Eighth New Jersey Universities Homeland Security Research Consortium Symposium
Homeland Security: From Face Recognition to Disease Detection, Natural Disasters to Transit Security

Friday, December 5, 2008
Princeton University

Organizing Committee:
Paul Lioy, University of Medicine and Dentistry of New Jersey, plioy at eohsi.rutgers.edu
Warren Powell, Princeton University, powell at Princeton.EDU
Fred Roberts, DIMACS, Rutgers University, froberts at dimacs.rutgers.edu
Presented by the New Jersey Universities Homeland Security Research Consortium.

Abstracts:

Poster Title: Video-Rate Terahertz Interferometric Synthetic Aperture Imaging

Robert Barat, New Jersey Institute of Technology;
Zhiwei Liu, New Jersey Institute of Technology;
Ke Su, New Jersey Institute of Technology;
John Federici, New Jersey Institute of Technology;
Dale Gary, New Jersey Institute of Technology;
Zoi-HeleniMichalopoulou, New Jersey Institute of Technology

Because electromagnetic waves in the terahertz (THz) range pass through many common dielectric barriers, and produce characteristic absorption and reflection spectra when interacting with many explosive materials, THz has the potential to become the basis for an explosive detection security system. Active THz imaging systems have many hardware challenges, though, including the need for high-power illumination sources, detector sensitivity, and fast imaging speed. In this presentation, experimental results of a video-rate THz synthetic aperture interferometric imaging system are presented. The 2D image of a continuous wave point source at 0.1 THz is reconstructed at a rate of 16 milliseconds per frame (62 frames/second) with a four element detector array. The image resolution and quality are affected by the number of detectors and the configuration of the detection array. Details of the hardware system, video rate THz image, and the efforts to combine a high-power illumination source with the CW photo-mixing detection system will be presented.


Poster Title: Privacy preserving publication of network data

Smriti Bhagat, Computer Science, Rutgers University

In recent years, there has been a rapid growth in many types of interaction networks, notably, social networks such as Facebook, MySpace, LinkedIn, Twitter; blogs networks, and even online networks for special interest such as cancer awareness etc. These networks encode not just personal information of the users including their location, age, relationship status, and interests, but also sensitive interactions among users of the network. It is important to anonymize this data to protect the privacy of individuals before it is stored, shared or published for various analyses. In this work, we propose a framework to represent such rich communication networks as simple bipartite graphs that encode multiple types of interactions among users. We describe two anonymization techniques based on partitioning nodes of a graph into classes and provide privacy guarantees for each. Further, we present experimental results on anonymized data from a popular social network, demonstrating the high utility achieved on several queries while guaranteeing privacy.

This work is done in collaboration with Graham Cormode, and Balachander Krishnamurthy and Divesh Srivastava.


Presentation Title: Disaster preparedness and evacuation behavioral response

Jon Carnegie, Alan M. Voorhees Transportation Center, Rutgers University

There are many factors which influence a person's decision to evacuate in response to a natural or man-made disaster. For example, the type of disaster, distance from the event, time of day, access to resources such as transportation and a place to stay, individual risk perceptions, and a variety of socio-demographic characteristics can play a role in evacuation decision-making. Similarly, disaster preparedness may depend on a person's risk perceptions, which in turn may depend on a variety of socio-demographic factors. Successful evacuation planning, in part, relies on understanding how prepared citizens are to deal with disaster situations and how they may respond to a situation that may require evacuation. This session will present preliminary findings from a citizen survey on disaster preparedness and evacuation behavior conducted by the Alan M. Voorhees Transportation Center at Rutgers University as part of a regional evacuation planning study. The study, which is being conducted for the northern New Jersey Urban Areas Security Initiative (UASI) Region, New Jersey Office of Homeland Security and Preparedness and the NJ Office of Emergency Management, covers Bergen, Essex, Hudson, Middlesex, Morris, Passaic and Union counties, including the principal cities of Newark and Jersey City.


Poster Title: Cluster detection and pervasive surveillance of nuclear materials using mobile sensors

Jerry Cheng, Computer Science, Rutgers University;
Minge Xie, Computer Science, Rutgers University

Pervasive surveillance of nuclear materials provides an effective way to protect against terrorist attack. The advancement of technology makes nuclear detection devices both economic and portable. The GPS (Global Positioning System) is becoming commonly available. It is feasible for the mass production and installation of such devices on taxi cabs in major cities of U.S.


Presentation Title: Public/Private sector collaboration model during response scenarios

Michael Chumer, NJIT

The research is grounded in an action research/activity theory/articulation frame designed to investigate technology "mashups" that can be used during command center operations. The research focuses on the response dimension of emergency management and utilizes the test EOC at ARDEC in Picatinny Arsenal. SMEs involved in this research includes businesses from the New Jersey Business Force and integrates with the DHS and NORAD/Northcom.


