authors: Felipe Ochoa Virijevic, Parth Doshi, Zain A Mukaty 

Advisor:  Prof. Andrew Huemmler

Citizens Bank Park, the home stadium of the Philadelphia Phillies, is located within city limits and is accessible by car, train and bus. In the 81 home games of their 2012 season, the Phillies  had an average attendance of 44,021, for a total of over 3.5 million fan trips. All these fans generate greenhouse gases traveling to and from the stadium.


The Phillies have started the ”Red Goes Green” initiative to reduce their environmental impact by installing  solar panels, planting trees, and buying offsets for their carbon emmissions. They also offer tips for fans who want to help with this mission.  No significant  efforts have been made so far, however, to quantify and reduce the environmental footprint  of these fans traveling to and from the stadium.


This system meets two important  needs that would  help the Phillies  and their fans further reduce their carbon footprint.


First, it estimates the total amount of emissions currently  generated in based on the average distance traveled by fans and on the types of transportation they use. These parameters are in turn estimated by a comprehensive  traffic model.


Second, the system provides fans information  regarding alternative travel options to and from the stadium by interfacing with the SEPTA website.  The tool is sensitive to the unusually-high demand placed on transportation infrastructure  around the game, and it gives fans information on the congestion levels, travel time, and environmental impact of each travel option.

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Wireless Neural Recording System

Authors: Tedd Ahn, Alex Hildick-Smith, Rick Krajewski, Rick Krajewski

Advisor: Jan Van der Spiegel, Milin Zhang

Neurons and their signal pathways have been a topic of research for as long as there has been
technology to analyze them. Learning more about these signals, and their correlation to the
nervous system, is important for a myriad of medical applications. Brain computer interfaces,
rehabilitation, and prosthetic limbs are but a few examples of areas that can benefit from neural
research. Traditionally systems to record neural signals have been wired modules, to facilitate
data flow and minimize system complexity. This requires the subject to be relatively stationary
and restricts research on the neural behavior during movement.
The purpose of our project is to build a prototype of a wireless neural recording system, which
will allow more flexibility in the observation of the subject and in the placement of the system. It
is composed of an analog front-end sampling module, a microcontroller to handle data flow and
repackaging, a wireless module to transmit the data to a PC, and a MATLAB-based graphical
user interface on the PC to provide live data processing.
The hardware for the system is composed of two main parts. A 4x2 inch printed circuit board
that is battery powered plugs directly into a microcontroller development board. This portion
could interface with four probes implanted in a subject’s brain, and transmit the obtained neural
signals wirelessly. The second portion receives the signals with a wireless receiver and interfaces
with a PC through a second microcontroller. The graphical user interface on a PC provides basic
signal processing capabilities.

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GIS System for SEPTA Railroad System

Authors: Scott Biddle, Arda Kuyumcu, Amanda Pacheco, Gorkem Yutseven 

Advisor:  Prof. C. J. Taylor

The Southeastern Pennsylvania Transportation Authority (SEPTA) is one of the largest metropolitan transit systems in the world, with an annual ridership of nearly 340 million. A major concern with such a large transportation system is safety: each year, many safety incidents occur on SEPTA transit systems, particularly the Regional Rail Lines. Our work discusses the proposed implementation of a Geographic Information System (GIS) to be used by SEPTA. GIS help to transform collected geographic data into useful information.  Safety incident reporting is an area where SEPTA does not have a uniform data visualization tool, nor a GIS, nor any means to analyze and make use of their data.

The implementation attempts to provide various information and analytics tools to SEPTA safety personnel. The web application we will build is going to transform the unstructured incident data to a powerful analysis tool. The first problem our GIS will solve is identification of the specific regions the SEPTA staff should concentrate its efforts on in order to reduce railway incidents. Additionally, the system would be able to add additional layers of data to make an even more detailed analysis of the incidents.

Our system looks to find correlations between areas where accidents occur the most, and its possible causations such as high traffic, or large populations. Finally, the system helps SEPTA to locate target potential schools where safety education should be provided sufficiently, in order to decrease the incidence of safety incidents.


