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ARMY

 

PROPOSAL SUBMITTAL

  

The United States Army Research Office (ARO), reporting to the Army Research Laboratory (ARL) manages the Army’s Small Business Technology Transfer (STTR) Program. The following pages list topics that have been approved for the fiscal year 2007 STTR program. Proposals addressing these areas will be accepted for consideration if they are received no later than the closing date and hour of this solicitation.

 

The Army anticipates funding sufficient to award one or two STTR Phase I contracts to small businesses with their partner research institutions in each topic area. Awards will be made on the basis of technical evaluations using the criteria contained in the solicitation, within the bounds of STTR funds available to the Army. If no proposals within a given area merit support relative to those in other areas, the Army will not award any contracts for that topic. Phase I contracts are limited to a maximum of $100,000 over a period not to exceed six months.

 

Please Note!

 

The Army requires that your entire proposal (consisting of Proposal Cover Sheets, the full Technical Proposal, Cost Proposal-using the template provided and Company Commercialization Report) must be submitted electronically through the DoD-wide SBIR/STTR Proposal Submission Website (/submission). A hardcopy is NOT required.  Hand or electronic signature on the proposal is also NOT required.

 

The DoD-wide SBIR/STTR Proposal Submission system (available at /submission) will lead you through the preparation and submission of your proposal. Refer to section 3.0 at the front of this solicitation for detailed instructions on Phase I proposal format. You must include a Company Commercialization Report as part of each proposal you submit; however, it does not count against the proposal page limit. If you have not updated your commercialization information in the past year, or need to review a copy of your report, visit the DoD SBIR/STTR Proposal Submission site. Please note that improper handling of the Commercialization Report may result in the proposal being substantially delayed and that information provided may have a direct impact on the review of the proposal. Refer to section 3.5d at the front of this solicitation for detailed instructions on the Company Commercialization Report.

 

If you collaborate with a university, please highlight the research that they are doing and verify that the work is FUNDAMENTAL RESEARCH.

Be reminded that if your proposal is selected for award, the technical abstract and discussion of anticipated benefits will be publicly released on the Internet therefore, do not include proprietary or classified information in these sections. DoD will not accept classified proposals for the STTR Program. Note also that the DoD web site contains timely information on firm, award, and abstract data for all DoD SBIR/STTR Phase I and II awards going back several years. This information can be viewed on the DoD SBIR/STTR Awards Search website at /awards.

Based upon progress achieved under a Phase I contract, utilizing the criteria in Section 4.3, a firm may be invited to submit a Phase II proposal (with the exception of Fast Track Phase II proposals – see Section 4.5 of this solicitation). Phase II proposals should be structured as follows: the first 10-12 months (base effort) should be approximately $375,000; the second 10-12 months of funding should also be approximately $375,000. The entire Phase II effort should generally not exceed $750,000. Contract structure for the Phase II contract is at the discretion of the Army’s Contracting Officer after negotiations with the small business.

The Army does not issue interim or option funding between STTR phase I and II efforts, but will provide accelerated phase II proposal evaluation and contracting for projects that qualify for fast-track status.

Army STTR Contracts may be fully funded or funded using options or incremental funding.

CONTRACTOR MANPOWER REPORTING (CMR) (Note: Applicable only to U.S. Army issued STTR contracts)

 

Accounting for Contract Services, otherwise known as Contractor Manpower Reporting (CMR), is a Department of Defense Business Initiative Council (BIC) sponsored program to obtain better visibility of the contractor service workforce.  This reporting requirement applies to all STTR contracts issued by an Army Contracting Office.

 

Offerors are instructed to include an estimate for the cost of complying with CMR as part of the cost proposal for Phase I ($100,000 max) and Phase II ($750,000 max), under “CMR Compliance” in Other Direct Costs. This is an estimated total cost (if any) that would be incurred to comply with the CMR requirement. Only proposals that receive an award will be required to deliver CMR reporting, i.e. if the proposal is selected and an award is made, the contract will include a deliverable for CMR.

 

To date, there has been a wide range of estimated costs for CMR.  While most final negotiated costs have been minimal, there appears to be some higher cost estimates that can often be attributed to misunderstanding the requirement.  The STTR program desires for the Government to pay a fair and reasonable price.  This technical analysis is intended to help determine this fair and reasonable price for CMR as it applies to STTR contracts.