Poster Title: Critical Infrastructure Protection (CIP) interdependency study

Michael Chumer, NJIT

This study is designed to develop a baseline CIP interdependency model for the State of New Jersey. The study will consist of gathering data both qualitatively and quantitatively from the 9 states in the All Hazards Consortium consisting of (NY, NJ, PA, DE, MD, VA, W.VA, NC, and Washington DC). Interdependency models currently being employed will be analyzed in order to develop and generalizable model that has utility for NJ. Cross sector interdependency issues will also be a study deliverable.


Poster Title: Investigating cell phones in the international arena

Eamon P. Doherty, Cybercrime Training Lab Director, Fairleigh Dickinson University;
J.J. Park, Fordham University;
Joel Liebesfeld, Countermeasures Security. Inc.;
Todd Liebesfeld Esq., Countermeasures Security. Inc.;
Gary Stephenson, Cincinnati Associates, UK

Fairleigh Dickinson University has taken a leadership position in the arena of cell phone investigation instruction by developing and offering instruction to law enforcement officers, private security professionals, and students interested in Cybercrime from around the world. Large groups of visiting students from Kyungnam University in South Korea have studied cell phone forensics at FDU and discussed the need for changes in American Cell Phone Forensic software so as to facilitate examinations of cell phones from Asia and the Middle East. Cell phones generally are most advanced in the Far East, followed by the European Community, and then by the United States. Some of the advancements include higher resolution cameras, increased features, and encryption. Most cell Phone Forensic software can only accommodate examinations of recently released American cell phones and a limited number of U.K. phones. This makes it difficult for law enforcement personnel to investigate foreign cell phones from persons In the United States who are the subject of lawful investigations. Our poster will show some simulated cell phone investigations being performed in the United States, UK, and by visiting South Korean students, some of whom are policemen.


Poster Title: Computational modeling of indoor dynamics of chemical warfare agents: Case study with indoor releases of Sarin

P.G. Georgopoulos, Environmental and Occupational Health Sciences Institute (EOHSI), Rutgers University;
S.K. Stamatelos, Environmental and Occupational Health Sciences Institute (EOHSI), Rutgers University;
P. George, Environmental and Occupational Health Sciences Institute (EOHSI), Rutgers University;
S.S. Isukapalli, Environmental and Occupational Health Sciences Institute (EOHSI), Rutgers University

Estimation of short term human inhalation exposures to airborne contaminants indoors poses special challenges depending on the physical, chemical and toxicological properties of the contaminant considered. The majority of currently used models for either residential or occupational applications typically consider idealized configurations of source and receptor settings and employ various simplifying assumptions with respect to mixing and transport processes. However, indoor airflows can be very complex due to factors such as heat sources, obstacles such as furniture, electrical equipment, and the presence and motion of humans. These factors may result in concentration profiles that cannot be adequately captured by "conventional" methods but may be important, especially in the case of highly toxic agents, where human movement and posture will affect contaminant transport and exposure patterns. Alternatively, Computational Fluid Dynamics (CFD) techniques allow estimation of detailed transport patterns through the numerical solution of 3D mass, energy and momentum balance equations, accounting for local mechanical and thermal convection effects on the transport, mixing and deposition of contaminants. Case studies are presented that compare the application of a series of both screening and CFD approaches in calculating exposures for scenarios involving the release of the chemical warfare agent, sarin, in idealized as well as realistic indoor environments. The exposure metrics include temporal profiles in terms of Acute Exposure Guideline Limits (AEGL) values, corresponding to different lengths of exposure. Sensitivities of the estimates developed through different parameterizations and approaches are presented to complement their evaluation. Limitations and strengths of the different methods are identified and their implications in modeling situations, such as emergency events in specific occupational settings (e.g. healthcare facilities), are discussed.


Poster Title: Bioinformatics techniques for disease detection and finding medical countermeasures: Case study with Sulfur Mustard

P.G. Georgopoulos, Environmental and Occupational Health Sciences Institute (EOHSI), Rutgers University;
D.R. Gerecke, Environmental and Occupational Health Sciences Institute (EOHSI), Rutgers University;
M. Chen, Environmental and Occupational Health Sciences Institute (EOHSI), Rutgers University;
M.K. Gordon, Environmental and Occupational Health Sciences Institute (EOHSI), Rutgers University;
Y.C. Chang, Environmental and Occupational Health Sciences Institute (EOHSI), Rutgers University;
W. Tong, U.S. Food and Drug Administration;
I.P. Androulakis, Biomedical Engineering, Rutgers University

