Automated Knowledge Generation with Persistent Surveillance Video

The Air Force has increasingly invested in persistent surveillance platforms gathering a large amount of surveillance video. Ordinarily, intelligence analysts watch the video to determine if suspicious activities are occurring. This approach to video analysis can be a very time and manpower intensive process. Instead, this thesis proposes that by using tracks generated from persistent video, we can build a model to detect events for an intelligence analyst. The event that we chose to detect was a suspicious surveillance activity known as a casing event. To test our model we used Global Positioning System (GPS) tracks generated from vehicles driving in an urban area. The results show that over 400 vehicles can be monitored simultaneously in real-time and casing events are detected with high probability (43 of 43 events detected with only 4 false positives). Casing event detections are augmented by determining which buildings are being targeted. In addition, persistent surveillance video is used to construct a social network from vehicle tracks based on the interactions of those tracks. Social networks that are constructed give us further information about the suspicious actors flagged by the casing event detector by telling us who the suspicious actor has interacted with and what buildings they have visited. The end result is a process that automatically generates information from persistent surveillance video providing additional knowledge and understanding to intelligence analysts about terrorist activities

An Operational Utility Assessment: Measuring the Effectiveness of the Joint Concept Technology Demonstration (JCTD), Joint Forces Protection Advance Security System (JFPASS)

Sponsored Report (for Acquisition Research Program)Planning modern military operations requires an accurate intelligence assessment of potential threats, combined with a detailed assessment of the physical theater of operations. This information can then be combined with equipment and manpower resources to set up a logistically supportable operation that mitigates as much of the enemy threat as possible. Given such a daunting challenge, military planners often turn to intelligent software agents to support their efforts. The success of the mission often hinges on the accuracy of these plans and the integrity of the security umbrella provided. The purpose of this project is to provide a comprehensive assessment of the Joint Forces Protection Advanced Security System (JFPASS) Joint Concept Technology Demonstration (JCTD) to better meet force-protection needs. It will also address the adaptability of this technology to an ever-changing enemy threat by the use of intelligent software. This project will collect and analyze data pertaining to the research, development, testing, and effectiveness of the JFPASS and develop an operational effectiveness model to quantify overall system performance.Naval Postgraduate School Acquisition Research ProgramApproved for public release; distribution is unlimited

Emerging Potable Water Technologies

Water is essential to keep up life, especially safe drinking water is one of the first priorities. As water quality is important, many nations endeavor to guard the water and to increase access to potable water. Fortification of water supplies from contamination is the earliest stripe of defence. Water purification is very important aspect, presently there are number of drinking water technologies available mostly based on ion exchange, ultra filtration and reverse osmosis techniques, but still about five million people die annually from water born diseases. The objective of this review is to provide direction on the chemical safety of drinking-water and also monitoring of chemicals in drinking-water. Water treatment potential technologies can solve diverse drinking water issues in case of chemical contamination, which is the second objective. The purpose of this review is to make survey of currently available and future emerging technologies for drinking water. Several purification techniques have been adopted to meet the standards. There is a necessity of wide-ranging global approach to tackle the problem of water pollution devastating thousand of lives annually rather than to develop nuclear and biological weapons. This document will also be useful to public health authorities, those responsible for setting standards and for surveillance of drinking-water quality, and to water supply agencies responsible for water quality management

A methodology for the efficient integration of transient constraints in the design of aircraft dynamic systems

Transient regimes experienced by dynamic systems may have severe impacts on the operation of the aircraft. They are often regulated by dynamic constraints, requiring the dynamic signals to remain within bounds whose values vary with time. The verification of these peculiar types of constraints, which generally requires high-fidelity time-domain simulation, intervenes late in the system development process, thus potentially causing costly design iterations. The research objective of this thesis is to develop a methodology that integrates the verification of dynamic constraints in the early specification of dynamic systems. In order to circumvent the inefficiencies of time-domain simulation, multivariate dynamic surrogate models of the original time-domain simulation models are generated using wavelet neural networks (or wavenets). Concurrently, an alternate approach is formulated, in which the envelope of the dynamic response, extracted via a wavelet-based multiresolution analysis scheme, is subject to transient constraints. Dynamic surrogate models using sigmoid-based neural networks are generated to emulate the transient behavior of the envelope of the time-domain response. The run-time efficiency of the resulting dynamic surrogate models enables the implementation of a data farming approach, in which the full design space is sampled through a Monte-Carlo Simulation. An interactive visualization environment, enabling what-if analyses, is developed; the user can thereby instantaneously comprehend the transient response of the system (or its envelope) and its sensitivities to design and operation variables, as well as filter the design space to have it exhibit only the design scenarios verifying the dynamic constraints. The proposed methodology, along with its foundational hypotheses, is tested on the design and optimization of a 350VDC network, where a generator and its control system are concurrently designed in order to minimize the electrical losses, while ensuring that the transient undervoltage induced by peak demands in the consumption of a motor does not violate transient power quality constraints.Ph.D.Committee Chair: Mavris, Dimitri; Committee Member: Charrier, Jean-Jacques; Committee Member: Garcia, Elena; Committee Member: Grijalva, Santiago; Committee Member: Schrage, Danie