 

       The Office of the Assistant Secretary of the Army (Manpower & Reserve Affairs) operates and maintains the secure CMR System. The CMR website is located here: https://contractormanpower.army.pentagon.mil/.

 

       The CMR requirement consists of the following 13 items, which are located within the contract document, the contractor's existing cost accounting system (i.e. estimated direct labor hours, estimated direct labor dollars), or obtained from the contracting officer representative:

(1) Contracting Office, Contracting Officer, Contracting Officer's Technical Representative;

(2) Contract number, including task and delivery order number;

(3) Beginning and ending dates covered by reporting period;

(4) Contractor name, address, phone number, e-mail address, identity of contractor employee entering data;

(5) Estimated direct labor hours (including sub-contractors);

(6) Estimated direct labor dollars paid this reporting period (including sub-contractors);

(7) Total payments (including sub-contractors);

(8) Predominant Federal Service Code (FSC) reflecting services provided by contractor (and separate predominant FSC for each sub-contractor if different);

(9) Estimated data collection cost;

(10) Organizational title associated with the Unit Identification Code (UIC) for the Army Requiring Activity (The Army Requiring Activity is responsible for providing the contractor with its UIC for the purposes of reporting this information);

(11) Locations where contractor and sub-contractors perform the work (specified by zip code in the United States and nearest city, country, when in an overseas location, using standardized nomenclature provided on website);

(12) Presence of deployment or contingency contract language; and

(13) Number of contractor and sub-contractor employees deployed in theater this reporting period (by country).

 

       The reporting period will be the period of performance not to exceed 12 months ending September 30 of each government fiscal year and must be reported by 31 October of each calendar year.

 

       According to the required CMR contract language, the contractor may use a direct XML data transfer to the Contractor Manpower Reporting System database server or fill in the fields on the Government website.  The CMR website also has a no-cost CMR XML Converter Tool.

 

       The CMR FAQ explains that a fair and reasonable price for CMR should not exceed 20 hours per contractor.  Please note that this charge is PER CONTRACTOR not PER CONTRACT, for an optional one time set up of the XML schema to upload the data to the server from the contractor's payroll systems automatically.  This is not a required technical approach for compliance with this requirement, nor is it likely the most economical for small businesses.  If this is the chosen approach, the CMR FAQ goes on to explain that this is a ONE TIME CHARGE, and there should be no direct charge for recurring reporting.  This would exclude charging for any future Government contract or to charge against the current STTR contract if the one time set up of XML was previously funded in a prior Government contract. 

 

       Given the small size of our STTR contracts and companies, it is our opinion that the modification of contractor payroll systems for automatic XML data transfer is not in the best interest of the Government.  CMR is an annual reporting requirement that can be achieved through multiple means to include manual entry, MS Excel spreadsheet development, or use of the free Government XML converter tool.  The annual reporting should take less than a few hours annually by an administrative level employee.  Depending on labor rates, we would expect the total annual cost for STTR companies to not exceed $500 annually, or to be included in overhead rates. 

Army STTR 07 Topic Index

A07-T001 Long life, low power, multicell battery

A07-T002 Software Anti-Tamper for Matrix based Algorithms

A07-T003 Modular and Authorable Intelligent Tutoring System for Immersive Scenario-Based Training

A07-T004 DRIVING WISDOM: Web-based Training for Young Adults to Improve Operator Judgments that Mitigate Crash Risk in Privately Owned Vehicles

A07-T005 Interband Resonant-Tunneling-Diode (I-RTD) Hybrid Terahertz Oscillator

A07-T006 Nanostructures for dislocation blocking in infrared detectors

A07-T007 Efficient and Robust Algorithms for Real-time Video Tracking of Multiple Moving Targets

A07-T008 Algorithms for Image Content Indexing and Information Retrieval from Unstructured or Semi-structured Complex Database

A07-T009 Frequency-agile monolithic Ka-band filter

A07-T010 Development of Amorphous Alloy Surface Coatings as Replacement for Chromate Technology

A07-T011 A Compact Membrane-Reactor Methanol Reformer

A07-T012 Molecular Shape Detection for Chemical Analysis

A07-T013 Dynamic Data-Driven Prognostics and Condition Monitoring of On-board Electronics