Sulfur mustard (HD, SM), is a chemical warfare agent that can penetrate human skin causing extensive blistering at the dermal-epidermal junction after a latency period of several hours. To better understand the progression of SM-induced blistering, gene expression profiling for mouse skin was performed after a single high dose of SM exposure. Punch biopsies of mouse ears were collected at both early and late time periods following SM exposure (previous studies only considered early time periods). The biopsies were examined for pathological disturbances and the samples further assayed for gene expression profiling using the Affymetrix microarray analysis system. Principal component analysis and hierarchical cluster analysis of the differently expressed genes, performed with ArrayTrack showed clear separation of the SM group from the control. Pathway analysis employing the KEGG library as well as Ingenuity Pathway Analysis (IPA) indicated that cytokine-cytokine receptor interaction, cell adhesion molecules (CAMs), and hematopoietic cell lineage are common pathways affected at different time points. Gene ontology analysis identified the most significantly altered biological processes as the immune response, inflammatory response, and chemotaxis; these findings are consistent with other reported results for shorter time periods. Additional microarray experiments were conducted to assess the impact of an inhibitor (MMP-2/MMP-9 inhibitor) on the response to SM exposure. Subtle, but clearly identifiable differences in gene expression were noted when inhibitor was added. These results can help in understanding the molecular mechanism of SM-induced blistering, as well as to test the efficacy of different inhibitors.


Poster Title: An adaptable platform for network intrusion detection systems

Nitesh B. Guinde, ECE Department, NJIT;
Sotirios G. Ziavras, ECE Department, NJIT

Deep packet inspection forms the backbone of any network intrusion detection system. The process involves matching known malicious patterns against the incoming traffic payload. Pattern matching in software is very slow in comparison to network transfer speeds. Due to the high complexity of the matching problem, only FPGA (Field-Programmable Gate Array) or ASIC (Application-Specific Integrated Circuit) design platforms can provide efficient solutions. FPGAs present us with powerful choices for deep packet inspection due to their programmability in the field that permits target architecture specialization for high speed and effectiveness. However, most of the current deep packet inspection solutions that employ FPGAs involve reprogramming the entire FPGA fabric in order to make small updates to the matching rules. ASIC designs, on the other hand, are resilient to updates for newly discovered patterns. In contrast, our low-cost FPGA-based solution carries out pattern matching at high speed and also allows changes to the set of stored patterns without hardware reconfiguration. We first apply an off-line optimization method to find sub-pattern similarities across the known malicious patterns and then compress these patterns into bit vectors for efficient storage into on-chip memory. By doing so, the required matching circuitry results in very substantial area savings. The bit vectors for run-time updates could be generated quite easily by a system administrator using a simple C program. A run-time addition to the rule set involves the storing of the created bit vectors into the FPGA memory. Compared to earlier approaches, not only is our strategy more efficient while supporting runtime updates, but it also results in chip-area savings.


Presentation Title: Advanced collector for airborne bioagents

Taewon Han, Environmental Sciences, Rutgers University;
Hey-Reoun An, Environmental Sciences, Rutgers University;
Gediminas Mainelis, Environmental Sciences, Rutgers University

Presence of airborne bioagents, including presence of airborne biowarfare agents, is determined by pulling air through a collector, depositing airborne particles onto/into collection substrate and analyzing the substrate for presence of particles of interest. The performance of any collector is defined by its collection efficiency (fraction of airborne particles deposited in the collection substrate) and its concentration rate. The currently available samplers feature concentration rates is approximately ~104-105/min. In this research we designed and tested a radically new and advanced bioagent collector featuring the concentration rate of > 106-107/min. In this sampler the airborne bioagents are electrostatically deposited on a narrow electrode covered with a superhydrophobic material from which they are removed by a tiny (5-40 ÁL) rolling water droplet. The liquid containing particles can then be analyzed by a variety of techniques including microscopy, Polymerase Chain Reaction (PCR) and similar techniques. Our tests with Bacillus anthracis simulants and droplets as small as 5ÁL revealed that the sampler achieved concentration rate of 1.3x106/min ? much higher than existing samplers. The sampler was shown to be able to sustain the efficient collection over prolonged periods of time and was compatible with PCR. The new technology offers an advantage of faster detection of low airborne bioagent concentrations.