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Authors:  Jonatha Post, Alec Miller, Elizabeth Rubenfield, Nora Turek

Advisor:  Prof. Jan Van der Spiegel



In order to extend existing infrastructure systems, such as rail lines, transportation agencies must allocate a significant amount of time and capital to creating a proposal for the extension plan and surveying the surrounding region.  The consulting firms hired during this process to formalize extension plans are expensive and, in many cases, the resulting plan fails to meet FTA requirements for funding. Thus, agencies spend a great deal of money furthering projects that are doomed to fail from the start.

In response to this problem, our team has built the ExtensionEvaluator, a tool that can be used in the preliminary planning stages of capital projects in order to determine whether the project is likely to meet the requirements set forth by the FTA.  SEPTA and other transportation agencies can use a program like ExtensionEvaluator to conduct a preliminary screen of the economic, environmental, and mobility-improvement conditions that must be met by extensions before engaging in contracts with external consultants.

Using the FTA requirements as a framework, we created a model of the requirements that extension plans must meet.  Cost-effectiveness, economic development, mobility improvement, land use, and environmental benefit are calculated using inputs provided by the user in order to determine a preliminary rating that the plan could expect to receive.  This tool could eliminate unnecessary spending by capital-constrained transportation agencies and allow such agencies to focus on more successful projects. 

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Farm to Philly: Logistics of Implementing an E-Commerce System in Philadelphia Farming Co-ops

Authors: Katie Jordan, Jocelyn Ye, Kathleen Mantell, Andrea Yoss

Advisor: Dr Scott and Dr Sobkiw           


Community food co-ops are small businesses that specialize in aggregating and selling locally grown produce to community members. Despite increasing demand for this higher-quality produce, many of Philadelphia’s urban consumers do not have access to co-ops in their neighborhoods. This project aims to help co-ops integrate e-commerce into their established businesses as a new outlet for sales, boost profits for local Pennsylvania farmers, and ultimately increase the amount of locally-grown produce sold in Philadelphia.

Based on the factors and metrics that have been determined to be the most relevant for local co-ops (namely, cost and efficiency), our tool provides a recommendation for the optimal design of the fulfillment and delivery components of an e-commerce system. The tool allows co-op managers to enter inputs such as profits, daily sales, and growth estimates, and in turn receive output information such as feasibility of investing in external warehousing or other storage solutions, networking effects with other community co-ops, and suggested number of delivery trucks. These recommendations are generated through programmed algorithms in MATLAB and JAVA.

Additionally, our project showcases a prototype of a Graphical User Interface in the form of an e-commerce website. This prototype incorporates aspects of our recommended fulfillment and delivery systems, as well as important external factors that we have identified through our verification and validation processes.

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Pedestrian Safety System

Authors: Nikhil Karnik, Jordan Parker, Rahul Bhan, Vaibhav Wardhen

Advisor: Prof Dan Lee

When city buses execute turns, they risk colliding with pedestrians standing on the curb. The South Eastern Public Transportation Authority (SEPTA) encounters approximately 100 bus accidents annually, 60% of which occur while buses are turning. Transportation authorities are exposed to significant litigation risk from such accidents, with jury awards costing operators upto $20mm annually. Thus, a system is needed to reduce the risk turning buses pose to pedestrians.

The competing Turn Warning system, implemented by Clever Devices, requires a sensor to be placed on the bus’s steering column. The system is costly, difficult to install, and does not provide pedestrians with sufficient time to respond to a warning.

Our Pedestrian Safety System combines GPS and IMU devices in order to anticipate a turn and sound an appropriate warning. The system operates with greater accuracy, efficacy and a lower cost. The GPS system determines whether a bus is approaching an intersection at which it will turn. When the bus is near the intersection, a warning system is triggered. If the IMU detects that the turn is not taking place, the warning stops. The locations of expected turns are known beforehand. Hence, our system is route-specific and is currently being trialed on the LUCY bus loop.

The warning system consists of a flashing light and speaker system. The intensity of the warning issued is adjusted depending on the risk-level of each intersection. Our system ensures that pedestrians are issued warnings with enough time to respond, whilst maximizing accuracy and minimizing cost.