A07-T014 Discontinuous Element Software for Computing 2D and 3D Failure of Materials under Ballistic Impact

A07-T015 Portable Fully-Automated Soil Property Measurement Probe

A07-T016 Synthesis and Scaleup of Fuel-Cell Compatible Alkaline Electrolyte Membranes

A07-T017 Ultrasound Assisted Oxidative Desulfurization of JP-8 Fuel

A07-T018 High efficiency deep green light emitting diode

A07-T019 Super-resolution adaptive laser beam projection system

A07-T020 Fiber nonlinearity based entangled-photon sources

A07-T021 Low Data Rate Frequency-Shifted Reference Ultra-Wideband (UWB) Communication Systems

A07-T022 Diluted-Magnetic Semiconductor (DMS) Tunneling Devices for the Terahertz Regime

A07-T023 Modular Protein Manufacturing Platform

A07-T024 Aerosolization of Densified Powders Using Sublimable Solids

A07-T025 Passive Detection and Prediction of Degradation in Critical Utility Pipeline Infrastructure

A07-T026 Statistical Mobility Prediction for Small Unmanned Ground Vehicles

A07-T027 Terrain Analysis from Unmanned Ground Vehicle Sensors

A07-T028 Reduced-Order High-Fidelity Models for Signature Propagation

A07-T029 Development of an Advanced Comfortable Prosthetic Socket

A07-T030 Chromatophore-Based Toxicity Sensor for Water

A07-T031 Development of Virtual Reality Tools for Training and Rehabilitation of Patient Using Advanced Prosthesis

A07-T032 Improved Lightweight Surgical Instrument and Linen Field Sterilization via Chlorine Dioxide or Alternative Methodology

A07-T033 Novel Topical Arthropod Repellent Formulation(s) with Superior Efficacy and High User Acceptability

A07-T034 High-Throughput Screening of Natural Product Extracts for Biologically Active Small Molecules

A07-T035 Multi-Analyte, Wearable Chemical Nanosensor for Warfighter Physiological Status Monitor (WPSM)

A07-T036 Innovative Lightweight Energy and Water Efficient Treatment System for Fluid Medical Waste in an Austere Deployed Environment

A07-T037 Retinal Oximeter for Scientific and Clinical Applications

A07-T038 Military Surgical Information System

A07-T039 Real-Time, In Vivo Imaging to Identify Tumor Margins

A07-T040 Standoff Remote Triage Sensor Array for Robotic Casualty Extraction Systems

Army STTR 07 Topic Descriptions

A07-T001 TITLE: Long life, low power, multicell battery

TECHNOLOGY AREAS: Ground/Sea Vehicles, Electronics

The technology within this topic is restricted under the International Traffic in Arms Regulation (ITAR), which controls the export and import of defense-related material and services. Offerors must disclose any proposed use of foreign nationals, their country of origin, and what tasks each would accomplish in the statement of work in accordance with section 3.5.b.(7) of the solicitation.

OBJECTIVE: Develop a low-power miniature (coin cell or similar) battery with a 30-plus year operational lifespan that is suitable for battery-backed static random access memory (SRAM) and environmentally friendly with minimal disposal issues.

DESCRIPTION: This effort will focus on identifying new and innovative multi-cell battery technologies suitable for powering battery-backup, low power static random access memories (SRAM). The new multi-cell battery shall be a low power miniature (coin cell or similar) battery with a 30 plus year operational lifespan. The new battery technology shall not incorporate toxic metals like cadmium, lead, mercury, etc. and minimize the amount of hazardous materials. New battery technology shall not be constructed from energetic materials that may be explosive under certain conditions. New battery shall not use radioactive materials. New battery technology shall not use high temperature thermal battery technologies. The goal is to create an environmentally friendly battery with minimal disposal issues. The new battery technology will be suitable for battery-backed SRAM memories and SRAM memories for bitstream keys inside field programmable gate arrays (FPGA).

Current battery technology has focused on extending the life of the battery. An alternate approach would be to combine multiple cells inside a battery. Each cell is initially in an inert state. After activation, a cell will operate as a traditional low power battery-backup for low power SRAM typically used to store FPGA bitstream keys. A low activation energy of less than 1% of each cell’s capacity is desired. The time to activate the cell should be less than 1 hour.