Presentation Title: Computational modeling for supporting emergency event response: Population exposures to anthrax

S.S. Isukapalli, Environmental and Occupational Health Sciences Institute (EOHSI), Rutgers University;
P.J. Lioy, Environmental and Occupational Health Sciences Institute (EOHSI), Rutgers University;
P.G. Georgopoulos, Environmental and Occupational Health Sciences Institute (EOHSI), Rutgers University

This study presents a modular modeling system for performing source-to-dose-to-effect analysis of inhalation anthrax infections from airborne releases of anthrax spores. This is based on the modeling environment for total risk studies (MENTOR). The system, MENTOR-2E (MENTOR for Emergency Events), provides mechanistically consistent analysis of inhalation exposures for various release scenarios, while allowing consideration of specific susceptible subpopulations (such as the elderly) at the resolution of individual census tracts. MENTOR-2E includes atmospheric dispersion modeling, statistically representative samples of individuals along with corresponding activity patterns, and population-based dosimetry modeling that accounts for activity and physiological variability. Two hypothetical release scenarios were simulated: a 100 g release of weaponized B. anthracis over a period of (a) one hour and (b) 10 hours, and the impact of these releases on population in the State of New Jersey was studied. Results were compared with those from simplified modeling of population dynamics (location, activities, etc.), and atmospheric dispersion of anthrax spores. The comparisons showed that in the two release scenarios simulated, each major approximation resulted in an overestimation of the number of probable infections by a factor of 5 to 10; these overestimations can have significant public health implications when preparing for and responding effectively to an actual release. This is in addition to uncertainties in dose-response modeling, which result in an additional factor of 5 to 10 variation in estimated casualties. TheMENTOR-2E system has been developed in a modular fashion so that improvements in individual modules can be readily made without impacting the other modules, and provides a first step toward the development of models that can be used in supporting real-time decision making.


Poster Title: Research and education directions in Homeland Security: NJIT's MS in Critical Infrastructure Systems

Fadi A. Karaa, Critical Infrastructure, NJIT

One of the key objectives of homeland security is to meet the challenges of the National Infrastructure Protection Plan (NIPP). The requirements of this new "all-hazards" approach create levels of complexity never seen in history. Such a multi-dimensional complexity stems from a number of factors, including the integration of various technical performance models of the combined built and natural environments, as well as the development of programmatic, organizational and resource preparedness and response strategies for never-before experienced scenarios. Such a new set of priorities poses educational and research challenges that require significant joint effort across academic disciplines and institutions in order to influence the state of the art and the practice, and train new generations of researchers and professionals in industry and federal, state, and local government. One such initiative that aims to contribute in meeting the challenges of these modern times is NJIT's Graduate Program in Critical Infrastructure Systems. Its multi-disciplinary structure, and its applicability to a wide range of professions engaged in critical infrastructure and homeland security are described in this presentation. Also presented are some of its key research programs across functional and disciplinary boundaries, including large-scale flood response modeling, supply chain security management and water and wastewater infrastructure management.


Presentation Title: University Center for Disaster Preparedness and Emergency Response

Cliff Lacy, UMDNJ

A joint initiative of: UMDNJ-Robert Wood Johnson Medical School, Rutgers, the State University of New Jersey, and Robert Wood Johnson University Hospital with Clifton R. Lacy, MD; Judith E. Burgis; Lawrence Garinello, MHA; Jeffrey D. Laskin, PhD; Paul Lioy, PhD; Ali Maher, PhD; Fred S. Roberts, PhD

The mission of UCDPER is to develop and implement initiatives to protect: the lives, health, and well-being of the general public, vulnerable populations, and the workforce, and also the societal, economic, and physical infrastructure of New Jersey and the nation, through research, education, community outreach, and clinical advances in preparedness and response to all-hazards emergencies, disasters, and terrorism. UCDPER brings multidisciplinary expertise in medicine and health care, pharmacology and drug development, environmental and exposure science, mathematics and computational science, engineering and transportation science, communications, and social/behavioral science to help prepare the nation for natural disasters, accidental emergencies, and/or terrorist attacks.

UCDPER builds upon the assets of the three partner institutions in a unique collaboration which includes recognized strengths in disaster medicine, exposure science, and the mathematics and computer science of massive information analysis. UCDPER brings together highly successful interdisciplinary activities such as the Level 1 Trauma Center at RWJUH/UMDNJ-RWJMS, the EPA Center on Exposure and Risk Modeling at UMDNJ-RWJMS, the NIH CounterACT Center at UMDNJ/Rutgers, the Center for Advanced Infrastructure and Transportation at Rutgers, the DHS University Center of Excellence in Dynamic Data Analysis at Rutgers, and the International Center for Terror Medicine at RWJUH.

The presentation highlights selected ongoing and developing initiatives of UCDPER.


Presentation Title: From face/iris recognition to image search, video retrieval, video surveillance and ATR

Chengjun Liu, Computer Science, New Jersey Institute of Technology

NJIT achieved the best face recognition performance on the most challenging Face Recognition Grand Challenge (FRGC) experiment at the 3rd FRGC Workshop. As face recognition is one of the key technologies in homeland security, this talk will first focus on our recent face and iris detection and recognition technologies and their performance. Image search and video retrieval are important to homeland security as well. We all know that Google celebrated its 10th birthday in October and YouTube was purchased at multiple billion dollars last year. But Google is limited to text search, and YouTube is just a video sharing website, so neither is able to do image search or video retrieval. Our recent work extends our Face Detection and Recognition technologies into image search and video retrieval. Finally, Video Surveillance and Automatic Target Detection and Recognition (ATR) also play a very important role in homeland security. Even though video cameras are installed everywhere, automatic monitoring of the surveillance video for real-time security is still waiting for a robust solution. We plan to further extend our Face Detection and Recognition technologies into Video Surveillance and ATR for both military applications and homeland security.