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ATS: Adaptive Traffic System

Authors:  Kevin Jiang, Shreshth Sonkiya, Charles Jeon, Thomas Ly

Advisors:  Prof. Dan Lee, Dr. Vukan Vuchic

In urban city environments, fixed-cycle traffic light controllers lead to additional waiting times for drivers and pedestrians. With the onset of Intelligent Transportation Systems (ITS), vehicles can be detected with underground induction loops, and pedestrians with curbside push button poles (binary presence), allowing traffic light controllers to vary the green light times. The problem, however, lies in that many cities cannot afford to implement these systems and do not want to deal with the construction times and hassle of installation. Additionally, ITS systems do not take into account the actual number of pedestrians waiting to cross the street.

We propose a cost-effective ITS system with a 25% increased throughput (compared to fixed-time systems during cases with at least a 5:1 uneven distribution of traffic between opposing traffic lanes), at 1/4 the cost and without the need for heavy roadside construction. Additionally, our system will be able to count the number of pedestrians waiting to cross the street. Four cameras, routers, and ping sensors will be able to detect the general volume of vehicle and pedestrian traffic within the 5 seconds leading up to the traffic light change, and use this information to adjust the upcoming phase duration given to the waiting lane.

We have shown decreased waiting times for both vehicles and pedestrians with our adaptive phase algorithm for a two-phase, four-way-intersection and we are also able to detect the number of vehicles and pedestrians using the hardware and software solutions we have created.

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Renewable Energy Investment Model Within Africa

Authors: Ogugua Chioke and Kavaneet Dhami

Advisor: Prof. Victor Preciado, Prof Ufuk Topcu


Nigeria is one of the largest exporters of petroleum & gas in the world but yet about 60-70% of its population does not have access to constant electricity. This is due to the high-levels of corruption within the system as well as the mismanagement of funds obtained from the exportation of petroleum & gas. In April 2001, the Nigerian government, in association with other world governments, agreed to partake in Millennium Development Goals that would ensure the world poverty level to be halved by 2020. As power is a major contribution to economic growth in any country, the Nigerian government realized the urgency in improving its power generation capacity and decided to boost its renewable energy industry.

This model was ultimately aimed at creating a more structured and effective tool for sourcing foreign investments into the renewable energy industry in Nigeria. The model divided Nigeria into four regions and took inputs about geographical factors of these regions to assess energy generation potentials for various renewable energy sources within these regions. The first phase of this model provided calculations about the projected annual costs of each renewable energy source, and the projected annual revenue to be generated from each renewable source. Using this information, and taking into account inflation rates as well as annual rates of increase of costs, a net-present worth analysis was performed to evaluate the first-phase economic feasibility of each renewable energy source in each of the four regions. The second phase of this model involved incorporating all the hard data onto a more interactive format using web-design skills. It provided a more user-friendly approach to the information that we are presenting. Ultimately, this model serves as a medium for channeling direct foreign investments into the Nigerian renewable energy market.

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Network Resiliency in the Financial System

Authors: Matthew Rybak, Melissa Rudofsky, Saad Anwar, Michael Plis, Sandeep Chalam

Advisor: Professor Ali Jadbabaie


In the aftermath of the 2008 financial meltdown, it was identified that a more prudent method of evaluating banks’ exposure to risk is to view the financial system as a holistic network, rather than evaluating each bank’s risk independent of its peers. Today, markets for individual financial instruments feature banks that are more influential, or “central” in the network, meaning that they are most active in terms of its number of trading partners. When a bank in the network experiences a significant loss in capital (a “shock”) and is unable to make its payments to its creditors, its trading partners are at risk of becoming bankrupt too.

Our product employs a mechanism that models what is known as financial contagion, showing which banks would suffer bankruptcy as a result of a shock affecting one bank in the network. Our product shows existing network structures for common financial instruments and the user is able to expose individual banks to a hypothetical shock as an input. Our model is used to show that different network structures are the cause different rates of contagion and bankruptcy, irrespective of the health of an individual bank’s balance sheet. Users are able to use this product to evaluate the risk associated with their location in the network, and decide whether it is beneficial to change trading partners.

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