In concept, when a cell is approaching the end-of-life, another cell is activated, effectively extending the life of the multi-cell battery. In a four cell battery, with 5 years of operational life per cell; a 20 year lifetime is possible. Minimum lifetime for each cell, once activated, under an average 0.25/n mW load, is one month (approximately 0.2/n watt-hours) where n is the number of cells ( n >=1 ) inside the battery. The weighting, for evaluating the technical merits of the new and innovative battery technology, will be battery life (2), nontoxic, non-hazardous materials (1), and disposal (1).

PHASE I: Contractor will analyze and design a novel concept battery cell. The new battery technology shall not incorporate hazardous or toxic materials like cadmium, lead, mercury, etc. New battery technology shall not be constructed from energetic materials that may be explosive under certain conditions. New battery shall not use radioactive materials. New battery technology shall not use high temperature thermal battery technologies. The goal is to create an environmentally friendly battery with minimal disposal issues.

While in an inert state, the battery has a shelf life of 25 plus years at 25 degrees Celsius. Nominal operating temperature range with slightly reduced performance: -10 degrees Celsius to +40 degrees Celsius. Operation over the industrial temperature range of -40 to +85 degrees Celsius with reduced performance is desired. Battery operation with reduced performance over part or all of the full military temperature range of -50 degrees Celsius to +125 degrees Celsius will be considered a plus.

Upon activation, a cell will provide power for a battery-backed SRAM memory for 0.1 (lower limit) to 5 plus years at 25 degrees Celsius. The energy for activation should be less than 10 % of each individual cell’s energy capacity with a goal of less than 1 %. Contractor shall perform an accelerated aging test on the cell to determine the shelf life in the inert, inactivated state and the operational lifespan of the cell for a simulated SRAM battery back-up memory.

The requirement for the new battery is to operate over the industrial temperature range of -40 to +85 degrees Celsius. We are also interested in the potential performance of the battery over the full military temperature range of -50 to +125 degrees C. The contractor shall conduct an accelerated aging test over the industrial temperature range of -40 to +85 C. Operation over a wider temperature range up to the full military temperature range of -50 to +125 C will be considered a plus.

Contractor shall provide a report describing accelerated aging test and battery lifespan for current levels of 0.1 to 10 equivalent loads for a SRAM with at least 256 bit memory capacity.

PHASE II: Contractor shall develop a multi-cell battery based on the technologies from Phase I to create a battery with greater than a 25 year operational lifespan powering a battery backed SRAM at 25 degrees Celsius. Contractor shall have an independent verification and validation (IV&V) to validate the batteries performance over the industrial temperature range of -40 to +85 degrees Celsius and for current levels of 0.1 to 10 equivalent loads for a SRAM with at least 256 bit memory capacity. Operation over a wider temperature range up to the full military temperature range of -50 to +125 C will be considered a plus. Contractor shall provide a report on the IV&V.

PHASE III: Contractor shall team with a prime contractor and commercialize the new battery technology. The contractor is encouraged to team with a defense prime contractor and a traditional commercial corporation to market the technology to both military and commercial end users. Contractor shall provide an IV&V report on accelerated aging tests for a production level battery showing mean battery life as a function of temperature over the industrial temperature range of -40 to +85 degrees Celsius and for current levels of 0.1 to 10 equivalent loads for a SRAM with at least 256 bit memory capacity. Operation over a wider temperature range up to the full military temperature range of -50 to +125 degrees Celsius will be considered a plus. Contractor shall have an independent laboratory test the battery to flight safety requirements of the FAA. Contractor shall provide an independent laboratory report on the battery’s materials and disposal issues. Contractor shall provide a material safety data sheet on battery family.

REFERENCES:

1. N. Weste, and D. Harris: “CMOS VLSI Design: A Circuits and Systems Perspective,” Addison Wesley, 2004. ISBN: 0321149017.

2. R. Kaushik, S. Prasad: “Low Voltage CMOS VLSI Circuit Design,” Wiley, 1999, ISBN: 047111488X.

3. D. Linden and T. Reddy: “Handbook of Batteries,” McGraw-Hill Companies, 2001, ISBN: 0071359788.

4. University of California: “Researchers create first nanofluidic transistor,” /news4815.html.

5. Gillette Company: “Zinc-Air Bulletin,” 2004, /oem/Primary/Zinc /Zinc_Air_Tech_Bulletin.pdf.

6. V. Barsukov and F. Beck: “New Promising Electrochemical Systems for Rechargeable Batteries: Proceedings of the NATO Advanced Research Workshop,” Springer London, Limited, 1996, ISBN: 0792339487.