The Face Recognition and Video Processing Lab at NJIT focuses on Face and Iris Detection and Recognition, and Video Processing. Our work is published in the premier journals in our field, and is well cited. For example, SCOPUS shows that some of our recent journal papers receive more than 800 citations. For more details, please visit our lab webpage at http://www.cs.njit.edu/liu/FRVPlab/index.html.


Presentation Title: Development and deployment of the miniature integrated nuclear detection system

Lewis Meixler, Plasma Physics Laboratory, Princeton University

Pre 9/11, PPPL had developed specialized monitoring techniques for in-situ, real-time, ambient temperature, identification of various radionuclides present in the first wall and collateral structures of the Tokamak Fusion Test Reactor (TFTR). Resident radionuclides, which were the result of operating the reactor with a Deuterium - Tritium (D-T) fuel mix, mostly consisted of the radionuclides H-3 (remnants of reactor fuel), Co-60, Mn-54, Co-57, and other trace elements (from neutron activation). The purpose of the measurements was to map the distribution of the various radionuclides within the confines of the reactor vessel. Post 9/11, it became evident that the technology developed for identifying weaker energy radionuclides mixed with more energetic radionuclides entrained within the TFTR vacuum vessel, could have applications in the Homeland Security arena. The result was the development of the Miniature Integrated Nuclear Detection System (MINDS) which was engineered for the rapid detection of radiological dispersion devices (RDD's) commonly known as dirty bombs. The MINDS was designed to be easily deployed, robust, provide a high degree of accuracy, and differentiate medical and low hazard radionuclide signatures from those which could be used in RDD's. The talk will discuss the development of the technology, methodology employed, current deployment venues, and detection challenges.


Presentation Title: Dynamically enhanced command information delivery

Allen E. Milewski, Rapid Response Institute and Department of Software Engineering, Monmouth University;
Robert M. Kelly, Rapid Response Institute and Department of Software Engineering, Monmouth University

We describe the prototype DECIDE (Dynamically Enhanced Command Information Delivery) System, an information visualization system for emergency managers. The goals of the DECIDE project include conveying of incident information to emergency managers, increasing decision efficiency and accuracy, and improving training exercises.


Poster Title: Airborne engineered nanoparticles: Practical application and implications for health and the environment

Yevgen Nazarenko, Environmental Sciences, Rutgers University;
Gediminas Mainelis, Environmental Sciences, Rutgers University

Toxicity of airborne nanoparticles that is exhibited already in the airborne phase has been explored in this project for the first time. Airborne phase interaction of manufactured nanoparticles with microorganisms such as Pseudomonas fluorescens and Bacillus subtilis and effects of certain nanoparticles on microorganism physiology and viability are being investigated in my ongoing pilot project. The obtained results indicate in-air toxicity of certain airborne manmade nanoparticles including silver, synthesized in different ways, nano iron oxide, carbon including fullerenes and nanotubes. The discovered toxicity opens a new potential application for certain types of nanoparticles in the aerosol state leading to their possible use as inactivation and neutralization agents for biothreat microorganisms, including quantitative measurement of viability changes and structural cell changes after nanoparticle exposure to nanoparticles in the airborne state.


Presentation Title: Development of a transportation model for planning evacuations in Northern New Jersey

Kaan Ozbay, Civil and Environmental Engineering, Rutgers University;
Jon A. Carnegie, Alan M. Voorhees Transportation Center, Rutgers University;
Mustafa Anil Yazici, Civil and Environmental Engineering, Rutgers University;
Eren Erman Ozguven, Civil and Environmental Engineering, Rutgers University;
Bekir Bartin, Civil and Environmental Engineering, Rutgers University;
Jian Li, Civil and Environmental Engineering, Rutgers University

In this paper, we will briefly describe the modeling efforts for the development of evacuation plans in Northern New Jersey. The evacuation modeling and analysis task identifies the types of traffic movements associated with an evacuation that are related with the development of clearance times, and evacuation routes. The problem can be stated as follows [1], [2]:

Given:

* Transportation network with link capacities (vehicles per hour),
* Number of people to be evacuated and their locations,
* Evacuation destinations.

Output:

* Routes to be taken and scheduling of people on each route,
* Traffic volumes and critical roadway segments,
* Shelter demand and capacity consideration.