A review of Terahertz technology and Metamaterial based electromagnetic absorber at Terahertz band

 Terahertz (THz) technology, a new step towards the wireless communication is a recent topic of research. THz radiation has unique properties which make it better than microwaves, infrared, X-rays, etc. These radiations have wide applications in various fields like imaging, spectroscopy, security, biomedicine, sub-millimeter astronomy, in communication, etc. THz radiation sources and detectors play a vital role in the THz communication system.  The sources and detectors for THz radiation are still in a developing stage. As in naturally occurring materials, there is lack of good terahertz characteristic, so researchers are moving towards artificial one, i.e., the metamaterial based design. Metamaterial based design of generation and detection of THz radiation is the recent demands in the field of THz communication. Hence, we are focussing on the metamaterial based terahertz transmitter and receiver. So in this paper, a brief study of the THz technology based on metamaterial has been carried out and presented here

2008 Annual Report of the Graduate School of Engineering and Management, Air Force Institute of Technology

The Graduate School\u27s Annual Report highlights research focus areas, new academic programs, faculty accomplishments and news, and provides top-level sponsor-funded research data and information

Corruption and Pro-Poor Growth Outcomes: Evidence and Lessons for African Countries

There is growing consensus that corruption hurts economic performance by reducing private investment, adversely affecting the quantity and quality of public infrastructure, reducing tax revenue, and reducing human capital accumulation. In addition to inefficiency effects—lower growth for a given endowment in factors and technology—corruption also has adverse distributional effects as it hurts the poor disproportionately. For a given level of government budget and national income, high corruption countries have lower literacy rates, higher mortality rates, and overall worse human development outcomes. Corruption deepens poverty by reducing pro-poor pubic expenditures, creating artificial shortages and congestion in public services, and inducing a policy bias in favor of capital intensity, which perpetuates unemployment. High levels of corruption in African countries constitute one of the factors behind slow growth and limited progress in poverty reduction. Eradicating corruption in African bureaucracies is a challenging task, especially because it is a systemic phenomenon with effects that often lag far behind the causes. Therefore, explicit strategies are necessary to change the incentive structure by modifying the payoffs and sanctions that govern the interactions between bureaucrats and private economic operators. Strategies to fight corruption include measures to increase transparency in the management of public resources, establishing an incentive structure that rewards honest behavior among civil servants, enforcing transparency in international contracts and equal penalties to all parties to corrupt deals, and promotion of a free and responsible media.Corruption; pro-poor growth; rent-seeking; African countries

WHAT IS TECHNOLOGY STRATEGY?

The purpose of this thesis is to explore and define the framework for a type of military development strategy that links technological decisions to strategic effects—technology strategy. This study is novel, as most approaches to technology strategy focus on producing technology as an end in itself instead of focusing on technology development and acquisition as the principal means for achieving strategic effects. By placing technology as the means and strategic effects as the ends, this study deduces an original, perhaps seminal, description of technology strategy and a framework for its formulation. Arms-racing case studies and an exploration of offense-defense theory structure this exploration and enable the observation of technology strategy’s core characteristics, which are its relationships to doctrinal innovation and organizational design, forms or templates, approaches to acquisition, and potential pitfalls. The structural components of the technology strategy concept illuminated are then arranged in a proposed taxonomy that fits within the U.S. military’s joint concept development process. Beyond the descriptive and structural components, this study also identifies notable best practices in the application of technology strategy, particularly those that an effective technology strategy should encompass—both the decisions surrounding which weapons, transportation, and information systems to invest in, and their implications, in practice, for organization and doctrine.Outstanding ThesisMajor, United States Air ForceApproved for public release. Distribution is unlimited

Approach to Assess the Resiliency of Electric Power Grids

Today�s electric power grids face serious challenges due to overstressed networks, need to assimilate variable generation, strict environmental regulations and widespread weather-caused outages. There is an urgent need to improve grid resilience and system security more than ever before. Amidst such challenges, the best approach would be to focus primarily on the grid intelligence rather than implementing redundant preventive measures. The foundation of any intelligent operational strategy would be on the ability of the grid to assess its current dynamic state instantaneously. Traditional forms of real-time power system security assessment consist mainly of methods based on power flow analyses. Such methods do not consider the dynamics inherent in the system and hence, are static in nature. However, in order to capture the nonlinear dynamics present in the system, it is necessary to carry out time-domain simulations (TDS) that are computationally too involved to be performed in real-time. Machine learning (ML) techniques have the capability to organize data gathered from such simulations and thereby extract useful information in order to better assess the system security instantaneously. This dissertation presents a framework that would enable implementation of machine learning techniques for real-time assessment of grid resilience. An IEEE 14-bus test system is used in this work for simulation purposes. Firstly, a set of multiple steady-state operating points is generated by performing a SSA on the base case of the power system. Secondly, a TDS is performed on each operating point to assess the grid resilience against a specific disturbance, thus generating a database for this work. This work highlights the importance and need for selecting a few operating points as �landmarks� in the operational space under consideration for prediction of power system security. Further, a few heuristics are developed so as to rank all the operating points of the system. The proposed ranking methodologies are used to select the best landmarks in order to improve prediction accuracy on the original database, thereby enhancing the ability to assess grid resilience instantaneously.Electrical Engineerin