7. R. Dell, and D. Rand: “Understanding Batteries,” Royal Society of Chemistry, 2001, ISBN: 0854046054.

8. T. Minami, et al.: “Solid State Ionics for Batteries,” Springer-Verlag New York, LLC, 2005, ISBN: 4431249745.

9. N. Nguyen and S. Wereley: “Fundamentals and Applications of Microfluidics, Second Edition,” Artech House, 2006, ISBN: 1580539726.

10. C. Liu: “Foundations of MEMS,” Prentice Hall, 2005, ISBN: 0131472860.

11. N. Maluf and K. Williams: “Introduction to Microelectromechanical Systems Engineering,” Artech House, ISBN: 1580535909.

12. Technology Review: “Higher-Capacity Lithium-Ion Batteries” /read_article.aspx?id=17017&ch=nanotech , June 2006.

13. J. Walko: “Nanobattery technology could eliminate fire risks,” /showArticle.jhtml;jsessionid=TSOLYR5YS2YPMQSNDLRSKH0CJUNN2JVN?articleID=192203405 August 23, 2006.

14. MIT Tech Talk: “Researchers employ virus to build tiny batteries,” Vol. 50, No. 23, April 2006, http://web.mit.edu/newsoffice/2006/techtalk50-23.pdf.

15. D. Teeters, et al.: “Nano-battery systems,” US Patent 6,586,133, July 2003. pto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PALL&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.htm&r=1&f=G&l=50&s1=6586133.PN.&OS=PN/6586133&RS=PN/6586133

16. Brown University: “Brown University engineers create a better battery – with plastic,” /news77371085.html.

KEYWORDS: Electronics, battery, field programmable gate arrays, FPGA, SRAM, micro-electromechanical systems, MEMS, micro-fluidic systems.

A07-T002 TITLE: Software Anti-Tamper for Matrix based Algorithms

TECHNOLOGY AREAS: Information Systems

The technology within this topic is restricted under the International Traffic in Arms Regulation (ITAR), which controls the export and import of defense-related material and services. Offerors must disclose any proposed use of foreign nationals, their country of origin, and what tasks each would accomplish in the statement of work in accordance with section 3.5.b.(7) of the solicitation.

OBJECTIVE: Research objective is to investigate improving software level obfuscation for highly regular matrix based algorithms. A number, of recursive algorithms or adaptive algorithms, consists of an iterative matrix equation W(k+1) = f [W(k)] + other terms where W( ) is a matrix. The highly regular structure makes reverse engineering trivial. Software obfuscation increases the difficulty of reverse engineering software. For matrix equations, there are other options for obfuscation at the algorithm level: similarity transforms, transformations for “sparse” matrix equations, etc. The goal here is to combine iterative matrix equations with clever matrix transformations (possibly time varying transformations) with traditional code obfuscation techniques to improve software anti-tamper for matrix intensive algorithms. Some possible applications for obfuscation at the matrix equation level include: Kalman filtering, least-mean squares (LMS) algorithm, state space control theory, short-term Fourier transform, wavelet signal processing, Gerchberg-Saxton algorithm, and streaming real-time image processing. The contractor is asked to select a matrix intensive algorithm and examine obfuscation at the matrix equation level. Contractor may also select an appropriate function domain(s): time, frequency, time-frequency, space, wavelet, etc.

DESCRIPTION: All U.S. Army Program Executive Offices (PEOs) and Program Managers (PMs) are now charged with executing Army and Department of Defense (DoD) anti-tamper policies in the design and implementation of their systems to afford maximum protection of U.S. technologies, thus providing maximum protection against them being obtained and utilized and/or exploited by foreign adversaries. One area of vulnerability is in the software in a weapons system, where there are many critical technologies that can be compromised. Techniques are now emerging to begin to try to combat this loss of the U.S. technological advantage, but further advances are necessary to provide useful toolsets to the U.S. Army PEOs and PMs for employment in their systems. As AT is a relatively new area of concern, the development of AT techniques is in a somewhat immature state and new ideas are always needed.