Objective:

* Minimize total time needed for evacuation,
* Minimize computational overhead.

In this context, the objectives of this study are to:

1. Define and develop the evacuation road network,
2. Develop realistic evacuation scenarios including evacuation demand matrices based on stated preference surveys,
3. Use the developed road network along with the realistic evacuation scenarios and corresponding demand matrices to estimate the clearance times (the time it takes to clear the roadways within the evacuation region for all evacuating vehicles),
4. Based on the estimates of developed evacuation model, examine general traffic control issues that could affect traffic flow along critical roadway segments.

In this project, several selected scenarios proposed by the project team for Northern New Jersey were modeled and analyzed. For all the scenarios, NJRTM-E model, which uses CUBE, Fortran and TP+ software, developed for the NJTPA region is employed (See [3], [4] for details). An important aspect of this study is to make maximum use of regional planning models to take advantage of time and financial investment made in these models. Existing planning models such as NJRTM-E have many desirable characteristics and strengths that make them excellent platforms to be modified for accommodating the special needs of evacuation planning. One of these modifications is the development of realistic demand matrices under evacuation conditions. Since the work on the stated-preference surveys that will be used to develop realistic evacuation demand matrices is still going on, the research team carried out a sensitivity analysis of demand for different demand levels (e.g. single and double demand) and operational aspects (e.g. different road block schemes). The demand levels and the road blocking during evacuation were found to affect the clearance and average travel times during evacuation. The other important modification is the addition of time dimension to the existing model, which will be addressed in the second year of this project.

Based on the preliminary findings of this study, more detailed analysis of road blocking schemes and contraflow operations for some selected roadways are going to be carried out. As future tasks, besides the analysis of additional scenarios, use of dynamic assignment technique that can add the time-dimension is proposed for smaller networks. This kind of dynamic approach will be reliable only with the help of behavioral data, which will be obtained from the resident survey prepared and customized by the research team according to the needs of the proposed tasks.

REFERENCES

1. Shekhar S., "Evacuation Route Planning: Scalable Approaches", Presentation at ITS Minnesota, March 2006.
2. Apalachee Bay Hurricane Evacuation Study Technical Report, Federal Emergency Management Agency & U.S. Army Corps of Engineers, March 1997.
3. North Jersey Regional Transportation Model- Transportation Modeling Overview, North Jersey Transportation Planning Authority Training Sessions Volume 1, Newark, New Jersey, May 19, 2008.
4. North Jersey Regional Transportation Model- Enhanced Overview for Experienced Modelers, North Jersey Transportation Planning Authority Training Sessions Volume 2, Newark, New Jersey, May 19, 2008.


Panel Title: UMDNJ Regional Biocontainment Laboratory

David Perlin, Public Health Research Institute, UMDNJ

The new UMDNJ Regional Biocontainment Laboratory (RBL) on the campus of New Jersey Medical School (NJMS) in Newark is a highly specialized biosafety level 3 (BSL3) research facility, which is intended to advance the goals of the national biodefense research agenda by addressing basic biology, pathogenicity and host response, and promoting the development of new vaccines, therapeutics and diagnostics. The 35,000 GSF RBL is one of 13 regional and national centers across the U.S. funded by NIH-NIAID. The RBL will support the research objectives of scientists at NJMS, the greater UMDNJ campuses, and the Northeast Biodefense Center (NBC), as part of the NIH region II, regional center of excellence in biodefense and emerging infectious diseases (RCE-BEID). It provides state-of-the-art facilities and technical support for laboratory and animal-based investigations of BSL3 pathogens including category A-C select agents (e.g. Yersinia pestis, Bacillus anthracis, Burkholderia mallei, Francisella tularensis, H5N1-flu, XDR-TB, West Nile Virus, etc.). The RBL greatly expands the existing BSL3 laboratory and animal support infrastructure in-place at New Jersey Medical School. The RBL also provides a public health benefit by making expertise and laboratory capacity available to public health authorities in the event of an infectious disease outbreak to address the need for laboratory surge capacity. Finally, the RBL will provide an outstanding environment for the training of scientists and support staff in a rapidly expanding discipline of science.


Panel Title: Optimal learning and change detection for Homeland Security

Warren Powell, Princeton University;
Savas Dayanik, Princeton University

Homeland security often poses problems where we have to determine what information to collect, when collecting information is time consuming and/or expensive. One setting arises where we are observing information (indicators of disease outbreaks or radiation) where we have to decide whether to continue observing, or to stop and draw a conclusion that a change is due to a benign or aggressive source. In other settings, we have to collect information from the field, whether it be testing new technologies or procedures, observing websites or communication channels, or actually measuring the presence of radiation in the atmosphere or disease in the population. We have developed new methods for determining how to collect information in the most efficient way using a concept called the knowledge gradient. We will review rur adaptation of this idea to problems arising in homeland security.


Panel Title: The Rapid Response Institute - Four years later

Barbara T. Reagor, Monmouth University;
William M. Tepfenhart, Monmouth University

The Rapid Response Institute (RRI) was established in 2004 to leverage Monmouth University's ABET-accredited software engineering expertise to enable early and rapid detection of and responses to chemical or biological terrorist attacks, specifically by focusing on the manipulation of relevant data bases. Through awarded Congressional and Senate Appropriations, Monmouth University has been able to establish its reputation and expertise as a formidable Software Engineering Research Institute. Currently 100 % of the awards are used to support the institute administration, program management, visiting researchers, MU Professors' Research during the school year and the summers, and both undergraduate and graduate student research programs. A review of the current research programs and awards will be presented.


Poster Title: Communicating decisions when there is no one to talk to

Barbara T. Reagor, Rapid Response Institute, Monmouth University;
James Hammill, Rapid Response Institute, Monmouth University

Hurricane Katrina lead to the collapse of communications networks and critical infrastructure that left calls for help from the citizens in New Orleans unheard, and emergency response efforts in turmoil and crippled. Rescue teams were prepared to respond, but quickly faced the reality that the destruction of the critical infrastructure obviated their ability to communicate over normal modes, not only in the affected area, but across the country. The inability to communicate decisions was the same as having no decisions at all.

Even when critical infrastructure is intact and working, the release of a biological or chemical agent sufficient enough to cause incapacitation or death of a large population can lead to the same command decision failure experienced with Katrina. The human intervention needed to monitor critical systems and respond to prevent catastrophic cascading events depends on the ability to share knowledge and obtain a common operating picture.

We are presenting the above poster at 2008 CBD S&T Conference in November. I would love to share it with the consortium on Dec. 5th as well. Our poster is 8 feet wide and 4 feet high.


Presentation Title: Real time monitoring of weather conditions for Homeland Security purposes

David A. Robinson, Office of the New Jersey State Climatologist, Rutgers University

The New Jersey Weather and Climate Network (NJWxNet) is a comprehensive information resource for NJ weather monitoring, weather forecasting and weather/climate-related decision making. It is a unique "network of networks", arguably the densest mesonet in the nation in the most densely populated state. Data are gathered each hour from over 150 stations, including approximately 40 operated by the Office of the New Jersey State Climatologist (ONJSC), along with more than 100 stations maintained by the South Jersey Resource Conservation and Development Council, the National Weather Service, the U.S. Geological Survey, the US Forest Service, the NJ Department of Transportation, and others. At the ONJSC, raw data are processed into a common database, with data and derived products made available in colorful maps, graphs and tables via the NJWxNet web site (http://climate.rutgers.edu/njwxnet) within minutes of the observation. Network particulars will be discussed along with examples of how data and products are being or could be used by Homeland security and emergency management entities. Lessons learned and future plans will also be addressed.


Panel Title: DHS Center for Secure and Resilient Maritime Commerce

Hady Salloum, Stevens Institute of Technology

The National Center for Secure and Resilient Maritime Commerce (CSR) brings together a unique set of academic institutions and public and private sector partners with diverse expertise and significant experience in developing new knowledge, models, tools, policies and procedures, and education/training methodologies related to global maritime security and coastal safety. The Center partners have expertise in national Marine Transportation System (MTS) policy, ocean engineering, maritime security, marine sciences, satellite and radar remote sensing, marine transportation and logistics, systems engineering, oceanography, computer science, naval architecture, physics, sociology, psychology, US and international law, and economics. The partners have worked together in numerous US and international projects related to the safe, secure and environmentally responsible transit of cargo and passengers via the MTS, as well as the short and long-term impacts of coastal hazards on socio-economic systems, ecosystems and living marine resources. These partnerships, resources and capabilities will be applied to the Center's goals of:

1. Improving port security and the security of coastal and offshore (Exclusive Economic Zone or EEZ) operations and leveraging security investments to also improve economic performance;
2. Improving emergency response to events in the maritime domain; and
3. Improving the resiliency of the MTS, offshore operations, and our nation's coastal environments.

The technologies, systems, and procedures that will emerge from CSR will be transformational. For example, sensors, models and systems under development by the partners for coastal environment observing and forecasting can be converted into a dual-use network that provides Maritime Domain Awareness in the coastal and maritime approaches of the entire Exclusive Economic Zone and extending to the high seas. These and other opportunities for leveraging existing investments to achieve both security and economic transformational progress for the nation and for its maritime businesses will be pursued. CSR will function as a resource for DHS in all areas of maritime security and coastal safety, drawing on the expertise of more than 100 PhD-level professionals, with the geographical and technical diversity that is required in a leading-edge, fast-responding technical asset to DHS and the nation.