The goal of software obfuscation is, through transformations, clever disguise, or restructuring of the program, to make it more difficult to reverse engineer computer software. Army and DoD systems use navigation software where data from several sensors are blended together with a Kalman filter. A Kalman filter is a highly, regular, recursive matrix equation. The structured nature of a Kalman filter makes software obfuscation more difficult. We would like to investigate the possibility of obfuscation at the algorithm level combined with traditional software obfuscation for anti-tamper. The objective section describes some other possible matrix equations for study.

“No technique is invulnerable or even clearly superior to the others in all circumstances; therefore, a mix of protection techniques allows the defense to capitalize on the strengths of each technique while also masking the shortfalls of other techniques.” http://www.stsc.hill.af.mil/crosstalk/2004/11/0411atallah.html.

It should also be noted, that the use of off-the-shelf components in a system can seriously compromise an AT design due to the ready availability of open-source documentation. The effort should therefore focus on denying an adversary access to enough information to begin such a data search. The technologies/techniques developed should inhibit an adversary’s exploitation and/or reverse engineering effort to a point where it will require a significant resource investment to compromise, allowing the U.S. time to advance its own technology or otherwise mitigate the loss. As a result, the U.S. Army can continue to maintain a technological edge in support of its warfighters.

PHASE I: Contractor shall select a recursive or iterative matrix intensive algorithm. Some possible algorithms are presented in the objective section. Contractor shall propose algorithm level obfuscation technique(s) for the selected algorithm. Some potential challenges for obfuscating matrix equations include performance degradation, error propagation, algorithm stability, and convergence issues. Series approximations to matrix and integral equations may lead to difficulties with convergence. A series of obfuscated terms may lead to problems with correctly deciding the appropriate point to truncate series terms. Problems with finite numerical precision may cause convergence and stability problems. Obfuscation of near singular matrices may result in additional convergence and stability problems. Other numerical, convergence issues, and algorithm stability issues may also be present.

Contractor shall propose an algorithm level obfuscation technique(s) for a selected matrix intensive algorithm. Contractor shall provide a report discussing the feasibility of matrix equation level obfuscation and address the limitations imposed by performance degradation, error propagation, approximations, convergence and stability. Contractor shall provide an estimate, based on his past software anti-tamper knowledge and experience, of the level of anti-tamper protection provided by the proposed matrix algorithm obfuscation concepts.

PHASE II: Contractor shall develop the concepts from Phase I into a functional prototype. Contractor shall provide a report discussing numerical, convergence, and stability issues for the matrix algorithm obfuscation. Contractor shall describe conditions where the matrix level obfuscation provides good convergence and stability. Contractor shall also describe conditions where convergence and stability are poor. Contractor shall combine matrix level obfuscation with tradition software obfuscation techniques.

Contractor shall demonstrate matrix algorithm obfuscation and software obfuscation running on an embedded computer with an operating system. Contractor shall have an independent verification and validation (IV&V) performed to test the anti-tamper/anti-reverse engineering provided by the matrix algorithm level obfuscation and traditional software obfuscation. Contractor shall provide a detailed IV&V report of the anti-tamper/anti-reverse engineering provided by the matrix algorithm level obfuscation and software obfuscation. Contractor shall provide a detailed report(s) describing functionality of the anti-tamper tool.

PHASE III: Contractor shall develop a production grade matrix algorithm obfuscation and traditional software obfuscation tool. Contractor is encourage to team with a prime contractor to apply the new obfuscation technology to a current production level system. Contractor is encourage to consider a version of the obfuscation tool for Homeland Security applications.

Contractor shall demonstrate matrix algorithm obfuscation and software obfuscation running on an embedded computer with an operating system. Contractor shall have an independent verification and validation (IV&V) performed to test the anti-tamper/anti-reverse engineering provided by the matrix algorithm obfuscation and traditional software obfuscation. Contractor shall provide a detailed IV&V report of the anti-tamper/anti-reverse engineering provided by the matrix algorithm obfuscation and software obfuscation. Contractor shall provide a detailed report(s) describing functionality of anti-tamper tool.

REFERENCES:

1. P. Zarchan, and H. Musoff: “Fundamentals of Kalman Filtering: A Practical Approach,” American Institute of Aeronautics & Astronautics, March 2005, ISBN: 1563476940.