Poster Title: Multi-objective optimization of a Port-of-Entry Inspection policy

Christina Schroepfer Young, Rutgers University;
Yada Zhu, Rutgers University;
Li Mingyu, Rutgers University;
Elsayed Elsayed, Rutgers University;
Tsvetan Asamov, Rutgers University

At the port-of-entry containers are inspected through a specific sequence of sensor stations to detect the presence of nuclear materials, biological and chemical agents, and other illegal cargo. The inspection policy, which includes the sequence in which sensors are applied and the threshold levels used at the inspection stations, affects the probability of misclassifying a container as well as the cost and time spent in inspection. In this paper we consider a system operating with a Boolean decision function combining station results and present a multi-objective optimization approach to determine the optimal sensor arrangement and threshold levels while considering cost and time. The total cost includes cost incurred by misclassification errors and the total expected cost of inspection, while the time represents the total expected time a container spends in the inspection system. Examples which apply the approach in various systems are presented.


Poster Title: Port-of-Entry Inspection policies: Incorporation of measurement error

Christina Schroepfer Young, Rutgers University;
Yada Zhu, Rutgers University;
Li Mingyu, Rutgers University;
Elsayed Elsayed, Rutgers University;
Tsvetan Asamov, Rutgers University

Formulating a model of the inspection of containers arriving to a port-of-entry allows for optimization of the process to attain optimal performance in terms of misclassification errors and other measures. The effect of potential changes can also be determined, and the performance of various inspection policies can be compared. In modeling the inspection process we include an error term that accounts for measurement error contributed by the sensor, in addition to the natural variation of readings from containers. When a simple pass/fail threshold is used, containers with readings close to the threshold value are at risk for misclassification. A second inspection of all containers would reduce the impact of the measurement errors on misclassification but would be inefficient and unnecessary. However, applying a repeat inspection to a selection of containers which are at higher risk of misclassification could be a practical option. We propose such a process of selecting containers for re-inspection by applying a band around a given threshold value T, similar to the concept of a guard band in manufacturing. The optimization of an inspection policy involving such a re-inspection process would include both T and the re-inspection bandwidth. In this paper three inspection policies are proposed, two of which involve repeated inspection of selected containers. The optimization of each of the policies is carried out under various conditions and their performances are compared.


Presentation Title: EmAuth: A framework for cross-organizational vouching

Qian Yang, Computer Science, Rutgers University;
Danfeng Yao, Computer Science, Rutgers University

Pervasive computing allows data to be collected using sensors and mobile devices. Recent studies show that in emergency and crisis situations conventional access control mechanisms are too rigid for crossorganizational information sharing. There is an increasing need to secure the information collected from the pervasive computing environments, and yet to be able to allow flexible data sharing to facilitate problemsolving and decisionmaking.

Our work investigates the two seemingly contradictory factors, secure access and flexible adaptation, and designs an decentralized authorization model for emergency and crisis situations. We describe an emergency authorization system called EmAuth where a lightweight cryptographic vouching scheme is used to provide the assured crossdomain access. EmAuth is a general framework that supports expressive policy requirements and specifications. We demonstrate its use in encoding organizational role hierarchy for the authorization purpose in a privacypreserving fashion.


Presentation Title: Surface enhanced raman spectroscopic detection of explosives

Anna Zarow, Chemistry and Environmental Science, New Jersey Institute of Technology;
Frank J. Owens, Chemistry and Environmental Science, New Jersey Institute of Technology;
Zafar Iqbal, Chemistry and Environmental Science, New Jersey Institute of Technology

Periodic arrays of gold-coated, inverted square pyramidal cavities etched on a silicon wafer were used to induce surface-enhanced Raman scattering (SERS) to detect trace amounts of the aromatic organic energetic molecules, 2,4,6 trinitrotoluene (TNT), non-aromatic organic explosives, 1,3,5-trinitroperhydro-1,3,5-triazine (known as RDX), and 1,3,5,7-tetranitro-1,3,5,7-tetrazocane (known as HMX), and the largely ionic inorganic energetic compound, ammonium nitrate (NH4NO3). Extremely reproducible enhanced Raman spectra on the SERS-active regions were obtained using 632.8 nm and 785 nm laser excitation at high sensitivity levels for TNT of 23 parts per million (ppm). Lower sensitivity levels than TNT are observed for ionic NH4NO3 at 2.5 parts per million, and non-aromatic RDX and HMX at 12.7 parts per million. Results for stand-off SERS detection currently at three feet using a fiber-optic Raman system will also be discussed. The mechanism of SERS induced on these substrates by the strong interaction of trapped surface plasmons within the void architecture of the cavities with incident visible and near-infrared laser radiation, will also be briefly discussed.


Document last modified on December 4, 2008.