2. M. Grewal, and A. P. Andrews: “Kalman Filtering: Theory and Practice Using MATLAB,” Wiley, Jan. 2001, ISBN: 0471392545.

3. G. Welch and G. Bishop: “An Introduction to the Kalman Filter,” Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, February 2001, http://terra.cs.nps.navy.mil/Dist/2001/Courses/cd2/courses/51/Papers/kalman_intro.pdf .

4. J. Podesta: “Brief Tutorial on the Kalman Filter,” RDEC, Picatinny, Nov. 1994, http://handle.dtic.mil/100.2/ADA286571.

5. S. Haykin: “Least-Mean-Square Adaptive Filters,” Wiley, September 2003, ISBN: 0471215708.

6. A. D. Poularikas, and Z. M. Ramadan: “Adaptive Filtering Primer with MATLAB,” CRC Press, February 2006, ISBN: 0849370434.

7. S. Qian: “Introduction to Time-Frequency and Wavelet Transforms,” Pearson Education, November 2001, ISBN: 0130303607.

8. D. Hill and B. Kolman: “Modern Matrix Algebra,” Prentice Hall, 2000, ISBN: 0139488529.

9. D. Poole: “Linear Algebra: A Modern Introduction (with CD-ROM),” Brooks/Cole, February 2005, ISBN: 0534998453.

10. M. J. Atallah, E. D. Bryant, and M. R. Stytz, “A Survey of Anti-Tamper Technologies,” Cross Talk, Nov. 2004, http://www.stsc.hill.af.mil/crosstalk/2004/11/0411atallah.html.

11. E. Eilam: “Secrets of Reverse Engineering,” Wiley, April 2005, ISBN: 0764574817.

12. L. M. Willis and P. Newcomb (editors): “Reverse Engineering,” Springer-Verlag, New York, July 1996, ISBN: 079239756.

13. K. A Ingle: “Reverse Engineering,” McGraw-Hill Professional, 1994, ISBN: 0070316937.

14. P. Cerven: “Crackproof Your Software: Protect Your Software Against Crackers,” No Starch Press, 2002, ISBN: 1886411794.

15. B. Friedland: “Control System Design: An Introduction to State-Space Methods,” Dover Publications, March 2005, ISBN: 0486442780.

16. K. Ogata: “Modern Control Engineering,” Prentice Hall Professional Technical Reference, November 2001, ISBN: 0130609072.

17. S. Janardhanan: “Discrete-time Sliding Mode Control,” Springer-Verlag, New York, October 2005, ISBN: 3540281401.

18. “Short term Fourier transform,” /wiki/ Short_Term_Fourier_Transform.

19. J. R. Fienup:  "Phase retrieval algorithms: a comparison,"  Applied Optics, Vol. 21, No. 15, pp. 2758-2769, August 1, 1982. http://www.optics.rochester.edu/workgroups/fienup/PUBLICATIONS/AO82_PRComparison.pdf

20. : “Gerchberg-Saxton Algorithm,” /wiki/ Gerchberg_saxton_algorithm.

21. : “Singular value decomposition,” /wiki/ Singular_value_decomposition.

22. : “Pseudoinverse,” /wiki/Pseudoinverse.

23. T. Maggiano:  "Phase Retrieval Algorithms and their Applications," University of Arizona-Optical Science Center, http://www.u.arizona.edu/~tlmaggia/Fienup.pdf.

KEYWORDS: Information technology devices, software obfuscation, Kalman filter, least-mean-square, LMS, signal processing, image processing, adaptive filter, matrix algebra, linear algebra, state space, anti-tamper, AT, reverse engineering, anti-reverse engineering, ARE, software protection

A07-T003 TITLE: Modular and Authorable Intelligent Tutoring System for Immersive Scenario-Based Training

TECHNOLOGY AREAS: Human Systems

OBJECTIVE: To develop an intelligent tutoring system that could be linked with multiple immersive scenario-based training systems and could be updated by a person without specialized computer experience. The system would monitor trainee performance, provide targeted instructional feedback, and evaluate how well the trainee performed during a training scenario based on training objectives.

DESCRIPTION: Scenario-based training games are currently being used in the Army for a broad range of training domains (e.g., military tactics, support and stability operations, weapons operation, and language training). The research indicates that effectiveness of these training tools is currently mixed (Beal, 2005; Hays, 2005). One reason why training games may not be living up to the hype is that the “instructor” functions of training environments are not regularly included as part of the system (Hays 2005; Belanich, Mullin, Dressel, 2004; Bloom, 1984). One goal of this project is to develop a modular intelligent tutoring system that could be linked to different Army-based training games in order to provide the needed instructor functionality that is currently lacking in many game-based training systems.

For a modular ITS to work appropriately, it would need to exchange data with multiple scenario-based training platforms. The data coming from the training platform would indicate the state of the scenario and provide a low-level depiction of trainee performance. The ITS would use this data to develop a high-level understanding of trainee performance as compared to a model of the training domain. Data going to the training platform would include data to modify the scenario to meet the instructional need of the trainee, which would include instructional feedback.

For scenario-based training systems to be useful to a rapidly evolving military, they need to be easily authorable to keep up with the ever-changing current operating environment. This flexibility needs to be provided to the instructors who implement these types of training systems so they can adequately match the scenario content with the appropriate training objectives (Ainsworth & Fleming, 2006). Therefore, a second goal of this project is to develop an ITS that can be easily authorable by a typical instructor (i.e., person without highly specialized computer skills).

Intelligent tutors are effective training tools, but usually require skilled personnel to develop the system for a particular training platform. An ITS that can be adapted to work with multiple Army-based training platforms and is easily updateable would offer powerful training options to the military that are currently not available. While scenario-based (game-based) training systems have demonstrated limited effectiveness (Hays. 2005), if they are armed with a robust ITS companion to elicit important lessons and training objectives, these training systems may reach their full potential for training today’s Soldiers.

PHASE I: Phase I should determine the feasibility of producing a modular intelligent tutoring system that works with multiple immersive Army scenario-based training systems and covers a range of actions (e.g., speech acts and physical acts). The deliverable for this phase includes a feasibility study with specific recommendations for the system to be developed during the Phase II effort.

PHASE II: In Phase II, the findings of Phase I should be used to develop a working prototype of the system to be assessed by instructors using immersive Army scenario-based training systems. Integration of the ITS with two different scenario-based training platforms would be considered success.

PHASE III: Ownership of a modular intelligent tutor system that can be used by various scenario-based training systems should position the company well for integrating their system into game-based training programs in use by the military, as well as private and public sectors. Because the system is modular, it could be linked with a variety of scenario-based training systems. The system would also find a receptive market in both the training and educational fields, where scenario-based training systems are growing.

REFERENCES:

1. Shaaron Ainsworth & Piers Fleming, Evaluating authoring tools for teachers as instructional designers, Computers in Human Behavior, v. 22, p. 131-148, 2006

2. Scott Beal, Using Games for Training Dismounted Light Infantry Leaders: Emergent Questions and Lessons Learned (ARI Research Report 1841). U.S. Army Research Institute for the Behavioral and Social Sciences: Arlington, VA, September 2005

3. James Belanich, Laura N. Mullin, & J. Douglas Dressel, Symposium on PC-based simulations and gaming for military training (ARI Research Product 2005-01). Alexandria, VA: US Army Research Institute for the Behavioral and Social Sciences, October 2004

4. Benjamin S. Bloom, The 2 sigma problem: the search for methods of group instruction as effective as one-to-one tutoring. Educational Researcher, v. 13, n. 6, p. 4–16, June-July 1984

5. Robert T. Hays, The effectiveness of instructional games: A literature review and discussion. (Tech Report 2005-004). Naval Air Warfare Center Training Systems Division, Orlando, FL, November 2005

KEYWORDS: intelligent tutoring system, scenario, game-based training, simulation, serious games, authoring, instruction

A07-T004 TITLE: DRIVING WISDOM: Web-based Training for Young Adults to Improve Operator Judgments that Mitigate Crash Risk in Privately Owned Vehicles

TECHNOLOGY AREAS: Human Systems

OBJECTIVE: Develop new transformative technologies to improve driver safety. Analyze and develop a knowledge base of driver judgments that balance moderately risky but common hazards with ongoing, transportation requirements; and evaluate web-based, training methods in order to motivate young adults (moderately experienced drivers aged 20 to 35) to learn and apply this information in their daily driving. The tutoring module will tailor instructional feedback to student responses and personal characteristics.



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